https://cpw.cvlcollections.org/files/original/3adca87aaf9abe042e2fc4c4271ad14c.pdf 7fad827db0996ca75568cd5ca84d0d9f PDF Text Text 1 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT state of Colorado cost center 3430 Project No. W-153-R-11 Mammals Program Work Package No. __0_6_6-2______ Preble's Meadow Jumping Mouse conservation Task No. : Preble's Meadow Jumping Mouse conservation Period Covered: Author: July 1, 1997 - June 30, 1998 Tanya Shenk ABSTRACT A draft conservation plan, entitled 'Conservation Assessment and Preliminary Conservation Strategy for Preble's Meadow Jumping Mouse (Zapus hudsonius preblei)' was completed and submitted to the .USFWS on January 9, 1998 during the Open Comment Period for the Proposed Listing of Preble's meadow jumping mouse as endangered. The conservation plan was divided into two parts. The first part, a conservation assessment summarized and evaluated available information on the taxonomy, distribution, and ecology of z. h. preblei and identified potential threats to the conservation of the mouse. The second part, a preliminary conservation strategy outlines the goals and objectives of a conservation strategy for z. h. preblei and summarized prioritized research needs to provide necessary information to develop sound conservation strategies. From this list of prioritized research needs two study plans were completed and research begun on both starting in May 1998. These research plans are designed to investigate (1) temporal and spatial variation in the demography of Preble's meadow jumping mouse and (2) habitat use and distribution of Preble's meadow jumping mouse in Larimer and Weld Counties, Colorado. ��3 Preble's Meadow Jumping Mouse Conservation Plan Tanya Shenk P.H. OBJECTIVE Develop and implement a conservation plan for Preble's meadow jumping mouse in Colorado. SEGMENT OBJECTIVES 1. Complete a literature search for all known, relevant information to develop a conservation plan for Preble's meadow jumping mouse. 2. Complete an inventory of current research being conducted on Preble's meadow jumping mouse. 3. Evaluate known information on Preble's meadow jumping mouse in the context of providing information necessary to develop sound strategies for conservation of Preble's meadow jumping mouse. 4. Define and prioritize needed research components to develop sound strategies for conservation of Preble's meadow jumping mouse. s. Begin study design for research to address a high priority need to develop sound strategies for conservation of Preble's meadow jumping mouse. 6. Complete a draft conservation plan for Preble's meadow jumping mouse. RESULTS AND DISCUSSIQH 1. Complete a literature search for all known, relevant information to develop a conservation plan for Preble's meadow jumping mouse. A literature search was completed, the information was summarized and presented in the draft conservation plan (see Appendix A). 2. Complete an inventory of current research being conducted on Preble's meadow jumping mouse. There are four research projects being conducted on z. h. preblei, with a fifth planned to begin spring of 1998 (Table 1). Each of these projects is designed to provide further information on the ecology or demography of Preble's meadow jumping mouse. However, if research methodologies were standardized and coordinated across all the projects, comparability and quality of the data would be greatly enhanced. Such a coordinated effort would maximize data quantity, quality, and comparability over varying conditions throughout the range of z. h. preblei in the most effective and efficient way possible. Comparable information gained across the ecological range of z. h. preblei would then provide more useful information to develop sound management strategies for conservation of the mouse. To achieve such a coordinated research effort all project leaders must agree to follow data collection protocols, establish 'ownership' of data and future publications, and work cooperatively to share equipment and technical assistance during peak data collection periods. To facilitate such a mutual effort will require the participation of all �4 project leaders conducting field studies of z. h. preblei as well as cooperative investigators, and specialized data analysts with expertise in the study design, analysis, and interpretation of mark-recapture and telemetry data. Therefore, I organized a Preble's Meadow Jumping Mouse Research Working Group with the following objective: To explore the idea of coordination of research efforts across multiple principal investigators to enhance comparability and quality of data across the range of z. h. preblei for use in developing sound management strategies for conservation of the mouse. Such an effort would maximize data qu~ntity, quality, and comparability over varying conditions throughout the range of z. h. preblei in the most effective and efficient way possible. To make this work, all principle investigators must agree to follow data collection protocols, establish 'ownership' of data and future publications, and work cooperatively on the possible sharing of equipment and technical assistance during peak data collection periods. This working group needs to involve all interested principle investigators involved in field studies of z. h. preblei as well as cooperative investigators, and specialized data analysts with expertise in the study design, analysis, and interpretation of mark-recapture and telemetry data. The first meeting of the working group (November 12, 1997) was a success with all principle investigators supportive of the idea of a coordinated, cooperative research program. The second meeting of the Research Working Group is scheduled for February 4, 1998 where we will outline what research questions will be addressed at which sites and draft standardized protocols for data collection. A proposed agenda for the Research Working Group includes the following tasks, task leaders, and a timetable to initiate a cooperative research effort: Task Task Leader, Affiliation Date Identify all potential participants: project leaders, cooperating investigators, data analysts. Prioritize research questions. T. Shenk, Colorado Division of Wildlife January 1998 All project leaders* Identify sites to best address prioritized research needs. Design studies specific to research question to be addressed at each site. All project leaders January 1998 January 1998 JanuaryFebruary 1998 All project leaders, cooperating investigators, data analysts All project leaders March 1998 Evaluate needs at each site to conduct specified research. March 1998 Identify discrepancies between All project leaders needs and available funds, equipment, and personnel currently allocated for each site. Attempt to balance discrepancies. March 1998 All project leaders, cooperating investigators * To date: M. Bakeman, c. Meaney, T. Ryon, R. Schorr, T. Shenk �5 3. Evaluate known information on Preble's meadow jumping mouse in the context of providing information necessary to develop sound strategies for conservation of Preble's meadow jumping mouse. Known information on the ecology of Preble's meadow jumping mouse was summarized and presented in the Conservation Plan (see Appendix A). 4. Define and prioritize needed research components to develop sound strategies for conservation of Preble's meadow jumping mouse. The following outline is a complete list of research needs to provide information to develop sound management strategies for conservation of z. h. preblei. Research needs are not listed in order of priority, but listed in a logical manner to provide completion of needs. Demographic studies: Information on the population dynamics of Preble's meadow jumping mouse is necessary to determine which areas support populations where the rate of population growth is~ 1. Key parameters to estimate include: Survival: • estimates of survival, including ► annual ► over-summer ► over-hibernation • investigate possible factors affecting survival, including ► weight sex age abundance (i.e., density dependent response) habitat features: stream reach, vegetation composition weather ► predation ► disease Approach: mark-recapture techniques ► ► ► ► ► Recruitment: • estimate recruitment (as an alternative to reproductive parameters listed below) • investigate possible factors affecting recruitment, including ► weather ► habitat features Approach: mark-recapture techniques Population structure: • estimate sex ratios • estimate age ratios Approach: mark-recapture techniques Abundance: • estimate abundance investigate factors affecting abundance, including ► habitat features (see under habitat use) Approach: mark-recapture techniques for closed populations • Immigration, emigration: • estimate rates of immigration and emigration �6 • investigate possible factors affecting immigration, emigration habitat features (see under habitat use) ► abundance (i.e., density-dependent response) Approach: estimate rates from mark-recapture data, identify existence with radio telemetry ► Reproduction: • • • • • estimate number of litters per year estimate number of young per litter estimate age at first reproduction estimate juvenile survival investigate possible factors affecting reproduction, including ► habitat features: food availability, nest site availability, cover availability ► abundance (i.e., density-dependent response) ► weather Approach: from telemetry work Dispersal is a key process in metapopulation theory and to maintain genetic diversity between isolated populations. Key parameters to evaluate include: Dispersal Studies: Population parameters • who disperses • time of dispersal • estimate rate Approach: estimate rate with mark-recapture, document who and when from both telemetry and mark-recapture data Habitat parameters • • • through what habitat end point descriptions (disperses from what to what) landscape features (connectivity with other riparian strips, corridor use, overland use) Approach: document where from both telemetry and mark-recapture data Conservation of z. h. preblei should maintain populations throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Key concerns include: Distribution Studies: Range-wide distribution: • conduct trapping surveys to better define the eastern boundary of the range of z. h. preblei • conduct trapping surveys in areas of potential sympatry of z. h. preblei with z. princeps Approach: determine from trapping surveys Habitat Studies: To identify and define habitat requirements of z. h. preblei studies should be conducted to address the following: Habitat use: • • • estimate distances traveled: daily, seasonally describe landscape features (connectivity with other potential sites, geology) determine seasonal use �7 • • • • • describe hibernacula describe nest sites estimate distance to nearest open water from other habitats used describe hydrology (water quality, flow) in areas of use evaluate effects of abundance on habitat used (i.e., density dependent responses) Approach: estimate from telemetry work Physiological Studies: Physiological studies will provide information on the mechanisms driving habitat selection. Physiological requirements: • estimate dependency of z. h. preblei on open water • determine energetic requirements to survive hibernation Approach: estimate from laboratory studies Systematic Studies: To better define the relationship of z. h. preblei to other subspecies of z. hudsonius and other species of Zapus the following studies should continue. Molecular systematic relationships: • further explore genetic relationships among different z. h. preblei populations • further explore genetic relationships among different subspecies of z. hudsonius • further explore genetic relationships among different species of Zapus. Approach: explore through laboratory studies Systematic relationships: • link genetic relationships to systematic studies of z. hudsonius. Approach: explore through museum studies Community Studies: Composition of the community where z. h. preblei occur could help explain ecological tolerances of the subspecies, providing insight to the mechanisms determining its distribution. Small mammal assemblages: • comparison of small mammal assemblages in areas where populations of z. h. preblei occur and areas where they do not ► species composition ► relative abundance Approach: estimate from trapping surveys There are currently five research projects on z. h. preblei planned to begin spring of 1998. Each of these projects is designed to provide further information on the ecology or demography of Preble's meadow jumping mouse. However, if research methodologies were standardized and coordinated across all the projects, comparability and quality of the data would be greatly enhanced. Such a coordinated effort would maximize data quantity, quality, and comparability over varying conditions throughout the range of z. h. preblei in the most effective and efficient way possible. Comparable information gained across the ecological range of z. h. preblei would then provide more useful information for use in developing sound management strategies for �8 conservation of the mouse. Therefore, a research group was formed including all principal investigators of the five studies as well as other interested personnel. This research group has developed standardized protocols to be followed in all studies. These include protocols on techniques, data collection, and data analyses for (1) mark-recapture, (2) radio-telemetry, (3) habitat use, and (4) genetic sampling. 5. Begin study design for research co address a high priority need co develop sound strategies for conservation of Preble's meadow jumping mouse. There are four components of z. h. preblei ecology that are currently unknown and yet key to any sound conservation strategy for the subspecies. These are (1) detailed demographic studies estimating survival and reproduction and determining the factors influencing each of the parameters, (2) detailed studies evaluating movements and dispersal habitat of individuals within and among populations, (3) detailed studies to define hibernation needs, primarily descriptions of suitable hibernacula criteria and food requirements for sufficient fat storage prior to immergence, and (4) better defined distributions of the mouse. The following describes the research I will be conducting beginning Spring 1998 to address these needs. Demography Study: Information on the population dynamics of Preble's meadow jumping mouse is necessary to determine which areas support populations where the rate of population growth is stable or suggests an increasing population. Key parameters to estimate include survival (annual, over-summer, and over-hibernation), reproduction, dispersal rates, and density. A combination of mark-recapture techniques and radio-telemetry studies will be used to estimate these parameters and evaluate possible factors affecting such parameters. Intensive trapping efforts will be conducted in June and August of 1998 and in May of 1999 within a given population. All animals captured will be permanently marked with PIT (passive integrated transponders) tags. Select mice will also be fitted with radio transmitters. Survival estimates and evaluation of possible factors affecting survival, including weight, sex, age, abundance (i.e., density dependent response), habitat features (stream reach, vegetational composition), and weather will be obtained from data collected from mark-recapture efforts. Dispersal is a key process in meta-population theory and to maintain genetic diversity between isolated populations. The key objectives are to estimate rate of dispersal and to determine who disperses, time of dispersal, and describe suitable dispersal habitat. These estimates will be obtained from analyses of both the markrecapture data and from following radio-collared individuals. Estimates of immigration and emigration rates will be obtained from data collected during the mark-recapture efforts as well as an evaluation of possible factors affecting these rates including habitat features and abundance (i.e., density-dependent response). Data on who disperses, when dispersal occurs, and dispersal habitat will be obtained by following radio-collared animals. From the mark-recapture data collected during the trapping sessions, abundance and density estimates can also be made. Other ancillary information which can be obtained from data collected during �9 the tapping sessions include estimates of sex and age ratios within the populations sampled. Reproduction parameters such as number of litters per year, number of young per litter, and age at first reproduction will be estimated from radio-collared females. An analysis of variance will be conducted to evaluate possible factors affecting reproduction, including habitat features such as food availability, nest site availability, and cover availability as well as the possible effects of abundance (i.e., density-dependent response) and weather. A complete study plan entitled "Temporal and spatial variation in the demography of Preble's meadow jumping mouse (Zapus hudsonius preblei) is included in Appendix B. Distribution, Habitat Use, and Monitoring Study: Conservation of z. h. preblei should maintain populations throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Key concerns include range-wide distribution, habitat use, and population persistence at a given site. To address these concerns a study will be designed where a sampling frame of suitable habitat will be constructed. The starting point for developing the sampling frame will be to determine the feasible distributional range of z. h. preblei. A conservative approach will be used for elevational and directional limitations. Once the potential distribution map is developed, all but potentially suitable habitat within the feasible range of the subspecies will be eliminated. From this sampling frame, random sites will be selected to conduct trapping surveys. Therefore, all successful trapping sites will provide further information on the distribution of the mouse. Information on habitat will be collected at all sites surveyed, regardless of trapping success for Preble's meadow jumping mouse. Comparisons of habitat variables from both successful and unsuccessful sites will be used to better define suitable habitat for the subspecies. Habitat variables recorded will include both site level characteristics such as vegetational composition, cover, and composition of ·other small mammal species·as well as landscape level characteristics including connectivity with other potential sites, geology, hydrology, and distance to development. Data collected on movements of radiotelemetered mice will also provide information on seasonal use of different habitats, dispersal corridor and end point habitat characteristics, and descriptions of nest sites and hibernacula. Repeated annual visits to the randomly selected sites will provide information on population persistence at a given site. Such a monitoring scheme will be necessary for evaluating the continued status of the mouse as well potentially evaluating the efficacy of any conservation planning efforts. Genetic tissue samples will also be collected from mice captured at these new locations. Future genetic analyses should help to better define the relationship among (1) different populations of z. h. preblei, (2) other subspecies of z. hudsonius and (3) other species of Zapus. A complete study plan entitled "Habitat use and distribution of Preble"s meadow jumping mouse (Zapus hudsonius preblei) in Larimer and Weld Counties, Colorado" is included in Appendix C. 6. Complete a draft conservation plan for Preble's meadow jumping mouse. The draft conservation plan, entitled 'Conservation Assessment �10 and Preliminary Conservation Strategy for Preble's Meadow Jumping Mouse (Zapus hudsonius preblei)' was completed and is attached as Appendix A. The document was submitted to the USFWS during the Open Comment Period for the Proposed Listing of Preble's meadow jumping mouse as endangered. Prepared by ~---_5/J_ ~ a Shenk �Table 1. Current and proposed research projects for Preble's meadow jumping mouse. Marking method Study location Principle Investigate r Pit tags Parameters to estimate Telemetr Surviva Reproducti Recruitme Abundanc Diapers Habita Populatio Stomach t Uset on nt y 1 e al n content structure analyses Rocky Flats Tom Ryon X X X X X AOA* Air Force Academy Rob Schorr X X X X X AOA X X AOA X X AOA Boulder Open Carron Meaney Space Lyons X Mark Bakeman Cherokee Park? Tanya Shenk X X X X X X X X AOA Douglas Cty (Plum Creek)? Tanya Shenk X X X X X X X X AOA * AOA As opportunity arises I-' I-' ��13 APPENDIX A CONSERVATION ASSESS:MENT AND PRELIMINARY CONSERVATION STRATEGY FOR PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) prepared by Tanya Shenk Colorado Division of Wildlife 317 West Prospect Fort Collins, Colorado 80526 January 1998 �14 EXECUTIVE SUMMARY In 1994 a petition was submitted to the U. S. Fish and Wildlife Service from the Biodiversity Legal Foundation (USFWS 1997a) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) under the Endangered Species Act (ESA). A Proposed Rule to list Preble's meadow jumping mouse as endangered under the ESA was submitted by the U. S. Fish and Wildlife Service on March 25, 1997 (USFWS 1997a). Following the Proposed Rule to list the species as endangered, the Colorado Division of Wildlife agreed to develop a species conservation assessment and preliminary conservation strategy which would provide a framework for conservation efforts. This document is the result of that agreement between the Colorado Division of Wildlife and The U.S. Fish and Wildlife Service. Therefore, the purpose of this document is to summarize the current known ecology and status of Z. h. preblei, to outline goals for conservation of the subspecies, to prioritize what information is most needed to develop sound conservation strategies to meet those goals, and to suggest future research required to provide such information. This document will provide the Colorado Division of Wildlife with a prioritized list of research needs to direct ecologists and managers toward obtaining the necessary information for developing, implementing, and evaluating strategies for conserving the Preble's meadow jumping mouse. Should the Final Decision list the species as either threatened or endangered, this document could also provide scientific information for any Habitat Conservation Plan(s) to be developed under the ESA. Any conservation plan for Z. h. preblei should address what is needed for recovery of the subspecies, including how much habitat is needed and where, what information and conservation actions are needed, whether restorations are needed, and what biological information is needed to manage or conserve the mouse. Some of the basic information required to define these needs includes the distribution of the mouse and its habitat, population dynamics (survival, reproduction, and dispersal), minimal habitat requirements, genetic variation between and among populations, physiology, hibernation requirements, and resilience of populations to human alteration of their habitat. This document attempts to summarize what is currently known on each of these topics, prioritizes what information is still most needed to develop conservation strategies based on the conservation goals, and suggests future research required to provide missing information. A review of the studies conducted on Preble's meadow jumping mouse shows that there is insufficient information to fully address defining range-wide ecological requirements, limiting factors, limits of species tolerance, or population status. Most work to date has focused on geographic distribution (presence or absence of Z. h. preb/ei), taxonomy, and habitat descriptions of sites where mice have and have not been captured. Although available information is limited, it is clear that measures must be taken to begin developing a conservation strategy for Z. h. preblei. The primary objectives necessary to develop a successful conservation strategy for Preble's meadow jumping mouse are: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. Document the present distribution of Z. h. preblei. Identify populations of Z. h. preblei where the rate of population growth ~ 1. Protect populations of Z. h. preblei where the rate of population growth~ 1. Maintain current range of natural variability of Z. h. preblei. Identify ecological requirements for sustaining viable populations of Z. h. preblei throughout its range of natural variability. Protect habitats to sustain existing populations of Z. h. preblei where the rate of population growth~. 1. Promote protection and management of habitat for conservation of Z. h. preblei in all currently or recently occupied habitat, and in habitat suitable for restoration of mouse populations. Monitor the status of populations of Z. h. preblei throughout its known range to detect changes in local distribution. Identify threats to the conservation of Z. h. preblei. Eliminate or minimize threats to conservation of Z. h. preblei. �15 11. 12. 13. Integrate Preble's meadow jumping mouse conservation strategy objectives with management and habitat objectives of other Front Range riparian species. Promote scientific management of Preble's meadow jumping mouse. Promote public support for conservation efforts and scientific management of Preble's meadow jumping mouse through public education. In order to achieve the stated objectives outlined above, the following actions must occur: 1. 2. 3. 4. 5. 6. 7. 8. 9. Conduct population studies to estimate and determine what factors influence demographic parameters and rate of population change. Conduct studies to better define the ecological requirements of Z. h. preblei (food, cover, water, hibernation requirements, etc.). Conduct research to evaluate the effects of potential threats on survival, reproduction, dispersal, and abundance of Preble's meadow jumping mouse. Implement habitat and population management practices that emphasize the conservation of Preble's meadow jumping mouse throughout the natural variability of its range. Develop survey protocols to monitor trends in the distribution of Z. h. preblei and protocols to store and analyze survey data. Conduct trapping surveys to better define the boundaries of the range of Z h. preblei. Implement research on Preble's meadow jumping mouse biology to better understand the mechanisms driving the ecological requirements. Further explore genetic relationships among different Z. h. preblei populations, among different subspecies of Z. hudsonius, and among different species of Zapus. Develop educational programs to promote positive public support for Preble's meadow jumping mouse conservation. The criterion to be used to evaluate the success of this program will be the maintenance of local selfsustaining populations of Preble's meadow jumping mouse which are geographically distributed throughout the range of the subspecies and throughout the natural variation of its ecological requirements. The document is divided into two parts. The first part, a conservation assessment will ( 1) summarize available information on the taxonomy, distribution, and ecology of Z. h. preblei; and (2) identify potential threats to the conservation of the mouse. The second part, a preliminmy conservation strategy, will (1) outline the goals and objectives of a conservation strategy for Z. h. preblei; and (2) summarize prioritized research needs to provide necessmy information to develop sound conservation strategies. ACKNOWLEDGMENTS This document could not have been prepared without generous help from all members of the 'Z. h. preblei Conservation Document Working Group' (Mark E. Bakeman, Carron A. Meaney, Chris Pague, and Peter Plage). Members gave freely of their time and expertise and readily shared their data, anecdotal observations, impressions, and scientific interpretations. This working group truly exemplified how scientists should interact when working toward a common goal. Additional scientific contributions came from David M. Armstrong, Alan B. Franklin, Lawrence A. Riggs, Thomas R Ryon, Robert Schorr, Rick Schroeder, and Bruce Wunder. Technical support during this effort was provided by Alan B. Franklin, David Lovell, Francie Pusatari, and Michael Wunder. Logistical support was provided by Steven Nesta, Douglas Robotham, Judy Sheppard, and John Stover. �16 CONSERVATION ASSESSMENT INTRODUCTION The following is a summary of information collected primarily from the five studies conducted on Z. h. preb/ei. The longest and most varied studies have been conducted on the Rocky Flats Environmental Technology Site (I 990 through the present) including distribution studies, habitat surveys, location ofhibernacula, fat requirements for hibernation, and genetic studies conducted by M. Bakeman, A. Deans, F. Harrington, T. Ryon, R Stoecker, and B. Wunder. Range-wide distributional and vegetation surveys have been conducted on sites other than Rocky Flats Environmental Technology Site by (1) Meaney et al. (1995, 1996, 1997), funded by the Colorado Division of Wildlife, (2) City of Boulder Open Space and Boulder County Open Space, (3) Ensight Technical Services of Boulder, Colorado funded by the Colorado Department of Transportation, (4) the Colorado Natural Heritage Program, (5) U. S. Forest Service, Medicine Bow National Forest, Wyoming, and (6) numerous other environmental consulting firms. An evaluation of historical Z. h. preblei sites was conducted by Ryon (1996). Genetics studies were conducted in 1995 by B. Wunder and in 1996 and 1997 by Biosphere Genetics, Inc. Where data were not available for Z. h. preblei, information from studies of other subspecies of Z. hudsonius was provided. In particular, studies conducted by Quimby (1951) and Whitaker (1963) provided substantial information on the species. Caution must be used in extrapolating information reported for other subspecies of Z. hudsonius to Z. h. preblei, although, such information is useful as a general framework from which to work until such information becomes available for Z. h. preblei itself Possible threats to the conservation of Preble's meadow jumping mouse were derived from both general principles of conservation biology and information specific to Zapus hudsonius in general, or the subspecies itself TAXONOMY Description Quimby (1951) described Z. hudsonius as follows: 'A mouse-like rodent with greatly enlarged hind feet and an exceptionally long tail. The forelegs are relatively short. The ears are somewhat conspicuous. The body is clothed in moderately long, somewhat dense hair of a rather coarse texture and several colors. The dorsal portions are marked by a broad stripe of brownish hairs many of which are tipped with black giving the region a grayish-black appearance. The sides are bright yellowishorange, whereas the underparts and feet are white. The tail is bicolor, dark above and light below, and sparsely covered with hair which is longer on the terminal part. The mammae are eight, and quite prominent in lactating females. The male genitalia are inconspicuous except during the breeding season when the scrotal sac becomes enlarged. The testes enlarge and may be either abdominal, inguinal, or scrotal during this period.' The skull of Z. hudsonius is small and light with a narrower braincase and smaller molars than in Z. princeps (from Fitzgerald et al. 1994 p. 18). However, Fitzgerald et al. (1994) urge caution in distinguishing the two species ·or Zapus in Colorado. Such caution is further warranted by the recent conflicting identifications of mice based on genetic characteristics (see Genetics section below). E. A. Preble (1899) first collected the specimen that is, now, the holotype for Z. h. preblei at Loveland, Colorado in 1895 and assigned it taxonomically to Z. h. campestris. Krutzsch (1954) revised the taxonomy of Z. hudsonius and assigned the meadow jumping mice from Colorado and southeastern Wyoming to their own distinct subspecies. Krutzch (1954) described this subspecies as having fewer black-tipped dorsal hairs and a less distinct dorsal band; smaller cranial measurements; a narrower interorbital constriction; smaller, less inflated auditory bullae; narrower incisive foramina; and a more inflated frontal region (Fig. 1) than Z. h. campestris. Krutzch named this subspecies Z. h. preblei in honor of the collector of the holotype (and previous reviewer of genus). �17 Figure 1. Preble's meadow jumping mouse (Z. h. preblei). Note the long tail curves around handlers index finger and the dark dorsal stripe. Also note the large hind foot and small first digits on front and rear feet (insert). Photographs by Norm Clippinger. Measurements for meadow jumping mice in Colorado are: total length 187-255 mm; length of tail 108-155 mm; length ofhindfoot 28-35 mm (Fitzgerald et al. 1994). Body weights of meadow jumping mice are variable, not only for different animals, but for the same individual depending on activity or season (Quimby 1951). Such variability arises from sex, age, reproductive status, preparation for entering hibernation, and condition on emergence from hibernation. Mean body weights reported for adult Preble's meadow jumping mice are 19g (n = 37; Meaney et al. 1996), 23.5g (n = 5, se = 1.2g; Colorado Natural Heritage Program, unpublished data);22.7g (n = 30, se = 0.1g; M. Bakeman unpublished data 1997), 20.3 g (n = 26, se = 0.5g; Meaney et al. 1997). Two species of ectoparasites have been identified on Preble's meadow jumping mice (R Schorr, personal communication). These includes fleas (Megabothris abantis, (identified by K. Gage of the Center for Disease Control) and a larval form of a tick, either Ixodes sculptus or L kingi. Genetics The family Zapodidae (jumping mice) consists of small to medium-sized mice with enlarged hind feet and exceptionally long tails. Four living genera are recognized in this family, two of which, Zapus and Napaeozapus, are found in North America (Hall 1981). There are three living species of the genus Zapus: Z. trinotatus (Pacific jumping mouse), Z. princeps (western jumping mouse), and Z. hudsonius (meadow jumping mouse). Z. h. preblei is one of twelve living subspecies of the species Z. hudsonius (Fig. 2a, Krutzsch 1954, Hafner et al. 1981). Z. h. preblei was first described by Krutzsch (1954) from a specimen collected by E. A. Preble in 1895 near Loveland, Colorado. Genetics work using DNA sequencing of the mitochondrial DNA non-coding or re D-loop .tE region was conducted by Biosphere Genetics, Inc., to help determine whether populations of Z. h. preblei constitute one or more distinct evolutionary units. Genetic samples were collected from livetrapped mice, following a protocol specified by Biosphere Genetics, Inc., adapted and updated from the U.S. Fish and Wildlife Service standardized protocol. Sampling in 1996 and 1997 by all field crews (project leaders M. Bakeman, C. Meaney, T. Ryon, B. Stoecker, Colorado Natural Heritage Program) �18 was performed on meadow jumping mice presumed to be Z. h. preblei, yielding samples from 72 individual mice. Twenty genetic samples were also prepared from specimens provided either directly or indirectly by five different museums and university cooperators. Samples analyzed from livetrapped mice came from 23 locations in Colorado and two locations in Wyoming (Table 1). Samples analyzed from specimens provided by museums and cooperators represented reference material for species and subspecies from Colorado, Indiana, Minnesota, Nebraska, New Mexico, and Wyoming (Table 1; Fig. 2a and b). Preliminary DNA sequencing work in 1996 using a 550 basepair fragment of the mitochondrial DNA non-coding region examined 16 individuals from seven locations in Colorado and found two populations from Las Animas County (Lake Dorothey area) to be distinct from five other populations which ranged from Boulder County south to El Paso County. As more samples from additional trapping locations and museum specimens were brought in to the analysis in 1997, a smaller segment of the non-coding region included within the original 550 base-pair fragment was used to avoid problems with non-specificity of one of the primers. DNA sequences were obtained for 433 basepair-long fragments in all samples analyzed in both years. Phylogenetic relationships among the samples were inferred from maximum parsimony analysis. Strength of these phylogentic relationships were evaluated using bootstrap analysis (see Riggs et al. 1997, Appendix A for detailed methodology). Analysis of the mitochondrial DNA sequence data indicates that mice sampled from southeastern Albany County, Wyoming, south along the Front Range of the Rocky Mountains to western Las Animas County, Colorado (Purgatoire Campground, San Isabel National Forest), form a coherent genetic group (Fig. 3, L. Riggs et al. 1997). This group of samples are distinct from samples obtained from mice from three other populations. Genetic samples from mice captured in the Dorothey Lakes area of southern Colorado (Las Animas County) group together and are most closely allied with · Z. h. luteus, a subspecies described from New Mexico (Riggs et al. 1997). The single genetic sample collected from Weld County, Colorado (Lone Tree Creek) and six samples obtained from Warren Air Force Base in Laramie County, Wyoming are most similar to reference samples of Z. princeps from Colorado (Larimer County) and New Mexico (Taos County) (Riggs et al. 1997). The sequence data indicate that the samples from specimens identified as Z. h. luteus and samples from specimens of Z. princeps are more closely allied with each other than either is with the samples defining the Z. h. preblei gro.up. This closer alliance of the samples of Z. h. luteus with Z. princeps rather than Z. h. preblei conflicts with results ofHafher et al. (1981), based on a combination of pelage, morphologic, and genetic data, which support a closer alliance with Z. hudsonius. Phylogenetic analysis indicates that the group of samples referred to as Z. h. preblei cannot at this point be distinguished clearly from four reference samples of Z. h. campestris from Weston County, Wyoming (two samples), Custer County, South Dakota (two samples), one sample of Z. h. pallidus from Garden County, Nebraska, or from two samples of Z. h. intermedius from an unspecified county in Minnesota (Fig. 3, L. Riggs et al. 1997). A suggestion from the analyses is that Z. hudsonius from Indiana (presumed to be Z. h. americanus) may have shared a common ancestor with the progenitors of samples from Z. h. luteus and Z. princeps more recently than with the Z. h. preblei group and perhaps other subspecies described for the north central states (Riggs et al. 1997). A more complete biosystematic evaluation of jumping mice is needed to clarify and further refine relationships among populations of the group referred to as Z. h. preblei as well as to other subspecies and species of the genus 7Apus. Such·an evaluation requires detailed analyses of pelage, morphometric, and genetic data from sufficient numbers of individuals to adequately represent the populations of interest. However, the mitochondrial DNA non-coding (D-loop) sequence data available at this time are consistent with the view that a geographically contiguous set of populations previously recognized as Preble's meadow jumping mouse form a homogenous group recognizably distinct from other nearby populations and from another geographically-adjacent species of the genus (Riggs et al. 1997). Therefore, given the genetic data available, Riggs et al. (I 997) conclude Preble's meadow jumping mouse is a distinct population of Z. hudsonius. �a. l. 2. 3. 4. S. 6. 7. 8. 9. 10. II. 12. Z h. acadicvs Z h. a/cccnsls Z h. amerlcanus Z h. campestrls Z h. canadensts Z h. hudsonlus Z h. lntennedius Z h. la,Jas Z h. pallidus Z h. pnblei Z h. tenellus Z h. luteus b. ... Figure 2. Range of Z. hudsonius and its 12 subspecies (a) and Z. princeps (b) (modified from Hall 1981). Stars .indicate locations where reference samples were collected from specimens at either museums or from university cooperators for genetic analysis. Reference samples for Z. h. luteus include two from Otero County, New Mexico, and two samples from Sandoval County, New Mexico. Reference samples for Z. h. campestris include two from Weston County, Wyoming, and two samples from Custer County, South Dakota. Two reference samples of Z. h. intermedius came from Minnesota. Two samples of either Z. h. americanus or Z. h. intermedius came from Indiana. One sample of Z. h. pallidus came from Garden County, Nebraska. Reference samples for Z. prlnceps princeps include one sample from Taos County, New Mexico, and four samples from Larimer County, Colorado. �20 Table 1. List of specimens from which samples were taken for genetic analyses. Each specimen is identified by a genetic code name, general location, and origin of the specimen. Code Location BAD BOS BVC CCF CCR CGA CZP DC DMNH Origin of Specimen Badwater Creek, Natrona County, WY hudsonius South Boulder Creek, Boulder County, CO Beaver Creek, El Paso County, CO Warren Air Force Base, Laramie County, WY Chicorica Creek, Lake Dorothey State Park, Las Animas Co., CO Medicine Bow NF, Albany County, WY Neota Creek, Larimer County, CO U. S. Air Force Academy, El Paso County, CO San Isabel National Forest, Las Animas County, CO ZAHU East Plum Creek, Douglas County, CO Hay Gulch, Elbert County, CO Coal Creek, Jefferson County, CO Lake De Smet near Buffalo, Johnson County, WY hudsonius Lone Pine Creek, Larimer County, CO Lone Tree Creek, Weld County, CO Marshall Road, Dry Creek Ditch #2, Boulder County, CO Rabbit Creek, Larimer County, CO Rocky Flats Environmental Technology Site, Jefferson County, CO Roxborough State Park, Douglas County, CO Smith Creek, U. S. Air Force Academy, El Paso County, CO St. Vrain, Boulder County Open Space, Boulder County, CO West Fork Schwacheim Creek, Lake Dorothey, Las Animas Co., CO Woodhouse Ranch, Douglas County, CO West Plum Creek, Douglas County, CO Monument Creek, El Paso County, CO Ralston Creek, Jefferson County, CO Indiana ZHCSDC Custer County, SD EPC HAY JCC LDS LPC LTC ~ RBC RF ROX SCR STV WFS WHR WPC WRN WRP ZHCWYW Weston County, WY ZHLNMO Otero County, NM ZHLNMS Sandoval County, NM ZHPNEC Cherry County, NE ZHPNEG Garden County, NE ZPPCOG Grand County, CO ZPPNMf Taos County, NM Museum specimen identified as Z. Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Museum specimen identified as Zapus Z. h. preblei survey From B. Wunder identified as Z. princeps Z. h. preblei survey Museum specimen identified as Z. princeps princeps Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Museum specimen identified as Z. Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Museum specimen identified as Zapus Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Z. h. preblei survey Museum specimen, may be either Z. h. intermedius or Z. h. americanus Museum specimen identified as Z. h. campestris Museum specimen identified as Z. h. campestris Museum specimen identified as Z. h. luteus Museum specimen identified as Z. h. luteus Museum specimen identified as Z. h. pallidus Museum specimen identified as Z. h. pallidus Museum specimen identified as Z. p. princeps Museum specimen identified as Z. p. princeps �21 MRD97&lMNH9716 ROX9701 80S9706 EPC9701 ZHCSOC2--- 70 LOS1 - - RSS1076 OZP1 OCR ZH.N Figure 3. Graphical representation of the genetic relationships among the single most-representative individuals from eachpopulation or reference group ofjumping mice sampled as determined by Riggs ct al. (1997). The more branching that occurs between the center circle and the edge of the circle, the more dissimilar that sample, or group of samples is from the rest of the samples. The numbers on the lines emanating from the center circle are bootstrap values. Bootstrap values greater than 90 indicate those relationships which are strongly supported. Each specimen location can be derived by matching the sample code with those in Table 1. Numbers following the alphabetical code in this figure denote the sample number used in the analyses from that location. �22 DISTRIBUTION The meadow jumping mouse (Z. hudsonius) is broadly distributed across North America from the Atlantic to Pacific coasts, extending south into the United States to Alabama and Georgia and west across the Great Plains to the base of the Rocky Mountains (Fig. 2a). In general, it is a common inhabitant of moist, grassy and herbaceous fields. Eleven living subspecies have been described (Whitaker 1972). Hafner et al. {1981) describe a twelfth subspecies, Z. h. luteus. Z. h. preblei occurs only in eastern Colorado and southeastern Wyoming (Krutzsch 1954, Long 1965, Armstrong 1972). From its limited ecological and geographic distribution, Fitzgerald et al. (1994) suggest it is an Ice Age relict, once widespread in tallgrass prairie across the eastern plains of Colorado but now restricted to scattered localities on the Colorado Piedmont. Similar relict populations of meadow jumping mice in the White Mountains of Arizona and the Sacramento Mountains and Rio Grande Valley of New Mexico are described as the subspecies Z. h. luteus (Hafner et al. 1981). Numerous surveys have been conducted since 1990 to establish the current distribution of Preble's meadow jumping mouse {Fig. 4). Surveys have been funded by the U. S. Fish and Wildlife Service, Rocky Flats Environmental Technology Site, Colorado Division of Wildlife, U. S. Air Force Academy, Warren Air Force Base, Colorado Department of Transportation, City of Boulder Open Space and Real Estate Department, and Boulder County Parks and Open Space Department (Armstrong et al. 1997, P. Plage, personal communication). From 1990 to 1997 such surveys have yielded captures of Preble's meadow jumping mouse, based on field identification and supported by the genetic analyses, at the following sites: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Lone Pine Creek, Larimer County, Colorado Rabbit Creek, Larimer County, Colorado St. Vrain Creek and associated tributaries in Boulder County, Colorado City of Boulder Open Space, along South Boulder Creek and its tributaries, Boulder County, Colorado Coal Creek, Jefferson County, Colorado Rocky Flats Environmental Technology Site, Jefferson County, Colorado White Ranch P,ark, Ralston Creek, Jefferson County, Colorado Plum Creek drainages including Indian Creek, West Plum Creek, and East Plum Creek, Douglas County, Colorado Roxborough State Park, Douglas County, Colorado Hay Creek, Elbert County, Colorado Monument Creek on the U. S. Air Force Academy {AFAC) and tributaries of Monument Creek off the AFAC including Smith Creek, Pine Creek, and Jackson Creek, El Paso County, Colorado Medicine Bow National Forest, Albany County, Wyoming Two more sites yielded mice that were identified as Z. h. preblei in the field but were genetically found to be more closely allied with Z. princeps (see Genetics section). These sites include: I. 2. Warren Air Force Base, Laramie County, Wyoming Lone Tree Creek, Weld County, Colorado Similarity of the habitat at these sites compared to those where Z. h. preblei (as determined genetically) were found suggests the possibility of areas of sympatry or parapatry between the two species of Zapus. According to Fitzgerald et al. (1994) the distributions of Z. princeps (Fig. 2b) and Z. hudsonius (Fig. 2a) do overlap. The area of overlap occurs in eastern Wyoming. The distribution of Z. hudsonius in Colorado is now known to be larger than shown in Fitzgerald et al. (I 994). The boundaries are currently as far south as Las Animas County (based on genetically identified specimens of Z. h. �23 Platte Goshen □ Albany □ □ □ □ • Wyoming Laramie Weld Colorado Boulder 0 Adams Denver Arap~hoe • Elbert □ El Paso r:fl □ Pueblo Las Animas a New Mexico Figure 4. Distn"bution of historical occurrence (o) of Z. h. preb/ei, sites trapped since 1990 where Z. h. preblei were found(•). sites trapped since 1990 whereZ. h. preb/ei were not found(□). sites where mice were found and identified as Z. h. preb/ei in the field but were genetically identified as Z. princeps {[!I), and sites where mice were found and identified as Z. princeps but were genetically found to be Z. h. preblei (D). �24 preblei). Captures of Z. princeps and Z. hudsonius (as identified in the museum) have occurred as close as 8 miles within the same drainage (Armstrong 1972). Z. princeps were reported captured in 1981 (Olson and Knopf 1988) at the Lone Pine site in Larimer County, Colorado, where Z. h. preblei were captured this year. Because neither specimens or genetic samples were taken in the 1981 study, identification of those mice will remain in question. The discrepancy may be explained by field misidentification or Meaney et al. (I 997) also suggest this discrepancy might be explained by displacement of Z. princeps with Z. h. preblei sometime in the 16 intervening years between trapping efforts. Although assumed to have different ecological requirements, genetic evidence presented here suggests further investigation of possible distributional overlap between Z. h. preblei and Z. princeps. Several notable results from the genetic analysis of specimens acquired from the Denver Museum of Natural History may affect the location of the southern distribution of Z. h. preblei. One site yielded mice identified as Z. p. princeps in the field but were found to be genetically more closely allied with Z. h. preblei. This site is the most southern location to date of Z. h. preblei and is located at: I. Purgatoire Campground, San Isabel National Forest, Las Animas County, Colorado Also from Las Animas County were mice collected and identified as Z. h. luteus (Jones 1996), an identification also supported by the genetic analysis. These mice were from: 1. 2. Lake Dorothey State Wildlife Area, Chicorica Creek, Las Animas County, Colorado Lake Dorothey State Wildlife Area, West Fork Schwacheim Creek, Las Animas County, Colorado These sites suggest a more northerly distribution of Z. h. luteus, currently known only from limited areas in New Mexico and Arizona (Hafner et al. 1981). Identifying the southern boundary of Z. h. preblei clearly needs further study. Trapping surveys have also provided evidence that a number of historically occupied sites are no longer inhabited by the mouse. Ryon (I 996) trapped eight sites of historically occupied sites with no captures of Z. h. preblei. The eight historic sites had suffered either direct disturbances or increasing isolation as a result of past land use, affecting vegetation structure and composition (Ryon 1997). Thus, although the perimeter of the range of Z. h. preblei may or may not have remained the same, specific locations within the range have definitely changed and may have decreased. The pattern of successful and unsuccessful capture sites (Fig. 4) also suggests that development of the Denver metropolitan area may have created a north-south severing of the range of Z. h. preblei. ECOLOGY The ecology of Preble's meadow jumping mouse has not been studied in detail. However, from the limited information available there appear to be a number of similarities in its natural history and ecological requirements to populations of Z. hudsonius studied in more detail in the eastern and midwestern United States. Therefore, select information available on eastern subspecies of Z. hudsonius is presented below to provide some framework for and possible limitations in ecological tolerances for Z. h. preblei. However, it is critical to acknowledge the limitation and possible misleading effects of extrapolating biological information, natural history, and ecological requirements from one subspecies to another, across the geographic range of a species. Demography Reproduction: Meadow jumping mice have been observed to produce up to three litters per season (Whitaker 1963). Breeding peaks appear to occur in early to mid-June and August with a possible third litter in September (Whitaker 1963). Juvenile Z. h. preblei have been observed in June, August, and September (Meaney et al. 1996, 1997, PTI 1996a, M. Bakeman unpublished data, T. Ryon unpublished data), suggesting two litters per year. Z. hudsonius typically have litters of 5-6 young per �25 litter (Quimby 1951 ). Age of first reproduction is unknown for Z. h. preblei, however, females of Z. hudsonius have been observed to give birth at 3 months (i.e., females born in June have been observed to give birth in August of the same year). Gestation period is approximately 18 days (Quimby 1951). Young remain dependent on the female for approximately 18 days (Quimby 1951). No evidence of male parental care exists for Z. hudsonius (Whitaker 1963). Survival: No information exists on survival rates for populations of Z. h. preblei. Whitaker (1963) observed an over-winter loss of 67% in a New York population of meadow jumping mice. Most of this loss was.assumed to be from insufficient fat stores to survive hibernation. Besides insufficient fat storage prior to hibernation, other observed mortality factors in Z. hudsonius include predation (Whitaker 1963, Poly and Boucher 1997} and cannibalism (Sheldon 1934). Other assumed mortality factors for Z. h. preblei include starvation, exposure, and disease. Population Structure: Armstrong et al. (1997) reported an overall sex ratio for all captured Preble's meadow jumping mice of 51. 6 males: 48.4 females; approximately 86. 0% of captures were identified as adults. However, Armstrong et al. (1997) suggested that these data be interpreted with caution because of possible differences in field techniques. Longevity: Very few individuals of Z. h. preblei have been permanently marked. Therefore, recapture information, necessary to determine longevity, is minimal. Several recaptures have yielded adults surviving through two years, indicating a longevity of at least three years (T. Ryon, unpublished data). One recapture history from Rocky Flats Environmental Technology Site recorded an adult male in 1996, two years after it was first captured as an adult in 1994, indicating survival of at least four years (PTI 1996b). Quimby (1951) found that only a low percentage of Z. hudsonius lived two years or more, but gave two records of mice that lived for at least two years under natural conditions. Whitaker (1963) reported a female living at least two years. Dispersal.: Dispersal information will be key to any conservation strategy designed for Preble's meadow jumping mouse. Key factors include (1) which segment of the population disperses, (2) when do they disperse, (3) through what habitat do they disperse, (4) how far will individuals disperse (i.e., what is the maximum distance that separates adjacent populations) and (5) how critical is dispersal (both into and out of a population) to the persistence of a given population. The only data available on dispersal and/or movement for Z. h. preblei are from marked mice at Rocky Flats Environmental Technology Site (T. Ryon unpublished data). Two mice, an adult female and an adult male, were observed approximately 1.6 kilometers from previous locations (incidences occurred separately). Each of the locations were in the same drainage (Woman Creek). Population Persistence: For purposes here, population persistence is defined as the presence of Z. h. preblei at the same site for multiple years. The majority of recent locations of meadow jumping mice have been the result of survey efforts that focused only on determining presence of Z. h. preblei. Once survey protocols (USFWS 1997b) are met [i.e., a minimum of 400 trapnights (one trap set for one night = 1 trapnight) conducted] sites are typically not revisited eliminating the possibility of determining population persistence at these sites. Thus, these and other sites not yet surveyed may or may not have persistent populations. Areas where trapping was conducted over multiple years as part of further research, yielded three sites in Colorado that support persistent populations: Rocky Flats Environmental Technology Site, the U. S. Air Force Academy near Colorado Springs, and Boulder Open Space on South Boulder Creek. Besides establishing the presence of Z. h. preblei over multiple years, other considerations of persistence include (1) presence in consecutive years versus a 'blinking' in and out of a population as would be expected in a metapopulation [a set of local populations which interact via dispersal of individuals moving among populations and where local extinctions and recolonizations occur (Levins �26 1970)], (2) how populations are sustained in a given area (e.g., source or sink populations), (3) maximum abundance supportable by a given area, and (4) fluctuations in abundance of a population over years. If Z. h. preblei exist in areas as part of a metapopulation or as a series of source-sink populations it would be critical to conserve and protect all key sub-population areas as well as critical habitat for dispersal. Detailed population studies, including estimating and determining factors affecting survival, reproduction, and dispersal rates, must be conducted to determine if Z. h. preblei occurs as either metapopulations or in source-sink populations. There have been no such studies conducted on Z. h. preblei or Z. hudsonius elsewhere to provide any supporting or refuting evidence of this hypothesis. Consistently low abundance in a given area due to limiting ecological requirements (e.g., size of area of suitable habitat) or fluctuations in population abundance, including years of low abundance, must be considered in any conservation strategies for Z. h. preblei because of the threat of complete loss of the population due to catastrophic or extreme environmental conditions. Some evidence exists for such fluctuations in population abundance at Rocky Flats Environmental Technology Site. Trapping surveys on the Woman Creek drainage yielded the following captures of Z. h. preblei: seven in 1993 (EG&G 1993), zero in 1994 (T. Ryon, unpublished data), one in 1995 (T. Ryon, unpublished data), two in 1996 (PTI 1996a), and 33 in 1997 (T. Ryon, unpublished data). Trapping effort was consistent from 1995-1997. Repeated trapping surveys conducted over different years intermittently yielded successful captures of Z. h. preblei along the St. Vrain Creek and lower Coal Creek (three in 1989, zero in 1992, zero in 1994, zero in 1996, one in 1997, M. Bakeman, unpublished data). If protocols in each year were the same, these data also suggest populations may undergo fluctuations in abundance. Hibernation Jumping mice of the genus Zapus are true hibernators, spending much of their lives in hibernation. Meadow jumping mice spend approximately 7 months (~210 days) per year in hibernation (Quimby 1951) whereas estimates for Z. princeps indicate that some populations (e.g., in the western mountains of Utah) spend up to 300 days per year in hibernation (Cranford 1983). Males emerge prior to females (Bailey 1923, Bailey 1929, Hamilton 1935, Quimby 1951, Whitaker 1963) with the earliest annual recorded dates for Z. hudsonius males being April 25-May 16 and females May 4-26. Trapping surveys for Z. h. preblei were not designed to provide estimates for dates of immergence or emergence. However, such dates might be approximated by earliest spring and latest fall capture dates. The earliest spring capture date recorded for an adult male was May 5 in 1993 at Rocky Flats Environmental Technology Site (M. Bakeman unpublished data) and for an adult female, May 21 in 1996 also at Rocky Flats Environmental Technology Site (PTI 1996b). Latest fall capture date for an adult male was October 10 in 1994 at South Boulder Creek (ERO Resources 1995) and September 28 in 1995 at the Van Fleet Parcel on South Boulder Creek (Armstrong et al. 1997). A juvenile male was captured as late as October 26 and a female juvenile on October 27 both in 1995 at Rocky Flats Environmental Technology Site (M. Bakeman, unpublished data). Whitaker (1963) reported a 67% loss of individuals over hibernation and that average body mass of individuals emerging from hibernation was greater than the average for mice entering hibernation. Because no mice are known to store food in their hibemacula, this indicates that the lighter individuals died during hibernation and only those entering with higher masses survived. All the energy they use during hibernation and the periodic arousals (the energetically most expensive part of hibernation) must be the fat they carry into hibernation (B. Wunder, personal communication). Thus, the ability to put on sufficient fat for overwinter survival during hibernation is a critical factor in the life history of these mice. Jumping mice hibernate in underground burrows (Quimby 1951, Whitaker 1963). They are excellent burrowers and create their own hibemacula Meadow jumping mice are generally solitary hibernators, however, there have been occurrences of more than one mouse found in a single hibemaculum. One hibemaculum, located on Rocky Flats Environmental Technology Site, used by Z. �27 h. preblei has been located (Armstrong et al. 1997). This site was 9m above a creek bed (Walnut Creek); it had a thick cover of chokecherry (Prunus virginiana) and snowberry (Symphoricarpos spp.), the mouse was found in a leaf litter nest 30cm beneath the ground in coarse textured soil (Armstrong et al. 1997). Four possible hibemacula were located by tracking radio-telemetered mice at the U. S. Air Force Academy in fall 1997. These sites are located 7, 12, 29, and 31 m from a creek bed (R Schorr, personal communication). There was no consistency among sites in aspect (N/NW, SISE, E, and none [level ground]). Three sites were in vegetation dominated by coyote willow (Salix exigua), one site was in vegetation dominated by snowberry and mullein (Verbascum thapsus). However, all four hibemacula appear to be below coyote willows. These four U. S. Air Force Academy sites have not been disturbed to protect any hibernating mice and therefore are only possible hibemacula because there is no confirmation a mouse is actually hibernating there. Confirmation of a true hibemaculum cannot be made until a chamber, or nest is located. These sites may also possibly be locations of radios discarded by the mice or dead mice. Behavior Jumping mice, including Preble's meadow jumping mouse, are primarily nocturnal or crepuscular but can be observed during the day. Unlike most other nocturnal small mammals Preble's meadow jumping mice do not spend the day underground. The mice can be observed during the day, often under shrubs attempting to remain still (M. Bakeman, T. Ryon, R Schorr personal communication). The shrubs may provide either cover from predators or thermo~regulation. As their common name suggests, the saltatorial ability ofjumping mice is well developed. Although longer jumps have been observed the typical behavior is an initial jump of 60 - 90cm followed by rapid jumps of approximately 30cm (Quimby 1951). The more common mode of locomotion, however, is to crawl through or under grass and other vegetation flattening their bodies close to the ground and proceeding quadrupedally (Quimby 1951). Similar jumping and crawling behavior has been observed in Preble's meadow jumping mice as well as running, jumping, and climbing through shrub canopies (M. Bakeman, C. Meaney, T. Ryon, R Schorr personal communication). Given their preponderance for riparian habitats, it is not surprising to find that the mice are also strong swimmers (M. Bakeman, C. Meaney, R Schorr, personal communication). Both swimming and jumping abilities apparently serve more commonly as mechanisms for retreat from either predation or perceived threats rather than as typical mechanisms for locomotion. The mouse is also adapted for digging and creates nests of grass, leaves, and woody material (Harrington et al. 1996). All nests found at the Rocky Flats Technology Site, with the exception of the hibemaculum, were above-ground, generally at the base of willow (Salix spp.) clumps (M. Bakeman, personal communication). There does not appear to be any social structure among individuals within a population of jumping mice. No evidence exists for parental care by the male or any interaction between males and females after breeding occurs. Adults of the species Z. hudsonius are essentially solitary individuals. Except when young, jumping mice are usually silent. On occasion adults have been heard to emit chirps and other sounds (Quimby 1951, Whitaker 1963). No observations have been made of vocalizations by Preble's meadow jumping mice. Drumming noises can be produced by vibrating the tail rapidly against a surface (Svihla and Svihla 1933, Sheldon 1938, Whitaker 1963). Tail rattling, appearing to be a nervous reaction when placed in a capture bag, has been observed in Preble's meadow jumping mouse (M. Bakeman, personal communication). Quimby (1951) and Whitaker (1963) reported that mice in the genus Zapus often washed their feet, faces, and especially their tails. The tail was grasped in the forepaws, and passed completely through the mouth, whereas the hands and feet were washed by means of the forepaws. Bailey (1926) found that jumping mice would reach as high as it could on grass stems, bite them off and pull them to the ground, repeating the procedure until the head was reached and eaten. This process would result in a pile of pieces of grass stem, often with the rachis and glumes on top. Whitaker (1963) found similar behavior in his study of meadow jumping mice in New York. M. �28 Bakeman (personal communication) found piles of pieces of grass stem in areas where Preble's meadow jumping mice were known to occur, however these piles may also have been created by individuals of the species Microtus. Food Preferences Specific food habits are unknown for Preble's meadow jumping mouse. Armstrong et al. (I 997) summarized what is currently known about food habits of meadow jumping mice in general as follows: Studies of food habits in central and eastern United States indicate they are governed by • availability more than preference (Whitaker 1963). Grass seeds of several species are probably the most important component of the diet, and mice will shift to those species that have available seed. Invertebrates and fungi are also readily eaten. Mice feed on both adult and larval invertebrates, especially Coleoptera (beetles). Invertebrate feeding is very important in the spring as mice emerge from hibernation, and may consist of half of the diet at that time. Mice also feed on various species of fungi, which are often encountered during burrowing activity. As the growing season progresses, graminoid seeds dominate the diet. There is no reason to believe food habitats of one subspecies should differ greatly from those of other subspecies. This belief is further supported by the indirect evidence available that food habits of Z. h. preblei are similar to that described above (i.e., the observation of the piles of grass stems observed in areas where the subspecies is known to occur [see Behavior section]). • As true hibernators, meadow jumping mice do not cache food in their hibernacula Therefore, it is assumed they require high quality food for high fat accumulation prior to immergence. Preble's meadow jumping mice have been observed to increase body weight by 10% in the 2-3 weeks prior to immergence. Laboratory studies show the mouse can gain mass at rates up to 1.0 grams per day (B. Wunder, personal communication). This ability to increase fat reserves at such a rate is used by the mice for preparation to enter hibernation. However, for the mice to successfully gain enough fat prior to hibernation to ensure a high probability of survival throughout hibernation, food of sufficient quality must be available. No specific information is available on what foods Preble's meadow jumping mice eat to meet these ecological requirements. However, from late August through early September, when adults begin to gain weight, there are many species of graminoids that have available seed. In most years, grasshoppers are also readily available and probably dominate invertebrate biomass in most habitats. Preble's meadow jumping mice are most often found near open water. Dependency on open water has not been established, however work is currently in progress to establish if such a need exists (B. Wunder, personal communication). Based on trapping records at Rocky Flats Environmental Technology Site, trapping success at some sites declines dramatically after creekflow ceases, and it is suspected there may be a shift in site use because of the absence of open water (M. Bakeman personal communication). Habitat Use Landscape scale: The habitat matrix within the range of Z. h. preblei is mixed grasslands adjacent to the Colorado Front Range along the Piedmont and along the base of the Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, Preble's ~eadow jumping mice occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major components. The first component is a supply of open water, at least in part of the active season (M. Bakeman, C. Meaney, personal communication). Secondly, areas where Preble's meadow jumping mouse has been found have dense cover (M. Bakeman, C. Meaney, personal communication). �29 If Preble's meadow jumping mouse behaves as a metapopulation in the classical sense of a set of local populations linked by infrequent dispersal then habitat includes not just one area of suitable habitation but also areas suitable for nearby mouse populations. These suitable areas must also be linked by dispersal habitat. If the mice are dependent on dense riparian habitat for dispersal as well as for areas to reproduce, persistence of discrete populations would require a mosaic of suitable discrete riparian patches interconnected with dispersal corridors of similarly dense riparian vegetation. If mouse populations function in a source (populations where growth rate~ 1) and sink (those populations where growth rate< 1, maintained through immigration) system, it will be critical to identify and protect those populations serving as sources. Thus, for a source-sink population critical habitat will include those areas that support source population, dispersal habitat to sink areas will be less critical. If local mouse populations are functionally discrete, such a mosaic of interconnected areas of suitable habitat would provide a buffer for local, and source, populations against deleterious stochastic events by providing the opportunity for local population failures to be 'rescued' by immigration from other populations. Areas of suitable habitat must also provide requirements to survive throughout the life cycle. These requirements must provide necessities for both the active period and hibernation periods. During the active p·eriod suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence), and dispersal. The hibernation period requires sufficient food supplies to assure fat storage prior to hibernation and suitable hibemacula (see Hibernation above). Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. Site sca/,e: Based on studies of Z. h. preblei and Z. hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but is often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). Preble's meadow jumping mice have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road use, and moderate cattle grazing (M. Bakeman, personal communication). The majority of sites where Z. h. preblei have been found consist of multistoried cover but the species composing the cover vary greatly (Armstrong et al. 1997, Meaney et al. 1997) . Vegetation composition of the dense cover varies considerably and includes both native and non-native species (Meaney et al. 1996, 1997, Armstrong et al. 1997, M. Bakeman, personal communication). The herbaceous understory can be primarily grasses or forbs or a mixture of the two. Few of the sites, however, are dominated by fewer than two understory species. The tall shrub canopy at most sites is willow (several species), although scrub oak, birch, and alder occur in sites south of the Palmer Divide (Armstrong et al. 1997). Ponderosa pine is the most common tree at higher elevations. The mouse appears to tolerate weedy or exotic species in areas that are structurally diverse and species rich; nearly every successful site contained Canada thistle (Armstrong et al. 1997). Thus, the mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. Preble's meadow jumping mouse mice are typically not found in upland areas away from riparian habitats but are most often captured where either ground water daylights to seep springs or on main water channels (M. Bakeman, T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. Movement of Z. h. preblei on Woman Creek at Rocky Flats Technology Site suggests mice move along corridors of shrub cover, generally Salix exigua (PTI 1996a, T. Ryon, unpublished data), suggesting dispersal habitat is similar to habitats used for other activities. �30 SMALL MAMMAL ASSEMBLAGE Preble's meadow jumping mice are only one component of the small mammal community inhabiting areas where they were captured. These mice were more often found at sites with high species richness and abundance of small mammals (Armstrong et al. 1997, Meaney et al. 1997). The variety and relative abundance of other small mammalian species trapped during surveys for Preble's meadow jumping mouse provide some framework for comparison of small mammal assemblages at sites where Z. h. preblei occurred and sites where no Preble's meadow jumping mice were captured (Table 2). All trapped sites were either historical sites of known occurrence or apparently suitable habitat for Z. h. preblei, providing a common basis for comparison. Three small mammal species (Spermophilus variegatus, Peromyscus nasutus, and Rattus norvegicus) were not captured where Z. h. preblei occurred but were captured in unsuccessful sites. However, total capture occurrences of these three species were only one or two sites and the species comprised an extremely small percentage of the species caught in those areas (Table 2) providing too little information for speculating on possible interactions between these species and Z. h. preblei. Table 2. Small mammal community analysis from sites where Preble's meadow jumping mice (Zapus hudsonius preblei) were captured (n = 28) and not-captured (n = 35). Reported here are number of occUITences a given species was found in areas with and without Preble's meadow jumping mice captures (n and mean percentage and standard error (se) of capture that given species contributed to total small mammal captures at a given site. Data are summarized from Armstrong et al. (1997) and Meaney et al. (1997). All sites were either areas of historical occUITence of Preble's meadow jumeing mice {n = 82 or OCCUITed in areas of aeearently suitable habitat. 0) Z. h. preblei Not Captured Z. h. preblei Captured Species % Capture mean (se) no % Capture mean (se) no Zapus hudsonius prehlei 28 6.65 (1.38) 35 Spennophilus variegatus 0 0 2.0 Peromyscus nasutus 0 0 3.0 Rattus norvegicus 0 0 2 9.5 (8.2) l.0(-) 0 0 Mustela sp. Chaeotodipus hispidus 2 1.4 (0.2) 5 3.0 (0.8) Mus musculus 3 5.8 (4.6) 17 18.4 (6.0) Sorex cinereus 4 1.1 (0.7) 5 2.0 (0.5) Microtus longicaudus 5 15.8 (6.3) 3 9.6 (4.3) Neotoma mexicana 5 6.1(1.7) 8 12.5 (3.6) Reithrodontomys megalotis 5 3.6(1.4) II 3.7 (0.6) Microtus spp. 8 18.3 (6.4) 4 5.7 (4.3) Microtus ochrogaster 18 16.0 (3.7) 25 13.0(3.5) Microtus pennsylvanicus 21 26.2 (4.4) 32 25.8 (4.4) Peromyscus maniculatus 27 50.4 (3.4) 32 54.8 (5.2) �31 The higher occurrence and percent composition of capture of Mus musculus, the house mouse, in areas where Z. h. preblei was not caught might suggest degradation of habitat for Z. h. preblei in those areas or possibly competition between the two species (Ryon 1996). The house mouse, thrives in areas of human habitation and croplands, but also occurs in abandoned fields and ditch banks where they may displace native rodents (Fitzgerald et al. 1994). Ryon (1996) also reported the presence of domestic cats (Fe/is catus) at sites where Z. h. preblei historically occurred but were not found during his study. Contrarily, C. Miller (personal communication) reported house cats along South Boulder Creek where Preble's meadow jumping mice are known to occur. Caution must be used when percentage of capture is used as an index.to the composition and relative abundance of small mammals within a given area Captures may be influenced by trap placement, bait, season, or trapping protocol. Percentage of capture for a given species may also be biased because of either trap-shy or trap-happy individuals within a species or because some species, in general, tend to be easier or harder to trap. Preble's meadow jumping mice appear to favor 'clean' traps. Once traps have been used and soiled by individuals of other species, the probability of capturing a meadow jumping mouse in that trap appears to decrease (M. Bakeman, A. Deans, F. Harrington, T. Ryon, personal communication). For example, of the 60 captures of Z. h. preblei by M. Bakeman (unpublished data) in 1997 all were captured in traps that had only previously been occupied by Preble's meadow jumping mice. Evidence to the contrary, however, also exists. On at least one occasion, R Schorr (personal communication) caught a Preble's meadow jumping mouse in a trap previously occupied by Sorex sp. If one does assume no trapping biases occurred, where captured, Z. hudsonius was one of the less common species in the areas trapped (Table 2). If such rarity in areas of occurrence is genuine then this combined with both its limited distribution and absence from historically occupied areas supports the need for immediate protection of the subspecies and its habitat. POSSIBLE THREATS TO CONSERVATION •The range of Z. h. preblei corresponds largely to the rapidly developing ~ront Range Urban Corridor that runs from Colorado Springs, Colorado to Laramie, Wyoming. Therefore, possible threats to Z. h. preblei survival may include the widespread destruction and modification of riparian corridors and wet meadow habitats by human land uses (USFWS 1997 a). Agricultural, residential, commercial, industrial, and recreational development are likely the cause of such impacts. Specific activities such as water diversion, stream channelization, and sand, gravel and aggregate mining have impacted habitats required by the mouse Other activities such as overgrazing and development of recreational trails may also impact Preble's meadow jumping mouse habitat. Armstrong et al. (1997) summarized results of habitat studies conducted on Z. h. preblei, including the following summary of disturbance elements. Over the past 100 years the [riparian habitat used by Z. h. preblei] has become increasingly urbanized as influenced by grazing, water diversions, wetland conversion, and real estate development. Compton and Hugie (1993) identified agricultural, residential, and commercial development as habitat impacts and suspected grazing as having a negative influence on meadow jumping mouse habitat. Ryon ( 1996) identified alterations to habitat at eight historic meadow jumping mouse sites. These alterations include water diversion, highway construction, gravel mining, grazing, and real estate development. Although suitable habitat exists within this landscape unit, the anthropogenic influence is changing the unit as a whole and fragmenting and degrading riparian areas in general. The effect of these land use practices on mouse distribution is poorly understood. Several investigators have been puzzled at the lack of jumping mice at sites with seemingly well structured habitat, and the presence of mice at a few sites with less than optimal conditions. Land use histoiy of an area may provide clues as to whether mice are at a site or if they can be �32 restored. The reviewers of the [Report on Habitat Findings of the Preble's Meadow Jwnping Mouse, edited by M. Bakeman] list six potential impacts that were thought to play a role in distribution of Z. h. preblei including trails, grazing, mining, development, haying, and riparian hydrology. In order to threaten conservation of Z. h. preblei a feature or features of their ecological requirements must be altered in such a way as to make the area unusable to the mouse or limit its usefulness to such an extent as to deplete the areas' potential for supporting a viable population of Z. h. preblei. Therefore, a threat is defined as any activity that_has the potential to negatively alter any ecological requirements of Z. h. preblei. Effects of the potential threats, listed below, may be permanent or temporary. Management strategies may be developed to offset or eliminate effects from various activities. However, such management strategies are only as good as our knowledge of the full complement of ecological requirements necessary to maintain a viable population of Z. h. preblei. The following defines such ecological requirements, provides specific examples of activities that could negatively alter these requirements, and suggests how these negative impacts would affect the mouse. Vegetation composition and structure Vegetation composition and structure affects many of the ecological requirements of meadow jumping mice including food, cover, nest sites, and suitable dispersal corridors. Vegetation composition in areas inhabited by Preble's meadow jumping mouse must include species that would provide not only daily nutritional requirements but also high quality foods necessary for the quick, high fat storage that occurs prior to hibernation. Cover may provide concealment from predators, areas for thermoregulation, and raw material for above-ground nests. Above ground nests appear to be associated with woody (tree and shrub) structures (M. Bakeman, personal communication). Dispersal habitat must provide sufficient cover and food to assure successful dispersal from one area to another. Activities which could threaten vegetation structure include: grazing, development (including residential, commercial, industrial, and recreational), fire, sand, gravel and aggregate mining. Grazing may alter vegetation structure by either decreasing or eliminating sufficient tree, shrub, and/or tall grass cover. Heavy grazing is especially hard on woody plants. Species composition may also be altered by grazing, eliminating critical food resources. Development of an area may impact species composition, abundance, and density. Developments such as cutbanks would eliminate all vegetation. Short-term effects of fire may be deleterious if above-ground nests (especially with young) are destroyed. Longterm effects may be minimal, if the population can withstand minor losses. Mining operations for aggregate material generally eliminates most vegetation, affecting both structure and composition. Possible deleterious effects on populations of Z. h. preblei include decreased survival, reproduction, or ability to disperse. Riparian Hydrology Hydrology includes physical presence of open water, water quality, seasonality of available open water and amount of water flow. Activities which could threaten suitable hydrologic regimes for populations of Z. h. preblei include water diversion projects, water management projects including irrigation regimes and ditch maintenance, and pollution. These activities could result in loss or increase of surface water supplies, alter flooding events which may be necessary to maintain vegetation composition and structure, and produce siltation in catchment areas. Such activities do not actually have to occur on areas of suitable Z. h. preblei habitat but could occur upstream or downstream of the site. Mining operations can indirectly affect habitat by altering downstream hydrological flows of both surface water and groundwater. Urbanization may affect water quality and stream flows through siltation of catchment areas, presence of pesticides in water, increased nutrient load, and vegetation composition. At Rocky Flats Technology Site, Preble's meadow jumping mice are most often captured where either ground �33 water daylights to seep springs or on main channels fed by seep springs (T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. Possible deleterious effects on populations of Z. h. preblei if riparian hydrology is altered include decreased survival or reproduction. H abitaJ structure Habitat structure includes size of suitable area, connectivity of suitable sites to other suitable sites through corridors, and inclusion of all ecological requirements within a given area Thus, altering habitat structure could result in fragmentation of a suitable site, isolation. of a site to other suitable sites, degradation of a suitable site, or total loss of useable habitat Activities which could threaten habitat structure include: aggregate mining, grazing, real estate development, pollution, and fire. Movement of Preble's meadow jumping mice on Woman Creek at Rocky Flats Technology Site suggests mice move along corridors to patches of the most suitable habitat. Most captures occur in areas of shrub cover, generally Salix exigua (PTI 1996a, T. Ryon, personal communication). Possible deleterious effects on populations of Z. h. preblei include decreased abundance due to a decrease in suitable habitat, loss of inter-connectivity of sites that may be necessary to maintain viable populations either in a source-sink or metapopulation situation, and may also result in decreased gene flow through isolation. Distribution Distribution can be defined on several scales: range perimeter, distribution within the range, and distribution within connected suitable habitat. As discussed above (see Distribution section), based on a comparison of currently known sites and historical sites of occurrence of Z h. preblei it is clear distribution (within the historical range) has already been altered. Activities which could alter distribution of Z. h. preblei include real estate development and sand, gravel and aggregate mining by severely degrading or completely eliminating required habitat. Possible deleterious effects on Z. h. preblei include loss of populations throughout the complete ecological range of suitable habitat and further fragmentation within the range of Z h. preblei. These effects could (I) eliminate critical populations of Z. h. preblei to maintain possible metapopulations or source populations or (2) restrict gene flow among populations. Geomorphology Geomorphology is defined as the description of features of the earth's surface as explained by the underlying dynamic and structural geology. Important geomorphological features that may help delineate habitat for Z. h. preblei include stream and floodplain geometry. Steepness of stream banks may affect vegetation composition ans structure. Underground structure along stream banks may provide critical hibemacula sites. Activities that would affect geomorphology include development and mining of sand, gravel, and aggregate material. Preble's meadow jumping mice have rarely been captured in steep-sided drainages (M. Bakeman, personal communication). Possible deleterious affects of altering the geomorphology in areas used by Preble's meadow jumping mouse include decreased survival due, possibly, to insufficient availability of suitable hibemacula Animal Community Composition Animal community composition includes the ocuurance and abundance of all other species in Preble's meadow jumping mouse habitat. The primary activity that may affect populations of Z. h. preblei is development. In particular, the introduction of the house mouse and the house cat may alter the suitability of a site for Preble's meadow jumping mouse; the house cat as a new and effective predator, the house mouse as a possible �34 competitor for resources. Other possible effects of altering the animal community is the introduction of new diseases and parasites to Preble's meadow jumping mouse. The possible deleterious effects of altering the animal community within areas of habitat for Preble's meadow jumping mouse include decreased survival through increased predation, disease, parasites, or competition for resources. CONSERVATION STRATEGY INTRODUCTION This preliminary conservation strategy describes the current status and the goal, objectives, strategies, and research that should be implemented to maintain and restore viable populations of Z. hudsonius throughout its range and to conserve and manage Preble's meadow jumping mouse habitat. This is intended to be a preliminary planning effort based on the best scientific data available to date. This strategy may also serve as a starting point for more comprehensive conservation planning efforts regarding Z. h. preblei. • This strategy is designed to be implemented through the cooperation of state, federal, and municipal government agencies, and involve partnerships with private conservation organizations, individuals, and landowners. The outlined conservation strategy objectives are not necessarily listed in order of priority, but in a logical manner that provides for completion of information needs prior to addressing specific actions. CURRENT STATUS On March 25, 1997 the U. S. Fish and Wildlife Service (USFWS) published a proposed rule in the Federal Register (62 FR 14093) to list Preble's meadow jumping mouse (Z. h. preblei) as 'endangered' under the Federal Endangered Species Act (ESA). Final ruling on the proposed listing is scheduled by March 25, 1998. There are three possible outcomes depending on progress of conservation efforts and knowledge gained prior to the decision date: list as endangered, list as threatened, or withdraw the proposal. The primary reason for the proposed listing of Preble's meadow jumping mouse under Section 4 of the ESA is 'present or threatened destruction, or modification ofits habitat or range' as well as lack of meaningful protection. The listing decision will be made by the U. S. Fish and Wildlife Service solely on the basis of the best scientific data available. As stated in USWFS 1997b: "All Federal agencies have responsibility under section 7(a)(4) of the ESA to protect proposed endangered and threatened species and habitats on which they depend. For projects where a Federal nexus exists (Federal permit, Federal funding, projects on Federal land) and there is potential affect on Z. h. preblei or its habitat, the Federal action agency should contact the USFWS. In addition, the USFWS encourages all Federal agencies to review their properties and projects and make funds available to conduct Z. h. preblei surveys in all potential habitat. It is also imperative to make project proponents aware of the presence of Z. h. preblei should it be listed prior to the time all actions related to any project are completed. Section 9(a)(l) of the ESA prohibits the take (i.e., harass, harm, pursue, hunt, shoot, kill, wound, trap, capture, or collect, or to attempt to engage in any such conduct) of federally endangered or threatened species, except as provided in sections 6(g)(2) and 10 of the ESA. If Z. h. preb/ei is listed while a project is impacting it or its habitats, the ESA would enter into effect to protect Z. h. preblei. A project occurring in poor or marginal habitat but having potential to disrupt a travel corridor (such as a road crossing a creek) is also of concern as well as the question of secondary impacts from proposed projects. Projects removed from potential Z. h. preblei habitat that have the potential to adversely impact the habitat may also require a survey. For example, a residential or commercial development upslope from a creek supporting potential Z. h. preblei habitat may significantly increase runoff or otherwise impact the hydrology, and thereby the habitat present on the creek." Therefore, even prior to a decision on the proposed listing, there is a �35 great need to provide information on the ecology and ecological requirements necessary for conservation of Z. h. preblei. The species Z. hudsonius was designated as Colorado nongame wildlife (Colorado Division of Wildlife Regulations, Chapter 10, Article N, #1004 A 6), which provides a legal protection against taking. It is also a Colorado Division of Wildlife Species of Special Concern, which is an administrative classification rather than a legal one. However, there are current efforts within the Colorado Division of Wildlife to list the subspecies as State Endangered (J. Sheppard, personal communication), defined as any species or subspecies of native wildlife whose prospects for survival or recruitment within the state are in immediate jeopardy. The Colorado Natural Heritage Program (1997) lists the mouse as an S2 species: imperiled in the state because of rarity (6 to 20 occurrences) or because of other factors demonstrably making it very vulnerable to extirpation from the state. Conservation of Preble's meadow jumping mouse was also listed as a specific task to be addressed by both the State of Colorado and the Department of the Interior in the Memorandum of Agreement (94SMU-058), signed by Governor Roy Romer and Interior Secretary Bruce Babbitt on November 29, 1995, between the State of Colorado and the Department of the Interior concerning 'Programs to Manage Colorado's Declining Native Species.' The Wyoming Natural Diversity Database (Fertig 1997) ranks Z. h. preblei as S 1: critically imperiled in the state because of extreme rarity (five or fewer extant occurrences or very few remaining individuals) or because of some factor of the subspecies life history that makes it vulnerable to extinction. The Wyoming Department of Game and Fish (1998) ranks the subspecies as nongame through their Nongame and Wildlife Habitat Protection Programs. GOAL The goal of this conservation strategy for Preble's meadow jumping mouse should work towards the sustainability, protection, and restoration of Z. h. preblei populations and habitats on both private and public lands to provide the spatial, genetic, and demographic structure needed to promote long-term species viability and provide species management flexibility. Specific objectives include the following. OBJECTIVES I. 2. Document the present distribution of Z. h. preblei. This will require the following: • Conduct trapping surveys to better define the boundaries of the range of Z. h. preblei.; conduct trapping surveys in areas of potential sympatry of Z. h. • preblei with Z. princeps; evaluate effect of small mammal species richness and composition on the distribution and/or abundance of Z. h. preblei. • Further explore genetic relationships among different Z. h. preblei populations, among different subspecies of Z. hudsonius, and among different species of Z:O.pus. Identify populations of Z. h. preblei where the rate of population growth <!: 1. This will require population studies to estimate the following parameters: • Survival (annual, over-summer, over-hibernation), and identity of factors affecting survival [e.g., weight, sex, age, abundance (i.e., density dependent Z. h. preblei response), habitat features (e.g., stream reach, vegetation composition), weather, predation, disease]. • Reproductive and developmental parameters (i.e., number oflitters per year, number of young per litter, age at first reproduction, juvenile survival), and identity of factors affecting reproduction [e.g., habitat features (i.e., food quality, nest site availability, cover availability), abundance (i.e., density dependent response), weather]. • Recruitment, and identity of factors affecting recruitment (e.g., weather, habitat features). • Immigration and emigration rates, and identity of factors affecting immigration, emigration (e.g., age, habitat features, abundance). �36 3. 4. 5. • Population structure (sex and age ratios) • Dispersal parameters (rate, who disperses, time of dispersal) • Abundance, and identity of factors affecting abundance (e.g., habitat features). • Rate of population change. Protect populations of Z. h. preblei where the rate of population growth is ::1: I. Maintain current range of natural variability of Z. h. preblei. Identify ecological requirements for sustaining viable populations of Z. h. preblei throughout its range of natural variability. This will require research to address the following: • Estimate habitat use [distances traveled (daily, seasonally), landscape features (connectivity with other potential sites, geology), seasonal use, hibemacula, nest sites, distance to nearest open water, hydrology (water quality, flow), abundance (i.e., density dependent responses), and cover]. • Dispersal habitat [end point descriptions (disperses from what to what), landscape features (connectivity with other riparian strips, corridor use, overland use]. • Physiology (e.g., estimate dependency of Z. h. preblei on open water, food habits, effects of varying water quality on Z. h. preb/ei physiology) . • 6. 7. 8. 9. 10. 11. 12. 13. Protect habitats to sustain or restore populations of Z. h. preblei with high where the rate of population growth ::1: 1. Promote protection, management, and possible restoration of habitat for conservation of Z. h. preblei in all currently or recently occupied and suitable habitat. Monitor the status of Z. h. preblei populations throughout its range to detect changes in local distribution. Identify threats to the conservation of Z. h. preblei. Eliminate or minimize threats to Z. h. preblei conservation. Integrate Preble's meadow jumping mouse conservation strategy objectives with management and habitat objectives of other Front Range riparian species. Promote scientific management of Preble's meadow jumping mouse. Promote public support for Z. h. preblei conservation efforts and scientific management of Preble's meadow jumping mouse through public education. RESEARCH NEEDS There are currently four research projects being conducted on Z. h. preblei, with a fifth planned to begin spring of 1998. Each of these projects is designed to provide further information on the ecology or demography of Preble's meadow jumping mouse. However, if research methodologies were standardized and coordinated across all the projects, comparability and quality of the data would be greatly enhanced. Such a coordinated effort would maximize data quantity, quality, and comparability over varying conditions throughout the range of Z. h. preblei in the most effective and efficient way possible. Comparable information gained across the ecological range of Z. h. preblei would then provide more useful information for use in developing sound management strategies for conservation of the mouse. To achieve such a coordinated research effort all project leaders must agree to follow data collection protocols, establish 'ownership' of data and future publications, and work cooperatively on the possible sharing of equipment and technical assistance during peak data collection periods. To facilitate such a mutual effort will require the participation of all project leaders conducting field studies of Z. h. preblei as well as cooperative investigators, and specialized data analysts with expertise in the study design, analysis, and interpretation of mark-recapture and telemetry data A proposed agenda including tasks, task leaders, and a timetable to initiate a cooperative research effort include: �37 Task Task Leader, Affiliation Date Identify all potential participants: project leaders, cooperating investigators, data analysts. T. Shenk, Colorado Division of Wildlife January 1998 Prioritize research questions. All project leaders* January 1998 Identify sites to best address prioritized research needs. All project leaders January 1998 Design studies specific to research question to be addressed at each site. All project leaders, cooperating investigators, data analysts January-February 1998 Evaluate needs at each site to conduct specified research. All project leaders March 1998 Identify discrepancies between needs and available funds, equipment, and personnel currently allocated for each site. All project leaders March 1998 Attempt to balance discrepancies. All project leaders, cooperating investigators March 1998 * To date: M. Bakeman, C. Meaney, T. Ryon, R. Schorr, T. Shenk The following outline lists research needs to provide information to develop sound management strategies for conservation of Z. h. preblei. Research needs are not listed in order of priority, but listed in a logical manner to provide completion of needs. There are three components of Z. h. preblei ecology that are currently unknown and yet key to any sound conservation strategy for the subspecies. These are (I) detailed demographic studies estimating survival and reproduction and determining the factors influencing each of the parameters, (2) detailed studies evaluating movements and dispersal habitat of individuals within and among populations, and (3) detailed studies to define hibernation needs, primarily descriptions of suitable hibernacula criteria and food requirements for sufficient fat storage prior to immergence. Demographic studies: Information on the population dynamics of Preble's meadow jumping mouse is necessary to determine which areas support populations where the rate of population growth is <!: 1. Key parameters to estimate include: Survival: • estimates of survival, including ► annual ► over-summer ► over-hibernation • investigate possible factors affecting survival, including ► weight ► sex ► age ► abundance (i.e., density dependent response) ► habitat features: stream reach, vegetation composition ► weather ► predation ► disease Approach: mark-recapture techniques �38 Recruitment: • estimate recruitment (as an alternative to reproductive parameters listed below) • investigate possible factors affecting recruitment, including ► weather ► habitat features Approach: mark-recapture techniques Population structure: • estimate sex ratios • estimate age ratios Approach: mark-recapture techniques Abundance: • estimate abundance • investigate factors affecting abundance, including ► habitat features (see under habitat use) Approach: mark-recapture techniques for closed populations Immigration, emigration: • estimate rates of immigration and emigration • investigate possible factors affecting immigration, emigration ► habitat features (see under habitat use) ► abundance (i.e., density-dependent response) Approach: estimate rates from mark-recapture data, identify existence with radio telemetry Reproduction: • estimate number of litters per year • estimate number of young per litter • estimate age at first reproduction • estimate juvenile survival • investigate possible factors affecting reproduction, including ► habitat features: food availability, nest site availability, cover availability ► abundance (i.e., density-dependent response) ► weather Approach: from telemetry work Dispersal Studies: Dispersal is a key process in metapopulation theory and to maintain genetic diversity between isolated populations. Key parameters to evaluate include: Population parameters • who disperses • time of dispersal • estimate rate Approach: estimate rate with mark-recapture, document who and when from both telemetry and mark-recapture data Habitat parameters • through what habitat • end point descriptions (disperses from what to what) • landscape features (connectivity with other riparian strips, corridor use, overland use) Approach: document where from both telemetry and mark-recapture data �39 Distribution Studies: Conservation of Z. h. preblei should maintain populations throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Key concerns include: Range-wide distribution: • conduct trapping surveys to better define the eastern boundary of the range of Z. h. preblei • conduct trapping surveys in areas of potential sympatry of Z. h. preblei with Z. princeps Approach: determine from trapping surveys Habitat Studies: To identify and define habitat requirements of Z. h. preblei studies should be conducted to address the following: Habitat use: • estimate distances traveled: daily, seasonally • describe landscape features (connectivity with other potential sites, geology) • determine seasonal use • describe hibernacula • describe nest sites • estimate distance to nearest open water from other habitats used • describe hydrology (water quality, flow) in areas of use • evaluate effects of abundance on habitat used (i.e., density dependent responses) Approach: estimate from telemetry work Physiological Studies: Physiological studies will provide information on the mechanisms driving habitat selection. Physiological, requirements: • estimate dependency of Z. h. preblei on open water • determine energetic requirements to survive hibernation Approach: estimate from laboratoiy studies Systematic Studies: To better define the relationship of Z. h. preblei to other subspecies of Z. hudsonius and other species of Zapus the following studies should continue. Molecular systematic relationships: • further explore genetic relationships among different Z. h. preblei populations • further explore genetic relationships among different subspecies of Z. hudsonius • further explore genetic relationships among different species of Zapus. Approach: explore through laboratoiy studies Systematic relationships: • link genetic relationships to systematic studies of Z. hudsonius. Approach: explore through museum studies Community Studies: Composition of the community where Z. h. preblei occur could help explain ecological tolerances of the subspecies, providing insight to the mechanisms determining its distribution. Small mammal assemblages: • comparison of small mammal assemblages in areas where populations of Z. h. preblei occur and areas where they do not ► species composition ► relative abundance Approach: estimate from trapping surveys �40 LITERATURE CITED Armstrong, D. M. 1972. Distribution of mammals in Colorado. University of Kansas, Museum of Natural History Monograph 3:1-415. Armstrong, D. M., M. E. Bakeman, A Deans, C. A Meaney, and T. R Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Bailey, B. 1929. Mammals of Sherburne County, Minnesota. Journal ofMammalogy 10:153-164. Bailey, V. 1923. Mammals of the District of Columbia Proceedings of the Biological Society. Washington 36:103-138. Bailey, V. 1926. A biological survey ofNorth Dakota. U.S. Department of Agriculture North American Fauna No. 49:117-119. Colorado Division of Wildlife. 1997. Colorado's endangered, threatened, special concern, undetermined status and candidate species -Terrestrial species. Draft Report for the Colorado Division of Wildlife. Colorado Natural Heritage Program. 1997. Colorado's Natural Heritage: Rare and imperiled animals, plants, and plant communities. Volume III, No. 1. Unpublished Report for the Colorado Natural Heritage Program. Compton, S. A, and RD. Hugie. 1993. Status report on z.apus hudsonius preblei, a candidate endangered species. Pioneer Environmental Services, Inc. Report for the USFWS. Logan, Utah Logan, Utah. Cranford, J. A 1983. Ecological strategies of a small hibernator, the western jumping mouse Zapus princeps. Canadian Journal of Zoology 61:232-240. EG&G. 1993. Report of Findings: 2nd Year Survey for the Preble's meadow jumping mouse. Prepared by Stoecker Environmental Consultants for ESCO Associates, Inc., Rocky Flats Environmental Technology Site, Jefferson County, Colorado ERO Resources. 1995. Environmental review of South Boulder Creek Management Area Prepared for City of Boulder Real Estate/Open Space Department. Prepared by ERO Resources Crp., Denver, Colorado in association with Stoecker Ecological Consultants, Boulder, Colorado. Fertig, W. 1997. Wyoming plant and animal species of special concern. Wyoming Natural Diversity Database. Laramie, Wyoming. Fitzgerald, J.P., C. A Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. Hafuer, D. J., K. E. Petersen, and T. L. Yates. 1981. Evolutionary relationships of jumping mice (genus Zapus) of the southwestern United States. Journal ofMammalogy 62:501-512. Hall, E. R 1981. The mammals of North America John Wiley and Sons, Inc., New York, New York, 2 volumes. Hamilton, W. J., Jr. 1935. Habits of jumping mice. American Midland Naturalist 16:187-200. Harrington, F. A., A Deans, M. E. Bakeman, and B. J. Bevirt. 1996. Recent studies of Preble's meadow jumping mouse at the Rocky Flats Site, Colorado. Journal of the Colorado-Wyoming Academy of Science 28(1 ): Abstract 18. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. Levins, R 1970. Extinction. Lectures in Mathematical Life Sciences 2:75-107. Long, C. A 1965. The mammals ofWyoming. University of Kansas Publications, Museum of Natural History, 14:493-758. Meaney, C. A and N. W. Clippinger. 1995. A survey ofpreble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado division of Wildlife. Meaney, C. A, N. W. Clippinger, A Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. �41 Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preb/ei) in Colorado. Report prepared for the Colorado Division of Wildlife. Olson, T. E., and F. L. Knopf 1988. Patterns of relative diversity within riparian small mammal communities, Platte River watershed, Colorado. Pg. 379-386 in: Proceedings of the symposium: Management of amphibians, reptiles and small mammals in North America Flagstaff, Arizona U.S. Forest Service, General Technical Report RM-166. Poly, W. J., and C. E. Boucher. 1997. Record of a creek chub preying on a jumping mouse in Bruffey Creek, West Virginia Brimleyana 24: 29-32. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. PTI Environmental Services. 1996b. Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Spring 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, Zapus hudsonius. Ecological Monographs 21:61-95. Riggs, L.A., J.M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation. Final Report for the Colorado Division of Wildlife. Denver, Colorado. Ryon, T. R 1996. Evaluation of historical capture sites of the Preble's meadow jumping mouse in Colorado, final report. MS Thesis. University of Denver, Denver, Colorado. Ryon, T. R 1997. The evaluation of historic capture sites of the Preble's meadow jumping mouse in Colorado. in Report on habitat findings of the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Sheldon, C. 1934. Studies on the life histories of Zapus and Napaeozapus in Nova Scotia Journal of Mammalogy 15:290-300. Sheldon, C. 1938. Vermont jumping mice of the genus Zapus. Journal ofMammalogy 19:324-332. Svihla, A. and R D. Svihla 1933. Notes on the jumping mouse, Zapus trinotatus trinotatus Rhoads. Journal ofMammalogy 14:131-134. USFWS. 1997a Proposal to list the Preble's meadow jumping mouse as an endangered species. USFWS 50 CFR part 17. USFWS. 1997b. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. Whitaker, J. 0., Jr. 1972. Zapus hudsonius. Mammalian Species 11:1-7. Wyoming Game and Fish Department. 1998. Native species status classification system. Cheyenne, Wyoming. ��43 APPENDIX A Evaluating distinctness and evolutionary significance of Preble's meadow jumping Biosphere mouse: Phylogeography of mitochondrial DNA non-coding region variation. Final genetics Report to the Colorado Division of Wildlife inc Reply to: Box 9528, Berkeley, CA 94709 Tel: 510/531-4848 Fax: 510/530-0580 Email: bgioigc.org EVALUATING DISTINCTNESS & EVOLtrrIONARY SIGNIFICANCE OF PREBLE'S MEADOW JUMPING MOUSE: PIIYLOGEOGRAPHY OF MITOCHONDRIAL DNA NON-CODING REGION VARIATION FINAL REPORT DECEMBER 8, 1997 Submitted by Lawrence A. Riggs, Ph.D. John M. Dempcy, M.A. Cristian Orrego, Ph.D. Biosphere Genetics, Inc. Berkeley, CA Submitted to Judy Sheppard -Terrestrial Section Colorado Division ofWddlife Denver,CO �I • 44 Evaluating Distinctness & Evolutionary Significance of Preble's Meadow Jumping Mouse: Phylogeography of Mitochondrial DNA Non-Coding Region Variation Lawrence A. Riggs, John M. Dempcy, and Cristian Orrego SUMMARY We have generated molecular genetic data fotJ1:!~tal_Qf92.jup1ping mice including 71 sampled from 20 populations in Colorado and four populations in Wyoming, and 21 specimens representing three reference groups of closely related tua. DNA sequences obtained for a.433 basepair (bp)-long portion of the mitochondrial DNA non-coding region (sometimes referred to as the D-loop) in all samples indiQate that a group of populations ranging from southeastern Albany County, Wyoming, south along the Front Range of the Rocky Mountains to western Las Animas County, Colorado, fonn a coherent group, both genetically and geographically. This group, which we refer to as the "Preble's group" is distinct from four of five other populations sampled by live trapping or from museum specimens and may be somewhat differentiated from the fifth of these. The Preble's group is also clearly distinct from two of the three reference groups and less markedly differentiated from the third. Phylogenetic analyses based on these data are still at a preliminary stage and indicate that the Preble's group of populations is most closely allied with, and not strongly differentiated from, samples of Z. h. intennedius from Minnesota. Of the four populations that appear to be distinct from the Preble's group, two sampled near the Colorado-New Mexico border are closely allied with museum specimens identified as Z. h. luteus from New Mexico. Two others from the vicinity of Cheyenne, Wyoming, are most similar to representative samples of Z. princeps from western Larimer Co., Colorado and are next most closely allied with a Z. princeps specimen from northern New Mexico. A suggestion from our analysis is that Z. hudsonius from Indiana (possibly either Z. h. americanus or Z. h. intennedius based on distribution) may be the most ancestral of the populations and taxa sampled and may have shared a common ancestor with progenitors of fonns presently known as .Z: princeps princeps and Z. h. luteus. BACKGROUND • Recent applications of molecular genetic methods in systematics, population genetics, and conservation biology have demonstrated that variation in DNA markers can • be highly infonnative in the evaluation of genetic distinctness and evolutionary significance, two important determinants in decisions regarding application of the Federal Endangered Species Act of 1973 as amended and interpreted by the U. S. Congress. The study descnoed here sought to discoyer whether and how molecular data might support and help objectify the view, based on other more traditional criteria, of the Preble's mouse as an evolutionary unit distinct from other species and subspecies in the genus 7,apus. I, �45 Preblc's DNA study Final Report/12-8-97 Work funded by the Colorado Division of Wtldlife (hereafter CDW) and performed by Biosphere Genetics, Inc. has evaluated the ability of three different approaches to quantifying variation in the DNA molecule to provide reliable and infonnative data addressing issues of key importance in the decision of whether or not to list the Preble,s mouse. Previous reports to CDW have summarized our finding that RAPD (randomly amplified polymorphic DNA) markers are not sufficiently repeatable for use in the context of this study. Methods to assay variation in ~other class of genetic markers found in nuclear DNA called microsatellites or simple sequence repeats, although •potentially promising, are not yet sufficiently well developed and validated for zapodids to apply at this time. A third approach, DNA sequencing of the mitochondrial DNA noncoding region which includes the D-loop, emerged from preliminary work as the method most appropriate and informative, in combination with other more traditional criteria, for the determination ofwhether populations of the Preble's meadow jumping mouse (Zapus hudsonius preblei) constitute one or more distinct evolutionary units with significance warranting protection under the Federal Endangered Species Act. Results based on sequence variation in the mitochondrial DNA non-coding region assayed in a subsample of the 54 mice presumed to be Preble's obtained during the summer of 1996 indicated: (1) that 7 populations sampled at sites ranging from Longmont to Colorado Springs in Colorado varied relativ~ly little from one another,, (2) that two other populations sampled in Las Animas County near Lake Dorothey were similar to one another but differed quite markedly from the first group, and (3) that none of the individuals sampled in Laramie 'l ~ County in Wyoming could be assayed using the techniques successfully applied to the other samples, suggesting that this population may also differ to some degree from those in Colorado. Field surveys of the occurrence of the Preble"s meadow jumping mouse conducted by several individuals and organizations during the summer of 1996 were extended to additional sites in the summer of 1997. CDW spo0$0red some of these efforts and coordinated the collection, recording and· delivery of tissue samples for DNA analyses performed by Biosphere Genetics, Inc., also under contract with the Division. In addition, the U. S. Air Force supported DNA analysis of samples _obtained from trapping efforts during the· summer of 1996 on the Warren Air Force Base and the inclusion of reference material representing two additional subspecies of Zapus hudsonius,, Z. k palustris, and Z. k campestris. • METHODS Tissue Sampling and Storage A sampling protocol and data forms for using in obtaining samples for.DNA analysis were developed for CDW and distnouted to all parties participating in the coordinated trapping effort. The disseminated protocol, adapted and updated from the •U.S. Fish and Wtldlife Service standardized protocol, descnoed handling and instrument cleansing procedures to minimize contamination of the sample with human or other mammalian.DNA Very small samples of tissue were obtained from live-trapped �I. 46 Prcble's DNA study Final Rci,ort/12-8-97 • specimens of mpz(s by using a tagging punch (National Band and Tag Co., Newport, KY) to remove one or more plugs of tissue from the outer portion of each mouse,s ear. In some cases, ear tissue was obtained by clipping or notching the ear with scissors. Tissue plugs or pieces from a given animal were placed in a cryogenic screw-cap vial filled 1/31/2 full with 95% ethanol and labeled with an alpha-numeric code intended to uniquely specify trapping location and the individual animal caught. Hair samples were collected by some participants and placed either in a separate labeled vial or ~ the same vial containine the ear tissue. Samples were conveyed to CDW and accumulatec;{ into lots for deliveiy to BGL When ·samples were transported from the field or shipped by common canier, they were at ambient temperature. Upon receipt at BGI, samples were kept refiigerated at 4°C until tlie time of DNA extraction. Specimens obtained from field surveys and miscellaneous museum specimens used to expand coverage of the potential range of the taxa examined in this study are listed in Table 1 of the Appendix to this report. Reference specimen tissues used for comparison with field-sampledjumping mice were provided from four separate museum collections (see Appendix I, Table 2) as toes clipped from museum specimens or as small pieces of internal organs maintained iri the museum,s frozen collection, usually at-70°C. Toe clips were shipped at ambient temperature and refiigerated at 4°C upon receipt. Frozen specimens were shipped on dry ice and extracted upon receipt with any remaining tissue being transferred to ethanol for further storage. Reference specimens are listed in Table 2 of the Appendix to this report. DNA Extraction & Purification We extracted DNA from plugs or pieces of ear tissue using the Hair Lysis Buffer (HLB) method similar to that of Greer et al. (1995). The tissue was rinsed, either with a jet of triple-distilled water or by agitation in a drop of distilled water on Parafilm®, then placed in a volume ofHLB and incub~ted at S6° C with periodic agitation for 10-12 hours. In most cases, this process completely digested the sample leaving only a trace of particulate matter suspended or settled in the bottom of the tube. With the particulates centrifuged to the bottom, aliquots of the extract were withdrawn for fractionation and for purification prior to use in DNA amplifications. Raw DNA extracts were run out on 1.5% agarose gels and stained with ethidium bromide to quantify the DNA by comparison with staining intensity of Lambda Hind m fragments run on the same gel. We used Prep-AGenen.1 (Bio-Rad, Hercules, CA) to purify the DNA preparations before sequencing. Amplification of Mitochondrial DNA Non-coding Region Sequences We began our examination of the mitochondrial non-coding region using the primers designated as ECO-THR (L15996) and BAM-TDKD (Hl6401) to amplify an approximately SSO bp-long segment between the threonine tRNA gene near the •cytochrome b end of the non-coding region and the TDKD site approximately half way· through the non-coding region. 1 This primer combination, first used to study human 1 The ECO- and BAM- portions of these primer designations refer to.the addition of restriction enzyme sequences at the 5' end of the primer sequence. These "tails" are not essential for the present application and we will use primer designations with and without this notation interchangeably in this report. Biosphere Genetics,. Inc. l>age 3 �47 Final Report/12-8-97 Preblc's DNA study populations (Vigilant et al. 1989) had worked well in studies of other mammals and typically revealed amounts of sequence variation appropriate to differentiating subspecies and geographically isolated populations. Because the non-coding region includes a structure descnoed as a displacement or "D" loop known from work on human and cattle DNA, we will occasionally refer to the region of DNA studied here as the D-loop. Amplifications with the above primers were performed in 12.5 µI reaction volumes using 1 µI oftemplate DNA, 1 unit of the DNA polymerase, Klentaq-1 (Ab Peptides, St. Lo~ MO), and other reaction components in standard proportions. A Teg~e PH~2 . thetmocylcer was used to implement a program using an initial denaturation at 94°C for 3 minutes followed by 42 cycies with denaturing at 94° for 45 seconds., annealing at 55° for 1 minutes, and extension at 72° for 1 minutes followed by a final extension at 72° for 5 minutes. Pro4ucts were fractionated on 1.5% agarose gels. ~plification ofthe 550 bp D-loop fragment was successful, but primer dimer and secondary products also appeared, sometimes in considerable amounts. We experimented with a variety of modifications to obtain cleaner product (prim~ reduction, additions ofMgCh at various levels, alternative forms ofDNA polymerase, etc) and were ultimately able to obtain product with a • minimum"ofthese additional elements ii1 many, but not all, samples of mice presumed to be Z h. preblei. Following the optimization effort, revised reaction conditions were used to assess D-loop fragment amplification success with all new DNA extracts in 12.S µI reactions, then applied with slight modifications to the thermocyler program to amplify targeted products in SO µI reaction volumes to obtain sufficient quantities for automated sequencing. Two or three SO µI reactions were run for each sample, depending on prior estimates of the amount of template available in individual DNA extractions~ The quantity and quality of product generated by each reaction was assessed by agarose gel fractionation. Reaction volumes were combined when necessary, then cleaned with the solid-phase reversiole immobilization method (DeAngelis et a 1995) using carboxyl coated magnetic particles (PerSeptive BioSystems Inc, Cam6ridge, MA). Oeaned, resuspended DNA products were then dried down to a pellet mthe bottom of a 1.5 ml eppie tube for shipping by overnight service at ambient temperature to automated sequencing s~ce. an Resolution of Amplification Problems Some DNA extra~ most notably those of Z. princeps and of putative Z k , preblei populations sampled at the Warren Air Force Base in Wyoming, did not amplify well or at all with the ECO-THR/BAM-TDKD primer combination. We first suspected that this OCCWTecl because the TDKD primer designed from sequence information on the human D-loop was not finding sufficient complementarity on the heterologous primer site in at least some 7.ap,IS populations or taxa. Conventional wisdom suggested that the ECO-nm. primer site should be-highly conserved in vertebrates. Based on this reasolling, we designed two ~ew primers for the middle of the D-loop. We examined D-loop sequences available from Genbank for rat (Rattus norwegicus), mouse (Mus musculus), vole (Clethrionomysglareolus), gopher (Thomomys bottae), and kangaroo rat (Dipodomys ordii) as well as our own sequence data for ?.opus. Sequences for the Paee4 �48 Final Report/12-8-97 · relevant portion of the D-loop for Mus, Clethrio11omys and Zapus were used to identify a primer site most likely to be reasonably conserved in muroid and dipodoid rodents. The primers designed for this new site are designated PRDL L-15738 (forward primer) and PRDL H-15720 (reverse primer). We had these primers synthesized (Operon Technologies, Alameda, CA) for testing and possible use in resolving the difficulties mentioned above. The relative positions and priming directions of all primers are shown in Figure 1. We used PRD¼.!!_-1S~~0 iq coµibination with ECO-THR. in an attempt to amplify those samples that had not.amplified with the ECO-THR/BAM-TDKD primer combination. We also attempted to _amplify the entire D-loop by using ECO-THR. in combination with PHE-rev H29, a primer previously designed for general use in amplifying portions of the D-loop in mammals (A. Gavazzi, unpublished). Fmally we ..test~ PRDL L-1S738 in combination with PHE-rev H29 for the pwpose of generating D. loop fragments spanning the TDKD site for automated sequencing of this site in 'Zapus. :resting of these primers on 7.apus DNA extracts revealed that: 1) the ECO-THR/PRDL H-1S720 primer combination amplified in only two ~f20 samples and did nothing to solve the previous difficulties encountered with the ECO-THR/BAM-TDKD combination; 2) the ECO-THR/PHE-rev H29 combination produced a fragment ca. 1500 bp long, apparently spanning the D-loop successfully in some cases, but not with the DNA extracts that had been previously problematic, and 3) the PRDL L-15738/PHE-rev H29 combination produced multiple bands in some cases and no amplification in others. We inferred from these results that our original problem in amplifying some Zapus samples, most notably those assigned to. Z. princeps and the samples from the Warren Air Force Base, was not with the lDKD site, but rather with annealing of the ECO-THR primer designed for a conserved section of the human threonine tRNA gene to the het~rologous sequence in 7Apus. Reexamination of the sequences successfully obtained in preliminaly work on 'Zapus suggested that a primer site that would be more highly-conserved between 7.apus and other mammals might be present internal to the one primed by ECO-THR. Further testing showed that an available primer designated PROC, for priming of a sequence on the praline tRNA gene, when used in combination with the BAM-TDKD primer, was uniformly very successful in amplifying a 433 bp fragment (excluding primer sequences) of the D-loop. While we have been reluctant to give up on efforts to access -information about variation existing in and around the THR site, the PROC/BAM-TDKD primer combination was clearly the tool of choice for compiling the dataset required for this study within the time frame required. The results presented in this report are for the 433· bp segment of the D-loop falling between the proximal ends of these primer ~ites. ca. Automated Sequencing DNA sequencing of both the S50 bp and 433 bp fragments of the D-loop generated as descnoed above was perfonned by The University of Maine DNA Sequencing Core Facility using an ABI model 373A Stretch DNA sequencer. Results of . one.sequencing pass in each direction were received by e-mail as attached files in ABI •format. Pherograms in these files were viewed with the program Chromas (v. 1.4, Co1:1or Biosphere Genetics. Inc. Pages �49 Preblc's DNA study 1HR PROC Final Rcport/12-8-97 PRDLL15738 ldtNAua! lcRNAno! _I_______N_•_oo_&a_sepaa_·_ _ _ _ _ _ _! ,cRNA,_! ~ PRD H-1S720 ~ IDKD PHEA. Fig. 1. Relative positions of the primers used in this study for amplification of the mitochondrial DNA non-coding region. which includes the D-loop. Primers nm. and IDKD were from Vigilant ct al. (1995), PHE-rev 1129 was from Anita Oavazti and primers prdl L-15738 and prdl H-1S720 arc two new primers designed for this study to work with .2apus and other rodents. Primers arc used in pair-wise combinations to amplify segments of DNA lying between their positions on this simplified map. The relative positions of coding and non-coding regions arc indicated by labeled areas. McCarthey, Griffith University, Brisbane, Queensland, Australia) and machine-assigned sequences were exported as text files for use in subsequent analysis. Data Analysis Text files containing the two sequencing reads generated from opposite ends of the amplified fragment were entered into the program MacDNASIS (v. 1, Hitachi Sofl:ware Engineering Co., Ltd., San Bruno, CA) and combined to obuun a consensus sequence for the amplified region of each individual mouse sampled. Sequ~®S obtained from both THR-IDKD and PROC-Ti>KD amplifications were used as available. However, since the more inclusive THR-TDKD sequences were not available for individuals assigned to ·z princeps and samples ultimately found to be more closely related to Z princeps than to the Preble's samples, and since the longer sequences were of variable quality at the beginning of the 5' to 3' read in a number of the Preble's samples, we~ only the 433 bp sequence available in all samples in all subsequent data analysis. Consensus sequences were aligned manually using the multiple sequence option of MacDNASIS. The program MacClade (v. 3, Maddison, 1992) was used to create· a data matrix of character states for 58 variable sites in the aligned sequences for phylogenetic analyses. Phylogenetic trees were generated using the parsimony algorithm in PAUP (v. 3.1.1, Swofford, 1993). To expedite review of various options for the rooting of trees; one individual was selected as most representative of each population (fewest changes frQm the most commonly shared state at the SS variable sites treated as cbaracters in the .DNA sequence) and used in the depiction of,nost-parsimonious trees and in bootstrap analyses. Bootstrap analyses used the 50% majority rule with 100 replications. Biosphcn: Genetics. Inc. Page6 �sircble's DNA study Final Report/12-8-97 Strict £8§1i8~ iii ~ lffii Iii I • ·---. ~ mi ™ 00 ~OSN I II m§ I I I I I ~ -r.= ========= ~--~~ . __ _ _ _ _ _ _ _ _ _r--_- _ -_ -_-_ -_ -_ -_ --t I I Figure ·2. Strict consensµs tree, identical to_ the single most parsimonious tree generated using the "branch and bound" option of PAUP v. 3.1.1 (Swofford 1993) on.sequences for all samples analyzed. Length of this shortest tree is 61 evolutioruuy steps; consistency index (Cl)= 0.869. Although not supported by bootstrap analysis in the conte.u of phylogenetic analysis, sub-groupings of populations considered here to be part of the Preble's group suggest that population subdivision may be discemable by more appropriate population-analytic methods. Biosphere Genetics. Inc. Pagc7 ,. �51 Final Report/12.S-97 Preble's DNA study RESULTS Figure 2 illustrates phylogenetic relationships among all samples included in the study to date, inferred from maximum parsimony analysis (length = 61 steps, consistency index [CI] =0.869). Bootstrap analysis for the entire dataset was not practical for this report. However, bootstrap analyses were performed for various outgroup scenarios using one individual from each population as described above. No outgroup was designated for the analysis shown in Figure 2. ·-·The important relationships in Figure 2 are perhaps more easily seen in the unrooted, circular fonnat tree generated using one representative individual from each population (Figure 3). •No meaning is attached to the length ofbranches hi this tree. The 19 branches that join the baseline in the center directly (11 o'clock to S o'clock on the diagram) and four more samples that ·are shown grouped together and joining the baseline with• a bootstrap value of 53 (indicating little support for treating this group of samples as distinct from the other 19) form a relatively homogenous group. Also not strongly diff'erenti~ed is the group of three r~p~enting reference samples of Z. h. intennedius from Minnesota and Z. k campestris from South Dakota as well as an individual museum . specimen designated as only Z. hudsonius from Johnson County, Wyoming. Bootstrap values indicate strong support for reco~g samples of Z. princeps, Z. k luteus, and populations affiliated with them in the diagram as distinct from the Preble's group. Further observations following from the analysis are discussed in the following section. DISCUSSION Preliminary data analyses conducted before all new populations sampled during the summer of 1997 and reference material had been analyzed ex_a.mined three options for the rooting of the phylogenetic tree. When the Indiana population of Z. hudsonius was assigned as the outgroup (one most parsimonious tree, length·= 63, CI= 0.921), the strong relationships in the tree were the same ones seen in the tree generated when no outgroup was assigned (Figures 2 and 3). Essentially, populations ofjumping mice ranging from southeastern Albany County in Wyoming south along the Front Range of the Rocky Mountains to western Las Animas County in Colorado were seen to fonn a coherent group within which separate populations or groups of populations were not strongly differentiated. Designating Z. princeps as the outgroup resulted in Indiana Z. . hudsonius appearing as the sister group to the assemblage of presumed Preble's populations with the populations from the Colorado-New Mexico border· and the Warren Air Force Base joining the tree at an intennediate level. Bootstrap values for the resulting tree were uniformly high, but we have not yet resolved doubts about whether Z. prlnceps can properly be treated as ancestral to Z. hudsonius. Finally, designating Z. hudsonius intennedius from Minnesota as the outgroup in earlier analyses resulted in a tree in which all the branches to the Preble's popuiations samples joined the baseline as undifferentiated from the outgrqup. Biosphere Genetics. Inc. Pages �52 Prcblc's DNA study Final Report/12-8-97 MRD97<flMNH9716 ROX9701 CGA1 80S9706 ·--- EPC9701 LOSt - - RF96100 RSS1076 -------------- Figure 3. Bootstrap consensus tree (50% majority rule, 100 replications), based on analysis of single most-representative individual from each population or reference group, obtained with no outgroup designated. ijootstrap values are shown next to relevant branches in the tree. Bootstrap values greater than 90% indicate those relationships which are strongly supported. • • Bwsphcrc Genetics. Inc. ·' • �Preble's DNA study Final Report/12-8-97 There are several notable observations for individual population samples among our findings based-on analyses completed in late November, 1997. We summarize these here in list form with population/sample codes in parentheses referring to designations in the tables of the Appendix: 1. The six jumping mice caught at the Warren Air Force Base (CCF) in the summer of 1996 (identified by field workers as Preble's) and an individual jumping mouse caught in Weld County, Colorado just south of Cheyenne, Wyoming (LTC), are indistinguishable from reference samples ofZ. princeps (CZP) provided by Dr. B~ce Wunder from Larimer County, Colorado. Bootstrap values indicate that this group is, in tum, most closely affiliated with, but distinct from, a sample of Z. princeps from Taos·county, New Mexico. • 2. The eastem-m~st sample identified in the field as Z. h. preb/ei, a single individual from Elbert County, Colorado (HAY), is confirmed to belong in the Preble's group by DNA sequence obtained from a sample of three hairs. 3. Jumping mice caught at two sites in the Lake Dorothey area on the Colorado-New Mexi~ border (CCR and WFS), suspected on the basis of morphological traits to be similar to Z. h. luteus (Cheryl A Jones, personal communication), are confirmed to be so on the basis of the non-coding region sequence data. There is also a reasonably strong indication (bootstrap value·= 88) that these two populations and the Z. h. luteus samples are, together, likely to have shared a common ancestor with progenitors of Z. princeps reference samples and the populations sampled north (CCF) and south (LTC) of Cheyenne, Wyoming. This finding is in contrast to the conclusions ofHafher et al. (1981) (but see next comment). 4. A suggestion from our analysis (not strongly supported by bootstrap analysis) is that Z. hudsonius from Indiana (possibly either Z. h. americanus or Z. h. intennedius based on distnl>ution) may be the most ancestral of the populations and taxa sampled and may have shared a common ancestor with progenitors of i'ornis presently known as Z. princeps princeps and Z. h. luteus. We speculate that the forms recognized as subspecies of Z. princeps and Z. hudsonius present today in the Rocky Mountain and Northern Great Plains region may be the derivatives of two separate range expansions occurring at different times during the Pleistocene. 5. Two ·rererence samples obtained from the Denver Museum of Natural Histoiy, originally identified as Z. princeps from the San Isabel National Forest-in. western Las Animas County, appear on the basi$ of non-coding region sequence data to belong to the Preble's group. 6. A single jumping mouse specimen obtained by Chris Garber from the Medicine Bow National Forest in Wyoming, identified as a Preble's mouse by Dr. David Annstrong on the basis of his analysis of poorly preserved skeletal material, is confirmed to be a Preble's by DNA sequencing from a piece of preserved skin. 7. One reference collection sample identified as Z. h. pallidus from Garden County, Nebraska (ZHPNEG), and two samples identified as .Z: h. campestris from ~eston Biosphere Genetics. Inc. Page 10 53 �I. 54 Preble's DNA study FinalRcport/12-8-97 County, Wyoming (ZHPWYW), are indistinguishable from other samples in the Preble's group in the present analysis. 8. Two reference collection samples identified as Z. h. campestris from Custer County, South Dakota, are found to be most similar to a museum specimen identified only to species level as Z. hudsonius from the vicinity of Buffalo in Johnson County, Wyoming. • Further Researc~ Needs ·--Additional sample.materials and analyses may be required to achieve a rigorous view of the relationships of the group referred to here as Preble's to other subspecies and species of the genus Zapus in North America.- The choice ofan appropriate outgroup remains unresolved, and could benefit from further input from those knowledgeable about evolution and morphology of the Zapodids in North America and elsewhere. Based on extensive work on limb myology of the Dipodoidea (Stein, 1990), the superfamily to • which the genus and the rest of the family Zapodidae belong, the genus Sicista (the birch mice), represented by species in Europe and Asia, would appear to be an appropriate outgrouj>. However, divergence between 7.apus and Sicista may be too great to be effectively measured by variation in the D-loop. Another North American genus, Napeozapus, has been suggested as a possible outgroup for this analysis. However, slightly greater adaptation for saltatorial ability and a higher tooth count in Napeozapus than in Zapus would suggest that the former is derived rather than ancestral to the latter. Sequence information for the cytochrome b gene potentially forthcoming from other researchers (T. Yates, personal communication) may be helpful in sorting out relationships at the species and higher taxonomic levels and may be a useful complement to the noncoding region sequence data in elucidating relationships potentially traceable to • Pleistocene glaciation events. We have begun to examine a portion of the cytochrome b gene and the neighboring threonine gene in a separate study. . The DNA sequence results reported here indicate the ~eed for a reexamination of external and skeletal morphology in Zapus. .In at least a few cases (DMNH, LDS), the sequence data suggest that .even species level identifications cannot always be made unambiguously in the field. Patterns of morphological variation across the range of the species and subspecies of interest may be such that more careful examination of museum accessions is to be recommended as well. One promising dental character that may distinguish Z. hudsonius·from Z. princeps is the presence of a deep anteromedian fold 'in the anteroconid of the molar ml in the former as descnoed by Klingener (1963) and applied in an analysis of cave floor faunal remains by Hafner (1993). It will be interesting to learn what this character may say about the taxonomic identity of the. samples referenced above and about specimens available in museum collections for the areas near the northeQt and sotithem boundaries of the Preble's mouse range. • Further analysis of molecular markers at the species, subspecies, and population levels is needed to confirm the findings suggested by this study and to further delineate patterns of variation bearing on conservation and management ofZ. h. preblei. We have material in hand to continue to expand sample sizes for a number of the populations already swveyed and our initial contacts with several museums in the context of the Biosphere Genetics, Inc. Page 11 �Preblc's DNA study Final Rcport/12-8-97 55 present study indicate that sample sizes of comparative taxa can also be increased for at least some parts of the relevant subspecis ranges. Because there has been relatively little recent suivey activity in Wyoming and only a few reference specimens from museum collections were included in this study, the northern extent of populations assignable to the Preble's group is poorly defined. New trapping suivey initiatives and DNA analysis of more material available from museums would address this situation. We also recommend that a nuclear DNA dataset be generated to complement the mitochondrial DNA dataset. A portion of our work not reported here has evaluated two classes ofDN~ markers potentially appropriate to tills task and b ~ applications of ipicrosatellite methods to development of markers likelyto be applicable both to phylogenetic analysis of relationships at the species and subspecies level and to population genetic analyses supporting assessment and monitoring of population differentiation and gene flow, genetic ·parameters of population viability, and mating system analysis. • We expect that further examination of the results obtained in this study, both by ourselves and others, will lead to a more comprehensive definition of research needs and priorities along two possibly divergent paths, one inclined to address fundamental issues of systematics and biology, and the other focused more sharply on the near-term requirements that may be imposed by the outcome of the pending decision on the status of the Preble's mouse by the U.S. Fish and Wddlife-Service. We urge that planning attention be devoted to providing for both ongoing research and for integration of assessment and monitoring activities into any prospective recovery effort.. Molecular ecology has much to offer in both areas of endeavor. . Conclusion Based on resuits.to date, we conclude that mitochondrial DNA non-coding region (D-loop) sequence data appear consistent with the view that a geographically contiguous set of populations previously recognized as the Preble's mea<Jow jumping mouse (Z. h. • preblei) form a homogenous group recogniz.ably distinct from other nearby populations and from another geographically-adjacent species of the genus. Biosphere Genetics. Inc. Page 12 �56 Preble's DNA study Final Report/12-8-97 REFERENCES CITED DeAngelis, M.M., D. G. Wang, and T. L. Hawkins. 1995. Solid-phase reversible immobilization for the isolation of PCR products. Nucleic Acids Research 23{22):4742-4743. Greer, C.E., C.M Wheeler, and M.M. Manos. 1995. PCR ampijfication from Paraffinembedded tissues: Sample preparation ~d the effects of fixation. pp .99-112, in: PCR Primer, A Laboratory Manual, C.W. Dieffenbach and G.S. D.veksler (eds.. ) CHSL Press, New York, 1995. Hafner, D.J. 1993. Reinterpretation of the Wiconsinan mammalian fauna and paleoenvironment ofthe Edwards Plateau, Texas. J. Mamm. 74(1):162-167. Hafner, D.J., K.E. Petersen, and T.L. Yates. 1981. Evolutionary relationships ofjumping mice (genus Zap11s) of the Southwestern United States. J. Mamm. 62(3):501-512. Klingener. D. 1963. Dental evolution of Za.pus. I. Mamm. 44:248-260. Maddison, W.P. and D.R. Maddison. 1992. MacClade v. 3: analysis of phylogeny and character evolution. Sinauer Associates, Inc. Sunderland, Massachusetts. Stein, B. R. 1990. Limb myology and phylogenetic relationships in the superfamily Dipodoidea (birch mice, jumping mice, arid jerboas). Z. zool. Syst. Evolut.-forsch. 28:299-314. Swofford, D.L. 1993. PAUP - Phylogenetic Analysis Using Parsimony- version 3.1.1. Computer program distributed by the Illinois Natural His~ory Survey. Campaign, Illinois. Vigilant, L., R. Pennington, H. Harpending, T.D. Kocher, and AC. Wilson. 1989. Mitochondrial DNA sequences in single hairs from a southern African population. Proc. Natl. Acad. Sci. USA, 86:9350-9354. Walsh, P.S., D.A. Metzger, and R. Higushi. 1991. Chelex® 100 as a·medium for simple extraction of DNA for PCR-based typing from forensic material. Biotechniques. 10(4):506-513. Biosphere Genetics. Inc. Page 13 �57 Appendix Tables in this appendix contain information on the populations and species samples included in • this study. All samples received ·for which DNA was extracted are listed.· Those for which DNA. sequence data was successfully obtained for the analyses reported in. the main document are indicated as explained in each table. Additions and corrections were still being received as the final draft of this report was going to press. Questions about incomplete or inaccurate data should be referred to the Colorado Division ofWddlife, Terrestrial Section, Attn: Judy Sheppard. A "°"'"nrliv A �Table 1. Sampling locations for jumping mice analyzed as put~tive Preble's mice as {Zapus hudsonius prcblei). This table includes both samples obtained by live-trapping during the summers of 1996 and 1997, and samples from museum specimens not identified to subspecies or otherwise designated as reference material (included in Table 2). Numbers of samples for which DNA sequence data were successfully obtained in time for the analyses presented in the main body of the report arc shown in parentheses under the number of samples processed. The individuals included in the analyses arc indicated·by an.asterix in the column headed "Original sample #s." S1D1plo Codo BAD BOS Locality/site name & desaiption or other soorce informltkin B■dwttcrCredc, Natrona Co., Wyoming . 'oNIAl rein.and SoUlh BoalderCredc. near intcnedion with Eat Boulder Dltdi, on City ofBoulder Open Sptee. Boulder Co;. CO. 5300 ft. Lousivi'Uo Quadrangle, T J S, R 70 W No. Original • -1011. 1 m CU13469• 13 B0S9702 (1) • BOS9703 BOS9704 B0S9105 BOS9706• 8089707 BO89708 BOS9709 BO89710 BOS9711 BO89712 BO89715 BO89716 4 (2) BVC Bemr Credc, 2 1/2 milea SW of Monument, El Pllo Co., CO. 7000 ft. Palmer Lake quadrangle. T 11 S, R 68 W CCF Crow Credc, Wamn Air Form Bue, Laramie 6 Co., WY. [elmitionanclquadrangloNIA) T14N,R67W (6) CCR Crlo:,rica Credc, Lako Dorothay Stlto W"ddlifo Area, LIi Anhnn Co., co DC CCF9604• 6 (4) N Brandl, Middle Fode. Lodgq,olo Credc. Polo Mt. Umt, Modi.cine Bow National Foreat, ce. 2 ml. S, 15 ml. B.Laramie, Aibeny Co., WY, 7600ft. -•o•NIA1 Deaclman Credc, U.S. Air Foroo Mademy, El 1 (1) PuoCo..CO, (2) {elevation and qu■dnmglo NIA) CCF9602• CC~3• [Elev.-?) CGA BVC9701 • BVC9702 BVC9703• BVC9704• CCF960l• 5 CCF9605* ·CCF9606• 432• 433• 503 504 .. 505• 506• [Specimen tag] 97DC02N 97DC03N .97DCQ2s• 97DCOSS• 97DC07S 1/4-1/4 Section NIA Lat-Loog coordinirtcs NIA 3, W 1/2 3, Wl/2 3, Wl/2 3, Wl/2 3, W 1/2 3, Wl/2 3, Wl/2 3, Wl/2 3, Wl/2 3, Wl/2 3, Wl/2 3, W lf.2 3, W 1/2 39"59' 30" N . 105°12'55" w 29.NE 1/4 29,NEl/4 29,NE 1/4 29.NE 1/4 27 27 27 27 27 27 NIA 39"03'27.2" 104°53'49.8" NIA 39"00'02" 104°21'39" UTM Coords. NIA 4818450.00, 4427090.00 4811450.00, 4427090,00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00. 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 4818450.00, 4427090.00 Collettor(1) Spoosorin&'Participating 0rl!llnizlrtion(1) P.Robfntcn&E. ·Andenon C. Meaney & N. Clippinger Univ. of Colorado Museum. Boulder. CO Colorado Division of Wildlife Carron Mean.:y, Consultant i i 5088970.00, 4323168.00 5088970.00, 4323168.00 5088970.00, 4323168.00 5088970.00, 4323168.00 NIA N. Clippinger NIA C.AJones C. Flemming C.Paguo • Colorado Division of Wildlife Carron Meanc:y. Consultant Colorado Natural Heritage Program U. S. Air Force Denver Mll!eum of Natural History ' TlSN R71 W sec 11 NIA NIA NIA NIA C.O■rber (collector) D. Aimstra:tg 4318360.00. 513700.00 4318360.00. 513700.00 4318360.00, 513700.00 4318380.00, 513650.00 4318300.00, 513650.00 P.Sd!uennan, s. Aslc, University Museum, Univ. ofColorado Colorado Naturill Heritage Program J. Hobert Paee A-2 U1 (X) �i Table 1 continued (2nd page). EPC Eat PJmn Creek. 6500 ft. Doagtu Co., CO. DawlanButtoquadranglo, T9S,R67W BAY JCC IDS I.PC Hay Ouldl, tn'butaryto Running Crock near Mer, Elbat Co., CO. 6,225ft. Cabin Ouldl 'e, T7S.R64W. Coll Creek. R.lnlom'Edwmk Homeateld Ranch, Jeffinon Co., co. (Bin.•?) IEdondo-~- 00) T 2 S. R 70 W Lib De Snxtnear Baflitlo. Johnson Co., WY. [elmdlon and quadranglo NIA] I 3 (1) BPC9701• BPC9702 EPCf703 9,E 1/2 9,E 1/2 9,E 1/2 I (I) HAY-1• E 1/2 NIA 4 (3) 9601* 9602• 9603 9604• CU15132• 7,8,17,18 [Information neededftom collecton] [Information needod) C.Flcmming C.Plgue NIA NIA NIA LPC970l• LPC9702• LPC9703• LPC9704* LPC970.5 LPC9706 LPC9707 LPC9708 LPC9709 LPC9710 LTC-1* 4,SW 114 9NW,NW 4,SW 1/4 9NW,NW 4;SW1/4 9NW,NW 4,SW 114 9NW,NW 4,SWl/4 9NWNW NENE,SE SE 40046'11.0" 10.5°21'36.7" 4696010.00, 45132560.00 4696010.00, 45132560.00 4696010.00, 45132560.00 4696010.00, 45132560.00 4696010.00, 45132560.00 4696010.00, 4.5132.560.00 4696010.00, 45132560.00 4696010.00, 4.5132560.00 4696010.00, 45132560.00 4696010.00. 45132560.00 5063300.00, 45333900.00 A.Crockett J.MMerritt D. Armstronst A. Deans MRD970l• 16,NW 1/4 39"58'1.6" 105°13'.59.7'' 4798400.00, 44242200.00 A. Deans 21,NW 1/4 18, SE 114 1.5,NW 1/4 10,SW 1/4 10,SWt/4 10, SW 1/4 10,SW 1/4 10.SWl/4 40049'2.5.6" 105°21"8.6" 471.5010.00, 4.5212170.00 471.5010.00, 4.5212170.00 471.5010.00, 4.5212170.00 4702850.00, 4.5194120.00 471.5010.00, 4.5212170.00 4715010.00, 4.5212170.00 4702850.00, 4.5212170.00 47028.50.00, 4.5212170.00 A. Dean's Colorado Division of Wildlife Carron t..-1.:an,:y. Consuhant T.Ryon PTI Environmental Services I (I) Lem PinoCreek. Lowerai«okeo State WildHfl, Area. Llrlmer Co., 00. 6200 ft. Livamoro Mountain quadrangle, T 10 N. R 71 10 (4) Lem Tree Creek. at 1-25, llOl1han podim Weld Co., CO. 5,900 ft. Carr Soulhwest quadrangle, T. ll-12N.R.67W. ManhaD Road, Dry Crock Ditdl #2, bctwem Mmball road and South BoulderCredc. Boulder Co., CO. 5700 ft. Louimllo • TlS.R70W Rabbit Creek. Lower C!erokeo SWA CL 9 mi. NW Uwnnoro, La1'.im«Co. 00. 6300 ft. Livamoro Mountain quadranglo ,T 10 N, R 71 1 (1) 8 (4) RBC9701° RBC9702• RBC9703• RBC9704• RBC970.5 RBC9706 RBC9707 RBC9708 Rocky Flm &tvha11nmtal Tedmology Sito, 1cfflnon Co. 00. 5780ft. Loufmllo, CO, T2 S, R 70 W 10 (6) ZAHl196-62• ZAHU96-63• w LTC MRD . RBC t (l) Atmendbc A 40057' 5.8" N 104"55'29.3" W 5090040.00, 4347802? 5090040.00, 4347802? 5090040.00, 4347802? 509.0040.00. 4347802? 540660.00, 4368470.00 (?) ADeana A.Dims A.Deana . w RF 39"16'46.3" N 104°53'44.2" w NIA ~· ZAHU96-6.5• HU96-100• HU96-10l• RF-97-102 RF-97-103 RF-97-104 RF-97-10.5 11,.5W 11,.5W 11,.5W 11.,w Colorado Division of Wildlife Canon Meaney. Consuhant Colorado Division of Wildlife Carron Meanev. Consuhant Colorado Natural Heritage Program Univ. of Colorado Museum. Boulder.CO Colorado Division of Wildlifo Carron M~ey. Consuhant Colorado Division of Wildlifo Carron Meanev. Consuhant Colorado Division of Wildlife Carron M.:aney. Consuhant l11 4832800.00, 44148500.00 4832800.00, 44148.500.00 4832800.00, 44148.500.00 4832800.00, 44148.500.00 ID Pa!.'c A-J �°'0 Table I, continued (3rd page). Roxborough Statol'mknearjundim of Willow Creek and UttJo wmow Croelc, Dougln Co., CO. 7300 ft. Xnsl« quadrangle, T 7 S, R 69 2 (2) SCR Smllh Croelc, U.S. Air For00 Acadmly, El Paso Co., CO. 6,860 ft. Monummt quadrangle, T12S,R67W 6 (6) STV &. Vraln R., Boulder County Open Spaco, Hygiene, BoutderCo., CO. ,,060 ft. Hygiene quadrangle, T 3 N. R 70 W 6 (5) WFS Wat.POik Sdiachheim Croelc, Lak, Dorothcy State Wildlife Area. Las Anlmu Co., CO [Elev.•?) JOuadnmltlo • ?t ITwmrn>,/RnVSeo • ?l Woodhomc Randt, Douglu Co., CO. 5,760 ft. Kass1« quandrang1e. T 7 S, R68 W 4 (4) ROX w WHR 7 (5) ROX970l• 24,E 1/2 ROX9702• 24, E 1/2 SCRI• SCR2• SCRJ• SCRS* SCR6* SCR7STVl STV2• STV3• STV4• STV5• STV6• 530• 531* 532* 533• WHRl• wmu•- 39° 25'44.s'' 105°03'48.9" 39° 26'10.l" 105°04'24.0" 4945290.00, 43643880.00 6NE,SE 114 NIA 36, SE 1/4 AI>eam Colorado Division of Wildlife Carron Meaney. Consuhant NIA C. Meaney Colorado Division ofWidlifc NIA NIA C. Meaney Colorado Division of Wildlife NIA 37"00'25" 104"22'32" NIA C.A.Jonea Dcnva- Museum of Natural History 36, NE 114, SWl/4 NIA NIA C.Meancyand N. Clippinger Colorado Division of Wildlife 36, SW 1/4, Elt'2 [Need info. from collector] [Infonnstion needed) ? ? NIA NIA 4309600.00, 5139400.00 4309580.00. 5139400.00 4309550.00, 5139400.00 4309SS0.OO, S139400.00 P.Sdtuerman S.Ask J. Hobert 04774210.00. 44084950.00 04774210.0Q. 440845>50.00 04774210.00. 44084950.00 JanPdcrsoo 4936880.00, 43651170.00 WHR3 WHR4* WHR5• WPC Well l'1um Croelc, Dougln Co., CO {Detailed dc,c:ription needed from collector] [Elav.•?) [Quadnmglo • ?). T 7 S, R 68 W WRN Monummt Creek near cx1ofluaicnrith Pinc Croelc, N. tide of Woodman ROid, Et Paso Co., co. WRP WhiteRmdll'm. Ralltm Croelc,oJfHwy.U norlh o!Ooldm. Jeft'encn Co., Colorado, 5740 ft. Ratstm Butt.es quadnmgtc, T 2 S. R._70 W Appendix A 8 (8) s (1) 3 (2) WHR6* WHR7 WPCl• WPC2• WPCJ* .WPC4• WPC5* WPC6* WPC7• WPC8• 97WRN130 97WRN138• 97WRN142 97WRN143 9'7WRN75 WRffl25 WRm41• WRm49• 31 Colorado Natural Heritage Program Page A-4 �Table 2. Reference specimens ofjumping mice provided by museums and other investigators, used as representatives of recognized species and subspecies of the genus Zapus for comparison with specimens listed in Table 1. Original 11mplo Specimen information provided by IOUr00 Individual or imtftuden ~Creek.FR 1'6 off'Col(? Hwy 14, LarfmerCo.CO. 10,000ft. Aalgnedto Zap,11 prtncq,, No. (4) CZPB• CZP9' DMNH Pmptoiro Campground, 262.S m. San babel National Porat, Lu Anlmn Co.. Colorado. Aalffll'!dto 7..tmtt, Drlnt:.DI at DMNH 2 (1) CZP12' CZP13' 7916' 7917 RSS Zaprt, httd,omr11 amplca provided by Bnaco 2 (2) Sample Code CZP ZHLNMO Wunder, Anoka County. Minnelcta. maine, NB 1/4 ofNB, Sec. l, T31N, R23W Presumed to bo Z. h. lntmrtdtit1 Zaprt, httd,omr11 mq,lca provided by Bruce Wunder, origin in Indiana; may be Z. h. tnrmn.dml or Z. h. ammcamu Zapr,1 hffdl0fffl11 can,patrll ftom Culta' Co., 81), provided by tho Mulcmn ofNatural m.iirv. Unfv. ofKanm Zaprt, httdltmltt1 can,patrt1 ftom Weston Co.. WY,providedbytho MulCUID ofNatural m..trv. Unfv. of'Kanm Zaprt, httd,omr11 (lttter11) ftom Otero Co., NM ZHLNMS Zaprt, httd,omr11 (lt1ter11) from Sandoval Co., ZAHU ZHCSDC ZHCWYW Fmton Lake, NM ZHPNBC Zaprt, httdionhll pc,llldt11 from Cieny Co., NB ZHPNEO Zap,11 ln1dionh11 pc,11ldt11 from Oanlm Co., NB ZPPCOG ZPPNMT Zaprt, prtncq,1 prtnc,p1 ftom Ptannigan C-. Onmd "-" CO Zaprt, prtncq,1 prtnc,p1 ftom Taos Co., NM nos. 1/4-1/4 Section NIA Lit-Long UTM Collecton'Sourco Coopenting Institution Coordinatea NIA NIA B. Wunda- Colorado State University NIA 37°15'00" N 105°6'30"W NIA C.AJones Daiver Museum of Natural History RSS 1076' RSS1077' NIA NIA NIA B. WundaRobatSikes ElmerBumey Colorado Stat.: University University of Minnesota 2 (2) ZAHU-253' ZAHU-300• NIA NIA NIA Colorado Stat.: University 2 (2) 109994' 109995• NIA NIA NIA B. Wunder collected by John WhiUalcec R. Timm T.Holmes 2 42469' 42470• NIA NIA NIA (2) R. Timm T.Holmes Natural History Museum, Univ. of Kansas, La\vrmcc 2 (2) NK87&• NK879• NIA NIA NIA T.Yates B.Gannon. 2 (2) NK3835' NK3837' NIA NIA NIA T.Y~ B.qannon 2. . -87043 87044 115762' 2 m 115763 CU14912 2 (0) CU14913 NK811 2 (1) NK814' NIA NIA NIA NIA NIA NIA NIA NIA NIA R. Timm T.Holmea R. Timm T.Holmes AdeQueiroz NIA NIA NIA Museum of Southwestern Biology, Univ. ofNew Mexico, Albuouemue. NM Museum of Southwestern Biology, Univ. ofNew Mexico. Albuouemue, NM Natural History Museum. Univ. ofKansas. Lawrmcc Natural History Museum, Univ. of Kansas, Lawrmcc Univ. of Colorado Museum. Boulder, CO Museum of Southwestern Biology, Univ. ofNew Mexico, AJbum,,.,.,,.,,. NM 4 (O} D. Annstrcn2 T. Yates B.Gannon . Natural History Musc:um. Univ. ofKansas, Lawrence NIA• not available for this report. In some cases the indicated information may be obtained from the person or institution supplying the material analyzed or can be inferred from other available information. ..... °' Am,cndixA ��63 I State of ___C ....o"""l,...o=ra...,d...,o.___ __ Project No. W-153-R-l l Work Plan No. _ _..,._0=66=2=---Task No. _ _ _ _--=-3_ _ __ APPENDIXB 11 STUDY PLAN Cost Center 3430 Mammals Research Conservation ofPreble's meadowjumpin2 mouse Temporal and spatial variation in the demography of Preble's meadow jumping mouse (Zapus hudsonius preblei) TEMPORAL AND SPATIAL VARIATION IN THE DEMOGRAPHY OF PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) A. NEED On May 12, 1998 the U.S. Fish and Wildlife Service (USFWS) published a final rule in the Federal Register ( 63 FR 26517) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) as 'threatened' under the Federal Endangered Species Act (ESA) of 1973, as amended. Recovery goals for Preble's meadow jumping mouse should work towards the sustainability, protection, and restoration of Z. h. preblei populations and habitats on both private and public lands to provide the spatial, genetic, and demographic structure needed to promote long-term species viability and provide species management flexibility. Recovery efforts for the subspecies will be most effective ifreliable information is available on the basic ecology of the subspecies and this information used to design recovery efforts such as Habitat Conservation Plans. A review of studies conducted on Preble's meadow jumping mouse shows that there is insufficient information to fully address defining rangewide ecological requirements, limiting factors, limits of species tolerance, or population status (Shenk 1998). Most work to date has focused on geographic distribution (presence or absence of Z. h. preb/ei), taxonomy, and habitat descriptions of sites where mice have and have not been captured. For Preble's meadow jumping mouse in particular, information on dispersal, habitat use, and population dynamics is most needed to identify minimal ecological requirements of the subspecies. Monitoring, by way of estimating demographic parameters (such as survival, abundance, and reproduction), of a single population over time provides an opportunity to document demography of a species, estimate temporal fluctuations in demography, and gain insights into the temporal variation inherent in demographic parameters. Monitoring of multiple populations over time and over multiple geographic locations provides the opportunity to gain further understanding of population processes and detaches time effects from spatial effects. Population monitoring activities do not constitute scientific experiments, in the spirit of manipulation of salient ecological variables, however, replication of monitoring activities for natural populations over long periods of time and in diverse geographic locations can lead to insights into population processes (Cook and Campbell 1979). These insights can then be translated into hypotheses useful for predicting changes in population demography resulting from either natural perturbations (e.g., flooding events) or anthropogenic modifications (e.g., gravel mining). Experimentation would then be required to test these hypotheses and establish cause and effect. There are three components of Z. h. preblei ecology that are currently unknown and yet key to any sound conservation strategy for the subspecies. These are (I) detailed demographic studies estimating survival, reproduction, immigration, emigration, and abundance and determining the factors influencing each of the parameters, (2) detailed studies evaluating movements and dispersal habitat of individuals within and among populations, and (3) detailed studies to define hibernation needs, primarily descriptions of suitable hibemacula criteria and food requirements for sufficient fat storage prior to immergence. The overall objective of this study is to provide estimates for all three of these �64 needs from three different populations of Preble's meadow jumping mouse. Thus, providing the opportunity to estimate spatial variation in the demography of the species. The three study populations occur in areas of different habitat matrices. The first study area limits animals within the population to a single drainage. The second population occurs in an area that combines a tributary and main drainage. The third population occurs in an area with both a tributary and main drainage as well as a series of ponds and irrigation ditches available to the animals. Continuing the study for multiple years will provide the opportunity to estimate temporal variation in the demography of the subspecies. B. OBJECTIVES Specific objectives for this study on Preble's meadow jumping mouse include: I. 2. 3. 4. 5. 6. 7. Evaluate temporal and spatial variation in daily and seasonal movements of Preble's meadow jumping mouse. Estimate and evaluate temporal and spatial variation of over-summer, over-winter, and annual survival rates for Preble's meadow jumping mouse. Estimate and evaluate temporal and spatial variation of reproduction, immigration, and emigration for Preble's meadow jumping mouse.. Estimate and evaluate spatial variation in abundance and density for Preble's meadow jumping mice. Evaluate temporal and spatial variation of habitat use in Preble's meadow jumping mouse. Document temporal and spatial differences in composition of foods consumed by Preble's meadow jumping mice. Collect genetic tissue samples for future analyses to document and compare variation within and among populations of Preble's meadow jumping mouse. C. EXPECTED RESULTS There are three components of Z. h. preblei ecology that are currently unknown and yet key to any sound conservation strategy for the subspecies. These are (I) detailed demographic studies estimating survival, reproduction, immigration, emigration, and abundance and determining the factors influencing each of the parameters, (2) detailed studies evaluating movements and dispersal habitat of individuals within and among populations, and (3) detailed studies to define hibernation needs, primarily descriptions of suitable hibemacula criteria and food requirements for sufficient fat storage prior to immergence. The overall objective of this study is to provide estimates for all three of these needs from three different populations of Preble's meadow jumping mouse providing the opportunity to estimation spatial variation in the demography of the species. Continuing the study for multiple years will provide the opportunity to estimate temporal variation in the demography of the subspecies Performance Indicators I. Provide descriptions of movements of mice for three Preble's meadow jumping mouse populations. 2. Provide estimates of survival and reproduction for three Preble's meadow jumping mouse populations. 3. Provide estimates of immigration, emigration, and abundance for three Preble's meadow jumping mouse populations. 4. Describe over-summer foods consumed by three Preble's meadow jumping mouse populations. 5. Quantify habitat characteristics of three sites where Preble's meadow jumping mouse are known to occur. 6. Analyze and publish results of research �65 D. APPROACH Study Site Selection All three study sites selected are areas where Preble's meadow jumping mouse (PMJM) has been found in the last two years. To evaluate spatial differences in movement of PMJM, sites were selected that provided a variety of habitat matrices available to the mouse. The first site selected, CDOW Maytag property, has one primary water source available to the mouse. This water source is East Plum Creek. Therefore we predict mice will restrict their movements to up and down this single drainage. The second site, Colorado Open Lands Pine Cliff Ranch, provides both a tributary (Garber Creek) and a main stem drainage (West Plum Creek). This provides the opportunity to investigate whether PMJM will move overland to move from one drainage to another or if they are restricted to moving only along riparian corridors. The third study site, CDOW Woodhouse Property and Dupont Property, provides an area containing a tributary (Indian Creek),a main stem drainage (West Plum Creek), and a series of ponds and irrigation ditches scattered throughout the property. This provides an even greater opportunity to investigate how much the mice will use upland areas or if they restrict their movements strictly to riparian corridors. Each of these unique habitat matrices provides the opportunity to estimate spatial variation in nightly and seasonal movements of PMJM. Movement Study Background Movement and dispersal pattern information will be key to any conservation strategy designed for Preble's meadow jumping mouse. Key factors include (1) which segment of the population disperses, (2) when do they disperse, (3) through what habitat do they disperse, (4) how far will individuals disperse (i.e., what is the maximum distance that separates adjacent populations) and (5) how critical is dispersal (both into and out of a population) to the persistence of a given population. The only currently available data on dispersal and/or movement for Z. h. preblei are from marked mice at Rocky Flats Environmental Technology Site (T. Ryon unpublished data). Two mice, an adult female and an adult male, were observed approximately 1.6 kilometers from previous locations (incidences occurred separately). Each of the locations were in the same drainage (Woman Creek). Objectives The PMJM movement study is designed to describe nightly and seasonal movement patterns of PMJM and to describe habitats used by PMJM. Specific objectives include: 1. 2. 3. 4. 5. Describe nightly movements of PMJM. Evaluate difference in nightly movements as they relate to sex, age, and habitat available to the animals. Describe 30-day (or life of the radio transmitter) interval movements of PMJM. Evaluate difference in 30-day (or life of the radio transmitter) interval movements as they relate to sex, age, and habitat available to the animals. Describe seasonal movements of PMJM. Evaluate difference in seasonal movements as they relate to sex, age, and habitat available to the animals. Describe habitats where mice occur: movement corridors, end point descriptions (disperses from what to what), and landscape features (connectivity with other riparian strips). Estimate the mean amount of time PMJM spend in each available habitat. Approach Movement data will be documented primarily from locations of radio-tagged mice from each of the three study populations. To place radio transmitters on the animals, mice will be captured in Sherman live traps. Mice weighing> 18 grams will be fitted with MD-2C, I-gram radio transmitters supplied by Holohill Systems Ltd. (used successfully on PMJM by R Schorr, personal �66 communication). A maximum of 30 mice at each study site will be radio-tagged. The following procedures will be used to capture and attach the transmitters to the mice. Trapping session details Timing of surveys 1. Four 7-day trapping sessions will be conducted during the following weeks: June 2-9, 1998; July 21-28, 1998; September 8-15, 1998; and June 2-9, 1999. 2. Due to the nocturnal nature of PMJM, traps will be set between 19:00hrs and 21 :OOhrs and checked as early as possible in the morning beginning at 5:00hrs (to reduce stress and the potential for predation on trapped animals). Time required to complete the traplines will vary depending on how many animals are caught. Trapping protocols 1. Trappers will be advised to follow the Center for Disease Control's Hantavirus instructions and recommendations when dealing with rodents which include: a Baseline blood serum samples will be collected and stored at Poudre Valley Hospital for all surveyors. b. Respirators are available for use by surveyors if they request their use. c. Surgical gloves will be used at all times when handling rodents. d. All equipment will be rinsed first with a I 0% bleach solution, then water after use. e. Traps and any equipment that may have rodent feces or urine on it will not be transported in the interior of a vehicle. f Traps will be cleaned after each use by a mouse. g. If a surveyor becomes ill with hantavirus symptoms they will report immediately to a medical facility. 2. Trappers must be in possession of both a federal and state collecting permit. Trapping methodology 1. Small mammal Sherman live traps {folding and non-folding) will be used to conduct the trapping sessions. 2. Traps will be set in two parallel lines of trap stations (1 trap per station) on either side of the drainage. Trap stations will be 5 meters apart for a total of 250 meters; the parallel transects will be IO meters apart unless extent of habitat, terrain topography, or stream hydrology do not allow. 3. Location of transects will be recorded on field data sheets and identified on 7½ minute topographic maps. Locations will also be recorded to the nearest 5 meters in UTM coordinates using a Trimble Geo-Explorer GPS. 4. In case of windy conditions or large number of trap-tampering predators (i.e., raccoons, foxes, coyotes, etc.), traps will be secured to the ground with hoops of heavy-gauge malleable wire, stakes, or with other materials that can effectively secure/immobilize the traps. 5. A small (~I inch) ball of polyester quilt or wool (fleece) will be placed in each trap as nesting/bedding material. 6. Baiting materials will be Manna Pro Sweet 3-way Livestock feed which contains no animal matter. Ingredients include flaked barley, flaked corn, flaked oats, and cane molasses. Peanut butter will be used to stick the bait to the trap. 7. Checking of the traps will be conducted by two surveyors; one person will handle the traps and animals captured, the other person will record the data Handling of captured animals 1. All animal captures will be recorded. �67 2. 3. 4. 5. If an animal has been captured in a trap, a ziplock plastic bag will be placed over the end of the trap. The trap will be opened allowing the animal to fall into the plastic bag. The animal will be identified to species while in the plastic bag. If the animal is not a PMJM, identification of the animal will be recorded and the animal set free. Each captured PMJM will be scanned to detect the presence/absence of a PIT tag and/or radio-collar. If a PIT tag or radio-collar is detected and the mouse has been captured at that same site within the 7-day trapping effort, identification of the mouse will be recorded and the mouse will be released. If the animal is a PMJM and no PIT tag or radio collar is detected the PMJM will be anesthetized for further processing, as follows. All PMJM will be PIT-tagged. If the PMJM weighs > 18 g a radio-collar will also be put on the animal Anesthesia The following protocol has been used successfully on PMJM by R Schorr (personal communication). I. Measure I ml ofMetofane (methoxyflurane) onto one cotton ball. 2. Place ball into ziplock bag and seal (to keep Metofane fumes in bag). 3. Lay bag still and move away. This should minimize stress for the mouse and the time the mouse struggles in the bag, decreasing the amount of time required for the metofane to work. 4. After the animal stops movement, wait I minute before removing it from the baggie. The animal should remain anesthetized for 2-3 minutes. 5. Time animal is exposed to Metofane and reaction to the anesthesia will be recorded. PIT tagging the animal The following protocol has been used successfully on PMJM (C. Meaney, personal communication). I. Each PMJM will have a PIT tag inserted above the shoulder blades by lifting the skin on its back and inserting the needle with. the PIT tag under their skin and injecting the tag. Verification of the PIT tag identification number will be made before insertion into the mouse by running the PIT tag scanner across it. 2. Skin behind the opening will then be pinched to prevent emergence of the tag. 3. Surgical glue will then be applied to the opening to prevent the PIT tag from exiting the body and prevent infection of the mouse. 4. A PIT tag scanner will be held over the mouse to again verify PIT tag identification number and that it still works after the insertion procedure (note: PIT tag will be scanned twice during application to mouse, or once if mouse was previously PIT tagged). 5. PIT tag identification number will be recorded on the field data form and the mouse released. 6. If, at any time during the handling of the PMJM the animal appears to be severely stressed (dramatic changes in heartbeat, respiration and responsiveness or gums turning blue) the animal will be released immediately. Collaring the animal The following protocol has been used successfully on PMJM (R Schorr, personal communication). I. Make sure transmitter is functioning before collaring the animal with the transmitter by tuning the receiver to the transmitter frequency to make sure there is a signal. 2. Slide crimp and then tubing onto the antenna �68 3. 4. 5. 6. 7. 8. Guide antenna through the channel of the transmitter. As antenna exits the transmitter, guide it through the crimp. Keep loop made by antenna large enough to fit over the mouse's head. Once over the neck of the animal, pull antenna to reduce collar size, making sure rubber tubing is on the dorsal side of the neck. The purpose of the rubber tubing is to prevent damage to the collar and prevent the person attaching the collar from cinching the collar too tight. Make sure collar can rotate freely around the animals neck, but not loose enough to be removed. Pinch metal crimp to hold the antenna in the desired collar position. Approximately 2 inches of antenna will be pointing out behind the animal. Measurements 1. Each PMJM will be weighed while in the bag, recording the weight in grams using a Pesola spring balance. 2. Sex, age Guvenile, adult), and reproductive condition (pregnant, lactating or nonbreeding if it is female; for males the position of the testes will indicate if in breeding status or non-breeding status) will be noted. 3. Each PMJM will be measured (total length, length of body, length of hind foot - heel to distal end of claws) in millimeters. Measurements of total body and tail length will be taken with the mouse on a firm surface to minimize error. 4. Capture of every PMJM will be documented by taking a photograph of the mouse on first capture. If the mouse has been captured previously as noted by the detection of a PIT tag, no photograph needs to be taken. 5. If there are feces in the trap where a PMJM was captured, the feces will be collected in a plastic bag labeled with date and location of the site. Fecal samples will be kept cool until returned to the CDOW office where they will be frozen. Fecal samples will be analyzed by the Composition Analysis Laboratory, Inc, 622 ½ Whedbee, Fort Collins, CO for content. Handling of trap mortalities and injuries I. All trap mortalities will be recorded on a 'Trap Mortality' data form which includes information on species, potential duration of time spent in the trap, any information available on cause of death, etc. 2. All animals found dead in a trap will be double-bagged in a plastic bags and placed in a cooler with ice. Specimens should be frozen as soon as possible and deposited the CDOW freezer at the office in Fort Collins. All specimens will be sent to the Colorado State University Diagnostic Laboratory for detection of any disease and/or other conditions that may have contributed to cause of death. All PMJM specimens will be returned to the CDOW. 3. A museum card will be completed and attached to each PMJM specimen and given to Cheri Jones, Curator ofMammalogy at the Denver Museum of Natural History, for study skins and tissue storage once the Diagnostic Laboratory has completed their evaluation. 4. If an animal is severely injured (e.g., severed limb, large lacerations) it will be euthanized by soaking a cotton ball in Metofane (methoxyflurane) and placing the cotton ball and the mouse in a ziplock baggie until the animal stops breathing. All specimens will then go through steps 1-3 above. 5. If an animal appears to be only slightly injured (e.g., broken tail, small laceration) the animal will be released to the wild. If an animal appears to be cold stressed attempts will be made to warm it by holding it in the surveyors hands and/or against their body. If the animal appears to be heat stressed, isopropyl alcohol will be applied with a cotton swab to the ears, arm pits, and feet to cool it down. �69 Training of field crews 1. All field technicians will be required to spend a full day at the Denver Museum of Natural History Zoology Department viewing and handling specimens of all small mammal species likely to be captured in Douglas County. 2. All field technicians will be provided with a small mammal field guide and a key specifically designed to list the species most likely to be captured on the trapping sites. 3. All field technicians will participate in 4 days of practice trapping at the Frank State Wildlife Area from May 26-29. During these trapping sessions all technicians will learn how to place, bait and set traps. Field identification will be practiced on all animals caught each day and verified by crew leaders. All field technicians will also practice handling, measuring, implanting PIT tags, and taking genetic tissue samples from deer mice (Peromyscus manicu/atus) until they are competent in this procedure. Data collection Once transmitters are in place, locations of individual mice will be made nightly. Because very little is known about the movements of PMJM the pilot protocols will be established. As we learn more about PMJM movements, protocols will be adjusted to maximize efficiency and data collection. To describe nightly movements the following parameters will be estimated: 1. Minimum and maximum distances moved each night animal is followed. 2. Mean minimum and maximum distances moved each night for all mice. 3. Minimum and maximum distances moved away from the stream center each night by individual mice. 4. Mean minimum and maximum distances moved away from the stream center each night for all mice. To describe 30-day (or life of the radio transmitter) movements the following parameters will be estimated: Minimum and maximum distances moved each 30-day (or life of the radio transmitter) 1. interval animal is followed. 2. Mean minimum and maximum distances moved each 30-day (or life of the radio transmitter) for all mice. Minimum and maximum distances moved away from the stream center each 30-day (or 3. life of the radio transmitter) interval by individual mice. Mean minimum and maximum distances moved away from the stream center each 304. day (or life of the radio transmitter) interval for all mice. Locations: 1. A minimum of 6 locations per individual mouse per night will be made. As many mice as possible will be tracked on a given night as is feasible to assure the minimum 6 locations per individual. Each individual mouse should be tracked a minimum of 3 nights per week. 2. The 6 locations per night per individual will be scattered throughout the night to maximize information learned about nightly movements (i.e., 8 locations taken within a single hour contains less information than 8 locations taken one each hour). 3. Three bearings will be taken for each location from pre-determined way stations to estimate location of the mouse. 4. Daytime locations will be taken as time permits. �70 Demography Study Background Information on the population dynamics of Preble's meadow jumping mouse is necessary to determine which areas support viable populations. To begin to evaluate the viability of a population information on key demographic parameters must be obtained. Below is a summary of what is know to date on the demography of Preble's meadow jumping mouse. Abundance: There is no information on range-wide abundance of Preble's meadow jumping mouse. However, from trapping surveys it appears that where the subspecies does occur it exists in low densities and thus one of the rarer components of the small mammal assemblage present. Reproduction: Meadow jumping mice have been observed to produce up to three litters per season (Whitaker 1963). Breeding peaks appear to occur in early to mid-June and August with a possible third litter in September (Whitaker 1963). Juvenile Z. h. preb/ei have been observed in June, August, and September (Meaney et al. 1996, 1997, PTI 1996a, M. Bakeman unpublished data, T. Ryon unpublished data), suggesting two litters per year. Z. hudsonius typically have litters of 5-6 young per litter (Quimby 1951 ). Age of first reproduction is unknown for Z. h. preblei, however, females of Z. hudsonius have been observed to give birth at 3 months (i.e., females born in June have been observed to give birth in August of the same year). Gestation period is approximately 18 days (Quimby 1951 ). Young remain dependent on the female for approximately 18 days (Quimby 1951). No evidence of male parental care exists for Z. hudsonius (Whitaker 1963). Survival: No information exists on survival rates for populations of Z. h. preblei. Whitaker (1963) reported a 67% loss of individuals over hibernation and that average body mass of individuals emerging from hibernation was greater than the average for mice entering hibernation. Because no mice are known to store food in their hibernacula, this indicates that the lighter individuals died during hibernation and only those entering with higher masses survived. All the energy they use during hibernation and the periodic arousals (the energetically most expensive part of hibernation) must be the fat they carry into hibernation (B. Wunder, personal communication). Thus, the ability to put on sufficient fat for overwinter survival during hibernation is a critical factor in the life history of these mice. Besides insufficient fat storage prior to hibernation, other observed mortality factors in Z. hudsonius include predation (Whitaker 1963, Poly and Boucher 1997) and cannibalism (Sheldon 1934). Other assumed mortality factors for Z. h. preblei include starvation, exposure, and disease. Population Structure: Armstrong et al. (1997) reported an overall sex ratio for all captured Preble's meadow jumping mice of 51. 6 males: 48. 4 females; approximately 86. 0% of captures were identified as adults. However, Armstrong et al. (1997) suggested that these data be interpreted with caution because of possible differences in field techniques. Longevity: Very few individuals of Z. h. preb/ei have been permanently marked. Therefore, recapture information, necessary to determine longevity, is minimal. Several recaptures have yielded adults surviving through two years, indicating a longevity of at least three years (T. Ryon, unpublished data). One recapture history from Rocky Flats Environmental Technology Site recorded an adult male in 1996, two years after it was first captured as an adult in 1994, indicating survival of at least four years {PTI 1996b). Quimby (1951) found that only a low percentage of Z. hudsonius lived two years or more, but gave two records of mice that lived for at least two years under natural conditions. Whitaker (1963) reported a female living at least two years. Objectives Objectives of the demography study are to: 1. Estimate abundance of PMJM at each of three study populations. 2. Estimate over-summer, over-winter, and annual survival of PMJM at each of three study populations. 3. Estimate temporary emigration of PMJM at each of three study populations. 4. Estimate immigration of marked PMJM back into each of three study populations. 5. Evaluate the affect of weight, sex, age, abundance (i.e., density dependent response), �71 6. and habitat features such as stream reach, vegetation composition and density on survival, reproduction, abundance, temporary emigration, and immigration of marked animals back into three study populations of PMJM. Estimate age and sex ratios of PMJM at each of three study populations. Approach Mark-recapture estimation techniques will be used to estimate abundance, over-summer survival, over-winter survival, temporary emigration and immigration of marked animals back in to the three study populations of PMJM. Abundance: Abundance will be estimated using Pollock's Robust Design (see Kendall et al. 1997, 1995 and Kendall and Nichols 1995 for detail). The robust design is a combination of the CormackJolly-Seber (CJS)(Cormack 1964, Jolly 1965, Seber 1965) live recapture model and the closed capture models. The key difference from the CJS model is that instead of just one capture occasion between survival intervals multiple capture occasions are used. These occasions are close together in time allowing the assumption that no mortality or emigration occurs during theses short time intervals. The closely spaced encounter occasions are termed "trapping sessions" and each trapping session can be viewed as a closed capture survey. Four 7-day trapping sessions will be conducted during the following weeks: June 2-9, 1998; July 21-28, 1998; September 8-15, 1998; and June 2-9, 1999. Survival: By using the estimate of the probability that an animal is captured at least once from the trapping sessions designed to estimate abundance, survival between the longer intervals can be estimated. Four 7-day trapping sessions will be conducted during the following weeks: June 2-9, 1998; July 21-28, 1998; September 8-15, 1998; and June 2-9, 1999. Thus, estimates of over-summer survival, over-hibernation survival, annual survival and survival from June-July, July-August, and August-September can be made. Temporary emigration and immigration: The longer intervals between trapping sessions also allows estimation of temporary emigration from the trapping area, and immigration of marked animals back to the trapping area Reproduction: Reproductive parameters will be estimated by following radio-tagged females to nest sites. At each nest found the following will be recorded: date, number of young in each nest and number oflitters observed for individual females throughout the year Habitat Use Study Background The habitat matrix within the range of Z. h. preblei is mixed grasslands adjacent to the Colorado Front Range along the Piedmont and along the base of the Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, Preble's meadow jumping mice occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major components. The first component is a supply of open water, at least in part of the active season (M. Bakeman, C. Meaney, personal communication). Secondly, areas where Preble's meadow jumping mouse has been found have dense cover (M. Bakeman, C. Meaney, personal communication). If Preble's meadow jumping mouse behaves as a metapopulation in the classical sense of a set of local populations linked by infrequent dispersal then habitat includes not just one area of suitable habitation but also areas suitable for nearby mouse populations. These suitable areas must also be linked by dispersal habitat. If the mice are dependent on dense riparian habitat for dispersal as well as for areas to reproduce, persistence of discrete populations would require a mosaic of suitable discrete riparian patches interconnected with dispersal corridors of similarly dense riparian vegetation. If mouse populations function in a source (populations where growth rate~ 1) and sink (those populations where �72 growth rate < 1, maintained through immigration) system, it will be critical to identify and protect those populations serving as sources. Thus, for a source-sink population critical habitat will include those areas that support source population, dispersal habitat to sink areas will be less critical. If local mouse populations are functionally discrete, such a mosaic of interconnected areas of suitable habitat would provide a buffer for local, and source, populations against deleterious stochastic events by providing the opportunity for local population failures to be 'rescued' by immigration from other populations. Areas of suitable habitat must also provide requirements to survive throughout the life cycle. These requirements must provide necessities for both the active period and hibernation periods. During the active period suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence), and dispersal. The hibernation period requires sufficient food supplies to assure fat storage prior to hibernation and suitable hibernacula Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. Based on studies of Z. h. preblei and Z hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but is often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). Preble's meadow jumping mice have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road use, and moderate cattle grazing (M. Bakeman, personal communication). The majority of sites where Z. h. preblei have been found consist of multistoried cover but the species composing the cover vary greatly (Armstrong et al. 1997, Meaner et al .. 1997). Vegetation composition of the dense cover varies considerably and includes both native and non-native species (Meaner et al. 1996, 1997, Armstrong et al. 1997, M. Bakeman, personal communication). The herbaceous understory can be primarily grasses or forbs or a mixture of the two. Few of the sites, however, are dominated by fewer than two understory species. The tall shrub canopy at most sites is willow (several species), although scrub oak, birch, and alder occur in sites south of the Palmer Divide (Armstrong et al. 1997). Ponderosa pine is the most common tree at higher elevations. The mouse appears to tolerate weedy or exotic species in areas that are structurally diverse and species rich; nearly every successful site contained Canada thistle (Armstrong et al. 1997). Thus, the mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. Preble's meadow jumping mouse mice are typically not found in upland areas away from riparian habitats but are most often captured where either ground water daylights to seep springs or on main water channels (M. Bakeman, T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. Movement of Z. h. preblei on Woman Creek at Rocky Flats Technology Site suggests mice move along corridors of shrub cover, generally Salix exigua (PTI 1996a, T. Ryon, unpublished data), suggesting dispersal habitat is similar to habitats used for other activities. Jumping mice of the genus Zapus are true hibernators, spending much of their lives in hibernation. Meadow jumping mice spend approximately 7 months (~210 days) per year in hibernation (Quimby 1951) whereas estimates for Z. princeps indicate that some populations (e.g., in the western mountains of Utah) spend up to 300 days per year in hibernation (Cranford 1983). Males emerge prior to females (Bailey 1923, Bailey 1929, Hamilton 1935, Quimby 1951, Whitaker 1963) with the earliest annual recorded dates for Z. hudsonius males being April 25-May 16 and females May 4-26. Latest fall capture date for an adult male was October 10 in 1994 at South Boulder Creek (ERO Resources 1995) and September 28 in 1995 at the Van Fleet Parcel on South Boulder Creek (Armstrong et al. 1997). A juvenile male was captured as late as October 26 and a female juvenile on �73 October 27 both in 1995 at Rocky Flats Environmental Technology Site (M. Bakeman, unpublished data). Jumping mice hibernate in underground burrows (Quimby 1951, Whitaker 1963). They are excellent burrowers and create their own hibernacula Meadow jumping mice are generally solitary hibernators, however, there have been occurrences of more than one mouse found in a single hibernaculum. One hibernaculum, located on Rocky Flats Environmental Technology Site, used by Z. h. preblei has been located (Armstrong et al. 1997). This site was 9m above a creek bed (Walnut Creek); it had a thick cover of chokecherry (Prunus virginiana) and snowberry (Symphoricarpos spp.), the mouse was found in a leaf litter nest 30cm beneath the ground in coarse textured soil (Armstrong et al. 1997). Four possible hibernacula were located by tracking radio-telemetered mice at the U. S. Air Force Academy in fall 1997. These sites are located 7, 12, 29, and 31m from a creek bed (R Schorr, personal communication). There was no consistency among sites in aspect (N/NW, SISE, E, and none [level ground]). Three sites were in vegetation dominated by coyote willow (Salix exigua), one site was in vegetation dominated by snowberry and mullein (Verbascum thapsus). However, all four hibernacula appear to be below coyote willows. These four U. S. Air Force Academy sites have not been disturbed to protect any hibernating mice and therefore are only possible hibernacula because there is no confirmation a mouse is actually hibernating there. Confirmation of a true hibernaculum cannot be made until a chamber, or nest is located. These sites may also possibly be locations ofradios discarded by the mice or dead mice. Objective The objective of the habitat study is to identify and refine habitat requirements of Z. h. preblei, including hibernation sites, and to determine if they influenced any of the demographic parameters that will be estimated in this study. Approach The general approach is to measure both site specific and landscape features at each of the three population study sites to document the extent of spatial variation. These quantitative measures of spatial variation will be used in the analyses to determine if they influenced any of the demographic parameters that will be estimated in this study. The following habitat characteristics will be measured and recorded for each site. Micro-site habitat characteristics 1. Cover will be measured at 20 random locations along the 250 meter sampled stream stretch. Mean cover and standard error of the mean will be estimated. Cover will be estimated using a vegetation profile board (Nudds 1977) that allows for an assessment of visual obstruction in 0.5 meter vertical intervals above ground. The board will be 1.5 meters high and 30.48 cm wide. The board is marked in alternate black and white colors at 0.5 meter intervals. Horizontal cover is assessed in each interval by viewing the board from 15 meters away in a randomly chosen direction. The percentage of each interval concealed by vegetation is recorded as 0-20, 21-40, 41-60, 61-80, and 81-100% estimated concealment. 2. Vegetation species composition and richness will be estimated using the Modified-Whittaker nested vegetation sampling method (Stohlgren et al. 1995). A modified Whittaker plot is 20meters x 50-meters with 10 lm2 and 2 10m2 subplots arranged systematically around the perimeter and 1 100m2 subplot centered in the inside of the 20 meter by 50 meter plot. Species composition and percent cover of each species is recorded for each subplot. 3. Soil samples will be taken at each site for a hydrometer textural analysis (percent sand, silt and clay). Samples will be collected using a soil probe. Samples will be taken from 0-12 inches, and 12+ to 24 inches. The 0-12 inch sample will be taken first, removing the probe and soil. Sample will be placed in a labeled ziplock bag. The probe will then be placed in the same hole for the 12+ - 24 inch probe. With that soil sample being placed in a separately labeled ziplock bag. The hydrometer textural analysis will be conducted at the CSU Soils Laboratory. �74 4. 5. 6. 7. Mean stream width will be estimated by measuring stream width at 30 locations along the entire site sampled. The 30 locations will be stratified equidistant from each other to cover the entire stream stretch in increments of site stream length/20. Describe potential hibernacula: upland vegetation, take soil sample at site. Describe nest sites (what they are made of, placement). Compare parameter estimates from 1-6 for the three population study sites. Landscape habitat characteristics The following landscape habitat characteristics will be measured using either GIS, topographic maps, or aerial infrared photography. 1. Estimate distance to nearest human habitation and human disturbance. 2. Estimate connectivity of sites to other streams. 3. Estimate total length of stream stretch at each site and total length of stream stretch with suitable habitat at each site. 4. Compare parameter estimates from 1-3 for the three population study sites. Hibernation site measurements Hibernation sites will be identified by following radio-collared mice in late September and early October. Once a radio-signal remains stationary for 7-10 nights we will assume we have located a hibernaculum. The following measurements will be taken at each hibernation site: 1. 2. 3. 4. Distance ofhibernaculum to stream. Vertical elevation from hibernaculum to stream. Soil sample (as described above for the Habitat Use Study). Vegetation species richness within a 5-m radius. Density of vegetation (measured as described above for the Habitat Use Study). Composition of Seasonal Food Consumption Study Background Specific food habits are unknown for Preble's meadow jumping mouse. Armstrong et al. (I 997) summarized what is currently known about food habits of meadow jumping mice in general as follows: Studies of food habits in central and eastern United States indicate they are governed by availability more than preference (Whitaker 1963). Grass seeds of several species are probably the most important component of the diet, and mice will shift to those species that have available seed. Invertebrates and fungi are also readily eaten. Mice feed on both adult and larval invertebrates, especially Coleoptera (beetles). Invertebrate feeding is very important in the spring as mice emerge from hibernation, and may consist of half of the diet at that time. Mice also feed on various species of fungi, which are often encountered during burrowing activity. As the growing season progresses, graminoid seeds dominate the diet. There is no reason to believe food habitats of one subspecies should differ greatly from those of other subspecies. This belief is further supported by the indirect evidence available that food habits of Z. h. preblei are similar to that described above (i.e., the observation of the piles of grass stems observed in areas where the subspecies is known to occur). As true hibernators, meadow jumping mice do not cache food in their hibernacula Therefore, it is assumed they require high quality food for high fat accumulation prior to immergence. Preble's meadow jumping mice have been observed to increase body weight by 10% in the 2-3 weeks prior to immergence. Laboratory studies show the mouse can gain mass at rates up to 1.0 grams per day (B. Wunder, personal communication). This ability to increase fat reserves at such a rate is used by the �75 mice for preparation to enter hibernation. However, for the mice to successfully gain enough fat prior to hibernation to ensure a high probability of survival throughout hibernation, food of sufficient quality must be available. No specific information is available on what foods Preble's meadow jumping mice eat to meet these ecological requirements. However, from late August through early September, when adults begin to gain weight, there are many species of graminoids that have available seed. In most years, grasshoppers are also readily available and probably dominate invertebrate biomass in most habitats. Objective The objective of this study is to document seasonal changes in foods consumed by Preble's meadow jumping mice. Approach Fecal samples from traps where PMJM are captured during the four trapping sessions will be collected and analyzed for composition and percentage of each discrete food type identified in the total sample. Changes in foods composition by either food type and or percent occurrence will be analyzed for spatial and temporal differences. Spatial differences will be defined as differences among the three populations studied. Temporal differences will be defined as differences among the three trapping sessions (June, July, September). Molecular Systematic Study Background The family Zapodidae Gumping mice) consists of small to medium-sized mice with enlarged hind feet and exceptionally long tails. Four living genera are recognized in this family, two of which, Zapus and Napaeozapus, are found in North America (Hall 1981). There are three living species of the genus Zapus: Z. trinotatus (Pacific jumping mouse), Z. princeps (western jumping mouse), and Z. hudsonius (meadow jumping mouse). Z. h. preblei is one of twelve living subspecies of the species Z. hudsonius (Krutzsch 1954, Hafner et al. 1981). Z. h. preblei was first described by Krutzsch (1954) from a specimen collected by E. A. Preble in 1895 near Loveland, Colorado. Quimby (1951) described the species Z. hudsonius as follows: 'A mouse-like rodent with greatly enlarged hind feet and an exceptionally long tail. The forelegs are relatively short. The ears are somewhat conspicuous. The body is clothed in moderately long, somewhat dense hair of a rather coarse texture and several colors. The dorsal portions are marked by a broad stripe of brownish hairs many of which are tipped with black giving the region a grayish-black appearance. The sides are bright yellowish-orange, whereas the underparts and feet are white. The tail is bicolor, dark above and light below, and sparsely covered with hair which is longer on the terminal part. The mammae are eight, and quite prominent in lactating females. The male genitalia are inconspicuous except during the breeding season when the scrotal sac becomes enlarged. The testes enlarge and may be either abdominal, inguinal, or scrotal during this period.' The skull of Z. hudsonius is small and light with a narrower braincase and smaller molars than in Z. princeps (from Fitzgerald et al. 1994 p. 18). However, Fitzgerald et al. (1994) urge caution in distinguishing the two species of Zapus in Colorado. Such caution is further warranted by the recent conflicting identifications of mice based on genetic characteristics. Analysis of mitochondrial DNA sequence data from 92 individual mice indicates that mice sampled from southeastern Albany County, Wyoming, south along the Front Range of the Rocky Mountains to western Las Animas County, Colorado (Purgatoire Campground, San Isabel National Forest}, form a coherent genetic group (Riggs et al. 1997). This group of samples are distinct from samples obtained from mice from three other populations. Genetic samples from mice captured in the Dorothey Lakes area of southern Colorado (Las Animas County) group together and are most closely allied with Z. h. luteus, a subspecies described from New Mexico (Riggs et al. 1997). The single genetic sample collected from Weld County, Colorado (Lone Tree Creek) and six samples obtained �76 from Warren Air Force Base in Laramie County, Wyoming are most similar to reference samples of Z. princeps from Colorado (Larimer County) and New Mexico (Taos County) (Riggs et al. 1997). The sequence data indicate that the samples from specimens identified as Z. h. luteus and samples from specimens of Z. princeps are more closely allied with each other than either is with the samples defining the Z. h. preblei group. This closer alliance of the samples of Z. h. luteus with Z. princeps rather than Z. h. preblei conflicts with results ofHafuer et al. (1981), based on a combination of pelage, morphologic, and genetic data, which support a closer alliance with Z. hudsonius. A more complete biosystematic evaluation of jumping mice is needed to clarify and further refine relationships among populations of the group referred to as Z. h. preblei as well as to other subspecies and species of the genus 'Zapus. Such an evaluation requires detailed analyses of pelage, morphometric, and genetic data from sufficient numbers of individuals to adequately represent the populations of interest. However, the mitochondrial DNA non-coding (D-loop) sequence data available at this time are consistent with the view that a geographically contiguous set of populations previously recognized as Preble's meadow jumping mouse form a homogenous group recognizably distinct from other nearby populations and from another geographically-adjacent species of the genus (Riggs et al. 1997). Therefore, given the genetic data available, Riggs et al. (1997) conclude Preble's meadow jumping mouse is a distinct population of Z. hudsonius. Objective The objective of the genetic component of this study is to document genetic variation within and among the three study site populations. Efforts are underway to secure funding for this study. Approach Genetic tissue samples will be collected from at least 10 and not more than 30 PMJM captured at each study site. A sample of at least 10 individuals from a population will provide enough information to document the genetic variation within the population, samples sizes in excess of 30 contribute little to documenting the genetic variation within the population (T. Quinn, personal communication). Genetic tissue sampling: collection ofear tissue samples using ear punch tool The following protocol for collection of genetic tissue samples has been used successfully on PMJM (M. Bakeman, C. Meaney, T. Ryon, R Schorr, personal communication). Before checking traps, ear punch tools will be cleaned by immersing them in a 10% bleach solution for a few minutes, then rinsing thoroughly with clean water. Tools will be dried thoroughly. A small screw-cap container will be useful to contain the bleach solution and to receive used ear punch tools. A sports bottle or other container with a squirt or pop-up top may be used for rinsing. Any previously used containers will be washed thoroughly by hand or in the dishwasher and not used for other purposes (e.g., drinking) while in the field. 1. A fresh pair of clean latex gloves will be used when handling each mouse. 2. With a clean ear punch tool, 2 tissue plugs will be obtained from the mouse's ear. If there is excessive bleeding, gentle pressure will be applied to the site with a small , dry piece of cotton for 1 minute. Punch may be applied to deliver the plug as a small circlet of tissue (about the size of the head of a pin) onto a finger of your gloved hand. Placement of the punch may be done in any way that is convenient. 3. Place the finger tip tightly over the end of an opened sample vial and shake to wash the tissue plug into the ethanol. 4. Repeat until all three tissue plugs have been collected into the same sample vial. Inspect the tube to see that all plugs have made it into the ethanol. 5. Close the sample vial--screw the cap on firmly and check that there is no leakage of ethanol when the tube is inverted. Label both the vial and the corresponding record on the data sheet (see item 6 below) with a. unique identifier as follows. Use a seven-place alpha-numeric code composed of the following: �77 - A three-letter designator for the survey location (e.g., WPC = West Plum Creek, GCR = Garber Creek). A number beginning with two digits indicating the year (e.g., 98) followed by 2 digits specifying the individual trapped, numbered sequentially. Example: WPC9801 = first animal sampled at West Plum Creek in 1998. 6. Note: The combined seven-place alpha-numeric code needs to be a unique identifier for an individual mouse across all locations and sites being trapped in studies coordinated by the Colorado Division of Wildlife. Record information for the individual sampled on the data sheet provided. Repetitive entries may be completed before or after the field session but do not allow much time to elapse before doing this--what is obvious to you at the time may not be so obvious later on. Information for each sample needs to be complete and unambiguous if the sample itself is to be useful. After returning from the field, samples will be kept in a cool place or refrigerated until delivery to the CDOW office at 317 West Prospect, Fort Collins, CO where they will be kept in the freezer for analyses. E. LOCATION CDOW Maytag Property is located seven miles south of Castle Rock, Colorado along East Plum Creek. CDOW Woodhouse Property is located on Indian Creek, a tributary of Plum Creek near Louviers, Colorado. The Dupont Property is located west and south of the town of Louviers and contains the eastern stretch of Indian Creek and its confluence with Plum Creek. Pine Cliff Ranch, owned by Colorado Open Lands, is located on Garber Creek and extends eastward to its confluence with West Plum Creek, 5 miles west of Sedalia Training sessions for all field technicians and crew leaders will take place at the Frank State Wildlife Area and Kodak State Wildlife Area located in Weld County, Colorado. Data analyses and office work will be conducted at the CDOW Research Center, 317 West Prospect, Fort Collins, Colorado. F. SCHEDULE April-May April April-May May June 2-9 June-July July July 21-28 July-Aug Sep 8 -15 Sept-Oct, Sept-Oct. December April 1999 Complete Study Plan for a demography study of Preble's meadow jumping mouse Select study sites Purchase equipment for summer 1998 field season Advertize for, hire, and train 4 technicians Conduct first trapping session Collect movement data Collect site and landscape scale habitat data Conduct second trapping session Collect movement data Conduct third trapping survey Collect movement data Collect data on possible hibernation sites Complete preliminary report for Preble's meadow jumping mouse technical working group Complete Final report for 1998 summer field season �78 F. PERSONNEL Tanya Shenk Gary C. White 2 Crew Leaders 2 Field Technicians G. Principal Investigator Statistical Consultant CDOW temporary technicians CNHP temporary technicians BUDGET Operating Expenses radio transmitters (150 @$150) radio receiver (3 @ $2565 ) pit tag scanner (6@$600) pit tags (200 @$10.00) 3 portable communication radios & battery recharger maps computer software, upgrades office supplies photographic equipment, expenses field equipment misc. hardware Personnel 2 field technician for 4 months each 2 crew leader for 6 months $22,500 . $ 7,695 $ 3,600 $ 2,000 $ 2,100 $ 500 $ 1,500 $ 300 $ 500 $ 800 $ 500 $12,000 $30,000 Travel 30,000 miles @0.12 per mile vehicle rental: 3 vehicles, 4 mo. @$120 per month overnight travel 30 days@$75 per day TOTAL $ 3,600 $ 1,440 $ 2,250 $75,365 �79 I. LITERATURE CITED Armstrong, D. M., M. E. Bakeman, A. Deans, C. A. Meaney, and T. R Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Bailey, B. 1929. Mammals of Sherburne County, Minnesota. Journal ofMammalogy 10:153-164. Bailey, V. 1923. Mammals of the District of Columbia Proceedings of the Biological Society. Washington 36:103-138. Cook, T. D. and D. C. Campbell. 1979. Quasi-experimentation: design and analysis issues for field settings. Houghton-Mifflin, Boston. Cormack, RM. 1964. Estimates of survival from the sightings of marked animals. Biometrika 51 :429-438. ERO Resources. 1995. Environmental review of South Boulder Creek Management Area Prepared for City of Boulder Real Estate/Open Space Department. Prepared by ERO Resources Crp., Denver, Colorado in association with Stoecker Ecological Consultants, Boulder, Colorado. Fitzgerald, J.P., C. A. Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. Hafner, D. J., K. E. Petersen, and T. L. Yates. 1981. Evolutionary relationships of jumping mice (genus Zapus) of the southwestern United States. Journal ofMammalogy 62:501-512. Hall, E. R 1981. The mammals of North America John Wiley and Sons, Inc., New York, New York, 2 volumes. Hamilton, W. J., Jr. 1935. Habits of jumping mice. American Midland Naturalist 16:187-200. Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration stochastic model. Biometrika 52:225-247. Jones, C. A. 1996. Mammals of the James John and Lake Dorothey State Wildlife Areas. Final Report, submitted to the Colorado Division of Wildlife and Colorado Natural Areas Program. Kendall, W. L., and J. D. Nichols. 1995. On the use of secondary capture-recapture samples to estimate temporary emigration and breeding proportions. Journal of Applied Statistics.22:751762. Kendall, W. L., K. H. Pollock, and C. Brownie. 1995. A likelihood-based approach to capturerecapture estimation of demographic parameters under the robust design. Biometrics 51 :293308. Kendall, W. L., J. D. Nichols, and J.E. Hines. 1997. Estimating temporary emigration using capturerecapture data with Pollock's robust design. Ecology 78:563-578. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. Meaney, C. A., N. W. Clippinger, A. Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 5:113-117. Poly, W. J., and C. E. Boucher. 1997. Record of a creek chub preying on a jumping mouse in Bruffey Creek, West Virginia Brimleyana 24: 29-32. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. �80 PTI Environmental Services. 1996b. Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Spring 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, 7.apus hudsonius. Ecological Monographs 21:61-95. Riggs, L.A., J.M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation. Final Report for the Colorado Division of Wildlife. Denver, Colorado. Seber, G. A. F. 1965. A note on the multiple recapture census. Biometrika 52:249-259. Sheldon, C. 1934. Studies on the life histories of 7.apus and Napaeozapus in Nova Scotia Journal of Mammalogy 15:290-300. Shenk, T. M. 1998. Conservation assessment and preliminary conservation strategy for Preble's meadow jumping mouse (7.apus hudsonius preblei). Special Report. Colorado Division of Wildlife (in review). Stohlgren,T. J., M. B. Falkner, and L. D. Schell. 1995. A Modified-Whittaker nested vegetation sampling method. Vegetatio 117: 113-121. USFWS. 1997. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, 7.apus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. �81 APPENDIXC STUDY PLAN State of Colorado ProjectNo. W-153-R-ll Work Plan No._....,0=6=6=2_ _ __ Task No. ______2_ _ _ __ Cost Center 3430 Mammals Research Conservation of Preble's meadow jumping mouse (.Zaous hudsonius oreblei) Habitat use and distribution of Preble's meadow jumping mouse (Zapus hudsonius preblei) in Larimer and Weld Counties, Colorado HABITAT USE AND DISTRIBUTION OF PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) IN LARIMER AND WELD COUNTIES, COLORADO A. NEED On May 12, 1998 the U. S. Fish and Wildlife Service (USFWS) published a final rule in the Federal Register (63 FR 26517) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) as 'threatened' under the Federal Endangered Species Act (ESA) of 1973, as amended. Scarcity of suitable habitat presumably limits current distribution of Preble's meadow jumping mouse and thus, maintenance of quality habitat has been identified by the USFWS (63 FR 26517) as the principal conservation goal. Although Meaney et al. (1997) reported an improved ability to recognize suitable habitat for Preble's meadow jumping mouse, a more refined and complete definition of potentially suitable habitat for the mouse does not exist. Because the protection of potentially suitable habitat for Preble's meadow jumping mouse may occur under the ESA, as well as protection of known locations where the subspecies occurs, the definition of potentially suitable habitat, as determined by the USFWS, will directly influence site specific regulatory procedures. Ideally, a definition of potentially suitable habitat for the subspecies would identify areas where the Preble's meadow jumping mouse could survive and reproduce in sufficient numbers to sustain populations throughout its range of natural variability over an extended length of time. During the active period of the life cycle of the mouse, suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence}, and dispersal. The hibernation period requires habitat with sufficient food supplies to assure fat storage prior to hibernation and hibernacula sites. Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. Because very little is known about the ecological requirements of the subspecies, potentially suitable habitat is currently defined only as areas of well-developed, dense herbaceous vegetation consisting of a variety of grasses, forbs and thick shrubs in close proximity to open water. This definition is vague and possibly incomplete. Very few surveys for determining the presence or absence of Preble's meadow jumping mouse have been conducted in Larimer or Weld Counties, Colorado. Of the surveys nine conducted since 1990, only three sites yielded captures of Preble's meadow jumping mouse. Therefore, very little information is known about habitat use or current distribution of the subspecies in these two counties. Quantifying and comparing both landscape and site specific characteristics of habitats where mice are found and not found in these two counties would further our understanding of habitat use by the subspecies, particularly in the northern half of its probable range. Any new locations where Preble's �82 meadow jumping mouse are found during this study would contribute to the range-wide distribution map currently available for the subspecies. Repeated annual visits to these same randomly selected sites would also provide information on population persistence at a given site. Such a monitoring scheme would be necessary for evaluating the continued status of the mouse at each site, providing further information as to the suitability of the habitat for long-term persistence of the population. Both Larimer and Weld Counties include habitat that is currently perceived to be outside the ecological limitations of Preble's meadow jumping mouse. Larimer County provides the opportunity to explore elevational limitations, currently thought to be 7400 feet (2260m) (USFWS 1997); Weld County extends beyond the currently believed eastern boundary of the subspecies. Both of these boundaries will be challenged by selecting survey sites within the two counties beyond the perceived ecological limits of the subspecies. Genetic tissue samples will be collected on all Preble's meadow jumping mice captured to assist identification through DNA analysis, particularly for those animals captured outside the currently perceived ecological limits, and to provide information for future studies to better define the relationships among different populations of Z. h. preblei, other subspecies of Z. hudsonius and other species of Zapus. Thus, the primary objective of this study is to quantify and define habitats used and identify ecological limitations of the subspecies in Larimer and Weld Counties, Colorado. Such information could be used by the USFWS to further refine the current definition of potentially suitable habitat for Preble's meadow jumping mouse. B. OBJECTIVES Specific objectives for this study on Preble's meadow jumping mouse (PMJM) include: 1. Define and quantify habitat characteristics at sites where PMJM was found and sites where PMJM was not found. 2. Identify elevational and eastern boundary limitations for PMJM in Larimer and Weld Counties, Colorado. 3. Describe the distribution of the PMJM in Larimer and Weld Counties, Colorado. 4. Select sites and establish monitoring protocols for determining long-term trends in populations of PMJM. 5. Collect genetic tissue samples to assure identification of PMJM captured during this study and for future genetic analyses to better define the relationship of populations of Z. h. preblei to each other, other subspecies of Z. hudsonius and other species of Zapus. C. EXPECTED RESULTS Conservation of Z. h. preblei should include maintaining populations of the subspecies throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Key concerns include range-wide distribution, habitat use, and population persistence at a given site. This study will address these concerns. Comparisons of habitat variables from both successful and unsuccessful sites will be used to better define suitable habitat for the subspecies. Habitat variables recorded will include both site level characteristics such as vegetational composition, cover, and composition of other small mammal species as well as landscape level characteristics including connectivity with other potential sites, geology, hydrology, and distance to development. Repeated annual visits to the randomly selected sites will provide information on population persistence and site fidelity of individuals at the given sites. Such a monitoring scheme will be necessary for evaluating the continued status of the mouse at given sites and provide further information on the suitability of the �83 habitat to sustain populations of PMJM over the long term. Genetic tissue samples collected from PMJM captured will be used to confirm identification of the mice and for future analyses to better define the relationship among (1) different populations of Z. h. preblei, (2) other subspecies of Z. hudsonius and (3) other species of Zapus. Performa.nce Indicators 1. Provide a definition of and quantify habitat characteristics at sites where PMJM was found and sites where PMJM was not found in Larimer and Weld Counties, Colorado. 2. Update the known distribution of PMJM in Larimer and Weld Counties, Colorado. 3. Provide monitoring sites and protocols for determining persistence trends of PMJM at a given site. 4. Genetically identify all PMJM captured. 5. Complete a genetic tissue sample collection for future genetic analyses to better define the relationship of populations of Z. h. preblei to each other, other subspecies of Z. hudsonius and other species of Zapus. 6. Analyze and publish results of research. 7. Update and modify the CDOW conservation plan for PMJM. D. APPROACH Distribution Study Background The meadow jumping mouse (Z. hudsonius) is broadly distributed across North America from the Atlantic to Pacific coasts, extending south into the United States to Alabama and Georgia and west across the Great Plains to the base of the Rocky Mountains. In general, it is a common inhabitant of moist, grassy and herbaceous fields. Eleven living subspecies have been described (Whitaker 1972). Hafner et al. (1981) describe a twelfth subspecies, Z. h. luteus. Z. h. preblei occurs only in eastern Colorado and southeastern Wyoming (Krutzsch 1954, Long 1965, Armstrong 1972). From its limited ecological and geographic distribution, Fitzgerald et al. (1994) suggest it is an Ice Age relict, once widespread in tallgrass prairie across the eastern plains of Colorado but now restricted to scattered localities on the Colorado Piedmont. Similar relict populations of meadow jumping mice in the White Mountains of Arizona and the Sacramento Mountains and Rio Grande Valley of New Mexico are described as the subspecies Z. h. luteus (Hafner et al. 1981). Numerous surveys have been conducted since 1990 to establish the current distribution of Preble's meadow jumping mouse. Surveys have been funded by the U. S. Fish and Wildlife Service, Rocky Flats Environmental Technology Site, Colorado Division of Wildlife, U.S. Air Force Academy, Warren Air Force Base, Colorado Department of Transportation, City of Boulder Open Space, and City of Boulder Greenways Program (Armstrong et al. 1997, P. Plage, personal communication). From 1990 to 1997 such surveys have yielded captures of Preble's meadow jumping mouse, based on field identification and supported by the genetic analyses, at the following sites: 1. 2. 3. 4. Lone Pine Creek, Larimer County, Colorado Rabbit Creek, Larimer County, Colorado St. Vrain Creek and associated tributaries in Boulder County, Colorado City of Boulder Open Space, along South Boulder Creek and its tributaries, Boulder County, Colorado �84 5. 6. 7. 8. 9. 10. 11. 12. Coal Creek, Jefferson County, Colorado Rocky Flats Environmental Technology Site, Jefferson County, Colorado White Ranch Park, Ralston Creek, Jefferson County, Colorado Plum Creek drainages including Indian Creek, West Plum Creek, and East Plum Creek, Douglas County, Colorado Roxborough State Park, Douglas County, Colorado Hay Creek, Elbert County, Colorado Monument Creek on the U. S. Air Force Academy (AF AC) and tributaries of Monument Creek off the AFAC including Smith Creek, Pine Creek, and Jackson Creek, El Paso County, Colorado Medicine Bow National Forest, Albany County, Wyoming Two more sites yielded mice that were identified as Z. h. preblei in the field but were genetically found to be more closely allied with the western jumping mouse, Z. princeps. These sites include: 1. 2. Warren Air Force Base, Laramie County, Wyoming Lone Tree Creek, Weld County, Colorado Similarity of the habitat at these two sites compared to those where Z. h. preblei (as determined genetically) were found suggests the possibility of areas of sympatry or parapatry between the two species of Za.pus. According to Fitzgerald et al. (1994) the distributions of Z. princeps and Z. hudsonius do overlap. The area of overlap occurs in eastern Wyoming. The distribution of Z. hudsonius in Colorado is now known to be larger than shown in Fitzgerald et al. (1994). The boundaries are currently as far south as Las Animas County (based on genetically identified specimens of Z. h. preblei). Captures of Z. princeps and Z. hudsonius (as identified in the museum) have occurred as close as eight miles of one another within the same drainage (Armstrong 1972). Z. princeps were reported captured in 1981 (Olson and Knopf 1988) at the Lone Pine site in Larimer County, Colorado, where Z. h. preblei were captured this year. Because neither specimens or genetic samples were taken in the 1981 study, identification of those mice will remain in question. The discrepancy may be explained by field misidentification or Meaney et al. (1997) also suggest this discrepancy might be explained by displacement of Z. princeps with Z. h. preblei sometime in the sixteen intervening years between trapping efforts. Although assumed to have different ecological requirements, genetic evidence presented here suggests further investigation of possible distributional overlap between Z. h. preblei and Z. princeps. Several notable results from the genetic analysis of specimens acquired from the Denver Museum of Natural History may affect the location of the southern distribution of Z. h. preblei. One site yielded mice identified as Z. p. princeps in the field but were found to be genetically more closely allied with Z. h. preblei. This site is the most southern location to date of Z. h. preblei and is located at: 1. Purgatoire Campground, San Isabel National Forest, Las Animas County, Colorado Also from Las Animas County were mice collected and identified as Z. h. luteus (Jones 1996), an identification also supported by the genetic analysis. These mice were from: 1. 2. Lake Dorothey State Wildlife Area, Chicorica Creek, Las Animas County, Colorado Lake Dorothey State Wildlife Area, West Fork Schwacheim Creek, Las Animas County, Colorado These sites suggest a more northerly distribution of Z. h. luteus, currently known only from limited areas in New Mexico and Arizona (Hafner et al. 1981 ). Identifying the southern boundary of Z. h. preblei clearly needs further study. �85 Objective Conservation of Z. h. preblei should require maintaining populations of the subspecies throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Specific objectives for the distributional component of this study are to (1) clarify the distribution of the subspecies in Larimer and Weld Counties, Colorado, and (2) define and quantify the amount of suitable habitat within Larimer and Weld Counties. Approach To meet these objectives, this study will include (I) constructing a sampling frame of potentially suitable habitat within the area of interest (Larimer and Weld Counties, Colorado) and (2) conducting trapping surveys to determine presence or absence at 30 sites randomly selected from the sampling frame. Specific approaches to each of these tasks follow. Sampling.frame A sampling frame will be developed to delineate potentially suitable habitat for PMJM from unsuitable habitat. To produce a preliminary map displaying existing potential habitat for Preble's meadow jumping mouse would require at least three primary layers of ecological information. Two initial layers, hydrology and vegetative cover would provide a map displaying all areas where these two ecological requirements of Preble's meadow jumping mouse co-occur. The hydrology layer must be in enough detail to provide locations of intermittent and small order streams as well as identify water source (e.g., irrigation ditches, stream, seep). Degree of density of vegetative cover is sufficient for initial mapping efforts. Demarcation of shrub, trees and grasses will suffice in these initial efforts rather than species identification. However, not all combinations of vegetative cover and water provide sufficient habitat to support Preble's meadow jumping mouse. Thus, mapping potential habitat in such a way would produce a map displaying far more potential habitat than exists. For example, an extremely critical ecological requirement for the survival of the mouse, that to date we have very little information for, is potential hibemacula sites. As a possible index to hibemacula habitat, a third GIS layer, indicating the presence of alluvial deposits may provide some insight in to hibernation requirements. Areas where alluvial deposits co-occur with the presence of water and vegetative cover may provide a more realistic map of potentially suitable habitat for the mouse. Our ability to survey a site selected at random will be restricted to those areas where we are able to obtain permission to access the land. We should be able to survey any randomly selected site on public lands and thus our inference should be unrestricted. Such readily available access will probably not occur on privately owned or leased lands, thus, restricting inferences made on private lands. By stratifying the sampling frame, this lack of access on private lands will not restrict inferences that can be made on public lands. Inference on private lands will depend on the percent of access we get from private landowners. The sampling frame will be developed from the 1:24,000 scale Hydrographic GIS layer developed by the CDOW (Reese Tietje, unpublished data). From this sampling frame a three-stage sampling design will be used to select the 30 random sites for doing PMJM surveys. Primary sampling units will be 3rd order streams. Of the 150 3rd order streams that exist within the sampling frame, 30 will be selected on public lands, 30 on private lands. The secondary sampling unit will be the stream stretch selected within the primary (3rd order stream) unit. The tertiary sampling unit will be the actual sites along the stream stretch selected at the secondary sampling stage that will be sampled. Each of the primary, secondary, and tertiary sampling units will be selected using simple random sampling. If the secondary sampling unit does not yield potentially suitable habitat (i.e., no dense vegetation) secondary sampling units will continue to be selected at random until one yields potentially suitable habitat. Determination of suitable habitat will be made by field site visits. Total stream length of all the secondary sampling units will be recorded as well as total stream length containing potentially suitable habitat. From these measurements an estimate of the probability �86 of potentially suitable habitat occurring within the primary sampling unit will be made for each area surveyed. A mean estimate, over all sites surveyed, of the probability of a primary sampling unit having potentially suitable habitat will then be made. Because of the random selection of primary sampling units, inference can be made as to the probability of potentially suitable habitat existing on all 3rd order streams within the sampling frame. By recording presence or absence of PMJM within the tertiary sampling units we can estimate the probability of PMJM occurring within potentially suitable habitat. Because of the random selection of sampling units in each of the two strata {public and private lands) we can then estimate the probability of PMJM occurring in potentially suitable habitat within both public and private lands. Trapping surveys Trapping surveys to determine presence/absence of PMJM will primarily be conducted following protocols defined by the USFWS (1997). Additional guidelines have also been developed to accommodate the needs of this project. A brief summary of these guidelines follow. Landowner contact 1. To request permission to conduct surveys on private property, landowners will first be notified by letter. The letter will briefly describe the project and outline specifically how they might be affected if PMJM were found on their property. The letter will be followed by a phone call to determine if permission will be granted by the landowner for access to the property or not. 2. No private property will be surveyed without prior consent of the landowner. 3. To request permission to conduct surveys on public land, the agency (e.g., USFS, State Forest, etc.) responsible will be contacted. Timing ofsurveys I. Trapping surveys will be conducted within the period from June 1 to September 15, 1998. These dates correspond to dates when the mouse is known to be out of hibernation. 2. Due to the nocturnal nature of PMJM, traps will be set between l 900hrs and 21 00hrs and checked as early as possible in the morning beginning at 500hrs (to reduce stress and the potential for predation on trapped animals). Time required to complete the traplines will vary depending on how many animals are caught. 3. Absence of PMJM at a site will be defined as no captures of PMJM from a minimum of three consecutive nights and 750 trapnights (a trap night is defined as the sum total number of traps available each night). 4. Presence of PMJM at a site will be defined as at least one capture of PMJM at the site. However, to accommodate sample size requirements for the monitoring and genetics study (see below) trapping efforts will continue until at least 10 individuals are tagged with Passive Integrated Transponders (PIT) tags. Survey protocols 1. Surveyors will be advised to follow the Center for Disease Control's Hantavirus instructions and recommendations when dealing with rodents which include: a Baseline blood serum samples will be collected and stored at Poudre Valley Hospital for all surveyors. b. Respirators are available for use by surveyors if they request their use. c. Surgical gloves will be used at all times when handling rodents. d. All equipment will be rinsed first with a 10% bleach solution, then water after use. e. Traps and any equipment that may have rodent feces or urine on it will not be transported in the interior of a vehicle. �87 2. 3. f. Traps will be cleaned after each use by a mouse. g. If a surveyor becomes ill with hantavirus symptoms they will report immediately to a medical facility. Surveyors must be in possession of both a federal and state collecting permit. If PMJM is found at previously undocumented sites these locations must be reported within one day to the USFWS. Survey methodology I. Small mammal Sherman live traps (folding and non-folding) will be used to conduct the surveys. 2. Traps will be set in two parallel lines of trap stations (I trap per station) on either side of the drainage. Trap stations will be 5 meters apart for a total of 250 meters; the parallel transects will be 10 meters apart unless extent of habitat, terrain topography, or stream hydrology do not allow. 3. Location of transects will be recorded on field data sheets (see Appendix B) and identified on 7½ minute topographic maps. Locations will also be recorded to the nearest 5 meters in UTM coordinates using a Trimble Geo-Explorer GPS. 4. In case of windy conditions or large number of trap-tampering predators (i.e., raccoons, foxes, coyotes, etc.), traps will be secured to the ground with hoops of heavy-gauge malleable wire, stakes, or with other materials that can effectively secure/immobilize the traps. 5. A small (~I inch) ball of polyester quilt or wool (fleece) will be placed in each trap as nesting/bedding material. 6. Baiting materials will be Manna Pro Sweet 3-way Livestock feed which contains no animal matter. Ingredients include flaked barley, flaked com, flaked oats, and cane molasses. Peanut butter will be used to stick the bait to the trap. 7. Checking of the traps will be conducted by two surveyors; one person will handle the traps and animals captured, the other person will record the data Handling ofcaptured animals I. All animal captures will be recorded (see Appendix A, Data Forms). I. If an animal has been captured in a trap, a ziplock plastic bag will be placed over the end of the trap. The trap will be opened allowing the animal to fall into the plastic bag. The animal will be identified to species while in the plastic bag. 2. If the animal is not a PMJM, identification of the animal will be recorded and the animal set free. 3. Each captured PMJM will be scanned to detect the presence/absence of a PIT tag. If a PIT tag is detected and the mouse has been captured at that same site within the 4-day trapping effort, identification of the mouse will be recorded and the mouse will be released. 4. If the animal is a PMJM and no PIT tag is detected.the PMJM will be weighed while in the bag, recording the weight in grams using a Pesola spring balance. 5. Sex, age (juvenile, adult), and reproductive condition (pregnant, lactating or nonlactating, inactive if it is female; for males the position of the testes - scrotal, inguinal, or abdominal) will be noted. 6. Each PMJM will be measured (total length, length of body, length ofhind foot-heel to distal end of claws) in millimeters. Measurements of total body and tail length will be taken with the mouse on a firm surface to minimize error. 7. Capture of every PMJM will be documented by taking two photographs of the mouse on first capture. If the mouse has been captured previously as noted by the detection of a PIT tag, no photograph needs to be taken. �88 8. 9. 10. 11. 12. 13. 14. Each PMJM will have a PIT tag inserted above the shoulder blades by lifting the skin on its back and inserting the needle with the PIT tag under their skin and injecting the tag. Verification of the PIT tag identification number will be made before insertion into the mouse by running the PIT tag scanner across it. Skin behind the opening will then be pinched to prevent emergence of the tag. Surgical glue will then be applied to the opening to prevent the PIT tag from exiting the body and prevent infection of the mouse. A PIT tag scanner will be held over the mouse to again verify PIT tag identification number and that it still works after the insertion procedure (note: PIT tag will be scanned twice during application to mouse, or once if mouse was previously PIT tagged) .• PIT tag identification number will be recorded on the field data form and the mouse released. If there are feces in the trap where a PMJM was captured, the feces will be collected in a plastic bag labeled with date and location of the site. Fecal samples will be kept cool until returned to the CDOW office where they will be frozen. Fecal samples will be analyzed by the Composition Analysis Laboratory, Inc, 622 ½ Whedbee, Fort Collins, CO for content. If, at any time during the handling of the PMJM the animal appears to be severely stressed (dramatic changes in respiration, heartbeat or responsiveness or gums turning blue) the animal will be released immediately. Handling of trap mortalities and injuries 1. All trap mortalities will be recorded on a 'Trap Mortality' data form which includes information on species, potential duration of time spent in the trap, any information available on cause of death, etc. (see Appendix A, Data Formsf 2. All animals found dead in a trap will be double-bagged in a plastic bags and placed in a cooler with ice. Specimens should be frozen as soon as possible and deposited the CDOW freezer at the office in Fort Collins. All specimens will be sent to the Colorado State University Diagnostic Laboratory for detection of any disease and/or other conditions that may have contributed to cause of death. All PMJM specimens will be returned to the CDOW. 3. A museum card will be completed and attached to each PMJM specimen and given to Cheri Jones, Curator of Mammalogy at the Denver Museum of Natural History, for study skins and tissue storage once the Diagnostic Laboratory has completed their evaluation. 4. If an animal is severely injured it will be euthanized by soaking a cotton ball in Metofane (methoxyflurane) and placing the cotton ball and the mouse in a ziplock bag until the animal stops breathing. All specimens will then go through steps 1-3 above. 5. If an animal appears to be only slightly injured (e.g., broken tail, small laceration) the animal will be released to the wild. If an animal appears to be cold stressed attempts will be made to warm it by holding it in the surveyors hands and/or against their body. If the animal appears to be heat stressed, isopropyl alcohol will be applied with a cotton swab to the ears, arm pits, and feet to cool it down. Training offield crews 1. 2. All field technicians will be required to spend a full day at the Denver Museum of Natural History Zoology Department viewing and handling specimens of all small mammal species likely to be captured in Larimer and Weld Counties. All field technicians will be provided with a small mammal field guide and a key specifically designed to list the species most likely to be captured on the trapping sites. �89 3. All field technicians will participate in 4 days of practice trapping at the Frank State Wildlife Area and/or the Air Force Academy from May 26-29. During these trapping sessions all technicians will learn how to place, bait and set traps. Field identification will be practiced on all animals caught each day and verified by crew leaders. All field technicians will also practice handling, measuring, implanting PIT tags, and taking genetic tissue samples from deer mice (Peromyscus maniculatus) until they are competent in this procedure. Habitat Use Study Background Site scale: Based on studies of Z. h. preblei and Z. hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but is often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). Preble's meadow jumping mice have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road use, and moderate cattle grazing (M. Bakeman, personal communication). The majority of sites where Z. h. preblei have been found consist of multistoried cover but the species composing the cover vary greatly (Armstrong et al. 1997, Meaney et al. 1997). Vegetation composition of the dense cover varies considerably and includes both native and non-native species (Meaney et al. 1996, 1997, Armstrong et al. 1997, M. Bakeman, personal communication). The herbaceous understory can be primarily grasses or forbs or a mixture of the two. Few of the sites, however, are dominated by fewer than two understory species. The tall shrub canopy at most sites is willow (Salix spp.), although scrub oak (Quercus gambelli), birch (Betula spp.), and alder (A/nus spp.) occur in sites south of the Palmer Divide (Armstrong et al. 1997). Ponderosa pine (Pinus ponderosa) is the most common tree at higher elevations. The mouse appears to tolerate weedy or exotic species in areas that are structurally diverse and species rich; nearly every successful site contained Canada thistle (Cirsium arvense) (Armstrong et al. 1997). Thus, the mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. Preble's meadow jumping mouse mice are typically not found in upland areas away from riparian habitats but are most often captured where either ground water surfaces to seep springs or on main water channels (M. Bakeman, T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. Movement of Z. h. preblei on Woman Creek at Rocky Flats Technology Site suggests mice move along corridors of shrub cover, generally Salix exigua (PTI 1996a, T. Ryon, unpublished data), suggesting dispersal habitat is similar to habitats used for other activities. Small mammal assemblage: Preble's meadow jumping mice are only one component of the small mammal community inhabiting areas where they were captured. These mice were more often found at sites with high species richness and small mammal abundance (Armstrong et al. 1997, Meaney et al. 1997). The variety and relative abundance of other small mammalian species trapped during surveys for Preble's meadow jumping mouse provide some framework for comparison of small mammal assemblages at sites where Z. h. preblei occurred and sites where none were captured. All trapped sites were either historical sites of known occurrence or apparently suitable habitat for Z. h. preblei, providing a common basis for comparison. Three small mammal species (Spermophilus variegatus, Peromyscus nasutus, and Rattus norvegicus) were not captured where Z. h. preblei occurred but were captured in unsuccessful sites. However, captures of these three species only occurred at one or two sites and the species comprised an extremely small percentage of the species �90 caught in those areas providing too little information for speculating on possible interactions between these species and Z. h. preblei. The higher occurrence and percent composition of capture of Mus musculus, the house mouse, in areas where Z. h. preb/ei was not caught might suggest degradation of habitat for Z. h. preblei in those areas or possibly competition between the two species (Ryon 1996). The house mouse, thrives in areas of human habitation and croplands, but also occurs in abandoned fields and ditch banks where they may displace native rodents (Fitzgerald et al. 1994). Ryon (1996) also reported the presence of domestic cats (Fe/is catus) at sites where Z. h. preblei historically occurred but were not found during his study. Contrarily, C. Miller (personal communication) reported house cats along South Boulder Creek where Preble's meadow jumping mice are known to occur. Landscape scale: Areas of suitable habitat must provide requirements for PMJM to survive throughout its life cycle. These requirements must provide necessities for both the active period and hibernation periods. During the active period suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence), and dispersal. The hibernation period requires sufficient food supplies to assure fat storage prior to hibernation and suitable hibernacula Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. The habitat matrix within the range of Z. h. preblei is mixed grasslands adjacent to the Colorado Front Range along the Piedmont and along the base of the Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, Preble's meadow jumping mice occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major components. The first component is a supply of open water, at least in part of the active season (M. Bakeman, C. Meaney, personal communication). Secondly, areas where Preble's meadow jumping mouse has been found have dense cover (M. Bakeman, C. Meaney, personal communication). If Preble's meadow jumping mouse behaves as a metapopulation in the classical sense [a set of local populations which interact via dispersal of individuals moving among populations and where local extinctions and recolonizations occur (Levins 1970)] then habitat includes not just one area of suitable habitation but also areas suitable for nearby mouse populations. These suitable areas must also be linked by dispersal habitat. If the mice are dependent on dense riparian habitat for dispersal, as well as for areas to reproduce, persistence of discrete populations would require a mosaic of suitable discrete riparian patches interconnected with dispersal corridors of similarly dense riparian vegetation. If mouse populations function in a source (populations where growth rate~ 1) and sink (those populations where growth rate < 1, maintained through immigration) system, it will be critical to identify and protect those populations serving as sources. Thus, for a source-sink population critical habitat will include those areas that support source population, dispersal habitat to sink areas will be less critical. If local mouse populations are functionally discrete, such a mosaic of interconnected areas of suitable habitat would provide a buffer for local, and source, populations against deleterious stochastic events by providing the opportunity for local population failures to be 'rescued' by immigration from other populations. Objective The objective of the habitat study is to identify and refine ecological requirements of Z. h. preblei in Larimer and Weld Counties, Colorado. Approach The general approach is to measure both site specific and landscape features of 30 sites selected at random to be surveyed for the presence of PMJM. A comparison of sites where PMJM are found and are not found will then be made in an attempt to refine our current understanding of the ecological requirements of the subspecies. The following habitat characteristics will be measured and recorded for each site. �91 Micro-site habitat characteristics 1. Cover will be measured at 20 random locations along the 250 meter sampled stream stretch. Mean cover and standard error of the mean will be estimated. Cover will be estimated using a vegetation profile board (Nudds 1977) that allows for an assessment of visual obstruction in 0.5 meter vertical intervals above ground. The board will be 1.5 meters high and 30.48 cm wide. The board is marked in alternate black and white colors at 0.5 meter intervals. Horizontal cover is assessed in each interval by viewing the board from 15 meters away in a randomly chosen direction. The percentage of each interval concealed by vegetation is recorded as 0-20, 21-40, 41-60, 61-80, and 81-100% estimated concealment. 2. Vegetation species composition and richness will be estimated using the Modified-Whittaker nested vegetation sampling method (Stohlgren et al. 1995). A modified Whittaker plot is 20meters x 50-meters with 10 lm2 and 2 10m2 subplots arranged systematically around the perimeter and 1 100m2 subplot centered in the inside of the 20 meter by 50 meter plot. Species composition and percent cover (optical estimate) of each species is recorded for each subplot. 3. Soil samples will be taken at each site for a hydrometer textural analysis (percent sand, silt and clay). Samples will be collected using a soil probe. Samples will be taken from 0-12 inches, and 12+ to 24 inches. The 0-12 inch sample will be taken first, removing the probe and soil. Sample will be placed in a labeled ziplock bag. The probe will then be placed in the same hole for the 12+ - 24 inch probe, with that soil sample being placed in a separately labeled ziplock bag. The hydrometer textural analysis will be conducted at the CSU Soils Laboratory. 4. Mean stream width will be estimated by measuring stream width at 30 locations along the entire site sampled. The 30 locations will be stratified equidistant from each other to cover the entire stream stretch in increments of site stream length/30. 5. Compare parameter estimates from 1-4 for sites where PMJM were captured and sites where PMJM were not captured. Landscape habitat characteristics The following landscape habitat characteristics will be measured using either GIS, topographic maps, or aerial infrared photography. 1. Estimate distance to nearest human habitation and human disturbance. 2. Estimate connectivity of sites to other streams from I :24,000 topographic maps. 3. Estimate total length of stream stretch at each site and total length of stream stretch with suitable habitat at each site. 4. Compare parameter estimates from 1-3 for sites where PMJM were captured and sites where PMJM were not captured. Monitoring Study Background For purposes here, population persistence is defined as the presence of Z. h. preblei at the same site for multiple years. The majority of recent locations of meadow jumping mice have been the result of survey efforts that focused only on determining presence of Z. h. preblei. Once survey protocols (USFWS 1997) are met [i.e., a minimum of 400 trapnights (one trap set for one night= I trapnight) conducted] sites are typically not revisited eliminating the possibility of determining population persistence at these sites. Thus, these and other sites not yet surveyed may or may not have persistent populations. Areas where trapping was conducted over multiple years as part of further research, yielded three sites in Colorado that support persistent populations: Rocky Flats Environmental Technology Site, the U. S. Air Force Academy near Colorado Springs, and Boulder Open Space on South Boulder Creek. Besides establishing the presence of Z. h. preblei over multiple years, other considerations of persistence include (I) presence in consecutive years versus a 'blinking' in and out of a population as would be expected in a metapopulation, (2) how populations are sustained in a given area (e.g., source or sink populations), (3) maximum abundance supportable by a given area, and (4) fluctuations in �92 abundance of a population over years. If Z. h. preblei exist in areas as part of a metapopulation or as a series of source-sink populations it would be critical to conserve and protect all key sub-population areas as well as critical habitat for dispersal. Detailed population studies, including estimating and determining factors affecting survival, reproduction, and dispersal rates, must be conducted to determine if Z. h. preblei occurs as either metapopulations or in source-sink populations. There have been no such studies conducted on Z. h. preblei or Z. hudsonius elsewhere to provide any supporting or refuting evidence for either metapopulation or source-sink structure. Consistently low abundance in a given area due to limiting ecological requirements (e.g., size of area of suitable habitat) or fluctuations in population abundance, including years of low abundance, must be considered in any conservation strategies for Z. h. preblei because of the threat of complete loss of the population due to catastrophic or extreme environmental conditions. Some evidence exists for such fluctuations in population abundance at Rocky Flats Environmental Technology Site. Trapping surveys on the Woman Creek drainage yielded the following captures of Z. h. preblei: seven in 1993 (EG&G 1993), zero in 1994 (T. Ryon, unpublished data), one in 1995 (T. Ryon, unpublished data), two in 1996 (PTI 1996a), and 33 in 1997 (T. Ryon, unpublished data). Trapping effort was consistent from 1995-1997. Repeated trapping surveys conducted over different years intermittently yielded successful captures of Z. h. preblei along the St. Vrain Creek and lower Coal Creek (three in 1989, zero in 1992, zero in 1994, zero in 1996, one in 1997, M. Bakeman, unpublished data). If protocols in each year were the same, these data also suggest populations may undergo fluctuations in abundance. Objective The objective of the monitoring study is to establish a monitoring protocol to evaluate the status (i.e., presence or absence) of Z. h. preblei populations at specific sites and to detect changes in local distribution from year to year. Detection of PIT-tagged individuals from year to year will also provide evidence for site fidelity and/or movements of individual mice from one area to another. Approach Trapping surveys will be repeated each year at 20 randomly selected sites of those surveyed. Of the sites surveyed, monitoring sites will be established from a random selection often sites where no PMJM are captured and 10 sites where PMJM are captured in 1998. These 20 sites will be surveyed every year thereafter. 1. 3. 4. 5. 6. 7. Trapping surveys will be conducted as described in the Distribution Study. Habitat will be evaluated at all sites as described in the Habitat Use Study and comparisons made to results from previous years. Each PMJM captured will be PIT-tagged as per the protocols outlined in the Distribution Study. Population persistence at a given site will be evaluated as the number of years when a given site hadPMJM. Recaptures of PIT-tagged individuals will be mapped from year to year to provide evidence for site fidelity and/or movements of individual mice from one area to another. Detailed protocols for long-term data analyses will be designed once a state-wide, long-term monitoring program is fully developed. Molecular Systematic Study Background The family Zapodidae Gumping mice) consists of small to medium-sized mice with enlarged hind feet and exceptionally long tails. Four living genera are recognized in this family, two of which, 'Zapus and Napaeozapus, are found in North America (Hall 1981). There are three living species of the genus 'Zapus: Z. trinotatus (Pacific jumping mouse), Z. princeps (western jumping mouse), and Z. hudsonius (meadow jumping mouse). Z. h. preblei is one of twelve living subspecies of the species Z. �93 hudsonius (Krutzsch 1954, Hafner et al. 1981). Z. h. preblei was first described by Krutzsch (1954) from a specimen collected by E. A. Preble in 1895 near Loveland, Colorado. Quimby (I 951) described the species Z. hudsonius as follows: 'A mouse-like rodent with greatly enlarged hind feet and an exceptionally long tail. The forelegs are relatively short. The ears are somewhat conspicuous. The body is clothed in moderately long, somewhat dense hair of a rather coarse texture and several colors. The dorsal portions are marked by a broad stripe of brownish hairs many of which are tipped with black giving the region a grayish-black appearance. The sides are bright yellowish-orange, whereas the underparts and feet are white. The tail is bicolor, dark above and light below, and sparsely covered with hair which is longer on the terminal part. The mammae are eight, and quite prominent in lactating females. The male genitalia are inconspicuous except during the breeding season when the scrotal sac becomes enlarged. The testes enlarge and may be either abdominal, inguinal, or scrotal during this period.' The skull of Z. hudsonius is small and light with a narrower braincase and smaller molars than in Z. princeps (from Fitzgerald et al. 1994 p. 18). However, Fitzgerald et al. (I 994) urge caution in distinguishing the two species of Zapus in Colorado. Such caution is further warranted by the recent conflicting identifications of mice based on genetic characteristics. Analysis of mitochondrial DNA sequence data from 92 individual mice indicates that mice sampled from southeastern Albany County, Wyoming, south along the Front Range of the Rocky Mountains to western Las Animas County, Colorado (Purgatoire Campground, San Isabel National Forest), form a coherent genetic group (Riggs et al. 1997). This group of samples are distinct from samples obtained from mice from three other populations. Genetic samples from mice captured in the Dorothey Lakes area of southern Colorado (Las Animas County) group together and are most closely allied with Z. h. luteus, a subspecies described from New Mexico (Riggs et al. 1997). The single genetic sample collected from Weld County, Colorado (Lone Tree Creek) and six samples obtained from Warren Air Force Base in Laramie County, Wyoming are most similar to reference samples of Z. princeps from Colorado (Larimer County) and New Mexico (Taos County) (Riggs et al. 1997). The sequence data indicate that the samples from specimens identified as Z. h. luteus and samples from specimens of Z. princeps are more closely allied with each other than either is with the samples defining the Z. h. preblei group. This closer alliance of the samples of Z. h. luteus with Z. princeps rather than Z. h. preblei conflicts with results ofHafuer et al. (1981), based on a combination of pelage, morphologic, and genetic data, which support a closer alliance with Z. hudsonius. A more complete biosystematic evaluation of jumping mice is needed to clarify and further refine relationships among populations of the group referred to as Z. h. preblei as well as to other subspecies and species of the genus Zapus. Such an evaluation requires detailed analyses of pelage, morphometric, and genetic data from sufficient numbers of individuals to adequately represent the populations of interest. However, the mitochondrial DNA non-coding (D-loop) sequence data available at this time are consistent with the view that a geographically contiguous set of populations previously recognized as Preble's meadow jumping mouse form a homogenous group recognizably distinct from other nearby populations and from another geographically-adjacent species of the genus (Riggs et al. 1997). Therefore, given the genetic data available, Riggs et al. (I 997) conclude Preble's meadow jumping mouse is a distinct population of Z. hudsonius. Objective Because of the uncertainty of the identification of the mice captured in Weld County, Colorado, and because currently perceived ecological boundaries of PMJM will be challenged in the survey effort, the objective of the genetic component of this study is to genetically identify the PMJM captured during this study. Therefore, genetic tissue samples will be collected from each PMJM captured to confirm identification of the animal. These genetic tissue samples could also provide further data to better define the relationships of different populations of Z. h. preblei as well as to other subspecies of Z. hudsonius and other species of Zapus through molecular systematic relationships and to link these genetic relationships to systematic studies of Z. hudsonius. Efforts are underway to secure funding for these studies. �94 Approach Genetic tissue samples will be collected from every PMJM captured during the study. To date, positive identification of the individual to subspecies cannot be made using only genetic information. However, results of the DNA analysis combined with the morphometric data that will also be collected (e.g., body length, tail length) and the photograph of the individual should provide sufficient information to support the field identification to subspecies. As established by the USFWS (1997) Survey Guidelines, presence of PMJM is established when only one individual is captured. Thus, we could stop our trapping efforts after the first PMJM capture. However, because we would also like to provide sufficient genetic data to more fully explore the relationships of different populations of Z h. preblei we will attempt to collect genetic tissue samples from a minimum of IO individuals per successful survey site. A sample of at least IO individuals from a population will provide enough information to document the genetic variation within the population (T. Quinn, personal communication). Genetic tissue sampling: collection ofear tissue samples using ear punch tool The following protocol has been used on PMJM (M. Bakeman, C. Meaney, T. Ryon, R Schorr, personal communication). Before checking traps, clean the ear punch tools by immersing them in a I 0% bleach solution for a few minutes, then rinsing thoroughly with clean water. Dry tools thoroughly. A small screw-cap container will be useful to contain the bleach solution and to receive used ear punch tools. A sports bottle or other container with a squirt or pop-up top may be used for rinsing. Wash any previously used containers thoroughly by hand or in the dishwasher and do not use for other purposes (e.g., drinking) while in the field. I. Use a fresh pair of clean latex gloves when handling each mouse. 2. With a clean ear punch tool, obtain 2 tissue plugs from the mouse's ear. If there is excessive bleeding, gentle pressure will be applied to the injured area for approximately I minute. Punch may be applied to deliver the plug as a small circlet of tissue (about the size of the head of a pin) onto a finger of your gloved hand. [Placement of the punch may be done in any way that is convenient or useful as an ear mark in the context of your own work. A consistent location on one ear can help identify recaptured mice that have already been sampled.] 3. Place the finger tip tightly over the end of an opened sample vial and shake to wash the tissue plug into the ethanol. 4. Repeat until all three tissue plugs have been collected into the same sample vial. Inspect the tube to see that all plugs have made it into the ethanol. 5. Close the sample vial--screw the cap on firmly and check that there is no leakage of ethanol when the tube is inverted. Label both the vial and the corresponding record on the data sheet (see item 6 below) with a unique identifier as follows. Use a seven-place alpha-numeric code composed of the following: - A three-letter designator for the survey location (e.g., STV = St. Vrain, SCR = Smith Creek). A number beginning with two digits indicating the year (e.g., 98) followed by 2 digits specifying the individual trapped, numbered sequentially. Example: STV9801 = first animal sampled at St. Vrain in 1998. 6. Note: The combined seven-place alpha-numeric code needs to be a unique identifier for an individual mouse across all locations and sites being trapped in studies coordinated by the Colorado Division of Wildlife. Record information for the individual sampled on the data sheet provided. Be sure to include all data requested. Repetitive entries may be completed before or after the field session but we �95 recommend not allowing much time to elapse before doing this--what is obvious to you at the time may not be so obvious to us, or to you, later on. Information for each sample needs to be complete and unambiguous if the sample itself is to be useful. After returning from the field, samples will be kept in a cool place or refrigerated until delivery to the CDOW office at 317 West Prospect, Fort Collins, CO where they will be kept in the freezer for analyses. E. LOCATION Trapping surveys will be conducted at 30 sites selected at random from the sampling frame developed for Larimer and Weld Counties, Colorado. No survey site will occur at elevations greater than 7600 feet and not east of the UTM Easting Coordinate of 602000. The molecular systematic studies will be conducted in genetic laboratories using the genetic tissue samples collected in the field (ear punches). Training sessions for all field technicians and crew leaders will take place at the Frank State Wildlife Area located in Larimer County, Colorado 2.3 miles east ofl-25 on Highway 392 and 0.5 miles south on County Road 13. Data analyses and office work will be conducted at the CDOW Research Center, 317 West Prospect, Fort Collins, Colorado. F. SCHEDULE March 1998 April 1998 May 1998 May 1998 May 1998 June-September 1998 October 1998 Oct 1998-March 1999 December 1998 Aprill999 Aprill999 G. Purchase equipment for summer 1998 field season Complete sampling frame and select trapping sites Complete Study Plan for a distribution study of Preble's meadow jumping mouse Advertize for, hire, and train technicians Train field crews Conduct trapping surveys, collect site habitat data Conduct GIS analyses of the sites surveyed Conduct analyses Provide USFWS with a preliminary report of the results of the study Complete analyses for 1998 season. Submit Final Report for the 1998 season to the CDOW and USFWS PERSONNEL Tanya Shenk Gary C. White I CDOWTFTE 4 CNHP temporary employees Principal Investigator Statistical Consultant Field Crew leader Field Technicians �96 H. BUDGET The following is a budget to conduct habitat use and distributional information for 30 sites to be completed in summer 1998. Operating Expenses PIT Tags PIT tag scanners PIT tag software genetic sampling kit expenses traps topographic maps photographic equipment, expenses laboratory analyses (fecal, soil) camera trap supplies misc. equipment (gloves, cotton, bait, etc.) $ $ $ $ $ $ $ $ $ $ Personnel 4 field technician for 3.5 months each 1 crew leader for 5 months GIS contract work Statistical consultant $24,000 $24,000 $ 4,000 $ 3,000 Travel 30,000 miles @0.12 per mile vehicle rental: 3 vehicles, 4 mo. @$120 per month overnight travel 30 days @$75 per day $ $ $ TOTAL $80,290 I. 3,000 1,800 300 500 2,000 500 3,500 1,200 5,000 200 3,600 1,440 2,250 LITERATURE CITED Armstrong, D. M. 1972. Distribution of mammals in Colorado. University of Kansas, Museum of Natural History Monograph 3:1-415. Armstrong, D. M., M. E. Bakeman, A. Deans, C. A. Meaney, and T. R Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. EG&G. 1993. Report of Findings: 2nd Year Survey for the Preble's meadow jumping mouse. Prepared by Stoecker Environmental Consultants for ESCO Associates, Inc., Rocky Flats Environmental Technology Site, Jefferson County, Colorado Fitzgerald, J.P., C. A. Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. Hafner, D. J., K. E. Petersen, and T. L. Yates. 1981. Evolutionary relationships of jumping mice (genus Zapus) of the southwestern United States. Journal ofMammalogy 62:501-512. �97 Hall, E. R 1981. The mammals of North America John Wiley and Sons, Inc., New York, New York, 2 volumes. Jones, C. A. 1996. Mammals of the James John and Lake Dorothey State Wildlife Areas. Final Report, submitted to the Colorado Division of Wildlife and Colorado Natural Areas Program. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. Levins, R 1970. Extinction. Lectures in Mathematical Life Sciences 2:75-107. Long, C. A. 1965. The mammals of Wyoming. University of Kansas Publications, Museum of Natural History, 14:493-758. Meaney, C. A., N. W. Clippinger, A. Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mo.use (:lapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 5:113-117. Olson, T. E., and F. L. Knopf. 1988. Patterns of relative diversity within riparian small mammal communities, Platte River watershed, Colorado. Pg. 379-386 in: Proceedings of the symposium: Management of amphibians, reptiles and small mammals in North America. Flagstaff, Arizona U. S. Forest Service, General Technical Report RM-166. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, Zapus hudsonius. Ecological Monographs 21:61-95. Riggs, L. A., J. M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation Final Report for the Colorado Division of Wildlife. Denver, Colorado. Ryon, T. R 1996. Evaluation of historical capture sites of the Preble's meadow jumping mouse in Colorado, final report. MS Thesis. University of Denver, Denver, Colorado. Stohlgren,T. J., M. B. Falkner, and L. D. Schell. 1995. A Modified-Whittaker nested vegetation sampling method. Vegetatio 117: 113-121. USFWS. 1997a Proposal to list the Preble's meadow jumping mouse as an endangered species. USFWS 50 CFR part 17. �98 USFWS. 1997b. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. Whitaker, J. 0., Jr. 1972. Zapus hudsonius. Mammalian Species 11:1-7. �0 Entcrcu 0 Checked SMALL MAMMAL TRAPPING FORM DATE_ _ _/_· _J___ _ SITEI.D(DRAINAGE). _ _ _ _ _ _ _ _ _ _ _ TOPOQUAD. NAME _ _ _ _ _ _ _ _ _ _UlME _ _ _ _ _ _ _ _ _ _ _UTMN_ _ _ _ _ _ _ _ _ _ _ PAGE HANDLER_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ TRAP TYPE _ _ _ _ _ _ _ _ _ _ _ __ TEMPERATURE _ _ _ __ OBS NUM Tnp NO. OF TRAPS _ _ _ _ _ _ SAMPLE SITE _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ TIME START _ _ _ _ TIMEFINISH _ _ _ __ CLOUD COVER (0-8) _ __ WIND _ _ _ _ _ _ __ COMMONNAME OF RECORDER._ _ _ _ _ _ _ _ _ _ _ _ _ __ [NJ/ TOTAL BAG MORT WT(I) WT(g). TAIL LENGTII B°"1 Length HIND FOOT (111111) (mm) (mm) PRECIPITATION _ _ _ _ _ _ _ _ _ _ __ EAR (mm) SEX REP. #Ear COND Plugs PITT1g# RADIO PJM SIie FREQ Phoeo Pbollo COMMENTS ~~ &~ "r1Z 0 t:, ~ ~ > '°ID COMMENTS:_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ �100 Zapus hudsonius preblei Injury/Mortality Documentation Found dead Found severely injured, euthanized Slightly injured, returned to wild Died during handling Date/Time:------------------------------Location: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Weather Conditions: - - - - - - - - - - - - - - - - - - - - - - - - - - Approximate Time Trap Set:._ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Time Trap Checked:._ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Field Technician(s) Present: Information: Species: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ PIT TAG Number: - - - - - - - - - - - - - - - - - - - - - - - - - - Weight (g): - - - - - - - - - - - - - - - - - - - - - - - - - Total Body Length (mm): - - - - - - - - - - - - - - - - - - - - - - Tail Length ( m m ) : - - - - - - - - - - - - - - - - - - - - - - - - - Hindfoot Length (mm): - - - - - - - - - - - - - - - - - - - - - - Ear Length ( m m ) : - - - - - - - - - - - - - - - - - - - - - - - - Sex: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Reproductive Condition(s): - - - - - - - - - - - - - - - - - - - - - - - - Description of Injury: - - - - - - - - - - - - - - - - - - - - - - - - - - Details of Probable Reasons for Injury or Mortality: Signature of Technician(s): �1 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT State of ----..-=..a---=="'------Colorado P roj ect No. _ _ _W..:..:--=15:;..;:3;_-R=:.;::...;-1=2'---_ _ __ Work Package No. _0=6=6=2'--------Task No. _ _ _ _-=-1_ _ _ _ _ _ __ Cost Center 3430 Mammals Program Preble's Meadow Jumping Mouse Conservation Develop Conservation Plan for Preble's Meadow Jumping Mouse Period Covered: July 1, 1998 - June 30, 1999 Author: Tanya M. Shenk ·Personnel: J. Brinker, J. Eussen, M. Miller, M. Sivert, M. Wild, CDOW, K Burnham, G. White, CSU ABSTRACT Preliminary analysis of the movement data collected on radio-collared PMJM indicate (1) maximum movements of> 1 mile, (2) greater use of upland habitats than previously assumed, (3) general site fidelity to both daytime nesting sites and nighttime feeding sites, (4) seasonal shifts in movement patterns, (5) use of both perennial and intermittent tributaries adjacent to the capture drainage, and (6) long distance movements in September to new locations, presumably in preparation for hibernation. Mouse locations were categorized by the distance criteria used in the USFWS Proposed 4-D Rule to provide the greatest amount of information to evaluate if the proposed regulations would be sufficient to ensure protection of PMJM. Given the high proportion of locations within both the proposed buffer zone (150-300 feet) and outside any area of protection(> 300 feet), data from this study do not support the regulations regarding the 300 foot protection zone from the center of the capture stream. Analyses were not completed using the criteria of protection up to 300 feet from the edge of contiguous wetlands because a delineation of contiguous wetlands for any of the three study sites is not yet available. Once these contiguous wetlands are mapped, similar analyses will be conducted using edge of the wetland rather than stream center for perpendicular distance measurements. Eight possible hibemacula were located during this study. Five of the eight mice using these possible hibemacula traveled ;;,: 90 meters from the center of their typical September night time locations. Vegetation characteristics of the eight sites located during this study are similar to other hibemacula described for PMJM. Natural mortality factors documented during this study included predation by house cats, garter snakes, rattlesnakes, and fox as well as accidents by drowning and road kill. High percentages of arthropods and endogenous fungus were found in the 85 PMJM fecal samples analyzed thus far. The combination of shifts in both general mouse movements, individual mouse movements, and diet provide strong circumstantial evidence that PMJM may be selecting for or require specific seasonal diets. A total of39 sites were surveyed for PMJM in Larimer and Weld Counties, Colorado with a total of 16,671 trap-nights completed. Of the 39 sites survey, Zapus spp. were captured at 21 �2 locations. A total of 71 unique individuals were captured in the 21 locations, with recaptures of 14 of those individuals. All sites where Zapus spp. were captured were located in Larimer County. lbree soil samples from 0-12 inches and 12-24 inches were collected at all sites where possible. Soils at some sites were too rocky to collect the 12-24 inch soil samples. Nine fecal samples were collected from traps where Zapus spp. were captured. Initial result indicate that arthropods, fungus, and willows are important dietary components of the Zapus diet. Measurements of habitat characteristics at both the site and landscape levels were completed. Genetic tissue samples were collected from 68 of the 71 jumping mice captured. Analyses of these tissue samples is pending. A total of 186 individual mice were captured and PIT-tagged at three study sites (73 mice at Maytag Property, 77 mice at PineCliffRanch, and 36 mice at Woodhouse Ranch) during the 1998 field season. These mice were captured over three different trapping sessions with an effort of 17,330 trapnights. Genetic tissue samples were collect!;ld for at least 30 individual mice at each of the three study sites. Density estimates were expected to increase as the summer progressed to account for the birth pulses in late June, and late July-August. This was the trend observed at Maytag. PMJM densities at Woodhouse Ranch increased from June to July but did not increase further during the September trapping session. Mean PMJM density over all sites and sessions was 40.5 (range 16.9-79.0) mice per . kilometer of stream stretch. Defining summer as June 1 - October 5, over-summer survival was estimated as 0.36 (se = 0.056) over all three study sites. Temporary emigration and immigration rates were estimated but both had extremely high variances associated with those estimates. Thus, these estimates cannot be used, with any confidence, to provide information on movements of mice into and out of these populations. Very little new information was gained during this study on reproductive parameters of PMJM. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia However, we were unable to loca~e any breeding nests. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during both the July and September trapping sessions. Preliminary results from the demography, movement and distribution studies of PMJM have suggested the need to continue with research currently being addressed in these three studies. However, the preliminary results also suggest further research be conducted on (1) use of upland habitat by PMJM, (2) refining water requirements of PMJM (i.e., do they require stream habitat or are wetland areas sufficient), (3) range-wide distributional boundaries (e.g., elevation restrictions), and (4) investigating areas of potential sympatry or hibridization with Z. princeps (western jumping mouse). The demography and movement studies will be modified during the summer 1999 field season to further investigate upland use and water requirements. This report includes results from only the first year of a multi-year project to follow individually marked PMJM through time. Collection of more data, and more years of data, will improve our ability to evaluate demographic parameters, movement patterns, and habitat use and evaluate how they vary across space and time. �3 PREBLES'S MEADOW JUMPING MOUSE CONSERVATION Tanya M. Shenk P.N. OBJECTIVE Develop and implement a conservation plan for Preble's meadow jumping mouse in Colorado. SEGMENT OBJECTIVES 1. Evaluate movement data of Preble's meadow jumping mouse as it relates to landscape features at two study sites. 2. Conduct presence/absence surveys for Preble's meadow jumping mouse at 30 sites in Larimer and Weld Counties, Colorado. 3. Refine and prioritize needed research components to develop sound strategies for conservation of Preble's meadow jumping mouse. 4. Analyze data and prepare a Federal Aid Job Progress Report. Status Report I, Evaluate movement data ofPreble's meadow jumping mouse as it relates to landscape features at two study sites. Movement data of PMJM were collected on radio-collared mice to evaluate the effects of landscape features on movement patterns. Preliminary analysis of the movement data is presented as a draft manuscript, Movement patterns ofPreble's meadow jumping mouse (Zapus hudsonius preblei) as they vary across time and space, in Appendix A In summary, movement data collected on radio-collared PMJM indicate (I) maximum movements of> I mile, (2) greater use of upland habitats than previously assumed, (3) general site fidelity to both daytime nesting sites and nighttime feeding sites, (4) seasonal shifts in movement patterns, (5) use of both perennial and intermittent tributaries adjacent to the capture drainage, and (6) long distance movements in September to new locations, presumably in preparation for hibernation. 2. Conduct presence/absence surveys for Preble's meadow jumping mouse at 30 sites in Larimer and Weld Counties, Colorado. a. Presence/absence surveys Preliminary analysis of the PMJM survey data is presented as a draft manuscript, Habitat use and distribution of Preble's meadow jumping mouse (Zapus hudsonius preblei) in Larimer and Weld Counties, Colorado, in Appendix B. In summary, a total of39 sites were surveyed for PMJM in Larimer and Weld Counties, Colorado with a total of 16,671 trap-nights completed. Of the 39 sites survey, Zapus spp. were �4 captured at 21 locations. A total of 71 unique individuals were captured in the 21 locations, with recaptures of 14 of those individuals. All sites where Zapus spp. were captured were located in Larimer County. Three soil samples from 0-12 inches and 12-24 inches were collected at all sites where possible. Soils at some sites were too rocky to collect the 12-24 inch soil samples. Nine fecal samples were collected from traps where Zapus spp. were captu{ed. Initial result indicate that arthropods, fungus, and willows are important dietary components of the Zapus diet. Measurements of habitat characteristics at both the site and landscape levels were completed. Genetic tissue samples were collected from 68 of the 71 jumping mice captured. b. Abundance, over-summer survival, over-winter, annual survival estimates and population age and sex structure ofPreble 's meadow jumping mouse populations at two study sites. Preliminary analysis of the demography study ofPMJM is presented as a draft manuscript, Temporal and spatial variation in the demography ofPreble's meadow jumping mouse (Zapus hudsonius preblei), in Appendix C. In summary, a total of 186 individual mice were captured and PIT-tagged at three study sites. Mean PMJM density over all sites and sessions was 40.5 (range 16.9-79.0) mice per kilometer of stream stretch. Defining summer as June 1 - October 5, over-summer survival was estimated as 0.36 (se = 0.056) over all three study sites. Temporary emigration and immigration rates were estimated but both had extremely high variances associated with those estimates. Thus, these estimates cannot be used, with any confidence, to provide information on movements of mice into and out of these populations. Very little new information was gained during this study on reproductive parameters of PMJM. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia However, we were unable to locate any breeding nests. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during both the July and September trapping sessions, indicating two birth pulses. 4. Refine and prioritize needed research components to develop sound strategies for conservation ofPreble's meadow jumping mouse. Preliminary results from the demography, movement and distribution studies of PMJM have suggested the need to continue with research currently being addressed in these three studies. However, the preliminary results also suggest further research be conducted on (1) use of upland habitat by PMJM, (2) refining water requirements of PMJM (i.e., do they require stream habitat or are wetland areas sufficient), (3) range-wide distributional boundaries (e.g., elevation restrictions), and (4) investigating areas of potential sympatry or hibridization with Z. princeps (western jumping mouse). The demography and movement studies will be modified during the summer 1999 field season to further investigate upland use and water requirements. 5. Analyze data and prepare a Federal Aid Job Progress Report. A Federal Aid Job Progress Report was submitted to the CDOW on August 16, 1999. �5 APPENDIX A MOVEMENT PATTERNS OF PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) As THEY VARY ACROSS TIME AND SPACE Tanya Shenk and Maile M. Sivert Abstract Preliminary analysis of the movement data collected on radio-collared Preble's meadow jumping mice (PMJM) indicate (I) maximum movements of> I mile, (2) greater use of upland habitats than previously assumed, (3) general site fidelity to both daytime nesting sites and nighttime feeding sites, (4) seasonal shifts in movement patterns, (5) use of both perennial and intermittent tributaries adjacent to the capture drainage, and (6) long distance movements in September to new locations, presumably in preparation for hibernation. Mouse locations were categorized by the distance criteria used in the USFWS Proposed 4-D Rule to provide the greatest amount of information to evaluate if the proposed regulations would be sufficient to ensure protection of PMJM. Given the high proportion oflocations within both the proposed buffer zone (150-300 feet) and outside any area of protection(> 300 feet), data from this study do not support the regulations regarding the 300 foot protection zone from the center of the capture stream. Analyses were not completed using the criteria of protection up to 300 feet from the edge of contiguous wetlands because a delineation of contiguous wetlands for any of the three study sites is not yet available. Once these contiguous wetlands are mapped, similar analyses will be conducted using edge of the wetland rather than stream center for perpendicular distance measurements. Eight possible hibernacula were located during this study. Five of the eight mice using these possible hibernacula traveled :?: 90 meters from the center of their typical September night time locations. Vegetation characteristics of the eight sites located during this study are similar to other hibernacula described for PMJM. Natural mortality factors documented during this study included predation by house cats, garter snakes, rattlesnakes, and fox as well as accidents by drowning and road kill. High percentages of arthropods and endogenous fungus were found in the 85 PMJM fecal samples analyzed thus far. The combination of shifts in both general mouse movements, individual mouse movements, and diet provide strong circumstantial evidence that PMJM may be selecting for or require specific seasonal diets. These data are limited to the first year of a multi-year study and thus annual variation in mouse movement patterns cannot yet be addressed. Continuation of this study, at least through the 1999 field season will provide information on annual variation in PMJM movement patterns. This is an interim progress report. Further analyses will be conducted on these data and data collected during the 1999 field season. llltroduction Movement and dispersal pattern information will be key to any conservation strategy designed for Preble's meadow jumping mouse (PMJM). Documenting daily and seasonal movement patterns of PMJM will provide information on habitats used by the mice and on the relative configuration and juxtaposition of these habitats. Configuration of habitats include vegetation and size of the areas used. Juxtaposition includes relative locations of different habitats used such as nest sites, feeding areas, and movement corridors connecting those areas. Key dispersal factors to document for PMJM include (I) which segment of the population disperses, (2) when do they disperse, (3) through what habitat do they disperse, (4) how far will individuals disperse (i.e., what is the maximum distance that separates adjacent populations) and (5) how critical is dispersal (both into and out of a population) to the persistence of a given population. �6 Areas of suitable habitat must provide requirements to survive throughout the life cycle. These requirements must provide necessities for both the active period and hibernation periods. During the active period suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence), and dispersal. The hibernation period requires sufficient food supplies to assure fat storage prior to hib~mation and suitable hibernacula Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable -corridors exist for seasonal movement among sites. The habitat matrix within the range of Z. h. preblei is mixed grasslands adjacent to the Colorado Front Range along the Piedmont and along the base of the Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, PMJM occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major components. The first component is a supply of open water, at least in part of the active season (M. Bakeman, C. Meaney, personal communication). Secondly, areas where PMJM has been found have dense cover (M. Bakeman, C. Meaney, personal communication). Based on studies of Z. h. preb/ei and Z. hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but are often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). The mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. PMJM are typically not found in upland areas away from riparian habitats but are most often captured where either ground water becomes visible as either seep springs or as main water channels (M. Bakeman,T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. PMJM have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road use, and moderate cattle grazing (M. Bakeman, personal communication). The only currently available data on dispersal and/or movement for Z. h. preblei are from marked mice at Rocky Flats Environmental Technology Site (T. Ryon unpublished data). Two mice, an adult female and an adult male, were observed approximately 1.6 kilometers from previous locations (incidences occurred separately). Each of the locations were in the same drainage (Woman Creek). Movement of Z. h. preblei on Woman Creek at Rocky Flats Technology Site suggests mice move along corridors of shrub cover, generally Salix exigua (PTI 1996a, T. Ryon, unpublished data), suggesting dispersal habitat is similar to habitats used for other activities. If PMJM occurs as metapopulations in the classical sense of a set oflocal populations linked by infrequent dispersal then habitat includes not just one area of suitable habitation but also areas suitable for nearby mouse populations. These suitable areas must also be linked by dispersal habitat. If the mice are dependent on dense riparian habitat for dispersal as well as for areas to reproduce, persistence of discrete populations would require a mosaic of suitable discrete riparian patches interconnected with dispersal corridors of similarly dense riparian vegetation. If mouse populations function in a source (populations where growth rate :2: 1) and sink (those populations where growth rate< 1, maintained through immigration) system, it will be critical to identify and protect those populations serving as sources. Thus, for a source-sink population critical habitat will include those areas that support source population, dispersal habitat to sink areas will be less critical. If local mouse populations are functionally discrete, such a mosaic of interconnected areas of suitable habitat would provide a buffer �7 for local, and source, populations against deleterious stochastic events by providing the opportunity for local population failures to be 'rescued' by immigration from other populations. To begin to understand PMJM movement, dispersal, and habitat use we monitored radiocollared mice at three different study areas. Study areas were selected to cover a variety of habitat configurations to evaluate spatial variation in movement patterns of PMJM. To address temporal variation in PMJM movement, dispersal, and habitat use we will' continue this study for at least one more field season at the same three field sites. This is an interim report, after one field season of data collection. Study sites To evaluate spatial differences in movements of PMJM, the three sites selected provided a variety of habitat matrices available to the mouse. The first site selected, the Maytag Property, has one primary water source available to the mouse. This water source is East Plum Creek. Therefore, we predicted mice would restrict their movements to up and down this single drainage. The second site, PineCliffRanch, has both a tributary (Garber Creek) and a main stem drainage (West Plum Creek). This provided the opportunity to investigate whether PMJM will use upland areas to move from one drainage to another or if they are restricted to only moving along riparian corridors. The third study site, Woodhouse Ranch, provided an area with a tributary (Indian Creek) and a series of ponds and irrigation ditches within 0.5 kilometers of the drainage. The configuration at Woodhouse Ranch provided an even greater opportunity to investigate how much the mice use upland areas or if they restrict their movements strictly to riparian corridors. By replicating the same methodologies at each of these three unique habitat matrices we can begin to estimate spatial variation in nightly and seasonal movements of PMJM. Objectives This PMJM movement study is designed to describe nightly and seasonal movement patterns of PMJM and to describe habitats used by PMJM. These movement patterns will be described for three different study areas to evaluate spatial variation, and over two different years at the same three study areas to evaluate temporal variation. Specific objectives include: 1. Describe nightly movements of PMJM. Evaluate difference in nightly movements as they relate to sex, age, and habitat available to the animals. I. Describe 30-day (or life of the radio transmitter) interval movements of PMJM. Evaluate difference in 30-day (or life of the radio transmitter) interval movements as they relate to sex, age, and habitat available to the animals. 2. Describe seasonal movements of PMJM. Evaluate difference in seasonal movements as they relate to sex, age, and habitat available to the animals. 3. Describe habitats where mice occur: movement corridors, end point descriptions (i.e., movement from what to what), and landscape features (connectivity with other riparian areas and other habitats used). 4. Estimate the mean amount of time PMJM spend in each available habitat. 5. Evaluate spatial and temporal variation in movement patterns of PMJM. The objective of the habitat use study is to identify and refine habitat requirements of Z. h. preblei, including hibernation sites, and to determine if they influenced any of the demographic parameters that will be estimated in this and complementary studies (see Shenk and Sivert 1999). �8 Metl,ods Movement data were documented primarily from locations of radio-collared mice from each of the three study populations. To place radio transmitters on the animals, mice were captured in Sherman live traps. Mice weighing> 18 grams were fitted with either :MD-2C, I-gram radio transmitters supplied by Holohill Systems Ltd. (used successfully on PMJM by R Schorr, personal communication) or I-gram radio transmitters supplied by Advanced Telemetry Systems (ATS). Three trapping sessions were conducted during the following weeks: June 2-9, 1998; July 21Aug 6, 1998; and September 8-15, 1998. Trappers were advised to follow the Center for Disease Control's Hantavirus instructions and recommendations when dealing with rodents. Due to the nocturnal nature of PMJM, traps were set between 19:00hrs and 21:00hrs and checked as early as possible in the morning beginning at 5:00hrs (to reduce stress and the potential for predation on trapped animals). Time required to complete the traplines varied depending on how many animals were caught. Small mammal Sherman live traps (folding and non-folding) were used to conduct the trapping sessions. Traps were set in two parallel lines of trap stations (1 trap per station) on either side of the drainage. Trap stations were 5 meters apart for a total of 250 meters; the parallel transects were 10 meters apart unless extent of habitat, terrain topography, or stream hydrology do not allow. Location of transects were recorded to the nearest 5 meters in UTM coordinates using a Trimble Geo-Explorer GPS. A small (~l inch) ball of polyester quilt material was placed in each trap as nesting/bedding material. Baiting material was Manna Pro Sweet 3-way Livestock feed which contains no animal matter; ingredients include flaked barley, flaked com, flaked oats, and cane molasses. Peanut butter was used to stick the bait to the trap. Traps were checked by two surveyors. All animal captures were recorded. If an animal was captured in a trap, a ziplock plastic bag was placed over the end of the trap. The trap was opened allowing the animal to fall into the plastic bag. The animal was identified to species while in the plastic bag. If the animal was not a PMJM, identification of the animal was recorded and the animal set free. Each captured PMJM was checked to detect the presence/absence of a PIT-tag and/or radio-collar. If a PIT-tag or radio-collar was detected and the mouse had been captured at that same site within the same trapping session, identification of the mouse was recorded and the mouse was released. If the animal was a PMJM and no PIT-tag or radio collar was detected the PMJM was anesthetized for further processing, as follows. All PMJM were PIT-tagged for a complementary demography study on PMJM at these same three study sites (see Shenk and Sivert 1999 for details). If the PMJM weighed> 18 g a radio-collar was also put on the animal. Each PMJM was weighed while in the bag, the weight recorded in grams using a Pesola spring balance. Sex, age (juvenile, adult), and reproductive condition (pregnant, lactating or non-breeding if it is female; for males the position of the testes indicated if in breeding status or non-breeding status) was noted. Each PMJM w~ measured (total length, length of body, length of hind foot-heel to distal end of claws) in millimeters. Mice were placed in a plexiglass photobox to reduce handling stress while taking the photograph. If the mouse had been captured previously as noted by the detection of a PITtag, no photograph was taken. If there were feces in the trap where a PMJM was captured, the fecal material was collected in a plastic bag labeled with date, location of the site, and animal PIT-tag number. Fecal samples were kept cool until returned to the CDOW office where they were frozen. Salt was added to each specimen bag for preservation. Once the field season was over all fecal samples were analyzed by the Composition Analysis Laboratory, Inc, 622 ½ Whedbee, Fort Collins, CO for content. All trap mortalities were recorded on a 'Trap Mortality' data form which included information on species, potential duration of time spent in the trap, and any information available to help determine cause of death. All animals found dead were double-bagged in a plastic bag and placed in a cooler with ice. Specimens were frozen as soon as possible and deposited in the CDOW freezer at the office . ·. . : �9 in Fort Collins. A museum card was completed and attached to each PMJM specimen and the specimen and card were given to Cheri Jones, Curator of Mammalogy at the Denver Museum of Natural History, for study skins and tissue storage. If an animal was severely injured (e.g., severed limb, large lacerations) it was euthanized by soaking a cotton ball in Metofane (methoxyflurane) and placing the cotton ball and the mouse in a ziplock bag until the animal stopped breathing. If an animal appeared to be only slightly injured (e.g., broken tail, small laceration) the animal was released to the wild. If an animal appeared to be coldstressed attempts were made to warm it by holding it in the surveyors hands and/or against their body. If the animal appeared to be heat stressed, isopropyl alcohol was applied with a cotton swab to the ears, arm pits, and feet to cool it down. During the last trapping session homeopathic first aid treatments were used in an attempt to minimize stress and improve recovery of each PMJM. Homeopathic first aid kits and instruction was provided by WildAgain Wildlife Rehabilitation, Evergreen, Colorado. PIT-tagging and radio-collaring Each PMJM was individually marked with a Passive Integrated Transponder (PIT-tag). PITtags are electromagnetic, glass-encased tags that emit a passive signal (125 kHz) that can be decoded by a portable reader. Destron-Fearing PIT-tags were used on all mice. We used portable readers from Biomark to read the PIT-tags. All mice were anesthetized to PIT-tag them. Anesthesia procedures followed protocols successfully used on PMJM before (R. Schorr personal communication). Mice were anesthetized by placing them and a cotton ball with 1 ml ofMetofane (methoxyflurane) into a sealed ziplock bag (to keep Metofane fumes in bag). The bag was then lain aside to minimize stress for the mouse and the time the mouse struggles in the bag. The less agitated the mouse is in the bag the less time required for the metofane to take affect. The mouse was observed at all times to make sure the mouse did not position itself such that the cotton ball was in direct contact with its face, which might cause the mouse to have a severe reaction to the anesthesia. After the animal stopped moving, the handlers waited one minute before removing the mouse from the bag. The animal typically remained anesthetized for 2-3 minutes once outside the bag. Each PMJM was PIT-tagged using a protocol successfully used by C. Meaney (personal communication). Each PMJM had a PIT-tag inserted above the shoulder blades by lifting the skin on its back and inserting the individually sterilized needle with the PIT-tag under their skin and injecting the tag. Verification of the PIT-tag identification number was made before and after insertion into the mouse by running the PIT-tag scanner across it. The skin behind the opening was then pinched to prevent emergence of the tag. PIT-tag identification number was recorded on the field data form. Each radio transmitter was checked to ensure proper functioning before collaring the animal with the transmitter by tuning the receiver to the transmitter frequency to make sure there was a signal. The radio antenna was fed through a small piece of plastic tubing and then back through the radio to make a collar of the plastic coated antenna. The loop made by the antenna was kept large enough to fit over the mouse's head. Once over the neck of the animal, the antenna was pulled to reduce collar size, making sure rubber tubing was on the dorsal side of the neck. The purpose of the rubber tubing was to prevent damage to the collar and prevent the person attaching the collar from cinching the collar too tight. The collar was tested to be sure it could rotate freely around the animals' neck, but was not loose enough to be removed. The metal crimp was flattened to hold the antenna in the desired collar position. Approximately two inches of antenna was left to extend out behind the animal. If, at any time during the handling of the PMJM the animal appeared to be severely stressed (dramatic changes in heartbeat, respiration and responsiveness or gums turning blue) first aid was administered and, once recovered, released without further processing. �IO Movement data Once transmitters were in place, locations of individual mice were made nightly. Because very little is known about the movements of PMJM pilot protocols were established and then modified. Final protocols included tracking up to eight individual mice per person per night. A minimum of six locations per individual mouse per night were made. Each individual mouse was tracked a minimum of three nights per week. The six locations per night per individual were scattered throughout the night to maximize information learned about nightly movements (i.e., eight locations taken within a single hour contains less information than eight locations taken one each hour). Each location was determined by locating the mouse and recording the position as a file in a Trimble Geo-Explorer GPS. Each GPS location (file) was differentially corrected for 2-5 meter accuracy. Daytime locations were taken as time permitted. To describe nightly movements the following parameters were estimated: (I) minimum and maximum distances moved each night animal was followed, (2) mean minimum and maximum distances moved each night for all mice, (3) minimum and maximum distances moved away from the stream center each night by individual mice, and (4) mean minimum and maximum distances moved away from the stream center each night for all mice. To describe 30-day (or life of the radio transmitter) movements the following parameters were estimated:(!) minimum and maximum distances moved each 30-day (or life of the radio transmitter) interval animal was followed, (2) mean minimum and maximum distances moved each 30-day (or life of the radio transmitter) for all mice, (3) minimum and maximum distances moved away from the stream center each 30-day (or life of the radio transmitter) interval by individual mice, (4) mean minimum and maximum distances moved away from the stream center each 30-day (or life of the radio transmitter) interval for all mice. Mortality factors for any mouse found dead was recorded Both site specific and landscape features were recorded at each of the three population study sites to document the extent of spatial variation. These quantitative measures of spatial variation were used in the analyses to determine if they influenced any of the movement parameters estimated in this study. The following habitat characteristics were measured and recorded for each site. ~ Site characteristics Cover was measured at 20 random locations along the 250 meter sampled stream stretch. Mean cover and standard error of the mean was estimated. Cover was estimated using a vegetation profile board (Nudds 1977) that allowed for an assessment of visual obstruction in 0.5 meter vertical intervals above ground. The board was 2.0 meters high and 30.48 cm wide. The board was marked in alternate black and white colors at 0.5 meter intervals. Horizontal cover was assessed in each interval by viewing the board from 15 meters away in a randomly chosen direction. The percentage of each interval concealed by vegetation was recorded as 0-20, 21-40, 41-60, 61-80, and 81-100% estimated concealment. Vegetation species composition and richness was estimated using the Modified-Whittaker nested vegetation sampling method (Stohlgren et al. 1995). A modified Whittaker plot is 20-meters x 50-meters with 10 I m2 and 2 10m2 subplots arranged systematically around the perimeter and 1 100m2 subplot centered in the inside of the 20 meter by 50 meter plot. Species composition and percent cover of each species was recorded for each subplot. Soil samples were taken at each site for a hydrometer textural analysis (percent sand, silt and clay). Samples were collected using a soil probe. Samples were taken from 0-12 inches, and 12+ to 24 inches. The 0-12 inch sample was taken first, removing the probe and soil. Samples were placed in a labeled ziplock bag. The probe was then placed in the same hole for the 12+ - 24 inch probe with that soil sample being placed in a separately labeled ziplock bag. The hydrometer textural analysis was conducted at the Colorado State University Soils Laboratory. �11 Mean stream width was estimated by measuring stream width at 30 locations along the entire site sampled. The 30 locations were stratified equidistant from each other to cover the entire stream stretch in increments of site stream length/30. Each nest site was described including distance from the stream and vegetation. Landscape characteristics The following landscape habitat characteristics were measured using either GIS, topographic maps, or aerial infrared photography. 1. Distance to nearest human habitation and human disturbance. 2. Connectivity of sites to other streams. 3. Total length of stream stretch at each site and total length of stream stretch with suitable habitat at each site. Hibernation site measurements Hibernation sites were identified by following radio-collared mice in late September and early October. Once a radio-signal remained stationary for 2-10 nights we assumed we located a hibernaculum. The following measurements were taken at each hibernation site: 1. 2. 3. 4. Distance ofhibernaculum to stream. Vertical elevation gain from stream to hibernaculum. A soil sample was taken as described above. Vegetation species richness within a 5-m radius. Density of vegetation was measured as described above. Results PIT-tagging and radio-tracking effort A total of 186 individual mice were captured and PIT-tagged at the three study sites (Table 1: 73 mice at Maytag Property, 77 mice at PineCliffRanch, and 36 mice at Woodhouse Ranch). These mice were captured over three different trapping session with an effort of 17,330 trap-nights. A total of 125 radio-collars were put on mice over the three trapping sessions (Table 1: 48 at Maytag property, 4 7 at PineCliff Ranch, and 3 0 at Woodhouse Ranch). A total of 62 females and 63 males were radiocollared over the field season. Initial protocols called for using triangulation methods (simultaneous compass bearing readings from three different locations) to determine mouse locations. Triangulation was used during the month of June. Locations were estimated in late June from these data and found to have large variances associated with most locations. Field protocols were changed for the latter two tracking sessions to walk-up locations. A walk-up location required technicians to use the signal strength indicator on the receiver to determine when they were within 2-7 meters of the mouse. GPS location files were collected each time a mouse was located. File name was recorded as well as the UTM coordinates displayed on the GPS. These files were later differentially corrected to provide a positional accuracy of 2-5 meters. Due to the large variances on the mouse locations collected during June these locations are not reported here. Further analyses will be conducted on these data to see if any information on PMJM movements can be gained. The walk-up method was first evaluated to ensure we were not causing the mice to move in response to us. Given the consistency of individual mouse locations throughout the night and on a day to day basis we felt the method was being employed in such a way that we were not affecting mouse movement patterns. However, it should be noted that T. Ryon (personal communication) observed mice moving in response to him when he tried to conduct similar walk-up locations. �12 Daily movements Percent of PMJM locations, as determined from radio-tracking, at each of three distance categories were calculated for each study site and the latter two radio-tracking sessions (Table 2). The majority of locations at Maytag, PineCliff, and Woodhouse were within 46m of stream center for both tracking periods (July-August and September-October). For all areas and tracking periods except Maytag during the last tracking session, 90% of PMJM movements were within 91m of either side of the center of the capture drainage. Mouse movements at Maytag during September-October resulted in 32.6% of the locations being> 91m from the stream center. Analyses were also conducted on mice captured on PineCliff Ranch separating mice by drainage of initial capture. These analyses were conducted to address questions that might arise when connecting drainages. occur in areas known to have PMJM, but only one drainage has been surveyed. Mice initially captured on Garber Creek showed similar movement patterns as far as distance from center of capture drainage (i.e., Garber Creek) as mice from both Maytag and Woodhouse (Table 2). Mice initially captured on West Plum Creek showed movements more often> 91m from center of the capture drainage (Table 2). Seasonal movement The distribution of mouse locations at Maytag Property for the July-August tracking session is different from the distribution of PMJM locations for the September-October tracking session. The pattern shifts from heavy use along East Plum Creek to the north of the trapline to a more concentrated distribution either side of the trap line. The more concentrated use of the areas east and west of the trap line also resulted in locations being further from the center of the creek. The northern end of the trap line is largely vegetated by willows with the remainder of the trap line more diversely vegetated. Mouse movements were more concentrated along the drainages at PineCliff Ranch during the September-October tracking sessions than during the July-August tracking sessions. Vegetation along both West Plum Creek and Garber Creek along the trapline was primarily willow. At Woodhouse Ranch, the distribution of mouse locations also shifted between tracking sessions. Mouse movements were more concentrated along the southern half of the trap line in September-October as compared to the more even distribution of mouse locations recorded for JulyAugust The northern end of the trap line is dominated by willows, the middle and southern end of the trapline is in more diverse riparian habitat. Eight mice were captured, radio-collared, and tracked for two tracking sessions, one mouse was captured, radio-collared, and tracked for all three tracking sessions (Table 3). Other mice were captured during more than one trapping session but radio collars were not replaced either because all the radio collars had been put on other mice or because the physical condition of the animal was such that we decided not to replace the radio-collar. Such conditions included mice who had significant hair worn off the neck from the previous radio collar. In no incidence did we find open wounds caused by radio collars. Of the nine mice radio-collared for more than one session, four provided information to evaluate seasonal changes in areas and habitats use between the July-August tracking period and the September-October tracking period. One mouse, a male from Maytag was observed only once during the September-October tracking session, providing no information concerning seasonal changes in movement patterns. Movement data from June have not been fully analyzed and are not included in this report. Thus, changes in areas used by individual mice between June and either the July-August or September-October tracking session are not summarized here. A female at Maytag exhibited a seasonal movement shift, small sample size prohibited any evaluation of the movement patterns of the Maytag male (n = l in September-October). There does not appear to be any shift in areas used by the male tracked during both latter sessions at Pine Cliff Ranch, �13 however, sample sizes were small (n = 17, 14). Two females at Woodhouse Ranch exhibited a shift in areas used between July-August and September-October. However, caution should be used in interpreting these results because of low sample sizes in the latter tracking session (n = 14, 6). Nest sites ,. Numerous daytime nest sites were located at all thee study sites. Nest sites were made of tightly woven vegetation, located on the ground. Nest material included leaves, grass, and small sticks. There was only one small entrance hole on each of the nests found. When observing mice in their nests the mice would peer out of the hole and remain motionless as long as we were present. No breeding nests were located, however there were several locations at each of the study sites where adult females returned to repeatedly. Each of these sites were in patches of extremely dense vegetation or underneath a large downed log. We did not disturb these areas because we did not want to cause failure of the nest. Hibemacula Eight potential hibernacula were located, at least one at each study site (Table 4). Mortality factors Mortalities factors of radio-collared mice included predation by rattlesnake, garter snake, fox, and house cat (Table 5). Four probable predations were also noted and identified by finding tightly crimped (i.e., no possibility of the mouse having slipped the collar over its head) radio-collars lying on the ground. Two accidental deaths were documented, a road kill and drowning. Mortality factors also included trapping and/or handling mortalities and unknown causes. Fecal analysis The amount of bait found in each of the fecal samples was quantified as either 100%, abundant (> 70%), trace (< 10%) or 0%. The following summaries are made after eliminating all samples of 100% bait, and then only classifying the fecal sample contents other than bait. Fecal analyses indicate a seasonal shift in diets. The most common item found in the fecal samples during the June trapping session at all three sites were arthropods. This was true for three of the five June samples collected at Maytag (Table 6), eight of ten June samples at PineCliff (Table 7), and four of five June samples collected at Woodhouse (Table 8). Other common items included endogenous fungus (1) and seed (1) at Maytag; endogenous fungus (2) at PineCliff,; and Poa (1) at Woodhouse. During the July 21-August 4 trapping session the most common items in the fecal samples at Maytag were arthropod (2), endogenous fungus (1), pollen (1), and Carex (1). During the same trapping period, the most common items in five of eight samples collected at PineCliff were endogenous fungus, the other three samples having a majority of arthropod (1 ), moss (1 ), and pollen (1 ). The two samples from Woodhouse during this trapping session were composed primarily of either mushroom or seed. On August 13, nine samples were collected during an extra trapping session (on the same trapline as the other trapping sessions occur) with the most common items in the fecal samples being moss (4), endogenous fungus (3) or pollen (2). All three samples collected from PMJM captured at a back drainage on August 23n1 at Woodhouse Ranch were primarily fungus. The September trapping session at Maytag yielded samples with majority fecal contents of arthropod (2), moss (2), pollen (2), endogenous fungus (1 ), and seed (1 ). Ten samples from PineCliff during September had majority fecal contents of arthropod (3), endogenous fungus (3), and seed (3). Eight of nine samples taken from Woodhouse contained primarily arthropods, with one a trace of seed. �14 Discussion Preliminary analysis of the movement data collected on radio-collared Preble's meadow jumping mice (PMJM) indicate (1) maximum movements of> 1 mile, (2) greater use of upland habitats than previously assumed, (3) general site fidelity to both daytime nesting sites and nighttime feeding sites, (4) seasonal shifts in movement patterns, (5) use of both perennial and intermittent tributaries adjacent to the capture drainage, and (6) long distance'movements in September to new locations, presumably in preparation for hibernation. Initial evaluation of PMJM movement data focused on maximum distances mice moved perpendicular to the capture drainage. This focus resulted from criteria used in the USFWS Draft 4-D Ruling (1998) to provide special regulations for the mouse. The 4-D Rule defines a Mouse Protection Area (MPA) as "extending 300 feet on each side of the stream measured from the centerline, or 300 feet from the exterior boundary of any contiguous wetlands, whichever is further." The 4-D Rule also states "the basis for the 300-foot standard is that mice have been documented to regularly move up to 150 feet from streams and wetlands. The remaining 150-foot zone serves as a buffer zone to avoid disturbance of PMJM habitat associated with human activities. We believe that this zone will encompass the normal home range of the Preble's and will provide an adequate buffer from adjoining development." Mouse locations were categorized by the distance criteria used in the 4-D Rule to provide the greatest amount of information to evaluate if the proposed regulations would be sufficient to ensure protection of PMJM. Given the high proportion oflocations within both the buffer zone (150-300 feet) and outside any area of protection(> 300 feet), data from this study do not support the regulations regarding the 300 foot buffer from the center of the capture stream. Analyses were not completed using the criteria of protection up to 300 feet from the edge of contiguous wetlands because a delineation of contiguous wetlands for any of the three study sites is not yet available. Once these contiguous wetlands are mapped, similar analyses will be conducted using edge of the wetland rather than stream center for perpendicular distance measurements. To address the issue of whether or not connected but untrapped tributaries should be included in the designation of MP A's, the more detailed analyses of mouse movements at PineCiiffRanch were conducted. The issue of whether or not Garber Creek, a tributary of West Plum Creek, would be included in that particular MP A is not at issue since both the main drainage, West Plum Creek and the tributary, Garber Creek have been trapped in that area with mice captured on both drainages. Rather, the analysis was conducted to test how well the proposed regulation to protect only 300 foot from the center of the capture stream would have 'encompassed the normal home range of the Preble's and will pro.vide an adequate buffer from adjoining development." It is clear from the results that the regulation would have failed to accomplish its objective, with up to 47% of the mouse locations falling beyond the 300 foot demarcation when only the capture drainage was considered. Use of tributaries was also an issue at the Maytag Property. Two mice moved away from East Plum Creek in September and focused their movements ~300 meters from their previous locations, up a dry drainage dominated by upland grasses and gambel oak. These two mice continued to use this new area and were not observed again near East Plum Creek for at least two weeks. Normal radiofailure (i.e., batteries failed after ~4 weeks) after this time did not allow us to determine if the mice ever returned to East Plum Creek or if they hibernated in their new location. No tributaries were available to mice at Woodhouse Ranch. In summary, movement patterns of mice at the Maytag Property suggest use of tributaries, and at PineCliffRanch extensive use of a tributary. Jumping mice of the genus Zapus are true hibernators, spending much of their lives in hibernation. Meadow jumping mice spend approximately 7 months (~210 days) per year in hibernation (Quimby 1951) whereas estimates for Z. princeps indicate that some populations (e.g., in the western mountains of Utah) spend up to 300 days per year in hibernation (Cranford 1983). �15 Jumping mice hibernate in underground burrows (Quimby 1951, Whitaker 1963). They are excellent burrowers and create their own hibernacula Meadow jumping mice are generally solitary hibernators, however, there have been occurrences of more than one mouse found in a single hibernaculum. Eight possible hibernacula were located during this study. The greatest perpendicular distance from the center of the main drainage at the site (East Plum Creek for Maytag Property, West Plum Creek for PineCliffRanch, and Indian Creek for Woodhouse Rari'ch) was 341 meters. However, if tributaries were considered, greatest distance from center of the nearest drainage to any of the eight sites. was 78 meters. Five of the eight mice using these possible hibernacula traveled ~ 90 meters from the center of their typical September night time locations. One mouse, a female at Maytag moved 750 meters to a possible hibernacula Vegetation characteristics of the eight sites located during this study (Table 4) are similar to other hibernacula described for PMJM. One confirmed hibernaculum, located on Rocky Flats Environmental Technology Site, used by Z. h. preblei has been located {Armstrong et al. 1997). This site was 9m above a creek bed (Walnut Creek); it had a thick cover of chokecherry (Prunus virginiana) and snowberry (Symphoricarpos spp.), the mouse was found in a leaf litter nest 30cm beneath the ground in coarse textured soil {Armstrong et al. 1997). Four possible hibernacula were located by tracking radio-telemetered mice at the U. S. Air Force Academy in fall 1997. These sites are located 7, 12, 29, and 3 lm from a creek bed (R Schorr, unpublished data). There was no consistency among sites in aspect. Three sites were in vegetation dominated by coyote willow (Salix exigua), one site was in vegetation dominated by snowberry and mullein (Verbascum thapsus). However, all four hibernacula appeared to be below coyote willows. The eight sites located during this study and the four U. S. Air Force Academy sites were not disturbed to protect any hibernating mice and therefore are only possible hibernacula because there is no confirmation a mouse actually hibernated there. Confirmation of a true hibernaculum cannot be made until a chamber, or nest is located. The other explanation for these collar locations might be either locations of radios discarded by the mice or dead mice carried underground by a predator. Location or more hibernation sites was limited primarily by normal battery failure of the radio transmitters before mice went into hibernation. Prior to the 1998 field season, natural mortality factors reported for Z. hudsonius included only insufficient fat storage prior to hibernation (Whitaker 1963 ), predation (Whitaker 1963, Poly and Boucher 1997, R. Schorr unpublished data) and cannibalism (Sheldon 1934). Other assumed natural mortality factors for Z. h. preblei included starvation, exposure, and disease. This study further reports confirmation of predation by house cats, garter snakes, rattlesnakes, and fox. Other documented natural mortality factors now include accidents by drowning and road kill. The high percentage of arthropods and endogenous fungus found in the fecal samples provides a new aspect to evaluating PMJM habitat requirements. When considering habitats used by PMJM, or in trying to predict habitats that might be suitable for the subspecies, consideration should be given as to whether those habitats could support the arthropods and fungus apparently being selected for by the mouse. Arthropods are a food source high in protein and fat which would benefit mice emerging from hibernation and mice preparing for hibernation. Whitaker (1963) reported a 67% loss of individuals over hibernation and that average body mass of individuals emerging from hibernation was greater than the average for mice entering hibernation. Because no mice are known to store food in their hibernacula, this indicates that the lighter individuals died during hibernation and only those entering with higher masses survived. All the energy they use during hibernation and the periodic arousals (the energetically most expensive part of hibernation) must be the fat they carry into hibernation (B. Wunder, personal communication). The ability to put on sufficient fat for overwinter survival during hibernation is a critical factor in the life history of these mice. Thus, appropriate and sufficient food sources must be available to the mouse to meet these nutritional requirements. �16 The apparent seasonal shift in mouse movements between the July-August and September tracking sessions may be a result of diet switching. The broader diets suggested by the fecal analyses from samples collected during July and August possibly represent both a wider availability of suitable foods and the ability of PMJM to exploit these resources. It might also suggest a need to exploit these other resources to provide the mouse with necessary food requirements for breeding. Because mice tracked during each session were not generally the same mice there is a possibility these apparent movement shifts might only be different areas used by different mice. The probability of this being the case is small for two reasons. The first is the low density of mice in the stream (Shenk and Sivert 1999). Given that, the proportion of mice followed during each session is a high proportion of the mice in the population. Thus, each subset of mice should be representative of the population. Secondly, evidence from the four mice followed during both the latter tracking sessions also exhibited movement shifts between sessions. The combination of shifts in both general mouse movements, individual mouse movements, and diet provide strong circumstantial evidence that PMJM may be selecting for or require specific seasonal diets. If this is the case, all these requirements must be considered and provided for to ensure conservation of the subspecies. A detailed literature search and further studies need to be conducted to investigate the possible implications of these dietary patterns. These data are limited to the first year of a multi-year study and thus annual variation in mouse movement patterns cannot yet be addressed. Continuation of this study, at least through the 1999 field season will provide information on annual variation in PMJM movement patterns. This study looked at PMJM movements at only three sites. These sites were selected based on known presence of PMJM. Other sites, perhaps because of different habitat configurations or sites of poorer quality may require mice to move further from the creek or may allow mice to remain closer to the creek in order to obtain all life requirements. However, these study sites were specifically selected to address spatial variation in movement patterns of PMJM due to different spatial configuration and juxtaposition of habitats. And although all study sites were different they could all be considered within the general description of what is consider typical habitat for PMJM. It should also be noted that we generally trapped along the creek. Thus, mice captured and subsequently radio-collared and followed were those mice that use the area near the most prominent drainage. If there are mice that do not regularly use the main channel and thus were not available for capture there would be a bias in the data towards fewer observations 300 feet away from the creek. To test for such a bias, further research needs to be conducted trying to capture mice further from the creek and compare their movements and locations of those movements in relation to distance from the creek. We plan to test for this bias during the 1999 field season at Maytag Property and Woodhouse Ranch. This is an interim progress report of a multi-year study. Further analyses will be conducted on these data and data collected during the 1999 field season. Literature Cited Armstrong, D. M., M. E. Bakeman, A. Deans, C. A. Meaney, and T. R. Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Bailey, B. 1929. Mammals of Sherburne County, Minnesota Journal ofMammalogy 10:153-164. Bailey, V. 1923. Mammals of the District of Columbia Proceedings of the Biological Society. Washington 36:103-138. Cook, T. D. and D. C. Campbell. 1979. Quasi-experimentation: design and analysis issues for field settings. Houghton-Miffiin, Boston. �17 Cormack, R. M. 1964. Estimates of survival from the sightings of marked animals. Biometrika 51:429-438. ERO Resources. 1995. Environmental review of South Boulder Creek Management Area Prepared for City of Boulder Real Estate/Open Space Department. Prepared by ERO Resources Crp., Denver, Colorado in association with Stoecker Ecological Consultants, Boulder, Colorado. Fitzgerald, J.P., C. A. Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. Hafner, D. J., K. E. Petersen, and T. L. Yates. 1981. Evolutionary relationships of jumping mice (genus Zapus) of the southwestern United States. Journal ofMammalogy 62:501-512. Hall, E. R. 1981. The mammals of North America. John Wiley and Sons, Inc., New York, New York, 2 volumes. Hamilton, W. J., Jr. 1935. Habits of jumping mice. American Midland Naturalist 16:187-200. Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration stochastic model. Biometrika 52:225-247. Jones, C. A. 1996. Mammals of the James John and Lake Dorothey State Wildlife Areas. Final Report, submitted to the Colorado Division of Wildlife and Colorado Natural Areas Program. Kendall, W. L., and J. D. Nichols. 1995. On the use of secondary capture-recapture samples to estimate temporary emigration and breeding proportions. Journal of Applied Statistics.22:751762. Kendall, W. L., K. H. Pollock, and C. Brownie. 1995. A likelihood-based approach to capturerecapture estimation of demographic parameters under the robust design. Biometrics 51 :293308. Kendall, W. L., J. D. Nichols, and J.E. Hines. 1997. Estimating temporary emigration using capturerecapture data with Pollock's robust design. Ecology 78:563-578. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. Meaney, C. A., N. W. Clippinger, A. Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 5:113-117. Poly, W. J., and C. E. Boucher. 1997. Record of a creek chub preying on a jumping mouse in Bruffey Creek, West Vjrginia Brimleyana 24: 29-32. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. PTI Environmental Services. 1996b. Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Spring 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, Zapus hudsonius. Ecological Monographs 21:61-95. Riggs, L. A., J. M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation. Final Report for the Colorado Division of Wildlife. Denver, Colorado. �18 Seber, G. A. F. I 965. A note on the multiple recapture census. Biometrika 52:249-259. Sheldo~ C. 1934. Studies on the life histories of Zapus and Napaeozapus in Nova Scotia Journal of Mammalogy 15:290-300. Shenk, T. M. 1998. Conservation assessment and preliminary conservation strategy for Preble's meadow jumping mouse (Zapus hudsonius preblei). Colqrado Division of Wildlife FY 199798 Annual Report. ... • Shenk, T. M. and M. M. Sivert. 1999. Temporal and spatial variation in the demography of Preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife JanuaryMarch 1999 Quarterly Report. Stohlgren,T. J., M. B. Falkner, and L. D. Schell. 1995. A Modified-Whittaker nested vegetation sampling method. Vegetatio 117: 113-121. USFWS. 1997. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33 :3. Table 1. Number of Preble's meadow jumping mice captured and radio-collared at each study site durin~ each traeein~ session. # CaQturedt Site Trapping session Trap nights Maytag June Maytag # Radio-collared female (%) male(%) total female male total 1949 9(64) 5 (36) 14 9 5 14 July 2370 15 (54) 13 (46) 28 ll 5 16 Maytag September 3256 18 (43) 24 (57) 42 IO 8 18 PineCliff June 1095 6 (32) 13 (68) 19 5 13 18 PineCliff July 1603 8(50) 8(50) 16 6 7 13 PineCliff September 1544 13 (28) 33(72) 46 4 12 16 Woodhouse June 1525 4 (57) 3 (43) 7 2 3 5 Woodhouse July 2420 9 (64) 5(36) 14 8 4 12 Woodhouse September 1568 8 (44) IO (56) 18 7 6 13 17330 90 114 204 62 63 125 TOTAlS t Some captured animals were PIT-tagged during previous trapping sessions �19 Table 2. Percent locations of Preble's meadow jumping mice at each of three distance categories for each study site and radio-tracking session. PineCliffRanch locations are also divided into percent locations for each distance category from center of the stream of initial capture for mice captured on either West Plum Creek or Garber Creek. % locations at each distance from center of main Site Tracking period N Maytag Jul-Aug 1998 Maytag <46m (150 feet) 46 - 91 m 150-300 feet >91 m (300 feet) 901 75.6 21.0 3.4 Sep-Oct 1998 900 47.8 19.6 32.6 PineCliff Ranch Jul-Aug 1998 302 86.1 11.9 2.0 PineCliff Ranch Sep-Oct 1998 520 81.2 9.2 9.6 Woodhouse Ranch Jul-Aug 1998 377 91.S 8.5 0.0 Woodhouse Ranch Sep-Oct 1998 533 67.6 32.1 0.4 Pine Cliff Ranch Garber Creek Jul-Aug 1998 210 68.1 10.S 21.4 Pine Cliff Ranch Garber Creek Sep-Oct 1998 499 75.6 9.8 14.6 Pine Cliff Ranch West Plum Creek Jul-Aug 1998 92 32.6 20.7 46.7 Pine Cliff Ranch West Plum Creek Sep-Oct 1998 21 52.4 0.0 47.6 Table 3. Preble's meadow jumping mice radio-collared and tracked (X) for more than one tracking session. Location of capture, sex, identification, and number of locations (n) for each mouse during each tracking session is noted. Tracking Session Site Sex PIT-tag# Maytag F Maytag Junei July-Aug n Sep-Oct 4140371625 X X 25 * F 4141435234 X Maytag F 4140753620 X Maytag F 41412B4A2D X Maytag M 4141241836 Woodhouse F 41413£610B Woodhouse F 41413E7B07 PineCliff F 4141125D66 PineCliff M 41413D4C04 1 Locational data from June is not included in this report. * Mouse captured but radio-collar not replaced. X X n X 52 X 82 103 X 105 X 93 X X 78 X 14 X 66 X s X 13 X 18 X IS * �20 Table 4. Possible hibemacula for Preble's meadow jumping mouse at three study areas in Douglas County, Colorado. Sex, beginning date of stationary signal, duration of stationary signal, distances from the main drainage (East Plum Creek at Maytag Property, West Plum Creek at PineCliffRanch, or Indian Creek at Woodhouse), nearest tributary, and center of night time locations are presented. Primary vegetation at the site is also noted. Distance (m) from: Site Sex Date Days Main Drainage Tributary Center Night Location Vegetation Woodhouse M 9/22 12 40 NIA 91 skunkbush, sumac, hawthome,chokecherry Woodhouse M 9/27 9 33 NIA 67 clematis vine, snowberry Woodhouse M 9129 5 23 NIA 116 narrowleaf cottonwood, Bromus spp., chokecherry PineCliff M 9117 5 210 JO 29 Salix spp. PineCliff M 9/23 11 35 40 90 Salix spp., alysium PineCliff M 9/23 11 120 35 70 Salix spp., grass PineCliff M 9/25 9 100 78 72 snowberry, Salix spp., alysium, thistle PineCliff F 9/25 9 70 l05 l05 snowberry, Salix spp. PineCliff M 9125 9 341 0 Salix spp., cottonwood, snowberry Maytag F 9/23 14 120 750 gambel oak, chokecherry, alysium NIA �Table 5. Known and probable mortalities of Preble's meadow jumping mice from Maytag Property, PineCliffRanch, and Woodhouse Ranch collected during the 1998 field season (June I-October 31 ). Probable cause of death, date radio-collars located, description of how what was found, sex of the animal 2 and dis12osition of s12ecimen noted. Site where found Mortality factor Date How obtained Sex Current location of specimen Maytag handling stress June 8 died during processing of the mouse, never came out of anesthesia female DMNH Maytag handling stress July 27 died from anesthesia shock female DMNH Maytag trap mortality June 10 trap mortality male Maytag trap mortality: heat stress Sept. 10 trap mortality, probably over-heated female DMNH DMNH Maytag predation July 2 tracked radio-collar, found collar in fox scat female no body, scat at CDOW Maytag predation Sept. 21 radio-collar tracked to a rattlesnake, waited and picked up snake scat with the radiocollar in it female no body, scat at CDOW Maytag road kill Sept. 15 tracked radio-collar; found highly decomposed, unsalvageable body covered with ants, side of road-probably road kill male no body Maytag unknown Aug. 1 tracked radio-collar; found highly decomposed, unsalvageable body male no body PineCliff possible predation Aug. 6 possible predation; crimp still tightly on collar when retrieved female no body PineCliff possible predation Aug. 12 tightly crimped collar found on ground, no part of mouse detected; suspect predation since movement detected earlier female no body PincCliff possible predation Sept. 13 possible predation; crimp still tightly on collar when retrieved male no body PineCliff drowning Aug. 6 radio-tracked collar; found mouse in water female rnv:IN-:::I Woodhouse handling stress June 5 died during handling while trying to readjust radio-collar male Woodhouse radio-collar: suffocation/starvation Aug. 6 radio-tracked collar, found dead mouse; collar may have been too tight female DMNH DMNH Woodhouse predation Aug. 11 radio-collar found in snake scat female no body, scat at CDOW Woodhouse predation Sept. 23 radio-collar tracked to a garter snake, waited and found collar in snake scat female no body, scat at CDOW Woodhouse predation Sept. 29 radio-collar tracked to a house cat, waited and found collar in house cat scat female no body, scat at CDOW Woodhouse possible predation Aug. I tightly crimped radio-collar found in exposed area female no body Woodhouse unknown Aug. 7 radio-tracked collar, found dead mouse (skeleton) on shrub female DMNH Woodhouse unknown Sept. 15 radio-tracked collar and found dead mouse male DMNH ts) �N Table 6. Percent contents of fecal samples collected from traps where Preble's meadow jumping mice were captured. All samples were collected N from Maytag Property during the 1998 field season. Several samples are from the same animal captured on different dates. Amount of bait in each samp 1e was quant1"fid o o t e samp l:),'T'fi e e as l00¾'A'f. 0 or ab un dant (703/cfh > or trace amount (103/cfth < e samp1:), e or Oo/cfh oO o o t e samp1e was b. rut. endogenous VerAgro- EquiLesunknown mushID Date Bait arthropod fungus seed moss IPOilen Poa Helianthus Salix 'querella bascum Carex ovron setum flower forb room 4l405E402 Jun 3 A 76 414l25476E 4141382614 Jun 3 T Jun4 T 64 7 ·4140271625 Jun 8 T 4 .4l4119674D Jun 11 A 91 4l407E5E35 4141106852 4141287948 Jul 21 Jul 21 0 100 16 Jul 28 100 41417Al807 • 4141297F0F Jul 28 Jul 28 100 A 4141407328 Jul 28 T 4141360708 41411E6879 4141283D24 4l4l3A026A Jul 29 Aug 3 Aug 13 A T UNKNOWN 4140371625 4140205478 4141187C76 4141284A2D . 4141241836 4140173A6D 414125476 • 4140753620 Aug 13 Aug 13 Aug 13 Aug 13 Aug 13 Aug 13 Aug 13 Aug 13 Seo 7 Seo 9 Sep 9 0 A A A T T T T T A A 92 23 13 16 4 l 96 9 4 82 18 2 47 30 4 3 17 96 16 25 7 46 11 29 67 59 12 60 2 46 3 25 20 6 98 4 41412CC443 41417CIE42 41411E6879 4141284A2D Sep IO Sep IO T Seo 11 Seo 12 A A 73 20 4140754707 Sen 12 T 24 21 12 3 16 5 ·" 2 5 2 43 16 14 90 11 6 100 100 100 T A 414164363C 24 89 78 11 5 84 30 19 84 4 65 5 5 27 80 7 35 34 �Table 7. Percent contents of fecal samples collected from traps where Preble's meadow jumping mice were captured. All samples were collected from PineCliffRan~h during the 1998 field season. Several samples are from the same animal captured on different dates. Amount of bait in each sample was quantified as 100%, 'A' for abundant (> 70% of the sample 'T' for trace amount(< 10% of the sample), or 0% of the sample was bait. ID UNKNOWN 4140761237 4141 IA3D4B 4140755157 UNKNOWN UNKNOWN 4140755157 UNKNOWN UNKNOWN 41411Alll4 4141714141 41413D4C04 4141505F54 ·.414125D66 413F6F7EOA 4140784Bl4 41411AEC12 41412F2433 41412F5E45 41413C604F .414176064A 4141656001 ;414138666D 41415B4748 41412F2F62 4141370528 4141350155 41415E434A 4141491F02 4140502204 Date Bait arthropod seed 100 Jun3 A Jun4 0 96 4 Jun4 A ,, 97 Jun4 A T Jun4 A Jun4 A 88 Jun4 8 T Jun 7 T T T Jun 8 A Jun 8 T 88 6 Jul 11 A 4 Jul 21 0 13 2 Jul 21 0 37 Jul 21 100 Jul 21 T 8 Jul 21 T 8 Jul 22 100 Jul 22 A Jul 24 A 41 Jul 24 A T 3 7 Seo9 T 3 8 Seo9 Seo 11 A 100 14 Seo 11 T 6 Sep 14 A 96 4 75 Seo 14 T 22 Sep 15 A 83 Sep 15 A T Sep 16 A Sep 16 T 17 endogenous Chenopodium grass Eleagnus Helianthus lilv oollen Salsola seed comoosite Festuca funl!US moss Bromus Poa seed 4 96 3 T 6 6 4 88 T 0 6 96 85 63 84 92 8 100 100 18 90 86 74 41 3 6 3 5 12 83 �· Ta,ble 8. Percent contents of fecal samples collected from traps where Preble's meadow jumping mice were captured. All samples were collected from Woodhouse Ranch during the 1998 field season. Several samples are from the same animal captured on different dates. Amount of bait in • each sample was quantified as 100%, 'A' for abundant(> 70% of the sample), 'T' for trace amount(< 10% of the sample), or 0% of the sample . was bait PIT-tag# Date Bait arthropod 41407B2575 Jun 3 A 100 414l3E610B Jun 3 A 100 41413E610B Jun4 A 100 41407B2575 Jun4 T 100 414147354F Jun4 T 24 UNKNOWN Jul 27 T 41413E610B Aug4 T 4141076B41 Aug4 100 4141250646 Aug23 0 12 41404A7D58 Aug23 T 4 '414128F2607 Aug23 0 41415D402E Aug23 100 41406A1049 Sep 9 A 100 4141313E6F Sep 9 A 74 4141350C2A Sep 10 JOO endogenous fungus mushroom Poa seed Agropyron Sporobolus seed Chenopodium composite Equisetum flower 76 50 50 23 77 88 96 89 11 26 T 414133085 Sep 10 A UNKNOWN Sep 11 0 100 414173462B Sep 11 T 70 4143P5772B Sep 11 0 45 4141611413 Sep 12 0 98 41414A6B6F Sep 12 0 88 4140241303 Sep 12 0 88 30 33 7 15 2 12 2 10 �25 APPENDIXB HABITAT USE AND DISTRIBUTION OF PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) IN LARIMER AND WELD COUNTIES, COLORADO Tanya M. Shenk and James T. Eussen Abstract A total of39 sites were surveyed for Preble's meadow jumping mouse in Larimer and Weld Counties, Colorado with a total of 16,671 trap-nights completed. Of the 39 sites survey, Zapus spp. were captured at 21 locations. A total of 71 unique individuals were captured in the 21 locations, with recaptures of 14 of those individuals. All sites where Zapus spp. were captured were located in Larimer County. Three soil samples from 0-12 inches and 12-24 inches were collected at all sites where possible. Soils at some sites were too rocky to collect the 12-24 inch soil samples. Nine fecal samples were collected from traps where Zapus spp. were captured. Initial result indicate that arthropods, fungus, and willows are important dietary components of the Zapus diet. Two trap mortalities of Zapus spp. occurred. Both specimens were saved and delivered to Cheri Jones of the Denver Museum of Natural History on October 26, 1998. Measurements of habitat characteristics at both the site and landscape levels were completed. Genetic tissue samples were collected from 68 of the 71 jumping mice captured. Analyses of these tissue samples is pending. Introduction The meadow jumping mouse (Z. hudsonius) is broadly distributed across North America from the Atlantic to Pacific coasts, extending south into the United States to Alabama and Georgia and west across the Great Plains to the base of the Rocky Mountains. In general, it is a common inhabitant of moist, grassy and herbaceous fields. Eleven living subspecies have been described (Whitaker 1972). Hafner et al. (1981) describe a twelfth subspecies, Z. h. luteus. Z. h. preblei occurs only in eastern Colorado and southeastern Wyoming (Krutzsch 1954, Long 1965, Armstrong 1972). From its limited ecological and geographic distribution, Fitzgerald et al. (1994) suggest it is an Ice Age relict, once widespread in tallgrass prairie across the eastern plains of Colorado but now restricted to scattered localities on the Colorado Piedmont. Similar relict populations of meadow jumping mice in the White Mountains of Arizona and the Sacramento Mountains and Rio Grande Valley of New Mexico are described as the subspecies Z. h. luteus (Hafner et al. 1981 ). On May 12, 1998 the U. S. Fish and Wildlife Service (USFWS) published a final rule in the Federal Register (63 FR 26517) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) as 'threatened' under the Federal Endangered Species Act (ESA) of 1973, as amended. Scarcity of suitable habitat presumably limits current distribution of Preble's meadow jumping mouse (PMJM) and thus, maintenance of quality habitat has been identified by the USFWS (63 FR 26517) as the principal conservation goal. Although Meaney et al. ( 1997) reported an improved ability to recognize suitable habitat for PMJM, a more refined and complete definition of potentially suitable habitat for the mouse does not exist. Because the protection of potentially suitable habitat for PMJM may occur under the ESA, as well as protection of known locations where the subspecies occurs, the definition of potentially suitable habitat, as determined by the USFWS, will directly influence site specific regulatory procedures. Ideally, a definition of potentially suitable habitat for the subspecies would identify areas where the PMJM could survive and reproduce in sufficient numbers to sustain populations throughout its range of natural variability over an extended length of time. During the active period of the life cycle of the mouse, suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting,. and rearing of young to independence), and dispersal. The hibernation period . .. . . ~ • . • �26 requires habitat with sufficient food supplies to assure fat storage prior to hibernation and hibernacula sites. Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. Because very little is known about the ecological requirements of the subspecies, potentially suitable habitat is currently defined only as areas of well-developed, dense herbaceous vegetation consisting of a variety of grasses, forbs and thick shrubs in close proximity to open water. This definition is vague and possibly incomplete. Numerous surveys have been conducted since 1990 to establish the current distribution of PMJM. However, very few surveys for determining the presence or absence of PMJM have been conducted in Larimer or Weld Counties, Colorado. Of the surveys conducted up to 1997, only three sites yielded captures of PMJM in either Larimer or Weld Counties. In Larimer County, two sites (Lone Pine and Rabbit Creeks) yielded captures of PMJM, based on field identification and supported by genetic analyses conducted to date (Riggs 1998). One mouse was captured on Lone Tree Creek in Weld County that was identified as Z. h. preblei in the field but was genetically found to be more . closely allied with the western jumping mouse, Z. princeps (Riggs 1998). Therefore, very little information is known about habitat use or current distribution of the subspecies in these two counties. Both Larimer and Weld Counties include habitat that is currently perceived to be outside the ecological limits of PMJM. Larimer County provides the opportunity to explore elevational limitations, currently thought to be 7400 feet (2260m) (USFWS 1997); Weld County extends beyond the currently believed eastern boundary of the subspecies. Both of these boundaries will be challenged by selecting survey sites within the two counties beyond the perceived ecological limits of the subspecies. Genetic tissue samples will be collected on all PMJM captured to assist identification through DNA analysis, particularly for those animals captured outside the currently perceived ecological limits, and to provide information for future studies to better define the relationships among different populations of Z. h. preblei, other subspecies of Z. hudsonius and other species of Zapus. Quantifying and comparing both landscape and site specific characteristics of habitats where PMJM are found and not found in these two counties would further our understanding of habitat use by the subspecies, particularly in the northern half of its probable range. Any new locations where PMJM are found during this study would contribute to the range-wide distribution map currently available for the subspecies. Repeated annual visits to these same randomly selected sites would also provide information on population persistence at a given site. Such a monitoring scheme would be necessary for evaluating the continued status of the mouse at each site, providing further information as to the suitability of the habitat for long-term persistence of the population. Thus, the primary objective of this study is to quantify and define habitats used and identify ecological limits of the subspecies in Larimer and Weld Counties, Colorado. Such information could be used by the USFWS to further refine the current definition of potentially suitable habitat for PMJM. Objectives Conservation of Z. h. preblei should require maintaining populations of the subspecies throughout the range of its natural variation and to try to identify ecological limits for the subspecies. Specific objectives for the distributional component of this study are to (1) clarify the distribution of the subspecies in Larimer and Weld Counties, Colorado, and (2) define and quantify the amount of suitable habitat within Larimer and Weld Counties. The objective of the habitat study is to identify and refine ecological requirements of Z. h. preblei in Larimer and Weld Counties, Colorado. Because of the uncertainty of the identification of the mouse captured in Weld County, Colorado, and because currently perceived ecological boundaries of PMJM will be challenged in the survey effort, the objective of the genetic component of this study is to genetically identify all Zapus spp captured during this study. Therefore, genetic tissue samples will be . collected from each jumping mouse captured to confirm identification of the animal. These genetic �27 tissue samples could also provide further data to better define the relationships of different populations of Z. h. preblei as well as to other subspecies of Z. hudsonius and other species of 7.apus through molecular systematic relationships and to link these genetic relationships to systematic studies of Z. hudsonius. Specific objectives for this study on PMJM include: . 1. Define and quantify habitat characteristics at sites wllere PMJM was found and sites where PMJM was not found. 2. Identify elevational and eastern boundary limitations for PMJM in Larimer and Weld Counties, Colorado. 3. Describe the distribution of PMJM in Larimer and Weld Counties, Colorado. 4. Select sites and establish monitoring protocols for determining long-term trends in populations of PMJM. 5. Collect genetic tissue samples to assure identification of jumping mice captured during this study and for future genetic analyses to better define the. relationship of populations of Z. h. preblei to each other, other subspecies of Z. hudsonius and other species of 7.apus. Study sites Trapping surveys will be conducted at a minimum of30 sites selected at random from the sampling frame developed for Larimer and Weld Counties, Colorado. No survey site will occur at elevations greater than 7600 feet and not east of the UTM Easting Coordinate of 602000. The molecular systematic studies will be conducted in genetic laboratories using the genetic tissue samples collected in the field (ear punches). Methods For simplicity, the methods described below assume all jumping mice captured are PMJM. To meet these objectives, this study included (1) constructing a sampling frame of potentially suitable habitat within the area of interest (Larimer and Weld Counties, Colorado) and (2) conducting trapping surveys to determine presence or absence at a minimum of 30 sites randomly selected from the sampling frame. Specific approaches to each of these tasks follow. Sampling frame A sampling frame was developed to delineate potentially suitable habitat for PMJM from unsuitable habitat. To produce a preliminary map displaying existing potential habitat for PMJM would require at least three primary layers of ecological information. Two initial layers, hydrology and vegetative cover would provide a map displaying all areas where these two ecological requirements of PMJM co-occur. The hydrology layer must be in enough detail to provide locations of intermittent and small order streams as well as identify water source (e.g., irrigation ditches, stream, seep). Degree of density of vegetative cover is sufficient for initial mapping efforts. Demarcation of shrub, trees and grasses will suffice in these initial efforts rather than species identification. However, not all combinations of vegetative cover and water provide sufficient habitat to support PMJM. Thus, mapping potential habitat as described above would produce a map displaying far more potential habitat than exists. For example, an extremely critical ecological requirement for the survival of the mouse, that to date we have very little information for, is potential hibernacula sites. As a possible index to hibernacula habitat, a third GIS layer, indicating the presence of alluvial deposits may provide some insight in to hibernation requirements. Areas where alluvial deposits co-occur with the presence of water and vegetative cover may provide a more realistic map of potentially suitable habitat for the mouse. Our ability to survey a site selected at random would be restricted to those areas where we are _able to bbtain permission to access th_e land. We shou_ld_be able_to survey any randomly se_lected site �28 on public lands and thus our inference should be unrestricted. Such readily available access would probably not occur on privately owned or leased lands, thus, restricting inferences made on private lands. By stratifying the sampling frame, this lack of access on private lands would not restrict inferences that can be made on public lands. Inference on private lands will depend on the percent of access we get from private landowners. The sampling frame was developed from the 1:24,000 sc'ale Hydrographic GIS layer developed by the CDOW (Reese Tietje, unpublished data). From this sampling frame a three-stage sampling design was used to select 40 random sites (to ensure meeting our objective of a minimum of 30) for conducting PMJM surveys. Primary sampling units were 3rd order streams. Of the 150 3rd order streams that exist within the sampling frame, 40 were selected on public lands, 40 on private lands. The secondary sampling unit was the stream stretch selected within the primary (3rd order stream) unit. The tertiary sampling unit was the actual sites along the stream stretch selected at the secondary sampling stage that were sampled. Each of the primary, secondary, and tertiary sampling units were selected using simple random sampling. If the secondary sampling unit did not yield potentially suitable habitat (i.e., no dense vegetation) secondary sampling units continued to be selected at random until one yielded potentially suitable habitat. Determination of suitable habitat was made by field site visits. Total stream length of all the secondary sampling units were recorded as well as total stream length containing potentially suitable habitat. From these measurements an estimate of the probability of potentially suitable habitat occurring within the primary sampling unit can be made for each area surveyed. A mean estimate, over all sites surveyed, of the probability of a primary sampling unit having potentially suitable habitat was made. Because of the random selection of primary sampling units, inference can be made as to the probability of potentially suitable habitat existing on all 3rd order streams within the sampling frame. By recording presence or absence of PMJM within the tertiary sampling units we can estimate the probability of PMJM occurring within potentially suitable habitat. Because of the random selection of sampling units in each of the two strata (public and private lands) we can then estimate the probability of PMJM occurring in potentially suitable habitat within both public and private lands. Trapping surveys Trapping surveys to determine presence/absence of PMJM were primarily conducted following protocols defined by the USFWS (1997). Additional guidelines have also been developed to accommodate the needs of this project. Trapping surveys were conducted within the period from June I to September 15, 1998. These dates correspond to dates when PMJM is known to be out of hibernation. Trappers were_advised to follow the Center for Disease Control's Hantavirus instructions and recommendations when dealing with rodents. Due to the nocturnal nature of PMJM, traps were set between 19:00hrs and 21 :00hrs and checked as early as possible in the morning beginning at 5:00hrs to reduce stress and the potential for predation on trapped animals. Time required to complete the traplines varied depending on how many animals were caught. Small mammal Sherman live traps (folding and non-folding) were used to conduct the trapping sessions. Traps were set in two parallel lines of trap stations (I trap per station) on either side of the drainage. Trap stations were 5 meters apart for a total of 250 meters; the parallel transects were 10 meters apart unless extent of habitat, terrain topography, or stream hydrology did not allow. Location of transects were recorded on field data sheets and 7.5° topographic maps. A small (~l inch) ball of polyester quilt was placed in each trap as nesting/bedding material. Baiting material was Manna Pro Sweet 3-way Livestock feed which contains no animal matter; ingredients include flaked barley, flaked corn, flaked oats, and cane molasses. Peanut butter was used to stick the bait to the trap. �29 Traps were checked by two surveyors. All animal captures were recorded. If an animal had been captured in a trap, a ziplock plastic bag was placed over the end of the trap. The trap was opened allowing the animal to fall into the plastic bag. The animal was identified to species while in the plastic bag. If the animal was not a PMJM, identification of the animal was recorded and the animal set free without further handling. Each captured PMJM was checked to detect the presence/absence of a PITtag (See below). If a PIT-tag was detected and the mouse had been captured at that same site within the same trapping session, identification of the mouse was recorded and the mouse was released. If the animal was a PMJM and no PIT-tag was detected the PMJM was anesthetized for further processing, as follows. All PMJM were PIT-tagged. Each PMJM was weighed while in the bag, recording the weight in grams using a Pesola spring balance. Sex, age (juvenile, adult), and reproductive condition (pregnant, lactating or nonbreeding if it was female; for males the position of the testes indicated if in breeding status or nonbreeding status) was noted. Each PMJM was measured (total length, length of body, length of hind foot - heel to distal end of claws) in millimeters. Capture of every PMJM was documented by taking a photograph of the mouse on first capture. Mice were placed in a plexiglass photobox to reduce handling stress while taking the photograph. If the mouse had been captured previously as noted by the detection of a PIT-tag, no photograph was taken. If there were feces in the trap where a PMJM was captured, the fecal material was collected in a plastic bag labeled with date, location of the site, and animal PIT-tag number. Fecal samples were kept cool until returned to the CDOW office where they were frozen. Salt was added to each specimen bag for preservation. Once the field season was over all fecal samples were analyzed by the Composition Analysis Laboratory, Inc, 622 ½ Whedbee, Fort Collins, CO for content. All trap mortalities were recorded on a 'Trap Mortality' data form which included information on species, potential duration of time spent in the trap, and any information available to help determine cause of death. All animals found dead were double-bagged in a plastic bag and placed in a cooler with ice. Specimens were frozen as soon as possible and deposited in the CDOW freezer at the office in Fort Collins. A museum card was completed and attached to each PMJM specimen and the specimen and card were given to Cheri Jones, Curator of Mammalogy at the Denver Museum of Natural History, for study skins and tissue storage. If an animal was severely injured (e.g., severed limb, large lacerations) it was euthanized by soaking a cotton ball in Metofane (methoxyflurane) and placing the cotton ball and the mouse in a ziplock bag until the animal stopped breathing. If an animal appeared to be only slightly injured (e.g., broken tail, small laceration) the animal was released to the wild. If an animal appeared to be coldstressed attempts were made to warm it by holding it in the surveyors hands and/or against their body. If the animal appeared to be heat stressed, isopropyl alcohol was applied with a cotton swab to the ears, arm pits, and feet to cool it down. PIT-tagging Each PMJM was individually marked with a Passive Integrated Transponder (PIT-tag). PITtags are electromagnetic, glass-encased tags that emit a passive signal (125 kHz) that can be decoded by a portable reader. Destron-Fearing PIT-tags were used on all mice. We used portable readers from Biomark to read the PIT-tags. All mice were anesthetized to PIT-tag them. Anesthesia procedures followed protocols successfully used on PMJM before (R. Schorr personal communication). Mice were anesthetized by placing them and a cotton ball with 1 ml ofMetofane (methoxyflurane) into a sealed ziplock bag (to keep Metofane fumes in bag). The bag was then lain aside to minimize stress for the mouse and the time the mouse struggles in the bag. The less agitated the mouse is in the bag the less time required for the metofane to take affect. The mouse was observed at all times to make sure the mouse did not .. position itself such that the c_otton ball was in direct cont~ct with its face, which might c~use the mouse �30 to have a severe reaction to the anesthesia After the animal stopped moving, the handlers waited one minute before removing the mouse from the bag. The animal typically remained anesthetized for 2-3 minutes once outside the bag. Each PMJM was PIT-tagged using a protocol successfully used by C. Meaney (personal communication). Each PMJM had a PIT-tag inserted above the s~oulder blades by lifting the skin on its back and inserting the individually sterilized needle with the PIT-tag under their skin and injecting the tag. Verification of the PIT-tag identification number was made before and after insertion into the mouse by running the PIT-tag scanner across it. The skin behind the opening was then pinched to prevent emergence of the tag. PIT-tag identification number was recorded on the field data form. If, at any time during the handling of the PMJM the animal appeared to be severely stressed (dramatic changes in heartbeat, respiration and responsiveness or gums turning blue) first aid was administered and, once recovered, released without further processing. Absence of PMJM at a site was defined as no captures of PMJM from a minimum of four consecutive nights and 400 trap nights ( a trap night is defined as the sum total number of traps available each night). Presence of PMJM at a site was defined as at least one capture of PMJM at the site. However, to accommodate sample size requirements for the monitoring and genetics study (see below) trapping efforts continued until at least 10 individuals were tagged with PIT-tags. Habitat Use The general approach was to measure both site specific and landscape features of at least 30 sites selected at random to be surveyed for the presence of PMJM. A comparison of sites where PMJM were found and were not found was then made in an attempt to refine our current understanding of the ecological requirements of the subspecies. The following habitat characteristics were measured and recorded for each site. Site characteristics Cover was measured at 20 random locations along the 250 meter sampled stream stretch. Mean cover and standard error of the mean will be estimated. Cover was estimated using a vegetation profile board (Nudds 1977) that allows for an assessment of visual obstruction in 0.5 meter vertical intervals above ground. The board was 2.0 meters high and 30.48 cm wide. The board was marked in alternate black and white colors at 0.25 (0.50) meter intervals. Horizontal cover was assessed in each interval by viewing the board from 15 meters away in a randomly chosen direction. The percentage of each interval concealed by vegetation was recorded as 0-20, 21-40, 41-60, 61-80, and 81-100% estimated concealment. Vegetation species composition and richness was estimated using the Modified-Whittaker nested vegetation sampling method (Stohlgren et al. 1995). A modified Whittaker plot is 20-meters x 50-meters with 10 lm2 and 2 10m2 subplots arranged systematically around the perimeter and 1 100m2 subplot centered in the inside of the 20 meter by 50 meter plot. Species composition and percent cover (optical estimate) of each species was recorded for each subplot. Soil samples were taken randomly at each site for a hydrometer textural analysis (percent sand, silt and clay). Samples were collected using an AMS 24" soil recovery probe. Samples were taken from 0-12 inches, and 12+ to 24 inches. The 0-12 inch sample was taken first, removing the probe and soil. Samples were placed in a labeled ziplock bag. The probe was then placed in the same hole for the 12+ - 24 inch probe, with that soil sample being placed in a separately labeled ziplock bag. The hydrometer textural analysis will be conducted at the CSU Soils Laboratory. Mean stream width was estimated by measuring stream width at 30 locations along the entire site sampled. The 30 locations were stratified equidistant from each other to cover the entire stream stretch in increments of site stream length/30. �31 The above listed parameter estimates will be compared for sites where PMJM were. captured and sites where PMJM were not captured. Landscape characteristics The following landscape habitat characteristics will be measured and compared for sites where PMJM were captured and sites where PMJM were not captured using either GIS, topographic maps, or aerial infrared photography. 1. Distance to nearest human habitation and human disturbance. 2. Connectivity of sites to other streams from 1:24,000 topographic maps. 3. Total length of stream stretch at each site and total length of stream stretch with suitable habitat at each site. Molecular Systematics Genetic tissue samples were collected from all PMJM captured during the study. To date, positive identification of the individual to subspecies cannot be made using only genetic information. However, results of the DNA analysis combined with the morphometric data that will also be collected (e.g., body length, tail length) and the photograph of the individual should provide sufficient information to support the field identification to subspecies. As established by the USFWS (1997) Survey Guidelines, presence of PMJM is established when only one individual is captured. Thus, we could stop our trapping efforts after the first PMJM capture. However, because we would also like to provide sufficient genetic data to more fully explore the relationships of different populations of Z. h. preblei we will attempt to collect genetic tissue samples from a minimum of 10 individuals per successful survey site. A sample of at least 10 individuals from a population will provide enough information to document the genetic variation within the population {T. Quinn, personal communication). Genetic tissue sampling Genetic tissue samples were collected from every PMJM captured at each survey site. The following protocol was used based on previous success with PMJM (M. Bakeman, C. Meaney, T. Ryon, R. Schorr, personal communication). A fresh pair of clean latex gloves were used to handle each mouse. With a clean ear punch tool, one tissue plug was obtained from each mouse ear. If there was excessive bleeding, gentle pressure was applied to the injured area for approximately one minute. Each ear plug was placed in a vial of 95% ethanol. Both the vial and the corresponding record on the data sheet were labeled with a unique identifier as follows. A seven-place alpha-numeric code was composed as follows: a three-letter designator for the survey location ( e.g., MYT = Maytag Property); a number beginning with two digits indicating the year (e.g-., 98); followed by 2 digits specifying the individual trapped, numbered sequentially. For example: MYT9801 = first animal sampled at Maytag Property in 1998. After returning from the field, all samples were put in a cool place or refrigerated until delivery to the CDOW office at 317 West Prospect, Fort Collins, CO where they are being held in the freezer for future analyses. Ear punch tools were cleaned after each use by immersing them in a 10% bleach solution for a few minutes, rinsing them thoroughly with clean water, and then dried thoroughly to prevent rusting. Dull ear punch were discarded and replaced with new sharp punches to ensure the quickest, cleanest cut possible. Results Trapping results Thirty-nine sites were surveyed for PMJM in Larimer and Weld Counties, Colorado (Fig. 1), with a total survey effort of 16,671 trap-nights. Of the 39 sites survey, Zapus spp. were captured at 21 survey sites (Table 1). A total of 71 unique. individuals-were captured in the 21 locations, wit}:l_· �32 recaptures of 14 of those individuals. All sites where jumping mice were captured were located in Larimer County. Two trap mortalities of Zapus spp. occurred. Both specimens were saved and delivered to Cheri Jones of the Denver Museum of Natural History on October 26, 1998. Numbers of other small mammal species captures was recorded for each site surveyed (Table < 2). Nine fecal samples were collected from traps where Zapus spp. were captured. Results of eight samples indicate the jumping mice at the capture sites in Larimer County feed on arthropods and fungus which occurred in 50% (4) of the samples, followed by willows, pollen, and moss occurring in 38% (3), 25% (2) and 25% (2) of samples respectively. Other food items found included, moss, horsetail, unknown flowers, and unknown seeds (Table 3). Habitat characteristics Measurements of habitat characteristics at both the site and landscape levels were completed. No single habitat feature could be identified as unique to either sites where jumping mice were captured or sites where jumping mice were not captured. Kentucky blue grass (Poa pratensis), snowberry (Symphoricarpos spp), several species of willow (Salix spp.), and Mountain Alder were most abundant in areas occupied by Zapus spp. Horsetail (Equisetum spp), wild rose (R.osa spp), and cottonwood were also common. Dominant vegetation at survey sites with negative trapping results for jumping mice included wheat grass {Agropyron spp), Canary reed grass (Phalaris angustifolia), thistle, and willows (Table 4). Russian olive (E/aeaqnus angustifolia) occurred in 6 (33%) of the areas where no jumping mice were found, while absent in areas where jumping mice were captured. Jumping mice were captured in vegetation adjacent to large rivers, small streams, ponds, ditches, and seeps. Mean stream width varied considerably for both sites where jumping mice were captured (0.3-24.Sm) and where no jumping mice were captured (0.0-20m)(Table 4). No jumping mice were found in locations surveyed east of Interstate 25(125) during 4,716 nights of trapping effort. Habitat features along certain stretches of Willow Creek within the Pawnee National Grasslands and near the town of Briggsdale are similar to areas where jumping mice were found west ofl25. However, these sites are extremely isolated and the surrounding landscape is in either rangeland or agriculture production. From late June through late August, 22 locations in Larimer County were surveyed. Zapus spp were found in 20 of these 22 sites. The exceptions being the effluent below Seaman Reservoir on the Poudre River and Soldier Canyon west ofHorsetooth Reservoir. Below Seaman Reservoir just prior to and during trapping efforts, livestock (primarily cattle) were allowed to graze along this section of the Poudre River. Habitat composition along Soldier Canyon is similar to that of Arthur's Rock ~3/4 miles to the south (occupied by Zapus spp). However water is permanent along the Arthur's Rock drainage but flows intermittently through Soldiers Canyon. Only one jumping mouse was captured west ofl25 after August 24 during 5,382 nights of trapping effort at nine different sites. All locations trapped after August 24 were within drainages known to be occupied by Zapus spp., including four sites along the Big Thompson River (this study), two along the Poudre River (this study), and one each along Rabbit Creek (Meaney et al. 1997), Bull Creek (this study) and Lone Tree Creek (Meaney et al. 1997). The surrounding areas that were trapped along Bull Creek and Lone Tree Creek had been extensively grazed, leaving only isolated patches of vegetation over most of the site, however all other locations were similar in habitat composition to known PMJM locations. Three soil samples from 0-12 inches and 12-24 inches were collected at all sites where possible. Soils at some sites were too rocky to collect the 12-24 inch soil samples. A total of 104 012inch samples and 46 12-24 inch soil samples were delivered on October 21, 1998 to the Colorado State University-Soil Composition lab for soil-textural analyses. To date-these analyses have not beeri. compJeted. �33 Genetic sampling Genetic tissue samples were collected from 68 of the 71 jumping mice captured. Analyses of these tissue samples is pending. Discussion The habitat matrix within the range of Z. h. preblei is mixed grasslands adjacent to the Colorado Front Range along the Piedmont and along the base ofti.e Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, PMJM occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major components. The first component is a supply of open water, at least in part of the active season (M. Bakeman, C. Meaney, personal communication). Secondly, areas where PMJM has been found have dense cover (M. Bakeman, C. Meaney, personal communication). Based on studies of Z. h. preb/ei and Z. hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but are often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). Vegetation at sites where Zapus spp were captured in this study were structurally diverse. No single plant species dominated areas occupied or unoccupied by Zapus spp. Such diversity in a multistory cover has been reported for the majority of other sites where Z. h. preblei have been found (Armstrong et al. 1997, Meaney et al. 1997). Vegetation composition of the dense cover varied considerably and included both native and non-native species as was found by other studies (Meaney et al. 1996, 1997, Armstrong et al. 1997, M. Bakeman, personal communication). Results from this study continue to support the habitat descriptions provided by Armstrong et al. (1997) which follows: The herbaceous understory is primarily grasses or forbs or a mixture of the two. Few of the sites, however, are dominated by fewer than two understory species. The tall shrub canopy at most sites is willow (Salix spp.), although scrub oak (Quercus gambelli), birch (Betula spp.), and alder (A/nus spp.) occur in sites south of the Palmer Divide Ponderosa pine (Pinus ponderosa) is the most common tree at higher elevations. The mouse appears to tolerate weedy or exotic species in areas that are structurally diverse and species rich; nearly every successful site contained Canada thistle (Cirsium arvense ). Thus, the mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. PMJM have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road use, and moderate cattle grazing (M. Bakeman, personal communication). Open water was present at all sites surveyed in this study, with stream width varying across locations with and without jumping mice. Jumping mice were captured in 21 new locations in both the Poudre River and the Big Thompson River drainages in Larimer County. No jumping mice were captured at any survey site located in Weld County, however there may still be some sites within and adjacent to the Pawnee National Grasslands that may support PMJM (M. Ball, personal communication). Fish Creek, north of Bull Creek is the only location trapped after the 24th of August where jumping mice occurred. Poor trap success in late summer especially in areas along the Big Thompson and Poudre Rivers, including locations near Cherokee Park SWA, may be influenced in part by jumping mice entering hibernation. Elevation at these sites ranged from 5800 ft along the Poudre River to 7600 ft along Bull Creek north of Cherokee Park, much higher then the maximum elevation in D_ouglas (Shen~.and S.i':ert 1999,a, l 999b.) and Boulder. Countie~_(M.eaney_et al 19_99) \1/,heren_o r_edu~tion..in trap success • • •• . ... " could be detect_~d. . . . . .. •; �34 Food habit studies using scat analysis indicate jumping mice captured in Larimer County fed on several different food types. This is similar to Shenk and Sivert (1999b) in Douglas County, Colorado who also reported several food items in Z. h. preblei scat. It appears jumping mice captured in Larimer County fed on willows, with willow present in 38% of the scats examined. This is in contrast to Shenk and Sivert (1999b) who report virtually no willows in the scat examined from 85 fecal samples collected at three sites in Douglas County. ,, PMJM are only one component of the small mammal community inhabiting areas where they were captured. These mice were more often found at sites with high species richness and small mammal abundance (Table 2). The highest occurrences of Mus musculus captures occurred on sites where jumping mice were not found. This is similar to results summarized in Shenk (1998). The presence oflarge numbers of house mice might suggest degradation of habitat for Z. h. preblei in those areas or possibly competition between the two species (Ryon 1996). Jumping mice were also not found in areas where large numbers of captures of deer mice (> 115) occurred. These preliminary analyses have treated all the jumping mice captured the same. However, the truth may be they are all PMJM, all western jumping mice, or a mixture of the two. Once the genetic study is completed and species identifications confirmed these analyses will need to be reevaluated in light of that information. If some of the mice captured are identified as western jumping mice it would be most beneficial to compare areas of occupancy by this species to areas occupied by PMJM and to areas potentially occupied by both. According to Fitzgerald et al. (1994) the distributions of Z. princeps and Z. hudsonius do overlap. The area of overlap occurs in eastern Wyoming. The distribution of Z. hudsonius in Colorado is now known to be larger than shown in Fitzgerald et al. (1994). The boundaries are currently as far south as Las Animas County, based on genetically identified specimens of Z. h. preblei (Riggs 1998). Captures of Z. princeps and Z. hudsonius (as identified in the museum) have occurred as close as eight miles of one another within the same drainage (Armstrong 1972). Z. princeps were reported captured in 1981 (Olson and Knopf 1988) at the Lone Pine site in Larimer County, Colorado, where Z. h. preblei were captured by Menaey et al. (1997). Because neither specimens or genetic samples were taken in the 1981 study, identification of those mice will remain in question. The discrepancy may be explained by field misidentification or Meaney et al. (1997) also suggest this discrepancy might be explained by displacement of Z. princeps with Z. h. preb/ei sometime in the sixteen intervening years between trapping efforts. Although assumed to have different ecological requirements, genetic evidence presented by Riggs (1998) suggests further investigation of possible distributional overlap between Z. h. preb/ei and Z. princeps. These preliminary results from this study suggests further research should be conducted to continue evaluating range-wide distributional boundaries (e.g., elevation restrictions). Further studies should also be conducted to investigate areas of potential sympatry or hibridization of PMJM with Z. princeps (western jumping mouse). Literature Cited Armstrong, D. M. 1972. Distribution of mammals in Colorado. University of Kansas, Museum of Natural History Monograph 3:1-415. Armstrong, D. M., M. E. Bakeman, A. Deans, C. A. Meaney, and T. R. Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. EG&G. 1993. Report of Findings: 2nd Year Survey for the Preble's meadow jumping mouse. Prepared by Stoecker Environmental Consultants for ESCO Associates, Inc., Rocky Flats Environmental Technology Site, Jefferson County, Colorado Fitzgerald, J. P., C. A. Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. H::uner, D. J., K, E. Petersen, .and T. L. Yates. 198 L Evolutionary relationships of jumping mice .,. . . . .. (genµs µipus) of the s,outhwestern U~ited States. Journ.~ of_M!iJllmalogy 6~:501-51.2 ... �35 Hall, E. R 1981. The mammals of North America John Wiley and Sons, Inc., New York, New York, 2 volumes. Jones, C. A. 1996. Mammals of the James John and Lake Dorothey State Wildlife Areas. Final Report, submitted to the Colorado Division of Wildlife and Colorado Natural Areas Program. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. •• Levins, R 1970. Extinction. Lectures in Mathematical Life Sciences 2:75-107. Long, C. A. 1965. The mammals of Wyoming. University of Kansas Publications, Museum of Natural History, 14:493-758. Meaney, C. A., N. W. Clippinger, A. Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 5:113-117. Olson, T. E., and F. L. Knopf 1988. Patterns ofrelative diversity within riparian small mammal communities, Platte River watershed, Colorado. Pg. 379-386 in: Proceedings of the symposium: Management of amphibians, reptiles and small mammals in North America Flagstaff, Arizona U.S. Forest Service, General Technical Report RM-166. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. • Quimby, D. C. 1951. The life history and ecology of the jumping mouse, Zapus hudsonius. Ecological Monographs 21:61-95. Riggs, L. A., J. M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation. Final Report for the Colorado Division of Wildlife. Denver, Colorado. Ryon, T. R 1996. Evaluation of historical capture sites of the Preble's meadow jumping mouse in Colorado, final report. MS Thesis. University of Denver, Denver, Colorado. Shenk, T. M. 1998. Conservation assessment and preliminary conservation strategy for Preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife FY 1997-98 Annual Report. Shenk, T. M. and M. M. Sivert. 1999. Temporal and spatial variation in the demography of Preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife JanuaryMarch 1999 Quarterly Report. Shenk, T. M. and Sivert M. 1999. Movement patterns of Preble's meadow jumping mouse (Zapus hudsonius preblei) as they vary across time and space. Colorado Division of Wildlife January March 1999 Quarterly Report. Stohlgren,T. J., M. B. Falkner, and L. D. Schell. 1995. A Modified-Whittaker nested vegetation sampling method. Vegetatio 117:113-121. USFWS. 1997a Proposal to list the Preble's meadow jumping mouse as an endangered species. USFWS 50 CFR part 17. USFWS. 1997b. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. Whitaker, J, 0., Jr. -1972. Zapus-.,hudsonius. M~malian Species.1.1:l-I .. _,. �36 Table I. Survey site locations and trapping results for presence ofjumping mice (Zapus spp.) in Larimer and Weld Counties, Colorado. Positive identification to species is pending. Number Weights (grams) General Description ofLocation 3 total 3 females 21, 23.5 unnamed drainage to north of Arthur's Rock drainage 7480 feet 13 total 6 females 7males 20, 21.5, 28, 22, 26.6, 19, 23, 22, 25, 20.5, 23, 22, 23 west of Prairie Divide Road E485875 N4498154 5120 feet 2 total I male I female 18.5, 19 near Watson Lake, northwest of Laporte 7nt987/9/98 E467500 N4502140 6320 feet 12 total 8 females 4 males 21.5,25, 19,20, 24, 21, 19, 21, 23.5, 21, 23 drainage runs along west side of Stove Prairie Road into the Poudre River Meadow Creek 7/10/987/13/98 E467149 N4524532 6680 feet 3 total 3 females 17,22.5,25.5 along Cherokee Park Road Young Gulch 7/12/987/15/98 E470750 N4502380 E470650 N4503800 6240 feet I total I female 2 total 2 female 22 tributary of Poudre River Dates trapped U1M coordinates Elevation Arthur's Rock 6/23/986/26/98 E485250 N4490700 5520 feet Bull Creek 6/28/987/1/98 E458594 N4525510 Poudre River 7ll/987/10/98 Skin Gulch Drainage ofZapus spp.found 5840 feet 33, 23.5 Sevenmile Creek 7/12/987/15/98 E450611 N4505834 7000 feet 2 total I female 1 male 24, 24.8 tributary of Poudre River N. Fork Poudre River 7/207/22/98 E468100 N 4527485 6440 feet 2 total I female I male 20, 22.5 Cherokee Park, drainage above Halligan Reservoir Pendergrass Creek 7/267/29/98 E461380 N 4501300 7000 feet I total I male 28 tributary ofS. Fork of the Poudre River Buck Gulch 8/3-4/98 E463575 N4502360 6400 feet 2 total 2 females 10, 23.5 tributary of Poudre River just east of Big Narrows Lakey Canyon 8/3-4/98 E466550 N 4491360 7120 feet ~ total 28.5, 22, 30, 13 tributary of Buckhorn Creek Little Bear Gulch 8/5-7/98 E 475650 N 4483745 6600 feet 2 total 2 female 29, 16 Buckhorn Mtn. area Bear Gulch 8/6-7/98 E 472500 N 4483550 7200 feet 1 total I female 19.5 tributary of Buckhorn Creek N. Fork, Big Thompson 8/9-11/98 E 462950 N 4478090 7080 feet 1 total 1 female 24.5 by Glen Haven N. Fork Poudre River 8/9-11/98 E 478692 N4516030 5900 feet 7 total 3 female 3 male _l escaped 22, 17.5, 17.5, 18, 17, 28, Robert's property 3 females 1 male �37 Drainage Dates trapped U1M Elevation Number ofZapus spp.found Weights (grams) General Description of Location coordinates North Poudre Canal 8/17-18/98 E478000 N 4518600 6000 feet 4 total 4 male 23, I 9, 13, 18 irrigation ditch and pond - Knight's property North Fork ofPoudre 8/18-19/98 E472935 N 4523400 6100 feet I total I female 28.5 Phantom Canyon Little Thompson River 8/19-20/98 E468500 N 4459400 6600 feet I total I male 17.5 northwest of Pinewood Sprngs, off Hwy 36 Cedar Creek 8/21-22/98 E 477097 N 4477899 6080 feet 5 total 3 female 20, 28, 18.5, 33, 15 2male Sheep Creek 8/21-22/98 E470451 N 4490818 6700 feet I total I male 18.5 tributary of Buckhorn Creek Fish Creek 9/9-10/98 E462800 N 4537100 7400 feet I total I female 18.5 tributary of Fish Creek 6/2-6/5/98 E 547250 N 4522450 5160 feet 0 E 502350 N 4506750 5180 feet drainage Geary Creek Windsor Ditch 6n-6n0t98 Geary Creek, Pawnee National Grasslands 0 Windsor ditch, Cobb LakeSWA Willow Creek · 6/116/14/98 E 537260 N 4521900 5200 feet Willow Creek 6/126/15/98 E 545310 N 4516687 5060 feet 0 Willow Creek, Pawnee National Grasslands Crow Creek 6/166/19/98 E 555711 N 4499260 4820 feet 0 Crow Creek, Pawnee National Grasslands Owl Creek 6/236/26/98 E 522550 N 4523050 5450 feet 0 Owl Creek, Pawnee National Grasslands Soldier Canyon 6/28-7/1/98 E 484350 N 4492950 5520-5600 feet 0 Soldier Canyon drainage, Lory State 0 Willow Creek, Pawnee National Grasslands Park Seaman Reservoir 7/237/26/98 E480I00 N 4505680 5400 feet 0 effiuent of Seaman Reservoir, North Fork of the Poudre River South Fork Rabbit Creek 8/248/27/98 E 470150 N 4515100 6334 feet 0 South Fork Rabbit Creek, Cherokee Park Banner Lakes 8/248/26/98 E 537850 N4435190 5030 feet 0 Banner Lakes SWA Big Thompson River 8/27-30/98 E497210 N 4470130 4870 feet 0 Big Thompson River at Simpson Ponds SWA South Side Ditch 9/1-4/98 E 484350 N 4473690 5100 feet 0 South Side Ditch, Big . ThompsoJJ. Canyon SWA �38 Dates trapped UfM Big Thompson River 9/1-4/98 Long Gulch Elevation Number ofZapus spp.found E467150 N4473120 6800 feet 0 Big Thompson River 9/1-9/4/98 E465850 N4473450 7100 feet 0 Long Gulch, Big Thompson drainage Lone Tree Creek 9/9-9/12/98 E506850 N4536000 E 506320 N 4535400 5900 feet 0 Long Tree Creek, Meadow Springs Ranch Bull Creek 9/129/15/98 E462150 N 4534150 7600 feet 0 Bull Creek South Fork Poudre River 9/139/16/98 E462250 N4503650 6400 feet 0 South Fork Poudre River Poudre River 9/139/16/98 E470955 N4504350 5800 feet 0 Poudre River Drainage coordinates Weights (grams) General Description ofLocation �•Table 2. Numbers of other small mammal captures at the 39 sites surveyed for Preble's meadow jumping mouse in Larimer and Weld Counties2 Colorado. S2ecies codes are listed below the table. Mumu Other Drainage PMJM Sos2 Sxs2 Tase Tahu Chhi Rese Perna Petr Pese Neme Mise • Arthur's Rock : Bull Creek • Poudre River at Watson Lake • Skin Gulch Meadow Creek Youn Gulch Seven Mile Creek North Fork Poudre River • •Pendergrass Creek Buck Gulch Lake Can on : Little Bear Gulch •. Bear Gulch : North Fork Big ThomQson • North Fork of Poudre River North Poudre Canal North Fork of Poudre River • Little ThomQson River Cedar Creek She Creek •• Fish Creek drainage Ge Creek Windsor Ditch • Willow Creek Willow Creek Crow Creek Owl Creek .•. Soldier Can on Seamen Reservoir South Fork Rabbit Creek . Banner Lakes 2 3 13 2 12 3 3 2 2 1 2 4 2 27 1 34 5 43 25 3 1 22 6 5 3 106 113 114 11 5 14 15 46 15 6 23 2 8 11 5 8 8 3 2 7 4 4 5 1 9 22 2 2 1 5 1 2 0 0 0 0 0 0 43 14 8 0 9 3 65 15 5 2 5 15 3 37 16 1 6 g 0 0 1 79 2 7 2 0 1 2 4 3 ,. 1 2 6 2 8 8 2 30 174 12 211 176 93 13 110 32 39 28 166 4 3 1 1 13 w. 6 '° �~ 0 PMJM Drainage Big Thompson River • South Side Ditch Big Thompson River Lon Gulch Lone Tree Creek 0 0 0 0 0 Bull Creek ., South Fork Poudre River 0 0 Poudre River Sosp Sysp Tasp Tahu 2 Chhi Resp Mumu IO 25 59 8 13 11 104 67 5 22 14 4 0 :' Sosp =Sorex spp. • Chhi =Clzaetodipus lzispidus Petr =Peromyscus troei ·: Mumu =Mus musculus Neme 16 31 1 1 3 ·' Pesp 28 12 186 83 174 1 4 Perna Petr 6 3 Misp Other 21 81 9 72 Tasp =Tamiasciurus hudsonicus Perna =Peromyscus maniculatus Neme= Neotoma mexicana Sysp =Sylvilagus spp. Resp =Reithrodontomys spp. Pesp =Peromyscus spp. Misp =Microtis spp. •. Table 3. Percent contents of fecal samples collected from traps where Preble's meadow jumping mice were captured. All samples were · collected during the 1998 field season. Amount of bait in each sample was quantified as 100%, 'A' for abundant(> 70% of the sample), T for trace amount (< 10% of the sample), or 0% of the sample was bait. endogenous Date Salix seed moss pollen Equisetum flower Salsola Location bait arthropods fungus PIT-tag ID# 41412PH3D : 4 I405A3326 41405C68l8 41414A5459 Juvenile Juvenile 41413A7757 4141310654 Juvenile Seven Mile Creek Seven Mile Creek North Fork Poudre North Fork Poudre Sheep Creek Buck Gulch Buck Gulch Bear Gulch Fish Creek July 14 July 18 July21 Aug 11 Aug22 Aug4 Aug4 Aug7 Sept 10 T T A T A A T A 0 2 89 11 53 9 89 41 6 78 91 15 100 T 7 9 7 7 100 79 7 �41 Table 4. Mean stream width and dominant understory, shrub, and overstory vegetation at each of the sites surveyed for Preble's meadow jumping in Larimer and Weld County, Colorado during 1998. Mean Stream wid~(m) Drainage:!: PMJM X Dominant Overstory se(X) Grass/Forb Shrub Tree Bluegrass/Horsetail Bluegrass AltaFescue Bluegrass/Canada Thistle Bluegrass/Canada thistle Wild Plum Willow Willow Snowbeny/ Chock Cherry Elm Mountain Alder Cottonwood Snowbeny Willow Wax.current Mountain alder Arthur's Rock Bull Creek Poudre R. at Watson Lake y y y 0.77 1.75 24.47 1.01 0.2 0.54 Skin Gulch y 0.28 5.15 Meadow Creek l.77 0.97 Young Gulch Seven Mile Creek y y y 1.22 3.38 1.06 1.14 North Fork Poudre River Pendergrass Creek Buck Gulch Lakey Canyon Little Bear Gulch Bear Gulch North Fork Big Thompson y y y y y y y 8.30 l.72 0.52 0.84 0.46 0.53 6.93 3.03 0.53 0.26 0.18 0.26 1.9 l.73 North Fork of Poudre River y y 12.50 11.97 6.97 y y y y y 8.30 2.93 2.07 2.58 0.49 1.43 1.82 1.1 0.4 2.12 0.00 7.07 9.20 0.91 5.74 2.41 Willow Creek Crow Creek N N N N N l.78 0.89 Owl Creek N 8.00 3.37 2.40 Wheatgrass Wheatgrass Canada Thistle Canada Thistle 0.39 Cone Flower North Poudre Canal North Fork of Poudre River Little Thompson River Cedar Creek Sheep Creek Fish Creek drainage Geary Creek Windsor Ditch Willow Creek Soldier Canyon Seamen Reservoir South Fork Rabbit Creek Banner Lakes Big Thompson River South Side Ditch Big Thompson River Long Gulch Lone Tree Creek N N N 1.20 9.87 0.52 5.20 10.27 14.17 15.53 1.18 3.84 0.20 8.53 1.24 0.42 0.79 2.41 Bluegrass Bluegrass Bluegrass/ wheatgrass Columbine Black-eyed susan Aster Bluegrass Bluegrass/ yarrow Bluegrass Bluegrass/Canada thistle Bluegrass Bluegrass/ Canada thistle Canada thistle Bluegrass Blue grama Canada thistle Wheatgrass Bluegrass/ Dandelion Cheatgrass Wheatgrass Canary Reed Grass Canary Reed Grass Canary Reed Grass Canada Thistle Horsetail Yarrow Cottonwood Ponderosa pine Juniper Willow Mountain alder Snowbeny Aspen/ maple Wax.current Juniper Wild rose/ wild grape Spruce Wild raspberry Aspen Willow Mountain alder Snowberry Mountain alder Willow Willow Cottonwood Cottonwood Snowbeny Willow Willow Wild rose Willow Mountain alder Cottonwood Ponderosa pine Mountain alder Ponderosa pine Cottonwood (Absent) Willow (Absent) Wax.Current Wax.Current Willow Willow Willow Willow Willow (Absent) (Absent) (Absent) Elm Russian Olive Cottonwood Ponderosa pine Mountain Alder Russian Olive Russian Olive Cottonwood Mountain Alder Ponderosa Pine Willow N 0.2 N 6.57 Snowbeny Willow N 0.38 N 0.25 Willow N Willow l.86 Snowberry N 0.1 Wild Rose Bull Creek N Juniper 1.18 Goosebcny South Fork Poudre River N ERR Golden Banner Snowbeny/ Wild Rose Ponderosa Pine Poudrc River N 20.00 Common Lupine Choke Cherry Juniwr i Drainages ar~ list~d in the same order ~s i~ Table 1 so that exa~t locations of each site could be obtained by using both tables. .. . ._ . .··.. �• II ■ l'=,-b'--tf-r----~~~>c-f'-J art ~ollins~ 1---1L • ■ Zapus spp. Found Site Trapped No Zapus spp. Found D County Line Nstreams /V Roads Figure 1. 1998 survey site locations and trapping results for presence of Preble's meadow jumping mouse (PMJM) in Larimer and Weld Counties, Colorado. Locations where PMJM were found are indicated by a red circle, locations where PMJM were not found are indicated by a green circle. �43 APPENDIXC TEMPORAL AND SPATIAL VARIATION IN THE DEMOGRAPHY OF PREBLE'S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) Tanya M. Shenk and Maile M. Sivert Abstract A total of 186 individual mice were captured and PIT-tagged at three study sites (73 mice at Maytag Property, 77 mice at PineCliffRanch, and 36 mice at Woodhouse Ranch). These mice were captured over three different trapping sessions with an effort of 17,330 trap-nights. Genetic tissue samples were collected for at least 30 individual mice at each of the three study sites. Density estimates were expected to increase as the summer progressed to account for the birth pulses in late June, and late July-August. This was the trend observed· at Maytag. PMJM densities at Woodhouse Ranch increased from June to July but did not increase further during the September trapping session. Mean PMJM density over all sites and sessions was 40.5 (range 16.9-79.0) mice per kilometer of stream stretch. Highest densities occurred at PineCliff, where the vegetation is primarily willow and both a mainstem and tributary were used by mice. Lowest densities occurred at Woodhouse Ranch where the riparian vegetation has fewer willow but was dense with other riparian vegetation. Vegetation at Maytag provided some areas of dense willow with the remaining areas being of moderate density of riparian vegetation. The lower density of PMJM reported for Woodhouse Ranch might be explained by the composition and densities of other small mammals at that site. Woodhouse Ranch had the highest captures of both house mice and voles of the three sites studied. Defining summer as June 1 - October 5, over-summer survival was estimated as 0.36 (se = 0.056) over all three study sites. Temporary emigration and immigration rates were estimated but both had extremely high variances associated with those estimates. Thus, these estimates cannot be used, with any confidence, to provide information on movements of mice into and out of these populations. Very little new information was gained during this study on reproductive parameters of PMJM. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia However, we were unable to locate any breeding nests. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during both the July and September trapping sess10ns. This report includes results from only the first year of a multi-year project to follow individually marked PMJM through time. Collection of more data, and more years of data, will improve our ability to evaluate demographic parameters and estimates of how they vary across space and time. Introduction On May 12, 1998 the U.S. Fish and Wildlife Service (USFWS) published a final rule in the Federal Register (63 FR 26517) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) as 'threatened' under the Federal Endangered Species Act (ESA) of 1973, as amended. Recovery goals for Preble's meadow jumping mouse (PMJM) should work towards the sustainability, protection, and restoration of Z. h. preblei populations and habitats on both private and public lands to provide the spatial, genetic, and demographic structure needed to promote long-term species viability and provide species management flexibility. Recovery efforts for the subspecies will be most effective if reliable information is available on the basic ecology of the subspecies and this information used to design recovery efforts such as Habitat Conservation Plans. A review of studies conducted on PMJM shows that there is insufficient information to fully address defining range-wide ecological requirements, .- . limiti~g _factors, .l.imits. of speci~s toler:µice, _oi:_popula~ion st~Ws (Shenk 199_8) .. Most work to date _has �44 focused on geographic distribution (presence or absence of Z. h. preblei), taxonomy, and habitat descriptions of sites where mice have and have not been captured. For PMJM in particular, information on dispersal, habitat use, and population dynamics is most needed to identify minimal ecological requirements of the subspecies. Monitoring, by way of estimating demographic parameters (such as survival, abundance, and reproduction), of a single population over time provides an opportunity to document demography of a species, estimate temporal fluctuations in demography, and gain insights into the temporal variation inherent in demographic parameters. Monitoring of multiple populations over time and over multiple geographic locations provides the opportunity to gain further understanding of population processes and detaches time effects from spatial effects. Population monitoring activities do not constitute scientific experiments, in the spirit of manipulation of salient ecological variables, however, replication of monitoring activities for natural populations over long periods of time and in diverse geographic locations can lead to insights into population processes (Cook and Campbell 1979). These insights can then be translated into hypotheses useful for predicting changes in population demography resulting from either natural perturbations (e.g., flooding events) or anthropogenic modifications (e.g., gravel mining). Experimentation would then be required to test these hypotheses and establish cause and effect. The primary objective of this study is to investigate spatial and temporal variation in the demography of PMJM. Demographic parameters to be estimated include survival, reproduction, temporary emigration, immigration, population structure, and density. These demographic parameters will be estimated from individually marked animals from geographically distinct populations. To evaluate spatial differences in the demography of PMJM, populations were selected from three sites that provided a variety of habitat matrices available to the mouse. Multiple years of conducting the study at those same sites will provide an estimate of the temporal variation in demography of PMJM. Study sites Demography of PMJM was evaluated for three populations. All three populations selected were located in areas where PMJM had previously been found. To evaluate spatial differences in the demography of PMJM, populations were selected on sites that provided a variety of habitat matrices available to the mouse. The first site selected, Colorado Division of Wildlife (CDOW) Maytag Property, has one primary water source available to the mouse. This water source is East Plum Creek. The second site, Colorado Open Lands PineCliffRanch, provides both a tributary (Garber Creek) and a main stem drainage (West Plum Creek). The third study site, CDOW Woodhouse Ranch provides an area containing a tributary (Indian Creek) and a series of ponds and irrigation ditches scattered throughout the property. Objectives Objectives of the demography study are to: 1. Estimate abundance and density of PMJM for each of three study populations. 2. Estimate over-summer, over-winter, and annual survival of PMJM at each of three study populations. 3. Estimate temporary emigration of PMJM at each of three study populations. 4. Estimate immigration of marked PMJM back into each of three study populations. 5. Estimate reproduction of PMJM at-each of three study populations. 6. Evaluate the affect of weight, sex, age, abundance (i.e., density dependent response), and habitat features such as stream reach, vegetation composition and density on survival, reproduction, abundance, temporary emigration, and immigration of marked animals back into three study populations of PMJM. .7, J;stimate _1;1ge ~d.se~ ratios 9f PMJM at e~Gh of three stµdy pop4lati.ons .. .. . . .- . ~ . . . .. �45 Met/,ods Trapping Three trapping sessions were conducted during the following weeks: June 2-9, 1998; July 21August 5, 1998; and September 8-15, 1998. Trappers were advised to follow the Center for Disease Control's Hantavirus instructions and recommendations when dealing with rodents. Due to the nocturnal nature of PMJM, traps were set between 19:00hrs an<l'21:00hrs and checked as early as possible in the morning beginning at 5:00hrs to reduce stress and the potential for predation on trapped animals. Time required to complete the traplines varied depending on how many animals were caught. Small mammal Sherman live traps (folding and non-folding) were used to conduct the trapping sessions. Traps were set in two parallel lines of trap stations (1 trap per station) on either side of the drainage. Trap stations were 5 meters apart for a total of 250 meters; the parallel transects were 10 meters apart unless extent of habitat, terrain topography, or stream hydrology did not allow. Location of transects were recorded on field data sheets. Each trap location was also recorded to the nearest 5 meters in UTM coordinates using a Trimble Geo-Explorer GPS. A small (~1 inch) ball of polyester quilt was placed in each trap as nesting/bedding material. Baiting material was Manna Pro Sweet 3-way Livestock feed which contains no animal matter; ingredients include flaked barley, flaked com, flaked oats, and cane molasses. Peanut butter was used to stick the bait to the trap. Traps were checked by two surveyors. All animal captures were recorded. If an animal had been captured in a trap, a ziplock plastic bag was placed over the end of the trap .. The trap was opened allowing the animal to fall into the plastic bag. The animal was identified to species while in the plastic bag. If the animal was not a PMJM, identification of the animal was recorded and the animal set free without further handling. Each captured PMJM was checked to detect the presence/absence of a PITtag and/or radio-collar. If a PIT-tag or radio-collar was detected and the mouse had been captured at that same site within the same trapping session, identification of the mouse was recorded and the mouse was released. If the animal. was a PMJM and no PIT-tag or radio collar was detected the PMJM was anesthetized for further processing, as follows. All PMJM were PIT-tagged. If the PMJM weighed> 18 g a radio-collar was also put on the animal for movement data collection (see Shenk and Sivert 1999). Each PMJM was weighed while in the bag, recording the weight in grams using a Pesola spring balance. Sex, age (juvenile, adult), and reproductive condition (pregnant, lactating or nonbreeding if it was female; for males the position of the testes indicated if in breeding status or nonbreeding status) was noted. Each PMJM was measured (total length, length of body, length of hind foot - heel to distal end of claws) in millimeters. Capture of every PMJM was documented by taking a photograph of the mouse on first capture. Mice were placed in a plexiglass photobox to reduce handling stress to take a photograph. If the mouse had been captured previously as noted by the detection of a PIT-tag, no photograph was taken. If there were feces in the trap where a PMJM was captured, the fecal material was collected in a plastic bag labeled with date, location of the site, and animal PIT-tag number. Fecal samples were kept cool until returned to the CDOW office where they were frozen. Salt was added to each specimen bag for preservation. Once the field season was over all fecal samples were analyzed by the Composition Analysis Laboratory, Inc, 622 ½ Whedbee, Fort Collins, CO for content. These analyses were for a complementary study on food habits and movements of PMJM at the same three study areas (see Shenk and Sivert 1999 for details). All trap mortalities were recorded on a 'Trap Mortality' data form which included information on species, potential duration of time spent in the trap, and any information available to help determine cause of death. All animals found dead were double-bagged in a plastic bag and placed in a cooler with ice. Specimens were frozen as soon as possible and deposited in the CDOW freezer at the office in.Fort Collins .. A museum card was.. completed and attached-to each PMJMspecimen.and the. �46 specimen and card were given to Cheri Jones, Curator of Mammalogy at the Denver Museum of Natural History, for study skins and tissue storage. If an animal was severely injured (e.g., severed limb, large lacerations) it was euthanized by soaking a cotton ball in Metofane (methoxyflurane) and placing the cotton ball and the mouse in a ziplock bag until the animal stopped breathing. If an animal appeared to be only slightly injured (e.g., broken tail, small laceration) the animal was released to the wild.' If an animal appeared to be coldstressed attempts were made to warm it by holding it in the surveyors hands and/or against their body. If the animal appeared to be heat stressed, isopropyl alcohol was applied with a cotton swab to the ears, arm pits, and feet to cool it down. During the last trapping session homeopathic first aid treatments were used in an attempt to minimize stress and improve recovery of each PMJM. Homeopathic first aid kits and instruction was provided by WildAgain Wildlife Rehabilitation, Evergreen, Colorado. PIT-tagging Each PMJM was individually marked with a Passive Integrated Transponder (PIT-tag). PITtags are electromagnetic, glass-encased tags that emit a passive signal (125 kHz) that can be decoded by a portable reader. Destron-Fearing PIT-tags were used on all mice. We used portable readers from · Biomark to read the PIT-tags. All mice were anesthetized to PIT-tag them. Anesthesia procedures followed protocols successfully used on PMJM before (R. Schorr personal communication). Mice were anesthetized by placing them and a cotton ball with 1 ml ofMetofane (methoxyflurane) into a sealed ziplock bag (to keep Metofane fumes in bag). The bag was then lain aside to minimize stress for the mouse and the time the mouse struggles in the bag. The less agitated the mouse is in the bag the less time required for the metofane to take affect. The mouse was observed at all times to make sure the mouse did not position itself such that the cotton ball was in direct contact with its face, which might cause the mouse to have a severe reaction to the anesthesia After the animal stopped moving, the handlers waited one minute before removing the mouse from the bag. The animal typically remained anesthetized for 2-3 minutes once outside the bag. Each PMJM was PIT-tagged using a protocol successfully used by C. Meaney (personal communication). Each PMJM had a PIT-tag inserted above the shoulder blades by lifting the skin on its back and inserting the individually sterilized needle with the PIT-tag under their skin and injecting the tag. Verification of the PIT-tag identification number was made before and after insertion into the mouse by running the PIT-tag scanner across it. The skin behind the opening was then pinched to prevent emergence of the tag. PIT-tag identification number was recorded on the field data form. If, at any time during the handling of the PMJM the animal appeared to be severely stressed (dramatic changes in heartbeat, respiration and responsiveness or gums turning blue) first aid was administered and, once recovered, released without further processing. Genetic tissue sampling Genetic tissue samples were collected from the first 30 PMJM captured at each study site. The following protocol was used based on previous success with PMJM (M. Bakeman, C. Meaney, T. Ryon, R. Schorr, personal communication). A fresh pair of clean latex gloves were used to handle each mouse. With a clean ear punch tool, one tissue plug was obtained from each mouse ear. If there was excessive bleeding, gentle pressure was applied to the injured area for approximately one minute. Each ear plug was placed in a vial of 95% ethanol. Both the vial and the corresponding record on the data sheet were labeled with a unique identifier as follows. A seven-place alpha-numeric code was composed as follows: a three-letter designator for the survey location (e.g., MYT = Maytag Property); a number beginning with two digits •. . . -indicating the year-.(e.g., 98); followed by 2- digits specifying the individual trapped, numbered . . . . -~~quentt<J:lly,. fot e.~ample: MYT_980J ;= fir~t ari~al sampled,at Maytag ProP.~rty)~ J9~_8. �47 After returning from the field, all samples were put in a cool place or refrigerated until delivery to the CDOW office at 317 West Prospect, Fort Collins, CO where they are being held in the freezer for future analyses. Ear punch tools were cleaned after each use by immersing them in a 10% bleach solution for a few minutes, rinsing them thoroughly with clean water, and then dried thoroughly to prevent rusting. Dull ear punch were discarded and replaced with new sharp punches to ensure the quickest, cleanest cut possible. ' Demographic parameter estimation Mark-recapture estimation techniques were used to estimate abundance, over-summer survival, over-winter survival, temporary emigration, and immigration of marked animals back in to the three study populations of PMJM. Abundance: Abundance was estimated using Pollock's Robust Design (see Kendall et al. 1997, 1995 and Kendall and Nichols 1995 for detail) in Program MARK (White and Burnham 1999). The robust design is a combination of the Cormack-Jolly-Seber (CJS)(Cormack 1964, Jolly 1965, Seber 1965) live recapture model and the closed capture models. The key difference from the CJS model is that instead of just one capture occasion between survival intervals multiple capture occasions are used. These occasions are close together in time allowing the assumption that no mortality or emigration occurs during these short time intervals. The closely spaced encounter occasions are termed "trapping sessions" and each trapping session is viewed as a closed capture survey whereby abundance can be estimated. Three 7-day trapping sessions were conducted during the following weeks: June 2-9, 1998; July 21-28, 1998; and September 8-15, 1998. Abundance estimates were calculated for each trapping session. Survival: By using the estimate of the probability that an animal is captured at least once from the trapping sessions designed to estimate abundance, survival between the longer intervals was estimated. Analyses were conducted to estimate over-summer survival, and survival from June-July and August-September. A fourth 7-day trapping session to be conducted June 1-8, 1999 will provide information to estimate over-hibernation and annual survival. Temporary emigration and immigration: The longer intervals between trapping sessions also allows estimation of temporary emigration from the trapping area, and immigration of marked animals back to the trapping area using Pollock's Robust Design. Reproduction: Reproductive parameters were estimated by evaluating the reproductive status and age of captured PMJM. Results Trapping and PIT-tagging Effort A total of 186 tndividual PMJM were captured from the three study areas during the three 1998 trapping sessions ·(Table 1: 73 at Maytag Property, 77 at PineCliff Ranch, and 36 at Woodhouse Ranch). These mice were captured over three different trapping sessions with an effort of 17,330 trapnights. Every PMJM captured was PIT-tagged, providing each mouse with a unique, permanent, lifetime identification marker. Other small mammals captured during the trapping sessions included Peromyscus spp., Mexican wood rat (Neotoma mexicana), house mouse (Mus musculus), vole (Microtis spp.), western harvest mouse (Reithrodontomys megalotis), hispid pocket mouse (Chaetodipus hispidus), and shrew (Sorex spp.). House mice were captured at all three study areas during either June or September (Tables 2, 3). Species and relative numbers of captures within each of those species were similar for Maytag Property and PineCliffRanch (Tables 2,3). Species richness and relative number of captures between these sites were also similar in June and September with the exception of an increase in vole captures at both sites in September. Most of these common species were also captured at Woocihouse Rqnch during both June-::. and September 2,3). However, hispid pocket mice an_d.. . . . . . .. . ·... ·........ ··. .· . -~ ... •.. . . . . . ,-, . . (Taples . ' .. . ... : . ·. -· . . .- .. - ~- ... . . . . . . . ·• .., . : : ;.. �48 Mexican woodrats were also captured at Woodhouse Ranch and not at either of the other two sites. Numbers of house mice and vole captures at Woodhouse Ranch were greater than at either Maytag or PineCliff during June and September, with numbers of captures for both species increasing in the September trapping session (Tables 2,3). Age and Sex Ratios As expected, no juvenile PMJM were captured during the June trapping session as it was too soon after hibernation for any litters to have been born and/or if born the juveniles would still be restricted to their nests. Juvenile mice were captured during both the July and September trapping sessions at all three sites. Juveniles as small as I 0g were captured. Sex ratios may be biased towards males, however further analyses need to be completed to confirm this hypothesis (Table I). Genetic tissue sampling Genetic tissue samples were collected from 40 individual mice at Maytag, 30 mice at PineCliff Ranch, and 32 mice at Woodhouse Ranch. Additional samples were collected from four mice captured at a back drainage on the Woodhouse Ranch. Samples are currently being stored in the cooler at the CDOW Research Center in Fort Collins, Colorado. A Request for Proposals was submitted through the Colorado Department of Natural Resources. A committee is currently evaluating the three proposal that were submitted. Samples from these three populations will be used in studies to evaluate genetic uniqueness of PMJM populations. Abundance and Density Mark-recapture analysis methodologies were used to estimate abundance at each of the three study sites for each of the three trapping sessions (Table 4). Abundance estimates and length of the trapline were used to estimate an unadjusted density of mice per kilometer of stream stretch. Mice that typically don't use the area of stream stretch where the traps were placed could be trapped because they were attracted to the area by the artificial food source. Including these mice in the density estimates for the stream stretch covered by the trapline would artificially increase density estimates. Therefore, an adjustment was made to the density estimates. Locations of each individual mouse were classified as either within the stream stretch that was trapped or above or below the stream stretch where traps were placed. If greater than 50% oflocations of an individual mouse were off the trapline the mouse was categorized as an 'off-trapline' mouse; if less than or 50% of the locations were within the trapline the mouse was categorized as an 'on-trapline' mouse. The percent of off-line mice for each trapping session and each site was calculated and a mean adjustment parameter (p) estimated. This adjustment parameter is sensitive to the length of the trapline. The shorter the trapline the greater the adjustment would have to be. Regression models were run and AIC used to select the best regression model to estimate p by trapline length. These adjustment parameters are simply an estimated percent of mice that should be considered resident mice along the stream stretch where traps were placed. The density estimates were then decreased to percentage p. Use of the adjustment parameter provided a more realistic estimate of density of mice per kilometer of stream stretch. Without the adjustment densities would be inflated. •·.· ·•.·· ·:·_. -· Survival Survival rate was estimated using the mark-recapture estimator for Pollock's Robust Design in Program MARK. The best fitting model combined data from all three study sites over all three trapping sessions. Survival was estimated as 0.75 (se = 0.033) for a five week period. Extrapolating this survival rate across the summer results in an over-summer (June 1- October 5, 18 weeks) survival rate of 0.355 (se = 0.056). No estimates of over-winter survival can be made until trapping sessions .occur in S.ummer.19.99~-, ...,. . - . ·. . ;_-. <,_ ,.... • •__ .... , .... , . . ...•...,_ ... _: .• �49 Temporary emigration and immigration Temporary emigration rate and immigration was estimated using the mark-recapture estimator for Pollock's Robust Design in Program MARK. The best fitting model combined data from all three study sites over all three trapping sessions for these two parameters. Temporary emigration was estimated as 0.64 (se = 2.21), immigration was estimated as 0.45,, (se = 89.94). Reproduction No estimates of reproduction could be made. We located what we believed to be nest sites at several locations. We believe these sites to be nest locations with young because we followed radiocollared adult females (see Shenk and Sivert 1999) to these sites on numerous morning during breeding season. However, all sites were in very thick vegetation and we were not able to visually observe a nest with young. We felt it to be in the best interest of the mouse to not disturb the areas which might possibly cause failure of the nest. Discussion Information on the population dynamics of PMJM is necessary to determine which areas support viable populations. To begin to evaluate the viability of a population information on key demographic parameters must be obtained. Conducting studies on individually marked animals provides the greatest insight on the demography of a population. In general, estimated sex ratios from this study are comparable to those found by Armstrong et al. ( 1997) who reported an overall sex ratio for all captured PMJM of 51. 6 males: 48.4 females; approximately 86.0% of captures were identified as adults. There is a possible male sex bias at PineCliffRanch. However, small sample sizes and possible trapping biases by sex may explain the discrepancy. Density estimates were expected to increase as the summer progressed to account for the birth pulses in late June, and late July-August. This was the trend observed at Maytag. PMJM densities at Woodhouse Ranch increased from June to July but did not increase further during the September trapping session. Mean PMJM density over all sites and sessions was 40.5 (range 16.9-79.0) mice per kilometer of stream stretch. Highest densities occurred at PineCliff, where the vegetation is primarily willow and both a mainstem and tributary were used by mice. Lowest densities occurred at Woodhouse Ranch where the riparian vegetation has fewer willow but was dense with other riparian vegetation. Vegetation at Maytag provided some areas of dense willow with the remaining areas being of moderate density of riparian vegetation. The lower density of PMJM reported for Woodhouse Ranch might be explained by the composition and densities of other small mammals at that site. Woodhouse Ranch had the highest captures of both house mice and voles of the three sites studied. Defining summer as June 1 - October 5, over-summer survival was estimated as 0.36 (se = 0.056) over all three study sites. Meaney et al. (1999) report a one-month summer survival rate of 78%. Extrapolating Meaney et al.'s (1999) estimate over our summer period(~ four months) would result in a similar over-summer survival rate estimate of 36%. Prior to studies conducted in 1998 no information existed on survival rates for populations of Z. h. preblei although Whitaker (1963) reported a 67% loss of Z. hudsonius over hibernation. Temporary emigration and immigration rates were estimated but both had extremely high variances associated with those estimates. Thus these estimates cannot be used, with any confidence, to provide information on movements of mice into and out of these populations. Very little new information was gained during this study on reproductive parameters of PMJM. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia. However, we were unable to locate any breeding nests. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during .both the. Ju_ly .wd .S_eptember trappi1.1g sessions, .. Giv.e_n .t.h~t Jm~e.d.ing pea,k.s appe_~ to, 9.c_<;,UJ: to. .. . •. ·'···· -· •. . . . . . ·•. _.,, ... �50 early to mid-June and August with a possible third litter in September (Whitaker 1963) this was not unexpected and agrees with previous observations (Meaney et al. 1996, 1997, PTI 1996a, M. Bakeman unpublished data, T. Ryon unpublished data). This report includes results from only the first year of a multi-year project to follow individually marked PMJM through time. Collection of more data, and more_ years of data, will improve our ability to evaluate demographic parameters and estimates of how they vary across space and time. ... ·.· ..• Literatllre Cited Armstrong, D. M., M. E. Bakeman, A Deans, C. A Meaney, and T. R Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Bailey, B. 1929. Mammals of Sherburne County, Minnesota Journal ofMammalogy 10:153-164. Bailey, V. 1923. Mammals of the District of Columbia Proceedings of the Biological Society. Washington 36:103-138. Cook, T. D. and D. C. Campbell. 1979. Quasi-experimentation: design and analysis issues for field settings. Houghton-Mifflin, Boston. Cormack, RM. 1964. Estimates of survival from the sightings of marked animals. Biometrika 51:429-438. ERO Resources. 1995. Environmental review of South Boulder Creek Management Area Prepared for City of Boulder Real Estate/Open Space Department. Prepared by ERO Resources Crp., Denver, Colorado in association with Stoecker Ecological Consultants, Boulder, Colorado. Fitzgerald, J.P., C. A Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History, University Press of Colorado. Niwot, Colorado. Hafuer, D. J., K. E. Petersen, and T. L. Yates; 1981. Evolutionary relationships of jumping mice (genus Zapus) of the southwestern United States. Journal ofMammalogy 62:501-512. Hall, E. R 1981. The mammals ofNorth America John Wiley and Sons, Inc., New York, New York, 2 volumes. Hamilton, W. J., Jr. 1935. Habits of jumping mice. American Midland Naturalist 16:187-200. Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration stochastic model. Biometrika 52:225-247. Jones, C. A 1996. Mammals of the James John and Lake Dorothey State Wildlife Areas. Final Report, submitted to the Colorado Division of Wildlife and Colorado Natural Areas Program. Kendall, W. L., and J. D. Nichols. 1995. On the use of secondary capture-recapture samples to estimate temporary emigration and breeding proportions. Journal of Applied Statistics.22:751762. Kendall, W. L., K. H. Pollock, and C. Brownie. 1995. A likelihood-based approach to capturerecapture estimation of demographic parameters under the robust design. Biometrics 51 :293308. Kendall, W. L., J. D. Nichols, and J.E. Hines. 1997. Estimating temporary emigration using capturerecapture data with Pollock's robust design. Ecology 78:563-578. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum of Natural History 7:349-472. Meaney, C. A, N. W. Clippinger, A Deans, and M. OShea-Stone. 1996. Second year survey for Preble's rrieadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A, A Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. . ._., .-. Report.pre,paredfor.theColorado.piyisiooofW.ildlife.... .. : . .., ,,. .- . . . ...._.. , .. .. . . .: . . . : · . ... ..•· . ·- .~ •. ~ ,• .. : �51 Meaney, C. A., A. Ruggles, B. Lubow, N. W. Clippinger, and A. Deans. 1999. Preliminary results: Second year study of the impact of trails on small mammals and population estimates for Preble's meadow jumping mice on City of Boulder Open Space. Report for Greenways Program, City of Boulder Transportation Department, City of Boulder Open Space, and Environmental Protection Agency, Region 8. . Nudds, T. D. 1977. Quantifying the vegetative structure ofwildllfe cover. Wildlife Society Bulletin 5:113-117. Poly, W. J., and C. E. Boucher. 1997. Record of a creek chub preying on a jumping mouse in Bruffey Creek, West Virginia Brimleyana 24: 29-32. PTI Environmental Services. 1996a Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. PTI Environmental Services. 1996b. Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Spring 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, Zapus hudsonius. Ecological Monographs 21:61-95. Riggs, L. A., J. M. Dempey, and C. Orrego. 1997. Evaluating distinctness and evolutionary significance of Preble's meadow jumping mouse: Phylogeography of mitochondrial DNA noncoding region variation. Final Report for the Colorado Division of Wildlife. Denver, Colorado. Seber, G. A. F. 1965. A note on the multiple recapture census. Biometrika 52:249-259. Sheldon, C. 1934. Studies on the life histories of Zapus and Napaeozapus in Nova Scotia Journal of Mammalogy 15:290-300. Shenk, T. M. 1998. Conservation assessment and preliminary conservation strategy for Preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife FY199798 Annual Report. Shenk, T. M. and Sivert M. 1999. Movement patterns of Preble's meadow jumping mouse (Zapus hudsonius preblei) as they vary across time and space. Colorado Division of Wildlife January - March 1999 Quarterly Report. Stohlgren,T. J., M. B. Falkner, and L. D. Schell. 1995. A Modified-Whittaker nested vegetation sampling method. Vegetatio 117:113-121. USFWS. 1997. Interim survey guidelines for Preble's meadow jumping mouse. USFWS. Denver, Colorado. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. . .-:- • • •· !.. • . . ~. .. . ·.• • . . -··: . .... .. ··. :· .. · ..... ·-· ···:· ·._: .... :- ... -.~ .· -. . . �52 Table 1. Number of Preble's meadow jumping mice PIT-tagged and captured at each of the three study sites for each of the three trapping sessions. Trapping effort is recorded as number of trap nights for each session at each site. # Capturedt # PIT-tagged Site Trapping session Trap nights Female Male Unknown Total Female(%) Male(%) Total Maytag Jun 1949 9 5 0 14 9 (64) 5 (36) 14 Maytag Jul 2370 13 13 0 26 15 (54) 13 (46) 28 Maytag Sep 3256 12 20 1 33 18 (43) 24 (57) 42 PineClitf Jun 1095 6 13 0 19 6 (32) 13 (68) 19 PineClitf Jul 1603 7 8 0 15 8 (50) 8 (50) 16 PineClitf Sep 1544 12 31 0 43 13 (28) 33(72) 46 Woodhouse Jun 1525 4 3 0 7 4 (57) 3 (43) 7 Woodhouse Jul 2420 8 5 0 13 9 (64) 5(36) 14 Woodhouse Sep 1568 6 9 1 16 8 (44) IO (56) 18 17330 77 107 2 186 90 114 204 TOTALS t Some captured animals were PIT-tagged during previous trapping sessions Table 2. Number of other small mammal species captured during the June 1998 trapping session at Maytag ProEerty, PineCliffRanch, and Woodhouse Ranch. Peromyscus Date Site seeMaytag 27 Jun2 42 Jun 3 Maytag Jun4 Maytag 48 Jun 5 Maytag 34 53 Jun 7 Maytag Jun 8 Maytag 39 Maytag 41 Jun 11 Maytag 45 Jun 12 _ 36 Jun 13 Maytag Jun2 Pine Cliff 36 Jun 3 Pine Cliff Jun 4 Pine Cliff 39 Jun 5 Pine Cliff 34 22 Jun 7 Pine Cliff Jun8 Pine Cliff 35 Woodhouse 13 Jun2 Woodhouse 23 Jun 3 Woodhouse 21 Jun4 Woodhouse 12 Jun 5 Woodhouse 13 Jun 7 Woodhouse 18 Jun 8 Jun 14 Woodhouse 16 • )u;i"15· •• Woodhouse ·s . ..~. ..... ;- .... -. •. ·-· '·.• Reithrodontomys Chaetodipus megalotis hispidus Microtis Harvest mice 4 1 0 2 2 2 0 0 6 3 0 0 0 I 4 o· • Hispid pocket mice 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 1 0 0 ff .... : . . spp. voles 0 0 0 2 4 0 Sorex spp. shrews 0 0 4 3 0 0 0 2 0 7 0 2 5 7 3 9 14 6 _.... ·. .. ••.. ··· 0 0 0 0 I 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Mus Zapus Neatoma muscu/us hudsonius mexicana House preblei Mexican mice PMJM woodrat 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 IO 3 5 4 3 3 5 5 0 0 0 _....... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 I 4 2 6 3 3 0 -.· .•...- ··- • •. () .• ::.- . . .~ '! • �53 Table 3. Number of other small mammal species captured during the September 1998 trapping session at Maytag ProEerty, PineCliffRanch, and Woodhouse Ranch. ReithroPero- dontomys Chaetodipus Mus myscus megalotis hispidus Microtis Sorex musculus ,·' Hispid house spp. harvest spp. spp. Date Site mice pocket mice voles shrews mice Sep9 Maytag 30 0 0 0 5 1 Maytag 39 Sep 10 0 0 4 0 1 Sep 11 Maytag 35 4 0 4 0 0 Sep 12 Maytag 35 6 0 8 0 0 31 Sep 13 Maytag 0 0 10 2 Sep 14 Maytag 30 3 0 9 2 0 Maytag Sep 15 36 2 0 17 2 2 Sep 16 Maytag 31 3 0 16 1 0 Sep9 Pinecliff 15 0 2 0 0 19 Sep 10 Pinecliff 0 0 4 0 Sep 11 Pinecliff 16 0 0 7 1 0 Sep 12 Pinecliff 21 0 0 7 0 0 Sep 13 Pinecliff 18 0 0 II 0 0 Sep 14 Pinecliff 17 0 0 8 0 0 Sep 15 Pinecliff 16 0 0 12 0 Sep 16 Pinecliff 22 0 0 16 1 0 Sep9 Woodhouse 15 0 1 47 2 7 Woodhouse 15 Sep 10 0 0 60 15 Sep 11 Woodhouse 18 70 0 0 21 Sep 12 Woodhouse 18 0 73 2 18 Sep 13 Woodhouse 13 0 67 0 13 Sep 14 Woodhouse 19 0 2 80 0 15 17 Sep 15 Woodhouse 0 3 73 2 14 Zapus hudsonius preb/ei PMJM 12 19 11 8 8 11 9 8 11 8 13 7 12 8 7 14 7 7 6 6 3 Neatoma mexicana Mexican woodrat 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 Table 4. Stream reach abundance (N) and density estimates for Preble's meadow jumping mouse (PMJM) from three sites in Douglas County, Colorado for three trapping sessions. Both adjusted and unadjusted density estimates (PMJM per km of stream stretch) are reported. Adjustments were made to the density estimates to account for the EOSitive bias introduced when animals are attracted to a traEline. Trapping session ii Maytag Jun 18 Maytag Jul 31 Maytag Sep 44 PineCliff Jun PineCliff Lower Upper (m) 2.7 15 21 550 32.7 0.80 26.0 11.4 20 42 608 51.0 0.81 41.4 1.8 42 46 494 89.l 0.78 69.3 30 5.7 24 36 490 61.2 0.78 47.5 Jul 17 0.9 16 18 504 33.7 0.78 26.3 PineCliff Sep 51 3.3 48 54 504 101.2 0.78 79.0 Woodhouse Jun 11 3.8 7 15 510 21.6 0.78 16.9 Woodhouse Jul 20 5.2 15 25 516 38.8 0.79 30.4 Woodhouse Se_Il ]7 2J ~74 J4.8 Q,8Q 20 . . se(N) :-.-·· __3.1 ... ·. Trapline Length Adjusted Density Unadjusted Density (PMJM/km) Site .... ; •·.- ... -_ .. 95% Confidence Interval p (PMJM/ km) 28 ....... -·- . �1 Colorado Division of Wildlife Wildlife Research Annual Report July 2000 JOB PROGRESS REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Program Work Package No. --~0'""""6-"-6=-2_ _ _ _ __ Preble's Meadow Jumping Mouse Conservation - Task No. Develop Conservation Plan for Preble's Meadow Jumping Mouse 1 Period Covered: July 1, 1999 - June 30, 2000 Author: Tanya M. Shenk and Gary C. White --------------------------- ABSTRACT The second field season of a three year study on the demography and movement patterns of Prebles meadow jumping mouse (Zapus hudsonius preblei) was completed. A total of 175 individual mice were captured on stream-side transects at three study sites (60 mice at Maytag Property, 60 mice at PineCliff Ranch, and 55 mice at Woodhouse Ranch) during the 1999 field season. These captures included 34 mice PIT-tagged in 1998 (14 at Maytag Property, 12 at PineCli:ffRanch, and 8 at Woodhouse Ranch). These mice were captured over three different trapping sessions with an effort of 19,222 trap-nights. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia. We were able to locate one potential maternal nest. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during both the July and September trapping sessions. Natural mortality factors documented during both years include predation by house cats, garter snakes, rattlesnakes, yellow-bellied racers, bullfrogs, weasel, and fox as well as accidents by drowning and ro.µl kill. In 1999 mice were also found in torpor throughout the summer, often in very exposed areas frequently resulting in death by either exposure or predation. Preliminary analysis of the movement data collected on radio-collared PMJM in 1999 support results found in 1998. In particular we were able to document again in this second field season that PMJM exhibit (1) greater use of upland habitats than previously assumed, (2) general site :fidelity to both daytin1e nesting sites and nighttime feeding sites, (3) seasonal shifts in movement patterns, and (4) use of both perennial and intermittent tributaries adjacent to the capture drainage. Detail~ vegetation maps for all three study sites were created th:-ough intensive field mapping. These maps will be used in conjunction with the movement data to further refine habitat use information. Thirteen possible hibernacula were located in 1999. Tirree sites were located at Woodhouse Ranch and ten possible hibernacula at Pine Cliff Ranch. In contrast to 1998 data, these potential hibernation sites were located closer to the stream. However, at both Pine Cliff and Woodhouse Ranches stream banks rise out of the floodplain in closer proximity to the stream than at Maytag Property where the potential hibernation sites located in 1998 were located long distances from the stream center. Vegetation characteristics of the 21 sites located during both 1998 and 1999 are similar to �2 other hibernacula described for PMJM. By cooperating with other researchers PMJM densities (mice/km of stream) were estimated from nine study areas during June 1998 and June 1999, providing a total of 15 study area x year combinations. With these limited data available, 68% of the variation in PMJM density was explained by a model that includes riparian shrub and tree cover (ha/km stream). These results suggest that habitat quality of PMJM can be predicted by the riparian shrub and tree cover available on a site. Preliminary results from the demography, movement and distribution studies of PMJM have suggested the need to continue with research questions currently being addressed. However, the preliminary results also suggest further research be conducted on (1) use of upland and riparian habitat by PMJM, (2) refining water requirements of PMJM (i.e., do they require stream habitat or are wetland areas sufficient?), (3) range-wide distributional boundaries (e.g., elevation restrictions), and (4) investigating areas of potential syrnpatry or hibridization with the western jumping mouse (Z. princeps). The demography and movement studies were modified for the summer 2000 field season to further investigate upland use and water requirements, including a habitat modification experiment. This report includes results from the first two years of a multi-year project to follow individually marked PMJM through time. Collection of more data, and more years of data, will improve our ability to evaluate demographic parameters, movement patterns, and habitat use and evaluate how they vary across space and time. �3 DEVELOP CONSERVATION PLAN FOR PREBLE'S MEADOW JUMPING MOUSE Tanya M. Shenk an" Gary C. White P. N. OBJECTIVE Conservation of Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. SEGMENT OBJECTIVES FY99-00 1. Estimate abundance, over-summer survival, annual survival, and population age and sex structure of Preble's meadow jumping mouse at three study sites. 2.. Evaluate movement data of Preble's meadow jumping mouse as it relates to landscape features at three study sites. 3. Refine and prioritize needed research components to develop sound strategies for conservation of Preble's meadow jumping mouse. 4. Develop study plan to evaluate meta-population dynamics in Preble's meadow jumping mouse (to be funded in FY00-01). 5. Prepare a Federal Aid Job Progress Report. PERFORMANCE INDICATORS FY99-00 1. 2. 3. 4. Second year survival rate estimates for three populations of PMJM. Second year abundance and density estimates for three populations of PMJM. Second year movement patterns for three populations of PMJM. Study plan for PMJM meta-population study. INTRODUCTION On May 12, 1998 the U.S. Fish and Wildlife Service (USFWS) published a final rule in the Federal Register (63 FR 26517) to list Preble's meadow jumping mouse (Zapus hudsonius preblei) as 'threatened' under the Federal Endangered Species Act (ESA) of 1973, as amended. Recovery goals for Preble's meadow jumping mouse (PMJM) should work towards the sustainability;. protection, and restoration of Z. h. preblei populations and habitats on both private and public lands to provide the spatial, genetic, and demographic structure needed to promote long-term species viability and provide species management flexibility. Recovery efforts for the subspecies will be most effective if reliable information is available on the basic ecology of the subspecies and this information used tc.> design recovery efforts such as Habitat Conservation Plans. A review of studies conducted on PMJM shows that there is insufficient information to fully address defining-range-wide ecological requirements, limiting factors, limits of species tolerance, or population status (Shenk 1998). Most work to date has focused on geographic distribution (presence or absence of Z. h. preblei), taxonomy, and habitat descriptions of sites where mice have and have not been captured. For PMJM in particular, information on dispersal, habitat use, and population dynamics is most needed to identify minimal ecological requirements of the subspecies. Monitoring, by way of estimating demographic parameters (such as survival, abundance, and reproduction), of a single population over time provides an opportunity to document demography of a �4 species, estimate temporal fluctuations in demography, and gain insights into the temporal variation inherent in demographic parameters. Monitoring of multiple populations over time and over multiple geographic locations provides the opportunity to gain further understanding of population processes and detaches time effects from spatial e:f;fects. Population monitoring activities do not constitute scientific experiments, in the spirit of manipulation of salient ecological variables, however, replication of monitoring activities for natural populations over long periods of time and in diverse geographic locations can lead to insights into population processes (Cook and Campbell 1979). These insights can then be translated into hypotheses useful for predicting changes in population demography resulting from either natural perturbations (e.g., flooding events) or anthropogenic modifications (e.g., gravel mining). Experimentation would then be required to test these hypotheses and establish cause and effect. Movement and dispersal pattern information will be key to any conservation strategy designed for PMJM. Documenting daily and seasonal movement patterns of PMJM will provide information on habitats used by the mice and on the relative configuration and juxtaposition of these habitats. Configuration of habitats include vegetation and size of the areas used. Juxtaposition includes relative locations of different habitats used such as nest sites, feeding areas, and movement corridors connecting those areas. Key dispersal factors to document for PMJM include (1) which segment of the population disperses, (2) when do they disperse, (3) through what habitat do they disperse, (4) how far will individuals disperse (i.e., what is the maximum distance that separates adjacent populations) and (5) how critical is dispersal (both into and out of a population) to the persistence of a given population. Areas of suitable habitat must provide requirements to survive throughout the life cycle. These requirements must provide necessities for both the active period and hibernation periods. During the active period suitable habitat must provide requirements for daily survival, reproductive activities (breeding, nesting, and rearing of young to independence), and dispersal. The hibernation period requires sufficient food supplies to assure fat storage prior to hibernation and suitable hibernacula. Habitat providing all seasonal and life cycle requirements may or may not occur in a single contiguous area. If not in a contiguous area, habitat patches must occur in a mosaic of usable areas where suitable corridors exist for seasonal movement among sites. The habitat matrix within the range of Z. h. preblei is mixed grasslands_adjacent to the Colorado Front Range along the Piedmont and along the base of the Laramie Mountains in Wyoming and extends to the Colorado plains. Within this matrix, PMJM occur along stream drainages that contain patches of suitable vegetation. Suitable habitat appears to have at least two major compop.ents. The first component is a supply of open water, at least in part of the active season. Secondly, areas where PMJM has been found have dense cover. Based on studies of Z. h. preblei and Z. hudsonius elsewhere, Z. h. preblei apparently occurs mostly in undergrowth consisting of grasses, forbs, or both in open wet meadows and riparian corridors, or where tall shrubs and low trees form an overstory and provide adequate cover (Armstrong et al. 1997). Meadow jumping mice are widespread in abandoned grassy fields, but are often more abundant in thick vegetation along ponds, streams, and marshes or in rank herbaceous vegetation of wooded areas (Whitaker 1963). The mouse does not appear to have an affinity toward any single plant species but instead favors sites that are structurally diverse and provide adequate cover and food throughout its life cycle. PMJM are typically not found in upland areas away from riparian habitats but are most often captured where either ground water becomes visible as either seep springs or as main water channels (M. Bakeman, T. Ryon, personal communication) suggesting a dependence on open water, at least during their active periods. PMJM have been trapped in natural riparian areas as well as areas altered by anthropogenic influence including ditches and wetlands adjacent to interstate highways, cement-lined ditches with tall cover, ditches along driveways and moderate road. use, and moderate cattle grazing. If PMJM occurs as metapopulations in the classical sense of a set of local populations linked by infrequent dispersal then habitat includes not just one area of suitable habitation but also areas suitable for nearby mouse populations. These suitable areas must also be linked by dispersal habitat. If the mice are �5 dependent on dense riparian habitat for dispersal as well as for areas to reproduce, persistence of discrete populations would require a mosaic of suitable discrete riparian patches interconnected with dispersal corridors of similarly dense riparian vegetation. If mouse populations function in a source (populations where growth rate~ 1) and sink (those populations where growth rate< 1, maintained through immigration) system, it will be critical to identify and protect those populations serving as sources. Thus, for a source-sink population critical habitat will include those areas that support source population, dispersal habitat to sink areas will be less critical. If local mouse populations are functionally discrete, such a mosaic of interconnected areas of suitable habitat would provide a buffer for local, and source, populations against deleterious stochastic events by providing the opportunity for local population failures to be 'rescued' by immigration from other populations. The primary objective of this study is to investigate spatial and temporal variation in the demography and movement patterns of PMJM. Demographic parameters to be estimated include survival, reproduction, temporary emigration, immigration, population structure, and density. These demographic parameters will be estimated from individually marked animals from geographically distinct populations. To evaluate spatial differences in the demography of PMJM, populations were selected from three sites that provided a variety of habitat matrices available to the mouse. To begin to understand PMJM movement, dispersal, and habitat use we monitored radio-collared mice at three different study areas .. Study areas were selected to cover a variety of habitat configurations to evaluate spatial variation: in movement patterns of PMJM. Multiple years of conducting the study at those same sites will provide an estimate of the temporal variation in demography and movement patterns of PMJM. STUDY SITES Demography and movement patterns of PMJM are being evaluated for three populations. All three populations selected were located in areas where PMJM had previously been found. To evaluate spatial differences in the demography and movement patterns of PMJM, populations were selected on sites that provided a variety of habitat matrices available to the mouse. The first site selected, Colorado Division of Wildlife (CDOW) Maytag Property, has one primary water source available to the mouse. This water source is East Plum Creek. The second site, PineCliff Ranch, provides both a tributary (Garber Creek) and a main stem drainage (West Plum Creek). This provided the opportunity to investigate whether PMJM will use upland areas to move from one drainage to another or if they are restricted to only moving along riparian corridors. The third study site, CDOW Woodhouse Ranch provides an area containing a tributary (Indian Creek) and a series of ponds and irrigation ditches scattered throughout the property. The configuration at Woodhouse Ranch provided an even greater opportunity to investigate how much the mice use upland areas or if they restrict their movements strictly to riparian corridors. By replicating the same methodologies at each of these three unique habitat matrices we can begin to estimate spatial variation in nightly and seasonai movements of PMJM. • ,, OBJECTIVES Objectives of the demography study are to: 1. Estimate abundance and density of PMJM for each of three study populations. 2. Estimate over-summer, over-winter, and annual survival of PMJM at each of three study populations. 3. Estimate temporary emigration of PMJM at each of three study populations. 4. Estimate immigration of marked PMJM back into each of three study populations. 5. Estimate reproduction of PMJM at each of three study populations. 6. Evaluate the affect of weight, sex, age, abundance (i.e., density dependent response), and habitat features such as stream reach, vegetation composition and density on survival, reproduction, abundance, temporary emigration, and immigration of marked animals back into three study populations of PMJM. �6 7. Estimate age and sex ratios of PMJM at each of three study populations. The PMJM movement study is designed to describe nightly and seasonal movement patterns of PMJM and to describe habitats used by PMJM. These movement patterns will be described for three different study areas to evaluate spatial variation, and over three different years at the same three study areas to evaluate temporal variation. Specific objectives include: 1. Describe nightly movements of PMJM. Evaluate difference in nightly movements as they relate to sex, age, and habitat available to the animals. 2. Describe 30-day (or life of the radio transmitter) interval movements of PMJM. Evaluate difference in 30-day (or life of the radio transmitter) interval movements as they relate to sex, age, and habitat available to the animals. 3. Describe seasonal movements of PMJM. Evaluate difference in seasonal movements as they relate to sex, age, and habitat available to the animals. 4. Describe habitats where mice occur: movement corridors, end point descriptions (i.e., movement from what to what), and landscape features (connectivity with other riparian areas and other habitats used). 5. Estimate the mean amount of time PMJM spend in each available habitat. 6. Evaluate spatial and temporal variation in movement patterns of PMJM. The objective of the habitat use study is to identify and refine habitat requirements of Z. h. preblei, including hibernation sites, and to determine if they influenced any of the demographic parameters that will be estimated in this and complementary studies (see Shenk and Sivert 1999a, 1999b). METHODS See Shenk and Sivert (1999a, 1999b) for field methods. RESULTS Demography Study Trapping and PJT-tagging Effort A total of 186 individual PMJM were captured from the three study areas during the three 1998 trapping sessions (fable 1: 73 at Maytag Property, 77 at PineCliffRanch, and 36 at Woodhouse Ranch). These mice were captured over three different trapping sessions with an effort of 17,330 trap-nights. Every PMJM captured was PIT-tagged, providing each mouse with a unique, permanent, life-time identification marker. A total of 175 individual mice were captured on stream-side transects at three study sites during the 1999 field season including 34 mice PIT-tagged in 1998 (fable 1). These mice were captured over three different trapping sessions with an effort of 19,222 trap-nights. Other small mammals captured during the trapping sessions included Peromyscus spp., Mexican wood rat (Neotoma mericana), house mouse (Mus musculus), vole (Microtis spp.), western harvest mouse (Reithrodontomys megalotis), hispid pocket mouse (Chaetodipus hispidus), and shrew (Sorex spp.). See Shenk and Sivert (1999a) for details of 1998 field season. Reproduction During both 1998 and 1999, most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia. We were able to locate one potential maternal nest in 1999. Juvenile mice were not captured during either June trapping sessions. Juvenile mice were captured at all three sites during both the July and September trapping sessions in both years. No estimates of reproduction could be made. �7 Survival Survival rate was estimated using the mark-recapture estimator for Pollock's Robust Design (see Kendall et al. 1995, 1997 and Kendall and Nichols 1995 for detail) in Program MARK (White and Burnham 1999). The robust design is a combination of the Cormack-Jolly-Seber (CJS)(Cormack 1964, Jolly 1965, Seber 1965) live recapture model and the closed capture models. The best fitting model combined data from all three study sites over all three trapping sessions in 1998. Survival was estimated as 0. 75 (se = 0.033) for a five week period in 1998. Extrapolating this survival rate across the summer results in an over-summer (June 1- October 5, 18 weeks) survival rate of 0355 (se = 0.056). No estimates of over-winter or summer survival in 1999 have been completed. Temporary emigration and immigration Temporary emigration rate and immigration was estimated using the mark-recapture estimator for Pollock's Robust Design in Program MARK. The best fitting model combined data from all three study sites over all three trapping sessions for these two parameters. Temporary emigration was estimated as 0.64 (se = 2.21), immigration was estimated as 0.45 (se = 89.94). Age and Sex Ratios As expected, no juvenile PMJM were captured during either June trapping session as it was too soon after hibernation for any litters to have been born and/or if born the juveniles would still be restricted to their nests. Juvenile mice were captured during both the July and September trapping sessions at all three sites in both years. Juveniles as small as 10g were captured. Sex ratios may be biased towards males, however further analyses need to be completed to confirm this hypothesis (Table 1). Density ,., Mark-recapture analysis was used to estimate abundance ( N) at each of the three study sites (Maytag Property, Woodhouse Ranch, and Pine Cliff Ranch) for each of the three trapping sessions in 1998 and for June 1999 (Table 2) using Program MARK (White and Burnham 1999) and Program CAPTURE (Otis et al. 1978, White et al. 1981). These abundance estimates and length of the trapline were used to estimate an unadjusted density of mice per kilometer of stream stretch. However, mice that typically don't use the area of stream stretch where the traps were placed could be· trapped because they were attracted to the area by the artificial food source. Including these mice in the density estimates for the stream stretch covered by the trapline would artificially increase density estimates. Therefore, an adjustment parameter was estimated to calibrate density estimates for a more realistic estimate of PMJM per kilometer of stream length. Without the adjustment densities would be inflated. In collaboration with other PMJM researchers (M. Bakeman, C. Meaney, T. Ryon, and R. Schorr) population estimates ( N) for a specified length of stream were determined with capture-r~pture techniques using Program MARK (White and Burnham 1999) and Program CAPTURE (Otis et al. 1978, White et al. 1981) for nine study areas over two years for early season trapping (June) only. To make these estimates comparable across study areas with unequal lengths of stream reaches trapped, mouse density (mice/km of stream) must be computed. However, traps tend to attract mice from some unknown distance, so that naive density estimate of N divided by stream length is biased high. To remove this bias, radio-tracking data were used to estimate the proportion of tiine (p) radio-collared mice spent within the original trapline once the traps were removed. Data from six study areas (Table 3) provided by this study and the study conducted by T. Ryon at Rocky Flats were used to estimate this correction factor (p) for population estimates from linear traplines or grids. Only these study areas had radio-collared mice available from which to estimate the correction factor. Corrections were applied to all study areas with the function relatingp to trapliri.e length (L) developed from these data. �8 The Michaelis-Menton model was fit to the observed p value: L; P; = - - - L;+2BSW where L; is the length of the trapline for grid i. Nonlinear least squares were used to minimize the sum of squared E; values to obtain an estimate of the unknown parameter, BSW (i.e., boundary strip width). Observations were weighted by the number of radi~llared mice providing the observed value of pi. Because the variance of a proportion is a function of the value of the proportion, a logistic transformation was used to stabilize the variances of the E; across the range of the P; values: Li + 2BSW Li 1 - ----Li + 2BSW Predicted values ofp (p) are obtained from either fitted model for a particular trap line length (L) by substituting the estimate of BSW into the predictive equation: A L p = L + 2BSW. Estimates of BSW for the two estimation methods are shown in Table 4, predicted values are shown in Table 3, and the fit of the two fitted equations is shown in Figure 1. The parameter estimate from the logistic transformation model was used to correct the population estimates, i.e., A L p=-----. L + 2x4I.5446 This model was preferred because of the variance stabilization provided by the logistic transformation. However, as shown in Figure 1, the difference in the predictions of the two fitted equations is not biologically important. To obtain an adjusted number of mice on a trapline or trapping grid, the estimated population on the grid (N) from mark-recapture estimation is multiplied by the correction (ft) from the above equation to give the adjusted number: The variance of Nadj is computed as the variance of a product using the delta method: �9 where var(p) = 4L 2 var(BSW) . (L + 2BSW)4 Similarly, density (mice per unit of length of stream) is computed. as the adjusted. population size divided by the length of the trapline or the original trapline or grid population estimate over the adjusted. length of the trapline: ·" Nadj N L L + 2BSW D=--=---- The variance of D is computed. using the delta method: D = var(Naqj) = _ _ _ 1 ___-var(N) + N2 var(BSW) . 2 4 2 L (L + 2 *BSW) (L + 2 *BSW) A Note that Var(BSW) = SE(BSW)2 with SE(BSW) given in Table 4. •As an example of the variance of p, a trapline length of 500m results in SE(p) = Jvar(p) = 0.02696. Confidence intervals on the fitted function of pare shown in Figure 2, computed. as ft±l.96xSE(p). An alternative approach to computing-confidence intervals on p that we would have thought would work better than the ±1.96SE(p) intervals shown in Figure 2 is to compute the confidence interval on the logit(p), and then back.;.transform the interval endpoints: 1 1 1 + exp(-(Iogit(p) - 1.96SE(logit(p))]' 1 + exp(-Vogit(p) + 1.96SEQogit(p))] where SE(logit(p)) = SE(BSW) = 9.1676/41.5446 = 0.22067 for the data presented. here. After BSW • -· computing confidence intervals by both methods, the results were only negligibly different, with the •· maximum difference in the interval lengths being only 0.00111 over the range of L from 100 to 2000m. Riparian Vegetation Cover Data 1'.otal area of riparian shrubs,trees, herbaceous cover, non-vegetated, and open water were computed for each $tlldy area from riparian vegetation maps (fable 5). These riparian maps were developed from photo interpretation of infrared aerial photography at a resolution of 1:24,000. Areas of riparian vegetation were calculated when patches of vegetation were greater than 24 m wide. To estimate area of each riparian vegetation classification for each study area, stream length for each study area was delineated on the riparian vegetation map. A 200-m buffer was then generated on either si~ of the study area stream reach. Within this 200-m buffer total area (ha) of patches with dominant vegetation classified as riparian �herbaceous, riparian shrub, riparian tree, non-vegetated, and open water were calculated using Arcinfo (ESRI 1987). No ground truthing of vegetation classification was performed. Statistical Analysis ofPMJM Density and Riparian Vegetation Cover The adjusted density and areas of riparian vegetative cover per km of stream (fable 5) were used to assess the relationship between PMJM density (mice/km of stream) and riparian vegetation cover. Estimates for multiple years for study areas were treated as separate estimates so that the year-to-year variation in PMJM density could be evaluated. An AN OVA of PMJM density for study area and year effects suggested no differences between years (1998: = 35.08, SE= 8.85; 1999: = 31.04, SE= 6.29; P = 0.511) or across study areas (P = 0.245). The variation in PMJM density across study areas is what we want to ex.plain with riparian vegetation cover differences across study areas. Individually, none of the vegetation cover variables were important predictors of PMJM density (fable 6). When model selection following Burnham and Anderson (1998) was performed across all models involving the riparian shrub, tree, herbaceous, non-vegetated, and open water cover (ha/km stream ) variables, the best AICc model was shrub and tree cover (fable 7) ex.plaining 68% of the variation in PMJM density. The next best model included open water as well as shrub and tree cover, explaining 71 % of the variation of PMJM density. The combination of riparian shrub and tree cover appears to be an important set of predictors for PMJM density based on the study areas included in this analysis. The parameter estimates for the best AICc model are shown in Table 8, and a residual plot in Figure 3. All riparian vegetation cover variables have positive slope parameters, indicating a positive influence on PMJM density over the range of the vegetation cover variables considered in this analysis. x x Movement Study Radio-tracking effort . A total of 125 radio-collars were put on mice over the three trapping sessions in summer 1998 (fable 9: 48 at Maytag Property, 47 at PineCli:ffRanch, and 30 at Woodhouse Ranch). A total of 62 females and 63 males were radio-collared over the 1998 field season. A total of 138 radio-collars were put on mice over the three trapping sessions in summer 1999 (fable 9: 51 at Maytag Property, 52 at PineCliffRanch, and 35 at Woodhouse Ranch). A total of 57 females and 81 males were radio-collared and tracked in 1999. Daily movements The general daily movement pattern throughout the active season was for mice to become active at dusk, remain active through the night, and to return to a day nest location at dawn. Most of our tracking was confined to night time movements; however we did make a greater effort in 1999 to confirm the mice were primarily in day nests during daylight hours. This was true for most daytime observations, however on occasion mice were active in the daytime as well. Percent of PMJM locations, as determined from radio-tracking, at each of three distance categories were calculated for each study site and the latter two radio-tracking sessions in 1998 (see Shenk and Sivert 1999b for details). The majority oflocations at Maytag, PineCliff: and Woodhouse were within 46m of stream center for both tracking periods (July-August and September-October). For all areas and tracking periods except Maytag during the last tracking session, 90% of PMJM movements were within 9 lm of either side of the center of the capture drainage. Mouse movements at Maytag during September-October resulted in 32.6% of the locations being> 91m from the stream center. Similar patterns were observed for 1999. • During nigh.time activity periods more than one mouse would often be found foraging in the same area. These foraging areas were often the same areas used by the same mice on numerous consecutive nights �11 Seasonal movement Field methods used in June 1998 did not allow us to document accurate June movement patterns for that year. The distribution of mouse locations in 1998 at Maytag Property for the July-August tracking session is different from the distribution of PMJM locations for the September-October tracking session. In 1998, the pattern shifted from heavy use along East Plum Creek to the north of the trapline to a more concentrated distribution either side of the trapline. The more concentrated use of the areas east and west of the trapline also resulted in locations being further from the center of the creek. The northern end of the trapline is largely vegetated by willows with the remainder of the trapline more diversely vegetated. In 1999 we were able to document movements for all three tracking sessions. Greatest movement away from the center of the stream occurred in the August session. In 1998, mouse movements were more concentrated along the drainages at PineCliff Ranch during the September-October tracking sessions than during the July-August tracking sessions. Vegetation along both West Plum Creek and Garber Creek along the trapline was primarily willow. In 1999, greatest movements from either stream center were documented during the August tracking session. At Woodhouse Ranch, the distribution of mouse locations also shifted between tracking sessions. Mouse movements during June 1999 were the most diverse of all tracking sessions. Mouse movements were more concentrated along the southern half of the trapline in September-October as compared to the more even distribution of mouse locations recorded for July-August in both 1998 and 1999. The northern end of the trapline is dominated by willows, the middle and southern end of the trapline is in more diverse riparian habitat. In September 1999 we had fewer mice radio-collared at each of the three sites because we were not able to trap mice. We assume the majority of the mice had already hibernated by the time we started our last trapping effort on September 9, 1999. Over the two-year study, 27 PMJM were captured, radio-collared, and tracked for more than one tracking session (fable 10) . Other mice were captured during more than one trapping session but radio collars were not replaced either because all the radio collars had been put on other mice or because the physical condition of the animal was such that we decided not to replace the radio-collar. Such conditions included mice who had significant hair worn off the neck from the previous radio collar. In no incidence did we find open wounds caused by radio collars. Of the 27 mice radio-collared for more than one session, we have only analyzed the mice captured in 1998. Of those, four provided information to evaluate seasonal changes in areas and habitats use between the July-August tracking period and the September-October tracking period: One mouse, a male from Maytag was observed only once during the September-October tracking session, providing no information concerning seasonal changes in movement patterns. Thus, changes in areas used by individual mice between June and either the July-August or September-October tracking session are not summarized here. A female at Maytag exhibited a seasonal movement shift, small sample size prohibited any evaluation of the movement patterns of the Maytag male (n = 1 in September-October). There does not appear to be any shift in areas used by the male tracked during both latter sessions at Pine Cliff Ranch, however, sample sizes were small (n = 17, 14). Two females at Woodhouse Ranch exhibited a shift in areas used between July-August and September-October. However, caution should be used in interpreting these results because of low sample sizes in the latter tracking session (n = 14, 6). Annual variation in movement patterns Preliminary comparisons of mouse movements from 1998 to-1999 for tracking sessions August and September were completed. Mouse movements during August tracking sessions were similar at Maytag Property. More mice were captured on the southern half of the Maytag Property in 1999 and this is reflected in the greater nUiilber of locations in the southern half of the property for that year. The same area located outside a 100m strip from the stream center was used both years during this tracking session and was comprised primarily of a seep area. August movements at Pine cliff Ranch were further from the �12 stream in 1999. Mice were also found using an ephemeral stream in August at PineCliff Ranch in 1999. 1bis stream was dry at the time. Similar mouse movements were observed at Woodhouse Ranch over both August tracking sessions although movements were more concentrated in the north in 1998 and more concentrated in the south in 1999; Temporal comparisons of mouse movements in the September tracking sessions are not entirely comparable because fewer mice were followed in the 1999 September tracking session because we were not able to capture mice. We assume a large portion of the mice in 1999 were already hibernating when we started our September trapping and radi~llaring session. We did not observe the greater movements away from the stream center at Maytag in 1999 that we observed there in 1998, however we probably missed most of the movements to hibernation sites. Movement patterns at PineClifffRanch and Woodhouse Ranch were similar for both September tracking sessions with movements being more concentrated near the stream. The same feeding hotspot at Woodhouse Ranch was used both years in September. Habitat Use Detailed vegetation maps were created using Global Positioning Systems. Combining these vegetation maps and locations of mice we will be able to describe in further detail habitat use. These analyses are not yet completed. Nest sites Numerous daytime nest sites were located at all three study sites from both years. Most nest sites were made of tightly woven vegetation, located on the ground. However, we also located underground daytime nests in summer 1999. Nest material included leaves, grass, and small sticks. There was only one small entrance hole on each of the nests found. When observing mice in their nests the mice would peer out of the hole and remain motionless as long as we were present. One possible maternal nest was located in 1999. This possible maternal nest was underground, made of densely packed grasses with the burrow lined as well. There also were several locations at each of the study sites where adult females returned to repeatedly. Each of these sites were in patches of extremely dense vegetation or underneath a large downed log. Hibernacula Potential hibernation sites were located by noting stationary radio-telemetry signals over repeated nights. These signals were coming from underground with no evidence of predation or slipped collars. Eight potential hibernacula were located, at least one at each study site in 1998. In 1999 a total of 13 potential hibernation sites were located. Three were located at Woodhouse Ranch (I female, 2 males) and IO sites at PineCliffRanch (2 females, 8 males). In contrast to 1998 data, these potential hibernation sites were located closer to the stream. However, at both Pine Cliff and Woodhouse Ranches stream banks rise out of the floodplain in closer proximity to the stream than at Maytag Property where the potential hibernation sites located in 1998 were located long distances from the stream center. Vegetation characteristics of the eight sites located during both 1998 and 1999 are similar to other hibernacula described for PMJM. Hibernation sites are considered potential until the sites can be dug up to confirm a hibernation chamber. One male mouse was dug up at Pine Cliff Ranch in 1999 to confirm the site as a true hibernation location and to gain information on the hibernation nest and chamber. The mouse was in the chamber and was not aroused when the earth was dug out around him. Once we finished our assessment of the nest the soil was put back in place, leaving the mouse in the chamber. The remaining hibernation sites will be dug up in June 2000 so as not to disturb other hibernating mice. We hope to confirm these sites as hibernation sites then and will document features of the hibernation sites at that time. �13 Mortality factors Mortalities factors of radicxollared mice in 1998 included predation by rattlesnake, garter snake, fox, and house cat. Four probable predations were also noted and identified by finding tightly crimped (i.e., no possibility of the mouse having slipped the collar over its head) radio-collars lying on the ground. Two accidental deaths were documented, a road kill and drowning. Mortality factors also included trapping and/or handling mortalities and unknown causes. In 1999 mortality factors also included predation by bullfrogs, weasel, and yellow-bellied racer (Table 11). Nine mice also died once they entered a state of torpor above ground. These mice either succumbed to cold or were predated on. Fecal analysis The amount of bait found in each of the fecal samples was quantified as either 100%, abundant(> 70%), trace(< 10%) or 0%. The following summaries are made after eliminating all samples of 100% bait, and then only classifying the fecal sample contents other than bait. Fecal analyses indicate a seasonal shift in diets. The most common item found in the fecal samples during the June trapping session at all three sites for 1998 were arthropods. This was true for three of the five June samples collected at Maytag, eight often June samples at PineCliff, and four of five June samples collected at Woodhouse. Other common items included endogenous fungus (1) and seed (1) at Maytag; endogenous fungus (2) at PineCliff,; and Poa (1) at Woodhouse. During the July 21-August 4, 1998 trapping session the most common items in the fecal samples at Maytag were arthropod (2), endogenous fungus (1), pollen (1), and Carex (1). During the same trapping period, the most common items in five of eight samples collected at PineCliff were endogenous fungus, the other three samples having a majority of arthropod (1), moss (1), and pollen (1). The two samples from Woodhouse during this trapping session were composed primarily of either mushroom or seed. On August 13, 1998, nine samples were collected during an extra trapping session (on the same trapline as the other trapping sessions occur) with the most common items in the fecal samples being moss (4), endogenous fungus (3) or pollen (2). All three samples collected from PMJM captured at a back drainage on August 23, 1998 at Woodhouse Ranch were primarily fungus. The September 1998 trapping session at Maytag yielded samples with majority fecal contents of arthropod (2), moss (2), pollen (2), endogenous fungus (1), and seed (1). Ten samples from PineCliff during September 1998 had majority fecal contents of arthropod (3), endogenous fungus (3), and seed (3). Eight of nine samples taken from Woodhouse contained primarily arthropods, with one a trace of seed. A total of 329 fecal samples were collected during the 1999 field season. Analyses of these samples have not been completed. We also collected 16 stomach samples from dead mice. Analyses of these stomach samples are not yet completed. DISCUSSION Information on the population dynamics of PMJM is necessary to determine which areas and habitats support viable populations. To begin to evaluate the viability of a population information on key demographic parameters must be obtained. Conducting studies on individually marked animals provides the greatest insight on the demography of a population. In general, estimated sex ratios from this study are comparable to those found by Armstrong et al. (1997) who reported an overall sex ratio for all captured PMJM of51.6 males: 48.4 females; approximately 86.0% of captures were identified as adults. There is a possible male sex bias at PineCliff Ranch. However, small sample sizes and possible trapping biases by sex may explain the discrepancy. Density estimates were expected to increase as the summer progressed to account for the birth pulses in late June, and late July-August. In 1998, this was the trend observed at Maytag. PMJM densities at Wcxx:lhouse Ranch increased from June to July but did not increase further during the September trapping session. Highest densities occurred at PineCliff, where the vegetation is primarily willow and both a �14 mainstem and tributary were used by mice. Lowest densities occurred at Woodhouse Ranch where the riparian vegetation has fewer willow but was dense with other riparian vegetation. Vegetation at Maytag provided some areas of dense willow with the remaining areas being of moderate density of riparian vegetation. The lower density of PMJM reported for Woodhouse Ranch might be explained by the composition and densities of other small mammals at that site. Woodhouse Ranch had the highest captures of both house mice and voles of the three sites studied. Defining summer as June 1 - October 5, over-summer survival was estimated as 0.36 (se = 0.056) over all three study sites. Meaney et al. (1999) report a one-month summer survival rate of 78%. Extrapolating Meaney et al. 's ( 1999) estimate over our summer period (- four months) would result in a similar oversummer survival rate estimate of 36%. Prior to studies conducted in 1998 no information existed on survival rates for populations of Z. h. preblei although Whitaker (1963) reported a 67% loss of Z. hudsonius over hibernation. Temporary emigration and immigration rates were estimated but both had extremely high variances associated with those estimates. Thus these estimates cannot be used, with any confidence, to provide information on movements of mice into and out of these populations. Very little new information was gained during this study on reproductive parameters of PMJM. Most adult mice captured exhibited evidence of active reproductive behavior, either pregnancy, lactation, or enlarged genitalia. Juvenile mice were not captured during the June trapping session. Juvenile mice were captured at all three sites during both the July and September trapping sessions. Given that breeding pea.ks appear to occur in early to mid-June and August with a possible third litter in September (Whitaker 1963) this was not unexpected and agrees with previous observations (Meaney et al. 1996, 1997, PTI 1996a, M. Bakeman unpublished data, T. Ryon unpublished data) Preliminary analysis of the movement data collected on radio-collared PMJM in 1999 supported results found in 1998. In particular we were able to document again in this second field season that PMJM exhibit (1) greater use of upland habitats than previously assumed, (2) general site fidelity to both daytime nesting sites and nighttime feeding sites, (3) seasonal shifts in movement patterns, and (4) use of both perennial and intermittent tributaries adjacent to the capture drainage. Jumping mice of the genus Zapus are true hibernators, spending much of their lives in hibernation. Meadow jumping mice spend approximately 7 months (-210 days) per year in hibernation (Quimby 1951) whereas estimates for Z. princeps indicate that some populations (e.g., in the western mountains of Utah) spend up to 300 days per year in hibernation (Cranford 1983). Jumping m.i,ce hibernate in underground burrows (Quimby 1951, Whitaker 1963). They are excellent burrowers and create their own hibemacula. Meadow jumping mice are generally solitary hibernators, however, there have been occurrences of more than one mouse found in a single hibemaculum. Eight possible hibemacula were located during 1998. Five of the eight mice using these possible hibernacula traveled ~ 90 meters from the center of their typical September night time locations. Of the 13 possible hibemacula located in 1999, three sites were located at Woodhouse Ranch and ten possible hibemacula at Pine Cliff Ranch. In contrast to 1998 data, these potential hibernation sites were located closer to the stream. However, at both Pine Cliff andWoodhouse Ranches stream banks rise out of the floodplain in closer proximity to the stream than at Maytag Property where the potential hibernation sites located in 1998 were located long distances from the stream center. Vegetation characteristics of all the potential hibemacula located over both years are similar to other hibemacula described for PMJM. One confirmed hibernaculum, located on Rocky Flats Environmental Technology Site, used by Z. h. preblei has been located (Armstrong et al. 1997). This site was 9m above a creek bed (Walnut Creek); it had a thick cover of chokecherry (Prunus virginiana) and snowberry (Symphoricarpos spp.), the mouse was found in a leaf litter nest 30cm beneath the ground in coarse textured soil (Armstrong et al. 1997). Four possible hibemacula were located by tracking radiotelemetered mice at the U. S. Air Force Academy in fall 1997. These sites are located 7, 12, 29, and 3 lm from a creek bed (R. Schorr, unpublished data). There was no consistency among sites in aspect. Three sites were in vegetation dominated by coyote willow (Salix exigua), one site was in vegetation dominated by snowberry and mullein (Verbascum thapsus). However, all four hibernacula appeared to be below �15 coyote willows. The eight sites located during this study and the four U. S. Air Force Academy sites were not disturbed to protect any hibernating mice and therefore are only possible hibernacula because there is no confirmation a mouse actually hibernated there. Confirmation of a true hibernaculum cannot be made until a chamber, or nest is located. The other explanation for these collar locations might be either locations of radios discarded by the mice or dead mice carried underground by a predator. Location or more hibernation sites was limited primarily by normal battery failure of the radio transmitters before mice went into hibernation. Prior to the 1998 field season, natural mortality factors reported for Z. hudsonius included only insufficient fat storage prior to hibernation (Whitaker 1963), predation (Whitaker 1963, Poly and Boucher 1997, R Schorr unpublished data) and cannibalism (Sheldon 1934). Other assumed natural mortality factors for Z h. preblei included starvation, exposure, and disease. Natural mortality factors documented during this study included predation by house cats, garter snakes, rattlesnakes, yellow-bellied racers, bullfrogs, weasel, and fox as well as accidents by drowning and road kill. In 1999.mice were also found in torpor throughout the summer, often in very exposed areas frequently resulting in death by either exposure or predation. Use of ephemeral drainages was observed at both Maytag Property (in l 998) and Pine Cliff Ranch (in 1999), Two mice moved away from East Plum Creek at Maytag Property in September 1998 and focused their movements ~300 meters from their previous locations, up a dry drainage dominated by upland grasses and gambel oak. These two mice continued to use this new area and were not observed again near East Plum Creek for at least two weeks. Normal radio-failure (i.e., batteries failed after ~4 weeks) after this time did not allow us to determine if the mice ever returned to East Plum Creek or if they hibernated in their new location. Use of the ephemeral drainage at Pine Cliff Ranch occurred in the August tracking session. The high percentage of arthropods and endogenous fungus found in the fecal samples provides a new aspect to evaluating PMJM habitat requirements. When considering habitats used by PMJM, or in trying to predict habitats that might be suitable for the subspecies, consideration should be given as to whether those habitats could support the arthropods and fungus apparently being selected for by the mouse. Arthropods are a food source high in protein and fat which would benefit mice emerging from hibernation and mice preparing for hibernation. Whitaker ( 1963) reported a 67% loss of individuals over hibernation and that average body mass of individuals emerging from hibernation was greater than the average for mice entering hibernation. Because no mice are known to store food in their hibernacula, this indicates that the lighter individuals died during hibernation and only those entering with higher masses survived. All the energy they use during hibernation and the periodic arousals (the energetically most expensive part of hibernation) must be the fat they carry into hibernation (B. Wunder, personal communication). The ability to put on sufficient fat for overwinter survival during hibernation is a critical factor in the life history of these mice. Thus, appropriate and sufficient food sources must be available to the mouse to meet these nutritional requirements. The apparent seasonal shift in mouse movements between the July-August and September tracking sessions may be a result of diet switching. The broader diets suggested by the fecal analyses from samples collected during July and August possibly represent both a wider availability of suitable foods and the ability of PMJM to exploit these resources. It might also suggest a need to exploit these other resources to provide the. mouse with necessary food requirements for breeding. Because mice tracked during each session were not generally the same mice there is a possibility these apparent movement shifts might only be different areas used by different mice. The probability of this being the case is small for two reasqns. The first is the low density of mice in the stream (Shenk and Sivert 1999). Given that, the proportion of mice followed during each session is a high p:,;-oportion of the mice in the population. Thus, each subset of mice should be representative of the population. Secondly, evidence from the four mice followed during both the latter tracking sessions also exhibited movement shifts between sessions. The combination of shifts in both general mouse movements, individual mouse movements, and diet provide strong circumstantial evidence that PMJM may be selecting for or require specific seasonal diets. If �16 this is the case, all these requirements must be considered and provided for to ensure conservation of the subspecies. A detailed literature search and further studies need to be conducted to investigate the possible implications of these dietary patterns. In comparing movement patterns from 1998 to 1999 we were able to evaluate annual variation in daily and seasonal movement patterns of PMJM. General patterns that emerged from the comparison of the two years included (1) similar areas being used by the mice over both years, (2) greater use of upland habitats than previously assumed, (2) general site fidelity to both daytime nesting sites and nighttime feeding sites, (3) seasonal shifts in movement patterns, and (4) use of both perennial and intermittent tributaries adjacent to the capture drainage. This study looked at PMJM movements at only three sites. These sites were selected based on known presence of PMJM. Other sites, perhaps because of different habitat configurations or sites of poorer quality may require mice to move further from the creek or may allow mice to remain closer to the creek in order to obtain all life requirements. However, these study sites were specifically selected to address spatial variation in movement patterns of PMJM due to different spatial configuration and juxtaposition of habitats. And although all study sites were different they could all be considered within the general description of what is consider typical habitat for PMJM. It should also be noted that we generally trapped along the creek. Thus, mice captured and subsequently radio-collared and followed were those mice that use the area near the most prominent drainage. If there are mice that do not regularly use the main channel and thus were not available for capture there would be a bias in the data towards fewer observations 300 feet away from the creek. To test for such a bias, traps were placed 300 m from the stream center at Maytag and Woodhouse Properties during suminer 1999 as part of a Master's Project conducted by a student ay Colorado State University. Capture of mice in transects placed away from the stream lends further support for use of habitats further from the creek than initially thought. Mice captured 300 meters from the stream moved near their capture site and between the capture site and the stream. The prevailing idea of what constitutes quality PMJM habitat is amount of riparian shrubs. Therefore, we focused our analysis on describing the relationship between PMJM densities and amount of various riparian vegetation cover, including riparian shrubs. This analysis is not meant to identify all critical components of PMJM habitat. For example, if a necessary component of PMJM habitat is open water, but not necessarily in any large amount, this analysis would not detect this relationship. The best model describing the relationship between PMJM density and riparian vegetation cover included shrub and tree cover, the next best model included open water as well as shrub and tree cover. Tree cover may also reflect shrub and herbaceous cover, because the tree canopy likely may be covering these other understory vegetation classes . Thus, results from this analysis appear to support the hypothesis that riparian shrubs are an important component of PMJM habitat. However, because the study areas included in this analysis were not randomly selected from all possible PMJM habitats, the conclusions reported here must be treated with some caution. To truly assess the relationship between PMJM density and riparian vegetation would require estimating densities from a random selection of areas presumed to have suitable PMJM habitat. Analysis of how the riparian vegetation characteristics at these study sites relates to their PMJM densities would then provide an unbiased estimate of the relationship. With.the limited data available, 68% of the variation in PMJM density is explained by a model that includes riparian shrub and tree cover (ha/km stream), as identified by the vegetation mapping techniques used in this study. These results suggest that habitat quality of PMJM can be predicted by the shrub and tree cover available on a site. This report includes results from only the first two years of a multi-year project to follow individually marked PMJM through time. Further analyses of these data, collection of more data, and more years of data, will continue to improve our ability to evaluate demographic parameters estimates and movement patterns of PMJM and of how they vary across space and time. Preliminary results from the demography, movement and distribution studies of PMJM have suggested the need to continue with research currently �17 being addressed in these three studies. However, the preliminary results also suggest further research be conducted on (1) use of upland habitat by PMJM, (2) refining water requirements of PMJM (i.e., do they require stream habitat or are wetland areas sufficient), (3) range-wide distributional boundaries (e.g., elevation restrictions), and (4) investigating areas of potential sympatry or hibridization with Z. princeps (western jumping mouse). The demography and movement studies will be modified during the summer 2000 field season to further investigate upland use and water requirements. Acknowledgments Additional data on PMJM densities for the vegetation analysis were provided by Mark Bakeman, Rob Schorr, Carron Meaney, and Tom Ryon. Bruce Lubow provided helpful comments on the first drafts of the adjusted PMJM density correction method, and computed the estimates ofPMJM population size for several of the study areas included in this analysis. Seth McClean with CDOW provided the riparian vegetation data. Mark Bakeman and Tom Ryon provided useful comments on earlier drafts of the vegetation analysis. Literature Cited Armstrong, D. M., M. E. Bakeman, A. Deans, C. A. Meaney, and T. R. Ryon. 1997. Conclusions and recommendations in: Report on habitat findings on the Preble's meadow jumping mouse. Edited by M. E. Bakeman. Report to USFWS and Colorado Division of Wildlife. Burnham, K. P., and D.R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. 353pp. Cook, T. D. and D. C. Campbell. 1979. Quasi-experimentation: design and analysis issues for field settings. Houghton-Mifllin, Boston. Cormack, R. M. 1964. Estimates of survival from the sightings of marked animals. Biometrika 51:429438. Cranford, J. A. 1983. Ecological strategies of a small hibernator, -the western jumping mouse Zapus princeps. Canadian Journal of Zoology 61:232-240. ESRI. 1987. ARC/INFO users manual. Environmental Systems Research Institute. Redlands, California, USA. Jolly, G. M. 1965. Explicit estimates from capture-recapture data with both death and immigration stochastic model. Biometrika 52:225-247. Kendall, W. L., and J. D. Nichols. 1995. On the use of secondary capture-recapture samples to estimate temporary emigration and breeding proportions. Journal of Applied Statistics.22:751-762. Kendall, W. L., K. H. Pollock, and C. Brownie. 1995. A likelihood-based approach to capture-recapture estimation of demographic parameters under the robust design. Biometrics 51:293-308. Kendall, W. L., J. D. Nichols, and J.E. Hines. 1997. Estimating tempqrary emigration using capturerecapture data with Pollock's robust design. Ecology 78:563-578. Krutzsch, P.H. 1954. North American jumping mice (genus Zapus). University of Kansas Publications, Museum ofNatural History 7:349-472. Meaney, C. A., N. W. Clippinger, A. Deans, and M. OShea-Stone. 1996. Second year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Deans, N. W. Clippinger, M. Rider, N. Daly, and M. O'Shea-Stone. 1997. Third year survey for Preble's meadow jumping mouse (Zapus hudsonius preblei) in Colorado. Report prepared for the Colorado Division of Wildlife. Meaney, C. A., A. Ruggles, B. Lubow, N. W. Clippinger, and A. Deans. 1999. Preliminary results: Second year study of the impact of trails on small mammals and population estimates for Preble's meadow jumping mice on City of Boulder Open Space. Report for Greenways Program, City of Boulder Transportation Department, City of Boulder Open Space, and Environmental Protection Agency, Region 8. �18 Otis, D. L., K. P. Burnham, G. C. White, and D. R Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monograph 62:1-135. Poly, W. J., and C. E. Boucher. 1997. Record ofa creek chub preying on a jumping mouse in Bruffey Creek, West Virginia. Brimleyana 24: 29-32. PTI Environmental Services. 1996a. Preble's Meadow Jumping Mouse Study at Rocky Flats . Environmental Technology Site, Annual Report 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. PTI Environmental Services. 1996b. Preble's Meadow Jumping Mouse Study at Rocky Flats Environmental Technology Site, Spring 1996. Final. Rocky Flats Environmental Technology Site, Golden, Colorado. Quimby, D. C. 1951. The life history and ecology of the jumping mouse, 7.apus hudsonius. Ecological Monographs 21 :61-95. Seber, G. A. F. 1965. A note on the multiple recapture census. Biometrika 52:249-259. Sheldon, C. 1934. Studies on the life histories of Zapus and Napaeozapus in Nova Scotia. Journal of Mammalogy 15:290-300. Shenk, T. M. 1998. Conservation assessment and preliminary conservation strategy for Preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife FY1997-98 Annual Report. Shenk, T. M. and Sivert M. 1999a. Temporal and spatial variation in the demography of preble's meadow jumping mouse (Zapus hudsonius preblei). Colorado Division of Wildlife. Annual Report 1999. Shenk, T. M. and Sivert M. 1999b. Movement patterns of Preble's meadow jumping mouse (Zapus hudsonius preblei) as they vary across time and space. Colorado Division of Wildlife. Annual Report. Whitaker, J. 0., Jr. 1963. A study of the meadow jumping mouse, Zapus hudsonius (Zimmerman), in cental New York. Ecological Monographs 33:3. White, G. C., D. R Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. LA-8787-NERP, Los Alamos National Laboratory, Los Alamos, New Mexico, USA 235 pp. White, G. C. and K. P. Burnham.1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement: 120-138. Table 1. Total number of individual Preble's meadow jumping mice (7.apus-hudsonius preblei) captured in 1998, new individuals captured in 1999, recaptures in 1999 from 1998, and total number of individual mice caetured in 1999 at three studr sites. New captures 1999 Total individuals captured 1998 Site 1999 from 1998 Recaptures in Total individuals captured 1999 F M u Total F M Total F M Total F M Total Maytag Property 34 38 1 73 19 27 46 4 10 14 23 37 60 PineCliff Ranch 25 52 0 77 19 29 48 4 8 12 23 37 60 Woodhouse 17 18 1 36 17 30 47 3 5 8 20 35 55 TOTAL 75 108 2 185 55 86 141 11 23 34 66 109 175 �19 -- Table 2. Stream reach abundance estimates (N) for Preble's meadow jumping mouse (PMJM) from three sites in Douglas County, Colorado for three traeeing sessions in 1998 and for June 1999. 95% Confidence Interval Trapping Session Site Maytag Maytag Maytag PineCliff PineCliff PineCliff Woodhouse Woodhouse Woodhouse Maytag Woodhouse PineCliff R se(N) June98 July98 September98 Junc98 July98 September98 June98 July98 September98 June99 June99 June99 18 31 44 30 17 51 11 20 20 35 32 28 2.7 11.4 1.8 5.7 0.9 3.3 3.8 5.2 3.1 3.8 3.2 2.1 Lower Upper 15 20 42 24 16 48 7 15 17 24 56 52 21 42 46 36 18 54 15 25 23 39 69 61 Trapline Length Adjusted Density (m) (PMJM/km) 550 608 494 490 504 504 510 516 574 1130 504 503 26.2 41.3 69.5 47.7 26.3 78.9 16.8 30.7 27.8 31.2 62.6 56.5 Table 3. Data on the proportion of locations (p) of Preble's meadow jumping mouse locations within the area defined by parallel lines running through either end of the trap line, sorted into ascending order by traeline length. Site Year Session Meanp SE(p) Weighted Fit Logistic Trapline No. Length Weighted Fit Mice Online Walnut Creek 1999 May/June 0.946 0.0040 0.761 0.796 325 5 A-upper Woodhouse 1999 0.629 0.0843 0.800 0.831 June 409 24 Woodhouse 1999 July 0.902 0.0532 0.800 0.831 409 19 Woodhouse 1999 Sept 409 1.000 0.0000 0.800 0.831 6 Walnut Creek 1999 May/June 490 0.308 0.827 0.855 1 Lower Maytag 1998 Sept 0.954 0.829 494 16 0.0385 0.856 Walnut Creek 1999 May/June 0.828 0.830 500 1 0.858 B-series PineCliff 1999 0.841 0.0670 0.831 0.858 June 503 12 PineCliff 1999 Sept 503 0.924 0.0464 0.831 0.858 15 PineCliff 1999 July 0.899 0.831 503 22 0.0372 0.858 PineCliff 1998 July 0.805 0.831 504 14 0'.0750 0.858 PineCliff 1998 0.671 0.831 Sept 504 16 0.0964 0.858 Woodhouse 1998 July 12 0.817 0.0712 0.835 0.861 516 Woodhouse 1998 Sept 14 0.883 0.0291 0.849 0.874 574 Maytag 1998 July 0.719 0.0744 0.856 0'.880 608 16 Maytag 1999 Sept 0.969 0.1664 0.917 0.932 1130 11 Maytag 1999 1130 26 0.908 0.0364 0.917 0.932 July Maytag 1999 7 0.873 0.917 0.932 June 1130 0.1339 �20 Table 4. Estimates of boundary strip width (BSW) for nonlinear weighted least squares fit and nonlinear weighted least squares fit with the logistic transformation. Method Estimate of BSW SE of estimate Nonlinear weighted least squares 51.1241 10.1033 Nonlinear weighted least squares with logistic transformation 41.5446 9.1676 Table 5. Data used to evaluate the relationship between Preble's meadow jumping mouse density and riparian vegetation cover. Adjusted Area (ha/km) Adjusted SE Stream InvestiStudy A..rea Year Density Adjusted Length HerbaNonOpen Tree gator (mice/km) Density Shrub (km) ceous Vegetated Water Shenk Maytag 1998 32.52 5.84 0.2619 2.4643 2.8571 1.3452 2.0357 0.84 Shenk Maytag 1999 29.04 3.05 0.1549 1.8239 1.9296 1.0000 1.7817 1.42 Shenk Pinecli.ff 1998 57.35 18.39 5.4324 3.3649 1.2432 0.0000 1.5946 0.74 Shenk Pinecli.ff 1999 53.79 5.52 5.4324 3.3649 1.2432 0.0000 1.5946 0.74 Shenk Woodhouse 1998 15.52 3.14 2.7600 0.0000 1.7200 0.0000 0.0000 0.50 Shenk Woodhouse 1999 48.52 3.52 2.7600 0.0000 1.7200 0.0000 0.0000 0.50 Bakeman Dirty Woman Cr. 1998 20.46 7.29 2.9190 1.3646 0.2987 0.0861 0.0354 3.95 Bakeman Dirty Woman Cr. 1999 6.89 2.11 1.3769 1.8396 0.4403 0.0000 0.0522 2.68 Bakeman Castle Rock 1999 41.70 26.91 3.8086 0.1584 0.2145 1.0066 1.1683 3.03 Schorr Monument Cr. 1998 67.08 13.34 5.9363 0.0000 0.4968 0.8535 0.0000 1.57 Schorr Monument Cr. 1999 28.75 8.52 5.9363 0.0000 0.4968 0.8535 0.0000 1.57 Meany South Boulder Cr. 1998 48.80 10.60 0.1640 27.4270 3.8629 0.0000 0.1933 4.45 Meany South Boulder Cr. 1999 34.50 7.75 0.1640 27.4270 3.8629 0.0000 0.1933 4.45 Ryon Walnut Cr. 1999 5.10 3.34 0.1231 1.0865 0.0416 0.0000 1.0266 6.01 Ryon Rock Cr. 1998 3.80 0.36 0.3815 0.9505 0.0000 0.0786 0.0219 14.13 Table 6. Results of linear regressions of Preble' s meadow jumping mouse density (mice/km stream ) predicted by riparian vegetation cover (ha/km stream) for 15 study area and year combinations from Table 5. Variable Shrub Herbaceous Tree Non-vegetated Total Cover Open Water Intercept 30.22 31.79 30.80 31.51 31.23 35.84 p R2 0.06 0.67 2.18 0.06 0.638 0.656 0.495 . 0.729 0.596 -2.35 .0.469 0.018 0.016 0.037 0.011 0.022 0.041 Slope 0.63 --· �21 Table 7. Summary of AICc model selection for the riparian vegetation cover (ha/km stream) variables Shrub, Tree, Herbaceous, Non-Vegetated, and Open Water predicting Prebles' meadow jumping mouse density (mice/km stream). AICc, ~-AICc, and Akaike Weights follow definitions in Burnham and Anderson (1998). Akaike R2 AICc ~-AICc Variables in Model Wei hts 83.5040 0.6831 0.0000 0.59584 Shrub Tree 86.6162 3.1122 0.7143 0.12570 Shrub Tree Open Water 87.4205 3.9165 0.08408 0.6986 Shrub Tree Non-Vegetated 88.1465 4.6425 0.6836 0.05848 Shrub Tree Herbaceous 89.0245 5.5205 0.5421 0.03770 Shrub Herbaceous 89.3639 5.8599 0.6569 0.03182 Shrub Herbaceous Open Water 90.9029 7.3989 0.6198 0.01474 Shrub Herbaceous Non-Vegetated 91.1034 7.5994 0.3216 0.01333 Shrub 91.8340 8.3300 0.7258 0.00925 Shrub Tree Herbaceous Open Water 92.3015 8.7975 0.7171 0.00732 Shrub Tree Non-Vegetated Open Water 92.8597 9.3557 0.7064 0.00554 Shrub Tree Herbaceous Non-Vegetated 93.5258 10.0218 0.3819 0.00397 Shrub Open Water 94.1043 10.6003 0.6810 0.00297 Shrub Herbaceous Non-Vegetated Open Water 94.5170 0.3396 11.0130 0.00242 Shrub Non-Vegetated 95.4143 11.9103 0.0957 0.00154 Tree 0.0462 96.2135 12.7095 0.00104 Open Water 96.3496 0.0375 12.8456 0.00097 Herbaceous 96.3621 12.8581 0.0367 0.00096 Non-Vegetated 0.3828 98.1688 14.6648 0.00039 Shrub Non-Vegetated Open Water 0.1358 98.5520 15.0480 0.00032 Tree Non-Vegetated 98.7044 15.2004 0.1270 0.00030 Tree Open Water 98.8480 15.3440 0.7345 0.00028 Shrub Tree Herbaceous Non-Vegetated Open Water 0.1059 99.0626 15.5586 0.00025 Herbaceous Non-Vegetated 0.1035 99.1022 15.5982 0.00024 Tree Herbaceous 99.1919 15.6879 0.0982 0.00023 Herbaceous Open Water 99.8370 0.0585 16.3330 0.00017 Non-Vegetated Open Water 0.1459 103.0432 19.5392 0.00003 Tree Non-Vegetated Open Water 0.1358 103.2184 19.7144 0.00003 Tree Herbaceous Non-Vegetated 103.3266 19.8226 0.00003 0.1296 Herbaceous Non-Vegetated Open Water 0.1273 103.3666 19.8626 0.00003 Tree Herbaceous Open Water 108.8576 25.3536 0.1470 0.00000 Tree Herbaceous Non-Vegetated Open Water Table 8. Parameter estimates for best AI Cc model explaining PMJM density (mice/km stream length) from vegetative cover variables (ha/km stream length). Standard Pr> jtj Variable t statistic Estimate Error 0.892 Intercept 0.14 0.9853 7.1047 Shrub Tree 7.2342 10.1308 1.5339 2.7381 4.72 3.70 <0.001 0.()03 �22 Table 9. Number of Preble's meadow jumping mice radi~llared at each study site during each trapping session for each l'.ear. 1999 1998 Site Session Trap nights Females Trap Nights Females -Males Tot.al Males Tot.al Maytag Jun Maytag Jul Maytag Sep PineCliff Jun PineCliff Jul PineCliff Sep Woodhouse Jun Woodhouse Jul Sep Woodhouse TOTALS 1949 2370 3256 1095 1603 1544 1525 2420 1568 17330 9 11 10 5 6 4 2 8 7 62 5 5 8 13 7 12 3 4 6 63 14 16 18 18 13 16 5 12 13 125 2604 3191 4341 742 1442 1921 1651 1215 2114 19222 6 10 3 7 6 7 7 8 3 57 12 13 7 .5 10 17 9 5 3 81 18 23 10 12 16 24 16 13 6 138 Table 10. Preble's meadow jumping mice radi~llared. and tracked for more than one tracking session. Location of capture, sex, identification, and number of locations for each mouse during each tracking session is noted. 1998 1999 PIT-tag# Site Sex Sep-Oct Jul-Aug Jun Jul-Aug Sep-Oct Maytag 414lf87C76 60 24 F 105 Maytag F 41412B4A2D 103 Maytag F 413E296246 73 7 Maytag F 4141276D78 76 3 82 Maytag F 4140753620 1 93 · Maytag M 4141241836 1 Maytag 4140754707 19 M 70 4135354E37 Maytag M 37 40 Maytag 41357B5A0E 38 M 49 61 13 Maytag M 414130663A 144 11 65 Maytag M 41411E6879 Maytag 4141445465 M 52 74 4141554B28 PineCliff F 44 21 PineCliff M 41413D4C04 18 15 4141144535 PineCliff M 21 38 PineCliff 413E02020F M 22 9 PineCliff M 414037184D 45 37 87 6 PineCliff M 4141714141 12 47 Woodhouse F 41413E610B 78 14 Woodhouse F 41413E7B07 5 66 63 16 Woodhouse F 41414C721F 39 Woodhouse F 41412A2508 84 93 Woodhouse 4141611413 42 8? M 46 Woodhouse M 4141074013 6 Woodhouse M 4141252D66 63?NC 64 Woodhouse M 41412D3509 59 ?NC Woodhouse 75 M 41406A1049 9 �23 Table 11. Causes of mortality of Preble's meadow jumping mice from Maytag Property, PineCliff Ranch, and Woodhouse Ranch collected during; the 1998 and 1999 field season (June I-October 31). 1998 1999 Cause of Total Mortality M.aytag PineCliff M.aytag Woodhouse PineCliff Woodhouse Predation Bullfrog Garter snake Rattlesnake 0 0 1 1 l 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 0 1 0 0 0 0 Yellowbellied racer Weasel Fox House cat Raptor Unknown Exposure Drowning Road.Kill Handlingffrap 0 Unknown TOTAL 1 8 1 4 5 0 0 0 2 0 0 0 0 0 1 0 0 l 0 0 1 0 1 0 0 0 1 0 0 0 2 2 1 0 0 19 4 9 0 5 2 0 1 6 3 0 2 3 24 13 17 1 7 2 0 0 0 2 2 8 4 5 3 0 0 2 0 1 ,--... 8 ell 5 1 1 1 4 1 9 17 74 ■ +---..-------------------------------------------------------1 ■ 0.9 -----=-----------===== --- Q.) < 0.8 --+-----~-----1- Q.) i::::: ·.§< 1--< i::::: 0 0.6 0 ·...... 0.5 ~ ,.D 0 1--< ~ ■ +------------------------------ b .......-< ■ 0.7 ■ -- - 0.4 - + - - - - - - - - I 0.3 200 --------------------------1 ■ - Observed Data Weighted Least Squares Weighted Least Squares Logistic 400 600 I I I 800 1000 1200 Trapline Length Figure 1. Observed estimates ofp with the fit of the weighted nonlinear least squares model, and the logistic transformed nonlinear least squares model. �24 1 0.9 0.8 ~ .-9 0.7 ~ 0.6 0.5 ---······························· 0.4 0 500 1000 1500 Trapline Length (m) 2000 Figure 2. Predicted p with 95% confidence intervals as a function oftrapline length in meters. 20 - . - - - - - - - - - - - - ~ • onument Creek •C~ouse 10 r✓.l 1 0 ·~ -10 r✓.l -20 • Maytag •Walnut Creek • Rock Creek • South Boulde Creek • Pinec. • Maytag • Pinecliff • Dirty Woman Creek . • South Boulder Creek • Dirty Woman Creek • Monument Creek •Woodhouse -30 - - - . + - - - + - - + - - - + - - - - - - - - + - - - - - + - - I 0 10 20 30 40 50 60 70 PMJM Density (mice/km) Figure 3. Residuals for the best AICc model explaining PMJM density (mice/km stream length) from the standardiz.ed vegetation cover variables shrubs and trees (ha/km stream length). � https://cpw.cvlcollections.org/files/original/757faa42748d04dc7c7887433dd58292.pdf dc54b75eddbf976e8545043ce4dbfe20 PDF Text Text 335 JOB PROGRESS REPORT State of Colorado Project No • .....e.W~-~1~5~3~-_R,.,__-~s'--------- Mammals Research Work Plan No. _ ___,l~0~A,.,__ _ _ _ _ _ __ _ Kit Fox Studies Job No. Kit Fox Status in Colorado 1 Period Covered: July 1, 1992 to June 30, 1993 Author: J.P. Fitzgerald and M. .Link, Univ. Northern Colorado, Greeley Personnel: T. Beck, c. Parmeter, (volunteers M. Reddy, T. Hugo from University of Northern Colorado). ABSTRACT Since 9 March 1992, 9 kit fox have been trapped in 2,725 trap nights of effort including 1,141 trap nights in the current reporting period. All individuals (5 males and 4 females) have been captured NE of Montrose in Delta and Montrose counties in desert-shrub/greasewood habitat. Three males and 4 females have been radio-collared and are periodically being monitored. One additional kit fox has been observed while spotlighting in Browns Park in extreme northwestern Moffat county . Den sites used by foxes are in steeper, rougher terrain than reported in the literature . Few kit fox have been reported harvested by trappers responding to the annual survey questionnaire distributed by the Colorado Division of Wildlife. Contacts with ranchers, land management agency personnel, CDOW employees, and local trappers have resulted in only three reports of kit fox in western Colorado. Live trapping efforts in areas from which kit fox have been historically reported have not resulted in any captures or visual observations. �337 KIT FOX (WLPES MACROTIS) DISTRIBUTION AND ABUNDANCE IN WESTERN COLORADO James P. Fitzgerald and Michelle Link P.N. Objective Document the geographic distribution and relative abundance of kit fox in western Colorado. Segment Objectives 1. 2. 3. 4. 5. Identify geographic extent of kit fox distribution in western Colorado. Determine habitat use by the species and general prey species abundance in areas used by kit fox. Compile general harvest information. Test different survey techniques in areas with kit fox populations. Identify suitable kit fox populations for more intensive ecological research. Methods Methods are generally the same as previously reported (Link and Beck 1992). However, captured kit fox are now being collared with transmitters (Model No. HLPM 2180 LD - Wildlife Materials, Inc.) for monitoring purposes. Results and Discussion Determination of Distribution Since the project began 9 March 1992 a total of 2,794 trap nights of effort have been expended (Table 1) resulting in capture of 9 kit fox. Seven of the captured fox, 3 males and 4 females have been radio-collared. Two of the females have been recaptured and their collars have been replaced. One adult female captured on 31 May 1992, rehabilitated in captivity with a broken jaw, and radioed and released to the wild in late summer 1992, was found dead from injuries (probably inflicted by a coyote) in mid December 1992. All animals have been captured in a 2590 ha area of Peach Valley in Montrose and Delta counties. Live trapping (1,210 trap nights) and spotlighting efforts (54 hours) during the fiscal year were concentrated in the Big Gypsum, Disappointment, Paradox and Peach valleys in southwestern Colorado and the Rangely-Dinosaur and Brown's Park areas of northwestern Colorado. Because of the capture of kit fox in the Peach Valley area in May and June of 1992 the area continued to receive periodic, concentrated search effort during the present reporting period. One animal identified by Link as a kit fox was observed by spotlight in the Browns Park area in late June 1993 but no animals were captured during 144 trap nights of effort in that location. Concerted effort will be expended in that area in 1993-94 to attempt to capture and verify presence of fox in Moffat County. Of particular interest is whether animals in Moffat County are "Swift or Kit" foxes as it is possible that "Swift" fox could occupy the "Red Desert" area of Wyoming and filter south into Moffat County rather than represent extensions of Kit fox populations from the Colorado River drainage of Utah. Sampling has included trapping in a number of different habitat types including: sagebrush-grasslands; margins of pinyon-juniper woodland, and desert-shrub/greasewood areas. To date, kit fox have only been captured in the desert-shrub/greasewood type common to the Peach Valley area. Much of the area occupied by kit fox in Peach Valley is dominated by mat saltbush (Atriplex corruaata) on the uplands and ridges with greasewood (Sarcobatus �338 Table 1. Areas searched, dates of search, and trap nights of effort spent in trapping, kit fox study, western Colorado, 1992 to June 30, 93. County and Area Montezuma Co. McElmo Canyon San Miguel Co. McIntyre Canyon Disappointment Valley Big Gypsum Valley Montrose Co. Paradox Valley Dates Searched Total Trap Nights Effort Fox Captures 100 Trap Nights 9/9-12/92 60 0 3/5-8/93 77 0 8/3-9/92 141 0 7/5-8/92; 7/29-8/1/92 174 0 8/10-20/92 141 0 168 0 192 836 0 1 Montrose co., Delta & Mesa co. Sinbad Valley 3/15-22/92 Delta to Grand 4/28-5/16/92 Junction Various - May to Present Peach Valley V Mesa co. Dolores River Valley-Gateway to Utah border 3/6-12/92 114 0 Colo. Natl. Mon. 4/20-23/92 78 0 N.W. Grand Junct. & Rabbit Valley Various - 1992-93 528 0 Rio Blanco Co. Rangely/Dinosaur 6/16-19/93 72 0 Moffat Co. Brown's Park 6/22-28/93 144 0 vermiculatus), Nuttall saltbush (A. nuttallii), shadscale (A. confertifolia, and sagebrush (Artemisia .!ll2.:.) occurring in more localized sites. A considerable amount of the Peach Valley area occupied by foxes is on lands used heavily by off road vehicles (ORV's). Habitat Use and Relationship of Prey Abundance to Kit Fox Abundance Determining the diets of kit foxes in the Peach Valley area will be part of the 93-94 work effort. Link has collected numerous kit fox scat samples from Peach Valley. Remains of white-tailed prairie dogs (Cynomys leucurus), cottontail (Sylvilagus audubonii), and cricetid mice (Peromyscus) have also been found at kit fox dens. No usable relationship appears to exist between numbers of lagomorphs spotlighted at night and distribution of kit fox. An average of .2 lagomorphs (mostly cottontails) have been recorded per road km in over 916 km surveyed (range 1.6 to 0 animals/km). In Peach Valley the average has also been .2/km in a total of 68 km censused. Lagomorph populations have been very low across V �339 western Colorado with highest numbers observed in the Sinbad Valley, Mack and Brown's Park areas. Den sites located in the Peach Valley area are not similar to those reported by other workers (Egoscue 1962, O'Neal et al. 1986, McGrew 1977) who have found most dens on relatively flat ground with multiple burrow entrances. out of 13 dens being used in Peach Valley, 4 are located in deep, dry washes, 4 are on the sides of hills with good drainage, two are half way up hills in washes, two are on top of ridges at 5,600 feet, and one is on the side of a large u-shaped bowl. Most dens are within 300 m of a well-traveled road, jeep trail, or pathway (ORV, horse). Use of these "atypical" den sites has led us to revise search efforts to focus on more broken terrain than suggested by the literature. General Harvest Information/ Other Reports of Kit Fox Table 2 indicates reported harvest data for kit fox from western COlorado. Take is estimated from trapper survey data and numbers may include other fox species. The numbers of animals trapped in Montezuma county in 1981, and reports of kit fox from La Plata county are doubtful. Table 2. Estimated harvest of kit fox from western Colorado based on trapper questionnaire returns to the Colorado Division of Wildlife, 1975-1992. Year \.__I County Delta Garfield Gunnison La Plata Mesa Moffat Montezuma Montrose Rio Blanco Totals 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 2 5 2 3 6 2 3 1 13 33 5 2 2 10 7 1 2 33 41 3 192 198 26 4 10 5 5 4 41 13 6 2 Link has made a concerted effort to question ranchers, agency personnel, or local trappers regarding their knowledge of kit fox. Few reports have been made. The district wildlife manager (DWM) in the Mack/Grand Junction West area reported seeing young kit fox in an arroyo north of Mack in 1988. Extensive trapping has not resulted in any captures in that area. The Fish and Wildlife Service at Browns Park National Wildlife Refuge had no records of kit foxes, but one employee (Brad Pech) reported that trappers had taken kit fox in that area several years ago. Link did spotlight an animal believed to be a kit fox in that area but none were trapped. The DWM (Divergie) and the Chevron Oil Company's on-site environmentalist (Sellars) at Rangely have never observed or heard of kit foxes in that area even after extensive spotlighting and surveying for Black-footed Ferrets. Ranchers (Tozer Bros.) from McElmo Canyon, Montezuma County, have not observed any kit fox and trapping efforts did not produce captures in 1992 in that area, although there are past records of kit fox in that area (Egoscue 1964). Likewise, trapping efforts in other areas reported to have kit fox by Miller and McCoy (1965) including the Colorado National Monument and near the Utah state line in the Grand Valley) have not resulted in any captures. The BLM ranger (Sering) assigned to the Delta and Montrose area reported to Link that he observed a kit fox on Flattop Mountain south of the Peach Valley area in June of this year. The Flattop area will be trapped and surveyed in 1993-94. �340 Test sampling techniques in areas with Kit Fox The Peach Valley area is the only site with a known population of kit fox. Those animals have been located by daytime sightings at dens close to roads or by live-trapping. Trapping success in Peach Valley is low with one capture per 100 trap nights effort. Two of the radio-collared animals (both females) have been recaptured 5 months after their first capture allowing for replacement of their radios. Males appear to be more difficult to recapture using present techniques. V Scent stations baited with standard lure (scented predator survey discs with FAS, Pocatello Supply Depot) were placed at 10 sites in Peach Valley in June 1992. No kit fox tracks were identified at any stations. The scent station surveys were abandoned because it was more efficient for one person to work a trap line than to maintain a station line. Spotlighting has resulted in observations of 2 kit fox in Peach Valley and 1 in Browns Park. Identify suitable kit fox populations for more intensive research The Peach Valley area bas from 4-8 adult fox based on monitoring of radioed animals. Since these animals represent the only kit fox presently known to occur in western Colorado the decision was made to radio-collar all animals captured on the site and to increase efforts to better understand habits of the animals in that area with the expectation that it may enhance efforts to locate other kit fox populations. A temporary worker (Parmeter) was hired from mid-January to mid-April to monitor fox in Peach Valley and to try winter trapping in the Grand Junction and McIntyre Canyon areas. Attempts to radiotrack animals at night in the Peach Valley area by both Link and Parmeter have not been effective for determining distances ranged from dens or areas being hunted. The foxes are aware of the researcher and their behaviors seem to be more intent in evading the tracker rather than on night hunting. In the 93-94 field season attempts will be made to track some radioed animals using teams of trackers stationed at high points of ground rather than a single individual. ~~~ti/res P. Fitzgerald Contractor, UNC and Michelle Link Graduate Research Assistant V �1 93 Colorado Division of Wildlife Wildlife Research Report June 30 1994 JOB PROGRESS REPORT State of -----~C~o~l~o~r~a~d;o=---Project No. W-153-R-7 Mammals Research Work Plan No. 10A Kit Fox Studies Job No. 1 Kit Fox (Vulpes macrotis) Status in Colorado Period Covered: Author: July 1, 1993 - June 30, 1994 J.P . Fitzgerald Personnel: J.P. Fitzgerald, M. Link, T. Verbeck, A. Anderson, L. Dent, J. Eussen, J. Prather, M. Reddy, D. Watson, T. Beck, B. Gill Abstract A total of 1754 trap nights of effort were expended in the project year to capture 18 kit fox. Trapping efforts included parts of Moffat, Mesa, Garfield, Delta, and Montrose counties. All captures were made in Montrose and Delta counties in Peach Valley (8), East of Montrose (9), or North of Delta (1). A reliable report of a "kit or swift" fox was received from U.S. Fish and Wildlife Service and BLM personnal in the Vermillion Creek area in northern Moffat County. Trapping to date in northern Moffat County has not resulted in any fox captures. Monitoring of radio-collared kit foxes in the Peach Valley study area in Montrose and Delta county continued. Four (F18, FS, M13, MS) of 6 radio-collared adults are still alive in that population. On 26 March and 13 April carcasses of two kit fox, M12 and an untagged animal of unknown sex, were recovered in TS0N, R9W, NE corner Section 8 within 100 m of each other. The cause of death could not be determined for either animal. East of Montrose, nine kit fox (4 adult females, 1 adult male, 1 male pup, 3 female pups) were captured and either radio-collared or ear tagged. Gill and field crew personnel have taken photographs of animals in that population. In March, the Wildlife Commission closed the season on kit fox and imposed trapping regulations for the Peach Valley area. The Director of the Division of Wildlife placed the species on the state special concern list. �195 KIT FOX (VULPES MACROTIS) STATUS IN COLORADO James P. Fitzgerald P. N. Objective Document the geographic distribution and relative abundance of kit fox in Western Colorado. Segment Objectives 1. Continue to monitor radio-collared foxes in the Peach Valley Area. 2. Write up_project results (M.A. thesis - Michelle Link in progress). 3. Begin extensive summer trapping effort. Methods Methods continue to be similar to those reported previously (Fitzgerald and Link 1993, Fitzgerald and-Verbeck 1993).·Field Personnel; At the start of the project year Michelle Link was replaced by Tom Verbeck to take over the kit fox field research. Verbeck worked from mid-August to January. Allan Anderson monitored fox populations in Peach Valley from March through late May. Verbeck resigned from the project in April. Three field crews: Matt Reddy-David Watson; Lonnie Dent-Jim Bussen; and Jake Prather (alone) began work on the project in late May. Results and Discussion Trapping Efforts: Between July 1, 1993 and June 30, 1994 a total of 1754 trap nights of effort have resulted in a total of 20 captures of 18 individual kit fox. All captures were made in Montrose or Delta County. Trapping efforts and locations are summarized in Table 1. In areas with known kit fox populations (Peach Valley, North of Delta, and Montrose East) a total of 1012 trap nights of effort-were expended in trapping the 18 animals captured (56 trap nights/fox). The capture rate of foxes in.traps placed near(< 200 m) known fox dens is much higher. The 18 individual animals were captured in a total of 45 trap nights, a capture rate of 2. 5 trap nights per ·fox. It appears that the methods we are employing catch kit foxes efficiently if foxes are present. It appears kit fox populations across the areas surveyed are very low resulting in many trap nights of effort with no captures. In comparing this years trapping effort to efforts by Link, she captured 9 kit fox during 2,725 trap nights of effort, with all 9 animals captured during 836 trap nights (93 trap nights/fox) of effort in Peach Valley (Fitzgerald and Link 1993). • The SW Regional Office of CDOW has hired Mr. Doug.McCauley, a taxidermist from Delta, to work with the project crew to find additional kit fox populations. Mr. McCauley believes that many more kit foxes exist than our trapping results would indicate. The understanding with Mr. McCaughley is that he will try to locate kit fox populations using predator calling and night lighting. He has to show either the project crew or someone from the SW Regional Office the exact location of occupied dens and verify the presence of kit fox in order to be paid his fee. To date he has not taken the crew out but has indicated to Dent and Eussen that he knows of 2 or 3 active dens on the Colorado-Utah border. We are still trying to schedule a time when he can go out with us. �196 Table 1. Areas searched, dates of searches, and trap nights of effort, kit fox study, western Colorado, July 1, 1993 - June 30, 1994. Area Searched and County • Dates Searched Number of Trap Nights Peach Valley Montrose Co. 8-29 to 12-6-93 4-5 to 4-24-94 232 139 0 North of Delta Delta Co. 11-19-93 to 1-6-94 5-27 to 5-30-94 245 39 0 284/1 fox Montrose East Montrose Co. 5-27 to 6-18-94 357 9 357/9 foxes West Gunnison Gorge. Delta Co. 12-14 to 12-16-93 60 0 60/0 SEW of Wells Gulch. Delta Co. 6-21 to 6-27-94 230 0 230/0 Brown's Park Moffat co. 10-5 to 10-12-93 151 0 151/0 Grand Junction NW, Mesa Co. 10-20 to 10-28-93 129 0 129/0 172 0 172/0 1754 18 1754/18 DeBeque/Parachute 5-30 to 6-7-93 Mesa/Garfield Co's Totals Captures Total Trap Nights and Success by Area 8 371/8 foxes l V Trapping and Monitoring Effort - Peach Valley Population: Verbeck from 29 August to 6 December conducted 232 trap nights of effort in Peach Valley resulting in 8 captures of foxes: M13 (captured twice), Fl4, MlS, M16, MB, F18, and an animal that escaped before it could be sexed or marked (Table 2). Animals which were recaptures (F14, MlS, MB, F18) were given new radio-collars and ear tags. Invariably ear tags were torn out on most of the foxes recaptured. Anderson conducted 139 trap nights of effort in Peach Valley from 5 April to 24 April with no animals captured and had difficulty picking up radio signals from collared animals .. Anderson picked up radio-signals from 5 ( Fl8, M12, MS, FS, M13) of the 6 adults radioed in the area. However, he was unable to locate their precise den sites because of field conditions and problems with radio-receivers. on 26 March, Anderson recovered the carcass of Ml2 within a hundred meters of its den but could not verify cause of death. He recovered the carcass of a kit fox that had no ear tags or collar about the same distance from that same den on 13 April. Again it was not possible to estimate cause of death. F14 has been missing since January unless she is represented by the carcass (no radio-collar found) located near Ml2 - they were both trying to pair in December and January. Field crews verified presence of M13, Fl8, MS on 19· June in T51N, R9W, S29,30. This is 4-6 Jan north of locat~ons Verbeck found them ·using in late fall ·and early· winter (Fitzgerald and Verbeck 1993). They also reported picking up good signals in TS0N, R9W, S4 from 150.037 radio - a radio frequency that Anderson attributed to Ml2 found dead on 26 March. This error has to be investigated and resolved, and attempts made to recapture and recollar an;mals in the valley. Field crews report that Ml3 is with an apparently unmarked female in a den with 4 pups close to the water tank in lower (north) Peach Valley. They have also seen several V �197 \...-I foxes crossing the road at night in that same part of Peach Valley. Attempts will be made later this summer to capture and radio those animals. Montrose East Population: Anderson on 23 May received word of a family of foxes along the Landfill Road (Bostwick Park Road) in T49N, RSW, NE7 and began to observe animals in early morning and late afternoons. He estimated as many as 12 animals in the area including pups of the year. He showed the summer field crews the site on 27 May. Since 28 May a total of 9 kit fox have been trapped and marked in that population (Table 3). The population includes several adult females which may represent yearling animals that did not breed. The whelping den included pups from apparently two different litters based on size differences and estimated numbers of pups (7-8). The Montrose East population is located southeast of Flattop Mesa. Habitat is similar to Peach Valley and there is nothing to preclude mixing of the two populations which are about 12 km apart. However, trapping efforts from Flattop Mesa north to upper Peach Valley have not resulted in any other fox captures. The large numbers of females present in the population are encouraging provided sufficient males are available for mating in 1994-95. Several enthusiastic local residents are aware of this population and watch it carefully attempting to protect animals from being shot since they are located close to a heavily used county road. Table 2. Kit fox trapped in Peach Valley, Montrose County, Colorado, 1992-July 1, 1994 and dates of last sightings/radio-signals. CR=Collar replaced; ETR = Ear tags replaced. ~- \...,,I Capture or Date ·Located Sex 5/14/92 . M 5/31/92 11/23/92 F 6/25/92 Ear Tag Number Weight Kg Radio Collar Frequency Location Fate 2.3 not collared T51N/R9W/S29 Unknown 1 2.0 150.238 T51~/R9W/S29 Tl5S/R94W/S27 Killed by Coyote M 4 2.2 not collared T50N/R9W/Sl6 Unknown 9/28/92 M 2 2.7 150.309 T50N/R9W/S9 Unknown 9/28/92 3/1/93 1/3/94 4/6/94 F 5 2.5 150.338 CR150.956 T50N/R9W/S9 T50N/R9W/Sl7 T50N/R9W/S17 T50N/R9W/S9 Signal Weak 9/28/92 3/2/93 9/22/93 1/6/94 F 2.6 150.379 CR150.850 CR150.889 T50N/R9W/S9 T50N/R9W/S9 T50N/R9W/S16 T50N/R9W/Sl7 Unknown 2/23/93 .10/26/93 12/6/93 1/6/94 3/9/94 5/22/94 6/19/94 F 7 2.5 150.638 ETR18 2.6 CRlS0.594 T51N/R9W/S29 T50N/R9W/S5 TSON/R9W/SS TSON/R9W/S5 T50N/R9W/S16 TSON/R9W/S18 T51N/R9W/S29 Alive 2/23/93 10/26/93 12/6/93 1/6/94 3/26/94 M 6 ETR14 8 2.4 3.0 150.468 3.1 CRlS0.189 T51N/R9W/S29 TSON/R9W/S5 TSON/R9W/S5 TSON/R9W/SS TSON/R9W/S5 �198 Table 2 cont. 5/21/94 6/19/94 4/21/93 9/24/93 10/23/93 TS0N/R9W/S5 TS1N/R9W/S30 12 ETRlS M 1/6/94 3/26/94 9/20/93 11/9/93 12/14/93 3/31/94 13 M 2.5 2.8 2.7 150.708 CR150.037 150.813 5/21/94 6/19/94 9/30/93 16 M 2.3 150.499 11/22/93 Alive T50N/R9W/S22 TS0N/R9W/S8 TS0N/R9W/S17 TS0N/R9W/S16 TS0N/R9W/S8 TS0N/R9W/S16 Dead T50N/R9W/S5 T51N/R9W/S29 Alive T50N/R9W/S17 TS0N/R9W/S17 Unknown TS0N/R9W/S16 T50N/R9W/S16 TS0N/R9W/S5 Table 3. Kit foxes trapped in the Montrose East population, Montrose County, 1994. NL= non-lactating females not pups of the year; L = lactating. Location Fate Weight Kg Radio Collar Frequency F(NL) 21 recaptured 2.5 150.947 ·T49N/R9W/S7 F(NL) 22 2.5 150.403 T49N/R9W/S7 Alive 5/29/94 F(NL) 23 2.25 150.33.8 T49N/R9W/S7 Alive 5/29/94 M pup 24 1.75 not-collared T49N/R9W/S7 . Alive 5/30/94 F pup Ll76/Rl77 1.5 not-collared T49N/R9W/S7 Alive 5/30/94 F pup Ll78/R179 1.45 not-collared T49N/R9W/S7 Alive 5/31/94 6/7/94 F (L) Ll80/Rl81 2.3 recaptured 150.940 T49N/R9W/S7 T49N/R9W/S7 Alive 6/1/94 F pup Ll83/Rl84 1.8 not-collared T49N/R9W/S7 Alive 6/3/94 M Ad not-collared T49N/R9W/S12 Alive Capture or Date Located sex 5/29/94 5/30/94 5/29/94 Ear Tag Number L185/R186 3.0 Alive V Use of Baits: Table 4 summarizes the baits used in traps which captured kit fox. Verbeck made a detailed analysis of what baits were used during his 817 trap nights of effort and we are following that procedure this field season. Anderson conducted 139 trap nights of effort in Peach Valley with no successful captures during the month of April. During that period he tried a variety of baits including commercial fox scent, sardines, commercial raccoon-fox scent, and dead chicks. Be also put out carcasses of dead white leghorn chickens near several dens in the Valley with foxes paying little attention to such carrion. Since late May crews have conducted an additional 798 trap nights using a variety of baits. During V �199 trapping efforts at East Montrose, emphasis was given to taking as many animals as possible in as few a trap nights as necessary. As a result of that effort many traps were baited with multiple baits consisting of road killed cottontails and/or prairie dogs and turkeys with the idea being that the foxes might respond best to a variety of fresh killed meats, a technique that worked well. Although baits from local road-killed mammals and birds might work better than turkeys or turkey-lure combinations the numbers of traps being run precludes exclusive use of such local carrion. Table 4. Summary of kit fox captures/recaptures and types of baits used. May 14, 1992 to June 30, 1994. Investigator/Year Link/ParmetQ.r 92 to July 93 Verbeck Aug 93 to Jan 94 Present Crews April - Present Baits cottontail Cottontail/Turkey Cottontail/Turkey/P. Dog Prairie Dog/Turkey Prairie Dog Turkey Turkey/Commercial Lure Pheasant Turkey/Big Game Commercial Lure or w Sardines Chicken/commercial Lure Total Trap Nights Effort l/<50 5/77 3/41 5/70 0/39 4/10 0/6 6/>2,600 2/<200 0/408 2/679 1/32 0/66 0/100 0/39 2,725 817 937 Other Activity: Based on recommendations made by Fitzgerald and presented to CDOW personnel 11/15/93, the Colorado Wildlife commission on 3/10/94 closed the season on kit fox in Colorado and imposed trap and trapping restrictions for the Peach Valley, area. The Director of the CDOW on 22 March, placed the kit fox on the list of species of "special concern." The agency is presently contemplating future management, including whether it should be listed as "thr~atened." A meeting of CDOW personnel and the contractor will take place in late summer 1994 to discuss these issues. Link is finishing her thesis incorporating some of Verbeck' s findings into the paper. Gill has photographed animals in the Montrose Bast group. �253 Colorado Division of Wildlife Wildlife Research Report July 1995 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-7 Mammals Research Work Plan No. 10A Kit Fox Studies Job No. Period Covered: Kit Fox (Vulpes macrotis) status in Colorado 1 July 1, 1994 to June 30, 1995 Author: _J.P. Fitzgerald Personnel: J.P. Fitzgerald, L. Dent, J. Eussen, M. Link, J. Prather, M. Reddy, D. Watson, R. Basagoitia, S. Boyle, R. Hays, T . Beck, B. Gill., J. Olterman ABSTRACT In FY1994-95, 2326 trap nights of effort resulted in 46 captures of 31 individual kit foxes . Eighteen were animals not previously captured. Since work began in March 1992, 6805 trap nights of effort have resulted in capture of 38 kit foxes : 10 adult males, 7 juvenile males, 14 adult females, and 6 juvenile females. Hundreds of square kilometers of what appears to be suitable habitat is unoccupied or occupied at low levels. Trapping was conducted in parts of Mesa, Garfield, Delta, Montrose, and Moffat counties. Captures were made in Mesa and Garfield Counties (10 kit fox), and in Montrose and Delta Counties (21 foxes). Most captures were in the Peach Valley and Montrose East areas. No captures were made in Brown's Park, Moffat County in 171 trap nights of effort. Attempts to locate foxes during the winter using ATV's were not successful due to lack of snow. Of 37 collared or ear tagged foxes caught since 1992, the fate of 23 is unknown, 7 are dead, 7 are alive. Movement of 3 foxes between Montrose East and Peach Valley was documented. Home ranges of 2 Peach Valley and Montrose East foxes were estimated to be from 1.5 to 7.7 km • Foxes used an average of 3.7 dens per individual during the tracking period. Reproductive success is low. Of 14 adult females captured since 1992 only 6 litters of pups have been produced. The Wildlife Commission expanded the area with trap restrictions to portions of Mesa, Garfield, and western Delta counties. Plans for the next fiscal year are to complete the search effort, finalize reports, and make recommendations for any continued research on the species. m~nm1~111,1~ i~m BDOWD1 □ 765 �255 KIT FOX (WLPES MACROTIS) STATUS IN COLORADO James P. Fitzgerald P. N. Objective Document the geographic distribution and relative abundance of kit fox in Western Colorado. Segment Objectives 1. 2. 3. 4. Continue to monitor radio-collared foxes in Montrose, Delta, Mesa and Garfield counties. Continue search for new kit fox populations. Complete write-up of earlier field study effort (M. Link Thesis). Complete plans for 1995-96 field efforts. Methods Field methods for live-trapping were similar to those reported previously (Fitzgerald and Link 1993, Fitzgerald and Verbeck 1993). Live-trapping effort was concentrated in the Gunnison and Colorado River drainages. Boyle radiotracked foxes in fall and winter in the Montrose East and Peach Valley areas to estimate home ranges and nightly movements. Boyle, Basagoitia, and Hays searched for fox tracks in fall and winter months using ATV's. Dent, Eussen and Hatch have continued the search effort and monitored radioed animals during this spring and early summer. Results and Discussion LIVE TRAPPING EFFORTS: A total of 2326 trap nights of effort resulted in 46 captures of 31 different individuals (Table 1). Sixteen were animals captured for the first time. Table 1. Trapping effort and numbers of individual kit foxes captured by county and area, 1 July 94 to 30 June 95, westcentral Colorado. Trap Nights Captures County and Area Mesa/Garfield West and North of Grand Junction Mesa/Delta SE of Grand Junction to Delta Montrose/Delta Delta to SE of Montrose Moffat Browns Park-Vermillion Creek Totals 1125 8 528 2 502 21 171 0 2,326 31 Since May 1992 we have captured, marked, and released 38 individual kit foxes. Baits have usually been road-killed prairie dogs, cottontails, and ground squirrels supplemented with turkey chicks. A commercial attractor scent (chicken and fish, Rob Erickson's on Target A.D.C.) has been used in conjunction with the baits since mid-May 1995 in all traps. Since March 1992 trapping efficiency and capture rates have increased (Table 2) although much of the increase is probably the result of more concentrated effort in areas where foxes are known to be present. Seventy percent of �256 Table 2. Trapping effectiveness and capture rates, March 1992 to July 1, 1995, Kit Fox survey western Colorado. Trap Period Trap Nights # Individual Total Fox TNE/Indiv TNE/All Captures* Fox Captured Fox Capt*. Mar 92-June 93 Peach Valley only 2725 836 9 9 9 9 303 93 303 July 93-June 94 1754 18 21 97 88 July 94-June 95 2326 31 46 75 50 6805 38** 75 179 91 Total 93 *TNE = Trap nights of effort, all captures includes recaptures. ** Total of all individuals captured during the entire project. captures have been in the months of May, July, August and September, when recaptures that occur within 2 weeks of the last capture are excluded (trap happy animals were often caught on consecutive days) (Table 3). Table 3. Trapping success by age, sex and month of capture, 1992 - July 1, 1995, for foxes captured or recaptured when recaptures occurred at least 2 weeks post capture. No captures were made in October or November. Jan Feb Mar Jul Aug Sep Dec Month Apr May Jun Total Male Adult Juv Female Adult Juv Unknown Tot 3 1 0 1 3 1 1 1 1 3 4 1 3 3 2 3 2. 4 3 2 4 8 3 11 12 4 0 1 17 6 5 0 1 4 2 l 6 9 1 23 10 1 57 Of 37 foxes (10 adult males, 7 juvenile males, 13 adult females, 6 juvenile females) captured and collared or ear tagged we have recaptured 14 of them (4 adult males, 2 juvenile males, 6 adult females, 2 juvenile females) at least once (range 1-6). Of 23 animals captured once, 5 were adult males, 6 adult females, 6 juvenile males, 5 juvenile females, and 1 sex unknown. Forty-three percent of our adult animals have been recaptured compared to 31% of the juveniles. In late spring-early summer 1995 we have not captured any foxes in almost 400 trap nights of effort including areas known to have foxes. This may reflect increasing trap wariness as well as a possible decline in populations. Different trapping methods, including selective use of padded jaw traps will be tried in some of the areas where we are finding sign of foxes but not making any catches. Mesa/Garfield (Wand N of Grand Junction): Eight kit foxes were captured during 732 trap nights of effort in July and August (Fig 1, Table 4). An additional 393 trap nights of effort in May and June 1995 have not resulted in any captures. These 8 fox are the first captured in 3 field seasons and 2059 total trap nights of effort since 1992. Seven of the 8 foxes were radio-collared, none have been located since April 1995. �257 Fig 1. Length of radio-contact and status of collared kit foxes, Mesa and Garfield Counties, July 1 1994 - June 30 1995. Month and Year J A 1994 O N D J S 1995 F M A M J Location Rabbit Valley M (194/195) 151.244* F (196/197) 151.221 F (198/199) 151.034 Prairie Canyon/Baxter Pass U (153/154) 151.082 X------------------------ unknown x--- unknown x- unknown X- unknown Corcoran Point F(Jl26/127) 150.834 M(l30/131) 150.468 F(l32/133) 150.638 x---------------------- unknown x--------------------------- unknown x--------------------------- unknown Cheney Res. M(JlOl/102) x- unknown * Ear tags in ( ) followed by radio-collar frequency \--I \--I Three of the 8 animals (1M,2F) were captured in Rabbit Valley close to the Utah border. Neither female has been located since September 1994. The male was last located on 10 April 95. An animal of unknown sex was captured and radio-collared on 21 Aug in Prairie Canyon, Garfield County. It was accompanied by another fox which was not captured. The collared animal has not been located since its date of capture. Four foxes (2M, 2F), 2 of them juveniles (lM, lF), were captured north of Grand Junction near Corcoran Point. Three of them were radio-collared. Two (Ml50.468, Fl50.638) were last located 9 April 95. The third has not been located since 12 Dec. Two other pups were observed but not captured at Corcoran Point, Basagoitia photographed kit foxes visiting guzzlers in this same area in the summer of 1994. Field crews this spring found fresh kit fox sign at Prairie canyon and Corcoran Point but did not capture any foxes. The radio-collars on the 7 animals in this portion of the study region are close to their expected battery life and may no longer be working. Hundreds of square kilometers of what appears to be suitable range is unoccupied or inhabited by scattered individuals difficult to detect and capture. Mesa/Delta Counties (Grand Junction to Delta): \--I Two animals, 1 juvenile male and 1 adult female were captured near Cheney Reservoir (near the Mesa-Delta County line) in 528 trap nights of effort. The female broke her jaw in the trap and died during rehabilitation efforts. The male has not been located since it was collared. A juvenile male (MlS0.980, ear tag 17) captured 22 Nov 93 by Verbeck in T14S/R95W/S33, northeast of Delta north of the Gunnison River has not been located since its capture. These 3 foxes are the only captures made in this section of the study area in 1597 trap nights of effort since 1992. Basagoitia reported on 5 Sept 94 seeing a live fox along Highway 50 south of Cheney Reservoir. On 3 Sept he observed 2 dead kit foxes on the highway in Delta county, 1, 2 km NW of Adobe Flats reservoir the other by the Alkali Flats road. Basagoitia photographed a kit fox at a guzzler in Wells Gulch during the summer of 1994. Basagoitia and Hays spent considerable time live-trapping and searching for fox tracks and sign using ATV's from Jan-April. They placed 4 road killed deer as baits but found no evidence of fox visiting the carcasses. Effort suggests few foxes �258 Table 4. Locations of radioed foxes in the lower Gunnison and Colorado River Valleys, Mesa and Garfield Counties July 1, 1994 to July 1, 1995. V Sex Ear Tag Number Radio Collar Frequency M 194/195 151.244 F F 196/197 198/199 151.221 151.034 Prairie Canyon/Baxter Pass 8/21/94 U 153/154 151.082 T7S R105W S12 150.834 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 TlOS RlOOW 35 Capture Site Date, and Date of Last Radio-Contact Rabbit Valley 8/2/94 12/19/94 4/10/95 8/2/94 8/10/94 9/9/94 Corcoran Point 7/15/94 12/19/94 3/20/95 7/15/94 7/17/94 12/19/94 3/20/95 4/9/95 7/19/94 12/19/94 3/20/95 4/9/95 Cheney Res. 7/11/94 7/13/94 F(J) 126/127 M(J) M 128/129 130-131 F 132-133 M(J) 101-102 150.851 Jaw Broken - Died in Rehab F(A) not radio-collared 150.468 150.638 Location TlOS Rl04W S20 TlOS Rl04W S20 TlOS Rl04W Sl7 TlOS Rl04W 12 TlOS R104W 13 TlOS R104W 13 T13S R98W Tl3S R98W V 30 30? live in this expanse of the Gunnison River basin with many kilometers of suitable habitat unoccupied or occupied at very low densities. Peach Valley and Montrose East Populations: We have spent 2240 trap nights of effort in the region from Delta south of the Gunnison River to south and east of Montrose since the study began in 1992. This is the center of our only population of foxes and the site of most of our radio-tracking effort. Twenty-seven of the 38 individual kit foxes have been taken from this area. During the 94-95 reporting period, in 452 trap nights of effort, a total of 8 new foxes were captured. Four were captured in Peach Valley: adult female (FlSl.083), adult male (Ml51.257) and 2 female pups too small to radio-collar (they were collared with pink nylon collars). At Montrose East, 3 adult (MlSl.160, MlSl.107, MlSl.042) and 1 juvenile (Ml51.131) male were captured. In Peach Valley 11 adult kit foxes (SF, 6M) have been captured and radioed since 31 May 1992 (Fig 2, Table 5). Five of those animals, 3 females and 2 males are dead. Two were killed by coyotes, the cause of death of the others is unknown. The status of 4 animals is unknown. Two animals, male 151.095 and female 151.083) are still alive. Two radio-collared males (Ml51.209, Ml51.056) have moved from Montrose East to Peach Valley. These 4 animals are the only radio-collared animals known to be alive in Peach Valley. V �259 Fig 2. 1995. Length of radio-contact with collared kit foxes, Peach Valley, 1992- * = Animals that have moved to Peach Valley from Montrose East. 1992 MJSN 1993 JMMJSN 1994 JFMAMJJASOND 1995 JFMAMJ Animal F0.238 x-------Dead X-Unknown M0.309 F0.873 x--------------------- -------------------------------Alive F0.889 X----------------------------------------------Dead Fl.009 X-------------------------------------------------Dead Ml.095 X--------------------------------------------------Alive M0.037 X----------------------Dead Ml.177 X--------------------------------Unknown M0.499 x--Unknown X------------Unknown Fl.083 Ml.257 x--------Dead Ml.209* X--------------------Alive Ml.056* X--------------------Alive Table 5. Kit fox radio-collared in Peach Valley, 1992 - July 1, 1995, and dates of last sightings/radio-signals. New radio-collar frequencies are shown as they are replaced. ETR = ear tag replaced. ~ ~ ~ ~ Capture or Date Located Sex 5/31/92 11/23/92 F 9/28/92 M 2 2.7 9/28/92 4/6/94 4/14/95 6/28/95 F 5 2.5 9/28/92 3/2/93 9/22/93 1/6/94 3/15/95 F Location Fate T51N/R9W/S29 T15S/R94W/S27 Dead (C) 150.309 T50N/R9W/S9 Unknown 150.338 150.956 150.873 T50N/R9W/S9 T50N/R9W/S9 T51N,R9W/S32 T51N,R9W/S32 Alive 150.379 150.850 150.889 T50N/R9W/S9 T50N/R9W/S9 T50N/R9W/S9 T50N/R9W/S17 T49N/R8W/S? Dead T51N/R9W/S29 T50N/R9W/S5 T50N/R9W/S10 T50N/R9W/S5 T51N,R9W,S29 Dead (C) T51N/R9W/S29 TS0N/R9W/S5 T50N/R9W/S10 T51N/R9W/S29 T51N/R9W/S29 Alive T50N/R9W/S22 T50N/R9W/S8 T50N/R9W/S8 Dead Ear Tag Number Weight Kg Radio Collar Frequency 1 2.0 150.238 6 2.4 (moved from PV to SE of Montrose) 2/23/93 12/6/93 9/5/94 2/28/95 4/14/95 F 2/23/93 12/6/93 9/9/94 1/25/95 6/28/95 M 4/21/93 9/24/93 3/26/94 M 7 ETR18 8 2.5 2.6 2.0 3.0 3.1 150.468 150.189 151.095 ETR147/148 12 ETR15 150.638 150.594 151.009 2.5 2.8 150.708 150.037 �260 Table 5 continued. 9/20/93 6/19/94 1/27/95 M 13 9/30/93 11/22/93 M 7/14/94 9/7/94 12/19/94 1/27/95 F 190/191 7/18/94 9/9/94 11/18/94 M(J) 192/193 2.7 ETR46/47 16 150.813 151.177 2.3 150.499 T50N/R9W/S16 T51N/R9W/S29 T51N/R9W/S29 Unknown T50N/R9W/S17 T50N/R9W/S17 Unknown 151.083 T51N/R9W/S31 T51N/R9W/S31 T51N/R9W/S29,30 T51N/R9W/S29 Unknown 151.257 TS0N/R9W/S10 T50N/R9W/S10 T50N/R9W/S21 Dead T51N/R9W/S29 M 30/151 151.209 (First captured on 8/26/94 in Montrose East as Ml51.107) T51N/R9W/S32 4/18/95 T51N/R9W/S32 6/29/95 Alive 151.056 T50N/R9W/S9 M 26/27 (First captured on 8/24/94 in Montrose East as Ml51.131) T50N/R9W/S9 6/20/95 Alive 1.9 1.6 V 1/27/95 4/13/95 * Dead (C); killed by coyote V Adult female (Fl50.873) was captured by Dent in mid-April. He reported she was lactating but that an injury to her right rear leg was causing her to limp. She is still alive but not believed to have any pups. Dent recovered the remains of female 151.009 in Peach Valley on 14 April and judged she had been killed by a coyote. Peach Valley female (FlS0.889) first captured 28 Sept 1992 was recovered dead on 15 Mar 1995, 19 Jan south of her capture area and south of the Montrose East population. The area her carcass was recovered in had been trapped by field crews in the summer of 1994 with no fresh fox sign reported. Trapping by Hays in the area the carcass was recovered in did not yield any other foxes. V The male foxes alive in Peach Valley include 2 animals (MlSl.209, MlSl.056) that moved from the Montrose East site to Peach Valley after early January 1995. Basagoitia and Hays on 27 Jan captured a male with only l ear tag (30) and no radio-collar they recollared the animal (Ml51.209). This animal was radio-collared (Ml51.107) and ear tagged 30/29 on 26 Aug in Montrose East by Boyle. Between 10 Jan and 27 Jan he moved from Montrose East to Peach Valley and lost his collar. Dent recovered collar 151.107 on 18 April close to the Water Tank in Peach Valley not far from the area Hays and Basagoitia recaptured and collared the fox as Ml51.209. Male 151.056 moved to Peach Valley from Montrose East between 10 Jan and 13 April when Dent recaptured him in Peach Valley. He replaced radio-collar 151.131 with a new unit (Ml51.056). Boyle first captured this fox in Montrose East on 25 Aug. The third male in Peach Valley, Ml51.095 is an animal that has stayed in the Valley since first captured on 23 Feb 1993. In 1994, the Montrose East population included at least 13 animals (4 ~dult females, 3 adult males, 3 female pups, 3 male pups) clustered in a 5knt' area (Fig 3, Table 6). As of 28 June 1995, 5 of 11 animals collared in 1994 are alive. Three, Fl51.288, Fl51.037, Ml51.237, are at the Montrose East site. Two males (MlSl.056, Ml51.209) have moved to Peach Valley. Two are dead, the fate of 4 is unknown. Olterman has made several flights over the study area ti V �261 trying to locate radio-collared foxes. He last flew on 27 June and will be making other flights in the next few weeks to attempt to locate missing animals. Brown's Park, Moffat County: In the project year we spent 171 trap nights of effort in Brown's Park with no captures. Clait Braun of the Colorado Division of Wildlife reported seeing a kit or swift fox near Vermillion Creek in July 1994. Dent in late August spotlighted a small fox in that area but could not make an identification. These observations along with reports in 1993 indicate kit or swift foxes live in Moffat County. Three summers of trap effort with a total of 616 trap nights have not resulted in any captures. Figure 3. Length of radio contact and fate of radio-collared kit foxes, Montrose East population, May 1994 to July 1, 1995. Month and Year and Area M J Animal ID Fl51.288 Fl51.146 Fl51.037 Fl50.037 Fl50.940 Fl51.019 ( .020) Ml51.237 Fl51.056 Ml51.160 Ml51.209 Ml51.042 X---------------------------------------Alive X------------------------------Unknown X-------------------------Unknown X------------------------------Unknown x------Dead x---------------Unknown (Collar recovered) X-----------------------------------Alive X----------------------------Alive in PV X--------------Unknown X----------------------------Alive in PV x-----Dead J 1994 A S O N D J 1995 F M A M J Table 6. Kit foxes trapped in the Montrose East population in 1994 and status on July 1 1995. NL = non-lactating females; L = lactating. Capture or Date Located Sex Ear Tag Number Weight Kg Radio Collar Frequency 5/29/94 8/26/94 12/22/94 F(NL) 21/32 2.5 2.4 150.947 2.8 151.288 150.403 ETR22/38 2.5 2.4 2.3 151.146 23 2.3 150.338 1/10/95 4/17/95 F(NL) 6/27/95 ~/ ~ 5/29/94 8/25/94 1/10/95 F(NL) 22/28 5/29/94 8/28/94 9/15/94 F(NL) 5/29/94 M pup (recaptured on 7/7/95 - now Fl51.037) 24 1.75 not-collared Location Fate T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S6,7 T49N/R8W/S6 T49N/R8W/S7 T49N/R8W/S7 Alive T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S7 Unknown T49N/R8W/S7 T49N/R8W/S7 T49N/R9W/S12 Alive T49N/R9W/S7 Unknown • �262 V Table 6 continued. 5/30/94 8/25/94 F pup 176/177 1.5 not-collared 2.3 150.037 1/10/95 V T49N/R8W/S7 T49N/R8W/S6 T49N/R9W/S7 Unknown 5/30/94 F pup 178/179 1.4 not-collared T49N/R8W/S7 Unknown 5/31/94 6/7/94 7/28/94 F (L) 180/181 2.3 150.940 T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S9 Dead 5/3/94 8/28/94 9/16/94 11/11/94 F pup 182/183 M Ad 8/25/94 12/22/94 M Pup 26/27 1/10/95 not-collared 2.2 151.019( .020) Collar recovered no trace of carcass 6/3/94 8/25/94 1/10/95 4/18/95 6/27/95 4/13/95 6/27/95 1.8 184/185 3.0 not-collared 2.5 150.708 151.237 2.0 151.131 Moved to Peach Valley 151.056 = T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S8 T49N/R8W/S8 Unknown T49N/RSW/S7 T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S7 T49N/R8W/S6 Alive T49N/RSW/S7 T49N/RSW/S7 T49N/R8W/S7 T50N/R9W/S9 T50N/R9W/S9 Alive 8/27/94 12/29/94 1/4/95 M Pup 33/34 1.5 151.160 T49N/R8W/S7 T49N/R8W/S6,7 T49N/RSW/12 Unknown 8/26/94 12/22/94 1/10/95 1/27/95 4/18/95 M Ad 29/30 2.4 151.107 T49N/R9W/S7 151.209 T51N/R9W/S29 T51N/R9W/S32 Alive T49N/R9W/S7 T49N/R8W/S8 T49N/R8W/S18 Dead(C) 8/27/94 11/9/94 11/22/94 Moved to Peach Valley M Ad 48/49 2.3 151.042 T49N/R8,9W/S7,12 T49N/R9W/S12,7 V Behaviors of foxes in Montrose East and Peach Valley: A report on kit fox activity patterns is appended to this report (Boyle 1995). Boyle estimated home range size for 7 kit foxes in the Montrose East population and 2 animals in Peach Valley (Table 7). Animals at Montrose East averaged 3.6km2 (range 1.5-5.9), those in Peach Valley 7.5-7.7km2 • Home range sizes may reflect habitat and prey abundance differences between the 2 sites. Three animals have moved from Montrose East to Peach Valley (Ml51.209, M151.056) or out of Peach Valley (F150.889). This is the first evidence of foxes moving between the 2 areas. Boyle (1995) reported fox tracks north of Flattop Mesa between Peach Valley and Montrose East and did not believe they were made by collared animals. Scattered individuals may inhabit the area between these 2 sites but to date we have not captured any and several landowners have refused permission to cross their properties. Most radio-collared animals have not moved far from their original capture locations (Table 5, 6). The eight foxes which we have had radio-collared for the greatest length of time (Table 8) show little movement from their original V �263 Table 7. Estimated home range size for nine kit foxes, Peach Valley and Montrose East populations, October-January 1994-1995. From Boyle (1995). Animal No. Age/Sex Montrose East 150.037 150.403 150.947 150.708 151.131 151.160 151.107 Ad Ad Ad Peach Valley 151.009 151.083 Ad F Ad F sites of capture. predation. Juv F F F M Juv M Juv M Juv M Home Range Kmi # of Locations 56 5.9 4.7 1.5 4.7 2.3 2.5 3.9 53 50 36 38 36 7.7 7.5 22 18 52 Fidelity towards home ranges may reduce the probability for Home ranges of animals in the Montrose East study area overlapped and the individuals using different dens varied over the field season (Boyle 1995). Boyle reported 9 individual foxes used an average of 3.7 dens (range 2-6) from late September to mid-January. A den complex adjacent to the main road through the study area was continuously used by 2-4 foxes from late November to January 10. Previous work by Verbeck (Fitzgerald and Verbeck 1993) and Link (1995) agree with Boyle's observation of frequent den changes with a tendency to favor some dens more than others. Boyle (1995) estimated total minimum distance travelled and straight-line maximum distances traveled during single night movements of 5 individual foxes in the Montrose East group. He estimated total minimum distance to average 6.2 Jan and maximum straight line distance to average 2.0 km. Movements of the observer in tracking foxes may have caused them to increase their movements more than might occur if undisturbed. Link, Beck and Dent (personal communications) reported kit foxes being radio-tracked on foot were aware of their presence and moved rapidly away from them. In the narrow Montrose East Valley it would be hard to avoid harassing the foxes when tracking their movements. Boyle's effort confirms our working assumption that foxes do not travel more than a few Jan's in their nightly forays and traps have to be set close together and left out for several days. Reproductive Success: In December Boyle reported transitory pairing of F150.947 and M 151.131, followed by F150.947 then denning with F150.403. Dent in April could not locate any paired animals but did trap a lactating female. Field crews working in late spring and summer have not located any dens with pups. Since May 1992, we have captured 14 adult females at times of the year when reproductive status could be determined. Four have shown evidence of lactation or contained uterine scars (Fl50.238). In Montrose East in spring and summer 1994, 4 of 5 adult females were non-lactating. This field season the only female (150.873) in Peach Valley does not appear to have pups. In Montrose East female 151.288 did not show signs of pregnancy or lactation in mid April. Female 150.338 (captured on 7 July 1995) shows no sign of bearing pups. Since 1992 we know of only 6 litters of pups, 3 in Peach Valley each with 2 pups, 2 in Montrose East with 7-8 pups using a single den, and 1 at Corcoran Point with 4 pups. The low numbers of adult females that are reproducing may be due to a number of different causes including: lack of �264 Table 8. Estimated size of range of 8 kit foxes radio-collared for at least 7 months, Peach Valley and Montrose East populations. Fox# Months Radioed Estimated Range (km2) Peach Valley FlS0.873 FlSl.009 FlS0.889 MlSl.095 MlSl.177 28 16 8 7 Montrose East FlSl.288 FlSl.037 MlSl.237 13 7+ 12+ 3 5 33 25+ 29+ 7 8 8 4 males, lack of adequate food, disturbance from field crews radio-tracking them, or, in the case of the Montrose East animals high population density in a limited spacial area. other Activity: Link has completed her M.A. Thesis detailing the first 2 years of the project. Copies are enclosed with this report. The Wildlife Commission acted in September 1994 to expand the area with trapping restrictions to protect kit fox. Field plans have been completed for the 95-96 year: 1. We will continue to radio-collar animals captured in Peach Valley, Montrose East or at Corcoran Point but will not radio individuals taken elsewhere. All captured animals will be ear-tagged. 2. We will conclude our extensive trapping efforts with work to concentrate on the 64 km area along the base of the Book Cliffs from Corcoran Point to the Utah border and the 38 km long area at the base of Grand Mesa from Cheney Reservoir to Wells Gulch. 3. We will spend additional time in Brown's Park trying to resolve if kit or swift foxes live there. 4. From September 1995 through June 1996 we will use a monthly aerial search as the primary method for monitoring radioed animals in the Gunnison and Colorado river drainages. s. Depending on weather we will conduct a limited amount of snow-tracking during the winter of 95-96. 6. By April, 1996 we will complete reports and recommendations for continued research on kit fox in western Colorado. V V By: James P. Fitzgerald Contractor, University of Northern Colorado. V �313 Colorado Division of Wildlife Wildlife Wildlife Research Report July 1996 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-7 Mammals Research Work Plan No. lOA c!9rt Fox studies Job No. Kit fox (Vulpes macrotis) Status in Colorado Period Covered: July 1, 1995 to June 30, 1996 Author: J.P. Fitzgerald Personnel: J . P. Fitzgerald, J. Eussen, c. Hatch, J. Prather, S . Lechman, L. Dent, D. Finley, J. Olterman, T. Beck. ABSTRACT In 1368 trap nights of effort 8 new kit foxes were captured. Five of them were from a family group (1 adult female, 2 female pups, 2 male pups) captured in July 1995 in Peach Valley. An adult male was captured at Cheney Reservoir and a juvenile male pup and adult female were captured at Corcoran Point. The total number of individual kit foxes trapped since 1992 is 47 with 33 of them from the Peach Valley-Montrose East complex. A total of 17 individual kit foxes were radio-tracked during 1995-96. Nine (53%) of the 17 animals died during the study period. Four deaths were attributed to coyotes, 2 to drowning, 1 to an automobile, and 2 from undetermined causes . Two litters of pups were born in the Montrose East area in 1996 with female F23 being killed by a coyote after her pups came above ground . . The fate of those p~ps is unknown. One other female living between Peach Valley and Montrose East may have young. J. Eussen will be working on kit fox food habits as a thesis project in 1996. The draft final report of project activities was completed and reviewed by T. Beck. Revisions are being made and the final report wlll be delivered by August 1. i]ID1i~Dm1 1 I BDOW010805 �315 KIT FOX (VULPES MACROTIS) STAms IR COI,9RADO James P. Fitzgerald P, N, QBJECTIYE Document the geographic distribution and relative abundance of kit fox in Western Colorado. SEGMENT QBJECTIYES 1. Continue to monitor radio-collared foxes in Montrose, Delta, Mesa and Garfield.counties. 2. Continue search for new kit fox populations. 3. Compl~te draft of final project report. METHODS Field methods for live-trapping were similar to those reported previously (Fitzgerald and Link 1993, Fitzgerald and Verbeck 1993). Limited trapping was also conducted using 1.5, soft-catch, leg-hold traps at baited dirt-hole sets. Trapping efforts were concentrated in the Gunnison and Colorado River Drainages in Mesa, Garfield, Delta, and Montrose counties and in northwestern Moffat county. Field personnel continued to monitor and document locatio~s of radio-collared foxes using searches with a fixed wing aircraft piloted by J. Olterman, or by ground tracking. RESULTS AND DJSCQSSIQH Live ~rapping Bffort From July 1, 1995 to June 30, .1996 we conducted 1368 trap nights of effort resulting in capture of 8 new foxes (Table 1.). All trapping was done in Moffat County.or in the Gunnison River-Lower Colorado River drainages in Mesa, Garfield, Delta and Montrose counties. Two foxes were captured at Corcoran Point, a juvenile male and-an adult female. An adult male was captured at Cheney Reservoir. In Peach Valley, 2 juvenile females, 2 juvenile males, and an adult female were captured at a whelping den (Table 2). Field crews again. failed to capture any foxes in Moffat County, although scat believed to be from kit or swift foxes was discovered and a CDOW biologist (C. Braun) reported seeing a swift or kit fox crossing the road near Vermillion Creek. The total number of individual kit foxes trapped since the study began in 1992 is 47. T~irty-three of the captures have been made in the Peach Valley-Montrose East complex. �316 Table 1. Trapping effort and numbers of individual kit foxes captured by county and area, July 1 1995-June 30, 1996. County/Area Trap Nights New· Captures· Mesa-Garfield Counties Prairie Canyon to Corcoran Point Areas 347 2 Mesa-Delta Counties Cheney Reservoir to -East of Del ta Airport 493 1 Montrose-Delta Counties Peach Valley-Montrose East Complex 368 5 Moffat County Browns Park-Vermillion . Creek 160 0 Location, sex, age class, ear-tag·number and radio-collar frequency for previously uncaptured kit foxes, 1995-96 fiscal year. Table 2. Location Sex/Ear Tag Radio-collar Date Captured Status M(J)310 F(A)311 150.189 8/12/95 151.-186 11/3/95 Unknown Dead M(A)312 151.083 12/4/95 Dead 150.029 150.728 150.004 150.920 151.009 7/28/95 7/26/95 7/.27/95 7/26/95 7/27/95 Alive Dead Dead Dead Alive V V V Corcoran Point Cheney Reservoir Peach Valley F(A)309 F(J)306 F(J)308 M(J)305 M(J)307 V �317 Monitoring of Radio-collared Foxes During the fiscal year, field crews periodically located radioed animals during ground searches. Jim Olterman also made a number of flights to locate animals. A total of 17 foxes (9 males, 8 females) were located and monitored during 1995-96, including 2 male and 2 female pups marked in July 1995, three of which have died (Table 3). Two litters of pups came above ground in May 1996 in Montrose East, one litter (F23's) had 4 pups, the other litter (F2l's) has an unknown number of young. F309 living between Peach Valley and Montrose East is also believed to have pups but the whelping den has not been located. Nine animals died during the year with deaths of 4 attributed to coyotes (F306, F308, F23, M312). Two died from probable drowning (M30, F311), 1 was road killed (M305) and two (M26, F309) died from undetermined causes. ~her Activity The first draft of the final report wae finished and reviewed by T. Beck. It is being revised and will be.submitted by the end-o~ August pending receipt of some additional information from the Montrose Office· of the BLM. The state of Utah has been contacted to see whether UNC can do some trapping in late summer along the Utah-Colorado border to assess kit fox populations in Utah that might provide migrants to Colorado stocks. J~ Eussen is collecting kit fox scat and will be doing a food habits analysis for a M.A. thesis using his materials and material collected by other field workers. By: James P. Fitzgerald, Contractor, University of Northern Colorado �318 Table 3. Kit foxes alive during the 1995-96 fiscal year and their status as of June 30 1996. Site & Date of Capture/ Tracking Corcoran Point 8/12/95 11/2/95 3/17/96 5/16/96 Sex/Age Ear Tag# Radio-collar Frequency JM 310 150.189 n.c. Location T9S,RlOOW,S25 T9S,RlOOW,S34 TlOS,RlOOW,SlO signal too weak to locate Status as of 30 June Dead Cheney Reservoir 12/4/95 AM 312 151.083 5/16/96 moved to Wells Gulch 6/18/96 T3S~R2E,S24 ·T4S, R3E, S13 T4S,R3E,S13 Dead Delta Airport 11/19/95 T14S,R96W,S36 Unknown AF 311 151.186 collar at private residence AM 33* 151.160 Peach Valley 9/28/92 AF 5 150.338 4/6/94 • 150.956 4/14/94 150.873 8/15/95 10/11/95 12/4/95 moved to Alkali Gulch 8/26/94 12/22/94 1/10/95 1/27/95 10/11/95 2/14/96 6/18/96 8/24/94 1/10/95 4/13/95 10/11/95 2/14/96 4/9/96 7/26/95 2/14/96 4/9/96 AM 30 151.107 moved to PV from ME 30/151 151.209 collar in Selig ~anal JM 26 151.131 moved to PV from ME 151.056 JF 306 150.728 V Unknown TlN,RlW,SlO TlOS,RlOOW,SlO T1N,R1E,S29 TlN,RlW,S36 11/3/95 3/17/96 5/16/96 6/18/96 V V V TSON,R9W,S9 T50N,R9W,S9 T51N,R9W,S32 T51N,R9W,S7 T51N,R9w,s29:..32 Tl5S,R97W,Sl Unknown T49N,R9W,S7 T49N,R9W,S12 T49N, R9W, S_12 T51N,R9W,S29 T51N,R9W,S29-32 T51N,R9W,S30 TS1N,R9W,S29 Dead T49N,R8W,S7 T49N,R8W,S7 T50N,R9W,S9 T51N,R9W,S29 T50N,R9W,S16 TSON,R9W,S16 Dead TSON,R9W,S16 TSON,R9W,Sl6 TSON,R9W,S16 Dead V V �Table 3 (continued) Site & Date of Capture/ Tracking Sex/Age Ear Tag# Radio-collar Frequency 7/26/95 12/25/95 JM 305 150.920 7/27/95 2/14/96 4/9/96 JF 308 150.004 moved to ME moved back to PV JM.307 7/27/95 5/16/96 6/18/96 7/28/95 2/14/96 • 6/18/96 n. c. 151.009 AF 309 150.029 moved to ME moved between ME and PV .Montrose East 5/29/94 8/26/94 4/17/95 2/14/96 6/18/96 AF 21 150.947 52/52 151.288 150.098 150.403 Location T50N,R9W,S16 Tl5S,R95W,S33 Status as of 30 June Dead T50N,R9W,Sl6 T49N,RSW,S24 T51N,R9W,S30 Dead T50N,R9W,Sl~ · T49N,R9W,S6 T49N,R9W,S6 Alive T50N,R9W,S16 T49N,R8W,S9 T49N,R8W,S3 Dead T49N,R8W,S7 T49N,R8W,S7 T49N,R8W,S7 T49N,RSW,S7 T49N,R9W,S6 Alive T49N,RSW,S7 T49N,R8W,S7 T49N,RSW,S7 Unknown T49N,R8W,S7 T49N,R8W,S7 T49N,R8W,S5 T49N,R8W,S7 T49N,R8W,S9 Dead 5/29/94 8/25/94 1/10/95 AF 22 5/29/94 9/15/94 7/7/95 2/14/96 6/18/96 AF 23 6/3/94 AM 184 n. c. 150.708 151.237 T49N,RSW,S7 T49N,RSW,S7 T49N,RSW,S7 TS0N,R9W,S18T50N:, R9w·, Sl6 T50N,R9W,S26 T49N,R9W,Sll-12 Alive JM 33 151.160 moved ~orth of Delta Airport T49N,RSW,S7 T49N,RSW,S6-7 T49N,RSW,S12 T14S,R69W,S36 moved to Alkali Gulch Tl5S,R97W,Sl 151.146 151.042 8/25/94 4/18/95 10/11/95 2/14/96 5/16/96 6/18/96 8/27/94 12/29/94 1/4/95 10/11/95 11/19/95 12/4/95 150.338 T14S,R96W,S36 Unknown ������������������������������������������������������������101 Colorado Division of Wildlife Wildlife Research Report July 1998 SEGMENT NARRATIVE State of Project No. Work Package No. Colorado W-153-R-ll 0663 Task No. cost center 3430 Mammals Program Species of Special Concern/Species at Risk conservation Kit fox conservation Period covered: July 1, 1997 - June 30, 1998 Author: T.D.I. Beck Personnel: T. Beck, G. Bock, D. Coven, J. Garner, R. Gill, M. McLain, P. Schnurr, L. Willmarth; CDOW ABSTRACT The Program Narrative was modified to more clearly outline the multiple stages of the development of a conservation strategy. The initial phase of biological assessment was begun this segment. Sixty-three cameras, triggered by active-infra-red sensors, were deployed throughout the Uncompahgre and Gunnison valleys. Seven photos of kit fox were obtained; all are believed to be different individuals. Four of the photos were at or near dens initially located by ground searches. In addition, 2 active kit fox dens were located; one of which had 2 individuals and the other only one. Of the 3 dens with pairs present, none appeared to have young-of-the-year. All but two of the photos and sightings were in the Peach Valley-Montrose East habitat area. This isolated area of habitat is only 90 km2 in area. The Gunnison Valley area comprises 316 km2 of habitat, of which approximately 50\ is deemed marginally suitable because of lack of den sites. No efforts were made to trap and collar kit fox during the whelping season. �103 KIT FOX (VULPES HACROTIS) STATUS IN COLORADO Thomas D. I. Beck P,N, Objective Develop and implement a conservation strategy to recover and conserve kit fox populations in Colorado. segment Objectives 1. Develop a conservation strategy to recover and conserve kit fox in western Colorado. 2. Survey for presence of fox in Gunnison valley area with infra-red activated cameras. 3. Capture and radio-collar adult kit fox in both the Uncompahgre and Gunnison valley areas. METHODS AND MATERIALS The earlier version of the Program Narrative was modified to more clearly outline the progressive stages of the conservation strategy development. The modified document was submitted in May 1998. Ground searches for kit fox sign and dens were conducted in the Uncompahgre and Gunnison valleys on 40 days during April-June 1998. Remote 35mm cameras, activated by active-infra-red sensors, were deployed in areas with fresh kit fox sign, areas with old fox dens, and likely travel areas. The camera system was developed by TrailMaster (Lenexa, KS) and was essentially the same system as used by Beck on black bear (Ursus americanus) studies (Beck 1995). The distance from the camera to the infra-red transmitter was 2 m; camera height above ground was 15-30 cm. A pipe was driven into the ground 10 cm in front of the infra-red transmitter and one of several baits (beaver meat, chicken flesh lure) were placed down in the pipe to minimize bird conflict. The recorder unit was programmed so that the infra-red beam had to be broken for 0.15 sec to be recorded ( value of P = 3) and only a 6 sec delay between successive pictures. Color print film, ASA 400, in rolls of 24 and 36 exposures were used. Cameras were left at locations for varying periods, depending on area, work schedule, and need for cameras in other areas. Observations of active kit fox dens were conducted at dusk on 9 evenings, in hopes of documenting presence of pups. Observations were made with binoculars or a night-vision scope at distances of 30 to 100 m. Maps of areal extent of salt desert shrub communities were obtained from CDOW Habitat Section. Also, 15-minute quad maps were used for plotting camera locations and all fresh fox sign. �104 RESULTS ARD DISCUSSION Program Narrative Modification The revised Program Narrative describes 5 phases in the development of a conservation strategy: Biological Assessment, Socio-Economic Assessment, Political Assessment, Conservation Planning and Implementation, and Conservation Evaluation. The development of a formal Conservation strategy will occur in Phase IV. It is believed that by doing the biological, social, and political assessments as precursors to the formal plan, support for the plan will be more wide-based and solid (Clark et al. 1994). Biological Assessment Analysis of the work reported by Fitzgerald (1996) suggested that summer was the period of lowest trap success, and the majority of search effort had been conducted in the summer. Thus it was deemed prudent to resurvey much of the available kit fox habitat during spring and fall seasons, utilizing a different technology than live-trapping. Ground searches for kit fox dens and spoor were conducted on 40 days during April-June, 1998 by either one or two researchers throughout the 406 km2 of habitat in the Gunnison and Uncompahgre valleys. Only 4 active dens were located, all in den complexes previously identified in the Uncompahgre Valley. Three of the dens supported kit fox pairs while the other had a single fox. Cameras were set near 3 of the 4 dens. The den in the Montrose land fill (kit fox pair) was not equipped with a camera because of the high human traffic flow by the den. The camera at the single den malfunctioned so no photos were made. We obtained 2 photos of kit fox at each of the other 2 dens. A total of 63 camera sets were made, for periods ranging from 7 to 28 days. Thirty-five of the sets were for periods of 10-15 days. Three kit fox photos were obtained in areas where we did not find active fox dens or spoor. Subsequent searches also resulted in no active dens found. Based on camera and ground searches, 8 kit fox were located in the Uncompahgre Valley and 2 in the Gunnison Valley just west of the Delta airport. Photos were obtained from all active den sites where cameras operated correctly; thus supporting the use of cameras as an effective survey tool. Based on 9 evening observations and 8 daytime examinations of den sites it did not appear that any of the 3 kit fox pairs produced any pups in Spring, 1998. Four natal dens of red fox (Vulpes vulpes) were located in the saltbush habitats in what appeared to be suitable kit fox habitat. The camera surveys also produced photos of the following: badger (3), house cat (3), dog (1), raccoon (7), cottontail rabbit (76), prairie dog (3), antelope ground squirrel (16), striped skunk (3), domestic cattle (6), magpies (44), horned lark (9), meadow lark (1), and a snake (1). Sixteen cameras produced no photos, 3 had mechanical malfunctions, and 2 were disturbed and made inoperable by people. The Uncompahgre Valley area is comprised of approximately 90 km2 of suitable kit fox habitat; arranged in an oblong pattern 30 km N-S with an average width of less than 4 km. Eight of the observed kit fox were in this area. This area is separated from the Gunnison Valley habitats by agricultural land, housing developments, a highway, and a river; resulting in a 7-9 km long obstacle course to inhibit dispersal. Based on the range of kit fox densities summarized by White and Garrott (1997) (0.16-0.7/km2 ) this area of habitat �105 would likely only support 14-63 kit foxes. this lower bound. Current density appears to be near The Gunnison Valley area is approximately 316 km2 of apparently suitable kit fox habitat. Only 2 kit fox were located in this region; both at the same camera and likely a pair. They were at the southern tip of the habitat area. Approximately 50% of the habitat is characterized by a volcanic rock cap which severely limits den sites. No old kit fox dens were located in these formations and only a few badger and coyote dens. It appears that the lack of old dens limits the value of this region. The northernmost section of possible habitat in the Gunnison Valley lies between Kannah Creek and the Colorado River. It is approximately 74 km2 in area but separated from the upper valley by extensive irrigated farm lands and new housing developments. No fresh or old kit fox sign was discovered in this area. It was decided not to trap and collar adult foxes during the whelping season because of the added stress of this activity to the individual foxes (Cypher 1997). The small number of kit foxes present seems to justify minimum intrusion during this period. Literature cited Beck, T.D.I. 1995. Development of black bear inventory techniques. Wildlife, Fed. Aid. Rep. W-153-R-8. llpp. Colo. Div. Clark, T.W., R.P. Reading, A.L. Clarke. Eds. 1994. Endangered Species Recovery:Finding the Lessons, Improving the Process. Island Press, Washington, D.C. 450 pp. Cypher, B.L. 1997. Effects of radiocollars on San Joaquin Kit Foxes. Wildl. Manage. 61(4):1412-1423. J. Fitzgerald, J.P. 1996. Status and distribution of the kit fox (Vulpes Colo. Div. Wildlife, Final Fed. Aid. Rep. 153-R-7. 78 pp. macrotis) in Western Colorado. White, P.J. and R.A. Garrott. 1997. Factors regulating kit fox populations. Can. J. Zool. 75:1982-1988. Prepared by Thomas Beck Wildlife Researcher w- �55 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-12 Work Package No. __0-=-66=3;;......__ _ _ __ Task No. - - - - ~ 1 ------- Cost Center 3430 Mammals Program Species of Special Concern/Species at Risk Conservation Kit fox Conservation Period Covered: July 1, 1998,. June 30, 1999 Author: T. D. I. Beck Personnel: T. Beck, D. Coven, P. Creeden, V. Graham, M McLain, P. Schnurr, B. Sommerville, L. Willmarth; CDOW ABSTRACT Biological assessment work was expanded to the Colorado River Valley in this segment Fiftyfour cameras, triggered by active-infra-red sensors, were deployed throughout a nearly 800 km2 area for 12-30 days each. No photos of kit fox were obtained. Surveys of kit fox dens active in 1998 found only one den active in 1999; however, the pair apparently did not have any young again this year. A combination of GAP mapping and ground mapping was used to estimate the habitat potential for restoration of kit fox in western Colorado. Three distinct areas were identified: the Colorado, Gunnison, and Uncompahgre Valleys. The Colorado valley is isolated from the other two by urban development and irrigated agriculture. The Colorado River Valley is the largest contiguous area (685 km2) and has the highest percentage of public land Thus, it is likely the best area for kit fox restoration efforts. Successful restoration of kit fox throughout the entire 1310 km2 of suitable kit fox habitat in Colorado could result in kit fox populations varying from 182-728; based on densities reported in the literature. Primary negative factors to be addressed are housing developments, greater isolation of habitats, and red fox pioneering into salt desert shrub communities. �57 KIT FOX (VULPES MACROTIS) STATUS IN COLORADO Thomas D. I. Beck P.N. Objective Develop and implement a conservation strategy to recover and conserve kit fox populations in Colorado. Segment Objectives 1. 2. 3. Conduct the biological assessment work necessary to develop an effective conservation strategy for the conservation of kit fox in western Colorado. Survey for presence of kit fox in Gunnison and ·uncompahgre Valley areas with infra-red activated cameras. Capture and radio-collar adult and juvenile kit fox in both the Uncompahgre and Gunnison valley areas. METHODS AND MATERIALS Plans for field work were modified significantly in July in response to the dearth of kit fox activity found in the Gunnison and Uncompahgre Valleys. Additionally, much oftheiandscape in the 2 valleys are either marginally suitable or becoming unsuitable through a combination of natural features and human development. Therefore, emphasis was shifted to better map the available habitat and conduct kit fox surveys in the Colorado River Valley. Ground searches for kit fox sign and dens were conducted in the Colorado River Valley on 40 days during September-November 1998. Remote 35mm cameras, activated by active-infra-red sensors, were deployed in areas with fresh kit fox sign, areas with old fox dens, and likely travel areas. The camera system was developed by TrailMaster (Lenexa, KS) and was essentially the same system as used by Beck on black bear (Ursus americanus) studies (Beck 1995). The distance from the camera to the infra-red transmitter was 2 m~ camera height above ground was 15-30_ cm. A pipe was driven into the ground 10 cm in front of the infra-red transmitter and one of several baits (beaver meat, chicken flesh lure) were placed down in the pipe to minimize bird conflict. The recorder unit was programmed so that the infra-red beam had to be broken for 0.15 sec to be recorded ( value of P = 3) and only a 6 sec delay between successive pictures. Color print film, _ASA 400, in rolls of24 and 36 exposures were used. Cameras were left at locations for varying periods of 12-30 days, depending on area, work schedule, and need for cameras in other areas. Observations of an active kit fox den were conducted at dusk on 3 evenings in May 1999, in hopes of documenting presence of pups. Observations were made with binoculars or a night-vision scope at distances of30 to 100 m. Historic den sites in the Uncompahgre Valley were visited in May 1999 to check for kit fox activity. Maps of areal extent of salt desert shrub communities were obtained from CDOW Habitat Section. Acreage of salt desert shrub and irrigated lands were estimated from the GAP maps. The land ownership of the primary habitat (salt desert shrub) was also estimated from the GAP maps. Onsite field mapping was conducted to better assess the utility of much of the salt desert shrub component on private land since much of this land has been undergoing significant housing development. Also, 15-minute quad maps were used for plotting camera locations and all fresh fox sign. �58 RES ULTS AND DISCUSSION Biological Assessment Kit Fox Distribution and Abundance - Analysis of the work reported by Fitzgerald (1996) suggested that summer was the period of lowest trap success, and the majority of search effort had been conducted in the summer. Thus it was deemed prudent to resurvey much of the available kit fox habitat during spring and fall seasons, utilizing a different technology than live-trapping. Ground searches for kit fox dens and spoor were conducted during spring 1998 in the Gunnison and Uncompahgre Valleys. Similar searches were conducted in the Colorado River Valley during September-November 1998. Fifty-four cameras were placed for periods of 12-30 days. Two camera units were stolen. No kit fox were photographed at the 52 sites spread throughout the approximately 800 km2 Colorado River valley. No active fox dens were located during ground searches. A variety of wildlife was photographed: cottontail rabbits (158),jackrabbits (7), antelope ground squirrel (2), coyote (6), badger (6), rock squirrel (6), bobcat (1), chipmunk (1), pronghorn (1), magpie (31 ), owl (1 ), unk. birds (3 ). Frequent rains and cold temperatures resulted in the loss of 38 images during the last 2 weeks of work because the plexiglass dust cover frosted over; causing a frosty blur on the photograph. In May, 1999 a dead male kit fox was recovered along a paved road in Colorado National Monument by DWM Paul Creeden. It was freshly killed when retrieved about 0430. The area is in the pinon-juniper vegetation community, approximately 500 m higher than the desert floor. About 3 hours was spent on a ground search in the area looking for any denning activity or otl;ter sign but none was found It was not the normal vegetation or terrain for kit fox. All kit fox dens-active in 1998 were checked in May 1999 for fox activity. The Montrose landfill den again had a pair of kit fox. This pair was observed on 3 evenings in May but there was no indication of pups. Volunteer observers who work at the landfill reported no pup activity during the summer. None of the other known kit fox dens checked had any indication of kit fox activity. Additionally, 3 of the red fox (Vulpes vulpes) dens active in 1998 which were located in the salt desert shrub community were also active in 1999. Prey Abundance - Comparative prey surveys were initially to be conducted in Fall 1998. However, based on the low numbers of kit fox located in Spring 1998 it was decided to expand general surveys to the Colorado River Valley instead Also, preliminary mapping suggested the Uncompahgre and Gunnison Valleys provided only modest opportunity for kit fox restoration because of limited habitat. In addition, the Colorado Legislature debated a bill in the 1999 session which could have restricted the authority of the CDOW to implement kit fox augmentation. This bill (HB 99-1299) was passed in late April and signed into law in May. However, final wording did not cover the kit fox program (in contrast to original language). However, it was decided not to do extensive prey base work pending resolution of this issue. Potential Habitat The western valleys of Colorado which historically supported kit fox were divided into 3 distinct valley segments: Uncompahgre, Gunnison, Colorado. The Gunnison Valley area was subdivided into 3 segments because the central segment is a region with basalt cap rock close to the surface and den sites are extremely limited. Even badger diggings are uncommon in this reach; which is also the area where 3 roadkill kit fox have been documented in the past 5 years. �59 Based on the GAP vegetation maps, there is an estimated 54 7 km2 of salt desert shrub in the Uncompahgre Valley unit (Fig. 1). This unit also has the highest area of irrigated farm land (528 km2), all of which historically was salt desert shrub. It also has a high proportion of existing salt desert shrub in private land status (45.8%). Ground mapping was conducted to exclude peripheral areas of salt desert shrub as well as areas which have been developed for human housing. Radio telemetry work on kit fox in this valley strongly indicated the kit foxes did not venture into the developed desert areas but remained in a relatively small core area Thus, the suitable kit fox habitat for the near future is more likely about 140 km2. This area is separated from the Gunnison Valley habitats by agricultural land, housing developments, a highway, and a river; resulting in a 7-9 km long obstacle course to inhibit dispersal. Based on the range of kit fox densities summarized by White and Garrott (1997) (0.160. 7/km2) this area of habitat would likely only support 22-98 kit foxes. The Gunnison Valley area has approximately 609 km2 of salt desert shrub vegetation (Fig. 2). Only 2 kit fox were located in this region in 1998, 5 were trapped here during 1993-1995, and 3 road kills have been documented. The East Gunnison area (179 km2) only has about 18 km2 of irrigated land but does have some residential development and the irrigated land may serve as a barrier to animals moving east of Surface Creek. Thus, suitable kit fox habitat for recovery is closer to 120 km2, of which 66% is in public ownership. The Central Gunnison area (250 km2) has about 10 km2 of irrigated farmland. This is the area of volcanic rock near the surface which appears to severely limit underground dens. Most of this land is in public ownership (81°/o) and housing development is less a problem here. Thus, about 225 km2of land is marginally suitable for kit fox recovery. Because of the lack of den sites for escapement, this area will likely always be a mortality sink for neighboring populations of kit fox. A small area near Cheney Reservoir has the more typical soil formations found in the salt desert shrub areas and did support a kit fox family in 1994-95. No kit fox activity has been recorded there since. The area is private land and the current owner has been unsuccessful at attempts to subdivide for housing, primarily because of issues of potable water supply. Unsolicited information from local varmint hunters suggests that red fox have been colonizing this area rapidly during the past 2 years. Earlier work on kit fox surveys in this area did not document red fox but both dens and red foxes were observed here in spring of 1998. The North Gunnison area abuts the Colorado River and Grand Junction urban area to the north. This area is highly impacted by housing development throughout the salt desert shrub type. Based on the GAP maps, there are 180 km2 of salt desert shrub in this unit, of which 48% is private. There is an additional 59 km2 of irrigated farm land. No kit fox have been located in this area by any of our surveys this decade. Suitable area for kit fox restoration in the near future is probably closer to 140 km2. Total suitable habitat for kit fox in the Gunnison Valley is approximately 385 km2. It is unlikely this area would support high densities of kit fox because of the denning problem in the Central area Thus, a projection of 50-150 kit fox possible should restoration be successful seems to be the best possible outcome. The housing development in the north coupled with the den problems in the central suggest that the East unit may be the best area for kit fox populations, which could then support 25-85 kit fox. The Colorado River Valley supports the largest intact area of salt desert shrub, about 797 km2 based on the GAP map. Most (85%) is in public ownership. Irrigated lands amount to 319 km2, mostly in the eastern end (Fig. 3). Ten kit fox were captured here in 1994 and 1995. An active den with a single kit fox was discovered in 1997 near Fruita However, the lack of any photographs of kit fox or sign at historic kit fox dens in 1998 strongly suggests the current density of kit fox in this valley is low. This unit appears to have the lowest probability for loss of kit fox habitat and will likely have at least 685 km 2 of suitable habitat for a long period. Based on kit fox densities reported in White and Garrott (1997), this area could potentially support 110-480 kit fox if fully occupied. �60 Capture Efforts It was decided not to trap and collar adult foxes during the whelping season because of the added stress of this activity to the individual foxes (Cypher 1997). The small number of kit foxes present seems to justify minimum intrusion during this period. There have been no juveniles located in 1998 or 1999 to tag. Literature Cited Beck, T. D. I. 1995. Development of black bear inventory techniques. Colo. Div. Wildlife, Fed. Aid. Rep. W-153-R-8. l lpp. Cypher, B. L. 1997. Effects ofradiocollars on San Joaquin Kit Foxes. J. Wildl. Manage. 61(4):14121423. Fitzgerald, J.P. 1996. Status and distribution of the kit fox (Vulpes macrotis) in Western Colorado. Colo. Div. Wildlife, Final Fed. Aid. Rept. W-153-R-7. 78 pp. White, P. J. and R A Garrott. 1997. Factors regulating kit fox populations. Can. J. Zool. 75: 19821988. �61 N A GREAT OUTDOORS C0L0llAD0 • Colorado Division of Wildlife May, 1999 e:::::! Irrigated Crop Type Ill Selected Vegetation Types• O 1 2 Kilometers ~ • Desert Shrub Saltbush Fans & Rats Greasewood Fans & Flats Figure 1. Selected vegetation types in the Uncompahgre Plateau. O 1 2 ~ 3 4 Miles i,i.iiiiij �N A O'I t-.J ,,,subUnlt Boundaries c;J Irrigated Crop Type ,,,.. f lm1ll Sefected Vegetation Types• • Desert Shrub Saltbush Fans & Flats ats / Grease~d Fans & Fla:_; ~ o 1 2 Kilometers ~ 01234Mlles ,.....-.J G!UAl" OUl"D00Jl5 Co LORAnO • Colorado Division of Wildlife May, 1999 Figure 2. Selected vegetation types in the Gunnison River Valley. DELTA �N A 0 Irrigated Crop Type 11111111 Selected Vegetation Types• Desert Shrub Saltbush Fans & Flats Greasewood Fans & Flats \ 0 1 2 Kilometers ~ -- 1 2 3 4 Miles a GREAT OUTD00ll5. COLORAnO (_ '- 0 0 of Wildlife 99 Figure 3. Selected vegetation types in the Colorado River Valley. �25 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB PROGRESS REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Research Program Work Package No. ___0"""6=-a6=3_ _ _ _ __ Task No. Kit Fox Conservation Kit Fox Augmentation Study 1 Period covered: July I, 1999 - June 30, 2000 Author: T.D.I. Beck Personnel: T. Beck, G. Byrne, CDOW; E. Everett, B. Miller; Denver Zoological Foundation. ABSTRACT Relative abundance of kit fox prey surveys were developed as a written protocol. However, administrative problems prevented conduct of the late-summer 1999 field surveys. Spring 2000 surveys which had been planned were deferred because of organizational changes within CDOW relative to management of threatened and endangered species. The new organizational unit is to develop a prioritization process for allocating resources among species and habitats and it was believed prudent to defer further field work pending this process since active kit fox augmentation had not begun. Surveys of historic kit fox dens in Uncompahgre Valley did not find evidence of pup production in 1999 and no active kit fox dens were located in spring 2000. Data on historic range rehabilitation projects in the shadscale desert communities of western Colorado was compiled. �27 KIT FOX AUGMENTATION STUDY Thomas D. I. Beck SEGMENT OBJECTIVES I . Compare relative abundance of potential kit fox prey between Uncompahgre and Colorado river valleys. 2. Capture as many kit fox as possible in Uncompahgre Valley for DNA work and pup dispersal. 3. Develop a kit fox reintroduction plan for Mesa County. METHODS AND MATERIALS Sampling protocols were developed for comparing relative abundance of small rodents and cottontail rabbits at 2 sites in each valley. Small rodent surveys were to use a 200-trap concentric trapping web. Snap traps were selected rather than live trapping because of concerns about hantavirus prevalence in these areas. Because such trapping removes captured individuals, trapping was to be conducted during late summer; presumably the time of highest animal density. Thus it would be unlikely to create a local depleted zone. Museum collections from these areas of Colorado are scarce so all trapped animals would have been saved for museum collections. Rabbit abundance was to be meas_ured by a combination of mark-resight estimation and spotlight counts. Hopefully the spotlight counts could be indexed to population estimations to provide a long-term monitoring index. Rabbit population monitoring would be conducted in early-spring; presumably the time of lowest animal abundance. Selection of only 2 sites per valley probably would not accurately represent the variation to be expected throughout the valley. However, this was the most that could be done with manpower and budget. Weekly precipitation records were collected from 6 stations maintained by NOAA in the Uncompahgre and Colorado river valleys in Colorado (Montrose, Olathe, Delta, Grand Junction, Fruita, Loma) for the growing season (March-October) for the period 1970-1998. Not all stations had data for each year. Historic kit fox dens were visited in July and August 1999 to survey for adult fox presence and pup •production. Historic dens and den areas were visited in April 2000 to examine for kit fox use. Records compiled by Ron Kufeld, CDOW retired, were searched to document all range restoration projects •conducted in the low elevation desert valleys. This data base was believed to be complete for the period 1960-1996. During other field activities, visits were made to most of the range project sites to see if any noticeable differences could be seen from surrounding desert vegetation. RESULTS AND DISCUSSIONS Because of administrative delays in allocating budgets and temporary FTE' s, the trapping webs could not be set and run prior to the graduate student having to attend classes. Thus the late-summer 1999 prey studies were deferred to spring of 2000. During late-fall 1999 the Colorado Div. of Wildlife altered its organizational structure and created a new section to deal with Species Conservation; specifically species �28 currently on either a federal or state list of threatened or endangered species or a species in decline with potential for listing. Thus lead role in kit fox restoration shifted to this new section. Discussions among administrators resulted in the decision to defer further field studies until the new section could develop a prioritiz.a.tion process for addressing the species conservation needs. Thus prey abundance surveys were deferred during spring 2000; awaiting the development of the new section priorities. All material collected during our kit fox research surveys has been copied to the new section. Den site surveys in summer of 1999 did not produce any evidence of pup production. There was only one active den found in spring 1999 and for the third consecutive year no pups were produced at this den. No active dens were located in spring 2000 in a survey of historic den sites. Extensive surveys were not conducted in areas where we had previously failed to find active kit fox dens based on the rationale that this declining population will not produce significant dispersal. Based on the lack of finding any active dens, no trapping operations were conducted in 2000. Earlier surveys based on trapping and infra-red photography clearly indicate that trapping rarely produced kit fox captures when field surveys could not find evidence of their presence prior to trapping. The growing season precipitation data was examined to see if any seasonal patterns emerged. The variability within a year and among sites was extremely high and no patterns by year or area were apparent. This is likely a reflection of the nature of the summer precipitation events, which are part of a regional monsoon pattern dominated by afternoon thunderstorms. These storm events are quite local in scope yet capable of delivering 2-3 cm of rain in less than an hour. Casual surveys of range rehabilitation sites indicated no difference from surrounding areas. Thus, when developing augmentation plans no special accord needs to be given to these historic management sites. No formal augmentation plan was developed pending results from the new organizational unit on priorities. However, the material needed to do so is on file. Contacts have been made with 2 surrounding states (Utah and Arizona) for sources of kit fox should augmentation move forward. Representatives of both states were confident of being able to provide kit foxes in adequate numbers. � https://cpw.cvlcollections.org/files/original/156cff7c1f3a7693c3dff9a140318378.pdf bddc59ce29c1e34a4c62424d2f469fd0 PDF Text Text 107 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT State of _____c...o....,.l..,o""'r..,a.,,d..,o"------ cost center 3430 -_1...s...J...-...B...-_.1....1____ : Mammals Program Project No. _ _....,w.... Work Package No. Species of special concern 0663 Lynx conservation Recovery Task No. Period Covered: July 1, 1997 - June 30, 1998 Author: D. F. Reed ABSTRACT A conservation strategy/recovery plan for lynx in Colorado was prepared and the draft revised January 12, 1998 (Chapter 1 in Seidel et al. 1998). This conservation strategy to recover and conserve lynx populations in Colorado provided general background on the species and generally identified the habitat goals and objectives of identifying potential habitat, identifying linkage zones, selecting suitable habitats, refining habitat suitability models, and refining habitat protection, as well as, conservation actions to be taken. Subsequently, more specific protocols were developed to assess potential lynx habitat based on the species' primary prey, the snowshoe hare.• The first protocol was for the winter track survey which was conducted during the winter. The second was for the snowshoe hare pellet counts (Krebs plots) which were begun toward the end of the segment. The routes selected for the winter track surveys were based upon accessibility and transportation mode (snowmobile, cross-country skis, etc.), and hence, were not randomly selected. Furthermore, sample sizes (routes per forest types) were small. Conclusions about representativeness should be made with caution. �109 LYNX CONSERVATION/RECOVERY Dale F. Reed P,N, OBJECTIVE Develop a conservation strategy to recover and conserve lynx populations in Colorado. SEGMENT OBJECTIVES 1. Prepare a conservation strategy/recovery plan for lynx in Colorado. 2. Assess potential habitat for lynx reintroduction. STUDY AREA The study area includes the forests (Aspen, Douglas Fir, Lodgepole Pine, mixed conifer, mixed forest, Ponderosa Pine, and Spruce-fir) and deciduous oak above 7,500 ft throughout the north-south western half of Colorado. METHODS AND MATERIALS The methods used in preparing the "Conservation Strategy/Recovery Plan" (Seidel et al. 1998) involved extensive literature review, writing, rewriting, editing, and coordination with the numerous authors, species experts, and agencies participating in its completion. The methods used in assessing potential habitat for lynx (Felis lynx) involved 1) a winter track survey where snowshoe hare (Lepus americanus) tracks (crossings and parallel movements) were counted in snow 24-28 hours after snowfalls (described by Byrne 1998) and 2) counts of snowshoe hare pellets (Kreb's plots; Krebs et al. 1987) via randomly selected points in the forest types and deciduous oak (see Study Area) as determined by statewide GAP data. RESULTS Results as in the "Conservation Strategy/Recovary Plan" are summarized in the following Executive Summary (Seidel et al. 1998:vii-x): EXECUTIVE SUMMARY Endangered Species Since life began on this planet many species have come and gone through natural changes in physical and biological conditions. Since these extinctions occur naturally why should we spend money and effort to conserve species that are nearing this end? How do they benefit society if restored? Congress addressed these questions in the preamble of the Endangered Species Act of 1973, "recognizing that endangered species of fish, wildlife, and plants are of aesthetic, ecological, educational, historical, recreational, and scientific value to the Nation and its people." Congress further stated its intent to protect and conserve the ecosystems and habitats. The State of Colorado �110 has adopted similar protections for species of special concern. The primary force driving the loss of these species is habitat destruction or human exploitation. While we do not know the causes for the decline in lynx (Lynx canadensis) in the Southern Rocky Mountains (SRM) human activity is at least partly responsible. We have the knowledge to conserve and reestablish these species. We also have the responsibility. History and Distribution Lynx historically occurred, at low densities, as forest carnivores in the SRM. There have been 12 investigations reported in Colorado since 1979 to document the presence of lynx or wolverine. Although the presence of both species has been suspected but not confirmed, and no viable populations have been found. There have been no field studies in the southern ranges in Wyoming or in New Mexico. Wyoming conducted a survey in 1986 of reported sightings but few of these reports were documented (Reeve et al. 1986). This draft does not include information on the Wyoming and New Mexico portions of the SRM. The final strategy will include a coverage of these areas. Any future decisions regarding lynx that affect neighboring states will require further investigation and coordination. Current Status At this time the lynx is classified as a federal "candidate" species by the Fish and Wildlife Service. In Colorado the lynx is classified as state endangered species and in New Mexico are protected species. Wyoming classifies lynx as Native Species Status Category II (Oakleaf et al. 1996). The Forest Service classifies lynx as a "sensitive species." Conservation Strategy On July 8, 1997, representatives of the U.S. Forest Service, U.S. Fish and Wildlife Service and the Colorado Division of Wildlife (CDOW) met to discuss a cooperative program for the conservation and reestablishment of lynx and wolverine in Colorado. On August 4, 1997, those agencies plus the National Park Service signed a letter agreeing to jointly prepare "A Candidate Conservation Strategy for Lynx and Wolverine in Colorado." The Colorado Division of Wildlife is the lead agency for these state listed species. Species Goal The goal of this strategy is the conservation and reestablishment of lynx within their former ranges by establishing populations which reprodu~e sufficiently to allow emigration into unoccupied suitable habitats. If this is accomplished, it would permit the downlisting of these species by the states from endangered. Both species are considered in this document due to expected economies of scale that will be realized in the habitat assessment, acquisition, and monitoring portions of this strategy. This document could serve as the basis for future recovery efforts in Colorado. Risks to the Species We can only speculate on the history of lynx populations in Colorado. Some speculate that trapping, hunting, and poisoning played a significant role in population reductions. If so, Amendment 14 approved by the voters of Colorado in 1996 greatly reduced that threat to future populations because it strongly restricts the use of poisons, leghold, kill-type and snare trapping devices in the State of Colorado. Removal of this historical source of mortality would enhance the probability of success for conservation and/or potential future reintroductions of lynx. A second primary mortality factor for lynx populations reported from other sites within their distribution is mortality of kittens or kits either through starvation or disturbance during rearing. �111 These are factors that can be addressed by specific management practices. Most of the potential habitat for these species in the SRM occurs on public land with the majority on National Forest System lands. Many National Forest lands in Colorado are designated and managed as wilderness. It is currently not known how much of that area has potential to support lynx populations. Habitat Goals for Lynx The first goal is to describe and map potential habitats for lynx in the SRM. The second goal is to protect those habitats that may be important for whatever lynx may still exist in the state and potential habitats for future reintroduction or reestablishment efforts. Habitat Evaluation Actions for Lynx Lynx foraging habitat requirements are inextricably linked to habitat requirements and population distribution of snowshoe hares (Lepus americanus) because that species is a staple prey item. Therefore habitats with abundant snowshoe hare populations would be considered the primary criterion for selecting potential locations for lynx reintroductions. The first step in the strategy will be to assess the potential habitats both for foraging and denning potential using GIS vegetation mapping. Key areas will be identified that contain at least the minimum requirements for species survival. The criteria used for this selection will come from the significant body of knowledge that exists for lynx habitats in other regions (Table 1). These same criteria have been used to develop potential habitat management guidelines that will be recommended to land managers until information obtained from monitoring reintroduced individuals suggests changes to those recommendations. Once key blocks of potential habitat are identified, the CDOW intends to conduct two surveys to detect snowshoe hare occurrence and estimate densities to validate or adjust initial habitat assumptions. Data from both surveys will be used to identify the 2 habitats with the greatest potential to support Colorado lynx. The actual reintroduction sites will be identified from the field surveys and modified or confirmed from advice from a peer review panel of qualified scientists with recognized expertise in lynx ecology and management. Reestablishment of lynx Reestablishment of viable lynx populations in Colorado requires reintroductions. A reintroduction would involve assessing potential release sites for habitat suitability, radio-marking lynx prior to release, and intensive monitoring of radio-marked animals. Lynx populations in Canada and Alaska currently are increasing toward peak population levels (Fontana pers. commun. 1997). Lynx selected for reintroduction otherwise would be killed and sold as pelts to be traded as fur. By paying a compensatory price, the CDOW can obtain lynx for reintroduction at a reasonable price and increase their chances of survival. When lynx are at the lower end of their population cycle, population levels would be insufficient to provide sufficient animals for reintroduction. Since wild lynx populations cycle every 10 to 12 years, there is a narrow 4- to 5-year window of opportunity to reintroduce lynx in Colorado's most suitable habitats. It is estimated that lynx would be needed to be released each year ( in each of 2 habitats each year) for 2 successive years to establish several viable breeding populations. Species Monitoring Radio-marked lynx will be intensively monitored by frequent relocations both from the air and the ground. Recorded data would include habitat selection patterns, seasonal home ranges, reproductive success, survival, and probable cause of death when mortalities are detected. This information would be �112 evaluated critically to determine if additional releases of these species into unoccupied habitats is warranted before additional releases are attempted. Revision Any strategies for conserving lynx in the SRM must be regarded as tentative because very little is known about their specific ecology and habitat requirements in the SRM. As the body of knowledge increases and new information is gained from post-release monitoring of both lynx and wolverine, the Conservation Strategy would be revised. Formal lynx and wolverine status reviews would be scheduled periodically (e.g., annually) by the Lynx and Wolverine Conservation Strategy Team to revise the lynx/wolverine Conservation Strategy as needed. Budget A draft budget is included in Appendix B. It is estimated that the cost to complete the first 3 years of this Conservation Strategy could approximate $2.5 million. The Division of Wildlife has committed to funding $700,000, leaving $1.8 million to be acquired from other sources. Habitat Protection Following the pre-release habitat suitability surveys, it will be necessary to develop interim guidelines to delineate, preserve and protect lynx habitats on public lands that are deemed critical to the conservation of these species. These interim habitat protection guidelines periodically would be revised as additional information surfaces from the post-release monitoring of radiomarked individuals. Guidelines will be based on the best scientific and economic information available; will conform to existing laws and regulations; and will be subjected to further peer and public review prior to implementation. These guidelines will be developed and amended into this document at a later date subject to concurrence by all signatories. Results of the winter track surveys were reported by Byrne (1998). Counts of snowshoe hare pellets (Kreb's plots; Krebs et al. 1987) were only begun toward the end of this segment - hence the results from this second method will not be available until the next segment. LITERATURE CITED Byrne, G. 1998. A Colorado winter track survey for snowshoe hares and other species. Colo. Div. Wildl. 35pp. Krebs, c. J., B. s. Gilbert, s. Boutin, and R. Boonstra 1987. Estimation of snowshoe hare density from turd transects. Can. J. Zool. 65:565-567. Seidel, J., B. Andree, s. Berlinger, K. Buell, G. Byrne, B. Gill, D. Kenvin, and D. Reed. 1998. Draft strategy for the conservation and reestablishment of lynx and wolverine in the southern Rocky Mountains. U.S. Forest service, National Park Service, U.S. Fish and Wildlife Service, and Colorado Division of Wildlife. 115pp. ~· Prepar:;~:2J/4&5JEU/ Dale F. Reed Wildlife Researcher �66 �65 Coiorado Division of Wildlife Wildlife Research Report July 1999 JOB FINAL REPORT State of ------=-=~=="------Colorado Project No. ----'-W-'---"1""'"53"'""--=-R"--""'12~---Work Package No. _0~6"-'6'""3_ _ _ _ _ __ Task No. _ _ _ _2 " ' - - - - - - - - - Cost Center 3430 Mammals Program Species of Special Concern Lynx Conservation/Recovery Period Covered: July 1, 1998 - June 30, 1999 Author: D. F. Reed ABSTRACT Snowshoe hare pellet counts (Krebs plots) were analyzed and a Division report prepared. BDOWD14185 �67 LYNX CONSERVATION/RECOVERY Dale F. Reed P.N. OBJECTIVE Task 2 - Develop a conservation strategy to recover and conserve lynx populations in Colorado. SEGMENT OBJECTIVES 1. Analyze data and prepare report. STUDY AREA The study area includes the forests (Aspen. Douglas Fir, Lodgepole Pine, mixed conifer, mixed forest, Ponderosa Pine, and Spruce-fir) and deciduous oak above 7,500 ft throughout the north-south western half of Colorado as reported by Reed (1998). METIIODS AND MATERIALS The methods used in assessing potential habitat for lynx (Fe/is lynx) involved counts of snowshoe hare pellets (Kreb' s plots; Krebs et al. 1987) via randomly selected points in forest types and deciduous oak as determined by statewide GAP data and as reported by Reed (I 998). RESULTS The results are in the report titled "Snowshoe hare density/distribution estimates - potential habitat for reintroduced lynx in Colorado" (Reed and Kindler 1999). LITERATURE CITED Krebs, C. J., B. S. Gilbert, S. Boutin, and R. Boonstra. 1987. Estimation of snowshoe hare density from turd transects. Can. J. Zool. 65:565-567. Reed, D. F. 1998. Lynx conservation/recovery. Colo. Div. Wildl. Res. Rep. July, 107-l 12pp. Reed, D. F., and J. Kindler. 1999. Snowshoe hare density/distribution estimates - potential habitat for reintroduced lynx in Colorado. Fort Collins, CO :Colo. Div. ofWildl. Division report; no. (in review). Prepared by _ _ _ _ _ _ _ __ Dale F. Reed � https://cpw.cvlcollections.org/files/original/2eb8d87cd168378fbddb2cf59080f9d6.pdf b14610cb2f685095678a3ec48ea998fa PDF Text Text 47 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB PROGRESS REPORT State of _ _ _ _ ____.C._.o=lo=rad=o=--------Project No. ________ W__--=-1~53__-___ R----1---4_______ Mammals Research Work Package No. _ _---'0'-'6a..a.7..a;..0_ _ _ _ __ Lynx Conservation Task No. 2 -------------- Lynx Veterinary Services and Diagnostics Period Covered: July 1, 1999 - June 30, 2000. Author: M. A. Wild. Personnel: T. Shenk, S. Dieterich, H. Dieterich, T. R. Spraker, D. H. Gould. ABSTRACT Fifty-six lynx (34 adult females, 19 adult males, 2 juvenile females, 1 juvenile male) were received from British Columbia, the Yukon, and Alaska during January - April 2000. Lynx arrived in generally good condition with the exception of one female lynx that required euthanasia due to an extensive foot lesion from trapping. All lynx were anesthetized (Telazol 2-3 mg/kg IM) for physical examination and identification at least twice during the =::3 week acclimation period at the captive holding facility. During captivity lynx maintained or improved body condition. Using abdominal radiographs, we diagnosed one female as pregnant and three others were suspicious. Seven lynx had lesions to 1-2 toes that required treatment. One of these lynx also had two fractured metacarpal bones that required splinting. All recovered and were released in Spring 2000. One lynx from the 1999 release was recaptured in March 2000. The lynx was emaciated but no other abnormalities were determined. He was released in May 2000 after rehabilitation. Fifteen mortalities were recorded in free-ranging lynx during FY2000. Eight of the carcasses were in advanced stages of decay (or only the collar was found) and cause of death could not be determined; however, in three of these cases we were able to rule out starvation as cause of death. Two lynx died from gunshot wounds, two from trauma, and one from predation. One trauma case and the predation case were in poor body condition. One male kitten died from starvation about 7 weeks postrelease. A female yearling died of pneumonic plague in Hinsdale County, Colorado. �48 �49 LYNX VETERINARY SERVICES AND DIAGNOSTICS Margaret A. Wild P. N. OBJECTIVES I. Provide veterinary care and diagnostic services for reintroduced lynx. SEGMENT OBJECTIVES I. Provide veterinary care and diagnostic services for reintroduced lynx. METHODS AND MATERIALS Lynx were trapped in British Columbia (BC) and the Yukon, Canada, and Alaska then transported by truck and/or airline to holding pens at the Frisco Creek Wildlife Hospital and Rehabilitation Center, Del Norte, Colorado. Care of lynx during captivity was based on the Husbandry and Management Protocol (Attachment I of Addendum A). Post-release, diagnostic and forensic services were provided to support ongoing research and law enforcement efforts. Carcasses were transported to the Colorado State Diagnostic Laboratory, Fort Collins, for examination by a board certified veterinary pathologist and a wildlife veterinarian. Complete post-mortem examination was conducted following the Necropsy Protocol (Attachment 2 of Addendum A). RESULTS AND DISCUSSION Results of the 1999 lynx reintroduction are summarized in Addendum A. An additional 56 lynx were received January-April 2000. Lynx appeared healthy on arrival with no transportation-related injuries. Captive management and husbandry techniques were similar to those reported in 1999; however, all lynx were held at least 3 weeks for acclimation and fattening prior to release. Releases occurred in early April through late May. Daily clinical assessment suggested that lynx adjusted well to confinement in our isolated holding facility. Daily feed intake was not quantified this year however consumption appeared similar to the average I 0-15% of body weight/day over a weekly basis that was observed in 1999. Health Assessment We anesthetized each lynx with about 2.5-3 mg/kg body weight Telazol IM for initial examination and sample collection (as described in Attachment 1 of Addendum A). One lynx (BC00F 17) was euthanized upon initial exam due to extensive foot lesions. The other 55 lynx were anesthetized again with about 2-2.5 mg/kg Telazol IM for placement of a radiocollar just prior to release. In general, lynx arrived in good condition. Upon arrival, females from British Columbia (BC; n = 9) and The Yukon (n = 20) averaged 8.86 kg (SE 0.28) and 8. 72 kg (SE= 0.22), respectively. At examination prior to release, body weights had increased to 10.23 kg (SE= 0.19) and 10.28 kg (SE= 0.13) for BC and Yukon females, respectively (Fig. I). Adult females from Alaska (n = 4) averaged 9.82 kg (SE= 0.67) at arrival and 11.91 (SE= 0.63) prior to release; however, one of these was known pregnant and three were suspected to be pregnant. Body weight change was less marked in male lynx. Upon arrival, adult males from BC (n = 9), The Yukon (n = �50 6), and Alaska (n = 4) averaged 12.2 kg (SE 0.53), 10.64 kg (SE= 0.32), and 11.23 (SE= 0.32) respectively. At examination prior to release, body weights were 12.93 kg (SE= 0.45), 12.13 kg (SE= 0.17), and 13.27 (SE= 0.63) for BC, Yukon, and Alaska males, respectively (Fig. I). One male kitten from The Yukon weighed 6.2 kg on arrival and 7.87 kg prior to release. Two female kittens from Alaska averaged 6.89 kg (SE= 0.34) on arrival and 9.17 kg (SE= 0.08) prior to release. Using radiographic examination of the growth plates of the distal radius and ulna as an indicator of age (Nava 1970), we determined that three juveniles were received (YK00M5, AK.00Fl, and AK.00F4). Apparently, the body length measurements that we collected in 1999 to distinguish kittens from adults proved useful in field evaluation oflynx and minimized the number of kittens that we received. This year we also adopted a new approach for estimating age of lynx based on percent pulp cavity in the canine tooth. This method has been used to age canine teeth collected from lynx carcasses (K. Poole, pers. comm.), but we attempted to collect the infonnation in situ using skull radiographs. Evaluation of the method is underway. Several injuries to lynx were found. Eight lynx had fractured toes or toes previously amputated by veterinarians in BC or The Yukon. Damage to the foot of one of these lynx (BC00F 17) was severe and involved the middle three toes on a front paw. Due to the poor prognosis, we euthanized this lynx at the time of initial veterinary examination. Of the remaining seven lynx, three lynx had one toe amputated (one of these lynx also had two fractured metacarpal bones that required splinting), two lynx had one toe amputated and an additional toe damaged, one lynx had two toes amputated, and one lynx had two fractured toes that were ankylosed but were not treated. Five other lynx had minor lacerations on the legs or face that healed without complications. Recapture On 24 March 2000, we recaptured a lynx (AK.99M9) released in 1999. Field observations by the lynx monitoring crew suggested that the lynx was severely emaciated. Live trapping the lynx failed, so we darted the lynx with Telazol (3 mg/kg) using the Dan-Inject CO2 pistol. Physical examination revealed severe emaciation (6 kg). It can be assumed that the lynx would have died if not recaptured. Blood work was unremarkable with the exception of a low titer to Toxoplasmosis; however, this was unlikely the cause of the abnormality. No underlying disease condition was found that would explain the debilitation. The lynx responded well to supportive care at the holding facility and was released in May 2000. Post-mortem Examination Fifteen mortalities were recorded in free-ranging lynx during FY2000 (Table 1; one of these was included in Addendum A as well). Eight of the carcasses were in advanced stages of decay (or only the collar was found) and cause of death could not be determined; however, in three of these cases we were able to rule out starvation as cause of death based on the presence oflipid in bone marrow. Two lynx died from gunshot wounds, two from trauma, and one from predation (apparently from a bobcat). One trauma case and the predation case were in poor body condition. One male kitten died from starvation about 7 weeks post-release. A female yearling died of pneumonic plague. The carcass was recovered in Hinsdale County, Colorado. Necropsy findings showed an acute fibrinous pneumonia. Plague was diagnosed by fluorescent antibody test and isolation of Yersinia pestis from lung and spleen samples. After this diagnosis, we retrieved bone marrow samples to test for plague in six other lynx that had died from unknown causes in 1999 and 2000. Fluorescent antibody test was negative on all of these cases. Plague in rodents is not uncommon in southwestern Colorado. This lynx most likely consumed a rodent or rabbit infected with plague. �51 LITERATURE CITED Nava, J. 1970. The reproductive biology of the Alaska lynx. M.S. Thesis. Univ. Alas., Fairbanks. 14lpp. Table l. Summary of mortalities in free-ranging lynx during FY 2000. Date1 Animal ID Sex Age State of Carcass Cause of Death 08/26/99 09/15/99 10/22/99 11/03/99 11/17/99 11/24/99 01/26/00 01/29/00 05/23/00 05/23/00 06/08/00 06/15/00 06/15/00 06/22/00 07/29/00 AK.99F18 AK.99F10 BC99-02 AK.99F27 AK.99M6 AK.99F15 YK99F4 AK.99Mll BCOOF3 YKOOM5 YK.99F3 AKOOF4 YK.99M6 AK.99Fl3 YKOOF17 F F 2 2 4 1 5 3 Good Poor Poor Good Good Good Good Minimal remains Good Good Poor Collar only Collar only Minimal remains Poor Trauma, emaciation2 Unknown, not starvation2 Unknown, not starvation2 Shot Shot Blunt trauma Predation, emaciation Unknown Pneumonic plague Starvation2 Unknown, not starvation2 Unknown Unknown Unknown Unknown2 M F M F F 5 M 3 1 0 3 0 4 1 2 F M F F M F F 1 Date mortality confirmed, date of death may have been earlier. 2 Plague negative on FA of bone marrow 14 12 'bl) c 10 i ·- 8 ~ 6 "'O 0 4 >. CQ I I ii d) 2 0 BC YK Females AK BC YK AK Males Fig. 1. Initial body weight (stippled) and body weight at release (solid) of female and male lynx reintroduced in 2000. �52 ADDENDUM A Status Report on the Health of Lynx Reintroduced to Colorado by Margaret A. Wild, DVM Colorado Division of Wildlife With additional information from Herman Dieterich, DVM, DACVS and Susan Dieterich Frisco Creek Wildlife Hospital and Rehabilitation Center For the 30-31 August 1999 CLAWS/LAT Meeting GOAL To assure optimal health of lynx reintroduced into Colorado. OBJECTIVES Objectives of the health program were: 1. 2. 3. 4. To protect the health of wild and domestic animals in Colorado. To optimize health oflynx released into Colorado. To optimiz.e welfare oflynx during transport and holding. To provide diagnostic and forensic services in the case of mortalities. MATERIALS AND METHODS Lynx were trapped in British Columbia (BC) and the Yukon, Canada, and Alaska then transported by truck and/or airline to holding pens at the Frisco Creek Wildlife Hospital and Rehabilitation Center, Del Norte, Colorado. Care of lynx during captivity was based on the Husbandry and Management Protocol (Attachment 1). Post-release, diagnostic and forensic services were provided to support ongoing research and law enforcement efforts. Carcasses were transported to the Colorado State Diagnostic Laboratory, Fort Collins, for examination by a board certified veterinary pathologist and a wi_ldlife veterinarian. Complete post-mortem examination was conducted following the Necropsy Protocol (Attachment 2). PRELIMINARY RES ULTS AND DISCUSSION Captive Management and Husbandry Forty-two lynx were received at the holding facility between 29 January and 14 April 1999. All appeared healthy on arrival with no transportation-related injuries. Individual lynx were held at the facility for varying lengths of time based on assigned release protocol. Lynx from BC were held <1- 7 wk (median 6.5 wk), from the Yukon 3 - 10 wk (median 8 wk), and from Alaska 3 - 6 wk (median 5) prior to release. Daily clinical assessment suggested that most lynx adjusted well to confinement in our isolated holding �53 facility. However, at least three lynx never adjusted to confinement; two paced the pen causing erosions on the palmar and plantar surfaces of the pads (AKFX99 and AKF499) and one appeared distressed and remained in relatively poor body condition (AKF1599). For other animals, clinical observations suggesting acclimation to confinement were supported by daily feed intake and body weight data. Lynx consumed on average about 10-15% of their body weight/day over a weekly average (Fig. 1) despite the fact that highly palatable feed items were not offered ad libitum. Lynx often fasted rather than consume less palatable items such as the prepared feline diet, fish, or beaver and engorged themselves on highly palatable items such as wild rabbits (up to >2 kg/day). Most lynx gained considerable body weight while in captivity (Fig. 2). In 1999, our initial plan was to hold lynx in captivity for as short a period as possible. We assumed that the animals would be distressed in confinement and would have a greater chance of survival if released immediately to the wild. However, we found that most lynx appeared to adjust to confinement without distress. Further, this period in confinement was likely beneficial to the animals in giving them time to acclimate to Colorado and to gain body weight prior to release. Health Assessment We anesthetized all lynx at least once for examination, and most were anesthetized again for placement of a radiocollar prior to release. We used 3-6 mg/kg body weight Telazol IM to perform 84 anesthetic events on 42 lynx. Of the 79 anesthesias induced with a single injection, mean induction time was 4.3 min (SE 0.2 min; range 2-10 min). Five other anesthesias required supplementation and mean induction time was extended to 16.2 min (SE 7.2 min; range 7-29 min). Full recovery was achieved in all cases on average 91 min (range 27-188 min) after initial Telazol injection. All parameters stayed within acceptable limits; however, lynx receiving 5-6 mg/kg were markedly deeper and oxygen saturation frequently dropped to 70 80%. Supplemental oxygen was administered in these cases. In general, lynx arrived in good condition. Lynx from the Yukon were in markedly better body condition than those from other sites (Fig. 2). Using radiographic examination of the growth plates of the distal radius and ulna as an indicator of age (Nava 1970), we determined that at least six juveniles were received (two from BC, one from the Yukon, and three from Alaska). Total length of the two juveniles from BC was markedly less than that of other lynx from BC Guveniles 78 cm, range in adults 87-97.5 cm). The juvenile from the Yukon was correctly identified using the body length criterion of Slough ( 1996); the juvenile was 90.2 cm while the adults were all well above Slough's 90.5 cm cut-off for adults (range 96105 cm). Identification of juveniles from Alaska was more difficult, likely in part because evaluation occurred later in the year. Three juveniles were identified based on lack of closure of the growth plate; these lynx ranged from 86-89.5 cm in length. Lynx classified as adults ranged from 89.5-106.5 cm. Given these findings, body length can likely be used as an indicator to classify juveniles; however, site-specific cut-off points for body length will be required (i.e., while Slough's classification is appropriate in the Yukon, it appears less reliable for BC and potentially Alaska). We also used radiography to diagnose advanced pregnancy (>45 days) in lynx. Six lynx (AKF299, AKF399, AKF499, AKF899, AKF1099, AKF1799) had fetuses with calcified skeletons present and two other lynx had radiographic evidence suggesting earlier pregnancy (AKF599, YKF599). Of these pregnant females, three have died as of 28 August 1999 (one starvation, one hit-by-car, one undetermined cause). Five lynx had lesions or fractures of one to three toes that required medical treatment or surgical amputation. Two lynx (BC99-8 and AKF499) had minor infections on one toe of a front foot that were treated medically. These animals recovered fully prior to release. Two lynx had fractures and/or freeze �54 damage to two toes on a front foot, with one toe amputated from each lynx (AKf 1099, AKf 1899). The remaining lynx had fractures and freeze damage to three toes on a hind foot that required amputation of all three toes (BC99-15). Of the three lynx released with toes amputated, two are alive and one has died (cause of death unknown, although animal was slightly emaciated and had traumatic injuries) as of 28 August 1999. Sample collection, treatments, and identification were as described in the Husbandry and Management Protocol; however, eartags were placed only in lynx from BC. An incidental finding observed in the majority oflynx from the Yukon and Alaska were pinpoint to 2 mm slightly raised lesions on the oral mucosa, primarily the ventral surface of the tongue. Biopsy samples were submitted to Colorado State Diagnostic Laboratory for histopathology. Results indicated the plaques were caused by a slightly thickened epidermal layer, with no specific lesions present. Otherwise, lynx remained healthy in captivity with the exception of one adult male (YKM 199) and one adult female (BC99-06). Lynx YKM199 exhibited paresis and muscle weakness of about I wk duration. Results of diagnostic procedures were unremarkable, with the exception of apparently enlarged kidneys on radiographs. The lynx was euthanized 29 April 1999 and a thorough post-mortem examination was performed. No gross or histologic lesions were found (kidneys were normal despite radiographic interpretation). Kidney lead levels were normal. Serology for Felv/FIV, CDV, FIP and Toxoplasma gondii were negative. Rabies and parasitology exam were negative. The cause of paresis in this lynx was undetermined; however, infectious diseases that could have affected other lynx in the holding facility were excluded from the list of possible causes. Lynx BC99-06 was diagnosed with an abdominal hernia after recapture. The lynx was initially released under protocol 1, then recaptured in a debilitated, emaciated state. The lynx was nursed back to health on a diet slowly increasing in amount. Although no adverse effects were observed during the rehabilitation, an abdominal hernia developed. The rent in the abdominal wall was surgically corrected without complication. Post-mortem Examination In addition to the one lynx euthanized and examined prior to release, as of 28 August 1999 we have examined 10 mortalities (Table I). Starvation was diagnosed as the cause of death in five lynx based on extreme emaciation as evidenced by lack of depot fat, muscle atrophy, and serous atrophy of bone marrow. Three other lynx that died acutely (one shot, two hit-by-car), were in good body condition. Cause of death in two lynx was undetermined. One lynx (AKF899) had undergone severe autolysis and dehydration prior to examination. No internal organs or bone marrow remained for examination. Another lynx (AKF1899) was in a moderate state of autolysis, however, a complete examination was still possible. Gross examination of this animal revealed slight emaciation and traumatic injuries. Histologic examination of tissues is pending. All carcasses have been tested for rabies and internal and external parasites. Rabies examination has been negative in all cases. Incidental findings on parasitology have included Trichinella, Trichuris, coccidia, Toxascaris, Taenia, giardia, and rodent fleas. LITERATURE CITED Nava, J. 1970. The reproductive biology of the Alaska lynx. M.S. Thesis. Univ. Alas., Fairbanks. 14lpp. Slough, B. G. 1996. Estimating lynx population age ratio with pelt-length data. Wild.I. Soc. Bull. 24:495499. �55 Attachment 1 Husbandry and Management of Captive Lynx at Frisco Creek Wildlife Hospital and Rehabilitation Center Husbandry Lynx will be held singly or in pairs in holding pens (about 5 m2) with attached nest boxes (about 0.7 m2) at the Frisco Creek Wildlife Hospital and Rehabilitation Center. Two units, each with 10 pens, are available. Pens are fully enclosed by fencing and have concrete floors. Straw or hay bedding will be placed in the nest box as well as in two additional piles in the pen. Pens will be cleaned daily. Fresh water, snow, and feed will also be provided ad libitum daily. Feed remaining in the pen after 24 hr will be inspected for quality and discarded if rejected by the animal or if unfit for consumption. Quantity of feed provided and removed will be measured daily. Type of feed will vary, but will consist primarily of domestic, cottontail, and jackrabbits, deer and elk meat, and poultry. Additional feeds may include a prepared feline diet, fish, wild birds, and small mammals (excluding plague vector species, i.e., prairie dogs). Head, kidneys, and urinary bladder will be removed from domestic rabbits prior to feeding to prevent transfer of Encephalitozoon cuniculi. Health and behavior oflynx will be observed twice daily. Individual animal records will be maintained and abnormalities reported to attending veterinarians. Site Security Animal housing units will remain under double lock except when access is required for animal care or other approved activities. Access to the holding pens will be limited to caretakers and visitors with approval from the Colorado Division of Wildlife (CDOW) Program Manager. Alarms and other security devices may be installed as needed. Handling When handling or transportation is required, lynx will be placed in their individual nest box or alternatively, a skykennel. If required, the lynx will be transferred from their nest box to a custom squeeze cage where they can be hand-injected with an anesthetic or other treatments. Lynx will be anesthetized by, or under the direct supervision of, a veterinarian with 5 mg/kg Telazol, IM. Temperature, pulse, respiration rate, oxygen saturation, and anesthetic depth will be assessed throughout the anesthetic event. A record for each anesthetic event will be completed (see attached). Supplemental oxygen will be provided by mask as needed. Lynx will not be returned to their pens until recovered from anesthesia. Examination and Animal Identification Lynx will receive a brief visual examination by a veterinarian upon arrival at the holding facility. Abnormalities will be noted and appropriate care provided. After 1-7 days rest, each lynx will be anesthetized for thorough examination. We will obtain a body weight and morphometric measurements, assess body condition, estimate age (based on tooth wear), take a photograph of the face, collect hair and whole blood for DNA analysis (R.Ramey, University of Colorado, Boulder) and blood for archiving, administer penicillin prophylactically (22,000 U/kg, SC), perform a thorough physical examination, and apply needed treatments and markings for identification. The physical examination will include close inspection of the condition of toes, claws, and teeth. We will use radiology to augment diagnosis of injuries, identify juveniles (based on lack of closure of the growth plate of the distal radius and ulna), and confirm late pregnancy. Other diagnostic samples will be collected as needed if abnormalities are found. If �56 written documentation is not available to confirm that required anthelmintic treatments have been provided, we will administer praziquantel (5 mg/kg SC), ivermectin (0.3 mg/kg SC), and topical dusting with carbaryl. Lynx will be identified with two subcutaneously placed transponders (one on dorsal midline, the other in the intermandibular area) and an eartag. A radiocollar will be placed on each lynx about 2-14 days prior to release. If additional anesthesias are required for placement of radiocollar, treatment, etc., determination of body weight and other required procedures may be repeated as well. Treatment and Euthanasia Medical treatments will be provided by, or under the direct supervision of, the attending veterinarians as needed. Surgery will be performed by a board certified veterinary surgeon. If euthanasia is required, ideally it will be performed with the lynx under anesthesia using an overdose of barbiturates. A diagnostic necropsy will be performed on all mortalities by a board certified veterinary pathologist. �57 ANIMAL CAPTURE RECORD Species: -L< nx- - - - - - - - - - - - - - - - - - - ~ I I 99 Date: Name of investigator(s): Sex: M 0 F 0 Est □ Actual O Age: _ _ Weight: _ _ __ Est □ Actual O Body Condition: Animal No. Excel Good O 0 Fair D Poor O Purpose of Capture: Pre-release exam. -----------------------------------Location of Capture: _J)ieterich 's Holding Pens Ambient Temperature: _ _ _ _ Weather Conditions: ____________________ Drug Administration Time Drug Method Dose Location lvermectin Praziquantel Penicillin Event Times Start Procedures: Immobilized: Recovered: Finish Procedures: Vital Signs Time Temp Pulse Respiration Results of Physical Exam: Body Measurements: Samples Taken: Blood- EDTA Blood-RU Hi Collar Freq Markings D D D D D Transponder Number BodvLenath Tai{Lenath cm cm cm cm cm Ear Tag Location Number Color Left Right Comments: Colorado Division of WIidiife Revision Date: 08124/00 �58 Attachment 2 Protocol for post-mortem sampling of lynx Contacts: Dr. Margaret Wild (CDOW) Dr. Dan Gould (CSUDL) All information releases and contact with press need to be through the CDOW. Margaret Wild will coordinate. The objectives of the post-mortem examination are to: 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, 3) archive samples for future reference (research or forensic). The gross necropsy and histology will be performed by, or under the lead and direct supervision of, a board certified veterinary pathologist. Preferably, Drs. Margaret Wild and/or Tanya Shenk of the Colorado Division of Wildlife (CDOW) will also be present. In general, the protocol will follow standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing. Some other data/samples listed below will be routinely collected for research, forensics, and archiving. Additional data/samples may be collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). Procedures: 1. 2. 3. 4. 5. 6. Remove the radio collar (animal ID will be the number written on the collar) Determine the body weight and note general body condition Note condition of the claws and teeth Collect external parasites and submit for ID If the carcass is in good condition, please skin and save the pelt (freeze) Remove and save PIT tags (about 1.5mm x 12mm rod-shaped transponder~ne under chin, the other on dorsal midline between the scapulae) 7. Conduct necropsy 8. Collect samples of all major organs including long bone, muscle, spinal cord, etc. (formalin) 9. Collect samples of all major organs including long bone, muscle, spinal cord, etc. (freeze) 10. Collect a 3cm x 3cm section of muscle (freeze) 11. Note condition of bone marrow in femur or other long bone 12. Collect a sample ofvas defcrens and testis (bag with a moist gauze and refrigerate) 13. Bag gut contents that could be used to determine diet (freeze) 14. Collect a fecal sample and submit for parasitology 15. Collect brain. Submit half for rabies exam; save other half in formalin 16. After examination, place the skull in one bag, the pelt in another bag, and other remains in a separate bag (freeze) The CDOW will retain all samples and carcass remains with the exception of: tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, other diagnostic samples. �59 Table 1. Mortality of lynx reintroduced to Colorado, February-August 1999. Animal ID YKM0199 BC99-01 BC99-09 BC99-07 BC99-08 AKM2399 AKF0499 BC99-06 AKF1799 AKF0899 AKF1899 Sex M M F F F M F F F F F Age Protocol Date of Death Weeks Out Cause of Death 2 NIA NIA 0 1 04129199 02124199 2 1 02/26199 3 3 1 03116199 6 0 2 7 1 3 04110199 06118199 4 1 3 06112/99 s Undetennined Starvation Starvation Starvation Starvation Shot Starvation 2 3 07/19199 7 HBC 2 3 07124199 11 HBC s 3 07131199 12 2 3 08126199 15 Undetennined Trawna., emaciation 3 1600 - 1400 Q) 1200 >. 800 bl) -- ~ 1000 C =-@ 0 600 ~ 400 200 0 3110 3117 3/24 I-._ 3131 4/7 Males -a- Females 4114 4/21 * Pregnant 4128 SIS I Fig. 1. Average daily feed intake of captive lynx reported weekly from 10 March through 5 May 1999. �60 16 14 ~ 12 rn 10 ~ 8 ~ 6 ,:Q 4 I 0 2 0 YK BC I□ Arrival Wt Im Release Wt AK I Fig. 2a. Body weight of adult male lynx from British Columbia (BC; n = 5 arrival. n = 3 release). Yukon (YK; n = 7 arrival, n = 5 release), and Alaska (AK; n = 7). 12 ~ .l=bO ·-Q) ~ >"'0 0 ,:Q 10 8 6 4 2 0 BC YK AK I□ Arrival Wt II Release Wt I Fig. 2b. Body mass of juvenile female lynx from British Columbia (BC. n = 1), Yukon (YK, n = 1). and Alaska (AK, n = 3). �61 14 12 'bi> 10 c ell ~ ~ 0 ~ 8 6 4 2 0 BC-O YK-P YK-0 BC-P AK-0 AK-P Fig 2c. Body mass of adult female lynx from British Columbia (BC; open n =4 arrival, n = 1, release; pregnant n = 0), Yukon (YK; open n = 2 arrival, n = 1 release; pregnant n = 1), and Alaska (AK; open n = 3; pregnant n = 7). 6 5 1-4 4 Q.) 1 3 2 1 0 Shot Starve Trauma Cause of Death I111 !Vele ■ Female Fig. 3. Lynx mortality by cause through August 1999. J HBC �62 4 3 ~ .0 e 2 z 1 0 Feb 111 Starve Mar Apr ■ Unk May IJJ Shot Fig. 4. Lynx mortality by month through August 1999. Jun IIIHBC Jul Aug ■ Trauma � https://cpw.cvlcollections.org/files/original/68d69b2c7ab7e63303dc55591394cc63.pdf 2301eb2cbeb1cd2229a2ee93ca4c09ab PDF Text Text 63 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB FINAL REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Research Program Work Package No. ------"-0___ 67"'--0"--_ _ _ _ __ Task No. Lynx Conservation Assessing Abundance of Snowshoe Hares 3 Period Covered: July 1, 1999 -June 30, 2000 Authors: D. F. Reed Personnel: D. F Reed, G. Byrne, T. Shenk, J. Kindler, P. Albers, T. Black, H. McNally, S. Znamenacek, K. Buell, S. King, G. Patton, J. Zahratka, L. Uphham, B. Andree, J. Hicks, ·L. Green, K. Wright, B. Heicher, P. Jones, D. Homan, R. Adams, S. Wait, D. Kenvin, B. Woodward, D. Boyer, K. Cordove, B. Ochs, T. McLean, A. Bellotti, K. Schrollt, G. Cross, F. Kelffuer, G. Madison, L. Dwyer, D. Swanson, D. Brownne, F. Pusateri, M. Wunder. ABSTRACT Data on hare density for this report were derived from pellet surveys using methods describe by Krebs et al. 1987. Samples were distributed among 5 blocks selected by biologist who believed them to be suitable for sustaining lynx populations. Sample sizes of plot arrays ranged from 62-239 with the most plot arrays occurring in block 5 (n = 239). Density calculations yielded 0.44 bares per ha for block 5 and lower densities for the remaining 4 blocks. Hare pellet densities were highest in white fir habitats; followed by limber pine and Englemann spruce habitats. Pellet densities were lowest in Gambel's oak and ponderosa pine habitats, but these were also habitats which were not intensively sampled. The most relevant results in this report are estimates of snowshoe density, the type of overstory in which . the highest densities occurred (Engleman Spruce, based on those with adequate sample size) and where the highest densities occurred (National Forests/wilderness areas and counties in Block 5; Figs. 4-8, 9, 10, 12 in Appendix 1). These indicate marginal densities for supporting reintroduced lynx according to the literature and, professionals working with these species. Granted that most of the work and most of the .professionals working in the field are in the northern boreal forests where snowshoe populations cycle dramatically. Poole (1995) reported that concomitant with the first full winter of low bare density in the Northwest Territories (91-92), all resident lynx died or dispersed in a 135-km2 study area. Marginal habitat conditions for hares probably result in a scarcity of prey and may explain the relatively large home ranges (and hence their behavioral adaptations toward dispersal) of the lynx (Koehler 1990, Roloff 1997). Demographic characteristics of lynx, if any successfully establish home ranges, may be representative of lynx populations along the southern periphery of their range where habitat conditions are marginal for snowshoe hares. �64 �65 SNOWSHOE HARE DENSITY/DISTRIBUTION ESTIMATES AND POTENTIAL RELEASE SITES FOR REINTRODUCING LYNX IN COLORADO D.F. Reed P.N. OBJECTIVES Analyze, summarize, and organize snowshoe hare survey data into a comprehensive final report for release to the public (Division Report No. 20). SEGMENT OBJECTIVES l. Analyze, summarize, and organize snowshoe hare survey data into a comprehensive final report for release to the public (Division Report No. 20). RESULTS Results of the analysis of snowshoe hare pellet sampling are detailed in the attached Appendix 1. Division staff contracted with West, Inc. to evaluate and review the adequacy of both the methodology and the analysis of these data and that report is contained in Appendix 2 �66 �67 APPENDIX 1. SNOWSHOE HARE DENSITY/DISTRIBUTION ESTIMATES AND POTENTIAL RELEASE SITES FOR REINTRODUCING LYNX IN COLORADO Dale F. Reed FOREWORD Native wildlife are valuable resources in Colorado. Such values are manifested in several ways. Some people enjoy seeing or photographing non-hunted species or get satisfaction from merely knowing that they exist as important components of the ecosystem. During the 1980s and 1990s interest increased in the concept of ecosystem management and in maintaining or enhancing biodiversity. Furthermore, interest in enhancing the numbers of or in reintroducing species such as the lynx (Felis lynx) gained momentum in the late 1990s. To that end, a reintroduction oflynx was planned for the winter and spring of 1999 and a prerequisite to such an effort should involve examining the distribution and abundance of its principal prey, the snowshoe hare (Lepus americanus). TABLE OF CONTENTS INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 METHODS ................................................................... . Krebs Plots ................................................................... . Habitat Attributes at Plot Sites ..................................................... . Model Probability Surface ........................................................ . Potential Release Sites ........................................................... . RESULTS AND DISCUSSION ................................................... . Krebs Plots .................................................................... . Habitat Attributes at Plot Sites ..................................................... . Model Probability Surface ........................................................ . Potential Release Sites ........................................................... . CONCLUSIONS/SUMMARY .................................................... . ACKNOWLEDGMENTS ........................................................ . LITERATURE CITED .......................................................... . TABLES 1 Number of points and plot arrays ................................................. . 2 Wyoming and Colorado hare densities .............................................. . 3 Probability of suitable hare habitat ................................................ . FIGURES l GAP Vegetation Classification and Survey Blocks 1-5 .................................. . 2 Random Sample Points Generated for Krebs plots ..................................... . 3 Krebs Plot Points Completed .................................................... . 4 Map of Snowshoe Hare Density by National Forest .................................... . 5 Graph of Snowshoe Hare Density by National Forest .................................. . 6 Map of Snowshoe Hare Density by County .......................................... . 7 Graph of Snowshoe Hare Density by County ......................................... . 8 Map of Snowshoe Hare Density by Block ........................................... . �68 9 Graph of Snowshoe Hare Density by Block .......................................... . IO Snowshoe Hare Density by Block Using "Old" Equation ............................... . 11 Snowshoe Hare Density by Elevation ............................................. . 12 Snowshoe Hare Density by Primary Overstory ...................................... . 13 Snowshoe Hare Density by Forest Structure ........................................ . 14 Snowshoe Hare Density by Primary Understory .................. : ................... . 15 Snowshoe Hare Density by Understory Density ...................................... . 16 Snowshoe Hare Density by Slope ................................................ . 17 Snowshoe Hare Density by Aspect ............................................... . 18 Snowshoe Hare Density by Domestic Grazing ....................................... . 19 Model Probability Surface for Blocks 1-5 .......................................... . 20 Predicted Areas with Greater than 80% Probability of Suitable Hare Habitat in Block 5 ........ . APPENDICIES A Krebs Pellet Plot Field Form ..................................................... . B Selected Data from Block 1 ..................................................... . C Selected Data from Block 2 ..................................................... . D Selected Data from Block 3 ..................................................... . E Selected Data from Block 4 ..................................................... . F Selected Data from Block 5 ...................................................... . G Genus-species Understory Abbreviations in Fig. 14 ................................... . H Summary by Hare Densities per Block, Primary Overstory, National Forest/Wilderness Areas, and by County ...................................................................... . �69 SNOWSHOE HARE DENSITY/DISTRIBUTION ESTIMATES AND POTENTIAL RELEASE SITES FOR REINTRODUCING LYNX IN COLORADO INTRODUCTION Based on a renewed interest in the lynx and the possibility of reintroducing the animal in Colorado, four agencies including the U.S. Forest service, National Park Service, U.S. Fish and Wildlife Service, and Colorado Division of Wildlife prepared a draft strategy for the conservation and reestablishment of lynx (Fe/is lynx) in the southern Rocky Mountains (Seidel et al. 1998). This draft outlined generally two methods for assessing snowshoe hare (Lepus americanus) habitat use or presence and abundance or population trends as recommended by Weaver (1997). The first method was winter track surveys and the second was counts of snowshoe hare pellets (fecal droppings). Tracks in the snow have long been used to note habitat use and the presence of animals (Forrest 1988, Halfpenny 1986). However, only careful approaches or methods may yield definitive density or population estimates (Becker et al. 1998). A winter track survey was completed during the winter months of 1998 and reported by Byrne (1998). • Counts of snowshoe hare fecal pellets have been used to estimate population trends or density (Angerbjorn 1983, Krebs et al. 1987, Wolff 1982). Angerbjorn (1983) estimated density in Sweden from counts of square-shaped quadrats of 0.1 m2 and obtained log-log regression: log (pellets)= 1.02 log (hare density)+ 0.44, where hare density is per hectare (ha). He found a close relationship between pellet counts and hare numbers (r2 = 0.91). Conversely, Wolff (1982:141) indicated that "...pellet counts can be used to indicate habitat use or population trends, but not to estimate population numbers." Krebs et al. (1987) found a relationship between mean pellet counts and mean hare density on 50 quadrats of0.155 m2 (5.08 x 305 cm). A modified version of his equation, log10 (hares/ha) = ((log 10 (pellets) - 0.2359] x 2.303) + 0.2773, was used by Slough and Mowat (1996). Since then, the equation has been modified several times. The purpose of this document is to report on snowshoe hare pellet counts, the results of estimating hare densities across major habitat types and associated selected habitat characteristics, and an approach for estimating hare habitat as it relates to providing the primary prey for reintroduced lynx. METHODS Krebs Plots Five major core areas were delineated for the Kreb's pelletplot counts (Fig. 1). The blocks were selected based on large contiguous parcels of land that appeared to have suitable habitat (oak, aspen, coniferous forest type or a mixture of these types). The vegetation data is from the Colorado GAP Analysis project (Thompson et al. 1993). Natural or manmade barriers, such as Interstate 70, further define the block boundaries. Small isolated blocks of suitable habitat such as Greenhorn Mountain, the Roan Plateau, Sangre de Cristos, and the Uncomphagre Plateau were not considered in the hare data collection and the GIS maps. Random points for each of the five blocks were generated using a program modified after Zack (pers. com., J. Zack) which created a grid for each vegetation type with random numbers between 0 and 100,000. A sub-program checked the number of cells containing identical values, and aggregated these until a total was reached that was equal or greater than the required number of random points. The centroids of the cells with values lower than this cut-off value were then plotted as an Arc/Info coverage. �70 The number of random points generated across the vegetation types (Fig. 2) were about 200 for blocks l, 4, and 5, and 100 for blocks 2 and 3 (in some cases random point program generated a few extra points). Initially, every 4th random point ploted on map (BLM Surface Mangement Status 1:100,000 scale) overlays were selected to insure wide distribution and randomness in case all points could not be completed. According to the protocol used, once the location was determined by use of a GPS unit (matching UTM coordinates generated for a given point as listed on the overlay) or map orienteering, a random bearing (0360 deg) was chosen, and a rectangular array of 10 Krebs plots was set (A), each 30 m apart (rectangular array= 30 m x 120 m, with 5 plots per side in direction and then in opposite direction of the bearing). Additionally, a second array (B) was selected at a randomly chosen bearing and distance (10-190 m inclusive) from the completion point (about 30 m from the beginning of the first array) of the first array (A). Hence, pellet counts were made for two fairly close areas near each randomly selected point. These pellets were tallied as either new or old and their means calculated. New and old pellets were differentiated by color, lighter tan being judged "new" (estimated from current season), and darker gray being judged "old" (estimated from before current season). The mean number of pellets (2 sets of 10, i.e. n = 20 plots for each randomly selected point [Fig. 31) was entered into a published equation to produce an estimated number of hares per hectare. This equation was a modified version of Krebs et al. (1987) (log 10 hares/ha= {[(0.8127 x log 10 pellets) - 0.2359] x 2.303} + 0.2773, as in Slough and Mowat 1996). Later, the equation was modified (per. com., K. Poole, 9 Nov 98). Still later, it was modified again (per. com., C. Krebs, 29 Sep 98 and 24 Nov 98). This third iteration, lo& (hares/ha)= (0.888962 x 10& [pellets] - 1.203391) x 1.567026, was recommended by Charles Krebs (per. com., C. Krebs, 24 Nov 98) and the one ultimately used for the overall analyses. It was based on his review of his data (collected samples from the Yukon: 1976-1996, n = 86, calculated from annual pellet counts in June and average densities of hares from the previous spring and autumn estimated by markrecapture including adding a correction for bias [Sprugel 1983]). Habitat Attributes at Plot Sites Categories other than those related to the plot locations (Name of Property, Game Management Unit [GMU], County, Lynx Survey Block Number, General Location Description, Land Status, and UTM coordinates) recorded on the field forms (Appendix A) included: - elevation - overstory (primary, secondary, and tertiary) - vegetative structure (e.g. mature, old growth) - understory vegetation (primary, secondary, and tertiary) - understory vegetation density (estimated visual obstruction of vegetation from IO m in front of a vertical I x 6 ft [0.30 x 1.83 m] white panel, marked off in ft2 [0.30 m2], where highest value of 6.0 = no visual obstruction, and to be recorded with photograph) - slope - aspect - overstory and understory distribution (patchy or continuous ) - domestic grazing presence or absence. Model Probability Surface A logistic model was used to generate a continuous surface representing the probability of any geographic location supporting snowshoe hare habitat (pers. com., M. Wunder). The results from the Krebs plot effort were examined spatially using chi-squared analysis to produce parameter estimates for the model. �71 Parameter values were estimated for each of vegetation (primary cover type), elevation, slope, and aspect using the Krebs plot coverage, the vegetation coverage from the GAP analysis project, and a digital elevation model (DEM) for the study area. The DEM was used to generate separate grids for elevation, slope and aspect. Parameter estimates with P-values less than 0.05 were then used in the logistic model, which was then run using the pertinent grids. The model equation follows: 1/l+exp(Ao + Aa *aspect+ Ae *elevation+ Av* vegetation), where Ao is the overall parameter estimate, Aa is the estimate value for aspect, Ae is that for elevation, and Av is that for vegetation. Release Sites Initially, release sites were selected based on the model probability surface, but for practical reasons of access and managing the media and number of observers during the releases, private land areas abutting potential lynx habitat or proximity to the Weminuche Wilderness were given high priority. Potential sites were inspected and coordinated with landowners and caretakers where appropriate. RESULTS AND DISCUSSION Krebs Plots Paired pellet plot arrays and single plot arrays were completed at 303 and 5 randomly selected points, respectively. Sample sizes of the number of plot arrays ranged from 62-239 (Table 1, Appendices B-F) with the most plot arrays (n = 239) completed in block 5 (Appendix F). Distribution of hare densities by National Forest (Figs. 4-5), by county (Figs. 6-7), and by block (Fig. 8), suggest that block 5 had the highest hare density. Density calculations yielded 0.44 hares per ha for block 5 and lower densities for the remaining blocks (Fig. 9). This mean of hares per ha in block 5 results from using the latest regression equation from Krebs as discussed under Krebs Plots in Methods. The initial calculation using an.earlier equation (Slough and Mowat [ 1996]) yielded a mean of almost 1.2 hares per ha (Fig. 10). Using different equations and possibly using them incorrectly yields substantially different results. Also, initial analysis of block 5 data using a SAS program used in the Northwest Territories (per. com., K. Poole, 14 Sep 98) was corrected as were the analyses of data from 2 areas over 2 years in Wyoming, where lynx were present (per. com., K. Poole, 9 Sep 98; per. com. T. Laurion, 18 May 99) (Table 2). Our calculations using the latest regression equation from Krebs (per. com., C. Krebs, 27 Oct 98 and 24 Nov 98), matched these same values (0.817, 0.856, 0.694, and 1.429, respectively) (Table 2). Thus, using the most current accepted calculations, the Wyoming areas having lynx present, had hare densities ranging from 0.817-1.429, similar to some other densities reported (0.73/ ha, Dolbeer and Clark 1975; 1.40/ha, Lima 1998; 2.40/ha, Meslow and Keith 1968), but subtantially lower than others (12.3/ha, Bailey et al. 1986), and all higher than that considered the lower "edge" for suppporting lynx (0.5/ha; C. Krebs, per. comm., 24 Nov 98). Dolbeer and Clark's (1975) 0.73 hares per ha might be considered a model for habitat in Colorado, but another study using 175 permanent plots, reports lower densities (0.053/ha in lodgepole pine and 0.068/ha in spruce/fir) (Shivery 1997). This causes concern that the density of our 0.44 hares per ha in block 5 may not be sufficient as a primary prey base to support lynx. Part of the problem, however, is that our data were collected randomly across 11 primary overstory types. The Wyoming data were collected from plots ~lected in coniferous forest types. �72 It is generally accepted that some of the primary overstory types (probably the 3 non-conifer types [aspen {Populus tremuloides}, willow {Salix spp}, and Gamble's oak {Quercus gambelii} or mixed mountain shrub], ponderosa pine (Pinus ponderosa), and bristlecone pine (Pinus aristata) might be expected to have low hare densities. Apparently this was the case based on our small sample sizes. Most of our samples were taken in 6 conifer types described below. Hence, the problem remains - we apparently have a relatively low density of hares if compared to the Wyoming data, but is it comparable? Given that Wyoming's plots were taken non-randomly in optimal habitats, the extent to which optimal habitat considerations could induce bias is unknown. It is possible that if we had used our method of selecting random samples in Wyoming that their means would have been lower. Similarly, it is possible that ifwe had sampled randomly in "optimal habitats" (whatever those are in Colorado) that our means would have been higher. In either case, how much lower, or higher, is simply unknown. This probably limits the utility of comparing these 2 sets of data. Habitat Attributes at Plot Sites Attributes from the plot locations as prescribed by data collection (Appendix A) across densities, included elevation (Fig. 11 ), 11 primary overstory or canopy types, - Lodgepole pine (Pinus contorta) - Englemann spruce (Picea engelmannli) - Subalpine fir (Abies lasiocarpa) - Douglas fir (Pseudotsuga menziesli) - Ponderosa pine - Limber pine (Pinus jlexi/is) - Bristlecone pine - White fir (Abies concolor) -Aspen -Willow - Gamble's oak or mixed mountain shrub (Fig. 12), structure (Fig. 13), primary understory vegetation (Fig. 14), vegetation density indices (Fig. 15), slope (Fig. 16), aspect (Fig. 17), and grazing (Fig. 18). The relationships between hare density and some of these attributes, i.e. elevation, structure, primary understory, aspect, and grazing, yielded relatively predictable results. Forest types preferred by hares in Colorado occur at higher elevations (Fig. 11). Limber pine and white fir show the highest hare densities, but with very small sample sizes these densities are probably not represen~ve (Fig. 12). Conversely, Englemann spruce had a sample of 220, lodgepole pine 108, subalpine fir 64, and Douglas fir 48 (Fig. 12). Willow had only one sample where it was considered the primary overstory and is not included in Fig. 12. For structure, most of the plots completed were in mature or old growth. The small sample of sapling/pole (n = 49 of 606 records, with only about 50% of the 49 having any pellets) and the even more negligible sample sizes ofGrass/Forb and Shrub/Seedling, essentially yield zero densities (Fig. 13). Selected understory species appear to be associated with higher hare densities than others (Fig. 14), but another measurement, the vegetation density indices, may suggest that the amount and height of the understory is limited (Fig. 15 and 376 photographs appended to data records). Most of the samples (245 and 97 of 428 records) occurred in the 5.0-6.0 and 4.0-4.9 categories, respectively, where little understory obscured the panel (Fig. 15). The value for <1.0 is unlikely to be representative. Other workers have suggested that predation on snowshoe hares may be heaviest in habitats that have little understory (Sievert and Keith 1985), that snowshoe hares avoided open understories and greater understory �73 density provided both escape and thermal cover (Litvaitis et al. 1985), and that height ofunderstory was important (Wolfe et al. [1982] found a strong correlation between hare use and cover densities at heights of 1. 0-2.5 m above ground, and that vegetation types in which cover densities above snow level [ 1. 0-1.5 m] were at least 40%, accounted for 85% of winter use by hares). Hare density shows a bimodal response to slope (Fig. 16), but upon inspection of photographs it appears that at least one field person consistently over-estimated degree of slope, probably skewing these data. In relation to aspect, hares probably avoided the wanner, dryer, southern exposures (Fig. 17). Hare density means from plots judged to have domestic grazing or not (Fig. 18) were predictably no different (0.358 vs 0.342, respectively). How recent or the extent of any grazing was not estimated. Judging vegetation distribution for overstory and understory as patchy or continuous (Appendix A) was largely dependent on "scale" and was therefore not analyzed. Similarly, "Old" pellets were not analyzed because their age or persistence could not be determined. Generally, these pellets occurred in low numbers and were noted in 402 of 613 records. Cottontail (Sylvilagus nuttalli) and jackrabbit (Lepus townsendi) pellets were noted in a low number of records and were not analyzed. Some overlap or abutting of habitat boundaries might be expected between hares and mountain cottontails, but doubtfully with jackrabbits. One could conclude, that if you counted jackrabbit pellets, you were in the "wrong" (i.e., non-hare) habitat. Model Probability Surface The probability values from the model were naturally distributed across fiv~ range classes (pers. com., M. Wunder). These were represented as zero percent probability, one to twenty percent, twenty to eighty, eighty to ninety-three and ninety-three to one hundred percent probability (Fig. 19). The most relevant results include the areas that were modeled as greater than 80 percent probability of hosting snowshoe hare habitat. Block 5 included the largest surface area and proportion of area that was modeled greater than 80 percent probability. Areas within a radius of 3.2 km from potential lynx release sites that were predicted with greater than 80% probability to provide suitable snowshoe hare habitat were delineated (Fig. 20). The distribution and amount of the area is shown in Table 3. It should be noted, however, that raw values for area may not be the best (and certainly is not the only) criterion for drawing conclusions about the suitability of an area for snowshoe hare or lynx. We did not develop any method for examining the distribution of this area for spatial context. If and when this issue is addressed in the future, it should be acknowledged that there are many varied factors involved with such an analysis. Release Sites Hence, one of the sites north of the Weminuche Wilderness, Humphreys (Goose Creek), was ultimately chosen for the initial release February 3-4, 1999. Similarly, other sites northwest, north, south, and southwest of the Weminuche Wilderness Area, were ultimately chosen for later releases in March. Release sites in Block 5 located northwest, north, and east (n = 4) and south and southwest (n = 4) of the Weminuche Wilderness were initially described using a predicted probability surface of snowshoe hare habitat (per. comm., M. Wunder) and examined using the following criteria: - ownership, public and private lands where permission for egress was obtained - access, where at least snowmobiles could be used to gain access - seclusion, where public access is generally not available - habitat near release site should have a range of 1,000-10,000 ha of continuous or at least only lightly broken conifer forests �74 - connectivity, where forest segments are sufficiently contiguous to allow for traveling lynx to avoid open areas The 4 sites northwest, north, and east of the Weminuche Wilderness Area were ranked as follows: -Humphreys (Goose Creek) - Red Mountain Ck - Rio Grand Reservoir, and - Big Meadows Similarly, the 4 sites located south and southwest of the Weminuche Wilderness Area were ranked as follows: - Weminuche Valley - Beaver Meadows - Endlich Mesa, and - Middle Mtn/Bear Ck CONCLUSIONS/SUMMARY The most relevant results in this report are the estimates of snowshoe hare density, the type of overstory in which the highest densities occurred (Engleman Spruce, based on those with adequate sample size) and where the highest densities occurred (National Forests/wilderness areas and counties in Block 5; Figs. 4-8, 9, 10, 12, and Appendix H). These indicate marginal densities for supporting reintroduced lynx according to the literature and professionals working with these species. Granted that most of the work and most of the professionals working in this field are in the northern boreal forests where snowshoe hare populations cycle dramatically. Poole (1995) reported that concomitant with the first full winter of low hare density in the North West Territories (91-92), all resident lynx died or dispersed in a 135-km2 study area. Marginal habitat conditions for hares probably result in a scarcity of prey and may explain the relatively large home ranges (and hence their behavioral adaptations toward dispersal) of the lynx (Koehler 1990, Roloff 1997). Demographic characteristics of lynx, if any successfully establish home ranges, may be representative of lynx populations along the southern periphery of their range where habitat conditions are mariginal for snowshoe hares. ACKNOWLEDGMENTS We especially thank Pam Albers, Travis Black, Heath McNally, and Steven Znamenacek for the completion of most of the Krebs plots. Other agency field assistance came from Steve King, Rocky Mountain National Park; Gary Patton, U.S. Fish and Wildlife; Kit Buell and Jennifer Zahratka, U.S. Forest Service; and Lee Upham and crews, Bureau of Land Management. Field work by Division personnel included Bill Andree, Jim Hicks, Larry Green, Kevin Wright, Bill Heicher, Paul Jones, Doug Homan, Rick Adams, Scot Wait, Dave Kenvin, Dale Reed, Gene Byrne, and Brent Woodward. Gene Byrne organized and coordinated the field work. Work by volunteers included Don Boyer, K. Cordova, Brett Ochs, Travis McLean, Amy Bellotti, Kathrin Schrott, Gretchen Cross, Francis Kleffner, Griffin Madison, Lynn Dwyer, and Dawson Swanson. Geographic Information Systems (GIS) support and cartography provided by Jon Kindler. Dawn Brownne assisted with data entry. Francie Pusateri provided advice and converted Visual dBase files to EXCEL. Mike Wunder, Natural Heritage Program, generated the model probability surface and associated figures. We also thank Tom Beck, Rich Reading, and Tanya Shenk for reviewing the manuscript. Work reported here was funded mostly by Division GoCo funds and from funds from Vail Associates. �75 LITERATURE CITED Angerbjorn, A. 1983. Reliability of pellet counts as density estimates of mountain hares. Finn. Game Res. 41:13-20. Bailey, T. N., E. E. Bangs, M. F. Portner, J. C. Malloy, and R. J. McAvinchey. 1986. An apparent overexploitated lynx population on the Kenai Peninsula, Alaska. J. Wildl. Manage. 50:279-290. Becker, E. F., M.A. Spindler, and T. 0. Osborne. 1998. A population estimator based on network sampling of tracks in the snow. J. Wildl. Manage. 62:968-977. Byrne, G. 1998. A Colorado winter track survey for snowshoe hares and other species. Colo. Div. Wildl. 35pp. Dolbeer, R. A., and W.R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. J. Wildl. Manage. 39:535-549. Forrest, L. R. 1988. Field guide to tracking animals in the snow. Stackpole Books, Harrisburg, PA. 185 pp. • Halfpenny, J. 1986. A field guide to mammal tracking in North America. Johnson Publishing Co., Boulder, CO. 161 pp. Koehler, G. M. 1990. Population and habitat characteristics oflynx and snowshoe hare in north central Washington. Can. J. Zool. 68:845-851. Krebs, C. J., B. S. Gilbert, S. Boutin, and R. Boonstra. 1987. Estimation of snowshoe hare density from turd transects. Can. J. Zool. 65:565-567. Lima, S. L. 1998. Nonlethal effects in the ecology of predatorprey interactions. BioSci. 48:25-34. Litvaitis, J. A., J. A. Sherburne, and J. A. Bissonnette. 1985. Influence of understory characteristics on snowshoe hare habitat use and density. J. Wildl. Manage. 49:866-873. Meslow, E. C., and L.B. Keith. 1968. Demographic parameters ofa snowshoe hare population. J. Wildl. Manage. 32(4):812-834. Poole, K. G. 1995. Spatial organization of a lynx population. Can. J. Zool. 73:632-641. Roloff, G. J., and J.B. Haufler. 1997. Establishing population viability planning objectives based on habitat potentials. Wildl. Soc. Bull. 25:895-904. Seidel, J., B. Andree, S. Berlinger, K. Buell, G. Byrne, B. Gill, D. Kenvin, and D. Reed. 1998. Draft strategy for the conservation and reestablishment of lynx and wolverine in the southern Rocky Mountains. U.S. Forest service, National Park Service, U.S. Fish and Wildlife Service, and Colorado Division of Wildlife. 115pp. Shively, K. 1997. Snowshoe hare density in Vail, Colorado; implications for lynx reintroduction. Unpub. Rep.:1-7. Sievert, P.R., and L.B. Keith. 1985. Survival of snowshoe hares at a geographic range boundary. J. Wildl. Manage. 49:854-866. Slough, B. G., and G. Mowat. 1996. Lynx population dynamics in an untrapped refugium. J. Wildl. Manage. 60:946-961. Sprugel, D. G. 1983. Correcting for bias in log-transformed allometric equations. Ecol. 64:209-210. Thompson, T. G., W. A. Reiners, and D. L. Schrupp. 1993. Colorado gap analysis vegetation classification (draft). Unpub. Rpt. Weaver, J. L. 1997. Reconnaissance oflynx habitat in Colorado. Wildl. Conserv. Soc. lOpp. Wolff, J. 0. 1982. Snowshoe hare. Pages 140-141 in CRC handbook of census methods for terrestrial vertebrates. Edited by D E Davis. CRC Press, Boca Raton, FL. Wolff, J. 0., N. V. Debyln, C. S. Winchell, and T. R. McCabe. 1982. Snowshoe hare cover relationships in northern Utah. J. Wildl. Manage. 46:662-670. �76 Table 1. Block numbers, number of points generated, points completed (2 plot arrays for each point with 5 exceptions where only 1 array was completed), and plot arrays completed ( 10 plots for each array). Block No. of Points No. of Points No. of Plot Arrays Generated Completed (2 x points completed) 1 2 3 4 5 Total 200 100 100 200 200 800 57 31 33.5 64.5 119.5 305.5 114 62 67 129 239 611 Table 2. Mean number of hare pellets per Krebs plot and calculated hare densities per ha in 2 areas over 2 years in Wyoming where l)'TIX occurred and in Block 5 of this study. Wyoming8 Colorado Area DUBOIS97 DUBOIS98 MERNA97 MERN98 BLOCK5 Pellets/plot Hares/ha 1.86 0.82 (0.64-1.05)b 1.96 0.86 (0.67-1.09) 1.55 0.69 (0.54-0.89) 3.49 1.43 (1.11-1.84) 0.94 0.44 (0.35-0.56) •Data from T. Laurion, calculations by K. Poole. b95% CI. Table 3. Study areas or blocks, areas with greater than 80 percent probability of providing suitable hare habitat, and the proportion of the study areas involved. Study Area/Block Area (ha) with > 80% Probability of Proportion (%) of Study Area Providing Suitable Hare Habitat 1 2 3 4 5 Total 460,753 97,920 110,233 587,903 658,258 1 915 067 20.3 11.7 15.7 21.4 24.1 93.2 �1 I~ /L~-1 Dociduou•Oak ■ Aapon II ~ 1111) l'l!illllZr,I s--·tc· r•-•·IC lllllliilfl Douglaa Fir Lodgepole Pino - 0 0 .. ■ ■ ~<.:onifor (me. Blue Sptueo) u ~ 100 40 IO r.a.. I -, ----.J---- I I ,- - - - - - I I I :------' I I - - - -1- - - - - I I ~J I I_ - - ... - - - ....:i ....:i �--..:i 00 F,~. 2- ......*.,,.,,,, Study Area BoundAly Sample Point , / ' ,, , County Boundaiy ~ Intemato Higb.Wlly 100 I I :- - - - - - - - - - - - - - - - - - - --------- I - - - .,. __ ..,,,.. I 'r , ... ···········-··········------·· , I - - - - - 1- - - - - _,_ - - - - - - - - - - - �............................ SNOWSHOE HARE DENSITY SA * Sample Point ##•,...,#>' , f;·I~. !J , /\ '/ Study Alea Boundaiy County Boundaiy /V Intemate Highway I * ,,,, ] "1c I, ** -,,_, * * I I I I I I ,_ - - - - ,.•• I ista : I I I I -----------~ __ ,_J I - - - - - - - - - -1- - - - - - ' ✓ I I I 'rI ,-- ' ·---·····----------·--······· 80 ,- - - - - - - - I I *• 40 Mio, - - - - - - - - - - - - - -I 'L, * ,, ' 0 100 I I I I ,,_J-,lc--- *' ,.,.;,., u ...... ,0 0 --,------ I /~, '...,I I - - I - - - - - 1- - - - - ~- - - - - - - - - - - - I �00 0 SNOWSHOE HARE DENSITY BY NATIONAL FOREST D 0 Hares/ha - ----------- - 0.3 • 0.399 Harea/ha ~ 0.001 • .099 Ham/ha - 0.4 - 0.499 Harea/ha I ll 0.1 • 0.199 Harea/ha - >0.5 Harea/ha 0.2 • 0.299 Harea/ha 0 0 -- ,- .. - - - 40 Ma.. +---------,~ I I ~ I I I I I I I I I -- I----------1 ~------------------ I I :______, I I ----------1------ I --7-----I I I ~-~----------T----------- I , ~, I I I I I 5 • ·---·-··········--···-------- I I I I '.J I I_ - - - - - - - I I - - - I - - - - - 1- - - - - _,_ - - - - - - - - - - I �:c A) a (II ;,. "CJ CD "'I ':r A) 0 0 ...... 0 ~ ~ (,) 0 0 :i:,.. en 0 a> 0 ...... 9 00 9 <O ARAPAHO NF BUFFALO PEAKS WILDERNESS GRAND MESA NF GUNNISON NF LAGARITA WILDERNESS AREA 6' ~ RIOGRANDE NF (II ~ ROCKY MOUNTAIN ii NATIONAL PARK CD i Al CQ CD :::c m a C ::s en CD ~ tr '< "'I ROOSEVELT NF (II )> ii? A) r ROUTT NF "Tl 0 i SAN !SABEL NF SANJUAN NF UNCOMPAHGRE NF WEST ELK WILDERNESS WHITE RIVER NF l.r1 18 �00 N SNOWSHOE HARB DENSITY BY COUNTY D OHatell'ha 0.3 - 0.399 Hare,/ha G 0.001 - .099 HIU'ea/ha Ill 0A - OA99 Hare,/ha flil 0.1 - 0.199 Hatell'ha - >0.$ Hare,/ha 1111 0.2 - 0.299 Hares/ha 0- 0 ~ 0 40 Mi,e I 1---~ I I I I I I ----- .. I I I I I :- - - - - - - - - - - - - - - I I I I , _ _ _ _ _ _1 I I I I I I I - - - - - - - - - -1- - - - - - --,------ I I I I /- -,- - - • • - • - - - - T - - - - - - - - • I I Pueblo , ;,-. ' f f f I I I ,. I.,,. )- I I '•I ' I I r' ' 1('" , ... I I ., __ ... ,,. ,- '.J I I_ - - - - - - - -- I -----1----1 '------------ �0 0 0 0 C> N :i,.. <J> 0 0 0 0 0 0 0 0 0 0 0 0 0 co 0 0 0 C> 0 0 0 iv 0 0 0 :I: ... II) (I) VJ 1:1 ... (I) ::r II) :c $1) ., CD CJ CD :::l LA 0 0 C :J ~ en ~ O" '< C) 0 C: :::l ~ ---0 £8 �---- SNOWSHOE HARB DENSITY (HARES/HA) 0<0.1 0.10. Ucmct,n 50 0 0 1---~ DENVER -- -,- - - --- - -- -- ' I I I I I I I I I -- I---------- 1 I I I -----------------I : ______1 ' I - - - - - - - - -' I I I I I I I I I I ~ontro - - - - - - - - . -1- - - - - - ..... ~:. \ I I I 'r--------------' \ , --,------ J- -,- - - - - " - " - - - T - - - - - - - - - • • • I \ Pueblo 'I ' . . \,-,1 \ r ...... ' . ' \ ' ... - , - -,---------~ I I '.J I , ,_ - - - - - - - -------- - - - - - -- - - - - - - - - - - - 1· ~,. / ... ,' \~ \ ) I 'r' ·:!'-~~: 5 Durango !'i; ············-··········--···· ., ~' - ... ,. I 00 -"" �85 0.60 0 50 0.40 C1l .s::. ... Q) Q. VJ ... 0.30 Q) C1l :I: 0.20 0.10 0.00 2 Fig. 9. bars). 4 5 Mean hare density (w/ SD) by block (samp~e sizes same as in Fig. 10). 2 Fig. 10. 3 3 4 Mean hare density by block using Kreb's oriqinal equation (sample sizes above 5 �86 3 25 ~ 2 "' ,E e ., 1/) ~ :!' 1.5 ·;;; ., C Cl e r"' 0.5 0 <7,000 FT. 8,000 • 8,999 7,000 • 7,999 9,000 • 9,999 10,000 • 10,999 11,000-11,999 >=12,000 El~vation Ranges Hares per ha z w Q'. Q'. ~ a: ii: a: 0 z :5 C) ii: w w Q. a:__. 0 0 ::::> 0 i1J __. m 0 < C) 0 w Cl) < z w 0 w __. ICl) ii: m Cl) 0 z z w __. < m w Cl) 0 ::::> Q. C) 0 __. < Cl) ::::E w z a: < Cl) Q'. w z Zw <o ::::E ::> Woc __. Q. ~ Cl) w z 0 Q. Fig.12. Hare density by primary overstory (sample sizes above bars). Q'. ii: w I- I ~ w z a: Q'. w m ::::E ::::; �87 Hare Density by Forest Structure 16 ,---,-:-=----,----.---,---, ~'. ,[ 1.4 1.2 ... ~ 1/) ., :. :S :i!- 0.8 'iii ., C C ; 0.6 ::c 0.4 0.2 SHRUB/SEEDLING GRASS/FORS SAPLING/POLE MATURE STAND OLD GROWTH ~orest Structure 1.2 08 "' a. 0 6 .. 1/) ~ ::c 04 0.2 AMAL Fig. 14 ARCO ARUV CA spp JU spp QUGA SHCA SYAL SYOC Hare density by selected primary understories (number of records n = 10 or>, and pellets n = 1 or>; abbr. see Appendix G). VACA VASC �88 OS Hares per ha 0.3 0.1 0 5.0-6.0 4.0-4.9 3.0-3.9 2.0-2.9 < 1.0 1.0-1.9 Fig. 15. Vegetation density indices by hare deniity. .; 2 ~., :. ;;_ ~ 1.5 'iii ., C: 0 ~ "' :c 0.5 0 < 10 10 - 19 20-29 30-39 40- 49 Slope Range (degrees) 50 -59 60-69 >= 70 �89 Hare Density by Aspect (Area 5) NORTH NORTHEAST EAST SOUTHEAST • SOUTH SOUTHWEST Aspect 0.4 0.35 0.3 0.25 0.2 0.15 0.1 a.as 0 Fig. 1a. Absence or presence of grazing (1st and 2nd bar, respectively) versus hare density. WEST NORTHWEST �rig. 1 CJ. Study area-wide view showing predicted probability surface of snowshoe hare nabitat, study area boundaries, roads, and municipality boundaries. Variable Ao Aa As Ae Av . . - - - - . , r - - : - - - - - - · ·····-· - ............... __ \0 0 Parameter p 0.0001 15.6638 0.2300 0.0503 0.8573 0.0641 0.0001 -0.7106 -1.4909 0.0130 i--.----_J ---~,~ .. I Model Surface = 1/1 +exp(Ao+Aa* Aspect+Ae"Elevation+Av*Vegetation) ,.J ' .. •\_,/ Highways Study Areas Predicted Probability -0 -1-20% 1 ·'?~~I 20-80% .--180-93% · - 93-100% ' , .. :<:. 'p-,1 Snowshoe hare data used in this map were collected by the CDOW, USFS, NPS, USFWS, biologists and numerous volunteers. \ J-{ait,y,.:'§, ..~ ~ The data were compiled and provided by CDOW staff The predictive model was constructed by CNHP staff ' ' '~\ \ e Co; Oll ;;,i'P ····-·••-···--- ---···----·-······--' �Fig. 20. Areas within a radius of 3.2 km from potential lynx release sites that are predicted with greater than 80% probability to provide suitable snowshoe hare habitat. • Potential release sites 80-100%Probability within two mile radius Wilderness and Research Natural Areas Predicted Probability of Suitable Habitat D . -0 -1-20% 1 :_._;· 120-80% ~80-93% - - 93-100% I I. ! Hectares Name Endlich Mesa 14 63 Weminuche Valley 596 Be aver Meadows 469 Big Meadows 2108 ----------------Rio Grande____ Reservo1___..__________ 1421 _ i Humphreys _ _ _ ____..__·"_--•________§_~_J ------.----- Mosca Divide Middle Mtn/Tuckervi Coal Bank/Lime _____,_____ Middle Mt~/Bear Cr 977 : Wi 11 i a rn s Cr TH 921 : West Fork San Juan 912 ----~---- ---------·--·--- i I ----------·--·-··---- Red Mountain Creek ----'------···· Transfer Pk. ---------Four mile TH 817. ---·- ----~ 794 656 ---------------------Middle Fork Piedra 610 ---------East Fork Piedra 431 ---------------Pl um ta w 120 ••••• . ; -····--··-·- - - - - - - - - - - - - - 0 40 Kilometers s . -·· - - · - - · - · • - · · - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - �92 Colo.--ado Di VI•sion of Wldlife - Krebs Pellet Plot Survey Form Krebs Plot# · - Observer(s): Slope: (in Degrees) lime: Date: Name of Property GMU: Lynx Suivey Block# (Adual) County: Start Location from? D General Location Description: D GPS Map D D Aspect 0 UTMY: UTMX: Zone: D D 12 13 App QH..J,.x A N D s □ E D □ Patchy □ Continuous Understory □ Patchy D Continuous KREBS PLOT DATA: s,_,, ____ New Old New Old J~bbit New Old -1 - -- l - - - 2 - - - - -j - -- 3 - - -! - -- _j - -- - -- I 4 - - D - - - • GPS □ 5 - - - 6 - - - 7 - - - Secondary OVerstory: 8 - - Tertiaty OVerstcxy: 9 - Vegetative Stn.icture Class: 10 _ feet other Prima,y Overatory: GraS$IFOrb L Shrublseedrmg Sapling/Pole Mature OldGl"OINth L Underatory Vegetative Type: Common Name 1 (Primary) 2 (8econdary) 3 (Tertiary) Grazed D KrebsFonn Yes □ 7-8-98 No i - -- - ~1 - -- - - - - -- - - - - - -- - - - - - I - , ,' OVerstory Type: other - 1 D Cott<intail Elevation (MSL): From: Topo - NE WN SE SW overstay J ·NAD27 D V\GS84 [J NAD83 i Rat 0--5 Moderate 6-20 Moderately steep 21-40 Steep 41 degrees or more Vegetation Distribution: land status COde: t D D D D w C D Datum: Density Index Photo Taken?· D Yes □ No -.. r- L ,. Land Status Codes: ,_ G ~e Private - P U.S. F. S. -F BLM-8 ~ State,LaAd Board - S OON-D National Park - N other- O (Explain) Overstory Veg. Type Codes: Lodgepole Pine - L mann S(:)(1!ce - S ~ Su pine Fir - F • lasFir-D ~ P erosa Pine - P Umber Pine - X Bristteoone Pine - B WliteFir-W Asoen-A WIICMt-Y Gamble's Oak or mixed mountain Shrub - C Comments (Continue on back if needed): _ _ _ _ _ _ _ _ __ �I KREBSPL LSBNUM UTMX FC-21-A FC-21-B FC-95-A FC-95-B FC-97-A FC-97-B FC-101-A 1 1 1 1 1 FC-101-B FC-178-A FC-178-B 1 1 1 1 1 1 1 1 1 1 1 1 VA-62-A VA-62-B VA-132-A VA-132-B VA-144-A VA-144-B VA-149-A VA-149-B VA-150-A VA-150-B VA-155-A VA-155-B VA-161-A VA-161-B VA-163-A VA-163-B EP-40-A EP-40-B VA-164-A VA-164-B VA-135-B VA-153-A VA-153-B VA-135-A WA-77-B WA-81-A WA-81-B WA-73-A WA-73-B WA-75-A WA-75-B VA-166-A VA-166-B DW-13-A DW-13-B DW-49-A 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 446555 446510 448682 448660 428211 428210 425389 UTMY 453580 397240 397326 392830 373296 373376 392913 403816 SN9 MEAN SN10 1 1 1 I 4489480 4505757 L 4505920 L 4373370 S 4372950 S 4424300 A 394760 4424351 L 371270 4410075 F 371161 4410046 F 406232 4405739 L 5 4 2 6 1 3 1 (, .. ' 1 4405872 S 4405295 L 4405428 L 4394020 L App~dix (J 2 425240 450931 450870 388866 389100 394594 406200 393331 393518 406653 406432 405438 405303 403862 403935 453565 SNS SN3 SN2 PRIMOVE SN1 4488703 F 4488640 S 4492238 S 4492180 S 4490776 S 4490840 S 4489448 0 1 1 1 1 1 1 1 43.9.3960 A 43!!6943 S 4386987 S 4384857 F 4364789 S 4442252 F 4442167 L 4381807 F 4381750 F 4419021 F 4399796 F 4399898 L 4419011 L 4528065 L 1 4538167 L 4531982 L 4532088 A 4376295 L 4376415 L 4374855 A 1 1 1 449594 4374855 A 434487 4398253 S 1 1 5 3 •1 2 407484 4521979 S 407495 4522070 S 406978 4538343 L 407057 405250 405123 406867 407088 449594 4 1 21 2 1 1 7 ·2 4 1 1 1 2 1 •1 1 1 1 1 1 1 2 1 1 1 3 1 3 2 1 4 1 2 10 1 1 3 4 1 16 4 4 1 . Page 1 of3 2 KREB'SN HARE DEN!- ' 0.4 -0.55929 0.2 -0.80394 0.1 -1.0486 0.1 • -1.0486 0 0 0.3 -0.66083 0 0 0 0 0.9 -0.27306 1.2 -0.17152 0 0 0 0 0.1 -1.0486 0 0 0.1 -1.0486 0 0 0 0 0.1 -1.0486 0.2 -0.80394 0.1 -1.0486 0.1 -1.0486 0.2 -0.80394 0 0 0 0 0 0 0 0 0.6 -0.41617 0.1 -1.0486 0.5 -0.48052 0 0 0.6 -0.41617 0.9 -0.27306 2.6 0.101391 1.2 -0.17152 0 0 0.1 -1.0486 0.1 -1.0486 0.1 -1.0486 0.1 -1.0486 0.7 -0.36176 0.3 -0.66083 0 0 0.5 -0.48052 2.1 0.026007 2.5 0.087548 0.9 -0.27306 0.275876311 0.1570576~ 0.08941368E 0. 08941368E ( 0.21836012~ ( ( 0.53326447< 0.67372666! ( ( 0.08941368( ( 0. 089413681 ( ( 0. 089413681 0.1570576! 0.089413681 0.089413681 0.1570576! I I I I 0.3835557: 0.08941368 1 0.33073167 0.3835557 0.53326447 1.26296421 0.67372666 0.08941368 0.08941368 0.08941368 0.08941368 0.43474840 0.21836012 0.33073167 1.06171345 1.22334116 0.53326M7 w �KREBSPL LSBNUM UTMX DW-49-B DW-50-A DW-50-B DW-53--A DW-53--B DW-56-A DW-56-B DW-145-Jl DW-145-8 DW-157-A DW-157-8 EP-30-A EP-30-B EP-33--A EP-33--8 EP-118-A EP-118-8 EP-38-A EP-38-B EP-180-A EP-180-8 EP-9-A EP-9-8 EP-31-A EP-31-B EP-26-A EP-26-8 EP-6-A EP-6-B EP-27-A EP-27-8 EP-1-A EP-1-B EP-4-A EP-4-8 EP-28-A EP-28-8 EP-24-A EP-24-B EP-32-A EP-32-B EP-11-A EP-11-B EP-8-A EP-8-8 EP-36-A 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 434500 426188 426270 435584 435605 454053 453998 451826 451826 461484 461435 444784 444662 451484 451463 451984 452014 450684 450679 450158 450001 442308 442240 445384 445432 452684 452726 437509 437449 438284 438338 427480 427373 422217 422068 425884 426471 431484 431517 432284 432314 425062 424950 433478 433573 429484 UTMY 4398210 S 4396472 S 4396380 S 4388779 S 4388725 S 4379173 S 4379265 S 4410001 L 4410131 L 4390954 L 4390970 L 4470479 S 4470409 X 4460879 X 4460801 X 4448579 F 4448550 F 4448279 F 4448511 F 4474204 L 4478203 F 4465163 S 4464949 F 4470179 L 4470199 L 447.13879 L 4478919 L 4471239 S 4471169 S 4476679 S 4476732 S 4472833 L 4472806 L 4470980 S 4470689 S 4474379 S 4473939 L 4482579 S 4482788 S 4461379 L 4461296 S SN3 SN2 PRIMOVE SN1 3 1 SN5 SN4 SN6 SN7 SN8 SN9 SN10 1 MEAN 3 1 1 1 2 1 8 1 1 1 1 1 1 2 3 7 1 0 1 0 1 1 3 5 1 2 4 1 1 2 1 1 4 1 1 3 8 1 2 2 4 3 1 ~ ' 1 2 1 1 1 1 1 1 2 1 2 2 4 1 1 1 4 0 1 1 2 2 1 4 1 4 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 3 1 1 2 1 1 3 1 .1 1 14 2 0 1 2 1 3 2 1 1 3 1 1 1 1 1 2 2 1 16 1 3 4464125 L 4464089 L 4451783 L 4451435 F 4452379 L Page2of3 KREB'S N HARE DENSI 0.8 -0.31463 0.5 -0.48052 0.1 -1.0486 1 -0.23587 0.1 -1.0486 0.5 -0.48052 0.8 -0.31463 0.3 -0.66083 0.6 -0.41617 0.3 -0.66083 1 -0.23587 2.1 0.026007 1.5 -0.09275 1.6 -0.06998 1 -0.23587 0.1 -1.0486 0.4 -0.55929 0.2 -0.80394 0 0 0.4 -0.55929 0 0 0.1 -1.0486 0 0 0.9 -0.27306 1 -0.23587 0.3 -0.66083 0.1 -1.0486 0.4 -0.55929 0.1 -1.0486 0.3 -0.66083 0.4 -0.55929 0.1 -1.0486 -1.0486 0.1 0.2 -0.80394 0.1 -1.0486 1.2 -0.17152 2.4 0.073139 0.2 -0.80394 1.6 -0.06998 0.1 -1.0486 0 0 0.3 -0.66083 0 0 0 0 0 0 0 0 0.48458460£ 0.33073167E 0.08941368E 0.58093962: 0.08941368E 0.33073167E 0.48458460£ 0.218360121 0.3835557c 0.218360121 0.58093962: 1.0617134~ 0.807690771 0.85118668: 0.58093962: 0.08941368E 0.275876311 0.15705761 ( 0.275876311 ( 0.08941368E ( 0.53326447t 0.58093962: 0.218360121 0.08941368E 0.275876311 0.08941368( 0.21836012', 0.275876311 0.08941368E 0. 08941368( 0.15705761 0.08941368( 0.67372666: 1.18342010·, 0.15705761 0.85118668( 0.08941368E ( 0.21836012'. ( ( ( ( �KREBSPL LSBNUM UTMX EP-36-8 EP-35-A EP-35-B SS-103-A SS-103-B SS-107-A SS-107-B SS-111-A SS-111-B S$115-A SS-115-B WA•TT•A SS-37-A SS-37-B VA-11-A VA-11-B VA-12-A VA-12-B VA-153-A VA-153-BVA-154-A VA-154-B 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 429442 434484 434201 406384 408211 386984 387083 413184 413242 406384 406348 403884 401384 401418 366284 365940 387284 387580 373284 373100 367984 368100 UTMY PRIMOVE SN1 4452678 L 4454279 L 4454346 L 4460379 S 4482059 S 4469379 S 4469472 S 4466179 L 4466143 L 4460379 L 4460391 L 4529079 F 4450579 S 4450424 S 4409979 A 4409800 S 4380379 S 4380600 S ~874 S 4399720 S 4399379 S 4398800 S SN3 SN2 SN4 SN5 SNS SN7 SNS SN9 SN10 MEAN 1 1 3 2 1 1 1 1 1 1 t 1 1 2 2 1 1 2 1 2 1 1 1 1 2 3 5 1 4 2 2 1 1 1 1 3 3 2 KREB'SN HARE DENSll 0 0 0 0 0 0 0 0 0.1 -1.0486 0 0 0 0 0 0 0.1 -1.0486 0 0 0 0 0.3 -0.66083 0 0 0.3 -0.66083 0 0 1.1 -0.20223 0.7 -0.36176 0.2 -0.80394 1.6 -0.06998 0.9 -0.27306 0.6 -0.41617 0.3 -0.66083 ( ( ( ( 0.08941368{ ( ( ( 0.089413681 I I 0.21836012 I 0.21836012 I 0.62772865 0.43474840: 0.1570576' 0.851186681 0.533264470.3835557; 0.21836012 \0 V, Page 3 of 3 �I KREBSPL LSBNUM UTMX CG-12-A CG-12-8 CG-78-A CG-78-B SS-21-A SS-21-B SS-24-A SS-24-B SS-29-A SS-29-B SS-31-A SS-31-B SS-33-A SS-33-B SS-37-A SS-37-B SS-91-A SS-91-B VA-41-A VA-41-B W-5-A W-5-B W-13-A W-13-B W-53-A W-53-B W-81-A W-81-B W-82-A W-82-B SS-35-A SS-35-B S$-65-A SS-65-B WA-45-A WA-45-B CR-73-A CR-73-B CR-46-A CR-46-B CR-49-A CR-49-B WA-85-A WA-85-B SS-66-A SS-66-B 2 2 2 2 2 2 2 2 2 2 2 2 UTMY 4516720 F 4516636 L 4518850 F 4518851 F 4470720 A 4470747 A 4451320 L 4451400 L 4439720 L 4439703 L 4437620 L 4437718 L 4432620 L 4432676 L 4429320 L 4429389 L 4467220 A 4467128 A 442-0619 L 4425591 L 4533917 L 453.3875 w 4513120 F 451"3062 F 4509020 L 45013942 A 4514220 A 4514433 F 4514120 A 4513955 L 4430920 F 4430965 A 4475620 S 4475833 S 4521319 S 4521281 S 4530820 A 2 2 2 323599 323546 322068 322094 367299 367408 351299 351255 355299 355435 363099 363097 361899 361730 342699 342599 366082 365986 345207 345219 336521 336407 331599 331657 345899 345745 347099 347250 331599 331514 345099 345191 355899 355886 346477 346543 330499 2 2 2 2 2 2 2 2 2 330582 4530639 L 310699 4518920 S 310548 4518948 S 313599 4518520 S 313790 4518470 S 333799 4482873 A 333714 4492646 A 352650 4468880 A 352523 4468800 A 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 SN2 PRIMOVE SN1 SNS SN3 SN9 AfpluY\,J,·-1. C. SN10 MEAN 1 1 1 2 1 5 :.! 1 1 1 1 1 1 2 2 3 41 1 1 13 2 1 .. , 2 1 1 4 1 6 3 2 2 9 1 3 1 2 4 2 1 9 1 11 2 2 9 2 2 1 1 1 9 2 1 1 2 2 4 2 Page 1 of 2 1 3 2 3 KREB'$ N HARE DENS~ 0.1 0 0.2 0.1 0 0 1.7 0 0.4 0 0 0 0.1 0.1 0.5 0 0.9 2.7 0 0 5.4 2.2 0.1 1.1 0 0 1.3 1.4 0 0 0 0 0 0 0.4 0.1 0 0 0.1 0 0 0 0.5 1.2 0.2 0 -1.0486 0 -0.80394 -1.0486 0 0 -0.04858 0 -0.55929 0 0 0 -1.0486 -1.0486 -0.48052 0 -0.27306 0.114712 0 0 0.359367 0.042427 -1.0486 -0.20223 0 0 -0.14326 -0.11711 0 0 0 0 0 0 -0.55929 -1.0486 0 0 -1.0486 0 0 0 -0.48052 -0.17152 -0.80394 0 0.08941368€ C 0.15705769 0.08941368€ C C 0.8941761 OE C 0.275876311 C C C 0.08941368€ 0.08941368€ o.33073167e C 0.533264474 1.302302811 C C 2.287532027 1.102623281 0.089413686 0.627728653 0 0 0.719011504 0. 76364 7967 C C C C C C 0.275876311 0.08941368€ C C 0.089413686 C C C 0.330731678 0.673726665 0.15705769 (\ �l KREBSPLLSBNUM UTMX SS-69-A SS-69-B WA•1·A WA-1·8 WA-17-A WA-17-B CR-50-A CR-50-8 CR-83-A SS-25-A SS-25-B WA-61-A WA-61-8 WA-86-A WA-9-A WA-9-B 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 355658 355565 334299 334285 361099 361201 303378 3Q3492 304699 359099 359206 353099 353099 345895 365099 365120 UTMY PRIMOVESN1 4461691 S 4461595 S 4540420 S 4540385 L 4497920 F 4497971 F 4514532 S 4514404 S 4508720 A 4450020 L 4450122 L 4493520 S 4493520 S 4491620 A 4528020 L 4527890 L SN3 SN2 SN4 SNS SN6 SN7 SNS SN9 SN10 MEAN 1 2 1 1 1 1 1 2 1 2 3 c.;.·.. 1 KREB'$ N HARE DENSIT 0 0.1 0.2 0.3 0 0.1 0 0.1 0 0 0 0 0.2 0.1 0.3 0.3 0 -1.0486 -0.80394 -0.66083 0 -1.0486 0 -1.0486 0 0 0 0 -0.80394 -1.0486 -0.66083 -0.66083 0 0. 089413686 0.15705769 0.218360121 C 0.089413686 C 0.08941368€ C C C C 0.1570576~ 0.08941368E 0.218360121 0.218360121 l,O Page 2 of 2 -..J �• KREBSPL LSBNUM UTMX GS-9-A GS-9-B GS-13-A GS-13-B GS-57-A GS-57-B GS-60-A GS-60-B GS-61-A GS-61-B GS-65-A GS-65-B GS-67-A GS-67-B GS-93-A GS-93-B GS-98-A GS-98-B M-25-A M-25-B M-71-A M-71-B M-73-A M-73-B M-1-A M-1-B M-74-A M-74-B M-77-A M-77-B M-79-A M-79-B VA-19-A VA-19-B ME-29-A ME-29-B ME-33-A ME-33-B ME-85-A ME-85-B ME-26-A ME-26-B ME-81-A ME-81-B ME-21-A ME-21-B 3 .3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 323290 323297 276237 276431 274782 274773 296592 296642 297492 297601 290492 290300 276892 276966 311992 311826 290592 290500 321592 321584 298192 298256 287292 287246 308292 308099 313192 313305 324792 324962 323992 324030 329547 329434 319157 319160 290592 290682 313870 313932 314992 315015 313492 313407 314792 314733 UTMY PRIMOVE SN1 4412469 F 4412272 F 4395669 0 4395598 0 4408689 S 4408444 S 4403498 S 4403428 S 4402598 S 4402735 S 4399198 S 4399250 S 4396587 A 4396513 0 440!i098 S 4405172 S 4397498 S 4397850 S 444-2998 S 444~917 S 445TT98 A 4457786 A 4455598 A 4455648 A 4448798 A 4448695 A 4454298 A 4454069 A 4452690 L 4452684 L 4450598 A 4450468 A 4416879 A 4416904 F 4435523 F 4435606 F 4432198 A 4432190 F 4440307 A 4440419 F 4441498 S 4441563 S 4448198 F 4448093 A 4446098 S 4446242 S SN4 SN3 SN2 SN9 SN10 MEAN Atf'a.~d tx D 1 1 4 4 2 5 3 1 1 8 1 3 1 3 L .. ' 7 1 1 1 1 1 1 2 3 3 10 13 1 3 1 3 1 5 5 1 1 4 5 2 1 1 27 23 1 1 1 2 2 2 1 3 1 2 2 2 5 1 1 1 1 1 1 1 1 1 6 1 1 2 1 1 1 1 2 Page 1 of 2 IO KREB'S N HARE DENSIT'I 00 0.1 -1.0486 0 0 0 0 0 0 0.2 -0.80394 0.5 -0.48052 0.6 -0.41617 0 0 0.9 -0.27306 1.3 -0.14326 0 0 0.4 -0.55929 0 0 0 0 0.9 -0.27306 0 0 0.1 -1.0486 0.5 -0.48052 0.3 -0.66083 1.3 -0.14326 1.3 -0.14326 0 0 0.7 -0.36176 0 0 0 0 0 0 0 0 0 0 4 0.253441 4 0.253441 0 0 0 0 0.6 -0.41617 0.4 -0.55929 0 0 0.1 -1.0486 0.1 -1.0486 0.1 -1.0486 0.5 -0.48052 1.6 -0.06998 0.3 -0.66083 0.2 -0.80394 0.3 -0.66083 0.1 -1.0486 0.1 -1.0486 0.3 -0.66083 0.08941368€ C C C 0.15705769 0.330731678 0.38355578 C 0. 5332644 74 0.719011504 C 0.275876311 C C 0.533264474 C 0.08941368€ 0.33073167t 0.218360121 0.719011504 0.719011504 C 0.434748402 C C C C C 1. 79242672: 1. 79242672: C C 0.3835557f 0.275876311 C 0.08941368€ 0.08941368E 0.08941368E 0.33073167( 0.85118668: 0.218360121 0.15705761 0.218360121 0.08941368E 0.08941368€ 0.218360121 �KREBSPLLSBNUM UTMX GS-53-A GS-53-B GS-69-A Gs-69-B GS-17-A GS-17-B GS-41-A GS-41-B GS-42-A GS-42-B GS-43-A GS-43-B ME-45-A ME-45-B ME-46-A ME-46-B ME-89-A ME-89-B GS-49-A ME-30-A ME-30-B 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 315807 315741 303319 303421 283207 283246 319767 319706 320543 320495 3204n 320499 295792 295928 291692 291663 295600 295532 268390 325792 325748 UTMY PRIMOVESN1 4412384 F 4412364 F 4391172 S 4391426 S 4400690 S 4400732 A 4422156 F 4422201 F 4421864 F 4421868 F 4421531 F 4421391 F 44;.:w98 S 4420845 S 4420398 S 4420254 S 44f6432 A 44~957 A 4415600 A 4433698 F 4433677 L SN3 SN2 SN4 SNS SN6 SN7 SNS SN9 2 2 8 1 2 1 1 0 1 8 2 8 1 SN10 MEAN 1 3 7 5 3 3 1 10 14 4 3 0 1 2 1 3 3 7 1 3 2 5 1 3 3 4 4 1 1 1 3 1 1 5 3 5 2 8 3 6 2 1 4 1 1 -. 1 1 6 KREB'$ N HARE DENSl1" 1.6 -0.06998 0 0 -1.0486 0.1 0.3 -0.66083 0.3 -0.66083 0 0 3.5 0.20631 3.2 0.17468 1.6 -0.06998 3.3 0.185541 2.3 0.058117 2.1 0.026007 0 0 0 0 0 0 0 0 0 0 0 0 0.1 -1.0486 0.1 -1.0486 0.6 -0.41617 0.851186685 0 0.089413686 0.218360121 0.218360121 0 1.60808792 1.495133686 0.851186685 1.532996908 1.143186215 1.061713454 01 0 0 0 0 0 0.089413686 0.089413686 0.38355578 l,C) l,C) Page 2 of 2 �KREBSPL LSBNUM UTMX UTMY PRIMOVE SN1 PA-12-A PA-12-B GU-82-A GU-82-B GU-86-A GU-86-B SA-14-A SA-14-8 SA-64-A SA-64-B CA-25-A CA-25-B CA-27-A CA-27-B CA-30-A CA-30-B CA-32-A CA-32-B CA-38-A CA-38-B CA-46-A CA-46-B 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 308071 4273055 D 308068 • 4273008 D 372071 4301755 L 371956 4301612 L 370471 4289955 L 370421 4290005 L 370371 4230655 P 370487 4230576 P 374471 4235455 L 374271 4235529 L 291683 4359468 A 291929 435a523 A 292637 4358699 A 292438 4358853 A 260735 4356491 A 260659 4356410 A 282106 435;!554 0 282058 4352570 0 293676 4335150 A 293766 4335189 A 253361 4321074 A 253422 4320992 A CA-119-A CA-119-B CA-132-A CA-132-B CA-141-A CA-141-B GU-61-A GU-61-B GU-80-A GU-80-B GU-82-A GU-82-B GU-86-A GU-86-B GU-89-A 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 283084 4357784 S 283109 4357727 S 307856 4337843 D 307950 4337810 D 313455 4326347 D 313440 4326279 D 412171 4308255 P 412146 4308040 P 398571 4312655 P 398581 4312777 P 372071 4301755 L 371956 4301612 L 370471 4289955 L 370421 4290005 L 394371 4280155 L 394552 4280140 L 372671 4274155 L 372600 4274150 L 364671 4269255 D 364685 4269700 D 292071 4292555 F 292034 4292573 F 290071 4291055 A 290001 4290862 A GU-89-B GU-91-A GU-91-B GU-92-A GU-92-B PA-19-A PA-19-B PA-56-A PA-56-B 4 4 SN3 SN2 SN8 3 0 2 4 18 2 1 0 0 2 6 0 1 0 0 0 0 0 2 1 Apf Q.M. d I.)( 0 SN10 MEAN 3 t 2 0 0 0 SN9 0 0 1 5 12 4 0 0 0 0 1 3 2 0 0 0 0 0 0 0 3 < • 1 6 1 1 1 2 5 1 3 1 1 6 1 2 1 2 3 3 1 6 7 2 2 1 1 1 3 4 18 2 1 6 1 2 1 2 1 1 2 1 2 2 4 1 5 1 3 12 4 33 1 2 1 1 Page 1 of 3 4 3 1 2 1 1 3 1 KREB'S N HARE DENSl°G: ,-., 0.38355578 0.38355578 0.627728653 1.495133686 0.978772092 0.434 748402 0.15705769 0.275876311 0 0 0 0 0.218360121 0 0 0 0 0. 089413686 0 0 0 0 0.330731678 0.673726665 0.894176106 0.434748402 0 0.38355578 0.484584609 0.15705769 0.533264474 0.484584609 0.627728653 1.495133686 0.978772092 0.434748402 1. 792426725 0.218360121 C C C C 0.38355578 0.15705769 C 0 0.6 -0.41617 0.6 -0.41617 1.1 -0.20223 3.2 0.17468 1.9 -0.00932 0.7 -0.36176 0.2 -0.80394 0.4 -0.55929 0 0 0 0 0 0 0 0 0.3 -0.66083 0 0 0 0 0 0 0 0 0.1 ·1.0486 0 0 0 0 0 0 0 0 0.5 -0.48052 1.2 -0.17152 1.7 -0.04858 0.7 -0.36176 0 0 0.6 -0.41617 0.8 -0.31463 0.2 -0.80394 0.9 -0.27306 0.8 -0.31463 1.1 -0.20223 3.2 0.17468 1.9 -0.00932 0.7 -0.36176 4 0.253441 0.3 -0.66083 0 0 0 0 0 0 0 0 0.6 -0.41617 0.2 -0.80394 0 0 0 0 �I KREBSPLLSBNUM UTMX SA-65-A SA-65-B SA-69-A SA-69-8 SA-67-A SA-67-8 SA-100-A SA-100-B SA-102-A SA-102-B SA-104-A SA-104-B SA-107-A SA-107-B SA-108-A SA-108-B SA-109-A SA-109-B SA-110-A SA-110-B VA-1-A VA-1-B VA-2-A VA-2-8 CA-33-A CA-33-B LE-3-A LE-3-8 CA-133-A CA-133-B LE-24-A LE-24-B LE-116-A LE-116-8 VA+A-2 VA-111-A VA-113-A CA-17-A- CA-17-B CA-123-A CA-123-B GU-52-A GU-52-B GIJ.157•A GIJ.157•8 GIJ.15a.A 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 ·4 4 4 4 4 4 4 4 4 4 4 4 4 4 UTMY PRIMOVE SN1 373071 373233 390271 390070 368013 367745 370371 370242 374271 374148 362171 362268 368771 368724 365571 365543 351871 351662 351530 351524 337267 337329 351577 351544 302269 302330 436930 436945 245402 245436 350683 350801 360122 360057 337271 356671 357371 296459 4235355 A 4235373 A 4230055 D 4229851 D 4231272 D 4231280 A 4246555 P 4246541 L 4245655 L 4245672 L 4241955 L 4241864 L 4236155 L 42~_6361 L 4234755 D 4234940 S 4231455 A 4231491 D 4229214 D 4229297 D 4380741 L 4380577 L 4374462 L 4374495 L 4351331 4351244 A 3397400 S 3397800 S 4335106 A 4335245 F 4370138 L 4369892 A 4371050 S 4370936 S 4380755 L 4379855 L 4378955 S 4373781 S 296390 315656 315720 327571 327548 348771 348674 365371 4373800 S 4351061 L 4350930 F 4296255 A 4296315 A 4303555 S 4303630 S 4309155 L SN2 SN4 SN3 SN5 SN6 SN7 SN9 SN8 SN10 MEAN 1 1 2 1 0 7 2 4 1 2 1 1 1 1 1 2 4 1 C, , 4 1 13 2 3 2 1 2 1 1 1 2 5 2 11 1 1 1 5 1 1 0 1 1 5 1 2 4 0 1 2 6 1 1 1 3 1 3 4 1 3 1 1 1 Page2of3 3 KREB'S N HARE DENSIT'° 0 0 0.2 -0.80394 1.6 -0.06998 0.3 -0.66083 0 0 0 0 0 0 0 0 0.1 -1.0486 0.1 -1.0486 0.1 -1.0486 0.2 -0.80394 0.3 -0.66083 0.4 -0.55929 0.4 -0.55929 0 0 0.3 -0.66083 0.6 -0.41617 2.4 0.073139 1.4 -0.11711 0.1 -1.0486 0.8 -0.31463 0 0 0.1 -1.0486 0 0 0 0 0 0 0 0 1.1 -0.20223 0 0 0 0 0 0 ·O 0 0.5 -0.48052 1.6 -0.06998 0.1 -1.0486 0 0 0.4 -0.55929 0.1 -1.0486 0.7 -0.36176 0.2 -0.80394 0 0 0 0 0 0 0 0 0 0 ( 0.1570576~ 0.85118668~ 0.218360121 ( ( ( ( 0.08941368( 0.08941368( 0.08941368( 0.1570576~ 0.21836012', 0.27587631, 0.27587631' ( 0.21836012' 0.38355571 1.18342010' 0.76364796; 0.08941368( 0.48458460( ( 0.08941368( ( ( ( ( 0.62772865 I I I I 0.33073167: 0.85118668: 0.089413681 I 0.27587631 0.089413681 0.43474840: 0.1570576' I I I I .... -- �- I KREBSPLLSBNUM UTMX GU-153-8 LE-9-A LE-9-8 LE-73-A LE-73-B LE•74•A LE-74-B LE-78-A LE-78-B LE-128-A LE-128-B LE-129-A LE-129-B LE-144-A LE•144-B PA-18-A PA-18-B PA•22·A PA-22-B PA-20-A PA-20-B PA-21·A PA-21·8 PA-186-A PA-186-B PA·187•A PA·187•B SA-106-A SA-106-B LE-29-A LE•29-B LE-120-A LE-120-B C0-148-B LE-5-A LE-5-B CR-83-8 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 365558 412871 412756 377871 377906 370877 370998 407171 407263 373571 373292 368871 369228 371171 371104 320871 320822 288076 288225 293771 293804 294371 294368 290271 290372 288471 288585 360209 360219 346471 346471 350771 350771 761178 380700 380520 304199 UTMY SN2 PRIMOVESN1 4309087 L 4317355 P 4317207 P 4334155 L 4334211 L 4333181 S 4333200 S 4318255 S 4318427 S 4347255 F 4346979 F 434.7155 F 4347084 F 4324855 L 4324853 L 4304655 S 4304619 S 4266178 S 4266146 A 4275055 F 4275216 F 4270255 S 4270108 S 4271155 S 4271208 S 4270055 S 4270239 S 4237602 S 4237494 S 4357055 L 4357055 L 4354155 L 4354155 L 4148888 S 4361960 S 4362240 S 4509001 A SN4 SN3 SNS SN6 SN7 SNS SN9 SN10 MEAN 1 1 1 1 1 2 1 1 1 3 2 1 1 L,,·• 1 1 1 1 6 1 1 2 2 2 1 1 1 1 1 1 1 1 1 3 2 1 1 2 4 1 1 1 1 1 2 1 1 1 1 8 5 1 1 Page 3 of 3 3 1 1 7 KREB'S N HARE DENSll:0 0.1 0 0 0.1 0.2 0.3 0.2 0.1 0.3 0.2 0 0 0.1 0.5 0.7 0.1 0 0.2 0.7 0.3 0.4 0.5 0.2 0.4 0.5 0.2 0.3 0.2 0 0 0 0 0 2.3 0.2 0.2 0 -1.0486 0 0 -1.0486 -0.80394 -0.66083 -0.80394 -1.0486 -0.66083 ·0.80394 0 0 ·1.0486 -0.48052 -0.36176 -1.0486 0 -0.80394 -0.36176 -0.66083 -0.55929 -0.48052 -0.80394 -0.55929 -0.48052 -0.80394 -0.66083 -0.80394 0 0 0 0 0 0.058117 -0.80394 -0.80394 0 N 0. 08941 368( ( ( 0.08941368( 0.1570576! 0.21836012~ 0.1570576! 0.08941368( 0.21836012' 0.1570576! ( ( 0.08941368( 0.330731671 0.43474840; 0.08941368( ( 0.1570576! 0.43474840; 0.21836012" 0.27587631" 0.330731671 0.1570576! 0.27587631 • 0.330731671 0.1570576! 0.21836012" 0.1570576! ( ( ( ( ( 1.14318621 ! 0.1570576! 0.1570576! ( �UTMY AN-152-A AN-152-B AN-156-A AN-156-B AN-157-A AN-157-B AN-158-A AN-158-B AN-160-A AN-160-B AN-168-B AN-168-A C0-14-A C0-148 C0-187-A C0-187-B DE-8-A DE-8-8 DE-13-A DE-13-B DE-49-A DE-49-B DE-54-A DE-54-B DE-89-B DE-89-A DE-146-A DE-146-B DU-30-A DU-30-B DU-192-A DU-192-B M0-3-A M0-3-B M0-28-A M0-28-8 M0-29-A M0-29-B M0-64-A M0-64-8 M0-66-A M0-66-B DU-186-A DU-186-8 DU-190-A DU-190-B 4145971 S 4143036 S 4142726 D 4142692 D 41'4'0671 S 4140586 S 4139791 S 4139726 S 4137071 S 4137124 S 4105024 S 4104968 S 4146928A 4146893 A 4145794 A 4145810 A 4189271 D 4189201 D 4151461 S 4151379 S 4205671 S 4205646 S 4158215 P 4158145 P 4203561 B 4203671 B 4152177 S 4152211 S 4135828 0 4135981 0 4134560 P 4134607 P. 4234397 A 4234334 A 4221691 0 4221649 0 4220445 A 4220443 A 4231212 D 4231125 D 4228274 S 4228172 S 4147354 0 4147273 P 4138467 D 4138570 D 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 370326 370357 367132 367087 369726 369772 366889 366884 371126 371201 375941 375935 747483 747553 748557 748500 364326 364304 370832 370796 378026 377952 368766 368729 364807 364826 335236 334987 319412 319396 251960 251911 277574 277510 249194 249047 258872 258968 277527 277463 277150 277120 254345 254522 265782 265683 'ffi SN2 PRIMOVE SN1 KREBSPL LSBNUM UTMX 1 SN3 1 3 1 4 4 2 1 0 1 0 0 0 0 1 2 SNS 3 2 2 6 5 0 0 3 0 1 0 A,o p~d ,·x F 1 5 2 0 0 2 3 0 3 1 0 1 0 1 0 0 1 2 0 0 0 4 0 0 0 1 1 2 5 l 1 0 0 0 11 5 2 0 0 1 3 11 10 2 2 0 0 4 . 0 1 2 1 1 1 0 0 1 0 0 1 1 0 4 3 6 23 SN9 0 0 19 0 1 1 0 0 2 2 0 0 2 1 SN10 MEAN 4 7 5 2 7 5 14 2 12 0 0 1 1 1 2 13 7 0 0 0 0 3 0 6 1 0 0 0 2 0 1 0 Page 1 of 6 KREB'S N HARE DENSITt 0.1 -1.0486 0.1 -1.0486 2.5 0.087548 5.1 0.339192 1.5 -0.09275 0.7 -0.36176 3.5 0.20631 2.5 0.087548 0.4 -0.55929 0.7 -0.36176 2.5 0.087548 3 0.1519 0 0 0 0 0 0 0 0 3.5 0.20631 1.3 -0.14326 0.2 -0.80394 1.3 -0.14326 0.4 -0.55929 0.2 -0.80394 0.4 -0.55929 0.7 -0.36176 0.1 -1.0486 0.1 -1.0486 0.2 -0.80394 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.4 -0.55929 0.8 -0.31463 0 0 0 0 0 0 0 0 0.08941368( 0.08941368( 1.2233411 SL 2.18369704! 0.80769077'. 0.43474840: 1.6080879: 1.22334116' 0.27587631' 0.43474840: 1.22334116' 1.41873187< ( ( ( ( 1.6080879: 0.71901150• 0.1570576! 0.71901150, 0.27587631 0.1570576! 0.27587631 0.43474840: 0.089413681 0.089413681 0.1570576' I ' 0.27587631 0.48458460 0 �I KREBSPLLSBNUM UTMX DU-193-A DU-193-B M0--2-B M0--2-A M0--60-A M()..60-B M0--61-A M0--61-B M()..65-A M0--65-B M0--68--A M0--68--B M0--79-A M0--79-B M0--179-A M0--179-B DE-144-A DE-144-B AN-167-A AN-167-B DU-33-A DU-33-B M0--4-B M0--4-A M0--26-A M0--26-B M0--72-A M0--72-B M0--77-A M0--77-B M()..80-B M0--80-A SA-1-A SA-1-B SA-39-A SA-39-B SA-41-A SA-41-B 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 SA-69-A SA-69-B SA-76-A SA-76-B SA-78--A SA-78--B S1-96-A 5 Sl-96-B 5 5 5 5 5 5 5 UTMY SN2 PRIMOVESN1 SN4 SN3 SNS SN6 SN7 SN8 SN9 SN10 MEAN 318011 4134176 P 318116 4134283 P 268285 42;¼~607 A 268326 4238671 A 284257 4241267 A 284212 4241345 A 280720 280683 286117 280095 281510 281561 242213 4234378 S 4234438 S 4229070 S 4229119 S 4225540 S 4225578 S 4211663 S 242282 4211746 S 241604 241618 373926 373904 379909 379825 268426 268396 271352 271426 265626 265631 276226 276156 271726 271755 251688 251626 '337326 337333 332426 332433 339126 339218 4222825 A 4222749 A 4152871 S 4152938 S 4105045 S 4105078 S 4136471 P 4136238 P 4232051 A 4232071 A 4235571 0 4235639 0 4222071 S 4222085 S 4215171 S 4215157 S 4211206 S 4211171 S 4244871 F 4244929 A 4230371 L 4230234 L 4235071 D 4234944 D 331926 332041 341126 341115 327073 327039 267926 267859 4224571 L 4224576 L 4217171 S 4217057 S 4213018 F 4213095 F 4196571 S 4196596 S 3 1 1 0 4 3 4 6 1 3 1 2 0 6 2 1 4 6 7 2 8 2 2 0 1 1 3 1 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 2 3 4 2 1 1 1 9 0 0 1 1 1 2 0 1 1 2 0 1 1 1 3 0 0 9 0 8 11 2 0 1 1 7 2 14 8 4 16 0 1 0 0 0 0 6 5 1 0 0 0 0 0 1 3 1 0 5 6 0 2 6 3 5 L > 4 7 1 13 23 12 1 3 2 6 2 4 2 8 0 5 1 7 0 3 1 1 0 0 0 2 0 0 0 0 2 0 3 7 7 0 5 9 0 0 1 1 2 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 3 2 1 2 1 1 1 2 3 3 13 1 10 Page 2 of6 7 2 2 2 6 1 1 1 5 5 2 2 1 2 3 2 2 3 4 6 1 KREB'S N HARE DENSIT' 0 0 0 0 0 0 0 0 0 0 0 0 1.2 -0.17152 2.1 0.026007 0.4 -0.55929 0.4 -0.55929 0.9 -0.27306 1.1 -0.20223 2.6 0.101391 2.2 0.042427 0 0 0 0 2.9 0.139934 5.3 0.35277 0.7 -0.36176 0.9 -0.27306 0 0 0 0 0 0 0 0 0 0 0 0 3.5 0.20631 2.2 0.042427 2 0.008786 3.2 0.17468 3.3 0.185541 0.9 -0.27306 1.2 -0.17152 0 0 0 0 0 0 0 0 0.3 -0.66083 0.2 -0.80394 1.8 -0.0284 1.1 -0.20223 1.4 -0.11711 1.4 -0.11711 1.9 -0.00932 1.9 -0.00932 3.1 0.163474 ( ( ( ( ( ( 0.67372666'. 1.06171345L 0.275876311 0.275876311 0.53326447.: o.62772865c 1.26296421; 1.10262328' ( ( 1.38017557( 2.25304338( 0.43474840: 0.53326447 1 ( ( ( ( ( ( 1.6080879: 1.10262328 • 1.02043701 I 1.49513368{ 1.53299690! 0.53326447< 0.67372666! ( ( ( I 0.21836012 0.1570576! 0.93669425( 0.62772865: 0. 76364 796' 0.76364796', 0.97877209: 0.97877209: 1.4570481 e· �KREBSPLLSBNUM UTMX SI-102-A SI-102-B SI-107-A St-107-B SI-120-A S1-120-B DE-111-A DE-111-B DE-112-A DE-112-B DE-138-A DE-138-B SI-50-A S1-50-B SI-86-A SI-86-B SI·110-A S1·110-B SI-113-A SI-113-B SI-122-A Sl-122-B SI-126-A SI-126-B DC-140-A DC-140-B DC-141-A DC-141-B SI·12-A S1-12-B SI-185-A . SI-185-B DU-147-A DU-147-B DU-145-A DU-145-B DU-151-A DU-151-B DU-154-A DU-154-B DU-189-A DU-189-B SI-123-A SI-123-B OE-132-A DE-132-B 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 UTMY 260726 41aa211 o 260809 4193273 D 274226 4188771 S 274147 4188681 S 317826 4171771 S 317901 4171806 S 344226 4185671 A 344198 4185621 A 350326 4183271 S 350264 4183331 S 351826 4157371 S 351853 4157311 S 298726 4201771 S 298652 4201741 S 308226 4206871 S 308294 4206850 S 293526 4186371 A 293451 4186413 A 294626 4182671 S 294582 4182594 S 316126 4171271 S 316056 4171236 S 319126 4168071 S 319118 4168086 S 761926 4156371 F 761750 4156280 F 761426 4156271 F 761350 4156350 F 247730 4156170 A 247800 4156200 A 253126 4155871 P 253110 • 4155730 D 261419 4150956 F 261451 4150964 S 245026 4152171 D 244980 4152260 D 248713 4146127 D 248830 4146020 D 281790 4144654 A 281712 4144508 A 257530 4140571 D 257150 4140565 D 254400 4170897 A 254369 4170937 D 334612 4165099 S 334624 4165200 S SN4 SN3 SN2 PRIMOVESN1 SN5 SNS SN7 SNS SN9 SN10 MEAN 4 2 7 7 4 3 1 2 2 1 1 2 2 1 8 7 1 8 4 5 5 10 1 3 6 4 6 3 5 1 8 5 16 4 6 18 1 1 2 2 3 3 5 1 3 2 14 3 3 9 5 2 8 1 4 5 7 2 5 1 8 1 6 3 1 2 5 4 8 5 ,. 2 1 2 10 5 9 3 1 3 12 7 26 7 11 3 4 4 7 3 2 5 1 4 9 14 6 7 6 19 1 7 4 8 2 7 11 12 2 4 6 3 2 1 1 4 3 1 1 19 5 3 1 1 3 2 1 3 1 2 3 3 1 11 1 1 1 2 1 1 3 1 1 1 1 3 4 I 2 8 1 1 Page 3 of 6 2 KREB'S N HARE DENSIT'i 0.4 -0.55929 0.7 -0.36176 0.7 -0.36176 3.3 0.185541 0.9 -0.27306 1.6 -0.06998 1.4 -0.11711 2.1 0.026007 4.3 0.278968 3.2 0.17468 1.6 -0.06998 2.4 0.073139 3.6 0.216253 7.3 0.465777 2.8 0.127548 4.5 0.295014 0 0 0 0 1.4 -0.11711 2.4 0.073139 2 0.008786 3.8 0.235337 1.9 -0.00932 3.3 0.185541 0 0 0 0 0 0 0 0 3.8 0.235337 1.7 -0.04858 0.3 -0.66083 0.4 -0.55929 1.8 -0.0284 0.5 -0.48052 0 0 0 0 0 0 0 0 0.1 -1.0486 0.3 -0.66083 0.9 -0.27306 0.4 -0.55929 0 0 0.2 -0.80394 0.1 -1.0486 1.4 -0.11711 0.275876311 0.434748402 0.43474840, 1.53299690f 0.53326447t 0.85118668: 0.76364796i 1.06171345': 1.90093784i 1.49513368€ 0.85118668: 1.183420101 1.645330m 2.92264992' 1.34136943: 1.97248834\ ( ( 0.76364796; 1.18342010' 1.02043701\ 1.71924109: 0.97877209: 1.532996901 I I I I 1.71924109 0.894176101 0.21836012 0.27587631 0.93669425 1 0.33073167, 0.08941368 0.21836012 0.53326447 0.27587631 0.1570576 0.08941368 0.7636479fr-, �KREBSPLLSBNUM UTMX SI-121-A SI-121-B DC-136-A DC-136-B AN-163-A AN-163-B AN-198-A AN-198-B AN-199-A AN-199-B AN-200-A AN-200-8 AN-208-A AN-208-B AN-210-A AN-210-8 DU-149-A DU-149-B AN-18-A AN-18-B AN-21-A AN-21-B AN-23-A AN-23-8 AN-20-A AN-20-8 AN-31-A AN-31-8 AN-37-A AN-37-B AN-38-A AN-38-B AN-56-A AN-56-B AN-153-A AN-153-B C0-15-A C0-15-B C0-148-A DC-118-A DC-118-B DC-119-A DC-119-B DC-100-A DC-100-8 OC-103-A 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 UTMY SN2 PRIMOVESN1 302378 302370 763726 763840 339226 339400 329626 329550 331126 331200 331426 331550 339626 339610 336626 336381 315226 315200 374826 374869 379849 379852 363426 363412 348526 348459 346626 346544 389326 389319 358726 368634 372726 372684 337526 337416 755508 755418 4171441 S 4171435 S 4161571 S 4161650 S 4127771 0 4127800 F 4128671 P 4128600 P 4126371 P 4126400 P 4125971 P 4126000 P 4107771 0 4107779 0 4105271 P 4105136 P 4147571 0 4147900 0 4114271 A 4114352 A 4108329 A 4108424 A 4096771 A 4096848 A 4112171 A 4112107 A 4102771 0 4102762 0 4100371 P 4100270 P 4096271 S 4096289 S 4112271 0 4112332 0 4145471 F 4145472 F 4143632 A 4143617 A 761083 763232 763168 763333 763262 746543 746470 751667 4148897 S 4173781 S 417;~814 S 4171687 S 4171605 S 4192851 S 41si824 s SN3 '. SNS SN4 2 1 2 SN6 SN? ,:• 1 3 1 2 2 1 1 3 5 6 3 7 11 3 5 1 2 MEAN 6 8 2 SN10 1 8 (. 8 SN9 4 1 3 2 2 SN8 3 5 6 3 2 4191077 S .. Page 4 of 6 2 1 4 1 2 KREB'S N HARE DENSI 1 -0.23587 0.2 -0.80394 1.1 -0.20223 1 -0.23587 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.4 -0.55929 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1 -0.20223 0 0 0 0 0.6 -0.41617 2.1 0.026007 0 0 0 0 2.4 0.073139 0 0 0 0 0.5 -0.48052 0.6 -0.41617 1 -0.23587 1.6 -0.06998 0 0 0.580939625 0.15705769 0.627728653 0.580939625 0 0 0 0 0 0 0 0 0 0 0 0 0 0.275876311 0 0 0 0 0 0 0 0 0 0 0 0 0 0.627728653 0 0 0.38355578 1.061713454 0 0 1.183420101 0 0 0.330731678 0.38355578 0.580939625 0.85118668" �KREBSPLLSBNUM UTMX DC-103-B OC-124-A DC-124-B DC-128-A DC-128-8 DE-142-A DE-142-8 DN-98-A DN-98-B DN-99-A ON-99-8 DU-35-A DU-35-B DU-194-A DU-194·8 DU-195-A DU-195-B DU-197-A DU-197-8 DU-201-A DU-201-B DU-204-A DU-204-B OC-9-A DC-9-B DC-97-A OC-97-B DC-101-A OC-101-B DC-104-A DC-104-B DC·108-A OC-108-B Sl-51-A S1-51-B Sl-87-A S1-87-B S1·90-B S1-90-A S1-106-A SI-106-B SI-109-A S1-109-B SI·114-A SI-114-B SI-11-A 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 UTMY SN2 PRIMOVESN1 751699 760062 760116 756231 756142 341726 341679 358626 358674 359126 359063 299926 299861 274126 274131 265726 265795 304326 304386 298826 298965 303126 303137 211626 211613 233026 232894 229826 229820 233926 233885 232026 232125 293005 293126 293826 293746 271226 271226 4191024 S 4169573 D 4169674 D 4166799 P 4166761 P 4154871 S 4154753 S 4195171 S 4195215 S 4194671 S 4194666 S 4130371 P 4130316 P 4132771 P 4132686 P 4132271 P 4132317 P 4130571 P 4130495 P 4124971 D 4125051 D 4119771 P 4119857 P 4181971 A 4181996 A 4196471 S 4196480 S 4193471 S 4193380 S 4190971 S 4190960 S 4188571 S 4188570 S 4199502 S 4199371 S 4206271 S 4206331 S 4203471 S 4203471 S 238966 238966 243126 243560 259926 260012 288426 4189716 S 4189971 S 4187271 S 4187052 S 4181871 S 4181977 S 4157071 A 9 1 5 1 6 1 1 3 ' SN4 SN3 5 4 SN5 3 1 7 9 SNS 2 5 5 SN? 1 3 8 SN8 SN9 4 8 1 8 SN10 MEAN 5 1 2 9 6 7 2 C 0 0 7 2 3 0 6 9 0 5 2 1 3 3 1 1 8 1 3 3 2 5 5 2 24 10 3 5 5 3 1 0 6 7 0 5 5 3 3 6 8 15 1 8 7 2 2 3 5 1 7 1 3 9 8 5 9 2 7 3 7 4 1 4 9 12 2 5 2 1 1 1 31 8 7 1 3 3 4 1 2 2 3 4 2 6 I 5 1 2 1 4 Page 5 of 6 2 4 3 6 4 7 1 2 KREB'S N HARE DENSIT'l 0 0 0 0 0 0 0 0 0 0 0 0 2.3 0.058117 1.9 -0.00932 2.8 0.127548 3.5 0.20631 2.8 0.127548 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0.008786 2.1 0.026007 3.4 0.196078 1.6 -0.06998 3.1 0.163474 4.7 0.310363 2.2 0.042427 1.7 -0.04858 2.2 0.042427 1.9 ·0.00932 2.4 0.073139 2.1 0.026007 2.2 0.042427 1.6 -0.06998 2.5 0.087548 3.3 0.185541 0 0 0 0 2.4 0.073139 1.8 -0.0284 0 0 0 0 0 0 0 0 1.143186215 0.978772092 1.341369433 1.60808792 1.341369433 0 0 C C C C C C C C C C C C 1.0204370H 1.06171345L 1.57064583; 0.85118668'. 1.45704818\ 2.04344557! 1.10262328 • 0.89417610{ 1.10262328 • 0.97877209; 1.1834201 o· 1.06171345' 1. 10262328 • 0.85118668! 1.22334116, 1.53299690! ( ( 1.1834201 o· 0.93669425{ .E -.....i �l KREBSPLLSBNUM UTMX Sl-11-B Sl-125-A Sl-125-B Sl-129-A St-129-B Sl-133-A Sl-133-B Sl-134-A Sl-134-B 5 5 5 5 5 5 5 5 5 288420 276100 276250 264326 264400 287326 287150 277726 277550 UTMY PRIMOVESN1 4156972 A 4167900 A 4167850 A 4166571 D 4166500 D 4164071 S 4164100 S 4162971 D 4163000 D SN2 SNS SN4 SN3 SN6 SN7 SN8 2 7 SN9 SN10 MEAN 5 7 3 3 1 1 9 2 2 9 Page 6 of 6 1 3 KREB'S N HARE DENSITY~ 0.2 1.2 0.7 0.6 1.1 0 0.5 0.2 1 -0.80394 -0.17152 -0.36176 -0.41617 -0.20223 0 -0.48052 -0.80394 -0.23587 0.15705769 0.673726665 0.434748402 0.38355578 0.627728653 0 0.330731678 0.15705769 0.580939625 �109 Appendix G Genus-species Abbr. Name Scientific Common AMAL Amelanchier alnifolia Serviceberry ARCO Arnica cordifolia Heart-leaved Arnica ARUV Arctostaphylos uvaursi Kinnikinnik CA spp Carex spp Sedge JU spp Juniperus spp Juniper Quercus gambelii Gambel's Oak QUGA " SHCA Shepherdia canadensis Buffaloberry SYAL Symphoricarpos albus Snowberry SYOC symphoricarpos occidentalis Snowberry VA spp Vaccinium spp Blueberry VASC Vaccinium scoparium Broom Huckleberry �110 Appendix I! SUMMARY BY FOREST ---- r· J_ - - ___j_ J --- --- j ---- ___ SAMPLE SIZE HARES PER HA j ------- - -- ------ -- --- ------ -------- -- - - - - -- --- 32 03142 ARAPAHO NF------- ------ -----0.5089 ____1_l BUFFALO PEAKS WILDERNESS 21 0.1046 GRAND MESA NF --------------------~ 63 0.3259 GUNNISON NF --7 0.8712 LAGARITA WILDERNESS AREA -------89 0.6679 RIOGRANDE NF 31 0.2744 ROCKY MOUNTAIN NATIONAL PARK 22 0.2158 ROOSEVELT NF 83 0.2114 ROUTT NF 16 0.2815 SAN !SABEL NF 92 0.3546 SANJUAN NF 45 0.7032 UNCOMPAHGRE NF 4 0.1352 WEST ELK WILDERNESS 94 0.2632 WHITE RIVER NF I SAMPLE SIZE HARES PER HA 95% Cl SUMMARY BY AR~I --- --------- ---· ---- ---- - ---- ------ ---- ------- - - - - -- - I " 114 62 67 129 239 0.29 0.27 0.41 0.28 0.56 0.16 0.14 0.22 0.16 0.35 AREA 1 AREA2 AREA3 AREA4 AREAS I SUMMARY BY PRIMARY OVERSTORY 0.2200 0.1900 0.3000 0.2100 0.4400 SAMPLE SIZE HARES PER HA I I 105 2 48 64 108 16 41 220 1 3 ASPEN BRISTLECONE PINE DOUGLAS FIR SUBALPINE FIR LODGEPOLE PINE GAMBLE'S OAK PONDEROSA PINE ENGLEMANN SPRUCE WHITE PINE UMBER PINE 0.1558 0.0894 0.3351 0.3301 0.2981 0.0056 0.0737 0.5163 1.1026 0.7466 I SUMMARY BY COUNTY -- ·1· I _ _ _ j _ __ - ARCHULETA ------1 BOULDER CHAFFEE ... CLEAR CREEK CONEJOS DELTA DOLORES EAGLE GARFIELD GILPIN GRAND GUNNISON HINSDALE JACKSON LA PLATA LAKE --- -- --- LARIMER MESA MINERAL MOFFAT MONTEZUMA OURAY I PARK PITKIN RIO GRANDE RIO BLANCO ROUTT SAGUACHE SANJUAN SANMIGUEL SARATOGA SUMMIT ---------·- ---------- . - - ---- ---------- - - - - - - - - - - -- - - - - - - - -- -------·- -- ----- - - ---- -------- - SAMPLE SIZE HARES PER HA - ----- - - - - - - - - - ----- - --------- - ~ - - --- 33 ~ - --- ----- - -------- ---- ----- i--------- -I------- - - - 6 -~ ------- 17 2 18 35 36 2 31 59 18 8 28 - 8 36 8 18 6 14 16 8 16 14 21 52 45 24 2 2 14 ----- 0.0438 0.1659 0.6117 0.3635 0.3642 0 0.6749 0.2941 0.3096 0.3010 0.1955 0.3163 0.9531 0.0769 0.3114 0.1931 0.2840 0.2152 0.7937 0.0874 0.0000 0.2864 0.4260 0.1393 0.9766 0.3316 0.1942 0.4143 0.5622 1.1828 0.1877 0.0888 �111 Review of the habitat assessment study of snowshoe hares by the Colorado Division of Wildlife • Shay Howlin Lyman McDonald West, Inc. 2003 Central Avenue Cheyenne, Wyoming 8200 I (307) 634-1756 February 14, 2000 In our examination of the issues surrounding the snowshoe hare pellet collection in 1998 we have identified 4 major concerns in the use of this data. Here we attempt to clarify these concerns and offer our analysis of their severity as they relate to the use of the pellet data as an index to sgowshoe hare abundance. CONCERNS OF REVIEWERS • Failure to validate or accurately duplicate Krebs' protocol This criticism is based on the premise that the division of wildlife (DOW) snowshoe bare pellet study intended to use the linear models developed by Krebs et al. (1996) to estimate snowshoe bare density based on the number of snowshoe hare pellets. Krebs' model for estimating the density of bares was developed in Canada with different snowshoe bare ecology and habitat. And the field protocol used by Krebs to develop the density estimation formula specified the removal of pellets from plots at a set time period before counting pellets. The DOW study protocol differed from Krebs' protocol in that they did not clear the study plots of old pellets berore conducting pellet surveys. The biologists conducting the surveys for the DOW were trained to age pellets and could identify last year versus current year pellets. In our view, the use of current year pellets can provide an index to abundance of snowshoe hares. The analysis of the DOW data does not need to validate or use Krebs' formula if only an index to abundance is attempted. • Failure to follow DOW survey protocol The DOW generated a random sample of survey points in each of the five study areas. The number of random points generated for the survey was roughly proportional to the size of the area. Recognizing the logistical problems associated with visiting all the random points, the DOW field crews reduced the number ofplots·to visit by selecting every fourth point from the original random sample (call this subset the reduced sample). DOW and BLM biologists surveyed additional points from the original random sample when conveniem. The resuiting dataset contains points in the reduced sample visited by the field crews, and points in the original sample visited by biologists opportunistically on the way to other points or other work. Since the resulting sample contains a �112 disproportionate number of points in block five, reviewers of the study have noted that the blocks with higher sampling intensity could result in increased chances of finding pockets of modest hare abundance. The fact that neither every point in the original random sample nor every point in the reduced sample was not surveyed resulted in a nonrandom sample of actual data. Biases associated with the selection of the plots sampled (i.e. closest to roads), makes the use of the data for an unbiased index to snowshoe hare abundance questionable. The tables below show the percent of original plots and the percent of the subset of plots that were surveyed in each block and were entered into the dataset called newform.xls (obtained from G. Byrne on December 28, 1999). Percentage of Krebs' plots sampled from original random sample. Block Number l 2 3 4 5 Number of Original Percent of plots sample size original visited sample 55 200 27.5 32 100 32.0 34 100 34.0 64 200 32.0 121 200 60.5 Percentage of Krebs' plots sampled from the reduced sample(every fourth plot from the ori inal sam le . Block Number l 2 3 4 5 Number of Reduced Percent of plots sample size reduced visited le 18 so 36.0 20 25 80.0 22 25 88.0 20 50 40.0 31 so 62.0 • Time frame of surveys The DOW conducted the snowshoe hare pellet surveys throughout the summer of 1998. One reviewer of the study contends that plots that were sampled later in the season had the potential to have more pellets, because there was more time for pellets to be dropped onto the plots and there are more hares due to the addition of hares to the population through parturition. From Figure I, it appears that each block had an even distribution of plots visited throughout the study period. If there was a time affect influencing the number of pellets on a plot, it appears it would have approximately the same influence in every block. • • Definition of suitable habitat The DOW protocol details the placement of the Krebs' plots once the randomly selected point is located. Plots were moved from the starting point to the nearest suitable �113 habitat (forest, willow, or mountain shrub habitat). A random number table was used to locate directions and distances to move the point to suitable habitat. If the first randomly selected direction or distance did not locate suitable habitat~ another direction and distance was chosen.: ' This protocol effectively reduces the area surveyed during the study to the "suitable habitat" in the study area. Field personnel made subjective determinations of suitable versus nonsuitable habitat, because a rigorous definition of suitable habitat is not easy to follow in the field. The actual size of the area that had a chance of being sampled is unknown and difficult to define. The size of this area could potentially be determined by the delineation of suitable habitat on the GIS vegetation coverage if definitions were consistent throughout the study. Figure I. Date of Division of Wildlife sampling of plots by block. - .. ..,..._ -······"· ---··- - - - - - ... - -· ... .. .. - ...... - - - - .. - ... -- • ~ 0 0 m 3 • • • • • •• --- - .. - • • 1 -..,_,-,-"T""""iy.::,MT""'T--,-T•-r-..--?-•-.-..-.-........,--,--..-,!!!•~-~H.;:,-~,-•::;,:-.y-r"•-.-'•--;..:;MT"""T"M~Nr'•'r••=-;:•=•MrrN'-re=,--r--,- Date CONCLUSIONS The failure of the DOW snowshoe hare study to validate or follow Krebs' protocol for the estimation of snowshoe hare density prohibits the use of the data in Krebs' estimation formulas. We do not feel this criticism discounts the use of the DOW data for an index of snowshoe hare abundance in the study area. The criticisms surrounding the time component of the study also do not seem to pose a critical problem when producing estimates of hare abundance by block. And if an estimate of suitable habitat can be made using the GIS coverage of the vegetation, the index of abundance can incorporate the amount of area surveyed. �114 Our review of the data revealed problems with the quality of the data. There were twelve missing dates in the dataset, and two dates that were 9 and 49 years before the bulk of the other observations. There were other simple errors in the plot identification variable that indicates the dataset was not verified. We recommend the data be checked for quality control-quality assurance before any analyses are conducted. If a truly random sample of Krebs' plots could be identified, we would recommend an analysis of the pellet data using only these plots. But neither all the points in the entire original sample were visited, nor were all the plots identified in the DOW biologists subset sample visited. We feel it is impossible to identify a sample of plots that were selected and visited that do not contain biases associated with the time and logistical constraints oflocating and sampling the pre-selected Krebs' plots. Therefore, we do not think this data is capable of producing an index of snowshoe hare abundance that is unbiased. The fieldwork associated with the collection of this data has provided information that can be used to design a study of snowshoe hare abundance that will be adequate to produce estimates by block. The study provides an estimate of the plot to plot variance in the number of pellets in the study area, as well as an idea of the number of randomly placed Krebs' plots that C&l1 be surveyed in a season. LITERATURE CITED Krebs, C.J., B.S. Gilbert, S. Boutin and R. Boonstra. 1987. Estimation of snowshoe hare population density from turd transects. Canadian Journal of Zoology. 65: 565567. � https://cpw.cvlcollections.org/files/original/6e3556eb1f4b3ee22038a42da446f254.pdf 50c421566fe5ea4f2eb4abb9de71bac1 PDF Text Text 113 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT Colorado state of cost center 3430 Project No. _,_,W~--1~5~3--~R~--l_l~----- Mammals. Research Work Package No. _ _~P~B~B~O,_______ : Black-footed Ferret Recovery Task No. __....;.._ _,,,_________ Monitoring and Managing Disease in Black-footed Ferrets Period Covered: Author: July 1, 1997 - June 30, 1998. M.A. Wild and K. T. Castle Personnel: E. Wheeler. ABSTRACT We prepared a Program Narrative describing research to support black-footed ferret (Mustela nigripes) recovery efforts in Colorado. The black-footed ferret is a federally listed endangered species in the United States. Blackfooted ferrets have been extirpated from Colorado, but are scheduled to be reintroduced to the wild at the Little Snake Management Area (LSMA) in Moffat County, Colorado in 1999. Our research can be sub-divided into two broad sections: disease monitoring and flea control as a tool to manage sylvatic plague in prairie dogs and black-footed ferrets. Disease monitoring will be performed using collection of carnivores (primarily coyotes) from the LSMA twice per year. Carnivores will be examined post-mortem for signs of active disease and serology will be performed to test for exposure to diseases potentially threatening black-footed ferrets. Results of testing in FY97/98 show that toxoplasmosis and tularemia are present at LSMA, but potential impact on black-footed ferrets is unknown. Two potentially devastating diseases, canine distemper and plague, are also present at LSMA. Although prevalence of titers to canine distemper virus (CDV) in coyotes appears low at LSMA, an increasing trend.in prevalence is suggested .. Titers to plague (Yersina pestis) were found in 65% and 48% of coyotes tested in the summer and winter collections, respectively. Titers were present in both adult and juvenile animals, suggesting ongoing plague activity in some areas. The second section of our Program Narrative describes experiments with captive white-tailed prairie dogs to evaluate insect growth regulators (IGRs) on control of prairie dog fleas (genus Oropsylla). Preliminary work to establish a captive colony of >30 white-tailed prairie dogs and to develop techniques to rear Oropsylla in an insectary have been initiated this fiscal year. ��115 MONITORING AND MANAGING DISEASE IN BLACK-FOOTED FERRETS Margaret A. Wild and Kevin T. Castle P. N. OBJECTIVES 1. Monitor enzootic disease activity threatening survival of black-footed ferrets reintroduced into the LSMA. 2. Write a Final Program Narrative describing an experiment to develop and evaluate management techniques to minimize disease-related mortality of reintroduced black-footed ferrets. SEGMENT OBJECTIVES 1. Determine the level of activity of canine distemper virus, Aleutian disease, toxoplasmosis, tularemia, and leptospirosis in carnivores and plague in prairie dogs (using coyotes as sentinels) in the LSMA by sampling ~20 coyotes in summer and winter. 2. Write a Final Program Narrative describing an experiment to develop and evaluate management techniques to minimize disease-related mortality of reintroduced black-footed ferrets. METHODS AND MATERIALS Carnivore Disease Survey Infectious diseases can severely impact the success of black-footed ferret (Mustela nigripes) reintroduction efforts. As part of the black-footed ferret reintroduction protocol, we monitored disease activity in carnivores in the Little Snake Management Area (LSMA), Colorado. Coyotes (Canis latrans) were collected during a summer and winter sampling period. Post-mortem examination and sample collection was performed as described in the Planning Program Narrative (Wild 1997). In addition to serologic assay for plague (Yersina pestis) using the passive hemagglutination inhibition test (PHA/PHI), sera collected in the winter sampling were also tested using the plague ELISA test. Proposed Research Experiments We compiled data and performed literature searches and interviews to prepare a Program Narrative. We initiated work on Phase I--Pilot Study as per the Program Narrative and captured white-tailed prairie dogs using techniques described in the attached protocol (Attachment 1). Black-footed Ferret Reintroduction We assisted in preparation of the Black-footed ferret allocation request submitted to the US Fish and Wildlife Service by the Colorado-Utah blackfooted ferret recovery working team in 1997 and 1998. �116 RESULTS AND DISCUSSION Carnivore Disease Survey With the assistance of USDA Wildlife Services and the Bureau of Land Management (BLM) we collected 20 coyotes from the LSMA between 21-25 July 1997 and 21 coyotes between 10-11 February 1998. Coyotes were collected using a combination of calling and aerial gunning. Death occurred rapidly and the collection technique was adequate, but much less efficient in summer than when used in the winter months. Coyotes were collected from various locations in the >4700 mi 2 management area; however, we focused on the Powderwash area and near the site of the pre-conditioning pens. No lesions indicative of active disease were noted on gross examination of carcasses. We found no serologic evidence of exposure to leptospirosis (serovars canicola, grippe, hardjo, ictero, and pomona). Coyotes were not tested for Aleutian Disease (a mustelid disease). Serologic titers were positive to toxoplasmosis in two coyotes (one· adult, one juvenile) collected in the winter sampling. Fifty percent of the coyotes sampled during the summer had positive titers to tularemia, while <5% of those sampled in winter were positive. Positive titers could have been associated with predation on rabbits, prairie dogs, or other rodents or exposure to ectoparasites. Duration of titers to tularemia are likely of short duration (<6 mo). The impact of tularemia or toxoplasmosis on blackfooted ferrets is not currently known; however, ferrets and humans are susceptible to these diseases. Although a relatively small proportion of coyotes had positive titers (~1:16) to canine distemper virus (CDV), data collected over the last 18 mo suggest a trend toward increasing prevalence of CDV at the LSMA (Fig. 1). Because CDV is a serious disease threat to blackfooted ferrets, a priority in the coming year will be to monitor the trend of CDV prevalence. Likewise, plague activity on the LSMA is of concern. In the summer collection, both juvenile (7/13) and adult (5/7) animals showed evidence of exposure to plague (titers >1:8; Fig. 2). Seropositive juveniles indicates that some active plague is continuing in the area. Samples collected in the winter were tested using the standard PHA/PHI test and also an ELISA test. The ELISA test may be more specific than the PHA/PHI test; however, it has not been fully validated and accepted (H. Edwards, pers. commun.). Results of the standard PHA/PHI test indicate about half (10/21) of the animals samples had positive plague titers (Fig. 2). Alternatively, results of the ELISA test suggest that 81% (17/21) of animals samples were positive. Anecdotal evidence suggests that localized outbreaks of plague may be occurring in some areas of the LSMA, while plague activity may be lesser in the other areas (M. Albee, pers. commun.). This localization of plague activity is not uncommon. Proposed Research Experiments Given the results of these initial surveys, plague appears to be the most significant disease threat currently to black-footed ferrets reintroduced into the LSMA. Further, it is now more apparent that research emphasis needs to be placed on management and control of plague in prairie dogs and black-footed ferrets. The Program Narrative describing this research is attached (Attachment 2). To support this research, we captured 34 white-tailed prairie dogs from the Arapaho National Wildlife Refuge (ANWR), Colorado. Initially, four adult males were captured in April to evaluate methodology. Thiry juveniles were then captured in June. Spring/summer capture is required because white-tailed prairie dogs hibernate. Further, juveniles can be easily differentiated from �117 adults in early summer (June). One prairie dog died from trauma at FWRF, but all prairie dogs remained healthy during the quarantine period. The housing and care protocol (see Program Narrative) appears sufficient for maintaining prairie dogs. The white-tailed prairie dogs are more fractious than anticipated; however, training continues in an attempt to habituate the animals to handling. We also initiated investigation of maintaining prairie dog fleas (.Oropsylla spp.) in artificial insectaries. Flea mortality has been high immediately after capture from ANWR and transport to Fort Collins. We will continue to modify our protocols to increase survival. Fleas that survive transport have been successfully maintained in the rearing medium. Pinky (neonatal) mice are provided to the fleas for a 24-hr period every 2-3 days as a blood source. Fleas have been observed to lay eggs, but the numbers (a few/day) are, as expected, low. Black-footed Ferret Reintroduction The U.S. Fish and Wildlife Service approved an allocation of black-footed ferrets for reintroduction into the LSMA in fall 1997; however, due to delay in publishing the final rule on experimental designation of the joint Colorado-Utah reintroduction sites, black-footed ferrets were not received this year. The Colorado-Utah site has received conditional approval for allocation of 20 black-footed ferrets later in 1998. LITERATURE CITED Wild, M.A. 1997. Monitoring and managing disease in black-footed ferrets. Colorado Div. Wildl. Res. Rep., 0880-1, Jul 1996 - Jun 1997, Fort Collins. Prepared by M~tJLJ Magaret A. Wild Wildlife Researcher ��119 ATTACHMENT 1 PROTOCOL FOR LIVE-TRAPPING PRAIRIE DOGS Prepared by: Kevin T. Castle, M.S. 17 March 1998 The following procedures are based on my personal experience with trapping a variety of mammals, and on the prairie dog trapping experiences of Hoogland (1995) and A. Schwartz (pers. commun.). Hoogland reported only 12 trap-related deaths in over 10,000 captures, and Schwartz observed only 5 deaths in approximately 1,700 captures; the average mortality rate is approximately 0.1%, so trapping mortality is unlikely if these procedures are followed. If an animal is severely injured (fracture, severe laceration), such that its ability to survive is markedly impaired, or it would suffer undue misery and stress, it will be euthanized. Euthanasia will be performed using an overdose of inhalant anesthetic, by placing the prairie dog in an induction chamber with a halothane-soaked gauze. If two trapping-related deaths occur, trapping will cease and the protocol will be reviewed and modified. Minor injuries or metabolic imbalances will be treated by, or under the supervision of, a veterinarian. One or two single or double-door Tomahawk traps (6" x 6" x 24") are placed near active burrows; single door traps seem to selectively capture juvenile prairie dogs, whereas double-door traps will capture both juveniles and adults. Traps are baited with rolled oats and/or "horse sweet mixture"; horse sweet mixture is sticky, and therefore tends to stay in place, rather than roll or blow away. During a 1-2 week "prebaiting" session, the traps are wired closed (to prevent unwanted, accidental entry), and bait is spread around the traps and burrows. Prebaiting allows the prairie dogs to become accustomed to having strange objects in their environment, and lets them associate the traps with the presence of food. In addition, the traps "weather" and take on a more natural scent; this is especially important for new, unused traps that may smell of oils used in the manufacturing process. After the prebaiting session, traps are set (opened and baited) just prior to sunset, and checked (minimally) at noon and at dusk the following day. It is better to set the traps at night rather than in the morning, to avoid disturbing any animals that become active early. Once disturbed, it may take from 15 minutes to several hours for an animal to re-emerge from its burrow, and any other animals may become more wary. Prairie dogs are diurnal, and are typically not seen above ground in inclement weather, so it is unlikely that any will be captured at night or when temperatures are very cold or very hot. Nonetheless, traps are not set during rain or snow, or when daytime ambient temperature is expected be below 20°F or above 90°F. Prairie dogs should be handled by experienced mammal trappers, wearing heavy leather or welder's gloves. Upon capture, each animal is placed into a coneshaped nylon or canvas bag for non-chemical immobilization. They are sexed and weighed, and age is determined (Hoogland 1995; cox and Franklin 1990). A numbered monel ear tag is attached to each animal. Released animals should be tagged also, to minimize the handling of animals recaptured at a later date. Animals are then transferred to individual mesh-bottom holding cages (minimum size= 18" x 18" x 18"), and the cages are covered for transport. At least part of the holding cage should remain covered at all times, to provide a hiding place for the animal; if possible, a nest box containing bedding material (e.g. "Bed-o'-cobs", care Fresh, hay) should be provided. Rodent chow, �120 alfalfa cubes, and water are provided ad lib. if transport/holding time will exceed 2 h. Animals held in the field should be kept indoors if possible, but minimally need to be protected from the elements and from potential predators. They should be checked every 3-4 h the first 1-2 days after capture, to assess health and acclimation to captivity, and at least once per day thereafter. Literature Cited: Hoogland, J. L. 1995. The black-tailed prairie dog: social life of a burrowing animal. University of Chicago Press, Chicago, 557 pp. �121 ATTACHMENT 2 PROGRAM NARRATIVE State of Colorado cost center 3430 Project No. W-153-R Mammals Program Black-footed Ferret conservation Work Package No._-P-8~8~0,..__ _ _ __ Task No. ______________ : Monitoring and Managing Disease in Black-footed Ferrets A. NEED The mission of the Colorado Division of Wildlife (CDOW) is to "perpetuate the wildlife resources of the state and provide people the .opportunity to enjoy them" (State of Colorado, 1994). Further, the CDOW Long Range Plan established a goal directing the Division to "cooperate with federal, state, county and local government agencies, private landowners and other organizations in evaluating the potential for restoration of extirpated species" (State of Colorado, 1994; Goal 8). The black-footed ferret (Hustela nigripes) is a federally listed endangered species in the United States. Black-footed ferrets have been extirpated from Colorado, but are scheduled to be reintroduced to the wild at the Little Snake Management Area (LSMA) in Moffat County, Colorado in 1999. Coyote Basin, Utah and White River Resource Area, Colorado are also under consideration for blackfooted ferret reintroduction efforts in the near future. The overall goal of ferret reintroduction is to contribute to the national black-footed ferret recovery plan objectives (U. s. Fish and Wildlife Service, 1988). The specific reintroduction objective for LSMA is to sustain a natural breeding population of 30 adult black-footed ferrets. success of ferret reintroduction programs in Wyoming, south Dakota, and Arizona have been hampered by multiple factors. Mortality rates, primarily from predation and disease, have been high (D. Biggins, pers. commun.; P. Marinari, pers. commun.). It has become apparent that improved methods for preconditioning ferrets prior to release, predator management, and disease management are prerequisite to success of future reintroduction efforts. Here, we will begin investigating the potential for impact of diseases on black-footed ferrets in the LSMA reintroduction site. Disease, primarily canine distemper and sylvatic plague, has been a significant factor limiting captive as well as free-ranging black-footed ferret populations. Mortality of black-footed ferrets from infection with canine distemper or sylvatic plague is extremely high (Williams et al., 1988; Williams et al., 1994). Further, mortality from sylvatic plague in prairie dogs can markedly impact prey base for black-footed ferrets. Before black-footed ferrets are reintroduced to the site, data on these potentially devastating diseases must be collected and unique plans for their management devised. B. OBJECTIVES 1. Monitor enzootic disease activity threatening survival of black-footed ferrets reintroduced into the LSMA. �122 2. C. Develop techniques to manage plague in the LSMA using insect growth regulators applied orally to prairie dogs. EXPECTED RESULTS AND BENEFITS Disease Monitoring Improved techniques for disease management will likely be required for the successful reintroduction of the extirpated black-footed ferret to Colorado. We must monitor enzootic disease activity to determine immediate risks to black-footed ferrets. Monitoring will also provide information on the epizootiology of diseases that will assist in formulating management plans for black-footed ferrets and may also aid in understanding population dynamics of other inhabitants. of the short grass prairie. Performance Indicator: Monitor disease status of ~40 carnivores in the LSMA annually and based on these findings make disease management recommendations to the Colorado-Utah black-footed ferret recovery working team. Flea control We believe that the proposed research will provide a novel and effective means of controlling plague in prairie dogs and black-footed ferrets. Sylvatic plague is transmitted primarily via the bite of infected fleas. Control of flea populations can be used to break the cycle and reduce the occurrence of disease. Products, such as lufenuron and pyriproxyfen, administered orally to pet animals have effectively controlled fleas (Blagburn et al, 1994; Hink et al., 1994; Palma et al., 1993). If these products are efficacious and safe in prairie dogs, and to black-footed ferrets which consume treated prairie dogs, then they could be used to control fleas, and plague, at reintroduction sites. Further, these products could be used as an alternative method of wildlife management in areas where sylvatic plague is a threat to public health. Performance Indicator: Provide a novel technique for the management of plague in the LSMA to protect the endangered black-footed ferret. D. APPROACH Disease Monitoring Rationale: Infectious diseases can severely impact the success of black-footed ferret reintroduction efforts. Canine distemper and sylvatic plague pose the greatest threats to black-footed ferret survival (Williams et al, 1988; Williams et al, 1994). Wild canids and mustelids, as well as domestic dogs, are susceptible to canine distemper and can serve as reservoirs for infection (Williams, 1982). Plague is maintained primarily in rodent populations, such as prairie dogs (Quan, 1982). Therefore, prior to reintroduction, status of diseases such as canine distemper and plague in sympatric wildlife populations must be determined to assess the risk to black-footed ferrets. We will monitor activity of canine distemper in carnivores, primarily coyotes (Canis latrans), by determining serologic titers and performing postmortem examination. Titers are useful in ascertaining if carnivores have recently been exposed to the virus. Postmortem examination is required to determine if carnivores have active infection with canine distemper. We will monitor plague activity in prairie dogs using coyotes as sentinels. Although coyotes are rarely involved in plague transmission, serologic testing of coyotes for titers to plague can �123 help define the extent of plague activity in rodent prey populations (Thomas and Hughes, 1992). Moreover, by sampling juvenile animals in the summer, recent plague activity can be identified. This survey of carnivores, combined with collaborative work by the Bureau of Land Management investigating changes in prairie dog numbers, will provide important information on activity of diseases that are potentially devastating to black-footed ferrets. Disease management activities will be driven by these findings. Methods: We will use survey of carnivores as a tool to determine status of canine distemper and sylvatic plague in LSMA. Surveys will be performed annually in January-March and July-September. Each survey will consist of a minimum sample of 20 coyotes. Aerial gunning will be used as the primary means of sample collection. Summer collections will focus on juvenile animals. Animals will be located by personnel in a fixed wing aircraft. Personnel from USDA Wildlife Services skilled in coyote control will fly over and shoot animals at close range (about 10-45 m) using a 12 g shotgun loaded with copper coated BB's or #4 buck shot. Multiple shots will be fired at the head of the animal. Ground crews will locate and recover the animal carcass. If the animal was not fatally wounded, ground crews will euthanatize animals with a shot to the neck or chest. Location of carcass collection will be recorded within 1/4 section. Surveys will be supplemented with additional samples collected opportunistically from carcasses of coyotes and other carnivores, including badger (Taxidea taxus), red fox (Vulpes vulpes), and striped skunk (Mephitis mephitis), killed as a result of hunting or by unintentional vehicular collision. Diagnostic techniques will include collection of blood samples for serology, collection of lower jaw for age determination, and postmortem examination to detect evidence of active disease. Serum will be harvested from blood samples, frozen, and submitted to Wyoming state Diagnostic Laboratory (WSVL, Laramie) for determination of titers to canine distemper using the serum neutralization test and to plague (Yersinia pestis) using the passive hemagglutination inhibition test. Titers to toxoplasmosis, tularemia, Aleutian disease (mustelids only), and leptospirosis will also be determined using samples collected during the initial carnivore survey. Gross necropsy will be performed by or under the direct supervision of a veterinarian. Routine tissue collection will include: samples of gross lesions, kidney, urinary bladder, lung, and brain placed in 10% buffered formalin; samples of lung, small intestine, and brain frozen; and samples of lesions stored fresh for immediate analysis. Samples of parasites will also be collected opportunistically; however, all badgers with dermatitis will be sampled for Filaria taxideae. Fixed tissues will be submitted to Dr. E. s. Williams, WSVL for histologic examination. Frozen samples will be stored by Colorado Division of Wildlife for analysis as needed (i.e., as indicated by histologic·or serologic findings). Fresh samples will be submitted to WSVL or Colorado State Veterinary Diagnostic Laboratory (CSVDL, Fort Collins). Parasites will be stored and submitted to WSVL or CSVDL as needed. Additional blood samples will be collected for serology as available from carcasses harvested by local hunters and from unintentional vehicular collision. Serum samples will be handled as previously described. Analysis: A titer of ~1:16 will be considered positive for antibodies against canine distemper virus or for antibodies against Yersinia pestis. We will use Fisher's exact test (or extensions) to statistically analyze the prevalence of antibodies among age classes and over time. �124 Flea Control Rationale: Mortality of black-footed ferrets from infection with sylvatic plague is extremely high (Williams et al., 1994). Further, mortality from sylvatic plague in prairie dogs can markedly impact prey base for black-footed ferrets. Plague has severely hampered reintroduction efforts in other states (P. Marinari, pers. commun.) and preliminary data suggest that plague activity is present in some areas of the LSMA (M. Albee, unpub. data). Successful reintroduction will likely require management techniques to control plague. Plague i~ maintained primarily in rodent populations, such as prairie dogs, where it is transmitted via the bite of an infected flea. Fleas of the genera Opisocroscis and Oropsylla have been associated with plague transmission in prairie dogs (Ubico et al., 1988). Insecticide dusts have been applied to prairie dogs burrows in an attempt to kill fleas and thus control plague. Carbary! has been the most commonly used insecticide; however, application is labor intensive and activity is short-lived (Barnes, 1993). Permethrin has been shown effective up to 84 days after application, but the authors warn that application at the recommended dosage rate would be highly laborious (Beard et al., 1992). Recently developed compounds used to control fleas in pet animals offer a promising alternative to insecticide dusts. Although topically applied flea adulticides, such as imidacloprid, are not feasible for use in wildlife, insect growth regulators (IGRs) with ovicidal and/or larvicidal activity could be delivered orally to free-ranging animals via bait. The IGR lufenuron is a benzoylphenylurea derivative which inhibits formation of chitin in the exoskeleton of insects (Cohen, 1987). A single oral dose of lufenuron has been shown effective in controlling the cat flea (Ccenocephalides felis felis) for at least 30 days in treated dogs (Hink et al., 1994) and cats (Blagburn et al., 1994). Davis (1997) reported a significant reduction in fleas on ground squirrels (Spermophilus beecheyi) that had been treated with lufenuron. Another IGR, pyriproxifen, exerts activity by mimicking natural insect juvenile hormones. Pyriproxifen has been shown effective in vitro in inhibiting normal egg production for 80 hr post-treatment (Palma et al., 1993) and may have other longer lasting means of control as well (T. Miller, pers. commun.). If these compounds proved efficacious over a period of time(~ 1 mo) when administered orally to prairie dogs, they could be applied over large areas of prairie dog habitat via a treated bait. However, prior to management application, the products should be evaluated in a controlled laboratory setting to determine an effective dose, duration of efficacy, product safety, and to formulate an acceptable bait carrier. If results of laboratory tests are positive, the products should be tested in a controlled field study to determine efficacy under natural conditions. Without this evaluation, the management potential of IGRs for controlling plague and protecting the health of the endangered blackfooted ferret, as well as human health, will be difficult to discern. Our work will be divided into three phases. Phase I will be pilot work to establish a colony of captive prairie dogs and to develop an environment suitable for flea survival and reproduction both on the prairie dogs (and in their bedding) and in an artificial medium. Before we can evaluate the efficacy of IGRs, we must be sure that fleas will survive and reproduce on our captive prairie dogs. Further, we will need to artificially rear prairie dog fleas for infestation of prairie dogs and assessment of egg viability. These techniques are not currently available (Barnes, 1993). Phase II will evaluate efficacy and safety of lufenuron and pyriproxifen fed to captive prairie dogs. Finally, in Phase III we will evaluate potentially efficacious IGRs (from phase II) in a limited field application. White-tailed prairie dogs (Cynomys leucurus) will be used as the study animal because this is the species of prairie dog present at the LSMA black-footed ferret reintroduction site. �125 Phase !--Pilot Study Methods: Capture of prairie dogs. White-tailed prairie dogs will be captured at the Arapaho National Wildlife Refuge, Colorado. One or two single or double-door Tomahawk traps (15 cm x 15 cm x 60 cm) will be placed near active burrows. Traps will be baited with horse sweet mixture (sweetened grain mixture). During a 1-2 week prebaiting session, the traps will be wired closed (to prevent unwanted, accidental entry), and bait will be spread around the traps and burrows. After the prebaiting session, traps will be set (opened and baited) just prior to sunset, and checked (minimally) at noon and at dusk the following day. Prairie dogs are diurnal, and are typically not seen above ground in inclement weather, so it is unlikely that any will be captured at night or when temperatures are very cold or very hot. Nonetheless, traps will not be set during rain or snow, or when daytime ambient temperature is expected be below -6 C or above 32 c. Prairie dogs will be handled by experienced mammal trappers, wearing heavy leather or welder's gloves. Upon capture, each animal will be physically restrained in a cone-shaped nylon or canvas bag. They will be sexed and weighed, and age determined (Hoogland, 1995; Cox and Franklin, 1990). A numbered monel ear tag will be attached to each animal. The animals will then be transferred to an individual mesh-bottom holding cage (minimum size= 45 cm x 45 cm x 45 cm) with nest box and covered for transport. Feed (e.g., rodent chow, alfalfa cubes) and water will be provided ad lib if transport/holding time will exceed 2 hr. care and housing of prairie dogs. Prairie dogs will be maintained indoors in individual cages (45 cm x 90 cm x 45 cm) with nest boxes at the Foothills Wildlife Research Facility (FWRF). Animals will be quarantined for 14 days upon return to FWRF to assess disease (plague) status. Due to our study needs, prairie dogs will not be treated to control external parasites. During the quarantine period, all personnel will be required to wear room-specific gloves and coveralls when in the room, whether observing animals or cleaning cages. Personnel will be informed of the clinical signs of plague in prairie dogs and humans and instructed to monitor themselves and their clothing for fleas. If plague is diagnosed in a prairie dog, all animals in the building will be euthanized with an overdose of halothane inhalant anesthetic. Our custom cage design is based on specific study needs (providing the prairie dogs with sufficient living space, while allowing us to rear and collect fleas), discussions with M. Metzger, and the published work of Hilton (1971). Individual prairie dog cages will be constructed of wood and wire fencing, with "no-see-um" netting over the top and covering potential flea escape routes. Half of the cage serves as a nest box, and the other half serves as a feeding area. Two hinged doors allow access to each half of the cage for cleaning or animal handling. The nest box is a 40 x 28 x 23 cm plastic container fitted with a wooden lid. The nest box has a 10 cm diameter hole in one wall to provide access to the feeding area; a 10 cm diameter piece of PVC tubing joins the nest box to the feeding area. The access hole can be covered to confine the animal to either side of the cage as necessary. Previous work on ground squirrels (Hilton, 1971) suggests that the animals are unlikely to defecate/urinate in the nest box, and Hoogland (1995) noted that there was little fecal matter in the burrows and nests of black-tailed prairie dogs he studied. Our preliminary work shows that defecation in the nest box is minimal, and that urination is very rare; we therefore do not expect the nest boxes to become soiled during experiments. �126 The floor of the feeding area consists of 1 cm mesh wire fencing, to allow feces, urine, and spilled food to fall through to a pan below. This mesh size prevents the animal's feet from becoming wedged in the floor, but may encourage the animal to spend most of its time in the nest box when not feeding. It is important for us to keep the animal in the nest box as much as possible, in order to enhance flea reproduction; many fleas of the genus Oropsylla are "nest fleas" and are associated with the host's body only when feeding (Hilton, 1971; M. Metzger, pers. comm.). Confining the prairie dogs and fleas to the nest box will also facilitate collection of fleas and.their eggs. A food dish and water bottle will be wired to the side of the feeding area. A 2.5 cm deep, removable, galvanized sheet metal pan will be placed under the entire cage to catch food, feces, urine, and any fleas that escape the nest box. All prairie dogs will be checked at least once per day. Fresh feed (rodent chow, alfalfa cubes) and water will be provided daily, and cage bottoms will be cleaned of feces each day. Pans will be cleaned and bedding will be replaced as needed, but a minimum of 2 times per week. Rooms (or nest boxes) will be maintained at approximately 24 C and 75% relative humidity to ensure flea survival and reproduction (M. Metzger, pers. commun.; Metzger and Rust, 1997). Two south-facing windows in the animal room should provide sufficient light for these fossorial animals, and will allow us to maintain the animals on a natural photoperiod. We do not anticipate any prairie dog mortality due to capture or experimental procedures. If an animal becomes sick or injured, and recovery is not likely, it will be euthanized with an overdose of halothane inhalant anesthetic. Pilot study. We will capture and house 3-5 prairie dogs for initial evaluation of our methods. Prairie dogs will be observed daily and weighed at least once per week, to help assess health and acclimation to captivity. If two or more animals do not adjust to our captive conditions (they refuse food and/or water or appear sick) we will review and modify our procedures. All prairie dogs that die in captivity will undergo a full post-mortem examination. Minor adjustments to husbandry may be made as needed to meet animal needs. One objective of the pilot study is to determine if prairie dogs can be trained to allow repeated grooming by handlers, without being chemically immobilized. Hoogland (1995) successfully groomed black-tailed prairie dogs without chemical immobilization, and one of us (KTC) repeatedly handled captive black-tailed prairie dogs that were distracted with a treat, such as a carrot. We will therefore attempt to handle each animal on a daily basis, in order to establish a routine whereby they become accustomed to being groomed. If we can train the animals to allow grooming, chemical immobilization will not be necessary. If chemical immobilization appears necessary, we will test the following methods to determine which to use in Phase II: 1) animals will be placed in an induction chamber and anesthetized with isoflurane. The animals will be removed from the chamber within 15 seconds after cessation of movement and anesthesia will be maintained via a mask; or 2) animals will be placed into a restraining cone and injected intramuscularly (IM) with a combination of ketamine (30 mg/kg) and diazepam (0.5 mg/kg) (Kreeger, 1997). During anesthesia, animals will be monitored visually for respiration, heartbeat, and signs of distress. Trained or immobilized prairie dogs will be groomed with a fine-toothed flea comb for 3 minutes; grooming will take place up to 3 times per week. After immobilization, each animal will be returned to its cage, and closely observed until it regains normal functions. �127 Concurrent to establishing the captive prairie dog colony, we will develop a technique to artificially rear prairie dog fleas of the genus Oropsylla. Although prairie dogs can harbor several genera of fleas, we have selected to maintain only Oropsylla because they are among the most common fleas of prairie dogs and they have been implicated in the transmission of plague (Ubico et al., 1988). Fleas will be collected by combing trapped prairie dogs and by swabbing of burrows (Barnes et al., 1972). Fleas will be placed in 500 ml glass jars each containing about 125 g of larva-rearing media consisting of wheast (Red Star Biologicals), dried beef blood (Monfort Biologicals), powdered dog chow, and sand. In the laboratory, live fleas will be anesthetized with CO2 and identified by comparison to a reference collection of preserved fleas. Because fleas are sensitive to changes in temperature and humidity, they will be maintained in an incubator at about 23-24 c and ~70% relative humidity (Metzger, pers. commun.). Appropriate relative humidity will be maintained using a super-saturated solution of potassium chloride (Winston and Bates, 1960). A natural photoperiod will be approximated within the incubator through the use of fluorescent lights and a timer. Fleas will be monitored daily for survival and reproduction. Modifications will be made as necessary to optimize flea performance. To determine adequacy of the cage environment for flea survival and reproduction, we will infest prairie dogs with about 20-50 male and female fleas. We will collect and count fleas from prairie dogs and their bedding at weekly intervals. Fleas will be collected from prairie dogs by combing (while distracted with a treat or while under anesthesia) for 3 min and from bedding by sifting and visual inspection. Fleas will be returned to the prairie dog after counting. Collections, and if needed reinfestations, will be continued until successful colonization occurs. If a severe allergic reaction or other health problem associated with flea infestation occurs, the prairie dog will be removed from the study and provided veterinary care or euthanized. Analysis: Evaluation of husbandry techniques and artificial flea rearing procedures will be subjective. No statistical analyses will be performed. Phase II--Laboratory Evaluation of IGRs Methods: Prairie dogs will be captured and maintained in captivity as described in Phase I. Laboratory evaluation of pyriproxifen and lufenuron will be divided into four experiments--efficacy dose titration, efficacy of controlling flea infestations in a simulated burrow environment, product safety, and bait formulation. Detailed Study Plans will be written for each of these experiments based on results of the Pilot Study; however, general procedures will be as follows. Efficacy dose titration. In this experiment we will determine an effective dose of pyriproxifen and of lufenuron to interrupt reproduction in prairie dog fleas and monitor duration of the products' efficacy. Prairie dogs (n = 21) will be blocked by sex and randomly divided into two treatment groups and a control group. In the first experiment, lufenuron will be evaluated at two dose rates. Treatment group 1 (n = 7) will receive 15 mg/kg and treatment group 2 (n = 7) will receive 45 mg/kg lufenuron PO. The control group (n = 7) will receive excipient suspension without lufenuron PO. After a sufficient washout period, the experiment will be repeated using pyriproxifen at anticipated dosages of 50 mg/kg and 100 mg/kg PO for treatment groups 1 and 2, respectively. Prairie dogs will be infested with fleas prior to treatment and periodically after treatment to maintain flea infestations. We will collect flea eggs prior to treatment and at 5 weekly intervals and determine egg �128 viability by rearing in artificial media. Number of eggs hatching in a specific time period (to be determined in Phase I) will be determined and compared between groups and over time. We may also collect blood from prairie dogs during the weekly samplings if an assay to determine serum levels of test product can be developed. Development of a successful artificial rearing system for prairie dog fleas is prerequisite to the performance of this experiment. If such a protocol is not developed, we will attempt to determine an effective dose using the methods described below for evaluation of efficacy in a simulated burrow environment. In this case, duration of efficacy will be more difficult to determine. Efficacy of controlling flea infestations in a simulated burrow environment. If results of the efficacy dose titration experiment suggest that a single oral dose of pyriproxifen and/or lufenuron is effective in controlling reproduction of prairie dog fleas for at least 4 wk, we will further evaluate the product(s) in a simulated burrow environment. The purpose of this experiment is to evaluate the ability of the test products to control prairie dog flea populations over an extended period. Prairie dogs (n = 20) will be blocked by sex and divided into treatment and control groups. They will be infested with fleas and treated monthly with pyriproxifen or lufenuron. Adult fleas on the animal and in the cage will be counted at 1-2 wk intervals for 12 wk. After counting, fleas will be returned to the animal. Number of fleas recovered will be compared between treatment groups and over time. Product safety. We will determine safety of an overdose of pyriproxifen and/or lufenuron. Prairie dogs (n = 20) will be divided into a treatment and control group. Prairie dogs in the two groups will be maintained similarly except the treatment group will receive an amount of product equal to that contained in the maximum calculated daily intake of treated bait. Overdose feeding will continue for a 3 day period. Health, attitude, and weight change of prairie dogs in the treatment and control groups will be monitored during, and for 1 wk following, this treatment. Based on type of action, these products should be safe in mammals (Blagburn et al., 1995; T. Miller, pers. commun.); however, if animals become moribund, they will be euthanatized. All dead animals will receive a complete postmortem examination. If the overdose of test product is safe in prairie dogs, product safety will be tested in black-footed ferrets or black-footed ferret x Siberian polecat hybrids. Ferrets maintained at other research facilities will be used as test animals and will be divided into a treatment and control group. Prairie dogs treated with three times the maximum daily dosage of test product (as described above) will be fed to ferrets in the treatment group for 7 days. Health, attitude, and weight change of ferrets in the treatment and control groups will be monitored during, and for 1 wk following, this treatment. Bait formulation. When an effective dose of pyriproxifen and/or lufenuron is determined, we will begin investigating formulation of a bait carrier. Because of differences in the chemical properties of the test products, unique formulations will likely be required for each product. Due to its high palatability, we will initially attempt to incorporate the test product into horse sweet feed (sweetened grain mixture); however, incorporation into a pelleted feed may be required to adequately deliver the product. Palatability of treated bait will be evaluated in feed-deprived (hungry) prairie dogs as well as those fed ad libitum maintenance diets (satiated). Blood samples may be collected from prairie dogs to determine serum level of test product after bait consumption. �129 Analysis: Efficacy dose titration. Efficacy of test product will be determined by comparing developmental success of eggs produced by fleas exposed to treated prairie dogs vs. eggs produced by fleas exposed to control group prairie dogs. These formulas will be used in efficacy determination: Developmental success= number emergent adult fleas x 100 number eggs collected Percentage efficacy= mean developmental success (control)- mean develqpmental success (treated) x 100 mean developmental success (control) Mean developmental success values for eggs collected from prairie dogs in each of the treatment groups will be analyzed using analysis of variance. Efficacy in a simulated burrow environment. Efficacy of test product will be determined by comparing number of fleas recovered from treatment and control prairie dogs and their cages on each sampling day using analysis of variance. Significant reductions in numbers of fleas on treated prairie dogs would signify interruption of the flea life cycle attributable to treatment with the test product. Product safety and Bait formulation: Evaluation of product safety and acceptability of bait will be subjective. No statistical analyses will be performed. Phase III-Field Evaluation of IGRs Methqds: Based on results of laboratory evaluations, we will evaluate pyriproxifen and/or lufenuron in a limited field application. Only product(s) that significantly reduced flea numbers on treated hosts for ~1 mo and that showed no adverse effects on captive prairie dogs and ferrets will be field tested. We will identify similar, yet geographically distinct, colonies of healthy prairie dogs for evaluation of the test product(s). Treatment colony(s) will receive bait fortified with the test compound while the control colony will receive bait only. Treatments will be applied at monthly intervals during the summer. Observations will be made to determine prairie dog numbers and consumption of bait by prairie dogs and non-target species. Flea indices (number of fleas per individual and number of fleas per burrow) will be determined by counting and identifying fleas collected by combing live-trapped prairie dogs and by swabbing burrows (Barnes et al., 1972). Blood samples may also be collected from prairie dogs to determine serum level of test product. Collections will be made at monthly intervals beginning ~l mo prior to initiation of treatment, continuing through the active season of prairie dogs (September), and resuming the following summer. Flea indices will be compared between treatment and control colonies and over time. Analysis: Efficacy of test product will be determined by comparing flea indices of control and treatment colonies at each sampling using analysis of variance. Significant reductions in numbers of fleas on prairie dogs at treated sites would signify interruption of the flea life cycle attributable to treatment with the test product. �130 schedule: Objective 1. Disease survey 2. Phase I--Pilot study 3. Phase II--Laboratory study 4. Phase III- Field study 5. Analyze data, report results E. Fiscal Year 1998-2002 1998-1999 1999-2000 2000-2001 2001-2002 LOCATION Planning, captive animal research, data analysis, and reporting will be carried out at the COlorado Division of Wildlife's Foothills Wildlife Research Facility, 4330 w. Laporte Ave., Fort Collins, Colorado. Carnivore disease survey will be conducted at the Little Snake Management Area, Moffat County, Colorado. Capture of prairie dogs to establish a captive colony will be at Arapaho National Wildlife Refuge, Jackson County, COlorado. Location of Phase III (field study) is yet to be determined, but will be reported in the detailed Study Plan for that experiment. F. ESTIMATED COST Fiscal Year Estimated costs 1998 1999 2000 2001 2002 G. $13,000 20,500 21,400 21,400 13,000 llE ReW,1irements PFTE 0.5 0.5 0.5 0.5 0.5 PERSONNEL Margaret A. Wild1 Kevin T. Castle1 Thomas A. Miller2 Craig Parks3 co-principal investigator Co-principal investigator CO-investigator CO-investigator Colorado Division of Wildlife, Fort Collins, COlorado Virbac, Inc., Fort Worth, Texas 3 Novartis Animal Health U.S., Greensboro, North Carolina 1 2 TFTE 0.25 0 0.5 0.5 0 �131 H. LITERATURE CITED Barnes, A. M. 1993. A review of plague and its relevance to prairie dog populations and the black-footed ferret. Proceedings of the symposium on the management of prairie dog complexes for the reintroduction of the blackfooted ferret. J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R. Crete, eds. 96pp. Barnes, A. M., L. J. Ogden, and E.G. Campos. 1972. Control of the plague vector, Opisocrostis hirsutus, by treatment of prairie dog (Cynomys ludovicianus) burrows with 2% carbaryl dust. Journal of Medical Entomology 9: 330-333. Beard, M. L., s. T. Rose, A. M. Barnes, and J. A. Montenieri. 1992. Control of Oropsylla hirsuta, a plague vector, by treatment of prairie dog burrows with 0.5% permethrin dust. Journal of Medical Entomology 29: 25-29. Blagburn, B. L., J. L. Vaughan, D.S. Lindsay, and G. L. Tebbitt. 1994. Efficacy dosage titration of lufenuron against developmental stages of fleas (Ctenocephalides felis felis) in cats. American Journal of Veterinary Research 55: 98-101. Blagburn, B. L., C. M. Hendrix, J. L. Vaughan, D. s. Lindsay, ands. H. Barnett. 1995. Efficacy of lufenuron against developmental stages of fleas (Ctenocephalides felis felis) in dogs housed in simulated home environments. American Journal of Veterinary Research 56: 464-467. Cohen, E. 1987. Interference with chitin biosynthesis in insects. In Chitin and benzoylphenyl ureas, series entomologica, vol. 38, J.E. Wright and A. Retnakaran (eds), Dr. W. Junk, Publishers, Boston, pp. 33-42. Cox, M. K. and W. L. Franklin. 1990. Premolar gap technique for aging live black-tailed prairie dogs. Journal of Wildlife Management 54:143-146. Davis, R. M. 1997. Use of an orally administered insect development inhibitor (lufenuron) as a flea control agent in the California ground squirrel, Spermophilus beecheyi. Fourth International Symposium on Ectoparasites of Pets, pp 31-35. Hilton, D. F. J. 1971. A method for rearing fleas of ground squirrels. Transactions of the Royal Society of Tropical Medicine and Hygiene 66: 188189. Hink, w. F., M. Zakson, ands. Barnett. 1994. Evaluation of a single oral dose of lufenuron to control flea infestations in dogs. American Journal of Veterinary Research 55: 822-824. Hoogland, J. L. 1995. The black-tailed prairie dog: social life of a burrowing animal. University of Chicago Press, Chicago, 557 pp. Kreeger, T. J. 1997. Handbook of Wildlife Chemical Immobilization. International Wildlife Veterinary Services, Inc., Laramie, WY. 342 pp. Metzger, M. E. and M. K. Rust. 1997. Effect of temperature on cat flea (Siphonaptera: Pulicidae) development and overwintering. Journal of Medical Entomology 34: 173-178. �132 Palma, K. G., s. M. Meola, and R. w. Meola. 1993. Mode of action of pyriproxifen and methoprene on eggs of Ctenocephalides felis (Siphonaptera: Pulicidae). Journal of Medical Entomology 30: 421-426. Quan, T. J. 1982. Plague. In Diseases of wildlife in Wyoming, E.T. Thorne, N. Kingston, w. R. Jolley, and R. c. Bergstrom (eds), Wyoming Game and Fish Department, Cheyenne, pp. 67-71. Rust, M. K. 1992. Influence of photoperiod on egg production ·of cat fleas (Siphonaptera: Pulicidae) infesting cats. Journal of Medical Entomology 29: 242-245. state of Colorado. 1994. Long Range Plan. Division of Wildlife. 32pp. Department of Natural Resources, Thomas, c. U., and P. E. Hughes. 1992. Plague surveillance by serological testing of coyotes (Canis latrans) in Los Angeles County, California. Journal of Wildlife Diseases 28:610-613. Ubico, S. R., G. O. Maupin, K. A. Fagerstone, and R. G. McLean. 1988. A plague epizootic in the white-tailed prairie dogs (Cynomys leucurus) of Meeteetse, Wyoming. Journal of Wildlife Diseases 24: 399-406. u. s. Fish and Wildlife Service. 1988. Black-footed Ferret Recovery Plan. 87pp. Williams, E. s. 1982. Canine distemper. In Diseases of wildlife in Wyoming. E.T. Thorne, N. Kingston, W.R. Jolley, and R. c. Bergstrom (eds), Wyoming Game and Fish Department, Cheyenne, pp. 10-13. Williams, E. S., K. Mills, D.R. Kwiatkowski, E.T. Thorne, and A. BoergerFields. 1994. Plague in a black-footed ferret (Hustela nigripes). Journal of Wildlife Diseases 30:581-585. Williams, E. S., E.T. Thorne, M. J. G. Appel, and D.·W. Belitsky. 1988. Canine distemper in black-footed ferrets (Hustela nigripes) from Wyoming. Journal of Wildlife Diseases 24:385-398. Winston, P. w., and D. H. Bates. 1960. saturated solutions for the control of humidity in biological research. Ecology 41: 232-237. �133 SEGMENT NARRATIVE state of Colorado Project No. W-153-R Work Package No. __0_8-8-0'------Task No. cost center 3430 Mammals Program Black-footed Ferret conservation Monitoring and Managing Disease in Black-footed Ferrets Planning Program Narrative Objectives: 1. Monitor enzootic disease activity threatening survival of black-footed ferrets reintroduced into the LSMA. 2. Develop techniques to manage plague in the LSMA using insect growth regulators applied orally to prairie dogs. Segment Objectives: 1. Determine the level of activity of canine distemper in carnivores and plague in prairie dogs (using coyotes as sentinels) in the LSMA by sampling ~40 coyotes. 2. Establish a colony of captive white-tailed prairie dogs that can sustain infestation with fleas of the genus Oropsylla. 3. Develop techniques to artificially rear fleas of the genus Oropsylla. 4. Determine an effective dose of pyriproxifen and of lufenuron to control fleas of the genus Oropsylla on prairie dogs. Estimated segment costs= $46,540 Personal Services Permanent employees (0.5 FTE) Temporary employees Contracts Total Personal Services Operating supplies and services Travel expenses capital eq,uipment $26,040 0 10.000 $36,040 $ 8,300 2,200 0 Total Operating $10,500 Total Costs $46,540 �69 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT ------~~----- State of Colorado Project No. _ _ _ _W'------1=5-=-3--=-R___--=-l=-2_ _ __ Work Package No . _..;;.0""'"88~0'--_ _ _ __ Task No. ______I.___ _ _ _ _ __ Mammals Research Black-footed Ferret Recovery Monitoring and Managing Disease in Black-footed Ferrets Period Covered: July 1, 1998 - June 30, 1999. Authors: .M. A. Wild and K. T. Castle Personnel: E. Wheeler. ABSTRACT The black-footed ferret is a federally listed endangered speci~s in the United States. Blackfooted ferrets-have been extirpated from Colorado, but are scheduled to be reintroduced to the wild at the Little Snake Management Area (LSMA) in Moffat County, Colorado in the near future. Our research can be sub-divided into two broad sections: disease monitoring in the proposed release area and flea control as a tool to manage sylvatic plague in prairie dogs and black-footed ferrets. Disease monitoring was performed using collection of carnivores (primarily coyotes) from the LSMA in July 1998 and February 1999. Two potentially devastating diseases, canine distemper and plague, are present at LSMA. Prevalence of titers to canine distemper virus (CDV) in coyotes are low ~10%). Prev~ence of titers to plague (Yersina pestis) were found in 60% and 20% of coyotes tested in the summer and winter collections, respectively. Titers were present in both adult and juvenile animals, suggesting ongoing plague activity in some areas. We began investigations into the bioavailability of lufenuron to orally dosed prairie dogs. A test dose of300 mg/kg body weight was determined and administered to 30 captive prairie dogs. Prairie dogs were divided into two groups (one group torpid, the other non-torpid). Blood samples for lufenuron assay were collected pre-treatment, at 1 wk postdosing, then at 2-wk intervals through week 9 post-dosing. No adverse affects to lufenuron were observed. Lufenuron assay is pending. We also attempted to establish a colony of fleas of the genus Dropsy/la for artificial infestations on captive prairie dogs. Although we were unsuccessful in establishing self-sustaining colonies of 0. tuberculata (the prairie dog flea) from wild populations, we did establish a thriving colony ofinsectary-reared 0. montana (the ground squirrel flea). These fleas will be used in future investigations into the efficacy of lufenuron to control fleas on captive prairie dogs. f '=ii WH t~ BDOW014186 ��71 MONITORING AND MANAGING DISEASE IN BLACK-FOOTED FERRETS Margaret A. Wild and Kevin T. Castle P. N. OBJECTNES 1. Monitor enzootic disease activity threatening survival of black-footed ferrets reintroduced into the LSMA. 2. Develop techniques to manage plague in the LSMA using insect growth regulators applied orally to prairie dogs. SEGMENT OBJECTNES 1. Determine the level of activity of canine distemper virus in carnivores and plague in prairie dogs (using coyotes as sentinels) in the LSMA by sampling >40 coyotes. \"' 2. Establish a colony of captive white-tailed prairie dogs that can sustain infestations ~eas__of.the genus Oropsylla. 3. Develop techniques to artificially rear fleas of the genus Oropsylla. 4. Determine an effective dose ofpyriproxifen and oflufenuron to control fleas of the genus Oropsylla on prairie dogs. METHODS AND MATERIALS Carnivore Disease Survey Infectious diseases can severely impact the success of black-footed ferret (Mustela nigripes) reintroduction efforts. As part of the black-footed ferret reintroduction protocol, we monitored disease activity in carnivores in the Little Snake Management Area (LSMA), Colorado. Coyotes (Canis latrans) were collected.in July 1998 and February 1999. Post-mortem examination and sample collection was performed as described in the Program Narrative (Wild 1998). Black-footed Ferret Reintroduction We assisted in preparation of the black-footed ferret allocation request submitted to the US Fish and Wildlife Service by the Colorado-Utah black-footed ferret recovery working team in 1999. We prepared a protocol for the care of captive black-footed ferrets at the LSMA {Attachment 1). Consultation on health matters and veterinary care were.provided for captive black-footed ferrets. Artificial Rearing of Oropsylla fleas In summer 1998 and spring 1999 we collected Oropsylla spp. fleas from prairie dog burrows at Arapaho National Wildlife Refuge. We attempted to maintain and propagate these wild fleas under �72 insectary conditions (Wild 1998). Additionally, we attempted to produce self-sustaining populations of 0. tubercu/ata within the nest boxes of four quarantined prairie dogs. To enhance flea survival, we placed a wooden box fitted with a screen top into each nest box. The wooden "flea refuge" allowed fleas to jump on or off the animal at will, and kept the prairie dog from stepping on fleas and eggs. We placed "bed-o-cobs" bedding material on the refuge floor in order to provide hiding places for the fleas. Each prairie dog was infested with up to 60 adult fleas (about 3:2 females:males). To count fleas, we anesthetized and groomed each animal periodically, and noted the number of surviving fleas found on the animal and in its nest box. Because of the decline in 0. tuberculata availability in the field and the low survivorship and reproduction of that species in the lab, we decided to explore the use oflaboratory-reared 0. montana for experimental purposes. 0. montana is generally found on ground squirrels, such as Spermophilus beecheyi (California ground squirrel); it should be able to reproduce when fed on the closely-related prairie dogs. Other researchers have maintained lab colonies of 0. montana for a number of years, and have found that the species readily reproduces when fed in artificial systems, and when fed on captive neonatal or adult rodents. While we would rather utilize true prairie dog fleas, such as 0. tuberculata, in our experiments, the use oflab-reared 0 montana offers some advantages over 0. tubercu/ata: 1) 0. montana is readily available; 2) the temperature and humidity preferences of the species are wellcharacterized, so it reproduces well in an insectary; and 3) lab-reared 0. montana are plague-free. In summer 1999 we acquired a small colony of about 400 0. montana from the Centers for Disease Control (CDC), Fort Collins. These fleas were maintained under insectary conditions (Wild 1998). Flea Control In Prairie Dogs Thirty-three white-tailed prairie dogs (Cynomys leucurus) collected in June 1998 from Arapaho National Wildlife Refuge were maintained at Foothills Wildlife Research Facility (FWRF). Details of animal husbandry and health are reported by Wild (1999). Initially, we planned to evaluate two insect growth regulators in captive prairie dogs: lufenuron and pyriproxyfen. However, after reviewing the literature, contacting product manufacturers, and investigating methods to measure efficacy, we have determined that lufenuron holds the most promise for effective application. Lufenuron is longer lasting than pyriproxyfen (Palma et al. 1993, Hink et al. 1994), researchers with Novartis (the manufacturer oflufenuron) are interested in collaboration, and a blood assay is available to measure lufenuron but not pyriproxyfen. We performed two studies to begin evaluating lufenuron in white-tailed prairie dogs. First, a pilot study to determine bioavailabilty oflufenuron administered orally to captive prairie dogs at three dosages: 20 mg/kg, 60 mg/kg, and 300 mg/kg (n = I at each dosage). Blood samples were collected for lufenuron assay pr~treatment and 1, 7, 28, 42, and 56 days post-dosing. Lufenuron assay using HPLC was performed by En-Cas Laboratories. Results of this pilot study were used in planning the following study to determined the seurm profile oflufenuron during active and torpid periods in orallydosed white-tailed prairie dogs: Bioavailability of lufenuron administered orally to captive white-tailed prairie dogs (Cynomys leucurus) Kevin T. Castle 1, Margaret A. Wild 1, and S. Craig Parks2 1 Colorado Division of Wildlife, 317 W. Prospect, Ft. Collins, CO 80526 2 Novartis Animal Health, P. 0. Box 26402, Greensboro, NC 27404 �73 Introduction Mortality of black-footed ferrets (Mustela nigripes) from infection with sylvatic plague is extremely high (Williams et al., 1994). Further, mortality from sylvatic plague in prairie dogs (Cynomys spp.) can markedly impact the prey base of black-footed ferrets. Plague has severely hampered reintroduction efforts in other states (P. Marinari, pers. comm.) and preliminary data suggest that plague activity is present in some areas of the Little Snake Management Area (Wild, unpub. data) where black-footed ferrets are scheduled to be released in late 1999. Successful reintroduction will likely require management techniques to control·plague. We believe that the proposed research will provide a novel and effective means of controlling plague in prairie dogs and black-footed ferrets. Plague is maintained primarily in rodent populations, where it is typically transmitted via the • bite of an infected flea Fleas of the genera Opisocrostis and Dropsy/la have been associated with plague transmission in prairie dogs (Ubico et al., 1988). Insecticide dusts have been applied to prairie dogs burrows in an attempt to kill fleas and thus control plague. Carbaryl has been the most commonly used insecticide; however, application is labor intensive and activity is short-lived (Barnes, 1993). Permethrin has been shown effective up to 84 days after· application (Beard et al., 1992), but the authors warn that application at the recommended dosage rate would be highly laborious. Recently developed compounds used to control fleas in pet animals offer a promising alternative to insecticide dusts. Although topically applied flea adulticides, such as imidacloprid, are not feasible for use in wildlife, insect growth regulators (IGRs) with ovicidal and/or larvicidal activity could be delivered orally to free-ranging animals via bait. The IGR lufenuron is a benzoylphenylurea derivative which inhibits formation of chitin in the exoskeleton of insects (Cohen, 1987). A single oral dose oflufenuron has been shown effective in controlling the cat flea (Ctenocephalidesfelisfelis) for at least 30 days in treated cats (Blagburn et al., I 994) and dogs (Hink et al., 1994). Davis (1997) reported a significant reduction in fleas on free-ranging ground squirrels (Spermophi/us beecheyi) that had been treated with lufenuron. Iflufenuron proves efficacious over a long period of time~ I mo) when administered orally to prairie dogs, it could be applied over large areas of prairie dog habitat via a treated bait. Prior to management application, lufenuron should be evaluated in a controlled laboratory setting to determine an effective dose, duration of efficacy, product safety, and to formulate an acceptable bait carrier. If results of laboratory tests are positive, lufenuron should be tested in a controlled field study to determine efficacy under natural conditions. Without this evaluation, the management potential ofIGRs for controlling plague and protecting the health of the endangered blackfooted ferret, as well as human health, will be difficult to discern. We have proposed studies to test the efficacy oflufenuron for controlling fleas on artificiallyinfested captive white-tailed prairie dogs (Cynomys leucurns; Wild and Castle, 1998); however, laboratory rearing of fleas has proven difficult thus far. Further, because Dropsy/la and Dpistocrostis fleas are most readily collected in spring and early summer, our lufenuron-efficacy work is limited to the summer months. As an alternative, preliminary, means oflufenuron evaluation, we will conduct a bioavailability study oflufenuron administered orally to captive white-tailed prairie dogs. Prescribed oral doses of lufenuron for domestic cats and dogs are 30 mg/kg and IO mg/kg body weight, respectively. The concentration oflufenuron in blood of protected animals is somewhat variable, but protection seems to be conferred to dogs and cats when blood levels reach at least 50-100 parts per billion (B. Blagburn, pers. comm.). No data are available regarding the bioavailability of ingested lufenuron in any wild rodent species; however, assay results are pending from a recent pilot study (Castle and Wild, 1998). Based on results from this pilot study and assuming 100 ppb as the efficacious blood level, we will determine the test dose for this experiment. Although the correlation between blood levels oflufenuron and efficacy of flea control in prairie dogs will need to be determined in future experiments, this preliminary work will provide insights into: 1) between-animal variability �74 and 2) features of the decay curve oflufenu~on (e.g. peak concentration and duration oflevels over 100 ppb) in the blood of prairie dogs. Because white-tailed prairie dogs are spontaneous, obligate hibernators, they exhibit marked changes in activity and physiologic function seasonally (Harlow, 1997). These activity and physiologic changes may influence lufenuron bioavailability. Throughout much of their range, adult white-tailed prairie dogs enter hibernation in August or early September, and juveniles begin hibernation in late September or early October. Before hibernating, they store large amounts of body fat, to provide energy during their winter-long fast (Harlow, 1997). It is possible that as fat is mobilized during hibernation and upon arousal, lipid-soluble materials that were ingested and stored during late summer and fall may also be mobilized. Because lufenuron is highly lipid-soluble (Blagburn et al., 1994), white-tailed prairie dogs fed treated bait prior to hibernation could potentially store the compound over . winter, and therefore be protected during winter and when they arouse in spring. If prairie dogs were thus protected, flea population increases could be pre-empted, and management of plague outbreaks would be enhanced. To test this hypothesis, we will compare blood lufenuron levels in active vs torpid prairie dogs in a controlled laboratory setting. To summarize, the objective of this study is to determine the serum profile oflufenuron during active and torpid periods in orally-dosed white-tailed prairie dogs. These data will be used in the design of future experiments to evaluate lufenuron in captive and free-ranging prairie dogs, and will provide insights on the between-animal and seasonal variation that is to be expected. When combined with efficacy information, blood assay for lufenuron would provide a useful tool for evaluating lufenuron treatment programs involving free-ranging animals. Methods Care and housing ofprairie dog All captive prairie dogs will be pair-housed in cages under the same conditions described in Castle and Wild, 1998. Prairie dog cages (46 x 91 x 46 cm) are constructed of wood and wire fencing. Half of the cage serves as a nest box, and the other half serves as a feeding area Two hinged doors allow access to each half of the cage for cleaning or animal handling. The nest box is a 40 x 28 x 23 cm plastic container· fitted with a wooden lid. The nest box has a 10 cm diameter hole in one wall to provide access to the feeding area; a 10 cm diameter piece of PVC pipe joins the nest b.ox to the feeding area The access hole can be covered to confine the animals to either side of the cage as necessary. Our preliminary work shows that defecation and urination in the nest box are minimal, so we do not expect the nest boxes to become soiled during experiments. The floor of the feeding area consists of 1cm mesh wire fencing to allow feces, urine, and spilled food to fall through to a newspaper-lined metal pan below. This mesh size prevents the animal's feet from becoming wedged in the floor, but may encourage the animal to spend most of its time in the nest box when not feeding. Newspaper in the metal pan will be changed daily if soiling occurs. Food (Teklad Rodent Blocks) will be provided ad libitum except as noted below. Water will be available at all times. Prairie dog cages will be kept in two similar buildings. Temperature in each building is thermostatically controlled, and artificial lighting is controlled with timers. Health and attitude of prairie dogs will be assessed daily during the experimental period. Body weight will be measured at 1-2 week intervals while each animal is anesthetized for blood collection. �75 Experimental Design Thirty captive white-tailed prairie_ dogs (16 males and 14 females) less than one year old will be blocked by sex and randomly divided into two treatment groups (n = 13 each) and two control groups (n = 2 each). Treatment group 1 and one control group (active-group animals) will be housed in a building under conditions that inhibit hibernation (14L: 1OD photoperiod plus natural lighting through windows, ambient temperatures above 15 °C). Treatment group 2 and a second control group (torpid-group animals) will be housed in a second building under conditions that promote hibernation (1 0L: 14D photoperiod, ambient temperature of 5-6 °C). Intermittent fasting of up to 2 d per 7 d period will also be used in some individuals to promote hibernation if temperature and photoperiod changes prove insufficient. Our goal is to expose the two groups to the most extreme conditions known to inhibit or promote torpor. We do not expect food deprivation to harm the torpid-group animals, because food intake between torpor bouts is minimal (Harlow, 1997). We have determined that these experimental conditions allow us to inhibit or promote hibernation in a majority of our white-tailed prairie dogs; however, despite our efforts, some animals housed under hibernation-promoting conditions remain active, while some housed under hibernationinhibiting conditions become torpid. We will therefore assess each animal daily, and record its activity level. Active-group prairie dogs that become torpid will be aroused by gentle shaking and rubbing; torpid-group animals that remain active will not be disturbed. We will assess the duration of torpor in torpid-group animals by placing a small amount of sawdust on the back of each torpid individual; the presence of sawdust on the back at subsequent checks will be interpreted to mean that the individual was torpid the entire period (Harlow, 1997). Dosing Methods Prairie dogs will be fasted for 24 h, then weighed prior to dosing; water will be available during the fast. After the fasting period, each individual in a cage will be confined to one-half of the cage by blocking off the nest box access hole, and temporarily removing the nest box. Each animal in treatment groups 1 and 2 will be fed a bolus dose of lufenuron (20-300 mg/kg dose, pending pilot trial results) mixed thoroughly in a highly palatable bait (ground rat chow and molasses). Control animals will receive the bait only. The bait will be offered in each animal's feeding dish. We previously determined that fasted prairie dogs consume up to 2 g of such a bait within about 30 min, and will consume up to 13 gin less than 12 h. We will observe the progress of bait ingestion in each animal to determine when the dose is ingested. We will weigh the bait/lufenuron mixture before and after the prairie dogs are dosed, in order to calculate the actual dose ingested. After both animals in a cage have consumed their dose, the nest box will be returned and they will again be pair-housed. Blood Collection We will collect 3 ml of blood from each prairie dog prior to lufenuron dosing, one week after dosing, then at 2 week intervals through week 9 post-dosing, or until torpor bouts are no longer observed. Anesthesia is required for blood collection. We have determined that prairie dogs respond very well to isoflurane anesthesia. Induction and recovery are quick (approximately 3-5 min for each), and we have detected no adverse effects. All prairie dogs will be aroused from torpor prior to anesthesia, in order to assure sufficient blood pressure for blood collection. Prairie dogs_will be placed into a plastic chamber for induction at a concentration of 4% isoflurane in oxygen, then anesthesia will be maintained via mask at about 2-2.5% isoflurane. Heart rate and respiration will be monitored during anesthesia. Blood will be collected by jugular venipuncture and placed into a glass vacutainer blood tube (without anticoagulant). Alternatively, if we are unable to collect an adequate blood sample �76 peripherally, we will collect blood from the vena cava or directly from the heart. Although cardiac puncture is considered to be a safe procedure for collection oflarge volumes of blood from laboratory rodents (CCAC, 1984), due to the increased risks involved with cardiac puncture (5-10% mortality expected; J. Wimsatt, pers. comm.), we will use this technique only to obtain critical samples. Serum will be harvested and frozen within 4 h of collection. Serum lufenuron concentration will be determined by HPLC at Novartis Laboratories. Product safety Based on mode of action, chitin inhibitors should be safe in mammals, even at very high doses (Blagbum et al., 1995; T. Miller, pers. comm.). Cats have been fed more than 5 times the prescribed dose oflufenuron without showing adverse side effects (B. Blagburn, pers. comm.). The high dose to which our prairie dogs may be exposed (300 mg/kg) is based upon our estimate of the maximum amount of bait a prairie dog might eat in a day in the field (40-60 g) and a reasonable lufenuron concentration in the bait (5 mg/g). We did not detect adverse effects from lufenuron administration during our pilot study, when 3 prairie dogs received doses of20-300 mg/kg. We do not anticipate any prairie dog mortality due to the dosing regime or blood collection. However, if an animal becomes sick or injured, and recovery is not likely, it will be euthanized with an overdose of inhalant anesthetic. A complete post-mortem examination will be performed on any animal that may die during the experimental period. Data Analysis We will compare lufenuron blood concentrations of the torpid- and active-group prairie dogs over time by conducting a profile analysis of the lufenuron decay curves. In addition, we will use analysis of covariance to compare: 1) peak concentrations obtained in each group, and 2) the duration of concentrations above 100 ppb in each group. The number of days an animal was observed to be active will serve as the covariate in our analyses. Group responses will be considered significantly different at p 0.05. Literature Cited Barnes, A. M. 1993. A review of plague and its relevance to prairie dog populations and the blackfooted ferret. Proceedings of the symposium on the management of prairie dog complexes for the reintroduction of the black-footed ferret. J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R Crete, eds. 96pp-. • Beard, M. L., S. T. Rose, A. M. Barnes, and J. A. Montenieri. 1992. Control of Oropsylla hirsuta, a plague vector, by treatment of prairie dog burrows with 0.5% permethrin dust. Journal of Medical Entomology 29:25-29. Blagbum, B. L., J. L. Vaughan, D.S. Lindsay, and G. L. Tebbitt. 1994. Efficacy dosage titration of lufenuron against developmental stages of fleas (Ctenocephalidesfelisfelis) in cats. American Journal of Veterinary Research 55:98-101. Blagburn, B. L., C. M. Hendrix, J. L. Vaughan, D. S. Lindsay, and S. H. Barnett. 1995. Efficacy of lufenuron against developmental stages of fleas (Ctenocephalidesfelisfelis) in dogs housed in simulated home environments. American Journal of Veterinary Research 56:464-467. Castle, K. T. and M. A. Wild. 1998. Safety and efficacy of pyriproxifen and lufenuron for the control of prairie dog fleas: a pilot study. Colorado Division of Wildlife Animal Care and Use Committee Study Plan. Canadian Council on Animal Care (CCAC). 1984. Guide to the care and use of experimental animals, Vol. 2. Ottawa, Ont., Canada �77 Cohen, E. 1987. Interference with chitin biosynthesis in insects. In Chitin and benzoylphenyl ureas, series entomologica, vol. 38, J.E. Wright and A. Retnakaran (eds), Dr. W. Junk, Publishers, Boston, pp.33-42. Davis, R. M. 1997. Use of an orally administered insect development inhibitor (lufenuron) as a flea control agent in the California ground squirrel, Spermophilus beecheyi. Fourth International Symposium on Ectoparasites of Pets, pp. 31-35. Harlow, H. J. 1997. Winter body fat, food consumption, and nonshivering thermogenesis of representative spontaneous and facultative hibernators: the white-tailed prairie dog and blacktailed prairie dog. Journal of Thermal Biology 22:21-30. Hink, W. F., M. Zakson, and S. Barnett. 1994. Evaluation of a single oral dose of Iufenuron to control flea infestations in dogs. American Journal of Veterinary Research 55:822-824. Ubico, S. R, G. 0. Maupin, K. A. Fagerstone, and R. G. McLean. 1988. A plague epizootic in the white-tailed prairie dogs (Cynomys leucurus) of Meeteetse, Wyoming. Journal of Wildlife Diseases 24:399-406. Williams, E. S.; K. Mills, D. R Kwiatkowski, E.T. Thome, and A. Boerger-Fields. 1994. Plague in a black-footed ferret (Mustela nigripes). Journal of Wildlife Diseases 30:581-585. Wild, M. A. and K. T. Castle 1998. Monitoring and managing disease in black-footed ferrets. Colorado Division of Wildlife Program Narrative, Project# W-153-R RESULTS AND DISCUSSION Carnivore Disease Survey With the assistance of USDA Wildlife Services and the Bureau of Land Management (BLM) we collected 19 coyotes and 4 badgers from the LSMA between 27-30 July 1998 and 20 coyotes between 11-12 February 1999. Coyotes were collected using a combination of calling and aerial gunning. Death occurred rapidly and the collection technique was adequate, but much less efficient in summer than in the winter months. Coyotes were collected from various locations in the >4 700 mi 2 management area; however, we focused on the Powderwash area and near the site of the preconditioning pens. No lesions indicative of active disease were noted on gross examination of carcasses. We found no serologic evidence of exposure to leptospirosis serovars canicola, grippo, hardjo, and pomona; however, low positive titers to serovar ictero were found in nine coyotes (five in July and four in February). No serologic titers to toxoplasmosis were found. Coyotes were not tested for Aleutian Disease (a mustelid disease), but all four badgers were sei-onegative for the disease. All badgers and 20% of coyotes sampled during the summer had positive titers to tularemia, while 10% of the coyotes sampled in winter were positive. Positive titers could have been associated with predation on rabbits, prairie dogs, or other rodents or exposure to ectoparasites. Duration of titers to tularemia are likely of short duration (<6 mo). The impact of tularemia or leptospirosis on black-footed ferrets is not currently known; however, ferrets and humans are susceptible to these diseases. Canine distemper virus (CDV) and plague are serious threats to survival of black-footed ferrets. The prevalence of coyotes with serological titers to CDV was .:S,10%; markedly lower than in previous years (Fig. 1). However, plague activity continues in LSMA as evidenced by titers in sampled coyotes (Fig. 2). Black-footed Ferret Reintroduction Nineteen black-footed ferrets (8 adult females, 5 juvenile females, 6 juvenile males) were received from the National Black-footed Ferret Conservation Center in November 1998 and placed in breeding pens at LSMA. Seventeen ferrets remained in good health with minimal health treatment �78 required. One adult female ferret died of a biliary adenocarcinoma and one juvenile female is missing and presumed dead. Ten female ferrets were paired with males and five of these gave birth. One litter was apparently consumed by the female when <l day of age. Toe· other four litters yielded 13 pups. Artificial Rearing of Dropsy/la fleas Although fleas had been abundant in the spring of 1998, in July fleas seemed to disappear from the field. Burrow swabs consistently returned 0, 1, or 2 fleas per burrow. Because most burrows had no fleas, the ratio of fleas/burrow dropped to less than 0.5. The cause of decline is unclear. One possibility is that because many burrows were filled in by prairie dogs escaping the summer heat, the nest areas that house a majority of fleas were no longer accessible from the surface. It is also possible that the flea populations experienced a real decrease during the summer, and that decrease was reflected in swabbing success. Our attempts to artificially rear Oropsylla fleas during summer 1998 met with limited success. We had successful completion of the life cycle within our rearing jars, but only about 4 adult fleas were produced from eggs laid in captivity. Our overall success was limited by low flea survival during transport to the lab, and the relatively low numbers of fleas available for collection in late summer when our facilities were readied for use (virtually no fleas were available in the field after 30 June). By the end of October 1998, no fleas were alive in our insectary. We resumed field collections of fleas on 5 April 1999, when snow cover had receded and prairie dog burrows were open. We inade five more trips to the field through the middle of May. A total of 1645 fleas (906 of these 0. tuberculata) were collected. We successfully increased flea survival during transport from the field to the lab by keeping fleas under cooler and more humid conditions. Most fleas collected were alive when they arrived at the lab. Unfortunately, adult flea mortality in the insectary was high, despite our attempts to keep the fleas well-fed and under optimal temperature and humidity conditions. Reproduction within the insectary was therefore limited. We collected 8 larva from the insectary jars, and placed them into a separate dish containing rearing media; none of the larva pupated. Attempts to produce self-sustaining populations of 0. tuberculata on prairie dogs were also disappointing. While a few fleas survived for 21-24 days on the prairie dogs, it became clear that selfsustaining populations were not possible under our conditions. Our lack of success was most likely due to our inability to properly mimic natural burrow conditions required by fleas (constant temperature and high humidity). We attempted to simulate burrow conditions by attaching insulation to each nest box (to maintain temperature), and by placing a screen-covered petri dish of moist vermiculite into the flea refuge (to increase humidity). We were able to keep temperatures fairly stable, but were not able to maintain high relative humidity within the nest boxes. Survival and reproduction of 0. montana in the insectary has been high. We will use 0. montana in future experiments investigating flea control in captive prairie dogs. Flea Control In Prairie Dogs In the pilot study we observed no adverse affects with any of the lufenuron dosages. Previous researchers have shown lufenuron to be efficacious for controlling fleas in cats and dogs when serum concentration is 50-100 parts per billion (ppb) (C. Parks, Pers. comm.). Our results indicate that, as expected, baseline samples contained no lufenuron, but that one day after dosing, blood concentration was at or above efficacious levels at all treatment levels. After one week, blood concentrations had decreased considerably; serum concentration in the animals dosed with 20 mg/kg and 60 mg/kg had fallen below the efficacious level, while the concentration in the animal fed 300 mg/kg remained well above the efficacious level at 220 ppb. Analyses of remaining blood samples are pending. �79 In January 1999, we performed the experiment titled "Bioavailability oflufenuron administered orally to captive white-tailed prairie dogs". All prairie dogs except for two non-torpid group animals ingested >95% of their bait within 18 h; all remaining bait was removed and weighed after 18 h. We observed all prairie dogs twice daily (8:00 am. and 4:00 p.m.) during the experiment for overall health and to quantify length of torpor bouts. Animals that were torpid for two consecutive observations were considered to have been torpid the entire time between observations, unless a small amount of sawdust placed on the back of torpid animals had been displaced. Animals that were torpid at one observation time then awake the next were considered to have awakened at the midway point between observations. Torpid-group animals found hibernating were allowed to remain torpid, while non-torpid group animals were awakened if found hibernating. All torpid animals were awakened prior to anesthesia and blood collection. The duration of the study was 1512 hours; torpid group animals were torpid for an average of 406 h (range= 0 - 936 h), while non-torpid group animals averaged 7.5 h torpid (range= 0 - 36 h). We detected no detrimental effects of lufenuron in any prairie dog, nor were any animals harmed by repeated anesthesia and blood collections. HPLC analysis for blood lufenuron concentrations is pending. LITERATURE CITED Hink, W. F., M. Zakson, and S. Barnett. 1994. Evaluation of a single oral dose oflufenuron to control flea infestations in dogs. Am. J. Vet. Res. 55:822-824. Palma, K. G., S. M. Meola, and R W. Meola 1993. Mode of action of pyriproxifen and methoprene on eggs ofCtenocephalides felis. J. Med. Entomol. 30:421-426. Wild, M. A 1998. Monitoring and managing disease in black-footed ferrets. Colorado Div. Wildl. Res. Rep., 0880-1, Jul 1997 -Jun 1998, Fort Collins. Wild, M. A 1999. Animal and pen support services for mammals research. Colorado Div. Wildl. Res. Rep., 8160-1, Jul 1998 - Jun 1999, Fort Collins. 25 20 uQ,) ~ 15 ro U) 'Q,) ..o 10 E ~ z 5 . . . .. . . . 1997-W ...... 1997-S 1998-W ■ •• 1998-S 1999-W Sample period 8 CDV positive □ CDV negative I Fig. 1. Prevalence of exposure to canine distemper virus (CDV) in coyotes from the Little Snake Management Area, Colorado, from winter 1997 through winter 1999. All positive coyotes were adults with the exception of one juvenile in summer 1998. Data from winter 1997 (age class unknown) provided by M. Albee. �80 A 20 15 .... Q) e 10 ::J z 5 0+-------~1997-W 1997-S 1998-W 1998-S 1999-W Sampling period B 20 15 .... e 10 Q) :::, z 5 1997-W 1997-S 1998-W 1998-S 1999-W Sampling period I mPlague-Pos £3 Plague-Neg I Fig. 2. Prevalence of exposure to plague in coyotes (A= juveniles~ B = adults) from the Little Snake Management Area, Colorado, from winter 1997 through winter 1999. Data from winter 1997 (age class unknown) provided by M. Albee. �81 ATIACHMENT I HUSBANDRY PROTOCOL FOR CARE OF CAPTIVE BLACK-FOOTED FERRETS AT THE LIITLE SNAKE MANAGEMENT AREA Pen Construction Breeding pens will be constructed over established prairie dogs towns. If an active prairie dog colony is not present, prairie dogs from plague-free areas will be reintroduced to the pen site prior to construction. Individual pens will be about 1500-5000 ft2 and constructed in clusters of four (four-plex design). Generally, females will be housed in three of the pens and a male in the fourth pen. Each pen will contain a vault capable of holding a buried insulated wooden nest box (about 12" x 20" x 16"), which will be covered with a roof to provide shade and to keep runoff away from the nest box. In the females' pens, the vault will be contained a sub-enclosure, or whelping pen, about 100 ft2 in size. A perimeter fence will be constructed around each four-plex or group offour-plexes. Tubing and traps will be placed at intervals along the fence to protect and capture potential escapees. Additionally, prior to initial introduction of breeding-age ferrets, the burrows will be checked using a "smoke test" and then radio-collared ferrets will be placed in the pens to further check pen sec~ty: Site Security Breeding pens will be located in a remote area with access limited to authorized personnel. Visitors will be allowed only on a limited basis and when accompanied ~y-site personnel. Human activity near the pens will be limited strictly to ferret husbandry and management practices. No_dogs will be allowed in the pen area Use of motorized vehicles in the pen ar~a, will be minimized. The perimeter fence will serve to contain escaped ferrets and as a deterrent to entrance of wild and feral carnivores; however, other means of carnivore control (nonlethal and lethal) may be necessary to protect ferrets. Biosafety protocols will include the use of site specific coveralls and boots by personnel handling ferrets or entering ferret pens. Treatment of shoe soles with a bacteriocidal/virucidal solution (e.g., Roccal-D) may substitute for designated footwear. Personnel will not enter ferret pens or handle ferrets if they are experiencing flu symptoms (fever, chills, body aches, respiratory signs); caretakers with cold symptoms should wear a mask and gloves when working around ferrets. Ideally, caretakers should receive flu shots annually. Only prairie dogs from the immediate vicinity of the pen site or those completing quarantine-will be provided to ferrets. Personnel will not handle carnivores or prairie dogs ( except those completing the quarantine period) during the work day prior to entering the pen site unless they shower and change clothes. Pets of site personnel should be vaccinated annually against canine distemper. General Husbandry Ferrets will be checked daily at dawn or dusk by trained caretakers. Caretakers should minimize contact with ferrets, but should observe ferrets directly or with binoculars to assess health status daily. Abnormalities will be noted in animal records and, if necessary, the attending veterinarian notified. If a ferret is not observed (directly or via sign, e.g., consumed food) for 3 consecutive days, a trap (attached to a nest box via tubing) will be placed in the pen. Traps will be checked at intervals appropriate to assure that the ferret is not adversely affected by temperature, weather, or restraint time �82 (generally, every 2-6 hr). Trapped ferrets will be weighed and examined grossly. Additional examination and treatment will be administered if necessary under the direction of the attending veterinarian. Body weights will be obtained monthly (and anytime the ferret is handled for other reasons) to monitor health status and to evaluate feeding programs. Ferrets will be trapped, weighed, briefly examined, and released qack to the pen. Transponder function will be checked at least once monthly and transponders will be replaced (with the ferret under anesthesia) if needed. Nest boxes will be provided only during periods when the ferret is confined to the whelping cage, e.g .. , the breeding and whelping period or during required confinement to prevent escape or enhance treatment. Nest boxes will be cleaned every other day ( excepting during breeding period when male and female are housed together and immediately prior to and following parturition) using pen-specific instruments, bedding, and trash can when kits are present or if a contagious disease is suspected. Wood shavings (not cedar) will be placed about 3-4 inches deep on one side of the nest box and about l inch deep of al phi-dry will be placed on the other side. A minimum-maximum thermometer will be placed on the roof of one nest box in each four-plex. Temperatures will be checked during nest box cleaning or daily during periods of extreme weather. Modifications to the nest box insulation may be needed if temperatures in the nest box are extreme. Maintenance diet will include live prairie dogs supplemented with frozen prairie dog and rabbit carcasses, hamsters, and dry ferret food (Totally Ferret). Dry ferret food will be used only a supplement if insufficient supplies of prairie dogs are available as food. Dry ferret food will not be provided as a sole feed source, but as a supplement to the meat diet. Prairie dogs will be collected, quarantined, and processed as described in the protocol by Marinari and Williams (1998). Rabbits will be procured from breeders and processed as prairie dogs; however, additionally the head and kidneys will be removed. Dry feed will be stored in rodent-proof containers prior to feeding. Whenever possible, live prairie dogs will be provided to ferrets; however, we will avoid offering large, aggressive prairie dogs and any prairie dog surviving > 3 days will be trapped and removed from the ferret pen. These prairie dogs will be euthanized and fed as meat. Female ferrets will be provided with. an average of 100 g feed/day and males will receive 125 g feed/d; however, ferrets may not be provided fresh feed daily (e.g., if a 500 g prairie dog is provided). Amount of feed provided to individuals will vary based on assessment of physical condition. Frozen prairie dogs will be thawed about 48 hr in a refrigerator prior to feeding. Feed may at times be provided in a trap (with the doors wired open) for training purposes. Unconsumed meat left in the pen will be discarded after 24 hr. Water will be injected into prairie dog carcasses during the winter or when available water is minimal. A water source will be provided, but may be frozen during the winter. If snow cover is not present, fresh water will be provided daily. Waterers will be cleaned weekly or more frequently if needed. Records will be maintained to document feed offered and estimate feed consumed by ferrets in each pen. During gestation, whelping, and lactation, modifications of the maintenance diet will be required. About 2 wk following breeding, feed will be increased 1.33 times the base diet. About 4 wk following breeding, feed will be increased to I .66 times the base diet. From whelping to weaning, feed will be offered ad libitum. Ideally, only live prairie dogs and hamsters should be offered, but if unfeasible, ferrets will be supplemented with prairie dog or rabbit meat or dry feed initially, then when kits begin to kill prey, only live prairie dogs (about 150 g/ferret) will be offered until release. as Breeding Management Adult males and females will be housed in separate pens except during the breeding period. The breeding period will vary annually based on weather, so multiple handling of ferrets may be required to assess reproductive status. Beginning about 1 February, or when signs of breeding behavior are noted (increased digging, marking, etc), males will be trapped weekly for breeding �83 soundness examination. With ferrets restrained in handling cages, the testes will be measured (width, depth) and tested for firmness. After testes are firm for 1 mo, males will be considered ready for breeding. When males are showing signs of reproductive activity (testes firm and about >20 mm width or depth), females will be trapped for signs of estrous. The females will be restrained in a handling cage and the vulva measured. If the vulva is small (<2 mm x 3 mm), the female will be trapped and measured again in about 7 days. If the vulva is beginning to swell, the female will be handled again at 3 day intervals to monitor the trend in change of the vulva Vaginal cytology may be used when the vulva shows a trend toward increasing size (generally to about 4 x 7 mm). When vaginal cytology indicates >90% comified cells, we will wait 5 days, then introduce the male to the females whelping pen (male and female will be restricted to whelping pen). The male and female will be monitored remotely using a pen camera or by watching from a distance and listening for vocalizations to determine compatibility and breeding activity. Breeding activity is assumed if chuckling is heard, copulation observed, and/or a neck stain is present on the female. In this case, the male will be removed 3 days after introduction. Function of the females transponder will be checked after copulation and replaced if necessary. If breeding activity is not observed, the male may be left with the female up to 7 days; however, if the male and female show no interest in one another (in separate areas of pen, no neck stain), the male may be removed after 24 hr and a new male introduced 1-2 days later. The male will be removed immediately if it shows aggressive behavior that threatens the female. Males will be given 3-4 days rest after each breeding. A male may be brought from a separate fourplex to breed a female if the resident male is incompatible or unavailable. The female will be trapped 7-10 days following suspected breeding for vaginal cytology. If cells remain highly cornified, breeding likely did not occur and the female will be re-paired. Records will be kept on results of breeding soundness exams, vaginal cytology, pairings, and breedings. The female will be restricted to the whelping area beginning 35 days post-breeding. A waterer will be placed in the whelping area and bedding material placed in the nest box. Vitamin K will be supplemented to the females diet at the rate of 5 drops/day from 5 days_prior to whelping to day 35 following whelping. On day 42 post-breeding, we will begin listening daily for sound from the nest box. If sounds are heard, the animals will be left undisturbed for 5 days. On day 5, the nest box will be cleaned using pen-specific bedding, instruments, and trash can. The nest box will be cleaned again on day 10 and the door to the whelping area opened. The nest box will be cleaned at 2 day intervals until the female moves the kits from the nest box. Prairie dogs and hamsters will be the only feed offered until kit release. If females do not whelp a second breeding will be attempted. About 10 days following the calculated whelping date we will again begin monitoring vaginal cytology. When 90% cornified cells are present, a male will be paired with the female as described previously. Kits will be trapped on day 90 for physical examination, marking with transponders, and vaccination against canine distemper virus (if vaccine available). Kits will be trapped subsequently for booster vaccines if needed. Care of Sick Animals Health status of ferrets will be checked daily (or as possible). Healthy ferrets should be active, consume feed, have a clean haircoat, and be free of physical abnormalities (lameness, cuts, swellings, etc.). The pen floor should also be examined for abnormal feces, blood (not from prey item), vo,mit, etc. Any abnormalities will be noted on the daily observation forms and the attending veterinarian notified. If there is any likelihood that the condition could be contagious, the caretaker will disinfect their hands and boots and ideally change coveralls before proceeding to other pens. If an animal is known to be sick, that animal will be cared for last (or by an alternative caretaker) using good sanitation techniques and any equipment used in the pen will be disinfected. Sick animals may be �84 confined to the nest box and whelping pen to aid in care and treatment. Alternatively, critically ill animals may be placed indoors in quarantine for treatment. If coccidiosis is suspected (lack of appetite, mustard-like feces) and the attending veterinarian cannot be reached, treatment can be initiated using 50 mg/kg Albon orally on day 1 followed by 25 mg/kg Albon orally daily for about 7 days. Fresh water must be available at all times when animals are treated with Albon (parenteral fluid therapy may be needed as well). Specimens (feces, discharges) should be obtained opportunistically if possible (using good sanitation practices) and placed in a whirlpack and refrigerated until further instructions are obtained. If a ferret is found dead, it should be double or triple bagged (e.g., in a ziplock or trash bag), labeled with animal ID, pen, and date and refrigerated. The carcass will be boxed in a cooler and submitted via overnight Federal Express to Dr. Beth Williams, Wyoming State Veterinary Laboratory for necropsy. The facility supervisor, attending veterinarian, and BFFCC should be notified for further instructions. Prairie dogs found sick or dead in the pen area should also be collected and submitted for necropsy. Caretakers should wear gloves and practice good sanitation measures whenever dealing with sick or dead animals. Release We will attempt to maintain 20 breeding animals of various ages: ideally, 5 female and 1 male I-year-olds, 5 female and 2 male 2-year-olds, 5 female and 1 male 3-year-old, and 1 male 4-year-old. Animals will be redistributed to pens each fall to maximize diversity in breeding pairs. Older adults and excess young of the y~ar will be released each fall when young are about 20 weeks of age. Prior to release, all ferrets will be fitted with radiocollars. �115 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB PROGRESS REPORT State of ----~~=~-----Colorado Project No. W-153-R-13 Mammals Research Work Package No. ___ 0_88_0_ _ _ _ _ __ Task No. 1 Black-footed Ferret Recovery Monitoring and Managing Disease in Black-footed Ferrets Period Covered: July. 1, 1999 - June 30, 2000. Authors: M.A. Wild and K. T. Castle Personnel: E. Wheeler, E. Schmal, and S. Kasven. \ ) ABSTRACT \ ) The black-footed ferret is a federally listed endangered species in the United States. Black-footed ferrets have been extirpated from Colorado, but were scheduled to be reintroduced to Moffat County, Colorado in 1999. However, due to high plague activity and low prairie dog densities at the Little Snake Management Area (LSMA), black-footed ferret reintroduction was postponed indefinitely at the site. The secondary site at Coyote Basin, Utah was readied and reintroduction of ferrets was performed there in 1999. The Wolf Creek site in Moffat County, Colorado is also being readied for reintroduction of ferrets, likely in 2001. Our work in support of black-footed ferret reintroduction can be sub-divided into three broad sections: disease monitoring in the proposed release areas in Colorado, care of black-footed ferrets, and flea control as a tool to manage sylvatic plague in prairie dogs and black-footed ferrets. Disease monitoring was performed using collection of coyotes from LSMA in July 1999 and from the Wolf Creek site in February 2000. Two potentially devastating diseases, canine distemper and plague, are present at LSMA. Although prevalence of positive titers to canine distemper virus (CDV) in coyotes ·have been relatively low over the last 3 years (:S33%), the prevalence of positive titers to plague (Yersina pestis) have been high (up to 89% positive). Titers were present in both adult and juvenile animals, suggesting ongoing plague activity in at least some sections of the management area. Samples collected from coyotes at the Wolf Creek site indicated substantially lower disease activity than at LSMA. Prevalence of positive titers to plague and to CDV was 7% of samples collected in February 2000. In general, captive black-footed ferrets maintained at the LSMA breeding and preconditioning pens remained healthy. One ferret died and another was presumed dead in the burrow system after a severe hailstorm. Of 13 kits born at the pens in spring 1999, 12 survived to weaning in fall 1999. These 12 kits in addition to 50 other black-footed ferrets were released at the Coyote Basin site in fall 1999. Twenty ferrets were maintained in the pens overwinter and produced 11 kits in spring 2000. We summarized research results and presented a paper titled "Dose titration and safety of lufenuron fed to captive white-tailed prairie dogs (Cynomys leucurus)" at the 2000 meeting of the �116 Wildlife Disease Association, Jackson, Wyoming. We also performed a trial to test' the efficacy of lufenuron in controlling fleas on captive prairie dogs. One week post-dosing, fleas that fed on prairie dog treated with 500 mg/kg lufenuron prcxiuced a lower proportion (p < 0.05) of viable rggs than those fed on control prairie dogs (mean 0.16 vs. 0.39, respectively). However, the proportion of viable eggs prcxiuced during week 2 post-dosing was low for each group (0.24 treatment vs. 0.17 control). By week 4 postdosing, egg prcxiuction had fallen to nearly zero in each group; however, the three eggs produced by fleas fed on treated prairie dogs were all viable. Although further, similarly controlled investigation is warranted, preliminary results suggest that given current techniques, the likelihood of lufenuron limiting fleas populations and breaking the plague cycle is not extremely promising. �117 MONITORING AND MANAGING DISEASE IN BLACK-FOOTED FERRETS Margaret A. Wild and Kevin T. Castle P. N. OBJECTIVES 1. Monitor disease activity threatening survival of black-footed ferrets reintroduced into the Little Snake Management Area (LSMA). 2. Develop techniques to manage plague in the LSMA using insect growth regulators applied orally to prairie dogs. SEGMENT OBJECTIVES 1. Provide ;ete~ care to captive and reintroduced black-footed ferrets. 2. Monitor and manage plague activity in LSMA. METHODS AND MATERIALS Carnivore Disease Survey Infectious diseases can severely impact the success of black-footed ferret (}Juste/a nigripes) reintroduction efforts. As part of the black-footed ferret reintroduction protocol, we monitored disease activity in carnivores at proposed ferret reintroduction sites: in July 1999 at the Little Snake Management Area (LSMA), Colorado and in February 2000 at the Wolf Creek Management Area (WCMA), Colorado. Coyotes (Canis latrans) were collected for post-mortem examination and samples collected as described in the Program Narrative (Wild and Castle 1998). Black-footed Ferret Reintroduction and Veterinary Care I assisted in preparation of the black-footed ferret allocation request submitted to the US Fish and Wildlife Service by the Colorado-Utah black-footed ferret recovery working team in 2000. I provided veterinary care and consultation on health matters for captive black-footed ferrets and black-footed ferret releases. Animal care was performed in accordance with the established protocol (Wild and Castle 1999). Flea Control In Prairie Dogs We completed the experiment "Bioavailability of lufenuron administered orally to captive white-tailed prairie dogs (Cynomys leucurus)" and performed a follow-up experiment "Efficacy of lufenuron for the control of fleas in white-tailed prairie dogs (Cynomy leucurus)". These studies were outlined in Wild and Castle 1998. The detailed study plan for the lufenuron bioavailability study and e:fp.cacy trial are reported in Wild and Castle 1999 and in Attachment 1, respectively. �118 RESULTS AND DISCUSSION Carnivore Disease Survey With the assistance of USDA Wildlife Services and the Bureau of Land Management (BLM) we collected 16 coyotes from the LSMA between 26-30 July 1999 and 14 coyotes from the Wolf Creek site on 8-9 February 2000. Coyotes were collected using a combination of calling and aerial gunning. Further collections were not possible due to weather constraints and aircraft availability. No lesions indicative of active disease were noted on gross examination of carcasses. Of the coyotes collected from the LSMA, 31 % (5/16) had positive titers to plague (Fig. I) using the standard HA/HI test while one additional coyote was positive using the ELISA test. Interestingly, all juveniles sampled this summer (n = 9) were negative to plague. Because the juvenile coyotes have consumed (sampled) prairie dogs from this summer only, lack of exposure may indicate that the prevalence of plague in prairie dogs in the area is declining. If this is the case, titers in adults would likely be from exposure in previous years. Alternatively, the prey base of the coyotes may have shifted to species that are less commonly infected with plague (e.g., rabbits) if the density of prairie dogs has been greatly reduced by plague. Forty-three percent of coyotes sampled (6/14 usable samples) had positive titers to tularemia. In contrast to plague, all positive titers to tularemia were observed in juvenile coyotes. As previously observed, tularemia appears to elicit a serologic response of short duration in coyotes. The impact of tularemia on black-footed ferrets and prairie dogs is unknown and warrants investigation. A titer to canine distemper virus (CDV) was found in only one of 14 serum samples tested (Fig. 2). Samples collected from coyotes at the Wolf Creek site indicate substantially lower disease activity than at LSMA. A 9-year-old male coyote had positive titers to plague and to CDV, but all other coyotes (n = 13) were negative to plague and CDV (7% positive; Fig. 3). The adult male and one additional juvenile coyote also had titers to tularemia (14% positive). Black-footed Ferret Reintroduction and Veterinary Care In general, captive black-footed ferrets maintained at LSMA remained healthy. One adult female was treated for an apparent mite infection and secondary bacterial pyoderma. Unfortunately, samples to confirm this diagnosis could not be collected prior to treatment; however, the ferret responded quickly and completely to therapy with ivermectin and amoxicillin. Additional cases of crusty skin have been successfully treated with ivermectin but confirmation of the etiology has not yet been made. A I-yr-old male was found dead and a 4-yr-old female was missing and presumed dead after a severe hailstorm. Necropsy results revealed death from blunt trauma. The death(s) occurred in the new pen complex where shallow burrow systems may have been flooded forcing ferrets to the surface in the severe weather. To avoid this problem in the future, additional above ground shelter will be provided. Of 13 kits born at the pens in spring 1999, 12 survived to weaning in fall 1999. One kit disappeared and is presumed dead in the burrow system. Based on results of carnivore disease monitoring over the past 3 years and prairie dog inventories performed in summer 1999, LSMA was determined to be currently unsuitable habitat for the release of black-footed ferrets. Prairie dog inventories performed by Utah Division of Wildlife showed insufficient densities of prairie dogs to support black-footed ferret reintroduction. As a result, ferrets were not released into LSMA but instead were released into Coyote Basin, Utah. Continued monitoring will determine when (if) LSMA can support reintroduction of black-footed ferrets. A secondary site in Colorado, (Wolf Creek) is also being readied for reintroduction of black-footed ferrets in fall 2000 or 2001. _ _, �119 The 12 kits produced onsite, in addition to three 1-yr-old males, and five 3-yr-old females from the LSMA pens were released at Coyote Basin in November 1999. Additionally, 19 kits and five 3-yr-old females from other captive breeding sites were pre-conditioned at the LSMA prior to release at Coyote Basin. The reintroduction was further supplemented with 28 ferrets released immediately upon arrival from other captive breeding sites without pre-conditioning at LSMA. Prior to release, ferrets were trapped for routine examination, treatment, and identification (Wild and Castle 1999) and a health certificate was issued for each individual. All appeared healthy except for the presence of ectoparasites (ticks, mites, fleas). Individual ferrets were treated with ivermectin and pen dusting was advised. In an attempt to meet our ideal age and sex structure of captive black-footed ferrets (Wild and Castle 1999), we retained seven ferrets and supplemented the population with 13 additional ferrets from other captive breeding facilities. Seven black-footed ferrets (five 1-yr-old females and two males) were retained in captivity at the LSMA pens. In November 1999, six adult females,'three female kits, and four male kits were added to this breeding group bringing the total number of ferrets at the LSMA pens to 20. Ferrets were maintained under the standard care protocol (Wild and Castle 1999). Females were paired with males in spring 2000, and four litters resulted. One litter was apparently consumed by the female when about 1 day of age. The other three litters yielded 11 kits. Flea Control In Prairie Dogs We presented results of the lufenuron dose titration study at the 2000 meeting of the Wildlife Disease Association, Jackson, Wyoming. The abstract of that presentation read: DOSE-TITRATION AND SAFETY OF LUFENURON FED TO CAPTIVE WHITE-TAILED PRAIRIE IX>GS (CYNOMYS LEUCURUS) KEVIN T. CASTLE Colorado Division of Wildlife, 317 W. Prospect St. Fort Collins, CO, 80521, MARGARET A. WILD, Colorado Division of Wildlife, 317 W. Prospect St. Fort Collins, CO, 80521, and S. CRAIG PARKS, Novartis Animal Health, P.O. Box 26402, Greensboro, NC 27404. Plague is a zoonotic disease that impacts populations of prairie dogs (Cynomys spp.) and other species, such as black-footed ferrets, that rely on them for food and shelter. Yerstnia pestis, the etiological agent of plague, is transmitted primarily by the bite of an infective flea. Recently developed compounds used to control fleas in pet animals offer a promising alternative to insecticide dusts for the control of fleas in wild rodents. Lufenuron is a lipid-soluble insect growth regulator with ovicidal and larvicidal activity. Lufenuron is efficacious for controlling fleas in cats and dogs at blood concentrations above 50-100 parts per billion (ppb). A single oral dose oflufenuron has been shown to be effective in controlling the cat flea (Ctenocephaltdes felts felts) for at least 30 days in treated cats and dogs. To date, there have been no studies conducted to detennine the duration oflufenuron blood concentrations in any prairie dog species. We compared lufenuron blood concentrations in white-tailed prairie dogs (C. leucurus) during periods of activity (nontorpid group) and hibernation (torpid group) during January-March 1999. We hypothesized that if high serum concentrations of lufenuron could be maintained over winter during hibernation or for > 1 mo in active prairie dogs, the compound may be effective for use in breaking the plague cycle. Thirty captive WTPD were fed 300 rrig/kg lufenuron; half the animals were allowed to become torpid, while the other half were kept awake. All animals remained healthy throughout the 9 week study period. Prairie dogs in the active group gained weight, while those in the torpid group lost weight over the 9 weeks. Blood was drawn from each animal prior to dosing, one week after dosing, then every other week until week 9 post-dosing. Serum was harvested and tested by HPLC for lufenuron concentration. Blood lufenuron concentration did not differ between the groups one week post-dosing. Concentration in both groups decreased over time, but the �120 concentration in torpid animals declined at a more gradual rate; after weeks 3, 5, and 7, lufenuron levels in torpid WfPD were significantly higher than levels in nontorpid WfPD. After nine weeks, blood levels were again similar, and had approached the limit of detection (10 ppb). Blood levels in nontorpid WfPD declined to <50 ppb after 3 weeks, while levels in torpid WfPD declined to <50 ppb after 7 weeks. Future studies will be required to determine efficacy of lufenuron in controlling fleas on WfPD. If effective blood concentrations are similar to dogs and cats, however, frequent dosing would be required to control flea numbers on prairie dogs and thus break the plague cycle. Results from this experiment indicated that blood concentrations of lufenuron did not reach initial levels as high as anticipated, nor were the concentrations maintained above 50 ppb for as long as anticipated (Fig. 4). The most likely cause of these low concentrations was poor absorption of the drug by prairie dogs. lbis may be due to the difference in gut morphology between rodents and carnivores. Alternatively, other aspects of pharmacokenetics may have been responsible for the low serum levels in prairie dogs despite dosing at rates 10-30 times higher than those recommended for cats and dogs, respectively. We followed up the dose titration experiment with an experiment to test the efficacy of oral lufenuron to control fleas on captive prairie dogs. Based on data from the bioavailability study, we increased the lufenuron dose to 500 mg/kg. Serum samples from the study have been submitted for lufenuron assay. Results are pending. Interpretation of efficacy results will rely on these serum lufenuron levels; however, we were able to make some preliminary comparisons between performance of fleas fed on treatment and control prairie dogs. One week post-dosing, fleas that fed on treated prairie dog produced a lower proportion (p < 0.05) of viable eggs than those fed on control prairie dogs (mean 0.16 vs. 039, respectively). Unfortunately, the proportion of viable eggs produced during week 2 post-dosing was low for each group (0.24 treatment vs. 0.17 control). By week 4 post-dosing, egg production had fallen to nearly zero in each group; however, the three eggs produced by fleas fed on treated prairie dogs were all viable. We are uncertain of the cause of the dramatic reduction in egg production and viability observed during the course of the experiment. Anecdotal reports suggest that flea production may be influenced seasonally (or at least cyclically) despite attempts to maintain controlled environmental conditions in the insectary (Metzger, Pers. Comm.). Regardless, it is unfortunate that serum levels oflufenuron decreased more rapidly than we had expected and that data did not support the hypothesis that lufenuron would be an effective means to significantly reduce flea production over the summer. Although further, similarly controlled investigation is warranted, preliminary results suggest that given current techniques, the likelihood of lufenuron limiting fleas populations and breaking the plague cycle is not extremely promising. Therefore, experiments into efficacy of controlling flea infestations in simulated burrow environments and in the field (described in Wild and Castle 1998) will not be performed. LITERATURE CITED Wild, M.A. and K. T. Castle. 1998. Monitoring and managing disease in black-footed ferrets. Colorado Div. Wildl. Res. Rep., 0880-1, Jul 1997 - Jun 1998, Fort Collins. Wild, M.A. and K. T. Castle. 1999. Monitoring and managing disease in black-footed ferrets. Colorado Div. Wildl. Res. Rep., 0880-1, Jul 1998 - Jun 1999, Fort Collins. �121 Attachment l Kevin T. Castle, Margaret A. Wild, and S. Craig Parks Colorado Division of Wildlife Foothills Wildlife Research Facility (KTC and MAW) Novartis Animal Health, Greensboro, NC (SCP) Introduction Black-footed ferret (Mustela nigripes) recovery plans call for the reintroduction of ferrets to sites characterized by the presence of viable populations of prairie dogs (Cynomys spp.), which provide food and shelter for ferrets. Unfortunately, prairie dogs inhabiting many potential reintroduction sites carry fleas that can serve as vectors ofYersinia pestis, the causative agent of plague (Ubico et al, 1988). Prairie dogs and ferrets are both highly susceptible to plague (Barnes, 1993; Williams et al., 1994) so the chances of successful ferret reintroduction will be enhanced if the numbers of fleas infesting a prairie dog colony can be significantly reduced. Lufenuron is a benzoylphenylurea derivative which inhibits formation of chitin in the exoskeleton of insects (Cohen, 1987). A single oral dose oflufenuron has been shown effective in controlling the cat flea (Ctenocephalides felts felis) for at least 30 days in treated cats (Blagburn et al., 1994) and dogs (Hink et al., 1994; Blagburn et al., 1995). No studies on the efficacy oflufenuron have been conducted with prairie dogs; however, Davis ( 1997) reported a significant reduction in fleas on free-ranging ground squirrels (Spermophilus beecheyi) that had been treated with lufenuron. We are performing a series of experiments to test the applicability oflufenuron to control fleas in captive, and ultimately wild, white-tailed prairie dogs (Cynomys leucurus). Thus far in pilot studies we have determined standard husbandry, maintenance, and handling protocols for captive prairie dogs and determined a test dose oflufenuron based upon a bioavailability study. We have also attempted to establish an insectary colony of a flea species (0ropsylla tuberculata) that naturally infests prairie dogs and their burrows. Oropsylla fleas are among the most common prairie dog fleas, and have been implicated in the transmission of plague in prairie dogs (Ubico et al., 1988). Fleas of this genus are nest fleas that infest the host only to obtain a blood meal. At other times the fleas select microenvironments within in the burrow system that are conducive to successful reproduction and survival. In pilot studies we were unable to develop methods to successfully maintain and produce self-sustaining populations of 0. tuberculata in an insectary. However, a related species, 0. montana, which naturally infests ground squirrels (e.g. Spermophilus beechyi) has been successfully maintained in the insectary using methods of M. Metzger and K. Gage (pers. comm). These fleas will feed on prairie dogs and successfully reproduce after ingesting a blood meal. Because of its similarity to 0. tuberculata, we will use 0. montana as a model to determine if flea reproduction can be controlled in lufenuron-treated prairie dogs. A chambered-flea system has been used to test on-host viability and fecundity of fleas on cats (Thomas et al. 1996) and laboratory mice (D. Engelthaller, pers. comm.). In this system, fleas are contained in a chamber attached to the host, and can obtain a blood meal through a mesh screen. This system has several advantages over other methods of artificial infestation. First, because a known number of adults can be placed into the chamber, flea mortality is easily noted, and survivorship can be determined. Second, sex ratios can be adjusted to maximize egg production. Third, eggs can be recovered readily, to determine viability. Fourth, the environment in the chamber will be warm and humid, and therefore conducive to adult and egg survival. Finally, fleas will not be able to leave the prairie dog, and therefore will not be able to infest caretakers or other animals. �122 In this study we will: 1) develop techniques for artificially infesting white-tailed prairie dogs with chambered populations of fleas, 2) test the flea control efficacy oflufenuron fed to white-tailed prairie dogs artificially infested with fleas, and 3) compare efficacy of flea control with serum lufenuron levels. Our working hypothesis is that fleas which feed on lufenuron-dosed prairie dogs will have reduced survival of eggs and larvae compared to fleas which feed on control animals that receive no lufenuron. Methods Prairie Dog Maintenance We will use 31 captive white-tailed prairie dogs maintained at the Foothills Wildlife Research Facility in Ft. Collins in our experiment. Prairie dogs will be housed singly (if used in experiments) or in pairs (if used for flea colony maintenance) in custom-designed cages (100 cm x 500 cm x 600 cm; Wild and Castle 1998). Prairie dogs will be observed daily, and will have ad libitum access to Teklad Rodent Blocks and water. Windows will provide a natural photoperiod, and a combination of timed heaters and air conditioners will be used to keep ambient temperature between 10 and 25° C. Twenty prairie dogs (10 males and 10 females) will be blocked by sex and randomly divided equally into a treatment group and a control group for the experiment. The treatment group will receive lufenuron while the control group will not. Because all animals cannot be housed in one building due to space limitations, the groups will be split evenly between two separate but similar buildings, to help control for any interbuilding differences (e.g. temperature, humidity) that may exist. The sample size of20 prairie dogs will allow us to detect a ~91 % reduction in the number of eggs that successfully hatch in the treated group given alpha = 0.10 and beta = 0 .90. An additional 11 captive prairie dogs will be maintained under similar conditions, but will not participate in the experiment. Instead, they will be used in the maintenance of the flea colony (see below). Lufenuron Dosing Prairie dogs in the experimental group will be fasted for 24 h prior to dosing; water will be available during the fast. After the fasting period (day 0), each experimental animal will be weighed, then offered a bolus dose oflufenuron (300 mg/kg body mass). Lufenuron will be mixed thoroughly in approximately 10 g of highly palatable bait (ground rat chow and molasses); control animals will receive bait only. We previously determined that a majority of fasted prairie dogs consume about 90-95% of their dose in less than 12 h. We will observe the progress of bait ingestion in each animal to determine when the dose is ingested. Remaining bait will be removed after 24 h. We will weigh the bait/lufenuron mixture before and after the prairie dogs are dosed, in order to calculate the actual dose ingested. After dosing, normal feeding will resume. Flea Infestation An initial stock of laboratory-reared, disease-free fleas (0. montana) will be obtained from Dr. Kenneth Gage at the Centers for Disease Control and Prevention (CDC) in Ft. Collins. Fleas will be housed in 500 ml glass jars containing larva-rearing media, to allow the population to be self-sustaining . Rearing media consists ofwheast (Red Star Biologicals), dried beef blood (Monfort Biologicals), powdered dog chow, and sand. Fleas will be maintained in an incubator at about 22-23° C and ~70% relative humidity (M. Metzger, pers. comm.) to ensure optimal reproduction. A natural photoperiod will be approximated within the incubator using fluorescent lights and a timer. Adult fleas must ingest a blood meal in order to reproduce. We will use two methods to provide blood meals to fleas held in the insectary for propagation of the colony. The first 1:11ethod will follow an established protocol (Castle and Wild 1998) to provide blood to the adult fleas in each rearing chamber, using neonatal rodents. Briefly, when fleas are in need of a blood meal (1-2 times per week), we will obtain �123 neonatal rodents from a private colony. The neonates will be placed into the insectaries with fleas for up to 24 h; previous work has shown that over 80% of the neonates are alive after 24 h. No food or water will be provided for the neonates, as they are strictly dependent on nursing. After feeding by the fleas, neonates will be euthanized by an overdose of inhalant anesthetic. Once per week, for 7 weeks, we will utilize the 11 non-experimental prairie dogs as blood sources, using the chambered flea technique described below. While the use of neonatal rodents is an efficient, approved method of providing blood to fleas, neonatal rodents are not always available from private colonies. Prairie dogs will therefore serve the dual purposes of providing blood meals when neonates are unavailable, and minimizing the number of neonatal rodents sacrificed. One week prior to study initiation, and on study days 2, 7, 14, 21, 28, 35, and 42 we will place flea chambers on experimental prairie dogs. Fleas feeding on treated prairie dogs will potentially be exposed to lufenuron from this blood meal. W.e will collect 50 adult female and 30 ad~lt male fleas from the insectary and place them"into a chamber (2.5 cm diameter). Each chamber will be-attached to a prairie dog so the fleas can obtain a blood meal. To attach the chambers, prairie dogs will be anesthetized using isoflurane delivered by a vaporizer. Respiration and depth of anesthesia will be monitored. A patch of fur on the dorsal thorax caudal to the shoulders will be shaved. A flea chamber will be placed on the skin, and taped into place using Elastikon and Vet-rap. The prairie dog will then be placed in a 30 cm x 20 cm x 20 cm holding box to recover from anesthesia, and will be monitored while the chamber is attached. Chambers will remain on each prairie dog for 30 min. At the end of the feeding time, the prairie dog will again be anesthetized with isoflurane, and the tape and chamber will be removed. Prairie dogs will be returned to their cages after recovery from anesthesia. Fleas will be observed for evidence of feeding by observation under a 10-20x ,;nicroscope, and blood-filled fleas will be placed in plastic vials and put into our insectary for egg recovery. 0. montana fleas typically lay eggs within 2-3 days of a blood meal (M. Metzger, pers. comm.), so adult dishes will be monitored every day for 7 days to monitor egg production. Eggs will be removed from the adult dish and placed in new vials inside the insectary; they will be observed every day for larval emergence. The total number of eggs produced by fleas from each prairie dog will be recorded, as will the number of larva that emerge each ·day. Unfed adult fleas will be returned to the insectary (prior to lufenuron dosing) or preserved in alcohol (after lufenuron dosing). Blood Collection Concentration of lufenuron in the blood may be an indicator of efficacy of flea control. To determine the relationship between blood lufenuron concentration and egg viability and larval development, we will collect 3 ml of blood from each anesthetized prairie dog prior to chamber attachment on each sampling day. Blood will be collected by jugular venipuncture and placed into a glass vacutainer blood tube without anticoagulant. Alternatively, ifwe are unable to collect an adequate blood sample peripherally, we will collect blood from the vena cava or directly from the heart. Although cardiac puncture is considered to be a safe procedure for collection of large volumes of blood from laboratory rodents (CCAC, 1984), due to the increased risks involved with cardiac puncture, we will use this technique only to obtain critical samples. Serum will be harvested and frozen within 4 h of collection. Serum lufenuron concentration will i>C? determined by HPLC at Novartis Laboratories. Based on our pilot studies and other literature (Blagbum et al. 1994, 1995; Thomas et al. 1996) we do not anticipate any prairie dog mortality due to the flea infestations, lufenuron dosing regime or blood collection, but if a severe allergic reaction or other health problem associated with our procedures occurs, the prairie dog will be removed from the study and provided veterinary care or euthanized with an overdose of inhalant anesthetic or barbiturate. A complete post-mortem examination will be performed on any animal that may die during the experimental period. �124 Data Analysis Efficacy of lufenuron will be determined by comparing developmental success of eggs produced by fleas exposed to treated prairie dogs vs. eggs produced by fleas exposed to control group prairie dogs. These formulas will be used in efficacy determination: Developmental success = number of larvae hatched x 100 number of eggs collected Percentage efficacy=mean developmental success (control) - mean developmental success (treated) x 100 mean developmental success (control) Mean developmental success values for eggs collected from prairie dogs at each sampling period will be analyzed using analysis of covariance, using blood lufenuron concentration at each time step as the covariate. Group responses will be considered significantly different ifp < 0.10. Literature Cited Barnes, A. M. 1993. A review of plague and its relevance to prairie dog populations and the black-footed ferret. Proceedings of the symposium on the management of prairie dog complexes for the reintroduction of the black-footed ferret. J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R. Crete, eds. 96pp. Blagburn, B. L., J. L. Vaughan, D.S. Lindsay, and G. L. Tebbitt. 1994. Efficacy dosage titration of lufenuron against developmental stages of fleas (Ctenocephalides felis felis) in cats. American Journal of Veterinary Research 55: 98-101. Blagburn, B. L., C. M. Hendrix, J. L. Vaughan, D.S. Lindsay, and S. H. Barnett. 1995. Efficacy of lufenuron against developmental stages of fleas (Ctenocephalides felis felis) in dogs housed in simulated home environments. American Journal of Veterinary Research 56: 464-467. Castle, K. T. and M.A. Wild. 1998. Protocol for the use of neonatal rodents as a blood source for insectary-reared fleas. Colorado Division of Wildlife Animal Care and Use Committee Study Plan. Canadian Council on Animal Care (CCAC). 1984. Guide to the care and use of experimental animals, Vol. 2. Ottawa, Ont., Canada. Cohen, E. 1987. Interference with chitin biosynthesis in insects. In Chitin and benzoylphenyl ureas, series entomologica, vol. 38, J.E. Wright and A. Retnakaran (eds), Dr. W. Junk, Publishers, Boston, pp.3342. Davis, R. M. 1997. Use of an orally administered insect development inhibitor (lufenuron) as a flea control agent in the California ground squirrel, Spermophilus beecheyi. Fourth International Symposium on Ectoparasites of Pets, pp. 31-35. Hilton, D. F. J. 1971. A method for rearing fleas of ground squirrels. Transactions of the Royal Society of Tropical Medicine and Hygiene. 66: 188-189. Hink, W. F., M. Zakson, and S. Barnett. 1994. Evaluation of a single oral dose oflufenuron to control flea infestations in dogs. American Journal of Veterinary Research 55: 822-824. Thomas, R. E., L. Wallenfels, and I. Popeil. 1996. On-host viability and fecundity of Ctenocephalides felis (Siphonaptera: Pulicidae), using a novel chambered flea technique. Journal of Medical Entomology 33: 250-256. Ubico, S. R., G. 0. Maupin, K. A. Fagerstone, and R. G. McLean. 1988. A plague epizootic in the whitetailed prairie dogs (Cynomys leucurus) of Meeteetse, Wyoming. Journal of Wildlife Diseases 24: 399-406. Williams, E. S., K. Mills, D.R. Kwiatkowski, E.T. Thome, and A. Boerger-Fields. 1994. Plague in a black-footed ferret (Mustela nigripes). Journal ofWildlife Diseases 30:581-585. Wild, M.A. and K. T. Castle 1998. Monitoring and managing disease in black-footed ferrets. Colorado Division of Wildlife Program Narrative, Project# W-153-R. \ ·\,,,_) �125 20 ~ - - - - - - - - - - - - - i ■ Plague-Neg>----------~ □ Plague-Pos 15 L. (1) ..0 E 10 ::::, z 5 1997-W 1997-S 1998-W 1998-S 1999-W 1999-S Fig. la. Prevalence of exposure to plague in juvenile coyotes from the Little Snake Management Area, Colorado, from winter 1997 through summer 1999. II Plague-Neg 20 □ Plague-Pas 15 Q) .0 E 10 :::J z 5 0 -+------'----'-~--'----'----'----------'-----.J'---..L.---'-----'-----'-----'---J 1997-W 1997-S 1998-W 1998-S 1999-W 1999-S Fig. lb. Prevalence of exposure to plague in adult coyotes from the Little Snake Management Area, Colorado, from winter 1997 through summer 1999. Data from winter 1997 (age class unknown) provided by M Albee. �126 25 - . - - - - - - i □ CDV positive II CDV negative 20 t> 15 J 10 5 0 1997-W 1997-S 1998-W 1998-S 1999-W 1999-S Fig. 2. Prevalence of exposure to canine distemper virus (CDV) in coyotes from the Little Snake Management Area, Colorado,' from winter i 997 through smnmer 1999. All positive coyotes were adults with the exception of one juvenile in summer 1998. Data from winter 1997 (age class unknown) provided by M. Albee. 20 , - - - - - - - - - - - , Ill Negative f - - - - - - - , □ Positive 15 .BS 10 z= 5 Plague Fig. 3. Prevalence of exposure to plague and canine distemper virus in adult coyotes from the Wolf Creek site, Colorado in winter 2000. 200 C: 0 175 "ia = 8 1-, 150 . _J25 C: .0 8 ~()() e= 75 C: 50 = 25 ca ...:I • . • • •• • 0 -t-----,--------.-------.----,,---,----,----r----r---, 2 3 4 5 6 7 8 9 10 Week Post-Dosing Fig. 4. Mean serum lufenuron concentrations of active ( ♦) and torpid (■) prairie dogs orally dosed with 300 mg/kg lufenuron. � https://cpw.cvlcollections.org/files/original/e26ad9d611c82f13cd9dee29ba29b8bb.pdf 4efbf3f5e4e8b5886e2515e7e8d4363d PDF Text Text 215 \ I ,/ Colorado Division of Wildlife Wildlife Research Report July 2000 I \ JOB PROGRESS REPORT State of _ _ _ _ _-=C=o=lo=ra=d=o'------- Cost Center 3430 Project _ _ _ _.....W-'---"-1=5=-3-"""'R=--=13~---- Mammals Research Work Package ---"""'3::....:0:....:;0""'1_ _ _ _ __ Deer Management Study No. -------=RMA==-=------- Technical Support for Deer Population Management at the Rocky MoW1tain Arsenal National Wildlife Refuge, Denver Colorado Period Covered: July 1, 1999 - June 30, 2000 Author: Dan L. Baker \ _) Personnel: M.A. Wild, T. M. Nett, J.C. Ritchie, D. Finley, M. Conner, L. Wheeler ABSTRACT We provided technical support for the management of mule and white-tailed deer populations at the Rocky Mountain National Wildlife Refuge, Denver, Colorado. Deer population demographics information was summarized from 1995-1999 and used to develop a simulation model to assist wildlife managers in evaluating alternative strategies for population control. As an alternative to annual culling of overabundant deer, we developed and tested a fertility control technology in captive mule deer. This contraceptive agent , was demonstrated to be 100 % effective in preventing pregnancy when delivered prior to the breeding season. Effective duration of the contraceptive was approximately 153 days. No negative effects on the nutrition, physiology, and general health of the treated animals were observed, however, breeding behavior of treated females was significantly (P :S 0.001) different from untreated co~trols. \ ) J m~i11~1i1mrnmnr BDOW016784 ��217 TECHNICAL SUPPORT FOR DEER POPULATION MANAGEMENT AT THE ROCKY MOUNTAIN ARSENAL NATIONAL WILDLIFE REFUGE, DENVER, COLORADO Dan L. Baker P. N. OBJECTIVES l. Provide technical support for the management of mule deer, white-tailed deer populations and their habitats at the Rocky Mountain Arsenal National Wildlife Refuge (RMA). 2. Develop a practical and acceptable technology to inhibit reproduction in mule deer and whitetailed deer populations at the RMA. 3. Develop a simulation model to predict impacts of alternative population control strategies at RMA. 4. Demonstrate the feasibility of population control strategies in a field application. SEGMENT OBJECTIVES l. Provide professional consultation relevant to the development of a deer management plan at the Rocky Mountain Arsenal National Wildlife Refuge. I 2. Develop and test a practical and acceptable technology to inhibit reproduction in captive mule deer. 3. Evaluate the effects of contraceptive technology on mule deer nutrition, physiology, general health, and breeding behavior. INTRODUCTION Deer Population Management Plan The Rocky Mountain Arsenal National Wildlife Refuge (RMA) has the potential to become one of the premier wildlife viewing areas in the United States. However, realizing that potential depends on wise management. In particular, the mule deer population contained within the boundary fence must be regulated in balance with the resources available. Experience with enclosed deer populations elsewhere has revealed that unregulated population increases will lead relentlessly to degradation of habitat, to widespread starvation, and eventually to catastrophic declines in animal numbers. Professional culling and fertility control offer alternative management strategies for regulating deer populations at the RMA. However, until fertility control technology is demonstrated to be a feasible and efficacious method for controlling free-ranging wild ungulate populations, annual culling of mule deer is the only viable management option available to resource biologist.at the RMA. Using either culling or contraceptives to meet deer population objectives will require, wildlife managers to choose specific tactics of treatment. Choices must be made on the number and age to treat, frequency of treatment, species, sex, etc. Decisions on the best tactics will depend on comparing the effects of �218 alternative management actions on population behavior. To assist in these decisions, we developed an interactive simulation model of deer population dynamics to allow managers to evaluate alternative treatment regimes on simulated populations before applying them to real animals. Critical to model performance is knowledge of population demographics of the RMA deer herds and requires information on sex and age composition, recruitment, pregnancy rates, fetal sex ratio, and estimates of population density. 1bis information together with knowledge of the habitat resources available to deer will provide a sound biological basis for management of deer populations at the RMA. Deer Fertility Control Contraception offers a viable alternative to culling as means oflong-term control of overabundant wild ungulates. During the last decade, research aimed at developing effective contraceptives for free-ranging wildlife populations has accelerated. These efforts have resulted in development and testing of a wide variety of potential contraceptive agents (Kirkpatrick and Turner 1985, Warren et al. 1995). One of the most promising new non-steroidal, non-vaccine, approaches to contraception involves synthetic analogs of gonadotropin-releasing hormone (GnRH). GnRH is a molecule produced in the hypothalamus of the brain. It directs specific cells in the pituitary gland to synthesize and secrete two important reproductive hormones; follicle stimulating hormone (FSH) and luteinizing hormone (LH). These latter two hormones, known as gonadotrophs, control the proper functioning of the ovaries in the female and testes in the male. Inhibition of ovulation caused by chronic administration of GnRH analogs has been successful in several species, including dogs (Vickery et al. 1989), cattle (Herschler and Vickery 1981), sheep (McNeilly and Fraser 1987), white-tailed deer (Becker and Katz 1995), and elk (Baker and Nett, unpublished data). Evidence from studies confirm that sustained release is the most effective approach for temporarily suppressing pituitary-gonadal function. The practicality of this approach, however, is dependent upon development of a long-acting, slow-release analog that can be remotely delivered. Recently, a practical mode of administration using subcutaneous implants has overcome the need for constant mechanical infusion of the analog. Slow release formulations of superactive GnRH analogs are now commercially available and have been shown to be effective in suppressing the pituitary-ovarian axis for up to 6 months in a variety of mammalian species (Fraser et al. 1987). To our knowledge, only limited investigations have been conducted to evaluate the effectiveness ofGnRH analogs in wild ungulates (Becker and Katz 1995, Baker and Nett 1998 unpublished data), however, the minimum dose of GnRH analog required for maximum pituitary stimulation is known for mule deer (Baker et al. 1995) and the minimum effective duration of controlled release GnRH-agonist implants has been determined to be at least 130 days in captive elk (Baker and Nett 1999, unpublished data). Additional research is needed to determine the effectiveness of these contraceptive agents in preventing pregnancy in mule deer and their maximum effective duration. Research is also needed to identify any nutritional, physiological or behavioral side-effects that may result from treatment. Thus, the objectives of our research are: 1) To evaluate the effectiveness and effective duration of GnRH analog in preventing pregnancy in mule deer. 2) To evaluate the effects ofGnRH analog on nutrition, physiology, general health and breeding behavior of captive mule deer. �219 We will test the null hypothesis ofno effect of GnRH analog on luteinizing hormone (LH) levels, pregnancy rates, social behavior, and general health of captive female mule deer. MATERIALS AND METHODS Deer Population Management Plan. The primary deer population management objective for the RMA is to maintain a healthy and productive mule and white-tailed deer population that is in balance with its habitat resources. Specific objectives include: 1) Manage total deer population levels at approximately 50% of habitat carrying capacity with a mule deer : white-tailed deer population ratio of 2: 1. The total winter population goals will be 550-650 mule deer and 250-350 white-tailed deer. 2) Manage sex and age composition of deer to achieve a high proportion of mature males relative to adult females. The sex and age composition goals will be 90 to 120 bucks:100 does with at least 50% of males older than 2 years of age. The status (population siz.e, condition, general health) of the deer population at the RMA was evaluated on an annual basis from 1995 to 1999 using the following demographic information. This information was incorporated into a culling/fertility contrbl simulation model that allowed RMA biologist to evaluate alternative population control strategies for meeting deer population objectives. Census. A total count of all deer on the RMA was conducted each winter from 1989 to 1998. Procedures were standardized for all counts by 1) conducting at least two consecutive aerial surveys each winter, 2) conducting surveys after trees and shrubs had dropped their leaves, 3) conducting surveys when snow cover was at least 95-100 %, 4) using the same 2 observers whenever possible, and 5) using a Bell Soloy helicopter that was flown at an average ground speed of 60 km/hr at altitudes from 24 to 35 m above ground. The helicopter flew transects approximately 400 m apart beginning on the south perimeter and preceding north along east to west transects. Observers searched areas on their respective sides of the helicopter. Temperature, visibility, and percentage snow cover were recorded for each flight. Deer were tallied by species but not classified by sex and age. Sex and Age Classification. Sex, age, and species composition of deer at the RMA were sampled each November. Three permanent survey routes were established by dividing the RMA into 3 separate geographical areas and identifying a permanent route within each area. Each route followed established roads and was chosen to observe the maximum number of deer within the area. The length of each route was determined by the driving distance that could be covered by one vehicle during the period 0700-1200. One pair of previously trained observers sampled each of the three areas each day~ the same pairs of observers were consistent across all days. Classifications were conducted at the peak of the breeding season (approx. Nov 22) to increase the probability of observing all age classes. Observations were made from a vehicle using 8 x 50 binoculars and 10-60x. spotting scopes. No classifications were attempted for deer that were farther than 200 m from the observer or for deer that were bedded. Deer were classified by species as either mule or white-tailed deer, and sex, and age as immature buck, mature buck, doe, fawn, and abnormal buck (Dasman and Taber 1956). Each year, prior to conducting surveys, observers independently classified the same deer from as many groups of deer as required to consistently obtain identical classifications. �220 Reproductive Parameters. We detennined pregnancy rates, fetal rates, fetal sex ratio, and average conception date for adult female mule deer collected from 1995 to 1999. Deer were shot through the spine in the cervical region with a high powered rifle at distances ranging from 30 - 75 m. Reproductive tracts were removed and examined for evidence of fetuses. Does lacking identifiable embryos or fetuses after January I were regarded as current breeding failures. If corpora lutea were present, we used only those does in which there was gross evidence, through presence of embryos or pigmented degenerating corpora lutea, that the doe either had been or was currently pregnant. During 1994 we measured fetal growth rates to estimate breeding dates. Adult does were collected at 4 time periods during gestation: January 25, February 16, March 9, and April 19. -Fetuses from each doe were removed in the field and transported to the laboratory for determination of sex and age. Fetal foreheadrump (mm), hind leg length (mm), and body mass (g) measurements were made according to methods described by Armstrong (1950). Measurements of twins and triplets were averaged to provide a single estimate of fetal age for each doe. We estimated the age of each fetus by using the linear regression of forehead-rump length (mm) (Y) and age (days) (X) established from known-age mule deer fetuses (Y = 124.6 + 3.2lx) (Hudson and Browman 1959). Culling/Fertility Control Model. We developed an interactive simulation model to allow RMA biologist to evaluate alternative mule deer culling strategies. This model combined extant knowledge of mule deer population biology with measured population parameters at the RMA to predict the proportion of male and female deer that need to be removed each year to accomplish management objectives. Table 1. Principal parameters in culling simulation model for mule deer at RMA. Reference Definition Value Measured Whittaker, 1992 Adult/yearling female survival 0.90 No Whittaker, 1992 Adult/yearling male survival 0.90 No Bartmann et al., 1992 Fawn survival coefficient a: 1.20 No Bartmann et al., 1992 Fawn survival coefficient P -0.053 No Fetal sex ratio(% males) 0.47-0.62 Yes December recruitment 0.59-0.72 Yes Deer Fertility Control Mule deer (OdocoUeus hemionus hemionus) are polyestrus owlators that exhibit highly seasonal patterns of reproduction that are controlled by photoperiod regimens. The onset of the breeding season occurs during decreasing daily photoperiods of autumn and is preceded by a period of deep anestrous in summer (Plotka et al.1977). The first ovulation of the breeding season is usually preceded by one or more silent ovulations associated with the formation of short-lived corpora lutea that serve to synchronize the first overt estrus within a herd (Thomas and McT.Cowan 1975). In temperate North America, the majority of conceptions occur in late November, but recurrent estrous cycles of 24 -28 days are possible through March if females fail to conceive (Knox et al. 1988). In early spring, coincidental with increasing day length, reproductive cycles cease and females remain anestrous until October. For pregnant females, parturition generally occurs in late May or early June, after a gestation period of about 200 days (Anderson and Medin 1966). Experimental Animals. We conducted two experiments to evaluate GnRH analog in captive tame and wild female mule deer. Experiment I was a highly controlled experiment using IO tame, adult females and 2 wild, adult male mule deer. Experiment 2 attempted to simulate the appli~on of contraceptive treatments �221 to free-ranging mule deer at the RMA. This effort involved 9 wild, adult female mule deer and 5 wild, adult male mule deer. These studies were conducted from November 3, 1999 until August 15, 2000 at the Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF), Fort Collins, Colorado. Experiment 1: Protocol Reproductive Status. Before randomly assigning animals to treatment groups, we detennined the reproductive status of all does by measuring serum progesterone levels at weekly intervals beginning November 10. For this sampling, deer were moved from 5 ha pastures to individual isolation pens, sedated (40-100 mg xylazine (100 mg/ml), IM) and blood samples collected (5ml). Animals were reversed with yohimbine (0 .125 mg/kg, IV) and returned to paddocks the same day. Sedation of deer was done in order to minimize potential adrenal secretion of exogenous progesterone during handling and blood sample collections (Plotka et al.1983, Asher et al. 1989). Treatments. Following fertility evaluations, 5 does were randomly selected to receive an analog of GnRH (LUPRON) and 5 does were assigned to a control group. Treatment does \,\'.ere given a subcutaneous implant containing 10 mg of LUPRON one week prior to being exposed to male deer. Based on previous studies with mule deer (Baker et al. 1994), and elk (Baker and Nett 1999), approximately 3-4 animals per treatment are sufficient to establish statistically significant differences among treatment means. Hormonal Evaluation. Prior to application of the contraceptive treatment, we measured the LH response of each doe in both LUPRON and CONTROL groups to a challenge dose of GnRH analog (1 ml/50 kg BW, IV) . Results from this trial provided a pretreatment baseline for comparison to future posttreatment LH responses. This and succeeding LH 1challenge trials were conducted as follows: On Day 1 of the trial, mule deer were moved from 5 ha pastures to individual isolation pens, sedated (4-6 ml, 5: 1 ketamine (lOOmg/ml):xylazine hydrochloride (100 mg/ml, IM), and fitted nonsurgically with indwelling jugular catheters. Animals were be reversed with yohimbine (0.125 mg/kg, IV). On Day 2, we administered GnRH analog (1µ /50 kg BW) through the cannula and collected blood samples (5 ml) at 0, 60, 120, 180, 240, 300, 360, and 480 minutes postinjection. Following the last blood collection, catheters were removed and each animal given Naxel (3 ml/deer, (50 mg/ml, I.V.). Animals were then returned to 5 ha pastures. Serum was stored at - 20 °c until analyzed for LH. The duration of contraceptive effectiveness was assessed by conducting GnRH challenge trials each month from November 1999 to April 2000. Hormonal Assays: After collection, blood was held at 4 °C for 24 h until serum was obtained by centrifugation. Serum progesterone concentrations was determined using RIA procedures (Niswender 1973). Sensitivity of the progesterone assay was 0.12 ng/ml. Female mule deer with progesterone levels above 1 ng/ml were considered reproductively active (Plotka et al. 1977). 1990). Mule deer with progesterone levels below 1 ng/ml were sampled 7 days later. If after three consecutive blood collections, progesterone levels remained lower than 1 ng/ml the animal was be removed from the experiment. Serum concentrations of LH were quantified by means of ovine LH RIA (Niswender et al. 1969). The limit of sensitivity of the assay was 0.4 ng/ml. Response Measurements. The effects of LUPRON on female mule deer were assessed by comparing responses of treated and control deer by the following methods: a) Hormonal response. Responsiveness of the pituitary to GnRH challenge were determined in three ways: 1) maximum LH (ng/ml) response achieved postinjection minus baseline, 2) time (hr) required to reach maximum LH, and 3) total amount ofLH secreted (ng/ml/min). b) Pregnancy rates. We assessed contraceptive effectiveness by determining the pregnancy rates in treated and control deer. A single blood sample (10 ml) was taken via jugular venipuncture from each animal for �222 pregnancy- specific protein B (PSPB) analysis approximately 60, 90, and 180 days post-conception (Willard et al. 1998). Animal handling and blood collections for PSPB follpwed methods previously described for hormonal assessment and were collected in conjunction with these measurements. Neonates born to any experimental animal were incorporated into the resident FWRF mule deer herd with the exception of fawns born after August 15. Because late born fawns may experience higher than nonnal over-winter mortality, and potentially compromise body condition and short-term fertility of the dam, neonates were removed from the dam and either bottle-raised or euthanized according to ACUC procedures. c) General health. Knowledge of the effects ofGnRH analogs on nutrition, body weight dynamics, blood chemistry and general health of mule deer is unknown. Previous experiments with domestic livestock (Herschler and Vickery 1981), companion animals (Vickery et al. 1989), white-tailed deer (Becker and Katz 1995), and elk (Baker and Nett 1999) have reported no measurable short-term physiological effects. We evaluated these potential side-effects by monitoring body weight, blood chemistry, hematology and overall health of all female deer. We collected blood (10 ml) for blood chemistry and hematology prior to treatment, and at 30, 90, and 180 days posttreatment. We weighed deer at monthly intervals and monitored feed intake on a weekly basis .. d) Breeding behavior. The effects of the GnRH analogs on breeding behavior of mule deer are not known. However, if gonadotroph cells are desensitized by long-acting synthetic GnRH analogs, down-regulation and diminished LH and FSH secretion can be induced. Reduced secretion of LH and FSH could decrease or disrupt ovarian function, estrus cycles and secondary sex characteristics. Furthermore, if pituitary responsiveness returns following depletion of GnRH analog implants, treated females could resume estrous cycles and become pregnant late in the l1reeding season. This, in turn, could have survival consequences for both the pregnant female and her neonate. We evaluated these potential effects by monitoring maintenance and sexual behavior of male and female mule deer during the nonnal breeding period and at the end of the predicted depletion of the GnRH analog (March-April). Each animal in each treatment and the breeding males was individually identified using color-coded neck bands or ear tags. We tested the null hypothesis that the frequency of sexual interactions between males and treated females would be similar to those of males and untreated females. We tested this hypothesis using focal-animal sampling procedures and discriminant function analysis (Lehner 1987). The exact experimental design depended on time-of-day effects, number of observers, length of required sampling period, number of bucks in pasture, and the number of bucks observable by one observer. Statistical All;Olysis. We analyzed data using least squares ANOVA for General Linear Models and the SAS Interactive Matrix Language. Response to contraceptive treatments was analyzed with two-way factorial analysis of variance for a randomized complete block design with repeated measures structure. Levels of GnRH analog were treatments; individual animals were blocks. Factors in the analysis were treatment and time. Treatment effects were tested using the animal-within-treatment variance as the error term. Time was treated as a within subject effect using a multivariate approach to repeated measures. We used orthogonal contrast to test for differences among individual means (Morrison 1976, Miller 1966). Experiment 2 : Protocol Treatments. Nine captive wild adult female deer (previously captured and currently being used in a companion study under an approved ACUC protocol) were systematically assigned to either the control (4 animals) or LUPRON treatment (5 animals). During October 21 - November 1, in association with routine FWRF management procedures, control females plus 5 wild adult male mule deer were sedated (0.075 mg/kg medetomidine and 2 mg/mg ketamine or 4.4 mg/kg Telazol and 2.2 mg/kg xylazine) via projectile �223 darts, and individually marked. Male deer were marked with color-coded ear tags and females with colorcoded neck bands. All deer were reversed using atipamezol (0.38 mg.kg) or yohimbine (0.15 mg/kg). On November 3, treatment females were captured and individually marked (following the same tranquilization procedures as previously described), and given a subcutaneous implant of LUPRON (10 mg/animal). Based on previous studies with mule deer (Baker et al. 1994), and elk ( Baker and Nett 1999) approximately 3-4 animals/treatment are adequate to detect statistically significant differences between treatment means. Response Measurements. The effects of LUPRON on female mule deer were assessed by comparing the responses of treated and control deer by the following methods: a). Fawning rates. We determined contraceptive effectiveness by comparing the fawning rates of treated and control deer. Beginning in early June, all does were observed for behavioral and clinical evidence of parturition. In addition, fawning paddocks were searched daily for neonates. Any treatment female that had not fawned by August 15, was tested for pregnancy using PSPB analysis (Willard et al. 1998). Any fawn born after August 15 was removed from the dam and either bottle-raised or euthanized according to ACUC procedures. b) Breeding behavior. Procedures for comparing breeding behavior of control and treated does was similar to those described in Experiment 1. Statistical Analysis. Differences among fawning rates between control and treated females was analyzed using unpaired ttest (p < 0.05) (Steel and Torrie 1960). ! RESULTS AND DISCUSSION Deer Population Management Census. Mule and white-tailed deer populations generally increased from 1989 to 1998 with relatively large fluctuations in total numbers from year to year, particularly for white-tailed deer (Table 2). Mule deer numbers increased by 75 .6 % and white-tailed deer by 77.1 % during the eight year measurement period. For mule deer, most of the increase in population size occurred between 1990 and 1993. During this time period, the population grew at a rate of about 20% per year. After annual culling was implemented in 1994, the annual growth rate of the population was reduced to approximately 4% per year. Presently (1998), mule deer numbers (637) are within the population objective set for this species (550650). The white-tailed deer population at the RMA has shown large fluctuations in size from year to year. It's not known if these annual fluctuations are due to actual changes in population numbers, measurement error, or a combination of these factors. Regardless, white-tailed deer appear to be increasing with the greatest increase occurring between 1997 and 1998 (+ 44.9 %). The current (1998) population size (318) is within the management objective set for this species (250-350) and is near the population ratio objective of 2: 1 mule deer:white-tailed deer. Due to lack of snow cover no winter counts were conducted in 1999. Biologist at the RMA generally believe that the total counts of white-tailed deer are less reliable than those for mule deer because of the different habitat types preferred by this species and differences in behavior during helicopter surveys. Mule deer are generally more gregarious in winter than white-tailed deer and found in more open habitats where they are more easily observed and accurately counted. They appear to be less fearful of helicopter flights and tend to stay in one place during surveys, thus minimizing duplicate counts. In contrast, white-tailed deer are more solitary and generally found in dense vegetation near streams �224 Table 2. Total counts of mule and white-tailed deer at the RMA during 1989 to 1999. Mule deer White-tailed deer Year Number Number %Change %Change 1990 154 73 1991 200 +23.0 72 -1.4 1992 286 +30.0 35 -51.4 1993 397 84 +58.3 +27.9 1994 1995 550 +62.3 +27.8 223 1996 501 168 -24.6 - 8.9 1997 657 175 +4.0 +23.7 1998 632 318 +45.0 -3.8 1999 No winter counts and woodlands. They are more easily frightened by low the flying helicopter and tend to run when being counted. For population management purposes. we assumed that helicopter surveys accounted for 90-95% of the total mule deer population and 80-85% of the total white-tailed deer population. Ser and Age Classification. We determined the species, sex. and age composition of deer at the RMA during November 1996 to 1999 (fable 3). An average of 466 (se ± 58) individual mule deer and 153 (se ± 22) white-tailed deer were observed and classified each year during this period. Mule Deer: Bucks. The proportion of male mule deer in the population remained relatively constant ( x = 42%, se ± 1.8) from 1996 to 1998 (fable 3). However, the composition of young and mature males in the herd changed over this same time period. The proportion of young male mule deer increased from 8% of the total population in 1996 to 17% in 1998 while mature males declined from 35% to 23%. Most of the decline occurred between 1996 and 1997. The increase in young males in the population is also reflected in the total male mule deer population. The ratio of young males:mature males increased from 26 to 72:100 mature males between 1996 and 1998 (fable 3). Surprisingly, the increase in young males occurred despite selective culling of this cohort each year. Clearly, the trend over the last three years has been an increasing proportion of young males and a decreasing proportion of mature males. Reasons for this trend are unknown. Currently, mature males comprise 57 % of the total male population which meets the objective for this segment of the population. However. management intervention may be needed to reverse this trend in order to meet current deer population objectives. Mule Deer: Does. The proportion of adult does in the population has remained relatively constant (x = 31%, se ± 3.1) during 1996 to 1998 (fable 3). Buck:doe ratios declined by 20% from 1996 to 1998 in large part due selective annual culling of young males. The 1998 buck:doe ratio is within management objects for this segment of the population. Mule Deer: Fawns. The proportion of fawns in the RMA mule deer population remained relatively stable (x = 23 %, se ± 0.67) from 1996 to 1998 (fable 3). However, mean fawn:doe ratios over this time period have steadily declined (27 %) suggesting a substantial reduction in fawn recruitment into the population. Reasons for this decline are unknown and may need to be addressed in the near future. �225 Table 3. Sex and age comeosition of the mule deer eoeulation at RMA during November 1996 to 1998. Mule Deer 1998 1996 1997 Means Mean S.E. S.E. S.E. Mean Category: 71.3 Young bucks 36.3 1.7 87.3 6.8 4.4 Mature bucks Adult does Fawns Abnormal bucks Animals observed Groues observed Ratios: Bucks: 100 does Fawns:100 does Young bucks: 100 mature bucks 139.0 124.3 98.3 3.3 401.3 109.3 10.6 11.8 4.7 0.9 25.7 11.3 150.0 197.0 140.3 6.3 581.0 247.6 1.7 2.0 5.8 2.2 7.0 11.7 98.0 153.0 91.6 3.3 417.3 182.6 9.6 7.8 10.0 0.9 27.2 14.7 142 81 23 8 120 71 30 3 113 59 76 4 25 1 58 4 72 6 White-tailed Deer: Bucks. Unlike male mule deer, the proportion of male white-tailed deer in the total population increased from 30% 1996 to 42% 1998 (fable 4). Almost all of the increase occurred from 1997 to 1998. Similar to male mule deef, this increase was primarily associated with an increase in the proportion of young bucks and a decrease in mature bucks in the total buck population. As of November 1998, mature bucks comprised approximately 62% of the bucks in the total buck population. White-tailed Deer: Does. The proportion of adult white-tailed does in the RMA herd was relatively constant from 1996 to 1998 (x = 43%, se ± 1.5) (fable 4). However, with the apparent increase in bucks over this same time period the buck:doe ratio increased dramatically from 65 bucks: 100 does in 1996 to 103 bucks:100 does in 1998. White-tailed Deer Fawns. The proportion of fawns in the total population increased for 22% in 1996 to 27% in 1997 and 1998 (fable 4). Fawn:doe ratios fluctuated from between 40 and 65 fawns:100 does during 1996 to 1998. Reproductive Parameters Pregnancy Rates: Reproductive data was collected from 164 adult female mule deer from 1995-1999 (fable 5). Mean pregnancy rate during this period was 91.4 %(se ± 4.0) and ranged from a low of 80 % in 1999 to a high of 100 % in 1997 and 1998. Average fetal rate for pregnant does was 1.72 fetuses/doe (se ± 0.05), and 1.54 fetuses/doe (se ± 0.09) for all does combined. Fetal Growth Rates and Estimated Conception Dates: We observed a significant (P = 0.001) linear relationship between fetal age and fetal body length (Fig. 1). The fetal growth rate for mule deer at the RMA was similar (P = 0.65) to the growth rates reported for known age mule deer fetuses (Hudson and Browman 1959) and greater (P = 0.01) than the growth rates for mule deer fetuses in the Piceance Basin, Colorado (Bartmann 1986). A common use of fetal growth rate is to estimate breeding dates. The growth rate for mule deer fetuses derived from data of Hudson and Browman (1959) was applied to fetal data collected from the RMA. �226 Linear regression of estimated breeding date on collection dates was calculated to estimate the breeding season (Fig. 2). The slope of this regression line was not significantly different from 0 (P = 0.034) indicating that fetal length measurements are a predictable indicator of conception dates for the period of gestation sampled. However, it should be noted that this relationship was established for adult female mule deer in good to excellent body condition. Other studies have shown that estimated breeding dates will vary during the gestation period depending on winter severity and its effect on fetal growth rates, particularly during the last trimester of pregnancy (Bartmann 1986). Based on calculated conception dates, we estimate that 95% of the breeding occurred between November 21 and December 1. Conception dates ranged from November 14 to December 7. The breeding season for does at RMA appears to be somewhat earlier (November 25 - December 15) and shorter in duration than the breeding season reported for mule deer in the Cache la Poudre drainage of north-central Colorado and from studies in west central Colorado (Anderson and Medin 1966). Table 4. Sex and age composition of the white-tailed deer population at RMA during November 1996 to 1998. Mule Deer 1998 1996 1997 Mean• S.E. Mean S.E. S.E. Mean Category: 21.0 6.5 Young bucks 6.0 20.7 3.2 1.5 33.7 34.0 2.9 Mature bucks 10.4 39.7 3.5 53.0 2.08 Adult does 61.3 83.7 6.8 9.3 36.3 Fawns 29.7 52.7 7.4 3.9 1.ft 0.0 0.0 0.0 0.0 0.0 0.0 Abnormal bucks 130.3 6.01 131.7 197.0 17.3 Animals observed 24.3 73.3 4.8 46.0 6.9 105.3 3.3 GrouES observed Ratios: 103 8 Bucks:100 does 65 15 2 71 42 2 63 8 Fawn: 100 does 47 6 Young bucks : 20 1 65 22 100 mature bucks 51 3 Fetal Sex Ratios: We examined 251 mule deer fetuses for evidence of sex during 1995 to 1999 (fable 6). Of these, 140 were males and 114 were females resulting in a pooled fetal sex ratio of 56% males and 44% females. The pooled fetal sex ratio for mule deer at the RMA is within the range of values reported elsewhere for Rocky Mountain mule deer (Medin and Anderson 1979, Robinette et al. 1955) and was not significantly different from unity (P = 0.23). However, fetal sex ratios deviated from 50:50 in 2 out of 5 years and favored males over females (P = 0.023). In only 1 year out of 5 did the fetal sex ratio favor females. Disease: 1998. During August 1998, epiz.ootic hemorrhagic disease virus (EHD) was diagnosed as the probable cause of death in 19 white-tailed deer and 21 mule deer at the RMA. However, the extent of deer mortality from this disease is unknown and was probably much greater than the 40 individual deer that were actually found. Culling Model. Professional culling of adult mule deer at the RMA was implemented on a prescribed basis beginning in November 1994. Prior to 1994, the mule deer population was increasing at a rate of approximately 20 % per year. Since 1994, annual culling has reduced the population growth rate to 4% per year and allowed resource managers to meet deer management objectives for this herd. To meet these �227 Table 5. Pregnancy and fetal rates of adult female mule deer collected at the RMA during 1995 to 1999. Fetal Rate <fetuses/doe} Year 1995 1996 1997 1998 1999 Mean SE n Sample Size 39 46 26 38 15 Pregnancy Rate(%) 92.3 84.9 100.0 100.0 80.0 91.4 4.0 5 Pregnant Does 1.61 1.59 1.88 1.63 1.91 1.72 0.07 5 Table 6. Fetal sex ratio for adult mule deer on the RMA during 1995 to 1999. Year Sample size Males(%) 1995 58 60.4 1996 62 62.9 1997 49 53.2 1998 62 47.4 1999 20 60.0 Total Does 1.48 1.34 1.88 1.63 1.53 1.54 0.09 5 Females(%) 39.6 37.1 47.8 52.5 40.0 objectives has required that resource mapagers remove approximately 10- 15% of the adult females and 610% of the young males from the popul!tion each year. These estimates vary each year depending on productivity of the population, changes in sex and age ratios, and deer habitat resources. The mathematical model used to estimate the number of animals that must be culled annually to maintain a target, steady state population appears to provide a reasonably accurate representation of mule deer population dynamics at the RMA. The efficacy of this model, however, is dependent on intensive monitoring of the population and adapting management actions to a changing environment. Deer Fertility Control Pregnancy Rates and Hormonal Responses In both Experiment 1 and 2, the LUPRON subcutaneous implant was 100% effective in preventing pregnancy in all female mule deer (n = 9) that were treated. Untreated control deer (n = 10) all delivered normal fawns. Duration of effectiveness varied among deer and ranged from 118 days to 210 days. Serum progesterone (P4) concentrations of treated females remained below 0.1 ng/ml for at least 118 days posttreatment (Fig. 1). Serum P4 levels in two out of three does remained below 0.1 ng/ml for at least 174 days and for at least 210 days in one doe. Administration of the depot formulation of LUPRON resulted in a significant (P :!> 0.001) decline in serum luteinizing hormone (LH) concentration after 47 days posttreatment (Fig. 2). Similar to P4 levels, LH remained below 1 ng/ml until 153 days posttreatment. These results suggest that GnRH induced interruption of reproductive cycles and pregnancy is associated with diminished progesterone and LH production, implying defective function of the corpus luteum. These luteolytic effects have been attributed to the well recognized desensitizing actions of elevated LH levels on ovarian LH receptors. �228 Breeding Behavior We collected data for 59 sampling periods: 24 morning periods totaling 37.0 hrs, 18 mid-day periods totaling 36.0 hrs, and 17 evening periods totaling 52.2 hrs, for an overall total of 125.2 hrs of observation. Time of day, date, and the interactions were not significant effects and were.dropped from the ANOVA model. The behavior rate of does treated with Lupron SQ was not different than for control does for copulatory or general breeding behaviors (fable 3). However, male pre-copulatory and female precopulatory behavior rates were higher for the Lupron SQ group compared to the control group (fable 3). If Lupron had no treatment effect, then the difference between behavior rates of control and treatment groups will equal zero. The difference in behavior rates for does treated with Lupron SQ and control does was not equal to zero for male pre-copulatory behaviors and was borderline significant at a 0.10 alphalevel for female pre-copulatory behaviors (fable 4). Behavior rates were almost identical for the control and Lupron SQ groups for copulatory and general breeding behavior categories. However, male and female pre-copulatory behavior rates for the Lupron SQ group were 2.0-5.5 times higher than for the control group. It is unclear why the Lupron SQ group had higher pre-copulatory be~vior rates, but similar rates of copulatory behavior. It is possible that sampling variation is responsible, especially given the small sample sizes. The rate of male pre-copulatory behavior was significantly higher toward the Lupron SQ group than the control group. Male pre-copulatory behavior rates were 2 times higher toward the Lupron SQ group. Although the rate of female pre-copulatory behavior was 5.5 times higher for the Lupron SQ group compared to the control group, this difference was not significant. 6 --- Deer K95 - -0- - Deer G96 84 118 -......-- DeerN93 5 ~ E oi .s "<t a.. 4 3 E :l ai Cl) 2 0 .... ' ' '' ' ',"' '' " Pretrmt 47 153 174 210 Days Posttreatment Figure 1. Serum progesterone (P4) levels in female mule deer before and after treatment with a subcutaneous implant containing 10 mg ofLUPRON. Each line and symbol represents an individual deer. �229 As with the elk, rates of general breeding behavior were similar for the 2 treatment groups. Although deer do not have a harem breeding system, the general breeding behaviors may be more concerned with dominance and represent indirect reproductive behaviors. ---- Deer K95 -¾- --0-- DeerG96 Deer N93 30 4 ~ E CD .s 20 I ...I . E ::, cii en Q .:,,: t'G Cl) \ 10 (l_ \ \ \ ·\ \ \ \ \ \ \ \ 'I:\ 'I' 0 Pretrmt 47 84 118 153 174 210 Days Posttreatment Figure 2. Serum luteinizing hormone (LH) levels in female mule deer before and after treatment with a subcutaneous implant containing 10 mg ofLUPRON. Each line and symbol represents an individual deer. Table 3. Mean rate of behavior and standard error for control and treatment deer groups; mean and standard error were estimated using type ill least-squares. Behavior category Treatment Group Copulatory Control Lupron SQ Male Pre-Copulatory Control Lupron SQ Female Pre-Copulatory Control Lupron SQ General Breeding Control Lupron SQ Mean SE (# behviors/h r') 0.010 0.011 0.007 0.010 0.466 0.944 0.124 0.010 0.055 0.004 0.028 0.107 0.029 0.021 0.111 0.101 �230 Table 4. Difference in deer behavior rates(# behaviors/hr) between control and treatment groups, standard error of the difference, and P-value of the difference (the probability that the behavior rates were equal); statistics were estimated using type III least-squares. Behavior Category Treatment Group Copulatory Control - Lupron SQ Male Pre-Copulatory Control - Lupron SQ Female Pre-Copulatory Control - Lupron SQ General Breeding Control - Lupron SQ Mean Difference SE P-Value -0.001 0.013 0.944 -0.478 0.162 0.003 -0.045 0.030 0.129 -0.004 0.035 0.900 LITERATURE CITED Adam, C. L., C. E. Moir, and T. Atkinson. 1985. Plasma concentrations of progesterone in female red deer (Cervus elaphus) during the breeding season, pregnancy, and anoestrus. J. Reprod. Fertil. 74:631-636. Anderson, A. E., and D. E. Medin. 1966. The breeding season in migratory mule deer. Colorado Division of Wildlife, Game Information &aflet No. 60. Armstrong, RA. 1950. Fetal development of the northern white-tailed deer (Odocoileus virgin/anus borealis, Miller). American Midland Naturalist 43:650-666. Asch, RH., F. J. Rojas, T. R Tice, and A. V. Schally. 1985. Studies of a controlled- release microcapsule formulation of an LH-RH agonist in the rhesus monkey menstrual cycle. Int. J. Fert. 30:19-26. Asher, G. W. 1985. Oestrous cycle and breeding season of farmed fallow deer, Dama dama. J. Reprod. Fertil. 75:521-529. Baker, D. L., M. W. Miller, and T. M. Nett. 1995. Gonadotropin-releasing hormone analog-induced patterns ofluteinizing hormone secretion in female wapiti (Cervus elaphus nelsoni) during the breeding season, anestrus, and pregnancy. Biol. ofReprod. 52:1193 - 1197. Bartmann, RM. 1986. Growth rates of mule deer fetuses under different winter conditions. Journal of Wildlife ~ement 46:245-248. Bartmann, RM., G. C. White, and L. C. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs No. 121. 39pp. Becker, S. E., Katz, L. S. 1995. Effects of gonadotropin - releasing hormone agonist on serum LH concentrations in female white-tailed deer. Small Ruminant Research 18:145-150. Casper, RF., and S.S. C. Yen. 1979. Induction ofluteolysis in the human with a long-acting analog of luteinizing hormone-releasing fuctor. Science 205:408-410. Clayton, R. N. 1982. GnRH modulation of its own pituitary receptors: evidence of biphasic regulation. Endocrinology 111:152-161. Cole, G. F. 1971. An ecological rationale for the natural or artificial regulation of native ungulates in parks. Transactions of the North American Wildlife and Natural Resources Conference 36:417426. Concannon, P. W., and V. N. Meyers-Wallen. 1991. Current and proposed methods for contraception and termination of pregnancy in dogs and cats. J. Am. Vet. Med. Assoc. 198:1214-1225. �231 Curlewis, J. D., A. S. I. Loudon, and A. P. M. Coleman. 1988. Oestrous cycles and the breeding season of the Pere David's deer hind (Elaphurus davidianus). J. Reprod. Fert. 82: 119-126. Dasmann, R. F., and R. D. Taber. 1956. Determining structure in Columbian black-tailed deer populations. Journal of Wildlife Management 20:78-83. Decker, D. J., and Gavin. 1987. Public attitudes toward a suburban deer herd. Wildlife Society Bulletin 16:53-75. Diamond, J. 1992. Must we shoot deer to save nature? Natural History August: 2-8. Fraser, H. M. 1983. Effect of treatment for one year with a luteinizing hormone-releasing hormone agonist on ovarian, thyroidal, and adrenal function and menstruation in the stumpta.iled monkey (Macaca arctoides). Endocrinology 112:245-253. __, M., J. Sandow, H. Seidel, and W. von Rechenberg. 1987. An implant of a gonadotropin releasing hormone agonist (burserelin) which suppresses ovarian function in the macaque for 3-5 months. Acta Endocrinologica 115: 521-427. Garrot, R. A. 1995. Effective management of free-ranging ungulate populations using contraception. Wildlife Society Bulletin. 23:445-452. Guinness, F. E., Lincoln, G. A., and Short, R. V. 1971. The reproductive cycle of the female red deer, Cervus elaphus L. J. Reprod. FertiL 27: 427-438. Hess, K. 1993. Rocky times in Rocky Mountain National Park. University. Press of Colorado, Niwot, Colorado. Herschler, R. C., and B. H. Vickery. 1981. The effects of LHRH ethylamide on the estrous cycle, weight gain, and feed efficiency in feedlot heifer. Amer. J. of Vet. Res. 42: 1405- 1408. Hobbs, N. T., D. L. Baker, and R. B. Gill. 1999. A general theory describing effects of fertility control on populations of ungulates. Journal ofWildlife Management (in press). Hone, J. 1992. Rate of increase and fertility control. J. Applied Ecology 29:695-698. Hudson, P., and L. G. Ludvig. 1959. Embryonic and fetal development of mule deer. Journal of Wildlife Management 23:295-304. Houston, D. B. 1971. Ecosystems of national parks. Science 172:648-651. __, 1982. The Northern Yellowstone Elk: Ecology and Management. MacMillan Publishing Company,. New York, New York. Jewell, P.A., and S. Holt. 1981. Problems in management oflocallyabundant wild animals. Academic Press. 32lpp. Jopson, N. B., M. W. Fisher, and J.M. Suttie. 1990. Plasma progesterone concentrations in cycling and ovariectomized red deer hinds: the effect of progesterone supplementation and adrenal stimulation. Animal Reprod. Sci. 23 :61-73. Kelly, R. W., K. P. McNatty, G. H. Moore, D. Ross, and M. Gibb. 1982. Plasma concentrations ofLH, prolactin, oestradiol and progesterone in female red deer during pregnancy. Journal of Reproduction and Fertility 64:475-483. Kirkpatrick, J. F., and J. W. Turner, Jr. 1985. Chemical fertility control 31!d wildlife management. Bioscience 35:485-491. Lehner, P. N. 1987. Design and execution of animal behavior research: an overview. Journal of Animal Science 65: 1213-1219. McCullough, D.R., K. W. Jennings, N. B. Gates, B. G. Elliot, and J.E. Didonato. 1997. Overabundant deer populations in California. Wildlife Society Bulletin 25:478-483. McNeilly, A. S., and H. M. Fraser. 1987. Effect of gonadotropin-releasing hormone agonist-induced suppression of LH and FSH on follicle growth and corpus luteum function in the ewe. J. Endocrinology 115:273-282. Medin, D. E., and A. E. Anderson. 1979. Modeling the dynamics ofa Colorado mule deer population. Wildlife Monographs No. 68. 77pp. Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epidemiology of chronic wasting disease in captive rocky mountain elk. Journal of Wildlife Diseases 34:532-538. �232 Miller, R.G. 1966. Simultaneous statistical inference. New York: McGraw-Hill Book Co. 152-168. Morrison, J. A. 1960. Characteristics of estrus in captive elk. Behavior 16:84-92. Morrison, D. F. 1976. Multivariate statistical methods. New York: McGraw-Hill Book Co. 145-194. Niswender, G.D., L. E. Reichert, Jr., A. R. Midgley, Jr., and A. V. Nalbandov. 1969. Radioimmunoassay for bovine and ovine luteinizing hormone. Endocrinology 84: 1166-1173. _ _ . 1973. Influence of the site of conjugation on the specificity of antibodies to progesterone. Steroids 22:413-424. O'Bryan, M. K., and D.R. McCullough. 1985. Survival of black-tailed deer following relocation in California. Journal ofWildlife Management 49:115-119. Robinette, W. L., and J. S. Gashwiler. 1955. Fertility of mule deer in Utah. Journal ofWildlife Management 19:115-136. Sandow, J. 1982. Inhibition of pituitary and testicular function by LHRH analogs. Pages 19-39 In: Jeffcoate S. L. and Sandlier (eds). Progress towards a male contraceptive. Wiley and Sons, Chichester. Singer, F. J., L. C. Zeigenfuss, R. G. Cates, and D. T. Barnett. 1998. Elk, multiple factors, and persistence of willows in national parks. Wildlife Society Bulletin 26:419-428. Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. J. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, J.M. Miller, and P.A. Merz. 1997. Spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoi/eus virginianus), and Rocky Mountain elk (Cervus elaphus nelsoni) in northcentral Colorado. Journal of Wildlife Diseases 33:1- 6. Vale, W., C. River, M. Brown, J. Leppaluoto, N. Ling, M. Monaham, and J. River. 1976. Pharmacology of hypothalamic peptides. Clio. Endocrin. 5(suppl): 261-273. Wagner, F. H., R. Foresta, R. B. Gill, D.R. McMullough, M. P. Pelton, W: F. Porter, and H. Salwasser. 1995. Wildlife policies in the U. S. National Parks. Island Press. Washington, D. C. 242pp. Warren, R. J., L. M. White, W.R. Lance. 1995. Management of urban deer populations with contraceptives: practicality and agency concerns. Wildlife Society Bulletin 23:441-444. White, C. A., C. E. Olmsted, and C. E. Kay. 1998. Aspen, elk, and fire in the Rocky Mountain national parks of North America. Wildlife Society Bulletin 26:449-462. Whittaker, D. G. 1995. Patterns of coexistence for sympatric mule and white-tailed deer on Rocky Mountain Arsenal, Colorado. Ph.D. Dissertation, University of Willard, S. T., R. G. Sasser, J.C. Gillespie, J. T. Jaques, T. H. Welsh, Jr., and R. D. Randel. 1994. • Methods for pregnancy determination and the effects of body condition on pregnancy status in Rocky Mountain elk. Theriogenology 42:1095-1102. Wright, R. G. 1988. Wildlife issues in national parks. Pp. 168-196 in W. J. Chandler (ed) Audubon Wildlife Report, National Audubon Society. _ _ 1992. Wildlife management and research in the national parks. University of Illinois Press. 224pp. Prepared by _ _ _ _ __ DanL. Baker Research Biologist � https://cpw.cvlcollections.org/files/original/9bdc01ae5ab39a2280ec012171d96662.pdf 113ce9dd666345a864ca310d412f6187 PDF Text Text 135 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT State of Colorado cost center 3430 Project No. W-153-R-ll Mammals Program 3001 Deer conservation Work Package No. Task N o . - - - - - - - - ~ - - - - - Period Covered: Author: Experimental Deer Inventory July 1, 1997 - June 30, 1998. R. M. Bartmann, T. M.. Pojar. Personnel: R. Arant, L. Bennett, G. Bock, D. c. Bowden, D. coven, M. Leslie, D. Masden, K. Miller, J. Olterman, M. Potter, G. Schoonveld, H. Spear, s. Steinert, J. Thomson, B. Watkins, G. c. White, and D. Younkin. Abstract An inventory system was developed to enable more precise monitoring of mule deer (Odocoileus hemionus) population status. It was implemented in 2 Data Analysis Units (DAU) in late 1997. A spreadsheet model was used to identify key parameters for model inputs. Allocation of sampling effort among the surveys required to obtain parameter estimates was based on annual variability associated with those estimates and sensitivity of the model to change in those estimates. Key parameters are· annual doe survival~ overwinter fawn survival, fawn:doe ratio and proportion of does in the population obtained from age/sex surveys, population size, and harvest. In D4, the fawn:doe ratio estimate was 58.8:100. None of 30 radiocollared does died during the segment and 10 of 38 fawns died for a 74% survival. In D19, the fawn:doe ratio estimate was 34.2:100. Five of 31 does died for an 84% survival and 20 of 39 fawns died for a 49% survival. A quadrat census to estimate population size could not be done in either DAU. �137 EXPERIMENTAL DEER INVENTORY Richard M. Bartmann and Thomas M. Pojar P. N. OBJECTIVES 1. Develop and test an experimental deer inventory system in 5 DAU's in western Colorado to determine efficacy in monitoring deer population status. 2. Publish results in a peer-reviewed scientific journal. SEGMENT OBJECTIVES 1. Estimate the annual doe survival rate in DAU's D-4 (Red Feather) and D-19 (Uncompahgre). 2. Estimate the over-winter fawn survival rate in DAU's D-4 (Red Feather) and D-19 (Uncompahgre). 3. Estimate the December fawn:doe and buck:doe ratios in DAU's D-4 (Red Feather) and D-19 (Uncompahgre). 4. Estimate winter deer density in DAU's D-4 (Red Feather) and D-19 (Uncompahgre). 5. Develop a spreadsheet model for predicting deer population performance in DAU's D-4 (Red Feather) and D-19 (Uncompahgre). 6. Analyze data and prepare an annual Federal Aid Job Progress report. INTRODUCTION During the early 1990's, mule deer populations in much of Colorado and the west began declining. The Colorado Division of Wildlife (CDOW) has collected data on deer populations for many years. These data consist primarily of harvest estimates collected state-wide every year, age/sex classifications made in most Game Management Units (GMU) every 1 or more years, and population estimates made in a few GMU's or DAU's infrequently. These data were assembled to try and determine if and when a deer decline occurred and its magnitude (Colo. Div. Wildl., unpubl. rep.). It was concluded the occurrence of a large-scale deer decline might be inferred but evidence was weak. This was partly because the data were inconsistent in the timing and manner in which they were collected, and also because additional key data on survival rates were not available. Thus, a new deer monitoring system was needed that would enable assessing deer population performance in a more timely and precise manner. STUDY AREAS It was originally planned to establish a new deer inventory system in 5 DAU's around the state. Later, it was decided that for evaluation purposes, 3 would suffice. Because of financial constraints, the system was implemented in 2 �138 DAU's the first year with the third DAU to be included the second year. The 2 DAU's selected for initial implementation of a new deer inventory system were D-4 ( Red Feather) in the northern front range and D-19 (Uncompahgre) in southwest Colorado. DAU D-4 consists of GMU's 7, 8, 9, 19, and 191. Winter range is a mountain shrub type with Ponderosa pine (Pinus ponderosa)- Douglas fir (Pseudotsuga menziesii) overstory in many places. DAU D-19 consists of GMU's 61 and 62. Winter range is primarily a pinyon (Pinus edulis)-juniper (Juniperus osteosperma)-sagebrush (Artemisia tridentata) type with considerable oakbrush (Quercus gambelli) interspersed. METHODS survival Basic methods for both DAU's were the same, although timing of their implementation varied. Annual doe survival and over-winter fawn survival were estimated from a sample of radio-collared animals. Seventy radiocollars were available the first winter and allocated to 30 does and 40 fawns. Deer were captured in early winter by netgunning from a helicopter. Annual doe survival was estimated for the period 1 December to 30 November. over-winter fawn survival estimated from 1 December to 15 June when they were considered adults. Capture locations were originally randomized throughout the winter range in each DAU, but problems developed with private land access and finding deer. Consequently, the helicopter crew was sent to accessible areas where deer were known present and instructed to put out a certain number of doe and fawn radiocollars. Each radiocollar had a mortality mode set for a 3-4-hour delay with frequencies in the 148-151 MHz range. Fawn collars were a drop-off type so they could be retrieved and reused. This precluded getting survival information on yearling females from 15 June to 30 November. Data from Piceance Basin indicates this is not a critical period from a survival standpoint, except during the hunting season, and hunting mortalities are censored anyway. Radiocollared deer were monitored from the air a minimum of once every 2 weeks from December through June. Each mortality was checked as soon as possible to try and determine cause of death. A~e/sex classifications Age/sex classifications were used to estimate fawn recruitment to December and post-season buck:doe ratios. A random-route survey was already in place in D4 and was used without modification for this study. Fifteen existing census quadrats were randomly selected and a route passing through each quadrat devised. The route was flown with a Bell Soloy helicopter using a GPS unit for navigating from point to point. In D-19, a random-route survey was designed similar to that in D-4. Each GMU was divided from north to south into strata at 1,000-meter intervals along UTM coordinates. Two existing census quadrats were randomly selected in each strata within a GMU and, starting at the top of the GMU, a line was drawn to connect quadrats in a zig-zag pattern from north to south. The process was then repeated for the other GMU. �139 Deer in groups encountered along the flight path were classed as fawns, does, bucks, or unknown. Estimates of fawn:doe and buck:doe ratios were based on groups using the estimator developed by Bowden et al. (1984). Population Size Deer population size was estimated from counts of deer on 0.65-km2 quadrats using procedures described by Kufeld et al. (1980). A quadrat census system was established in D-4 in 1985 and has been flown 7 times, the last in January 1997. The current design includes 98 quadrats in 15 strata, but the original data on the total sample area and strata poundaries could not be found. There was not enough time to gather the needed data to define a new total sample area and re-stratify, so the quadrat census was to be flown as in the past. The exception was that a Bell Soley helicopter was to be used instead of a Jet Ranger. Snow conditions along the front range are undependable. When adequate snow does occur to provide a good counting background, it usually lasts only a few days. Helicopters need to be scheduled in advance, so the chance of encountering good counting conditions was minuscule. Therefore, it was decided the D-4 survey would be flown regardless of snow cover. A quadrat census was established in GMU 62 in 1976. It was expanded to include GMU 61 in 1981. There are 346 quadrats in 13 strata which took -70 hours to survey. Only 30 hours were allocated for the census, so the number of quadrats was reduced to 140 by random selection. Population Model The POPII model is currently used to help manage deer populations. The model is complex and requires numerous parameter estimates with no supporting data. As a result, people are free to manipulate various parameters to try and make the model fit their preconceived ideas. A much simpler model is needed for which key inputs are derived from sample-based estimates. The new model will help determine the key types of data required and how to allocate costs and effort to obtain them. RESULTS Doe survival P.=.i: Thirty does were captured and radiocollared from 4-7 January 1998. The delay from the desired late November period was caused by contract problems. Monitoring was done from a fixed-wing aircraft about once every 2 weeks through June 1998. No does died during that period (Table 1). 12=.l.2.: Does were captured and radiocollared from 15-20 December 1997. Here again contract problems delayed the process. The first two does captured were given fawn radiocollars by mistake. Consequently, 31 does were finally radiocollared. Monitoring from a fixed-wing aircraft was done weekly the first month, but was increased to twice weekly the rest of the winter and spring to try and locate mortalities quicker. As of 30 June, 5 of the 31 does had died for a survival estimate of 84%. Annual doe survival is monitored until 30 November, so this rate could go lower. �140 Table 1. Fates of mule deer does and fawns radiocollared in DAU's D-4 (Red Feather) and D-19 {Uncompahgre) during the 1997-98 winter. D-4 Fate D-19 Does Fawns Does Fawns 30 28 26 19 Coyote 3 3 10 Lion 1 1 1 Survived Bobcat Unknown Predator 1 2 1 Starvation 1 1 Accident 1 1 Undetermined 3 5 Fawn survival ~ : Thirty-eight fawns were captured and radiocollared during the same period as for does. Two collars were temporarily misplaced and not put out. Ten fawns died for an over-winter survival rate of 74%. ~ : A doe radiocollar was erroneously placed on a fawn. This, together with the 2 fawn collars placed on does, resulted in only 39 fawns being radiocollared. Twenty fawns died by 15 June for an over-winter survival rate of 49%. The fawn that received a doe collar was 1 of the mortalities which eliminated the need to recapture it to prevent choking when it got older. Age/Sex Classifications D.=_4: The classification survey was flown 16-18 December. There were 950 deer classified for a fawn:doe ratio of 58.8 (95% CI= 52.9-65.2) and buck:doe ratio of 23.8 {95% CI= 19.4-28.6). ~ : The classification survey was flown 11-13 December. The random routes only took about 5 hours to complete with 358 deer classified. To use more of the 15 hours allocated for the survey, a non-random route was flown through the longer north-south length of each GMU. This produced another 831 deer in abo_ut •the same amount of time as for the random routes. For all data combined, the fawn:doe ratio estimate was 34.2 {95% CI= 30.937.7) and the buck:doe ratio estimate was 11.1 (95~ CI= 8.9-13.4). Comparing results from 2 route types, the fawn:doe ratio estimate was marginally higher (35.3 vs. 31.8) while the buck:doe ratio was nearly twice as high (12.8 vs. 7.0) on the non-random routes. Thus, the observer's knowledge about where to find large numbers of deer could bias ratio estimates, particularly for bucks. Population size D.=_4: contract problems prevented getting a helicopter before the mid-January cutoff date for conducting the survey, so it was not flown. �141 D.=.J..2.: Adequate snow conditions did not occur until late January. A population estimate has not been made since 1994, so it was decided to do the survey even though it was past the 15 January cutoff. Work was started 27 January, but weather and other problems prevented the survey from being completed in a reasonable time span, so it was canceled on 12 February after 63 quadrats had been flown. A valid population estimate cannot be made based on this incomplete data. Population Model Development of a population model to identify key inputs for refining the deer inventory system was begun with cooperators from Colorado State University. Deer population dynamics are much more complicated than the model portrays, but routine measurement of the wide array of inputs required for a more complicated model is unrealistic. Thus, it is a reasonable trade-off between what we can measure from a practical standpoint and what is needed to predict deer population status for management purposes. The model concentrates on predicting changes in the adult doe portion of the population as this is the key to evaluating population status. The model has only 2 age classes (fawns and adults) assigned to 3 categories (fawns, does, and bucks). Fawns are initially recruited to the population on 1 December when the fawn:doe ratio is estimated from age/sex classifications. The model contains 4 parameters that are year-specific: annual buck survival, annual doe survival, over-winter fawn survival, and December fawn recruitment. Buck survival has no influence on population status unless their numbers drop low enough to affect breeding; a phenomenon yet to be documented in hunted populations. Therefore, there is no real need for an estimate of buck survival. An indication of status can be derived from the buck:doe ratio estimate obtained from age/sex surveys, and the number of new bucks recruited is estimated from male fawns that survive to become yearlings. Thus, only the last 3 parameters need to be considered for the model. The strategy for managing a mule deer population is to estimate the doe segment so harvest can be adjusted to maintain the December doe population at some desired level. To do this, 3 more parameters have to be estimated in addition to the 3 mentioned above: total population size, the proportion of the population that is does, and doe harvest. A harvest estimate is already available from another source and fawn recruitment and the proportion of does in the population are obtained from the same survey, so we only need to consider 4 surveys to obtain 5 parameter estimates. The problem now comes down to how to allocate costs and effort to these 4 surveys to derive estimates of the 5 parameters that will result in the most precise prediction of the December doe population or, alternatively, the annual rate of population increase. Either will indicate the number of does that must be harvested to maintain the desired doe population level. This process is ongoing and will be completed in the next segment. �142 LITERATURE CITED Bowden, D. c., A. E. Anderson, and D. E. Medin. 1984. Sampling plans for mule deer sex and age ratios. Journal of Wildlife Management. 48:500-509. Kufeld, R. c., J. H. Olterman, and D. c. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management. 44:632-639. /? ~repared by ~ ~~\;£:::;______ WildLi.fe Researche~ ~%~ Wildlife Researcher ��85 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB FINAL REPORT State of: Colorado Project No. W-153-R-12 Work Package No._3~0~0~1~-----Task No. I Cost Center 3430 Mammals Program Deer Conservation Experimental Deer Inventory Period Covered: July 1, 1998 - June 30, 1999 Authors: R B. Gill, and T. M. Pojar Personnel: G. Schoonveld, S. Steinert, J. Olterman, C. Wagner, B. Watkins, R Bartmann, G. White ABSTRACT Over-winter (Nov-May) survival rates were estimated for 3 Data Analysis Units: Red Feather (D-4), Middle Park (D-9), and Uncompahgre (D-19). Overall 3 study areas, doe survival averaged 91.7% and fawn survival averaged 79.4%. Population estimates were obtained for D-9 in late January, 1999 by flying square mile quadrats allocated according to a stratified random sampling scheme. Deer density averaged 12.93 deer/km2 and projected to a total population of 11,016 deer± 2,337 (90% CI). Estimates of the ratios of bucks and fawns:100 does were obtained from helicopter counts conducted in December 1998. The buck:doe ratio was estimated to be 27 bucks: I 00 does. The fawn:doe ratio was estimated to be 62 fawns: I 00 does. �87 EXPERIMENTAL DEER INVENTORY R. Bruce Gill and Thomas M. Pojar P.N. OBJECTIVES I. Develop and test an experimental deer inventory system in 5 DAUs in western Colorado to determine efficacy in monitoring deer populations. 2. Publish results in a peer-reviewed scientific journal. SEGMENT NARRATIVES I. Estimate the annual doe survival rate in DAUs D-4 (Red Feather), D-9 (Middle Park), and D-19 (Uncompahgre). 2. Estimate over-winter fawn survival rate in DAUs d-4 (Red Feather), D-9 (Middle Park), and D19 (Uncompahgre). 3. Estimate the December fawn:doe and buck:doe ratios in DAU D-9 (Middle Park). 4. Estimate winter density in DAU D-9 (Middle Park). 5. Develop a spreadsheet model for predicting deer population performance in DAUs D-4 (Red Feather), D-9 (Middle Park), and D-19 (Uncompahgre). 6. Analyze data and prepare an annual Federal Aid Job Progress Report. INTRODUCTION Initial plans called for the development and testing of experimental inventory systems on 5 deer _Data Analysis Units (DAUs) across Colorado's important deer herds. Manpower and financial constraints limited the scope to 3 DAUs: Red Feather (D-4), Middle Park (D-9), and Uncompahgre (D-19). Measurements on each DAU were to continue for a period of 3-5 years before deciding whether to expand implementation of the experimental deer inventory system. However, the project's principal investigator, Richard M. Hartmann, retired during the segment and his vacancy remains unfilled. Consequently, it was decided to terminate the R&D component of the inventory system at the end of the current segment. This report, therefore, constitutes the Final Report of activities accomplished under Work Package 3001, Task I. STUDY AREAS Study aras D-4 and D-19 were described previously (Hartmann and Pojar 1998). Study area D-9 is situated in the headwaters area of the the Colorado River drainage encompassing areas below approximately 2,600 min elevation in Grand and Summit Counties. Winter range is primarily �88 sagebrush steppe vegetation type characterized by low growing(< 1 m) shrubs. Sagebrush species (Artemisia tridentata tridentata andArtemisia tridentata vaseyana) predominate with other shrub species such as rubber rabbitbrush (Chrysothamnus nauseosus), sticky-flowered rabbitbrush (Chrysothamnus viscidifloris), mountain snowberry (Symphoricarpus oreophilus), bitterbrush (Purshia tridentata), serviceberry {Amelanchier alnifo/ia), and chokecherry (Prunus virginiana)locally abundant (scientific names ·according to Weber 1976). Mule deer winter over approximately 850 km2 below 2600 m in elevation. METHODS Bartmann and Pojar (1998) thorougly described the methods used in this investigation, so they will not be repeated here. RESULTS Doe Survival Across all 3 study areas, doe survival during winter 1998-99 averaged 91. 7% with 121 of 132 does surving from November 1998 through May 31, 1999. This compares to an over-winter survival rate of 90.1 % for adult does throughout the previous winter (Bartmann 1998). No single source of mortality stood out as a primary {Table 1) which was similar to results from 1997-98. Fawn Survival In general, fawn survival throughout winter 1998-99 increased compared to 1997-98. In 199899, 127 of 160 radio-collared fawns survived from November 1, 1998 through May 31, 1999 for an overran survival rate of 79. 4 %. In 1997-98, 61. 0% of radio-collared fawns overall survived the winter. Sex and Age Composition Classification counts of mule deer in Middle Park Data Analysis Unit (D-9) were conducted during the period December 22-24, 1998 and included a total of912 deer, of which 15.9% were bucks, 32. 0% were fawns, and 52.1 % were does (Table 2). The ratio of bucks per 100 does computed to 30.5 ±4.8 bucks: 100 does and 61.5 ±7.5 fawns:100 does. Population Density Middle Park Data Analysis Unit (D-9) deer census quadrats were flown during the fourth week in January, 1998. Counting conditions and deer distribution were both ideal. Overall, 2,415 deer were tallied on 56 sample quadrats. Number of deer/km2 averaged 12.93 with a standard error of 4.00. When projected over the entire winter range ofD-9, the deer population was estimated at 11,016 deer ±2,337 (90% {Table 3). en �89 Table l. Fates of mule deer does and fawns radiocollared in DAUs D-4 (Red Feather), D-9 (Middle Park}, and D-19 (Uncomeahgre} during the 1998-99 winter. Red Feather Fate Uncompahgre Middle Park Does Fawns Does Fawns Does Fawns Total Radiocollared S2 so 40 so 40 60 Survived 4S 40 39 44 37 43 Coyote predation l 4 0 l l 7 2 0 0 0 2 1 0 3 0 2 2 0 0 0 0 0 0 0 0 0 0 2 Accidents 0 0 0 0 0 Unknown 2 0 0 2 4 10 1 6 J 17 Mtn. lion predation Other predators 0 Road kills 0 Hunter kills 2 Starvation 0 7 Total Mortality 1Total does not equal 100% because of rounding error. Table 2.- Results of mule deer classification counts in Middle Park Data Analysis Unit (D-9), December 22-24, 1998. GMU I-yr bucks 2-yr bucks Adult bucks Total bucks Does Fawns Total 12/23/98 27 6 6 ·3 15 66 44 12S 12/22-24/98 37 27 23 19 69 17S 98 342 12/23-24/98 181 6 5 2 13 44 17 74 12/23-24/98 28 7 12 3 22 130 92 244 12/24/98 18 11 10 5 26 60 41 127 -. - <ih Date Totals 32 145 47S 292 D-9 Swrunary 1-yr bucks: 100 does 2-yr bucks:100 does Adult bucks:100 does Total bucks:100 does Fawns:100 does Ratio estimates 12.0 11.8 6.7 30.S 61.S Lower90%CI 9.3 9.1 4.8 2S.9 54.3 Upper9O%CI 14.8 14.6 8.8 35.5 69.4 S7 56 �90 Table 3. Deer quadrat census results for Middle Park Data Analysis Unit (D-9), January 1998. Stratum Strata Deer Counted (km2) Population Estimate N n Total Dccr/km2 SE Total ±_90% 80.3 28.5 582 20.43 12.34 1640 629 2 222.7 10.4 13 1.25 3.17 280 449 3 189.1 46.6 . 730 15.66 7.64 2961 918 4 121.7 15.5 144 9.27 9.84 1128 761 5 72.5 15.5 378 24.33 26.41 1764 1216 6 88.1 15.5 494 31.79 24.59 2799 1375 7 77.7 12.9 74 5.71 5.40 444 266 Overall 852.1 145.0 2415 12.93 4.00 11016 2337 Spreadsheet Models A spreadsheet population model was developed in a Quatro Pro spreadsheet format for Red Feather (D-4), Middle Park (D-9), and Uncompahgre (D-19) Data Analysis Units. Disk copies of spreadsheets for each DAU were sent to Area Biologists responsible for managing each DAU. Copies of the spreadsheet fonnat may be obtained by writing to: Dr. Gary C. White 211 B JVK Wagar Bldg. Department of Fishery and Wildlife Biology Colorado State University Fort Collins, CO 80523 LITERATURE CITED Bartmann, R. M., and T. M. Pojar. 1998. Experimental deer inventory. Colorado Division of Wildlife. Wildlife Research Report, July, 1998, Part II: 135-142. Weber, W. A. I 976. Rocky mountain flora. Colorado Associated University Press. Boulder, CO. Prepared by _ _ _ _ _ _ _ _ _ __ R. Bruce Gill Wildlife Research Leader Thomas M. Pojar Wildlife Researcher � https://cpw.cvlcollections.org/files/original/9d51d60d346754558d312f84eb413df6.pdf d9368aa01bdf206ea3dd3a0f9b262bd5 PDF Text Text 145 DEER REPRODUCTION ASSESSMENT Richard M. Bartmann and Thomas M. Pojar P, N, OBJECTIVES 1. Estimate the variation in pregnancy-specific protein B (PSPB) levels in mule deer does in Game Management Unit (GMU) 19 (Poudre). 2. Develop a study plan to compare current mule deer reproductive rates to historic data to determine if differences exist that might contribute to the recent decline in deer populations in Colorado. SEGMENT OBJECTIVES 1. Estimate the variation in PSPB levels in mule deer does during 2 winter periods in GMU 19. 2. Test for differences in pregnancy rates of mule deer does between the 2 winter sample periods. 3. Develop a study plan to compare current and historic reproductive rates of mule deer in at least 2 areas of Colorado. 4. Analyze data and prepare an annual Federal Aid Job Progress report. INTRODUCTION An assessment of mule deer population status during the early to mid-1990's indicated that many populations across western Colorado had declined to various extents. However, the cause(s) was not identified. One indication of a problem was detection of a significant decline in December fawn:doe ratios in some DAU's over the past 20+ years. This suggested a possible problem with reproduction or neonatal mortality. A logical starting point to try and identify a problem was the breeding season--were does being bred? This was also the easiest aspect to investigate because it did not require killing deer to obtain samples. STUDY AREAS GMU 19 was selected for study because there was historic data for comparison. Winter range along the northern front range is a mountain shrub type with Ponderosa pine (Pinus ponderosa)-Douglas fir (Pseudocsuga menziesii) overstory. METHODS Pregnancy detection was via blood analysis to determine levels of PSPB. PSPB levels in blood have been used to detect pregnancy with a high degree of accuracy in various species including mule deer (Wood et al. 1986). Detection times post-conception have varied among species, but is generally considered reliable after about 24 days with cattle (Sasser et al. 1986). Therefore, delaying blood sample collection until early January was considered to provide an adequate interval post-breeding for detecting PSPB. Delaying the second set of collections until early February would detect pregnancies from �146 conceptions during the second estrus and provide an indication of the extent of late breeding. From 15-20 does (~1-year-old) were to be captured with Clover traps in early January and again in early February. However, helicopter netgunning of deer for survival work in DAU D-4, of which GMU 19 is part, was delayed until early January, so it was decided to collect blood samples from does captured for that project. Blood samples were submitted to BioTracking in Moscow, Idaho to assess levels of PSPB to determine pregnancy status. RESULTS Blood samples were obtained from 29 does captured 4-7 January 1998. Twentyseven were considered pregnant and 2 not pregnant. One doe was at the cut-off point of 93% (93.1%) and may have been a late breeder. The range in values for the pregnant does was 84.3-93.l with mean 88.5 and SE 0.36. Values for the 2 non-pregnant does were 102.6 and 102.8. The 27 pregnancies yielded a 93% pregnancy rate with all except possibly 1 apparently bred during the first estrus. Thus, late breeding did not appear a problem so no collections were done in February. The 93% pregnancy rate is barely significantly lower (P = 0.062) than the 100% rate derived from data for 49 does collected in GMU 19 from January-May 196165 (Anderson 1965a, 1965b, 1966). However, it is still considered a high rate with the conclusion that conception is apparently not a problem in DAU D-4. A next step would be to determine fetal rates, but this would involve euthanizing a large number of does during mid to late winter. One option is to have hunters collect does, but hunting seasons that late in winter are not well accepted. Therefore, no further work is planned to evaluate reproductive status until a satisfactory collection method is found for estimating fetal rates. LITERATURE CITED Anderson, A. E. 1965a. Reproductive studies. Colo. Dep. Game, Fish and Parks, Game Res. Rep. January:165-195. Anderson, A. E. 1965b. Reproductive studies. Colo. Dep. Game, Fish and Parks, Game Res. Rep. January:522-543. Anderson, A. E. 1966. Reproductive studies. Colo. Dep. Game, Fish and Parks, Game Res. Rep. January:275-307. Sasser, R. G., C. A. Ruder, K. A. Ivani, J.E. Butler, and w. C. Hamilton. 1986. Detection of pregnancy by radioimmunoassay of a novel pregnancyspecific protein in serum of cows and a profile of serum concentrations during gestation. Biol. Reprod. 35:936-942. Wood, A. K., R. E. Short, A. Darling, G. L. Dusek, R. G. Sasser, and C. A. Ruder. 1986. Serum assays for detecting pregnancy in mule and whitetailed deer. Journ:il of Wildlife Management. 50:684-687. ,,.71__ L - Prepared by .J(~~~,-_hJ:.~~d~;_:z.iiB~artm;;;zt.~~;n~n=··-=···=····==···=·:--:==::::::==-==WildLi.fe Researche~ Wildlife Researcher � https://cpw.cvlcollections.org/files/original/ebc33e7482d03efc32e7a2da5171b65d.pdf 3f9484b94f4f64460ae4c5468366fd41 PDF Text Text 147 Colorado Division Wildlife Research July 1998 of Wildlife Report JOB PROGRESS REPORT State of Project Work No. Package Colorado Cost Center W-153-R-ll Mammals No. ~3~0~0~1L_ Task No. Period _ 3430 Program Deer Conservation Monitoring and Managing Chronic Wasting Disease in Deer Covered: July 1, 1997 - June 30, 1998 Authors: M. W. Miller Personnel: S. Berry, K. Larsen, Wheeler, M. A. Wild, K. 1. O'Rourke, T. R. Spraker, and E. S. Williams S. Tracy, E. ABSTRACT Deer from throughout Colorado were examined for occurrence of chronic wasting disease using a combination of targeted surveys and harvest/road-kill surveys. We continued to develop and modify a statewide targeted surveillance program for acquiring, examining, and reporting on CWO suspects submitted from Colorado. Between June 1997 and May 1998, 6 chronic wasting disease (CWO)· cases were diagnosed among 16 "suspect" deer submitted from known endemic portions of northeastern Colorado; CWO was not diagnosed in any of 7 additional "suspect" deer submitted from elsewhere in Colorado. All confirmed CWO cases originated in game management units (GMUs) where the disease had been detected previously. Harvest and road-kill surveys were used to estimate CWO prevalence in enzootic management units. About 4.2% of deer harvested in Larimer County data analysis units (DAUs) (D4 or D10) and about 1.1% of deer harvested in South Platte River bottom units (DAU D44 plus GMUs 87, 90, 93, and 95) tested positive for CWO via immunostaining; none of the 171 deer harvested or culled in other select GMUs outside known enzootic areas tested positive for CWO. Prevalence estimates may be somewhat liberal because subclinical cases where either histopathological lesions or anti-PrP immunostaining reactions in brain tissue were included; of the 44 cases identified, ~none appeared to be suffering from clinical CWO and only 26 of 44 (59%) "positive" deer showed both histopathological lesions and immunostaining. In contrast to earlier observations derived from targeted surveillance data, CWO prevalence among male and female mule deer did not differ (P = 0.86). Age distribution of CWO-positive mule deer did not differ from sex-specific age distributions of negative animals. These data support the belief that CWO epidemiology is driven primarily by lateral transmission. �148 Requiring head submissions increased survey sample sizes for deer >4-fold compared to voluntary submissions in 1996. Based on harvest estimates from surveyed GMUs, compliance with mandatory submission regulations was about 75%. Unstaffed barrel sites still appear to be the most efficient method for sample collection~ Data from both targeted surveillance and surveys indicate that eastern Larimer County remains the most significant focus of CWO in Colorado, although some natural spread may be occurring both southward and eastward. Targeted ,surveillance of clinical suspects appears to be the most sensitive approach for initially detecting CWO in deer (and elk) populations throughout Colorado, and should be continued statewide. Once detected, combinations of harvest and road-kill surveys will be employed to estimate prevalence, monitor prevalence trends, and compare prevalence among DAUs. 'Because CWO appears to be more prevalent in deer than in elk in endemic areas, it follows that harvest surveys in high-risk areas should focus on deer rather than elk to be most effective in confirming absence of CWO in nonendemic areas. Cwo affected about 25% (5/25) of the adult (~1-yr-old) mule deer and about 46% (5/11) of the adult white-tailed deer in resident Foothills Wildlife Research Facility herds during the last biological year; CWO accounted for 83% of adult mule deer mortality and 100% of adult white-tailed deer mortality. Resident mule deer also represented the source of infection (treatment) in an ongoing 10-yr study of cattle susceptibility to CWO. No signs of neurological disease were observed in any of the 12 calves (subjects) or 12 mule deer fawns from the Rocky Mountain Arsenal National Wildlife Refuge (contact controls) housed with naturally~infected resident deer since July 1997; one calf died from gastrointestinal obstruction and bloat about 2 wk after entering the deer paddocks, and one fawn that apparently failed to adjust to captivity died about 1 mo after capture, presumably from hypothermia secondary to malnutrition. �149 MONITORING AND MANAGING CHRONIC WASTING DISEASE IN DEER M. W. Miller P. N. OBJECTIVES (1) Design, conduct, and report results of: (a) targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWO) in free-ranging deer populations; and (b) harvest or road-kill surveys to estimate and detect prevalence of CWO in enzootic deer populations. (2) Design, captive changes in conduct, and report results of experimental studies using deer naturally or experimentally infected with cwo. SEGMENT OBJECTIVES (1) Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWO in free-ranging deer populations statewide. (2) Conduct and report results of harvest surveys to estimate prevalence of CWO in DAUs D4, D10( +GMU 29), and D44 (+ GMUs 87, 93, and 95). (3) Continue experimental evaluation natural contact exposure. of cattle (4) Observe deer. of naturally-occurring epizootiological features susceptibility to cwo via CWO in captive INTRODUCTION Chronic wasting disease (CWO) affects native deer and elk, causing behavioral changes and progressive loss of body condition that invariably lead to the death of affected animals (Williams and Young 1992). Neither the causative agent nor its mode of transmission have been identified. There are no tests currently available for diagnosing CWo in live animals, and postmortem tests require microscopic examination of brain tissue. There are no known treatments for cwo. Previous attempts to eradicate CWO from research facilities failed on at least 2 occasions (Williams and Young 1992; Miller et al., 1998). Although similar in some respects to other transmissible spongiform encephalopathies that affect domestic sheep (scrapie) and cattle (bovine spongiform encephalopathy; "mad cow disease"), there is no evidence suggesting cwo can be naturally transmitted to domestic livestock, or that scrapie or SSE can be transmitted to native cervids. Moreover, there is no evidence suggesting that cwo presents a threat to human health. "Chronic wasting disease" was first recognized by biologists in the 1960's as a disease syndrome of captive deer held in wildlife research facilities in Ft. Collins, CO, and was subsequently recognized in captive deer, and later in captive elk, in wildlife research facilities near Ft. Collins, Kremmling, and Meeker, CO and Wheatland, WY (Williams and Young 1980, 1982). Since 1981, CWO has also been diagnosed in free-ranging mule deer, white-tailed deer, and elk from northcentral Colorado; most of these diagnoses have been made since 1990 �150 (Spraker et al. 1997). Although CWO was first diagnosed in captive cervids, the original source of CWO is unknown; whether CWO in captive cervids really preceded CWO in wild cervids, or vice versa, is equally uncertain (Spraker et al. 1997). At present, the known world-wide distribution of CWO in wild cervids appears to be limited to northeastern Colorado and southeastern Wyoming. In Colorado, free-ranging CWO cases have primarily originated from along the Front Range near Estes Park and west of Ft. Collins-Loveland. Cases were diagnosed in 6 different game management units (GMUs)(191, 9, 19, 20, 94, and 96) prior to 1996, but two GMUs (19, 20) yielded about 85% of the documented cases; the affected GMUs comprise portions of 3 deer (04, 010, 044) and 2 elk (E4, E9) data analysis units (DAUs). There is no evidence that wild deer or elk outside northeastern Colorado are infected with CWO. The significance of CWO and its impacts on native deer and elk populations are unclear. Simulation models of CWO dynamics predict that this disease could cause significant declines in affected deer and elk populations (Miller and McCarty, unpublished data). In light of CWO's potential impacts on wildlife resources and the difficulties inherent in eliminating CWO from captive or wild cervid populations once established, it seems most prudent to assume CWO could adversely affect native deer and elk populations and manage to reduce its occurrence and prevent its further spread. A more complete understanding of CWO is fundamental to developing a comprehensive management program. In 1996, ongoing surveillance efforts were enhanced to provide a better tool for estimating and monitoring changes in CWO prevalence in enzootic areas and for potentially detecting emergence of CWO in new areas. Reliable estimates of CWO prevalence are particularly critical to detecting"trends, predicting potential impacts of disease on long-term population performance, and assessing efficacy of management interventions; moreover, such data are needed to guide policy decisions and to provide information to hunters and other publics. Ultimately, surveillance data will "be the foundation of an adaptive resource management plan for CWO in deer and elk; that plan will provide a mechanism for incorporating new knowledge gained through surveys, modeling, and experimental studies into a continuously evolving management program formulated to reduce the occurrence of CWO and minimize the risk of its spread to other native deer and elk populations in Colorado. MATERIALS AND METHODS Surveillance We monitored deer populations throughout Colorado for occurrence of CWO using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: Targeted (= clinical disease) surveillance: Deer showing clinical signs consistent with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. The "suspect case" profile was defined as follows: • • Species: Age: mule deer white-tailed ~ 18 months deer �151 • Signs: emaciated and abnormal behavior &/or indifference to human activity &/or increased salivation &/or tremor, stumbling, incoordination &/or difficulty or inefficiency in chewing/swallowing increased drinking and urination &/or Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (Williams and Young 1993) was used to diagnose CWO; in some cases, immunohistochemistry or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: In order to obtain reliable estimates of CWO prevalence that will serve as a basis for monitoring responses to management interventions, we continued conducting harvest surveys on select deer populations. During the 1997-1998 hunting seasons, fresh brain and select lymphatic tissues were collected from deer harvested in enzootic GMUs; deer harvested or culled in other select GMUs throughout Colorado were also sampled as negative controls. Brain tissues were examined at the Colorado State University Diagnostic Laboratory for histopathological lesions (Williams and Young, 1993)or anti-PrP immunostaining reactions (O'Rourke et al., 1998) consistent with CWO infection. Because sample sizes for most individual GMUs were too small to provide reliable prevalence estimates by GMU, we pooled data by DAU for comparisons within and among species. We estimated specificity of imunohistochemistry using data from deer harvested outside known enzootic areas. Ages were estimated via replacement (4-6-mo-old, 16-18-mo-old, ~28-moold) and cementum annuli using first incisors from all positive deer and a random sample of negative deer (103 males and 100 females) harvested in four GMUs (9, 191, 19, 20); using these data, we compared sex-specific age frequency distributions for CWO-affected and unaffected male and female mule deer. Epizootiological Studies Epizootology of naturally-occurring CWO in captive mule deer and white-tailed ~ (Miller and Wild): Naturally-occurring CWO was a sporadic disease of resident FWRF mule deer prior to 1985 (Williams and Young, 1992), and also has occurred sporadically since 1994; no cases had been observed in resident white-tailed deer since their addition to FWRF in 1993. We maintained and observed 25 ~1-yr-old mule deer and 11 ~l-yr-old white-tailed deer in paddocks at CDOW's Foothills Wildlife Research Facility (FWRF) during July 1997-June 1998; 10 fawns were also born and recruited into the resident mule deer herd. Deer received natural forage, pelleted rations (high energy supplement and "browser" diet), and alfalfa hay; water and mineralized salt were available ad libitum. All deer were evaluated daily for clinical signs of CWO (and other health problems) in conjunction with routine feeding and handling activities. Resident mule deer also represented the source of infection (= "treatment") in an ongoing study of cattle susceptibility to CWO (see below). Cattle susceptibility to CWO (Williams and Miller): We continued monitoring cattle for clinical evidence of natural CWO transmission as part of a coordinated interagency effort to study cattle susceptibility to CWO. Twelve 4-mo-old calves purchased from a private ranch located near Sheridan, WY, were placed in paddocks at the FWRF with naturally-infected captive mule deer in July 1997 (see above for description of resident deer herd). Twelve 4-mo-old mule deer fawns were captured at the Rocky Mountain Arsenal National Wildlife �152 Refuge (RMANWR) in late September and placed in the same paddocks as contact controls for natural transmission (extensive ongoing surveillance of RMANWR deer has continued to confirm that this population is free of CWO). In a separate but related study, 20 additional 6-mo-old mule deer fawns were captured at the RMANWR in early December. Each fawn was given a single oral dose of about 5 g of fresh brain tissue homogenate from captive mule deer with clinical CWO. Fawns were then released into a separate paddock physically removed from the contact transmission study. These experimentally-infected fawns will serve two purposes: as controls for domestic calves orally inoculated with a single oral dose of about 50 g of this same CWO brain homogenate (Williams et al., 1998), and as subjects of a study on the pathogenesis of CWO in mule deer (Appendix A). RESULTS AND DISCUSSION Surveillance Targeted (= clinical disease) surveillance: Between June 1997 and May 1998, 6 chronic wasting disease (CWO) cases were diagnosed among 16 "suspect" deer submitted from known endemic portions of northeastern Colorado; CWO was not diagnosed in any of 7 additional "suspect" deer submitted from elsewhere in Colorado. All confirmed CWO cases originated in game management units (GMUs) where the disease had been detected previously. Males and females were represented equally. All CWO cases were observed and submitted during November-February, well within the October-April timeframe of most clinical case submissions (Spraker et al., 1997; Miller, 1997). Encephalitis, intoxication, neoplasia, and pneumonia were diagnosed among the 17 suspects not suffering from CWO; for most (9/17) non-CWO cases, no definitive explanation for clinical signs and condition could be determined from the samples submitted. Harvest surveys: We sampled and examined 1421 deer harvested in enzootic GMUs during 1997 archery, muzzleloader, and rifle seasons (Table 1). About 4.2% .(39/933) of deer harvested in Larimer bounty DAUs (04 and 010) tested. positive for CWO via immunostaining. Four GMUs (9, 191, 19, 20) yielded all of the positive deer detected in Larimer County units (04 and 010) (Table 1; Fig. 1); among these units, prevalence ranged from about 3-16%. Prevalence in sympatric elk populations (0-0.2%; Miller, 1998) was much lower than in deer (P < 0.009). Based on data from 1997 archery, muzzleloader, and rifle seasons, combined estimated mean CWO prevalence in 04 and 010 deer populations (4.2%) appeared to be essentially unchanged from 1995 (5.9%) and 1996 (5.7%); for the 3 GMUs (191, 19, 20) where sufficient samples sizes were available for 3 successive years (1995-1997), prevalence has not differed over time (P ~ 0.3). CWO was detected in about 1.1% (5/449) of deer harvested in South Platte River bottom units (DAU 044 plus GMUs 87, 90, 93, and 95·) (Table 1). Among river bottom and adjacent plains units, positive deer were harvested in GMUs 91, 95, 951, and 96 (Table 1; Fig. 1). None of the 171 deer harvested or culled in other select GMUs (mainly and 104) outside known enzootic areas tested positive for CWO. 66, 67, �153 rg 00o o o o • MD PositiveMdpos.txt • ELK PositiveElkpos.txt .•. WTD PositiveWtdpos.txt WTD NegativeWtdneg.tx o MD NegativeMdneg.txt RiverColo riv CountiesCounties A . /\I o \1---' ___, s Figure 1. About 4.2% of deer harvested in larimer County data analysis units (OAUs) (04 or 010) and about 1.1% of deer harvested in South Platte River bottom units (OAU D44 plus GMUs 87,90, 93, and 95) tested positive for CWO via immunostaining. Most positive cases were from eastern larimer County. As reorted previously (Miller, 1997), the foregoing prevalence estimates may be somewhat liberal because the definition of "positive" included subclinical cases where either histopathological lesions or anti-PrP immunostaining reactions in brain tissue were observed. Of the 44 cases identified, none appeared to be suffering from clinical cwo. Twenty-six of the 44 (59%) positive deer showed both histopathological lesions and immunostaining; the other 18 were classified as positive solely on the basis of immunostaining reactions. Although no known "false positives" were identified among the 171 deer examined from outside known enzootic DAUs (specificity ~0.979), further evaluation of both sensitivity and specificity of existing diagnostic techniques still appears warranted. In contrast to observations derived from targeted surveillance data (Spraker et al., 1997; Miller, 1997), CWO prevalence among male (5.5%) and female (4.8%) mule deer did not differ (P = 0.86) for animals harvested in four Larimer County GMUs (9, 191, 19, 20). Antlerless permit numbers issued for 1997 failed to produce targeted sample sizes of 250 adult (~1 yr) does/DAU: we received 195 usable samples from 04 and 151 from 010, including samples from archery, muzzleloader, and rifle seasons. Additional does will be examined during 1998 to increase sample sizes for comparison of prevalence between sexes. Age distribution of CWO-positive mule deer did not differ from respective sexspecific age distributions of negative animals (Fig. 2). These data support the belief (Miller et al., 1998) that CWO epidemiology is driven primarily by lateral transmission. If maternal transmission were the primary mode of transmission (as is believed to be the case in scrapie of domestic sheep), then an age distribution skewed toward younger aged animals would be expected, particularly among does where older-aged animals are more abundant. In light of an estimated 18-24 mo incubation period for CWO in deer (Williams et al., 1998), the rarity of preclinical disease in yearlings (-16-17-mo-old deer) �154 appears to be the strongest argument against maternal transmission being the most common route for CWO transmission. Although survival rates for male mule deer are substantially lower than for females, CWO appears equally prevalent among males and females and uniformly distributed among respective age classes. These data may reflect the potential inefficacy of random culling in reducing CWO prevalence, although relatively high female densities and the potential for female-male transmission could confound such interpretations. Requiring head submissions increased survey sample sizes >4-fold compared to voluntary submissions in 1996: in 04/010, we collected 938 deer heads, as compared to -200 collected in 1996. Limited licenses also may have aided in increasing deer submissions. Based on harvest estimates from surveyed GMUs (COOW, unpubl. data), compliance with mandatory submission regulations was about 75%. Unstaffed barrel sites still appear to be the most efficient method for sample collection. Epizootiologieal Studies Epidemiology of naturally-occurring CWO in captive mule deer and whitetailed deer (Miller and Wild): Five mule deer and 5 white-tailed deer developed clinical cwo during the last biological year (May, 1997-April 1998) (Fig. 3); two additional mule deer cases and one additiona white-tailed deer case occurred during May-June 1998. In all, CWO affected about 20% (5/25) of the adult (~l-yr-old) mule deer and about 46% (5/11) of the adult white-tailed deer in resident FWRF herds during the last biological year; CWO accounted for 83% of adult mule deer mortality and 100% of adult white-tailed deer mortality. ~ CWO-poalilv. D N.D.1I •.• ~ ...•• r::: • ~• :::J 1:r 7-'D ••,D B. Female mule d.er Age cia •• Rgure 2. Age frequency distributions did not differ between CWO-positive and negative (A) male or (8) female mule deer sampled via harvest surveys. A.ilule du, · ." '0 -·,." z , •• , , •• 7 , •• 3 · ... '0 .! ,." z V •• r Since mule deer were reintroduced into Figure 3. Both mule deer and white-tailed deer herds FWRF in late 1990, 17 of 59 (29%) resident at CDOW's Foothills Wildlife Research Facility animals that survived to >1 yr of age are now infected with chronic wasting disease. have succumbed to CWO. The index case in the most recent epizootic occurred in October 1994; 4-5 clinical cases Annual clinical have occurred in each subsequent biological year (Fig. 3A). prevalence has ranged from 2-20% (Fig. 4). Generating comparable epizootic �155 behavior in a forecasting model (Miller and Mccarty, unpubl. data) requires a transmission coefficient (~) of about 3.5 infectious contacts/infectious animal/yr (Fig. 4); two assumptions of this spreadsheet model, no environmental source of infection and a l2-mo incubation period prior to onset of clinical disease, seem somewhat questionable in light of recent experiences and may need to be reevaluated. _a-wd,.."..DldMr 50 40 ~ 30 fI) '0 [EJ~~oI" 25 20 15 ~ B r:::: '0 ~ fI) ..D E 20 ::::J Z 10 ~ l:. Based on observations made over the last 5 10 12 mo, CWO apparently can be an explosive disease 'in white-tailed deer populations. It follows that the relative rarity of o o 1995 1994 1996 1997 CWO in free-ranging white-tailed deer is Year probably more a function infrequent exposure rather than natural species resistance; white-tailed deer are relatively rare in the foothills of Figure 4. Modeled CWO dynamics eastern Larimer county where CWO is most simulated trends observed in FWRF deer prevalent. The source of infection for since 1994 when relatively high transmission our captive white-tailed deer herd is coefficients (13 = 3.5) were used. unclear. One possibility is introduction via two breeding males (C93, W93) that were intermittently housed with CWO-infected mule deer males; another possibility is transmission from infected mule deer via fenceline contact or environmental contamination. The essentially simultaneous occurrence of CWO in two does that had never been housed with mule deer seems to support the latter alternative. Cases in two additional animals 9 and 11 mo after the index case could be consistent with either a point source of exposure and variable incubation period or lateral transmission with a relatively short (-12 mo) incubation period. Data on pathogenesis, incubation periods, agent shedding, potential environmental sources of infection, and the relationship between infectiousness and onset of clinical signs for CWO in both white-tailed and mule deer are clearly needed to improve understanding of CWO epizootiology in both captive and free-ranging deer. Cattle susceptibility to CWO (Williams and Miller): One calf died from gastrointestinal obstruction and bloat about 2 wk after entering the deer paddocks, but the other 11 remained healthy throughout the first year of this 10-yr experiment. Similarly, 11 of the 12 control fawns from RMANWR remained healthy; one fawn that apparently failed to adjust to captivity died about 1 mo after capture, presumably from hypothermia secondary to malnutrition. Seven of the 25 >1-yr-old naturally-exposed resident FWRF deer developed clinical CWO and died or were euthanized during the first 12 mo of the study, thereby ensuring calves and control deer received some exposure to CWO. ACKNOWLEDGMENTS The statewide CWO monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those �156 regional and area biologists, district and area wildlife managers, volunteers, deer and elk hunters, and others who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. LITERATURE CITED Miller, M. W. 1997. Monitoring. and managing wildlife chronic wasting disease in Colorado. in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-10, WP2, J17. Colorado Division of Wildlife, Fort Collins, Colorado, USA, pp. 37-46. 1998. Monitoring and managing wildlife chronic wasting disease in elk. in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-11, WP3002, T3. Colorado Division of Wildlife, Fort Collins, Colorado, USA, in press. , M. A. Wild, and E. S. Williams. 1998. Epizootiology of chronic --wasting disease in captive Rocky Mountain elk. J. Wildl. Dis. 34: 532-538. O'Rourke, K. I., T. V. Baszler, J. M. Miller, T. R. Spraker, I. SadlerRiggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.1.5 defines a conserved epitope on the ruminant prion protein. J. Clin. Microbiol. 36: 1750-1755. Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. J. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, J. M. Miller, and P. A. Merz. 1997. spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus elaphus nelsoni) in northcentral Colorado. J. Wildl. Dis. 33:1-6. Williams, E. S., and S. Young. 1980. Chronic Wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16: 89-98. , and 1982. Spongiform encephalopathy --Journal of Wildlife Diseases 18: 465-471. __ ~' and Scientifique of Rocky Mountain elk. 1992. Spongiform encephalopathies in Cervidae. Revue et Technique Office International des Epizooties 11: 551-567. , and 1993. Neuropathology of chronic wasting disease in mule --deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. , M. W. Miller, T. J. Kreeger, H. Van Campen, and T. R. Spraker. 1998. --Susceptibility of cattle to cervid spongiform ~ncephalopathy. unpublished grant proposal, submitted to USDA, CSREES, Competitive Grants Program, 88 pp. c Wildlife Research Veterinarian National Research Initiative �157 Table 1. Results of 1997 CWD harvest surveys -- archery, muzzleloader, & rifle seasons. DEER DAU GMU # Examined # Positive D4 7 29 0 8 160 0 191 212 10 9 74 12 19 123 6 Total 598 28 20 335 11 Total 335 11 29 39 0 Total 39 0 87 37 0 90 1 0 91 54 1 . 92 41 0 93 53 0 94 55 0 95 97 2 951 56 1 96 55 1 Total 449 5 DI0 Boulder Plains Prevalence (95% CI) 0.047 (0.031-0.067) 0.033 (0.016-0.058) 0 (0-0.09) 0.011 (0.004-0.025) �158 �159 AJ;lpendix A STUDY PLAN Pathogenesis Elizabeth of Chronic Wasting S. Williams Disease and Michael in Mule Deer W. Miller Need Chronic wasting disease (CWO) is a transmissible spongiform encephalopathy (TSE)of native North American deer and elk (Williams and Young, 1980, 1982, 1992). The neuropathology of clinical CWO is well-described (Williams and Young, 1980, 1982, 1992, 1993; Spraker et al., 1997), but CWO pathogenesis remains largely unstudied. Among clinical CWO cases, the parasympathetic nucleus of the vagus and the olfactory stria are most consistently and severely affected (Williams and Young, 1993). Typical but less abundant lesions occur in the parasympathetic nucleus of the vagus, and sometimes the olfactory stria, in apparently subclinical CWO cases detected during harvest surveys (E. S. Williams, unpubl. data; T. R. Spraker, pers. comm.). Brain and various lymphoid tissues often stain intensively with anti-prion protein (PrP) immunostaining in clinical cases (Williams and Young, 1992; Spraker et al., 1997; E. S. Williams, unpubl. data; T. R. Spraker, pers. comm.). Immunostaining of brain and select lymphoid tissues, particularly tonsil, are usually positive in subclinical cases. Positive staining of tonsil and brain tissue can occur in the absence of spongiform lesions. Lymphoid Prpsc propagation apparently precedes development of detectable neurological lesions in scrapie (Schreuder et al., 1996, van Keulen et al., 1995, 1996), but not bovine spongiform encephalopathy (Wells et al., 1996). The presence of Prpsc in central nervous system and peripheral tissues has lead to development of immunohistochemistry (Miller et al., 1993; van Keulen et al., 1995, 1996; Schreuder et al., 1996) and immunoblotting (Farquhar et al., 1989; Ikegami et al., 1991; Race et al., 1992) as preclinical and clinical diagnostic tests for scrapie in sheep. These antemortem tests are based on biopsy and examination of lymphoid tissues, typically tonsil, lymph node, and spleen for Prpsc• Positive staining of lymphoid and salivary gland tissues in the absence of either lesions or staining in brain tissue has also been observed in deer and elk, but interpretation of these observations remains equivocal. Improved understanding of CWO pathogenesis would clearly facilitate the interpretation of diagnostic findings in subclinical CWO suspects detected via harvest surveys. Such understanding would also enhance interpretation of data being gathered in studies designed to evaluate antemortem diagnostic tests for CWO. Moreover, reliable pathogenesis data may offer valuable insights into initiation, duration, and routes of agent shedding, as well as other important aspects of CWO epizootiology. Here, we propose to study the pathogenesis of CWO in mule deer after oral exposure to infectious brain material. Objectives The specific objectives of this study are to: (1) describe the pathogenesis of CWO in mule deer after oral exposure to infectious material using histopathology, immunohistochemistry, and Western blot analyses; and (2) compare susceptibility, pathogenesis, and incubation periods between male and female deer. Additionally, animals challenged in this study will serve as controls for ongoing cattle challenge trials (Williams et al., 1997). �160 Materials and Methods We will study the pathogenesis of CWO in mule deer after oral exposure to infectious brain material. Twenty 5- to 6-mo-old mule deer fawns (10 males, 10 females) will be captured from the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR) and transported to the Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. Previous surveillance work has revealed that deer residing at RMANWR are presently unaffected by CWO, thereby ensuring fawns will not be exposed to CWO until inoculated experimentally. For capture, fawns will be anesthetized with tiletamine HCl and zolazepam (Telazol~; 5 mg/kg) and xylazine HCl (2.5 mg/kg) or carfentanil HCl (0.03 mg/kg) and xylazine (1 mg/kg) delivered intramuscularly (1M) via projectile syringe; if carfentanil is used, anesthesia will be antagonized with naltrexone HCl (100 mg/mg carfentanil) delivered intravenously (IV)(25%) and subcutaneously (SC) (75%) after initial handling and processing. Additional xylazine (20-100 mg IV or 1M) will be administered as needed to keep fawns sedated until they arrive at FWRF. (See appendix for detailed capture protocols.) Upon arrival at FWRF, residual sedation will be antagonized with IV yohimbine HCl (0.25 mg/kg). Once fawns are able to swallow effectively, each will receive about 5 g of homogenized brain material pool collected from mule deer previously diagnosed with spongiform encephalopathy; presence of scrapieassociated fibrils in this homogenate was previously confirmed via negativestain electron microscopy (E. S. Williams, unpubl. data). This homogenate is the same being used for oral and intracranial cattle challenges (Williams et al., 1997). Homogenate will be deposited into the posterior oropharynx using a modified syringe. Once fawns have swallowed the homogenate, they will be released into a 3 ha paddock. Alfalfa hay, pelleted supplemental diets (highenergy and "browser" rations), mineralized salt blocks, and water will be provided ad libitum. All fawns will be observed daily by animal caretakers and evaluated at least monthly by an attending veterinarian for signs of CWO. To study CWO pathogenesis, two fawns' (one male, one female) will be randomly sacrificed at 3, 6, 12, 18, 24, 30, 36, or 42 mo after oral challenge. At the time of sacrifice, fawns will be anesthetized with tiletamine HCl and zolazepam (Telazol~; 5 mg/kg) and xylazine Hel (2.5 mg/kg) delivered via projectile syringe. We will collect blood, saliva, feces, and cerebrospinal fluid from each fawn, then administer about 400 mEq KCl intravenously to induce cardiac arrest. The incubation period of CWO after oral challenge is unknown; however, because clinical CWO developed in mule deer 18 to 24 mo after intracranial challenge (E. S. Williams, unpubl. data), we anticipate that most study animals surviving >24 mo will develop Cwo 24 to 36 mo after oral challenge. Deer developing severe clinical CWO (characteristic behavioral changes accompanied by estimated >20% weight loss) will be euthanized as described above. Two age-matched control deer (one male, one female) will be collected from the RMANWR on the same schedule as challenged deer are sacrificed. Control deer will be anesthetized in the field as described above, sampled, and euthanized with KCl; if field anesthesia becomes infeasible, control deer will be killed by shooting in the neck with a highpowered (~0.223 cal) rifle. Saliva, feces, blood, and cerebrospinal fluid will be stored at -70 C for potential evaluation via Western blot or infectivity studies. Carcasses will be transported to the Wyoming State Veterinary Laboratory (WSVL) for complete necropsy and tissue sampling. Samples collected will include brain, spinal �161 cord, and numerous other tissues (Table 1). These tissues will be divided and subsamples fixed in 10% neutral phosphate-buffered formalin or in PLP solution (periodate, lysine, paraformaldehyde) at a concentration of 2% paraformaldehyde (van Keulen et al., 1996); additional subsamples will be stored unfixed at -70 C for studies of Prpsc accumulation. Carcasses will be incinerated once sampling is completed. Tissues will be examined via histopathology, immunocytochemistry, Western blot, and/or negative-stain electron microscopy. Histopathology will be conducted as previously described (Williams and Young, 1993). Central nervous system tissues will be removed within 4 hr following euthanasia. Brains will be sagittally sectioned and half fixed in 10% neutral phosphate-buffered formalin. Samples of spinal cord and other tissues (Table 1) will be similarly fixed. The other half of the brain and portions of the spinal cord will be frozen at -70 C. Paraffin blocks will be prepared from olfactory tubercle and cortex; cerebral cortex (frontal, parietal, temporal, and occipital lobes); basal ganglia; three levels of thalamus; two levels of mesencephalon; three levels of pons and cerebellum; medulla oblongata at the obex; medulla caudal to the obex; and multiple levels of spinal cord to include cervical, thoracic, and lumbar regions. Tissues will be sectioned at 5-6 ~m and stained with hematoxylin and eosin, Bodian's silver stain, luxol fast blue stains, and glial fibrillary acidic protein (Dako, Carpinteria, California) immunocytochemistry for astrocytosis as appropriate. Lesions will be compared to those previously described for CWO in mule deer and elk and other natural TSEs of animals (Williams and Young, 1993; Hadlow, 1996). We will test for Prpsc in formalin- or PLP solution-fixed, paraffin embedded tissues using minor modifications of the technique of van Keulen et al. (1995). We will use a polyclonal rabbit antiserum against ME7 scrapie strain passaged in mice (Rubenstein et al., 1986) (Department of Virology, New York State Office of Mental Retardation and Developmental Disabilities, Staten Island, New York) or mouse monoclonal antibody against ovine Prpsc (F89/160.1.5; O'Rourke et al., 1997) (USDA/ARS, Pullman, Washington). Briefly, paraffin embedded tissue sections will be deparaffinized, treated with 99% formic acid for 30 minutes, rinsed with PBS, and autoclaved for 10 minutes at 122 C in 10 x Automation buffer. Sections will be incubated in 4% normal goat serum for 20 minutes, incubated overnight at 4 C in primary antibody at 1:1500 dilution, rinsed, and incubated for 30 minutes with biotinylated anti-rabbit or anti-mouse IgG (Vector Laboratories, Burlingame, California). Slides will be rinsed, and ABC reagent (Vectastain Elite ABC kit, Vector Laboratories) applied for 30 minutes, rinsed and incubated with AEC substrate solution (Dako Laboratories, Carpinteria, california) for 10 minutes. Slides will be counter stained with Harris hematoxylin, rinsed, "blued" with lithium carbonate, rinsed again, and coversli~d. Positive and negative brain sections, normal rabbit serum, and PBS will be used as controls. Adequate primary antibody is available for the entire study. L Western blot assays will be conducted with modifications of the techniques of Rubenstein et al. (1986) and Collinge et al. (1996). Brain or lymphoid tissues will be homogenized in Tris buffer saline (TBS) at 50 mg/500 ~l followed by a 5 minute low speed centrifugation. 100 ~l supernatant is combined with 6 ~l 22% sarcosyl in TBS, mixed, 4 ~l (5mg/ml) proteinase K is added, mixed again, then incubated at 37 C for 1-2 hours. Aliquots will be collected for protein concentration determination using Pierce's Micro BCA protein assay. Equal volume of concentrated sample buffer (120 roM Tris-HCl pH 6.8, 142 roM BME, 200 roM DTT, 4% SDS, 0.02% BPB, 20% glycerol) will be added and the sample boiled for 5 minutes. Hot samples will be loaded on Mini-Vertical 4%/12% SDS-PAGE �162 (Laemmli). The samples will be electrophoresed at 100 v for 1.5-2 hours with BioRad's Protein SOS-PAGE molecular weight markers. A semidry transfer to 0.45 ~m pure nitrocellulose will be conducted using Towbin buffer according to manufacturer's instructions. Post-transfer, the gel will be Coomassie Blue G250 stained while the membrane is floated on TBST20 (10 roM Tris pH 8.0, 150 roM NaCI, 0.1% Tween2o) until wet, then submerged and rinsed. The membrane will be incubated in 1% NGS -TBST2o for 30 - 60 minutes at room temperature, washed two-three times for 10 minutes each in TBST2o, and TBST20 1:5,000 diluted primary antibody (polyc1onal rabbit or monoclonal mouse anti-Prpsc) added to the blot and incubated 2 hours at room temperature or overnight at 4 C. The antibody will be removed, the membrane washed two-three times for 10 minutes each, and secondary antibody (Promega's goat anti-rabbit conjugated alkaline phosphatase) diluted in TBST20 (per manufacturer's instructions) added and incubated 2 hours at room temperature. The membrane will be again washed two to three times followed by three 2 minute washes in distilled water and then a 5 minute TBS wash done twice. Promega's BCIP/NBT color development solution (made according to manufacturer's instructions) will be added and development monitored. The reaction will be stopped by several distilled water rinses. The membrane and stained gel will be recorded via CCO camera, digitized, and quantitated (Bio-Rad Molecular Analysis System). Scrapie-associated fibrils will be purified using a modification of the techniques of Hilmert and Oiringer (1984). One to two g of brain will be homogenized in 10% sarcosyl (pH 7.4) and N-octano1 added for a 30 minute incubation at room temperature. The homogenate will be centrifuged for 10 minutes at 3,000 x G (JA-20 rotor, J-21 Beckman centrifuge) and supernatant collected and centrifuged for 30 minutes at 22,000 X G. The supernatant will then be transferred to Beckman quick seal tubes and centrifuged at 215,000 X G (75T rotor, L8-80 Beckman centrifuge) for 2 hours. The pellet will be resuspended in 1% sarcosyl and 10% NaCI, stirred for 60 minutes at 37 C, and microfuged for 15 minutes. The pellet will then be resuspended -in 1% sarcosyl, 10% NaCI, and 5 ~g proteinase Klml added and stirred for 2 hours at 37 C. The suspension will be microfuged for 10 minutes. Negative staining will be conducted according to Scott et ale (1987, 1990). The pellet will be resuspended in 50 ~l distilled water and a 300 mesh plastic coated, carbon stabilized grid floated on a drop of suspension for 10 seconds, blotted and negative stained with 2% potassium phosphotungstate, pH 6.6. Some additional modifications of the procedures for SAF detection (Stack et al., 1995; 1996) are currently being tested at WSVL. We will describe distribution of Prpsc and microscopic lesions as determined by each of the foregoing assays, and relate these to both the chronological progression of clinical CWO and the potential shedding of agent from infected deer. Because our study is largely descriptive, no statistical analyses of pathology data will be attempted. Among fawns surviving long enough to develop clinical CWO, mean incubation times for males and females will be compared using Student's t-test (a = 0.1), and the proportions of males and females developing clinical cwo will be compared using Fisher's exact probability test (a 0.1). = Literature Cited Collinge, J., K. C. L. Sidle, J. Meads, J. Ironside, and A. F. Hill. 1966. Molecular analysis of prion strain variation and the aetiology of 'new variant' CJO. Nature 383: 685-690. Farquhar, C. F., R. A. Somerville, and L. A. Ritchie. 1989. Post-mortem immunodiagnosis of scrapie and bovine spongiform encephalopathy. Journal of Virological Methods 24: 215-222. �163 Hadlow, W. J. 1996. Differing neurohistologic images of scrapie, transmissible mink encephalopathy, and chronic wasting disease of mule deer and elk. In Bovine spongiform encephalopathy The BSE dilemma, Vol. C. J. Gibbs, Jr. (ed.). Springer-Verlag, New York, New York, pp. 122-137. Hilmert, H., and H. Diringer. 1984. A rapid and efficient method to enrich SAF-protein from scrapie brains of hamsters. Biosciences Reports 4: 165170. Ikegami, Y., M. Ito, H. Isomura, E. Momotani, K. Sasaki, Y. Muramatsu, N. Ishiguro, and M. Shinagawa. 1991. Pre-clinical and clinical diagnosis of scrapie by detection of PrP protein in tissues of sheep. Veterinary Record 128: 271-275. Miller, J. M., A. L. Jenny, W. D. Taylor, R. F. Marsh, R. Rubenstein, and R. E. Race. 1993. Immunohistochemical detection of prion protein in sheep with scrapie. Journal of Veterinary Diagnostic Investigation 5: 309-316. Race, R. E., D. Ernst, A. L. Jenny, W. D. Taylor, D. Sotton, and B. Caughhey. 1992. Diagnostic implications of detection of proteinase K-resistant protein in spleen, lymph nodes, and brain of sheep. American Journal of Veterinary Research 53: 883-889. Rubenstein, R., R. J. Kascsak, P. A. Merz, M. C. Papini, R. I. Carp, N. K. Robakis, and H. M. Wisniewski. 1986. Detection of scrapie-associated fibril (SAF) proteins using anti-SAF antibodies in non-purified tissue preparations. Journal of General Virology 67: 671-681. Schreuder, B. E. C., L. M. J. van Keulen, M. E. W. Vromans, J. P. M. Langveld, and M. A. Smits. 1996. Preclinical test for prion diseases. Nature 381: 563. Scott, A. C., S. H. Done, C. Venables, and M. Dawson. 1987. Detection of scrapie-associated fibrils as an aid to the diagnosis of natural sheep scrapie. Veterinary Record 120: 280-281. Scott, A. C., G. A. H. Wells, M. J. Stack, H. White, and M. Dawson. 1990. Bovine spongiform encephalopathy: Detection and quantitation of fibrils, fibril protein (PrP) and vacuolation in brain. Veterinary Microbiology 23: 295-305. Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. J. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, J. M. Miller, and P. A. Merz. 1997. Spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus), white-tailed deer (0. virgianus), and Rocky Mountain elk (Cervus elaphus nelsoni) in northcentral Colorado. Journal of Wildlife Diseases 33: 1-6. Stack, M. J., A. M. Aldrich, A. D. Kitching, and A. C. Scott. 1995. Comparative study of electron microscopal techniques for the detection of scrapie-associated fibrils. Research in Veterinary Science 59: 247-254. Stack, M. J., A. M. Aldrich, A. D. Kitching, and A. C. Scott. 1996. Comparison of biochemical extraction techniques for the detection of scrapieassociated fibrils in the central nervous system of sheep naturally affected with scrapie. Journal of comparative Pathology 115: 175-184. van Keulen, L. J. M., B. E. C. Schreuder, R. H. Meloen, M. Poe len-van den Berg, G. Mooij-Harkes, M. E. W. Vromans, and J. P. M. Langerveld. 1995. Immunohistochemical detection and localization of prion protein in bran tissue of sheep with natural scrapie. Veterinary Pathology 32: 299-308. van Keulen, L. M. J., B. E. C. Schreuder, R. H. Meloen, G. Mooij-Harkes; M. E. W. Vromans, and J. P. M. Langveld. 1996. Immunohistochemical detection of prion protein in lymphoid tissues of sheep with natural scrapie. Journal of Clinical Microbiology 34:1288-1231. Wells, G. A. H., M. Dawson, S. A. C. Hawkins, A. R. Austin, R. B. Green, I. Dexter, M. W. Horigan, and M. M. Simmons. 1996. Preliminary observations on the pathogenesis of experimental bovine spongiform encephalopathy. In �164 Bovine spongiform encephalopathy The BSE Dilemma, Vol. C. J. Gibbs, Jr. (ed.). Springer-Verlag, New York, New York, pp. 28-44. Williams, E. S. and S. Young. 1980. Chronic wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16: 89-98. Williams, E. S. and S. Young. 1982. Spongiform encephalopathy of Rocky Mountain elk. Journal of Wildlife Diseases 18: 463-471. Williams, E. S., and S. Young. 1992. Spongiform encephalopathies of Cervidae. Scientific and Technical Review Office of International Epizootics 11: 551-567. Williams, E. S. and S. Young. 1993. Neuropathology of chronic wasting disease of mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. Williams, E. S., M. W. Miller, T. J. Kreeger, and H. Van Campen. 1997. Susceptibility of cattle to cervid spongiform encephalopathy. Unpublished study plan, 66 pp. Table 1. Tissues to be collected and detection of Prpsc. Nervous Tissue brain (multiple levels) pituitary CSF dura spinal cord (cervical, thoracic, lumbar) dorsal root ganglia trigeminal ganglia stellate ganglia sciatic nerve radial nerve Muscle Tissue diaphragm semitendinosus muscle triceps muscle longissimus dorsi muscle Alimentary Tissue tongue submandibular lymph node parotid salivary gland esophagus rumen omasum abomasum duodenum distal ileum and Peyer's patches spiral colon feces pancreas liver from deer exposed to CWO for histopathology Lymphoid Tissue spleen thymus tonsil submandibular lymph node retropharyngeal lymph node bronchial lymph node mediastinal lymph node hepatic lymph node mesenteric lymph nodes ileocecal lymph node hepatic lymph node superficial cervical lymph node popliteal lymph node Other Tissues kidney urine adrenal gland .lung nasal mucosa left ventricle blood (serum, buffy bone marrow skin (head) bone (rib) coat, clot) �91 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT State of __,..--!:C~o~lo::.!.r=ad...,o,,-_ Project No. __ -..l..W!--...:..1=.:53:!...-~R~-~12~_ Work Package No. _---"'-30;:....;0::..,:1'-_ Task No. 3 ------~--------- Period Covered: Cost Center 3430 Mammals Program Deer Management Monitoring and Managing Disease in Deer Chronic Wasting July 1, 1998 - June 30, 1999 Authors: M. W. Miller, C. T. Larsen, and J. Gross Personnel: R Kahn. M. Leslie, K. I. O'Rourke, Williams T. R Spraker, E. Wheeler, M. A. Wild, and E. S. ABSTRACf . Deer from throughout Colorado were examined for occurrence of chronic wasting disease using a combination of targeted surveys and harvest/road-kill surveys. Between June 1998 and May 1999, 8 chronic wasting disease (CWD) cases were diagnosed among 25 "suspect" deer submitted from known endemic portions of northeastern Colorado; CWD was not diagnosed in any of 10 additional "suspect" deer submitted from elsewhere in Colorado. All confirmed CWD cases originated in game management units (GMUs) where the disease had been detected previously. We sampled over 1800 harvested or road-killed deer to randomly survey for CWD in select DAUs. Immunohistochemistry (llIC)-based prevalence in Larimer County (5%; 39/780) and South Platte River bottom/plains (1.6%; 5/315) DADs were unchanged from previous years. We detected no evidence ofCWD in any of369 samples from Middle Park, or in any of over 300 samples from other GMUs outside northeastern Colorado. Late doe hunts in Larimer County DAUs provided an additional 212 samples for comparison of CWD prevalence between sexes; based on data compiled over the last 2 years, CWD prevalence does not differ between male and female mule deer (P = 0.72). Since June 1998, CWD affected 8 of 29 adult (z l-yr-old) mule deer in the resident Foothills Wildlife Research Facility herd. No signs of neurological disease were observed in any of the 11 cattle (subjects) or 11 mule deer from the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR)(contact controls) housed with naturally-infected resident deer since July 1997. Using mc, Prpres was detected in brain tissue (medulla oblongata at the obex) from 1 of2 mule deer experimentally inoculated with a 5 g oral dose of brain tissue homogenate from CWD-infected deer 6 or 9 mo earlier. One of two deer examined 16 mo after inoculation (Pl) had lesions of spongiform encephalopathy, and both were mC-positive. Two deer examined 3 rno PI and 2 examined 12 rno PI were negative, as were all 10 uninoculated controls collected from RMANWR at the same intervals. One of the 8 remaining deer inoculated in December 1997 began �92 showing early clinical signs of CWD ~ 15 mo PI; a second began showing early signs 2-3 wks later, and subtle signs were noted in at least 4 of 8 inoculated deer alive 18 mo PI. An epidemic model of was developed to simulate the dynamics of chronic wasting disease in mule deer populations. As seen in earlier modeling exercises, simulations resulted in projections wherein either the disease or the deer population was eliminated; stable coexistence of chronic wasting disease could not be achieved in simulated populations. Productivity (i.e., harvest) was reduced in populations by very low rates of prevalence. Spread of CWD within a simulated population was highly sensitive to transmission rate, and very small decreases in transmission efficiency resulted in notable decreases in prevalence. Simulated test and slaughter programs revealed the importance of initiating control while CWD prevalence was low « 0.05). Low rates of test and slaughter (e.g., < 20% of the infected population) effectively eliminated wasting disease in simulated populations if control measures were initiated while prevalence was low (i.e., 0.01), but the likelihood of control diminished rapidly as disease prevalence increased. Test and slaughter programs will require an effort sustained over many decades to ensure elimination of chronic wasting disease. A statewide plan for monitoring and managing CWD in deer and elk was drafted. The plan has been distributed for internal and limited external review, and will be finalized by 30 September 1999. cwn �93 MONITORING AND MANAGING CHRONIC WASTING DISEASE IN DEER M. W. Miller and C. T. Larsen P. N. OBJECTIVES '"1. Design, conduct, and report results of: a. targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWD) in free-ranging deer populations; and b. harvest or road-kill surveys to estimate and detect changes in prevalence of CWD in enzootic deer populations. ,2. Design, conduct, and report results of experimental studies using captive deer naturally or experimentally infected with CWD. AGREEMENT OBJECTIVES 1. Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWD in free-ranging deer populations statewide. 2. Conduct and report results of harvest surveys to estimate prevalence ofCWD in DAUs D4, D9 (GMUs 18,28,37,371), DI0( +GMU 29), and D44 (+ GMUs 87, 90, 93, arid 95). 3. Continue an experiment evaluating cattle susceptibility to CWD via natural contact exposure. 4. Continue to study pathogenesis ofCWD in mule deer. 5. Develop an epidemic model ofCWD dynamics in deer populations. 6. Observe epidemiology of naturally-occurring CWD in captive deer. MATERIALS AND METHODS Surveillance We monitored deer populations throughout Colorado for occurrence of CWD using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: �94 Targeted (= clinical disease) surveillance: Deer showing clinical signs consistent with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. The "suspect case" profile was defined as follows: • Species: mule deer white-tailed deer • Age: ::::18 months • Signs: emaciated and abnormal behavior &lor indifference to human activity &lor increased salivation &lor tremor, stumbling, incoordination &lor difficulty or inefficiency in chewing/swallowing increased drinking and urination &lor Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (Williams and Young 1993) was used to diagnose CWO; in some cases, immunohistochemistry (ll:IC) or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: In order to obtain reliable estimates of CWO prevalence that will serve as a basis for monitoring responses to management interventions, we continued conducting harvest surveys on select deer populations. During the 1998-1999 hunting seasons, fresh brain and select lymphatic tissues were collected from deer harvested in enzootic GMUs; deer harvested or culled in other select GMUs throughout Colorado were also sampled as negative controls. Brain tissues were examined at the Colorado State University Diagnostic Laboratory for anti-PrP immunostaining reactions (O'Rourke et al., 1998) and histopathological lesions (Williams and Young, 1993) consistent with CWO infection. Epizootiological Studies Epizootology of naturally-occurring CWO in captive mule deer and white-tailed deer: Naturallyoccurring CWO was a sporadic disease of resident FWRF mule deer prior to 1985 (Williams and Young, 1992), and also has occurred sporadically since 1994; no cases had been observed in resident white-tailed deer since their addition to FWRF in 1993. We maintained and observed 29 ~ l-yr-old mule deer and 5 ~ l-yr-old white-tailed deer in paddocks at CDOW's Foothiils Wildlife Research Facility (FWRF) during May-September 1998. Deer received natural forage, pelleted rations (high energy supplement and "browser" diet), and alfalfa hay; water and mineralized salt were available ad libitum. All deer were evaluated daily for clinical signs of CWO (and other health problems) in conjunction with routine feeding and handling activities. Resident mule deer also represented the source of infection (= "treatment") in an ongoing study of cattle susceptibility to CWO (see below). Cattle susceptibility to CWO (Williams and Miller): We continued monitoring cattle for clinical evidence of natural CWO transmission as part of a coordinated interagency effort to study cattle susceptibility to CWO. Twelve 4-mo-old calves purchased from a private ranch located near Sheridan, WY, were placed in paddocks at the FWRF with naturally-infected captive mule deer in July 1997 (see above for description of resident deer herd). Twelve 4-mo-old mule deer fawns were captured at the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR) in late September and placed in the �95 same paddocks as contact controls for natural transmission (extensive ongoing surveillance of RMANWR deer has continued to confirm that this population is free of CWD). CWD Pathogenesis in mule deer (Williams and Miller): In a separate but related study, 20 additional 6mo-old mule deer fawns were captured at the RMANWR in early December. Each fawn was given a single oral dose of about 5 g of fresh brain tissue homogenate from captive mule deer with clinical CWD. Fawns were then released into a separate paddock physically removed from the contact transmission study. These experimentally-infected fawns serve two purposes: as controls for domestic calves orally inoculated with a single oral dose of about 50 g of this same CWD brain homogenate (Williams et al., 1998), and as subjects of a study on the pathogenesis of CWD in mule deer. We have randomly sacrificed 2 experimentally-infected deer at 3,6,9, 12, and 16 mo after inoculation; we also collected 2 age- and sex-matched control deer from RMANWR at each time step. Complete necropsies were performed and samples collected as described in the original study plan. . Select sections of brain tissue (obex) were examined after staining with hematoxylin and eosin (H&E) or anti-PrP immunostain (F89/160.1. 5; O'Rourke et al., 1998); examination of other tissues is pending. Epidemic modeling (Gross and Miller): We developed a mechanistic model to simulate the dynamics of chronic wasting disease in mule deer populations. The model projected age-specific disease dynamics, changes in population size, and control strategies involving selective removal of infected animals or changes in rates of disease transmission. Model parameters were estimated from observations of infected and uninfected deer in Colorado and Monte Carlo techniques were used to evaluate likely responses. Appendix A provides a more detailed description of our model. CWD Monitoring and Management Plan A statewide plan for monitoring and managing CWD in deer and elk was drafted. RESULTS AND DISCUSSION Surveillance Targeted (= clinical disease) surveillance: Between June 1998 and May 1999, 8 chronic wasting disease (CWD) cases were diagnosed among 25 "suspect" deer submitted from known endemic .portions of northeastern Colorado; CWD was not diagnosed in any of 10 additional "suspect" deer submitted from elsewhere in Colorado. All CWD cases confirmed in 1998-1999 were mule deer, and all originated in game management units (GMUs) where the disease had been detected previously. Harvest surveys: We sampled over 1800 harvested or road-killed deer to randomly survey for CWD in select DADs. ruC-based prevalence in Larimer County (5%; 39/780) and South Platte River bottom/plains (1.6%; 5/315) DADs were unchanged from previous years. We detected no evidence of CWD in any of369 samples from Middle Park, or in any of over 300 samples from other GMUs outside northeastern Colorado. Late doe hunts in Larimer County DADs provided an additional 212 samples for comparison of CWD prevalence between sexes; based on data compiled over the last 2 years, CWD prevalence does not differ between male and female mule deer (P = 0.72). �96 Survey data gathered during 1996-1999 indicate that CWD is generally more prevalent and more widely distributed in mule deer than in white-tailed deer in northeastern Colorado (Fig. 1). However, limited data from white-tailed deer harvested near the mouth of the Big Thompson Canyon west of Loveland suggest CWD could become quite prevalent among white-tailed deer (Fig. IB). In light of this potential and the apparent spread of CWD eastward along the Big Thompson/South Platte River corridor in both mule deer and white-tailed deer (Fig. 1), natural spread and eventual infection of more densely populated white-tailed deer habitats in the midwestern and eastern US should be anticipated in the coming decades unless management interventions are successfully identified and implemented. A.Muledeer Epizootiological Studies Epidemiology of naturally-occurring CWD in captive mule deer and whitetailed deer: Since June 1998, CWD affected 8 of 29 adult (~ l-yr-old) mule deer in the resident Foothills Wildlife Research Facility herd (Fig. 2A). Two other adult mule deer died between June and May; enterotoxemia was diagnosed in one, and pasteurellosis in the other. Although neither showed neuropathology consistent with CWD, 1 had IHC staining consistent with preclinical CWD. Resident mule deer also represented the source of infection (treatment) in an ongoing 10-yr study of cattle susceptibility to CWD (see below). One of 5 white-tailed deer remaining in our resident FWRF herd developed CWD and died in June 1999. In all, CWD has claimed 7 of 11 captive white-tailed deer held at FWRF since 1993 (Fig. 2B). One of the 4 remaining individuals is showing early signs of CWD. I B. White-tailed deer Figure 1. Estimated CWD prevalence (%) among subpopulations of (A) mule deer and (B) white-tailed deer in northeastern Colorado. Data were aggregated via known deer movement patterns. Prevalence estimates are based on IHC reactions only (IHC+ltotal). Evaluation of tonsillar biopsies from captive deer are still pending. Lack of results has precluded evaluation of tonsillar biopsy as a potential antemortem test for CWD in deer. Cattle susceptibility to CWD (Williams and Miller): No signs of neurological disease were observed in any of the II cattle (subjects) or II mule deer from the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR)(contact controls) housed with naturally-infected resident deer since July 1997. Neither of2 contact control deer that died during October-June showed neuropathology consistent with CWD, although both suffered from chronic weight loss; malnutrition probably contributed to at least I of these deaths. Fifteen of the 36 > l-yr-old naturally-exposed resident FWRF deer developed clinical �97 CWD and died or were euthanized during the first 24 mo of this study, thereby ensuring calves and control deer have received considerable exposure to CWD. Similarly, all 11 cattle exposed to a single 50 g oral dose of brain tissue homogenate from CWD-infected deer remained healthy 21 mo postinoculation (through 30 June 1999) (E. S. Williams, pers. comm.), as did all cattle exposed to CWD via intracerebral inoculation 22 mo ago (R. 1. Cutlip, pers. commun.). A. lD j - ".dee, ,._.-. :JJ ,-- •• : : :: o ~ 2l i 10 :: :: r-': : ::: • :: :::: :::: :::: ::: !---:: :: r'1i i~H:: ~~ ~i ~~ :: :: :: !_.-:: :: :: ! !; H ~~ ~. .: :. : 'III' 8. WlitR-t.Ied dHr lD .., i Xl o t 2) z Pathogenesis of CWD in mule deer (Williams and Miller): rcs Using ruc, Prp was detected in brain tissue (medulla oblongata at the obex) from 1 of2 muIe deer experimentally inoculated with CWD 6 or 9 mo earlier. One of two deer examined 16 mo after inocuIation (PI) had lesions of spongiform Figure 2. Chronic wasting encephalopathy, and both were ruC-positive. Two deer disease continued to affect both mule deer and whiteexamined 3 rno PI and 2 examined 12 mo PI were negative, as tailed deer held at FWRF. were all 10 uninoculated controls collected from RMANWR at the same intervals. One of the 8 remaining deer inoculated in December 1997 began showing early clinical signs of CWD ~ 15 mo PI; a second began showing early signs 2-3 wks later, and subtle signs were noted in at least 4 of 8 inocuIated deer alive 18 mo PI. ResuIts from examination of lymphoid tissues are pending. Epidemic modeling (Gross and Miller): Simulations ofCWD dynamics that used a broad range of parameter values resulted in projections in which either the disease or the deer population was eliminated. We did not identify a set of realistic parameters that resulted in stable coexistence of chronic wasting disease in deer populations. Population productivity (i.e., harvest) was reduced in populations by very low rates of prevalence due to the combined effects of a reduction in per-capita production and a decrease in population density. Spread of the disease was highly sensitive to the rate of transmission, and a very small decreases in the efficiency of transmission resuIted in notable decreases in rate of spread of the disease. Simulatedjest and slaughter programs revealed the importance of initiating control activities while prevalence of the disease was low « 0.05). Low rates of test and slaughter (e.g., < 20% of the infected population) effectively eliminated wasting disease in simulated populations if control measures were initiated while prevalence was low (i.e., 0.01), but the likelihood of control diminished rapidly as disease prevalence increased. Test and slaughter programs that examine will require an effort sustained over many decades to ensure elimination of chronic wasting disease. CWD Monitoring and Management Plan The draft monitoring and management plan (Appendix B) has been distributed for internal and limited external review, and will be finalized by 30 September 1999. Surveillance activities for 1998-1999, as well as surveillance planned for 1999-2000, reflect prioroties established in the monitoring portion of this plan. �98 ACKNOWLEDGMENTS . The statewide CWD monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those regional and area biologists, district and area wildlife managers, volunteers, deer hunters, and others who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. LITERATURE CITED K. 1, T. V. Baszler, 1. M. Miller, T. R Spraker, 1 Sadler-Riggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.1.5 defines a conserved epitope on the ruminant prion protein. }. Clin. Microbiol. 36:1750-1755. Williams, E. S., and S. Young. 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30:36-45. _--" M. W. Miller, T. 1. Kreeger, H. Van Campen, and T. R Spraker. 1998. Susceptibility of cattle O'Rourke, to cervid spongiform encephalopathy. unpublished grant proposal, submitted to USDA, CSREES, National Research Initiative Competitive Grants Program, 88 pp. Prepared by _ Michael W. Miller Wildlife Research Veterinarian �99 Appendix A CWO: Simulating Chronic Wasting Disease User's Manual and Model Documentation Version 1.0 June 1999 John E. Gross Natural Resource Ecology Laboratory Colorado State University Ft. Collins, CO USA 80523-1499 Email: JohnG@NREL.ColoState.edu �100 CWD: Simulating Chronic Wasting Disease Summary CWO is an individual-based model that represents the most important processes determining the dynamics of animal populations over periods of decades or centuries. It simulates reproduction, disease dynamics, and the interaction of the animals with environmental characteristics that can change through time. Each animal in the population is explicitly represented and individual characteristics including age, sex, and disease state are tracked for the life of an individual. The model simulates 1 to 3 disease period, and includes the capacity to model a wide variety of harvest scenarios. Files are written that facilitate analyses of population responses to disease, harvest, or environmental variation, including changes in disease prevalence, disease-caused mortality, harvest, and changes in population age/sex structure. CWO has a flexible structure and there are no inherent practical limitations to the . number of individuals that can be simulated during a run. Practical limits to the number of individuals are set only by the capabilities of the computer on which the model is run. Introduction To make informed decisions on management of large ungulates, biologists need to evaluate the consequences of alternative management actions on population processes. . Management' actions can include hunting by the public or agency personnel, vaccination, selective harvest, habitat modification, or a combination of these actions. The consequences of these decisions depend on a complex of factors, and it is thus difficult to evaluate the relative merits of alternative management plans. CWO was designed to simulate management actions that might be used in attempts to eliminate CWO or to inhibit its spread. The model simulates each individual in the population and explicitly represents reproduction, natural mortality, disease transmission, non-selective harvests (Le., hunting), and selective harvests (e.g., test and slaughter). The use of an individual-based model is particularly appropriate for CWO because stochastic effects are important in small populations, or where a small number of individuals have a large effect on population processes. This situation clearly applies to CWO, where the behavior of a small number of infectious individuals can have a profound influence on long-term dynamics of a much . larger population. �101 An Overview of Model Structure and General Features Animal populations are simulated within a landscape that potentially can consist of a single or multiple patches. Each individual is simulated and has attributes including a sex, age, disease state, and membership in a local population. Mortality and fecundity are stage specific processes, and each individual is assigned to a specific stage based on its age. Mortality is density-independent, and fecundity (recruitment) responds to density only when density exceeds a threshold value. CWO differs from other population simulators by . incorporating disease, modeling both males and females, and by including functions that permit age and sex-specific patterns of removal. Because the model is individual-based, it is appropriate for representing the dynamics of small populations as well as large. In general, the number of patches or individuals that can be simulated are limited only by computer memory and processor speed. In reality, it is much easier to generate complex model dynamics than It is to understand the output, and most practical limitations will result from' an inability to analyze and understand output. It is essential to run many simple simulations to ensure that you have a complete understanding of model behavior before introducing spatial structure or other complexities. i Patch Attributes and Dynamics A patch is an area of the landscape that can support a local population. A Patch has the attributes of area, current quality (see below), maximum quality, mean environmental quality (from 0-1), maximum environmental quality (0-1), deviation from mean quality, and time since disturbance. Overall patch quality is quantified in a single variable ("forage") calculated from a user-defined function that transforms current forage to quality multiplier' (from 0-1; Fig. 2). This "forage" quality multiplier is used by the local population each year to determine the ability of the patch to support a population of animals (see below). Patch dynamics are simulated by predicting "forage" as a function of time since disturbance. The function that determines "forage" is calculated from a linear interpolation between forage and time values that are user-defined. Patch attributes can dramatically affect population processes through densitydependent effects on recruitment. If you wish to remove density-dependent effects from the model and control populations through harvest, set the patch size to a number much larger than mean population size and set animal density (in the *.spc file) to a number greater than one. Recruitment and Death The likelihood of recruitment changes with animal age and varies from year to year. Yearly variation is represented by an "environmental quality" multiplier that modifies the average recruitment rates. Each year, the model selects a random deviate from a Beta distribution that represents the "environmental quality" for the current year. The distribution of "environmental quality" is defined by the mean and standard deviation (entered by the user), and if the standard deviation is set to 0 there is no annual variation in the overall rate of recruitment. Each year the model loops through all females and compares the probability that a female of that age recruits an offspring into the population to a uniform random deviate. If the random deviate is less than the probability, recruitment occurs. Animals are culled from the population at stage-specific rates once per year. Mortality rates are independent of animal density and are subject only to stochasticity due to random events and to acute catastrophes. Stage-specific mortality rates are input by the user, and �102 for each individual, these rates are compared to a uniform random deviate to determine whether that particular individual dies during the year. Animal density dependent can effect population dynamics by reducing the probability of recruiting into the population. There is no effect of density on survivorship. Population density affects recruitment only when it exceeds a density threshold. Above the density threshold, the probability of recruitment declines linearly to 0 at a user-defined upper recruitment bound (Fig. ). In most situations this model is used to simulate, density plays no role in population dynamics because populations are controlled primarily by harvest. Under these conditions, its best to set the patch size sufficiently large to ensure that a density function is never invoked. Animal and Patch Aging The age of both animals and patches are incremented at the end of summer, after dispersal and prior to mating. At this stage, any patch manipulations are input and patch disturbance occurs. New patch statistics are generated for each patch, to be used in the following year's simulation. Data Output Model output is generated at the end of each year. The frequency of model output to the screen is specific by the user, while file output is generated every year. Output files formats are designed for analysis by statistical packages (e.g., SAS, SPSS) and are fixed format. The year is incremented immediately before model output and before patch dynamics are simulated. Thus year 0 output records are initial conditions. Running a Simulation To run a simulation, it is first necessary to build a set of input files that contain the variables and parameters used in the simulation (Table 1). The overall model run (which may consist of a large number separate Monte Carlo simulations) is controlled by a file with the extension .run. This file contains the names of input files that define life history characteristics, patch attributes, disease dynamics, and other run-time information described in Table 1 and below. This section describes the input files necessary to conduct a model run. The appendices to this manual include sample input file of each type. Input Files A simulation is controlled by variables and parameters specified in files that define the characteristics of the. animal species and landscape, and by the a file that contains information specific to a particular run (e.g., the number of years to simulate, names of input files, and what information is to be written to output files). In general, lines in an input files begin with an integer that tells the program what the rest of the line contains. This is followed by a one word descriptor (e.g., a series of characters and/or numbers that contain no spaces) of that line, followed by one or more parameters. It is essential that the one word descriptor has no spaces, and that there is at lease one space between the descriptor and the parameter(s). Input files are summarized in Table 1. Summary of parameters contained in each input file. 1. *.run Simulation run parameter file: Contains the names of files with parameters to be used in a specific set of runs, the number of runs to be simulated, the length of �103 each run, and which output files are to be written. It contains a variable for the frequency of output to the screen and a delay interval so that screen output can be more easily viewed. Screen output is slow; you can dramatically speed model execution by increasing the interval at which output is printed to the screen. This is the"master" file that and it deals with the highest level of model control. Code: Inputs::ReadRUNFile 2. .. *.pch Patch attributes include the size of each patch, maximum quality of the patch (0-1.0), a mean quality and the standard deviation of the mean patch quality, an initial forage (which remains unchanged in the 'absence of disturbance). Specified changes to patch quality and/or size in a given year can be used to simulate prescribed bums or other management protocols. Code: LandScape::ReadPCHFile 3.:''. *.spc Species characteristics: sex ratio at birth (m:f), number of age/stage classes for males and females, ages associated with each class, litter size, stage specific mortality, birth schedule, adult male and female body size, maximum density. The density threshold is estimated from the maximum density of animals, patch quality, and patch area. This file also specifies a function that relates patch quality (summarized into one variable, called "forage", for convenience) to a quality multiplier. Linear interpolation is used to estimate quality for values intermediate to those entered. Code: MammaIData::ReadSPCFile 4. *.pop Population parameters: This file contains the initial 'size and composition (age, sex) of populations. Code: AnimaIPopulation::ReadPOPFileO 5. *.hrv Harvest. File with parameters that determine the rules used to implement harvests. This includes the frequency of harvest (every year, every other year, etc.), threshold population sizes for determining the size of harvest, rules that govern the number of animals harvested, and the age and sex composition of the harvested population. 6. *.dis Disease:. File with parameters that determine disease dynamics. Includes parameters for transmission, and transition from incubating to infected and infected to dead. ' Model Functions and Details This section describes the structure of specific model functions, the implementation functions, and sources of data used to parameterize the model. of model Patch Dynamics Patches are areas that potentially support a local population, and they are characterized by their area (_area) and quality (_qualify, 0-1), constrained to a maximum for each patch (_maxQualify). Patch quality defines the ability of the patch to support animals relative to their maximum density. For example, if the maximum density for a species is 10 and the quality of a particular patch 0.1, that patch �104 Table 1. Input file extensions and the types of data they contain. file name type of data example file parameters *.pch patch data size, maximum quality, time since disturbance *.spc species attributes sex ratio at birth, stage-specific fecundity and mortality, maximum *.pop local population data number of local populations, age and sex of the members in each *.run simulation run control # of years of the simulation, names of input and output files, output *.hrv harvest information frequency, number harvested, and composition of harvest *.dis disease parameters transmission and transition proabilities I will support 1 animal per unit of area (area is generally expressed in krrf). The quality of each patch can be affected by environmental stochasticity, which is characterized by a normal random variate with a specified mean LmeanEnvirQualify, 0:-1) and standard deviation LsdEnvirQualify). The quality of a patch during any given year is calculated from it's current forage (see Landscape, _forage), constrained to a _maxForage level specific to each patch, and the quality associated with a given value of forage: _qualify = f(minLforage,_maxForage)) and the effects of environmental _qualify = minLmaxQualify, stochasticity (if any): _qualify * norma/_randomLmeanEnvirQualify, _sdEnvirQuality). The function that calculates quality as a function of _forage is defined by the user. and linear interpolation is used to evaluate points between those defined in the input file. If current forage is greater than that defined by the user, the _forage value at the maximum _gTSinceDisfurb is used; e.g .• no values are extrapolated beyond the data. These are combined to determine the population size at which reproduction is inhibited, _densifyThresSize, as a function of patch quality and the maximum density of animals that the highest-quality patch could support. _densifyThresSize _qualify. = _maxDensify *_area * 50 100 150 200 250 300 S50 ••00 Forage This design has been implemented to Fig. 2. User-defined function relating quality to forage. reflect the observation that population size may be restricted by forage availability, which changes over time. or other habitat features (perhaps escape terrain) that do not change. The quality of any single patch is therefore constrained by both a "food" -type variable Lforage) and other patch characteristics LmaxQualify). Code: LocaIPop:SetDensThresSizeO; LocalPop:DensThresSizeO �105 Species Characteristics Each species to be modeled must be described by life history characteristics including the number of different stages for males and females LnMaleStages, _nFemaleStages), inclusive ages of each stage LmStageMinAge, _'StageMinAge), maximum number of young LmaxYoung), the probability of having O-_maxYoung (_pYoungm, stage-specific birth and death probabilities (_pRecruitj, _pMMortality;, _pFMortality;. where I is stage). Density Dependence Density dependence influences the probability of dispersal and recruitment of new individuals into the population. The probability of recruiting one or more young is stage-specific and is determined by user-input values. This probability is then modified to reflect the effects of density and environmental stochasticity, To calculate density-dependent effects, it is necessary to specify. a species-specific maximum density ·LmaxDensity, #/unit-area), the density a species achieves in optimal habitat.. The units of patch size and ...;,maxDensity (e.g., ha) must be the same. The density at which recruitment falls to zero is defined by _upperPopBound, a decimal value greater than 1 used to determine the population size at which the probability of recruiting an individual falls to zero in the absence of environmental stochasticity (Figure XX). When the population size in patch I is greater then _pop Ttuessize; the age-specific probability of recruitment (_pRecruif) is modified to reflect the density-dependence: _pRecruitj .' ( = _pRecruit j popSizej l-----------------------------------~--(l+_upperPopBoundj) ) _densThresSizej Effects of Density on Recruitment The probability of recruitment of a new individual can be further influenced by environmental stochasticity, which is constrained to the range of _envirQualMin andt: environmental Quality = maxL envirQualMin, nonnalrandomLmeanEnvirQualify,_ _pRecruitj 11-----------------,. l sdEnvirQuality)) = _pRecruitj *environmental Quality Fig. 3. DensitY effects, where A = _densThresSize Taken together, these functions account for annual.stochastic and B = _densThresSize • _upperPopBound fluctuations in habitat quality that affect "carrying capacity", and yearly fluctuations in recruitment that result from abiotic or biotic sources (weather, predation, etc.). -. Code: AnimaIPopulation::BreedAndRecruitO, LocaIPop::SetDensThresSizeO; LocaIPop::DensThresSizeO Data: MammaIData._envirQuaIMean, _envirQuaISD, _probRecruitD Mortality Natural mortality occurs once per year (Figure 1), and is a stage-specific function. Stage and sexspecific mortality rates are. user-specified parameters in the *.spc file. For each individual, a uniform random deviate (0-1) is compared to the probability of death. Code: AnimaIPopulation::CUII Aging At the end of each time loop, the age of each individuals is incremented by 1 and an appropriate adjustment is made to _tSinceDisfurbance for each patch and local population. Code: AnimaIPopulation:: AgeO; LocaIPop::SAgeO; LandScape:: SetTimeO �106 Model Output Model output is written to standard ASCII text files that are created in the current directory, typically the directory containing the input and executable files. By default, any existing files of with the same name are erased upon opening, except for the error log file. Output file formats are described below. Any errors that occur during the run are printed to the screen and error file, and the run will be aborted when a severe error is detected. Some common errors in input parameter values are automatically corrected (e.g., an out-of-range parameter), in which case a message is written to the error log file informing the user of any corrections. All simulation result files are formatted to facilitate input to programs for further analysis in statistics, graphics, or spreadsheet programs. Variables in output files are either space or comma delimited. File output ceases when an entire population goes extinct, except for data written to the summary output file. Thus if a population goes extinct in year 23 of a 50 year run, files will generally contain 24 years of data (year 0 + 23 years). The summary file will be filled with 0 values for the full length of the run (year 0 + 50 years). All output file names begin with the same prefix, which can be specified in the *.run file or which will default to "cwd". All output file names have an ".asc" extension except the error file. Output Files Produced by Every Run _pavg.as<;: - 1 line for each year of run. Mean and standard deviation of the number of susceptibles, incubating, infectious, and total population size. _ sum.asc - 1 line for. each year of each run. Number of susceptibles, incubating, infectious, and harvested. CWD _err. txt (if an error is detected). Error information Information about any errors detected during a run are printed to this file. Errors are assigned to categories Warning, Error, and Fatal Error. Warning messages signal an error than can be automatically corrected within the program or conditions that are unlikely to affect program results. Errors are more severe, and may be corrections to parameters that are frequently entered incorrectly or a condition within the program that may be irregular. Depending on the compilation, the program may abort upon detecting an error (this is a compiler switch, and cannot be changed by the user). The program always aborts when a Fatal Error is detected. Fatal errors are usually the result of an incorrect input file format, invalid parameter, or insufficient hard disk space or memory. Table 2. Output file names and contents. Files in italics are always produced, others are produced only when specified by a switching variable in the *.run file. Files are comma-delimited. File Columns Information cwd err.txt text Produced or appended to if an error is reported. _age I-many run, year, patch number, males by age (O-Age max), females by age (0Age max). Age max is specified in the *.spc file. disfxhs 1-5 run, year, patch number, period, disease-caused deaths by sex and age class -hrv l-many run, year, patch, population size category, males by age (O-MaxAge), females by age (O-MaxAge) _pavg l-many year, mean and standard deviation of susceptible, incubating, infectious, and total number of animals _prevAge l-many run, year, patch number, susceptible males by age category, susceptible females by age category, incubating by sex (m.f) and age category, infectious by sex (m, f) and age category sum 1-5 run, year, patch number, number of susceptible, incubating, infectious, and harvested animals ts 1-9 run, year, patch number, test&slaughter index (O=off, I=on), population size, prevalence before t&s, prevalence after t&s, males removed, females removed - (produced only when t&s is on) �107 Sample input files and formats General File Format Used by CWD The general format of CWD input files is to begin each line with an integer number that indicates the content of one or more lines of the input file. "99" is always used to indicate a comment and the program disregards all information on a line following the "99". In general, the integer is followed by one word (i.e., a series of characters and/or numbers that contains no spaces) describing the following parameter(s) or variable(s) .. The descriptive word can contain underscores, upper and lower case letters, numbers, or any other characters except blank spaces or tabs. For situations where there are a: variable number of input lines (e.g., the age structure of an initial population), lines may begin with a' data value not preceded by an integer indicating the line content. Sections of input than can include a variable number of lines always end with a delimiter, which is usually a number less than zero. It is essential that these file formats be followed, and users are very strongly encouraged to modify existing input files rather than create a new file. Virtually all errors in model runs can be traced to a mistake in an input file. Many (but not all) common mistakes in input files will be detected by the program and reported to the error file (CWD _err.txt). Model Run Data (*.run) "The *.run file is the first file read by CWD and it determines program operations at the highest levelwhich modules are used, the names of other input files, which files output files are to be written. _A value of 1 or greater turns on optional functions or optional outputs and the value "0" turns these ',' function off. If Random = 0, the same random number seed is used at the beginning of all runs. nlls option is used for debugging and Random should generally be set to "1". A delay can be used if you wish to slow the program in order to more easily view screen output. 99 cwd.run 99 -2 PCHFileName: cwd_inpt.pch 3 SPCFile: cwd_inpt.spc 4 POPFile: cwdjnpt.pop 5 Harvest: 1 cwd_inpt.hrv 6 Disease: 1 cwd_inpt.dis 9 Test&SI: 1 cwdjnpt.tst 99 -11 RunYears: 100 12 Runs: 250 14 ScreenOutputFreq: 50 99 - if random = 0 use same seed for all runs; if random = 1 use a different seed. 15 Random: 1 99 _ all output files will have the following "prefixed" to their names 99 _ E.g., the file beta_2_11_14_age.asc would be produced with this line. In addition, 99 _ any sensitivity variables are added to the file name (see below). 99 -16 OutputFilePrefix: beta_2_11_14 99 -21 PopAgeOut: 1 _age 22 PatchesOut: o _pch �108 23 DoDisOutput: 1 dis 29 doHarvestOutput: 1 harv 9999 -- line 31: on/off prevalence level to begin output, prevalence level to end output 99 so the following results is output when the prevalence level is >= 0.03 and <= 0.50. 991 .01 .50 31 doPrevAgeOutput_startPrev_endPrev: 1 disDths 32 doDisDeathsByPeriodOutput 9999 101 = sensitivity analysis. 99 Variables are repeated for each variable, so the number of 99 values on the line MUST be divisible by 4. 99 var_number smallest_val largest_val step 99 -101 sens vars 123.4.8 .05 Lines 21 -31: Any integer of 1 or greater tufns output on. 31: These files can be very large, thus they are produced only when prevalence in a patch is equal to or within the range of the starting and ending value. Patch Parameters (*.pclz) 99 filename: cwd_21 May.pch 10000 3 PatchArea: 4 MaxQuality: 1 5 MeanEnvQual: 1 6 sdEnvQual: .0 7 maxForage: 100 100 8 initialForage: PatchArea: Area of patch used by the local population. Set to a large value unless you want density.•.dependent population regulation to operate. MaxQuality: This value reflects the maximum density that a particular patch can support, relative to the species-specific maximum density. The species-specific maximum density is specified in the *.spc input file. MeanEnvQual: Mean quality of the patch (must b~ less than MaxQuality). sdEnvQuality: Standard deviation of the mean quality. If set to 0, there will be no annual variation in the value of the density threshold due to differences in patch quality. maxForage: Maximum forage value that will ever be obtained on a specific patch. initialForage: Forage value at start of the run �109 Harvest Populations are normally controlled by harvest of animals. The rate of harvest can vary depending on population size, which can be categorized as small, normal, or large. Input variables are used to determine threshold sizes between these categories. For each population size category, input variables specify age-specific rates of harvest. There are no limits to the number of age categories that can be specified, but if ages within a category overlap, the last value in the input file will be used. If you want harvest to be independent ot age, specify the same rate for all ages. i. Annual rates of harvest are determined each year by selecting the appropriate mean harvest rate from the input file (lines 11-17) and then modifying this rate to account for annual variation. Mean rates for all age groups are multiplied by a random deviate with mean 1 and CV from line 10. Thus annual variation for all age groups are correlated. 99 CWD for mule deer 99 Rule 1 has proportion harvested for low, med, and high pop numbers, by sex and age 1 harv_rule 1 10 CV_on_percent_harv .2 99 _ FEMALES min_age max_age portion_harvested. Ages are inclusive 11 F_Iow 0 20 .0 12 F_med 0 0 .01 12 F_med 1 2 .02 12 F_med 3 20 .07 13 F_hgh 0 0 .03 13 F_hgh 1 2 .05 13 F_hgh 3 20 .10 99 - MALES 15 M low 0 20 .0 16 M med 0 0 .02 16 M med 1 1 .06 16 M_med 2 20 .20 17 M_hgh 0 0 _..03 17 M_hgh 1 1 .09 17 M_hgh 2 20 .27 99 -- repeat lines 21 & 22 for each local population. 21 localPop 1 22 threshold numbers 500 1000 . �110 Test and Slaughter Test and slaughter is implemented by specifying the efficacy of the program for males and females. Efficacy is the product of the portion of the population tested and the likelihood that a positive animal will be detected. Variables in the input file determine whether the program is implemented from the beginning of the program, or after other criteria are met. A test and slaughter program can begin at a specific year of a model run, or after the population has achieved a specified prevalence rate. Efficacy is the product of the proportion of the population tested and ability to detect the disease. The variable on line 3 (periods to detect) is the number of periods of incubation that must elapse before a disease can be detected in an exposed individual. If there were 2 periods per year and this parameter were set to 1, an exposed individual would not be detected until they had incubated for a full period, equivalent to about 6 months. If you assume that rate of exposure is constant, one could interpret this to suggest that the average incubation time before detection would then be about 9 months, or one full period and (on average) half of another period. However, since test and slaughter occurs only once per year (after harvest and the second disease period), individuals infected during disease period 2 (falilwinter) will not be detected until the following year unless periods of detection is set to O. Infectious individuals are always detected. 99 cwd_test_ and_ slaughter.tst 99 3 periods_of_incubation_before_detection 4 local_pop_tested 1 5 Efficacy .5 6 Start_year 10 7 Start_prevalence .05 3 �III Sensitivity Analysis The model provides the user with very broad options to conduct sensitivity analysis. Todo so, specify on line 1.01in the run file the variable number (from the table below), the initial value, the maximum value, and the step (amount for the initial value to be incremented for each set of runs). Some variables (will in the future) also require that a local population be specified. When a sensitivity analysis is conducted, the names of all output files reflect this by adding the number of the variable and the step (starting with 0) of variable value to the file name. These values are added after the file name prefix specified on line 16 in the run file and before the normal file suffix. For example: lirie 16 in run file: 16 file_name: 24jan_larimer line 101 in run file: 101 sens_vars 121 .01 .10 .01 Which means: do runs with maternal transmission rates from 0.01 to .1 by .01. Ten sets of runswill be simulated, with 10 output files of each type (e.g., _pavg, _sum, etc.). The summary output files, for example, would be: 24jan_larimer_:_121_0_sum.asc 24jan_larimer_121_1_sum.asc 24jan_larimer_121_9_sum.asc If additional sensitivity variables are added, these are added to the file name in the general format: prefix_var#_step_var#_step ... suffix. There are no internal limits to the number of sensitivity variables, but since all levels are fully crossed, you can easily generate hundreds or even thousands of output files. The difficulties in analyzing such results are substantial. �112 Sensitivit~variables available for anal~sis. MammalData MammalData MammalData MammalData MammalData MammalData MammalData Number Variable name value or Mult # values 101 female survival multiplier 3 102 male survival multiplier 3 103 recruitment multiplier 3 104 sex ratio at birth value 3 105 mean environmental value 3 quality 106 std environmental quality value 3 121 maternal transmission value 3 122 prob. infected recruits value 3 123 period 1 beta value 3 124 period 2 beta value 3 125 period 3 beta value 3 beta for all periods 126 value 3 AnimalPop 21 periods for test detection value 3 LocalPopulation 51 LocalPopulation 61 LocalPoQulation 62 test efficacy mean - both value harvest lower threshold value harvest uQQerthreshold value 3 3 3 Class Affected MammalData MammalData MammalData MammalData MammalData �113 AppendixB Chronic Wasting Disease in Deer and Elk: DRAFT Colorado Statewide Monitoring and Experimental Management Plan M. W. Miller and R.H. Kahn Terrestrial Wildlife Resources, Colorado Division of Wildlife . Background Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (TSE) of native deer (Odocoileus spp.) and elk (Cervus elaphus nelsoni) characterized by behavioral changes and progressive loss of body condition that invariably lead to the death of affected animals (Williams and Young 1992). Neither the causative agent nor its mode of transmission have been identified. There are no tests currently available for diagnosing CWD in live animals, and extant postmortem tests require microscopic examination of brain tissue. There are no known treatments for CWD. Previous attempts to eradicate CWD from research facilities failed on at least 2 occasions (Williams and Young 1992; Miller et al. 1998). Although similar in some respects to other TSEs that affect domestic sheep (scrapie) and cattle (bovine spongiform encephalopathy; BSE), existing data indicate CWD cannot be naturally transmitted to domestic livestock, and that scrapie and BSE cannot be transmitted to native cervids. Moreover, available data indicate that CWD does not present a threat to human health. "Chronic wasting disease" was first recognized by biologists in the 1960's as a disease syndrome of captive deer held in wildlife research facilities in Ft. Collins, CO. This disease was subsequently recognized in captive deer, and later in captive elk, in wildlife research facilities near Ft. Collins, Kremmling, and Meeker, CO and Wheatland, WY (Williams and Young 1980, 1982), as well as at in least two zoological collections (Williams and Young, 1992). More recently, CWD has been diagnosed in captive elk residing in one game ranch in Saskatchewan (Spinato, pers. comm.), two ranches in South Dakota (Holland, 1997), one ranch in Nebraska (W. Cunningham, pers. comm.), and one ranch in Oklahoma (L. Detwiler, pers. comm.). Since 1981, over 100 cases of clinical and preclinical CWD also have been diagnosed in free-ranging mule deer (0. hemionus), white-tailed deer (0. virginianus), and elk from northeastern Colorado; most of these diagnoses have been made since 1990 (Spraker et al. 1997; Miller, 1997). At present, the known world-wide distribution of CWD in wild cervids appears to be limited to northeastern Colorado and southeastern Wyoming (Miller, 1997; Williams et al., 1998). Although CWD was first diagnosed in captive cervids, the original source of CWD in either captive cervids or free-ranging cervids is unknown; whether CWD in captive cervids really preceded CWD in wild cervids, or vice versa, is equally uncertain (Spraker et al. 1997). In Colorado, free-ranging CWD cases in deer and elk have originated from throughout the northeastern portion of'the state. Game Management Units (GMUs) yielding infected deer or elk include 7,8,9, 19, 191,20,29,91,93,94,95,951, and 96. Although cases have come from 13 different GMUs, two Data Analysis Units (D4, DI0) have yielded over 85% of the documented cases. Based on targeted surveillance data and select harvest surveys, wild deer or elk populations in other parts of Colorado are probably not infected with CWD (Miller, 1997; 1998). Both targeted and harvest surveys indicate GMUs 9, 191, 19, and 20 are the main foci ofCWD in Colorado; estimated prevalence in all four GMUs is ~3% (Miller, 1997; 1998; M.W. Miller, unpubl. data). Data from harvest surveys indicate that CWD is relatively rare in other parts of northeastern Colorado, probably affecting ~2% of the deer in GMUs 7, 8, 29, 91, 93, 94, and 96 (Fig. 1). Similarly, harvest surveys indicate <1 % of the elk in DAUs E4 and E9 are infected with CWD (Miller, 1997; 1998; M. W. Miller, unpubl. data). For deer populations in the four most heavily infected eastern Larimer County GMUs, no real trend in prevalence (increasing or decreasing) can be discerned from data available to date. In the absence of historical (20-30 years ago) prevalence data or reliable estimates of transmission rates, it is �114 also unclear whether overall incidence ofCWD in northcentral Colorado DAUs is stable or increasing, or whether short-term observations can accurately forecast long-term trends. Based on prevalence estimates and preliminary results of simulation modeling to predict dynamics and impacts of CWD on affected deer populations, it appears CWD was introduced into northern Larimer County over 30 yrs ago (M.W. Miller and C.W. McCarty, unpubl. data). Beyond Larimer County, the South Platte River corridor may be the single most predictable avenue for spread of CWD. Kufeld and Bowden (1995) reported that a proportion of South Platte River bottom deer were highly mobile; observed deer movements included some to and from eastern Larimer County along the Cache la Poudre and South Platte Rivers. These movement patterns provide a plausible mechanism for the apparent emergence of CWD in South Platte River GMUs detected recently through targeted surveillance and harvest surveys. Other likely routes for deer emigrating from Larimer County have not been identified, and may be less predictable. Altitudinal movements of some elk subpopulations in the southern part of Larimer County are also somewhat predictable (Bear, 1982). Although there is potential for elk to cross the Continental Divide through Rocky Mountain National Park, the relatively low prevalence of CWD among elk diminishes the likelihood of its spread via their movements. The significance of CWD and its impacts on native deer or elk populations have not been determined. Preliminary results of simulation modeling suggest that, sustained at 5% prevalence as observed in the four most heavily infected GMUs, CWD could impact wild deer herds and lead to population declines (M.W. Miller and C.W. McCarty, unpubl. data). Data on CWD prevalence in . female deer are particularly critical to predicting potential impacts of disease on long-term population performance and assessing efficacy of management interventions. Preliminary comparisons made in conjunction with 1997 and 1998 surveys showed no differences in CWD prevalence between male and . female mule deer harvested in Larimer County GMUs (M.W. Miller, 1998; unpubl. data); these data were comparable to results of simulation models where male and female deer were assumed to be equally susceptible to CWD. In the absence of data to the contrary, and considering the difficulties inherent in eliminating CWD from captive or wild cervid populations once established, it seems most prudent to assume CWD could adversely affect native deer or elk populations and manage to reduce its occurrence and prevent its further spread in Colorado. Unfortunately, there is considerable uncertainty in how to manage CWD in free-ranging wildlife, or whether such an endeavor could even be successful. Because a more complete understanding of CWD is fundamental to developing comprehensive management programs, the Colorado Division of Wildlife (CD OW) needs to further understanding about CWD and its management through surveillance and experimental management. Data from completed, ongoing, and proposed research, both basic and applied, will serve as the foundation of an adaptive resource management plan for CWD in deer and elk. This plan will provide a mechanism for incorporating new knowledge gained through surveys, modeling, research studies, and management experiments into a continuously evolving management program for CWD. STATEWIDE MONITORING PROGRAM Goals: 1. Provide reliable estimates of CWD distribution and prevalence to serve as a basis for management decisions and public information. 2. Provide information to improve understanding of CWD epidemiology. 3. Continue developing efficient and reliable techniques for detecting and monitoring CWD in freeranging populations. �115 Strategy: Reliable estimates of CWD prevalence in wild deer and elk populations are needed to guide policy decisions and monitor efficacy of management efforts. We will continue to monitor deer and elk populations throughout Colorado for occurrence of chronic wasting disease using a combination of extensive and intensive approaches. These have been organized and conducted as follows: Targeted (= clinical disease) surveillance: Ongoing statewide "targeted" surveillance (i.e., submissions of "suspect" deer & elk) will be used to determine & monitor changes in CWD distribution. Based on·. experiences in Colorado and elsewhere, this appears to be the most sensitive approach for determining CWD distribution & detecting range extensions (Miller, 1997). A program for acquiring, examining, reporting on, and summarizing "suspect" CWD cases occurring throughout Colorado has been in place since 1990 (Miller, 1997). This program has served to increase ongoing surveillance efforts by field personnel statewide by encouraging submission of carcasses from deer or elk showing clinical signs resembling CWD. A formalized process for submitting cases has been developed; this process includes criteria for acceptable submissions, submission forms, handling instructions, and a system for networking submissions within CDOW and among the 3 Colorado State Veterinary Diagnostic Laboratories and the Wyoming State Veterinary Laboratory. Under this program, deer and elk showing clinical signs consistent with those seen in chronic wasting disease are collected by field personnel statewide; a "suspect case" profile has been defined (Table 1). Brain tissues are subsequently examined for evidence ofspongiform encephalopathy. Where possible, whole carcasses will be submitted for complete necropsy; at minimum, heads from suspect animals will be submitted for examination and sampling. Ancillary diagnostics, including histopathology (Williams and Y oung,1993) and immunohistochemistry of brain tissue (Spraker et a1., 1997), will be performed on all suspect cases; other ancillary tests may also be used to confirmor support diagnoses. Preliminary examination and/or test results and final reports will be faxed to CDOWs Wildlife Research Center. Pertinent data from preliminary and final reports will be entered into a permanent database, and copies of reports will be filed as well as sent to appropriate field personnel. Results from targeted surveillance will be used to identify new potential foci of CWD infection for further evaluation via harvest or road-kill surveys. Harvest and road-kill surveys: Surveys of harvested or, in some areas, road-killed deer and elk will be conducted in endemic and high-risk DAUs/GMUs to estimate and monitor CWD prevalence. We will continue conducting annual surveys in DAUs or GMUs where CWD prevalence is >2% ("endemic foci") to obtain reliable-estimates of prevalence to use as a basis for monitoring natural trends, as well as responses to management interventions. Annual surveys will be designed to provide an estimated prevalence within ±2% at a 95% level of confidence for affected populations where true prevalence is 1%. In addition to annual surveys of endemic foci, we will also continue conducting a series of surveys for CWD in other select deer and elk populations throughout Colorado over the next 5 yrs, with a goal of determining statewide distribution of CWD. Our surveillance strategy is as follows: Areas newly identified as infected via targeted surveillance (e.g., GMU 29, South Platte River corridor GMUs) will be surveyed sufficiently to obtain a reliable prevalence estimate. In areas where estimated prevalence is <1 %, CWD will be regarded as a sporadic disease and populations will be monitored at ~5-yr intervals to detect increases in prevalence. Areas where estimated prevalence is >2% will be regarded as new endemic foci, and will be monitored annually to track changes in prevalence as described above. We also plan to continue conducting surveys of at least 5 other select deer populations where CWD has not been reported �116 previously. Target areas will include both high-risk (e.g., Middle Park, Piceance Basin) and low risk (e.g., San Luis Valley, Gunnison, southern Front Range) populations. Surveys will be designed such that the probability of failure to detect at least 1 case of CWD in an apparently-unaffected deer or elk population will be ,::::0.01even if herd prevalence is 1%. Finally, we will attempt to gather a sufficient number of random samples from DAUs statewide (n-l,OOO) to determine whether or not CWD should be generally regarded as endemic in Colorado's deer populations. A tentative schedule for the foregoing surveillance is outlined in Table 2. Harvest surveys will be conducted using techniques developed in Colorado since 1991. Because regulatory requirements for head submissions increase sample sizes >4-fold, submissions will be mandatory in most GMUs where surveys are being conducted. Limited licenses may also be used in select GMUs to aid in increasing compliance. Unstaffed barrel sites appear to be the most efficient method for sample collection, and will continue to be used as the primary method for conducting harvest surveys. Brainstem (obex) from ~ I-yr-old deer and elk will be.collected for CWD testing, and immunohistochemistry (IHC) using USDA monoclonal antibody F89/160.1.5 (O'Rourke et al., 1998) will be used as the primary screening tool. Reported prevalence estimates will continue to be based on numbers ofIHC:·positive cases; because IHC appears more sensitive than histopathology in detecting preclinical CWD cases, IHC-based prevalence estimates should provide a relatively unbiased measure of disease trends over time and allow more direct comparison between field data and simulation model predictions. EXPERIMENTAL MANAGEMENT There is no precedent for attempting to manage a TSE in free-ranging wildlife. Moreover, the biological need for such management is unclear at present. Programs for managing or eliminating TSEs of domestic livestock have proven only marginally successful, and the lack of obvious success in eradicating scrapie or BSE from endemic countries, compounded by epidemiological differences between CWD and other TSEs, make such programs rather poor models for prospective CWD management. Several fundainental features of CWD epidemiology are understood poorly, if at all; in particular, the influences of host (e.g., population density, intraspecific vs. interspecific transmission, genetics) and environmental factors (e.g., contamination, reservoirs, weather) on CWD dynamics remain undescribed. In light of the uncertainties associated with its epidemiology and ecology, we believe CWD management should be approached as an experiment, thereby allowing us to learn as we . take actions intended to reduce prevalence and limit distribution. The CDOW's initial approaches for attempting to control CWD in free-ranging deer and elk were outlined in an action plan for CWD drafted in 1995 (Miller et al., 1995; Appendix A). In addition to calling for a comprehensive public information campaign, this plan identified tactics for limiting distribution and reducing prevalence of CWD based on contemporary knowledge of the problem. Prompt removal of affected animals and enforcement of feeding prohibitions were recommended to help reduce CWD prevalence and transmission. Policies and regulations were also recommended, and subsequently instituted, to prevent wider distribution of CWD via human activities (e.g., trans locations, rehabilitation, game ranching). The plan also identified a need for more extensive surveillance to gather data on CWD distribution and prevalence. As more data on CWD distribution and prevalence have been gathered over the last 2.5 yrs, it has become apparent that CWD is more widely distributed and more prevalent in northeastern Colorado (and elsewhere) than initially believed. It follows that policy, goals, and strategies for CWD management in Colorado should be reevaluated in the context of new data, as well as changes in social and political attitudes toward animal TSEs. �117 Management policy: At present, the CDOW has no stated policy related to the management of chronic wasting disease in wild deer andelk. The lack ofa clear policy statement has led to internal confusion and disagreement over how to resolve conflicts with other policies and Long Range Plan objectives (e.g., increase recreational opportunities for deer and elk hunters). Recommendation: We recommend adoption of the following policy to guide decisions on deer and elk population management. in DAUs where CWD is endemic: Pl. The Colorado Division of Wildlife is committed to minimizing the threat that chronic wasting disease (CWD) poses to Colorado's native deer and elk resources. In DAUs where CWD is endemic, goals of reducing the occurrence and the further spread of CWD will serve as the primary basis for setting management objectives. Prospective management goals: We have. identified four overarching goals that could serve as a basis for decisions related to managing CWD: 1. "natural regulation", 2. containment, 3. reduction, 4. eradication. These goals represent a continuum of possible levels of intervention, ranging from benign. rs neglect to aggressive action. There are clear advantages and disadvantages associated with each of .. these prospective management goals. Although each progressive level offers more complete control of the problem, better control is accompanied by ever-increasing technical, fiscal, and political challenges, as outlined below: l."Naturai regulation": Directing no specific management intervention toward CWD beyond culling of reported clinical cases represents the status quo approach to both disease arid deer/elk population management. It could be argued that the ongoing activities described above constitute an attempt to manage CWD. Although the impacts of this approach on CWD prevalence in endemic foci remain undetermined, prevalence in endemic foci appears to have remained stable over at least the last J yrs. This approach offers the fewest technical challenges, may be regarded by some as "safest'unlight of the myriad of uncertainties in CWD epidemiology, and in the shortterm would be most sparing oflocal resources. Unfortunately, simulation models forecast that problems with CWD will likely get worse in affected populations if left largely unmanaged, the disease could become more widely distributed, and there are tangible potential impacts on wildlife resources, recreational opportunities, and revenues. In addition, perceived "inaction" may be unacceptable to some sportsmen's groups, agricultural interests, and perhaps the general public, and could lead to the loss of management authority by CDOW. Finally, opting for "natural regulation" seems biologically irresponsible. 2. Containment: Managing primarily to prevent spread of CWD from endemic foci would require additional knowledge of the mechanisms and probable routes of CWD dissemination, but many of the important strategic components needed to support this strategy are already in place. The likelihood of trans locating infected animals from endemic areas to other areas in Colorado or �118 elsewhere was significantly reduced by regulations adopted in 1996 (ch 14 ref). Between existing data from previous movement studies (e.g., Kufeld et al., 1989; Kufeld and Bowden, 1995) and data from studies initiated more recently, major natural emigration corridors from eastern Larimer County could probably be identified and subsequently might be interrupted via intensive culling operations. This approach, if successful, would limit the magnitude of the CWD problem while largely sparing local resources. This alternative may be more acceptable to sportsmen's groups and the general public than to agricultural interests, but is probably biologically justifiable. However, such an approach would require an essentially infinite long-term commitment and yet will not eliminate CWD entirely; prevalence could conceivably increase in endemic areas. There would likely be some local impacts on resources and recreational opportunities, perhaps accompanied by local public resistance. 3. Reduction: It may be possible to manage affected deer or elk populations to reduce CWD prevalence in endemic foci. A goal of prevalence reduction clearly demonstrates intent to limit the magnitude of the problem. It seems likely that this. approach would also provide for containment of CWD. Attempting to reduce CWD prevalence might improve "consumer confidence" among hunters in endemic GMUs. This alternative may be the most widely acceptable among sportsmen's groups, agricultural interests, and the general public in terms of responsible disease and resource management. It is probably biologically justifiable in view of projected long-term effects ofCWD on infected populations and the potential for CWD to spread from endemic foci if left unmanaged. As with the foregoing goal of disease containment, prevalence reduction will require a long-term commitment and may not eliminate CWD from endemic areas; depending on specific tactics employed, prevalence could even increase despite management efforts. This approach would likely cause more severe impacts on local resources and recreational opportunities, and consequently would be more likely to foster local public resistance to proposed management actions. 4. Eradication: Eradication is probably the most desirable goal of any attempt to manage CWD. Whether it would be feasible to completely eliminate CWD from Colorado remains highly questionable. Eradicating CWD would be the best means of restoring for "consumer confidence" among northeastern Colorado deer and elk hunters, and would presumably nullify concerns of traditional and alternative livestock interests about the potential for transmission to privately-owned animals. Perhaps most importantly, eliminating CWD would be the most effective way to preempt threats of its eventual spread to other native deer and elk populations in Colorado and elsewhere. Although desirable in concept, CWD eradication is probably infeasible given the complexities and uncertainties of its epidemiology. Eradication of CWD would require long-term commitment, and probably would exaet catastrophic impacts on resources and recreational opportunities in affected areas; broader ecological impacts (e.g., on predator-prey balances) could also be severe. Public resistance is likely to emerge, at least locally, as details of such a management program emerge. Finally, it is questionable whether the potential ecological costs of CWD eradication are biologically justifiable in light of the uncertainty about long-term impacts of the disease itself. Recommendations: Based on current understanding of CWD epidemiology, prevalence, and distribution in free-ranging deer in northeastern Colorado, we believe eradication is an extreme and unjustifiable management goal at this time. In light of the magnitude of prevalence and distribution CWD has reached in Larimer County deer populations under historical management regimes, however, continuing to rely on current management approaches seems equally unjustifiable. Consequently, we recommend an intermediate approach with two goals for managing CWD in deer and elk: �119 Gl. limit distribution ofCWD occurs. to no more than the 5 deer DAUs and 2 elk DAUs where it already G2. reduce average CWD prevalence among deer and elk to <1 % in each endemic DAU and <2% in each endemic GMU; and . '~ We believe achieving the foregoing management goals will serve to protect Colorado's deer and elk resources, restore confidence in the quality of deer and elk harvested in northeastern Colorado, and ameliorate political pressures from agricultural constituencies concerned about potential for transmission of CWD to domestic livestock or privately owned wildlife. Prospective management strategies: Effective strategies for managing CWD or any other TSE in free-ranging wildlife have never been identified or evaluated. Many conventional disease management options are precluded from consideration because vaccines, therapeutics, and live-animal tests for CWD are presently unavailable (Table 3). Contrary to experiences with domestic sheep (Goldmann et al., 1994), available data indicate relatively uniform genetic susceptibility to CWD among deer (K. I. O'Rourke and M. W. Miller, unpulb. data); consequently, genetic selection would probably have no impact on prevalence even if tools forits implementation were available. Similarly, controlling reproduction alone probably would be ineffective even if practical tools were available because maternal transmission alone is unlikely to be sustaining CWD prevalence at levels currently observed in some affected deer .populations. All remaining options we can identify to reduce CWD prevalence (Table 3) involve some form of aggressive population control directed at diminishing or preempting-disease transmission -- themagnitude and duration of such control will be driven by management objectives and population responses. Based on current understanding ofCWD epidemiology (Miller 1997, Miller et al., 1998, M.W. Miller, unpubl. data), we believe that strategies capable of lowering CWD transmission rates by reducing numbers of infected animals and point sources of environmental contamination (e.g., feeders) should be most effective in lowering prevalence; although the precise mechanisms of transmission have not been identified, those details will probably have little influence on the resolution of CWD management at the population level. General models predict that random culling should be less effective than selective culling in reducing disease prevalence (Barlow, 1996; McCarty and Miller, 1998). However, field data indicate that management strategies based on culling clinical suspects probably will miss a large proportion of the infected (and potentially infectious) individuals in a population; moreover, there is no practical way to apply "test and slaughter" regimes without an antemortem diagnostic-test for preclinical CWD. Accelerated culling of early clinical cases, either by humans or via predators, may help reduce CWD transmission and prevalence. Alternatively, if the probability of CWD transmission is density-dependent, then reducing deer or elk densities in endemic areas should lead to reduced CWD prevalence; to date, the hypothesis of density-dependent disease transmission remains untested. Obvious strategies for limiting CWD distribution remain equally elusive. The mechanisms driving the spread of CWD among deer and elk populations are even less apparent than those driving disease dynamics. It is possible that CWD distribution to date has been influenced by regular and/or random movements of deer and, less commonly, elk. Previous studies (Kufeld et al., 1989; Kufeld and Bowden, 1995; S. Steinert, pers. comm.; others?) have shown that proportions of both foothills and river bottom deer populations in northeastern Colorado are either migratory or mobile; the movement patterns documented in these studies provide at least a partial explanation for observed CWD distribution. It is also possible that CWD influences its own distribution by changing behaviors, range ..... �120 fidelity, and movement pattens of affected animals; observations of repetitive pacing in captive deer and elk affected by CWD could be manifested as extensive wandering movements of free-ranging individuals. Whether or not movement patterns or dispersal rates are density-dependent remains unclear; either way, reducing population size should also reduce the probability of affected individuals canying CWD to new areas. (However, we do recognize the possibility that at some lower threshold reduced density may actually promote deer and elk movements, particularly during the breeding season). Recommendations: Based on current uncertainty about how to effectively disrupt the processes that influence CWD epidemiology, prevalence, and distribution in free-ranging deer in northeastern Colorado, we recommend initiating controlled management experiments directed toward testing one (or both) of the following hypotheses: HI. CWD transmission and prevalence infoothills and river bottom deer populations can be diminished by a) selective culling; b) increasing natural mortality via mountain lion predation; OR c) reducing deer density in affected populations. H2. CWD distribution in foothills and river bottom habitats can be diminished by a) selective culling; . b) increasing natural mortality via mountain lion predation; OR c) reducing deer density in affected populations. We further recommend that the experiment(s) be designed and conducted in a way that facilitates achievement of two short-term management objectives: MI. to stem dispersal ofCWD via deer movements along the South Platte River corridor (GMUs 94, 951,96,91, and 92). M2. to reduce CWD prevalence among deer inhabiting the four most severely affected GMUs (9, 191, 19,20). Because CWD prevalence is low «1%) in elk, we recommend that populations in DAUs E4 and E9 should be maintained at or below current densities and monitored via harvest surveys at least every 5 yrs to detect potential increases in prevalence that.might warrant more aggressive management action. :. Design of Management Experiment We recommend using an adaptive resource management approach (Walters, 198_) to test candidate strategies for reducing CWD prevalence and distribution. Based on initial evaluations of these candidate strategies (Table 4), more detailed management experiments will be developed; as part of that process, decisions will be made on which, if any, approaches to pursue and where CWD management will be attempted. Tactics for accomplishing management approaches (e.g., harvest, selective culling, ground/aerial gunning, changes in predator harvest, etc.) will follow from internal consensus on which tactics are viable under the social and political constraints imposed by the area(s) selected for study. Prospective management tactics: Tactics supporting selected management strategies: �121 - harvest? (role of public hunting?) - shift emphasis from recreational opportunity to population management - modifications of GMU/ "management area" boundaries to focus mgt & distribute pressure - season structurellength & bag limits- reg changes - schedule - culling? - ground vs aerial vs capture & kill options - public vs agency c; - private land issues - fertility control? (probably not for reductions, but maybe to maintain) - agent, delivery, cost? - reduce predator quotas? (close seasons?) - predator introductions? - poisoning? - other? , '; . <" Issues surrounding CWD management - Should public hunting continue in endemic areas? - What are public desires/expectations related to CWD management? - Can we impose intensive population management on private lands? - What are reasonable expectations for funding and long-term agency/political/public - Others? commitment? Outstanding tasks (partial list) Human dimensions -- Public service -Funding (PBE)-- For both internal and external publics, seek consensus on: what direction to take, which strategies are most viablelleast objectionable, etc., impacts on recreational opportunity, trade-offs Seek/gain cooperation, access, etc. (follows from lID issues above) Estimate support required for evaluation of management activities, as well as fiscal impacts of candidate management approaches LITERATURE CITED Goldmann, W., N. Hunter, G. Smith, 1. Foster, and 1. Hope. 1994. PrP genotype and agent effects in scrapie: change in.allelic interaction with different isolates of agent in sheep, a natural host of scrapie. 1. Gen. Virol. 75:989-995. Miller, M. W. 1997. Monitoring and managing chronic wasting disease in Colorado. Pages _-_ in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-I0, Work Plan 2, Job 17. Colorado Division of Wildlife; Fort Collins, Colorado, USA. (in press) Miller, M. W. 1998. Monitoring and managing chronic wasting disease in deer. Pages _-_ in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-l1, Work Package 3001, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) Miller, M. W. 1998. Monitoring and managing chronic wasting disease in elk. Pages _-_ in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-ll, Work Package 3002, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) �122 Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epidemiology of chronic wasting disease in captive Rocky Mountain elk. J. Wildl. Dis. 34:532-536. Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. J. Adrian, G. G. Schoonveld, R. A. Spowart, K. 1. O'Rourke, J. M. Miller, and P. A. Merz. 1997. Spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus elaphus nelsoni) in northcentral Colorado. J. Wildl. Dis. 33:1-6. Williams, E. S., and S. Young. 1980. Chronic Wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16:89-98. and __ . 1982. Spongiform encephalopathy of Rocky Mountain elk. Journal of Wildlife Diseases 18: 465-471. and __ . 1992. Spongiform encephalopathies in Cervidae. Revue Scientifique et Technique Office International des Epizooties 11:551-567. ---' and __ . 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30:36-45. _-J _-J Table 1. Profiles used in chronic wasting disease targeted surveillance. • Species: • Age: mule deer white-tailed deer elk 2:. 18 months • Signs: emaciated and abnormal behavior &lor indifference to human activity &lor increased salivation &lor tremor, stumbling, incoordination &lor difficulty or inefficiency in chewing/swallowing increased drinking and urination &lor �123 Table 2. Tentative schedule for systematic statewide chronic wasting disease surveys of deer populations using harvest and/or road-kill samples. . CWD Status GMUs Years surveyed Endemic foci (:::::2%) 9, 19, 191,20 1996-2006 Endemic (~1%) .29 90,91,92,93 94 95,951,96 1997-2000 1997-1998;2004-2006 1997-2000 1996-1998,2004-2006 "High Risk" 87 :}8, 28, 37, 371 6, 16, 17, 161, 171 22 1997-2000 1998 1999-2001 1999 Other areas . 104 66,67 83 "Uncompahgre" "Southern Front Range" Random Statewide ..r- -. ~·i .. 1996-2000 1997-1998 1994-1993, 1998-1999 2000 2001 2002-2003 [Note: Survey targets and schedules subject to changes influenced by new data and availability of resources supporting CWD surveillance activities.] Table 3. Prospective strategies for chronic wasting disease management. Strategies for limiting distribution - preclude human-caused translocations (mostly done) - interrupt migration corridors (fencing?) - change habitat (improve/degrade to influence animal distribution?) - alter migratory behavior (how?) - reduce density (relationship between density & distribution untested) - other? Strategies for reducing prevalence - vaccination (no vaccine available) - treatment (no effective therapeutic drugs available) - genetic selection (evidence of uniform susceptibility) - fertility control (maternal transmission probably a minor contribution) - eliminate clinical suspects (misses carriers; ineffective to date) - test & slaughter (no reliable, practical live animal test) - selective culling (what criteria? mechanism?) - foster natural mortality (e.g., predation) to promote selective culling - reduce density (relationship between density & transmission untested) - other? �124 Table 4. Initial CWD management tactics to be evaluated via field studies and/or simulation modeling. Candidate tactic Schedule Selective culling via observation (± baiting) Modified "test and slaughter" (model/field) Selective culling via predation (modeling) Density reduction (modeling) Fertility control (modeling) 2/99-4/99 5/99-4/00 5/99-9/99 5/99-9/99 5/99-9/99 EXPERMIENTAL PLAN MANAGEMENT PROPOSAL -- NOT CURRENTLY INCLUDED IN DRAFT In all, eight management areas will be included in this before-and-after-controlled-intervention (BACI)experiment (Fig._); management areas will be paired, with four areas targeted for density reduction (50% reduction over a 2-yr period, then maintained at 50% of pretreatment density for 5 yr)' and four held under status quo management regimes (i.e., discourage feeding, eliminate suspects, etc.) as control areas (Table _). We will stagger the start of management treatments to minimize confounding effects of temporal variation on CWD prevalence and distribution (Table _). Deer density and CWD prevalence will be estimated annually in each management area, and mean CWD prevalences before and after management intervention will be compared to test density-dependent transmission hypotheses and assess the efficacy of treatment in reducing CWD prevalence. Similarly, CWD prevalence and distribution in GMUs adjacent to treatment and control areas will be compared to test hypotheses on density-dependent dispersal and assess the efficacy of treatment in stemming CWD dispersal. Table _. Treatment assignments and start dates for areas included in CWD management experiment. Location Treatment Control Start date northern Larimer County GMU9 GMU 191 1999-2000 southern Larimer County GMU 1ge/20ea GMU 19w120wb 2000-2001 South Platte River" bottom/plains GMU91 GMU92 1999-2000 South Platte River bottom/plains GMU96 GMU951 2000-2001 b GMU 19e120e will be the portions ofGMUs 19 and 20 east of the Pingree Park Road and ??? GMU 19w/20w will be the portions of GMUs 19 and 20 west of the Pingree Park Road and ??? 1 This preliminary treatment regime is subject to modification guided by simulation modeling exercises that will be completed later this year. �181 -..:':, \ "" Colorado Division of Wildlife Wildlife Research Report July 2000 / \ JOB PROGRESS REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Program Work Package No. __ ..:::.3.:::.;00~1~ Task No. 10 _ Deer Management Monitoring and Managing Chronic Wasting Disease in Deer Period Covered: July 1, 1999 - June 30, 2000 Authors: M. W. Miller, C. T. Larsen, M. Conner, and R. Kahn Personnel: J. Gross, C. Krumm, M. Leslie, E. Myers, K. I. O'Rourke, T. R. Spraker, E. Wheeler, M. A. Wild, and E. S. Williams ABSTRACT Deer from throughout Colorado were examined for occurrence of chronic wasting disease using a combination of targeted surveys and harvest/road-kill surveys. Between June 1999 and May 2000, 11 chronic wasting disease(CWD)cases were diagnosed among 22 suspect deer submitted from known endemic portions of northeastern Colorado. Thirteen additional suspect deer submitted from elsewhere in Colorado were all CWD-negative. All confirmed CWD cases originated in game management units (GMUs) where the disease had been detected previously. We sampled about 1450 harvested or road-killed deer during October-December to randomly survey for CWD in select data analysis units (DADs). Immunohistochemistry (llIC)-based prevalence in Larimer County (6.4%) and South Platte River bottom/plains DADs (0%) were comparable to previous years' estimates. All brain samples from deer harvested in North Park (n = 103), the Piceance Basin (n = 408), and the Uncompahgre Plateau (11 = 209) tested negative. Overall, 1355 mule deer harvested or road-killed outside northeastern Colorado have all tested negative for CWD; these data, combined with those from targeted surveillance, support the contention that CWD is not distributed throughout the state. Since June 1999, CWD affected 11 of 21 adult (;;.:l-yr-old) mule deer and 2 of 5 adult white-tailed deer in the resident Foothills Wildlife Research Facility (FWRF) herds. No signs of neurological disease were observed in any of the 11 cattle (subjects) housed with naturally-infected resident mule deer since July 1997, but 3 of 11 mule deer from the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR)(contact controls) held since October 1997 developed clinical CWD and were euthanized between November 1999 and June 2000. �182 Using ruc, Prl'?" was detected in brain tissue (medulla oblongata at the obex) from 2 mule deer experimentally inoculated with a 5 g oral dose of brain tissue homogenate from CWO-infected deer 20 mo earlier. One of the two deer examined 20 mo after inoculation (PI) also had gross lesions suggestive of I CWO and microscopic lesions of spongiform encephalopathy. Uninoculated controls collected from RMANWR at the same time were negative. Five of the 6 remaining inoculated deer died of clinical CWO or its sequelae 20-26 mo PI. Movements of radiocollared deer appeared related to spatial patterns in CWD prevalence described previously. Deer captured in GMU 9, where CWO prevalence is relatively high, moved north into areas of Wyoming with equally high prevalence; deer from GMU 191, located west and adjacent to GMU 9 and having relatively low levels of CWD prevalence, moved to the west into areas of even lower prevalence. Despite their proximity, there was no overlap in winter range for deer in GMU 9 and deer in GMU 191, and almost no overlap in summer range «1 %). Overall, deer movements appeared related to patterns of prevalence in DAD D4. It follows that migration and dispersal patterns of mule deer may explain, at least in part, spatial patterns of CWD prevalence in northcentral Colorado and southcentral Wyoming. Western blotting appears to have potential application as a tool in studying CWD transmission mechanisms. Preliminary evaluation revealed comparable sensitivity between Western blotting and ruc on both brain and lymphoid tissues. Although PrPCWD was not detected in saliva or buffy coat samples from infected deer, further development and evaluation of these and other potential media for CWD transmission appear warranted. Recommendations on a statewide approaches for monitoring and managing CWD in deer and elk, including policy, goals, and management objectives, were reviewed and finalized in November 1999; specific plans for CWD management will be included in individual DAU plans to be drafted in the next segment. Based on these recommendations, 3 interim management actions were undertaken: First, deer and elk population objectives for all DADs in the endemic area were reset to current (1999) levels regardless of previous longterm objectives established in DAD plans. Antlerless harvest levels were then set to hold populations at 1999 levels or, in cases where populations currently exceed DAU objectives, lower populations to objective within 2 years. Second, a more aggressive program for culling clinical suspects was instituted; this program enlists private landowners to assist in identifying and removing sick deer throughout the endemic area. Third, a management experiment to test relationships between CWD prevalence and deer density was planned and public information and regulation development processes supporting this experiment were initiated; that experiment will probably begin during winter 2000-2001. Surveillance activities for 19992000, as well as surveillance planned for 2000-2001, reflect priorities established in the monitoring portion of this plan. .j �183 MONITORING AND MANAGING CHRONIC WASTING DISEASE IN DEER M. W. Miller, C. T. Larsen, M. M. Conner, and R. Kahn P. N. OBJECTIVES ( I) Design, conduct, and report results of: (a) targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWD) in free-ranging deer populations; and (b) harvest or road-kill surveys to estimate and detect changes in prevalence of CWD in endemic deer populations. (2) Design, conduct, and report results of experimental studies using captive deer naturally or experimentally infected with CWD. AGREEMENT OBJECTIVES (1) Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWD in free-ranging deer populations statewide. (2) Conduct and report results of harvest surveys to estimate prevalence ofCWD in DAUs D3, D4, D 10( +GMU 29), and D44 (+ GMUs 87 and 95), as well as select GMUs in the Piceance Basin and Uncompahgre Plateau. (3) Continue an experiment evaluating cattle susceptibility to CWD via natural contact exposure. (4) Continue to study pathogenesis ofCWD in mule deer. (5) Conduct studies to determine factors contributing to occurrence and natural spread of CWD in northeastern Colorado. (6) Evaluate select strategies for managing deer to limit distribution and occurrence of CWD . MATERIALS AND METHODS Surveillance We monitored deer populations throughout Colorado for occurrence of CWD using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: Targeted (= clinical. disease) surveillance: Deer showing clinical signs consistent with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. The "suspect case" profile was defined as follows: • Species: • Age: mule deer white-tailed deer 2: 18 months �184 • Signs: emaciated and abnormal behavior &lor indifference to human activity &lor increased salivation &lor tremor, stumbling, incoordination &lor difficulty or inefficiency in chewing/swallowing &lor increased drinking and urination Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (Williams and Young 1993) was used to diagnose CWD; in some cases, immunohistochemistry (lliC) or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: In order to obtain reliable estimates of CWD prevalence that will serve as a basis for monitoring responses to management interventions, we continued conducting harvest surveys on select deer populations. During the 1999-2000 hunting seasons, fresh brain and select lymphatic tissues were collected from deer harvested in endemic game management units (GMUs). Deer harvested or culled in other select data analysis units (DAUs) throughout Colorado were also sampled as negative controls; in particular, deer populations in North Park (DAU D3), the Piceance Basin, and Uncompahgre Plateau were foci of surveillance activities. Brain tissues were examined at the Colorado State University Diagnostic Laboratory for anti-PrP inununostaining reactions (O'Rourke et at, 1998) and histopathological lesions (Williams and Young, 1993) consistent with CWD infection. Epidemiological Studies Epidemiology of naturally-occurring CWD in captive mule deer and white-tailed deer: Naturally-occurring CWD was a sporadic disease of resident FWRF mule deer prior to 1985 (Williams and Young, 1992), and also has occurred sporadically since 1994; no cases had been observed in resident white-tailed deer since their addition to FWRF in 1993. We maintained and observed 21 ~ l-yr-old mule deer and 5 ~ l-yr-old white-tailed deer in paddocks at CDOW's Foothills Wildlife Research Facility (FWRF) during this segment. Deer received natural forage, pelleted rations (high energy supplement and "browser" diet), and alfalfa hay; water and mineralized salt were available ad libitum. All deer were evaluated daily for clinical signs ofCWD (and other health problems) in conjunction with routine feeding and handling activities. Resident mule deer also represented the source of infection (= "treatment") in an ongoing study of cattle susceptibility to CWD (see below). Cattle susceptibility to CWD (Williams and Miller): We continued monitoring cattle for clinical evidence of natural CWD transmission as part of a coordinated interagency effort to study cattle susceptibility to CWD. Twelve 4-mo-old calves purchased from a private ranch located near Sheridan, WY, were placed in paddocks at the FWRF with naturally-infected captive mule deer in July 1997 (see above for description of resident deer herd). Twelve 4-mo-old mule deer fawns were captured at the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR) in late September and placed in the same paddocks as contact controls for natural transmission (extensive ongoing surveillance of RMANWR deer has continued to confirm that this population is free of CWD). CWD Pathogenesis in mule deer (Williams and Miller): In a separate but related study, 20 additional 6-moold mule deer fawns were captured at the RMANWR in early December 1997. Each fawn was given a single oral dose of about 5 g of fresh brain tissue homogenate from captive mule deer with clinical CWD. Fawns were then released into a separate paddock physically removed from the contact transmission study. These experimentally-infected fawns serve two purposes: as controls for domestic calves orally inoculated with a single oral dose of about 50 g of this same CWD brain homogenate (Williams et al., 1998), and as subjects of a study on the pathogenesis of CWD in mule deer. �185 We have randomly sacrificed 2 experimentally-infected deer at 3,6,9, 12, 16, and 20 mo after inoculation; we also collected 2 age- and sex-matched control deer from RMANWR at each time step. Complete necropsies were performed and samples collected as described in the original study plan. Select sections of brain tissue (obex) were examined after staining with hematoxylin and eosin (H&E) or anti-PrP immunostain (F89/160 .1.5; O'Rourke et al., 1998); examination of other tissues is pending. Spatial epidemiology of CWO in free-ranging mule deer (Conner and Miller): Dispersal and/or migration movements could be related to the spatial distribution and spread of CWO. To determine whether mule deer movements from areas of high CWO prevalence are related to levels of CWO prevalence in surrounding areas and/or mule deer populations, we captured and radiocollared mule deer in 2 areas of high CWO prevalence. On 9 December 1999 and 10 December Number 1999,42 deer were captured in game management unit Age Radiocollared Area Sex (GMU) 9 near Virginia Dale, and from 7 January 2000 to Male 14 Fawn 29 February 2000, 22 deer were captured in GMU20 near GMU9 4 Yearling Masonville (Table 1). Because mule deer typically 2 Adult disperse between 12 and 30 months of age, we focused our 18 Female Fawn capture efforts on fawns and yearlings (6-30 months of 0 Yearling age) in order to gather data on both dispersal and 4 Adult 42 Total migration movements. We collected location data on deer radiocollared from this study, as well as from deer 6 Male Fawn GMU20 radiocolIared for an ongoing survival study in DAU 4. 4 Yearling Telemetered mule deer were located every 6-8 weeks. 1 Adult From preliminary data, we developed graphical 6 Female Fawn Yearling 3 information system maps that included locations of 2 Adult summer and winter range and migration movements. We 22 Total also calculated overwinter survival rates in accordance Table 1. Sex and age composition of mule deer with protocols from an ongoing study of deer survival in radiocollared during winter 1999-2000 in GMUs 9 DAU D4 as a basis for comparing vital rates for deer in and 20. areas of high and low CWO prevalence. Utility of Western blotting in detection ofPrPCWD in excreta (Larsen and Miller): Mechanisms for transmission of CWO remain undescribed. Circumstantial evidence suggests either direct or indirect animal-to-animal transmission occurs, most likely via agent excreted in some combination of saliva, feces, urine, or placental tissues (Miller et al., 2000). However, progress in understanding CWO transmission routes has been hampered by lack of tools for detecting PrPCWD in non-tissue media. W~ conducted preliminary evaluations of Western blotting as a technique for detecting PrPCWD in both tissue and excreta samples. Details of Western blot methods are described in detail elsewhere (Larsen and Miller, 2000). Monitoring and Management Recommendations for statewide monitoring and management of CWO in deer and elk were finalized and adopted. RESULTS AND DISCUSSION Surveillance Targeted (= clinical disease) surveillance: Between June 1999 and May 2000, 11 chronic wasting disease (CWO) cases were diagnosed among 22 «suspect" deer submitted from known endemic portions of northeastern Colorado; CWO was not diagnosed in any of 13 additional «suspect" deer submitted from �186 elsewhere in Colorado. All CWD cases confirmed in 1999-2000 were mule deer, and all originated in game management units (GMUs) where the disease had been detected previously. Harvest surveys: We sampled about 1450 harvested or road-killed deer to randomly survey for CWD in select DAUs. ruC-based prevalence in Larimer County mule deer (6.4%; 311487) was similar to prevalence observed in previous years. In contrast, no cases were detected among 60 mule deer harvested from South Platte River bottom/plains DAUs. Improvements in ruc techniques that allow identification of very early preclinical cases (based on strong staining in lymphoid tissue even in the absence of staining in brain tissue) should aid in reducing the bias in our prevalence estimates; we anticipate that these techniques will be validated prior to the 2000-2001 survey season. Based on preliminary results, estimated prevalence will likely increase by about 25-35% when these very early cases are included; the latter will likely be much closer to true prevalence rates in infected populatiuons. We detected no evidence ofCWD in any of the brain samples from North Park (0/105), Piceance Basin (0/423), or Uncompahgre Plateau (0/205) GMUs, or in any of the other 150 samples from GMUs outside northeastern Colorado. Overall, 1355 mule deer harvested or road-killed outside northeastern Colorado have all tested negative for CWD; these data, combined with those from targeted surveillance, support the contention that CWD is not distributed throughout the state. Epidemiological Studies Epidemiology of naturally-occurring CWD in captive mule deer and white-tailed deer: Between June 1999 and May 2000, CWD affected 11 of21 adult (z l-yr-old) mule deer in the resident Foothills Wildlife Research Facility herd. Resident mule deer also represented the source of infection (treatment) in an ongoing 10-yr study of cattle susceptibility to CWO (see below). Two of 5 white-tailed deer remaining in our resident FWRF herd developed CWD during June-August 1999. The 3 remaining white-tailed deer were euthanized in September 1999 - 2 of the 3 showed mildmoderate spongiform encephalopathy on histopathology. In all, CWD claimed 8 of 11 captive white-tailed deer held at FWRF between 1993 and 1999 and, based on the findings in the deer euthanized in September, would have probably eliminated the entire population by 2001. Examinations of tonsillar biopsies from captive deer are still pending. Lack of results has precluded evaluation of tonsillar biopsy as a potential antemortem test for CWD in deer. Cattle susceptibility to CWD (Williams and Miller): No signs of neurological disease were observed in any of the 11 cattle (subjects) housed withnaturally-infected resident deer since July 1997. However, 3 of9 mule deer from the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR)(contact controls) developed clinical CWD between July 1999 and June 2000. Twenty-three of the 44 > l-yr-old naturallyexposed resident FWRF deer developed clinical CWO and diedor were euthanized during the first 36 mo of this study, thereby ensuring calves and control deer have received considerable exposure to CWD. All 11 cattle exposed to a single 50 g oral dose of brain tissue homogenate from CWD-infected deer remained healthy 33 mo postinoculation (through 30 June 2000) (E. S. Williams, pers. comm.). However, 3 of 14 cattle exposed to CWD via intracerebral inoculation died or were euthanized 22-27 mo postinoculation after showing varying combinations of neurological signs and weight loss; mc staining and Western blot results were consistent with probable CWD infection, although it is unclear whether infection with the CWD agent actually caused the clinical signs displayed by the 3 affected calves (R. J. Cutlip and A. Hamir , pers. comm.). �187 Pathogenesis of CWD in mule deer (Williams and Miller): Using IDC, Prpres was detected in brain tissue (medulla oblongata at the obex) from 1 of 2 mule deer experimentally inoculated with CWD 6 or 9 mo earlier. One of2 deer examined 16 or 20 mo after inoculation (PQ had lesions ofspongiform encephalopathy, and both were IHC-positive at each sampling. Two deer examined 3 mo PI and 2 examined 12 mo PI were negative, as were all 10 uninoculated controls collected from RMANWR at the same intervals. One of the 8 remaining deer inoculated in December 1997 began showing early clinical signs of CWO ~15 mo PI and died ~6 mo later; a second began showing early signs 2-3 wks later, and subtle signs were noted in at least 4 of 8 inoculated deer alive 18 mo PI. Of the 6 inoculated deer surviving >20 mo PI, 5 died or were euthanized in end-stage clinical CWD 20-26 mo PI; the remaining animal showed no appreciable clinical signs or lesions, and only minimal IHC staining in brain tissue, when euthanized 26 mo PI. Spatial epidemiology of CWO in free-ranging mule deer (Conner and Miller): . TIlls year served as a pilot study in which movements of mule deer were described. Most (86%) of the deer captured in GMU 9 and GMU 20 were fawns and yearlings (Table 1). From preliminary data, we mapped and visually compared locations of summer and winter range and migration movements _ SJmmer Heme Ranges SUmmer GMU20 in areas of high CWD C]GMJ aty prevalence (GMU 9, GMU N/l../Hiltl-y 20 20) to and areas oflower prevalence (GMU 191, 10 0 10 20 Kilanelers GMU 19) (Fig. 1). Movements of deer showed a remarkably clear Figure 2. Sununer and winter home range and movement patterns from winter to relationship to prevalence sununer home range for mule deer radiocollared in GMUs 9,191, 19, and 20. patterns. Deer in GMU 9, . where CWD prevalence is relatively high, moved north into areas of Wyoming with equally high prevalence. Deer in GMU 191, located west and adjacent to GMU 9 and having relatively low levels of CWO prevalence, moved to the west into areas of even lower prevalence. Despite their proximity, there was no overlap in winter range for deer in GMU 9 and deer in GMU 191, and almost no overlap in summer range 1%). Overall, deer movements appeared related to patterns of prevalence in DAU 4. It follows that migration patterns of mule deer may explain, at least in part, spatial patterns of CWD prevalence in northcentral Colorado and southcentral Wyoming. ~ WlnI ••• Home Ranges ~~~- « Overwinter fawn and adult survival was .estimated for 1 December to 15 June (Table 2). Survival did not differ betwee~ high prevalence (GMU 9) and lower prevalence GMUs in DAU D4 (GMUs 191 and 19); that is, all confidence intervals almost fully overlapped. TIlls is not surprising, because clinical CWO is �188 rare in the younger age classes that dominated our sample. Unfortunately, our sample sizes were insufficient to accurately estimate age- and sex-specific survival rates within GMUs, and thus comparisons of adult survival rates between high and low prevalence GMUs was precluded. We anticipate that cumulative data gathered over the next several years will eventually allow for such comparisons. Suvival Year 1900-00 Period 10 Dec-15 June Wrtering twa 06.U4 GMJ9 GMJ19 GMJ191 GMJ2) Sample Suvival Size Estimate 0.823 137 45 0.764 2) 0.612 0.940 52 2) 0.850 g)%CI 0.748 0.899 0.630 0.00) 0.378 0.843 0.874 1.000 o.eso 1.000 Table 2. Kaplan-Meier survival estimates for mule deer wintering in GMU 9, GMU 19, GMU 191, and GMU 20. Trap mortalities were excluded from survival calculations. Three deer radiocollared prior to 1999 were present in GMU 9, thus sample size was 45 rather than the 42 captured this year. Utility of Western blotting in detection ofPrPCWD in excreta (Larsen and Miller): Western blotting successfully detected PrPCWD in both brain and tonsil tissues from CWD-infected deer (fable 3, Fig. 2); all negative control samples tested negative. Sensitivity of Western blotting in these tissues appeared similar to mc. In contrast, we failed to demonstrate PrPCWD in either saliva or buffy coat extracted from blood. Whether PrPCWD does not occur in these media, or whether it is simply present at concentrations that fall below assay detection limits remains unclear. Tissue- and media-specific modifications in sample preparation procedures probably will be needed before Western blotting can be applied reliably to various materials of interest. In particular, modifications should focus on ways of concentrating the relatively small quantities of PrPCWD that may occur in excreta and environmental samples. Provided such obstacles can be overcome, Western blotting could have a variety of applications in studying CWD epidemiology. Monitoring and Management Recommendations for statewide monitoring and management of CWD (Appendix A) were finalized and adopted. Specific recommendations for policy, as well as management goals and objectives were as follows: Policy The Colorado Division of Wildlife is committed to minimizing the threat that chronic wasting disease (CWD) poses to Colorado's native deer and elk resources. In data analysis units (DAUs) where CWD is endemic, goals of reducing the occurrence and preventing the further spread of CWD will serve as the primary basis for setting management objectives. Goals The CDOW's goals for CWD management will be 1) to limit distribution ofCWD to no more than the 5 deer data analysis units (DAUs) and 2 elk DAUs where it already occurs and 2) to reduce average CWD prevalence among deer and elk to <1% in each endemic DAU and <2% in each endemic game management unit (GMU). Short-term objectives 1. Manage to prevent dispersal ofCWD beyond endemic DAUs via mule deer, white-tailed deer, and elk movements. 2. Manage to reduce CWD prevalence among deer inhabiting the three most severely affected GMUs (9,191,19) by ~50% within 10 years (by 2011). . 3. Manage to reduce CWD prevalence among deer and elk inhabiting all endemic DAUs to 51% within 20 years (by 2021). Based on these recommendations, 3 interim management actions were undertaken: First, deer and elk population objectives for all DAUs in the endemic area were reset to current (1999) levels regardless of previous long-term objectives established in DAU plans. Antlerless harvest levels were set to hold �189 populations at 1999 levels or, in cases where populations currently exceed DAU objectives, lower populations to those objective levels within 2 years. Second, a more aggressive program for culling clinical suspects was instituted; this program enlists private landowners to assist in identifying and removing sick deer throughout the endemic area. Third, a management experiment to test relationships between CWD prevalence and deer density was planned and public information and regulation development processes supporting this experiment were initiated; that experiment will probably begin during winter 2000-2001 (see details in Appendix B). Surveillance activities for 1999-2000, as well as surveillance planned for 2000-2001, reflect priorities established in the monitoring portion of this plan. ACKNOWLEDGMENTS The statewide CWD monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those regional and area biologists, district and area wildlife managers, volunteers, deer hunters, and others who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. LITERATURE CITED Larsen, C. T., and M. W. Miller. 2000. Evaluation of Western blotting as an investigation tool for chronic wasting disease in mule deer. Colorado division of Wildlife, unpublished report. ' Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. 1. Kreeger, C. T. Larsen, and E. T. Thome. 2000. Epizootiology of chr6nic wasting disease in free-ranging cervids in Colorado and Wyoming. Journal of Wildlife Diseases 38: 676-690. O'Rourke, K. I., T. V. Baszler, J. M. Miller, T. R. Spraker, I. Sadler-Riggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.l.5 defines a conserved epitope on the ruminant prion protein. 1. Clin. Microbiol. 36: 1750-1755. Williams, E. S., and S. Young. 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. ---' M. W. Miller, T. 1. Kreeger, H. Van Campen, and T. R. Spraker. 1998. Susceptibility of cattle to cervid spongiform encephalopathy. unpublished grant proposal, submitted to USDA, CSREES, National Research Initiative Competitive Grants Program, 88 pp. Prepared by Michael W. Miller Wildlife Research Veterinarian _ ��191 Appendix A Chronic Wasting Disease in Colorado Deer and Elk: Recommendations for Statewide Monitoring and Experimental Management Planning M W. Miller and R. H Kahn Terrestrial Wildlife Resources, Colorado Division of Wildlife Executive Summary Chronic wasting disease (CWO) is a transmissible spongiform encephalopathy (TSE) of native deer and elk that is endemic throughout northeastern Colorado and southeastern Wyoming. Estimated infection rates range from <1-15% in deer and s 1% in elk residing in northeastern Colorado game management units (GMUs). There is no precedent for attempting to manage a TSE in free-ranging wildlife, and the biological imperative for such management is not entirely clear. However, it seems most biologically responsible to assume that CWO adversely affects native deer and elk populations and consequently manage to prevent its further spread and reduce its occurrence in Colorado. The CDOW has been actively monitoring CWO distribution and prevalence for over 10 years. Ongoing surveillance programs should be continued to provide data on responses to management and public information on CWO. Future monitoring should focus on reconfirming the limited distribution of CWO in Colorado and on measuring responses to prospective disease management programs. At present, the CDOW has no stated po~cy on managing CWO in free-ranging deer and elk. Lack of clear policy has led to internal confusion, disagreement, and conflicts with other policies and Long Range Plan objectives (e.g., increase recreational opportunities for deer and elk hunters). Because CWO currently affects <5% of Colorado's deer and elk resources and recreational opportunities but threatens far more substantial resources both within and outside Colorado, the following policy should be adopted to guide decisions on deer and elk population management in data analysis units (DADs) where CWO is endemic: The Colorado Division of Wildlife is committed to minimizing the threat that chronic wasting disease (CWD) poses to Colorado's native deer and elk resources. In data analysis units (DAUs) where CWD is endemic, goals of reducing the occurrence and preventing the further spread of CWD will serve as the primary basis for setting management objectives. Based on current understanding of CWO in free-ranging deer and elk, eradication seems an extreme and unjustifiable management goal at this time. Considering the prevalence and distribution CWO has reached under historical management regimes, however, continuing to rely on current management approaches seems equally unjustifiable. Consequently, two intermediate goals for managing CWO in deer and elk should be adopted: The CDOW's goals for CWD management will be 1) to limit distribution ofCWD to no more than the 5 deer data analysis units (DAUs) and 2 elk DAUs where it already occurs and 2) to reduce average CWD prevalence among deer and elk to <1% in each endemic_DAU and <2% in each endemic game management unit (GMU). Achieving the foregoing management goals should protect Colorado's deer and elk resources, restore confidence in the quality of deer and elk harvested in northeastern Colorado, and address agricultural constituencies' concerns about risk of potential transmission to domestic livestock or privately-owned wildlife. To reach these goals, changes in population management should be made via revision ofDAU �192 plans for the 5 deer DADs and 2 elk DADs where CWD is endemic by 1 January 2001 in order to achieve three short-term management objectives: 1. Manage to prevent dispersal ofCWD beyond endemic DAUs via mule deer, white-tailed deer, and elk movements. 2. Manage to reduce CWD prevalence among deer inhabiting the three most severely affected GMUs (9, 191, 19) by ~50% within 10 years (by 2011). 3. Manage to reduce CWD prevalence among deer and elk inhabiting all endemic DAUs to 51% within 20 years (by 2021). Developing these plans will necessarily involve broader public input than typical DAD planning processes in order to properly balance statewide concerns over CWD and its management with local concerns about the impacts of proposed management actions. In light of uncertainties about CWD epidemiology and ecology, plans should be approached as experiments that provide a mechanism for learning while attempting disease management. Because CWD management will be experimental, individual DAD plans should be coordinated through CDOW's Terrestrial Resources Program to ensure that elements of uniformity, design, control, and implementation are identified and achieved. Plans for CWD management should be reviewed and, where necessary, revised every 5 years as part of an adaptive strategy for achieving management objectives. Specific strategies and tactics for accomplishing CWD management objectives should be identified in individual DAD plans. Many conventional disease management options (most notably, vaccines, therapeutics, and live-animal tests for CWD) are presently unavailable; all other prospective strategies identified to reduce CWD prevalence involve some form of aggressive culling or population control. It is likely that current season structure, bag limits, and/or administrative boundaries may be too inflexible to achieve management objectives. Some candidate tactics for CWD management may require modification or temporary suspension of Commission regulations, as well as considerable human dimensions efforts. Managing CWD represents an unprecedented challenge to CDOW's biologists, field personnel, public service representatives, and administrators. However, rising to meet this challenge is vastly preferable to a legacy of inaction that allows CWD to become more widespread at the expense of valuable wildlife resources in Colorado and elsewhere. Background Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (TSE) of native deer (Odocoileus spp.) and elk (Cervus elaphus nelsoni) characterized by behavioral changes and progressive loss of body condition that invariably leadto the death ofaffected animals (Williams and Young 1992). Neither the causative agent nor its mode of transmission have been fully identified; however, CWD is suspected to be caused by aunique strain ofprion transmitted from animal-to-animal via some combination of saliva, feces, urine, or other tissues or fluids (Miller et al. 1998, 2000; Williams et al. 2000). Both sexes and all age classes show relatively uniform susceptibility (Miller et al. 2000, Williams et al. 2000). There are no valid tests currently available for diagnosing CWD in live animals, and extant postmortem tests require microscopic examination of brain tissue. There are no known treatments for CWD. Previous attempts to eradicate CWD from research facilities failed on at least 2 occasions (Williams and Young 1992, Miller et al. 1998). Although similar in some respects to other TSEs that affect domestic sheep (scrapie) and cattle (bovine spongiform encephalopathy; BSE), existing and unpublished experimental data indicate CWD cannot be naturally transmitted to domestic livestock, and that scrapie and BSE cannot be naturally transmitted to native cervids. Moreover, available data indicate that CWD does not present a threat to human health. �193 "Chronic wasting disease" was first recognized by biologists in the 1960's as a disease syndrome of captive deer held in wildlife research facilities in Ft. Collins, CO. This disease was subsequently recognized in captive deer, and later in captive elk, in wildlife research facilities near Ft. Collins, Kremmling, and Meeker, CO and Wheatland, WY (Williams and Young 1980, 1982), as well as at in least two zoological collections (Williams and Young, 1992). Since 1996, CWD also has been diagnosed in captive elk residing in two game ranches in Saskatchewan, Canada, as well as five ranches in South Dakota, two ranches in Nebraska, and one ranch each in Oklahoma, Colorado, and Montana (Fig. 1). Over 100 cases of clinical CWD also have been diagnosed in free-ranging mule deer (0. hemionus), white-tailed deer (0. virginianusi, and elk from northeastern Colorado and southeastern Wyoming since 1981 (Miller et al. 2000). At present, the known world-wide distribution of CWD in wild cervids appears to be limited to northeastern Colorado and southeastern Wyoming (Miller et al. 2000). Although CWD was first diagnosed in captive cervids, the original source of CWD in either captive cervids or free-ranging cervids is unknown; whether CWD in captive cervids really preceded CWD in wild cervids, or vice versa, is equally uncertain (Spraker et al. 1997). Moreover, the relationship (if any) between CWD cases in privately-owned Figure 1. Distribution of chronic wasting disease in captive and freeelk industry and cases in ranging deer and elk (November 1999). free-ranging and research animals is unclear. A.MuJec2er In Colorado, free-ranging CWD cases in deer and elk have originated from throughout the northeastern portion of the state. Game management units (GMUs) yielding infected deer or elk include 7, 8,9, 19, 191, 20,29,91,93,94,95, 951, and 96. Although B. White-tailed ~er cases have come from 13 different GMUs, two data analysis units (04, 010) have yielded over 85% of the documented cases. Harvest surveys indicate GMUs 9,191, and 19 are the most extensively infected GMUs in Colorado; estimated Figure 2. Estimated CWD prevalence (%) among subpopulations of (A) mule deer and (B) prevalence ranges from white-tailed deer in northeastern Colorado. Data were aggregated on the basis of deer about 6-15% (Fig. 2) movement patterns. Prevalence estimates are based on immunohistochemistry reactions only (lliC+/total). (Miller et al. 2000). I �194 Data from harvest surveys indicate that CWD is less prevalent in GMUs surrounding this core area, affecting about 1-4% of the deer in GMUs 7,8,20,29,91,93,94,95,951, and 96 (Fig. 2). Similarly, harvest surveys indicate <1 % of the elk in DAUs E4 and E9 are infected with CWD (Miller et al. 2000). Based on targeted surveillance data and select harvest surveys, wild deer or elk populations in other parts of Colorado and Wyoming are probably not infected with CWD (Miller et al. 2000); similarly, surveillance data gathered to date indicate CWO has not yet spread to South Dakota, Nebraska, or Kansas (A. Jenny, USDAIAPHISNS/NVSL, pers. comm.). For infected deer populations northeastern Colorado, CWO prevalence appears to be stable; however, because small increases would be difficult to detect over only a few years it is doubtful that our short-term observations accurately reflect or forecast long-term trends. In the absence of historical (20-30 years ago) prevalence data or reliable estimates of transmission rates, changes in overall incidence or distribution of CWO in northcentral Colorado DAUs are probably best projected via modeling. Based on field data and results of simulation modeling to predict dynamics and impacts of CWO on affected deer populations, it appears CWO was introduced into northern Larimer County over 30 years ago (Miller et al. 2000, Gross and Miller 2000) and has increased in both prevalence and distribution since that time. Beyond the Larimer County foothills, the South Platte River bottom corridor appears to be the single most important and predictable avenue for spread ofCWD (Fig. 2). Kufeld and Bowden (1995) reported that a proportion of South Platte River bottom deer were highly mobile; observed deer movements included some to and from eastern Larimer County along the Cache la Poudre and South Platte Rivers. These movement patterns provide a plausible mechanism for the extent of CWD' s distribution across South Platte River bottom GMUs (Fig. 2) (Miller et al. 2000). Other likely routes for deer emigrating from eastern Larimer County have not been completely identified, and may be less predictable or less commonly used. Altitudinal movements of some elk subpopulations in the southern part of Larimer County are also somewhat predictable (Bear 1982). Although there is potential for elk to cross the Continental Divide through Rocky Mountain National Park, the relatively low prevalence of CWO among elk may diminish the likelihood of its spread via their movements. The significance of CWO and its impacts on native deer or elk populations have not been determined . . Preliminary results of simulation modeling suggest that, sustained at >5% prevalence as observed in the most heavily infected GMUs, CWO could impact wild deer herds and lead to population declines (Miller et al. 2000, Gross and Miller 2000). Analyses of harvest and other population data have not detected evidence of population depression attributable to CWD, but existing inventory data for deer in northeastern Colorado are probably insufficient to detect such trends (M. Conner, pers. comm.). In the absence of data to the contrary, and considering the difficulties inherent in eliminating CWO from captive or wild cervid populations once established, it seems most prudent to assume that CWO adversely affects native deer or elk populations and manage to prevent its further spread and reduce its OCcurrence in Colorado. . Unfortunately, there is considerable uncertainty in how to manage CWO in free-ranging wildlife, or whether such an endeavor could even be successful (Gross and Miller 2000). Because a more complete understanding of CWO is fundamental to developing comprehensive management programs, the Colorado Division of Wildlife (CDOW) needs to further understanding about CWO and its management through surveillance and experimental management. Data from completed, ongoing, and proposed research, both basic and applied, will serve as the foundation of a series of adaptive resource management plans for CWO in deer and elk. These plans will provide mechanisms for incorporating new knowledge gained through surveys, modeling, research studies, and management experiments into a continuously evolving management program for CWO. �195 STATEWIDE MONITORING PROGRAM The CDOW has been actively monitoring CWD distribution and prevalence for over 10 years. Ongoing surveillance programs should be continued in order to provide data on responses to management attempts, as well as public information on CWD. The recommended goals and strategies for statewide monitoring are as follows: . Goals: 1. Provide reliable estimates of CWD distribution and prevalence to serve as a basis for management decisions and public information. 2. Provide information to improve understanding ofCWD epidemiology. 3. Continue developing efficient and reliable techniques for detecting and monitoring CWD in free-ranging populations. Strategy: Reliable estimates of CWD prevalence in wild deer and elk populations are needed to guide policy decisions and monitor efficacy of management efforts. The CDOW should continue to monitor deer and elk populations throughout Colorado for occurrence of chronic wasting disease using a combination of extensive and intensive approaches. These have been organized and conducted as follows: Targeted (= clinical disease) surveillance: Ongoing statewide "targeted" surveillance (i.e., submissions of "suspect" deer & elk) will be used to determine & monitor changes in CWD distribution. Based on experiences in Colorado and elsewhere, this appears to be the most sensitive approach for determining CWD distribution and detecting range extensions (Miller et al. 2000). A program for acquiring, examining, reporting on, and summarizing "suspect" CWD cases occurring throughout Colorado has been in place since 1990. This program has served to increase ongoing surveillance efforts by field personnel statewide by encouraging submission of carcasses from deer or elk showing clinical signs resembling CWD. A formalized process for submitting cases has been developed; this process includes criteria for acceptable submissions, submission forms, handling instructions, and a system for networking submissions within CDOW and among the 3 Colorado State Veterinary Diagnostic Laboratories and the Wyoming State Veterinary Laboratory. Under this program, deer and elk showing clinical signs consistent with those seen in chronic wasting disease are collected by field personnel statewide; a "suspect case" profile has been defined (Table 1). Brain tissues are subsequently examined for evidence of spongiform encephalopathy. Where possible, whole carcasses will continue to be submitted for complete necropsy; at minimum, heads from suspect animals will be submitted for examination and sampling. Histopathology (Williams and Young, 1993) and immunohistochemistry of brain tissue (Spraker et al., 1997) will be performed on all suspect cases; other ancillary tests may also be used to confirm or support diagnoses. Pertinent data from preliminary and final reports will be entered into a permanent database, and copies of reports will be filed as well as sent to appropriate field personnel. Results from targeted surveillance should be used to identify new potential foci of CWD infection for further evaluation via harvest or road-kill surveys. Harvest and road-kill surveys: Surveys of harvested or, in some areas, road-killed deer and elk should be conducted in endemic, high-risk, and outlying DAUs/GMUs to estimate and monitor CWD prevalence. We recommend that initial surveys be conducted in all DAUs/GMUs where CWO is detected via targeted surveillance to estimate prevalence, as has been done to date. We also recommend continuing to conduct regular surveys at 1- to 5-year intervals in DAUs or GMUs where CWD is endemic to obtain reliable �196 estimates of prevalence to use as a basis for monitoring natural trends or responses to management interventions. Prevalence should be monitored annually in DAUs/GMUs where experimental management programs are implemented. Surveys should be designed to provide an estimated prevalence within ±2% at a 95% level of confidence for affected populations where true prevalence is 1%; we recognize that it may be necessary to pool data from successive years in order to achieve desired sample sizes. In addition to surveying endemic foci, CDOW should also continue conducting a series of surveys for CWD in other select deer and elk populations throughout Colorado over the next 2 years, with a goal of determining whether CWD is more widespread than suggested by targeted surveillance data. We recommend the following surveillance strategy: Areas newly identified as infected via targeted surveillance will be surveyed sufficiently to obtain a reliable prevalence estimate. Those areas where CWD is not being managed or where estimated prevalence is < 1% will be regarded as endemic and populations will be monitored at -5-year intervals to measure long-term trends in prevalence. Areas where experimental CWD management strategies are being tested (both treatment and control areas) will be monitored annually to track changes in prevalence and evaluate management efficacy. We also recommend conducting surveys of at least 2 other select deer populations where CWD has not been reported previously. Target areas remaining include one high-risk and one low risk population (fable 2). Surveys will be designed such that the probability of failure to detect at least I case of CWD in an apparentlyunaffected deer or elk population will be :sO.0 I even if herd prevalence is 1%. Finally, we will attempt to gather a sufficient number of random samples from DAUs statewide (n-l,OOO) to determine whether or not CWD should be generally regarded as endemic in Colorado's deer populations. Harvest surveys should continue to be conducted using techniques developed and evaluated in Colorado since 1991. With the advent of limited licensing for deer hunting statewide, mandatory submission requirements in GMUs where surveys are being conducted can be dropped after 1999. Limited licenses may be sought in select GMUs to aid in increasing compliance where elk surveillance is needed. Unstaffed barrel sites appear to be the most efficient method for sample collection, and should continue to be used as the primary method for conducting harvest surveys. Brainstem (medulla oblongata at the obex) from <!: 1year-old deer and elk will be collected for CWD testing, and immunohistochemistry (lliC) using USDA monoclonal antibody F89/160.1.5 (O'Rourke et al., 1998) should be used as the primary screening tool. Reported prevalence estimates will continue to be based on numbers of IRC-positive cases; because mc appears more sensitive than histopathology in detecting preclinical CWD cases, mC-based prevalence estimates should provide a relatively unbiased measure of disease trends over time and allow more direct comparison between field data and simulation model predictions. We also recommend continuing to evaluate lymphoid tissue (e.g., tonsil) IRC as a means of increasing survey sensitivity and as a tool for staging disease progress and monitoring responses to management attempts. EXPERIMENTAL MANAGEMENT There is no precedent for attempting to manage a TSE in free-ranging wildlife. Moreover, the biological imperative for such management is not entirely clear at present. Programs for managing or eliminating TSEs of domestic livestock have proven only marginally successful, and the lack of obvious success in eradicating scrapie or BSE from endemic countries, compounded by epidemiological differences between CWD and other TSEs, make such programs rather poor models for prospective CWD management. Several fundamental features of CWD epidemiology are understood poorly, if at all; in particular, the influences of host (e.g., population density, intraspecific vs. interspecific transmission, genetics) and environmental factors (e.g., contamination, reservoirs, weather) on CWD dynamics remain unclear. In light of the uncertainties associated with its epidemiology and ecology, we believe CWD management should be approached as an experiment, thereby allowing us to learn as we take actions intended to reduce prevalence and limit distribution. �197 . . The CDOW's initial approaches for attempting to control CWD in free-ranging deer and elk were outlined in an action plan for CWD drafted in 1995 (Miller et al. 1995; Appendix A). In addition to calling for a comprehensive public information campaign, this plan identified tactics for limiting distribution and reducing prevalence of CWD based on contemporary knowledge of the problem. Prompt removal of affected animals and enforcement of feeding prohibitions were recommended to help reduce CWD prevalence and transmission. Policies and regulations were also recommended, and subsequently instituted, to prevent wider distribution ofCWD via human activities (e.g., translocations, rehabilitation, game ranching). The plan also identified a need for more extensive surveillance to gather data on CWD distribution and prevalence. As more data on CWD distribution and prevalence have been gathered over the last 4 years, it has become apparent that CWD is more widely distributed and more prevalent in northeastern Colorado (and elsewhere) than initially believed (Miller et al. 2000). It follows that policy, goals, and strategies for experimental CWD management in Colorado should be reevaluated in the context of new data, as well as changes in social and political attitudes toward animal TSEs. Management policy: At present, the CDOW has no stated policy related to the management of chronic wasting disease in wild deer and elk. The lack of a clear policy statement has led to internal confusion and disagreement over how to resolve conflicts with other policies and Long Range Plan objectives (e.g., increase recreational opportunities for deer and elk hunters). . Recommendation: Because CWD currently affects a relatively small portion of Colorado's deer and elk resources «5% of both statewide populations and statewide harvests) but shows the potential to spread and thereby threaten more substantial resources both within and outside Colorado, we recommend adoption of the following policy to guide decisions on deer and elk population management in DAUs where CWD is endemic: PI. The Colorado Division of Wildlife is committed to minimizing the threat that chronic wasting disease (CWD) poses to Colorado's native deer and elk resources. In DAUs where CWD is endemic, goals of reducing the occurrence and preventing the further spread of CWD will serve as the primary basis for setting management objectives. The foregoing policy, if adopted, should provide clear direction and a solid foundation for developing goals, objectives, and strategies managing CWD, as detailed below. In the absence of this or a similar policy, CDOW's ability to develop and implement a comprehensive approach for managing CWD will be severely compromised. Prospective management goals and objectives: We have identified four overarching goals that could serve as a basis for decisions related to managing CWD: 1. modified "natural regulation", 2. containment, 3. reduction, 4. eradication. These goals represent a continuum of possible levels of intervention, ranging from benign neglect to aggressive action. There are clear advantages and disadvantages associated with each of these prospective management goals. Although each progressive level offers more complete control of the problem, better control is accompanied by ever-increasing technical, fiscal, and political challenges, as outlined below: �198 1. Modified "natural regulation": Directing no specific management intervention toward CWD beyond culling of reported clinical cases and enforcing feeding and rehabilitation regulations represents the status quo approach to both disease and affected deer and elk population management. It could be argued that the ongoing activities described above, combined with ongoing changes in habitats and movement corridors effected by development, collectively constitute an attempt to manage CWD. Although the impacts of this approach on CWD prevalence in endemic foci remain undetermined, prevalence in endemic foci appears to have remained stable over at least the last 3 years. This approach offers the fewest technical challenges, may be regarded by some as "safest" in light of the myriad of uncertainties in CWD epidemiology, and in the short-term would be most sparing of local resources. Based on current culling rates reflected by case submissions, <10% of clinical CWD cases are being detected and removed from affected populations annually in Larimer County (and fewer elsewhere). Unfortunately, simulation models forecast that problems with CWD will likely get worse in affected populations managed in this manner (Gross and Miller 2000). Continuing existing management practices will likely allow CWD to become more prevalent and widely distributed, with tangible potential impacts on wildlife resources, recreational opportunities, and revenues. In addition, perceived "inaction" may be unacceptable to some sportsmen's groups, agricultural interests, and perhaps the general public, and could lead to the loss of management authority by CDOW. Finally, opting for "natural regulation" of an emerging disease problem seems biologically irresponsible. 2. Containment: Managing primarily to prevent spread of CWD from endemic foci would require additional knowledge of the mechanisms and probable routes of CWD dissemination, but many of the important strategic components needed to support this strategy are already in place. The likelihood of translocating infected animals from endemic areas to other areas in Colorado or elsewhere was significantly reduced by Commission'regulations adopted in 1996. Between existing data from previous movement studies (e.g., Kufeld et al., 1989; Kufeld and Bowden, 1995) and data from studies initiated more recently, major natural emigration corridors from eastern Larimer County could probably be identified and subsequently might be interrupted via intensive culling operations. This approach, if successful, would limit the magnitude of the CWD problem while largely sparing local resources. This alternative may be more acceptable to sportsmen's groups and the general public than to agricultural interests, but is probably biologically justifiable. However, such an approach would require an essentially infinite long-term commitment and yet will not eliminate CWD entirely; prevalence could conceivably increase in endemic areas. There would likely be some local impacts on resources and recreational opportunities, perhaps accompanied by local public resistance. 3. Reduction: It may be possible to manage affected deer or elk populations to reduce CWD prevalence in endemic foci (Gross and Miller 2000). A goal of prevalence reduction clearly demonstrates intent to limit the magnitude of the problem. It seems likely that this approach would also provide for containment ofCWD. Attempting to reduce CWD prevalence might improve "consumer confidence" among hunters in endemic GMUs. This alternative may be the most widely acceptable among sportsmen's groups, agricultural interests, and the general public in terms of responsible disease and resource management. It is probably biologically justifiable in view of projected long-term effects of CWD on infected populations and the potential for CWD to spread from endemic foci if left unmanaged. As with the foregoing goal of disease containment, prevalence reduction will require a long-term commitment and may not eliminate CWD from endemic areas; however, early, aggressive intervention may increase the likelihood of management success (Gross and Miller 2000). Depending on specific tactics employed, prevalence could increase despite management efforts. This approach would likely cause more severe impacts on local resources and recreational opportunities, and consequently would be more likely to foster local public resistance to proposed management actions. 4. Eradication: Eradication is probably the most desirable goal of any attempt to manage CWD. Whether it would be feasible to completely eliminate CWD from Colorado remains highly questionable. �199 Eradicating CWD would be the best means of restoring for "consumer confidence" among northeastern Colorado deer and elk hunters, and would presumably nullify concerns of traditional and alternative livestock interests about the potential for transmission to privately-owned animals. Perhaps most importantly, eliminating CWD would be the most effective way to preempt threats of its eventual spread to other native deer and elk populations in Colorado and elsewhere. Although desirable in concept, CWD eradication is probably infeasible given the complexities and uncertainties of its epidemiology. Eradication of CWD would require long-term commitment, and probably would exact catastrophic impacts on resources and recreational opportunities in affected areas; broader ecological impacts (e.g., on predator-prey balances) also could be severe. Public resistance is likely to emerge, at least locally, as details of such a management program emerge. Finally, it is questionable whether the potential ecological costs of CWD eradication are biologically justifiable in light of the uncertainty about longterm impacts of the disease itself. Recommendations: Based on current understanding of CWD epidemiology, prevalence, and distribution in free-ranging deer and elk in northeastern Colorado, we believe eradication is an extreme and unjustifiable management goal at this time. In light of the magnitude of prevalence and distribution CWD has reached in Larimer County deer populations under historical management regimes, however, continuing to rely on current management approaches seems equally unjustifiable. Consequently, we recommend an intermediate approach with two goals for managing CWD in deer and elk: Gl. limit distribution occurs; and of CWD to no more than the 5 deer DAUs and 2 elk DAUs where it already G2. reduce average CWD prevalence among deer and elk to <1% in each endemic DAU and <2% in each endemic GMU. We believe achieving the foregoing management goals will serve to protect Colorado's deer and elk resources, restore confidence in the quality of deer and elk harvested in northeastern Colorado, and ameliorate political pressures from agricultural constituencies concerned about potential for transmission of CWD to domestic livestock or privately-owned wildlife. We further recommend DAU plans for the 5 deer DAUs (04, D5, DI0, D27, and D44) and 2 elk DAUs (E4, E9) where CWD is endemic be revised by I January 2001 to reflect changes in population management sufficient to achieve three short-term management objectives: Ml. to prevent further dispersal ofCWD beyond endemic DAUs via mule deer, white-tailed deer, and elk movements; and M2. to reduce CWD prevalence among deer inhabiting the three most severely affected GMUs (9, 191, 19) by ~50% within 10 years (by 2011); and M3. to reduce CWD prevalence among deer and elk inhabiting all endemic DAUs to ~1 % within 20 years (by 2021). Strategies for accomplishing management objectives will be identified in individual DAU plans. Developing these plans will necessarily involve broader public input than typical DAU planning processes in order to properly represent statewide concerns over CWO and its management; their development will entail collaborative efforts of Terrestrial Resources, Public Service, and Human Dimensions staffs. Because we regard any attempt to manage chronic wasting disease as experimental, we also recommend coordination through CDOW's Terrestrial Resources Program to ensure that elements of uniformity, design, and control are sufficient to implement management strategies and evaluate their effects. These plans should be �200 collectively reviewed, evaluated, and revised every 5 years as part of an adaptive process for achieving management goals. Where applicable, regulation adoption processes for implementing these DAU plans should be independent of the 5-year season structure process. Prospective management strategies: Prescribing specific management strategies is beyond the scope or intent of this document. However, we believe a clear understanding prospective strategies and options (or lack thereof) is a necessary prerequisite to adoption of the foregoing policy, goals, and objectives for managing CWD in northeastern Colorado. Consequently, we offer the following overview as a context for the decisions on CWD management recommended here. Effective strategies for managing CWD or any other TSE in free-ranging wildlife have never been identified or evaluated. Many conventional disease management options are precluded from consideration. Most notably, vaccines, therapeutics, and live-animal tests for CWD are presently unavailable (Table 3). Contrary to experiences with domestic sheep (Dawson et al. 1998), available data indicate relatively uniform genetic susceptibility to CWD among deer (K. I. O'Rourke and M. W. Miller, unpubl. data); consequently, genetic selection would probably have no impact on prevalence even if tools for its implementation were available. Similarly, controlling reproduction alone probably would be ineffective even if practical tools were available because maternal transmission alone is unlikely to be sustaining CWD prevalence at levels currently observed in some affected deer populations (Miller et al. 2000, Gross and Miller 2000). All other prospective options for reducing CWD prevalence that have been identified to date (Table 3) involve some form of aggressive culling br population control directed at diminishing or preempting disease transmission - the magnitude and duration of such control will be driven by GMU- and DAU-specific CWD prevalence, management objectives, and population responses. Based on current understanding of CWD epidemiology (Miller et al. 1998,2000; Gross and Miller 2000), strategies capable oflowering CWD transmission rates by reducing numbers of infected animals. and point sources of environmental contamination (e.g., feeders) should be most effective in lowering prevalence; although the precise mechanisms of transmission have not been identified, those details will probably have little influence on the resolution of CWD management at the population level. General models predict that random culling should be less effective than selective culling in reducing disease prevalence (Barlow 1996, McCarty and Miller 1998, Gross and Miller 2000). However, field data and pilot work indicate that management strategies based on culling clinical suspects probably will miss a large proportion of the infected (and potentially infectious) individuals in a population; moreover, there is no practical way to apply "test and slaughter" regimes without an antemortem diagnostic test for preclinical CWD. Accelerated culling of early clinical cases, either by humans or via predators, may help reduce CWD transmission and prevalence. Alternatively, if the probability ofCWD transmission is density-dependent, then reducing deer or elk densities in endemic areas should lead to reduced CWD prevalence; to date, .the hypothesis of densitydependent disease transmission remains untested. Obvious strategies for limiting CWD distribution remain equally elusive. The mechanisms driving the spread of CWO among deer and elk populations are even less apparent than those driving disease dynamics. It is possible that CWD distribution to date has been influenced by regular and/or random movements of deer and, less commonly, elk. Previous studies (Kufeld et al. 1989, Kufeld and Bowden 1995, S. Steinert pers. comm.) have shown that proportions of both foothills and river bottom deer populations in northeastern Colorado are either migratory or mobile; the movement patterns documented in these studies provide at least a partial explanation for observed CWO distribution. It is also possible that CWD influences its own distribution by changing behaviors, range fidelity, and movement pattens of affected animals; observations of repetitive pacing in captive deer and elk affected by CWO could be manifested as extensive wandering movements of free-ranging individuals. Whether or not movement �201 patterns or dispersal rates are density-dependent remains unclear; either way, reducing population size should also reduce the probability of affected individuals carrying CWD to new areas. (However, we do recognize the possibility that at some lower threshold reduced density may actually promote deer and elk movements, particularly during the breeding season). Experiments to Manage CWD: Based on current uncertainty about how to effectively disrupt the processes that influence CWD epidemiology, prevalence, and distribution in free-ranging deer in northeastern Colorado, we recommend initiating controlled management experiments directed toward testing one hypotheses about how best to manage CWD. Prospective testable hypotheses include: HI. CWD distribution in foothills and river bottom habitats can be diminished by a) selective culling; b) increasing natural mortality via mountain lion predation; OR c) reducing deer density in affected populations. H2. CWD transmission and prevalence in foothills and river bottom deer populations can be diminished by a) selective culling; b) increasing natural mortality via mountain lion predation; OR c) reducing deer density in affected populations. I We recommend using an adaptive resource management approach (Holling ~978, Walters and Holling 1990) to test candidate strategies for reducing CWD prevalence and distribution. Based on initial evaluations of these candidate strategies, more detailed management experiments can be developed in conjunction with the DAU planing process; as part of that process, decisions will be made on which, ifany, approaches to pursue and where CWD management will be attempted. Tactics for accomplishing management approaches (e.g., harvest, selective culling, ground/aerial gunning, changes in predator harvest, etc.) will follow from internal consensus on which tactics are viable under the social and political constraints imposed by the area(s) selected for study. All proposals should be review and approved through appropriate internal and public processes. However, because it is likely that conventional recreation-based season structures, bag limits, and/or administrative boundaries may be insufficient to accommodate experimental approaches for managing CWD, the processes for changing regulations supporting management experiments should be independent of the 5-year season structure process in order to maximize flexibility in this adaptive management approach. Prospective management tactics: Specific tactical recommendations employed in experimental CWD management should follow from the DAU planning process. As a general consideration, however, it is likely that current season structure, bag limits, and/or administrative boundaries may be too inflexible to accommodate experimental approaches for managing CWD that may be proposed for evaluation. Many candidate tactics (Table 4) for such management will require modification or temporary suspension of Commission regulations, as well as considerable human dimensions efforts. Within the confines of the broad policy, goals, and objectives provided, we believe specific tactics are best identified by a combination of Staff and field collaborators on a local level in conjunction with the DAU planning process and adopted as a package along with specific DAU plans for managing CWD. Developing comprehensive, objective-oriented DAU plans to manage CWD represents an unprecedented challenge to CDOW's biologists, field personnel, public service representatives, and administrators. �202 However, we believe rising to meet this challenge is vastly preferable to a legacy of inaction that will allow a potentially manageable wildlife health problem to become widespread at the expense of valuable wildlife resources in Colorado and elsewhere. LITERATURE CITED Barlow, N.D. 1996. The ecology of wildlife diesase control: simple models revisited. 1. Appl. Ecol. 33: 303-314. Bear, G. D. 1989. Seasonal distribution and population characteristics of elk in Estes Valley, Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. Special Report Number 65: 1- 14. Dawson, M. L. 1. Hoinville, B. D. Hosie, and N. Hunter. 1998. Guidance on the use ofPrP genotyping as an aid to the control of clinical scrapie. Vet. Rec. 142:623-625. " Gross, J. E., and M. W. Miller. 2000. Chronic wasting disease in mule deer: A model of disease dynamics, control options, and population consequences. 1. Wildl. Manage. (in reView). Holling, C. S. 1978. Adaptive environmental assessment and management. John Wiley and Sons, London, England. Kufeld, R. C. and D. C. Bowden. 1995. Mule deer and white-tailed deer inhabiting eastern Colorado plains river bottoms. Colorado Division of Wildlife, Fort Collins, Colorado. Technical Publication Number 41: 1- 58. Kufeld, R. C., D. C. Bowden, and D.L. Schrupp,. 1989. Distribution and movement of female mule deer in the Rocky Mountain foothills. J. Wildl. Manage. 53: 871-877. McCarty, C. W., and M. W. Miller 1998. A versatile model of disease transmission applied to forecasting bovine tuberculosis dynamics in white-tailed deer populations. J. Wildl. Dis. 34: 722-730. Miller, M. W. 1999. Monitoring and managing chronic wasting disease in deer. Pages _-_ in Wildlife Research Report, Manunals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-12, Work Package 3001, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) Miller, M. W. 1999. Monitoring and managing chronic wasting disease in elk. Pages _-_ in Wildlife Research Report, Manunals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-12, Work Package 3002, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epidemiology of chronic wasting disease in captive Rocky Mountain elk. J. Wildl. Dis. 34:532-536. Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. 1. Kreeger, and E. T. Thome. 2000. Epidemiology of chronic wasting disease in free-ranging cervids. J. Wildl. Dis. (in review). Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. 1. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, 1. M. Miller, and P. A. Merz. 1997. Spongiform encephalopathy in freeranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus elaphus nelsoni) in northcentral Colorado. J. Wildl. Dis. 33:1-6. Walters, C. J., and C. S. Holling. 1990. Large-scale management experiments and learning by doing. Ecology 71: 2060-2068. Williams, E. S., and S. Young. 1980. Chronic Wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16: 89-98. ~ and __ . 1982. Spongiform encephalopathy of Rocky Mountain elk. Journal of Wildlife Diseases 18: 465-471. ~ and .; __ . 1992. Spongiform encephalopathies in Cervidae. Revue Scientifique et Technique Office International des Epizooties 11: 551-567. _~ and __ . 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. �203 Table 1. Profiles used in chronic wasting disease targeted surveillance. • Species: • Age: • Signs: mule deer white-tailed deer elk ::::18 months emaciated and abnormal behavior &lor indifference to human activity &lor increased salivation &lor tremor, stumbling, incoordination &lor difficulty or inefficiency in chewing/swallowing &lor increased drinking and urination Table 2. Tentative schedule for systematic statewide chronic wasting disease surveys of deer populations using harvest and/or road-kill samples. . CWD Status GMUs Years surveyed Endemic 7,8,9, 19, 191,20 29,91,93,94,95,951,96 1996-1999 1997-1999 "High Risk" 87, 88, 89, 90, 92 104 18,28,37,371 6, 16, 17, 161, 171 22 97, 98, 99, 100, 101 1997-2000 1996-2000 1998 1999-2001 1999 2000-2001 Other areas 66,67 83 1997-1998 1993-1994, 1998 1999 2000-2001 2001-2003 "Uncompahgre" "Southern Front Range" Random Statewide [Note: Survey targets and schedules subject to changes influenced by new data and availability of resources supporting CWD surveillance activities.] �204 Table 3. Prospective strategies for chronic wasting disease management, as well as real or potential limitations of these strategies. Strategies for limiting distribution - vaccination (no vaccine available) - preclude human-caused trans locations (mostly done) - interrupt migration corridors (fencing, local population suppression?) - change habitat (improve/degrade to influence animal distribution?) - alter migratory behavior (selective culling?) - reduce density (relationship between density & distribution untested) Strategies for reducing prevalence - vaccination (no vaccine available) - treatment (no effective therapeutic drugs available) - genetic selection (evidence of uniform susceptibility) - fertility control (maternal transmission probably a minor contribution; no practical tools) - eliminate clinical suspects (ineffective to date; intensive effort necessary) - test & slaughter (no reliable, practical live animal test) - selective culling (what criteria? mechanism?) - foster natural mortality (e.g., predation) to promote selective culling - reduce density (relationship between density & transmission untested) Table 4. Prospective management tactics that could be needed to support selected management strategies, as well as potential issues or limitations ito specific tactics. Harvest (role of public hunting in disease management?) - separate species management for mule deer and white-tailed deer - shift emphasis from recreational opportunity to population management - modify GMU/ "management area" boundaries to focus management & distribute pressure - expand or modify season structure/length - increase bag limits - bounty/incentive programs Culling (public acceptance, access, efficiency?) - ground vs. aerial vs. capture & kill options - use of agency vs. public agents for culling operations - private land issues - bounty/incentive programs Fertility control (probably not useful for reductions, but maybe to maintain) - agent availability and environmental safety - delivery, cost Increase predation (livestock and public safety issues) - reduce predator quotas (close seasons?) - predator introductions Poisoning (specificity, environmental impacts, public acceptance?) �205 Appendix B Chronic Wasting Disease in Colorado Deer and Elk: Recommendations for Experimental Management in GMU 9 M W. Miller and R. H Kahn Terrestrial Wildlife Resources, Colorado Division of Wildlife Executive Summary Chronic wasting disease (CWO) is a transmissible spongiform encephalopathy (TSE) of native deer and elk that is endemic throughout northeastern Colorado and southeastern Wyoming. Estimated infection rates range from <1-15% in deer and 1% in elk residing in northeastern Colorado game management units (GMUs). There is no precedent for attempting to manage a TSE in free-ranging wildlife, and the biological imperative for such management is not entirely clear. However, it seems most biologically responsible to assume that CWO adversely affects native deer and elk populations and consequently manage to prevent its further spread and reduce its occurrence in Colorado. The Colorado Division of Wildlife is committed to minimizing the threat that CWO poses to Colorado's native deer and elk resources. In data analysis units (DAUs) where CWO is endemic, goals of reducing the occurrence and preventing the further spread of CWO currently serve as the primary basis for setting management objectives. Based on current understanding of CWO in free-ranging deer and elk, eradication seems an extreme and unjustifiable management goal at this time. Considering the prevalence and .. distribution CWO has reached under historical management regimes, however, continuing to rely on current management approaches seems equally unjustifiable. Specific strategies and tactics for accomplishing CWO management objectives need to be identified in individual DAU plans. However, many conventional disease management options (most notably, vaccines, therapeutics, and live-animal tests for CWO) are presently unavailable; all other prospective strategies identified to reduce CWO prevalence involve some form of aggressive culling or population control. Here, we propose a management experiment in GMU 9 to evaluate the efficacy of density reduction on CWO prevalence over time. Because current season structure and bag limits are too inflexible to achieve management objectives, we recommend draft language for modifying Commission regulations to support achievement of experimental management objectives. Managing CWO represents an unprecedented. challenge to CDOW's biologists, field personnel, public service representatives, and administrators, as well as to sportsmen, landowners, and other affected publics. However, rising to meet this challenge is vastly preferable to a legacy of inaction that allows CWO to become more widespread at the expense of valuable wildlife resources in Colorado and elsewhere. �206 Background Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (fSE) of native deer (Odocoileus spp.) and elk (Cervus elaphus nelsoni) characterized by behavioral changes and progressive loss of body condition that invariably lead to the death of affected animals (Williams and Young 1992). Neither the causative agent nor its mode of transmission have been fully identified; however, CWD is suspected to be caused by a unique strain ofprion transmitted from animal-to-animal via some combination of saliva, feces, urine, or other tissues or fluids (Miller et al. 1998, 2000; Williams et al. 2000). Both sexes and all age classes show relatively uniform susceptibility (Miller et al. 2000, Williams et al. 2000). There are no valid tests currently available for diagnosing CWD in live animals, and extant postmortem tests require microscopic examination of brain tissue. There are no known treatments for CWD. Previous attempts to eradicate CWD from research facilities failed on at least 2 occasions (Williams and Young 1992, Miller et al. 1998). Although similar in some respects to other TSEs that affect domestic sheep (scrapie) and cattle (bovine spongiform encephalopathy; BSE), existing and unpublished experimental data indicate CWO cannot be naturally transmitted to domestic livestock, and that scrapie and BSE cannot be naturally transmitted to native cervids. Moreover, available data indicate that CWD does not present a threat to human health. "Chronic wasting disease" was first recognized by biologists in the 1960's as a disease syndrome of captive deer held in wildlife research facilities in Ft. Collins, CO. This disease was subsequently recognized in captive deer, and later in captive elk, in wildlife research facilities near Ft. Collins, Kremmling, and Meeker, CO and Wheatland, WY (Williams and Young 1980, 1982), as well as at in least two zoological collections (Williams and Young, 1992). Since 1996, CWD also has been diagnosed in captive elk residing in two game ranches in Saskatchewan, Canada, as well as five ranches in South Dakota, two ranches in Nebraska, two ranches in Colorado, and' one ranch each in Oklahoma and Montana. Over 100 cases of clinical CWO also have been diagnosed in free-ranging mule deer (0. hemionus), white-tailed deer (0. virginianus), and elk from northeastern Colorado and southeastern Wyoming since 1981 (Miller et al. 2000). At present, the known distribution of CWD in wild cervids appears to be limited to northeastern Colorado and southeastern Wyoming (Miller et al. 2000). Although CWO was first diagnosed in captive cervids, the original source of CWO in either captive cervids or free-ranging cervids is unknown; whether CWO in captive cervids really preceded CWD in wild cervids, or vice versa, is equally uncertain (Spraker et al. 1997). Moreover, the relationship (if any) between CWD cases in privately-owned elk industry and cases in free-ranging and research animals is unclear. In Colorado, free-ranging CWO cases in deer and elk have originated from throughout the northeastern portion of the state. Game management units (GMUs) yielding infected deer or elk include 7,8,9, 19, 191, 20,29,91,93,94,95,951, and 96. Although cases have come from 13 different GMUs~ two data analysis units (04, DI0) have yielded over .85% of the documented cases. Harvest surveys indicate GMUs 9, 191, and 19 are the most extensively infected GMUs in Colorado; estimated prevalence ranges from about 615% (Miller et al. 2000). Data from harvest surveys indicate that CWD is less prevalent in GMUs surrounding this core area, affecting about 1-4% of the deer in GMUs 7, 8, 20, 29, 91, 93, 94, 95, 951, and 96. Similarly, harvest surveys indicate <1 % of the elk in DAUs E4 and E9 are infected with CWO (Miller et al. 2000). Based on targeted surveillance data and select harvest surveys, wild deer or elk populations in other parts of Colorado and Wyoming are probably not infected with CWO (Miller et al. 2000). Similarly, surveillance data gathered to date indicate CWO has not yet spread to South Dakota, Nebraska, or Kansas (A. Jenny, USDA-APHIS-VS-NVSL, pers. comm.). For infected deer populations northeastern Colorado, overall CWO prevalence appears to be stable; however, because small increases would be difficult to detect over only a few years it is doubtful that our short-term observations accurately reflect or forecast long-term trends. In the absence of historical (20-30 years ago) prevalence data or reliable estimates of transmission rates, changes in overall incidence or distribution of CWO in northcentral Colorado DAUs are probably best projected via modeling. Based on �207 field data and results of simulation modeling, it appears that CWD was introduced into northern Larimer County over 30 years ago (Miller et al. 2000, Gross and Miller 2000) and has increased in both prevalence and distribution since that time. The significance of CWD and its impacts on native deer or elk populations have not been determined. Preliminary results of simulation modeling suggest that, sustained at >5% prevalence as observed in the most heavily infected GMUs, CWD could impact wild deer herds and lead to population declines (Miller et al. 2000, Gross and Miller 2000). Analyses of harvest and other population data have not detected evidence of population depression attributable to CWD, but existing inventory data for deer in northeastern Colorado are probably insufficient to detect such trends. In the absence of data to the contrary, it seems most prudent to assume that CWD adversely affects native deer or elk populations and manage to prevent its further spread and reduce its occurrence in Colorado. Unfortunately, there is considerable uncertainty in how to manage CWD in free-ranging wildlife, or whether such an endeavor could even be successful (Gross and Miller 2000). Because a more complete understanding of CWD is fundamental to developing comprehensive management programs, the CDOW needs to further understanding about CWD and its management through surveillance and experimental management. EXPERIMENTAL MANAGEMENT There is no precedent for attempting to manage a TSE in free-ranging wildlife. Moreover, the biological imperative for such management is not entirely clear at present. Programs for managing or eliminating TSEs of domestic livestock have proven only marginally successful, and the lack of obvious success in eradicating scrapie or BSE from endemic countries, compounded by epidemiological differences between CWD and other TSEs, make such programs rather poor models for prospective CWD management. Several fundamental features ofCWD epidemiology are understood poorly, if at all; in particular, the influences of host (e.g., population density, intraspecific vs. interspecific transmission, genetics) and environmental factors (e.g., contamination, reservoirs, weather) on CWD dynamics remain unclear. In light of the uncertainties associated with its epidemiology and ecology, we believe CWD management should be approached as an experiment, thereby allowing us to learn as we take actions intended to reduce prevalence and limit distribution. The CDOW's initial approaches for attempting to control CWD in free-ranging deer and elk were outlined in an action plan for CWD drafted in 1995 (Miller et al. 1995). In addition to calling for a comprehensive public information campaign, this plan identified tactics for limiting distribution and reducing prevalence of CWD based on contemporary knowledge of the problem. Prompt removal of affected animals and enforcement of feeding prohibitions were recommended to help reduce CWD prevalence and transmission. Policies and regulations were also recommended, and subsequently instituted, to prevent wider distribution ofCWD via human activities (e.g., translocations, rehabilitation, game ranching). The plan also identified a need for more extensive surveillance to gather data on CWD distribution and prevalence. As more data on CWD distribution and prevalence have been gathered over the last 4 years, it has become apparent that CWD is more widely distributed and more prevalent in northeastern Colorado (and elsewhere) than initially believed (Miller et al. 2000). It follows that policy, goals, and strategies for experimental CWD management in Colorado should be reevaluated in the context of new data, as well as changes in social and political attitudes toward animal TSEs. The CDOW is committed to minimizing the threat CWD poses to Colorado's native deer and elk resources. In data analysis units (DAUs) where CWD is endemic, goals of reducing the occurrence and preventing the further spread of CWD currently serve as the primary basis for setting management objectives. Based on current understanding of CWD in free-ranging deer and elk, eradication seems an extreme and unjustifiable �208 management goal at this time. Considering the prevalence and distribution CWD has reached under historical management regimes, however, continuing to rely on current management approaches seems equally unjustifiable. Prospective management strategies: A clear understanding of prospective strategies and options (or lack thereof) is a necessary prerequisite to adoption of policy, goals, and objectives for managing CWD in northeastern Colorado. Consequently, we offer the following overview as a context for the recommendations on CWD. management described here. Effective strategies for managing CWD or any other TSE in free-ranging wildlife have never been identified or evaluated. Many conventional disease management options are precluded from consideration. Most notably, vaccines, therapeutics, and live-animal tests for CWD are presently unavailable (Table 1). Contrary to experiences with domestic sheep (Dawson et al. 1998), available data indicate relatively uniform genetic susceptibility to CWD among deer (K. I. O'Rourke and M. W. Miller, unpubl. data); consequently, genetic selection would probably have no impact on prevalence even if tools for its implementation were available. Similarly, controlling reproduction alone probably would be ineffective even if practical tools were available because maternal transmission alone is unlikely to be sustaining CWD prevalence at levels currently observed in some affected deer populations (Miller et al. 2000, Gross and Miller 2000). All other prospective options for reducing CWD prevalence that have been identified to date (Table 1) involve some form of aggressive culling or population control directed at diminishing or preempting disease transmission. The magnitude and duration of such control will be driven by GMU- and DAU-specific CWD prevalence, management objectives, and population responses. Based on current understanding of CWD epidemiology (Miller et al. 1998,2000; Gross and Miller 2000), strategies that lower CWD transmission rates by reducing numbers of infected animals and point sources of environmental contamination (e.g., feeders) should be most effective in lowering prevalence. (Although the precise mechanisms of transmission have not been identified, those details will probably have little influence on the resolution ofCWD management at the population level.) General models predict that random culling should be less effective than selective culling in reducing disease prevalence (Barlow 1996, McCarty and Miller 1998, Gross and Miller 2000). However, field data and pilot work indicate that management strategies based on culling clinical suspects probably will miss a large proportion of the infected (and potentially infectious) individuals in a population. Moreover, there is no practical way to apply "test and slaughter" regimes without an antemortem diagnostic test for preclinical CWD. Accelerated culling of early clinical cases, either by humans or via predators, may help reduce CWD transmission and prevalence. Alternatively, if the probability of CWD transmission is density-dependent, then reducing deer or elk densities in endemic areas should lead to reduced CWD prevalence; to date, the hypothesis of density- . dependent disease transmission remains untested. Obvious strategies for limiting CWD distribution remain equally elusive. The mechanisms driving the spread of CWD among deer and elk populations are even less apparent than those driving disease dynamics. It is possible that CWD distribution to date has been influenced by regular and/or random movements of deer and, less commonly, elk. Previous studies (Kufeld et al. 1989, Kufeld and Bowden 1995, S. Steinert pers. comm.) have shown that proportions of both foothills and river bottom deer populations in northeastern Colorado are either migratory or mobile. The movement patterns documented in these studies provide at least a partial explanation for observed CWD distribution. It is also possible that CWD influences its own distribution by changing behaviors, range fidelity, and movement patterns of affected animals; observations of repetitivepacing in captive deer and elk affected by CWD could be manifested as extensive wandering movements of free-ranging individuals. Whether or not movement patterns or dispersal rates are density-dependent remains unclear; either way, reducing population size should also reduce the probability of affected individuals carrying CWD to new areas. (However, we do �209 recognize the possibility that at some lower threshold reduced population density may actually promote deer and elk movements, particularly during the breeding season). Experiments to manage CWD: Based on current uncertainty about how to effectively disrupt the processes that influence CWD epidemiology, prevalence, and distribution in free-ranging deer in northeastern Colorado, we have recommend initiating controlled management experiments directed toward testing one hypotheses about how best to manage CWD. Prospective testable hypotheses include: HI. CWD distribution in foothills deer populations can be diminished by selective culling and by reducing deer density in affected populations. H2. CWD transmission and prevalence in foothills deer populations can be diminished by selective culling and by reducing deer density in affected populations. We recommend using an adaptive resource management approach (Holling 1978, Walters and Holling 1990) to test candidate strategies for reducing CWD prevalence and distribution. Based on initial evaluations of these candidate strategies, larger management experiments can be developed in conjunction with the DAU planing process. Prospective management tactics: Specific tactical recommendations employed in experimental CWD management should follow from the DAU planning process. As a general consideration, however, it is likely that current season structure, bag limits, and/or administrative boundaries may be too inflexible to accommodate experimental approaches for managing CWD that may be proposed for evaluation. Many candidate tactics (Table 2) for such management will require modification or temporary suspension of Commission regulations, as well as considerable human dimensions efforts. Within the confines of the broad policy, goals, and objectives provided, we believe specific tactics are best identified by a combination of staff and field collaborators on a local level in conjunction with the DAU planning process and adopted as a package along with specific DAU plans for managing CWD. Developing comprehensive, objective-oriented DAU plans to manage CWD represents an unprecedented challenge to CDOW's biologists, field personnel, public service representatives, and administrators. However, we believe rising to meet this challenge is vastly preferable to a legacy of inaction that will allow a potentially manageable wildlife health problem to become widespread at the expense of valuable wildlife resources in Colorado and elsewhere. Experimental management of CWD in GMU 9: Within endemic portions of northeastern Colorado, CWD prevalence is highest in GMU 9. Of 174 harvested deer from GMU 9 sampled during 1996-1999,29 (16.7%) tested positive for CWD (Miller et al. 2000); because diagnostic tests currently in use underestimate true CWD prevalence by a factor of about 0.8 (Miller et al. 2000), true prevalence in GMU 9 is likely closer to 20%. Highest densities of infected deer and highest local prevalence rates occur primarily in the northwestern portion of GMU 9 and coincide with areas of highest wintering deer densities in this GMU (Fig. 1). Although sample sizes for individual �210 CWO Density (No. PoslKm2) and locations of CWO Positive Mule Deer years are small and some year-to-year Clinical Cases and Hunter Survey Samples 1997-1999 variation probably occurs, CWD prevalence N among bucks harvested in GMU 9 has shown an increasing trend over the last 3 years (15.8% in 1997, 12.2% in 1998,20% in 1999), Computer models parameterized to reflect this observed 3-year trend forecast that CWD prevalence in GMU 9 will double in the ""'NH""" ••. next 10 years in the absence of some change in Ntransmission or population dynamics (Fig. 2). 6atv~""'.o Under modest assumptions of densityIIIRO.1.0.15 dependent CWD transmission, models predict that dramatic (e.g., 50% of current levels) reductions in deer density could prevent further increases in prevalence (Fig. 2). If transmission GMJ 9 KrigedON;) Pr8talenceEstinBtes: is more strongly density-dependent than 2x2 Km ard 100 NeaJestNeigl"bors assumed, then prevalence should actually decrease in response to density reductions. Conversely, if CWD transmission is not influenced by deer density, then models forecast that prevalence will continue to rise despite density reductions (Fig. 2). A l.ocII:lonsd~lcdPosiMs tiIrttGt SUN6f O-O 25 0.025·0.OS o.oS.0.1 Po!:itiw5INo. PosMn2) i 0.15002 0.2-0.25 • Understanding the relationship (or lack thereof) between deer density and CWD prevalence trends is fundamentally important to future decisions on CWD management throughout northeastern Colorado. In order to further this understanding, we recommend an experimental reduction in deer Figure 1.Highest densities of infected deer (upper map) densities in GMU 9 to assess the effects of such and highest local prevalence rates (lower map) occur management intervention on CWD prevalence. primarily in the northwestern portion of GMU 9. These We have selected GMU 9 as a study area heavily infected areas coincide with areas of highest primarily because CWD prevalence is high wintering deer densities in GMU 9. enough to allow reliable measurement and detection of trends over time. In addition, the resident deer population in GMU 9 is relatively small (about 1000 head) and insular. Our experimental management plan calls for reducing deer density in GMU 9 by about 50% over the next 2-3 years (20002002) and holding 'deer density at this reduced level for at least 5 years (2003-2007). CWD prevalence will be monitored via sampling of harvested deer; in addition; we will monitor radiocollared deer in GMU 9 and adjacent GMUs to examine effects of lowered density on home ranges and movement patterns. Prevalence trends will be compared to trends in surrounding GMUs. In cooperation with the Wyoming Game and Fish Department, we will also compare data from GMU 9 to data from a Wyoming "hunt area" (HA 64) where current CWO prevalence trends are very similar to those in GMU 9. Because density will not be reduced in HA 64 over the next several years, this population will serve as a control for our management experiment. Virtually all deer ranges in GMU 9 are in private ownership. Consequently, we have enlisted local landowners as partners in this proposed management experiment. Based on input from GMU 9 landowners, we recommend that density reductions be accomplished primarily via extended, limited access hunting seasons; in some cases, culling may be needed to augment removals via harvest. Draft language for regulations to establish these landowner-controlled hunts follows: �211 Draft regulation for experimental chronic wasting disease management in GMU 9 Chapter 2 Article VIII #250 E. Experimental Seasons for Chronic Wasting Disease Management a. All landowners with fee title or exclusive lease to more than (20 acres) of land located in GMU 9 are eligible to receive unlimited numbers of vouchers that may be used to purchase either-sex deer licenses validfor the time period 1 November 2000 through 28 February 2001. Licenses are valid only in GMU 9. All deer harvested under this experimental season shall have the heads submitted to the Division of Wildlife for chronic wasting disease testing. All other regulations are in effect for this season, including but not limited to method of take, tagging, hunting hours and care of game meat. Experimental season licenses will be considered additional licenses. Quotas or limits on geographic distribution of vouchers will be established by CDOW Terrestrial Resources staff, in consultation with Area personnel, in order to achieve uniform density reduction throughout GMU 9. Population trends will be monitored by both aerial inventory and modeling. LITERATURE CITED Barlow, N.D. 1996. The ecology of wildlife disease control: simple models revisited. J. Appl. Ecol. 33: 303-314. Bear, G. D. 1989. Seasonal distribution and population characteristics of elk in Estes Valley, Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. Special Report Number 65: 1- 14. Dawson, M. L. 1. Hoinville, B. D. Hosie, and N. Hunter. 1998. Guidance on the use ofPrP genotyping as an aid to the control of clinical scrapie. Vet. Rec. 142:623-625. Gross, J. E., and M. W. Miller. 2000. Chronic wasting disease in mule deer: A model of disease dynamics, control options, and population consequences. J. Wildl. Manage. (in review). Holling, C. S. 1978. Adaptive environmental assessment and management. John Wiley and Sons, London, England. Kufeld, R. C. and D. C. Bowden. 1995. Mule deer and white-tailed deer inhabiting eastern Colorado plains river bottoms. Colorado Division of Wildlife, Fort Collins, Colorado. Technical Publication Number 41: 1- 58. Kufeld, R. C., D. C. Bowden, and D.L. Schrupp,. 1989. Distribution and movement of female mule deer in the Rocky Mountain foothills. 1. Wildl. Manage. 53: 871-877. McCarty, C. W., and M. W. Miller 1998. Aversatile model of disease transmission applied to forecasting bovine tuberculosis dynamics in white-tailed deer populations. J. Wildl. Dis. 34: 722-730. Miller, M. W. 1999. Monitoring and managing chronic wasting disease in deer. Pages _-_ in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-12, Work Package 3001, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) Miller, M. W. 1999. Monitoring and managing chronic wasting disease in elk. Pages _-_ in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-12, Work Package 3002, Task 3. Colorado Division of Wildlife, Fort Collins, Colorado, USA. (in press) Miller, M. W., G. G. Schoonveld, B. Smith, R. A. Spowart, and R. H. Kahn. 1995. Chronic wasting disease - proposed action plan. Unpubished report, Colorado Division of Wildlife, Fort Collins, Colorado, 16 pp. Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epidemiology of chronic wasting disease in captive Rocky Mountain elk. J. Wildl. Dis. 34:532-536. �212 Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. J. Kreeger, C. T. Larsen, and E. T. Thome. 2000. Epizootiology of chronic wasting disease in free-ranging cervids in Colorado and Wyoming. J. Wildl. Dis. 36: (in press). Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. 1. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, 1. M. Miller, and P. A. Merz. 1997. Spongiform encephalopathy in freeranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus elaphus nelson i) in northcentral Colorado. J. Wildl. Dis. 33:1-6. Walters, C. 1., and C. S. Holling. 1990. Large-scale management experiments and learning by doing. Ecology 71: 2060-2068. Williams, E. S.; and S. Young. 1980. Chronic Wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16: 89-98. ____:> and __ . 1982. Spongiform encephalopathy of Rocky Mountain elk. Journal of Wildlife Diseases 18: 465-471. ____:> and __ . 1992. Spongiform encephalopathies in Cervidae. Revue Scientifique et Technique Office International des Epizooties 11: 551-567. ____:> and __ . 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. �213 Table 1. Prospective strategies for chronic wasting disease management (and real or potential limitations of these strategies). Strategies for limiting distribution - vaccination (no vaccine available) - preclude human-caused translocations (mostly done) - interrupt migration corridors (fencing, local population suppression?) - change habitat (improve/degrade to influence animal distribution?) - alter migratory behavior (selective culling?) - reduce density (relationship between density & distribution untested) Strategies for reducing prevalence - vaccination (no vaccine available) - treatment (no effective therapeutic drugs available) - genetic selection (evidence of uniform susceptibility) - fertility control (maternal transmission probably a minor contribution; no practical tools) - eliminate clinical suspects (ineffective to date; intensive effort necessary) - test & slaughter (no reliable, practical live animal test) - selective culling (what criteria? mechanism?) - foster natural mortality (e.g., predation) to promote selective culling - reduce density (relationship between density & transmission untested) Table 2. Prospective management tactics that could be needed to support selected management strategies, as well as potential issues or limitations specific tactics. to Harvest (role of public hunting in disease management?) - separate species management for mule deer and white-tailed deer - shift emphasis from recreational opportunity to population management modify GMU/ "management area" boundaries to focus management & distribute pressure - expand or modify season structurellength - increase bag limits - bounty/incentive programs Culling (public acceptance, access, efficiency?) - ground vs. aerial vs. capture & kill options - use of agency vs. public agents for culling operations - private land issues bounty/incentive programs Fertilitv control (probably not useful for reductions, but maybe to maintain) - agent availability and environmental safety - delivery, cost Increase predation (livestock and public safety issues) - reduce predator quotas (close seasons?) - predator introductions Poisoning (specificity, environmental impacts, public acceptance � https://cpw.cvlcollections.org/files/original/e6e06495c7e2a9214e255a329de730a0.pdf 2e4de18739ba3882f2c6408e487cf4f1 PDF Text Text 135 \ Colorado Division of Wildlife Wildlife Research Report Ju1y 2000 I " JOB PROGRESS REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Research Program Deer Conservation Work Package No. ---"3'"""0..;;..0-=-1_ _ _ __ Task No. 4 Effects of Habitat Enrichment on Mule Deer Recruitment and Survival Rates Period Covered: July 1, 1999 - June 30, 2000 Authors: C. J. Bishop and G. C. White Personnel: L. H. Carpenter, D. Coven, D. J. Freddy, R. B. Gill, R. Harthan, J. SaZina, B. E. Watkins, and B. Welch ) ABSTRACT A Program Narrative {Appendix A) was developed to test the effects of habitat enrichment on mule deer recruitment and survival rates on the Uncompahgre Plateau in southwest Colorado. Post hoc analyses were completed to evaluate the effects of buck harvest on age and sex ratios (Appendix B), and to roughly estimate the total number of deer in Colorado (Appendix C). ) �136 I \ �137 EFFECTS OF HABITAT ENRICHMENT ON MULE DEER RECRUITMENT AND SURVIVAL RA TES C. J. Bishop and G. C. White P. N. OBJECTIVES 1. To conduct a one-year pilot study to assess the logistical feasibility of the proposed study and to gather preliminary data to improve the study's efficiency and experimental design. 2. To determine experimentally whether enhancing mule deer nutrition during winter and early spring by supplemental feeding increases December fawn:doe ratios and overwinter fawn survival. 3. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. SEGMENT OBJECTIVES 1. Prepare a Program Narrative. 2. Plan field logistics and purchase equipment and supplies in preparation for initial field work beginning in FY 2000-01. INTRODUCTION Mule deer numbers apparently declined during the 1990 •s throughout much of the West, and have clearly decreased since the peak population levels documented in the 1940's-60's (Gill et al. 1999, Unsworth et al. 1999). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates that multiple interacting factors are responsible, habitat and predation have received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 1999). Together, predator control studies with adequate rigor indicate that predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat. Numerous research studies have evaluted mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation or habitat is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. We designed a field experiment to measure deer population responses to habitat enrichment treatments. We will conduct the study on the Uncompahgre Plateau, where several predator species are present in abundant numbers. Predator numbers will not be manipulated in any way. Habitat enrichment treatments will consist of supplemental feed provided to deer during the winter. If December fawn:doe ratios and overwinter fawn survival improve as a direct result o(the supplemental feed, then we can presume that deer nutrition is ultimately more limiting than predation. The field experiment also incorporates habitat manipulation treatments, which will consist of prescribed fire or mechanical techniques to set back succession ofpinyon-juniper habitat in an effort to improve the vigor and quality of winter habitat for mule deer. Deer population responses will be measured in relation to the habitat manipulations in the same manner as the supplemental feed. Thus, the experiment allows us to detennine whether nutritional quality �138 of habitat is ultimately more limiting than predation in a late-seral pinyon-juniper/sagebrush landscape, and if so, whether habitat can be effectively improved for mule deer. There have been several challenges to implementing this study. First, using supplemental feed in a field study sends a contradictory message to the public given the Division of Wildlife's policy on winter feeding. Second, the study is very expensive and therefore requires considerable Division support to implement. Third, logistical concerns raise the issue of whether the study can be carried out appropriately, such that response variables are representative of treatment differences and measured without bias yet with adequate precision. Finally, some personnel have questioned the need for such a study, particularly given the expense. In result, we gave a number of presentations explaining the study in detail to generate widespread support throughout the Division. We also decided to conduct a pilot study in the first year to address logistical concerns and to allow more time to generate necessary funding. MATERIALS AND METHODS Program Narrative Development We developed a Program Narrative (Appendix A), which addresses both the I-year pilot study as well as the complete 4-6 year study. The P. N. has not been peer-reviewed at this point, but will be peer-reviewed in early FY 2000-01 prior to the pilot study. The P. N. will be modified as necessary using results from the pilot study, and once again peer-reviewed assuming there are significant changes. We based the P. N. on an initial study proposal submitted by Gary White and Len Carpenter. We conducted a thorough literature review and discussed study methodologies with numerous Division personnel to refine field methods. We spent time in the field with the local Area Biologist, Bruce Watkins, and District Wildlife Manager, Dale Coven, assessing the Uncompahgre Plateau for potential treatment and control areas. We worked closely with the Uncompahgre Ecosystem Restoration Project (UERP) committee to select treatment/control sites in the context of proposed habitat manipulation areas. Uncompahgre Ecosystem Restoration Project The Uncompahgre Ecosystem Restoration Project (UERP) was initiated by the Division of Wildlife after former Director John Mumma allocated $500,000 of capital construction funds to habitat improvements for the benefit of mule deer. UERP is comprised of individuals from DOW, U.S. Forest Service, Bureau of Land Management (BLM), and the Colorado West Public Lands Partnership (PLP). Since the initial $500,000, more funds have been obtained for UERP by the other agencies and PLP. Mike McLain (AWM) and Bruce Watkins (Area Biologist) have represented DOW's interests in UERP from the onset, while Jim Gamer (Habitat Biologist) and I joined the effort this past winter. UERP's mission is to improve ecosystem health on the Uncompahgre Plateau through an integrated effort of the various agencies and groups involved. A primary goal is to increase species diversity, age diversity, and the quality of habitat communities on the Plateau in order to improve the distribution and quality of mule deer winter range. To accomplish this goal, UERP is using a landscape approach to treat habitat using various techniques, primarily prescribed fire and mechanical treatments. All treatments will be re-seeded with shrub-forb-grass mixtures in an attempt to prevent invasive weeds from establishing and to increase forage diversity for mule deer. Deer population responses on one of these habitat treatment areas will be intensively monitored as part of our study's experimental design. The various other habitat treatments will be implemented in a pattern of treatment and control areas such that long-term deer responses can be monitored using the current mule deer population monitoring system on the Uncompahgre Plateau. UERP is currently in the process of hiring a technical coordinator and a policy/education coordinator to facilitate project implementation. The technical coordinator will assist with project design, implementation, and evaluation; provide technical expertise and budget oversight; assist with grant writing and production �139 of project reports; and ensure that proposed projects comply with state and federal regulations. The policy/education coordinator will provide information concerning the project and generate support from government agencies, stakeholders, and the general public. In essence, the policy/education coordinator will serve a classic "information and education" role for UERP. Once the coordinators are hired, we will begin identifying specific treatment sites and proceed with actual habitat treatments. UERP's current timeline should enable some habitat manipulations to be completed in 2-3 years as needed for our habitat enrichment study. NEPA Requirements Since much of the field work for our habitat enrichment study will be conducted on BLM lands, we are subject to the requirements of the National Environmental Policy Act (NEPA). There are 2 types of experimental treatments in our study: (l) supplemental feeding and (2) habitat manipulations. We submitted our P. N. along with a detailed description of the supplemental feeding protocols to the Uncompahgre Field Office of the BLM. They determined that the feeding portion of our study meets the Categorical Exclusion requirement of NEPA, thereby granting approval to proceed without further review. As explained above, all habitat manipulations will be performed by UERP, which assumes the responsibility for obtaining NEPA approval and any other regulatory clearances. Presentations We presented our habitat enrichment study to both Division personnel and other groups throughout the year. For Division personnel, our goal was to explain the study and address a variety of concerns that had been raised. It was our intention to gain support for the study from the various leaders in the Wildlife Programs Branch, as well as managers and biologists in the West Region arid particularly those in Area 18 . .. ·For non-Division groups, we discussed the various issues affecting mule deer populations, and described the habitat enrichment study in light of how the Division of Wildlife is attempting to address mule deer concerns. We gave presentations at the following meetings, workshops, etc.: ♦ DWM Training Session (for incoming DWMs) - 1/5/2000, Denver • West Section Terrestrial Biologist Staff Meeting- 2/7/2000, Grand Junction ♦ CSU Students/Faculty, Wildlife Field Studies Class Trip - 3/11/2000, Uncompahgre Plateau ♦ Wildlife Programs Branch Meeting- 3/14/2000, Denver • Hunter Education Instructors, Big Game Workshop-4/15/2000, Montrose • Hunter Education Instructors, Masters Workshop- 5/6/2000, Winter Parle ♦ Colorado Elementary and Secondary Education Teachers, Teacher Education Program 6/23/2000, Ridgway State Park/Uncompahgre Plateau ♦ Area 18 Staff Meeting- 7/27/2000, Lone Cone Cabin The following presentation was also given, but was unrelated to the habitat enrichment study: ♦ Large Mammal Capture Techniques and Radio-Telemetry, CSU Wildlife Management Short Course - 3/29/2000, Fort Collins Other Activities Mule Deer Legislative Report Along with Mammals Research Leader, Bruce Gill, and other members of the research staff, I assisted in the writing, editing, and publication of "Declining Mule Deer Populations in Colorado: Reasons and Responses". The report was written for and submitted to the Colorado Legislature at their request. The report was distributed widely via hard copies and the internet. I was responsible for responding to a number of comments the Division received concerning the report. I presented the infonnation contained in the report in several of the presentations listed above. �140 Mule Deer Analyses I completed several analyses/data summaries of statewide mule deer population data. I evaluated the effects of limited buck harvest on mule deer sex and age ratios using data from quality (limited-harvest) Game Management Units (GMUs). I also developed a rough estimate of total deer numbers in Colorado by extrapolating deer density estimates from quadrat surveys to the total amount of delineated winter range in Colorado. In doing so, I summarized the square miles of delineated mule deer winter range by GMU and DAU throughout the state. These reports were distributed widely within the Division as a resource for management biologists. I also attempted to "back-model" statewide mule deer numbers to obtain an approximate estimate of Colorado's deer population in the 1950's. This daunting task has not been completed, although considerable effort was put forth. Different models were developed by changing assumptions; however, considerable refinement would be necessary before releasing any of the models. While completing this task, I compiled monthly weather data from approximately 80 Colorado weather stations from 1940-1999. Data were obtained from the W estem Regional Climate Center (www.wrcc.dri.edu/index.html). These spreadsheets, which contain various statewide summaries, are available. RESULTS AND DISCUSSION Habitat Enrichment Study The various presentations we gave were very effective in gaining greater support for the habitat enrichment study, particularly with Western slope managers and biologists. By openly discussing the major concerns, and deciding to pursue a pilot study in the first year, most DOW personnel are generally supportive of the study. Various personnel in the Montrose area have offered their assistance, and we have developed a good, cooperative working relationship with Bruce Watkins, the Area Biologist. Presentations given to non-Division groups were received very well. The different groups were supportive and interested in our proposed study as well as the Division's overall efforts to manage mule deer in light of declining numbers. Our presentations and other "I&E" efforts were necessary to create a favorable climate prior to initiating the study. It is important to note, however, that no presentations were given to the more outspoken critics of DOW. Budget concerns have subsided given that we have submitted requests for outside grants to fund a portion of the study, and because additional dollars may become available.in the research section during the next 2 or 3 years. Largely as a result ofUERP, a good relationship has been developed with the Uncompahgre Field Office of the BLM as well as Forest Service personnel. The BLM has offered to store the supplemental feed in their compound, and have been very cooperative in making the field work possible. They reviewed our study proposal to ensure compliance with NEPA, and spoke with grazing permitees in the area to inform them of the proposed study. These proactive efforts should prevent or at least alleviate any problems when field work begins. We selected several tentative treatment/control sites (experimental units) to be used for the study. We initially planned to identify a number of potential experimental units, and then randomly select which would be used in the study and which would be treatments and controls. However, given the logistical challenges of this study and the need to maintain some level of homogeneity among experimental units, random allocation is not realistic. In particular, feed treatment areas must be selected carefully to avoid feeding more deer than we can afford, and to avoid feeding significant numbers of elk. We are currently planning on distributing supplemental feed in the following 2 areas: (1) The Colona Tract of the Billy Creek State Wildlife Area (2) BLM Land adjacent to Shavano Valley as defined by the following: �141 Within Dry Creek Basin Quadrangle (USGS 7.5 Minute), will primarily include Section 6 in T. 48 N.R. 10 W. and Section 1 in T. 48 N.-R. 11 W. (38°26'00"-38°27'30" N Lat., 108°00'00"-108°02'30" W Long.). However, may also include Section 7 in T. 48 N .-R. 10 W. and Sections 2, 10, 11, 12, 13, 14, 15 in T. 48 N.-R. 11 W., depending on deer distribution and movements. This overall area roughly includes 38°25'00" - 38°27'30" Latitude and 108°00'00" - 108°04'30" Longitude. We are currently planning to use one of the following areas as a control area throughout the study (they are too close together to both be used): (1) Sims Mesa as defined by the following: Within Government Springs Quadrangle (USGS 7.5 Minute), will approximately include Sections 31, 32 in T. 48 N.-R. 9 W., and Sections 5, 6, 7, 8, 17, 18 in T. 47 N.-R. 9 W. (~38°19'30" - 38°22'30" N Lat. and 107°52'30" - 107°54'00" W Long.) (2) Government Springs as defined by the following: Within Colona and Government Springs Quadrangles (USGS 7.5 Minute), will approximately include Sections 9, 10, 15, 16, 17, 20, 21, 22 in T. 47 N.-R. 9 W. (~38°18'30" - 38°21 '00" N Lat. and 107°50'00" - 107°53'00" W Long.) There is little else to report concerning the study, other than we are in the process of purchasing supplies and equipment, and preparing for field work. We have purchased and received 65 radio-collars to be used in the pilot study, along with 15 additional collars from the Uncompahgre population monitoring work that will be used in conjunction with the study. We have purchased radio-telemetry equipment and are in the process of planning storage for and purchasing the supplemental feed. We are also working on drop-nets that will be used along with helicopter netguns to capture deer. Again, the Program Narrative explaining our detailed study plan is in Appendix A. Mule Deer Report The legislative report, "Declining Mule Deer Populations in Colorado: Reasons and Responses", has proven to be a beneficial document for explaining the complex array of factors currently affecting mule deer populations. During our presentations at 2 Hunter Education Workshops this spring, we presented and provided copies of the report to all instructors in attendance. We received feedback from these instructors as well as various other constituents responding to the report via email. The report is apparently upsetting to some individuals who strongly believe predator control is the only solution for reversing declining deer numbers, but for most others the report has provided a heightened awareness of issues surrounding mule deer management. Aside from predation, buck harvest is the other factor generating considerable debate. It would appear that certain sportsmen evaluate the fitness of deer populations in terms of trophy buck opportunities while hunting. This perception confuses objective evaluations of the effects oflow buck:doe ratios on declining deer populations. Clearly, low buck numbers impact hunter success rates, particularly for trophy bucks, yet existing data does not suggest that buck:doe ratios have had a significant impact on fawn production and recruitment. Harvest regulations represent a trade-off between quality hunting and hunting opportunity. However, currently there is no scientific basis for restricting buck harvest solely for the purpose of increasing fawn:doe ratios. In fact, if habitat is limiting many of our deer herds, it could have the opposite effect on fawn recruitment. Mule Deer Data Analyses Limited buck harvest in quality ,GMUs has resulted in modest increases in buck:doe ratios but has had no effect on fawn:doe ratios. The analysis and results are included in Appendix B. By extrapolating observed deer density estimates from quadrat surveys to the total amount of winter range in Colorado, I estimated approximately 575,000 - 580,000 deer in Colorado, which is very similar to the current estimate of deer numbers based on DAU population models. The analysis and results are located in Appendix C. �142 LITERATURE CITED Ballard, W. B, D. Lutz, T. W. Keegan, L. H. Carpenter, and J.C. deVos, Jr. 1999. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Unpublished manuscript. Connolly, G. E. 1981. Limiting factors and population regulation. -Pages 245-285 in 0. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA. Gill, R. B., T. D. I. Beck, C. J. Bishop, D. J. Freddy, N. T. Hobbs, R.H. Kahn, M. W. Miller, T. M. Pojar, and G. C. White. 1999. Declining mule deer populations in Colorado: reasons and responses. A report to the Colorado Legislature. Colorado Division of Wildlife, Denver, Colorado, USA. Unsworth, J. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Prepared by _ _ _ _ _ _ _ _ __ Chad Bishop Mammals Researcher �143 APPENDIX A PROGRAM NARRATIVE FY 2000-01 - 2006-07 State of -----=C_,._ol=o=rad=o_ _ _ __ Project No. _ _ _ _W-'-'--~15:;..:3a...-=R=--------Work Package No. ---"3-"0"""0-=--1_ _ _ __ Study No. _ _ _ _ _ _4 ~ - - - - - Cost Center 3430 Mammals Research Program Deer Conservation Effects of Habitat Enrichment on Mule Deer Recruitment and Survival Rates A. NEED Background Mule deer (Odocoileus hemionus hemionus) are a popular wildlife species with the public throughout their range. Sportsmen place high value on mule deer as a harvestable big game species, and outdoor enthusiasts of all kinds enjoy watching and photographing deer. The Colorado Division of Wildlife, along with other state wildlife agencies in the West, depend on revenue generated from mule deer license sales. Given such popularity and economic importance, an objective of western wildlife agencies has been to maintain healthy, productive deer populations. Unfortunately, mule deer numbers fluctuate widely, primarily in response to climatic and habitat conditions (Gill et al. 1999). Wildlife managers have had little success attempting to maintain stable populations over a long time period. Mule deer numbers peaked in the middle part of the 20th century, which for better or worse, set the standard that many people use to evaluate the status of current deer populations. Since the mid to late 1900's, deer numbers have generally declined to the present. In particular, two widespread declines have been documented; one occurred during the 1960 's through mid-1970 's (Workman and Low 1976), and the second occurred during the 1990's (Unsworth et al. 1999). The recent decline in mule deer populations has caused widespread concern as to the causative factors. Although reasons for declining populations are not clear and have been intensely debated, research indicates multiple interacting factors are responsible. These factors include habitat change, weather, urban development, predation, disease, competition with elk, among others (Gill et al. 1999). Ironically, many of these same factors were raised as reasons for the decline during the 1970's crisis. Great strides have been made during the past several decades to better understand the various aspects of mule deer ecology and population performance. The challenge facing managers is that there are no simple management solutions for increasing deer populations. In particular, harvest manipulations alone are rarely sufficient to direct population levels. By and large, sportsmen have suggested that predation is the major cause of declining deer numbers while biologists have implicated decreasing habitat quality as the primary cause. Management actions addressing either factor will be expensive; thus, high quality data should be obtained before any such management program is initiated. Predation Predator control efforts have been conducted on numerous occasions to evaluate whether predators may be limiting mule deer recruitment, and if so, whether predator control is a viable management strategy. Coyotes have been the primary target of such studies. Connolly (1981) summarized 12 studies assessing whether coyotes negatively impacted deer populations, which when taken together, did not provide a definitive answer as to whether coyotes are a major limiting factor of mule deer. Some of these studies found no benefit to controlling coyotes, and suggested that habitat quality was ultimately the limiting factor (Murie 1940, Leopold et al. 1951, Robinette et al. 1977). Other studies �144 were largely inconclusive (Smith and LeCount 1976, Robinette et al. 1977). The remaining studies found coyote control to be potentially beneficial (Hom 1941, Brown 1961, McMichael 1970, Knowles 1976, Schladweiler 1976, Austin et al. 1977, Robinette et al. 1977, Trainer et al. 1978, Lemos et al. 1978), but given lack of proper experimental controls in many cases, the results were largely speculative. Further, coyotes were primarily controlled by poisoning, which is no longer a possible management strategy for reducing coyote numbers. Trainer et al. (1978) and Lemos et al. (1978) suggested that coyotes were responsible for poor fawn survival in Oregon, but questioned whether aerial shooting of coyotes could effectively reduce coyote densities. Since Connolly's (1981) review of predation studies, several more predator control studies have been conducted. Hartmann et al. ( 1992) found no benefit to coyote control in a deer population in northwest Colorado, and provided strong experimental evidence that coyote predation was almost entirely compensatory. In response to the recent deer decline, several more predator control studies were initiated in various western states. The Idaho Department of Fish and Game and Montana Fish, Wildlife, and Parks each began independent predator control experiments in 1997 (Gill et al. 1999). Preliminary results from both studies indicate very little benefit from predator control, which has been primarily aimed at coyotes. To this point in each study, cost/benefit analyses render coyote control as an ineffective strategy for improving fawn recruitment. The Utah Division of Wildlife Resources implemented a coyote control management plan in 1997 (Gill et al. 1999). Coyotes were controlled at varying intensities in 15 herd units during 1997 and 1998. Winter fawn:doe ratios were higher in 1997 and 1998 than in 1995 and 1996 when coyotes were not controlled. However, this increase could not be attributed to the coyote control efforts. The experimental design was flawed, and fawn:doe ratios increased in Utah regardless of whether coyotes were controlled. In New Mexico, biologists from the Jicarilla Apache Reservation suggested that mule deer numbers increased from 1991 through 1999 as a result of predator control (Gill et al. 1999). However, the experimental design was flawed as well as the methods used to estimate deer numbers. Deer population counts were related only to number of hours flown while counting deer, and winter fawn:doe ratios did not improve despite coyote control. Connolly ( 1981) drew several conclusions regarding predator control management which are briefly summarized here: 1) careful localized study is required to determine whether observed predation is impacting deer numbers; 2) coyote and/or lion predation has not been documented as the principle cause of a mule deer population decline; 3) many predation studies may not have effectively controlled predators; 4) predator control is expensive yet cost/benefit analyses are lacking; 5) predator control may benefit deer populations that are below carrying capacity, but will not reverse deer declines that are a result of habitat deterioration. We drew several other reasonable conclusions from both past and present predator control studies: 1) predator control studies must incorporate experimental rigor in order to obtain useful results; 2) under circumstances when coyotes may be limiting deer populations, it appears very difficult and potentially cost prohibitive to effectively lower coyote densities on a management scale with currently available control techniques; 3) predator control will be ineffective in mule deer populations that are at or near carrying capacity (limited by habitat quality), where fawn survival is ultimately a function of density-dependence and not predation; 4) in predator control experiments, we typically cannot determine with much certainty whether habitat quality is ultimately limiting fawn recruitment, even when the predator control treatments are ineffective. Habitat Quality The importance of habitat quality and quantity for sustaining mule deer populations is well understood. In fact, various studies have provided considerable information regarding the components of quality habitat for deer; these studies include habitat selection (Ordway and Krausman 1986, Carson and Peek 1987, Kufeld et al. 1988, Bodurtha et al. 1989, Thomas and Irby 1991,"Armleder et al. 1994), diet composition/selection (Wallmo et al. 1973, Deschamp et al. 1979, Hartmann 1983, Campbell and �145 Johnson 1983, Gill et al. 1983, Kasworm et al. 1984, Sowell et al. 1985, Austin et al. 1994), nutrient analyses of forage (Bissell and Strong 1955, Smith 1957, Trout and Thiessen 1973, Urness et al. 1977, Tueller 1979, Bartmann 1983, Welch 1989, Austin et al. 1994), foraging preference theory (Nudds 1980, Hanley 1982, White 1983, Spalinger and Hobbs 1992, Parker et al. 1996, Hanley 1997), and energetics (Freddy 1984, Parker et al. 1984, Wickstrom et al. 1984, Hobbs 1989). It is generally accepted that most wildlife populations are limited by habitat in terms of carrying capacity, which incorporates all of the above components. At least theoretically, a deer population at carrying capacity cannot expand beyond its current siz.e, which makes carrying capacity a very useful parameter. However, given the complex, non-static relationships among biotic, physical, and edaphic factors of the environment, it can be very difficult and time consuming to quantify and track carrying capacity. In fact, carrying capacity of winter range continually changes as a function of the duration and severity of winter (Wallmo et al. 1977). Based on the concept of carrying capacity and its limiting factors, Wallmo et al. (1977) provided a model for evaluating deer habitat by quantifying the quality and quantity of forage in relation to mule deer requirements. Using our accumulated knowledge of deer habitat to qualitatively evaluate current Colorado deer ranges, it appears that habitat quality, and thus carrying capacity, has declined in some of these ranges as a result of habitat changes over time. Succession and disturbance are the principle components of habitat change. Generally speaking, mule deer are better adapted to earlier-seral habitats, particularly those that are part of a larger habitat complex in various successional stages (Bailey 1984). Disturbance-free communities will eventually succeed to later-seral or climax-type habitats, which have a lower carrying capacity for deer because of declining forage diversity and vigor. Thus, periodic disturbance may often be necessary for maintaining healthy deer populations. Fire suppression is believed to have fostered the expansion of late-seral, decadent habitats throughout many areas in the West. A particular concern has been the encroachment ofpinyon (Pinus spp.)-juniper (Juniperus spp.) into sagebrush (Artemisia spp.) habitats (Blackbum and Tueller 1970, Burkhardt and Tisdale 1976, Miller et al. 1999). Controlled bums and mechanical treatments have been used to restore various habitats to early-seral conditions (Bunting 1996, Riggs et al. 1996, Erskine and Goodrich 1999, Sorensen 1999, Stevens 1999). Following such habitat disturbances, deer have been found to prefer the disturbed habitat over the undisturbed habitat (Keay and Peek 1980, Farmer 1995). Prescribed fire in northern California improved black-tailed deer reproduction, which was considerably higher than in untreated habitat (Taber 1956, Taber and Dasmann 1958). Hobbs and Spowart (1984) increased the·nutrition in winter diets of mule deer following a prescribed fire in Colorado, which enabled greater foraging selectivity by deer. However, reintroducing fire into later-seral communities can potentially have negative impacts, given the increasing presence of exotic weeds. Some rangeland fires have perpetuated invasive weeds and substantially reduced browse species as a result (Loft and Menke 1990,"Clements and Young 1997, Bishop 1998). Thus, habitat treatments must be carefully planned and followed with reseeding to achieve desired objectives (Sheley et al. 1996, Goodrich and Rooks 1999, Svejcar 1999). Qualitative evidence suggests that habitat has declined in overall quality and quantity at the same time deer numbers have declined throughout the West. Clements and Young (1997) linked a declining deer population to habitat changes associated with grazing management, fire frequency, and invasion of exotic annual grasses. Similarly, Gill et al. (1999) discussed declining deer numbers in Colorado in relation to residential development, fire suppression, excessive herbivory from livestock and ungulates, and invasion of exotic plants. Various habitats have inevitably declined in productivity as a result of these factors, yet the impacts on deer populations have not been quantified. To better understand the implications of habitat quality and carrying capacity, we need to quantify how deer populations respond to changes in habitat. For management purposes, we need to improve our ability to actively manage habitat for the benefit of mule deer (Boyd et al. 1986). �146 Habitat vs. Predation There are two overwhelming problems in current deer management regarding predators and habitats. First, state agencies are becoming increasingly focused on predator control as a management solution, typically as a result of public and political pressure, without regard to site-specific factors affecting various deer populations or feasibility of predator control. Second, given the focus on predator control, research and management studies have not addressed whether improving habitat quality is a viable management solution for increasing deer numbers. The first problem may lead to unjustified and poorly planned predator control management at unrealistically large scales, as was done by the Utah Division of Wildlife Resources, which failed to effectively reduce predator numbers and therefore wasted valuable management dollars. Low fawn survival and declines in total deer numbers are not justification for predator control unless the deer population(s) are below habitat carrying capacity and predation has been identified as a major limiting factor (Connolly 1981, Ballard et al. 1999). If predator control is justified, it will not be beneficial for deer unless predator densities are sufficiently reduced, which has only been achieved with carefully planned control efforts over relatively small areas (Ballard et al. 1999). The bottom line is that experimental predator control studies cast a shadow of doubt on the utility of predator control as a large-scale management strategy for reversing declining trends in deer numbers and fawn recruitment. The question remains as to whether or not habitat quality is more of a limiting factor than predation in many of our deer herds. This question has rarely been rigorously addressed in past research and needs more attention given the current debate surrounding wildlife agencies across the West. The prevailing political tide is focused on predation as the overriding factor, yet there is no evidence to support that predators ar~ having an impact on Colorado's deer herds. We must determine whether habitat or predation is the more limiting factor before initiating a large-scale deer management program. The other question is whether fawn survival and recruitment can be increased by enhancing habitat quality in areas where habitat is perceived to be limiting. Much attention has been focused on predator control, which for numerous reasons previously discussed, appears to have limited applicability as a large-scale management strategy. However, virtually no studies have adequately assessed whether we can effectively improve habitat quality for deer to increase fawn recruitment and ultimately population productivity. lbis question has significant management implications for mule deer. Many biologists believe that the overall drop in deer numbers from the middle of the 20th century to the present is a result of declines in both habitat quality and quantity. Although predation may have slowed population recovery at various times and places, deer numbers are ultimately limited by habitat (Connolly 1981). It follows that improvements to habitat quality will provide a much greater long-term benefit to mule deer populations. Also, habitat improvements are self-sustaining for many years following treatment whereas predator control must be continually applied on an annual basis to have a long-term effect. Our proposed study will assess whether nutrition is ultimately more limiting than predation in a deer population with currently low fawn recruitment, and whether habitats can be manipulated to increase fawn survival and recruitment. The greatest management concern over mule deer is focused on herds below population objectives with low fawn recruitment. It is therefore sensible to select one of these herds to evaluate whether habitat/nutrition or predation is more limiting to the deer population. If habitat quality is identified as the ultimate problem, we must then determine whether we can improve the deer herd by manipulating habitat. Although various habitat complexes have been manipulated to benefit wildlife, deer responses have not been appropriately measured to determine if the treated habitat actually improved deer populations. Assessments of treated habitat have traditionally comprised arialyses of pellet-group counts, habitat selection, or forage selection pre- and post-treatment or between adjacent treated and untreated areas (Wallmo 1969, Wallmo et al. 1972, Keay and Peek 1980, Hobbs and Spowart 1984, Farmer 1995). These studies establish that deer used the treated habitat more than untreated habitat, or in some cases demonstrate that diet quality was greater in the treated �147 habitat, but they do not determine whether fawn survival or recruitment actually increased. Given the expense of treating habitat, we must ensure that such treatments will improve deer productivity to justify the cost. Mule deer management decisions with a biological basis incorporate knowledge as to what factors are limiting a·deer herd. Management decisions with a political basis are typically made without regard to biological considerations. The question is whether future deer management decisions will be based on political desires or biological data. The former may or may not benefit deer populations whereas the latter will provide a basis for increasing mule deer numbers as well as sport harvest. Although we must incorporate political decisions into our management programs, the Division of Wildlife will ultimately be held responsible for the future status of mule deer populations. Our only means of accountability is to ensure that our management decisions have scientific merit. This study allows the opportunity for the Division to obtain information necessary for making biologically justifiable management decisions for mule deer. B. OBJECTIVES 1. To conduct a one-year pilot study to assess the logistical feasibility of the proposed study herein and to gather preliminary data to improve the study's efficiency and experimental design. 2. To determine experimentally whether enhancing mule deer nutrition during winter and early spring by supplemental feeding increases December fawn:doe ratios and overwinter fawn survival. 3. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. Null Hypotheses: a. December fawn:doe ratios of deer groups that receive supplemental feed are not different from fawn:doe ratios of deer groups that do not receive supplemental-feed. b. Overwinter survival of fawns that receive supplemental feed is not different from survival of fawns that do not receive supplemental feed. c. December fawn:doe ratios of deer groups that utiliz.e habitat treatment areas are not different from fawn:doe ratios of deer groups that occupy untreated (control) areas. d. Overwinter survival of fawns that utilize habitat treatment areas is not different from survival of fawns that occupy untreated (control) areas. E. EXPECTED RESULTS There is an urgent need for information regarding the causative factors limiting mule deer populations that are currently below DAU (data analysis unit) objectives. This study will evaluate whether habitat or predation is the more limiting factor to fawn survival and recruitment on the Uncompahgre Plateau (DAU D-19), where December fawn:doe ratios have declined over the past 15 years. We will accomplish this by monitoring deer responses in relation to supplemental feed, which will be provided as a nutrition enhancement. We know that predators are killing fawns on the Uncompahgre Plateau (Pojar 2000, B. E. Watkins unpublished data). If this observed predation represents additive mortality, then the supplemental feed should not improve December fawn recruitment or overwinter fawn survival. In other words, it would suggest that predators are killing fawns regardless of their nutritional state. On the other hand, if the supplemental feed causes a beneficial response in the deer population, then predation is largely compensatory and not the main underlying problem. So if fawn survival and recruitment increases as a result of enhanced nutrition, without any manipulation of predator populations, we can assume that habitat is ultimately more limiting than predators. �148 If nutrition is found to be a critical problem, we need to evaluate management approaches for improving habitat quality. Given available information, we do not know whether habitat treatments benefit mule deer populations, even when they're designed to do so. This study will provide an experimental assessment of the effectiveness of habitat manipulations for improving deer populations. Results from the study will provide a quantitative basis for deciding which habitats to treat and how to treat them, by monitoring deer population parameters in response to various treatment techniques. The Division of Wildlife needs this information to plan management strategies for improving population productivity in Colorado deer herds. F. APPROACH 1. Pilot Study The primary purpose of the pilot study is to address a variety of logistical concerns that could impede both the quality and intent of the proposed study. If the pilot study runs smoothly or with only minor problems, then any necessary revisions will be made to the Program Narrative and we will pursue the actual study in the following year. On the other hand, if the pilot study reveals acute problems in proposed methodology that would prevent us from adequately testing our null hypotheses, then we will reevaluate the full-scale study. If possible, the Program Narrative will be modified to address these problems without compromising our experimental approach. Otherwise, a new experimental approach will be developed to address the same objectives, in which case we would not be able to pursue a full-scale study in the following fiscal year. The one-year pilot study will be very similar to the first year of the complete study described below, except that it will only comprise two experimental units and one response variable. The two experimental units will consist of a supplemental feed treatment area and a control area (Fig. 1). The single response variable will be December fawn:doe ratios, which will be measured the December following the pilot winter's treatments. We will capture and radio-collar 40 adult female mule deer in both the feed treatment area and the control area. This Program Narrative addresses the full-scale experiment, with specific references to the pilot study as necessary. 2. Experimental Approach a. Experimental Units Four areas on the Uncompahgre Plateau will be selected to create 4 experimental units (A-D) (Fig. 1). Treatments will be randomly assigned to the experimental units. The following criteria will be used to select experimental units: 1.) Deer densities (~50-80 deer/mi2): areas will be selected where deer densities are sufficient to meet sample size requirements within the experimental unit, while simultaneously selecting areas that will only require feeding less than ~500 animals during a normal winter 2.) Buffer zones: areas will be selected such that experimental units are separated by several miles of non-treatment area (buffers) to prevent deer from occupying more than one experimental unit 3.) Similarity: areas will be selected that comprise relatively similar habitat complexes and deer densities that are representative of the overall area 4.) Elk populations: areas will be selected that will minimize the number of elk present during normal winters Units B and C will be used alone during the pilot study, with Unit B receiving the supplemental feed treatment. In the full-scale study, Unit A will serve as a control area, that will not receive �149 any type of treatment throughout the study. Units Band C will be used to create a cross-over design with supplemental feeding. Deer will be fed on Unit B during the first 2 winters of the study, but not fed during winters 3 and 4. Deer will not be fed on Unit C during winters 1 and 2, but will be fed during years 3 and 4. Unit D will receive a habitat manipulation, which will consist of fire or mechanical treatment, or possibly a combination of both. Figure 1. Schematic representation of experimental units and their associated treatments. The pilot study will incorporate a supplemental feed treatment area and a control area. Supplemental feeding cross-over design will end after 4 years (not including the pilot study); monitoring in the habitat manipulation experimental unit and paired control area will likely continue for 2 additional years. Experimental units will be similar sized when initially selected. The mean deer density is approximately 50-80 deer/mi2 on the portion of the Uncompahgre Plateau where the study will be conducted. On average, 5 mi2 should contain anywhere from 250 to 400 deer, which is probably the minimum necessary to capture 40 does and 40 fawns from separate groups. Thus we will attempt to select experimental units that are at least 5 mi2 in size. The actual size of experimental units will ~ary, however, in relation to a particular treatment. Experimental units receiving the supplemental feed will need to remain relatively small to successfully feed all collared animals without feeding more than a total of ~500 deer. Maintaining the collared deer in a relatively small experimental unit should not be a problem because they will likely have smaller home ranges as a result of the feed. The habitat manipulation experimental unit will need to be larger to successfully treat enough habitat in a mosaic pattern where untreated habitat tracts remain within the unit. We will of course have to carefully monitor deer to ensure that they spend considerable time in the treated habitat. Assuming the manipulated habitat confers an advantage over adjacent untreated habitats, deer will likely demonstrate strong treatment site fidelity to capitalize on the more nutritious forage. Control areas can be even larger without impairing or biasing the experiment, and in the absence of feed or nutritionally enhanced forage, deer will probably utilize larger home ranges. Success of the study in terms of experimental unit size primarily depends on intervening space (buffer zone) between units. Theoretically, a control unit could be several times larger than a supplemental feed unit as long as the control animals do not enter any of the other experimental units. b. Response Variables The primary response variable will be fawn:doe ratios measured during the December following the previous winter's treatments. In other words, the fawns counted during December age classification will have been born the summer following the winter treatments, �150 and classified when they are 6 months of age. Fawn:doe ratios will be measured in Units B and C during the pilot year, and measured in each experimental unit during the initial 5 years of the full-scale study. That is, prior to the first winter treatment of feeding on Unit B in the pilot study, adult females will be radio-collared during the last half of November, and fawn:doe ratios will be estimated from the collared sample to test the procedure and to obtain initial pretreatment data. Ratios will then be measured in each of the following 5 Decembers to evaluate treatments in both the pilot and full-scale studies. Measurements will be continued for more than 5 years only on Units A and D to adequately evaluate the impact of the habitat manipulation on fawn:doe ratios. The second response variable will be overwinter fawn survival, measured directly from radio-collared fawns during the same winter as the treatments. Survival will be measured in each experimental unit for the first 4 winters of the full-scale study. Survival measurements will be continued for several more years in Units A and D to document the long-term impacts of the treatment. Overwinter fawn survival will not be measured during the pilot study. 3. Sample Size/Power Analysis a. Fawn:Doe Ratios The sampling unit of the proposed study is the same as the experimental units .. The primary response variable is the mean fawn:doe ratios of the radio-collared does wintering on the experimental unit of interest. We desire to detect an effect size, i.e., an increase in fawn:doe ratios in response to the treatments, in the range of 15 to 20 fawns per 100 does. These values are based on simple population models with overwinter fawn survival of 0.444, adult female survival of0.853, and December fawn:doe ratios of 66 fawns per 100 does to obtain a stationary population (Unsworth et al. 1999). The fawn:doe ratio for the Uncompahgre Plateau during the 1990's averaged approximately 40 fawns per 100 does (Fig. 2). 90 80 u, Q) 70 0 60 0 0 50 u, 40 0 ..... C: ~ co 30 20 LL 10 0 1982 1984 1986 1988 1990 1992 1994 1996 Year Figure 2. Post-season fawn:doe ratios for deer in DAU D-19, Uncompahgre Plateau, in southwest Colorado. 1998 �151 Fawn:doe ratios of the deer groups containing radio-collared animals will be the main source of variation in the study. Groups may contain non-reproductive females such as yearlings or barren old-age animals, and productivity per reproducing female varies. Based on surveys of DAU D-19 from 1992-96, the standard deviation of the fawn:doe ratio for groups with at least one adult female was 57, with a mean of 41. (Recent classifcation data from D-19 was not incorporated into the standard deviation estimate because fawn:doe ratios are now measured using quadrat classification as opposed to group classification.) Using an expected standard deviation of 57, the standard error of the mean fawn:doe ratio for 40 radio-collared does is 57/(40 1~ = 9.0, which is the expected standard deviation of measured fawn:doe ratios on each of the experimental units. We assessed power of the proposed experiment using SAS Analyst®. We used a two-sample I-test with a sample size of 4, representing the years of the study where treatment effects will be measured. The power of the design to detect an increase of20 fawns per 100 does is about 0.87 (Fig. 3). Another way to interpret this power estimate is to consider that the confidence interval on the treatment effect, e.g., effect of feeding, would not include zero 87% of the time for replications of the entire experiment. One source of variation has been neglected: sampling variance of the mean fawn:doe ratio of the 40 radio-collared does. This variance can be reduced by repeated helicopter surveys to estimate the fawn:doe ratio of the deer groups containing radio-collared does. Spatial variation between the 4 experimental units will also exist, but will be accounted for in the design and removed with the unit effect. Likewise, the temporal variation across years was included in the standard deviation of 57, but will be accounted for in the design by the year effect. Thus, we feel the power estimated in Figure 3 is reasonable for the proposed study. 1 0.9 0.8 0.7 L. Q) 0.6 ~ 0 a.. 0.5 0.4 0.3 0.2 0.1 -- -----... --- Increase in Fawns:100 Does: -- ·······10 ----15 .... - - - - -20 - - 25 --30 - 3 5 ...... ..... -40 ... - 2 3 4 Sample Size (years) 5 6 Figure 3. Expected power of detecting fill increase from 10 to 40 fawns per 100 does with 40 adult females collared per experimental writ, 8Ild a stfilldard deviation of the age ratio of 57. A power of 0.87 is slightly higher than the commonly accepted power of 0.80. A sample size of 35 radio-collared does in each experimental unit would achieve a power of approximately 0.80 using the previously described power calculations. However, it is likely that some fraction of the radio-collared does in December of one year will not be alive to be sampled in December the following year. Additionally, a few of the radio-collared animals may not remain on the experimental unit where they were initially radio-collared. Animals that switch experimental units during mid-winter will be discarded from the study because they would not �152 represent either of the treatment areas that they inhabited. Thus, 40 radio-collared does per experimental unit provides a slight cushion for collared doe losses from one December to the next. The habitat manipulation experimental unit along with the control unit will be measured for more than 4 years because it is likely that deer will respond more slowly and less dramatically than with the supplemental feed treatment. Thus, given >4 years of measurements, additional power will be obtained in the evaluation of habitat manipulations. b. Overwinter Fawn Survival A sample size of 40 fawns per experimental unit per year will provide power of O.81 to detect a difference of O.15 in survival between 2 experimental units if survival on the control unit is 0.40. We expect to see an increase in fawn survival (effect size) of approximately O.15, because this is the difference measured in the density reduction experiment conducted by White and Hartmann (1998). 4. Procedures a. Capture Methods Deer will be captured using helicopter net guns (Barrett et al. 1982, van Reenen 1982) and baited drop nets (Ramsey 1968, Schmidt et al. 1978). Deer in the experimental unit receiving the supplemental feed will be captured primarily with drop nets, where the bait will be partially composed of the supplemental feed. Deer receiving the supplemental feed treatments may also be captured via anesthesia from a projected syringe (dart) using the following procedure. Feeding will be initiated in the appropriate experimental unit. We will monitor feed sites from a nearby blind, and use a dart gun/projectile syringe to anesthetize deer that accept the feed. Deer will be anesthetiz.ed with tiletamine HCI and zolazepam (Telazol®, 5 mg/kg) and xylazine HCI (2.5 mg/kg) delivered intramuscularly. There are two primary advantages of using baited drop nets and dart gunning to capture deer in the supplemental feed treatment areas. First, deer will have demonstrated a willingness to consume the feed prior to being captured, which increases the likelihood that these animals will utilize the feed through the winter. Second, we will be able to capture the desired number of deer over a smaller geographical area than with net gunning. If the 40 does and 40 fawns are captured over too large of an area, it will be very difficult to successfully feed all 80 animals on a daily basis while attempting to feed no more than a total of ~500 animals. Deer will be fitted with leather radio collars equipped with mortality sensors, which after remaining motionless for 4 hours, increase the pulse rate of received signals. Permanent collars will be placed on females, while temporary collars will be placed on fawns. To make collars temporary, one end of the collar will be cut in half and r~ttached using rubber surgical tubing; fawns will shed the collars after approximately 6 months. Fawn collars will be reused annually, which will reduce costs after the initial year of the full-scale study. Doe collars will be equipped with a rectangular piece of flexible plastic (Ritchey® neck band material) stitched to the top-side of the collar. The piece of flexible plastic will be engraved with a unique identifier than can be visually identified and interpreted from the air. The plastic identifier will be used to ensure that each doe is accurately and individually identified during helicopter age and sex classification each December. A uniquely numbered ear tag will be placed on both does and fawns. We will record the weight of each fawn, and collect blood samples from both does and fawns whenever feasible to evaluate disease prevalence. �153 b. Measurement ofFawn:Doe Ratios Approximately 40 adult females will be captured and radio-collared in Units B and C from late November through mid December prior to the pilot study. The following winter, 40 adult females will be radio-collared in Units A and D, and additional females will be captured in Units B and C to maintain a sample size of 40 collared does in each experimental unit. This will result in a total sample size of 160 does during the full-scale study. Radio-collared animals will be monitored through the winter to determine survival and fidelity to a particular experimental unit. Does receiving the supplemental feed will be monitored to ensure that they actually consume the feed on a regular basis. The December following each winter, the group of deer with each radio-collared doe will be located by radio-tracking from a helicopter. Each deer group containing the collared doe will be counted and classified by age and sex. The procedure may be repeated if necessary to reduce the sampling variance of the estimates of fawn:doe ratios for each experimental unit. Since ratio estimates will be based on individual deer groups, we will attempt to capture each of the 40 does from separate groups of deer scattered throughout the experimental unit. Multiple collared does in the same group of deer during December classification flights will reduce our functional sample size. Additional deer will be radio-collared each December to maintain sample sizes at 40 collared does per experimental unit. c. Overwinter Fawn Survival Approximately 40 fawns (6 months old) will be captured and radio-collared during late November through mid December ofeach winter on each experimental unit during the fullscale study. Fawns will not be monitored during the pilot study. We will avoid capturing sibling fawns to ensure that independent samples are used to evaluate overwinter fawn survival. Survival will be directly measured through the winter by radio-monitoring collared fawns to determine fate (live/mortality). Fawns will also be mo_nitored to determine fidelity to the experimental units and to ensure that animals receiving the supplemental feed actually consume the feed. d. Feeding The supplemental feed provided to the deer will consist of pelleted rations developed by Baker and Hobbs (1985). Feed will be periodically transported to the experimental unit receiving the treatment, where the feed will be stored on site in a large steel bin. Pellets will be distributed daily via snowmobiles or ATV's along established trails throughout the experimental unit to provide a food source for the entire deer population in the treatment unit. This will prevent dominant animals from restricting access to the food supply because of the large area over which pellets will be distributed. Pellets will be supplied ad libitum such that a small residual remains when the next distribution of food is provided. Collared deer will be carefully monitored to ensure that treatment deer are consuming the feed whereas non-treatment deer are not. Deer that do not regularly consume the feed will be withdrawn from the sample. Any non-treatment deer that find and utilize the feed will likewise be removed from the sample. Keeping the experimental units spatially separate should minimize the latter problem. The pelleted ration will be commercially produced in the form of 2x lx0.5-cm wafers (Baker and Hobbs 1985). Feed constituents (i.e. digestibility, protein, gross energy etc.) vastly exceed those of typical winter range deer diets; exact constituent values are provided by Baker and Hobbs (1985). When provided ad libitum, the feed should allow deer to meet or exceed �154 nutritional requirements for growth and maintenance (Ullrey et al. 1967, Verme and illlrey 1972, Thompson et al. 1973, Smith et al. 1975, Baker et al. 1979, Holter et al. 1979). The basis for feeding such high quality pellets is to ensure that the treatment (enhanced nutrition) is effectively delivered to the deer. Our intent is not to determine the exact level of nutrition necessary to increase fawn recruitment, but rather to determine if nutrition is a limiting factor to recruitment. If nutrition is in fact limiting, we will rely on the habitat manipulation treatment to evaluate what exactly can be done via management to increase fawn survival and recruitment. e. Habitat Manipulations Habitat will be manipulated in experimental unit D through collaboration with the Uncompahgre Ecosystem Restoration Project (UERP) committee, which comprises personnel from the Division of Wildlife, U.S. Forest Service, Bureau of ~d Management, and the Colorado West Public Lands Partnership. The UERP committee is using an experimental landscape approach to manipulate various habitats in a mosaic pattern throughout the Uncompahgre Plateau. We will focus our intensive deer monitoring on one of these habitat manipulations that will be conducted in experimental unit D. The vast majority of deer winter range on the Uncompahgre Plateau comprises pinyon pine (Pinus edulis)-juniper (Juniperus spp.) habitat. Considerations and techniques for manipulating pinyon-juniper habitats have been evaluated in various areas throughout the West (Monsen and Stevens 1999), including considerations for benefiting wildlife (Fairchild 1999, Miller 1999). We will treat habitat primarily using fire (Erskine and Goodrich 1999, Goodrich and Barber 1999, Roberts 1999) and mechanical treatments such as rollerchopping (Sorensen 1999). The type of treatment used in the experimental unit will be based on several factors, which include topography, seral stage of the habitat, soil type, moisture regime, and information from previous studies. Regardless of the technique employed, treated area will be reseeded with a grass-forb-shrub mixture that is beneficial for mule deer. Reseeding will also be used to prevent invasive weeds from establishing in the newly disturbed areas (Sheley et al. 1996, Goodrich and Rooks 1999, Svejcar 1999). The proximate objective of the habitat manipulations is to raise the overall forage quality on treated areas in order to accomplish the ultimate objective of increased fawn recruitment. In order to meet minimum maintenance requirements, deer must consume diets containing approximately 50% digestibility (Ammann et al. 1973) and 5-7% crude protein (Einarson 1946, Dietz 1965, Murphy and Coates 1966, Holter et al. 1979). Most winter range browse ranges from 25-50% digestibility and 5-10% crude protein (Welch 1989), which is why deer rely heavily on pre-winter fat and protein stores in order to survive the winter. However, because the nutritional value of winter forage is on the borderline of satisfying minimum maintenance requirements, relatively modest increases in digestibility and protein should be beneficial for both fawn survival as well as doe productivity. The majority of forage currently available to deer during winter on the Uncompahgre Plateau consists of older-aged pinyonjuniper and decadent sagebrush (Artemisia spp.), and oakbrush (Quercus gambelli) at the higher winter range elevations. The pinyon-juniper overstory has eliminated most understory forbs, grasses and shrubs. Thus, plant species diversity is very limited, plant communities predominantly comprise older shrubs, and even after "spring green-up" occurs, the quantity of green forage is lacking throughout much of the winter range. Given these field observations, we expect to increase the nutritional quality of winter range habitat by achieving the following objectives with habitat treatments: 1.) Return portions of late-seral pinyon-juniper habitats to earlier successional stages in a mosaic pattern across the landscape �155 2.) Restore vigor to decadent sagebrush communities 3.) Increase the quantity and diversity of other winter browse species (primarily through reseeding): mountain mahogany (Cercocarpus montanus), serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), gray rabbitbrush (Chrysothamnus nauseosus), green rabbitbrush (C. viscidiflorus) ... 4.) Increase the extent of younger-aged, mixed shrub communities (by accomplishing the first 3 objectives) 5.) Create a productive understory by increasing the quantity and diversity of various forbs and grasses (by freeing up nutrient resources and reseeding) Radio-tracking will be used to monitor deer use of the newly treated areas during each winter following the treatment. We do not necessarily expect manipulated habitats to receive extensive deer use the first winter after treatment, particularly following fire treatment where considerable biomass is removed from the site. Depending on snow conditions, responding vegetation may or may not be available to the animals. In short, it may require 2 or 3 years before treated habitat confers an advantage over untreated habitat for mule deer during winter. However, if December fawn:doe ratios and overwinter fawn survival do not increase after several years, and we verify that collared animals are using the treated habitat, we will quantify the nutritional quality of various forage species sampled from both the treatment and control units. Nutrition will be evaluated based on both in vitro dry matter digestibility (Tilley and Terry 1963) and crude protein (A.O.A.C. 1984). If nutritional quality of forage is not greater in tlie treatment unit than in the control unit, then we will reevaluate our techniques used to manipulate habitats. Treatment techniques used by the UERP committee will then be modified in an attempt to better manipulate habitat for mule deer. If, on the other hand,· the nutritional quality of forage is significantly greater in the treatment area than in the control area, then we can assume one of two things. First, the increase in nutrition was not of sufficient magnitude to increase fawn survival or December recruitment. Or secondly, the deer did not spend enough time feeding in the treated habitat to benefit from the increased nutrition. This could occur if deer perceived an increased level of wlnerability from the changes in habitat structure. We would attempt to differentiate between these two scenarios with intensive radio-monitoring. f Statistical Methods We will test for differences between experimental units and years using the following statistical model: Yi.Jc=µ+ t:;- +A+ af3J1c + eifJ7iJ, whereyiJc= fawn:doe ratio for the ith deer group in treatment combinationjk; i = 1, 2, ... , nJ/c (deer groups);/= 1, 2, 3, 4 experimental units (control, supplemental feed, habitat manipulation); k= 1, 2, 3, 4 (6) years; a/Jic= interactions among experimental units and years; and ei(Jk) = random error associated withyiJ1<. As stated earlier, we will obtain baseline data on each experimental unit by measuring fawn:doe ratios the December prior to implementing the first treatments. By not implementing the habitat manipulation until the second year of the study, two years of baseline data on Unit D will provide an estimate of the differences between this unit and the others. Likewise, the cross-over design on the feeding treatment allows estimation of the year effects on Units Band C, relative to the overall control Unit A (Fig. 1). A similar model will be used to analyze overwinter fawn survival, but a logit-link :function will be used in place of the identity link function in the above general linear model. �156 We will test for differences in fawn weights using a similar mcxlel as above, except the response variable will be fawn mass instead of fawn:doe ratios. Various studies have closely linked December fawn mass to survival probability (Bartmann et al. 1992, Bishop 1998, Unsworth et al. 1999). Fawn mass analyses may help us describe or better understand observed changes (or lack thereof) in population parameters as a result of the treatments. At the minimum, mean December fawn mass from each experimental unit will allow us to evaluate whether fawns are entering the winter treatments with equal survival probability. At least during the first year of the study, the mean mass of fawns collared in December should be similar among the various experimental units, assuming fawns are randomly captured. It is possible, however, that in successive years December fawn mass might vary among the experimental units as a result of previous winter's treatment effects. Although we cannot directly link 6 month old fawns to the previous winter's experimental units, it is certainly possible that many of those fawns' mothers occupied the same treatment areas the winter before given home range site fidelity. For example, fawns collared during the second winter in Experimental Unit B (which received the feed the winter before) could be heavier than fawns in Unit A (control). If so, it would suggest that not only has the probability of survival to December increased, but given the overall greater early winter mass, probability of overwinter survival has increased as well. In short, increased doe nutrition may not only increase December fawn recruitment, but yearling recruitment as well. G. LOCATION OF WORK Research will be conducted on the Uncompahgre Plateau in southwest Colorado, which comprises DAU D-19 and GMUs (game management units) 61 and 62. H. WORK ASSIGNED TO: 1. 2. 3. 4. Chad J. Bishop, Mammals Researcher, Colorado Division of Wildlife Gary C. White, Professor of Wildlife Biology, Colorado State University R. Bruce Gill, Mammals Research Leader, Colorado Division of Wildlife Len H. Carpenter, Southwest Field Representative, Wildlife Management Institute E. RESOURCE REQUIREMENTS Fiscal Year Equipment and Sue12lies Rental Services Service Contracts Vehicles FfE Requirements PFfE TFfE Total Costs 2000-01 $28,300 $45,200 $50,000 $11,046 1.00 0.5 $201,548 2001-02 $87,850 $147,900 $50,000 $11,046 1.00 1.00 $374,408 2002-03 $57,850 $116,400 $50,000 $11,046 1.00 1.00 $312,908 2003-04 $57,850 $116,400 $50,000 $11,046 1.00 1.00 $312,908 2004-05 $57,850 $116,400 $50,000 $11,046 1.00 1.00 $312,908 2005-06 $37,600 $65,200 $50,000 $11,046 1.00 0.5 $230,848 2006-07 $17,600 $50,000 $50,000 $11,046 1.00 0.5 $195,648 �157 F. REPORT DUE DATES FY2000-01 Pilot Results/Revised Program Narrative FY2001-02 Progress Report FY2002-03 Progress Report FY2003-04 Progress _Report *FY2004-05 Progress Report FY2005-06 Progress Report *FY2006-07 Completion Report 8/1/01 8/1/02 8/1/03 8/1/04 8/1/05 8/1/06 8/1/07 *Supplemental Feed portion of experiment will be completed in FY2004-05. Monitoring of habitat manipulation experimental unit and control area will likely continue for 2 more years unless corresponding hypotheses can be adequately tested beforehand. We estimate to finish the completion report for the entire study following FY2006-07. G. LITERATURE CITED Ammann, A. P., R. L. Cowan, C. L. Mothershead, and B. R. Baumgardt. 1973. Dry matter and energy intake in relation to digestibility in white-tailed deer. Journal of Wildlife Management 37:195-201. Armleder, H. M., M. J. Waterhouse, D. G. Keisker, and R. J. Dawson. 1994. Winter habitat use by mule deer in the central interior of British Columbia. Canadian Journal of Zoology 72: 1721-1725. Association of Official Analytical Chemists (A.O.A.C.). 1984. Official methods of analysis. Fourteenth edition. Association of Official Analytical Chemists, Washington D.C., USA. Austin, D. D., R. Stevens, K. R. Jorgensen, and P. J. Urness. 1994. Preferences of mule deer for 16 grasses found on lntermountain winter ranges. 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The biology and utilization of shrubs. Academic Press, San Diego, California, USA. White, G. C., and R. M. Bartmann. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal ofWildlife Management 62:214-225. White, R. G. 1983. Foraging patterns and their multiplier effects on productivity of northern ungulates. Oikos 40:377-384. Wickstrom, M. L., C. T. Robbins, T. A. Hanley, D. E. Spalinger, and S. M. Parish. 1984. Food intake and foraging energetics of elk and mule deer. Journal of Wildlife Management 48:1285-1301. Workman, G. W., and J.B. Low, editors. 1976. Mule deer decline in the West: a symposium. Utah State University and Utah Agricultural Experiment Station, Logan, Utah, USA. �162 �163 APPENDIXB DRAFT EFFECTS OF LIMITED BUCK HARVEST ON MULE DEER SEX AND AGE RATIOS An A Posteriori Analysis Chad Bishop, Mammals Researcher Objective Determine whether significant reductions in buck harvest have improved buck:doe ratios and/or fawn:doe ratios in Colorado. Data Set lbis analysis focuses on mule deer populations occupying mountainous regions of Colorado, or those populations west ofl-25. Over the past 10 years, buck harvest restrictions were implemented in a number of Game Management Units (GMUs) within several deer Data Analysis Units (DAUs) in western Colorado (Table 1). Table 1. Deer DAUs and inclusive GMUs in western Colorado where buck harvest limitations were 1990 D-1 201 238 47 ,❖:-:-.-: 'ttltfNz'·:'\@f#@(tji 1992 D-14 44 666 157 1995 D-1 1, 2 123 21 21, 30 1219 595 i;E ,-4~™1e1iF-@!1@M?l,:::::il 1995 D-11 I used these various units to look at buck:doe and fawn:doe ratios an equal number of years before and after the harvest limitation was implemented. DAUs D-1 and D-11 were excluded from all analyses due to insufficient age and sex ratio data. Thus, my analysis of the effects of limited buck harvest is based on DAUs D-3, D-o, D-14, and D-19(GMU 61). I also looked at buck:doe and fawn:doe ratios in units where harvest limitations were not implemented prior to 1999. Again, I only used those DAUs with adequate sex and age ratio data available, which include: D-2, D-4, D-7, D-8, D-9, D-12, D-13, D-18, D-19(GMU62), D-20, D-21, D-22, D-24, D-25, D29, D-30, D-39, D-40, D-42, D-43, and D-51. I obtained nearly all harvest data and age and sex ratio data from the DEAMAN32 database. Data from 1997 and 1998 that was not available on my version ofDEAMAN was obtained from John Ellengberger. �164 Analysis Basic Methodology and Justification As now apparent, my primary goal was to determine whether a set of sex or age ratios prior to a buck harvest restriction differed from a set of corresponding ratios following the restriction. It seems logical, then, to think of a harvest treatment with two groups, or two treatment levels: pre- and post-harvest restriction (unlimited vs. limited buck harvest). I can see a couple ways to approach this analysis. One approach is to treat each ratio estimate as a sample observation, and then calculate a standard mean and variance of the ratios for each treatment category. In other words, follow standard analysis of variance procedures using only the ratio estimates themselves. However, each sex or age ratio estimate for a GMU or DAU has an associated standard error. Our confidence in the accuracy of any given ratio depends largely on the effort put forth for that particular classification. If we ignore this, then each measured ratio is assumed to be an equally accurate measure of the true value. Ideally, my analysis should incorporate the associated variance of each ratio estimate used to avoid bias. I therefore took two approaches: (1) I used Program CONTRAST to analyze age and sex ratio estimates and associated standard errors prior to and after the harvest restriction and (2) I used PROC GLM in SAS and did a standard analysis of variance using only the ratio estimates. Justification for these analyses follows. Program CONTRAST (Sauer and Williams 1989, JWM 53:137-142) is a generalized program designed to evaluate differences in survival based on survival rate estimates and associated standard errors. It is applicable to any type of rate estimates. Similar to my analysis here, it is desirable when estimates and associated standard errors derived from data are available, as opposed to having the raw data. It allows testing various hypotheses without ignoring the variance of estimates. As I alluded to above, the problem with analysis of variance is that the variances are ignored. I considered converting the age and sex ratios to rates, or proportions, which would be more similar to how survival rates are expressed. A typical buck:doe ratio (bucks/does) or fawn:doe ratio (fawns/does) can be expressed as a proportion: bucks/(bucks + does) or fawns/(fawns + does). However, the standard error calculated for an age or sex proportion, based on a binomial distribution, can be much more biased than the standard error estimator for an age or sex ratio. lbis occurs because of behavioral patterns in deer group formation, and resulting sampling schemes used to estimate age/sex ~tios where groups of deer are the sampling unit (Bowden et al. 1984, JWM 48:500-509). Thus, I chose to use the ratios and associated SE's. The chisquare statistic used in CONTRAST appears to be equally valid for analyzing age and sex ratio data. The same assumptions for survival or recovery rates within the confines of this statistic can be made for age and sex ratios given that the associated variance estimates are known. My second approach involved a standard analysis of variance, or multivariate analysis of variance, using buck:doe and fawn:doe ratios as the dependent variables. Although this analysis ignores the variance of each ratio estimate, it is not that different from many of the analyses we do. In many cases, samples obtained from field measur~inents have an associated error that we do not quantify. In other words, it is not uncommon for raw data values to only be an approximation of the true value. Quantifying the digestibility of forage is an example. Our measured digestibility of a plant sample is only an estimate of the true value, yet quantifying an appropriate variance for each individual sample is difficult to do. Based on this line of reasoning, I felt it appropriate to do an analysis of variance using only the ratio estimates as raw data points. It follows that some caution should be used in interpreting the data since we know beforehand that the accuracy of ratio estimates vary, yet this variance is not being accounted for. Program CONTRAST In my analysis of sex and age ratios, I chose to use an equal number of years before and after implementation of the harvest restriction. I began by analyzing each DAU individually because harvest limitations were implemented at various times. I then incorporated each of the DAUs into one analysis by �165 using buck:doe and fawn:doe ratios for 4 years prior to harvest limitation and 4 years following the limitation. This was decided based on the DAU with the least number of years of post-treatment data, D3. Thus, for this analysis of combined data. the 4 years pre- and post-harvest treatment were not necessarily the same (D-3: 1991-94/1995-98; D-6: 1987-90/1991-94; D-14 and D-19: 1988-91/1992-95). Buck:doe ratios increased following limited harvest in each DAU except for D-19, where buck:doe ratios declined (fable 2). Conversely, fawn:doe ratios declined following implementation of limited harvest in each of the DAUs (fable 3). Table 2. Results of analyses contrasting buck:doe ratios pre- and post-implementation of limited harvest ._ ' •. - =--- CO, = Pm-.:m .- C • - _z •• ,r.: .>:. ·:, ..... ·.• D-3 1991-98 18.9 26.4 D-14 1985-98 18.7 23.0 6.22 .013 D-3, D-6, D-14, D-19(GMU 61) 4yrsPre-& Post-Limit 15.8 18.3 6.10 .014 Table 3. Results of analyses contrasting fawn:doe ratios pre- and post-implementation oflimited harvest in ~Vi;;;W DAL~ i l l ~ ~ 4 : a ( ' u~ Pi~~ CO~==nL.\ST (~:~ ~:f "WHJm~~ l~), D-3 1991-98 D-14 1985-98 D-3, D-6, D-14, D-19(GMU61) 4 yrs Pre-& Post-Limit 56.1 48.1 59.4 45.3 95.07 <.001 (Multivariate) Analysis of Variance using PROC GLM in SAS DAUs D-3, D-6, D-14, D-19(GMU 61) I analyzed the same data using PROC GLM in SAS without incorporating the associated variance estimates. Buck:doe and fawn:doe ratios were the dependent variables while buck harvest was the independent variable. Buck harvest was treated as a categorical variable with two levels: (I) pre-harvest limitation and (2) post-harvest limitation. Results are reported for buck:doe and fawn:doe ratios separately based on the respective ANOVA's. However, each significant result reported from an AN OVA is protected by a significant overall MANOVA test. Failing to incorporate the standard error with each ratio estimate apparently resulted in a less efficient analysis. The change in buck:doe ratios following the harvest treatment was only significant in DAU D-3 (P = 0.020). The other comparisons among buck:doe ratios pre- and post-harvest treatment were not �166 significant (Table 4). Declines in fawn:doe ratios following the harvest restriction were significant in 3 of the analyses while not significant in DAUs D-3 and D-14 (Table 5). Table 4. Results of analyses contrasting buck:doe ratios pre- and post-implementation oflimited harvest in ~e·,r~t"~ DAU:!l. in lilii"i;:;~te,m Ql)ki,radl;l! mii:ini ~, ooaly~.i!.I ofv,arian~ mSAS_ D-3 1991-98 1;;;:;:;:;sMEi~Bf§J!m;;;.;;~;£f~:;;:;:;:;;:;112;_ D-14 18.9 26.4 11.39 .020 =~;i;t:;:·:::-=::#1111-=-?:!J!!!;tt~·:::!~t~iJ:~r··m_Yim'..='._=:=1:;~i:~·=mi@====t=mt~}·tfi~;:=::-:-:---:-:tti@:i:w=·\\,·.=.:.~=:5:~:mmmm}t;:t; 1985-98 18.7 23.0 1.61 .237 ;i-i·l·itllC, .:-,;;:;,:'.=;::.:1-::;:~J,l·:·1l·l·l:l·::1l·l1•gi1i,l;;!;;l~:-l·l·11;!-i!:•:-J-:-l-1i·l:·:·~1l-··!·11~w.:···l·l·l·l·:·l::::·ili l·l::·:·l·l····-11!1l::-:-:-:-:-:1J·il ~i-l•l-l-l-l-i:·J,·~:-~11il-1:-l-·-·_:.J.ili :·i·:·:·1:·:·11ii-i-l i-1l-l·J,·1~1l·l·l·li•l-i-i-it;llilil·li~l-i·l·l l ·l··- D-3, D-6, D-14, D-19(GMU 61) 4 yrs Pre- & Post-Limit 15.8 18.3 0.88 .357 Table 5. Results of analyses contrasting fawn:doe ratios pre- and post-implementation oflimited harvest . i,~1 ~v~r.a.l DAU~ i,!11 W~i;)f"fl C'\cilo:r~uk, ttiii!l'!:g :1m ~rn:thi~i~ ofl,i'.,!!;fiii"...-ic.:~ :i,rn S.ASL D-3 1991-98 56.1 48.1 3.42 .124 === :·!:·l·!::l:l:!··:::::!!l:l:!j·:::·!·!··:!··:I!!!!'~~,-!-::!·!·ll!!!·l~!:l·1!!~1~J.1::! D-14 1985-98 ~iinaiiiiiijiiii~ii~mifo1: .,. . D-3, D-6, D-14, D-19(GMU 61) 4 yrs Pre- & Post-Limit' 59.1 51.6 2.46 .151 45.3 15.87 <.001 ::i1iijiil1l!1:~ff-ii!iii1:i·i:i:i:-;~:iii·t,~-5 9 _4 Results from the chi-square analysis (Program CONTRAS1) are probably more informative because more infonnation was provided by incorporating the standard errors of ratio estimates. Nonetheless, both analyses indicate that buck:doe ratios, overall, have modestly increased following restricted harvest; and fawn:doe ratios have significantly declined despite the conservative buck harvest. All DA Us west ofl-25 with sufficient age and sex ratio data available Up to this point I have not included any data from units without harvest restrictions prior to 1999. My goal here is to compare buck:doe and fawn:doe ratios from the units with restricted harvest to those where harvest was not restricted. I once again used a multivariate analysis of variance with buck:doe and fawn:doe ratios as the independent variables, and as before, I will only report the univariate statistics. Since I combined all of the data into one analysis, I adopted the same procedure I used previously in selecting what data should be used: 4 years prior to and 4 years following the harvest limitation (based on the fact that D-3 only has 4 years of post-treatment data). Thus, the same data will be used for DA Us D3, D-6, D-14, and D-19(GMU 61) as used in the previous combined analyses. For all DAUs without harvest limitations, I used age and sex ratio data from 1991-98. I used 2 independent variables. The first is whether or not buck harvest was limited in each DAU prior to 1999: (1) yes or (2) no. The second �167 variable is a categorical time variable: (I) 1991-94 (or 4 yrs pre-harvest treatment for DA Us D-6, 14, 19) and (2) 1995-98 (or 4 yrs post-harvest treatment for DAUs D-6, 14, 19). Tp.us the model I used is: YJ11c = M + QJ + flx + !dl;1c + .iiutcJ where i = I,2, ... , n11 (replicates),j = I, 2 (DAU with, or without, harvest limitation), and k = I, 2 (199194/pre-harvest treatment or 1995-98/post-harvest treatment). My principal concern with this analysis is to determine whether there is a significant interaction. If limited harvest had a significant effect on buck:doe ratios, I would suspect ratios to increase from the first time category to the second time category for the DA Us where limited harvest was implemented. Conversely, I would suspect ratios to remain constant or decline from the first time category to the second time category for the DA Us where harvest was not limited. There were no significant differences among buck:doe ratios. Buck:doe ratios increased in the harvestrestricted DA Us after harvest was limited while ratios remained constant in the unlimited harvest DAUs, but the interaction was not significant (P = 0.348) (Fig. I). Fawn:doe ratios declined significantly from the pre-harvest treatment to the post-harvest treatment time period (P < 0.001). The interaction was significant (P = 0.006), with fawn:doe ratios declining much more dramatically in the limited harvest DAUs than in the unlimited harvest DAUs (Fig. 2). This indicates that buck harvest is probably of little concern in terms of fawn recruitment. Other factors are clearly affecting the deer populations in the DAUs where limited harvest was implemented. - DAUs without Limited Harvest • • • • • DAUs with Limited Harvest 20 18.3 •••••• 0 ~ 18 0:: Cl) 0 0 ~ 0 :::, m 16 17.3 - - - - -..-.~..:-:.....--··-- 17.5 ••••••• 15.8 14 Interaction not significant (P = .348) C: ca Cl) ~ •••••• 12 10 1991-94 1995-98 (Pre-Harvest Treatment} (Post-Harvest Treabnent} Figure 1. Mean buck:doe ratios in DA Us with and without harvest restrictions implemented prior to 1999. 1991-94 represents pre-harvest treatment while 1995-98 represents post-harvest treatment. �168 - • • • • • DA Us with Limited Harvest DAUs without Limited Harvest 70 .....ca0 Cl'.:'. 65 60 59.4 55 53.6 Q.) 0 0 C ~ ca 50 C ca Q.) 45 ~ 40 •• •• - •• •• LL •• •• •• •• •• . .. •• •• •• -49.8 •• •• •• 45.3 Significant Interaction ( P = .006) 35 1991-94 (Pre-Harvest Treatment) 1995-98 (Post-Harvest Treatment) Figure 2. Mean fawn:doe ratios in DA Us with and without harvest restrictions implemented prior to I 999. 1991-94 represents pre-harvest treatment while 1995-98 represents post-harvest treatment. Discussion and Conclusions Limited harvest in DAUs D-3, D-6, D-14, and D-19(GMU 61) have resulted in modest increases in buck:doe ratios overall. However, buck:doe ratios in D-19 (GMU 61) declined despite conservative harvest. There are several reasons why this may have occurred. First of all, GMUs 61 and 62, which together comprise DAU D-19, likely represent a single deer population, at least on summer range. Managing only half of the DAU, or half of this deer population, for limited harvest may have lessened the likelihood that buck:doe ratios would respond positively to the reduced harvest. Other scenarios could also be presented as reasons why differential harvest management in D-19 could influence the observed decline in buck:doe ratios in GMU 61. On a different note, declining buck:doe ratios in 61 could be another indicator of a much larger problem affecting the Uncompahgre deer herd. This is especially true when the declining fawn: doe ratio is taken into account. It is important to point out here that the 1999 buck:doe ratio estimate in GMU 61 was 21.3, which is much higher than has been observed over a number of years. The 1999 buck:doe ratio in GMU 62 dramatically increased as well (27 bucks/100 does). Interestingly, this coincided with the 1999 harvest limitation in GMU 62, which is the first time both GMUs in D-19 have been managed for conservative harvest. When I removed D-19- GMU 61 from the combined analysis of limited harvest units, there was of course a greater increase in buck:doe ratios. With D-19-0-MU 61 removed from the analysis of all DAU data, the interaction between lirnited/unlimi~ed harvest DAUs and pre/post harvest treatment was more pronounced, although not significant (P = 0.106). Limited buck harvest has had no effect on fu.wn:doe ratios. In fact, fu.wn:doe ratios have declined more rapidly in DAUs with limited harvest than those with unlimited harvest. Clearly, other factors of much more importance are affecting these populations. Based on this analysis, it-is very difficult to argue that �169 declining buck:doe ratios are a primary cause for declining fawn recruitment and declining deer numbers. If anything, low buck:doe ratios may be yet another indicator of declining herd productivity. In conclusion, substantial limitations on buck harvest is likely an effective management strategy for increasing the number of bucks in a population. However, buck:doe ratios have increased slowly in these limited harvest units. The judgment as to the effectiveness of this strategy depends on how much hunter opportunity is sacrificed. It seems logical to manage a segment of our DAUs for limited harvest, thereby increasing success rates of those hunters that draw a license while also increasing their chances for shooting a trophy animal. The remaining DAUs should then be managed for much more liberal buck harvest to provide as much hunter opportunity as possible. In other words, a balance needs to be achieved between providing quality hunting (in terms of success rates and trophy buck numbers) and hunting opportunity (in terms of hunter days afield). This will become an increasingly difficult management challenge in the future as Colorado's human population continues to grow along with further inevitable development of habitat. Conversely, limited buck harvest does not appear to be an effective management strategy for improving fawn recruitment or population productivity. For this objective, our management and research efforts must focus on other variables. Graphs presenting the basic data from limited harvest DAUs DAU D-3, GMUs: 6 16 161 17 171 Age and Sex Ratios Before and After Limited Harvest, 1991-98 . . Buck Harvest en a, ~ lfll Fawns:100 Does la Bucks:100 Does 600 500 70 488 56.1 48.1 ca ::c .:.::: u :s m 'ii :s C C < ci> ~ 60 400 50 en 0 ; cu ~ )( -< a, 40 300 u, a, C) 30 C :s 200 20 ::c 10 D.. en 100 0 Before Limited Harvest (1991-94) After Limited Harvest (1995-98) 0 0 �170 DAU D-6, GMU 10 Age and Sex Ratios Before and After Limited Harvest, 1983-98 Ill Buck Harvest -., CD ~ - Fawns:100 Does b~~,d Bucks:100 Does 600 80 522 68.5 70 500 60 C'CJ :::c .x 400 50 u :::, m ci :::, C C <( Cl > <( 300 40 30 200 20 0 .:: ;;_ ,c CD u, CD Cl -., <( C :::, :::c 0 100 0 ., 10 Before Limited Harvest (1983-90) After Limited Harvest (1991-98) a. 0 DAU D-14, GMU 44 Age and Sex Ratios Before and After Limited Harvest, 1985-98 Ill Buck Harvest -., •- Fawns:100 Does Mffil'fl Bucks:100 Does 70 800 700 666 59.1 60 CD ~ C'CJ 600 .x 500 C C <( Cl > <( 50 a:: 40 - 400 ·30 300 ,c u, CD Cl -...., <( C :::, 20 200 10 100 0 C'CJ CD :::, m ci :::, 0 .:: :::c u ., Before Limited Harvest (1985-91) After Limited Harvest (1992-98) 0 :::c 0 a. �171 DAU D-19, GMU 61 Age and Sex Ratios Before and After Limited Harvest, 1985-98 - Buck Harvest en Cl> ~ 1200 - Fawns:100 Does b::::::::::::d Bucks:100 Does 60 53.8 50 1000 C'CS C'CS :::c ~ 40 800 33.3 u :::, m 'ii :::, C C <( CJ) ~ en 0 .::: )( Cl> en 600 30 400 20 200 10 0 0:: Cl> CJ) <( C :::, :::c en 0 a. 0 Before Limited Harvest (1985-91) After Limited Harvest (1992-98) DAU's: D-3, D-6, D-14, D-19(GMU 61) Age and Sex Ratios 4 Years Before and 4 Years After Limited Harvest 1111 Buck Harvest Ill Fawns:100 Does EEi] Bucks:100 Does en Cl> ~ C'CS :::c 2800 70 2400 60 2000 50 0:: 40 - 45.3 m 'ii :::, C C <( C'CS )( 1600 en Cl> CJ) - 30 <( 800 20 :::c 400 10 a. 1200 C :::, 0 en Q ~ .:: Cl> ~ u :::, en 0 Before Limited Harvest After Limited Harvest 0 0 �172 �173 APPENDIXC DRAFf ESTIMATE OF COLORADO'S CURRENT MULE DEER NUMBERS How Many Deer Are There? Chad Bishop, Mammals Researcher Objective Estimate the current number of mule deer in the state of Colorado by extrapolating deer density estimates from quadrat population counts to the estimated amount of winter range in Colorado. Background Our current estimate of the total number of mule deer in the state of Colorado is derived from population models for each deer data analysis unit (DAU). The total number of deer is estimated by summing the individual population projections for each DAU. This is a rough estimate given that a number of the DAU models are built from insufficient data. We cannot appropriately measure all relevant population parameters in each DAU due to budget and logistical constraints. Given this inherent limitation, our current ( 1998) post-hunt population estimate of ~526,000 deer is based on the best information available. However, a number of our constituents believe this figure is too high. In essence, I believe they question our ability to predict total deer numbers from models. Population models can be complex and difficult to understand, particularly to those who lack a statistical or quantitative background. So it comes as no surprise that some sportsmen would doubt our model estimates, particularly when those estimates differ from their own preconceived notions. The purpose of this analysis was to estimate statewide mule deer numbers by extrapolating deer density estimates from DAUs where we have post-hunt population counts to other similar deer winter ranges in the state. Specifically, the number of deer per square mile measured in certain DAUs was applied to the total square miles of deer winter range in Colorado to estimate a total number of deer. In this manner, no models are used and the estimates are based on direct observations of deer/mi2. This procedure also allows us to evaluate whether our current model estimate of deer numbers is reasonable. There are definite weaknesses to this approach. First, estimates of deer density are absolutely relative to the amount of area designated as winter range. In other words, the legitimacy of the analysis depends on how accurately mule deer winter range has been delineated, and more so, whether the standards used to designate winter range were consistent from one biologist to the next around the state. This is a formidable task since the area used by a deer population during winter varies as a function of several environmental variables. Fortunately, similar criteria were used by biologists throughout the state to delineate mule deer winter range, which provided a degree of consistency from one DAU to the next. Another concern is that there is no rigorous way to evaluate whether deer densities measured in one DAU are representative of adjacent DAUs. As with the population modeling approach, this is an inherent limitation since we cannot measure all population parameters in every DAU. The analysis presented here is another approach to estimating the total number of deer in Colorado given the information we have available. The primary benefit of this analysis is that the public should be able to easily understand how the estimate was derived. �174 Methods Winter Range Area The total area (mi 2) of winter range in Colorado was determined for each GMU and DAU from the current mule deer winter range spatial data located on the Colorado Natural Diversity Information Source (NDIS) internet site: http://ndis.nrel.colostate.edu/ndis/ftp html site/statewide ftp.html (file: mule_deerst.tgz). The spatial data layers contained in the file, corresponding to mule deer seasonal activity ranges, were developed through a combined effort among DOW's WRIS (Wildlife Resource Information System) Biologists and Area Terrestrial Biologists. The winter range layer was developed according to the following criteria: 'lhat part of the overall range where 90% of the individuals are located during the average 5 winters out of 10 from the first heavy snowfall to spring green-up, or during a site specific period of winter as defined for each DAU". I used PC Arc/Info to combine the mule deer winter range spatial layer with the GMU-DAU spatial data layer (also obtained from the NDIS website), and then used the combined data layer in ArcView to estimate square miles of deer winter range by GMU and DAU (Fig. 1, Table 1). }o~,, l_E.-,.,,,.__;.:,:_ir--,....,......_· .. ~ · ,: gJ ·., ~~t~: D-47 D-46 D-28 Rm Winter Range Figure 1. Spatial distribution and area of delineated mule deer winter range by deer DAU in Colorado. �175 Table 1. Delineated mule deer winter range (W.R.) in square miles by GMU and DAU in Colorado. Deer Deer DAU GMU W.R DAU GMU (mi2) 1 2 201 Total 3 301 4 441 5 14 214 Total 6 16 161 17 171 Total 7 8 9 19 191 Total 87 88 89 90 93 95 97 98 99 100 101 102 Total 10 11 211 12 13 131 231 22 23 24 Total 32 1033 125 1190 533 334 156 64 32 1 2 1122 190 40 119 85 38 473 31 138 189 138 291 787 70 211 275 319 286 263 347 1038 741 298 522 373 4744 615 581 295 94 89 9 19 750 175 1 2014 15 35 36 45 Total 18 181 27 28 37 371 Total 20 21 30 Total 41 421 42 Total 43 47 471 Total 44 48 481 56 561 Total 49 57 58 581 59 Total 39 46 51 461 Total 40 61 62 Total W.R Deer DAU GMU W.R Deer DAU GMU (mi2) (mi2) 53 111 54 167 74 m@t».:t!HM 55 551 0 353 Total 60 85 70 96 71 69 711 83 83 Total 66 9 67 425 543 Total 68 608 397 681 1005 Total 118 29 38 104 317 Total All 539 143 72 73 13 Total 0 75 156 751 128 77 33 771 91 78 126 51 Total 301 83 218 85 851 255 140 492 568 Total All 278 2024 69 42 84 47 86 861 250 78 Total 80 459 81 488 626 Total 76 683 79 1308 Total .124 280 114 500 185 501 299 Total 310 63 1012 64 7 65 329 Total 1347 it.w.Uti 31 205 32 228 Total 433 33 257 25 230 26 487 34 227 Total 198 91 425 92 0 94 951 0 248 96 248 Total 301 150 102 302 t88.N All 317 105 1171 277 106 930 Total 264 511 512 116 1309 Total 0 ,@I».5tm 411 52 171 521 921 153 Total 151 lOfStm 74 1589 741 231 Total 260 491 63 252 '315 W.R (mi2) 11 219 490 230 81 185 266 261 126 387 187 77 62 31 170 63 72 92 87 234 547 37 227 212 658 96 28 124 62 107 63 232 33 467 499 �176 Mule Deer Density Estimates Conceptually, it is simple to estimate the total number of deer statewide by extrapolating several deer density estimates to the total amount of Colorado winter range: calculate a mean deer density and multiply it by the total square miles of winter range. However, we can be fairly certain that deer density varies across Colorado, and so using a single mean density may not be the best approach. Ideally, deer DA Us should be grouped according to ecological similarities such that deer density is somewhat similar across all winter range in the DAU grouping. Density estimates measured in one DAU would then be representative of the other DA Us in the group. The inherent limitation is that density estimates are needed for at least one of the group's DA Us. Thus, these DAU groupings are dependent on data availability. Mule deer density estimates were obtained from the DEAMAN database (Table 2). These estimates are not corrected for sightability bias, and therefore should represent conservative estimates of the true deer density. I took a several tiered approach to estimate statewide deer numbers from the existing density data. My first objective was to delineate groups of DA Us based on ecological similarities, where at least one DAU in the group had some density estimates available over the past 15 years (Fig. 2). The 15-year time limit was arbitrarily set based largely on available data. For each DAU with density estimates available, I calculated a high, low, and overall mean for the 15-year period. The high mean was calculated from the upper half of recorded density estimates while the low mean was calculated from the lower half of density estimates. The overall mean was naturally calculated using all density estimates recorded in the DAU during the 15 years. In several of these DA Us, only 2 density estimates were available during the 15-year period (D-2, D-6, D-12, and D-42). D-2 and D-12 were the only source of density data for their respective DAU groups, which is a limitation of this first objective analysis. DA Us D-6 and D-42 were in the same DAU group as D-7, which had 6 density estimates available. Density estimates from D-42, which were much higher than those from D-6 and D-7, were applied only to winter range in D-42 and not incorporated into the mean for the DAU group. D-50, which incorporates the Air Force Academy, had only one density estimate available. It was not grouped with any other DAUs, though, because it typically has had higher deer densities than areas adjacent to it. Figure 2 depicts these DAU groupings, and also shows which DA Us provided density data to estimate deer numbers. Table 2 lists the actual density data. This approach enabled me to keep DAU groupings small and more ecologically meaningful, to maximize my use of density data available in DEAMAN, and to estimate a minimum and maximum number of deer for the past 15-year period. The primary drawbacks of this approach were twofold: 1) only limited data was available for some DA Us ·and 2) resulting estimates of total deer numbers do not represent current numbers. My second objective was to use density estimates from only those DA Us with recent data(~ 1995), which primarily corresponded to the intensive deer population monitoring areas (D-4: Red Feather, D-9: Middle Parle, D-16: Cripple Creek, and D-19: Uncompahgre Plateau) (Fig. 3). D-24 in southwest . Colorado also had recent density data available. This required reducing the number of DAU groups, with each group now containing more DA Us. Again, I attempted to group DA Us based on ecological similarities given the obvious constraint that most DAUs do not have any recent data available. The purpose of this analysis was to obtain a current estimate of total deer numbers using recent density estimates while maintaining DAU groupings that are at least somewhat similar from a habitat and deer ecology standpoint. My final objective was to apply a single mean deer density, calculated from recent estimates only(~ 1995), to the total winter range west ofl-25 (Fig. 4). This approach also provides a current estimate of deer numbers in Colorado, but removes any DAU groupings. In all of these analyses, I have focused only on deer populations west ofl-25. There are no density estimates from quadrat counts available for deer populations east ofl-25, yet we would anticipate deer densities to be quite different in a plains landscape. Therefore, in DA Us east ofl-25 that have mule deer winter range delineated, I applied density estimates from the current DAU population models. This was �177 done only to complete my estimate of statewide deer numbers based on delineated winter range. I realize that applying density estimates from biologists' population models directly biases my analysis as an independent estimate. But again, it was only done east ofl-25, which represents a small portion of the state's total mule deer numbers. Also, there is no winter range delineated in deer DAUs 28, 33, 45, 46, 47, and 48, although mule deer are present. I did not include these DA Us in any of my estimates of total deer numbers. Table 2. Mule deer density estimates (deer/mi2) measured during quadrat population counts in various DAUs. Estimates were obtained from the DEAMAN 3.2 database. Year 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 D-2 13.88 Low Mean High Mean Overall Mean Recent(:2: 1995) 13.88 73.46 43.67 D-4 D-6 28.35 32.14 31.17 28.53 46.73 Density Estimate bv DAU" D-19b D-9 D-12 D-16 7.55 25.83 21.51 D-24 D-42c D-50<1 22.78 9.89 35.73 47.64 37.97 25.18 70.09 30.82 10.86 19.16 27.07 17.02 73.46 D-7 32.67 32.57 32.23 149.16 71.96 12.57 8.33 6.96 3.45 46.83 17.58 24.40 14.21 5.19 22.36 24.66 22.28 33.48 19.02 3.5 25.38 35.57 30.47 22.32 17.02 27.07 22.05 6.25 34.40 20.33 20.34 31.29 26.49 29.07 34.17 46.83 47.64 47.24 4.35 9.43 7.40 4.35 19.45 34.17 22.39 34.17 18.30 26.80 22.55 19.02 71.96 149.16 110.56 70.09 70.09 70.09 8Density estimates from all DAUs included in the table were used in the first objective analysis. Only those DAUs with recent (:2: 1995) density data were used in the second and third objective analyses. 1,n D-19, the delineated winter range was modified prior to the 1998 quadrat count to make it more representative of observed wintering deer distribution, which decreased the size of the winter range by 446 mi2. Thus, the density estimate measured in 1998 was based on a smaller winter range area than the densities measured prior to 1998. "For the first objective analysis, I assigned D-42 to the same DAU group as D-6 and D-7 (Fig. 2). However, because density estimates for D-42 were much higher than those for D-6 and D-7, they were applied only to winter range in D-42. Density estimates from D-6 and D-7 were used to calculate a mean deer density for this particular DAU group. dFor the first objective analysis, D-50 was not grouped with any other DAUs (Fig. 2) because it typically has had higher deer densities than areas adjacent to it. The single density estimate for D-50 was applied only to winter range in D-50. �178 Figure 2. First-level grouping of deer DAUs shown by like-patterned blocks. Density estimates based on quadrat counts were obtained from the labeled DAUs to estimate the number of deer in each DAU block. Current population models were used to derive density estimates east ofI-25. Figure 3. Second-level grouping of deer DAUs shown by like-patterned blocks. Density estimates based on quadrat counts were obtained from the labeled DAUs to estimate the number of deer in each DAU block. Current population models were used to derive density estimates east ofI-25. �179 j ~-iO M'U:li!!! ,Oe~r :R,ii!in-0,,;---··· ---~-..c:,.J \ \ ~~=•~ h:!r ! II I -~ ~W7d Figure 4. Third-level grouping of deer DAUs shown by like-colored blocks. Density estimates based on quadrat counts were obtained from the labeled DAUs to estimate the total number of deer in all DAUs west of 1-25. Current population models were used to derive density estimates east ofl-25. Results First Obiective My first estimates of statewide deer numbers incorporated measured density estimates from the past 15 years. I used the low mean density estimates from each DAU to calculate a minimum mean estimate of statewide deer numbers: 421,894 deer (408,486 west"ofl-25). I used the high mean density estimates from each DAU to calculate a maximum mean estimate of statewide deer numbers during this 15-year time period: 807,472 deer (794,065 west ofl-25). My final calculation incorporated the overall mean density estimates from each DAU over the 15 years: 608,608 deer (595,200 west of 1-25). Second and Third Obiectives Using DAU groupings (Fig. 3) based on recent(:.!: 1995) density data, the estimate of total deer numbers currently in Colorado is 575,912 deer (562,505 west of 1-25)). Applying a single mean density estimate to all DAUs west ofl-25, the estimate of total deer numbers currently in Colorado is 581,331 deer (567,923 west ofl-25). Discussion The purpose of this "analysis" was to develop an independent estimate of total deer numbers in the state of Colorado that did not incorporate any modeling, but rather application of measured density estimates obtained from direct observation during aerial quadrat counts. The analysis could certainly have been done· differently, particularly in regards to how the DAUs were grouped together; but it appears that any reasonable method using the available density estimates would have resulted in relatively similar figures. First Obiective I used this 15-year data set to incorporate density estimates from a greater number ofDAUs, and to place upper and lower bounds on the possible deer numbers in the state. Using a mean of the lowest density �180 estimates measured during the past 15 years in various DA Us, we would still estimate there to be at least 400,000 deer in Colorado. Conversely, using a mean of the highest density estimates measured, we wouldn't expect the total population to have been much more than 800,000 deer in the recent past. Second and Third Ob;ectives The second and third objectives dealt with recent density estimates, which was my primary focus. I estimated there to be approximately 575,000- 580,,000 deer currently in Colorado, and approximately 560,000- 570,000 deer west ofl-25. The 1998 estimate of total deer numbers based on summation of individual DAU population models is approximately 525,000 deer (actual estimate: 526,406), and approximately 495,000 deer west ofl-25 (actual estimate: 496,603). The estimates are surprisingly similar given the large degree of error involved with either method of estimating Colorado's total deer numbers. In my perspective, these 2 independent estimates provide the Division of Wildlife with greater confidence that 500,000 to 600,000 deer is a reasonable estimate of the state's total mule deer population. At the very least, this analysis suggests that our population models are not drastically overestimating deer numbers, which is what some of our constituents have claimed. As I stated in the methods section, I did not include several southeast Colorado DAUs (D-28, D-33, D-45, D-46, D-4 7, D-48) in my statewide analysis because winter range had not been delineated. The total number of deer from 1998 population models for these DA Us is 16,695 deer. To make the DAU model estimates more comparable to my estimate, I subtracted these deer from the statewide total (526,406 16,695 = 509,711). Thus, with the southeast plains DAUs excluded, population models indicate approximately 510,000 deer, as compared to my estimate of 575,000-580,000 deer. This further suggests that we are not overestimating deer numbers using DAU population models. I also used another approach to evaluate the legitimacy of our population models. I calculated a mean deer density per square mile of winter range using the DAU model estimate of total deer numbers. This provides another check on the accuracy of the DAU modeling approach because the resulting mean deer density should be in the ball park of density estimates that have actually been measured from quadrat counts. There are 32,230 square miles of deer winter range delineated in Colorado (which excludes the southeast plains DA Us described above). The 1998 DAU model estimates would indicate a statewide mean density of 16 deer per square mile (510,000 deer/32,230 m.i2). This is clearly a reasonable density estimate, which lends further credence to the accuracy of the DAU population models. I also calculated the mean deer density for DAUs west ofl-25 only. There are 26,070 square miles of deer winter range delineated west ofl-25, and 1998 DAU population models indicate approximately 495,000 deer west ofl25. This gives a mean deer density of 19 deer per square mile for DAUs west ofl-25, which is also quite reasonable. The mean deer density measured from recent(~ 1995) quadrat counts in several deer DA Us west ofl-25 (D-4, 9, 16, 19, 24) is 22 deer/m.i2 . Summary Our current (1998) DAU population model estimate of statewide deer numbers is roughly 525,000 deer (526,406). When the southeast plains deer DAUs are excluded (D-28, 33, 45, 46, 47, 48), this estimate reduces to approximately 510,000 deer (509,711). My estimate, calculated by extrapolating measured deer densities to the total amount of deer winter range, which also excludes these southeast plains DAUs, is 575,000-580,000 deer. Considering only DAUs west ofl-25, our population models indicate there are approximately 495,000 deer (496,603)~ while my estimate using measured deer densities in select DAUs indicates there are approximately 560,000-570,000 deer west ofl-25. This latter comparison is more appropriate because the estimates are completely independent of one another. The DAU population models indicate that the mean deer density on winter range west ofl-25 is 19 deer/mi2. The mean deer density measured from recent(~ 1995) quadrat counts in several deer DAUs west ofl-25 (D-4, 9, 16, 19, 24) is 22 deer/m.i2 . The Division's current estimate of deer numbers from DAU population models is reasonable, if not conservative. It appears justifiable to assume there are roughly 500,000 to 600,000 mule deer in Colorado. � https://cpw.cvlcollections.org/files/original/617928ca0c2442937a5a268eef5ccce6.pdf 99de95b5e4bd63e6fa8862aab289f4f0 PDF Text Text 125 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT Smteof __ ~ ~C~o~lo~r=ad~o~ _ Cost Center 3430 Mammals Program Project No. W..:...:..,_-1=5=3--=-R=-_",1=-2_,.....-_ Work Package No. ___,3::....:0=0~1 _ Deer Management Task No. -'4'-_ Regulation of Mule Deer and Elk Population Growth by F ertilitv Control Period Covered: July 1, 1998 - June 30, 1999 -Author: Dan L. Baker Personnel: T. M. Nett, M. A. Wild ABSTRACI' We conducted preliminary investigations to evaluate the effectiveness and side effects of two contraceptive agents in captive mule deer and elk. We treated female mule deer with a permanent fertility control agent (GnRH-PAP) and female elk with a temporary, reversible contraceptive. In mule deer, serum luteinizing hormone (LH) levels were reduced by 55-78% for at least 6 months following treatment. For elk, serum LH concentrations were reduced to baseline levels for 90 days posttreatment. Body weight dynamics, blood chemistry, hematology, and social behavior of female mule deer and elk appeared normal compared to untreated animals. �127 REGULATION OF MULE DEER POPULATION GROWTH BY FERTILITY CONTROL . Dan L. Baker P. N. OBJECTIVES 1. To develop a practical and acceptable technology to inhibit reproduction in mammalian species which cause damage or constitute a significant public nuisance. 2. To demonstrate the feasibility of such technology in a field application. 3. To predict population impacts of alternative contraceptive regimens using simulation modeling. SEGMENT OBJECTIVES 1. To develop and test GnRH-toxin conjugate in captive mule deer and elk. 2. To develop a si~ulation populations. model to evaluate the ability of contraceptives to regulate large ungulate INTRODUCTION Segment Objective 1: GnRH-ToxinlAgonist Controlling the abundance of animals is fundamental to contemporary wildlife management. This is particularly true for wild ungulates. The most compelling motivation for regulating ungulate numbers is that overabundance causes problems that can be biological, economical, or political in scope (Jewel and Holt, 1981). Resolving these problems requires controlling population growth. Wild ungulate populations have traditionally been regulated by influencing death rates using controlled harvest or CUlling. However, there are an increasing number of circumstances where these traditional methods are not feasible. The use of fertility control to decrease birth rates is one of the most promising approaches to the long-term control of overabundant wild ungulates. During the past decade, research aimed at developing effective contraceptives for free-ranging wildlife populations has accelerated. These efforts have resulted in development and testing of a wide variety of potential contraceptive agents (Kirkpatrick and Turner 1985, Warren et aI. 1995). One of the most promising new non-steroidal, non-vaccine, approaches to contraception involves synthetic analogs of gonadotropin-releasing hormone (GnRH). GnRH is a molecule produced in the hypothalamus of the brain. It directs specific cells in the pituitary gland to synthesize and secrete two important reproductive hormones; follicle stimulating hormone (FSH) and luteinizing hormone (LH). These latter two hormones, known as gonadotrophs, control the proper functioning of the ovaries in the female and testes in the male. Analogs of GnRH have the potential to either permanently or temporarily inhibit reproduction. For most free-ranging wild ungulate applications, permanent sterilization or a combination of permanent sterilization and culling have been proposed as the most efficacious approaches to population management (Hone 1992, Garrot 1995, Hobbs et al. 1999, in press). For this application, �128 superactive analogs ofGnRH are coupled to a cytotoxin. The GnRH-toxin conjugate specifically targets the gonadotroph cells and permanently inhibits the ability of the cell to secrete FSH and LH. This approach has several potential advantages over other methods of contraception. These include: 1) a single treatment should permanently sterilize an animal 2) the same treatment should be effective in both males and females and in different mammalian species 3) GnRH-toxin conjugate will be metabolized from the body within a few days of treatment 4) the proteinaceous nature of GnRH-toxin conjugate eliminates the possibility of passage through the food chain. 5) the small volume required for effective contraception would facilitate microencapsulation and administration by syringe dart or biodegradable projectiles. In other situations where wildlife managers need to maintain flexibility in the use of fertility control, reversible contraception may be desirable. Examples of these situations include 1) wild ungulate populations exposed to periodic, severe, unanticipated winter mortality, 2) populations with low genetic variability, 3) populations that cannot be effectively monitored, 4) populations where public attitudes are opposed to permanent contraception, or 5) populations where non-lethal hunting recreation is a primary management objective. In these situations, superactive analogs of GnRH without the toxin subunit would be more appropriate. The inhibitory actions of long-term GnRH analog agonist on the ovulatory cycle of humans and other mammals is well-established (Casper and Yen 1979, Fraser 1983, Fraser et al. 1987, Concannon et al. 1991). Constant administration of high .doses of GnRH agonist results in down regulation of the pituitary GnRH receptors and suppression ofsecretionofLH andESH. Continued· treatment suppresses LH secretion, preventing the maintenance of normal.luteal function, and thus prevents viable pregnancy. Inhibition of ovulation caused by chronic administration of GnRH agonist has been successful in several species, including dogs (Vickery et al. 1989), cattle (Herschler and Vickery 1981), sheep (McNeilly and Fraser 1987), white-tailed deer (Becker and Katz 1995), and elk (Baker and Nett, 1999). Evidence from studies on pituitary receptors and gonadotropin content in experimental animals treated by long-term infusion ofGnRH agonist shows that sustained release is themost effective approach for temporarily suppressing pituitary-gonadal function (Clayton 1982, Sandow 1982). The practicality of this approach, however, is dependent upon development of a long-acting, slow-release preparation of agonist that can be remotely delivered. Recently, a practical mode of administration using subcutaneous implants has overcome the need for constant mechanical infusion of the analog. Slow release formulations of superactive GnRH agonist are now commercially available and have been shown to be effective in suppressing the pituitary ovarian axis for up to 6 months in a variety of mammalian species (Fraser et al. 1987, Asch et al. 1985). To our knowledge, only limited investigations have been conducted with either of these fertility control techniques on wild ungulates (Baker 1994, Baker et al. 1995, Becker and Katz 1995). Thus the specific objectives of these investigations were: 1) To evaluate the effectiveness and duration ofa single dose application of GnRH-toxin conjugate and GnRH - Agonist in preventing normal production of reproductive hormones in captive mule deer and elk. 2) To evaluate the effects of these contraceptives on the general health, blood chemistry, and hematology in mule deer and elk. �129 Segment Objective 2: SimulationModeling Using either culling or contraceptives to meet deer population objectives will require, wildlife managers to choose specific tactics of treatment Choices must be made on the number and age to treat, frequency of treatment, species, sex, etc, Decisions on the best tactics will depend on comparing the effects of alternative management actions on population behavior. To assist in these decisions, we developed an interactive simulation model of deer population dynamics to allow managers to evaluate alternative treatment regimes on simulated populations before applying them to real animals. Critical to model performance is knowledge of population demographics of the RMA deer herd and requires information on sex and age composition, recruitment, pregnancy rates, fetal sex ratio, and estimates of population density. This information together with knowledge of the habitat resources available to deer will provide a sound biological basis for management of deer populations at the RMA. METHODS AND MATERIALS GnRH- Toxin! Agonist Experiment 1: Evaluation of GnRH-PAP in mule. deer. Previously, we conducted controlled experiments with captive mule deer to determine the most effective dose of GnRH analog and the season of the year when treatments would be most effective in preventing fertility (Baker 1997). Here, we evaluate the effectiveness of GnRH..,P AP in preventing normal production of luteinizing hormone (LH) and the duration of effectiveness. We will evaluate contraceptive effectiveness in 4 ovariectomized mule deer. . Protocol for Ovariectomy in Mule Deer Tonic secretion of pituitary LH is the result of an interplay between a stimulatory input from the brain and an inhibitory feedback from the gonads. In the intact female, estradiol secreted from the gonads is a potent negative feedback hormone on LH secretion during anestrus (Goodman and Karsch 1980). Since measurement ofLH secretion is the primary indicator of GnRH-toxin conjugate effectiveness, it is imperative that female mule deer in this experiment be ovariectomized. Ovariectomies of mule deer were conducted at FWRF during the week of May 11, 1998. Deer were isolated and fasted for about 24 hr prior to surgery to alleviate regurgitation and aspiration of rumen contents. On the day of surgery, anesthesia was induced with intramuscular (IM) administration of 100 mg xylazine w/o 500 mg ketamine depending on response of the animal. Deer were then intubated and surgical anesthesia was maintained using a rebreathing circuit with isoflurane. Anesthetized deer were prepared for surgery by clipping hair in the abdominal area. They were then carried to a designated surgery area., placed in right lateral recumbency, and the surgical site prepared using standard surgical scrub. The surgical area was prepared with sterile towels and a surgical drape. Ovariectomy was performed via mid-ventral laparotomy and require 20 - 30 min per animal. Surgeons were attired in a sterile gown, mask, cap, disposable shoe covers and sterile gloves. Surgical assistants wore cap, mask, and disposable shoe covers. The ovarian artery was ligated prior to removal of the ovary. The incision was closed using a continuous suture and the skin closed with interrupted mattress stitches. We reversed anesthesia with yohimbine at a dose of 0.2 mg/kg (N). To minimize infection, deer were given ceftiofur sodium (1.1 mg/kg IV) administered perioperatively. Phenylbutazone (4 mglkg) was administered orally when deer were partially recovered from anesthesia �130 and every 48 hr for up to one week, if needed. Animals were placed in isolation pens for 24 hr and were observed every 5 min during recovery from anesthesia. This procedure followed ARBL Standard Operating Procedure #1 - Protocol for OvariectomylLuteectomy in Ewes and was modified for use in mule deer at FWRF. GnRH-toxin Conjugate Protocol Approximately 6 weeks following ovariectomy, GnRH-toxin was administered. Four ovariectomized deer were moved from 5 ha pastures to individual isolation pens, sedated with xylazine (100 mg 1M), and administered IV an optimum dose of GnRH-toxin (3 J-lgl50 kgBW). Deer were then placed in individual isolation pens and fitted nonsurgically with indwelling jugular catheters. Indwelling catheters remained in deer for up to 6 weeks and were checked and flushed daily. Deer remained in individual isolation pens for the first 6 weeks of the trial. This minimized tranquilization and general handling of deer and allowed daily evaluation of intake and general health of experimental animals. After 6 weeks, catheters were removed and deer were returned to 5 ha pastures. For subsequent trials, deer were removed from 5 ha pastures one day prior to GnRH trials and fitted with indwelling jugular catheters. Sampling was conducted the next day, catheters removed and deer returned to 5 ha pastures. One week after GnRH-toxin treatment, GnRH analog challenge trials were conducted. Experimental animals were moved to individual isolation pens and 3 J-lgl50 kg BW GnRI:i analog (Baker 1997) was administered through the indwelling cannula Blood samples (5ml) were collected at 0,30,60,90, 120, 180,240,300, and 360 min postinjection. After collections, blood was held at 4 C for 24 hours and serum obtained by centrifugation. Serum was stored at -20 C until analyzed. GnRH ' analog challenge trials were repeated each weekfor 6 weeks, then twice monthly for 3 months, then _' once monthly for 1 year. . Serum concentrations ofLH were quantified by means of ovine LH RIA (Niswender et al. 1969). The limit of sensitivity of the assay is 0.4 nglml. Response of the pituitary to GnRH-toxin conjugate was be assessed by 1) maximum LH response achieved postinjection, 2) total amount ofLH secreted (nglml/min); estimated by calculating the area under the LH curve, and 3) an LH response of < 2.5 ng/ml following GnRH challenge was be considered sufficiently low to prevent ovulation. Experiment 2: Evaluation of GnRH- Agonist (Lupron) in elk. Here, we conducted a pilot experiment to evaluate the effectiveness of GnRH agonist analog in suppressing ovarian function in elk. We determined the most effective dose and evaluated the duration of effectiveness. We also used these studies to evaluate the safety and side effects (if any) of treatment on a small number of animals before proceeding to a larger investigation. The information collected in the pilot study was used to assess individual variation in treatment responses and to conduct statistical power analysis to increase efficiency of future research efforts, We conducted controlled experiments with adult, tame female elk at the Colorado Division of Wildlife's Foothills Wildlife Research Facility, Fort Collins, Colorado during November 1998 to March 1999, Objective: To determine the amount of GnRH agonist analog that will induce half-maximal release of LH in female elk during estrus and evaluate duration of effectiveness. Design: We observed the LH response offemale elk to three levels ofGnRH agonist (0, 19,39, and 78 J-lglhour) in a completely randomized design with two animals per level. Based on results from previous studies, we chose a range of doses that should include the biologically effective range for elk. �131 We evaluated the effective duration of treatments by monitoring ovarian function throughout the remainder of the breeding season (Nov - Apr). Dosage Trial - This experiment was conducted during the breeding season to insure that the pituitary gland was at its most active state when stimulated by the GnRH agonist. On Day 1 of the experiment, 9 female elk were moved from 5 ha pastures to individual isolation pens, sedated with xylazine hydrochloride (50-100 mg/animal, IM), fitted nonsurgically with indwelling jugular catheters and administered subcutaneously one of three experimental doses of GnRH agonist analog. The sampling period began at 1000 h. Blood samples (5 ml) were collected at 0,60, 120, 180,240,300,360,480 min, 12,24,36,48,84, and 240 h postinjection. Animals remained in isolation pens during the 10 day trial. Elk were observed daily for side effects of treatments (if any) and catheters flushed with sterile saline solution. Following the last blood collection, catheters were removed and animals returned to 5 ha paddocks. After collection, blood was held at 4 -c for 24 h until serum was obtained by centrifugation. Serum was then stored at - 20°C until analyzed for LH. Serum concentrations ofLH was quantified by means of ovine LH RIA (Niswender et al. 1969). The limit of sensitivity of the assay was 0.4 ng/ml. Analysis: Responsiveness of the pituitary to GnRH agonist analog challenge was assessed in four ways: 1) maximum LH response achieved postinjection minus baseline 2) time required to reach maximum LH 3) total amount ofLH secreted (ng/mllmin) 4) the amount ofLH required to induce half maximal release ofLH (EDso). Response to treatments was analyzed with a one way analysis of variance for a completely random design with 3 levels of dose as treatments and 3 individual animals as replications. Simulation Model We developed an interactive simulation model to allow RMA biologist to evaluate alternative mule deer culling strategies. This model combines extant knowledge of mule deer population biology with measured population parameters at the RMA to predict the proportion of male and female deer that need to be removed each year to accomplish management objectives for this herd. Table 1. Principal parameters in culling simulation model for mule deer at RMA. Definition Value Measured Adult/yearling female survival Adult/yearling male survival Fawn survival coefficient a Fawn survival coefficient 13 Fetal sex ratio ('Yo males) December recruitment 0.90 0.90 1.20 -0.053 0.47-0.62 0.59-0.72 No No No No Yes Yes Reference Whittaker, 1992 Whittaker, 1992 Bartmann et aI., 1992 Bartmann et aI., 1992 �132 RESULTS AND DISCUSSION GnRH Toxin/Agonist Experiment 1: Evaluation of GnRH-PAP in mule deer. Mean serum LH concentrations were reduced in all experimental animals compared to pretreatment levels following treatment with GnRH-PAP (Fig 1). Mean levels ofLH (ng/ml) were initially reduced 72% of pretreatment levels after 15 days, then increased to about 51% (se ± 0.75) after 33 days and have remained relatively unchanged through 100 days posttreatment. Body weight dynamics, blood chemistry, hematology and social behavior of treated deer appear normal compared to non-treated female deer. 125 100 I - ...J c: II) E 75 C"d II) •... II) •... a. - 50 0 ~ 25 o Pre Toxin 33 15 48 100 Days Figure 1. Luteinizing hormone release in ovariectomized female mule deer treated with GnRH-PAP during the breeding season. Experiment 2: Evaluation of GnRH-Agonist in Rocky Mountain Elk. Administration of GnRH-Agonist implants resulted in a prompt and expected increase in serum LH levels in all female elk. We observed an average peak LH response of 15.52 ng/ml (se ± 0.94) which occurred approximately 3.5 h posttreatment. Peak response (ng/ml) and time to peak (h) were not different (p > 0.01) among treatment levels. Serum LH levels returned to baseline after 12 hours for all elk. Subsequent challenge with an intravenous injection of 1 f.,l GnRHI50 kg BW at 35,75,110, and 130 days posttreatment resulted in a significant (p < 0.02) increase in LH levels of control elk compared to elk treated with GnRH-Agonist implants (Fig. 2). We did not observe a significant (p < 0.001) treatment difference among doses of GnRH-Agonist. Lack of treatment effect was not due to high variation among animals but instead to small differences among treatments responses. Serum LH levels of treated elk remained at baseline (0.34 ng/ml) for the duration of the experiment (130 days). These findings are consistent with other evidence for desensitization of the pituitary gonadotrophs due �133 --f- Control - -is - Low --0-- Mad ...+... High 25 20 E 0; c 15 :r: ...J ~ w 10 a.. 5 o o 35 75 110 130 TIME (DAYS) Figure 2. Effects of subcutaneous administration otGnRH-Agonist on serum LH concentrations in elk. Doses were: control = 0, low = 32.5 mg, medium = 65 mg, and high = 130 mg. to prolonged and sustained stimulation. The results of this study demonstrate that one subcutaneous implant containing at least 32.5 mg of GnRH-Agonist can suppress pituitary-ovarian function for at least 90 days in elk. Simulation Model . Professional culling of adult mule deer at the RMA was implemented on a prescribed basis beginning in November 1994. Prior to 1994, the mule deer population was increasing at a rate of approximately 20 % per year. Since 1994, annual culling has reduced the population growth rate to 4% per year and allowed resource managers to meet deer management objectives for this herd. To meet these objectives has required that resource managers remove approximately 10- 15% of the adult females and 6-10% of the young males from the population each year. These estimates vary each year depending on productivity of the population, changes in sex and age ratios, and deer habitat resources. The mathematical model used to estimate the number of animals that must be culled annually to maintain a target, steady state population appears to provide a reasonably accurate representation of mule deer population dynamics at the RMA.· The efficacy of this model, however, is dependent on intensive monitoring of the population and adapting management actions to a changing environment. LITERATURE CITED Asch, R H, F. J. Rojas, T. R Tice, and A. V. Schally. 1985. Studies of a controlled - release microcapsule formulation of an LH-RH agonist in the rhesus monkey menstrual cycle. International J. Fertility 56:78-81. Baker, D. L. 1997. Regulation of mule deer population growth by fertility control: laboratory, field, and simulation experiments. Pages 81- 87 in Wildlife Research Report, Mammals Research, �134 Federal Aid Projects, Job Progress Report, Project W-153-R-4, SP1, Jl. Colorado Division of Wildlife, Fort Collins, Colorado, USA. Baker, D. L., and N. T. Hobbs. 1996. Regulation of mule deer population growth by fertility control: laboratory, field, and simulation experiments. Pages 113 -148 in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-4, SPl, J1. Colorado Division of Wildlife, Fort Collins, Colorado, USA. Baker, D. L, M. W. Miller, and T. M. Nett. 1995. Gonadotropin-releasing hormone analog-induced patterns of luteinizing hormone secretion in female wapiti (Cervus elaphus nelson i) during the breeding season, anestrus, and pregnancy. Bio. Reprod. 52: 1193-1197. Becker, S. E., Katz, L. S. 1995. Effects of gonadotropin - releasing hormone agonist on serum LH concentrations in female white-tailed deer. Small Ruminant Research 18: 145-150. Casper, R. F., and S. S. C. Yen. 1979. Induction of luteolysis in the human with a long-acting analog of luteinizing hormone-releasing factor. Science 205 :408-41 O. Clayton, R. N. 1982. GnRH modulation of its own pituitary receptors: evidence ofbiphasic regulation. Endocrinology 111: 152-161. Concannon, P. W., and V. N. Meyers-Wallen, 1991. Current and proposed methods for contraception and termination of pregnancy in dogs and cats. 1. Am. Vet. Med. Assoc. 198:1214-1225. Fraser, H. M. 1983. Effect of treatment for one year with a luteinizing hormone-releasing hormone agonist on ovarian, thyroidal, and adrenal function and menstruation in the stump tailed monkey (Macaca arctoides). Endocrinology 112:245-253. __ , M., 1. Sandow, H. Seidel, and W. von Rechenberg. 1987. An implant of a gonadotropin releasing hormone agonist (burserelin) which suppresses ovarian function in the macaque for 3-5 months. Acta Endocrinological 15: 521-427. Garrot, R. A. 1995. Effective management of free-ranging ungulate populations using contraception. Wildlife Society Bulletin 23:445-452. Goodman, R. L., and F. 1. Karsch. 1980. Pulsatile secretion of luteinizing hormone: differential suppression by ovarian steroids. Endocrinology 107:1286-1290. Herschler, R. C., and B. H. Vickery. 1981. The effects ofLHRH ethylamide on the estrous cycle, weight gain, and feed efficiency in feedlot heifer. Amer. 1. of Vet. Res. 42: 1405-1408. Hobbs, N. T., D. L. Baker, and R. B. Gill. 1999. A general theory describing effects offertility control on populations of ungulates. Journal of Wildlife Management (in press). Hone, 1. 1992. Rate of increase and fertility control. 1. Applied Ecology 29:695-698. Jewell, P. A., and S. Holt. 1981. Problems in management oflocally abundant wild animals. Academic Press. 321pp. Kirkpatrick, 1. F., and 1. W. Turner, Jr. 1985. Chemical fertility control and wildlife management. Bioscience 35:485-491. McNeilly, A. S., and H. M. Fraser. 1987. Effect of gonadotropin-releasing hormone agonist-induced suppression ofLH and FSH on follicle growth and corpus luteum function in the ewe. 1. Endocrinology 115:273-282. Niswender, G. D., L. E. Reichert, Jr., A. R. Midgley, Jr., and A. V. Nalbandov. 1969. Radioimmunoassay for bovine and ovine luteinizing hormone. Endocrinology 84: 1166-1173. ___ . 1973. Influence of the site of conjugation on the specificity of antibodies to progesterone. Steroids 22:413-424. Sandow,1. 1982. Inhibition of pituitary and testicular function by LHRH analogs. Pages 19-39 in Jeffcoate S. L. and Sandlier (eds). Progress towards a male contraceptive. Wiley and Sons, Chichester. Warren, R. 1., L. M. White, W. R. Lance. 1995. Management of urban deer populations with contraceptives: practicality and agency concerns. Wildlife Society Bulletin 23: 441-444. � https://cpw.cvlcollections.org/files/original/1040e3b2c3c260e7bf139285e9591ed7.pdf 693594c505c12c29068f49a3d60674b9 PDF Text Text 135 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT Smteof ~C~o~lo~r~ad~o~ _ ,Project No. W.!.!--1~5~3~-R~-..!..12~ __ Work Package No. __ ~3~0:..:::0..!..1 _ -=5:..__ _ Task No.' Cost Center 3430 Mammals Program Deer Conservation Investigating Factors Contributing to Declining Mule Deer Numbers Period Covered: July 1 1998 - June 30, 1999 Authors: T. M. Pojar and W. F. Andelt '" Personnel.. R Arant, D. L. Baker, B. Banulis, D. Hartmann, G. Bock, D. C. Bowden, M. Caddy, D. Coven, B. Devries, B. Diamond, B. Dreher, 1. Ellenberger, V. Graham, D. Gustine, P. Hayden, G. Hust, C. Krumm, A Larsen, K. Larsen, S. Larsen, D. Masden, D. Matiatos, M W. Miller, C. Oliver. J. Olterman, M. Potter, E. Scott, L. Spicer, D. Steele, C. Wagner,:a. Watkins, M. Wild, M. Zeeman, S. Znamenacek. ABSTRACT Long-term data indicate that fawn:doe ratios have shown a significant and consistent decline over the past 20 years in most deer management units in Colorado as well as in most of the western states, This has resulted in a general decline in mule deer (Odocoileus hemionus) density and diminished recreational potential from this major resource. It is important for the Division of Wildlife to elucidate the factors contributing to the reduced doe:fawn radios and the declining deer populations. Reproduction and neonatal survival are 2 important components of population recruitment. Therefore, 2 studies were initiated during this segment to investigate pregnancy and fetal rates of adult does and the survival of neonatal fawns. Both of these studies were done on the Uncompahgre Plateau and, in addition, a supplemental neonate fawn survival study was done in Middle park. Thirty-seven of 40 (93%) adult does on the Uncompahgre Plateau were detected pregnant with transrectal ultrasound. The proportion of does detected pregnant with ultrasound did not differ (P = 0.817) from the proportion of does pregnant (91.4% of303 does) in previous Colorado studies. The average number of fetuses/doe, 1.70, (n=40) for adult does on the Uncompahgre Plateau was not less (Z = 0.340, P = 0.367) than the fetal rate of 1.74 (n=276) in previous Colorado studies. We therefore conclude that does are getting bred and producing fetuses at normal rates for the species and that this component of , the reproductive cycle is most likely not responsible for declining December fawn:doe ratios and, 'consequently, declining deer populations. The field operation was done during February 5-8, 1999; a draft of the manuscript to be submitted to a peer reviewed publication is in Appendix I. The objective of the fawn survival investigation was to put radios on 60 neonatal fawns on the Uncompahgre and 20 neonatal fawns in Middle Park. By June 30, 1999, we had put out 50 and 14 radios on fawns on the �136 Uncompahgre and in Middle Park, respectively for a total of 64 radioed fawns. First fawns were captured on June 9 in both areas and fawn capture peaked during June 13-24 with 76% of the total captured during this time; 19 fawns (30%) were captured during June 22-24. The first mortality was recorded on June 13 with the peak of mortality (50% of total) during June 28-July 12. Causes of mortality when divided between predation, sickness/starvation, and unknown was 47%, 47%, and 6%, respectively. As of this date (August 18, 1999) 30 of64 fawns have died for a mortality rate of 46.9%, Fawns were monitored every day (except weekends) from capture with the exception of the period of July 5-27 when they were monitored twice a day. After July 27 they were again monitored daily except on weekends. Eleven of the 14 fawns that died of causes other that predation (or unknown causes) have been necropsied thus far; all had in common severe thymic atrophy indicating a compromised immune system and chronic stress. It is difficult to discern if the stressor(s) predisposed them to the variety of other pathogens that appeared to be factors in their deaths. Some of the disease agents identified were: Cryptosporidia, Pasteurella, E. Coli, BVD, and a hemorrhagic disease (Blue Tongue or EHD). It should be noted that mortality attributed to predation is probably liberal because the fawn's sickness (including diarrhea in many cases) and weakened condition probably predisposed them to olfactory or visual location by a predator. Positively identifying scavenging vs. predation was difficult even when they were monitored once or twice a day because dense vegetation precluded tracking for evidence of pursuit and kill sites as can be done with snow cover. �137 MULE DEER PREGNANCY AND FETAL RATES William F. Andelt and Thomas M. Pojar P. N. OBJECTNES 1. Estimate pregnancy and fetal rates of adult mule deer does on the Uncompahgre Plateau during the 1998-1999 reproductive cycle. 2. Publish results in a peer-reviewed scientific journal (Appendix I). SEGMENT OBJECTNES 1. Estimate accuracy of an ultrasound system for detecting' pregnancy and number of fetuses in mule deer does maintained at the Colorado Division of Wildlife's Foothills Research Facility in Northwest Fort Collins and in mule deer does collected on the USFWS Rocky Mountain Arsenal. 2. Estimate pregnancy and fetal rates of adult mule deer in DAU D-19 (Uncompahgre). 3. Compare pregnancy and fetal rates of adult mule deer to historic rates in Colorado. 4. Analyze data and prepare an annual Federal Aid Job Progress report. RESULTS See Appendix I for the Research Program Narrative and a draft of the manuscript to be submitted to a peer reviewed publication. �138 �139 lMPACT OF PREDATION AND VEGETATIVE COVER ON MULE DEER FAWN SURVIVAL Thomas M. Pojar and William F. Andelt P. N. OBJECTIVES 1. Identify agents of neonatal mule deer fawn mortality from birth to 6 months of age. SEGMENT OBJECTIVES 1. Capture and radio collar 30-35 neonatal fawns each on the Uncompahgre Plateau (D-19), Middle Park (D-9), and Red Feathers (D-4). 2. Measure vegetative density and height at fawn bed sites. 3. Measure distance between successive bed sites for individual fawns. 4. Compare fawn survival and causes of mortality among 3 vegetatively and ecologically different study areas. 5. Correlate height and density of vegetation at fawn birth sites and bed sites with percent of fawns killed by predators. 6. Compare height and density of vegetation at fawn bed sites and random sites. INTRODUCTION The Research Program Narrative is in Appendix II. Because of budget redirection to accomplish the estimation of pregnancy and fetal rates via ultrasound the objectives outlined in the PN were modified to fit within budget, personnel, and logistic constraints. Major changes include: 1. Limit the fawn collaring effort to the Uncompahgre and Middle Park rather than attempt to do it on 3 study areas. Because of the size and diversity of vegetative communities on the Uncompahgre and because of intense political interest in this area, the target sampling intensity was increased to 60 fawns. The target sample in Middle park was reduced to 20 fawns due to the redirection of resources. 2. Abandon the idea of measuring vegetation at bed sites because of evidence that persistent disturbance of bed sites reduces survival of young ungulates (Philips 1998). 3. The logistics of placing an adequate crew in remote fawning areas and the unknown of whether or not fawns could be captured in sufficient numbers given deer density, terrain, and vegetative cover encountered negated many of the objectives in the PN. In essence, this investigation was reduced to placing emphasis on determining if fawns can be captured under these conditions and, if so, monitor their survival and causes of mortality. Summer fawn survival and causes of mortality are 2 important factors impacting deer population performance. STUDY AREAS There are 2 study areas involved in this investigation, the Uncompahgre Plateau and Middle Park. The Uncompahgre Plateau includes Game Management Units 61 and 62. It is a high elevation plateau, oriented northwest-southeast, formed by a structural uplift that is characterized by steep canyons in both directions from the divide ridge that runs the length of the plateau. The soils are primarily shallow with areas of rich deeper soils that support aspen (Populus tremuloides) communities at intermediate to higher elevations. High elevations have extensive stands of spruce-fir �140 (Picea-Abies) and fir-aspen (Abies-Populus tremuloides). The crest of the plateau peaks at about 9,500 ft (2,898 m) and declines in both directions through oakbrush (Quercus gambellii), pinyonjuniper (Pinus edulis-Juniperus osteosperma), and large sagebrush (Artemisia tridentata) parks as the elevation decreases. A thorough description of the physiography, geography, climate, and vegetation can be found in Anderson et. aI (1992) and Kufeld (1979). Middle Park is a high mountain park with similar plant communities as the Uncompahgre Plateau at similar elevations. A description of the area can be found in Tiedeman et. aI (1987). MElHODS Radio collared does were used to locate fawning areas although no special effort was made to capture the fawns of radioed does. The strategy for capturing fawns involved observing does for behavioral and physical signs, such as udder development, of having fawned. If it was determined that these indicators suggested that the doe had fawned, the area was searched for the fawn(s). Once located, the fawn was approached from behind (out of direct eyesight) and restrained for weighing, measuring, and putting on the radio collar. ·The collars used were expandable with elastic and loops sewed with cotton thread to accommodate growth and to drop off at about 6 months; they weighed about 65 g. RESULTS A total of 64 fawns were captured and radio collared; 50 on the Uncomphagre Plateau and 14 in Middle Park. The first fawns were captured on June 9 with 76% of the total captures made during June 13-24; the peak 3-day period of capture was June 22-24 when 30% of the captures were made (Figure 1). Total fawn mortality as of this writing (August 18) is 30 with 14 from a condition that is generally described as sickness/starvation (S/S), 14 from predation, and 2 from unknown causes where only the collar was found (Table 1). The 14 that died from SIS were all collected, frozen or stored on ice, and later necropsied at the Colorado State University Veterinary Teaching Hospital in Fort Collins. Results thus far are preliminary with some of the lab tests still pending and that is the reason for categorizing these deaths as general SIS. Some disease agents have been identified but it is not known if these were the cause of the fawns deaths. A common condition in all of the fawns is that they had atrophied thymus glands indicating chronic stress and probable immunodeficiency which could have predisposed them to succumbing to the pathogens that they encountered. Some of the pathogens 25 20 (/) c: i& u, -- 15 .c 10 0 •... Cl> E ::::J Z 5 6/1-6/3 6rT-6/9 6/13-6/15 6/19-6/21 6125-6/27 6/4--616 6/10-6/12 6/16-6/18 6/22-6124 6/28-6/30 Date Figure 1. Dates of fawn capture combined Uncompahgre Plateau and Middle Park. from 2 areas in Colorado. 1999- �141 identified are: the parasite Crhyptosporidia, Pasterrella, E. Coli, Bovine Virus Diarrhea (BVD), and a hemorrhagic disease (Blue Tongue or Epizootic Hemorrhagic Disease (EHD». In addition to the 30 dead radioed fawns, we found 2 stillborns, 2 other intact fawn carcasses, and one adult doe carcass. One of the stillborns was fresh enough to necropsy and was small {1.5 kg) and also had an atrophied thymus. The lab results on the adult doe are not complete but she showed some signs of a hemorrhagic condition; the other carcases were in stages of decomposition that precluded materials collection. Determining if a fawn died from some other cause or was killed by a predator is difficult. Because the fawns were monitored on a daily or twice daily schedule, all carcasses that were found partially eaten were attributed to predation; some errors were undoubtedly made by doing this which would inflate the deaths attributed to predation. Vegetation was too thick to discern tracks of a chase and capture as is possible during winter with snow cover, so unless the predation was actually witnessed, there will always be doubt as to the whether or not predation was the cause of death. In 2 instances, only the collar was found with no other tracks or supporting evidence of predation. These are categorized as "unknown" but are likely predator kills. It is unlikely that the collars were slipped because they fit snugly around the neck. One of these collars had a triangular rip that could have been caused by a predator tooth (or barbed wire), the other was without marks or blood so it's categorization is even less certain. With nearly half of the fawns dying of SIS it is probable that some portion of the fawns eaten by a predator were in some stage of "sic knessl starvation" resulting in them being more susceptible to discovery by a predator ~ Several of the fawns that died had diarrhea which would have broken their .shield of scentlessness that protects them from predators early in life. Other fawns that were in a diseased or weaken state may have lacked normal hiding or escape behavior that would have predisposed them to either visual or olfactory location by a predator in the vicinity. The classical evidence that an animal was alive when bitten (i.e. predated) by a predator is subcutaneous hemorrhage; this, however, does not establish that the prey was in a healthy state when preyed upon. The peak of mortalities from all causes was during June 28-July 11 with 16 of30 (53%) dying during this 14-day period (Figure 2); 5 from SIS and 11 from predation. One fawn died on the 2nd day after capture and was judged to be a day old at capture. It was found to have no milk in it's abomasum and had a small amount of forage in it's rumen both of which indicate that it had not nursed and was starving. It is not possible to determine if this fawn was abandoned because of handling or if the dam was not providing milk; a doe was in the area (and acting maternal) during capture and 2 days later when the fawn carcass was recovered. If the fawn was truly a day old when captured and had not nursed by that time it is possible that there was a bonding or lactation problem on the part of the doe. 5 CI) Q) E (ij 4 t 0 ~ c: 3 3: -.8 <IS u.. 2 0 E 1 ::s z 0 .•.... N 0 .•... CD 00 .•.... fb .•.... C{i CD ~ g ch C:! <0 .•... N ~ ,..._ 0 .•... 00 .•.... fb .•... -.. ,..._ j:::: Dates ..,. . ~ ~ ,..._ g, 00 ~ It) £2 00 .•... .•.... , ~ 00 Figure 2. Neonatal fawn mortality from all causes for the Uncompahgre and Middle Park, Colorado, 1999. ,..._ .•... &b .•.... -.. 00 Plateau �142 All of the other SIS occurred on the 3rd, or later, day after capture. Six fawns died between the 3ni and 5th day after capture and the rest of them (77%) died after the 6th day of capture (Figure 3). It is interesting to note that there were 2 somewhat long time spans where there were no mortalities from any cause - 6 days, July 14-19, and 17 days, July 26- August 13. It seems that if there were constant predator pressure on neonatal fawns as a food source and that sickness were not a factor in predator location of fawns, then there would not be these long spans of no mortality on the marked fawns. However, it is possible that just by chance alone, predators did not encounter a marked fawn during these time periods. One radio was verified to have failed and It is believed that 2 other radios ceased to work because extensive ground and aerial searches failed to make signal contact. A set of twins that were radioed recently disappeared after domestic sheep were herded into the area they were inhabiting; no signal was obtained with a ground search of the area so an aerial search will be made. 12,------------- -, 10 CI.I ~ tIS u.. '0 8 6 ~ g :z: 4 2 <0 r= 1 Days From Capture Figure 3. Days from capture that fawns died from any cause. Total for fawns captured on the Uncompahgre Plateau and Middle Par1<.Colorado. 1999. CONCLUSIONS The following conclusions can be made from this investigation. 1. It is possible to capture neonatal fawns under the conditions found on the Uncompahgre Plateau and in Middle Park. Success in capturing fawns is dependent mostly on doe density which dictates the number of does that the capture crew can encounter during a search. Road network is also important because of the greater mobility of the capture crew and, therefore, a greater probability of encountering does .. And finally, experience of the capture crew is a major factor in the success of finding fawns. Dense vegetative cover and roadless areas make sighting of does and capture of fawns unproductive for reasonable sample sizes. 2. There is evidence that there are stress factors impacting the 2 mule deer populations that were sampled. Atrophied thymus glands of all the intact carcasses recovered along with a variety of pathogenic agents identified suggests that the stressor(s) resulted in a suppressed immune response in the fawns making them susceptible to encountered pathogens. It has been demonstrated that thymus gland size in mule deer is seasonally cyclic with the peak during summer (good nutrition) and the trough during winter (limited resources) (Anderson et aI. 1974). Ozoga and Verme (1978:794) have demonstrated the relation between thymus size and dietary plane in white-tailed deer (0. Virginianus) fawns in controlled tests. They also noted that the thymus glands offawns dying of disease or malnutrition within a month of birth were "extremely small" compared to fawns dying of other causes (accidents). �143 LITERATORE CITED Anderson, A E., D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40, Colorado Division of Wildlife. Anderson, A E., D. E. Medin, and D. C. Bowden. 1974. Growth and morphometry of the carcass, selected bones, organs, and glands of mule deer. Wildlife Monographs, No. 39. Kufeld, R C. 1979. History and current status of the mule deer population of the east side of the Uncompahgre Plateau. Division Report No. 11, Colorado Division of Wildlife. Ozoga, J. J. and L. J. Verme. 1978. The thymus gland as a nutritional status indicator in deer. Journal of Wildlife Management, 42:791-798. Philips, G. E. 1998. Effects of human-induced disturbance during calving season on reproductive success of elk in the upper Eagle River valley. Ph. D. Dissertation, Colorado State University, Fort Collins. .Tiedeman, J. A, R E. Francis, C. Terwilliger, Jr., and L. H. Carpenter. 1987. Shrub-steppe habitat types of Middle Park, Colorado. USDA Forest Service Research Paper RM-273, Rocky Mountain Forest and Range Experiment Station, Fort Collins. Table 1. Neonatal fawns captured and radio collared on the Uncompahgre Plateau and Middle Park, Colorado, 1999. Radio frequencies in the 149-150 KHz band are Uncompahgre fawns and 173 KHz radios are Middle Park fawns. ID Date Sex Weight (kg) Hindfoot Date Probable 149.410/99 06/1611999 M 3.5 24.4 07/0111999 Predation 150.010/99 0611511999 F 0.0 24.9 150.020/99 06/0911999 F 0.0 24.7 150.030/99 06114/1999 F 0.0 27.3 06/2911999 Sick/Starve 150.040/99 06114/1999 F 0.0 27.6 07/0611999 Sick/Starve 150.050/99 06/1511999 F 0.0 27.9 150.070/99 0611711999 M 3.8 26.0 08/1811999 Predation 150.080/99 06/2211999 F 4.4 27.0 06118/1999 Sick/Starve 06/29/1999 Predation 150.090/99 06/2111999 F 5.9 27.6 150.100/99 06/2111999 M 5.2 26.4 150.110/99 06114/1999 U 2.3 0.0 150.120/99 06/1711999 F 5.0 26.0 150.130/99 0611411999 F 2.5 24.8 150.140/99 06110/1999 F 3.3 24.4 150.150/99 06/1711999 M 5.3 26.7 07/2011999 Predation 150.160/99 06/2211999 F 0.0 26.0 06/3011999 Predation 150.170/99 0611511999 F 3.7 26.0 150.180/99 06/2111999 F 6.1 29.2 07/2511999 Sick/Starve 07/0711999 Sick/Starve 150.190/99 0611511999 M 4.0 26.0 150.200/99 06/2211999 M 3.3 24.1 150.210/99 06/2411999 F 4.4 26.4 150.220/99 06/1611999 M 3.8 24.4 150.230/99 06/2211999 F 5.3 28.6 150.270/99 06/23/1999 M 5.6 26.4 �144 Weight (kg) Hindfoot Date Probable M 3.1 25.0 06118/1999 Sick/Starve M 4.6 26.0 0611611999 M 0.0 26.7 150.310/99 06/2811999 F 5.6 28.6 150.320/99 06123/1999 M 6.0 27.9 150.340/99 06/2311999 F 5.6 27.6 06/30/1999 Sick/Starve 150.350/99 0611711999 M 0.0 28.7 06/22/1999 Sick/Starve 150.360/99 06/2411999 M 6.0 26.7 150.370/99 06/2311999 M 6.0 27.3 150.380/99 0612411999 M 2.4 23.2 07/1111999 Predation 150.390/99 06/2411999 F 3.8 26.7 07/0111999 Predation 150.400/99 06/2211999 M 5.0 27.3 150.420/99 06128/1999 F 4.2 26.2 150.430/99 06124/1999 M 5.3 26.7 0711111999 Unknown 0811611999 Predation ID Date Sex 150.280al99 06/15/1999 150.280b/99 06/28/1999 150.290/99 150.440/99 06/2511999 M 6.0 29.2 150.45Q/99 06115/1999 F 3.5 25.7 150.460/99 06124/1999 M 3.1 23.5 150.480/99 06/3011999 F 4.2 24.8 08/16/1999 Sick/Starve 150.510/99 0611611999 F 3.6 24.1 07/0111999 Predation 150.520/99 06116/1999 F 3.5 24.8 07/0811999 Predation 150.530/99 06114/1999 M 3.6 25.4 150.540/99 06/29/1999 M 4.5 26.0 150.570199 06/24/1999 F 2.5 21.9 0711311999 Sick/Starve 150.600/99 06/2911999 M 6.0 28.9 150.610/99 06/18/1999 M 3.6 25.4 07/23/1999 Sick/Starve 150.620/99 06/30/1999 M 4.5 24.4 07/0511999 Predation 173.510/99 06/0911999 M 4.5 26.7 0611311999 Sick/Starve 173.540/99 0611111999 F 3.8 26.0 07/2211999 Predation 173.550/99 0612411999 F 4.7 27.3 173.560/99 06/2111999 F 4.1 26.0 173.590/99 06/2211999 M 5.5 28.6 173.600/99 06/2111999 F 4.1 26.0 173.610/99 06/2111999 M 5.1 28.6 06/25/1999 Sick/Starve 07/0811999 Predation -. 173.630/99 06/2111999 F 3.8 25.4 173.640al99 06/22/1999 M 4.5 26.7 06/2511999 Sick/Starve 173.640b/99 06/30/1999 M 4.2 25.4 08/16/1999 Predation 173.660/99 06/29/1999 M 6.5 27.9 173.670/99 06/2511999 F 6.0 29.2 173.690/99 06/19/1999 U 0.0 0.0 07/0511999 Unknown 173.700/99 06/1811999 M 4.7 27.0 'Due to the preliminary nature of this report, the causes of death have been put into only 3 categories, sick/starve, predation, and unknown. The unknown category includes 2 radios that were found that had no other evidence present. It is suspected that these were actually predator kills because the collars fit snug enough that slipping the collar was unlikely, in addition, one of the collars had a small triangular rip in it that could be consistent with a predator tooth tear. �145 APPENDIX I Research Program Narrative and Draft Manuscript MULE DEER PREGNANCY AND FETAL RATES ON THE UNCOMPAHGRE PLATEAU January 12, 1999 Principal Investigators: WILLIAM F. ANDELT Department of Fishery and Wildlife Biology Colorado State University Fort Collins, CO 80523 970-491-7093 mOMAS M. POJAR Colorado Division of Wildlife 317 W. Prospect Fort Collins, CO 80526 970-472-4308 �146 �147 PROGRAM NARRATIVE State of. ___;C::::;o::::..:l~or:..::a:::::d~o_ Project No .. W..!.!._-~15~3::....-.:!:.::R,__ _ Work Package No. ---,3~0~0~1,-_ Task No. -=5'--_ Cost Center 3430 Mammals Program Deer Conservation Mule Deer Pregnancy and Fetal Rates on the Uncompahgre Plateau NEED Fawn:doe (f:d) ratios obtained in December on the Uncompahgre Plateau (Game Management Units 61 and 62, Data Analysis Unit (DAU) D-19) have declined (t = -3.39, P = 0.004) by an average of 1.8 fawns: 100 does per year from 1982-1998. December ratios ranged from a high of79f:l00d in 1982 to a low of 32f: 1OOdin 1996 and 34f: 100d in 1997; there were 51.9f: 1OOdin 1998. Besides low December f:d ratios, over-winter (December - May) fawn survival on the Uncompahgre Plateau was 49% during the winter of 1997-1998 (Bartmann and Pojar 1998a). The low December f:d ratios and poor over-winter survival of fawns for the Uncompahgre deer herd is of concern to the public and game managers. It is unknown if the low December ratios are due to a failure to breed, reduced fetal production, resorption/abortion offetuses, or low summer and fall fawn survival (Bartmann 1998). Pregnancy and Fetal Rates Pregnancy rates are key information to determine if does are breeding. Recent data show that the pregnancy rate during January 1998 of93.0% for 29 does ~ 1 year old in the Red Feather DAU (Bartmann and Pojar 1998b) was similar to 92.0% of 163 does ~ 2 years old in the same area during 1961-1964 (Medin and Anderson 1979). A 94.8% pregnancy rate for does ~ 2 years old (n = 114) and a 94.0% pregnancy rate for does> 1 year old (n = 134) in Middle Park (DAU D-9) was reported by Gill (1971) during 1969-197l. Other pregnancy rates and locations reported in the literature are as follows: 100% for does ~ 2 years old (n = 18) on the Forbes-Trinchera Ranch, Colorado (Freddy 1988), 89% (n = 47) during 1973 and 82% (n = 83) during 1978 in the Piceance Basin, Colorado (Bartmann 1998), and 94% of mule deer does> 1 year old in a California study (Salwasser et al. 1978). The 1998 data collected in Colorado appears to be normal and does not indicate that pregnancy rate is a contributing factor to the low f:d ratios, however these data were not collected in the Uncompahgre DAU where December f:d ratios were lowest. Fetal rates, the number of fetuses per pregnant doe, that are in a normal range for the species would indicate that nutritional and other needs of breeding does are being met. The fetal rate for does > 2 years old was 1.83 (n = 41) in the Cache la Poudre River drainage from 1961-1965 (Medin and Anderson 1979), 1.82 (n = 114) in Middle Park (Gill 1971), 1.89 (n = 18) on the Forbes-Trinchera Ranch (Freddy 1988), and l.46 (n = 61) and 1.65 (n = 37) in the Piceance Basin (G. C. White, Colorado State University, personal communication). Salwasser et al. (1978) reported a fetal rate of l.62 for 2 and 3 year old mule deer does (n = 47) and a rate of l.85 for does> 4 years old (n = 34) in California To help ascertain the cause of low fawn:doe ratios on the Uncompahgre Plateau of Colorado, an investigation to estimate: a) the proportion of ~ 2 year old does that become pregnant and b) the number of fetuses produced is needed. Estimates of pregnancy and fetal rates will indicate if these critical reproductive parameters are within the normal range for the species and will contribute to the understanding of the causes of the observed low f.d ratios and low recruitment into the Uncompahgre mule deer population. �148 OBJECTIVES We propose to estimate pregnancy and fetal rates of adult mule deer does on the Uncompahgre Plateau during the 1998-1999 reproductive cycle. HYPOTHESES H"l: H,,2: Pregnancy rates of adult mule deer does on the Uncompahgre Plateau during the 1998-1999 reproductive cycle do not differ from historic pregnancy rates (93%) in Colorado. Fetal rates of adult mule deer does on the Uncompahgre Plateau during the 1998-1999 reproductive cycle do not differ from historic fetal rates (1.74 fawns per adult doe) in Colorado. EXPECTED RESULTS OR BENEFITS This research will help ascertain if pregnancy and fetal rates are outside the normal range expected for mule deer in Colorado and if they are contributing factors to the observed low December fawn:doe ratios. Knowledge of fetal rates is essential for determining what factors might be causing the low fawn:doe ratios observed in Colorado. Recruitment into a mule deer population is dependent on adequate pregnancy and fetal rates, and young survival through breeding age. This investigation will provide information on the early stages of the recruitment process, i.e. whether or not does are becoming pregnant and producing normal litters. These data are imperative before research and management experiments are conducted to estimate the effect of various experimental manipulations on fawn:doe ratios. APPROACH Capture and Handling of Does Forty mature does C:::. 2 years old) will be captured using a helicopter and netgun on the Uncompahgre Plateau during February 1999. The deer usually will be pursued for < 2 minutes. We expect < 2% of the captured does to sustain injuries or mortalities (R. M. Bartmann, Colorado Division of Wildlife and A. W. Alldredge, Colorado State University, personal communications). Captured does will be hobbled, blindfolded, and transported via helicopterto a base station, usually < 5 miles from the capture site to.minimize stress, where they will be processed. Does captured < 2 miles from the processing station will be released at the station, whereas does captured> 2 miles from the station will be released at the capture site. We anticipate that does will not be held for more than 30 minutes. Pregnancy and Fetal Detection The does will be manually restrained without the use of a tranquilizer to allow quick release at the processing site, unless we find sedation is necessary. If necessary, does will be sedated with ketamine and xylazine and reversed with yohimbine. The does will be placed in lateral or sternal recumbency, depending on location of the fetuses. We will use trans rectal ultrasonography, pioneered by Lindahl (1971) and applied in field situations by Barrett (1981), Smith and Lindzey (1982). White et al. (1989), and Stephenson et al. (1995), to estimate pregnancy and fetal rate. A portable ultrasound unit available from the Colorado State University Veterinary Teaching Hospital will be used; the �149 equipment will be transported in a mobile processing station to within 5 miles of capture sites to minimize transport time and stress on the does. Blood will be collected by carotid venipuncture and serum pregnancy-specific protein-B (PSPB) (Sasser et al, 1986) will be used to provide a second estimate of pregnancy rates (Stephenson et al. 1995). The use of ultrasonography to detect pregnancy is a well tested method and provides accurate estimates of pregnancy rates in elk (Cervus elephus) (Bingham et al. 1990, Revol and Wilson 1991, Willard et al, 1994). Transrectal ultrasonography was found to accurately detect pregnancy in domestic sheep (Schrick and Inskeep 1993) and fallow deer (Dama dama; Lenz et al. 1993). Because the method is not as well tested to detect the number of fetuses carried by pregnant female mule deer, we will have controls in our study to document the accuracy of the method and make adjustment in the observed fetal rate if necessary. Ten potentially pregnant does that are held in captivity in the Colorado Division of Wildlife Big Game Research Facility on the Foothills Campus, Fort Collins will be untrasounded for pregnancy and fetal rates as a control on the methodology and to test the proposed handling and restraint methods to be used on does during the field operation. These does will be under close surveillance throughout pregnancy and during fawning to verify the ultrasound results. In addition, we will have access to ~ 10 deer to be collected in January or February on the Rocky Mountain Arsenal. These does will be ultrasounded and then necropsied for immediate verification of the effectiveness of detecting the number of fetuses. Ninety-five percent of Colorado mule deer conception dates, based on back-dating from fetal forehead-rump measurements, over a 3 year span (n=135) were reported to be between November 18 and December 12 (Gill 1972). Ultrasounding for fetal rate is most successful on small ungulates during 30-60 days into pregnancy (LaRue Johnson, CSU Veterinary Teaching Hospital, personal communication). We will target the time period ofJanuary 20 through February 10 to do the. ultrasounding. Dr. LaRue Johnson will perform the ultrasounding procedures. Animal Care and Use All capture and handling of animals will comply with the standards of the Colorado State University and Colorado Division of Wildlife Animal Care and Use committees. We will secure trespass permission from study site owners prior to the study. Sample Sizes and Power of Tests The following power analysis (Table 1) was developed to estimate sample sizes necessary to detect various mean departures of fetal rates from historic levels for adult does. For the historic data, we used the weighted mean of fetal rates for adult does from the Poudre River drainage (n = 41, = 1.83, SD = 0.44; Medin and Anderson 1979), Middle park (n = 119, x = 1.86, SD = 0.57; Gill 1971), the Forbes-Trinchera Ranch (n = 18, x = 1.89, SD = 0.47; Freddy 1988), and the Piceance Basin ([1973: n = 61, x= 1.46, SD = 0.77][1978: n = 37, x = 1.65, SD = 0.72]; G. C. White, Colorado State University, personal communication) to estimate the historic mean (1.74) and standard deviation (0.64). We used an expected 1999 standard deviation equal to the historic standard deviation (0.64; G. C. White, personal communication). An alpha of 0.05 was used in our estimates of power. Power of 0.8 or higher is desired. x �150 Table 1. One-tailed power to estimate if 1999 fetal rates differ from historic rate of 1.74 fawns per mature doe (;:: 2 years old). Sample size (n) Fetal rate Power Sample size (n) Fetal rate Power 20 20 20 20 30 30 30 30 40 40 40 40 1.3 1.4 1.5 1.6 1.3 1.4 1.5 1.6 1.3 1.4 1.5 1.6 0.91 0.74 0.49 0.24 0.97 0.87 0.62 0.31 0.99 0.93 0.72 0.36 50 50 50 50 60 60 60 60 80 80 80 80 1.3 1.4 1.5 1.6 1.3 1.4 1.5 1.6 1.3 1.4 1.5 1.6 1.00 0.97 0.79 0.41 1.00 0.98 0.84 0.46 1.00 0.99 0.91 0.53 Regarding sample sizes, the desired differential in fetal rate that we wish to detect is somewhat problematic. We are primarily interested in ascertaining if pregnancy rates and fetal rates are a major contributor to the observed low December fawn:doe ratio (0.36 fawns/doe predicted by the regression equation in 1998) on the Uncompahgre Plateau. Considering historic fetal rates of L 74 fetuses/doe, there apparently is a major failure to breed, inadequate fetal production, a major loss of fetuses, high neonatal fawn mortality, or a combination of these factors which result in only 0.36 fawns/doe (predicted by regression) remaining in December 1998. On average, fawn:doe ratios in Colorado have declined by about 0.015 fawns/doe/year during the last 20 years which results in a decline of about 0.3 fawns/doe over the 20 years. Fawn:doe ratios on the Uncompahgre Plateau have declined by 0.018 fawns/doe/year during the last 17 years (1982-1998), resulting in a decline of 0.30 fawns/doe over the 17 years. Thus, to determine if fetal rates contribute to the observed changes, we will attempt to detect a change of 0.30 fawns/doe. A change of 0.30 fawns/doe represents 21 % of the 1.4 (1.74 - 0.36 [predicted by the regression equation for 1998] = 1.4) reduction in the fawn:doe ratio from fetal counts to December age-ratio counts. Thus, we believe that detecting 21% (±) of the overall loss of fetuses/fawns from the fetal stage of reproduction to December will provide strong evidence that fetal production is or is not a major contributing factor to low fawn:doe ratios. To detect a change of 0.30 fawns/doe, about 40 does will be necessary for our evaluation. Data Analyses Fetal rates obtained during 1999 on the Uncompahgre Plateau will be compared to historic rates with a Z test. Significance level to reject the null hypothesis will be at P < 0.05. LOCATION This study will be conducted on the Uncompahgre 62 (D-19). Plateau, Big Game Management Units 61 and �151 WORK SCHEDULE Jan-Feb 1999 Mar-Jun 1999 Capture and ultrasound does Data analysis and write report PERSONNEL Thomas M. Pojar F. Andelt LaRue W. Johnson David C. Bowden Kenneth P. Burnham Co-Principal Investigator, Colorado Division of WildlifeWilliam Co-Principal Investigator, Department of Fishery and Wildlife Biology, Colorado State University Co-Principal Investigator, College of Veterinary Medicine and Biomedical Sciences, Colorado State University Statistical Consultant, Department of Statistics, Colorado State University Colorado Cooperative Fish and Wildlife Research Unit, Department of Fishery and Wildlife Biology, Colorado State University ESTIMATED COST Item Helicopter capture Veterinary consulting Ultrasound rental Travel expenses Vehicle Mileage TOTAL 10% contingency GRAND TOTAL Number 40 does 1 1 15 days 1 month 2,000 miles CostlItem $ 400 $1,000 $ 600 $ 95 $ 400 $ 0.15 Total $16,000 $ 1,000 $ 600 $ 1,425 $ 400 $ 300 $19,725 1,972 $21,697 s LITERA TURE CITED Barrett, R H. 1981. Pregnancy diagnosis with doppler ultrasonic fetal pulse detectors. Wildlife Society Bulletin 9:60-62. Bartmann, R M. 1998. A prospectus on mule deer in Colorado. Colorado Division of Wildlife, Fort Collins, Colorado, Unpublished report. Bartmann, R M., and T. M. Pojar 1998a Experimental deer inventory. Colorado Division of Wildlife, FederalAid in Wildlife Restoration Job Progress Report, Project W-153-R-ll, July. _, and _. 1998b. Deer reproduction assessment. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-153-R-11, July. Bingham, C. M., P. R. Wilson, and A S. Davies. 1990. Real-time ultrasonography for pregnancy diagnosis and estimation of fetal age in farmed red deer. Veterinary Record 126:102-106. Freddy, D. 1. 1988. Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-153-R-2, July. Gill, R B. 1971. Middle Park deer study - productivity and mortality. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-38-R-25. July:189-207. _. 1972. Productivity studies of mule deer in Middle Park, Colorado: Second Annual Mule Deer Workshop, Elko, Nevada, January 12. Xerox. Lenz, M. F., A W. English, and A Dradjat. 1993. Real-time ultrasonography for pregnancy diagnosis and foetal ageing in fallow deer. Australian Veterinary Journal 70:373-375. �152 Lindahl, I. L. 1971. Pregnancy diagnosis in the ewe by intrarectal doppler. Journal of Animal Science 32:922-925. Medin, D. E., and A. E. Anderson. 1979. Modeling the dynamics of a Colorado mule deer population. Wildlife Monographs 68:1-77. Revel, B., and P. R Wilson. 1991. Ultrasonography of the reproductive tract and early pregnancy in red .deer. Veterinary Record 128:229-233. Salwasser, H., S. A. Holl, G. A. Ashcraft. 1978. Fawn production and survival in the North Kings River deer herd. California Fish and Game 64:38-52. Sasser, R G., C. A. Ruder, and K. A. Ivani. 1986. Pregnancy detection in farm animals by radioimmunoassay of a pregnancy-specific protein in serum. in 1. Hau, ed., Pregnancy proteins in animals. Walter de Gruyer & Co. Berlin. Schrick, F. N., and E. K. Inskeep. 1993. Determination of early pregnancy in ewes utilizing transrectal ultrasonography. Theriogenology 40:295-306. Smith, R B., and F. G. Lindzey. 1982. Use of ultrasound for detecting pregnancy in mule deer. Journal of Wildlife Management 46:1089-1092. Stephenson, T. R, 1. W. Testa. G. P. Adams, R G. Sasser, C. C. Schwartz, and K. 1. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167-172. Welker, H. 1. 1986. Fawn mortality in the Lake Hollow deer herd, Tehama County, California California Fish and Game 72:99-102. White, I. R, W. A. C. KcKelvy, S. Busby, A. Sneddon, and W. 1. Hamilton. 1989. Diagnosis of pregnancy and prediction of fetal age in red deer by real-time untrasonic scanning. The Veterinary Record 124:395-397. Willard, S. T., R G. Sasser, J. C. Gillespie, J. T. Jaques, T. H. Welsh, Jr., and RD. Randel. 1994. Methods for pregnancy determination and the effects of body condition on pregnancy status in Rocky Mountain elk (Cervus elephus nelsonii. Theriogenology 42:1095-1102. �153 DRAFT MANUSCRIPT ESTIMATION OF MULE DEER PREGNANCY AND FETAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO USING TRANSRECTAL ULTRASOUND William F. Andelt, Thomas M. Pojar, and LaRue W. Johnson Abstract Mule deer (Odocoileus hemionus) populations apparently have declined in several western states during the 1990's. In Colorado, mule deer fawn:doe ratios in December have declined by 0.15 fawns/doe/year from 1972 through 1995. Significant declines in the fawn:doe ratio have especially occurred on the Uncompahgre Plateau near Montrose, Colorado. Thus, we estimated adult mule deer pregnancy and fetal rates on the Uncompahgre Plateau during the 1998-1999 reproductive cycle to determine if lower pregnancy or fetal production was the cause of the deer decline. Thirty-seven of 40 (93%) adult does on the Uncompahgre Plateau were detected pregnant with ultrasound, and 36 of the 40 does were detected pregnant with pregnancy-specific protein-B (PSPB). The proportion of does detected pregnant with ultrasound does not differ (Xl) = 0.053, P = 0.817) from the proportion of does pregnant (91.4% of303 does) in previous studies in Colorado. The average number of fetuses/doe for all adult does (pregnant and non-pregnant) on the Uncompahgre Plateau (n = 40, '! = 1.70, SE = 0.109) was not less (Z = 0.340, P = 0.367) than in previous studies (n = 276, '! = 1.74, SE = 0.038). The average number of fetuses/doe for pregnant adult does on the Uncompahgre Plateau (n = 37, '!= 1.84, SE = 0.082) also was not less (Z = 0.260, P = 0.397) than in previous studies (n=258, '! = 1.86, SE = 0.028). INTRODUCTION Mule deer (Odocoileus hemionus) populations apparently have declined in several western states of the United States during the 1990's (Unsworth et al. 1999). In Colorado, mule deer fawn:doe ratios in December have declined by 0.15 fawns/doe/year from 1972 through 1995 (G. C. White, Colorado State University, unpublished data). In particular, fawn:doe ratios on the Uncompahgre Plateau of Colorado have declined (I = -3.39, P = 0.004) by an average of 0.18 fawns/doe/year from 1982-1998, and have ranged from a high of 79 fawns/100 does in 1982 to a low of 32 fawns/l00 does in 1996 and 34 fawns/100 does in 1997 (Colorado Division of Wildlife, unpublished data). In addition to low December fawn:doe ratios, over-winter (December - May) fawn survival on the Uncompahgre Plateau was 49% during the winter of 1997-1998 (Bartmann and Pojar 1998a). The low December fawn:doe ratios are a concern to the public and game managers. Pregnancy rates of collected adult (2:2years old) female mule deer have ranged from 97 to 100% during the 1960's, 1970's, and 1980's in Colorado (Gill 1971, 1972; Medin and Anderson 1979; Freddy 1987, 1988). The average numbers offetuses per adult doe (fetal rate) have ranged from an average of 1.83 to 1.91 (Medin and Anderson 1979; Gill 1971, 1972; Freddy 1987, 1988) during the same period in various areas of Colorado. Several hypotheses exist to explain the decline in December mule deer fawn:doe ratios including a failure to breed, reduced fetal production, resorption/abortion of fetuses, or low summer and fall fawn survival (R. M. Bartmann, Colorado Division of Wildlife, personal communication) mediated by low �154 buck doe ratios and a protracted fawning period, poor habitat quality and reduced nutrition or hiding cover, more predators and increased predation, competition with elk (Cervus elaphus), disease, poisonous plants; drought, or perhaps a combination of these factors. Our objectives in this study were to determine adult mule deer pregnancy and fetal rates on the Uncompahgre Plateau, Colorado during the 1998-1999 reproductive cycle. We hypothesized that pregnancy and fetal rates did not differ from rates obtained during the 1960's, 1970's, and 1980's in Colorado. Transrectal ultrasonography has been used to accurately detect pregnancy in domestic sheep (Schrick and Inskeep 1993), fallow deer (Dama dama; Lenz et aI. 1993), red deer (Cervus elaphus; Bingham et aI. 1990, Wilson and Bingham 1990, Revol and Wilson 1991), and elk (Willard et aI. 1994). Pregnancy-specific protein-B has been used to reliably detect pregnancy in mule deer and white-tailed deer (Odocoi/eus virginianus; Wood et aI. 1986), muskoxen (Ovibos moschatus; Rowell et aI. 1989), fallow deer (Wilker et aI. 1993), moose (Alces alces; Haigh et aI. 1993, Stephenson et aI. 1995), and elk (Willard et aI. 1994, Noyes et aI. 1997). Because neither technique has been used extensively in mule deer, with the exception of Smith and Lindzey (1982) and Wood et aI. (1986), we also verified the accuracy of both techniques. STIJDY AREAS To assess accuracy in determining pregnancy and number of fetuses per mule deer doe, we investigated captive does at the Colorado Division of Wildlife's Foothills Research Facility in Northwest Fort Collins,and wild does that were culled on the USFWS Rocky Mountain Arsenal, Commerce City, Colorado. In our main study, we ultrasounded does on the Uncompahgre Plateau (Game Management Units 61 and 62, Data Analysis Unit (DAU) D-19) in southwestern Colorado. The plateau is about 100 km long and 29-40 km wide, and is bounded by the San Miguel and Dolores rivers on the southwest and west, the Uncompahgre and Gunnison rivers on the east, the Colorado river on the North, and an escarpment of Dakota sandstone above Pleasant Valley and Dallas creeks on the southeast (Anderson et aI. 1992). Topography ranges from gently rolling to steep canyons. Deer were captured on winter range consisting of Pinyon pine (Pinus edulis)-Utahjuniper (Juniperus osteospenna)-sagebrush interspersed with open sagebrush parks. The climate is semi-arid, with warm summers and cold winter. METHODS We evaluated 10__ captive and 15 wild mule deer does to ascertain the accuracy of ultrasound and PSPB for detecting pregnancy and fetal rates. We restrained 6 (5 or 6 years old) of the 10 captive does in a capture pen and immobilized them with an intramuscular injection of 420-500 mg ofketamine and 80-100 mg ofxylazine (a 5:1 mixture) on 25 January 1999. We also immobilized 4 yearling (about 1.6 years old) captive does with a dart gun using 250 mg oftelazol and 125 mg ofxylazine. After processing, tranquilization was reversed with 10 mg of yohimbine. We evaluated the 15 wild does (2 yearling and 13 adults), which were culled for herd management purposes by the U.S. Fish and Wildlife Service, on 31 January 1999. We captured 40 adult mule deer does on the Uncompahgre Plateau with a netgun fired from a Hughes 500C helicopter (Helicopter Capture Services, Marysvale, Utah, USA; Barrett et aI. 1982). The does were captured on deer winter range in proportion to their density within 8 strata located around the edge of the plateau. The deer were manually restrained, hobbled, blindfolded, and transported by helicopter to a base station, usually <6 km from the capture site, where they were processed on 5-8 February 1999. We aged each doe as ajuvenile, yearling, or adult by tooth replacement and wear, weighed each doe, and injected the first 32 does subcutaneously �155 with 5 ml of vitamins A (500,000 iu's), D3 (50,000 iu's), and E (1,500,000 iu's). We attached a 148 MHz telemetry collar, and, after processing, released all except 1 doe at the processing sites; the 1 doe was transported by helicopter to the capture site and released there because a steep canyon separated the capture and processing sites. In addition, 1 juvenile female, 2 yearling females, and 2 males were captured. The juvenile was immediately released at the processing site, the 2 yearlings were processed similar to the adult does and released at the processing site, and the 2 males were immediately released at the capture site. We processed and released does within about 30 minutes of capture. We placed the 25 does used for accuracy evaluation and the 40 study does in dorsal recumbency and used a portable ultrasound unit (Aloka 500V, Aloka, Wallingford, Connecticut, USA) with a 5 MHZ linear-array probe, powered by a portable generator in the field, to ascertain pregnancy and number of fetuses/doe via trans rectal ultrasonography (Smith and Lindzey 1982, Bingham et al. 1990, Stephenson et al. 1995). We also collected about 10 ml of blood viajugular venipuncture to assess levels ofPSPB and ascertain pregnancy status. The blood was allowed to clot, centrifuged, and, the serum was decanted and stored on ice and then frozen. The serum was submitted to BioTracking (Moscow, Idaho, USA) to assess levels ofPSPB (Stephenson et al. 1995, Noyes et al. 1997). We ascertained accuracy of the ultrasound and PSPB procedures by performing necropsies and counting the number of fetuses in 1 captive doe that died from chronic wasting disease and 3 other does that were euthanized because of chronic wasting disease (M. A. Wild, Colorado Division of Wildlife, personal communication). We also ascertained accuracy of the ultrasound and PSPB by counting the number of fawns born during May-June 1999 for the other 6 captive does, whereas we necropsied the does collected on the Rocky Mountain Arsenal to determine the number of fetuses. One of us (L WJ) had extensive experience using ultrasound techniques and conducted all ultrasound procedures. Apriori, we conducted a power analysis to estimated the sample size necessary to detect a departure in fetal rates from previous studies of fetal rates in Colorado. For the previous studies, we used the weighted mean of fetal rates for adult does from .the Poudre River drainage (n = 41, x = 1.83, SD = 0.44; Medin and Anderson 1979), Middle Park (n = 119, x= 1.86, SD = 0.57; Gill 1971), the Forbes-Trinchera Ranch (n = 33, x = 1.91, SD = 0.46; Freddy 1987, 1988), and the Piceance Basin ([1973: n = 61, x= 1.46, SD = 0.77][1978: n = 37, x= 1.65, SD = 0.72]; G. C. White, Colorado State University, personal communication) to estimate a historic mean (1.74) and standard deviation (0.64). We used an expected 1999 standard deviation equal to the historic standard deviation (0.64; G. C. White, personal communication) in our analysis. We were primarily interested in ascertaining if pregnancy rates and fetal rates were a major contributor to the observed low December fawn:doe ratio (0.36 fawns/doe predicted by the regression equation for 1998 using data on fawn:doe ratios from 1982-1998) on the Uncompahgre Plateau. Considering historic fetal rates of 1.74 fetuses/doe, and a predicted fawn:doe ratio of 0.36 remaining on the Uncompahgre Plateau in December 1998, there is considerable loss of fetuses or fawns. On average, fawn:doe ratios in Colorado have declined by about 0.015 fawns/doe/year from 1972 to 1995 which results in a decline of about 0.3 fawns/doe over the 23 years. Fawn:doe ratios on the Uncompahgre Plateau have declined by 0.018 fawns/doe/year during the last 17 years (1982-1998), resulting in a decline of 0.30 fawns/doe over the 17 years. Thus, we attempted to determine if fetal rates contributed to the observed change of 0.30 fawns/doe which represents only 21% of the observed reduction in the fawn:doe ratio of 1.4 (1.74 - 0.36 [predicted by the regression equation for 1998] = 1.4). Thus, our sample size of 40 does was aprior estimated to have power of 80% for detecting a change of 0.3 fawns/doe at an alpha of 0.05. The proportion of adult does pregnant during 1999 was compared to historic data with a chisquare test (proc Freq, SAS Institute 1988). Fetal rates obtained during 1999 were compared to historic rates with a Z-test. An alpha level 0[0.05 was considered significant. �156 RESULTS Via necropsy or observing newborn fawns, we ascertained that 1 of the 10 captive does did not have a fetus, 3 does produced 1 fetus or fawn, and 6 does produced twin fetuses or fawns. Via ultrasound, we estimated that 3 captive does had single fetuses, 6 does had twins, and 1 doe had triplets. Thus, for each of 3 does, we estimated 1 more fetus via ultrasound compared to necropsies or observation of newborn fawns. All does were detected pregnant via PSPB levels. We necropsied the 15 culled mule deer does (2 yearlings and 13 adults) and found 5 does (2 yearlings and 3 adults) were barren, 3 does each contained 1 fetus, 6 does contained twins, and 1 doe contained triplets. Using ultrasound, we accurately detected all 15 does as pregnant or not pregnant. We also detected the correct number of fetuses per doe for 12 of the 15 does. We incorrectly detected 3 fetuses via ultrasound in 1 doe but she had only 2 fetuses, and we detected only 1 of 2 fetuses in 2 other does. PSPB levels indicated that 12 of the 15 does were pregnant; two of the 12 does were not detected-pregnant via both ultrasound and necropsy .. Thirty-seven of the 40 (93%) adult does on the Uncompahgre Plateau were detected pregnant with ultrasound. This proportion does not differ (XZJ = 0.053, P = 0.817) from the proportion of does pregnant (91.4% of303 does) in previous studies in Colorado (Gill 1971, 1972; Medin and Anderson 1979; Freddy 1987, 1988; R M. Bartmann, Colorado Division of Wildlife, unpublished data). The average number of fetuses/doe for all adult does (pregnant and non-pregnant) on the Uncompahgre Plateau (n = 40, ~= 1.70, SE = 0.109) was not less (Z= 0.340, P = 0.367) than in previous studies (n = 276, ~= 1.74, SE = 0.038; Gill 1971, 1972; Medin and Anderson 1979; Freddy 1987, 1988; R M. Bartmann, Colorado Division of Wildlife, unpublished data). The average number of fetuses/doe for pregnant adult does on the Uncompahgre Plateau (n = 37, ~ = 1.84, SE = 0.082) also was not less (Z = 0.260, P = 0.397) than in previous studies (n = 258, ~ = 1.86, SE = 0.028). PSPB levels concurred with ultrasound in ascertaining pregnancy in 39 of the 40 does; PSPB levels indicated 1 doe was not pregnant whereas 2 fetuses were visually detected via ultrasound. DISCUSSION We failed to detect a difference in pregnancy and fetal rates of adult female mule deer between our and previous studies in Colorado. Bartmann and Pojar (1998b) also found a relative high pregnancy rate of93.0% for 29 does ~1 year old near Red Feather, Colorado during January 1998. Thus, a failure to breed or maintain pregnancy thru at least early February can be discounted as the cause of the low fawn:doe ratios observed on the Uncompahgre Plateau. We restricted our. analyses of pregnancy and fetal rates to adult (~2 years old) mule deer does. We did not include yearlings in our sample because a lower proportion of yearlings become pregnant and they have lower fetal rates which would have biased our comparisons to historic rates unless the proportions of yearlings in both samples were equal. �157 LITERATIJRECITED Anderson, A. E., D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Colorado Division of Wildlife Technical Publication No. 40. Fort Collins, Colorado, USA. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R M. 1998. A prospectus on mule deer in Colorado. Colorado Division of Wildlife, Fort Collins, Colorado, USA. Unpublished report. _, and T. M. Pojar 1998a. Experimental deer inventory. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration, Project W-153-R-11, Progress Report . ._, and _. 1998b. Deer reproduction assessment. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration, Project W-153-R-11, Progress Report. Bingham, C. M., P. R Wilson, and A. S. Davies. 1990. Real-time ultrasonography for pregnancy diagnosis and estimation of fetal age in farmed red deer. The Veterinary Record 126:102-106. Freddy, D. J. 1987. Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration, Project 01-03-047, Progress Report. Freddy, D. J. 1988. Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration, Project W-153-R-2, Progress Report. Gill, R B. 1971. Middle Park deer study - productivity and mortality. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration, Project W-38-R-25, Progress Report. _. 1972. Productivity studies of mule deer in Middle Park, Colorado. Second Annual Mule Deer Workshop, Elko, Nevada Haigh, J. C., W. J. Dalton, C. A. Ruder, and R G. Sasser. 1993. Diagnosis of pregnancy in moose using a bovine assay for pregnancy-specific protein B. Theriogenology 40:905-911. Lenz, M. F., A. W. English, and A. Dradjat. 1993. Real-time ultrasonography for pregnancy diagnosis and foetal ageing in fallow deer. Australian Veterinary Journal 70:373-375. Medin, D. E., and A. E. Anderson. 1979. Modeling the dynamics of a Colorado mule deer population. Wildlife Monographs 68: 1-77. Noyes, J. H., R G. Sasser, B. K. Johnson, L. D. Bryant, and B. Alexander. 1997. Accuracy of pregnancy detection by serum protein (PSPB) in elk. Wildlife Society Bulletin 25:695-698. Revol, B., and P. R Wilson. 1991. Ultrasonography of the reproductive tract and early pregnancy in red deer. The Veterinary Record 128:229-233. Rowell, J. E., P. F. Flood, C. A. Ruder, and R G. Sasser. 1989. Pregnancy-specific protein in the plasma of captive muskoxen. Journal of Wildlife Management 53:899-901. . Salwasser, H., S. A. Hell, G. A. Ashcraft. 1978. Fawn production and survival in the North Kings River deer herd. California Fish and Game 64:38-52. SAS Institute Inc. 1988. SAS/STAT User's guide, release 6.03 edition, SAS Institute Inc., Cary, North Carolina, USA. Schrick, F. N., and E. K. Inskeep. 1993. Determination of early pregnancy in ewes utilizing transrectal ultrasonography. Theriogenology 40:295-306. Smith, R B., and F. G. Lindzey. 1982. Use of ultrasound for detecting pregnancy in mule deer. Journal of Wildlife Management 46:1089-1092. Stephenson, T. R, J. W. Testa G. P. Adams, R. G. Sasser, C. C. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167-172. Unsworth, J. W., D. F. Pac, G. C. White, R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. �158 Wilker, c., B. Ball, T. Reimers, G. Sasser, M. Brunner, B. Alexander, and M. Giaquinto. 1993. Use of pregnancy-specific protein-B and estrone sulfate for determination of pregnancy on day 49 in fallow deer (Dama dama). Willard, S. T., R G. Sasser, J. C. Gillespie, J. T. Jaques, T. H. Welsh, Jr., and RD. Randel. 1994. Methods for pregnancy determination and the effects of body condition on pregnancy status in Rocky Mountain elk (Cervus elephus nelsoni). Theriogenology 42:1095-1102. Wilson, P. R, and C. M. Bingham. 1990. Accuracy of pregnancy diagnosis and prediction of calving date in red deer using real-time ultrasound scanning. The Veterinary Record 126:133-135. Wood, A. K., R E. Short, A. Darling, G. L. Dusek, R G. Sasser, and C. A. Ruder. 1986. Serum assays for detecting pregnancy in mule and white-tailed deer. Journal of Wildlife Management 50:684--687. �159 APPENDIX II Research Program Narrative IMPACT OF PREDATION AND VEGETATIVE COVER ON NEONATAL MULE DEER FAWN SURVIVAL 21 October 1998 Principal Investigators: THOMAS M. POJAR Colorado Division of Wildlife 317 W. Prospect Fort Collins, CO 80526 970-472-4308 WILLIAM F. ANDELT Department of Fishery and Wildlife Biology Colorado State University Fort Collins, CO 80523 970-491- 7093 �160 �161 PROGRAM NARRATIVE State of --"C=o=lo=r=ad=o~ _ Project No. W!..!.--.:..:15::..::3:....-R~ _ Work Package No. _;3:::..;0:<...:0'-"1 _ Task No. ----:.4 _ Cost Center 3430 Mammals Program Deer Conservation Impact of Predation and Vegetative Cover on Mule Deer Fawn Survival NEED There is evidence that the mule deer (Odocoileus hemionus) population in Colorado has declined during recent years due mostly to low fawn survival and subsequent low population recruitment (Bartmann 1997). Colorado Division of Wildlife quadrat surveys to estimate population size suggest that some mule deer herds have declined by 31 % since 1992 while some have not shown much change during this time (Bartmann 1997). On 2 areas where recent over-winter (1997-98) survival was estimated, rates of fawn and adult doe survival was 74% (n = 38) and 100% (n = 30) for the Red Feather herd (D-4) and 49% (n = 39) and 84% (n =31) for the Uncompahgre herd (D-19), respectively (Bartmann and Pojar 1998a). This supports the contention that some of the purported population declines may be influenced by over-winter fawn survival. However, some herds have low December fawn:doe ratios indicating possible deficiencies in 2 major population growth mechanisms - initial fawn production (pregnancy rates) and neonatal fawn survival (Bartmann 1998). Pregnancy rates during January 1998 were 93% for 29 does >1 year old in the Red Feather DAU (Bartmann and Pojar 1998b) which was similar to 92.0% ofl63 does (>2 years old) pregnant in the same area during 1961-1964 (Medin and Anderson 1979), a 94.8% pregnancy rate for adult does (n = 114) and a 94.0% pregnancy rate for adult and yearling does (n = 134) in Middle Park (Gill 1971), and rates of 89% (n = 47) during 1973 and 82% (n = 83) during 1978 in the Piceance Basin (Bartmann 1998). The 1998 data indicate that the proportion of does becoming pregnant probably was not contributing to the low fawn:doe ratios, however these data were not collected in the Uncompahgre DAU where ratios were lowest. Pregnancy rates will be obtained in the Uncompahgre DAU during January 1999 to ascertain if these rates are contributing to the low fawn:doe ratios. Fetal rates for does older than yearlings were 1.83 (n = 41) in the Cache la Poudre River drainage from 1961-1965 (Medin and Anderson 1979) and 1.82 (n = 114) in Middle Park (Gill 1971). If fetal rates are currently as high as they were in the 1960's, then high rates of fawn mortality are likely responsible for the low. and declining fawn:doe ratios. Thus, determining the causes and magnitude of fawn mortality from birth through December will be extremely important for understanding mule deer population trends in Colorado. Low neonatal fawn survival is probably the most sensitive indicator that the environmental needs of populations are not being met (Gaillard et al. 1998). Fawn:doe ratios obtained in December have declined by an average of 1.5 fawns per 100 does per year from 1972-1995 (Bartmann 1997, G. C. White, Dept. Fishery and Wildlife Biology, Colorado State University, pers. commun.). December 1997 fawn:doe ratios were 34.2 in the Uncompahgre DAU and 58.8 in the Red Feather DAU (Bartmann and Pojar 1998a). The December fawn:doe ratios and over-winter survival rates indicate that the status of the Uncompahgre deer herd is of greatest concern. Gruell (1986) hypothesizes that historic (1880-1930) domestic livestock grazing and fire suppression caused successional changes in rangeland communities favoring shrubby species resulting in optimal mule deer habitat during the period 1930-1960. These conditions resulted in the irruption and overpopulation of deer herds and may have reduced present day carrying capacity which may be �162 mediated by lower nutrition andlor greater susceptibility to predation (see also Salwasser et al. 1978). Fire suppression and removal of herbaceous species by grazing can foster conditions that favor woody species invasion (Skovlin 1991) and decadent/senescent stands of shrubby species (Clements and Young 1996) thereby reducing the canying capacity for deer. Once the stable state of a particular vegetation type has been disrupted, especially in arid or semi-arid rangeland types, the vegetative community may stabilize at a lower successional state that is highly resistant to change without drastic perturbations (Laycock 1991). It is possible this situation is in process on the Uncompahgre Plateau (and other areas of the West) with the constant expansion of the pinon-juniper vegetative community into sagebrush and grassland communities. A low fawn:doe ratio on the Uncompahgre DAU could result from several causes including malnutrition and predation. Competition with elk (Cervus elaphus) for food or space on wintering grounds, or for fawning sites on summer range may cause poor neonate survival through decreased nutrition or increased susceptibility to predation. Livestock grazing can reduce forbs and fawn hiding cover (Loft et al. 1987) which can influence nutrition and predation (Smith and LeCount 1979, Bowyer and Bleich 1984), but there likely is less livestock grazing now thanwhen deer were more abundant indicating recent grazing may not be the cause of the decline. A short-term drought may have reduced forage for lactating does, may have protracted the fawning period making fawns more susceptible to predators as in white-tailed deer (Odocoi/eus virginianus, Andelt et al. 1987), or reduced alternate prey for predators which may be exacerbating the low fawn:doe ratios. Smith and LeCount (1979) reported that survival of mule deer fawns was associated with winter forb yield and October-April rainfall of the winter-spring period preceding the fawning period. Coyotes (Canis latrans) and other predators kill and eat mule deer fawns and adults, however the population impact of this predation is variable. Connolly (1978) cited 31 studies which reported predation as a limiting or regulating influence on ungulate populations in North America Connolly (1978) also cited 27 studies which indicated that predators did not limit or control the size of ungulate populations. Filonov (1980) provides evidence that the total loss to natural mortality for ungulates is relatively stable and that it is maintained by a complex system of compensating mechanisms, one of which is predation. Because of functional substitution of mortality factors, the various reasons for natural mortality are independent of the total mortality and the range of mortality rates remains somewhat constant. An example of compensatory mortality was demonstrated in the Piceance Basin of Colorado where predator control reduced overwinter mule deer mortality to predators, but the effect was compensated for by additional mortality due to starvation (Bartrnann et al. 1992). We need to determine the causes of neonatal fawn mortality in areas with low fawn:doe ratios, such as Uncompahgre Plateau, so that we know where to focus experimental research and management. Predator density is one factor that may have a significant impact on fawn survival independent of vegetational or nutritional components of the habitat (Smith et al. 1986). Coyotes, black bears (Ursus americanus), mountain lions (Felis concolor), and bobcats (Felis rufus) are found on the Uncompahgre Plateau and in other areas of Colorado, and may have a limiting effect on mule deer. Coyotes have been responsible for high neonatal white-tailed deer fawn (Cook et al. 1971, Garner et al. 1976, Litvaitis and Bartush 1980, Stout 1982), high neonatal mule deer fawn (Steigers and Flinders 1980, Steigers 1981), and high overwinter mule deer fawn (White et al. 1987) mortality. Beck (1995) reported a density of O. 93 black bears/mf on the Uncompahgre Plateau, and black bears can prey on mule deer fawns (Smith 1983), white-tailed deer fawns (Ozoga and Verme 1982, 1986; Mathews and Porter 1988), and elk calves (Schlegel 1976). Anderson et al. (1992) estimated that a minimum population of34 mountain lions on 3,120 km2 of the Uncompahgre Plateau may have killed 1,885 to 2,060 mule deer or about 8 to 12% of the estimated wintering deer population during 1987. Welker (1986) reported that mountain lions killed 2 or 3 of 16 radioed mule deer fawns; Bleich and Taylor (1998) found that mountain lion predation on adult does was the primary source of mortality in northeastem California herds. Bobcats also kill deer (Litvaitis et al. 1986) and pronghorn fawns �163 (Antilocapra americana) (Autenrieth 1982, 1984). Although these predators kill deer, their impact on mule deer fawn:doe ratios in Colorado is unknown. If predators are responsible for the low fawn:doe ratios, we need to determine which predator is the major contributor, and if some factors, such as low hiding cover, less alternate prey (Horejsi 1982, Andelt et al. 1987), a protracted fawning season, predator abundance, and possibly a high predator:deer ratio are making fawns more vulnerable to predation. Height of vegetation apparently plays an important role in the survival of neonate ungulates. Riley and Dood (1984) and Boyer et al. (1998) reported that mule deer fawns and (Decker 1991) reported that white-tailed deer fawns selected habitat types with dense vegetative cover. Horejsi (1982) reported that in years of drought, mule deer fawn survival was lower in areas oflivestock grazing and attributed this to decreased ground cover. Benzon (1996) reported that white-tailed deer fawns in the Black Hills, South Dakota, selected an understory of grasses for diurnal bed sites; height and density of vegetation was higher at bed sites than what was randomly available. Tucker and Garner (1983) reported that bed sites of pronghorn <4 weeks old were found in cover taller than that in surrounding areas. Autenrieth (1982, 1984) suggested that taller cover was important for reducing pronghorn fawn mortality to predators. Rothchild (1993) reported that vegetation was taller at the bed sites of pronghorn fawns than at random sites and the vegetation also was taller at bed sites of surviving pronghorn fawns compared to fawns that did not survive. Rothchild et al. (1984) suggested that pronghorn fawns with larger home ranges may sustain higher coyote predation in tall grass prairie of east central Kansas. Fawns have an infinite number of potential bed site locations within their home ranges. Measurement of random sites that are possible bed sites should be within a typical home range of a fawn. Home ranges of mule deer fawns in northern Colorado were variable and estimated at 130 ha from 10 June through August (Geduldig 1981). Average summer home range size offawns was 185 ha in the Missouri River Breaks, Montana and home range size decreased with increased population size (Riley and Dood 1984). Home range size of fawns increased with age in south-central Washington and averaged 257 ha for fawns 60 days or older (Steigers and Flinders 1980). Mule deer fawns traveled variable distances each day, and these distances more than doubled when fawns were 61-90 days old (640 m) compared to when 1-30 days old (319 m) (Steigers and Flinders 1980). OBJECTIVES We propose to identify the agents of mortality and quantify the extent of depredations on neonatal mule deer fawns. We also propose to correlate height, density, and composition of vegetation at fawn birth and bed sites with fawn survival. HYPOTHESES Our hypotheses are divided under two research areas, predation and vegetative cover. 1. What is the contribution of coyotes and other predators to neonatal mule deer fawn mortality? Hoi: The proportions of fawns killed by coyotes, black bears, mountain lions, and bobcats do not differ from one another. H.,2: Predation on fawns is not related to sex or activity of fawns; activity as measured by the distance between successive bed sites. Ho3: Predation on fawns to 8 weeks of age is not related to the average distance between a fawn and its mother. H04: Survival offawns and causes of mortality do not differ among 3 vegetatively and ecologically different study areas. Hos: Fawn birth weights and measurements do not differ among study areas. Roo: Distances between fawn bed sites do not differ among study areas. �164 2. Do height and density, and/or composition of vegetation at fawn birth and bed sites correlate with the percent of fawns killed by predators? H"I: Predation rates on fawns is not related to height and density (visual obstruction readings), and/or composition of vegetation at birth and bed sites. Ho2: Height and density (visual obstruction readings, VOR), and/or composition of vegetation do not differ between fawn bed sites and random sites. Ho3: Height and density (VOR), and/or composition of vegetation at fawn bed sites and random sites do not vary among study areas. EXPECTED RESULTS OR BENEFITS This research will quantify the amount and causes of neonatal fawn mortality and contribution of various predators to this mortality. The influence of vegetative characteristics at birth and bed sites on subsequent fawn survival will be estimated. Knowledge of these factors will assist in evaluating the causes of low December fawn:doe ratios and will guide future research to determine the effect of various experimental manipulations on neonatal fawn survival. For political, social, and economic reasons, we need to have knowledge about the causes of low fawn:doe ratios before corrective action is taken. APPROACH Animal Care and Use: All capture and handling of animals will comply with the standards of the Colorado Division of Wildlife and Colorado State University Animal Care and Use Committees. We will obtain a collectors permit from the Colorado Division of Wildlife and secure trespass permission from study site owners prior to the study. Fawn Capture: In a related study, 40 radioed mature does will be monitored on each study area to determine adult doe survival (Federal Aid Project W-153-R); fawns will be located primarily by monitoring these does and capturing their fawns. Our objective will be to capture and radio 25-35 fawns on each of 3 study areas. Three study areas will be selected based on : a) contrasting vegetative/ecological characteristics, b) a range in fawn:doe ratios indicating contrasting fawn survival rates, and c) availability of radio collared does to minimize fawn capture costs and ensure randomness in fawn capture. Three candidate areas which meet all 3 characteristics are: The Uncompahgre, Middle Park, and Red Feathers DAUs. Fawns <10 days old will be captured and fitted with expandable, drop-off radio collars. Fawns younger than 24 hr will not be captured to allow dam-newborn fawn bonding (White et al. 1972). Precautions will be taken to minimize injury or abandonment by the dam from the capture operation based on recommendations of Beale and Smith (1973) and Livezey (1990). The radio collars and all handling equipment will be stored in containers with native shrub/tree (sagebrush or juniper) material to help mask "unnatural" odors. Plastic gloves will be worn by the handlers. Fawn Processing: Captured fawns will be blindfolded, weighed, and the right hind foot will be measured as an index of skeletal size. If age is not known from observed parturition, it will be estimated by hoof condition and length, umbilical condition, and general body size, activity, and hair coat condition will be subjective measures of age. Each fawn will be individually marked with a plastic ear tag in the right ear; the ear tag will have engraved numbers which contrast to the color of the tag. An expandable radio transmitter (with mortality sensor) collar will be fitted; the collar will be designed to drop off after about 6 months. Before release, the fawn will be examined for injuries and it's general health and condition will be noted and recorded. Each fawn will be carefully observed after release and, . if possible, observed until it is rejoined by it's mother. �165 Fawn and Doe Monitoring: Each fawn and doe will be radio located daily for the first 6 weeks of the fawn's life, every 3rd day for the next month, and then once weekly through the end of November. Precautions will be taken to avoid disturbance of the fawn or dam during radio relocation except when prescribed bed site measurements are taken (see below). Radios on mortality signal will be located and the carcass (if available) will be examined for cause of death using criteria outlined in White (1973), Wade and Bowns (1984), Acorn and Dorrance (1990), and Andelt et al. (1998). If the carcass is missing, the general area will be surveyed for signs of predation and our best judgement of cause of death will be made or the cause will be recorded as "unknown". Birth and Bed Site Measurements: Vegetative cover will be measured at birth sites when they can be positively identified. Measurements will be taken at bed sites every 5th day to minimize disturbance of individual fawns. If a bedded fawn is found and does not flush, the point of observation will be flagged and GPS coordinates will be recorded. Distance to the bed sitewill be measured with a laser range finding scope (e.g. Bushnell "yardage Pro") and the direction to the site will be measured with a hand held compass. Marked bed sites will be measured the next day to minimize any changes in vegetation from time of use. The objective will be to obtain lObed site measurements for each fawn during their first 8 weeks of life. Micro habitat vegetational measurements of birth and bed sites will be a modification of those taken by Benzon (1996). Cover of shrubs by species, grass, and forbs will be estimated using 4 0.1 m2 (20 x 50 em) quadrants (Daubenmire 1959) 'placed in the 4 cardinal directions length-wise from the bed center; the 20 em end of the frame will be centered on and touching the bed site center stake. Visual obstruction from the birthlbed site will be estimated from the 4 cardinal directions using a robel pole viewed from a distance of 4 m and height of 0.5 m from the site (Robel et al. 1970). No adjustments will be made for relief in the terrain. For every birth or bed site measured, we will take identical measurements on IO.random sites within aBO ha square area centered on the bed site. The random sites will be located using random coordinates. Sample Sizes and Power of Tests: Estimates of the means and variances of2 or more treatments are necessary before conducting power analyses. Estimates of these parameters are not known for the proportions of fawns killed by various predators, and the effect of vegetation height on susceptibility of fawns to predation. However, some educated guesses about the magnitude of these parameters will help determine sample sizes. We calculated power for our hypotheses of primary management interest including: 1) proportions of fawns killed by various predators, and 2) the effect of vegetation height on susceptibility of fawns to predation. We calculated for vegetation height vs. susceptibility to predation by using 2 height categories, whereas the actual analysis' will consist of regression using a continuum of vegetation heights. Thus, the power of the actual experiment likely will be somewhat less than presented below. We did not calculate power for our hypothesis of differences in vegetation height at fawn bed sites and random sites because sample sizes will be inherently larger that number 2 above. An alpha of 0.05 was used in all estimates of power. Power of 0.8 or higher is desired. Data Analyses: The proportions of fawns killed and the proportions killed by various causes of mortality (predation, disease, malnutrition) will be compared among study areas with chi-square (proc Freq, SAS Institute, Inc. 1988). The proportion of fawns killed by various predators and the proportions of male and female fawns killed by predators will be compared with chi-square. The effect of distance between bed sites and the distance between fawns and their mothers on fawn survival will be estimated with logistic regression (Proc Genmod, SAS Institute Inc. 1993) by blocking on study areas. Fawn birth weights and measurements, and distances between consecutive bed sites will be compared among study areas with analysis of variance. The effect of vegetation height and density (VOR) on survival of fawns will be estimated with logistic regression (proc Genmod, SAS Institute Inc. 1993) by blocking on study �166 Power for Evaluating if the Expected Relative Proportions of Fawns Killed by Coyotes, Black Bears, and Mountain Lions Varies from Equality (i.e. 0.33 killed by each predator): Fawns killed en) 10 20 30 50 75 100 10 20 30 50 75 100 Coyotes 0.5 0.5 0.5 0.5 0.5 0.5 0.7 0.7 0.7 0.7 0.7 0.7 Proportion killed by various predators Black Bears Mountain Lions 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 Power 0.16 0.27 0.39 0.60 0.79 0.90 0.59 0.89 0.98 1.00 1.00 1.00 I-Sided Power for the Effect of Vegetation Height on Survival of Fawns to 2 Months: Sample sizes Short 20 40 40 80 40 40 40 Tall 20 40 40 80 40 40 40 ProPQrtion surviving Short Tall 0.7 0.8 0.7 0.8 0.7 0.9 0.7 0.9 0.5 0.64 0.5. 0.7 0.5 0.8 Power 0.11 0.18 0.61 0.88 0.27 0.73 0.80 areas (Appendix 1). The height and density of vegetation at fawn bed sites and random sites will be compared with analysis of variance by blocking on study areas. The proportion of vegetation that is composed of forbs, grass, and shrubs will be compared between bed sites and random sites and among study areas with analysis of variance. Significance level to reject the null hypothesis will be at P < 0.05. LOCATION This study will be done on 3 areas, Uncompahgre Plateau (D-19), Middle Park (D-9), and Red Feathers (D-4). WORK SCHEDULE Oct-Dec 1998 Jan-May 1999 Jun-Dec 1999 Jan-Jun 2000 Complete Program Narrative and confirm study area selection Procure and test field equipment and hire summer crew Capture, radio collar, and track fawns Data analysis and report writing PERSONNEL Thomas M. Pojar Co-Principal Investigator, CDOW William F. Andelt Co-Principal Investigator, Department of Fishery and Wildlife Biology, Colorado State University �167 David C. Bowden Statistical Consultant, Department of Statistics, Colorado State University Gary C. White Analytical Consultant, Department of Fishery and Wildlife Biology, Colorado State University ESTIMATED COST Personal Services PFTE costs Andelt Pojar TFTE costs Operating Vehicle (4x4) Radios Field equipment Travel Expenses Capitol TOTAL 5% contingency GRAND TOTAL FY 98-99· FY 99-00b Totalc $ 56,250 $ 45,000 $ 18,216 $ 75,000 $ 60,000 $ 26,717 $131,250 $105,000 $ 44,933 $ 18,306 $ 22,000 $ 13,500 $ 1,800 $ 33,900 na na $ 2,250 0 $197,867 $ 9,893 $207,760 $ 52,206 $ 22,000 $ 13,500 $ 4,050 0 $372,939 $ 18,647 $391,586 o $175,072 $ 8,754 $183,826 "Cost for FY 1998-99, representing field operations during May-June, 1999. "Cost for completion of the 1999 field operation during FY 1999-00, July-December 1999. "Total cost for 1 complete field season spanning 2 fiscal years. LITERATURE CITED Acorn, R. C., and M. 1. Dorrance. 1990. Methods of investigating predation of livestock. Alberta Agric. Prot. Branch. Edmonton. 36pp. Andelt, W. F., M. Bruscino, and C. Niemeyer. 1998. Interpreting the physical evidence of predation on big game animals and domestic livestock. Unpublished. Andelt, W. F., 1. G. Kie, F. F. Knowlton, and K. Cardwell. 1987. Variation in coyote diets associated with season and successional changes in vegetation. Journal of Wildlife Management 51:273277. Anderson, A. E., D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Colorado Division of Wildlife Technical Publication No. 40. Fort Collins, Colorado, USA. Anderson, A. E., and D. E. Medin. 1965a. Reproductive studies. Colorado Game, Fish, and Parks Department, Federal Aid in Wildlife Restoration Job Progress Report, Project W-38-R-4. January:165-193. Anderson, A. E., and D. E. Medin. 1965b. Reproductive studies. Colorado Game, Fish, and Parks Department, Federal Aid in Wildlife Restoration Job Progress Report, Project W-38-R-4. January Part 4:522-552. �168 Anderson, A. 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Pojar 1998a Experimental deer inventory. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-153-R-ll, July. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Beale, D. M., and A. D. Smith. 1973. Mortality of pronghorn antelope fawns in western Utah. Journal of Wildlife Management. 37:343-352. Beck, T. 1995. Development of black bear inventory techniques. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-153-R-8, WP 5, Job 2, July. Benzon, T. A. 1996. Mortality and habitat use of white-tailed deer fawns in the Northern Black Hills, South Dakota, 1991-1994. Completion Report. Pittman-Robertson Project W-75-R-34. Bowyer, R. T., and V. C. Bleich. 1984. Effects of cattle grazing on selected habitats of southern mule deer. California Fish and Game 70:240-247. Boyer, R. T., 1. G. Kie, and V. Van Ballenberghe. 1998. Habitat selection by neonatal black-tailed deer: climate, forage, or risk of predation. Journal of Mammalogy 79:415-425. Clements, C. D., and 1. A. Young. 1997. A viewpoint: Rangeland health and mule deer habitat. Journal of Range Management 50:129-138. Connolly, G. E. 1978. Predators and predator control in big game management. Pages 369-394 in 1. L. Schmidt and D. L. Gilbert, eds. Big game of North America Stackpole Books, Harrisburg, Pa Daubenmire, R. 1959. A canopy-coverage method of vegetation analysis. Northwest Science. 33:4364. Filonov, C. 1980. Predator-prey problems in nature reserves of the European part of the RSFSR. Journal of Wildlife Management. 44:389-396. Gaillard, J. M., M. Festa-Bianchet, and N. G. Yoccoz. 1998. Population dynamics oflarge herbivores: variable recruitment with constant adult survival. Trends in Ecology and Evolution 13:58-63. Garner, G. W., J. A. Morrison, and J. C. Lewis. 1976. Mortality of white-tailed deer fawns in the Wichita Mountains, Oklahoma. Proceedings of the Annual Conference of Southeastern Fish and Wildlife Agencies 30:493-506. Geduldig. H. L. 1981. Summer home range of mule deer fawns. Journal of Wildlife Management 45:726-728. Gill, R. B. 1971. Middle Park deer study - productivity and mortality. Colorado Division of Wildlife, Federal Aid in Wildlife Restoration Job Progress Report, Project W-38~R-25. July:189-207. Gruell, G. E. 1986. Post-1900 mule deer irruptions in the Intermountain West. United States Department of agriculture, Forest Service. Intermountain Research Station, Ogden, Utah. General Technical Report INT-206. �169 Horejsi, R G. 1982. Mule deer fawn survival on cattle-grazed and ungrazed desert ranges. Arizona Game and Fish Department Federal Aid Project Report, Phoenix. 43pp. Laycock, W. A. 1991. Stable states and thresholds of range condition on North American rangelands: A viewpoint. Journal of Range Management 44:427-433. Litvaitis, J. A and W. S. Bartush. 1980. Coyote-deer interactions during the fawning season in Oklahoma Southwestern Naturalist 25: 117-118. Litvaitis, J. A, A G. Clark, and J. H. Hunt. 1986. Prey selection and fat deposits of bobcats (Felis rufus) during autunm and winter in Maine. Journal ofMammalogy 67:389-392. Livezey, K. B. 1990. Toward the reduction of marking-induced abandonment of newborn ungulates. Wildlife Society Bulletin 18:193-203. . Loft, E. R, J. W. Menke, J. G. Kie, and R. C. Bertram. 1987. Influence of cattle stocking rate on the structural profile of deer hiding cover. Journal of Wildlife Management 51:655-664. Mathews, N. E., and W. F. Porter. 1988. Black bear predation of white-tailed deer neonates in the central Adirondacks. Canadian Journal of Zoology 66: 1241-1242. Medin, D. E., and A. E. Anderson. 1979. Modeling the dynamics of a Colorado mule deer population. Wildlife Monographs 68: 1-77. Ozoga, J. J., and L. J. Verme. 1982. Predation by black bears on new-born white-tailed deer. Journal ofMammalogy 63:695-696. Ozoga, J. J., and L. J. Verme. 1986. Relation of maternal age to fawn-rearing success in white-tailed deer. Journal of Wildlife Management 50:480-486. Riley, S. J. and A. R Dood. 1984. Summer movements, home range, habitat use, and behavior of rriule deer fawns. Journal of Wildlife Management 48: 1302-1310. _ Robel, R J., J. N. Briggs, A. D. Dayton, and L. C. Hulbert. 1970. Relationships between visual obstruction measurements and weight of grassland vegetation. Journal of Range Management. 23:295-297. Rothchild, S. L. 1993. Mortality, home range, and habitat use of pronghorn fawns within tallgrass prairie of eastern Kansas .. M.S. thesis, Emporia State University. 85pp. Rothchild, S. L., E. J. Finck, and K. E. Sexson. 1994. Mortality and bedding site selection of pronghorn fawns in tall grass prairie. Proceedings of the Pronghorn Antelope Workshop 16:104-116. Salwasser, H., S. A Holl, G. A Ashcraft. 1978. Fawn production and survival in the North Kings River deer herd. California Fish and Game 64:38-52. SAS Institute Inc. 1988. SAS/STAT user's guide. Version 6.03. SAS Institute Inc., Cary, North Carolina. SAS Institute Inc. 1993. SASR Technical Report P-243, SAS/STATR Software: The GENMOD Procedure, Release 6.09, Cary, North Carolina Schlegel, M. 1976. Factors affecting calf elk survival in Northcentral Idaho. A progress report. Proceedings of the Western Association of State Game and Fish Commissioners 56:342-355. Skovlin, J. M. 1991. Fifty years of research progress: a historical document on the Starky Experimental Forest and Range. General Technical Report PNW-GTR-266. Portland, Oregon: U. S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Smith, R 1983. Mule deer reproduction and survival in the LaSal Mountains of Utah, 1983. M.S. thesis, Utah State University, Logan. Smith, R H., and A LeCount. 1979. Some factors affecting survival of desert mule deer fawns. Journal of Wildlife Management 43:657-665 Smith, R H., D. J. Neff, and N. G. Woolsey. 1986. Pronghorn response to coyote control - a benefit cost analysis. Wildlife Society Bulletin 14:226-231. . Steigers, W. D., Jr. 1981. Habitat use and mortality of mule deer fawns in western South Dakota Ph.D. Dissertation, Brigham Young University. 206pp. �170 Steigers, W. D., Jr., and 1. T. Flinders. 1980. Mortality arid movements of mule deer fawns in Washington. Journal of Wildlife Management 44:381-388. Stout, G. C. 1982. Effects of coyote reduction on white-tailed deer productivity on Fort Sill, Oklahoma. Wildlife Society Bulletin 10:329-332. Tucker, R. D. and G. W. Gamer. 1983. Habitat selection and vegetational characteristics of antelope fawn bedsites in West Texas. Wade, D. A, and J. E. Bowns. 1984. Procedures for evaluating predation on livestock and wildlife. Texas Agricultural Experiment Station Bulletin B-1429, College Station. Welker, H. J. 1986. Fawn mortality in the Lake Hollow deer herd, Tehama County, California California Fish and Game 72:99-102. White, G. C., R. A Garrott, R. M. Bartmann, L. H. Carpenter, and A W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852-859. White, M. 1973. Description of remains of deer fawns killed by coyotes. Journal of Marnmalogy 54:291-293. . White, M., F. F. Knowlton, and W. C. Glazener. 1972. Effects of dam-newborn fawn behavior on capture and mortality. Journal of Wildlife Management 36:897-906. Prepared by _ Thomas M. Pojar Wildlife Researcher Colorado Division of Wildlife William F. Andelt Associate Professor Department of Fishery and Wildlife Biology Colorado State University Appendix 1. Logistic regression table for the effect of vegetation height on survival offawns. The analyses will be conducted with SAS using Proc Genmod. Numerator Source Height Areas DF 1 2 M.S. height area Denominator DF M.S. Fawns -5 Error (Model) Fawns -5 Error (Model) �127 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB PROGRESS State of Project No. Colorado Cost Center 3430 W-153-R-13 Mammals Program Work Package No. _---'3:;...;:0'-"'0..:...1 Task No. 1 Period Covered: REPORT Deer Conservation _ Investigating Factors Contributing to Declining Mule Deer Numbers July 1 1999 June 30, 2000 Author: T. M. Pojar Personnel: _) .-- / T. Baker, T. Beck, C. Bishop, G. Bock, D. Coven, L. Dehart, B. Diamond, B. Dreher, J. Ellenberger, V. Graham, J. Griggs, D. Gustine, B. Hoffner, B. Lamont, M. King, K. Larsen, M. Mclain, H. McNally, K. Miller, M. W. Miller, E. Myers, J. Olterman, D . Schweitzer, T. Spraker, B. Watkins, S. Znamenacek. ABSTRACT Long-term data indicate that fawn:doe ratios have shown a significant and consistent decline over the past 20 years in most deer management units in Colorado as well as in most of the western states. This has resulted in a general decline in mule deer (Odocoileus hemionus) density and diminished recreational potential from this major resource. It is important for the Division of Wildlife to understand the factors contributing to the reduced fawn:doe ratios and the declining deer populations. Neonatal survival (birth to 6 months of age) is an important component of population recruitment. This is the second year of monitoring cause-specific neonatal fawn mortality on the Uncompahgre Plateau. In 1999, a sample of 50 fawns was radioed and during the 2000 fawning season 88 fawns were captured. Fawns were captured as . near birth as possible and are monitored to about 6 months of age. A new design radio collar that weighed 1109 was used on the 2000 season fawns. The collar was expandable and used latex tubing to facilitate drop-off in about 6 months. Neonatal fawn survival for 1999 was 38%. Of the 50 fawns collared, 30% died of sickness/starvation, 26% from predators (12% coyote, 8% feline, and 6% bear), 4% from unknown causes, and 2% from poaching. Thirty-one of 50 fawns died with 58% dying from causes other than predation. Monitoring is in progress for the 2000 season fawns. Early season 2000 mortality is less than it was in 1999. Deaths from sickness/starvation are half (10% vs. 20%) what they were in 1999 (as of . August 1) and predation is about three-fourths (15% vs. 20% that of 1999 (Figure 1). June 2000 was warm and dry, which may have affected early fawn survival. On the Uncompahgre, December fawn:doe ), ratios are negatively correlated (r = -0.8183) with the preceding June precipitation (R~.6697, P=0.0038). /i: d However, mean temperature for June had a weak positive correlation (r = 0.2756) and was not significant (R2 =.0.0760, P = 0.4409). The peak offawning was between June 14thand June 26th when 93% of the -, �128 fawns were caught (Figure 2). Year 2000 fawns were slightly larger than the 1999 fawns in terms of body weight and hindfoot length. Neither the difference in weight, 4.4692 (2000)vs. 4.3714 kg (1999), nor the difference in hing foot length, 10.474 (2000) vs. 10.297 (1999) inches, was statistically different, P = 0.5845 and P = 0.1309, respectively. �129 IMPACT OF PREDATION AND VEGETATIVE COVER ON MULE DEER FAWN SURVIVAL Thomas M. Pojar P. N. OBJECTIVES 1. Identify agents of neonatal mule deer fawn mortality from birth to 6 months of age. SEGMENT OBJECTIVES 1. Capture and radio collar 30-35 neonatal fawns each on the Uncompahgre Plateau (D-19), Middle Park (D-9), and Red Feathers (D-4). 2. Measure vegetative density and height at fawn bed sites. 3. Measure distance between successive bed sites for individual fawns. 4. Compare fawn survival and causes of mortality among 3 vegetational and ecologically different study areas. 5. Correlate height and density of vegetation at fawn birth sites and bed sites with percent of fawns killed by predators. 6. Compare height and density of vegetation at fawn bed sites and random sites. INTRODUCTION Major changes in the original Program Narrative include: 1. Limit the fawn collaring effort to the Uncompahgre Plateau (D-19). Because of the size of the area and diversity of vegetative communities on the Uncompahgre and because of intense political interest in this area, all resources were concentrated on the Uncompahgre during this segment. The target sampling intensity was increased to 80 fawns with emphasis placed on getting the sample widely distributed over the entire 2,300 square mile area. 2. Abandon the idea of measuring vegetation at bed sites because of evidence that persistent disturbance of bed sites reduces survival of young ungulates (Philips 1998). 3. The logistics of placing an adequate crew in remote fawning areas and the unknown of whether or not fawns could be captured in sufficient numbers given deer density, terrain, and vegetative cover encountered negated many of the objectives in the PN. In essence, this investigation was reduced to placing emphasis on capturing fawns on the Uncompahgre and monitoring their survival and causes of mortality. Summer fawn survival and causes of mortality are 2 important factors impacting deer population performance. STUDY AREA The study area is described in Pojar and Andelt (1999). METHODS Radio collared does were used to locate fawning areas although no special effort was made to capture the fawns of radioed does. The strategy for capturing fawns involved observing does for behavioral and physical signs, such as udder development, of having fawned. If it was determined that these indicators suggested that the doe had fawned, the area was searched for the fawn(s). Once located, �130 the fawn was approached from behind (out of direct eyesight) and restrained for weighing, measuring, and putting on the radio collar. Processing usually took less than 5 minutes. The collars used were made of 1.5-inch elastic with an expansion ratio of 1.5:1 and equipped with surgical tubing to allow the collar to drop off after about 6 months. Each collar weighed 110 g. The circumference of the collar was 10 inches, 6 of that was elastic. The 6 inches of elastic has the ability to expand to 9 inches. A l-inch loop was sewn in the elastic reducing the collar circumference to 9 inches. The loop was sewn with 4 stitches of cotton thread with the intent that these would rip out within 2-3 weeks after the collar was put on a fawn. When the collar was put on a fawn it was 9 inches in circumference and fit quite loosely. When the loop was released the circumference increased to 10 inches and as the elastic relaxed the collar could expand another 3 inches giving a totally expanded circumference of 13 inches. Collars were hung outside in the shade for several days before use to help dissipate any fabric and human scents associated with manufacture. When taken to the field in workers backpacks, the collars were sealed in zip loc bags. If a collar was to be recycled, i.e. removed from a dead fawn and reused, it was washed in tap water (no soap), hung out to dry, then placed in aplastic bag with native forage. RESULTS By recycling some of the collars, 88 fawns were radioed. The sample was roughly distributed according to deer density on the summer range. The sample of radioed fawns were distributed across the Uncompahgre Plateau as follows: North (Cold Springs) 29, central (25 Mesa) 16, south (Celesca) 33, and far south (10). Thus far, the collars are expanding as expected. From recovered collars, it appears the cotton stitching rips out in about 4 weeks or less. There was only one instance of suspected slippage of a collar and it is possible the fawn was killed or scavenged and the collar carried away from the carcass. Of the fawns recovered, there was no sign of the collar causing abrasions on the skin, however, there was slight hair loss in some cases from the collar being loose enough to rotate or move on the neck. The fawns captured during 2000 had a mean weight of 4.47 kg compared to 4.37 kg in 1999; this difference was not significant (P=0.5845). The hind foot length of 10.48 inches in 2000 was not different from that of 1999, 10.30 inches (P=0.1309). There was a noticeable difference in the weather, both precipitation and temperature, during the fawning period between 1999 and 2000 with the most recent year being warmer and dryer. Early sickness/starvation deaths (through August 1) in 2000 were half (10% vs. 20%) what they were in 1999 (Figure 1). It was theorized that the warmer, dryer June weather was a key factor in neonate fawn survival. Weather data for the Montrose area was tabulated for the past 10 years. I tested the hypothesis that June temperature and precipitation are related to the subsequent early winter (December) fawn:doe ratios collected during helicopter classification surveys done by management personnel. The correlation with precipitation was highly significant and negatively correlated (r = -0.8183) with subsequent fawn:doe ratios, R2 = 0.67, P = 0.0038; temperature had a slight positive correlation (r = 0.2756) with fawn:doe ratios but it was not significant, R2 = 0.0760, P = 0.4432. Although the search for newborn fawns began in early June, the first fawns were not caught until June 14thin 2000. In the 13-day period between June 14thand June 26th, 93% of the fawns were caught. The last fawn was caught on July 9th (Figure 2). In 1999, the 17-day period from June 13 to June 30,96% of the fawns were captured; the first fawns were captured on June 9th. From this data there is no evidence that a double fawning peak is occurring on the Uncompahgre Plateau. Data on captured fawns is in Table 1. Although the information for 2000 regarding mortalities only goes through August Pt, Figure 3 shows a comparison of total cause-specific mortality for 1999 (total) and 2000 (through August 1~. �131 LITERATURE CITED Philips, G. E. 1998. Effects of human-induced disturbance during calving season on reproductive success of elk in the upper Eagle River valley. Ph. D. Dissertation, Colorado State University, Ft. Collins. Pojar, T. M. and W. F. Andelt. 1999. Investigation offactors contributing to declining mule deer numbers. Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-12, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Table l. Neonatal mule deer fawns captured and radio collared on the Uncompahgre Plateau, Colorado 2000. The mortality data is very preliminary and represents only deaths through August 1,2000. Probable Cause Radio I.D. Date of Capture location UTM Hindfoot Date Sex Wt Recovered of Death Capture Coordinates (kg) (inches) East North 150.023 6-15 703980 4268055 F 10.75 4.4 150.033 6-18 700954 4278742 F 10.25 4.7 150.044 6-16 702309 4280011 F 11.125 5.3 150.054 6-24 703446 4267697 F 11.25 5.1 150.064 6-18 700353 10.625 4274667 M 5.0 150.074 6-24 703050 4267256 M 11.00 4.4 150.084 6-24 703442 4267726 M 6.1 11.00 150.094 6-18 704622 4274176 M 11.00 5.0 150.104 6-22 700255 10.625 4282798 F 5.5 150.114 6-19 697815 5.3 11.375 4283738 M 150.134 6-20 6+ 11.875 703390 4279744 M Sick/starve 150.146 6-19 7-9 701207 4279027 M 9.75 3.9 150.155 6-20 702179 10.125 4275357 F 4.1 150.163 6-18 700357 10.50 4283325 M 4.2 7-19 Sick/starve 150.184 6-22 703468 10.00 4279642 M 4.0 150.192 6-20 702293 4.5 10.125 4281859 M 150.204 6-22 '4.7 700428 4283374 M 10.25 150.214 6-26 704463 10.50 4272215 F 4.7 Coyote 150.223 6-21 751358 6-23 4236752 M 3.6 10.50 150.234 6-20 727652 10.125 4252092 F 3.5 723136 150.244 6-26 4257872 F 10.625 5.7 150.254 6-22 730938 4264027 M 3.9 9.625 150.263 6-19 750827 4230756 M 4.0 10.25 150.272 6-25 700728 10.25 4284815 M 3.75 150.283 6-25 703475 10.50 4279355 F 5.0 10.00 150.294 6-26 241593 4235614 M 4.2 Sick/starve 150.303 6-21 760162 11.25 7-31 4237065 M 5.2 7-3 Bear 150.314 6-23 732743 4251998 M 11.125 5.0 150.324 6-26 241806 9.50 4236255 M 2.9 721362 10.00 8-1 Coyote 150.334 6-22 4264368 M 4.6 150.344 6-20 720095 4265861 F 5.2 11.00 Coyote 150.353 6-24 730048 9.75 7-27 4263042 F 3.4 150.362 6-20 748878 4231358 M 10.625 4.6 150.374 6-21 756526 10.75 4248692 M 5.1 150.383 6-26 728565 4254798 M 3.4 9.875 Coyote 150.393 6-21 10.125 7-5 743115 4255001 F 3.8 150.423 6-25 10.25 730831 4263910 M 4.0 150.434 6-18 757228 4232141 F 5.3 11.25 7-17 _~LcJcl~L ___ 6-20 4.~~!~2~_ __I4.~~I~ ___ J':____4.]___ J.9.:~Q_____ -----------__ l_?.9A4.4. -------- �132 Table 1 Continued Radio I.D. Date of Capture 150.455 150.464 150.473 150.484 150.495 150.504 150.514 150.524 150.545 150.553 150.564 150.573 150.584 150.593 150.604 151.114 151.123 151.144 151.153 151.164 151.173 151.195 151.203 151.233 151.245 151.254 151.263 151.274 151.284 151.294 151.314 151.324 151.333 150.013A 150.013B 150. 124A 150. 124B 150.172A 150.172B 150.403A 150.403B 150.415A 150.415B 150.533A 150.533B 151.134A 151.134B 151.183A 151.l83B 6-19 6-16 6-19 6-14 6-17 6-19 6-16 6-19 6-19 6-23 6-17 6-15 6-17 6-14 6-20 6-15 6-16 6-18 6-18 6-18 6-18 6-18 6-26 6-17 6-17 6-14 6-14 6-22 6-22 6-22 6-19 6-22 6-15 6-26 7-6 6-24 6-27 6-20 6-26 6-26 7-9 6-18 6-26 6-21 6-29 6-16 6-30 6-18 7-5 Capture location UTM Coordinates North East 762275 4233303 755233 4247651 760381 4232242 754488 4235165 756570 4233083 762275 4233303 4247828 754392 727428 4251901 749686 4229850 755706 4231637 4246702 757702 752002 4249457 754295 4247567 4249079 752525 754867 4231692 756942 4231730 754848 4331643 751910 4249670 751910 4249670 4249165 752547 752639 4248689 742905 4240385 731972 4251646 4251207 750332 754406 4248275 248077 4233576 248077 4233576 762261 4224531 761180 4220892 761688 4221672 761310 4220980 761688 4221672 761539 4223050 703376 4267562 704293 4269378 705226 4269426 4274463 704284 702297 4280730 730004 4261815 728978 4254395 702133 4280026 730056 4262079 730074 4261926 751358 4236752 707752 4270072 755167 4231731 707752 4270072 746380 4247269 701385 4279114 Sex Wt (kg) Hindfoot (inches) M M M F M M M F M M F M M M F M F F F F F M F M M F M F F F F F F F F F F M M M M F F M F F F F M 5.7 3.1 5.3 3.8 4.1 5.2 4.5 3.6 5.1 3.8 3.0 4.7 4.8 3.6 4.8 4.3 3.6 3.8 3.6 5.0 4.1 4.7 5.7 4.7 5.2 4.3 4.6 4.8 6.1 3.4 3.1 3.6 3.5 6.0 5.8 3.4 4.0 4.9 5.0' 4.3 6.7 3.5 3.0 3.7 6.1 4.4 5.0 4.0 6+ 11.50 9.625 10.50 10.50 10.25 10.75 10.625 10.25 10.25 10.50 9.625 11.00 11.125 10.125 10.25 10.50 9.875 10.25 9.75 10.50 10.625 10.75 11.125 10.25 11.375 10.83 10.25 10.43 12.20 10.16 8.86 10.00 9.76 11.00 11.00 8.00 10.25 11.00 10.875 10.625 11.50 9.875 8.875 10.50 10.625 10.75 11.50 10.125 11.75 Date Recovered Probable Cause of Death 7-8 Sick/starve 6-30 7-31 6-25 Coyote Bear?· Sick/starve 6-23 Sick/starve 7-3 Bear 6-24 . 7-5 6-23 7-31 6-21 Sick/starve Bear Coyote Sick/starve Coyote 6-26 7-6 Coyote Coyote �133 YEAR 2000 - Through Number of fawns radioed Number of fawn deaths Cause Predation Sick/starve Total Alive % of morts Number 13 9 66 August 1 88 % of Total Sample 22 Predation 'lb % of total 59% 41% 15% 10% 75% Sick/starve 10% Total Alive 75% YEAR 1999 - Through Number of fawns radioed Number of fawn deaths Cause Predation Sick/starve Total Alive Number 10 10 30 August 1 50 20 % ofTo~1 % of morts % of total 50% 20% 50% 20% 60% Sample Predation 20% Figure 1. Comparison of cause-specific mule deer fawn mortality, Uncompahgre Plateau, Colorado. represents mortality from collaring through August 1st. 14 "'C Cl) 12 •... .aa. 10 C'O () 8 - - 6 I-- o c ~ u. o o Z 4 f- f- 2 o lLU .IL_I_ Jul8 Jun 14 Jun 18 Jun 22 Jun 26 Jun 30 Jul4 Jun 16 Jun 20 Jun 24 Jun 28 Jut 2 Jut6 Figure 2. Capture dates for year 2000 fawns from the Uncompahgre Plateau, Colorado. Data �CAUSE-SPECIFIC FAWN MORTALITY - UNCOMPAHGRE 2000 (Through Aug 1) Number of fawns radloe 88 Num ber of fawn deaths 22 Cause Number % of mort % of total 8 36% 9% Coyote 4 18% 5% Bear Unk Pred 1 5% 1% Sick/starve 9 41% 10% 66 75% Total Alive •....• w .j::o. r----------------------------, % of Total Sample Bear 5% Unk Pred 1% Sick/starve 10% % or Mortalltl •• '" ,... CAUSE-SPECIFIC FAWN MORTALITY - UNCOMPAHGRE 1999 (Total for year) Number of fawns radloe 50 ...--'---------------------------, Number of fawn deaths ·31 Number % of mort % of total Cause Coyote 6 19% 12% 4 13% 8% Feline Bear 3 10% 6% Sick/starve 15 48% 30% Totalilive Unknown 2 6% 4% 38% Poached 1 3% 2% Total alive 19 38% ./. of Total Sample Coyote 12% Bear 6% % or Mortalltl.s •..". Unknown 4% Sick/starve 30% '''' Figure 3. Comparison of cause-specific mortality for 1999 and 2000, Uncompahgre Plateau, Colorado. The tabulation of 1999 includes the entire period from fawn capture to approximately 6 months of age. The data for 2000 only goes through August 1, 2000 (the date of this writing). � https://cpw.cvlcollections.org/files/original/8b8f55665099434ac957088b1ddf478a.pdf b4be7d2fb2190aa2718befefd68d3bea PDF Text Text 83 Colorado Division of Wildlife Wildlife Research Report July 1993 JOB PROGRESS REPORT State of ______..!C~o~l~o~r~a~d~o~---Project No. W-153-R-6 Mammals Research Work Plan No. -~3_ _ _ _ _ _ __ Elk Investigations Job No. ---~9_________ Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size Period Covered:; Author: July 1, 1992 - June 30, 1993 D. J. Freddy Personnel: R. Bartmann, and C. McCarty, CDOW; White, CSU. C. Vardeman, D. Bowden and G. Abstract A detailed study plan for this project was completed and approved through the required peer-review system. The study area selected was that portion of Game Management Unit 42 south of Newcastle and Rifle, Colorado . Two elk corral traps were refurbished for use in December 1993 and arrangements made to contract trapping of 100 elk using a helicopter . Radio-collars for adult cows and male and female calves were designed and purchased. �85 JOB PROGRESS REPORT ESTIMATING SURVIVAL RATES OF ELK AND DEVELOPING TECHNIQUES TO ESTIMATE POPULATION SIZE David J. Freddy P. N. OBJECTIVE Estimate survival rates of adult female and calf elk and develop techniques to estimate population size. SEGMENT OBJECTIVES 1. Complete detailed and approved study plan and select study area. 2. Refurbish elk traps and identify potential trap-site locations within the selected study area. 3. Design expandable radio-collars for calves and purchase and assemble collar materials transmitter units. A complete copy of the approved study plan presented. �86 STUDY PLAN FOR RESEARCH FOR 'FY 1992-93 - 1996-97 V State of ___c~o~l~o~r~a~d~o:.-_ _ Project No. 4400 Work Plan No. Job No. Hunt 3 9 0715 Mammals I Research Elk Investigations Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size ESTIMATING SURVIVAL RATES OF ELK AND DEVELOPING TECHNIQUES TO ESTIMATE POPULATION SIZE Principal Investigators David J. Freddy, Wildlife Researcher, Mammals Research R. Bruce Gill, Wildlife Research Leader, Mammals Research Cooperators John E. Ellenberger, Wildlife Biologist, Northwest Region James H. Olterman, Wildlife Biologist, Southwest Region David C. Bowden, Professor Statistics, Colo. St. Univ. Gary C. lJltite, Professor Wildlife Biology, Colo. St. Univ. STUDY PLAN APPROVAL Prepared by: _____________Date : _ _ _ __ Submitted by: ____________Date : _ _ _ __ Reviewed by: _____________Date : _________ _____________Date: _ _ _ __ _____________ Date: _ _ _ __ _____________ Date: _ _ _ __ Approved by: _____________ Date : _ _ _ __ Biometrician _____________Date: _ _ _ __ V �87 FREDDY STUDY PLAN PROGRAM NARRATIVE State of ---~C~o~l_o~r~a~d~o____ Project No. 4400 Work Plan No. Job No. I. \....,,._/ Hunt 3 9 0715 Mammals I Research Elk Investigations Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size NEED Elk (Cervus elaphus nelsoni) are a high-profile wildlife resource throughout much of Colorado because they provide recreation for persons who hunt, watch, and photograph wildlife (Freddy et al. 1993). The popularity of elk with the public is undoubtedly related to the expanding geographic distribution and increasing size of the State's elk population. This burgeoning elk resource has many benefits but frequent social, political, and economic conflicts suggest elk, to some degree, have reached a "social" carrying capacity. Balancing these uses and conflicts by maintaining acceptable numbers of elk is a challenge for future management of this species in Colorado. The positive and negative economic impacts of elk are often the most influential forces directing management of elk. In 1990 and 1991, 193-194,000 hunters harvested 46-51,000 elk in Colorado (CDOW 1990, 1991). In doing so, hunters generated at least $20 million in yearly license revenue to the Colorado Division of Wildlife (CDOW) and contributed about $250 million in direct and secondary expenditures to the yearly economy of Colorado (Freddy et al. 1993). Revenues derived from elk hunting provide the financial resources for many wildlife programs of the CDOW and for many private businesses in the State. However, rising numbers of elk and attendant harvests have also brought about conflicts with agricultural interests. Demands to reduce elk populations and expand payments for damage by elk to cultivated and native forage on private lands have resulted in the CDOW altering statewide objectives for elk from increasing to decreasing the total population and creating a Habitat Partnership Program with private land owners. This partnership to cooperatively manage elk that impact private lands may reach expenditures of $1 million annually. The core of the conflict in elk management, in part, stems from inadequate estimates of population size resulting in an inability to establish management objectives for specific populations that are agreeable to competing interests. Even when objectives are established, we can not readily quantify impacts of management decisions because current methodology for monitoring populations is neither precise nor accurate. �88 FREDDY STUDY PLAN The CDOW has relied on computer modeling, rather than direct measurements, to generate estimates of population size. This approach has been inadequate because model outputs have not been validated with independent estimates of population size. Estimates of population size and subsequent proposed harvest levels have, therefore, been subjected to endless debate. Computer models based on POP-II (Bartholow 1992) or POPMOD ('White 1992) function best when natural rates of survival or mortality, hunter harvests, and population size are reliably measured. In the current modeling process, survival of calves from June 1 until September 1 is implicitly estimated by measured post-hunting season calf:cow ratios, which along with bull:cow ratios, are used to estimate composition of the pre-hunting season population. However, the size of the preseason population is not measured. From this preseason population, hunter harvests, which are adequately measured, are subtracted resulting in a prewinter population. The prewinter population is multiplied by rates of survival, which are not measured, to estimate a postwinter population and subsequently the next preseason population. Obvious missing links in this modeling process are measured estimates of survival for calves and adult females during winter (Nelson and Peek 1982) and population size at some time during the annual cycle. Importantly, estimates of population size independent of the modeling process could be used to align models on measured values. The current modeling process is prone to many subjective estimates regarding population size and survival rates which has resulted in diminished confidence in using models to guide management of elk populations (Freddy 1987). The CDOW recognized the need to improve monitoring status of ungulate populations during 3 planning efforts. First, the statewide Long Range Plan (LRP), approved in 1988 and updated in 1991 (CDOW 1991b), highlighted the need for improved population data to accommodate increasing recreational demands and reduce conflicts among competing interests. The LRP targeted 25% of the revenues generated from increasing hunting license fees towards improving and expanding efforts to monitor ungulate populations. In 1991, increased fees associated with elk licenses generated approximately $4.5 millon in new revenue potentially resulting in $1.1 millon towards expanded population monitoring. Second, CDOW terrestrial biologists at a statewide meeting held in July 1991 stated that obtaining quantified estimates of survival rates and population size were their priority needs for developing more reliable models of elk populations. Third, the CDOW Deer and Elk Management Analysis Guide, approved in November 1991, identified as priority issues the need to obtain reliable estimates of population size and survival rates of calves and adult female elk (Freddy et al. 1993). Estimating both survival rates and population size are fundamental to developing systems for monitoring and predicting changes in elk populations. We believe estimating calf and adult female survival rates during winter and annual survival rates of adult females are a higher priority than estimating adult male survival rates primarily because most males are harvested when they reach legal age and contribute little to problems of either population growth or decline. Models having valid estimates of survival rates for calves and adult females along with currently obtained estimates of harvests and population composition will provide more defensible estimates of population . V �89 FREDDY STUDY PLAN size and trend than similar estimates derived from current models. However, an independent estimate of population size generated from a sampling system designed to enumerate elk would provide the opportunity to validate population estimates derived from models. Ideally, estimates of both survival and size would be obtained simultaneously. Changes in either calf or adult female survival have pronounced effects on population growth and greater effects than changes in fecundity (Nelson and Peek 1982). Sensitivity analyses indicated population growth is more affected by changes in survival rates of adult females than to equivalent changes in calf survival. A 15% increase in adult female survival resulted in a population increase 7x that of the increase from a 15% change in calf survival (Table 1). Although small changes in adult female survival can have major effects on population growth if compounded for 10-20 years, we expect calf survival to be more variable among years and our ability to detect changes in calf survival should be greater than detecting smaller, but important changes in adult female survival (White et al. 1987, Bear 1989, Bartmann et al. 1992). Because there are few estimates of either calf or adult female survival rates, we need to measure both simultaneously to document the relative differences in survival rates and patterns of mortality in order to develop more reliable population models. \.-,I' An example of how measurements of survival can alter our perception and modeling of populations involves the Piceance deer population in northwest Colorado. Measured overwinter survival of fawns (0.22) was much lower than perceived, and survival of adult females (0.82) was more stable among years than anticipated (White et al. 1987). Using measured rates of survival in existing models of this deer population resulted in radical changes in estimated population size, and served to focus wildlife managers on probable causes of low fawn recruitment and solutions to improve recruitment (Bartmann and White 1991, Bartmann et al. 1992). �90 FREDDY STUDY PLAN Table 1. Sensitivity analysis for 3, 10, and 15% increases in survival rates of calves and adult females for a beginning population of 1000 elk simulated for 20 years. Initial survival rates for calves (0.705) and adult cows (0.800) essentially stabilized population growth for 20 years. Growth rate increase equals the percent increase in yearly average growth rate compared to stabilized average growth rate, Change in Calf Survival Rate Calf Survival Ad. Female Survival 8 Ad. Male Survival Avg. Yrly. Growth Rate Growth Rate Increase End 20 Yr. Pop. Size 0% +3% +10% +15% 0.705 0.800 0.650 0.82% 0.00% 990 0.726 0.800 0.650 1.49% 82.5% 1109 0. 775 0.800 0.650 3.21% 293.0% 1441 0.811 0.800 0.650 4.61% 465.0% 1742 Change in Adult Cow Survival Rate +15% 0% +3% +10% Calf Survival Ad. Female Survival Ad. Male Survival Avg. Yrly. Growth Rate Growth Rate Increase End 20 Yr. Pop. Size a Ad.-adult ~ 0.705 0.800 0.650 0.82% 0.00% 990 0.705 0.824 0.650 3.35% 310% 1531 0.705 0.880 0.650 12.1% 1378% 4093 0.705 0.920 0.650 22.1% 2609% 8038 V 1 year old. Our lack of adequate population data on elk is not without just cause as known methodologies are limited and expensive. As resource.managers, we have likely reached a threshold where we must expand our investment in monitoring the processes that affect the growth or decline of the elk resource to accommodate the rising and often conflicting demands for managing elk. II . OBJECTIVES Our objectives are to provide reliable estimates of survival rates for calves and adult females overwinter and adult females throughout the year, and develop and test a system for estimating population size. Our efforts will focus on elk inhabiting winter ranges south of NewCastle and Rifle, Colorado. Our specific objectives are: 1) Estimate survival rates of calves from 1 December - 31 May within± 15% of the true survival rate at the 95% confidence interval and identify sources of mortality using adequate numbers of radio-collared calves. 2) Estimate winter (1 December - 31 May) and yearly (1 December - 30 November) survival rates of adult females within± 10% of the true V �91 FREDDY STUDY PLAN survival rate at the 95% confidence interval and identify sources of mortality using adequate numbers of radio-collared adults. 3) Monitor the fate of yearling bull elk radio-collared as calves in relation to antler-point restrictions designed to protect yearling bulls from harvest. 4) Develop and test a system to estimate population size during winter within± 20% of the true population size -at the 90% confidence interval using radio-collared elk to evaluate sighting bias and to provide population estimates based on random plot searches and mark-resight theory. 5) Provide data on general movements, distribution, and dispersal of radio-collared elk within the study area. Establish cooperative studies with universities and land management agencies to investigate specific aspects of habitats used by elk and to relate genetic characteristics of elk to their survival. III. EXPECTED RESULTS OR BENEFITS This investigation will provide estimates of survival rates for calf and adult female elk in a selected elk population during 4 consecutive years. These estimates will immediately assist CDOW biologists not only in refining population models for this specific population but also in providing estimates of survival that may be applicable to modeling other elk populations inhabiting similar habitats. Quantified estimates of survival will allow objective assessment of whether major restructuring of current population models is necessary. In the process of estimating survival rates, we will document sources of mortality. Our efforts to estimate population size are inherently more difficult than estimating survival rates. If we obtain relatively precise and unbiased estimates of true population size, the CDOW will have a method to obtain valid independent estimates of population size to compare with estimates derived from modeling, and therefore, provide another objective basis for assessing the current modeling process. If our efforts provide less than satisfactory results, we will have an objective basis for either continuing with refinements or discontinuing efforts to estimate population size and invest in measuring other population parameters. IV. APPROACH A. Survival General Approach We will estimate survival rates for calves (6 mos old) and adult females (~ 1 yr old) during winter, 1 December - 31 May, and for adult females annually, 1 December - 30 November, by using radio-telemetry collars that emit a mortality pulse code when animals remain motionless for 4-6 hours (White 1983, Bear 1989, White et al. 1987). Radios provide the ability to know the fate of individual animals (alive or dead) over discrete periods of time unlike marking animals with other types of tags that are seldom recovered upon the animal's death (White and Garrott 1990). Improved longevity of batteries �92 FREDDY STUDY PLAN for radio collars will allow us to monitor status of individual animals for up to 4+ years. Survival will be monitored from 1993-94 through 1996-97. V We assume that radio-collaring calf and adult female elk does not bias estimates of survival rates by jeopardizing or enhancing the welfare of individuals. This assumption can be violated in studies involving birds when transmitter packages exceed critical weight/body size ratios (Burger et al. 1991, Foster et al. 1992) but does not appear to be a detectable bias with ungulates when radio collars weigh about 0.8% of an animal's body weight (Garrott et al. 1985, White et al. 1987). Although some level of bias may occur, radio collars will likely provide much less positively biased estimates of survival compared to other indirect methods (Bartmann 1984, Zager and Leptich 1991). Radio collars used in this project will weigh about 1.1 kg and represent about 0.8% of calf and 0.5% of adult female body weights. Collars for adult females will be of fixed circumference and fitted for each individual. Collars for male and female calves will allow for expansion to adult size (Bear 1986, White et al. 1987, Appendix I). We assume that survival of those animals captured unbiasedly represents survival of individuals in the population. Individual behavior, social behavior, trapping method, and distribution of trapping effort all potentially bias those individuals trapped and marked (White el al. 1982, Garrott and White 1982). Recognizing these problems, we will capture elk with the objectives of marking animals throughout the distribution of the population and reducing influences of social hierarchies. The study area will be divided into several zones each having multiple capture sites to assure that marked elk represent the population. Capture quotas for calves and adult females will be established for each zone. A Hughes 500 helicopter and a net-gun will be used to capture individuals from groups of elk in more remote areas where portable corral traps would be inefficient to use. In those areas inhabited by people or having agricultural activities, we will use portable corral traps to capture groups of elk. Elk caught in corral traps are likely less affected by social dominance hierarchies than elk captured with single animal Clover traps (Garrott and White 1982, Bear et al. 1989). For groups of elk captured in traps, only a fraction of each group will be randomly selected and radio collared. We will attempt to collar equal numbers of adult females and calves within each capture method. Trapping will occur from approximately 29 November-20 December each year. While handling animals we will minimize capture stress and follow guidelines for animal welfare (Appendix II). V Each collared animal will be individually recognizable based on radio collar frequency, an external symbol/number on the top surface of the collar, and a numbered metal ear-tag placed in each ear. Radio collars will be white with a black symbol/number (Appendix III). Additionally, male and female calves or yearlings captured but not collared will be ear-tagged to provide additional data on dispersal when and if recovered as harvested animals during hunting seasons. Collared calves, and when possible, yearling females, will be weighed to nearest 0.5 kg. Additionally, hind foot lengths and total body lengths will be measured for calves. Blood samples will be obtained via venepuncture to assess pregnancy status of adult females using progesterone assays (Freddy u �93 FREDDY STUDY PLAN 1991) and from calves for potential genetic analyses related to measured survival rates (Pemberton et al. 1988). All collared elk will be aged as calves, yearlings, or young (2-3 yrs), prime·(4-10 yrs), and old(~ 10 yrs) adults based on visual inspection of tooth replacement and wear (Quimby and Gaab 1957). We will use periodic and systematic aerial and ground searches throughout areas inhabited by collared elk to determine.their life or death status based on pulse rates of collars (Gilmer et al. 1981). Animals will be monitored daily from the ground during winter with aerial searches done twice per month depending upon frequency of mortalities and relative ability to monitor all animals from the ground. During spring, summer, and fall we will conduct monthly or bi-monthly aerial searches. During fall hunting seasons, aerial searches may be conducted weekly in conjunction with intensified ground searches. Mortalities coarsely located during aerial surveys will be found from ground searches using hand-held antennas. Criteria for assigning probable cause of death (primarily during winter) will include body position, presence of bite or claw marks and subdermal hemorrhaging, tracks, drag marks, and when necessary rumen or tissue samples (Wade and Browns 1982). Potential causes of death include starvation, accidental trauma, plant poisoning, predation by black bears, mountain lions, coyotes, and domestic dogs, and legal and illegal hunter harvest (Bear 1989, Schlegel 1977). Analyses Number of animals collared depends on expected survival rates, desired precision, and degree of statistical power desired for comparative tests. The few studies that have estimated survival rates for elk used either age structure analyses or radio collars. Annual survival rates estimated from age structure analyses were: 64% for all calves (overwinter only) in Yellowstone National Park (Houston 1982); 61% for female and 26% for male calves in Jackson Hole, Wyoming (Boyce 1989); 90% for all calves in Colorado's White River population (Laake 1992): and for adult females, 97% (Houston 1982), 68% (Boyce 1989), and 79% (Laake 1992). Annual survival rates based on radio telemetry were: 93% for male and female calves pooled with adult females (nonhunted segments of the population) in northern New Mexico (White 1983); 75-94% for calves through their first 9 months in Rocky Mountain National Park, Colorado (Bear 1989); 100% for calves from shortly after birth through their first winter in central Colorado (de Vergie 1989); 88% for adult females in northern Idaho where all mortality was attributed to hunting (Leptich and Zager 1991); and nearly 100% for adult females in northern Colorado (overwinter only, G.D. Bear pers. comm.). These results suggest that survival may be> 70% for calves and> 85% for adult females·overwinter with annual survival rates for adult females varying due to intensity of hunting. We will radio-collar 75 calves (38 female, 37 male) yearly and initially collar 75 adult females and maintain at least 75 adults(~ 1 year old) collared in the population yearly to estimate rates of survival for these 2 age classes of animals. Assuming 75 collars remain functioning and survival is~ 0.7 or~ 0.9, 95% confidence intervals will be S ± 15% or S ± 8% of the �94 FREDDY STUDY PLAN mean survival rate, respectively. If survival for either calves or adults approaches 0.5 then considerably more collars must be deployed to maintain high precision (Appendix IV). These confidence intervals are calculated as 1.96 ± vVAR(S) where survival (S) is a binomial with a variance, VAR(S) - S(lS)/n, and n is number of collars deployed (White et al. 1982). Power (1-beta) to detect differences in survival rates~ 0.20 among years or age/sex classes will be~ 0.70 but power will be S 0.25 for differences in survival S 0.10 when survival rate is 0.7 and alpha - 0.05. If survival is 0.9, power will be ~ 0.80 for differences in survival~ 0.20 and 0.40 for differences S 0.10 (Appendix IV, White and Garrott 1990:32). Reliably detecting differences of 0.05 in survival rates would require deployment of about 1,000 collars yearly for each age class. Analyses of survival rates assumes that individual animals are known to be either alive or dead during specific time intervals of interest and that their individual life status is independent among animals. This binomial approach is most correct if all animals of interest enter and leave the population simultaneously and there are no animals of unknown status (censored) due to emigration or failure of radio collars (White and Garrott 1990). Typically, animals are trapped and marked over varying time periods and some animals emigrate or radio collars fail. To account for these problems, we will use a staggered entry Kaplan-Meier analysis, which is a modification of the binomial estimator, to estimate survival rates (Pollock et al. 1989, White and Garrott 1990, Bartmann et al. 1992). If no censoring occurs, the Kaplan-Meier approach will provide an estimate identical to the binomial estimator. We believe the binomial approach and attendant assumptions provides a more realistic basis for estimating survival rates than alternative approaches that assume constant survival rates for specified time intervals (Heisy and Fuller 1985). Staggered entry Kaplan-Meier analyses are readily available in programs written for SAS (SAS 1988, White and Garrott 1990, G. C. White, pers. comm.). The PC database program RADIOS (G. C. White pers. comm) will be used to store data on each collared animal. We will test the following generalized hypotheses: Ho: Survival Rate - S Scalves - Sadult females during winter Ho: Smale calves - Sfamale calves H0 : Sadult females H0 : Scalves during winter is equal among years is equal among years We anticipate the following comparative analyses of survival rates using data from animals of known fate. We will conduct pair-wise comparisons using log-rank tests (Pollock et al. 1989, Bartmann et al. 1992) to compare survival functions for: calves and adult females during winter and for male and female calves during winter. Program SURVIV (White and Garrott 1990) will be used to test for differences in survival rates among and between age classes and years (Table 2). For example, to compare survival rates of adult females among V V �95 FREDDY STUDY PLAN years, constraints for program SURVIV would be S1 - S2 , S1 - S3, S1 - S4, and to compare survival of adult females and calves within years, constraints would be S1 - S5, S2 - S61 S3 - S7 , S4 - S8 • Similar constraint pairings would occur for comparisons between male and female calves. These reduced models of survival would be tested against a generalized model that estimates all survival parameters individually, using log-likelihood ratio and goodness-offit tests in program SURVIV. Tests will be significant at PS 0.05. Table 2. SURVIV. Age/Sex Class ~ Generalized structure for analyzing survival rates with program Year Radios Deployed Proportions Lived Died Adult Females 93-94 94-95 95-96 96-97 75 75+ 75+ 75+ S1 S2 S3 S4 (l-S1) (l-S 2 ) (l-S3) (l-S4) Calves 93-94 94-95 95-96 94-95 75 75 75 75 Ss (1-Ss) (1-S6) (l-S7) (1-Sa) s6 S1 Sa -----------------------------------------------------------------------------93-94 37 (l-Sg) Male Calves Female Calves S9 94-95 95-96 94-95 37 37 37 S10 Su S12 (l-S10) (l-S 11 ) (l-S12) 93-94 94-95 95-96 94-95 38 38 38 38 S13 S14 S15 (l-S 13 ) (l-S14) (l-S15) (l-S 16 ) s16 We will assess whether calf survival can be predicted from body weight, hind foot length, or total body length at time of trapping (continuous variable) and sex, year, and trapping zone(s) (categorical variables) using logistic regression. We will also assess whether calf and/or adult survival can be predicted from weather variables such as mean monthly snow depth and temperature using logistic regression (PROC LOGISTIC, PROC CATMOD, SAS 1988; Bartmann et al. 1992). Tests will be significant at PS 0.05. We will use NOAA weather data from Rifle, Collbran, and Bonham Reservoir, Colorado, USDASCS snow depth coarses at Overland and Park Reservoirs on the Grand Mesa, and establish our own snow measurement coarse and weather station on the Garfield Creek State Wildlife Area deer/elk winter range. We will monitor fate of yearling bulls collared as calves immediately before and during hunting seasons to ascertain whether yearling bulls are illegally taken by hunters in areas where these bulls are protected from �96 FREDDY STUDY PLAN harvest by antler-point restrictions. Our selected study area is subject to antler-point restrictions during all hunting seasons but is adjacent to management areas where antler restrictions are not in effect during all seasons. Some yearling bulls may disperse into areas where they will be legal as yearlings, some will undoubtedly reside along the border where combinations of restrictions apply, and some will remain within the antler-point restriction area. We must assume hunters would select against yearling bulls having white radio collars compared to yearling bulls without collars resulting in negatively biased estimates of illegal harvest. However, if several collared bulls are taken illegally, we have evidence that a problem exists and the basis for designing a study specifically to test hypotheses regarding harvests of yearling bulls. If no bulls are illegally taken we cannot conclude that illegal harvest does not exist because the collars may effectively cause hunters to avoid taking marked bulls. u B. Population Size General Approach Counting all animals in a specific area is the intuitive approach to determining population size. Unfortunately, total counts over large areas are prohibitively costly in time and money and generally highly inaccurate because many animals present are not seen and counted (Caughley 1977). Efforts to improve population counts have followed 2 basic paths: designing sampling systems with statistical rigor to obtain precise estimates that often underestimate true population size (Siniff and Skoog 1964, Kufeld et. al. 1980), and developing procedures to correct for missed animals to improve accuracy of estimates (Bartmann et al. 1986, Samuel et al. 1987). Efforts to minimize numbers of animals missed during aerial counts often focused on variables that affect actual counting conditions such as experience of observers, height and speed of aircraft, type of aircraft, search time, weather conditions, and extent of snow background (Erickson and Siniff 1963, Caughley 1974, Gasaway et al. 1986). Although standardizing procedures may reduce variability between sampled counts, animals are stili missed, often in percentages exceeding 30% (Bartmann et al. 1986). Other efforts at improving accuracy attempted to model the probability of detecting animals. This probability function depends on group size, animal behavior, vegetation type and density, and age and sex class of individual (Floyd et al. 1979, Burnham et al. 1980, Samuel and Pollock 1981, Pollock and Kendall 1987, Samuel et al. 1987, Unsworth et al. 1990, Samuel et al. 1992). One solution to correcting for bias therefore lies in calculating probabilities of detection and correcting observed counts. We propose a multiple-step approach to developing a system to estimate elk densities: 1) estimate degree of sighting or counting bias on sample quadrats and develop an equation for predicting sightability using radiocollared elk as a known subpopulation, 2) apply predictive sighting bias correction factors to adjust counts of elk on sampled quadrats used to estimate density of elk over a large area and use mark-resight estimators based on radio-collared elk to provide an additional estimate of elk density from counts of marked and unmarked elk on the same quadrats, and 3) conduct multiple counts of elk on quadrats to test the repeatability of estimates based on the predictive sighting equation and mark-resight estimators. Elk radio-collared to estimate rates of survival will be used in developing methods to estimate population size. V �97 FREDDY STUDY PLAN Fundamentally, we believe a sampling system using quadrats instead of transects will be most appropriate for estimating densities of elk. Although line transect theory accounts for missing animals (negative sighting bias) (White et al. 1989), our experience with line transects to estimate densities of elk in portions of Middle Park, Colorado indicates too few groups of elk will likely be detected to provide reasonable precision, even with intensive repeated flights of transects (Freddy 1991). Additionally, quadrats are easier to fly than transects in rough terrain inhabited by elk. Initially, we will use a 2.59 km.2 quadrat. Developing a Sightability Model Given the premise of using a 2.59 km.2 quadrat as a sampling unit, we will estimate the probability, or degree of bias, of detecting elk on this size of quadrat using radio-collared elk (Samuel et al. 1987, Ackerman 1988). These authors used logistic regression to develop sighting models to predict the probability of detecting elk and mule deer (Odocoileus hemionus). Samuel et al. (1987) found group size and percent vegetation canopy coverage were the most useful variables to predict the probability of detecting elk in forested terrain of northern Idaho (n - 111 trials) while Ackerman (1988) found group size, animal activity, and vegetation type most useful for predicting detection of mule deer in brush-dominated habitats in southeastern Idaho (n 277 trials). Probability of sighting elk has been 0.35-0.95 in dense or .. open vegetation, respectively (Samuel et al. 1987) and 0.6-0.7 in mixed conifersagebrush (Artemisia tridentata) habitats (Bear et al. 1989). The logistic regression for predicting sightability is p.. exp(u) 1 + exp(u) where p - the sighting probability, (exp) - 2.718 1 and u - b 0 + b 1x 1 +b 2x 2 + ... bn'Xn, the multiple linear regression equation of (n) variables affecting sightability. Correction factors for each group of elk detected are obtained by inverting the estimated sighting probability (Samuel et al. 1987). The primary advantage of this sighting bias model approach is .that marked animals are not needed in the elk population once the model has been developed unlike traditional mark-resight models that require marking animals before every survey. The primary assumptions of this approach are: 1) Behavior of elk is not altered by the radio collar, 2) Visual detection of elk is not enhanced by the presence of the radio collar as concluded by Bartmann et al. 1987 1 Samuel et al. 1987, Ackerman 1988, and Bear et al. 1989 1 3) Selected radio-collared elk can be located to within a quadrat, 4) Collared elk can be individually identified either by radio frequency or collar symbol/numbers when detected, 5) Observers attempting to visually detect collared elk do not know the locations of marked elk, 6) The dependent variable, sighting probability, is asymptotic between values of O and 1, �98 FREDDY STUDY PLAN 7) The independent variables, whether numeric or categorical, are measured accurately, 8) Selected elk represent heterogenous habitats typically frequented by elk. V Major hypotheses to be tested are: 1) Logistic regression improves precision of sighting probability compared to a simple binomial sighting probability model, and 2) Predictive sighting models are repeatable among periods of time (years). The entire winter range within the study area will be divided into 2.59 lan2 units having boundaries based on topographic features instead of cadastral surveys. These irregularly shaped units will be approximately equal in size. Sightability tests will be conducted during 2 5-day periods in Januaryearly February 1994 and during 3 5-day periods in December, January, and February 1994-95. Our objective is to complete 80 test trials (16/day) on marked animals (seen or missed) during each 5-day period. We anticipate searching 16 quadrats/day at a rate of 15 min/quadrat resulting in 4-5 hours of helicopter use per day. During the 5 days, we will systematically cover the study area. During the first year, up to 150 different collared elk will be available which should reduce our need to repeat trials on individual elk during any 5-day period. We will conduct tests during the morning and afternoon and avoid mid-day to approximate traditional time periods when elk counts are conducted. Because sighting bias is largely associated with small groups of elk, we will attempt to fly when elk are widely distributed in small groups (Appendix VI). V A primary observer in a Cessna 185 will locate selected radio-collared elk (Gilmer et al. 1981) and assign each elk to a quadrat or quadrats if animals are near a quadrat boundary. Within 2 hours of locating an elk, 2 observers along with the pilot in a Bell-Soloy helicopter will search assigned quadrat(s) and enumerate all groups of elk and identify all radio-collared elk on the quadrat. Radio-collared elk will be identified either by the symbol/number on the collar and/or radio frequency using a receiver-scanner in the helicopter (Appendix I). When observers have completed their search of each quadrat they will check via radio with the primary observer to determine if they found the assigned elk. If the elk was found they will proceed to the next quadrat, but if the elk was missed the helicopter crew will immediately find the marked elk using telemetry and document its location as on or off the assigned quadrat. If more than 1 assigned elk occurs in a group only one animal will be used because observations may not be independent. If an assigned elk is missed and then found off the quadrat, the trial will be voided. To maintain vigilant observers, the helicopter crew will be assigned quadrats where there are no known radio-collared elk to serve as controls. For each group detected on a quadrat, observers will assign classification variables to describe conditions potentially affecting detection of each group whether or not the group contained a marked elk. These independent variables will be group size, activity of animal first detected in the group, vegetation type, percent vegetation canopy density, and V �99 FREDDY STUDY PLAN percent snow cover. These variables must also be noted for those groups containing assigned marked elk that are missed during the initial search of the quadrat. Additional independent variables assigned to all groups observed during a flight will be year, flight, pilot, observer, search time per quadrat, and age/sex of marked animals detected (Appendix V). During the first year we will attempt to use only one experienced observer, navigator, and pilot in the helicopter with the intent of controlling these variables. The helicopter crew will be trained prior to collecting data. We anticipate group size, activity, vegetation type, and percent vegetation canopy cover may significantly influence sighting probability (Samuel et al. 1987 and Ackerman 1988). We also anticipate that percent vegetation canopy cover may be difficult to judge. Samuel et al. (1987) worked primarily in habitats having tall conifers. They considered vertical canopy cover to be any vegetation obstructing the observer's view of an elk group for up to 30 m around the group (Unsworth et al. 1991). Ackerman (1988) correctly noted that animals are seldom viewed from vertical but rather from oblique angles. Confounding this perception of visual obstruction are • deciduous habitats, such as oakbrush (Quercus gambelii) and aspen (Populus tremuloides), that can be seen through during winter and only partially obscure one's view of elk even when canopy coverage may approach 100%. A similar problem involves sagebrush which can effectively hide a bedded animal with little distinguishable vertical canopy. We will follow suggestions by Unsworth et al. (1991) but anticipate this to be a difficult variable to estimate. Using stepwise logistic regression (SAS 1988), independent variables will be evaluated as to their significance in predicting the probability of sighting elk (groups seen or missed) to develop a predictive sightability model. Model fit will be assessed using AIC and log-likelihood values. We anticipate transforming some independent numeric variables .to improve conformity of data to model assumptions. We will compare simple binomial and complex sightability models using computer simulations to assess whether independent variables meaningfully improve precision of the sighting probability estimator and also compare the mean and variance of estimates of elk density derived from corrected and uncorrected counts of elk on quadrats. Sightability models among flight periods will be compared to assess the repeatability of the sighting model when pilot and observers remain constant. If we achieve a sample of 80 trials/flight period, power (1-beta) at alpha - 0.05 to detect a difference between sighting models will be about 0.57 (SE~0.016) (sighting models from Samuel et al. 1987 for sighting functions at 20 and 40% vegetation cover). Power improves to about 0.87 (SE=0.006) when n > 160 trials. These power calculations assume surveys will encounter groups of elk at frequencies of group sizes similar to those observed during preliminary sampling flights (Appendix VI, Table 2). If observed sizes of groups shift towards large groups then power of tests would be less because differences in sighting probabilities between models is most pronounced for small groups (Appendix VI). �100 FREDDY STUDY PLAN Comparing Population Estimators We will estimate total population size within the study area during winter using 3 approaches based on a random quadrat sampling system. This effort will begin in 1994-95 with one flight of quadrats to evaluate logistics, adequacy of sampling, and initial estimates of population size and then continue in 1995-96 and 1996-97 with 3 repeated flights each year if quality of results justifies the effort. We will randomly select about 15% of the potential quadrats and search these quadrats each flight following procedures suggested by Kufeld et al.(1980). Sampling may be stratified according to expected animal density based on distribution of radio-collared elk in 1993-94. For quadrats, we will use 3 estimators to calculate density of elk and all 3 estimators will use the same counts of elk generated from each flight: 1) uncorrected counts of elk on quadrats, 2) counts of elk on quadrats corrected for sighting bias based on the appropriate sighting bias model, and 3) counts of elk on quadrats corrected for sighting bias based on Lincoln-Petersen mark-resight estimator combined for repeated flights using the joint hypergeometric maximum likelihood estimator (JHE) (White and Garrott 1990). The Lincoln-Petersen estimator for each individual flight is: A N1 - -11!1 + 1} Cn 1 + 1) -1 V (m1 + 1) with an estimated variance of A A Var CN1) - ....!n1 + 1) Cn1 + 1) Cn~1lln1-=-m1l (m1 + 1) 2 (m1 + 2) A A A and a nominal 95% confidence interval of N1 ± 1.96 vVar(N1 ) where n 1 is number of radio-collared elk, n 1 is number of elk observed on each aerial survey, and m1 is number of marked elk observed on.each survey. We will compare means and variances of estimates derived from each method. Assumptions for each estimator are: Uncorrected Counts: a) All elk on the quadrats are counted and b) only elk on quadrats are counted (no boundary errors). Assumption a) is likely violated and is the reason for developing a sighting bias model to correct counts. Corrected Counts: c) assumptions are listed in the previous section. We will apply sighting bias corrections to each observed group of elk according to the sighting bias model. Lincoln-Petersen Mark-Resight: d) probability of sighting marked and unmarked elk is the same, e) marked and unmarked elk are correctly classified (marks are discernible), f) marked elk are randomly selected and distributed throughout the population or at least resighting effort is randomly distributed throughout the population, g) each animal has an V �101 FREDDY STUDY PLAN identical but independent probability of being resighted, h) number of marked elk (radio collars) in the population is known at the time of the survey which implies that marks are not lost or unaccounted for, and i) the population is geographically and demographically closed; i.e., there is no immigration or emigration, recruitment or death during the survey in a geographically defined area (Otis et al. 1978, Bear et al. 1989). Assumptions for Lincoln-Petersen mark-resight estimates may be the most difficult to achieve and evaluate. To achieve adequate numbers of marked animals in the population, elk marked each year must accumulate and be used during the years of population surveys. We implicitly assume that detection of white radio collars from year 8 is equal to detection of white collars from yearb when surveys are flown in yearc, otherwise there will be different sighting probabilities for each cohort of marked elk. We also must assume there will be some (1-5%) nonoperative radio collars on live elk which would create an error in knowing how many elk are marked within the area surveyed (fixed-winged flights will be conducted prior to population surveys to determine number of functioning radios in the sampled area using and observer independent of counters). This type of error would cause positive bias in population estimates. Bear et al. (1989) identified marker visibility, random sampling of the population, and heterogeneous sighting probabilities due to group size or vegetation type as problems associated with applying mark-resight estimators to elk populations. We have attempted to address these concerns by using high-contrast white collars not prone to color bias, helicopters to capture elk throughout the distribution of the population, use of random sampling to survey the population, and use of multiple independent aerial resight (recapture) surveys to reduce recapture bias associated with other recapture techniques and to improve precision of estimates (Otis et al. 1978, Bartmann et al. 1987, Bear et al. 1989, Neal et al. 1993). Effects of group size and vegetation type are sources of sighting heterogeneity which can bias the variance of the estimate and may negatively bias the estimate (Bear et al. 1989, Neal et al. 1993). Comparing variances of estimates derived from markresight and the sighting probability model may provide some insight into the severity of heterogenous sighting probabilities. Population estimates based on the JHE mark-resight approach will be calculated using the program NOREMARK (G. White, pers. comm.). We also used NOREMARK to simulate expected quality of population estimates for the JHE estimator given the following constraints. If the real population consists of 2,000 elk, 200 elk are marked with radio collars, about 10% of all elk are observed on each flight ([sighting probability - 0.60) x [proportion of area sampled - 0.15)), and 3 replicate flights are completed, we should achieve a 90% confidence interval about the true population of± 20% with a 1% positively biased estimate of population size. Confidence interval coverage would be 89% (n - 500 Monte Carlo simulations). During the second year of the project when mark-resight surveys will be initiated on quadrats, there could be about 200 marked elk in the population. Precision of JHE estimates would improve to± 15% if 300 marked elk were available or 5 replicate flights were completed. These would be potential design options if marked elk continued to accumulate in the third or fourth year of the project or helicopter hours were �102 FREDDY STUDY PLAN V reallocated among uses or increased. The JHE estimator does not require that marked elk are individually identified, only that marked and unmarked elk are discerned. If we can consistently identify individual elk by collar numbers or radio frequency, the Minta-Mangel mark-resight model can be used to estimate population size and associated variance (Minta and Mangel 1989) using program N0REMARX. Variance of this estimator can be calculated as described by Minta-Mangel (1989) or in a new approach developed by Bowden (1993, unpubl. ms.). Complete capture histories on each marked elk would also allow an assessment of bias associated with the estimate of N due to unequal individual capture probabilities. Unequal capture probabilities can be caused by individual animal behavior, time intervals between initial capture and resight surveys, and heterogeneity of capture probabilities due to factors of age, sex, social dominance, or habitat. Program CAPTURE will be usedAto evaluate the most appropriate capture probability model to estimate N (Rexstad and Burnham 1991). C. Distribution and Movements of Elk General Approach All visual sightings of live and dead collared elk will be assigned UTM coordinates as determined from USGS topographic maps. Visual sightings of collared elk during winter will occur during ground surveys to determine life/death status of elk and during aerial surveys to estimate population density. These locations will provide a general perspective of the distribution of elk on their winter range. V Seasonal patterns of movement will be obtained primarily from aerial surveys. Accurate seasonal locations on all collared elk would be cost prohibitive and not commensurate with the main objectives of the project. Therefore we plan to randomly select 20% of the calves (8 M, 8 F) and 20% of the adult females (15) and monitor their locations periodically to reveal patterns of seasonal movement. Yearling males marked as calves will be located prior to hunting seasons to monitor their fates in relation to antler-point restrictions. Distribution and movement data will be plotted following suggestions of White and Garrott (1990). V. SCHEDULE Activity Approximate Date Phase !--Complete detailed study plan, July 1992-June 1993 select study location, refurbish elk traps, purchase radio collars for calves and design expandable collars for calves. Phase !!--Complete initial purchase of July 1993-June 1994 radio collars; trap and radio-collar Trapping 12/93 elk to estimate survival; begin surveys Sighting bias to design sighting bias estimator. 1 & 2/94 V �103 FREDDY STUDY PLAN July 1994-June 1995 Phase III--Continue radio-collaring Trapping 12/94 elk for estimating survival, Sighting bias 12/94, continue testing sighting bias estimator, estimate population 1/95, 2/95; Pop. Est. 1 & 2/95 size using quadrats and mark-resight. Phase IV-- Estimate pop. size July 1995-June 1997 size using sighting bias correction, Trapping 12/95 & quadrats, and mark-resight. Continue 12/96; Pop. Est. trapping to estimate survival. 1/96 &1/97 VI. PERSONNEL PROGRAM RESPONSIBILITIES David J. Freddy: Principal Investigator responsible for final project design, organizing field personnel, obtaining and organizing data, financial control, coordinating publications. R. Bruce Gill: Provide administrative support, input for study design, and liaison with other administrative sections within the Division of Wildlife or other natural resource agencies. \,_,_,/ John H. Ellenberger and James H. Olterman: Provide input for study design and location, coordinate study with Regional activities, and logistical support. David C. Bowden and Gary C. White: Provide input for study design and statistical protocol, conduct data analyses, and provide software support. �104 FREDDY STUDY PLAN VII. V BUDGET-SUMMARY ACTIVITY FY92-93 Personal Operating Travel Capital Total 55,773 26,800 1,200 4,700 88,473 W/ 4% inflation BUDGET-ITEMIZED FY94-95 FY95-96 FY96-97 70,706 72,236 70,706 72,236 66,370 93,045 66,020 72,270 4,940 4,940 4,680 5,590 0 5,700 0 0 141,666 154,886 142,016 170.871 161,081 FY92-93 PERSONAL SERVICES $49,841 A. D.J. FREDDY 12 MOS $2,509 8. MAMMALS SECR. 1 MOS $0 C. UTILITY I 6 MOS OCT-MAR $2,723 D. UTILITY 1, TRAPPING E. WORK STUDY STUDENT, 1 YEAR $700 $0 F. VOLUNTEER FOR 20 DAYS $55,773 SUB-TOTAL OPERATING G. VEHICLES MILEAGE, 4X4, 3 $2,200 H. VEHICLES, SNOWMOBILES, ATV $0 I. NEW RADIO COLLARS $19,500 J. REFURBISHED RADIO COLLARS $0 $3,000 J. TRAPPING, BAIT, SUPPLIES $1,500 K. MISC. SUPPLIES, SERVICES L. FIXEDWINGED, MORT. SURV. $600 M. FIXEDWINGED, SIGHT. SURV. $0 N. HELICOPTER, SIGHT. SURVEYS $0 0. HELICOPTER, QUAD. SURVEYS $0 P. HELICOPTER, NONRANDOM SURV. $0 Q. HELICOPTER TRAPPING $0 SUB-TOTAL $26,800 TRAVEL R. DJF 10 DAYS, STANDARD $650 S. DJF DAYS TRAPPING $550 $0 T. VOLUNTEER, TRAPPING U. REGION PERSONS, TRAPPING $0 $0 V. REGION PERSONS, SURVEYS $1,200 SUB-TOTAL CAPITAL EXPENSES $3,200 W. RADIO TELEMETRY RECEIVER X. PACK-SETS/LAPTOP COMPUTER $1,500 $4,700 SUB-TOTAL PROJECT YEARLY TOTAL WITH 4X INFLATION FY93-94 $88,473 177,706 147,333 FY93-94 FY94-95 FY95-96 $56,796 $56,796 $2,500 $9,180 $3,060 $700 $0 $72,236 $56,796 $56,796 $2,500 $9,180 $3,060 $700 $0 $72,236 $2,500 $9,180 $1,530 $700 $0 $70,706 $2,500 $9,180 $1,530 $700 $0 $70,706 $5,720 $350 $8,600 $0 $2,500 $2,500 $3,150 $2,700 $21,750 $0 $0 $25,000 $72,270 $5,720 $350 $15,000 $4,050 $2,500 $2,500 $3,150 $4,050 $32,625 $4,350 $0 $18,750 $93,045 $5,720 $5,720 $350 $350 $6,000 $5,000 $6,750 $5,400 $2,500 $2,500 $2,500 $2,500 $3,150 $3,150 $1,800 $1,800 $0 $0 $21,750 $21,750 $4,350 $4,350 $12,500 $12,500 $66,020 ,$66,370 $650 $1,365 $0 $1,365 $1,300 $4,680 $650 $1,365 $0 $1,365 . $2,210 $5,590 $650 $1,365 $0 $1,365 $1,560 $4,940 $650 $1,365 $0 $1,3~5 $1,560 $4,940 $3,700 $2,000 $5,700 $0 $0 $0 $0 $0 $0 $0 $0 $0 147,697 FY96-97 $154,886 $170,871 $141,666 $142,016 $161,081 $177,706 $147,333 $147,697 """**************************************"""1Tt*"""1Tt*****"""************************************* 0 REGION TRAPPING MDAYS 65 REGION PILOT, HRS 20 REGION BIOL.,FLYING MDAYS REGION PICKUP(S)+TRAP TRAILER(S) TRAP A/N REGION SKIDOO ALPINE AND ATV 3 REGION PROP. TECH. MDAYS 21 65 20 TRAP A/N 3 21 80 34 TRAP A/N 3 21 55 24 TRAP A/N 3 21 55 24 TRAP A/N 3 -- V .. �105 FREDDY STUDY PLAN VIII. LOCATION We selected the eastern portion of GMU 42 within the Grand Mesa DAU (E14) for conducting this project (Appendix VII). This area encompasses about 1,028 km2 (397 mi 2 ) in the Divide Creek drainages located south of the towns of Newcastle and Rifle in west-central Colorado. We estimate that 1500-3000 elk inhabit about 642 km2 (248 mi 2 ) of winter range within this area. This area meets the following necessary criteria: 1) the elk population is relatively "closed" during the winter, that is, subject to minimal emigration or immigration, and assumes a somewhat static distribution during winter; 2) the winter range generally has reliable snow cover to facilitate detecting elk during population surveys and mixed vegetation types consisting of oakbrush, aspen, sagebrush, juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), mixed conifers (Picea sp., Abies sp.) and agricultural fields typical of many elk winter ranges in western Colorado; 3) there is dependable access for research purposes to both private and public lands and dependable public access to public lands for hunting; 4) there is minimal large-scale land-use conflict problems such as agricultural damage; 5) there is local, area, and regional CDOW support for conducting the project in this area; and 6) the airport at Rifle will provide readily accessible support services. IX. LITERATURE CITED Ackerman, B. B. 1988. Visability bias of mule deer aerial census procedures in southeast Idaho. Phd. Thesis. University of Idaho, Moscow. 106pp. Bartholow, J. 1992. Pop-II system documentation. Fossil Creek Software, Fort Collins, CO. 50pp. Bartmann, R. M. 1984. Estimating mule deer winter mortality in Colorado. J. Wildl. Manage. 48:262-267. _ _ , Carpenter, L. H., R. A. Garrott, and D. C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildl. Soc. Bull. 14:356-363. ___ , and G. C. White. 1991. Compensatory effects of harvest in a mule deer population. Colo. Div. Wildl. Game Res. Rep. July:28-40. ___ , , L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildl. Monogr. 121. 39pp. ___ , , ___ , and R. A. Garrott. 1987. Aerial mark-recapture estimates of confined mule deer in pinyon-juniper woodland. J. Wildl. Manage. 51:41-46. Bear, G.D. 1986. Expanding telemetry collar for elk calves. Colo. Div. Wildl. Game Info. Leaflet 112. 2pp. 1989. Seasonal distribution and population characteristics of elk in Estes Valley, Colorado. Colo. Div. Wildl. Spec. Rep. 65. 14pp. ___ , G. C. White, L. H. Carpenter., R. B. Gill, and D. J. Essex. 1989. Evaluation of aerial mark-resighting estimates of elk populations. J. Wildl. Manage. 53:908-915. Bowden, D. C. A simple technique for estimating population size. Unpubl. ms. 17pp. Boyce, M. S. 1989. The Jackson elk herd, intensive wildlife management in North America. Cambridge Univ. Press, Cambridge. 306pp. �106 FREDDY STUDY PLAN Burger L. W., Jr., M. R. Ryan, D. P. Jones, and A. P Wywialowski. 1991. Radio transmitters bias estimation of movements and survival. J. Wildl. Manage. 55:693-697. Burnham, K. P., D.R. Anderson, and J. L. Laake. 1980. Estimation of density from line transect sampling of biological populations. Wildl. Mono. 72. 202pp. Caughley, G. 1974. Bias in aerial survey. J. Wildl. Manage. 38:921-933. 1977. Analysis of vertebrate populations. John Wiley & Sons, New York. 232pp. Colorado Division of Wildlife. 1990. Colorado big game harvest. Colo. Div. Wildl., Denver. 173pp. _ _ . 1991. Colorado big game harvest. Colo. Div. Wildl., Denver. 172pp. _ _ . 1991b. Long Range Plan (revised). Colo. Div. Wildl., Denver. 16pp. de Vergie, W. J. 1989. Elk movements, dispersal, and winter range carrying capacity in the upper Eagle River valley, Colorado. MSc. Thesis, Colorado St. Univ., Fort Collins. 124pp. Erickson, A. W., and D. B. Siniff. 1963. A statistical evaluation of factors influencing aerial survey results on brown bears. Trans. N. Am. Wildl. Conf. 28:391-409. Foster, C. C., E. D. Forsman, E. C. Meslow, G. S. Miller, J. A. Reid, F. F. Wanger, A. B. Carey, and J.B. Lint. 1992. Survival and reproduction of radio-marked adult spotted owls. J. Wildl. Manage. 56:91-95. Floyd, T. J., L. D. Mech, and M. E. Nelson. 1979. An improved method of censusing deer in deciduous-coniferous forests. J. Wildl. Manage. 43: 258-261. Freddy, D. J. 1987. The White River elk herd: a perspective, 1960-85. Colo. Div. Wildl. Tech. Publ. 37. 64pp. 1991. Elk census methodology. Colo. Div. Wildl. Game Res. Rep. July: 59-72. _ _ , D. L. Baker, R. M. Bartmann, and R. C. Kufeld 1993. Deer and elk management analysis guide, 1992-1994. Colo. Div. Wildl., Div. Rep. 17. 77pp. (In press). Garrott, R. A., and G. C. White. 1982. Age and sex selectivity in trapping mule deer. J. Wildl. Manage. 46:1083-1086. Garrott, R. A., R. M. Bartmann, and G. C. White. 1985. Comparison of radiotransmitter packages relative to deer fawn mortality. J. Wildl. Manage. 49:758-759. Gasaway, W. C., S. D. DuBois, D. J. Reed, and S. J. Harbo. 1986. Estimating moose population parameters from aerial surveys. Institute of Arctic Biol., Biol. Papers Univ. of Alaska No. 22. 108pp. . Gilmer, D. S., L. M. Cowardin, R. L. Duval, L. M. Mechlin, C. W. Shaiffer, and V. B. Kuechle. 1981. Procedures for the use of aircraft in wildlife biotelemetry studies. USDI Fish & Wildl. Serv. Resource Publ. 140. 19pp. Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and causespecific mortality rates using telemetry data. J. Wildl. Manage. 49:668-674. Houston, D. B. 1982. The northern Yellowstone elk, ecology and management. Macmillan Publ. Co., Inc. New York. 474pp. Kufeld, R. C., J. H. 0lterman, and D. C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. J. Wildl. Manage. 44:632-639. V ., �107 FREDDY STUDY PLAN Laake, J. L. 1992. Catch-per-unit-effort models: an application to an elk population in Colorado. Pages 44-55 in D.R. McCullough and R.H. Barrett, eds., Wildlife 2001: Populations. Elsevier Publ., London. Leptich, D. J., and P. Zager. 1991. Road access management effects on elk mortality and population dynamics. Pages 126-131 in A.G. Christensen, L. J. Lyon, and T. N. Lonner, comps., Proc. Elk Vulnerability Symp. Montana St. Univ. , Bozeman. Minta, S. and M. Mangel. 1989. A simple population estimate based on simulation for capture-recapture and capture resight data. Ecology 70:1738-1751. Neal, A. K., G. C. White, R. B. Gill, and D. F. Reed. 1993. Evaluation of mark-resight methods to estimate mountain sheep numbers. J. Wildl. Manage. (In press). Nelson, L. J., and J.M. Peek. 1982. Effect of survival and fecundity on rate of increase of elk. J. Wildl. Manage. 46:535-540. Pemberton, J.M., S. D. Albon, F. E. Guinness, T. H. Glutton-Brock, and R. J. Berry. 1988. Genetic variation and juvenile survival in red deer. Evolution 42:921-934. Pollock, K. H., and W. L. Kendall. 1987. Visibility bias in aerial surveys: A review of estimation procedures. J. Wildl. Manage. 51:502-510. ___ , S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. J. Wildl. Manage. 53:7-15. Quimby, D. C., and J. E. Gaab. 1957. Mandibular dentition as an age indicator in Rocky Mountain elk. J. Wildl. Manage. 21:134-153. Rexstad, E., and K. Burnham. 1991. User's guide for interactive program CAPTURE. Coop. Fish & Wildl. Res. Unit, Colorado St. Univ., Fort Collins. 29pp. Samuel, M. D. and K. H. Pollock. 1981. Correction of visibility bias in aerial surveys where animals occur in groups. J. Wildl. Manage. 45:993997. _ _ , E. O. Garton, M. W. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. J. Wildl. Manage. 51:622-630. ___ , R. K. Steinhorst, E. 0. Garton, and J. W. Unsworth. 1992. Estimation of wildlife population ratios incorporating survey ~esign and visibility bias. J. Wildl. Manage. 56:718-725. SAS Institute, Inc. 1988. SAS Language guide for personal computers. SAS Institute Inc., Cary, NC. 1028pp. Sauer, J. R., and M. S. Boyce. 1983. Density dependence and survival of elk in northwestern Wyoming. J. Wildl. Manage. 47:31-37. Schlegel, M. W. 1977. Factors affecting calf elk survival on Coolwater Ridge in north central Idaho. Pages 35-37 in Proc. Western States Elk Workshop, Estes Park, Colo. Siniff, D. B., and R. 0. Skoog. 1964. Aerial censusing of caribou using stratified random sampling. J. Wildl. Manage. 28:391-401. Unsworth, J. W., L. Kuck, and E. 0. Garton. 1990. Elk sightability model validation at the National Bison Range, Montana. Wildl. Soc. Bull. 18:113-115. ___ , F. A. Leban, G. A. Sargeant, E. 0. Garton, M.A. Hurley, J. R. Pope, and D. J. Leptich. 1991. Aerial survey: user's manual with practical tips for designing and conducting aerial big game surveys. Idaho Dep. �108 FREDDY STUDY PLAN Game & Fish, Boise. 54pp. Wade, D. A., and J. E. Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas Agric. Expt. Sta. Publ. B-1429. 42pp. u White, G. C. 1983. Numerical estimation of survival rates from band recovery and biotelemetry data. J. Wildl. Manage. 47:716-728. _ _ . 1992. DEAMAN database manager and population modeling procedures; Colorado Division of Wildlife User's manual and reference. Colorado St. Univ., Fort Collins. 109pp. ___ ,D.R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capturerecapture and removal methods for sampling closed populations. Los Alamos Natl. Lab. IA-8787-NERP. 235pp. ___ , R. M. Bartmann, L. H. Carpenter, and R. A. Garrott. 1989. Evaluation of aerial line transects for estimting mule deer densities. J. Wildl. Manage. 53:625-635. ___ , and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego. 383pp. ___ , R. M. Bartmann, L. H. Carpenter, and A. W. Alldrege. 1987. Survival of mule deer in northwest Colorado. J. Wildl. Manage. 51:852859. Zager, P., and D. J. Leptich. 1991. Comparing two methods of calculating elk survival rates. Pages 106-109 in A.G. Christensen, L. J. Lyon, and T. N. Lonner, comps., Proc. Elk Vulnerability Symp. Montana St. Univ., Bozeman. APPENDIX I Specifications for Radio Collars Pulse Rate Normal: 60-65 ppm Pulse Rate Mortality: 120-130 ppm Motion Sensor Delay: 4-6 hrs Batteries: 4+ year life, 2 lithium D-cells adults, 1 lithium D-cell calves Antenna: External whip, pvc coated Collar Material: 7.6 cm (3") wide white colored smooth surfaced conveyor belting, 2 layers sewn together, 0.64 cm (1/4") total thickness Additional Material: Bright white with black core Ritchie All-Flex rubber material for identifcation symbol/number placed as a sleeve over top portion of collar Collar Size: 61-81 cm (24-32") adult females, individually fitted 61-81 cm (24-32") expandable for female calves 61-97 cm (24-38") expandable for male calves Collar Weight: About 1.1 kg V �109 FREDDY STUDY PLAN APPENDIX II Animal Welfare Concerns There are 3 potential issues regarding animal welfare: use of ear-tags, use of radio collars, and capture techniques. Ear-tags: To permanently mark radio-collared animals and some non-collared animals, an aluminum, numbered and colored ear-tag will be placed in each ear. Tags are self-piercing using special pliers and have been used for many years on elk. To reduce potential problems of tag loss, tags will be placed on front edge of the ear about 1/3 to 1/2-way above the base of the ear and the edge of the tag will be flush with the edge of the ear. Radio collars: Fitted size of radio collars is based on measurements from hunter-killed elk and captive research elk and testing of actual collars on captive elk. The basic expandable design for calves has been extensively field tested on deer and moose. Capture Techniques: We will capture elk in traditional corral traps capable of holding several elk at one time and by net-gunning individual elk from a helicopter. We expect a 1-2% serious injury/mortality rate with either technique. Animals having a broken leg, neck, or pelvis will be euthanized with a gunshot to the head following euthanasia procedures in our Animal Welfare guide. All persons involved in capture will be trained to properly euthanize appropriate animals. Capture techniques will be constantly monitored and changed if necessary to insure that minor injuries to animals do not chronically occur. Animals captured with a helicopter will be hobbled and blindfolded and slung under the helicopter to a nearby field processing point where they will be collared, weighed, etc. and then released at that site. We aniticapte 1-5 minutes to capture the elk, 1-2 minutes to ferry the elk to .processing point, and 3-4 minutes to process the elk before release. This technique has been successfully used to capture and radio-collar elk in Arizona, Colorado, Idaho, Montana, Oregon, and Washington. Because of short handling times, mortalities due to capture have been rare. Animals captured in corral traps will be blindfolded as they are processed in the chutes. Calves may be hobbled or walked into a holding box for weighing. We prefer to trigger traps manually using a solenoid system so we can be selective about animals captured and reduce the time animals are in traps. However, traps may be triggered by animals entering and in such cases animals may be in the trap overnight. Food will be provided via alfalfa used as bait. We will use the minimum number of persons to process elk to reduce capture stress. �110 FREDDY STUDY PLAN . APPENDIX III Visual Identification System for Radio Collars Numbers, symbols, and letters will be used in ordered combinations to identify individual elk primarily during mark-resight aerial surveys. No more than 3 characters will be used to identify an individual and there will always be a 2-digit number. Numbers Used ( 8) : •0 , 1, 2 , 3 , 4 , 5 , 6 , and 7 Symbols Used (5): ., ■, ♦, ◄, + Letters Used (11): A, C, F, H, K, N, P, T, V, X, y 10, 20, 11, 21, 12, 22, 13, 23, 14, 24, 15, 25, 16, 26, 17, 27, Number Matrix 30, 40, 50, 60, 31, 41, 51, 61, 32, 42, 52, 62, 33, 43, 53, 63, 34, 44, 54, 64, 35, 45, 55, 65, 36, 46, 56, 66, 37, 47, 57, 67, 70 71 72 73 74 75 76 77 Each Symbol with each number represents 56 identification codes; all symbols with each number equals 280 codes or animals. Each letter with each number represents 56 codes; all letters with each number equals 616 codes or animals. Therefore, 896 different animals can be individually marked using this system. V �.L.L.L FREDDY STUDY PLAN APPENDIX IV ,. Precision and Power of Survival Estimates and Tests 30 ii 25 S•0.50 ! .. I ... 120 0 115 ~ !, 10 S •0.80 .. S •0.80 • S • 0.70 ■ • * 5 50 100 75 RADlO COLLARS DEPLOYED 1 =. 0 I I DETECT DIFFERENCES IN SURVIVAL OF: DIFF•O.25 DIFF•0.2 DIFF•0.1 DIFF•0.05 o.a ... --------······· 0.8 @ .. -.... ffi 0.4 ··········•••••••••••• ~ I ..----· --- ---------······ ................................... ...................... ···-·••" ..... 0.2 a. 0 20 40 60 75 80 100 RADIOCOUARS DEPLOYED 1.2 ! I I @ DETECT DIFFERENCES IN SURVIVAL OF: DIFF•O.25 DIFF•0.2 DIFF•0.1 DIFF•0.05 1 ---------~------------------------------ o.a ············••••••••••••••• 0.8 Ii ~ ~ ·~ I - .-··············· ................................................. ... 0.4 0.2 0 20 40 60 75 RADIO COLLARS DEPLOYED 80 100 �112 FREDDY STUDY PLAN V APPENDIX V Classification variables for elk groups and flight conditions for sightability trials, Group Size 1 2 3 Vegatation Type Activity Level Oakbrush-dense/continuous Oakbrush-scattered/clumped Aspen Sagebrush Pinyon-Juniper Tall Conifer Agri. Fields/Clearings Riparian Bedded Standing Moving 4 5 6 7 8 9 10-14 15-19 20-24 ~25 % Vegetation Canopy Vertical Cover 0-15 16-25 26-35 36-45 46-55 56-65 66-75 76-85 86-100 %Snow Cover Snow Type 0 Fresh New Snow Old snow with old tracks 1-25 26-50 51-75 76-99 100 Lighting Conditions Age/Sex Marked Elk Bright Sun/High Contrast Male Calf Female Calf Hazy Sun Adult Female Overcast, dull light Yearling Male Adult Male Search Rate Year/Period Pilot Observer 1993-94-I 1993-94-II 1994-95-I 1994-95-II 1994-95-III 1993 1993 1994 1994 km2 / min �113 FREDDY STUDY PLAN APPENDIX VI Power Considerations for Sightability Models Dr. David C. Bowden Consider the logistic model (1) below which describes the probability of observing elk groups for a given set of observational conditions. Assume that the same model also describes the probability of observing elk groups for a different set of conditions but with a different value for the parameter Po• Suppose data is obtained under both sets of conditions. This section describes the results of a simulation study which investigates the power of a test of the hypothesis that the parameter value for Po is the same for both sets of conditions. In the simulation study, observations were generated as if two sets of conditions applied. Then a test of equality of the 2 Po values was performed. This process was repeated 1000 times. The proportion of times that the null hypothesis was rejected estimates the power of the given test. Following Samuel et al. (1987), it is assumed that the probability of sighting elk groups in uniform habitat relative to percent vegetation cover can be adequately modeled as P = 1/ (1 + exp (- ((3 0 +P 1 ln (g)) ) (1) where pis the probability of sighting a group of size gin the specified habitat, Po and P1 are parameters and ln(g) is the natural logarithm of g. Those authors estimated the parameter values to be .22 and 1.55, respectively for habitat locations with 20 % vegetation cover and -0.78 and 1.55 with 40% vegetation cover. These sets of estimates were used to specify the parameter values for the simulation study. Table 1 gives values of p for the 2 sets of parameter values and a few choices of group sizes. Thus the problem of interest is, "What is the chance that a change in sighting probabilities as given in Table 1 will be detected if the conditions of the simulation study apply?" �114 FREDDY STUDY PLAN V Table 1. Probability of sighting given 2 sets of parameter values at different group sizes (g). Sample 1 uses Po = . 22 and P1 = 1, 55 in function (1) and Sample 2 uses Po m - • 78 and p1 = 1. 55. Group size(g) PROBABILITY SAMPLE 1 SAMPLE 2 1 .555 .314 2 .785 .573 3 .872 .716 4 .914 .797 5 .938 .847 6 .952 .881 10 .978 .942 15 .988 .968 20 .992 .979 30 .996 .989 Generation of observations for a single iteration in the simulation study is described next. A set of n elk groups were used to generate 2 samples of elk group observational data. Sample 1 was generated by taking an observation from a Bernoulli random variable for each group where the probability of success is given by probability function (1) with Po = .22 and p1 = 1. 55 , that is, a random uniform number on the interval [O, 1), say u, was selected, if u~p then the group was said to be sighted otherwise it was not sighted. The second sample of n observations was independently generated with the same group sizes using parameter values Po c - • 7 8 and p1 = 1. 55 and function (1) to obtain the needed probability of success. ·The 2 samples of sighting data were pooled and then analyzed using the SAS logistic regression procedure. The following model was fit to the pooled data set: p = 1 / ( 1 + exp ( - ( PO + P1 ln ( g > + P2 z ) ) ) (2) where z is an indicator variable which is equal to O if the observation came from sample 1 and is equal to 1 if the observation came from sample 2. The question of interest is, "What is the power of a «-.05 test of the hypothesis that p2 O versus an alternative hypothesis 11 2 .. O when actually p2 = -1 ?" This null hypothesis is equivalent to stating that the 2 samples were generated from the same logistic function. Of course the power of the test depends on the distribution of group sizes and the number of groups in each sample. It should also be clear from Table 1 that groups of sizes 1-10 are needed to obtain reasonable power unless very large numbers of groups are observed in both samples. Group sizes used in the study are those obtained from a sample survey i.: V �115 FREDDY STUDY PLAN of a winter elk population. This sample survey was a stratified random quadrat count in game management unit 23, 24 on January 18-19, 1989 by C. Reichert, J.Ellenberger, and D. Freddy. During the sample survey, 84 elk groups were observed and group size recorded (Table 2). Table 2. Frequency distribution of the 84 elk group sizes. Group size 1 2 3 4 5 6 7 8 9 Frequency 9 12 10 9 10 5 4 4 6 Group size 10 11 12 13 16 18 19 20 39 Frequency 1 3 2 3 1 1 1 2 1 Two independent simulation studies were performed using the frequency distribution ·of group sizes from Table 2 in the data generation step. Each study consisted in 1000 replications of pairs of samples generated as described above. In the first study, for each of the 84 listed group sizes, a determination of sighting or not was made, independently, using the 2 probability sighting functions. In the second study the frequency of groups of a given size·in Table 2 was doubled to give 2 samples of size 168, replicated 1000 times. For each replication the 2 samples were pooled and model (2) fitted. Then the null hypothesis that 11 2 = O was tested. The number of rejections of this null hypothesis is shown for the 1000 replications in Table 3 as 10 sets of 100 tests each. The standard error of the estimated power was calculated using variation among the 10 sets. Thus given 2 independent samples of observations each based on 84 groups with frequency distribution listed in Table 2, a 5% significance level test has an estimated power of . 57 ( se-.016) of rejecting H0 : 11 2 = O when P2 = -1. The estimated power when the number of groups is doubled (n-168 each) is estimated to be .873 ( se-.006). �116 FREDDY STUDY PLAN V Table 3. Proportion of rejections of the null hypothesis H0 : p2 = O vs HA: P2 ~ O when P2 = -1 , for 10 sets of 100 replications each, Cl = . 05. Set Sample I Sample II 1 .58 .89 2 .59 .89 3 .62 .88 4 .66 .86 5 .57 .91 6 .58 .88 7 .52 .85 8 .51 .88 9 .57 .86 10 .50 .90 Mean .57 .88 SE .016 .006 u Reference Samuel, M., E. Garton, M. Schlegel, and R. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. J. Wildl. Manage. 51: 622-630. V �.&..&., FREDDY STUDY PLAN APPENDIX VII Location of the study area in the eastern portion of Game Management Unit 42 within the Grand Mesa Data Analysis Unit E-14. 50 MILES NEWCASTLE GRAND MESA DAU E-14 UNIT B DARY GRAND JUNCTION �27 Colorado Division of Wildlife Wildlife Research Report July 1994 ~~ JOB PROGRESS REPORT State of Colorado Project No. W-153-R-7 Mammals Research Work Plan No. 3 Elk Investigations Job No. 9 Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size Period Covered: Author: July 1, 1993 - June 30, 1994 D. J. Freddy Personnel: F. Barnes, J. Broderick, G. Byrne, D. Crane, J. Ellenberger, J. Frothingham, V. Graham, J . Gray, R. Hays, c. Kolus, G. Loucks, J. Pelletier, S. Rivera, P. Will, CDOW; D. Bowden, C. Vardeman, G. White, CSU; M. Miller, C. McCarty, R. Witt, Volunteers; USFS Rifle, BLM Glenwood Springs, Cooperating. Abstract We radio-collared 73 calf elk (Cervus elaphus nelsoni) (6 mos old) and 68 adult female elk(~ 1 year old) in December 1993 to estimate survival rates during winter and used these same elk in 110 aerial sighting bias trials to develop models for estimating degree of negative sighting bias when counting elk with a helicopter on sample quadrats. Elk were captured using portable corral traps and helicopter net-gunning. Survival rates(± 95% CI) from December 1993 to June 1994 were 0 . 918 + 0.063 for calves and 0.956 + 0.049 for adult females. Suspected causes of death were primarily malnutrition and predation for calves and shooting and predation for adult females. Calves suspected of dying from malnutrition had marrow fat values< 13% at death and body weights< 102 kg at capture . Blood tests for brucellosis were negative in all 43 adult females sampled while progesterone assays indicated 74-80% of the adult females were pregnant. Observers did not count 15.4% of the elk during sighting trials resulting in a simple binomial correction factor of 0.846 ± 0.071 (± 95% CI). Univariate tests, however, indicated elk age, log(ln)initial group size, log(ln) total group size, elk behavior, vegetation type, percent occlusion cover, percent snow cover, and wind conditions affected sightability of elk (P ~ 0.05). Step-down regression analyses produced a complex 12 parameter sighting model inclusive of elk age, elk behavior, vegetation type, log total group size, and percent snow cover. Simpler models inclusive of log total group size or log total group size and percent occlusion cover may be more utilitarian and provide acceptably precise correction factors. The simple binomial correction model provided unacceptably inflated and imprecise correction factors which supported incorporating the variable total group size into sighting bias models. �29 JOB PROGRESS REPORT ESTIMATING SURVIVAL RATES OF ELK AND DEVELOPING TECHNIQUES TO ESTIMATE POPULATION SIZE David J. Freddy P.H. OBJECTIVE Estimate survival rates of adult female and calf elk and develop techniques to estimate population size. SEGMEw.l? OBJECTIVES 1. Radio-collar 75 adult female and 75 calf elk during December 1993 in Game Management Unit 42 south of Rifle, Colorado. 2. Estimate winter and annual survival rates of calf and adult female elk from known fates of radioed elk. 3. Estimate probability of sighting and counting elk during helicopter surveys using radioed elk as a known population. 4. Analyze survival and sightability data and summarize annually in Federal Aid Job Progress reports IRTRODUCTIOH Elk (Cervus elaphus nelsoni) are a high-profile and burgeoning wildlife resource throughout much of Colorado. This burgeoning resource has many benefits but frequent social, political, and economic conflicts suggest elk, to some degree, have reached a "social" carrying capacity. Many conflicts arise, in part, from an inadequate ability to predict the dynamics of elk populations. Key population parameters such as survival rates of calves and adult females and total population size are seldom measured resulting in computer models of elk population dynamics that are based on minimal data. Such models can be of little predictive value and, as such, diminish confidence in using models to guide management of elk populations. our objectives are to provide reliable estimates of survival rates for calves and adult females during winter and for adult females throughout the year for the period 1993-94 through 1997-98. Additionally, we will develop and test a system for estimating population size that will incorporate estimates of sighting bias in conjunction with a random sampling system using search quadrats as sample units. our winter study area encompasses about 839 Jan2 (324 mi2) in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado~ Elk winter range vegetation types include juniper-pinyon woodland (Juniperus ost;eosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnirolia), aspen (Populus t;remuloides), sagebrush µrt;emisia t;rident;at;a), and agricultural fields ·(Freddy 1993). �30 METHODS Marking V We placed radio collars (l72-176MHz) having mortality sensors on 73 calves (6 mos old), of which 36 were males and 37 were females, and 68 adult females(~ l year old). Of these, 54 calves and 46 adults were trapped from 2-6 December 1993 using helicopter net-gunning and 19 calves and 22 adults were trapped from 10-20 December using portable corral traps. Helicopter capture occurred at 17 remote sites located primarily on public lands while corral-trapping occurred at 3 sites primarily on private lands. Trapping effort was allocated among 8 geographic trap zones to assure that radioed elk were representative of most if not all segments of the population (Table 1). Number of elk to be captured in each zone was established prior to trapping based on distribution and relative numbers of elk observed during sex and age ratio classification flights completed annually in January from 1989 to 1993. Collars for adults were fixed in c·ircumference while those for both male and female calves were expandable to accommodate growth when animals became adults. Additionally, all radio collars had a 2 character visual identification code on the dorsal surface of the collar consisting of letters, numbers, or-symbols. Collars were white with black symbols. Calves captured by net-gunning were ferried by helicopter to processing points usually within 1.6 km of capture sites. At processing points, body weight, total body length, and hind foot length were measured and calves were then radio-collared and released. Similar measurements were also made on calves that were corral-trapped and then released at the trap site. Body measurements for calves were compared between sexes using Proc FREQ and Proc GLM (SAS 1988). Physiological Assays Serum samples were obtained from adult females captured by net-gunning for brucellosis tests (USDA Lab, Denver) and progesterone assays (Physiology Lab, Colo. St. Univ.). Fat content (percent dry matter) of femur marrow or lower jawbone marrow obtained from dead radioed elk was determined (Colo. Div. Wildl. Lab, Ft. Collins). Survival We monitored life or death .status of radioed elk during daily ground surveys and aerial surveys conducted at 2-4 week intervals from December 1993 through April 1994 and via monthly aerial surveys in May and June 1994. Survival rat~s (S) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) = S(l-S)/n (White and Garrot 1990)(Proc FREQ, SAS 1988). We chose not to use the staggered entry approach and did not use a Kaplan-Meier approach because no animals were censored (White and Garrot 1990). Life or death status of all radioed calves was known for the period 2 December through 15 June. On 15 June, calves become yearlings for purposes of calculating rates of calf survival. Life·or death status was known for 65 of 68 adult females through 15 June with all females of known status through 28 April. Sighting Bias We conducted 110 aerial sighting bias trials that targeted individual radioed elk located on search quadrats (Samuel et al. 1987). Trials were conducted on 25, 27, 28, and 31 January, l, and 14-17 February, and on 9 March. Search quadrats were approximately 2.6 km (l mi2 ) in size with boundaries based on topographic features We used a Bell B-1-Soloy helicopter, the same pilot, and observation teams composed of 2 persons selected from 3 observers and 2 navigators for all V �31 trials. The Bell-Soley offers good forward and lateral visibility. Navigators were seated in the middle with the pilot to their left and the primary observer to their right. Navigators were highly experienced at flying sample quadrats and observers had high, moderate, low experience in flying sample quadrats. However, all observers were well experienced in conducting sex and age ratio helicopter survey flights for elk. The helicopter was flown at speeds of 65-95 Janph at 25-40 m above the vegetation canopy when flying the perimeter of search quadrats and weather permitting, at slower speeds and lower heights when searching the interior of quadrats. Searching time per quadrat ranged from 10-50 minutes. Sighting bias trails were usually conducted in 2 sessions each day. Op to 8 different radioed elk were located via telemetry with a Cessna 185 during each early morning and mid-day session. Locations of elk were assigned to a previously determined search quadrat. Assignment to a quadrat was confirmed by a technician on the ground who checked Loran-c locations obtained by plane with latitude-longitude locations of quadrats plotted on USGS 7.5 minute topographic maps. The navigator was given a list of 5-8 target elk and quadrats per session but no information as to where target elk were located within quadrats. Usually within 2 hours of locating target elk with the plane, the helicopter team searched the quadrat and counted all groups of elk until either·the target radioed elk was seen or until the entire quadrat had been searched and the target elk not seen. If a target elk was missed, the helicopter team located the elk via telemetry immediately after completing their search of the quadrat to determine whether the elk was on or off the quadrat at the time they flew the quadrat. The helicopter team recorded initial group size, total group size, activity behavior, vegetation type, percent occlusion cover, and percent snow cover for the portion of each group initially detected whether or not a group contained a radioed elk (Appendix I). Snow type, light conditions, wind conditions were assessed for each quadrat. When radioed elk were observed, they were usually individually identified by the number/symbol code, and if a target elk, the search was then terminated. Several radioed elk were often seen per quadrat. After completing the search of a quadrat, observers located target elk that were missed, and, if found on the quadrat, observers recorded all sighting variables for the missed group. Usually 10-12 trials were conducted each day. Successful trials occurred when the target elk was on the assigned quadrat whether or not that elk was seen. Unsuccessful tr-ials occurred when target elk were found off the assigned quadrat immediately subsequent to the time the quadrat was flown. Elk were off quadrats primarily due to their movements that occurred between the time elk were located with the plane and the time the helicopter team flew the quadrat. We wanted to avoid any positive effects on sightability that might be gained if an observer located a target elk during 1 trial and then was assigned that same target elk during another trial. Thus, elk were targets for an individual observer only once. However, the same navigator was involved in 2 trials with each of 2 elk, but the 2 trials were generally 2-4 weeks apart and we suspect the navigator had little influence on the ability of the ·-·.observation team to detect ·the target elk. We subsequently targeted 90 different radioed elk: 70 were targeted 1 time and 20 were targeted 2 times during the 110 trials and for 106 trials,· there was a unique combination of observer and navigator attempting to detect the targeted elk. Sighting bias models were developed using logistic regression (Pree GENMOD, SAS). The dichotomous classification of groups seen or missed was the dependent variable. Initial group size, total group size, activity behavior, vegetation type, percent occlusion cover, and percent snow cover, etc. were independent variables. Significance level for independent variables was PS 0.05 for univariate tests and PS 0.10 for stepwise regression in multivariate models. Relative efficiency of models was assessed using AIC values (Akaike Information Criterion= -2(-log likelihood value)+ 2[No. model parameters)). Observer, navigator, trap method, elk sex, elk age, activity, vegetation type, �32 snow type, and wind were treated as class variables and group size, percent occlusion cover, and percent snow cover were treated as continuous variables. Variances for estimates of total elk that were derived from sighting models followed a modified version of that presented by Steinhorst and Samuel (1989)(pers. comm. D. Bowden and G. White). V Movements We located 34 radioed elk (17 adult females, 17 calves [9 males, 8 females) at least once per month since capture via telemetry using a Cessna 185. These elk were selected at random from within trap zones and equalized by age class. These elk will be monitored seasonally to document general movements and areas of use with results reported next year. • RESULTS ARD DISCUSSION Survival From 2 December 1993 through 15 June 1994, 6 calves died (4 male, 2 female) and 3 adult females died (Table 2). Overwinter survial rate(± 951 CI) for calves was 0.918 ± 0.063 and for adult females was 0.956 ± 0.049. These survival rates were associated with a winter considered to be mild in both temperature and snow depth. Suspected· causes of death were primarily malnutrition and predation _for calves and shooting and predation for adult females (Table 2). Those calves dying from malnutrition had marrow fat values< 131 at death and body weights< 102 kg at capture. The 2 smallest male calves weighed (Table 3) died of suspected· malnutrition (Table 2). Male calves had larger body weights (P = 0.03), longer hind leg lengths (P = 0.07), and higher condition indexes (P = 0.03) than female calves. Total body lengths were not different between sexes (P = 0.36)(Table 4). Blood Assays Brucellosis tests were negative for all 43 adult females sampled. Progesterone assays indicated 25 (741) of 34 adult females were pregnant (1.37-4.69 ng/ml), 2 (61) were possibly pregnant (1.02-1.04 ng/ml), and 7 (201) were not pregnant(~ 0.37 ng/ml) (Freddy 1989). Of the females judged not pregnant, 5 were judged to be 2-4 years old and 2, 5-9 years old. Sighting Bias We completed 99 successful sighting trials involving 45 adult females and 54 calves of which 26 were males and 28 were females. Elk involved in 11 unsuccessful trials we1;e .6 adult females and 5 calves. Overall, observers missed 15.41 of the targeted elk (Table S). The degree of negative sighting bias was not different among observers (P = 0.53) ranging from 12.2 to 21.91. Therefore, the simple binomial correction factor(± 951 CI) for detecting elk was 0.846 ± 0.071. Of the 16 target elk missed during successful trials (representing 16 target groups), 14 (881) were calves (SM, 9F) and 2 (121) were adult females. Frequency of missing male and female calves was not different between sexes (P = 0.28). Calves missed were in groups of~ 4 elk, except for 1 group of 30 elk. Capturing calves with a helicopter or corral trap had no effect on their sightability (P = 0.66). Univariate tests indicated elk age (calf or adult), initial group size, log(ln) initial group size, total group size, log(ln) total group size, activity behavior, vegetation type, percent occlusion cover, percent snow cover, and wind conditions affected the probability of sighting elk (P ~ a.as, Tables 6, 7). The ln total group size was the most efficient of these single variable models (AIC = 74.678; intercept= 0.1215, group size coefficient= V �33 1.3073). Log transformations of either initial group size or total group size provided more efficient models than untransformed values (Table 7). The initial multivariate model for stepwise regression incorporated elk age, ln total group size, activity behavior, vegetation type, percent occlusion cover, percent snow cover, and wind conditions. Vegetation type, percent occlusion cover, and wind were not significant (Model A, Table 8). Proceeding in a step-down process, wind was dropped as the least significant variable from model A, then percent occlusion cover from model B, to derive model C in which elk age, activity behavior, vegetation type, ln total group size, and percent snow cover were all significant. However, model C necessitated estimates of coefficients for 12 parameters which makes this model unwieldy and likely subject to highly imprecise estimates of corrected numbers of elk although this model had a relatively low AIC value (Table 8). other models having fewer parameters were assessed. In model D having 3 primary variables, elk age was not significant, but ln total group size, percent occlusion cover, and the interaction of elk age and ln total group size were significant (Table 8). This significant interaction term reflected that although calves were the predominate class of elk missed, they were almost always in small groups when found after completely searching quadrats. We are not sure whether calves were missed because they were in separate small groups (assumed, true sighting bias) or because they represented a fraction of a larger group that was detected but the calves were not seen (count·ing bias). Missed groups involving targeted calves were seldom the only group of elk on the quadrat. Model E includes _ln total group size and percent occlusion cover which mimics variables used in sighting-models developed in Idaho for elk (Samuel et al. 1987). These models were surprisingly similar considering that the Idaho model was developed in tall conifer habitats and based only on sightability of adult elk (Samuel et al. 1987) (Table 9). Model F includes only ln total group size and had the highest AIC value but probability of detecting a·group increased rapidly to~ 0.90 for groups~ 6 elk (Table 8, Fig. 1). The degree to which selected models corrected number of elk counted and the variances of corrected counts were assessed. The simple binomial correction, model G, inflated counts the most (18%) and had nearly the highest variance (Table 10). Inflated counts resulted from applying the 0.846 correction factor to large groups of elk which had a sighting probability of nearly 1.0 (Fig. 1) and needed no adjustment in numbers. Models E and F having ln total group size or ln total group size and percent occlusion cover had similarly low variances and low corrections for counts of 3-4% (Table 10). These 2 models highlight the need to include group size as an adjustment variable for correcting counts. Adding percent snow cover as an additional variable, model H, markedly increased the variance and provided minimal additional correction to counts (Table 10). We caution, however, that small variances and potentially precise estimates about corrected counts per quadrat based on adjustments for group size may not result in highly precise estimates of population size because of variance associated with total counts of elk among sample quadrats when a sampling system is employed (otten et al. 1993). CORCLUSIORS We obtained acceptably precise estimates of calf and adult survival rates during winter and recommend continuing our current sampling effort of monitoring 75 radioed calves and 75 radioed adult females in 1994-95. Efforts to measure and develop criteria to adjust for negative bias in counts of elk were promising and we.recommend conducting an additional 100 sighting bias trials in 1994-95 to refine a sighting bias model. We are particularly interested in evaluating effects of elk age (calves) on sighting bias and assessing potential heterogeneity of sighting probabilities for individual elk among years by resighting elk in 1994-95 that were involved in trials in 199394. �34 LITERATURB CITED Freddy, D. J. 1989. Effect of elk harvest systems on elk breeding biology. Colo. Div. Wildl. Game Res. Rep. July(l): 35-60. Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 83-117. Samuel, M. D., E. O. Garton, M. W. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Wildl. Manage. 51:622-630. J. otten, M. R., J.B. Haufler, s. R. Winterstein, and L. c. Bender. 1993. An aerial censusing procedure for elk in Michigan. Wildl. Soc. Bull. 21: 73-80. SAS Institute Inc. 1988. SAS/STAT User's Guide, 6.03. SAS Institute, Inc., . Cary, NC. 1028pp. Steinhorst, R. K., and M. D. Samuel. 1989. Sightability adjustment methods for aerial surveys of wildlife populations. Biometrics 45:415-425. White, G. c., and R. A. Garrot. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego. 383pp. V V �35 Table 1. Capture objectives and numbers of elk radioed in 8 trapzones, Game Management Unit 42, December, 1993. \,.._,I Trap Zone A B C D E F G H Blls Col11i;:ed• I.2tBJ. He1f.g ~2D:11 Capture O)zjectj.ve Bame Garfield Gibson Uncle Bob West Divide Hightower Middle Kamm West Kamm Dry Hollow 8 Adult Eel!H!lgs 4 12 12 10 10 8 8 10 10 25 29 21 17 0 19 29 21 17 0 0 8 6 6 0 44 35 0 35 7 9 1 19 150 141 100 41 36 37 68 20 24 26 All Calve! Hales [emale1 3 1 5 8 10 7 6 5 4 3 0 0 3 2 0 6 0 0 0 0 • Helio - Helic~pter net-gunning, Corral - corral-trap. Table 2. Causes of mortality for radioed elk in Game Management Unit 42, l December-ls June 1993-94. Radiocollar ~ l!:!!S!H!DSX Sex tgg• 172.090/93 172.542/93 172.690/93 172.899/93 173.000/93 173.262/93 173.289/93 173.461/93 173.469/93 F p 11 yrs 6 yrs 8 yrs 10 mos 11 mos 10 moo 10 mos 1 F F F M M M M 9'mos- 11 mos Date Dead Batimated cmase of Deatb 1/16/94 2/01/94 1/24/94 3/18/94 4/25/94 3/18/94 3/22/94 2/07/94 4/25/94 Wounding LOBS cougar kill Gunshot, poached Cougar kill Malnutrition Possible predation Undetermined Malnutrition Malnutrition Body wt:. Usg!b Harrow Fat E1;ce11Ji Da Hatte, not available 18.0° not available 2e.sd 12.6c 28.9d not available 2.1° 2. ,c 86 102 ·108 111 82 77 Approxlmata age at death. b Whole body weight at capture in December 1993. ° Fat content of either the right-or left femur bone marrow. d Fat content: of lower jaw bona marrow. Table 3. Frequency distribution of whole body weights for male and female elk ·calves trapped in Game Management Unit 42, December, 1993. Percentage per weight class shown in parentheses. Bodv Wgigb~ glll! (kg! 100-109 110-119 120-129 130-139 140-149 Total 3 (8.6) 6 (17.1) 12 (34.3) 10 (28.1) 1 (2.9) 1 (2.9) 35 (100) 8 (22.9) 12 (34.3) 4 (11.4) 6 (17.1) 0 (0.0) 0 (O.O) 35 (100) Sax 70-79 80-89 90-99 Mala 1 (2.9) 1 (2.9) Pamala 1 (2.9) 4 ( 11. 4) �36 Table 4. Body measurements for elk calves trapped in Game Management Unit 42, December, 1993. Mean Meaeurement; Body Weight (kg) 112. 7 191.2 Body Length (cm) Bindfoot Length (cm) 56.3 0.59 Condition Index (Wt./Body Length) MaJ.e CaJ.veg Min Max o Mean 141.0 35 210.0 36 61.0 36 0.67 35 SD 13.7 10.2 2.2 77.0 164.0 52.0 0.43 o.os Eemale ~iJ.ves SD Mi.n HM 103.8 12.2 188.9 54.8 9.8 76.0 167.0 51.0 123.0 35 207.0 35 0~55 2.1 o.os 0.46 59.0 0.64 u 34 34 Table S. Summary of elk sighting bias trials conducted in Game Management Unit 42, January-March 1994. Percentages shown in parentheses. 0bB8!::£8E Trials 6tt:eme51 Trials• Hot Usem2J.!} Trials Uae!lzie Trial Blk Detectgs! Trial Blk Hot ggtected JB 29 3 4 DK 36 45 26(90) 32(89) 22(84.6) JE 4 41(91) 36(87.8) 4(15.4) 7(21.9) 5(12.2) Totals 110 11 99(90) 83(84.6) 16(15.4) 25(78.1) V Table 6. Blk sightability survey.results by major independent variables from Game Management Unit 42, January-March, 1994. !IEialalSI IISh SIEmll!I ,,. 6 7 1 1 0 0 0 1 0 0.57 0.59 0.92 0.86 1.00 1.00 1.00 0.93 1.00 Iii.lad Ian 4 5 6 7-15 ~ 16-30 31+ v-... 'fype Cleariq/Ag Ripuian &&;Bruh O&Jcbnab PiDyaa-Junipm: 6 Aap8D 3 2 Tall CODJ.far ocal. COVU(~) 0-19 20-39 40-59 60-19 80-100 I 8 10 11 6 5 5 17 14 7 Baddad Standing Hoving Navigator GB VG 9 1 3 40 26 3 1 DH 1.00 1.00 1.00 O.89 O.81 Bllc,,Aga 0.33 calf sax o.so i'amala 22 25 23 12 1 O.96 0.89 O.79 o.ao 0.25 !!Ei.llalSI 11,111£1 lama ~ snow cover (I) 9 2 53 2 28 5 11 5 45 38 0.29 0.86 0.93 a.so 0.88 0-19 20-49 50-99 100 4 7 5 5 9 Trap (All elk) COffal Trap 4 BelJ.c:optar 12 Trap (calvaa) • corral Trap 3 Balicoptar 11 y-,£.Iblilty (group• 11aen / gmup■ seen plua groups iiilaaacl). 22 0.85 25 36 O.78 43 40 a.ea 0.96 0.74 21 19 O.81 0.68 27 56 O.87 O.82 11 0.79 0.73 29 3 2 0.40 3 4 29 48 0.97 0.84 1 9 0.57 Snow Type l're■h Old . Adult hmala 2 calf (H + I') 14 Hal.a 1 3 6 3 3 ~ Obaerver JB JB 0 0 0 5 11521 SIES!HDII lli.lllml IUD Behavior GJ:Oup S1:a 1 2 3 !1d1blo Wind Light ~ate St=ng 4 12 21 16 0 0 67 14 62 2 0.84 0.84 0.81 1.00 1.00 Ll.gbt Bright Dull Ba:y 12 52 0 11 4 20 0.81 1.00 0.83 V �37 Table 7. summary of variables ·tested in univariate tests using logistic regression for elk sightability trials, Game Management Unit 42, January-March, 1994. Likelihood Ratio Prob. >Chi-Square Variable Date of Sight Trial Sigh't; Trial Navigator Observer Individual Elk Sex of Elk Age of Elk Capture Type Initial Group Size Log(ln) Initial Group Size Total Group Size Log(ln) Total Group Size Elk Activity Vegetation Type Oc~lusion Cover I Snow Cover I Temperature Wind Conditions Light Conditions snow Type 8 AJ:C 0.7152 0.5936 0.2763 0.5399 0.5650 0.6257 0.0022 0.5453 0.0166 0.0044 0.0027 0.0001 . 0.0014 0.0405 0.0010 0.0275 0.3127 0.0449 0.1233 0.9797 Sign./ Nonsign. NSign NSign NSign NSign NSign • NSign Aic4 91.450 91.299 90.398 90.351 12.318 91.345 82.170 93.218 SIGN NSign SIGN SIGN SIGN SIGN SIGN SIGN SIGN SIGN 85.844 83.468 82.589 74.678 82.435 90.417 80.703 86.725 91.023 89.376 91.397 93.583 NSign SIGN NSign NSign = Akalke's Information Criterion Table 8. Multivariate analyses of factors affecting sighting probability based on stepwise logistic regression for elk in Game Management Unit 42, JanuaryHarch, 1994. Model A No. Parameters + Intercept 14 B 13 C D 12 6 E p 2 3 1 Ageaelk age class, Aic6 Parameters Used• Age , Act , Vega, Wind, LnGroup, Covert, sncw1• Age•, Act•, Vega•, LnGroup•, Covert, Snow%• Age•, Act•, Vega•, LnGroup•, Snow,• Age, LnGroup•, Covert• LnGroup•, Cover,• LnGroup• • • • Value 58.32 58.96 59.16 62.61 68.89 74.68 Act::aelk activity class, Vege~egetatlon type class, wind=wind class, LnGroup=log total group size, COvert=occlusion cover percent, Snorimsnow cover percent, * Denotes variable as significant . in model, Pm S 0.10). b Lower AIC value denotes better fitting model. �38 Table 9. Comparison of logistic regression models incorporating log(ln) group · size and percent occlusion cover or percent vegetation cover for sightability trials involving elk in Colorado and Idaho. Variable Coeffiecent Constant-Colorado 1.98 constant-Idaho 1.22 ln Group Size-Colorado 1.23 ln Group Size-Idaho 1.55 I 0ccl. Cover-Coloraod -0.04 I Vege. Cover-Idaho -o.os 1 SE 0.86 o. 674 0.40 0.37 4 0.02 0.01• Calculated from Table 2 in Samuel et al. 1987. Table 10. Estimated variance components and estimated corrected numbers of elk for selected sightability models for elk in Game Management Unit 42, 1994. Corrected Percent variance· 0 Totala gqg;aqt;ion Estimate0 COvarianca0 Model Elk 49,264 1,666 610 2,534 118 a-Binomial1 46,121 1,454 543 103 284 12 246 l'-LnGroup 1,462 104 873 264 111 498 B-LnGroup+ COvarl 284,549 1,489 -805,323 806,283 283,588 106 B-LnGroup+ Covarl+ Snpwt · • Variance from binomial sighting probability of groups. b Variance from predicted sighting probability_. 0 Variance frcm covariance of predicted sighting probability;; d Variance of estimate of total elk. • f Binomial model uses simple sighting bias correction of 0.846 applied to all observed groups of elk. 0 Total elk observed in groups u~ed to develop models was 1,405 elk in 99 groups. V V �39 z 1.0 o·o.s i== U 0.8 w ti 0.1 C 0.6 MEAN LL O 0.5 95 % Cl ~ 0.4 :l 0.3 m <C 0.2 m 0 0.1 £C Q. 0 1 2 3 4 5 6 7 7 20 60 150 400 1100 LOG (In) TOTAL GROUP SIZE 3 TOTAL GROUP SIZE RG. 1. Probability of detecting elk by group size, +/- 95% Cl, Game Management Unit 42, January - March, 1994. Group sizes observed during sighting ~ias trials ranged from 1 - 400. �40 15 Appendix I. Procedures for flying quadrats and definitions of variables assigned to each group of elk observed on guadrats. A. PROCEDURES FOR FLYING QUADRATS: 1. OBTAIN PROPER MAPS, ARRANGE IN ORDER OF NEED, DECIDE ON GENERAL ROUTE TO QUADRAT, HIGHLIGHT QUADRAT BORDERS lJITH FELT MARKER, AND DETERMINE LIKELY STARTING POINT. MAKE SURE NAVIGATOR HAS LISTING OF FREQUENCIES AND NECKBANDS TO DETECT (MINIMIZE ANY TALK ABOUT TARGET ANIMALS) AND THAT TELONICS TR-2 RECEIVER IS LOADED AND READY TO GO. CHECK TELEMETRY SYSTEM ON HELICOPTER WITH • DUMMY COLLAR. 2. FLY PERIMETER OF QUADRAT FIRST IN A CLOCKYISE MANNER SO THE INSIDE OF THE QUADRAT IS TO THE RIGHT OF THE PRIMARY OBSERVER. 3. DETERMINE STATUS OF GROUPS OF ELK ON PERIMETER. A. ELK MOVING OFF THE QUADRAT WHEN DETECTED ARE CONSIDERED ON THE QUADRAT. B. ELK MOVING ONTO THE QUADRAT WHEN DETECTED ARE CONSIDERED OFF THE QUADRAT. C. IF A GROUP IS STANDING ON THE PERIMETER, COUNT THOSE ELK INSIDE THE QUADRAT. D. RESIST THE TEMPTATION TO LEAVE THE PERIMETER TO COUNT A GROUP ON THE INSIDE OF THE QUADRAT. USE YOUR BEST JUDGEMENT AT THE TIME OF DETECTION. E. IF A MARKED ELK IS DETECTED NEAR THE BORDER BE SURE TO NOTE ALL IMPORTANT DATA VARIABLES AS THIS ELK COULD BE THE TARGET ELK. 4. FLY INTERIOR OF QUADRAT. A. FLY THE INTERIOR OF THE QUADRAT SYSTEMATICALLY IN STRIPS OR STRIP.CONTOURS. USE PROMINENT TERRAIN FEATURES TO DIVIDE THE QUADRAT INTO SMALLER COUNTING BLOCKS. IF DECIDE TO FLY STRIP-CONTOURS, WORKING FROM THE HIGHEST TO LOWEST ELEVATION USUALLY . WORKS BEST. B. BE PATIENT AND STRIVE FOR 100% COVERAGE. 5. WHEN MULTIPLE GROUPS OF ELK ARE DETECTED ·SIMULTANEOUSLY, FOLLOW THESES GUIDELINES. A. PRIMARY OBSERVER SHOULD BEGIN OBTAINING DATA ON GROUP NEAREST THE HELICOPTER AND USE HELICOPTER TO KEEP GROUPS SEPARATED. B. NAVIGATOR SHOULD FOCUS MOMENTARILY ON SECOND GROUP OBSERVED AND NOTE LOCATION, ACTIVITY AND NUMBER OF ANIMALS FIRST SEEN. C. AFTER COMPLETING DATA COLLECTION ON FIRST GROUP, PROCEED TO LOCATION OF SECOND GROUP, DETERMINE VEGETATION TYPE, OCCLUSION%, AND SNOW COVER% AT SITE OF DETECTION, THEN FIND AND COUNT SECOND GROUP. 6. RULES FOR MARKED ANIMALS A. FOR EVERY MARKED ELK SEEN (UNTIL THE TARGET ELK IS DETECTED) ·oBTAIN A POSITIVE IDENTIFICATION VIA THE NECKBAND NUMBER OR WITH TELEMETRY TO DETERMINE THAT THE MARKED ELK IS OR IS NOT THE TARGET ANIMAL. B. IF MARKED ELK ARE SEEN AFTER DETECTING THE TARGET ELK, OBTAIN AN IDENTIFICATION FROM THE.NECKBAND WITHOUT UNDULY HARASSING THE ELK OR USING TOO MUCH TIME. 7. RULES FOR DETECTING THE TARGET MARKED ELK A. YOU WILL ESTABLISH A FLIGHT PATTERN TO COVER THE ENTIRE QUADRAT. WHEN YOU HAVE COMPLETED THIS PATTERN, YOU ARE DONE FLYING THE QUADRAT. IF YOU HAVE NOT DETECTED THE TARGET ANIMAL DURING THIS PATTERN, DO NOT V �41 16 RE-SEARCH THE QUADRAT AS THIS WOULD BE DISHONEST; IE, DO NOT SEARCH FOREVER TO FIND THE TARGET ELK, IT MAY NOT BE THERE OR THERE MAY NOT BE ONE TO FIND! B. IF YOU DO NOT FIND THE TARGET ELK AFTER COMPLETING YOUR FLIGHT PATTERN, TURN ON THE RECEIVER AND START SEARCHING THE QUADRAT FOR A SIGNAL. C. IF THE TARGET ELK IS ON THE QUADRAT, COUNT THE GROUP AS THOUGH IT WAS ANY OTHER GROUP OF ELK, AND BE SURE TO OBTAIN ALL VARIABLES ASSOCIATED WITH THAT GROUP. THIS IS THE MOST IMPORTANT DATA WE CAN COLLECT IN REGARDS TO SIGHTING BIAS ADJUSTMENT FACTORS AS IT REPRESENTS AN ELK YOU DID NOT SEE. D. IF THE TARGET ELK IS DEFINITELY OFF THE QUADRAT SPEND SOME TIME LOCATING IT BECAUSE IT COULD BE NEAR THE BOUNDARY AND MAY HAVE RUN OFF THE QUADRAT (BACKTRACK TO DETERMINE IF LEFT QUADRAT). SPEND ENOUGH TIME SEARCHING TO DETERMINE TO YOUR SATISFACTION THAT THE ELK WAS LIKELY OFF THE OUADRAT DURING YOUR TIME ON THE OUADRAT. E. NOTE NUMBER OF MARKED ANIMALS SEEN IN EACH GROUP, AND ID'S OF THOSE ELK IF OBTAINED. LOCATIONS OF ELK SEEN ON A QUADRAT WILL BE ASSUMED TO BE THE MIDDLE OF THE QUADRAT FOR PURPOSES ~F DISTRIBUTION AND MOVEMENT INFORMATION UNLESS YOU OBTAIN A LORAN-C LOCATION FROM THE HELICOPTER. B. DEFINITIONS THAT APPLY TO EACH GROUP OF ELK DETECTED ON A QUADRAT. OUR DEFINITIONS ARE BASED ON THE HYPOTHESIS THAT DETECTING ELK IS DEPENDENT ON INITIALLY DETECTING SOME FRACTION OF EACH GROUP. 1. DETECTION GROUP SIZE: NUMBER OF ELK INITIALLY DETECTED WEN AN OBSERVER SEES A GROUP. THIS NUMBER WILL REPRESENT SOME PORTION OF THE TOTAL GROUP SIZE. 2. ANIMAL ACTIVITY: THE ACTIVITY OF THE ELK INITIALLY DETECTED OR THE ACTIVITY OF THE MAJORITY OF THE ELK INITIALLY DETECTED. ACTIVITY CLASSES WILL •• BE BEDDED-B, STANDING-S, MOVING-M. 3. VEGETATION TYPE: THE PREDOMINATE TYPE OF VEGETATION FOR 30 METERS AROUND THE INITIAL ELK SEEN. VEGETATION TYPES ARE: OK--OAKBRUSH-TALL MOUNTAIN SHRUB SG--SAGEBRUSH-(INCLUDING GREASEWOOD & RABBITBRUSH) AS--ASPEN PJ--PINYON-JUNIPER TC--TALL CONIFER (DOUGLAS FIR, ENGELMANN SPRUCE, LODGEPOLE PINE) • RP--RIPARIAN (COTTONWOOD/WILLOW BOTTOMS) CA--CLEARINGS/AGRICULTURAL FIELDS (CLEARINGS CAN BE NATURAL MEADOWS, CLEAR-CUTS COVERED WITH SNOW, DRILL-PADS, OR ANY SIZEABLE OPENING THAT APPEARS TO BE A CLEARING DUE TO SHORT VEGETATION AND/OR SNOW COVER) 4. % OCCLUSION COVER: AN ESTIMATE OF THE PERCENTAGE OF THE OBSBRVER'S VIEW BLOCKED BY VEGETATION INTERFERING WITH THE OBSERVERS ABILITY TO SEE THE INITIAL ELK DETECTED IN A SPACE OF 30 METERS AROUND THE ELK. OBSERVERS WILL ESTIMATE IN INCREMENTS OF 10%, IE; 0, 10, 20, 30, ... , 100. DATA WILL BE POOLED IATER. VEGETATION INCLUDES STEMS AND TRUNKS OF DECIDUOUS SHRUBS AND TREES, TRUNKS AND LEAVES OF EVERGREEN CONIFERS, LEAVES AND STEMS OF ANY OTHER EVERGREEN SPECIES. GRASS AND SHORT SAGEBRUSH SHOULD HAVE 0% OCCLUSION COVER �42 17 EXCEPT POSSIBLY WHEN ELK ARE BEDDED·;. 5. %SNOW COVER: THE PERCENTAGE OF BARE GROUND COVERED BY SNOW FOR 30 M AROUND _THE INITIAL ELK DETECTED. OBSERVERS WILL ESTIMATE IN INCREMENTS OF 10%, IE; 0, 10, 20, 30, .... 100. DATA WILL BE POOLED LATER. 6. TOTAL ELK IN GROUP: THE TOTAL NUMBER OF ELK COUNTED IN A GROUP. A GROUP IS DEFINED AS A CLUSTER OF ELK ACTING INDEPENDENTLY EITHER IN BEHAVIOR OR SPACE FROM ANOTHER CLUSTER OF ELK. GUIDELINES FOR DEFINING A GROUP ARE: CLUSTERS OF ELK SEPARATED BY >30 METERS OR CLUSTERS SHOWING DIFFERENT PATrERNS OF BEHAVIOR. DEFINING A GROUP CAN BE SUBJECTIVE IF ELK ARE AT HIGH DENSITIES ON THE QUADRAT. THESE DEFINITIONS APPLY TO AMBIENT CONDITIONS EXISTING ON EACH QUADRAT·AT THE TIME OF FLYING 1. WIND: WIND WAS : LIGHT-L, MODERATE-M, OR STRONG-S IN RELATION TO THE RELATIVE EFFECT OF THE WIND ON. THE ABILITY TO FLY THE QUADRAT IN A SLOW, LOW AND DELIBERATE MANNER. 2. LIGHT CONDITIONS: LIGHT CONDITIONS WERE EITHER: BRIGHT SUNSHINE WITH HIGH CONTRAST-B, HAZY SUNSHINE WITH HIGH THIN CLOUDS-H, OR DULL SUNSHINE DUE TO OVERCAST OF CLOUDS-D. 3. SNOW TYPE: SNOW TYPE IS EITHER FR.ESH SNOW THAT HAS FALLEN WITHIN THE PAST 48 HRS-F, OR OLD SNOW THAT IS OLDER THAN 48 HRS-0. ·sNOW CONDITIONS WILL LIKELY BE THE SAME FOR ALL GROUPS OF ELK DETECTED ON A QUADRAT. ~ 3. TEMPERATURE: TEMPERATURE (F) DURING THE MORNING AND AFTERNOON FLIGHTS AS MEASURED AT THE BASE OF OPERATIONS FOR EACH FLIGHT \ J ""--" �63 Colorado Division of Wildlife Wildlife Research Report July 1995 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-8 Mammals Research Work Plan No. 3 Elk Investigations Job No. 9 Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size Period Covered: Author: July 1, 1994 - June 30, 1995 D. J. Freddy Personnel: F. Barnes, J. Broderick, G. Byrne, A. Coriell, D. Crane, J. Ellenberger, J . Frothingham, v. Graham, J. Gray, R. Hays, G. Loucks, P. Will, R. Witt CDOW; D. Bowden, C. Vardeman, G. White, CSU; K. Crane, C. McCarty, D. Ouren, volunteers; USFS Rifle, BLM Glenwood Springs, cooperating. ABSTRACT We radio-collared 69 calf elk (Cervus elaphus nelsoni) (6 months old) and an additional 14 adult female elk(~ 1 year old) in December 1994 to estimate survival rates during winter and used these same elk in 103 aerial sighting bias trials to develop models for estimating degree of negative sighting bias when counting elk with a helicopter on sample quadrats. Elk were captured using portable corral traps and helicopter net-gunning . Survival rates(± 95% CI) from December 1994 to June 1995 were 0 . 90 ± 0.07 for calves and 0 . 96 ± 0.04 for adult females. Suspected causes of death were malnutrition and predation for calves and shooting and predation for adult females. Calves suspected of dying from malnutrition had marrow fat values <13% at death and body weights <102 kg at capture while calves dying from predation had marrow fat values of 3.7-35.6% and body weights of 86-140kg. For adults ~1 year-old, hunting accounted for 88% of 24 deaths. Average sighting probability of elk groups was 82.3% which equates to a 17.7% negative sighting bias. There were no differences in sighting bias between years (P > 0.70) but there were differences in sighting bias among observers (P = 0 . 06) which ranged from 9 . 3% to 22.4%. Univariate tests indicated elk age (calf or adult), elk sex (calves only), initial group size, log(ln) initial group size, total group size, log(ln) total group size, activity behavior, vegetation type, percent vegetation occlusion cover, observer, navigator, pilot, and trapping method affected the probability of sighting elk (P ~ 06). Multivariate analyses incorporated elk age, ln total group size, activity behavior, vegetation type, percent vegetation occlusion cover, percent snow cover, navigator, observer, and year. The best sightability model out of 2,048 possible models was a complex 12 parameter model involving nearly all major variables. We are currently assessing the effects on sighting probability of using less complex models. �65 JOB PROGRESS REPORT BSTIMM?IHG SURVIVAL RADS OP BLK ARD DBVBLOPIHG BCIIHIQUBS m BSTIMAD POP~IOH SIZB David J. Freddy P. H. OBJECTIVE Estimate survival rates of adult female and calf elk and develop techniques to estimate population size. SEGMEtr.r OBJECTIVES 1. Radio-collar 75 calf and 15 adult female elk during December 1994 in Game Management Unit 42 south of Rifle, Colorado. 2. Estimate winter and annual survival rates of calf and adult female elk from known fates of radioed elk. 3. Estimate probability of sighting and counting elk during helicopter surveys using radioed elk as a known population. 4. Estimate density of elk in a portion of GMU-42 using a quadrat sampling system. 5. Analyze survival and sightability data and summarize annually in Federal Aid Job Progress reports INTRODUCTION our objectives are to provide reliable estimates of survival rates for calves and adult females during winter and for adult females throughout the year for the period 1993-94 through 1997-98. Additionally, we will develop and test a system for estimating population size that will incorporate estimates of sighting bias in conjunction with a random sampling system using search quadrats as sample units. our winter study area encompasses about 839 Jan2 (324 mi1 ) in the eastern half of Game Management Unit 42 south and east of Rifle, COlorado. Elk winter range vegetation types include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnirolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields (Freddy 1993, 1994). METHODS Marking We placed radio collars (172-176MHz) having mortality sensors on 69 calves (6 months old), of which 33 were males and 36 were females, and 14 adult females (~ 1 year old). Of these, 65 calves and 2 adults were trapped from 7-11 December 1994 using helicopter net-gunning and 4 calves and 6 adult females were trapped from 13-21 December using portable corral traps. Six adult females were captured in corral traps 2 March 1995 to elucidate movements of elk associated with a specific area of private land. Helicopter capture occurred at 11 remote sites located primarily on public lands while corraltrapping occurred at 3 sites, 2 on private and 1 on public lands. Trapping effort was allocated among 8 geographic trap zones to assure that radioed elk were representative of most if not all segments of the population (Table 1). Radio collars were of the same type used in 1993 (Freddy 1994). �66 Calves captured by net-gunning were ferried by helicopter to processing points usually within 1.6 Jan of capture sites. At processing points, body weight, total body length, hind foot length, and rectal body temperature (F) were measured and calves were then radio-collared and released. Similar measurements were also made on calves that were corral-trapped and then released at the trap site. Body measurements for calves were compared between sexes using Proc FREQ, GLM, and REG (SAS 1988). V V survival We monitored life or death status of radioed elk during daily ground surveys and aerial surveys conducted at 2-4 week intervals from December 1994 through April 1995 and via monthly aerial surveys from May to November 1994 and May to June 1995. Survival rates (S) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) = S(l-S)/n (White and Garrott 1990)(Proc FREQ, SAS 1988). We chose not to use the staggered entry approach and did not use a Kaplan-Meier approach because few animals were censored (White and Garrott 1990). Life or death status of all calves radioed in December 1994 (68 with functional collars) was known for the period 7 December 1994 through 15 June 1995 (1 male calf collar, 173.949/94, failed 2 weeks post-capture and although the calf was seen alive through 30 January 1995 it was excluded from estimates of survival rates). On 15 June, calves become yearlings for purposes of calculating rates of calf survival. Life or death status for adult females, yearling females, and yearling males collared in December 1993 or 1994 was known for 117 of 118 animals through 15 June 1995. All 6 adult females collared 2 March 1995 were alive as of 15 June 1995 but were not used in calculations of survival for time periods prior to 14 June 1995. Fat content (percent dry matter) of femur marrow and estimates of age based on dental cementum were obtained for dead radioed elk (Colo. Div. Wildl. Lab, Ft. Collins). Sighting Bias V V Procedures for conducting aerial sighting trials were identical in 1994 and 1995 (Freddy 1994). In 1995, we conducted 103 sighting bias trials that targeted radiocollared elk on 23, 24, 26, 28, and 30 January and 6-8 and 21 February. We again used a Bell-Soley helicopter and the same observers and navigators as in 1994. The pilot which flew all trials in 1994 flew 77 (75%) of the trials in 1995 with 2 additional pilots flying the remaining 26 trials. Observers indicated that all pilots provided comparable and acceptable service. Sighting bias models were developed using logistic regression (Proc GENMOD, SAS). The dichotomous classification of groups seen or missed was the dependent variable. Initial group size (ln), total group size (ln), activity behavior, vegetation type, percent occlusion cover, percent snow cover, snow type, year, observer, navigator, trap method, temperature, wind, lighting conditions, pilot, time interval, and time of day were independent variables. Observer, navigator, pilot, trap method, elk sex, elk age, activity, vegetation type, snow type, time interval, time of day, light conditions, and wind were treated as class variables and group size, percent occlusion cover, and percent snow cover were treated as continuous variables. Significance level for independent variables was P ~ 0.06 for univariate tests. Relative efficiency of models using all possible combinations of significant variables was assessed using AIC values (Akaike Information criterion= -2(-log likelihood value)+ 2[No. model parameters)). Population Estimates Elk population size in GMU 42 from East Alkali Creek to Beaver Creek was estimated during January and February 1995. Three independent estimates of size or density were obtained. On 19 January, a nonrandom elk sex/age V V �67 classification flight using a helicopter was flown during which numbers of marked (radiocollared) and unmarked elk were counted. From 22-24 February, 40 randomly selected quadrats approximately 1 mi2 (2.59 km2) in size were flown using a helicopter and during these flights numbers of marked and unmarked elk were counted. For these 2 flights, we used a simple Lincoln-Peterson estimator based on ratios of marked and unmarked elk (White and Garrott 1990) to estimate total numbers of elk. The third estimate of population size resulted from projecting the average number of elk counted per sample quadrat to the entire segment of winter range sampled by the quadrat system. The number of elk counted by direct observation at the time of the flights that were on private land areas not surveyed by the 3 flights were added to each of the 3 estimates of population size to arrive at an estimate of total elk in GMU 42 east of Beaver Creek. At this time, no adjustments have been make for sighting bias for counts of elk on quadrats. Movements We continued to locate 37 radioed elk at least once per month since capture to document seasonal movements via telemetry using a Cessna 185. These elk were selected at random from within trap zones and equalized by age class. As of 14 June 1995 these elk were classified as 15 adult females, 7 yearling females, 4 female calves, 7 yearling males, and 4 male calves. During 199394, 6 of 34 elk monitored for locations died. These 6 were replaced at random primarily with 6 month-old calves captured in December 1994 in the same trap zone(s) as those elk that died. During June 1995, we selected an additional 28 adult females at random to document locations during the calving period. As needed, we located other elk to document unusual movements. RESULTS AND DISCUSSION Survival ~ Between 1 December 1993 and 14 June 1995, 37 of 190 radiocollared elk died (Appendix 1). Of these 37, hunting was apparently involved in 571 of the deaths. For adults ~1 year-old, hunting accounted for as, of 24 deaths. There were 2 periods of mortality during the year. Calves died from February to May while adults died during fall and early winter when hunting seasons occurred (Fig. 1). Survival rates(± 951 CI) for calves during winter, 1 December - 14 June, were 0.92 ± 0.06 in 1993-94 and 0.90 ± 0.07 in 1994-95 (Table 3). Sex of dead calves was 4 male and 2 female in 1993-94 and 4 females and 3 males in 1994-95 (Table 2). These survival rates were associated with winters considered mild in temperature and having low or moderate snow depths. In 1994-95, considerable snow fell during March and April but usually melted rapidly at lower elevations. ~ Suspected causes of death for calves during winter were, mountain lion predation (311), malnutrition (231), and unknown (461) (Table 4). For the unknown category, bear predation was suspected once (3/1/95) as was lion predation (3/18/94) (Table 2). Those calves dying from malnutrition had marrow fat values <131 at death and body weights <102 kg at capture while calves likely dying from predation had marrow fat values 3.7-35.61 and body weights 86-140 kg (Table 2). There were no calf mortalities during capture and no evidence that capture procedures directly induced mortality in either year. In 1993-94 the first mortality involved an 82 kg female suspected of dying from malnutrition at 59 days post-capture while in 1994-95 the first mortality was an 86 kg female suspected of dying from mountain lion predation at 72 days post-capture. At capture, this last female had an abnormally articulating front shoulder which may have been injured during or prior to capture but the injury appeared to minimally affect her mobility upon release at capture. �68 Survival rates(± 951 CI) for adult females during winter, 1 December - 14 June, were 0.96 ± 0.05.in 1993-94 and 0.96 ± 0.04 in 1994-95 (Table 3). Of 7 winter deaths during both years, 5 (711) were due to legal (1) and illegal (l) hunting or wounding loss (3) during late rifle seasons (Table 4). Natural deaths (2) were attributed to mountain lion predation and unknown but possible lion predation. Of the 3 elk lost to wounding, 2 were suspicious kills. Both of these elk died from 1 rifle shot to the upper neck or head in relatively plain sight near or on an agricultural field where retrieval of the carcass was not difficult. These animals may have been accidentally shot, maliciously shot, or abandoned because of the radiocollar. Survival rates during winter 1994-95 were 1.00 for juvenile males and females age 18-23 months and radiocollared as calves (Table 3). V u Annual survival rate for adult females, 1 December 1993 - 30 November 1994, was 0.77 ± 0.10 (Table 3). Of the 15 deaths involving adult females marked in December 1993, 13 (87%) were associated with hunting. The 2 natural deaths were due to lion predation during winter and an unusual breech birth that occurred about 1 October 1994. Hunting deaths were attributed to legal hunting (6, fall seasons), illegal hunting (1, late season), wounding loss (5, 4 fall seasons, 1 late season), and presumed hunting (1, fall seasons). We examined all 5 carcasses attributed to wounding loss. Based on locations and physical position of the carcasses, we found no compelling evidence that hunters had likely found the animal and then left the carcass because it was radiocollared. Thus, we do not believe at this time that wounding loss during fall seasons is resulting from hunters being afraid to claim a radiocollared animal. Depending on the type of hunting season and GMU, yearling males with spike antlers are not legal quarry. In general, yearling males are not legal quarry in any part of the study area until the third combined rifle season in late October. In August 1994, there were 32 yearling males alive that were radiocollared as calves. Life/death status of all 32 was determined through 14 June 1995. Of these 32 yearlings, 4 (12.51) were known or presumed to be illegally taken during hunting seasons. Three carcasses were recovered in the following general condition: shot, eviscerated, and left in the field (1st rifle season); shot, not eviscerated, and left in the field (2nd rifle season); shot, eviscerated, head removed, partially packed-out, and radiocollar buried under debris (3rd rifle season). The telemetry signal of the fourth animal, presumed shot and removed, could not be heard after 4 October 1994. V Calf Body Size Male calves had larger body weights (P = 0.001), longer total body length (P = 0.06), longer hind leg lengths (P = 0.06), and higher condition indexes (P = 0.06) than female calves (Tables 5, 6). Body weights and measurements were not different between years for male or female calves (P > 0.30). Predicting body weight from body measurements does not look promising at this time, although all regressions were significant (P < 0.001). The multiple regression using body length and hindfoot length as independent variables provided the best correlation coefficients (.r) of 0.59-0.67. Sighting Bias In 1994 and 1995, we conducted 213 sighting trials of which 192 (90%) were successful, and each observer was involved in 70-72 sighting trials during both years (Table 7). Successful trials occurred when the targeted elk was on the assigned flight quadrat whether or not that elk was seen by observers. Unsuccessful trials occurred when the target elk was found off the assigned quadrat immediately subsequent to the time the quadrat was flown by the helicopter team. Elk were off quadrats primarily due to their movements between the time elk were located with the Cessna 185 and the time the helicopter team flew the quadrat. Usually only 1 elk was targeted per quadrat even though several radiocollared elk may have been present on a quadrat to insure that targeted elk were in separate and independent groups. V V �69 During the 2 years, 143 different elk were used in 192 successful trials (Table 8). Most elk were targeted only once during the 2 years. Targeted elk included adult females, yearling females, female calves, yearling males (spike-antlered), and male calves. Calves comprised 53-54% of the targeted elk within each year. Yearling males were only available as targets during 1995 (Table 9). We used as many different radiocollared elk as possible to avoid any positive effects on sightability that might have occurred if an observer or navigator had been involved in locating a target elk more than once. Observers were not assigned the same target- elk within the same year, except in 1995 an observer was given the same elk twice but the animal was on 2 different search quadrats. During both years, there were 11 cases where a target elk was given to the same observer for 2 trials. In 7 of these cases, the targeted elk was a calf the first year and a yearling the second year, while in the 4 remaining cases, the target elk was an adult in both years. In all 11 instances, elk were on different search quadrats in both years. During both years, there were 24 cases where a navigator was involved with the same target elk during 2 trials. Only 3 of these cases occurred in the same year and the targeted elk was on a different search quadrat on each occasion. Average sighting probability was 82.3% which equates to a 17.7% negative sighting bias (Table 7). There were no differences in sighting bias between years (P > 0.70) but there were differences in sighting bias among observers (P = 0.06) which ranged from 9.3% to 22.4% (Table 7). Univariate tests indicated elk age (calf or adult), elk sex (calves only) initial group size, log(ln) initial group size, total group size, log(ln) total group size, activity behavior, vegetation type, percent occlusion cover, observer, navigator, pilot, and trapping method affected the probability of sighting elk (P ~ 0.06, Tables 11, 12). Adult females were more sightable than calves (P = 0.03) as were male calves compared to female calves (P = 0.06). Elk caught in corral traps were more sightable than those caught with a helicopter and this effect was primarily associated with adult females (P = 0.05), not calves. Multivariate analyses incorporated elk age, ln total group size, activity behavior, vegetation type, percent vegetation occlusion cover, percent snow cover, navigator, observer, and year. According to AIC criteria, the best sightability model out of 2,048 possible models was a complex 12 parameter model involving nearly all major variables. Ln group size, percent vegetation cover, and observer persisted as significant variables as number of parameters was reduced (Table 13). Models incorporating elk age, observer, and navigator are likely not practical for field application. We are currently comparing these 12 best fitting models to assess what effects each model has on predicting sightability of our known population of elk groups. This process will hopefully produce a less complex sighting model. When the same variables are used to build sighting models, results from Idaho (Samuel et al. 1987) and Colorado strongly suggest there are common factors affecting sightability of elk in broadly different landscapes. For coniferous landscapes in Idaho the best elk sightability model was: Y = 1.22 + l.55(LnGroupSize) - 0.05(% vegetation cover). For oakbrush landscapes in Colorado, elk sightability was: Y = 1.23 + l.08(LnGroupSize) - 0.03(% vegetation cover). Effects on sightability of group size and vegetation cover are shown in Fig. 2. Unfortunately at this time, this 3 parameter model ranked 1,165 out of 2,048 Colorado models. The most efficient 3 parameter model incorporated elk activity instead of vegetation cover (Table 13). Group size is a variable that must be incorporated into any sighting model to correct for the propensity to miss groups containing <7 elk (Fig. 2). our data indicates that groups of elk observed but not targeted for sighting trials were smaller than our target groups (P =0.02). This indicates our radiocollared elk groups biasly represented all possible groups of elk which �70 V likely reflects a trapping bias. This data however, also strongly suggests that the need to correct for group size will be greater in actual surveys. Population Estimates Initial estimates of elk population size ranged from 2,049 to 4,339 and were generally imprecise (Table 10). For mark-resight estimators, the nonrandom flight provided the most precise estimate(± 271) because more unmarked and marked elk were observed compared to the quadrat flight(± 47% precision). However, both mark-resight flights provided estimates of similar magnitude: 3,810 and 4,339 elk. The lower quadrat estimate of 2,049 elk probably reflects a need to restratify and reallocate sample units. Precision of the quadrat sample estimate can likely be improved by altering strata, increasing sample size, and increasing the quadrats allocated to high density strata. The imprecision of both the quadrat and quadrat mark-resight estimates(+ 471) indicate more quadrats need to be flown along with refining strata boundaries. Count data indicates that major changes are needed in delineating the Garfield High and East Divide creek low strata. Of the 15 (38%) quadrats where no elk were counted, 8 occurred in these 2 strata. Consideration will be given to assigning each individual quadrat to high and low strata even if quadrats are adjacent to each other. Elk Movements As of 15 April 1995, 22 radioed elk had dispersed to a winter range outside the winter range in GMO 42 where they had originally been trapped in December 1993 (Table 14). Of 35 females collared as calves in December 1993 and recruited into the population as yearlings in June 1994, 8 (231) dispersed during summer-fall 1994 to another winter range. Likewise, of 32 male calves recruited as yearlings in June 1994, 6 (191) dispersed during summer-fall to another winter range. Eight (12%) of 65 adult females alive in June 1994 dispersed during summer-fall to another winter range. Seven (321) of the dispersing elk moved to areas outside of DAU E-14, with 6 of these elk moving into GMO 43 immediately east of DAU E-14 (Table 14). The longest dispersal movement involved an adult female elk (172.480/93) that moved to Beaver Creek west of Gunnison, a straight line distance of about 80 miles. This elk had been neckbanded as a young adult in Beaver Creek in 1991 (GMO 54), then radiocollared in GMO 42 in 1993, and subsequently returned to the drainage where it was originally marked in January 1994 (visual and telemetry location). As of June 1995, this elk had returned to GMO 42. We are currently creating a GIS land database for the area frequented by radiocollared elk. This is a volunteer cooperative effort through the National Biological Service. We believe plots of elk locations and movements using this database will be forthcoming in 1996. CONCLUSIONS We obtained acceptably precise estimates of calf and adult survival rates during winter and recommend continuing our current sampling effort of monitoring 75 radioed calves and >75 radioed adult females in 1995-96. Efforts to measure and develop criteria to adjust for negative bias in counts of elk were promising and we are currently assessing the relative efficiency of several sighting models. We recommend conducting the planned replicate surveys using sample quadrats to estimate elk density from mark-resight estimators and sighting bias correction models in 1995-96. V �71 LITERATURE CITED Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 83-117. Freddy, D. J. 1994. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 27-42. Samuel, M. D., E. o. Garton, M. w. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Wildl. Manage. 51:622-630. SAS Institute Inc. 1988. SAS/STAT User's Guide, 6.03. SAS Institute, Inc., Cary, NC. 1028pp. White, G. c., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego. 383pp. Prepared by ___________________ David J. Freddy Life/Science Researcher J. �Table 1. Capture objectives and numbers of elk radioed in 8 trapzones, December 1993 and December 1994 1 GMU 42. Objectives and elk ca~tured for 1994 are in ~arentheses. Elk Collared8 Capture Calves Adult Trap Objective Total Helio Corral Males Females Females Zone Name 8 ( 6) 3 ( 3) Garfield 0( 0) 8( 6) 1( 3) 8( 5) 4( 0) A Gibson 25(17) 19 ( 7) 6.(10) 20( 8) 5( 5) 8( 6) 12 ( 6) B Uncle Bob 24(13) 29(13) 29(13) 0( 0) 10( 7) 7 ( 6) C 12( 0) 26(13) 0( 0) 5 ( 1) 21(11) 21(11) West Divide D 6( 8) 10( 2) 17(17) 17(17) Hightower 0( 0) 10(10) 4( 9) 3( 8) 10( 0) E 0(13) 0(13) Middle Mamm 10( 8) 0( 0) 0( 8) 0( 5) F 0( 0) 8( 8) 2 ( 0) 3 ( 0) West Mamm 6( 0) 6( 0) 0( 0) G 1( 0) 35 ( 6 )b 0( 0) 35( 6) Dry Hollow 44(21) 7 ( 0) 9( 0) 19( 6) H 141(83) 100(67) 41(16) 36(33) 37(36) 150(86) 68(14) All a Belio b All ~ = Helicopter net-gunning, corral= corral-trap. 6 adult females captured 2 March 1995 Table 2. Causes of mortality and body condition for radioed calf elk in GMU 42, 1 December 1993 - 14 June 1995. Date Estimated Body Marrow Fat Radiocollar Dead Cause of Death Sex Age8 Freggency Wt. 'kg}b Percent Drl!: Matter 172.899/93 173.000/93 173.262/93 173.289/93 173.461/93 173.469/93 173.870/94 174.119/94 174.140/94 173.789/94 173.640/94 174.170/94 173.589/95 F F M M M M F M M F F M F 9 mos 10 mos 9 mos 9 mos 8 mos 10 mos 8 mos 9 mos 9 mos 9 mos 9 mos 10 mos 12 mos 3/18/94 4/25/94 3/18/94 3/22/94 2/07/94 4/25/94 2/21/95 3/01/95 3/14/95 3/20/95 3/30/95 4/25/95 6/01/95 Mt.Lion kill Malnutrition Unknown, Predation? Unknown Malnutrition Malnutrition Mt.Lion kill Unknown, Predation? Mt.Lion kill Unknown Unknown Mt.Lion kill Unknown 86 102 108 111 82 28.54 12.6c 28.9 4 not available 2.lc 77 2. 7c 86 140 112 100 89 140 117 not available 3. 7c 35.6c 76.2c not available 17.4c not available a Approximate age at death, assume 15 June birthdate. body weight at capture in December 1993 or 1994. c Fat content of either the right or left femur bone marrow at death. b Whole d Fat C C content of lower jaw bone marrow at death. CC C C �( ( ( ( ( ( Table 3. Survival rates of radiocollared elk in GMU 42 for different age and sex classes during 4 time periods from 1 December 1993 through 14 June 1995. Survival rates calculated as a simple binomial of elk alive at end of time period divided by elk alive at beginning of time period with a variance of S(l-S)/n. Calves were 6-12 months old and collared at 6 months of age. Yearlings were 12 - 18 months old and juveniles were 18 - 23 months old and both were collared as 6 month old calves in December 1993. Adult females were ~l year-old when captured or recruited in December. Time Period Age/Sex Class 1 DEC 93 - 14 JUN 94 A8 0 6 Surv. Ratec Calves 73 6 15 JUN 94 - 30 NOV 94 A D Surv. Rate 1 DEC 93 - NOV 30 94 A D Surv. Rate 0.92 ± 0.06 1 Dec 94 - 14 JUN 95 A D Surv. Rate 68 7 0.90 ± 0.07 28 34f 0 O -1.00 1.00 94 4 0.96 ± 0.04 190 11 M + F Yearlings Male Female 32 35 4d le 0.88 ± 0.12 0.97 ± 0.06 Juveniles Male Female Adult Females 68 3 Totals 141 9 0.96 ± 0.05 648 12h 131 17 0.81 ± 0.15 67 15 67 15 0.77 ± 0.10 Number of radiocollared elk alive at beginning of time period. radiocollared elk dying during time period. c Survival rate± 95% confidence interval. d One elk (173.309/93) disappeared during October hunting seasons and presumed dead. e One elk (172.800/93) disappeared during November hunting seasons and presumed dead. f Yearling females are included in adult female survival rates during this time period. 8 One elk (172.011/93) censored from calculations because animal was missing. h One elk (172.649/93) disappeared during October hunting seasons and presumed dead. 8 b Number of �74 Table 4. Causes of deaths in radiocollared elk from GMO 42 between 1 December 1993 and 14 June 1995. Calves were 6-12 months old and collared at 6 months of age. Yearling males and females were 12-18 months old and collared as 6 month old calves. Juvenile males and females were 18-23 months old and collared as 6 month old calves. Adult females were ~l year-old when collared or recruited in December. Cause of Death Calves Malnutrition Predation-Lion Accident Legal Bunting Archery/Muzzle Rifle Rifle/Late Wounding Loss Archery/Muzzle Rifle Rifle/Late Illegal Bunting Presumed Bunting Unknown 3 4 0 0 Total Yearl. Males 0 0 0 0 0 0 0 0 0 0 0 6 13 4 0 0 0 1 0 0 0 0 0 Total 1 7 7 2 4 1 7 0 0 0 0 0 0 V 3 5 1 1 0 0 0 0 0 0 0 0 0 Adult Females 0 0 0 0 0 0 0 3 1a 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Elk Age/Sex Class Yearl. Juv. Juv. Females Males Females V 7 1 3 3 4 3 7 19 37 Elk (173.309/93) was a spike-antlered male that disappeared during October hunting seasons and presumed dead and illegally shot. b Elk (172.800/93) disappeared during November hunting season and is a presumed hunting mortality. c Elk (172.649/93) disappeared during October hunting seasons and is a presumed hunting mortality. a V �( ( ( ( ( Table 5. Frequency distribution of whole body weights for male and female elk calves trapped in Game · Management Unit 42. December, 1993 and 1994. Percentage per weight class shown in parentheses. Year Sex 70-79 80-89 90-99 Body Weight Class (kg) 100-109 120-129 110-119 130-139 140-149 Total 1993 1994 M M 1(2.9) 1(3.0) 1(2.9) 1(3.0) 3(8.6) 2(6.0) 6(17.1) 6(18.2) 12(34.3) 13(39.4) 10(28.6) 6(18.2) 1(2.9) 2(6.0) 1(2.9) 2(6.0) 35(100) 33(100) 1993 1994 F F 1(2.9) 2(5.7) 4(11.4) 4(11.4) 8(22.9) 7(20.0) 12(34.3) 10(28.6) 4(11.4) 10(28.6) 6(17.1) 2( 5.7) 0(0.0) 0(0.0) 0(0.0) 0(0.0) 35(100) 35(100) Table 6. Body measurements for elk calves trapped in Game Management Unit 42. December, 1993. 1994. SD 112.7 191.2 Body Length (cm) Hindfoot Length (cm) 56.3 Condition Index 0.59 (Wt./Body Length) 13.7 10.2 2.2 14.2 Measurement 1993 Body Weight (kg) 1994 Male Calves Min Max Mean Year Body Weight (kg) 113.5 190.3 Body Length (cm) Bindfoot Length (cm) 56.9 Condition Index 0.59 (Wt./Body Length) o.os 9.2 1.8 o.os Female Calves Min Max n Mean SD 77.0 164.0 52.0 0.43 141.0 35 210.0 36 61.0 36 0.67 35 103.8 188.9 54.8 12.2 9.8 2.1 76.0 167.0 51.0 0.46 123.0 35 207.0 35 59.0 34 0.64 34 71.0 168.0 140.0 33 204.0 32 59.0 32 0.69 32 103.0 186.3 55.1 13.3 70.0 166.0 128.0 35 207.0 36 59.0 36 0.65 35 so.a 0.42 o.ss o.os o.ss a.a 2.1 0.06 so.a 0.42 n ( �76 V Table 7. Summary of elk sighting bias trials conducted in GMU 42 during 1994 and 1995. Trials Target Target Trials Not Trials Elk Elk Not Observer Yr lttem;eted Useable Detected Useable Detected Broderick Ellenberger Masden Totals 94 95 94-95 94 95 94-95 94 95 94-95 94 95 94-95 29 42 71 36 36 72 45 25 70 110 103 213 3 7 10 4 1 5 4 2 6 11 10 21 26(90%) 35(90%) 61(90%) 32(89%) 35(97%) 67(93%) 41(91%) 23(92%) 64(91%) 99(90%) 93(90%) 192(90%) 22 27 49 25 27 49 36 22 58 83 76 159 ------ V 4(15.4%) 8(22.9%) 12(19.&%) 7(21.9%) 8(22.9%) 12(19.7%) 5(12.2%) 1( 4.3%) 6( 9.3%) 17(17.2%) 17(18.3%) 34(17.7%) Table 8. Numbers and frequency of individual elk targeted during successful sighting bias trials in GMU 42. 1994 and 1995. No. No. Elk No. Elk No. Elk Elk Used in Used in Used in Total Year Used 1 Trial 2 Trials 3 Trials Trials 1994 1995 1994-95 77 90 143 67 87 101 16 3 35 99 93 192 0 0 7 V Table 9. Age and sex of elk targeted during successful sighting bias trials in GMU 42. 1994 and 1995. Female Male Year Adult Yearling Calf Calf Total Yearling 1994 39(39%) 1995 20(21%) 1994-95 59(31%) 6( 6%) 28(28%) 10(11%) 26(28%) 16( 8%) 54(28%) 0( 0%) 15(16%) 15( 8%) 26(26%) 22(24%) 48(25%) 99(100%) 93(100%) 192(100%) Table 10. Summary of population estimates for elk in GMU 42, January and February. 1995. Estimate Private Total Densit! Land Elkb Elk/mi c Method Estimate Date + 95% CI8 Mark-Resight +399 3,810 3,411±27% 14 (267 mi2 ) 1/19/95 NonRandom Flight +565 4,339 Mark-Resight 3,744±47% 19 (234 mi2 ) 2/24/95 Random Quadrats Flight Random Quadrats +565 2,049 1,484±47% 9 (234 mi2 ) 2/24/95 Flight 8 Number of elk estimated In survey area actually flown. b Elk directly counted on private land area not included in survey flight. c Density for area represented by survey flight area plus private land area. V V �( ( ( ( ( Table 11. Elk sightability survey results by major independent variables from Game Management Unit 42, Januaa-March, 1994 and 1995. No. Grou:gs Missed Seen Variable ya Variable 0.52 0.63 Behavior Bedded standing Moving Group Size 12 9 2 5 0 1 4 1 2 3 4 5 6 7+ Vega. Type Clearing/Ag Riparian Sagebrush Oakbrush Pinyan-Juniper Aspen Tall Conifer 13 15 21 14 15 12 69 0.91 0.74 1.00 0.92 0.94 JE 0 0 1 14 9 7 2 13 1 6 89 42 7 1 1.00 1.00 0.86 0.86 0.82 o.so 0.33 Occl. Cover(\) 0-19 20-39 40-59 60-79 80-100 2 11 10 6 4 4 V=visibility • Navigator GB VG FB Observer JB 35 60 43 18 3 0.95 0.85 0.81 0.75 0.43 DM Elk Age Adult Female Calf (M + F) Yearling Calf Sex Male Female Trap (All elk) Corral Trap Helicopter Trap (calves) Corral Trap Helicopter No. Grou:12s Missed Seen Variable Missed Seen Snow Cover (%) 9 4 20 6 41 112 0.40 0.91 0.85 0-19 20-49 50-99 100 3 5 5 20 9 9 47 94 0.75 0.64 22 11 0 68 81 10 0.76 0.88 1.00 Snow Type Fresh Old 5 28 35 124 0.88 12 15 6 49 52 58 o.80 0.78 0.91 Wind Light Moderate Strong 32 1 0 137 20 2 0.81 0.95 1.00 4 21 8 55 81 23 0.93 0.79 0.74 Light Bright Dull Hazy 22 3 8 97 24 38 0.82 0.89 0.83 6 15 42 39 0.88 0.72 32 0 1 139 10 10 0.81 1.00 0.91 9 24 61 98 0.87 o.80 4 29 45 114 0.92 0.80 3 18 14 67 0.82 0.78 Pilot ET BB pp 0.90 0.82 0.82 Time (groups seen I groups seen plus gr~ups missed). AM PM ( �78 Table 12. Variables tested in univariate tests using logistic regression for elk sightability trials, Game Management Unit 42, January-March, 1994 and 1995. Significance level at P < 0.06. Variable Significant Date of Trial Sex of Elk Calves Age of Elk Initial Group Size Log(ln) Initial Group Size Total Group Size Log(ln) Total Group Size Elk Activity Vegetation Type Occlusion Cover % Observer. Navigator Pilot Snow Cover % Snow Type Temperature Wind Conditions Light Conditions Time Interval Time of Day Trap Type No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No Yes Sign. Year Effect Sign. Year Interaction No No No No No No No No No No No No Yes No No No No No No No No Yes No No No No No No No No No No Yes No No No No No No Yes Table 13. The best fitting sightability model at each level of 1 to 12 parameters according to Akaike Information Criterion (AIC). Rank is the relative rank of each model among 2,048 models which used variables in all possible combinations. "Yes" denotes variables used in models. Variables In Models No. Ln Elk Group Elk Vege. %Vege. %Snow AIC ParamObs. Cover Cover Nav. Year eters Age Size Act. Tv1>8 Rank 1 2 7 4 48 61 152 463 869 1019 1403 1890 2028 12 11 10 9 8 7 6 5 4 3 2 2 1a Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes V V V Yes Yes Yes Yes Yes Yes Yes Yes Yes a The one parameter model includes only the intercept which equates to the average sightability of elk which was 0.823. V �79 V ·~ Table 14. Radiocollared elk captured in GMU 42 during Deceri>er 1993 and thought to have dispersed out of GMU 42 to a new winter ranse as of 15 Aeril 1995. Locations ,GMUs2 determined~ aerial telemetrx. New Trap Location Descrietion Sex GMU Zone Age0 Freauencx 3+ Fourmile Ck (Loe.Elk) F 43 D 172.207/93 3+ 421,42 Beaver-Buzzard Cks, Alkali Ck. (Loe.Elk) F 172.219/93 D 5+ Ees t Muddy Ck F 521 C 172.249/93 2+ Middle Th0[1')Son Ck F 172.308/93 D 43 3+ Beaver Ck, Gumisonb F 54 172.480/93 H 5+ N.Fk.Gwv,ison, Near Paonia 172.459/93 F 521 E 2+ Roaring Fk R., Glenwood Sprgs. (Loe.Elk) 172.509/93 F 43 H 1+ F 421 Hawxhurst Ck 172.830/93 B 1+ Threemile Ck, Roaring Fk. River F 172.849/93 A 43 1+ East Muddy Ck, Paonia Reservoir F 172.921/93 C 521 1+ Redstone; Porcupine Ck F 172.929/93 C 43 1+ East Muddy Ck, Paonia Reservoir 172.961/93 F D 521 1+ Hawxhurst Ck, Brush Ck 173.010/93 F 421 G 1+ 173.020/93 F 421 Hawxhurst Ck, Brush CK G 2+ 173.070/93 F 42,West Parechute;Monunent Gulch E 1+ 173.090/93 F Roering Fk River, Crystal Ranch H 43 1+ 173.279/93 East Muddy Ck, Paonia Reservoir C M 521 1+ 173.300/93 C M 521 East Muddy Ck 1+ 173.332/93 Clover Gulch, Hawxhurst Ck D M 421 1+ 173.370/93 E M 421 Plateau Ck/Salt Ck 1+ 173.390/93 West Muddy Ck, Pilot Knob D M 521 1+ 173.450/93 Kimball Ck, Wallace Ck M 421 H 6 Age of elk in years as of April 1995 b This elk returned to GMU 42 during June 1995, a movement distance of about 80 airline miles. ~ \.._,,,I ~ \,,,..,/' Appendix 1. Mortalities of radiocollared elk from 1 Deceri>er 1993 - 14 June 1995. Age is approximate age in years of elk at death; C=calf 6·12 months old, Y=yearling 12-18 months old. Body weight measured in Deceni>er when eLk caetured as calves. Body Frequency ID/ Date Tree Cause of Death Year caetured Site Zone Sex Age Wt.,kg} Heard Dead 172.039/93 Undetermined mortality GR B F 2+ 06/14/95 172.080/93 GM A F 5+ 11/05/94 Legal harvest rifle season 172.090/93 F 5+ 01/16/94 Wounding loss late rifle season GR B 172.160/93 Legal harvest rifle season cc C F 2+ 10/23/94 172.181/93 F 2+ MC C 11/03/94 Wounding loss rifle season 172.201/93 GS C Wounding loss rifle season F 2+ 11/15/94 HY C F 2+ 10/04/94 Legal harvest archery/nuzzle season 172.258/93 172.277/93 F 2+ GS C 10/04/94 Wounding loss archery/nuzzle season F 5+ 172.290/93 SG 10/23/94 Legal harvest rifle season 172.369/93 AC F 2+ 09/18/94 Legal harvest archery/nuzzle season 172.409/93 AC F 5+ 12/29/94 WOWlding loss late rifle season 172.542/93 FS F 9+ 02/01/94 Mountain lion predation 172.570/93 F 9+ 11/03/94 WOWlding loss rifle season PG 172.581/93 F 2+ Legal harvest rifle sea·son PG 10/17/94 172.610/93 F 2+ PG 10/04/94 Accident, breech birth of calf 172.649/93 PG F Y+ 11/15/94 Disappear rifle season F 2+ 172.670/93 01/16/95 Legal harvest late rifle season PG 172.678/93 F 9+ 12/22/94 Wounding loss late rifle season PG FM F 5+ 172.690/93 01/24/94 Illegal harvest, poached 172.800/93 SR F Y+ 11/15/94 Disappear rifle season 172.899/93 BC F C 86.0 03/18/94 Mountain lion predation 173.000/93 WM G F C 102.0 04/25/94 Malnutrition M y 173.190/93 BC C Illegal harvest rifle season 10/29/94 111.0 BR A 173.232/93 M y 105.0 11/15/94 Illegal harvest rifle season 173.262/93 BC C M C 108.0 03/18/94 Undetermined mortality 173.289/93 MC C M C 111.0 03/22/94 Undetermined mortality 173.309/93 HY C M y 11/15/94 124.0 Disappear rifle season 173.320/93 HY C M y 118.0 10/20/94 Illegal harvest rifle season 173.461/93 M C 02/07/94 Malnutrition PG H 82.0 173.469/93 FS H M C 04/25/94 Malnutrition 77.0 173.589/94 0G B F C 117.0 06/01/95 Undetermined mortality 173.640/94 MC C F C 89.0 03/30/95 Undetermined mortality 173.789/94 F C MR E 100.0 03/20/95 Undetermined mortality 173.870/94 F C 86.0 02/21/95 SM D Mountain lion predation 174.119/94 F M C 03/01/95 MM 140.0 Undetermined mortality 174.140/94 M C F 112.0 03/14/95 MM Mountain lion predation 174.170/94 FM B M C 04/25/95 140.0 Mountain lion predation �87 Colorado Division of Wildlife Wildlife Research Report July 1996 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-9 work Plan No. Mammals Research _..>L,.__________ Job No. _ _ _ _.....,.____________ Elk Investigations Estimating Survival Rates of Elk and Developing Techniques to Estimate Population size Period Covered: Author: July 1, 1995 - June 30, 1996 D. J. Freddy Personnel: J. Broderick, G. Byrne, A. Coriell, D. crane, J. Ellenberger, D. Fox, J . Frothingham, v. Graham, J. Gray, G. Loucks, D. Masden, C. Mehaffy, J. Ritchie, L. Stevens, P. Will, CDOW; D. Bowden, G. White, CSU; CSU Diagnostic Laboratory; K. Crane, c. McCarty, N. Miers, D. Ouren, A. Ryel, volunteers; BLM Glenwood Springs, NBS Ft. Collins, Rocky Mountain Elk Foundation, USFS Rifle, cooperating. ABSTRACT We captured and radio-collared 71 calf elk (Cervus elaphus nelsoni) 6-months old in December 1995 to estimate survival rates during winter 1995-96 and to increase numbers of radiocollared elk available for experiments utilizing mark-resight models to estimate population density. Elk were captured using helicopter net-gunning and portable corral traps. Survival rates(± 95% CI) for 6-11 month old calves during winter-spring were 0 . 92 ± 0.06, 0.90 ± 0.07, and 0.88 ± 0.08 in 1993-94, 1994-95, and 1995-96, respectively. Survival was similar among years (P > 0.50) and sexes (P > 0.70). Suspected primary causes of death for calves were predation (57%) and malnutrition (33%). Survival rates for adult females(~ 12 months old) during winter-spring were 0 . 96 ± 0 . 05, 0.96 ± 0.04, and 0.95 ± 0.04 also during 1993-94, 1994-95, and 1995-96 and survival was similar among years (P > 0.70). Hunting was the primary cause of death (57%) for adult females during winter-spring. Annual survival rates (l December-30 November) for adult females were 0.78 ± 0 . 10 and 0.84 ± 0.09 in 1993- 94 and 1994-95, respectively. Survival was similar between years (P > 0.50) and hunting annually accounted for 88% of the adult female deaths. Hunting removed 79 % of the adult 2-year old males. Survival of males from 6month old calf to 35-month old adult were 0.09 ± 0.10 compared to 0.86 ± 0.12 for females of the same cohort. Wounding loss on adult males was 9% and illegal loss of yearling males averaged 10%. Estimates of population size based on mark-resight estimators ranged from 3, 2 72 -3,618 elk or about 26 elk/mi2 of winter range. The IEJHE mark-resight model using data pooled from 1~~ 1ffil1~ii11 ~~1ffif BDOW01 □ 789 �4 aeria l flights provided the best estimate of population size which was 3,415 elk wit h a 95% CI of 3,129-3,807. Estimates based on counts of elk on randoml y selected 1 mi2-quadrats during 2 replicate flights were 2,165 and 3,175 e lk. Sighting bias models to adjust for negative bias of quadrat counts are cur rently being evaluated. We believe stratified sampling systems using quadrat s as sample plots and with counts corrected for sighting bias holds promise for providing reasonable estimates of population size. �:~JXf._ li10,)fh f ..:.1 :. 87 ... "--~ .:/{ \ .. ' / Colorado Division of Wildlife Wildlife Research Report July 1996 JOB PROGRESS REPOR~ state of Colorado Project No. W-153-R-9 Mammals Research Elk Investigations Work Plan No. Job No. ____ __________ __.._ : Estimating Survival Rates of Elk and Developing Techniques to Estimate Population size Period Covered: Author: ;~~~ :;;;tt·\: ( ~~ July 1, 1995 - June 30, 1996 D. J. Freddy Personnel: J. Broderick, G. Byrne, A. Coriell, D. Crane, J. Ellenberger, D. Fox, J. Frothingham, v. Graham, J. Gray, G. Loucks, D. Masden, C. Mehaffy, J. Ritchie, L. Stevens, P. Will, CDOW; D. Bowden, G. White, CSU; CSU Diagnostic Laboratory; K. Crane, c. McCarty, N. Miers, D. Ouren, A. Ryel, volunteers; BLM Glenwood Springs, NBS Ft. Collins, Rocky Mountain Elk Foundation, USFS Rifle, cooperating. ABSTRACT We captured and radio-collared 71 calf elk (Cervus elaphus nelsoni) 6-months. old in December 1995 to estimate survival rates during winter 1995-96 and to increase numbers of radiocollared elk available for experiments utilizing mark-resight models to estimate population density. Elk were captured using helicopter net-gunning and portable corral traps. Survival rates(± 95% CI) for 6-11 month old calves during winter-spring were 0.92 ± 0.06, 0.90 ± 0.07, and 0.88 ± 0.08 in 1993-94, 1994-95, and 1995-96, respectively. Survival was similar among years (P > 0.50) and sexes (P > 0.70). Suspected primary causes of death for calves were predation (57%) and malnutrition (33%). Survival rates for adult females(~ 12 months old) during winter-spring were 0.96 ± 0.05, 0.96 ± 0.04, and 0.95 ± 0.04 also during 1993-94, 1994-95, and 1995-96 and survival was similar among years (P > 0.70). Hunting was the primary cause of death (57%) for adult females during winter-spring. Annual survival rates (l December-JO November) for adult females were 0.7~ ± 0.10 and 0.84 ± 0.09 in 1993-94 and 1994-95, respectively. Survival was similar between years (P > 0.50) and hunting annually accounted for 88% of the adult female deaths. Hunting removed 79% of the adult 2-year old males. Survival of males from 6month old calf to 35-month old adult we~e 0.09 ± 0.10 compared to 0.86 ± 0.12 for females of the same cohort. Wounding loss on adult males was 9% and illegal loss of yearling males averaged 10%. Estimates of population size based on mark-resight estimators ranged from 3,272-3,618 elk or about 26 elk/mi2 of winter range. The IEJHE mark-res.ight model using data pooled f rem 1iiiHi1ili • BDOWD1 □ 789 �4 aerial flights provided the best estimate of population size which w~s elk with a 95% CI of 3,129-3,807. Estimates based on counts of- elk on " ,, .. :-. randomly selected 1 mi2 -quadrats during 2. replicate flights -were '2,'16sJka"/\.:. 3 I 175 elk. Sighting bias models to adjust for negative bias of quadr~t''9otii1€e :. are currently being evaluated. We believe stratified sampling ·systems ~:11~~?9 · • quadrats as sample plots and with counts corrected for sighting bias holds'· :> • ~. promise for providing reasonable estimates of population size. ,' �89 BS!rIMA!rIHG SURVIVAL RADS OF ELK AND DEVELOPING !rECBRIQlJBS m BS~IMAm POPULA~IOH SIZE David J. Freddy P, ff, OBJECTIVE Estimate survival rates of adult female a·nd calf elk and develop techniques to estimate population size. SEGMEHT OBJECTIVES 1. Radio-collar 75 calf and 15 adult female elk during December 1995 in Game Management Unit 42 south of Rifle, COlorado. 2. Estimate winter and annual survival r~tes of calf and adult elk from known fates of radioed elk. 3. Estimate density of elk in a portion of GMU-42 using 2 replicate flights of a quadrat sampling system. Apply sighting bias corrections to adjus~ numbers of elk counted during each replicate. Compare biase adjusted estimates with mark-resight estimates based on numbers of marked elk seen during the 2 replicate flights plus 2 nonrandom mark-resight flights. 4. Analyze data and summarize annually in Federal Aid Job Progress reports 5. Prepare_ draft of manuscript on sighting bias models developed from data collected in 1994 and 1995. 6. Continue to monitor locations and movements of selected radiocollared elk. INTRQDUCTXQH Our objectives-are to provide reliable estimates of survival rates for calves and -adult females during winter and for adult females throughout the year for the period 1993-94 through 1996-97. Additionally, we will develop and test a system for estimating population size that will incorporate estimates of sighting bias in conjunction with a random sampling system using search quadrats as sample units. our winter study area encompasses about 839 Jan2 (324 mi2 ) in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado. Elk winter range vegetation types include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain sh~ub (Ouercus gambelii-Amelanchier alnifolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields (Freddy 1993, 1994). �90 METHODS • Marking We placed radio collars (172-176MBz) ·having mortality sensors on 71 calves (6 months old), of which 37 were males and 34 were females. Of these, 68 calves were trapped from. 8-11 December 1995 using helicopter net-gunning and 3 calves were trapped on 21 December using portable corral trap.a. Helicopter capture occurred at 10 remote sites located primarily. on public lands while corraltrapping occurred at 1 site on public lands. Trapping effort was all9cated among 8 geographic trap zones to assure that radioed elk were representative of most if n9t all segments of th~ population (Table 1). Radio collars were of the same type used in 1993 and 1994 (Freddy 1994). Calves captured by net-gunning were ferried by helicopter to processing points usually within 1. 6 Jan of capture sites. At processing points·, body weight, total body length, hind foot length, and rectal body temperature (F) were measured and calves were then radio-collared and released. Similar measurements were also made on calves that were_ corral-trapped and then released at the trap site. Body measurements for calves were compared between sexes and years using Pree FREQ, GLM, and REG (SAS 1988)·. survival We monitored life or death status of radioed elk during daily ground surveys and aerial surveys conducted at 2-4 week intervals from December 1995 through ·April 1996 and via monthly aerial surveys from M~y to November 1995 and May to. June 1996. Survival rates (S) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) ~ S(l-S)/n (White and Garrott 1990) (Pree FREQ, .SAS 1988). Survival rates are expressed as the mean estimate ± the 95% confidence interval. We used x2 -contigency tests to compare survival rates. we· chose not to use the staggered entry approach and did not use a Kaplan-Meier approach because elk were captured in~ short time interval and few animals were censored (White and Garrott 1990). We defined 4 major time intervals for survival analyses: winter-spring was 1 December to 14 June, summer-fall was 15 June to 30 November, annual was 1 December to 30 November to coincide with timing of capture and radiqcallaring, and yearly for yearling elk aged 12-23 months was 15 June to subsequent.14 June. Life or death status of all calves radioed in.December 1995 (71) was known for the period 8 December 1995 through 15 June 1996 except for 1 male calf collar, 174.619/95 which apparently slipped off the elk in May 1996. on 15 June·,· calves become yearlings for purposes of calculating rates of calf surviYal. Life or death status for adult females, adult males, yearling females, and y~arling males collared iri December 1993 or 1994 was known for 198 of 205 elk through_ 15 June 1996. Causes of death were-estimated from multiple sources of evidence including: presence or absence of gunshot wounds, presence or absence of bite wounds on carcass and predator tracks or ~cat at carcass site, p:tiysical positioning of carcass remains whether buried, covered, scattered, or consolidated, re.lative amount of internal fa~ and marrow fat if pre~~nt with carcass, and results of histopathology an~ marrow fat analyses (Wade ~nd Browns 1982, Halfpenny and Biesiot 1986). Fat co_ntent (percent dry matter) of .bone· marrow and estimates of age based on d~ntal cementum were obtained for dead elk by the Colorado Division of Wildlife Laboratory while histopathology analyses were provided by ( / \ �91 the Colorado State University Veterinary Diagnostic Laborat.ory. Photographs were taken of nearly all mortalities so that physical evidence could be reviewed and judged by outside experts (pers. comm. A. Anderson, T. Beck, w. Andelt). Pgpulation Estimates Elk population size in GMU 42 from East Alkali Creek west to. Grass Mesa was estimated during mid-January and early March 1996. We counted elk using a· Bell-Soley helicopter on 4 flights. Two replicate flights involved counting elk on 53 quadrats about 1 mi 2 (2.59 km2 ) in size representing.a 40% strati£ ied random sample of t.he 132 mi2 winter range. • Each potential quadrat in 8 geograhic. blocks were ranked as a high or low density quadrat resulting in 14 strata. Intensity of sampling was 60% in high density and 32% in low density strata with a minimum of 3 quadrats in any one strata~ Two flights involved counting elk.encountered on a nonrandom route that traversed the same 132 mi 2 area. One flight of each type was conduct~d during the time periods 15-20 January and 29 February-3 March 1996. During helicopter surveys, fixedwinged flights were conducted to locate 219 radiocollared elk to determine whether these marked elk were within or outside the 132 mi2 sample area. During all flights, numbers of marked and unmarked elk were tallied by observers. We gener~ted estimates of population size using several markresight estimators for each individual flight, pairs of flights, and all 4 flights pooled using program NOREMARK (White 1996). We considered. estimates based on all 4 flights pooled to be our best estimate of population size- and the b~nchmark against which individual flights, especially·quadrats, would be compared. Estimates from quadrat sampling were computed using program DEAMAN (Colo. Div. Wildl. software). At this time, we have~ applied sighting bias correction factors to the counts of elk observed on quadrats •(Freddy 1995) .• Movements We continued to locate selected radioed.elk at least once per month since capture to document seasonal movements via telemetry using a Cessna 185. These elk were selected at random from within trap zones and equalized by age class in Janaury 1994. Elk from the original sample that died were replaced each subsequent January primarily with randomly selected 6 month-old calves of· the same sex from the same trap zone(s) as elk that died. As of 1 January 1996, these 4·4 elk were classified as 22 adult females, 4 yearling females, 6 • female ca·lves, 2 adult males, 4 yearling males, and 6 male calves. During June 1996, we agaln located 28 adult ·females that. were selected at random in 1995 to document locations during the calving period. As needed, we located other elk to document· unusual movements. RESULTS AND DISCUSSION c;apture Two elk calves died during helicopter net-gunning activities. These have been the only deaths during capture of 235 elk using the helicopter. one calf died_ of a bro~en neck during capture and one calf (174.800/95) di~d within 10 days of capture due to the effects of capture myopathy (histopathology, CSU Diagnostic Lab) and was subsequently censored from survival analyses. �92 survival ~ Between 1 December 1993 and 14 June 1996, 86 radiocollared elk died (Table 2, Appendix 1). Hunting was apparently· involved in 661 of the deaths. For adults ~1 year-old, hunting accounted for 87% of 65 deaths. There were 2 periods of mortality during the year. Calves died from February to May while adults died during fall and early winter when hunting seasons occurred (Fig. 1) . . Calves survival rates for 6-11 month old calves during winter-spring were 0.92 ± 0.06, 0.90 ± 0.01, and a.as± o.oa in 1993-94, 1994-95,· and 1995-96, respectively (Table 3). We failed to detect differences in survival of calves among years (X 22 = 0.40, P >0.50), between sexes· pooled among year·s (X21 = 0.58, P >0.70), and between sexes within each yearly cohort (X21 S 0.79, P > 0.70) (Tables 3, 5, 6). Sex of dead calves for all years was 12 male and 9 female (Table 2). These survival rates were associated with winters considered mild in temperature and having low or moderate snow depths. In 1994-95, considerable snow fell during March and April but usually melted rapidly at lower elevations. Causes of death for calves during winter-spring were suspected malnutrition (33%), mountain lion predation (33%), ·suspected predation (19%), bear predation (5%), and unknown cause (10%) (Tables 2, 4). Percent fat in bone marrow of calves suspected of dying from predation was 82 for males {(range 6495, n = 6) and 48 for females (range 29-63, n = 3) and for calves dying from suspected malnutrition, 14 for males (range 0.2-41, n = 3) and 11 for females (rang~ 8-15, n = 3) (Table 4). Yearlings -:i survival rates for elk 12-23.months of age were 0.86 ± 0.09·for males (n = 57) and 0.95 ± 0.05 for females (n = 66) when yearlings were pooled among years and hunting mortalities were included (Tables 5, 6). Excluding or censoring hunting mortalities increased survival rates to 0.98 ± 0.04 for males and 0.98 ± 0.03 for females. Males had lower survival rates when hunting mortalities were included (X2 1 = 3.38, P = 0.07) but not when hunting mortalities were • excluded (x\ = 0.03, P > 0.50). Of the 11 deaths involving elk 12-23 months old, 9 (82%) were hunting related (Table 3). Adult FemalQs ·Survival rates for adult females(~ 12 months of age) during winter-spring and inclusive· of hU:ntin_g mortalities were 0.96 ± 0.05, 0.96_ ± 0.04, and 0.-95 ± 0.04 in 1993-94, 1994-95, and 1995-96, respectively. Excluding hunting mortalities increased·survival to 0.98 ± 0.03, 0.99 ± 0.02, and 0.97 ± 0.03 in the same 3 years (Table 7). We failed to detect differences in survival among years inclusive (x22 = 0.37, P >= 0.50) or exclusive (X22 = 1.52, P > 0.70) of hunting mortalities. Of 14 winter-spring deaths, 8 (57_1) were related to late-season rifle hunting: 4 legal and 1 illegal harvest and 3 wounding losses (Table 2). Six natural deaths included 2 suspected predation, 3 of unknown cause,_ and 1 calvingrelated~ Of the 3 elk lost to wounding, 2 were suspici9us kills. Both of these elk died from 1 rifle shot to the upper neck or head in relatively plain ( ( �93 sight near or on an agricultural field where retrieval of the carcass was not difficult. These animals may_have been accidentally shot, maliciously shot, .or abandoned because of the radiocollar. Survival rates for adult females(~ 12 months of age) during summer-fall and -inclusive of hunting mortalities were 0.87 ± 0.07 and 0.94 ± 0.04 in ·1994 and 1995, respectively. Excludlng hunting mortalities increased survival to 0.99 ± 0.02 and 1.00 in the same 2 years (Table 7). We failed to detect differences in survival among years inclusive (X21 = 3.13, P = 0.09) or exclusive (x\ = 1.38, P > 0.70) of hunting mortalities. Hunting accounted for 20 (95%) of 21 summer-fall deaths. The one natural death was ~alvingrelated. During hunting seasons in Fall 1994 and 1995, 100 and 129 radiocollared adult females, respectively, were a~ailable to hunters (Table 7). Proportions of these marked elk lost to hunting-related mortalities were 12 1k in 1994 and 8% • in 1995. Annual survival rates for adult females(~ 12 months of age) marked as a cohort in December 1993, inclusive of hunting mortalities, were 0.78 ± 0.10 and 0.84 ± 0.09 in 1993-94 and 1994-95, respectively. Excluding hunting mortalities increased survival to 0.96 ± 0.05·and 0.98 ± 0.04, respectively (Table 8). We failed to detect differences in survival among years inclusive (X21 = 0.19, P > 0.50) or exclusive (x\ = 0.15, P > 0.50) of hunting mortalities. For this cohort of adult females, hunting accounted for 22 (88%) of 25 deaths during both years. Adult Males Survival of males from 6-month old calf t~ 35 months of age was 0.09 ± 0.10 compared to 0.86 ± 0.12 for females of.the same calf cohort (Table 5). Hunting was the overwhelming cause of mortality among male elk. From the 1993-94 calf cohort of 36 male calves, 28 (78%). lived to become 2-year old· legal branch-antlered bulls for ·the 1995 hunting seasons. Of these 28, 22 or 79% were harvested in the Fall of 1995 inclusive of 2 wounding losses (9% of 22). Rifle seasons accounted for 16 (73%) of the hunting mortalities (Table 2) . . Most of these 2.-year old bulls were harvest~d .in the Grand Mesa DAU or in adjacent GMO 43 .. One.exception was a bull taken during archery ·season in GMO 63 on Black Mesa about 100 miles south of its capture site in GMO 42. One surviving bull was located in March 1996 in GMO 4.7 east of Basalt, co about 35 miles southeast of its capture site in GMO 42. Yearling spike-antlered bulls were generally not legal quarry during hunting seasons. In 1994, 32 yearling bulls from the 1993-94 calf cohort entered the hunting seasons presumably as spike-antlered bulls and 4 (12.5%) were illegally taken with 3 taken during rifle seasons and 1 taken prior to rifle seasons. In 1995, 30 yearling bulls from the 1994-95 calf cohort entered the hunting season and 2 (7%) were illegally taken and 1 (3%) was fatally wounded during ar9hery season in an ar~a where the bull was legal q,.Jarry. cal:f Body ·size Body weights of male and females calves were largest in 1995 with the inerease most pronounced for males (Tables 9, 10).. Increases in weights were not unexpected as the locally moist summer of 1995 wa·s favorable to forage production on summer ranges. However, we failed to detect.differences in �94 body·weights among years (P = 0.206) and any interaction between year and sex (P = 0.380). overall, male calves had larger body weights (P = 0.0001), longer total body length (P = 0.0386), longer hind leg lengths (P = 0.0001), and higher condition indexes (P = 0.0001) than female calves (Table 10). Accurately predicting body weight from total body length, hind foot length, or a combination of·these 2 measurements does not look promising at this time, although all regressions were significant (P < 0.0001). The multiple regression using body length and hindfoot length as independent variables provided the best correlation coefficients (r2) of 0.63 for female calves, 0.69 for.male calves, and 0.69 for sexes combined. Calves suspected of dying from predation (Table 4) averaged 121 kg in weight for males (range 100-140 kg, n = 6) and 91 kg for females (range 79-117, n = 5). Predators thus appeared to take larger than average males and smaller than average females (Table 10). Calves suspected of dying from malnutrition (Table 4) averaged 95 kg in weight for males (~ange ~7-127, n = 3) and 107 kg for females (range 100~120, n = 3). Malnutrition thus appeared to affect smaller than average males .and average sized females (Table 10). Pgpulation Estimates Our elk population was not geographically or demographically closed during the time interval encompassing flights. During our first pair of flights, some elk were still moving down in elevation in response to heavy snow in early January resulting in.fewer than expected radiocollars on the sample area. By the March flights, all elk had reached elevations encompassed by the sample area but some elk moved lower in elevation onto private lands outside of but adjacent to the sample area and some elk moved to winter ranges adjacent to but also outside the sample area. These movements resulted in radiocollared elk moving into and out of a "pool" of elk that was different and larger than the elk population encompassed. by the. sample area. Between pairs of flights, 2 radiocollared elk died indicating some los~ of elk was occurring during our flight time interval. Fortunately, both quadrat and nonrandom flights reflected proportionately similar and positive changes in total elk and total marked elk counted between pairs of flights indicating that movements of marked and unmarked elk into the sample area were similar (Table 11). ( ( Population estimates from 4 mark-resight estimators ranged from 3,272-3,618 elk or 24.8-27.4 elk/mi2 of winter range within the sample area (Table 12). At· this time, the estimate of 3,415 elk generate~ by the Immigration/Emigration JHE mark-resight estimator is probably the best estimate of population size on the sample area because it accounts for movement of elk on and off the sample area. Adding the 165 elk directly counted on private lands in lower Divide Creek and Hunter.Mesa (57 mi 2 area) increased the population to 3,580 elk in the intensive study area. In January 1995, a single nonrandom flight produced a Lincoln-Peterson mark-resigh~ estimate of 3,411 elk and adding 399 elk counted on private lands in lower Divide creek and Hunter Mesa.to this estimate.increased the_ population to 3,810 elk in the intensive study area in 1995 (Freddy 1995). Population estimates for the larger "pool" of elk within which radiocollared elk were moving ranged from 3,969-4,004 elk as estimated by the IEJHE and BE mark-resight estimators (Table 12). This "pool" ~stimate wo~ld include el~ on the Divide creek and Hunter Mesa private lands and some addit!onal elk on areas ~djacent to the western boundary of the intensive study area. ( G �95 Population estimates from quadrat flights 1 (2,165 elk) and 2 (3,175 elk) were lower than the IEJHE mark-resight estimate (3,415) (Table 12). Although both quadrat flights were subject to sampling error, the lower . estimate from the first flight may reflect a less favorable distribution of elk ~uring that flight. Confidence intervals overlapped between quadrat flight 2 and IEJHE suggesting estimates were not different. Quadrat estimates will be adjusted upward for sighting bias and at that time more conclusive comparisons to markresight estimators will be made (Freddy 1995, Samuel et al . 1987). Elk densij:ies ~ 50/mi2 occurred within the Garfield Creek High, West Divide Creek 2 West High, and Grass Mesa Low strata which together encompass about 25 mi of winter range (Table 13). Elk Movements In December 1994, 33 male and 36 female calves and 8 adult females were radiocollared. Of these elk, 27 male and 31 female calves and all 8 adults survived to 30 November 1995. None of the adult females dispersed during winter 1995-96 to a winter range outside of the intensive study area in GMO 42. However, 25 (9M, 16F) or 43% .of the surviving yearling elk dispersed to winter ranges outside the intensive study area (Table 14). Rates of dispersal were 33% for males and 52% for females. Calves trapped in zones E and F, which encompass Alkali, Dry Hollow, and the Mamm creeks, comprised 68% (17) of the dispersing yearlings but only 45% of the surviving yearlings. Calves trapped in zones E and F dispersed to winter ranges near the towns of Collbran, Parachute-Rulison, and Paonia. Calves trapped in zones C and D which encompass West Divide Creek comprised 28% of the dispersing juveniles and these elk primarily moved south to winter ranges near Paonia and Paonia Reservoir. We are. currently creating a GIS land database for the area frequented by radiocollared elk. This is a cooperative effort through the National Biological Service and Rocky Mountain Elk Foundation . We believe plots of elk locations and movements using this database will be forthcoming in 1996. 12 lililllll CAL VE S 10 - ~ ADULT lfALES l<<<·>I ADULT FEtlALES 8 •••••• •••4••• •• •••• •••••• •••••• •••••••• •• •••••••••••• • •••••n•--• • ••• • •• •••u•••••••• • •••••• • ••••••••• • ••• • ••••• •••••• o o o o o o o o o o O o o U OO • • o • • O o o O oOOOO 00000000• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • O oOo O O OOO O OOOOOO H Q P! r..i 6 •o• o o•••• ~ ~ 4 2 ···········-······· ···········~-,................................ . 0 Figure 1. Timing of deaths for calf and adult elk, 1993-1996. 12 months old and adults were >12 months old. Calves were 6- �96 CQNCLUSXQRS \._/ We obtained acceptably precise estimates .of calf and adult survival rates and recommend continuing our current sampling effort of capturing and radiocollaring 70 calves in 1996-97 and co~tinuing to monitor> 75 radioed adult females and> 25 radioed adult males in 1996-97. We recommend conducting replicate aerial surveys in 1996-97 to estimate elk density ~sing sample quadrats, mark-resight estimators, and sighting bias correction models to complete our evaluation evaluating techniques to estimate elk density. LITERATURE CITED Freddy~ D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep.· July: 83-117. Freddy, D. J. 1994. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 27-42. Freddy, D. J. 1995. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. J~ly. Halfpenny, J. c., and E. A. Biesiot. 1986. A field guide to mammal tracking in North America. Johnson Books, Boulder, co. 161pp. • Samuel, M. D., E. o. Garton, M. W. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Wildl. Manage. 51:622-630. J. SAS Institute Inc. 1988. SAS/STAT User's Guide, 6.03. SAS Institute, Inc., Cary, NC. 1028pp. Wade, D. A., and J. E. Browns·. 1982. Procedures for evaluating predation on livestock and wildlife. Texas Agric. Expt. Sta. Publ. B-1429. 42pp. White, G. c. 1996. NOREMARK: Population estimation from mark-resighting surveys. Wildl. Soc. Bull. 24:50-52. White, G. c., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego. 383pp·. Prepared by ____________________ David J. Freddy Life/Science Researcher �( in 8 trapzones. December 1993.1994. and 1995 within Game Management Unit 42. Table 1. El.k capture objectives and numbers of elk radiocollared Elk Col lared1 Calves Collared ·Elk Captur~ Years Corral Objectives Males TotalLYeac Helicoeter Females Years Adult Females Collared Trap 93 94 95 93 94 95 Total 93 94 95 93 94 95 93 94 95 93 94 95 Total Zone Name 93 94 95 Total A B C D E F G H Garfield Gibson Uncle Bob West Divide Hightower Middle Manm West Manm Dry Hollow All 5 8 13 13 10 8 8 21 6 12 11 11 10 9 10 6 8 6 4 25 17 7 29 13 14 21 11 18 • 17 17 14 0 13 9 6 ·O 5 35 6b 0 8 6 4 19 7 4 29 13 14 21 11 18 17 17 14 0 13 9 6 0 5 0 0 0 0 0 0 6 10 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 6 0 18 49 56 50 48 22 11 41 150 86 75 141 83 71 100 67 68 41 295 8 20 24 26 10 10 8 44 16 3 3 4 0 2 7 3 1 5 4 7 10 1 8 9 ·8 8 5 0 1 0 0 36 ·33 37 5 10 5 1 8 7 6 3 0 3 9 3 3 6 3 6 4 8 10 8 6 5 4 O· 4 0 0 37 36 34 14 31 44 38 • 22 10 4 12 12 10 10 • 0 1 16 19 0 0 6 0 0 0 2 0 0 0 0 0 0 0 6 0 213 68 14 0 38 4 18 12 12 10 0 1 25 82 •Helicopter= Helicopter net-gunning, Corral= corral-trapping. 6 adult females cap~ured 2 March 1995 b All Table _3. Survival rates of calve~ with sexes pooled for 1 December - 14 June each year 1993-94, 1994-95, and 1995-96. Survival· rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(lS)/n collars. Elk Age and Time Period (dates) • Calves Cal~,es Calves Survival 'L 95\- CI U 9~%' CI n collars Censored1 Died Nonhunting Hunting 12/01/9306/14/94 12/01/9406/14/95 12/01/9506/14/96 0.92 0.85 0.98 73 .0. 90 0.83 0.97 0.88 0.81 0.96' 69 0 6 6 0 69b 0 7 7 0 2c 8 8 0 • Censored denotes collar failure and/or animal life/death status not known. b Includes (173.949/94) male whose collar'failed 12/94 but seen alive 1/95, 1/96. c Censored elk were (174.619/95) for slipped collar and (174.800/95) for trap-related mortality. �98 ~ Table 2. Causes of deaths in radiocollared elk between 1 December 1993 and 14 June 1996. Calves (M=male, F=female) were 6-12 months old and collared at 6 months of age. Yearling males and females were 12-18 months old and collared as 6 month old calves. Juvenile males and females were 18-23 months old and collared as 6 month old calves. Adult males and females were .2. 24-months old at time of death. Elk AgelSex Class at Death Total Adult Juvenile Calves Yearl±ng All Cause of Death M F F MF M F F M M Malnutrition Unknown-Suspect Malnutrition Predation-Lion Predation-Bear Unknown Predator Unknown-Suspect Predation Ac'cident-Birthing '....,_/ ') 2 2 0 0 0 0 0 1 2 5 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 0 0 0 Legal Hunting Archery Muzzleloading Archery/Muzzle Rifle-First Rifle-Second .·-· Rifle-Third Rifle-Late 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 1 Wounding Loss Archery/Muzzle Rifle-Regular Rifle-Late 0 0 0 0 0 0 1 Illegal Hunting Rifle-Regul'ar Out-of-Season 0 0 0 0 s• Presumed Hunting Disappear-Rifle Seasons 0 Unkl'lown Cause Totals 0 0 ·o 0 2 2 4 0 1 5 2 3 3 8 1 0 0 1 1 1 1 2 2 0 3 2 5 2 1 5 2 7 0 1 0 1 0 0 0 0 1 0 1 1 1 0 2 4 6 2 2· 4 6 0 0 0 () 0 6 2 4 0 2 4 0 2 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 lb lb 0 0 2 0 0 1 ·o 12 ·9 7 3 1 O· 0 0 0 0 0 0 0 0 0 0 0 0 0 o. .o 5 5 1 8 6 5 1 2 4 2 6 0 3 3 .5 0 0 5 1 1 1 2b 2b 3 3 6 0 0 2 2 3 5 0 22 32 42 44 86 4 3 0 ( ( • These elk were illegally shot as spike-antlered yearling males: (173.190/93), (173.232/93), (173.320/93), (113.919/94), (174.059/94). "Th~ elk disappeared during rifle hunting seasons and are.presumably dead and legally harvested: (17_2.207/93), (172.649/93), (172.800/93), (173.309/93), (173.390/93), (173.439/93). One exception may b-..; spike:..anttered yearling male (173.309/93) that disappeared during the first rifle season in 1994 when spike-antlered bulls were not legal. ( \ \J �( ( Table 4. Estimated causes of mortality and associated body condition for 21 radiocollared calf elk 6-11 14 June 1996. months old, 1 December 1993 Ag~• Body> Marrow. Trap Frequency ID/ t Fat Date Dead Cause of Death & Code No. Sex {months} Wt. {kg} zone Year Ca12tured - 172.899/93 173. 000/93 173. 262/93 173.289/93 173.461/93 173.469/93 173.589/94 173.640/94 173.789/94 173.870/94 174.119/94. 174.140/94 174.170/94 174.220/95 174.230/95 174.240/95 174.339/95 174.500/95 174 .·609/95" 174.689/95 .·174 ;789/95 C G C C H H B C E D F F B F F E E F F M M M M F F F F M M M M M M F C F B o· C F M M 9 10 ·9 9 8 10 12 9 9 86.0 102.0 108.0 111.0 82.0 77.0 117.0 89.0 100.-0 03/18/94 04/25/94 03/18/94 03/22/94 02/07/94 04/25/94 06/01/95 03/30/95 03/20/95 8 86.0 140.0 112.0 140.0 02/21/95 03/01/95 03/14/95 04/25/95 . 127. 0 120.0 115.0 79.0 78.0 120.0 100.0 04/08/96 . o~/24/96 04/17/96 03/27/96 04/16/96 04/15/96 02/05./96 05/22/96 9 9. 10 9 10 10 9 10 10 7 11 • Approximate age at death assuming rs June binhdate. • Whole body weight at capture in December of 1993, 1994, or 1995. c Fat content as percent dry matter of bone marrow from either femur of carcass. • Fat content as percent dry matter of bone marrow from either ~andible of carcass. • Fat content as percent dry matter of bone marrow from either humerus of carcass. 28. 50d 8. 03c 2a. sad 0 .21c 0. 27c 51. 71c 14 ."•71c 94. 97c 64 _44·c 76. osc 41. oac 86. 2ac 62. 97c 34. 56c 10. 2ac 91. 90c 75. 32e Lion Predation-3 Malnutrition-6 Unknown-11 Unknown-11 Malnutriton-6 Malnutrition-6 Unknown; suspect predation-30 Unknown; suspect p:t:edation-30 Unknown; suspect malnutrition-31 Lion Predation-3 Bear Predation-35 Lion·Predation-3 Lion Predation-3 Unknown; suspect malnutrition-31 Lion Predation-3 . Lion Predation-3 Unknown Predator-5 Unknown; suspect malnutrition-31 Malnutrition-6 Lion Predation-3 Unknown; suspect predat;.ion-30 �( ..... 8 Table 5. Survival rates.for the cohort of 6-month old elk calves radiocollared in December 1993 for 6 time periods from. 1 December 1993 through 14 June 1996·when elk were 35 months old. Survival rates for male and female calves pooled when 6-11 months old were. 0.92 (95% CI 0.86-0.98, n=73). Survival rates (S) calculated as a mean estimate of (alive)/{alive + dead) and variance S(l-S)/n collars. Elk Age (months) and Time Period (dates) 12 - 17 18 - 23 24 - 29 30 - 35 6 - 11 6 - 35 06/15/9412/01/9406/15/95.12/01/9512/0l/9312/01/9311/30/94 06/14/95 11/30/95 ~6/14/96 06/14/94 06/14/96 MALES Survival L 95% CI U 95% CI n collars Censored1 Died Nonhunting Hunting 0.89 0.78 0.99 36 0 4 4 0.88 ·o.76 0.99 32 0 4b 1.00 28 0 0 0 0 0 0 4 0.95 0.87 1.00 37 0 2 2 0.97 0.92 1.00 35 0 1' 0 1.00 0 1 0 0.21 0.06 0.37 28c 0 1.00 0.00 o. 00. 3 22d 0 0 0 0 22 3e 0.09 0.00 0.19 33 3 30 4 26 FEMALES Survival L 95% CI U 95% CI n collars Censored1 Died Nonhunting HUiiting 34 0 0 0 0.97 0.91 1.00 34 0 l 0 1 • Censored denotes collar failure and/or anima1 life/death status not known. 1> Collar (173~309/93) "disappeared" during Fall 1994 hunting seasons and assumed dead. ' Includes collar (173.241/93) that failed in August 1995 but bull seen alive Januacy 1996. d Three collars (173..390/93, 173.402/93, 173.439/93) "disappeared" during Fall 1995 hunting seasons and assumed dead. • Three collars censored; (173.241/93) failed, (173.340/93) not heard spring 1996, (173.381/93) slipped off 12/01/95. ' Collar (172.800/93) "disappeared" during Fall 1994 hunting seasons and assumed dead. 0.97 0.9~ 1.00 33 0 1 0 1 0.86 0.98 0.75 37 0 5 2 3 �( ( Table 6. Survival r.ates for the cohort· of 6-month old elk calves radiocollared in December 1994 for 4 time periods from 1 December 199~ through 14 June 1996 and survival rates for the cohort of 6-month elk calv.es radiocollared in December 1995 for one time period .. Survival rates for male and female caives pooleq when 6-·11 months old were 0.90 in 1994 (95% CI. 0.83-0.97, n=69) and 0.88 in 1995 (95% CI 0.81-0.96, n=69). Survival rates (S}calculated as a mean estimate of (alive)/(alive + dead) and variance S{l-S)/n collars. Elk Age (months) and Time Period (dates) • ____________1=9-9-4___C=a=l=f__C=o=h=o=r-t____· _ _ _ _ _ _ 1995 Calf-Cohort 12 - 17 18 - 23. 6 - 24 6 - 11 6 - 11 06/15/~512/01/95-· 12/01/9412/01/9512/01/9411/30/95 06/14/96 06/14/96. 06/14/96 06/14/95 MALES Survival L 95% CI U 95% CI n colla_rs Censored• Died Nonhunting Hunting FEMALES Survival L 95% CI U 95% CI n collars Censored• Died Nonhunting Hunting 0.91 0.81 1.00 0.90 0.79 1.00 33b 30b 0 3 3 0 0 3 0 3 0.89 0.78 0.99 36 0 4 4 0 0.97 0.91 1.00 32 0 1 0 1 0.95 0.87 1.00 22 5c 1 1 0. 0.97 0.90 1.00 30 1c 1 1 0 0.75 0.59 0.91 28 0.86 0.74 0.98 35 5 7 4 3 2d 0.83 Q.70 0.96 35 1 6 5 1 0.91 0.81 1.00 5 5 0 34 0 3 3· 0 • Censored denotes collar failure and/or animal life/death status not known. 11 Includes collar (173.949/94} that failed in December 1994 but male seen alive in January 199~ ' Censored elk were (173.949/94) failure, (173.981/94}~ (174.019/94), (174.090/94), (174.160/95) not heard spring 1996. • Censored elk were (174.619/95}slipped collar, (174.800/95)capture mortality. c Cenosred elk was (173.719/94) slipped collar. _., 0 _., �( ( ( .... 2 Table 7. Survival rates for all radiocollared adult female elk >12-months old during 5 periods from 1 December 1993 through 14 June 1996. Survival rates (S) calculated as a mean estimate of (alive)/(aliye + dead) and variance S (1-S) /n collars·. Elk Age and Time Period (dates) Adult Adult Adult Adult Adult 06/15/94.12/01/9406/15/9512/01/9512/01/9311/30/95 06/14/96 06/14/95 11/30/94 06/14/94 0.87 0.96 0.94 0.95 0.96 Survival 0.90 0.91 0.80 0.92 0.91 L 95% CI 1.00 0.98 0.99 0.94 1.00 U 95% CI 95bg 129bh 68bc 100bf 119 1 n collars 2j 0 0 0 0 Censored• 9d 13c 7 4 3 Died 0 4 1 1 1 Nonhunting 8 3 12 3 2 H~ting • Censored denotes collar failure and/or animal life/death stams unknown. b Includes collar (172.011 /93) that failed 4/ 1994 but seen alive in 1/ 1996 c Collars (172.800/93, 172.649/93) "disappeared" Fall 1994 hunting seasons.assumed dead. 4 Collar (172.207/93) "disappeared" Fall 1995 hunting·seasons, assumed dead. • Composition is 6 females 18+ and 62 females 30+ _months old. r Composed of 35-12+, 6-24+, and 59-36+ months old females. 'Composed of 34-18+, and 61-30+ montho old females. h Composed of 32-12+, 34-24+, and 63-36+-month old females. 1 Composed.of 30-18+ and 80-30+ monthos old females. J Censored (172.011/93) failure and (173.719/94) slipped collar. ·Table 8. Survival rates for the group of adult female elk >12-months old radiocollared in December 1993 for 8 time periods from 1 December 1993 through 14 June 1996. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead). and variance S(l-S)/n collars. Elk Age and.Time Period (dates) • Adult Adult Adult ·Adult Adult Adul-t Adult Adult 12/01/9406/15/9512/01/9512/01/9312/01/9412/01/9306/15/9412/0l/9311/30/94' 06/14/95 11/30/95 06/14/96' 11/30/95 06/14/96 11/30/94 06/i4/94 0.93 0.88 0.93 0.78 0.84 0.58 0.82 0.96 Survival 0.85 0.78 0.68 0.85 0. 75. 0.46 0.72 0.91 L 95% CI 0.88 0.70 0.97 1.00 0.93 0.99 0.91 1.00 U 95%-CI 53b f 68b r . 68bc 67f 65br 53br 49b r 42' n collars 1 11 . 0 .o 0 0 0 1 0 Censored• 29cd 15c 10d 4 · 6d 3 3 Died 6' l· 2 1 0 3 1 .Nonhunting 3 6 0 22 13 9 2 Hunting • Censored denotes collar failure and/or animal life/death stams unknown. 11 Includes collar (172.011/93) failed 4/1994 but seen alive 1/1996. c Collar (172.649/93) "disappeared" Fall 1994 hunting seasons, assumed dead. d Collar (172.207/93) "disappeared" Fall 1995 hunting seasons, assumed dead . .,---- I. \ • Composed of 6-18+ and 62-30+ month old females. r Composed of 100% females 24+ months old. 'Censored (172.011/93) failure of unknown status Spring 1996. �( ( ,, Table 9. Frequency distribution of whole body weights for male and female elk calves trapped in Game Management Unit 42. December. 1993. 1994, and 1995. Percentage per weight class shown in parentheses. Bod~ Weight Class {kg} Year Sex 60-69 70-79 80-89 90-99 100-109 110-119 120-129 130-139 140-149 Total 1993 1994 1995 M M M 0(0.0) 0(0.0) 0(0.0) 1 (2. 9) 1(3.0) 0(0.0) 1(2.9) 1(3.0) 0(0.0) 3(8.6) 2(6.0} 4(11.4) 6·(.17 .1) 6(18.2) 3(8.6) 12(34.3) 13(39.4) 8 (22. 9} 10(28.6) 6(18.2) 9(25.7) 1 (2. 9) . 2(6.0) 10(28.6) 1 (2. 9} 2(6.0) 1(~.9} 35(100) · 33 (100) 35(100) 1993 1994 1995 F F F 0(0.0) 0(0.0) 1(3.1) 1(2.9) 2(5.7) 2(6.3) 4(11.4) 4 (11. 4) 1(3.1) 8(22.9) 7(20.0) 3 (9.4) 12(34.3) 10(28.6) 14(43.8) 4 (11. 4) 10(28.6) 5(15.6) 6(17.1) 2( 5.7) 6(18.8) 0(0.0) 0(0.0) 0(0.0} 0(0.0) 0(0.0) o·(o. 0) 35 (100} 35(100)" 32 (100) Bod~ measurements for elk calves traooed in Game Management Unit 42. December. 1993, 1994·, 1995. Male Calves Female-Calves • Min Mean Max SD Min Max n SD n Mean Measurement Table 10. Year 1993 112.7 13.7 Body Weight (kg) 191.2 10.2 Body Length (cm} Hindfoot Length (cm} 56.3 • 2 .2 Condition Index8 0.59 o.~5 77.0 164.0 52.0 0.43 141.0 210.0 61. 0 0.67 35 36 36 35 103.8 188.9 54.8 0.55 12.2 9.8 2.1 0.05 76.0 167.0 51.0• 0.46 123.0 35 207.0 ·35 59.0 34 0.64 34 1994 113.5 14.2 Body Weight (kg} 190.3 9.2 Body Length (cm) 1.8 Hindfoot Length (cm} 56.9 0. 59. 0.05 Condition Index 71.0 168.0 50.0 o.42 140.0 204.0 59.0 0.69 33 32 32 32 103.0 186.3 55.1 0.55 13.3 8.8 2.1 0.06 70.0 166.0 50.0 0.42 128.0 207.0 59.0 0.65 35 36 36 35 1995 119.1 .13. 6 Body Weight (kg} 194.0 9.3 Body Length (cm} Hindfoot Length (cm} 57.4 2~2 0.61 0.05 Condition Index 92.0 166.0 53.0 0.50 141.0 206 .0. 61.0 0. 71 35 36 36 34· 105.7 189.4 54.9 0.56 -15.2 11.4 2.3 0.06 60.0 158.0 47.0 0.38 129.0 203.0 59.0 0.66 32 34 34 32 71.0 ·1~1.0 103 164.0 210.0 104 SO. O· 6LO 104 0.71 .101 0.42 104.l· 188.2 54.9 0.55 13.5 10.0 2.1 0.06 60.0 158.0 47.0 0.38 129.0 102 207.0 105 59.0 104 0.67 101 115.1 All .. Body Weight (kg) 191.9 Years Body Length (cm) 'Hindfoot Length (cm} 56.9 0.60 Condition Index 14.0 9.6 2.1 0.05 • Condition index= (Weight/body length). ... 8 �104 Table 11. Summary of flights to estimate elk population size and density on 132 mi 2 of winter range in GMU 42 south of Rifle and Newcastle, Colorado, January/March 1996. Total Flight Marked Marked Unmarked • Elk Flight Elk Elk Date Elk Time (hrs) Flight (M/D) Available Counted Counted Counted Quadrat 1, NonRandom 1 NonRandom 2 Quadrat 2 4 Flights Pooled Flight Quadrat 1 NoriRandom 1 NonRandom 2 Quadrat 2 • 1/15-18 1/19.-20 2/29 3/1-3 128 128 137· 137 32 54 80 49 853' 1300 1918 1324 885 1354 1998 1373 19.6 8.5 • 8.0 19.1 154• Marked/ Unmarked 0.0375 0.0415 0.0417 0.0370 Marked/ Marked+Unmarked 0.0362 0.0399 0.0400 0.0357 Proportion of Available Marks Seen {+/- 95% CI) 0.2500 (0.0749) 0.42.19 (0.0~57) 0.5839 (0.0825) 0.3577 (0.0803) --------- ---------------------------------------------------------------- Changes in Total' Elk Observed: Quadrat 1 vs. Quadrat 2: +488 elk or 55% increase over Quadrat 1 NRandom l vs. NRandom 2: +644 elk or·48% increase-over NRandom 1 Changes in Total Marked Elk Observed: Quadrat 1 vs. Quadrat 2: +17 marked elk or 53% increase over Quadrat 1 NRandom 1 vs . NRandom 2 : +2.6 marked elk or 4 8 %- increase over NRandom 1 Marked Elk Deaths: During the population estimate interval (1/15i96 - ·3/3/96), 2. radiocollared elk died: 174.689/95 male calf on 2/5/96 and. 172.070/93 ~dult female on 2/12/96 . . • Marked elk available with inunigration/emmigration·movements involving 41 elk; 25 elk moved onto and 16 moved off'. the intensive • sampling area during the time interval between 1/20/96 and 2/29/96. ") Table 12. Estimates of population size and density for elk on 132 mi 2 of winter range in GMU 42 south of Rifle ~nd Newcastle, Colorado, January/March 1996. Density Pvt. Model Population '. Flights ·95% Conf: Int. Land1 Estimator Estimate /mi2 JHEb 165 4 Flights Pooled 3,168-3,840 26.3 3,47~ IEJHEC 4 Flights Pooled 3, 129-3, 8_07 165 25.9 3,415 BEd Quad l+NonRandom 1 2,764-3,872 24.8 165 3,272 Quad 2+NonRandom-2 BE 3,169-4,130 27.4 165 3,618 4 Flights Pooled 3, 969c 3,621-4,446 IEJHE 4 Fligh~s Pooled 4, 004f BE 3,560-4,504 StRSg Quadrats-1;-'light 1 1,356-2,974 11 16.4 165 2,165 Q~adrats Flight 2 165 StRS 3,175 24.1 2' 205-4' 145 11 • Elk on p(ivate land enumerated by dir~ct counts must be added to p~pula.tion estimate for estimated total elk in the intensive study area. " Joint Hypergeometric Mark-Resight Estimator that"assumes a geographically closed population and homogeneous sighting probabilities of individual elk. • • Immigration/Emigration Joint Hypergeometric Mark-Resight Estimator that allows for mqvement of elk on/off intensive study· area but assumes homogeneous sighting probabilities of elk. d Bow.den Mark-Resight estimator allows for some violation of ,a geographically closed population but allows for heterogeneous sighting probabilities of elk. c Estimate of total pool of elk within which radiocollared elk are distributed on or just off the intensive study area; equates to N' estimate." r Estimate of total pool of elk; equates to fir. • 1 Stratified random sample of qua:drats with counts of elk not adjusted for sighting bias. h 90% confidence intervals. (' u I t �( ,,( ( :! Table 13. Counts of elk on quad.rats during 2 replicate flights in February and March, 1996-in GMU 42 south of Rifle and Newcastle, Colorado. Strata Qyadrats Elk ElklQyadrat Po:eulation Size Size {mi2> n Counted Mean N StdErr. Strata Total± 90% CI Quad.rat Flight 1 10 10 133 26.60 5 16.l07 26_5 Garfield High 266 83· 20.75 16 4 17.970 . 16 332 473 Garfield Low · 8 .80 16 16 5 44 4.023 106 141 E. Divide.Low 6 6 4 23.75 95 11. 800 143 116 w. Div.· East High 10 15. 0,0 10 3 45 6.535 150 107 w. Div. East Low ·3 5 28 5 9.33 5.283 47 43 W. Div. West High 9 3 13 4.33 2.762 9 41 w. Div. West Low 39 8 4 44 11.00 8 4.103 88 Hightower High 54 6 185 30.83 19 19 16.425 586 513 Hightower Low 3 3 15 5.00 0.000 3 15 0 D. Hollow High 3 0 0.00 0.000 9 9 0 0 -D. Hollow Low 5 161 53.. 67 27.282 268 5 3 224 w. Mamm High ,7 65' 3 13.00 3 5.674 7 91 w. Mamm·Low 0 0.00 0.000 0 9 9 3 0 Grass Mesa Low ·16.40 52 885 132 2165 809 Totals 90% Conf. Int ..on Population: 1356 to 2974 90% Conf. Int. as percen~ of estimte·: 37.38% -----------~-------------------------------------------------------------------- --------------------Quad.rat Flight· 2Garfield High Garfield Low E. Divide Low W.·Div. East High W. Div. East Low w. Div. West iiigh W. Div. West Low Hightower High Hightower Low D. Hollow High D. Hollow Low w. Mamm High w. Mamm Low Grass Mesa Low Totals 10 16 16 6 10 5 9 8 19 3 9 5 7 9 132 10 16 16 6 10 5 9 8 19 3 9 5 7 9 5 5 5 4 3 3 3 386 121 34 147 53 149 4 56 41 6 3 3 3 3 3 53 90%' Conf. Int. dn Population: 2205 tc;> 4145 11 6 77 87 16 189 1373 77 .20 24.20 6.80 36.75 17.67 4~L67 3.67 14.00 6.83 2.00 25.67 29.00 5.33 63.00 24.05 38.032 7.976 2.627 9.937 8.030 6.786 1.905 7 .9·21 3.608 0.000 20.957 10.973 1.764 39.466 772 387 10_9 221 177 248 33 112 130 6 231 145 37 567 3175 626 210 69 98 132 56 28 104 113 0 310 90 20 584 970 90% Conf. Int. as percent of estimate: 30.56% .... ~ �108 Table 14. Radiocollared elk captured on winter range in GMU 42 during December 1994 that dispersed out of GMU 42 to a new winter range as of 27 March 1996. Locations (GMUs) determined by aerial telemetry. Trap New Location.Description Age• Sex GMU Frequency Zone 173.621/94 LOWER WEST MUDDY CREEK C 1+ F 521 173.659/94 MCCLURE PASS HIGHWAY C 1+ F 521 DEADHORSE CREEK 173.66.9/94 D 1+ F 521 173.679/94 TERROR CREEK D 1+ F 521 HIGHTOWER MT. BUZZARD CREEK 173. 689/94 E 1+ 421 F 173.699/94 E SMALLEY GULCH 1+ F 421 173.709/94 D DEADHORSE CREEK 1+ F 521 173.719/94 D VEGA RESERVOIR 1+ 421 F 173.739/94 E MCCLURE PASS HIGHWAY 1+ F 521 173.750/94 1+ E LEROUX CREEK F .52 173.760/94 E COLLIER CREEK 1+ F 421 173.799/94 F 1+ MORRISANA MESA F 42 West 173.829/94 PARACHUTE, WALLACE CREEK F 1+ F 42 West 173.840/94LE MCCLURE PASS HIGHWAY 1+ F F 521 173.859/94 D TERROR CREEK 1+ F 521 173.990/94 C PAONIA RESERVOIR 1+ M 521 BUCK.MESA SOMMERSET 174.030/94LE E 1+ M 521 174.039/94 E HAWXHURST CREEK 1+ M 421 174.049/94 F VEGA RESERVOIR 1+ M 421 174.069/94 E HUBBARD CREEK 1+ M 521 174.080/94 E HAWXHURST CREEK 1+ 421 -~ .• M 174.109/94LE F 1+ GRASSEY GULCH 421 174.129/94 F 1+ LEROUX CREEK M 52 174.150/9:4 F 1+ PORCUPINE CREEK F 42 West 174.181/94 B 1+ LOWER EAST MUDDY CREEK M 521 1 Age of elk in years as of March 1996 b LE= Location elk rout~nely located. ( ( �107 ~ ( \..I ) ( \-.I Appendix I. Mortalities of 86 radiocollared elk from 1 ·oeceniJer 1.993 through 14 June 1996. Age is approximate age in years of elk at death; c=calf 6-12 months old, Y=yearling 12-18 months old. Body weight measured in December when elk caetured as calves. Frequency ID/ !;!ate Trae Bodi Site Zone Sex Ase \IT. ,ksl Heard Dead cause- of Death &Code Nunber Year caetured Legal harvest rifle season-28 BR A 172.030/93 5+ 10/27/95· F Unknown; suspect predation-30 GR B 2+ 06/14/95 172.039/93 F Unknown-11 A 02/12/96 172.070/93 BR F 11 Legal harvest rifle season-28 172.080/93 GM 11/05/94 A F 5+ Wounding loss late rifle season-26 172.090/93 01/16/94 GR B F 11 Wounding loss rifle season-25 172.139/93 BC C 10/19/95 F 17 Legal harvest rifle season-28 cc 2+ 10/23/94 172.160/93 C F Woun<Hng loss rifle season-25 • 172.181/93 11/03/94 MC C F 3 Wounding loss rifle season-25 172.201/93 11/15/94 GS C 3 F Disappear rifle season-22 172.207/93 SG 11/30/95 D F 2+ Legal -harvest archery/muzzle season-27 172.258/93 HY 10/04/94 C F 2+ Wounding loss archery/muzzle season-24 GS 10/04/94 112.2n193 C F 3 Legal harvest· rifle season-28 172.290/93 SG D 10/23/94 F 5+ Legal harvest archery season-33 172.369/93 AC E 09/18/94 F 2+ Legal- harvest late rifle season-29 172.369/94 FM 2+ 01/14/96 B F Wounding loss late rifle season-26 AC E 12/29/94 172.409/93 F 8 Legal ·harvest rifle season-28 FS 172.509/93 10/21/95 H F 3 Lion predation-3 FS 172.542/93 02/01/94 H F 6 Legal harvest late rifle season-29 5+ 172.549/93 PG H 11/28/95 F Wounding loss rifle season-25 PG 172.570/93 11/03/94 F 16 PG· Legal harvest rifle season-28 172.581/93 2+ 10/17/94 F Legal harvest late rifle season-29 FM 12/08/95 172.581/94 F 2+ Unkncwn-11 2+ 172.590/93 PG 04/24/96 F Accident; birthing/calving-32 172.610/93 10/04/94 PG F 3 Accident; birthing/calving-32 172.639/93 06/19/96 PG F 16 Disappear rifle season-22 172.649/93 PG 11/30/94 F 2 Legal harvest late rifle season-29 172.670/93 PG 01/16/95 F ·4 Wounding loss late rifle season-26 172.678/93 PG 12/22/94 F 9 Illegal kill-7 172.690/93 FM F 8 01/?4/94 Legal harvest rifle season-28 172.699/93 FM 5+ 11/05/95 F y Disappear rifle season-22 . SR 172.800/~ F 105.0 11/30/94 Lion predation-3 172.899/93 BC C C 86.0 03/18/94 F Legal harvest rifle season-28 GH 172.950/93 D 2 107.0 10/18/95 F Malnutrition-6 173.000/93 \lM G C 102.0 04/25/94 F Legal harvest rifle season-28 173.041/93 GM A M 2 107.0 10/19/95 Legal harvest -late rifle season-29 173.060/93 MH E 99.0 12/27/95 F 2 Legal harvest rifle season-28 173.120/93 GM A 99.0 10/14/95 M 2 Illegal kill rifle season-9 173.190/93 BC C 111.0 10/29/94 M y Wounding loss rifle season-25 GR 173.201/93 106.0 11/30/95 B M 2 Legal harvest rifle season-28 173.210/93 GC B M 2 108.0 10/19/95 Legal harvest rifle season-28 173.219/93 BC 111.0 11/06/95' C M 2 Illegal kill rifle season-9 173.232/93 BR A M y 101.0 11/15/94 BC Unknown-11 173.262/93 C ·108.0 03/18/94 M C Legal harvest rifle season-28 173~269/93 MC C M 2 121.0 11/06/95 • 173.289/93 MC C 111.0 03/22/94 .Unknown-11 M C 173.300/93 Legal harvest rifle season-28 GS C 119.0 10/24/95 M 2 Disappear rifle season-22 173.309/93 HY C M y -124.0 11/30/94Illegal kill rifle season-9 173.320/93 HY C 118.0 10/20/94 M y 1.egal harvest muzzleloading season-34 173.332/93 GH D M 2 125.0 09/12/95 SG Legal harvest rifle season-28 173.351/93 D .M 2 103.0 11/05/95 Legal harvest archery season-33 173.359/93 AC E 111.0 09/06/95 M 2 Legal harvest rifle season-28 173.370/93 MH E . 141.0 11/08/95 M 2 Disappear rifle season-22 173.390/93 MG D 113.0 11/30/95 M 2 ·Legal harvest rifle season-28 MG 173.402/93 D 2 M 118.0 10/18/95 Wounding loss rifle season-25 173.410/93 WM G M 2 90.0 11/02/95 Legal harvest rifle season-28 173.420/93 G WM 125.0 10/24/95 M 2 _Legal harvest archery season-33 173.429/93 MH .E M 2 126.0 09/14/95 173.439/93 PG H .M 2 o.o 11/30/95 Disappear rifle season-22 Legal harvest rifle season-28 173.450/93 PG H M 2 113.0 10/15/95 173.461/93 Malnutrition-6 PG H M C 82.0 02/07/94 173.461/94 CM A M y 123.0 09/19/95' Wounding loss archery/muzzle season-24 . 173.469/93 FS H M C n.o 04/25/94 Malnutrition-6 173.479/93 Legal harvest archery ~eason-33 FS H M 2 122.0 09/10/95 Legal harvest archery season-33 173.492/93 FS H M 2 110.0 09/03/95 Legal harvest archery season-33 FM 173.510/93 B M 2 91.Q 08/28/95 Legal harvest rifle season-28 173.521/93 FM B M 2 124.0 10/17/95 Legal harvest archery season-33 173.549/94 HM B F y 106.0 09/07/95 y Unknown-1l PR 173.580/94 A 114.0 12/21/95 F -----------------------------------------------------------. -------. -----------------·---------- �108 ~ Appendix I. Frequency ID/ Year Captured 173.589/94 173.640/94 173.789/94 173.870/94 173.919/94 174.059/94 174.101/94 174.119/94 174.140/94 174.170/94 174.220/95 174.230/95 174.240/95 174.339/95 174.500/95 174.609/95 174.689/95 174.789/95 Continued. Trae Date ~ sue Zone Sex Age \IT. Ckg> Heard Dead cause of Death OG -B MC MR C SM D BC MR MM MM MM C FM MS MS MO MO LB GB AP w E E F F f. B F F E E C B D C F F F F M MM M M M M M M F F F M M C C C C y y Y+ C C C C C C C C C C C 117.0 06/01/95 89.0 03/30/95 100.0 03/20/95 86.0 02/21/95 114.0 11/02/95 126.0 "10/17/95 117.0 05/24/96 .140.0 03/01/95 112.0 03/14/95 140.0 04/25/95 127.0. 04/08/96 120.0 . 04/24/96 115.0 04/17/96 79.0 03/27/96 78.0 04/16/96 120.0 04/15/96 100.0 02/05/96 0.0 05/22/96 Unknown; suspect predation-30 Unknown; suspect predatfon-30 Unknown; suspect malnutrition-31 Lion predation-3 Illegal kill rifle season-9 Illegal kill rifle season-9 Unknown; suspect predation-30 Beer predation-35 Lion predation-3 Lion predation .. 3 Unknown; suspect malnutrition-31 Lion predation-3 Lion predation-3 Unknown predator-5 Unknown; suspect malnutrition-31 Malnutrition-6 Lion predation-3 . Unknown; suspect predat i on-30 ( L -o-···_1ii_ 1 :' .. :i \;~:g)'., • �47 Colorado Division of Wildlife Wildlife Research Report July 1997 JOB PROGRESS REPORT State of Colorado Project No. W-153-R-10 Mammals Research work Plan No. - -><-- - -- -- - - - - Elk Investigations Job No. _ _ _ _.,___ _ _ _ _ _ _ _ _ __ Estimating Survival Rates of Elk Developing Techniques to Estimate Population Size Period Covered:; Author: July 1, 1996 - June 30, 1997 D. J. Freddy Personnel: J. Broderick, G. Byrne, J. Ellenberger, D. Fox, J. Frothingham, V. Graham, D. Masden, C. Mehaffy, M. Okata, J. Ritchie, P. Will, R. Winn, CDOW; D. Bowden, G. White, CSU; Diagnostic Laboratory, CSU; N. Miers, D. Ouren, volunteers; BLM Glenwood Springs, CO, NBS Ft. Collins, CO, USFS Rifle, CO, Rocky Mountain Elk Foundation, cooperating . Abstract We captured and radio-collared 70 calf elk (Cervus elaphus nelsoni) 6-months old in December 1996 to estimate survival rates during winter 1996-97 and to increase numbers of radiocollared elk available for experiments utilizing mark-resight models to estimate population density. Elk were captured using helicopter net-gunning and portable corral traps. Survival rates(± 95% CI) for 6-11 month old calves during winter-spring averaged 0.89 ± 0.04 with yearly rates ranging from 0.86 to 0.92 between 1993-94 and 1996-97. Survival was similar among years (P > 0.50) and sexes (P > 0 . 50). Primary causes of death for calves were suspected predation (58%) and suspe cted malnutritio n (26%) . Survival of adult females(~ 12 months old) during winter-spring averaged 0.96 ± 0.02 and was similar among years (P > 0 . 60) with yearly rates ranging from 0 . 94 to 0.98 between 1993-94 and 1996-97 . Hunting was the primary cause of death (59%) for adult females during winter-spring. Survival of elk 18-23 -months of age during winter-spring averaged 0.97 ± 0.03 for males and 0.97 ± 0.04 for females. Annual survival (1 December-30 November ) of adult females averaged 0.81 ± 0 . 06 from 1993-94 through 1995-96 and survival was simi lar among years (P > 0.50) with hunting accounting for 81% of the deaths . Survival during summer-fall for adult females averaged 0.90 ± 0.03 with hunting accounting for 95% of the deaths. Survival during summerfall for elk 12-17 -months of age averaged 0.87 ± 0.07 for males and 0.94 ± 0.05 for females with all deaths attributed to hunting . Surviv al during summer-fall for male elk 24-months old averaged 0.15 ± 0.10 with all deaths due to hunting. Elk population size in 1997 was 1,854 ± 194 (95% CI) based on random quadrat sampling and 3,610 ± 641 based on the JHE pooled mark-resight estimator. These estimates were different (P < 0.05) and continued the disturbing trend of quadrats estimating only 51-93% of the numbers of elk estimated by mark-resight estimators. Adjusting quadrat estimates with �48 sightin g bias formulas did not meaningfully narrow differences observed between quadrats and mark-resight estimators. Discrepancies in estimators reflect the possibility that we may be violating major assumptions(s) underlying either mark-resight or quadrat theory. We believe further field testing to evaluate potential sources of bias will be necessary to evaluate these techniques to estimate population size. ✓ �49 JOB PROGRESS REPORT ESTIMATING SURVIVAL RATES OF ELK AND DEVELOPING TECHNIQUES TO ESTIMATE POPULATION SIZE David J. Freddy P. B, OBJBCTXVB Estimate survival rates of adult female and calf elk and develop techniques to estimate population size. SEGMENT QBJICZXDI 1. Radio-collar 35 male and 35 female calf elk in December 1996 in GMU-42. 2. Estimate winter and annual survival rates of calf and previously radiocollared adult female and male elk from known fates of radiocollared animals. 3. Estimate density of elk in a portion of GMU-42 using 4 helicopter flights involving 2 nonrandom mark-resight flights and 2 flights using a random quadrat sampling system. Apply sighting bias corrections to adjust numbers of elk counted on quadrat flights. compare bias adjusted quadrat estimates with mark-resight estimates based on numbers of marked elk seen during all 4 flights. 4. Analyze data and summarize annually in Federal Aid Job Progress reports. 5. Prepare draft of manuscript on sighting bias models developed from data collected in 1994 and 1995. 6. Continue to monitor locations and movements of selected radiocollared elk. INTRQDUCTXOB our _objectives are to provide reliable estimates of survival rates for calves during winter and for adult females and males throughout the year for· the period 1993-94 through 1996-97. For adults, we are especially interested in survival rates inclusive ~f hunting mortalities which reflects human-induced rates of removal and exclusive of hunting mortalities which reflects natural rates of survival. Additionally, we will develop and test a system for estimating population size that will incorporate estimates of sighting bias in conjunction with a random sampling system using search quadrats as sample units. our winter study area encompasses about 839 lan2 (324 mi2 ) in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado. Elk winter range vegetation types include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambeliiAmelanchier aJ.nirolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields (Freddy 1993, 1994). METHODS Cftpt;ura apd Markip,g we placed radio collars (172-176MHz) having mortality sensors on 70 6-month old calves, of which 35 were males and 35 were females. Calves were trapped �50 from 7-10 Deceml:>er 1996 using helicopter net-gunning. Helicopter capture ~ccurred at 10 remote sites located primarily on public lands. Trapping effort was allocated among 8 geographic trap zones to assure that radioed elk were representative of most if not all se~ents of the population (Table·l). Radio collars were of the same type used in previous years (Freddy 1994). V Calves captured by net-gunning were ferried by helicopter to processing points usually within 1.6 Jan of capture sites. At processing points, body weight, total body length, hind foot length, and rectal body temperature (F) were measured and calves were then radio-collared and released. Body measurements for calves were compared between sexes and years using Proo FREQ and GLM (SAS 1988). sury,iya1 We monitored life or death status of radioed elk during daily ground surveys and aerial surveys conducted at.2-4 week intervals from December 1996 through April 1997 and via aerial surveys at 2-4 week intervals from July to November 1996 and May to June 1997. Life or death status of all calves radioed in December 1996 (70) was known for the period 7 December 1996 through 14 June 1997 which is the time period over which survival rates for calves, age 6-11 months, are calculated. On 15 June, calves by definition become 12-mon~h old yearlings. Life or death status of 151 female and male elk previously collared in December 1993-1995 that had survived to 14 June 1996 was known for 148 of these elk through 15 June 1997. survival ·rates (S) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) = S(l-S)/n (White and Garrott 1990). Survival rates are expressed as the mean estimate± the 95% confidence interval. We used x2 -contingency tests to compare survival rates. We defined 4 major time intervals for survival analyses: winter-spring was 1 December to 14 June, summer-fall was 15 June to 30 November, annual was 1 December to 30 November to coincide with timing of capture and radiocallaring, and yearly, only for yearling elk aged 12-23 months, was 15 June to subsequent 14 June. V Causes of death were estimated from multiple sources of evidence including: presence or absence of gunshot wounds, presence or absence of bite wounds on carcass and predator tracks or scat at carcass site, physical positioning of carcass remains whether buried, covered, scattered, or consolidated, relative amount of internal fat and marrow fat if present with carcass, and results of histopathology and marrow fat analyses (Wade and Browns 1982, Halfpenny and Biesiot 1986). Fat content (percent dry matter) of bone marrow and estimates of age based on dental cementum were obtained for dead elk by the COlorado Division of Wildlife Laboratory while histopathology analyses were provided by the Colorado State University Veterinary Diagnostic Laboratory. Photographs were taken of nearly all mortalities so that physical evidence could be reviewed and judged by outside experts (pers. comm. A. Anderson, T. Beck, w. Andelt). • • Pgpu1at,ion 11t,imates We continued to evaluate methods to estimate elk population size or density during winter in that portion of GMU 42 from East Alkali Creek west to Grass Mesa, south of Rifle, co. In previous years, 951 confidence intervals about population estimates based on quadrat sampling exceeded± 301 of the estimated population size. We addressed this problem by refining strata boundaries and \...,,) �51 by sampling 100\ of those quadrats in high density strata, effectively reducing sampling error to 0 in these high density strata. About 30% of the quadrats in low density strata were randomonly sampled which was similar to previous years. With this strategy, we selected 72 quadrats in 15 strata . representing a 53% sample of the 137 mi 2 (351 Jan2 ) winter range (Table 14). As in winter 1996, each potential quadrat was ·rated as high or low in expected density, individual quadrat boundaries remained unchanged from previous years and were based on topographic features, and quadrats were about 1 mi2 (2.6Jan2 ) in size. We felt this strategy to increase numbers of quadrats flown during 1 flight, instead of flying 2 replicates of a smaller sample of quadrats per flight as originally planned, would be more cost-effective in addressing problems of precision. We counted elk during 3 flights using a Bell-Soley helicopter having a pilot, observer, and navigator-observer, all of whom could potentially detect elk during surveys. One flight per day was flown on 10 and 13 February 1997 to count as many marked and unmarked elk as possible encountered along a nonrandom route within the 137 mi2 area with flying time limited to about 7.5 hours per flight. On 11 and 12 February, marked and unmarked elk were counted on quadrats. Two helicopters were used each day and assigned to different strata to shorten the total time interval over which quadrats were completed. Total flight time for both helicopters was 29 hours. Pilots were common to all 3 flights. The primary observer on nonrandom flights did not participate in quadrat flights. The navigator-observer for the nonrandom flights was 1 of 3 primary observers used on quadrat flights while navigator-observers for quadrat flights only flew quadrats. On February 11 and 12, fixed-wing flights were conducted to confirm locations of 223 radiocollared elk to determine whether these elk were within or outside of the 137 mi2 sample area. We generated estimates of population size for each individual flight and 3 flights pooled using several mark-resight estimators in program.NOREMARK (White 1996). We considered estimates based on a11· 3 flights pooled to be our best estimate of population size and the benchmark against which estunates based on quadrat sampling would be compared. Estimates of population size based.on stratified random quadrat sampling were computed using program DEAMAN (COlo. Div. Wildl. software). We then applied a sighting bias correction formula to each group of elk counted on each quadrat, resulting in adjus~ed counts per quadrat, and recalculated populations estimates based on quadrat sampling. To correct for negative sighting bias, we used a s~ple 2 parameter formula to correct for the probability of detecting an individual group: Ycc:orrectedCJrOup size> = l.1619(Log Group Size(countec1>) + 0.0806 (Freddy 1995). Movements We continued to locate selected radioed elk at least once per month since capture to document seasonal movements via telem~try using a Cessna 185. These elk were originally selected at random from within trap zones ·and equalized by age class in January 1994. Elk from the original sample that died were replaced each subsequent January primarily with randomly selected 6 month-old calves of the same sex from the same trap zone(s) as elk that died. As of 1 January 1997, these 44 elk were classified as 23 adult females, 4 yearling females, 5 female calves, 1 adult male, 5 yearling males, and 6 male calves. Durlng June 1997, we again located an additional 28 adult females, that were originally selected at random in 19.95, to document locations during the calving period. Females from the original sample that died were replaced each subsequent June with adult females randomly selected from the same trap �52 zones of elk that died. movements. As needed, we located other elk to document unusual RESULTS ANP pxscussJoR V capture There were no acute deaths of calves during capture. One male calf (174.619/96) died within 14 days of capture due to the effects of capture myopathy (histopathology, CSU Diagnostic Lab) and was subsequently censored from survival analyses ~Table 3). suryiyal Between 1 December 1993 and 14 June 1997, 146 radiocollared elk died (Table 2, Appendix 1). Hunting was apparently involved in 71% of the deaths. For adults ~12 months old, hunting accounted for 901 of 115 deaths. There were 2 periods of mortality during the year. Adults died primarily from September to January when hunting seasons occurred (Fig. 1) while calves died primarily from February to May (Fig. 2). calves survival for calves during winter-spring averaged 0.89 ± 0.04 (n = 280) with yearly rates ranging from 0.86 to 0.92 (Table 3). We failed to detect differences in survival of calves among years (X23 = 1.5, P >0.50), between sexes pooled among years (X21 = 0.43, P >0.50), and between sexes within each yearly cohort (x21 ~ 0.79, P > 0.40) (Tables 3, 5, 6, 7). Sex of dead calves for all years was 17 male and 14 female (Table 2). These survival rates were associated with winters considered mild in temperature. Snow was usually low or moderate in depth except in 1995 when considerable snow fell during March and April but usually melted rapidly at lower elevations, and in 1997 when a storm in January delivered at least 40 cm of snow on lower elevation winter ranges. Rain in January 1997 subsequently settled this snow to about 25 cm and caused severe crusting of snow. Elk in some segments of the lower winter range moved in excess of 24 Jan to·areas at even lower elevations along the Colorado River near Rulison and Parachute, co soon after this storm occurred. Survival rates of elk, however, remaineq high and apparently were not greatly affected by this weather event. Primary causes of death for all calves during winter-spring were malnutrition (131), suspected malnutrition (13%), mountain lion predation (35%), suspected predation (23%), and unknown cause (10%) (Tables 2, 4). Timing of deaths peaked in March and April for both males and females (Fig. 3). Deaths attributed to predation occurred from January into June and those attributed to malnutrition occurred from February to May (Fig. 2) but both presumed causes of mortality peaked in March and April suggesting a functional change in vulnerability of calves during these months. However, percent fat content in marrow of calves lost to predation and malnutrition suggested that malnutrition may not have predisposed calves to predation. Percent fat in bone marrow of calves suspected of dying from predation was 69 for.males (range 2-95, n = 10) and 36 f~r females (range 8-63, n = 8) and for calves dying from suspected malnutrition, 11 for males (range 0.2-41, n = 4) and 18 for females (range 8-31, n = 3) (Table 4). Possibly elk become more sedentary during March and April to conserve energy reserves and thus more predictable in behavior allowing predators, especially mountain lions, to hunt calves efficiently. V �53 Calf Body Size Averaged over all years, male calves had larger body weights, longer total body length, longer hind leg lengths, and higher condition indexes (PS 0.023) than female calves (Tables 11, 12). Differences in body size were greatest for weight, as males (115 kg) were about 81 larger in mass than females (106 kg). Differences between sexes in other body dimensions were <31. This advantage in mass, however, did not translate into higher rates of survival for male calves. Bddy weights were largest for males in 1995 (119 kg), for females in 1996 (110 kg), and for sexes combined in 1995 (113 kg) (Table 12), but we failed to detect differences in body weights among years (P = 0.15) and there was no interaction between year and sex (P = 0.34). Increases in weights in 1995 were not unexpected as the locally moist summer was favorable to forage production on summer ranges. Weights measured at capture in December for calves suspected of dying from predation (Table 4) averaged 116 kg for males (range 72-140 kg, n = 9) and 96 kg for females (range 78-120, n = 10). Predators thus appeared to take males of average and females of smaller than average size (Table 12). Weights of calves suspected of dying from malnutrition (Table 4) averaged 93 kg for males (range 77-127, n = 5) and 101 kg for females (range 100-102, n = 3). Malnutrition thu~ appeared to affect smaller than average sized males and females (Table 12). Weights of calves dying from all causes aver-aged 108 kg for males (range 72-140, n = 16) and 97 kg for females (range 78-120, n = 14) (Table 4), which was about 71 below average weights at capture for both sexes. Yearlings Yearly survival for elk 12-23 -months of age was 0.84 ± 0.08 for males (n = 90) and 0.91 ± 0.06 for females (n = 97) when averaged among years with hunting deaths included (Tables 5, 6, 7). Survival among years for males ranged from 0.79 to 0.88 and for females from 0.81 to 0.97. We failed to detect differences in yearly survival rates among years for males (X22 = 0.88, P > 0.50) but survival was lower (0.81) for females in 1996-97 (X22 = 5.75, P = 0.06). Yearling males were subjected to about the same rate of illegal hunting during all years which accounted for most of the male mortality, while in 1996-97, females had a lower survival rate because 5 of 6 deaths were hunting related (Tables 5, 6, 7). With hunting deaths included, we failed to detect differences in survival between sexes within (x\ s 2.25, P > 0.15) and among years (x\ = 1.71, P > 0.25). Of 23 deaths, 19 (831) were hunting related. Bunting deaths involved 12 males of which 9 (75%) were classified as illegal kills (Table 2). • Yearly survival for elk 12-23 -months of age was 0.97 ± 0.03 for males (n = 79) and 0.98 ± 0.02 for females (n = 91) when averaged among years with hunting deaths censored (Tables s, 6, 7). Survival among years for males ranged from 0.96 to 1.00 and for females from 0.97 to 1.00. We failed to detect differences· in yearly survival rates among years for males (X22 = 1.14, P > 0.50) and for females (x22 = 1.23, P > 0.50), and between sexes within and among years· (x\ s 0.007, P > 0.90). survival during summer-fall for yearling elk 12-17 -months of age was 0.87 ± 0.07 for males (n c 91) and 0.94 ± 0.05 for females (n = 98) when averaged among years ·and inclusive of hunting deaths, and 1.00 for both males (n = 79) and females (n = 92) with hunting deaths censored (Tables 5, 6, 7). survival among years for males ranged from 0.83 to 0.90 and for females from 0.87 to �54 0.97 inclusive of hunting mortalities. We failed to detect differences in survival rates among years for both males (X22 = 0.70, P > 0.50) and females (x22 = 3.63, P > 0.20) inclusive or exclusive of hunting deaths. Survival rates of females (0.94) were higher than males (0.87) when averaged among years and inclusive of hunting deaths (x2 1 = 2.73, P = 0.10). There were no non-hunting deaths during summer-fall for either males or females (Table 2). V survival during winter-spring for yearling elk 18-23 -months of age was 0.97 ± 0.03 for males (n = 78) and 0.97 ± 0.0.04 for females (n = 91) when averaged among years and inclusive of hunting deaths, and 0.97 ± 0.93 for males (n = 78) and 0.98 ± 0.03 for females (n = 90) wi~h hunting deaths·censored (Tables 5, 6, 7). We failed to detect differences in survival rates among years for both males (X22 = 1.16 P > 0.50) and females (X22 < 2.59, P > 0.30) inclusive or exclusive of hunting deaths. We also failed to detect differences in survival rates between sexes within and among years inclusive or exclusive of hunting deaths (X2 1 < 0.24 P > 0.50). During winter-spring, there were 2 nonhunti~g deaths each for males and females and 1 illegal hunting death for a female (Table 2). Yearling spike-antlered males were·generally not legal quarry during hunting seasons. In 1994, 32 yearling males from the 1993-94 calf cohort entered the hunting seasons presumably as spike-antlered males and 4 (131) were illegally taken during rifle seasons. In 1995, 30 yearling males from ~he 1994-95 calf cohort entered the hunting season and 2 (71) were illegally taken and 1 (31) was fatally wounded during archery season in an area where the elk was legal quarry. In 1996, 29 yearling males· from the 1995-96 calf cohort entered the hunting seasons and 4 (14%) were illegally taken during rifle seasons and 1 (3%) was an assumed wounding loss during rifle seasons because the animal had a 3 x 3 antler point configuration that may have resembled a legal branchantlered male (Tables 2, 5, 6, 7). • V Adult Females Survival during winter-spring for all adult females ~12-months of age was 0.96 ± 0.02 (n = 409) when averaged among years and inclusive of hunting deaths and 0.98 ± 0.01 (n = 399) with hunting deaths censored. Survival among years ranged from 0.94 to 0.98 and from o.·97 to 0.99, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (X23 = 1.93, P >= 0.50) or exclusive (X23 = 2.85, P > 0.60) of hunting mortalities (Table 8). There were 17 winter-spring deaths, of which 10 (591) involved hunting: 5 were killed and 3 were wounded during rifle late-seasons and 2 were illegally shot out of hunting seasons (Table 2)'. Seven natural deaths were attributed to mountain lion predation (1), suspected predation (2), complic~tions while calving (1), and unknown cause (3) (Table 2). survival during summer-fall for all adult females ~12-months of age was 0.90 ± 0.03 (n = 372) when averaged among years and inclusive of hunting deaths and 0.99 ± 0.01 (n = 337) with hunting deaths censored. Survival among years ranged from 0.87 to 0.94 and from 0.99 to 1.00, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (X22 = 3.31, P > 0.15) or exclusive (x22 = 1.24, P > 0.50) of hunting mortalities (Table 8). Hunting was involved in 35 (95%) of 37 summer-fall deaths: 24 were killed, 8 were wounded, and 3 disappeared during archery, muzzleloading, and rifle seasons. Natural deaths were attributed to suspected predation (1) and complications while calving (1) (Table 2). At the beginning of hunting seasons in fall 1994, 1995, and 1996 V · �55 there were 99, 129, and 142 radiocollared adult females (~12-months of age), respectively, available to hunters (Table 8, non-hunting deaths censored). Percent of marked elk removed by all types of hunting-related mortalities averaged 101 annually (range= 6-12). Annual survival for adult females ~12-months of age marked as a cohort in December 1993 was 0.81 ± 0.06 (n = 163) when averaged among years and inclusive of hunting deaths and 0.96 ± 0.04 (n = 138) with hunting deaths censored. Survival among years ranged from 0.78 to 0.88 and from 0.92 to 0.98, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (X21 = 0.19, P > 0.50) or exclusive (x21 = 0.15, P > 0.50) of hunting mortalities (Table 9). For this cohort of adult females, hunting was involved in 25 (81%) of 31 deaths during all years: 13 were killed, 9 were wounded, and 2 disappeared during archery, muzzleloading, and rifle seasons and 1 was illegally killed out of hunting seasons. Natural deaths were attributed to mountain lion predation (1), suspected predation (1), and complications while calving (2). Adult Males Survival during summer-fall for all adult males 24-months of age was 0.15 ± 0.10 (n = 53) when averaged among years and inclusive of hunting deaths and 1.00 (n = 8) with hunting deaths censored. Survival among years ranged from 0.08 to 0.21 inclusive of hunting mortalities. We failed to detect differences in survival among years (x2 1 = 1.86, P > 0.20) (Table 5, 6). All deaths were attributed to hunting. At 24-months of age, males are branchantlered and therefore become legal quarry for hunters. Two of 4 males that lived to be 36-months old survived their second hunting season as legal quarry. Survival during winter-spring for adult males >30-months of age was 1.00 (n = 8) during all years (Tables 5, 6). There were no non-hunting deaths of adult males. Hunting was the cause of mortality among male elk ~24-months of age. From the 1993-94 cohort of 36 male calves, 28 (78%) lived to become 24-month old ·branch-antlered males and enter the 1995 hunting seasons. Of these 28, 22 (791) were harvested in 1995 inclusive of 2 that disappeared during hunting seasons and 2 wounding losses (9% of 22). From the 1994-95 cohort of 33 male calves, 25 lived to 24-months and entered the 1996 hunting seasons. Of these 25, 23 (921) were harvested in 1996 inclusive of 2 that disappeared during hunting seasons, 1 illegally taken during rifle season, and 1 wounding loss (41 of 23). Regular rifle seasons accounted for 33 (701) of the hunting mortalities (Table 2). Most 24-month old males were harvested in the Grand Mesa DAU or in adjacent GMU 43. Exceptions were 3 males killed in GMUs 63 and 52 about 160 Jan south of where these males were captured as calves in GMU 42. The differential impact of hunting on survival and recruitment of males and femal~s to young adult age classes is demonstrated by net survival rates of calf cohorts. For 1993-94 and 1994-~5 calf cohorts, net survival from 6 to 36 months of age averaged 0.09 for males and 0.80 for females (Tables 5, 6). Survival Rates and Population Modeling We incorporated estimates of survival rates, population size, and composition into a simple spreadsheet model to assess potential for population growth or decline (Table 13). We used natural survival rates (hunting deaths censored) �58 for summer-fall and winter-spring time periods for adult males, yearling males, adult females, yearling females, and calves. Hunting deaths were incorporated as ha~vest removal rates for each sex/age class. We assumed survival of calves o-s months of age during summer was 1.0 because the model uses post-season calf:cow ratios ·(measured in January) as an estimate of net calf recruitment to the beginning of winter (December). We also assumed that the recruited sex ratio calves to December is 1:1. Modeling suggests that if harvest rates of antlered elk remained as measured and harvest rates of antlerless elk were reduced to 0, the population could grow at an annual rate of 17%. Current rates of ant~erless harvest allow annual growth rates of 71. To stabilize population growth, harvest rates on antlerless age classes must increase nearly two-fold. Obtaining this level of harvest could be a formidable management challenge. Pqpulation Estimates Elk population size in 1997 was 1,854 ± 194 (951 CI) based on quadrat sampling and 3,610 ± 641 based on the JHE pooled mark-resight estimator (Tables 14, 15, 16). The quadrat sample was lower than the JBE estimate (P s 0.05). We achieved our primary goal of improving precision of the quadrat estimate to facilitate detecting differences in quadrat and mark-resight estimators (Table 16). A disturbing trend has emerged in estimates of population size during the last 3 years. Quadrats provided estimates of size that represented only 51 to 931 of the numbers of elk estimated by pooled mark-resight estimators, excluding initial and preliminary quaclrat sampling in 1995 when the quadrat estimate was 39% of the mark-resight estimate. Mark-resight estimates have ranged from 3,177-3,924 elk based on pooled or individual flights while quadrat estimates have ranged from 1,854-3,387 elk (Table 16). The consistent magnitude in discrepancy among mark-resight and quadrat estimates was demonstrated well in 1997 as the 3, one-sample Lincoln-Peterson mark-resight estimates, whether based on marked and unmarked elk counted on nonrandom flights or on quadrats, were 3,289-3,924 elk while the estimate based on stratified quadrat sampling was 1,854 elk (Table 16). The 3 mark-resight estimates were based on 3 flights that were independent in methodology, strongly suggesting that the probability of detecting marked elk is consistent among different combinations of observers and types of flight patterns. A similar trend among estimates occurred in 1996 (Table 16). We adjusted quadrat estimates for sighting bias using a simple 2 parameter sighting bias model. Adjusting for sighting bias increased quadrat estimates only 7-14% (Table 16). Using more complex sighting models did not meaningfully narrow the differences observed between quadrat and mark-resight estimates. Discrepancies in estimators reflect the real possibility that we may be violating a major assumption(s) underlying either mark-resight estimators or quadrat sampling with sighting bias corrections. Three important potential sources of bias are: 1) detecting and accurately counting groups of elk but missing marked elk within detected groups would inflate mark-resight estimates, 2) overestimating numbers of marked elk within the sample area at the time of flights would inflate mark-resight estimates, and 3) detecting a lower than expected percentage of elk groups on quadrats would deflate quadrat estimates. If bias 1) is true, we suggest that behavior of marked elk when approached by a helicopter would be different than other elk in the same group V �57 with the possibility that marked elk either do not move with the group when the group is initially disturbed or they move away from the group reducing the chances of observers seeing marks. Another possibility is that some fraction of the white collars used as marks were not visible due to discoloration but we tend to discount this possibility because collars that were returned by hunters or were removed from other recovered mortalities were still white. If bias 2) is true, accuracy in determining elk locations during specific census location flights was much poorer than our measured accuracy of ~300 m. We cannot eliminate this source of bias, but each marked elk was located and the estimated GPS location verified on maps delineating the sample area. If bias 3) is true, our estimated sightability of elk groups on quadrats which was 82% and developed during 199 test trials (Freddy 1995) greatly 9verestimates the true detection rate achieved during manag~ent application of quadrat sampling, even though observers used during testing and application remained the same individuals. The magnitude of discrepancy between estimators would further suggest that we not only missed groups on quadrats, but groups relatively large in size, even though sightability of groups ~7 in size exceeded 0.90 (Freddy 1995). We are currently trying to evaluate the most likely source(s) of bias and then develop procedures to test the appropriate hypothesis during winter 1997-98. Elk Movements In December 19·95, 35 male and 34 female calves were radiocollared and of these elk, 24 males and 27 females survived to become 18-months old on 1 December 1996 (Table 7). By the end of winter 1996-97, 21 (7M, 14F) or 41% had dispersed to a winter range outside of the intensive winter range study area in GMU _42 where these elk were initially captured (Table 17). Rates of dispersal were 29% for males and 52% for females. Calves trapped in zones E, F, and G which encompass Alkali, Dry Hollow, and the Mamm creeks, comprised 43% (9)·of the dispersing yearlings and these elk moved priJnarily west to winter ranges near the towns of Collbran and Parachute-Rulison. Calves trapped in zones C and D which encompass West Divide Creek, also comprised 43% of the dispersing juveniles and these elk moved south and southwest to winter ranges near Paonia Reservoir and Hotchkiss. We completed initial draft maps (1:100,000 scale) of a GIS land database for the area frequented by radiocollared elk as part of a cooperative effort through the National Biological Service, Rocky Mountain Elk Foundation, USFS, and BLM. Layers of GIS information include topography, based on 1:24,000 scale USGS quadrangles, land ownership, hydrology, transportation, transportation management zones, winter trapzones for elk, all elk locations, locations of female elk in June, and locations of all elk mortalities. Maps will be reviewed for accuracy by cooperating agencies. we will acquire. vegetation-type coverage for the area and develop a relational database between elk locations and GIS layers to allow descriptive analyses of areas frequented by elk. sighting Bias Draft Manuscript Discrepancies in estimates of population size based on quadrats, sighting-bias adjusted quadrats, and mark-resight estimators prompted us to re-evaluate potential sources of bias in all of these estimators. We therefore, have delayed drafting and submitting for peer review a manuscript evaluating sighting bias adjusted estimates of population size. �58 CQRCLUSJQHS We obtained acceptably precise estimates of calf and adult survival rates and recommend monitoring survival of remaining radiocollared adult male and female elk during the next 2 years. We recommend conducting aerial surveys in 199798 to estimate bias in detecting and counting marked elk on sample quadrats and mark-resight surveys to complete our evaluation of techniques to estimate elk density. LXUMTQRB CJUP Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 83-117. • Freddy, D. J. 1994. Estimating survival rates of elk and developing techniques to estimate population size. COlo. Div. Wildl. Game Res. Rep. July: 27-42. Freddy, D. J. 1995. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July. Halfpenny, J. c., and E. A. Biesiot. 1986. A field guide to mammal tracking in North America. Johnson Books, Boulder, co. 161pp. SAS Institute Inc. 1988. SAS/STAT User's Guide, 6.03. SAS Institute, Inc., Cary, NC. 1028pp. Wade, D. A., and J. E~ Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas Agric. Expt. Sta. Publ. B-1429. 42pp. White, G. c. 1996. NOREMARK: Population estimation from mark-resighting surveys. Wildl. Soc. Bull. 24:50-52. White, G. c., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data·. Academic Press, Inc., San Diego. 383pp. Prepared by - 1 . . U ~ ~ ~ ~ ~ ~ ~ ~ L - - - - - D L V �( ( ( Zone Name 93 24 95 96 umbers of elk rad oco lared i Decerrber Ca Elk Col lac Corral HelfcS!Qter Years Males Iota laea£ 93 94 5 6 93 94 95 96 Total 93 94 95 96 93-24 95 9 A B Garfield Gibson . ·Uncle Bob West Divide Hightower Middle Manm 8 5 6 8 20 8 12 12 24 13 11 12 26 13 11 10 10 10 10 .10 10 8 9 10 8 8 10 8 44 21 6 0 8 6 4 9 25 17 7 7 29 13 14 14 21 11 18 10 17 17 14 12 0 13 9 4 6 0 5 14 35 6b O 0 8 6 4 9 19 7 4 7 29 13 14 14 21 111810 17 17 14 12 0 13 9 4 6 0 5 14 0 0 0 0 .0 0 6 10 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o •o· 35 6 0 0 27 56 70 60 60 26 25 41 3 3 1 3 5 5 4 4 10 7 10 7 5 1 8 3 4 9 8 7 0 8 5 2 2 0 1 9 7 0 0 0 3 7 7 5 2 5 0 38 150 86 75 70 141 83 71 70 100 67 68 70 41 16 3 0 365 36 33 37 35 37 36 34 35 Table Trap C o. E F G H ap ure West Manm Dry Hollow All Obfectjves and 1996 in G Years Total 1 8 7 6 3 3 6 3 6 4 8 10 3 ·s 6 0 5 4 3 0 4 9 0 0 6 Adult Females Collared 93 94 95 96 Total 48 50 26 24 16 4 12 12 10 10 0 1 19 0 6 0 2 0 0 0 6 0 0 0 0 283 68 14 0 23 58 0 0 0 0 0 0 0 0 0 0 0 0 0 4 18 12 12 10 0 1 25 82 •Helicopter= Helicopter net·gtmning, Corral= corral-~rapping. b All 6 adult females captured 2 March 1995 Table 3. Survival rates of 6-11 month old calves with sexes pooled for the winter-spring time period 1 December - 14 June each year i993-94 through 1996-97. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(l-S)/n collars. Elk Age and Time Period (dates) Calves Calves Calves Calves Calves 12/01/9312/01/9•12/01/95All Years 12/01/96•06/14/94 06/14/95 06/14/96 Pooled 06/14/97 Survival L 951 CI U 951 CI n collars Censored' Died Nonhunting Bunting 0.92 0.85 0.98 73 0 ,6 6 0 0.90 0.83 0.97 69b 0 7 7 0 0.88 0.81 0.96 69 2c 8 8 0 • Censored denotes collar failure and/or animal life/death status not known. ' Includes (173.949/94) male whose collar failed 12194 but seen alive 1195, 1196. c Censored elk were (174.619195) male for slipped collar and (174.800195) male for trap-related mortality. • Censored elk was (174.619196)male for trap-related mortality. 0.86 0.77 0.94 69 ld 10 10 0 0.89 0.85 0.93 280 3c,d 31 31 0 �60 Table 2. Causes of deaths in radiocollared elk between 1 December 1993 and 14 June 1997. Calves (M=male, F=female) were 6-11 months old and collared at 6 months of age. Yearling males and·females were 12-17 months old and juvenile males and females were 18-23 months old and all were collared as 6-month old calves. Adult-males and females were> 24-months old at time of death. Elk AgeLSex Class at Death cause of Death Calves Yearling Juvenile Adult Total and -Code M F F M F M F All M F M Natural Causes Malnutrit;i.on-6 2 2 0 2 2 4 0 0 0 0 0 Unknown-Suspect 3 Malnutrition-31 4 0 0 1 3 1 0 0 0 0 7 7 12 5 Predation-Lion-3 4 0 1 0 0 0 0 Predation-Bear-JS 1 0 1 0 0 0 1 0 0 0 0 0 Unknown Predator-5 0 0 1 0 0 1 1 0 0 0 Unknown-suspect Predation-30 2 11 2 5 3 8 0 1 1 0 0 Accident-Birthing-32 0 0 2 0 2 0 2 0 0 0 0 Accident-Fell-10 0 0 ·J 1 0 0 1 0 1 0 0 2 2 Unknown Cause-11 2 1 0 0 6 0 1 0 Subtotals 17 14 42 .Q. Q .Q. 1· ll 23 a a • Legal Bunting Archery-33 Muzzleloading-34 Archery/Muzzle-27 Rifle-First-28 Rifle-Second-28 Rifle-Third-28 Rifle-Late-29 Subtotals 0 0 0 0 0 0 .Q. 0 0 .Q. .Q. 0 .i Wounding Loss Archery/Muzzle-24 Rifle-Regular-25 Rifle-Late-26 Subtotals 0 0 0 Q 0 0 0 .Q. 1 1 1 0 :Illegal Bunting Rifle-Regular-9 OUt-of-Season-7 Subtotals 0 0 o· 0 Q .Q. • 0 0 .Q. Presumed Bunting Disappear-Rifle Seasons-22 Disappear-Archery/ Muzzle-21 Subtotals Totals 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 8 0 4 0 0 0 0 0 13 7 7 0 0 6 .Q. 39 25 0 0 0 0 Q 1 2 1 0 3 1. 9• .2 0 0 .Q. 0 0 .Q. 0 1 1. 0 lb lb 0 0 .Q. .o 0 1. 1. ·17' 14 12 6 0 7 4 0 a 0 4 .Q. 0 0 .Q. 0 2 1 1 6 8 4 4 3 1 0 12 7 1 17 14 11 6 13 7 7 0 39 29 il 2 3 2 6 4 4 7 4 6 9 3 16 .J. 10 0 3 .2 ll 1 0 10 0 -0 0 10 2 1. 1 1. a 0 3b 2b 4 3 0 .Q. 0 .Q. 0 a 1 .2 0 1 !. .J. §.. 2 3 47 45 78 68 146 1 10 2 12 7 • These elk were illegally shot as spike-andeml yearling males: (173.190/93), (173.232/93),(173.320/93), (173.919/94), (174.0S9/94) (174.140/95), (174.200/95), (174.679/9S), (174.719/95). • These elk clisappearcd during rifle hunting seasons and arc presumably dead and legally harvested: (171.207/93), (172.649193), (171.8()()/93), (173.309/93), (173.390/93), (173.439/93), (174.001/94), (174.181194). One exception may be yearling male (173.309/93) that disappeared during die first rifle season in 199:4 when spikc-antleml bplls were not legal. • V �( ( ( Table 4. Estimated causes of mortality and associated body condition for 31 radiocollared calf elk 6-11 months old 1 December 199 - 14 June 1 Marrow Frequency ID/ Trap Age• Date Dead t Fat Cause of Death & Code No. Year Captured Zone Sex (months) 28. soa 86.0 03/18/94 Lion Predation-3 172.899/93 C F 9 8. 03c 102.0 04/25/94 Malnutrition-6 173.000/93 G F 10 28. 88d 108.0 03/18/94 Unknown-11 173.262/93 C M 9 111.0 03/22/94 Unknown-11 173.289/93 C M • 9 N/A1 0.21c 82.0 02/07/94 Malnutrition-6 173.461/93 H M 8 0.27c 77 .-0 04/25/94 Malnutri'tion-6 173.469/93 H M 10 51.71c 1_17. 0 06/01/95 Unknown; suspect predation-30 173.S89/94 B F 12 89.0 17~.640/94 C. F 9 03/30/95 Unknown; suspect predation-30 N/A' 14. 71c 100.0 03/20/95 Unknown; suspect malnutrition-31 173.789/94 E F 9 86.0 02/21/95 Lion Predation-3 173.870/94 D F 8 N/A' 94. 97c 140.0 Bear Predation-35 03/01/95 174.119/94 F M 9 64. 44c .112.0 03/14/95 Lion Predation-3 174.140/94 F M 9 76. 05c: 140.0 04/25/95 Lion Predation-3 174.170/94 B M 10 41. osc 127.0 04/08/96 unknown; suspect malnutrition-31 174.220/95 F M 10 2 .47c 120.0 04/24/96 Lion Predation-3 174.230/95 F M 10 86. 2ac 115.0 04/17/96 Lion Predation-3 174.240/95 E M 10 62. 97c 79.0 03/27/96 unknown Predator-5 174.339/95 E F 9 34. 56c: 78.0 04/16/96 unknown; suspect predation-JO 174.500/95 C F 10 10. 29c 120.0 04/15/96 unknown; suspect predation-30 174.609/95 B F 10 91. goc 100.0 02/05/96 Lion. Predation-3 174.689/95 D M 8 05/22/96 unknown; suspect predation-30 75. 32° 174.789/95 C M 11 79. 99c 72.0 01/08/97 Lion Predation-3 173.370/96 E M 7 69. 36c 116.0 02/19/97 173.381/96 E M 8 unknown; suspect predation-30 30. soc 173.640/96. A F 9 102.0 03/16/97 Malnutrition-6 8 .age 89.5 174.520/96 A F 10 04/25/97 Lion Predation-3 103.0 174.689/96 G M 11 None1 05/14/97 Urµcnown; suspect malnutrition-31 51. 99c 04/09/97" 125.0 174.800/96 E M 10 Lion Predation-3 83. 94c 105.5 174.910/96 D F 8 02/27/97 unknown; suspect predation-JO 91.5 175.059/96 C F 8 02/13/97 N/A1 • Unknown-11 8.03c 111.0 175.130/96 A F 9 03/24/97 Lion·Predation-3 77. 5. l. 99c 175.170/96 D M 9 03/26/97 unknown; suspect malnutrition-31 • Approximate age at death assuming 15 June birthdate. • Whole body weight at capture in December of 1993, 1994, 1995, or 1996. c Pat content as percent dly matter· of bone manow from either femur of carcass. • Pat content as percent dly matter of bone marrow from either mandtl>le of carcass. • Pat content as peicent dly matter of bone marrow from either humerus of carcass. ' No suitable bones remaining with carcass. • No marrow observ~ in one long bone remaining with carcass. �Table 5. Survival rates for winter-spring and summer-fall time periods from 1 December 1993-14 June 1997· for the cohort of 6-morith old calves radiocollared in December 1993. Survival rates for male and female calves pooled when 6-11 months old were 0.92 (95% CI 0.86-0.98, n=73). Survival rates (S) calculated as a mean estimate of Calive)/Calive + dead) and variance SCl-S)/n collars. Elk Age (months) and Time Period (dates) 18 - 23 24 - 29 30 - 35 36 - 41 42 - 47 6 - 47 12 - 17 6 - 11 12/01/96._ 12/01/9406/15/9512/01/9506/15/9612/01/9306/15/9412/01/9306/14/95 11/30/95 06/14/96 11/30/96 06/14/97 11/30/94 06/14/97 06/14/94 MALES Survival L 951 CI U 951 CI n collars Censored• . Died Nonhunting Hunting 0.89 Q.78 0.99 36 0.88 0.76 0.99 32 1.00 0.21 0.06 0.37 1.00 0.00 0.00 1.00 28 4 4 0 4 4 0 0 29c 0 0.50 0.00 1.00 2c 0 2' 0 4b 0 0 2 0 32 0 4 0 22d 0 0 0 0 ·4 0 22 0 2 0 28 0.97 0.92 1.00 35 1.00 0.97 0.91 1.00 0.84 0.71 0.97 1.00 34 0~97 0.91 1.00 34 33 32 27 0.73 0.58 0.88 37 0 1' 0 0 0 0 0 0 0 1 l 0 l 5 0 ·10 0 0 0 2 8 0 FEMALES Survival L 951 CI U 951 CI n collars Censored• Died Nonhuriting ·Hunting 0.95 0.87 1.00 37 0 2 2 0 0 1 0 0 0 1 • Censored denotes collar failure and/or animal life/death status not known. 11 Collar (173.309/93) •disappeatecr during Fall 1994 hunting seasons and assumed dead. c Includes collar (173.241/93) that failed in August 1995 but bull seen alive January 1996. • Two collars (173.390/93), (173.439/93) "disappeared" during Fall 1995 hunting seasons and assumed dead. • Two collars censoml: (173.241/93) failed, (173.381/93) slipped off 12/01/95. ' Collar (172.800/93) •disappeared" during Fall 1994 hunting seasons and assumed dead. • Includes (173.340193) alive 5/17/'Tl. C C 5 0.06 0.00 0.14 34 2c �( ( ( Table 6. Survival·rates for winter-spring and summer-fall time periods from 1 December 1994-14 June .1997 for the cohort of 6-month old cal v.es radiocollared 'in December 1994. Survival rates for male and female calves·pooled when 6-11 months old were 0.90 (95% CI 0.83-0.97, na69). Survival rates (S) calculated as a mean estimate of {alive)/{alive + dead) and variance S(l-S)/n collars. . Elk Age (months) and Time Period (dates) 12 - 17 18 - 23 24 - 29 30 - 35 6 - 35 6 - 11 06/15/9512/01/9506/15/9612/01/9612/01/9412/01/9406/14/96 11/30/96 06/14/97 06/14/97 11/30/95 06/14/95 MALES Survival 0.91 L 951 CI 0.81 U 951 CI n collars Censored• Died Nonhunting Bunting 1.00 33b 0 3 3 0 0.90 0.79 1.00 30b 0 3 0 3 FEMALES Survival L 951 CI. U 95' CI n collars Censored• Died • Nonhunting Bunting 0.89 0.78 0.99 36 0 4 4 0 0.97 0.91 1.00 32 0 1 0 1 0.96 0.88 1.00 26 1c 1 1 0 0.97 0.90 1.00 30 ld 1 l· 0 . 0.08 0.00 0.19 25 0 23 0 23 ·1.00 0.93 0.83 1.00 29 0 2 0 2 0.96 • Censored denotes collar failure and/or animal life/death status not known. ~ Includes collar (173.949/94) that failed in December 1994 but male seen alive in January 1996 • Censored elk was (173.949/94)failure. which was killed in first rifle season 1996. • Censored elk was (173.719/94) slipped collar. • Includes (174.030/94)alive 6/4/97. 2e 0 0 0 0 0.89 1.00 27 0 1 0 1 0.06 0.00 0.15 32 1c 3Q 4 26 0.74 0.59 0.89 35 ld 9 5 4 �Table 7. Survival rates for winter-spring and summer-fall time periods from l December 1995-14 June 1997 for the cohort of 6-month old calves radiocollared in December 1995 and survival rates for winter-spring for 6-11 month old elk calves radiocollared in December 1996. Survival rates for male and female calves pooled when 6-11 months old were 0.88 in 1995 (95% CI 0.81-0.96, n=69) and 0.86 in 1996 (95% CI 0.77-0.94, n=69). Survival rates (Sl calculated as a mean estimate of (alive)/(alive+dead) and variance of S{l-S)/n collars. Elk Age {months) and Time Period (dates) • ·1995 Calf Cohort 1996 Calf Cohort 6·;_ 11 6 - 23 18 - 23 12 - 17 6 - 11 12/01/9612/0l/9506/15/9612/0l/9512/0l/9606/14/97 06/14/97 11/30/96 06/14/96 06/14/97 MALES Survival L 951 CI U 951 CI n collars Censored• Died Nonhunting Bunting 0.86 0.74 0.99· 35 2b. 5 5 0 FEMALES Survival L 951 CI U 951 CI n collars Censored• Died Nonhunting Hunting 0.91 0.81 1.00 34 0 3 3 0 0.83 ·o.68 0.97 29 1c 5 0 5 0.96 0.87 1.00 24 0 l 1 0.68 0.51 0.84 34 3b,c 11 6 0 5 5 5 0 0.87 0.75 0.99 31 0 0.93 0.82 1.00 27 0 0.86 0.98 0.74 35 0 4 0 2 1 4 l 0.74 0.58 0.89 34 0 9 4 5 0.85 0.73 0.98 34 ld 5 5 0 • Censored denotes collar failure and/or animal life/death stablS not known. • Censored elk were (174.619/95) slipped collar, (174.800/95) capture mortality. • Censored elk was (174.660195) slipped collar July 1997. • Censored elk was (174.619196) male trap-related mortality. C C C �( ( ( Table 8. Survival rates for winter-spring and sununer-fall. time periods from 1 December 1993 - 14 June 1997 for all radiocollared adult female elk ~12-months old. Survival rates .(S) calculated as a mean estimate of (alive)/(alive + dead} and variance S(l-S)/n collars. Elk Age and Time Period (dates) Adult Adult Adult Adult Adult Adult Adult 06/15/9412/01/9406/15/9512/01/9506/15/9612/01/9612/01/9311/30/94 11/30/95 06/14/95 11/30/96 06/14/97 06/14/9~ ~6/14/94 Survival L 951 CI U 951 CI n collars censored• Died Nqnhunting Hunting 0.96 0.91 1.00 68be 0 3 1 2 0.87 0.80 0.94 0.96 0.92 1.00 lOObf . 95b1 0 13c 1 12 0 4 1 3 0.94 0.90 0.98 129bh 0 9d 0 8 • Censored denotes collar fa11ure and/or animal life/death stams unknown. c Collars (172:800/93,172.649/93)"disappemc:r Fall 1994 hunting seasons,assumeddead. • Composition is 6 females 18+ and 62 females 30+ months old. • Composed of 34-18+, and 61-30+ months old females. 1 aomposed of 30-18+ ·and 89-30+ months old females. k Composed of 31-12+. 29-24+, and 83-36+ months old females. 0.94 0.90 0.98 1191 • 2J 7 4 3 0.89 .0.84 0.94 1431t 0 '16 1 15 0.98 0.95 1.00 1271 0 3 1 2 11 Includes collar (172.011/93) that failed 4/1994 but seen alive in 1/1996 • Collar (172.207/93) "disappeared" Fall 1995 hunting seasons, assumed dead. ' Composed of 35-12+, 6-24+, and 59-36+ months old females. h Composed of 32-12+, 34-24+, and 63-36+ months old females. J Censored (172.011/93) failwe and (173.719/94) slipped collar. 1 Composedof27-18+ and 100-30+ month old females. Table 9 . . survival rates for winter-spring and sumroer-fail time periods from 1 December 1993 - 14 June 1997 for the group of adult female elk that were ~12-months old when radiocollared in December 1993. survival rates (S) calculated as a mean estimate of Calive)/(alive + dead) and variance S(l-S)/n collars. Elk Age and Time Period (dates) Adult Adult Adult • Adult Adult Adult Adult 12/01/93- 06/15/94- 12/01/94- 06/15/95- 12/01/95- 06/15/96- 12/01/9606/14/94 11/30/94 06/14/95 11/30/95 06/14/96 11/30/96 06/14/97 0.82 0.96 0.93 0.88 0.93 0~92 Survival 1.00 0.72 0.91 0.85 0.78 0.85 0.84 L 951 CI 0.91 1.00 0.99 0.97 1.00 1.00 U 951 CI 68be 65bf 53b f 49b f 42f 39 1 36r n collars 0 0 1i 0 Censored• 0 0 0 4 6d 3 3 3 Died 0 Nonhunting 1 1 0 3 0 0 2 Bunting 3 6 0 3 0 • Censored denotes collar failure and/or animal life/death status unknown • Collar (172.649/93) "disappeared" Fall 1994 hunting seasons, assumed dead. • . Composed of 6-18+ and 62-30+ month old females. 1 . Censored (172.011/93) failure of unknown status spring 1996. 11 Includes collar (172.0ll/93)failed 411994 but seen alive 1/1996. • Collar (172.207/93) •disappeared" Fall 1995 hunting seasons, assumed dead. r Composed of 100% females 24+ months old. ffl �Table 10. Annual ·survival rates from 1 December 1993-30 November 1996 for the group of adult female elk that were ~12-months old when radiocollared in December 1993. Survival rates (S) calculated as a mean estimate of (al~ve)/(alive+dead) and variance S(l-S)/n collars. Adult Survival L 951 CI U 951 CI n collars Censored• Died· Nonhunting Bunting Elk Age and.Time Period (dates) Adult Adult Adult 12/01/93~11/30/94 0.78 0.68 0.88 12/0i/94-11/30/95 0.84 0.75 0.93 12/01/95-11/30/96 0.86. 0.75 0.97 12/01/93-06/14/97 0.54 0.42 0.66 . 68b,f 53b,f 42f 19· 67f 19 6 3 31 3 25 0 15c 0 ·2 1. 9 iOd 13 • Censored denotes collar failure and/or animal Jif~d~th etatua unknown. • Collar (172.649/9~) "disappeared" Fall 1994 bunting seasons, assumed dead. • Compoeed of 6-18+ and 62-30+ month old females. • 1 Censored (172.011/93) failure 4/1996. 6 b Includes collar (172.011/98) failed 4/1994 but seen alive 1/1996. Collar (172.207/93) "disappeared" Fall 1995 bunting seasons, assumed dead. ' Composed of 100% females 24+ months old. d Table 13. Data matrix for simple population model using spreadsheet software. We used a post-hunt (December) population composition of 50 calves:100 females (age 2 12-months) and 4 adult males:16 yearling: 100 females and an estimated population of 3,600 e~k. Annual population growth rate is about 7% when using this matrix Fall.Hunting Survival Rate Survival Rate Harvest Rate • Elk Sex/Age Class Winter-Spring summer-Fall Elk Sex/Age Class· Adult Males 0.82 1.00 1.00 Adult Males Age 230 months Age 24-29 months Yearling Males Age 12-17 months :t.00 0.13 Yearling Males Age 1·8-23 months 0.97 Adult Females Age 224 months 0.99 0.10 Adult Females Age ~30 months 0.98 Yearling Females Age 12-17 months 1.00 0.06 Yearling Females Age 18-2·3 months 0.97 Calves Age o-s months 1.00 o. 02 .Calves Age 6-11 months 0.89 1 ~stimated from harvest surveys. ( C ( �( ( ( Table 11. Frequency distribution of whole body weights for male and female elk calves trapped in Game Management unit 42. December. 1993~1996. Percentage per weight class shown in parentheses. Body Weight Class (kg) • Year sex 60-69 70-79 80-89 90-99 100-109 110-119 120-129 130-139 140-149 Total 1993 1994 1995 1996 ALL 1993 1994 1995 1996 ALL M M M M M F F F F ·F 0 (0. 0) 0 (0. 0) • 0(0.0) 0(0.0) 0(0.0) 0(0.0) 0(0.0) 1 (3 .1) 0(0.0) 1(0.7) 1 (2. 9) 1(3.0) 0(0.0) 3(8.6) 5(3.6) 1(2.9) 2(5.7) 2(6~3) 0(0.0) 5(3.7) 1( 2~9) 1( 3.0) 3( 8.6) 2( 6.0) 6(17.1) 6(18.2) 0 ( 0. 0) 4 ( 11. 4) 3 ( 8. 6) 0( 0.0) 3( 8.6) 6(17.1) 2( 1.4) 12( 8.7) 21(15.2) 12(34.3) 13(39.4) 8(22.9) 5(14.3) 38(27.50 4(11.4) 8(22.9) 4(11.4) 7120.0) 1( 3.1) 3( 9.4) l(' 2.9) 6(17.6) 10( 7.4) 24(17.6) 4(11.4) 10(28.6) 5(15.6) 10(29.4) 29(21.3) 12(34.3) 10(28.6) 14(43.8) 8(23.5) 44(32.4) 10(28.6) 6(18.2) 9(25.7) 13(37.1) 38 (27 -:5) 4 (2. 9) 35(100) 33(100) 35(100) 35(100) 138(100) 0(0.0) 0(0.0) 0(0.0) 0(0.0) 0(0.0) 35(100) 35(iOO) 32(100) 34 (100) 136(100) 1 ( 2. 9) 1(2.9) 2c 2 (6. 0) 1 (2. 9) 6·.o> 10(28.6) 5(14.3) 18 ('13. 0) 6(17~1) 0 ( 0. 0) 2 ( 5. 7) 6 (18 .·8) 0( 0.0) 8(23.5) 22(16.1) 1 ( 2. 9) 1 ( 0. 7) 0 ( 0. 0) 0(0.0) Body measurements for elk calves trapped in Game Management Unit 42. December. 1993-1996. Male Calves Female Calves Mean SD Min Max n Mean SD Min Max n Measurement 112.7 13.7 77.0 141.0 35 103.8 12.2 76.0 123.0 35 Body Weight (kg) ·191.2 10.2 164.0 210.0 36 188.9 9.8 167.0 207.0 35 Body Length. (cm) 2.2 52.0 61.0 36 54.8 2.1 51.0 59.0 34 Hindfoot Length (cm) 56.3 0.59 0.05 0.43 0.67 35 0.55 0.05 0.46 0.64· 34 Condition Ind~r Table 12. Year 1993 113.5 Body Weight (kg) Body Length (cm) 190.3 Hindfoot Length (cm) 56.9 0.59 Condition Index 14.2 9.2 1.8 0.05 71.0 168.0 50.0 0.42 140.0 204.0 59.0 0.69 33 32 32 32 103.0 186.3 55.1 0.55 13.3 2.1 0.06 70.0 128.0 166.0' 207.0 50.0 59.0 0.42 0.65 1995 Body Weight (kg) 119.l 194.0 Body Length (cm) Hindfoot Length (cm) 57.4 0.61 Condition Index 13.6 9.3 2.2 0.05 92.0 166.0 53.0 0.50 141.0 206.0 61.0 0~71 35 36 36 34 105.7 189.4 54 ..9 0.56 15.2 11.4 2.3 0.06 60.0 158.0 47.0 0.38 129.0 • 32 203.0 34 59.0 34 0.66 32 1996 114.3 Body Weight (kg) Body Length (cm) 187.6 Hindfoot Length (cm) 57.7 0.61 Condition Index 17.1 11.5 2.3 0.07 72.0 160.0 52.0 0.44 136.0 202.5 60.5 0.70 35 35 34 35 109.5 187.4 56.8 0.58 12.4 9.0 2.4 0.05 81.5 170.5 52.5 0.47 136.0 210.0 62.0 0.69 '114.9 Al.1- Body Weight {kg) 190.8 Years Body Length (cm) Hindfoot Length (cm) 57.1 0.60 Condition Index 14.8 10.3· 2.2 0.06 71.0 160.0 50.0 0.42- 141.0 1·38 210.0 139 61.0 138 0.71 136 105.5 188.0 55.4 0.56 13.4 9.8· 2.3 0.06 60.0 158.0 47.0 0.38 136.0-136 210.0 140 62.0 138 0.69 135 1994 • Condition index= (Weight/body length). 8.8 35 36 36 35 34 35 34 34 �20 Table 14. Colorado. Counts of elk on quadrats 11 and 12 February, 1997 in GMO 42 south of Rifle .and Newcastle, Strata Size (mi2> Strata Totals 10 17 16 6 11 10 17 16 6 11 Garfie;Ld High Garfield Low B. Divide Low w. Div. Bast High· w. Div. Bast Low W. Div. West High W. Div. West Low Hightower Low Upper Alkali Ck. High Upper Alkali Ck. Low Low.Alkali Ck. Low Upper DryHollow Low Lower Mamm Ck. Low W.Mamm-Grass Mesa Low W.Mamm-Grass Mesa High Qyadrats N n 5 5 9 9 4 5 10 10 13 9 9 4 5 10 10 13 10 8 3 6 4 4 3 3 4 3 5 Elk Counted 191 54 8 205 49 89 27 0 88 48 85 ElklQJaadrat Mean StdErr. Po:gulation Size Total+ 90% CI 19.10 6.75 2.67 34.17 12.25 22.25 9.00 0.00 22.00 16.00 17.00 191 115 43 205 135 111 81 0 4 . '58 86 14 17.20 4.67 244 34.86 1246 13.54 5 5 7 7 5 3 7 137 137 72 14.50 0.000 1.859 2.404 0.000 3.573 2.991 2.449 0.000 0.000 5.514 4 .• 738 3.309 2.423 1.520 0.000 0 52 63 0 65 25 36 0 88 0 80 170 45 78 54 52 145 224 23 244 13 0 1854 164 Table 15. Summary of helicopter flights used to estimate· elk population size and density on 137 mi2 of winter range in GMO 42 south of Rifle and Newcastle, Colorado, during February. 1997. Proportion ~arked Total Elk Marked Elk Marked Elk Elk Proportion Flight Available• Counted Counted Counted Hours Counted Dates Marked Type NonRandoml 2/10 Quadrats 2/11-12 NonRandom2 2/13 7.5 29.0 7.8 120 120 120 31 43 33 29 40 29 0.2583 0.3583 0.2750 838 1203 1069 869 1246 1102 0.0357 0.0345 0.0299 ~umber of marked elk within the 132 mi2 sample area. "Number of marked elk individually identified during flights based on number/symbol identifier seen on collar. ( C �( ( Table 1.6 .• Summary of flights to estimate .elk population size from 1994-1997 in GMU 42 south of Rifle and Newcastle 1 ColoradQ. Area (mi2) Minimum Elk 95% C. I. Population Approximate Method Flownllirs• %Precision CountedLFlight Estimate 95% Conf. Int. Estimator Flight Date Feb. 1997 Feb. 1997 Feb. 1997 Feb. 1997 Feb .. 1997 'All 1997 Quadrats-StRSb Quadrats~stRS~sBAc Quadrats-StRS-LPd NonRandom Flight,REPl-LP NonRandom Flight,REP2-LP 3 Flights Pooled-JHEC 137/29.0 137/29.0 137/29.0 137/ 7.5 137/ 7.8 137/44.3 1246 1246 1246 869 1102 1246 1.854 2105 3428 3289 3924 3610 1660-2048 1851-2359 2643-4213 2344-4233 2839-5010 3116-4251 11 12 23 -29 28 18 Jan. 1996 Jan. 1996 Jan. 1996 Mar. 1996 Mar. 1996 Mar. 1996 Jan. 1996 Mar. 1996 All 1996 All 1996 Quadrats,REPl-StRS Quadrats,REPl-StRS-SBA Quadrats,REPl.-StRS-LP Quadrats,REP2-StRS Quadrats,RBP2-StRS-SBA Quadrats,REP2-StRS-LP NonRandom Flight,REPl.-LP NonRandom Flight,REP2-LP 4 Flights Pooled-JHE 4 Flights Pooled-IEJHEe 132/19.6 132/19.6 132/19.6 132/19.l 132/1"9 .1 132/19.l 132/ 8.5 132/ 8.0 13·2/55. 2 132/55.2 885 885 885 1373 1373 1373 1354 1998 1998 1998 2165 2336 3463 3175 3387 3791 3177 3405 3472 3415 1265-3065 1294-3378 2477-4448 2098-4252 2189-4585 2975-4607 2560-3795 2941-3869 3168-3840 3129-3807. 42 45 28 34 35 Feb. 1995 Feb. 1995 Feb. _1995 Quadrats-StRS Quadrats-StRS-SBA Quadrats-StRS-LP 177/17.5 177/17.5 177 /11. 5 361 36.l 361 1484 169_8 3774 787-2181 928-2468 1993·-5555 8Hours of helicopter time per flight. 'Stratified random ·sampte of quadrats with counts of elk not adjusted for sighting bias. •Stratified random sample of quadrats with counts of elk adjusted for sighting bias. 'One sample Lincoln-Peterson mark-resight estimator. •Joint Hypergeometric mark-resight estimator for nonrandom and quadrat(unadjusted)flights pooled. . 'Immigration/Emigration Joint Hypergeometric mark-resight estimator that allows for movement of elk on/off intensive study area. 22 19 14 11 12 47 45 47 �70 Table 17. Radiocollared elk captured as calves on winter range in GMO 42 during December 1995. that dispersed out of GMO 42 to a new winter range as of Locations {GMOs} determined b~ aerial telemetry. March 1~97. Trap New Fregyency Age• Sex GMO Zone Location Descri~tion 173.899/95 F 21 F 42 West Battlement Creek F 173.909/95LE 21 F 421 Hawxhurst Creek 174.301/95 E 21 F Porucpine Creek 42 West 174-. 360/95 E 21 F Wallace Creek 42 West 174.370/95 E 21 F 521 Drift Creek F 174.391/95 D 21 Paonia Reservoir 521 174.431/95LE D 21 F Buck Mesa 521 174.451/95 D 21 F Thompson _Creek 43 174.491/95 C 21 F Holms Mesa 42 West B 174.532/95 21 F Thompson Creek 43 174.551/95 G 21 F Porcupine Creek 42 West 174.580/95 G 21 F .Porcupine Creek 42 West 174.589/95LE G 21 421 Hawxhurst Creek F A 174.600/95 21 F 42 West Holms Mesa 174.119/95 B 21 M 42 West Holms Mesa E 174.629/95LE 21 M 42 West Rulison D 174.719/95 21 Buck Mesa M 521 Grassey·Gulch C 174.770/95 21 M 421 C Anthracite Creek 174.780/95 21 M ·53 174.809/95 C 21 Sommerset M 521 174.851/95 C 21 M 52 Oak Mesa V • Age of elk in months as of March 1997. b LE-~ Location elk routinely located. ~ V �71 30 25 '--/ c::::n ADULTMALES 0 w 20 a:: w en 15 z 10 a :i!: ::, - ADULT FEMALES ~~ ~ n=61 n=54 5 0 , ~<I:- ., ~~ ~" #' 'b<8 MONTH Fig. 1. Timing of deaths for adut elk >=12-months of age, 1993-94-1996-97. 12 - 10 0 w 8 w m 6 z 4 0 a:: :E ::, ~ CALVES n =31 !!!!!!! PREDATION U;lmmm MALNUTRITION :I I I ______O_T_H_E_R_ _ _ _ _ __ mi.............. 2 0 JAN FEB MAR MAY APR JUN MONlH Fig. 2. liming and estimated causes of deaths for calf elk 1993-94 - 1996-97. Calves were of both sexes and 6-11 months of age. 7 6 0 5 - Uiliilii!i!I FEMALES n = 14 • MALES n=17 w c 0::: 4 w ~ => z ·111111 _______________ 3 UnH ·:::: 2 1 0 ~· JAN FEB APR MAR MAY JUN MONlH Fig. ·3. limi~ of deaths for male and female calf elk 1993-94 -1996-97. Calves were 6-11 montt:,s of age. �72 Appendix I. Mortalities of 146 radiocollared elk from 1 Oeced)er 1993 through 14 -June 1997. Age is eeeroxfmate e9e in iears of elk at death: C=calf 6-11 months old 1 Y:Xearlf!JS 12-23 months old. Frequency 10/ Death Tree Year caetured Site Zone Sex Age Date Cause of Death &Code Nu:nber 172.030/93 F BR A 5 27-0ct-95 Legal kill rifle season-28 172.039/93 GR B F Unknown-suspect predation-30 4 14-Jun-95 172.070/93 BR A F 11 12-Feb-96 Unknown-11 172.080/93 GM A F 6 05-Nov-94 Legal kill rifle season-28 GR B F 11 16-Jan-94 172.090/93 Wounding loss late rifle season-26 172.101/93 F SR B Legal kill rifle season-28 • 8 14-oct-96 GC B F 172.128/93 8 31-0Ct-96 Wounding loss rifle season-25 F 172.139/93 BC C 17 19-0Ct-95 Wounding loss rifle season-25 F 172.160/93 cc C 3 23-oct-94 Legal kill rifle season-28 172.181/93 MC C F 3 03-Nov-94 Wounding loss rifle season-25 172.201/93 GS C F 3 15-Nov-94 Wounding l_oss rifle season-25 172.207/93 SG D F 4 30-Nov-95 Disappear rifle season-22 . 172.258/93 HY C F 3 04-0ct-94 • Legal kill archery/n1.1zzle season-27 GS C 172.277/93 F 3 04-0ct-94 Wounding loss archery/n1.1zzl~-24 172.290/93 F SG D 6 23-0ct-94 Legal kill rifle season-28 172.290/94 SM D F 4 16-Sep-96 Legal kill nuzzleloading season-34 172.369/93 F AC E 18-Sep-94 3 Legal kill archery season-33 172.369/94 F FM B 4 Legal kill late rifle season-29 14-Jan-96 172.409/93 F AC E 29-Dec-94 8 Wounding loss late rifle season-26 MH E F 8 172.459/93 Legal kill rifle season-28 24-0Ct-96 FS ff F 3 21-0Ct-95 172.509/93 Legal kill rifle season-28 FS ff 172.542/93 F 6 01-Feb-94 Mountain lion predation-3 172.549/93 PG ff F 28-Nov-95 7 Legal kill late rifle season-29 172.570/93 PG ff F 16 03-Nov-94 Wounding loss rifle season-25 172.581/93 PG H 3 F Legal kill rifle season•28 17-oct-94 F 172.581/94 FM B 3 08-Dec-95 Legal kill late r.ffle season-29 F 172.590/93 PG ff 5 24-Apr-96 Unknown-11 F 172.610/93 • PG ff 3 04-0Ct-94 Accident, birthing/calving-32 F 172.639/93 PG ff 16 14-Jun-96 Accident, birthing/calving-32 172.649/93 F PG ff 2 30-Nov-94 Disappear rifle season-22 172.670/93 F PG H Legal kill late rifle season-29· 16-Jan-95 4 PG H F 9 22-Dec-94 Wounding loss late rifle season-26 172.678/93 F FM B 8 172.690/93 Illegal kill-7 24-Jan-94 172.699/93 FM B F 7 05-Nov-95 Legal kill rifle season-28 172.749/95 LS ff F 11 07-Aug-96 Unknown-suspect predation-30 y SR B 172.800/93 F 30-Nov-94 Disappear rifle season-22 172.821/93 EG B F 3 08-Sep-96 Legal kill archery season-33 F 172.890/93 BC C 3 06-Nov-96 Legal kill rifle season-28 172.899/93 BC C F C 18-Mar-94 Mountain lion predation-3 172.950/93 GH D F 2 18-0ct-95 ·Legal kill rifle season-28 F 173.000/93 WM G C 25-Apr-94 Malnutrition-6 173.041/93 GM A M 2 19-0Ct-95 Legal kill rifle season-28 MH E F 2 27-Dec-95 173.060/93 Legal kill late rifle season-29 173.081/93 FS H F Legal kill rifle season-28 3 22-0ct-96 GM A 173.120/93 M 2 14-0ct-95 Legal kill rifle season-28 173.140/93 PG H F 3 31-0Ct-96 Wounding loss rifle season-25 FS H 173.160/93 F 3 13-Nov-96 Legal kill rifle season-28 y 173.190/93 BC C M 29-oct-94 . Illegal kill rifle season-9 173.201/93 GR B M 2 30-Nov-95 Wounding loss rifle season-25 173.210/93 GC B M 2 19-0ct-95 Legal kill rifle season-28 BC C M 173.219/93 06-Nov-95 2 Legal kill rifle season-28 y 173.232/93 BR A M 15-Nov-94 Illegal kill rifle season-9 173.262/93 BC C M C 18-Mar-94 Unknown-11 173.262/94 HM B M 2 12-0ct-96 Legal ki U rifle ~eason-28 173.269/93 MC C M 2 06-Nov-95 Legal kill rifle season-28 3 MC C 173.279/93 M 12-0Ct-96 Legal kill rifle season-28 173.289/93 C 22.;.Mar-94 MC M C Unknown-11 173.289/94 PR A M 2 18-Sep-~6 Legal kill nuzzleloading season-34 GS C 173.300/93 M 2 Legal kill rifle season-28 24-0ct-95 y 173.309/93" HY C M 30-Nov-94 Disappear rifl_e season-22 y 173.320/93. HY C M 20-0ct-94 Illegal ldll rifle season-9 173.320/94 HM B M 2 Legal kill archery season-33 14·Sep·96 173~332/93 GH D M 2 12-Sep-95 Legal kill nuzzleloading season-34 SG · D 173.351/93 M 2 05-Nov-95 Legal kill rifle season-28 173.359/93 AC E M 2 06-sep-95 Legal kill archery season-33 173.370/93 MH E M 2 08-Nov-95 Legal kill rifle season-28 M· RG E 173.370/96 C 08-Jan-97 Mountain lion predation-3 RG E 173.381/96 M C 19-Feb-97 Unknown-suspect predation-30 MG D 173.390/93 M 2 • 30-Noy.:.95 Disappear rifle season-22 MG D M Legal kill rifle season-28 173.402/93 2 18-0ct-95 G 173.410/93 Wounding loss rifle .season-25 WM M 2 02-Nov-95 f7.f~420/93 M WM G. 2 24-oct-95 Legal ~~ Ll rff le season-28__ --------------------------------------------------- --------------------------------~--------------- V V' V �73 Appendix 1. <continued> Frequency ID/ Trap Year Captured Site Zone Sex 173.429/93 MH E M 173.439/93 PG H M 173.450/93 PG H M 173.461/93 PG H M 173.461/94 CM A M 173.469/93 FS H M PR A M 173.469/94 173.479/93 FS H M 173.492/93 FS H M 173.502/93 FS H M 173.510/93 FM B M 173.521/93 FM B M OG B M 173.540/94 173.549/94 HM B F 173.580/94 PR A F 173~589/94 OG B F 173.640/94 MC C F GM A F 173.640/96 BG E F 173.689/94 173.789/94 MR E F 173.829/94 MM F F SM D F 173.859/94 173.870/94 SM D F 173.919/94 BC C M 173.929/94 BC C M 173.939/94 BC C M .173.959/94 BC C M 173.970/94 MC C M 173.981/94 MP D M BC C M 173.990/94 174.001/94 BG E M 174.009/94 BG E M 174.019/94 BG E M 174.039/94 MR E M 174.049/94 MM F M 174.059/94 MR E M 174.069/94 BG E M 174.090/94 MR E M 174.101/94 MM F M 174.109/94 MM F M 174.119/94 MM F M 174.129/94 MM F M 174.140/94 MM F M GB B M 174.140/95 174.150/94 MM F M 174.160/94 MM F M 174.170/94 FM B M 174~181/94 FM B M 174.200/95 MS F M 174.220/95 MS F M 174.230/95 MS F M 174.240/95 MD E M 174.319/95 MS F F 174.329/95 MD E F 174.339/95 MD E F 174.360/95 MD E F 174.401/95 AP D F 174.500/95 LB C F 174.520/95 KR B F 174.520/96 GM A F BL A F 174.560/95 174.609/95 GB B F 174.679/95 HG E M 174.689/95 AP D M 174.689/96 EW G M. 174.729/95 VM D M 174.789/95 WD C M 174.800/96 BG E M 174.809/95 W C M 174.861/95 KR B M . ,174.910/96 LM D F 175.059/96 BC C F 175.130/96 GM A F 175.170/96 LM D M Death Date l 14-Sep-95 2 30-Nov-95 2 15-0ct-95 C 07-Feb-94 Y 19-Sep-95 Age C 25-Apr-94 2 20-0ct-96 2 2 3 2 2 2 Y Y C c C c 2 10·Sep·95 03·Sep·95 13-Nov-96 28-Aug-95 17-0ct-95 13-0ct.:.96 . 07-Sep-95 21-Dec-95 01-Jun-95 30-Mar-95 16-Mar-97 31-0ct-96 20-Mar-95 10-Jan-97 2 23-0ct-96 2 C • 21-Feb-95 Y 02-Nov-95 2 2 2 2 2 2 2 2 2 2 2 Y 2 2 Y 2 C 2 c Y 2 2 16-0ct-96 18-Sep-96 02-Nov-96 20-0ct-96 02-Nov-96 20-0ct-96 30-Nov-96 12-0ct-96 13-Nov-96 05-Sep-96 14-Sep-96 17-0ct-95 26-Sep-96 20-0ct-96 . 24-May-96 19-oct-96 01-Mar-95 14-oct-96 14-Mar-95 30-Nov-96 14-0ct-96 15-Sep-96 C 25-Apr-95 2 Y C C C Y Y c Y 2 30-Nov-96 18-0ct-96 08-Apr-96 24-Apr-96 17-Apr-96 02-0ct-96 C Y C Y C Y C C v 03-Sep-96 27-Mar-96 22-Apr-97 22-Sep-96 16-Apr-96 21·Sep·9~ 25-Apr-97 14-May-97 15-Apr-96 13-Nov-96 0S·Feb-96 14-May-97 17-oct-96 C C Y Y 09-Apr-97 22-Apr-97 31-0ct-96 C C - 13-Feb:.97 c C 22-May-96 27-Feb-97 24-Mar-97 26-Mar-97 Cause of Death & Code Nllli)er Legal kill archery season=33 Disappear rifle season-22 Legal kill rifle season-28 Malnutrition-6 Wounding loss archery/111.1zzle·24 Malnutrition-6 Legal kill rifle season-28 Legal kill archery season-33 Legal kill archery season-33 Legal kill rifle season-28 Legal kill archery season~33 Legal kill rifle season-28 Legal kill rifle season-28 Legal kill archery season-33 Unknown-11 Unknown-suspect predation-30 Unknown-suspect predatfon-30 Malnutrition-6 Legal kill rifle season-28 Unknown-suspect malnutrition-31 leg~l kill late rifle season-29 Legal kill rifle season-28 Mmntain lion predation-3 Illegal kill rifle season-9 Legal kill rifle season-28 Legal kill archery season-33 Legal kill rifle season-~8 Legal kill rifle season-28 Legal kill rifle season-28 Legal kill rifle season-28 Disappear archery/111.1zzle season-21 Legal kill rifle season-28. Illegal kill rifle season-9 Legal kill archery season-33 Legal kill 111.1zzleloading season-34 Illegal kill rifle season-9 Wounding loss archery/111.1zzle-24 Legal kill rifle season-28 Unknown-suspect predation-30 Legal kill rifle season-28 Bear predation-35 Legal kill rifle season-28 Mountain lion predation-3 Illegal kill rifle season-9 Legal kill rifle season-28 Legal Id l.l n.izzleloading season-34 Mountain lion predation-3 Disappear rifle season-22 Illegal kill rifle season-9 . Unknown-suspect malnutrition-31 Mountain lion predation-3 Mountain lion predation-3 Wounding loss archery/n.izzle-24 Legal kill archery season-33 Unknown predator-5 Unknown-suspect predation-30 Legal kill 111.1zzleloading season-34 · Unknown-suspect predation-30 Legal kill n.izzleloading season-34 Mountain lion predation-3 Illegal kill-7 Unknown-suspect predation-30 Illegal kill rifle season-9 Mountain lion predation-3 Unknown-suspect malnutrition-31 Illegal kill rifle season-9 Unknown-suspect predation-30 Mountain lion predation-3 Accident, fell-10 Wounding loss rifle season-25 Unknown-suspect predatfon-30 Unknown· 11 • Mountain· lion predation-3 Unknown-suspect malnutrition-3'1 �177 Colorado Division Wildlife Research July 1998 of Wildlife Report JOB PROGRESS state Work Colorado of Project No. Package W-153-R-11 Mammals 3002 Elk Inyestigations Task No. Period Author: REPORT Research Estimating Developing PQpulation Covered:i July Survival Rates of Elk and Techniques to Estimate Size 1, 1997 - June 30, 1998 D. J. Freddy Personnel: R. Adams, T. Beck, J. Broderick, G. Byrne, D. Crane, R. Del Piccolo, J. Ellenberger, J. Frothingham, V. Graham, D. Homan, R. Kahn, K. Madariaga, D. Masden, C. Mehaffy, P. Neil, J. olterman, J. Thompson, P. Will, K. Wright, S. Yamashita, D. Younkin, CDOW; W. Andelt, D. Bowden, G. White, CSU; Diagnostic Laboratory, CSU; D. Ouren, USGS-BRO, BLM Glenwood springs, CO, USFS Rifle, CO, Rocky Mountain Elk Foundation, cooperating. Abstract During 1997-98 we monitored survival of 210 adult elk radio-collared in previous years and we conducted an applied sighting bias trial to further test methods of estimating elk density. We summarized average survival rates (± 95% CI) for elk between 1993-94 and 1997-98. Survival during summer-fall for females age ~12 months averaged 0.90 ± 0.03 inclusive of hunting deaths (n=524 elk-years) and 0.99 ± 0.01 with hunting deaths censored (n=476 elk-years). Survival during winter-spring for females age ~18 months averaged 0.97 ± 0.01 inclusive of hunting deaths (n=547 elk-years) and 0.99 ± 0.01 with hunting deaths censored (n=536 elk-years). Survival during summer-fall for males age ~24 months was 0.20 ± 0.09 inclusive of hunting deaths (n=82 elk-years) and 1.00 with hunting deaths censored (n=16 elk-years). 'Survival during winterspring for males age ~30 months was 1.00 (n=13 elk-years). Hunting related deaths were the primary cause of mortality for adult elk and annually removed 80% of the adult males, 11% of the yearling males, and 9% of the adult females. For adult females, deaths due to wounding and illegal kills exceeded the absolute number of females dying from natural 'causes during 5 years. High adult and calf natural survival rates allow this population to grow an estimated 7% annually with current levels of hunting mortality. Further tests of sighting bias revealed that failure to count all, elk in groups, as opposed to failure to detect groups, is likely the primary cause of negatively biased estimates of elk density based on quadrat sampling. Counting error may approach 25%. Therefore, sighting bias models developed to account for errors in detecting elk on quadrats do not adequately increase estimates of elk numbers. We did not find evidence indicating mark-resight estimates of elk numberS were positively biased. �179 ESTIMATING SURVIVAL JOB PROGRESS REPORT RATES OF ELK AND DEVELOPING ESTIMATE POPULATION SIZE David TECHNIQUES TO J. Freddy P. H. OBJECTIVE Estimate survival rates of adult ,female, adult male, techniques to estimate population size. SEGMENT and calf elk and develop OBJECTIVES 1. Estimate winter, summer, and annual survival rates of adult female male elk from known fates of previously radio-collared elk. 2. Estimate density of elk in a portion of GMU-42 using a helicopter and employing mark-resight density estimators and random quadrat density estimators to evaluate potential errors in meeting assumptions of markresight theory and sighting bias correction theory. 3. Analyze data and summarize annually in Federal Aid Job Progress and Report. INTRODUCTION Our objectives are to provide reliable estimates of survival rates for calves during winter and for adult females and males throughout the year and to develop and test a system to estimate elk densities on winter ranges. Estimates of calf survival were obtained during winters 1993-94 through 199697 and summarized in Freddy (1997). We are continuing to obtain estimates of survival for adult males and females. For adults, we are interested in survival rates inclusive of hunting mortalities to document human-induced rates of survival and exclusive of hunting mortalities to estimate natural rates of survival. We are evaluating a system for estimating population size or density that incorporates estimates of sighting bias in conjunction with random sampling of search quadrats as sample units. OUr winter study area encompasses about 839 km2 (324 mi2) in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado. This area is part of the Grand Mesa Elk Data Analysis Unit E-14. Elk winter habitats include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnifolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields below elevations of 9,800 ft. In summer, elk use oakbrush-mountain shrub, aspen, and subalpine fir-Engelmann spruce (Abies lasiocarpa-Picea engelmannii) meadow systems throughout the Grand Mesa region up to elevations of 12,000 ft. (Freddy 1993). METHODS We placed radio collars (172-176MHz) having mortality sensors on elk calve.s age 6 months and adults age ~18 months during December 1993-1996 (Freddy 1997). Elk were captured using helicopter net-gunning and portable corral traps (Freddy 1997). During 1997-98, we monitored 210 adult elk having functioning radios as of July 1997. Collars were white and had black identification symbols on dorsal surfaces of collars to allow observers in helicopters to individually identify elk. �180 Estimating Elk Survival Rates We monitored life or death status of radioed elk with aerial surveys using a Cessna 185 at 2-4 week intervals from December 1993 to June 1998 and with daily ground surveys from December-April each year from 1993-94 to 1996-97. Survival rates (5) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) = S(l-S)/n collars (White and Garrott 1990). Survival rates are expressed as the mean estimate ± the 95% confidence interval. We used x2-contingency tests to compare survival rates between sexes and among time intervals (PROC FREQ, SAS 1988). Sample sizes refer to numbers of individual radioed elk except when referenced as elk-years which denotes that individual radioed elk, because they survived for several years, were used repeatedly in successive yearly time intervals to calculate pooled average survival rates among years. Elk-years represents the numbers of times elk were at risk during time intervals. We defined 4 major time intervals for survival analyses: winter-spring was 1 December to 14 June, summer-fall was 15 June to 30 November, annual was 1 December to 30 November to coincide with timing of capture and collaring, and yearly was 15 June to subsequent 14 June used only for yearling elk aged 12-23 months. For adult elk during these time intervals, we calculated survival rates inclusive of natural and hunting-related mortalities, exclusive of hunting mortalities, and exclusive of natural mortalities. Excluding, or censoring hunting mortalities, provided estimates of natural survival rates. Excluding natural mortalities but including hunting mortalities provided estimates of hunting removal rates. Censoring elk associated with categories of mortalities reduced sample sizes used to estimate survival rates. Elk were also censored if radios failed or if their life/death status was unknown after an extended period of time. Archery, muzzleloading, and rifle hunting seasons occurred from about 1 September to 15 November each year during the summer-fall time interval. Laterifle seasons restricted hunters to taking only antlerless elk and occurred yearly from about 25 November-3l January which included portions of the summer-fall and winter-spring time intervals. Yearling spike-antlered males were generally not legal quarry in most areas frequented by radioed elk. Male elk become legal quarry when branch-antlered usually at age 2 years. Cause of death of radioed elk recovered in the field was estimated from presence or absence of gunshot wounds or bite wounds on carcass, predator tracks or scat at carcass site, physical positioning of carcass remains whether buried, covered, scattered, or consolidated (Wade and Browns 1982, Halfpenny and Biesiot 1986), relative amount of internal fat and marrow fat if present with carcass, and results of histopathology and marrow fat analyses. Fat content (percent dry matter) of bone marrow and estimates of age based on dental cementum were obtained for dead elk by the Colorado Division of Wildlife Laboratory while histopathology analyses were provided by the Colorado State University Veterinary Diagnostic Laboratory. Photographs were taken of nearly all mortalities so that physical evidence could be reviewed and judged by outside experts (pers. comm. T. Beck, W. Ahdelt). Estimating Elk Densities During 3 applied surveys in winters 199~ and 1997, we estimated numbers of elk on 132-137 mi2 of winter range with helicopter counts of marked (radioed) and unmarked elk on random quadrats and along nonrandom flight paths. Estimated numbers of elk for the 3 surveys based on actual counts of elk on quadrats were 51, 63, and 93% of the estimated numbers of elk obtained from markresight formulas using counts of marked and unmarked elk. Adjusting actual �181 quadrat counts with previously developed sighting bias models did not meaningfully increase quadrat estimates in comparison to mark-resight estimates (Freddy 1996, 1997). We had 3 important concerns: 1) sighting bias corrections developed during previous testing trials were biased high and provided inadequate corrections for applied surveys, 2) observers failed to see marks on elk in groups that were detected and counted accurately causing inflated mark-resight estimates of elk numbers, and 3) observers failed to count all elk within groups that were detected on quadrats with elk not counted inclusive of both marked and unmarked elk causing deflated counts of elk on quadrats. This last concern represented counting error that would not be accounted for by sighting bias corrections. In 1998, we conducted an applied sighting bias trial on quadrats along with mark-resight surveys to again compare estimates of elk numbers based on quadrat counts and mark-resight surveys. We selected 44 mi2 in West Divide and Alkali creeks that were a portion of the winter range sampled with quadrats and mark-resight surveys in 1996 and 1997 and a portion of the area used to conduct sighting bias trials in 1994 and 1995. This area was dominated by oakbrush and pinyon-juniper habitats. For this test, all marked elk were age ~18 months unlike previous sighting tests and winter range surveys that also included marked calves age 6 months. Locations of all radioed elk within this 44 mi2 area were obtained by telemetry using a Cessna 185 and ARNAV Star5000 GPS system on 26 February, 1998. Radioed elk represented a population of known size which we used to evaluate the magnitude of sighting detection bias. During 3 days from 27 February to 1 March, elk were counted on all 44, 1-mi2 quadrats using a Bell-Soloy helicopter flown at 40-50 mph. A flight crew was a pilot, navigator, and observer and crews changed each day among 3 observers, 2 navigators, and 1 pilot all of whom were involved in previous sighting bias tests and winter range surveys. Members of flight crews had no knowledge of the number or locations of marked elk within the survey area. Flight crews flew nearly 7 hours each day to complete quadrats which was similar to daily flying time and fatigue commonly associated with applied surveys. Quadrats were flown using the same helicopter and counting procedures that were used in previous sighting tests and surveys (Freddy 1994-1997). Observers recorded the standard sighting bias variables of group size, elk behavior, habitat type, percent screening cover, and percent snow cover for all groups seen. As flight crews completed quadrats, they maintained a list of marked elk seen and their GPS locations (Garmin Pilot III) and whether or not marked elk were or could have been individually identified. Those marked elk not seen or those seen but not individually identified during counts were then found by a second independent flight crew using a Bell-Soloy helicopter and telemetry. These missed elk were found on the same day an average 3.6 hours after quadrats were flown. For every missed' or unidentified marked elk group, the second flight crew recorded the GPS location (Garmin Pilot III) of the group and standard sighting bias variables. Those elk seen but not individually identified by quadrat crews were assigned as a specific individual elk based upon proximity of locations of where such elk were seen by quadrat crews compared to locations of these elk when found by the second flight crew. Locations and status of all marked elk were therefore known during the time quadrats were flown. A sighting trial occurred when marked elk were detected during quadrat counts and when marked elk were missed and later found by the second flight crew. To �182 maintain independent observations of marked elk, only 1 sighting trial occurred if there was more than 1 marked elk in a group. Otherwise, detecting or missing a marked elk constituted a sighting trial. Two mark-resight flights using the same helicopters were conducted on 1 and 2 March after quadrat counts were completed. These flights followed a nonrandom path through the same 44-mi2 with the intent of counting as many elk as possible within allotted flight time. The navigator for both flights had not participated in quadrat counts. The observer for the first flight was an observer during part of the quadrat counts while the observer for the second flight had not participated in quadrat counts. These 2 observers were the same persons who conducted mark-resight flights during winter range surveys in 1996 and 1997. At the conclusion of the second mark-resight flight, locations of collared elk not seen were confirmed to be within the sample area using the helicopter and telemetry. Weather conditions during flights were variable but similar to conditions experienced during previous winter range surveys. Quadrats were flown with generally acceptable visibility in hazy to bright sunshine and light to moderate wind speeds although brief snow squalls occurred on 27 and 28 February. Nonrandom flights were flown during hazy to bright sunshine and low wind speeds. Snow cover was nearly 100% in all areas with depths estimated to be 0.5 to 2.5 ft. Fresh snow was received on 24 and 25 February. Minimum night temperatures were 2-13 OF and were the coldest measured during the 14 days previous to flights. Maximum day temperatures were 27-35. OF. Number of elk on the search area was estimated using 3 approaches: from actual counts of elk on quadrats, from adjusting quadrat counts with sighting bias correction models, and from using the Bowden (BE) and lmmigration-EmigrationJHE (lMJHE) mark-resight estimators in program NOREMARK (White 1996). Elk counted on quadrats were potentially a total count because 100% of the search area was flown and because all 44 sample units were flown, there was no sampling variance associated with estimates based on quadrats. To adjust for elk groups likely missed on quadrats, we applied sighting bias corrections to elk groups counted on each quadrat which adjusted counts per quadrat and provided a sighting bias corrected total population estimate. We used 3 sighting correction models based on all sighting trials (n = 224) to .correct for probabilities of detecting elk groups, where probability of detection is [n = eU / 1 + eU] with u representing the linear regression of variables affecting the probability of detecting a group: 1. u = 1.342(LogGroupSize(countedd - 0.131 2. u = 1.230(LogGroupSize(co=ted» - 2.127(Bedded) + 0.291 3. u = 1.135(LogGroupSize(co=ted» - 1.822(Bedded) - 0.031(%Cover) + 1.517 probability of detecting an elk group was adjusted for group size, for bedded or not bedded behavior when detected, and for percent vegetation screening cover (Samuel et al. 1987, Freddy'1995). Relative AlC model performance values of 172, 160, and 154 for models 1-3, respectively, indicated model 3 was the most parsimonious model. We pooled counts of marked and unmarked elk seen during quadrat counts and mark-resight flights. Estimated numbers of elk based on all 3 flights pooled was considered to be the best estimate of population size and the benchmark against which quadrat counts were compared. Both the BE and lEJHE estimators account for movement of elk on and off the search area but the BE better accounts for heterogenous sighting probabilities among individual elk (Bowden 1995, White 1996). �183 Moyements We continued to precisely locate selected radioed elk at least once ~r month since their capture to document seasonal movements using a Cessna 185. These elk were originally selected at random from within trap zones and equalized by age class in January 1994. Elk from the original sample that died were replaced each subsequent January with randomly selected elk that were usually of the same sex, age class, and trap zone as elk that died. All replacement elk in January 1998 were yearling or older because additional calves were not marked in December 1997. As of 1 January 1998, these 44 elk were classified as 27 adult females, 5 yearling females, 4 adult males, and 8 yearling males. During June 1998, we again located an additional 28 adult females that were originally selected at random in 1995 to document their locations during the calving period. Females from the original 1995 sample that died were replaced each subsequent June with adult females randomly selected from the same trap zones of elk that died. As needed, we located other elk to document unusual movements. RESULTS AND DISCUSSIQH Survival Estimates Between 1 December 1993 and 14 June 1998, 181 radioed elk died of which 31 were calves 6-11 months old and 150 were adults ~12 months old (Table 1, Appendix I). Calves died of natural causes (Freddy 1997) while for adults ~12 months old, hunting accounted for 92% of 150 deaths. Yearlings Survival during summer-fall for yearling elk age 12-17 months was 0.89 ± 0.06 for males (n = 120) and 0.95 ± 0.04 for females (n = 128) when averaged among 4 years and inclusive of hunting deaths, and 1.00 for both males (n = 107) and females (n = 122) with hunting deaths censored. All deaths for males and females during summer-fall were due to hunting. Survival among years for males ranged from 0.83 to 0.97 and for females from 0.87 to 1.00 inclusive of hunting deaths. We failed to detect differences in survival between sexes within years (P ~ 0.13) and among years for both males (P ~ 0.39) and females (P ~ 0.09) inclusive of hunting deaths. Survival of females (0.95) tended to be higher than males (0.89) when averaged among years and inclusive of hunting deaths (P = 0.07) Cl'ables 2-5). Survival during winter-spring for yearling elk age 18-23 months was 0.98 ± 0.02 for males (n = 106) and 0.97 ± 0.0.03 for females (n = 121) when averaged among 4 years and inclusive of hunting deaths, and 0.98 ± 0.02 for males (n = 106) and 0.98 ± 0.02 for females (n = 120) with hunting deaths censored. Survival among years for males ranged from 0.96 to 1.00, inclusive or exclusive of hunting deaths. Survival for females ranged from 0.93 to 1.00 and 0.96 to 1.00 inclusive and exclusive of hunting deaths, respectively. We failed to detect differences in survival among ye~rs for both males (P ~ 0.51) and females (P ~ 0.22) inclusive or exclusive of hunting deaths. We also failed to detect differences in survival between sexes within years (P ~ 0.62) and among years (P ~ 0.76) inclusive or exclusive of hunting deaths (Tables 25). During winter-spring, there were 2 nonhunting deaths each for males and females and 1 illegal hunting death for a female (Table 1). Yearly survival for elk age 12-23 months was 0.87 ± 0.06 for males (n = 119) and 0.93 ± 0.05 for females (n = 127) when averaged among 4 years with hunting deaths included. Survival among years for males ranged from 0.79 to 0.97 and for females from 0.81 to 1.00. We failed to detect differences in yearly survival among years for males (P = 0.27) but survival was lower (0.81) for �184 females in 1996-97 (P = 0.02). Yearling males were subjected to about the same rate of illegal hunting during all years which accounted for most of the male mortality, while in 1996-97, females had a lower survival rate because 5 of 6 deaths were hunting related (Tables 2-5). With hunting deaths included, we failed to detect differences in survival between sexes within (P ~ 0.13) and among years (P = 0.15). Of 24 deaths involving yearling elk, 20 (83%) were hunting related (Table 1). With hunting deaths censored, yearly survival for elk age 12-23 months was 0.98 ± 0.02 for males (n = 106) and 0.98 ± 0.02 for females (n = 120) when averaged among 4 years. Survival among years for males and females ranged from 0.96 to 1.00. We failed to detect differences in yearly survival among years for males (P = 0.51) and for females (P = 0.50), and between sexes within and among years (P ~ 0.90) (Tables 2-5). Yearling spike-antlered males were generally not legal quarry during hunting seasons. Each year from 1994-1997, 29-32 yearling males radioed as calves entered the fall hunting seasons presumably as spike-antlered males. OVer 4 years, illegal harvest removed 10% of the yearling males with yearly rates ranging from 3 to 17%. Of 12 elk illegally killed, 11 were taken during rifle seasons and 1 during archery seasons. In addition to these 12 elk, 1 male was fatally wounded during archery season in an area where the elk was legal quarry. Overall, 11% of the yearling males were annually removed by hunting (Tables 1, 2-5). Adult Females Survival during summer-fall for all adult females age ~12 months was 0.90 ± 0.03 (n = 524 elk-years) when averaged among 4 years and inclusive of hunting deaths and 0.99 ± 0.01 (n = 476 elk-years) with hunting deaths censored. Survival among years ranged from 0.87 to 0.94 and from 0.99 to 1.00, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (P = 0.30) or exclusive (P = 0.46) of hunting mortalities (Table 6). Hunting was involved in 48 (96%) of 50 summer-fall deaths: 32 were killed, 12 were wounded, and 4 disappeared during hunting seasons and presumed legally killed. One natural death was attributed each to suspected predation and complications while calving. At the beginning of fall hunting seasons, there were 99, 129, 142, and 152 radioed adult females age ~12 months available to hunters in 1994, 1995, 1996 and 1997, respectively, representing 522 elk-years (Table 6, nonhunting deaths censored). During summer-fall, 9% of these radioeq elk were removed annually by all types of hunting mortality (range = 6-12%). Survival during winter-spring for all adult females age ~18 months was 0.97 ± 0.01 (n = 547 elk-years) when averaged among 5 years and inclusive of hunting deaths and 0.99 ± 0.01 (n = 536 elk-years) with hunting deaths censored. Survival among years ranged from 0.94 to 0.99 and from 0.97 to 0.99, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (P = 0.34) or exclusive (P = 0.40) of hunting mortalities (Table 6). There were 19 winter-spring deaths, of which 11 (58%) involved hunting with 5 killed and 3 wounded during rifle late-seasons and 3 illegally killed out of hunting seasons. Natural deaths were attributed to mountain lion predation (1), suspected predation (2), complications while calving (1), accidental fall (1), and unknown cause (3) (Table 1). During winter-spring, 2% of these radioed elk were removed annually by all types of hunting mortality. �185 Estimates of adult female survival using all females age ~12 months could be biased because of the constant yearly recruitment of yearling females into this radioed population of adults afforded by many radioed calves surviving to yearling age and no similar yearly recruitment of additional older adult females into the radioed population. We therefore estimated survival rates for adult females age ~24 months by excluding recruitment of yearlings age 1223 months and for 68 adult females initially collared as a cohort in December 1993 whose age at capture ranged from 18 months (n=6) to 10+ years. Survival during summer-fall for adult females age ~24 months was 0.89 ± 0.03 (n = 396 elk-years) when averaged among 4 years and inclusive of hunting deaths and 0.99 ± 0.01 (n = 354 elk-years) with hunting deaths censored. Survival among years ranged from 0.82 to 0.93 and from 0.99 to 1.00, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (P = 0.17) or exclusive (P = 0.38) of hunting mortalities (Table 7). Hunting was involved in 42 (95%) of 44 summer-fall deaths. During summer-fall, 11% of these radioed elk were removed annually by all types of hunting mortality (range 7-17%). Survival during winter-spring for adult females age ~30 months was 0.96 ± 0.02 (n = 420 elk-years) when averaged among 5 years and inclusive of hunting deaths and 0.98 ± 0.01 (n = 410 elk-years) with hunting deaths censored. Survival among years ranged from 0.93 to 0'.99 and from 0.97 to 0.99, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (P = 0.15) or exclusive (P = 0.39) of hunting deaths (Table 7). There were 16 winter-spring deaths with 10 (63%) attributed to hunting. During winter-spring, 2% of these radioed elk were removed annually by all types of hunting mortality (range 1-5%). Using the 1993 cohort of adult females, survival during summer-fall was 0.88 ± 0.05 (n = 189 elk-years) when averaged among 4 years and inclusive of hunting deaths and 0.99 ± 0.01 (n = 167 elk-years) with hunting deaths censored. Survival among years ranged from 0.82 to 0.94 and from 0.98 to 1.00, inclusive and exclusive of hunting deaths, respectively. We failed to detect differences in survival among years inclusive (P = 0.20) or exclusive (P = 0.55) of hunting mortalities (Table 8). Hunting was involved in 22 (96%) of 23 summer-fall deaths. Percent of these radioed elk removed during summerfall by all types of hunting-related mortalities averaged 12 annually (range = 6-17%). Interestingly, as this cohort collectively increased in age from 1994 to 1997, the annual percentage of elk removed by hunting during summer-fall steadily declined from 17 to 6%. For the 1993 cohort, survival during winter-spring age was 0.95 ± 0.03 (n = 233 elk-years) when averaged among 5.years and inclusive of hunting deaths and 0.98 ± 0.02 (n = 227 elk-years) with hunting deaths censored. Survival among years ranged from 0.92 to 1.00 and from 0.93 to 1.00, inclusive and exclusive of hunting mortalities, respectively. We failed detect differences in survival among years inclusive (P = 0.47) or exclusive (P = 0.17) of hunting deaths (Table 8). There were 11 winter-spring deaths, of which 6 (55%) involved hunting. During winter-spring, 3% of these radioed elk were removed annually by all types of hunting mortality. to Overall, survival rates for adult females during summer-fall and winter-spring were the same among age groups of adult females. Natural survival rates exceeded 0.98 for all time intervals and groupings (Table 9). �186 Annual survival rate using the 1993 cohort was 0.83 ± 0.07 (n = 199 elk-years) when averaged among 4 years and inclusive of hunting deaths and 0.97 ± 0.03 (n = 170 elk-years) with hunting deaths censored. Survival among years ranged from 0.78 to 0.94 and from 0.92 to 1.00, inclusive and exclusive of hunting mortalities, respectively. We failed to detect differences in survival among years inclusive (P = 0.17) or exclusive (P = 0.34) of hunting mortalities (Table 10). Annually, 14% of these radioed elk were removed by all types of hunting mortality (range 8-20%). Removal rates of females by hunting during summer-fall were compared between yearling females age 12-17 months and adult females age ~24 months. Removal rates were higher for adult females (0.11) than yearling females (0.05) when averaged among 4 years (P = 0.04). This difference was caused by extremes in removal rates in 1994 when 17% of adults and 3% of yearlings were removed (P =0.05) and in 1997 when 11% of adults and 0% yearlings were removed (P = 0.06). In 1995 and 1996, removal rates were not different (P > 0.41) but rates for yearlings (3%) tended to be lower than for adults (7-9%). These rates suggest that vulnerability of yearling and adult females to hunting is different. Adult Males Survival during summer-fall for adult males age 24-29 months was 0 •. 17 ± 0.09 (n = 75) when averaged among 3 years and inclusive of hunting deaths and 1.00 (n = 13) with hunting deaths censored. Survival among years ranged from 0.08 to 0.23 inclusive of hunting mortalities. We failed to detect differences in survival among years (P > 0.32) (Tables 2-4). All deaths were attributed to hunting resulting in removal rates averaging 83% collectively for all fall hunting seasons each year. Through fall 1997, 7 males had survived at least 1 year of hunting seasons and were available during at least 1 additional year of hunting seasons as 3 or 4 year-olds. Survival during summer-fall for adult males age ~24 months was 0.20 ± 0.09 (n = 82 elk-years) when averaged among 3 years and inclusive of hunting deaths and 1.00 (n = 16 elk-years) with hunting deaths censored. Survival among years ranged from 0.14 to 0.24 inclusive of hunting mortalities. We failed to detect differences in survival among years (P > 0.61) (Tables 2-4). All deaths were attributed to hunting resulting in removal rates averaging 80% collectively for all legal males during fall hunting seasons each year. Survival during winter-spring for adult males age ~30 months was 1.00 (n = 13 elk-years) during all years (Tables 2-5). There were no hunting or nonhunting deaths of adult males during winter-spring. Hunting was the cause of mortality among male elk age ~24 months. From the 1993-94 cohort of 36 male calves, 28 lived to age 24-months with 22 (79%) harvested in 1995 inclusive of 2 that disappeared 'and 2 wounding losses during rifle seasons. From the 1994-95 cohort of 33 male calves, 25 lived to 24months and 23 (92%) were harvested in 1996 including 2 that disappeared during seasons, 1 illegally taken during rifle seasons, and 1 wounding loss during archery/muzzleloading season. From the 1995-96 cohort of 33 male calves, 22 lived to 24-months and 17 (77%) were harvested in 1997 including 1 that disappeared, 1 illegally taken, and 4 wounding losses during rifle seasons. Comparative Survival of Adult Males and Females The differential impact of hunting on survival and recruitment of males and females to young adult age classes is demonstrated by net survival rates of �187 calf cohorts. For 1993-94, 1994-95, and 1995-96 calf cohorts, net survival from age 6 to 35 months averaged 0.10 for males and 0.73 for females (Tables 2-4). Only 3 (4%) of a potential 69 males survived from age 6 months to 48 months (Tables 2,3). Hunting Mortality Per Season Distribution of all types of hunting mortalities for male elk age >12 months during hunting seasons 1994-1997 was: Archery 15%, Muzzleloading 5%, RifleFirst 42%, Rifle-Second 25%, Rifle-Third 13%, Rifle-Late 0%, Illegal out-ofSeason 0%. Distribution of all hunting mortalities for female elk age >12 months was: Archery 14%, Muzzleloading 7%, Rifle-First 19%, Rifle-Second 31%, Rifle-Third 10%, Rifle-Late 15%, Illegal out-of-Season 4%. All female and nearly all male elk killed by hunters died within the Grand Mesa DAU E-14 or adjacent GMU 43. Exceptions were 6 adult males that dispersed long distances and were killed near Ruedi Reservoir, Black Mesa, Tomichi Dome, Gothic, and Anthracite Creek in GMUs 47, 63, 54, 55, 551, and 521 up to 100 mi south or east of their capture sites. These 6 males represented 9% of adult males age ~24 months that were taken by hunters. Adjusting Hunting Harvest Estimates Surveys used to estimate legal hunter harvest do not account for wounding losses or illegal kills. Estimates of the proportion of the legal kill that these additional deaths represent were made based on fates of radioed elk during hunting seasons 1994-97. We defined legal kill to be the number of radioed elk known to be harvested plus those whose radio signals disappeared during hunting seasons and were subsequently assumed to be legally killed. This legal kill would most likely represent the kill estimated by harvest surveys. Wounding losses and illegal kills represented deaths not accounted for by surveys. Total kill which was known for radioed elk could thus be expressed as (legal kill)*(X)= total kill where (X) represents a correction factor. correction factors by sex/age class were 1.16 for adult males, 1.11 for yearling males, and ~ 1.4 for all categories of adult females (Table 11). Rifle and late-rifle seasons involving adult female elk had high correction factors of 1.35-2.00. Losses of adult females not reported or estimated can be important in modeling populations. Total unreported losses of adult females during hunting seasons 1994-1997 was 18 which was 1.8x the 10 natural deaths of adult females in the comparative time interval of 1 December 1993-14 June 1998 (Tables 6, 11). An argument could be made that estimating unreported losses is as important as estimating natural mortality rates. Survival Rates and Population Modeling Survival and removal rates were incorporated into a simple spreadsheet model to assess trends in population growth (Table 12). Natural survival rates (hunting deaths censored) were used for summer-farl and winter-spring time intervals for adult males, yearling males, adult females, yearling females, and calves. Hunting deaths of all types were incorporated as total harvest removal rates for each sex/age class. Using total removal rates is a simpler method than using correction factors to account for unreported .harvest. This model assumed survival of calves 0-5 months of age during summer was 1.00 because the model uses post-season calf:cow ratios measured in January as an estimate of net calf recruitment to December. Recruited sex ratio of calves to December was assumed to be 1:1. �188 Modeling suggests that if harvest rates of antlered elk remained as measured and harvest rates of antler less elk were reduced to 0, the population could grow at an annual rate of 18%. Current rates of antlerless harvest allow annual growth rates of about 7.5%. To stabilize population growth, harvest rates on adult and yearling female and calf age classes must increase nearly 2X. population Estimates Movements of marked elk on and off the survey area during days when flights were conducted resulted in 34 marked elk (27 female, 7.male) and 38 marked elk (31 female, 7 male) within the area during quadrat and mark-resight flights, respectively. Elk movements were usually <600 yards and near sample area boundaries. Ratios of marked/unmarked elk counted were similar among quadrat and nonrandom flights ranging from 0.029 to 0.036 (Table 13). These ratios were generally lower than ratios of 0.031-0.042 observed during extensive survey flights in 1996 and 1997 when marked calves were available in addition to marked adults. Observers used 19.7±2.1 (95% CI) minutes to count 17.5 elk per quadrat (range=0-68). Observers 1B and 2E encountered similar densities of elk and had similar search times in oakbrush habitat while observer 3M had lower elk densities and higher search times in pinyon-juniper habitat (Table 14). During 3 extensive surveys in 1996 and 1997, these same observers used 17.6, 16.9, and 19.8 minutes to count 17.0, 25.9, and 17.3 elk, respectively, per quadrat (n=177). Searching effort during the 1998 sighting trial was therefore representative of searching effort during previous extensive surveys. During nonrandom flights, detection rates of marked elk were 0.32 and 0.45 with effective searching rates of 4.9 and 6.00 minutes per mi2 of search area during flights 1 and 2, respectively (Table 13). During nonrandom flights for extensive surveys in 1996 and 1997, detection rates of marked elk were 0.260.58 with effective searching rates of 3.3-3.9 minutes per mi2 of search area. Nonrandom flights in 1998 were therefore representative of flights during extensive surveys. Observers completed 32 sighting trials while counting elk on quadrats. Average sighting bias or detection rate for marked elk groups among observers was 0.78±0.15 (95% CI) (Table 14). This sighting bias rate was similar to the average sighting bias rate of 0.82+ 0.06 (95% CI) for these same 3 observers during sighting bias test trials (n=192) conducted in 1994 and 1995. Therefore, sighting bias rate estimated from test trials appears to be representative of sighting bias during applied surveys. Observers failed to detect 7 marked elk during sighting trials. When found after quadrats were completed, 6 of these elk were in groups of ~2 elk, 4 were bedded and appeared to have been bedded for several hours, 5 were in screening cover densities ~60%, and 5 were reluctant to move even when disturbed at close distances with the helicopter (Table 15). Importantly, the white collars were easily visible and thus, failure to detect marked elk was not likely due to failure to see marks. Of these 7 missed elk, 3 were males and 4 were females resulting in detection rates of 0.57 for adult males and 0.85 for adult females. Of the 7 missed elk, 3 were found in close proximity to other groups that were likely counted by quadrat crews. This lends credence to the possibility that some marked elk were not counted within detected groups because not all elk, �189 both marked and unmarked, were seen when groups were detected. This type of counting error is plausible as groups detected in dense pinyon-juniper or oakbrush often begin to move and observers concentrate on counting the moving elk and fail to see elk in the group that remain bedded or move in a different direction. Estimated number of elk on the search area was 1,179 based on the BE markresight estimator (Table 17). The 771 elk counted on quadrats represented 65% of the BE while sighting bias adjusted quadrat counts represented 73-75% of the BE. We propose that the 25% difference between sighting adjusted estimates and the BE represents counting error. This degree of counting error would equate to adding 2.2 elk per group to an average group size of 5.2 elk for the 148 groups detected (Table 18). Counting error, as opposed to detection error, appears to be the primary cause of negatively biased estimates of elk density based on quadrat sampling. Elk Moyements Yearling elk originally trapped as calves and surv1v1ng to age 18 months dispersed to winter ranges not affiliated with their natal capture winter range at rates of 43, 42, and 33% in winters 1995-96, 1996-97, 1997-98, respectively. Each year, 40-52% of the yearling females dispersed while only 25-33% of the yearling males dispersed. Yearling elk moved primarily west or south to winter ranges near the towns of Rulison, Parachute, Collbran, Hotchkiss, Paonia, and Paonia Reservoir. Specifically for the 1996 cohort of radioed calves, 28 males and 30 females survived to age 18 months in December 1997 (Table 5). By end of winter 199798, 19 (7M, 12F) or 33% had dispersed to other winter ranges (Table 19). Calves trapped in Alkali, Dry Hollow, and the Mammm creeks (zones E, F, G) comprised 79% of the dispersing yearlings and these elk moved primarily west to winter ranges near Collbran, Rulison, and Parachute. Calves trapped in West Divide Creek (zone D) comprised 16% of the dispersing yearlings and these elk moved to winter ranges near Collbran and also south towards Paonia Reservoir. We continue to cooperate with the USGS-BRO, USFS, and BLM with the support of the Rocky Mountain Elk Foundation to develop a GIS database allowing analyses relating elk locations, movements, and home ranges to habitat components. CONCLUSIQNS Hunting related mortalities were the primary cause of death for adult female and male elk. For adult males, all deaths to age 48 months were related to hunting. For adult females, deaths due to wounding and illegal kills exceeded the absolute number of females dying from natural causes during 5 years. Natural survival rates for adult females and males were ~0.98 during winterspring and summer-fall. High adult and calf survival rates allow this population to potentially increase 18% annually in the absence of hunting antlerless elk. Current hunting removal rates of 9% for adult females age ~12 months allows the modeled population to grow 7% annually. Failure to count all elk in groups, as opposed to failure to detect groups, appears to be the primary cause of negatively biased estimates of elk density based on quadrat sampling. Counting error may approach 25%. Sighting bias models developed to account for errors in detecting elk on quadrats inadequately increased estimates of elk numbers when compared to numbers estimated by mark-resight formulas. We did not find evidence indicating markresight estimates of elk numbers were positively biased. �190 LITERATURE CITED Bowden, D. C., and R. C. Kufeld. 1995. Generalized mark-sight population size estimation applied to Colorado moose. J. Wildl. Manage. 59: 840851. Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wild1. Game Res. Rep. July: 83-117. Freddy, D. J. 1994. Estimating survival rates of elk and developing techniques to estimate population size. colo. Div. Wildl. Game Res. Rep. July: 27-42. Freddy, D. J. 1995. Estimating survival rates of elk and developing techniques to estimate population size. colo. Div. Wildl. Game Res. Rep. July: 63-79. Freddy, D. J. 1996. Estimating survival rates of elk and developing techniques to estimate population size. colo. Div. Wildl. Game Res. Rep. July: 87-108. Freddy, D. J. 1997. Estimating survival rates of elk and developing techniques to estimate population size. Colo. Div. Wildl. Game Res. Rep. July: 47-73. Hal.fpenny, J. C., and E. A. Biesiot. 1986. A field guide to mammal in North America. Johnson Books, Boulder, CO. 161pp. tracking Samuel, M. D., E. O. Garton, M. w. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Wildl. Manage. 51:622-630. SAS Institute Inc. 1988. Cary, NC. 1028pp. SAS/STAT User's Guide, 1982. Procedures Texas Agric. Expt. 6.03. SAS Institute, J. Inc., for evaluating predation on Sta. Publ. B-1429. 42pp. Wade, D. A., and J. E. Browns. livestock and wildlife. White, G. C. 1996. NOREMARK: Population estimation surveys. Wildl. Soc. Bull. 24:50-52. White, G. C., and R. A. Garrott. 1990. Analysis of wildlife data. Academic Press, Inc., San Diego. 383pp. from mark-resighting radio-tracking �191 Table 1. Causes of deaths in radio-collared elk between 1 December 1993 and 14 June 1998. Calves (M=male, F=female) were age 6-11 months and collared at age 6 months. Yearling males and females were age 12-17 months and juvenile males and females were age 18-23 months and all were collared at age 6 months. Adult males and females were ase >24 months at time of death. "Elk Ase!Sex Class at Death Yearling Juyenile Adult Total Cause of Death Calves All M F M F M F M F and -Code M F Natural causes o o 4 o o o 2 2 Malnutrition-6 2 2 o Unknown-Suspect o o o 3 1 4 Malnutrition-31 3 1 o o o o 1 5 13 Predation-Lion-3 o o o o 8 8 4 o o o o o Predation-Bear-35 o o o o o 0 o o o 1 1 Unknown Predator-5 o 1 o o o o Unknown-Suspect o 2 3 8 11 Predation-30 2 5 o o 1 1 2 o 0 o o 2 o 2 Accident-Birthing-32 o o o o 1 1 2 Accident-Fell-10 o 0 o o 1 o 1 1 o 2 2 4 6 Unknown Cause-11 2 1 o o o Subtotals .Q .Q .Q .a. .l.2. II sa 2. 111l 2. Legal Bunting 8 2 12 o 0 2 8 4 o Archery-33 o o 4 2 4 4 8 Muzzleloading-34 o 2 o o o 0 o 1 o 1 1 o Archery/Muzzle-27 o 0 o o o 29 22 7 22 7 Rifle-First-46 o 0 o o o o 20 o 0 10 10 10 10 o Rifle-Second-47 o o o 8 5 8 5 13 o 0 o Rifle-Third-48 o o o o 6 o 6 6 Rifle-Late-29 o 0 o o o o Subtotals .Q .Q .6..2. .Q .Q .Q sa aa sa II .i Wounding Loss 1 o 0 2 o 1 1 1 Archery/Muzzle-24 o o o 3 o 0 o o 1 1 2 Archery-52 1 1 o 3 2 o 0 o 1 1 2 Rifle-First-43 o o o 9 o 0 o 3 6 3 6 Rifle-Second-44 o o o 2 1 1 1 1 Rifle-Third-45 o 0 o o o o 1 1 o 1 o Rifle-Unk.Reg.-25 o 0 o o o o 3 o 3 o 3 Rifle-Late-26 o 0 o o o o Subtotals .Q .Q .Q .Q aa 1. II .a. .15. ~ ~ Illegal Bunting 5 o o 5 o Rifle-First-49 o 0 o o o 5 6 1 o 6 o Rifle-Second-50 o 0 5 o o o 1 o o o o 0 o o 1 Rifle-Third-51 1 o o 0 1 1 o 1 o Rifle-Unk.Reg.-9 o o o o 1 o o 1 o Archery Season-8 o 0 1 o o o 3 o 2 o 3 Out-of-Season-7 o 0 o o o 1 Subtotals .Q .Q .Q 11 2. 2. II .3. .u: .Q ~ Presumed Buntin~ 1 1 Missing-ArchMuzz-21 o 0 o o o o o 1 o o 0 5 o 2 3 3 2 Missing-Rifle 1st-40 o o o 3 1 Missing-Rifle 2nd-41 o 0 o 1 o 1 1 2 o o 0 o o o o o o Missing-Rifle 3rd-42 o o o Subtotals .Q .Q .Q .Q .Q .2. .3. .5. .5. .i ~ Totals 17 14 13 6 2 3 66 60 98 83 181 • These elk were illegally shot as spike-antlered yearling males: (173.190/93) (173.232/93) (173.309/93) (173.320/93) (173.919/94) (174.059/94) (174.140/95) (174.200/95) (174.679/95) (174.729/95) (174.861/95) (173.210/96). (173.309/93) disappeared in 1994 during first rifle season when spike-antlered yearling males were not legal and was assumed to have been taken illegally. All other illegal deaths were confirmed. • These elk disappeared during hunting seasons and remained missing for several months and are assumed dead and legally harvested: (172.207/93) (172.649/93) (172.800/93) (172.961/93) (173.390/93) (173.439/93) (174.001/94) (174.181/94) (174.770/95). �Table 2. Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 1998 for the cohort of calves age 6 months radio-collared in December 1993. Survival rate for male and female calves pooled when age 6-11 mohths was 0.92 (95% CI 0.86-0.98, n=73). Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(1-S)/n collars. Elk Elk Age (months) and Time Period (WS or SF dates) 18-23 24-29 30-35 36-41 42-47 6-59 6-11 (mos) l2.:.ll ~ ~ .WS WS SF WS SF WS SF WS SF ALL 1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1994 1993-98 1993-94 MALES Survival L 95% CI U 95% CI n collars censo.redDied Nonhunt Hunt 0.89 0.78 0.99 36 0.88 0.76 0.99 32 0 o b 1.00 28 o o o o 0.21 0.06 0.37 28° 1. 00 0.00 0.00 0.50 0.00 1. 00 1. 00 0.00 0.00 4 4 2f o 22d o o o 2 o o o o 1 19 33 o 2e 1 33 4 4 0 4 0.95 0.87 0.97 0.92 1. 00 1. 00 1. 00 0.97 0.91 1. 00 37 35 34 34 33 0.84 0.71 0.97 32 censo red- o o o o o Died Nonhunt. Hunt 2 2 1h 1 1 5 o o o o 1 o o o o 1 1 5 FEMALES Survival L 95% CI U 95% CI n collars o 4 o 1. 00 o 22 0.97 0.91 o 2 1. 00 27 o o o o 3e,9 o 4 1 29 0.89 0.76 1. 00 27 0.96 0.87 1. 00 24 0.62 0.46 0.78 37 o o o 31 o 1 1 3 3 o 11 • Censored denotes collar failure and/or animal life/death status not known. Collar (173.309/93) disappeared 1994 hunting seasons and assumed dead. • Includes (173.241/93) collar failure August 1995 but seen January 1996. d Two collars (173.390/93). (173.439/93) disappeared 1995 hunting seasons and assumed dead. • Two collars censored; (173.241/93). collar failed August 1995. (173.381/93) slipped off December Includes (173.340/93) alive May 1997. 9 Censored elk was (173.249/93) slipped collar September 1997. • Collar (172.961/93) disappeared 1997 hunting seasons and assumed dead. h Collar (172.800/93) disappeared 1994 hunting seasons and assumed dead. b 1995. 14 ,_. It) (IJ �Table 3. Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1994-14 June 1998 for the cohort of calves age 6 months radio-collared in December 1994. Survival rate for male and female calves pooled when age 6-11 months was 0.90 (95% CI 0.83-0.97, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(l-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 18-23 24-29 30-35 36-41 42-47 ~ 6-11 (mos) l2...:.l1 WS SF WS SF WS. ALL SF WS 1996-97 1997 1995-96 1996 1997-98 1994-98 1995 1994-~5 MALES Survival L 95% CI U 95% CI n collars censozedDied Nonhunt Hunt 0.91 0.81 1. 00 33b 0 3 3 0 0.90 0.79 1. 00 30b 0.96 0.88 1. 00 26 0.08 0.00 0.19 25 o o 23 o 1c 1 1 3 o 23 o o o o FEMALES Survival L 95% CI U 95% CI n collars 0.89 0.78 0.99 36 0.97 0.91 1. 00 32 0.97 0.90 1.00 30 0.93 0.83 1. 00 29 0.96 0.89 1. 00 27 0.85 0.70 0.99 26 censo.red= o o o o o Died Nonhunt Hunt 4 4 1 2 1 4 o 1e 1 1 o o o o 1 o 2 1 4 3 o 1. 00 2d 0.50 0.00 1. 00 2 1. 00 o o o o o 1 o 1 1 C 31 4 27 1.00 22 o o o o Censored denotes collar failure and/or animal life/death status not known. b Includes (173.949/94) collar failure December 1994 but seen January 1996 Censored elk was (173.949/94) collar failure, which was killed in first rifle season d Includes (174.030/94) alive June 1997 . • Censored elk was (173.719/94) slipped collar May 1996. 0.03 0.00 0.09 32 lC 0.63 0.46 0.79 35 1d 13 5 8 1996. I-' 10 W �Table 4. Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1995-14 June 1998 for the cohort of calves age 6 months radio-collared in December 1995. Survival rate for male and female calves pooled when age 6-11 months was 0.88 in 1995 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance of S(l-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 6-11(mos) 12-17 18-23 24-29 30-35 6-35 WS SF WS SF WS ALL 1997 1997-98 1995-98 1996-97 1996 1995-96 MALES Survival L 95% CI U 95% CI n collars 0.86 0.74 0.98 35 censored- 2h 0.83 0.68 0.97 2,9. F 5 0.96 0.87 1. 00 24 o 0.23 0.04 0.41 22 1d 17 o 1 1 5 o 17 0.93 0.82 1. 00 4 1e 0.13 0.01 0.24 32 sh,e,d,e o o o 28 1.00 Died Nonhunt' Hunt 5 5 0 FEMALES Survival L 95% CI U 95% CI n collars 0.91 0.81 1. 00 34 0.87 0.75 0.99 31 27 0.83 0.66 0.99 23 18 0.58 0.40 0.76 31 0 o o 2f .19 3f,9 3 3 0 4 2 4 o 1 1 o o o o 4 cenaoredDied Nonhunt Hunt • Censored b Censored Censored d Censored • Censored , Censored 9 Censored C 4 1. 00 o 4 6 22 13 9 denotes collar failure and/or animal life/death status not known. elk were (174.619/95) slipped collar May 1996, (174.800/95) capture mortality. elk was (174.660/95) slipped collar July 1996. elk was (174.671/95) likely collar failure July 1997 . elk was (174.190/95) slipped collar May 1998. elk· were (174.441/95) slipped collar August 1997. and (174.580/95) likely collar elk was (174.470/95) likely collar failure December 1997. failure July 1997. •.... 10 ,j:o �Table 5: Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 1998 for the cohort of calves age 6 months radio-collared in December 1996. Survival rate for male and female calves pooled when age 6-11 months was 0.86 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance of S(l-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 6-11(mos) 12-17 18-23 6-23 ALL WS SF WS 1996-98 1997-98 1997 1996-97 MALES Survival L 95% CI U 95% CI n collars cenaor-ed- 0.85 0.73 0.98 34 1b Died Nonhunt Hunt 5 5 0 FEMALES Survival L 95% CI U 95% CI n collars censo.redDied Nonhunt Hunt 0.86 0.74 0.98 35 0 5 5 0 • Censored b Censored 1. 00 0.97 0.90 1. 00 29 0 1 0 1 28 0 0 0 0 1. 00 1. 00 30 0 0 0 0 30 0 0 0 0 0.82 0.69 0.96 34 1b 6 5 1 0.86 0.74 0.98 35 0 5 5 0 denotes collar failure and/or animal life/death elk was (174.619/96) capture mortality. status not known. I-' 1.0 til �Table 6. Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS 1 December14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 1998 for all Survival rates (S) calculated as a mean estimate of radio-collared adult female elk age ~12 months. (alive)/(alive + dead) and variance S(l-S)/n collars. Elk Age and Time Period (WS or SF dates) Adult Agylt Adult Adult Adult Adyl!;; Adylt AQylt AQJ.!.lt WS SF WS SF SF WS WS SF WS 1996 1995 1995-96 1996-97 1997 1997-98 1994-95 1994 1993-94 0.94 0.89 0.98 0.94 0.91 0.96 0 .. 99 0.'87 0.96 Survival 0.90 0.84 0.95 0.90 0.87 0.97 0.92 0.80 0.91 L 95% CI 0.94 0.98 1.00 0.98 0.96 1.00 1.00 0.94 1.00 U 95% CI 129b h 1271 100b f 68b e 95b 9 119i 143k 152m 138 n collars j n 1P 2 0 0 2 0 0 0 0 censoxed" 7 16 8d 3 13 2 4 13c 3 Died 4 1 1 0 0 1 1 1 1 Nonhunt 3 15 2 8 13 1 3 12 2 Hunt ---- 0 b Includes (172.011/93) collar failure April 1994, seen January 1996 • Censored denotes collar failure or life/death status unknown. d Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead. • Collars (172.800/93,172.649/93) disappeared 1994 hunt seasons. f Composed of 35-12+, 6-24+, and 59-36+ months old females. • Composed of 6-18+ and 62-30+ months old females. h Composed of 32-12+, 34-24+, and 63-36+ months old females. 9 Composed of 34-18+ and ·61-30+ months old females. j Censored (172.011/93) failure and (173.719/94) slipped collar. 1 Composed of 30-18+ ~d 89-30+ months old females. I Composed of 27-18+ and 100-30+ month old females. k composed ot 31-12+, 29-24+, and 83-36+ months old females. m Composed of 30-12+, 23-24+, and 99-36+ months old females. n Censored (174.4-41/95) slipped collar August 1997 (174.580/95) likely failure June 1997 p Censored (174.470/95) likely collar failure August 1997. o Composed of 30-18+ and 108-30+ months old females. I-' 10 0'1 �Table 7. Survival rates, inclusive of nonhunting and hunting mortalities, for winter-spring (WS 1 December14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 1998 for radio-collared adult female elk age ~24 months. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(l-S)/n collars. Elk Age and Time Period (WS or SF dates) Adult Adyl!;; Adult 8,gult Agylt; 8,gylt; Agylt 8,gylt; Agyl!;; WS SF WS SF SF WS WS SF WS 1995 1995-96 1996· 1996-97 1997 1997-98 1994-95 1994 1993-94 0.93 0.89 0.93 0.99 0.89 0.98 0.82 0.93 0.95 Survival 0.84 0.88 0.88 0.97 0.84 0.96 0.87 0.72 0.90 L 95% CI 0.98 0.99 0.95 1. 00 0.95 1.00 0.91 0.99 1.00 U 95% CI 112 97 89 100 122 108 61 65 62 n collars 1b 1d 0 0 0 2c 0 0 cenaoxed0 7 6 12 1 13 2 4 12 3 Died 3 1 0 0 0 1 1 1 1 Nonhunt ·3 11 7 1 13 1 3 11 2 Hunt • Censored o Censored denotes collars collar failure or life/death (174.441/95) (174.580/95) status unknown. S d Censored Censored collar collar (172.011/93) 174.470/95) Table 8. Survival rates, inclusive of nonhuntng and hunting mortalities, for winter-spring (WS, 1 December14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 1998 for the group of adult female elk age ~18 months when radio-collared in December 1993. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(l-S)/n collars. Elk Age and Time Period (dates) Adult Adult 8,dylt Agylt; 8,dult Agyl!;; Adyl!;; 8,gl.l.lt My,lt WS SF SF WS WS SF WS SF WS 1995 1995-96 1996 1994-95 1996-97 1997 1994 1997-98 1993-94 0.93 0.92 0.88 1. 00 0.93 0.94 0.82 0.97 0.96 Survival 0.85 0.78 0.84 0.85 0.87 0.72 0.92 0.91 L 95% CI 0.97 1.00 1.00 0.99 1.00 0.91 1.00 1.00 U 95% CI 49b h 53b f 42h 65b f 68b e 391 361 36j 34j n collars 19 0 0 0 0 0 0 0 censor-ed- 0 d c 3 3 6 0 4 2 12 1 3 Died 0 3 0 0 1 0 0 1 1 Nonhunt 0 3 6 0 3 2 11 1 2 Hunt • Censored denotes collar failure or life/death status unknown o Collar (172.649/93) disappeared 1994 hunt seasons. • Composed of 6-·18+ and 62-30+ month old fe!llales. • Censored (172.011/93) collar failure April 1994. , Composed of 100% females 48+ months old. Includes (172.011/93) collar failure April 1994 but seen Jan. 1996. Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead. , Composed of 100% females 24+ months old, h Composed of 100% females 36+ months old. l Composed of 100% females 60+ months old. b d I-' 10 -.J �Table 9. Summary of summer-fall (15 June-30 November) and winter-spring (1 December-14 June) survival rates inclusive and exclusive of hunting deaths among different age groupings of adult females averaged among years, 1993-94 - 1997-98. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(l-S)/n elk-years. Winter-Spring Average 5 Years Summer-Fall Average 4 Year's Age Grouping survival ±95% CI Elk-years Age Grouping Survival ±95% eI Elk-years Includes Hunting Age ~12 monthsb Age ~24 monthsC 1993 Cohortd Deathsa 0.90 0.89 0.88 0.03 0.03 0.05 524 396 189 Age ~18 months Age ~30 months 1993 Cohort 0.97 0.96 0.95 0.01 0.02 0.03 547 420 233 Excludes Hunting Age ~12 monthsb Age ~24 monthsC 1993 cohortd Deathse 0.99 0.99 0.99 0.01 0.01 0.01 476 354 167 Age ~18 months Age ~30 months 1993 Cohort 0.99 0.98 0.98 0.01 0.01 0.02 536 410 227 "Includes "Includes dIncludes "Includes hunting and natural deaths. bIncludes all females age ~12 months. only females age ~24 months by censoring yearling females recruited from calves. only females in 1993 trapped cohort having age 18 months to 10+ years. only natural deaths and represents natural survival rate. Table 10. Annual survival rates from 1 December-30 November each year 1993-94 - 1996-97 and overall survival through 14 June 1998 for the group of adult female elk age ~18 months when radio-collared in December 1993. Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance S(1S)/n collars. Survival L 95% CI U 95% CI n collars censor-ed" Died Nonhunt Hunt Adult 19931994 0.78 0.68 0.88 68b•e 0 15C 2 13 Elk Age and Time Period Agult Adult Adult 19961995 1994 1997 1996 1995 0.94 0.86 0.84 0.87 0.75 0.75 1. 00 0.97 0.93 53b•f 36i 429 1h 0 0 d 2 6 10 0 3 1 2 3 9 " Censored denotes collar failure or life/death status unknown. " Collar (172.649/93) disappeared 1994 hunt seasons. • Composed of 6-18+ and 62-30+ month old females. 9 Composed of 36+ month old females. I Composed of 48+ month old females. (dates) AgyH 19931998 0.51 0.39 0.63 67 1h 33 6 27 Includes collar (i72.011/93) failed 4/1994 but seen alive 1/1996. Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead . ' Composed of 100% females 24+ months old. h Censored (172.011/93) failure 4/1996. b d •.... 10 co �Table 11. Correction factors calculated to estimate total numbers of elk removed by all sources of hunting mortality from total numbers of elk 'legally removed' by hunting during 1994-1997 hunting seasons. Wounding Illegal Legal Total Correction Elk Sex/Age Class Or Loss Killb .xi u> xu iKilledc Factord Hunting Season fQ~ ~~~L8S~ ~lg~~~~ 57 7 2 66 0 1 12 13 1.16 1.11 e 41 15 3 59 1.44 35 12 3 50 1. 43f 37 14 2 53 1. 43 5 1 1 7 1.40 44 6 2 52 1.18 26 9 0 35 1.35 Rifle Late Season for Females Age ~ 12 months 6 3 3 12 2.00 Archery for Males Age ~ 99 0 0 9 1. 00 4 3h 0 7 1. 75 4 1 0 5 1.25 Males Age ~ 24 months Males Age 12-23 months Females Age ~ 12 months Females Age ~ 12 months Females Age ~ 24 months Females Age 12-23 months EQ~ Hynting ~easQn~ Rifle pt, 2nd, & 3rd for Males Age ~ 24 months Rifle pt, 2nd, & 3rd for Females Age ~ 12 months 24 Archery for Females Age ~ months 12 mbnths Muzzleloading for Males Age ~ 24 months Muzzleloading for Females Age ~ 12 months 0 5 0 5 1. 00 • Legal kill equals known-killed plus dl.sappeared during hunting seasons and assumed legally killed. These eLk represent kill that could be estimated by hunter harvest surveys. b Wounding loss and illegal kills would not be estimated by hunter harvest surveys. Total elk removed by all sources of hunting. d Multiply legal kill by correction factor to estimate total elk removed by hunting. For yearling males, mUltiply modeled numbers of yearlings by 1.11 if yearling males are not legal quarry . • Removal rate measured from known illegal hunting. ! Correction factor calculated without including mortalities associated with late rifle seasons. 9 Includes one legal kill that may have been from either archery or muzzleloading seasons. h Includes one wounding loss that may have been from either archery or muzzleloading seasons. the legal C estimates of I-' 10 10 �Table 12. Data matrix for simple population model using spreadsheet software. We used a post-hunt (December) population composition of 50 calves:100 females age L12 months and 4 adult males:16 yearling males:100 adult females and an estimated population of 3,600 elk. Fall Hunting Natural Survival Natural Survival Removal Rate Elk Sex/Age Class Rate Winter-Spring Rate Summer-Fall Elk Sex/Age Class 0.80 Adult Males 1. 00 1. 00 Adult Males Age L30 months Age 2.24 months Yearling Males Age 12-17 months 1. 00 0.11 Yearling Males Age 18-23 months 0.98 Adult Females Age L 24 months 0.99 0.11 Adult Females Age 2.30 months 0.98 Yearling Females Age 12-17 months 1. 00 0.05 Yearling Females Age 18-23 months 0.98 Calves Age 0-5 months 1. 00 0.02a Calves Age 6-11 months 0.89 • Estrmated from harvest surveys. IIJ o o �201 Table 13. Elk counted during quadrat and nonrandom flights on 44 mi2 in West Divide and Alkali creeks, GMU 42, 27 February-2 March,1998. Survey Marked Elk Unmarked Total Marked/ Flight Flight Available Seen Elk Seen Elk Seen Unmarked Hours Quadrats 34A 27 744 771 0.036 17.2 NonRandom-1 38 12 420 432 0.029 3.6 NonRandom-2 38 17 534 551 0.032 4.4 Totals 38 56 1698 1754 0.033 25.2 a Four elk off sample area during quadrat counts were on sample area during nonrandom flights. Table 14. Summary of quadrat flights for each observer, 27 February - 1 March, 1998. Total Minutes Marked Elk/ Sighting Trial Seen/ Flown/. Observer Quadrats Total Unmarked Quadrat Quadrat Marked Elk (Date) Flown (Range) (Range) Seen(%) Missed Elk Seen Seen 20.6 1B 18 371 0.039 18.5 14 1 (0-68) (2/28) (0.93) (10-27) 2E (2/27) 17 3M (3/01) 9 loa 5 314 0.040 18.5 (0-55) 17.8 (10-35) 1 86 0.012 9.6 (0-29) 25.4 (18-39) (0.67) 1 (0.50) 17.5 19.7 771 0.036 25 7 (0-68) (10-39) . (0.78) aTwo elk groups each contained 2 marked elk that were seen but each group represented only 1 sighting trial. Observer 2E saw a total of12 marked elk. Totals 44 Table 15. Status of marked elk missed on quadrats during sighting trials and subsequently found using telemetry. Marked Statul2When Marked Elk Foynd %Snow %Screening Group Elk Cover Cover Habitat Observer Missed Size Behavior Sex 100 Juniper 50 Standing 1 1 IB M 2E 5 F F M F M 1 sa 1 1A 1 Bedded Bedded Bedded Moving Bedded Oakbrush Oakbrush Oakbrush Oakbrush Oakbrush 70 70 70 70 60 100 100 100 100 100 2A 50 30 Juniper Standing 3M 1 F AThese 3 elk may represent groups or portions of groups of elk that were detected during quadrat counts but marked elk and other elk in the group were not seen due to elk behavior or vegetation. For all 3 groups, additional marked or unmarked elk were seen in close proximity. �202 Table 16. Frequencies at which individual marked elk were seen during quadrat and nonrandom flights, 27 February-2 March, 1998. Maximum frequency equals 3. Frequencies represent heterogeneity of sighting probabilities among elk Total Marks Frequency Seen During Flightsa Frequency Seenb Seen 0 1 2 3 1 56 5 20 8 5 5 a Of the 56 marked elk seen, 46 or 82% were individually identified by numbers/symbols on the collars or telemetry frequency. Elk not identified had lost the numbers/symbols on collars and were seen during nonrandom flights. b Includes 5 observations of elk seen but not individually identified. C Of the 5 elk not seen, 3 were females and 2 were males. Table 17. Estimated numbers of elk in survey area based on quadrats, sighting bias adjusted quadrats, and Bowden and Immigration-Emigration Joint Hypergeometric mark-resight estimators calculated using program NOREMARK. Both mark-resight estimators account for populations not closed to movement during time of surveys. Conf. Int. Width 25% Conf. Limits Total Elk Upper Percenta Lower Elk Estimator Estimate 771 Quadrats 944 14 124 882 820 Quadrats Adj. Model 1b c 952 814 16 138 Quadrats Adj. Model 2 883 14 116 915 857 799 Quadrats Adj. Model 3d 1,430 457 973 39 Bowden Estimator 1,179 1,337 370 33 967 Imm/EmmJHE Estimator l,115e a Width as percent of total estimate. b Quadrat counts adjusted; (LOG GROUP SIZE)+(INTERCEPT); AIC=172. C Quadrat counts adjusted; (LOG GROUP SIZE)+(BEDDED)+(INTERCEPT); AIC=160. d Quadrat counts adjusted; (LOG GROUP SIZE)+(BEDDED)+(%COVER)+(INTERCEPT); AIC=154. e Represents daily population estimate on sample area. Extant population estimate was 1,162 elk. Table 18. February-1 Total Groups 148 Number and size of elk groups seen during quadrat March 1998. FI:~gyen!;;;:l!: of Grou:Q Sizes Seen 25-30 10-24 7-9 4-6 1 2-3 2 18 21 34 35 38 counts, 27 Average Group Size 5.2 �203 Table 19. Radio-collared elk captured as calves on winter range in GMU 42 during December 1996 that dispersed out of GMU 42 to a new winter range as of March 1998. Locations (GMUs) determined by aerial telemetry. Trap New Frequency Zone Agea Sex GMU Location Description porcupine Creek-Holms Mesa 172.899/96 G 21 F 42 West 173.450/96 Wallace Creek-Samson Mesa G 21 M 42 West East Fork Wallace Creek 173.789/96 42 West G 21 F Low Beaver Creek 173.870/96 G 21 F 42 West Plateau Creek-Hayes Mesa 174.059/96 G 21 M 421 Taughenbauh-Grass Mesas 174.220/96 F 21 42 West M Porcupine Creek-Holms Mesa 174.789/96LE G 21 M 42 West 174.929/96 D 421 Pole Gulch-Collier Creek 21 F East Muddy-Little Henderson Creek 174.949/96LE D 21 521 F Hawxhurst Creek~Grassy Gulch 174.969/96 D 421 F 21 East Muddy-Little Henderson Creek 174.998/96 E 521 21 F Hawxhurst Creek 175.020/96 F 421 21 F Low Beaver Creek 175.039/96 G F 42 West 21 West Muddy-Ault Creek 175.050/96LE E 521 F 21 42 West Wallace Creek-Sugarloaf Mtn. 175.070/96 E F 21 Low Fourmile Creek 175.089/96 A F 43 21 Wallace Creek-Sugarloaf Mtn. 175.180/96 E M 42 West 21 Plateau Creek-Red Mountain 175.189/96LE E M 421 21 Low Wallace Creek-High Mesa 175.199/96 G M 42 West 21 a b Age of elk in months as of March 1998. LE = Location elk routinely located. �204 Appendix I. Mortalities of 181 radio-collared elk from 1 December 1993 through 14 June 1998. Age is aBeroximate age in years of elk at death: C=calf age 6-11 months, Y=yearling age 12-23 months. Frequency 101 Q~ath Ira!2 Age Year Ca~tured Site Zone Sex Date Cause of Death & Code Number 172.030/93 BR A F 5 27-0ct-95 Legal kill second rifle season-47 172.039/93 GR B F 4 14-Jun-95 Unknown-suspect predation-30 172.070/93 BR A F 11 12-Feb-96 Unknown-11 172.080/93 GM A F 6 05-Nov-94 Legal kill third rifle season-48 172.090/93 GR B F 11 16-Jan-94 Wounding loss late rifle season-26 172.101/93 SR B F 8 14-0ct-96 Legal kill first rifle season-46 172.128/93 GC B F 8 31-0ct-96 Wounding loss second rifle season-44 172.139/93 F BC C 17 19-0ct-95 Wounding loss first rifle season-43 172.160/93 CC C F 3 23-0ct-94 Legal kill second rifle season-47 172.181/93 MC C F 3 03-Nov-94 Wounding loss second rifle season-44 172.201/93 GS C F 3 15-Nov-94 Wounding loss second rifle season-44 172.207193 SG 0 F 4 30-Nov-95 Disappear first rifle season-40 172.258/93 HY F C 3 04-0ct-94 Legal kill archery/muzzle season-27 1n.277/93 GS C F 3 04-0ct-94 Wounding loss archery/muzzle-24 172.290/93 SG 0 F 6 23-0ct-94 Legal kill second rifle season-47 172.290/94 SM 0 F 4 16-Sep-96 Legal kill muzzleloading season-34 172.300/93 AC E F 8 30-0ct-97 Wounding loss second rifle season-44 172.369/93 AC E F 3 18-Sep-94 Legal kill archery season-33 172.369/94 FM B F 4 14-Jan-96 Legal kill late rifle season-29 172.409/93 AC F E 8 29-0ec-94 Wounding loss late rifle season-26 172.459/93 MH E F 8 24-0ct-96 Legal kill second rifle season-47 172.509/93 FS H F 3 21-0ct-95 Legal kill second rifle season-47 172.542/93 FS H F 01-Feb-94 Mountain lion predation-3 6 172.549/93 PG H F 7 28-Nov-95 Legal kill late rifle season-29 172.570/93 PG H F 16 03-Nov-94 Wounding loss second rifle season-44 172.581/93 PG H F 3 17-0ct-94 Legal kill first rifle season-46 172.581194 FM B F 3 08-0ec-95 Legal kill late rifle season-29 172.590/93 PG H F 24-Apr-96 Unknown-11 5 172.610/93 PG F 04-0ct-94 Accident, birthing/calving-32 H 3 172.639193 PG F 14-Jun-96 Accident, birthing/calving-32 H 16 172.649193 PG F 30-Nov-94 Disappear first rifle season-40 H 2 172.658/93 PG F Legal kill third rifle season-48 H 5 02-Nov-97 16~Jan-95 172.670/93 PG H F Legal kill late rifle season-29 4 172.678/93 PG H F 22-0ec-94 Wounding loss late rifle season-26 9 172.690/93 FM B F 24-Jan-94 Illegal kill-7 8 172.699/93 Legal kill third rifle season-48 FM B F 7 05-Nov-95 Unknown-suspect predation-30 172.749/95 LS H F 11 07-Aug-96 172.800/93 Disappear second rifle season-41 SR B F Y 30-Nov-94 172.821/93 EG Legal kill archery season-33 B F 3 08-Sep-96 Legal kill third rifle season-48 172.890/93 F 06-Nov-96 BC C 3 Mountain lion predation-3 172.899/93 BC C F 18-Mar-94 C Legal kill first rifle season-46 172.950/93 GH 0 F 18-0ct-95 2 172.961/93 F 30-0ct-97 Disappear second rifle season-41 MG 0 4 173.000/93 25-Apr-94 Malnutrition-6 \lM G F C 07-Jan-98 Accident-fell-10 173.010/93 \lM G F 4 Legal kill first rifle season-46 173.041/93 M 19-0ct-95 GM A 2 27_'Oec-95 Legal kill late rifle season-29 173.060/93 MH E F 2 Illegal kill-7 03-Mar-98 173.070/93 MH E F 5 Legal kill second rifle season-47 173.081193 FS H F 3 22-Oct-96 Legal kill second rifle season-47 24-0ct-97 173.090/93 FS H F 4 Legal kill second rifle season-47 173.100/93 F 30-0ct-97 FS H 4 Legal kill first rifle season-46 .14-Oct-95 173.120/93 GM A M 2 Wounding loss second rifle season-44 31-0ct-96 173. 140i93 PG H F 3 Legal kill third rifle season-48 173.160/93 FS F 13-Nov-96 H 3 Illegal kill second rifle season-50 BC 29-0ct-94 173.190/93 C M Y Wounding loss thtrd rifle season-45 173.201193 GR M 30-Nov-95 B 2 Legal ki II first rifle season-ee 19-0ct-95 173.210/93 GC B M 2 Illegal kill archery/muzz. season-8 30-0ct-97 173.210/96 LM 0 M 2 Legal kill third rifle season-48 06-Nov-95 173.219/93 BC M 2 C Illegal kill second rifle season-50 15-Nov-94 M Y 173.232193 BR A 18-Mar-94 173.262/93 BC M C Unknown-" C Legal kill first rifle season-46 M 12-0ct-96 173.262/94 HM B 2 Legal kill third rifle season-48 06-Nov-95 173.269/93 MC C M 2 Legal ki LL. first rifle season-46 12-0ct-96 MC 3 173.279/93 C M Unknown-11 22-Mar-94 MC C M C 173.289/93 Legal kill muzzleloading season-34 M 18-Sep-96 173.289/94 PR A 2 Legal kill second rifle season-47 24-Oct-95 GS C M 2 173.300/93 Illegal kill first rifle season-49 30-Nov-94 HY C M Y 173.309/93 Illegal kill first rifle season-49 20-0ct-94 HY C M Y 173.320/93 Legal kill archery season-33 14-Sep-96 HM M 2 173.320/94 B !~~}~L~~ _____ ~~__E_____ ~____ ~___ ~~~~~~:?] ______ ~~2!_~L~~~!~~~~2~l~[_s:2~~~:~~ __________________ . �205 A~ndix I. (continued) Frequency 10/ Ira~ Year CaE!tured Site Zone 173.340/93 D SG 173.351/93 SG D 173.359/93 AC E 173.370/93 MH E 173.370/96 RG E 173.381/96 RG E D 173.390/93 MG 173.402193 MG D 173.410/93 WM G WM 173.420/93 G 173.429/93 MH E 173.439/93 PG H 173.450/93 PG H 173.461/93 PG H 173.461/94 CM A 173.469/93 FS H 173.469/94 PR A 173.479/93 FS H 173.492/93 FS H 173.502193 FS H 173.510/93 FM B 173.521/93 FM B 173.540/94 OG B B 173.549/94 HM 173.569/94 PR A A 173.580/94 PR 173.589/94 OG B 173.610/94 BC C 173.640/94 MC C 173.640/96 GM A 173.649/94 BC C BG 173.689/94 E 173.789/94 E MR MM F 173.819/94 MM F 173.829/94 173.859/94 SM D 173.870/94 SM D 173.919/94 BC C 173.929/94 BC C 173.939/94 BC C BC 173.959/94 C C 173.970/94 MC 173.981/94 MP D 173.990/94 BC C 174.001/94 BG E E 174.009/94 BG BG E 174.019/94 MR E 174.039/94 174.049/94 MM F E 174.059/94 MR E 174.069/94 BG 174.080/94 MR E E 174.090/94 MR ,174.101/94 F MM 174.109/94 MM F F 174.119/94 MM 174.119/95 GB B F 174.129/94 MM 174.140/94 MM F B 174~140/95 GB F 174.150/94 MM F 174.160/94 MM FM B 174.170/94 FM B 174.181/94 MS F 174.200/95 MS F 174.210/95 MS F 174.220/95 MS F 174.230/95 MD E 174.240/95 MS F 174.319/95 MD E 174.329/95 Sex M M M M M M M M M M M M M M M M M M M M M M M F F F F F F F F F F F F F F M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M F F Q~ath Date 20-0ct-97 05-Nov-95 06-Sep-95 08-Nov-95 08-Jan-97 19-Feb-97 30-Nov-95 18-0ct-95 02-Nov-95 24-0ct-95 14-Sep-95 30-Nov-95 15-0ct-95 07-Feb-94 19-5ep-95 25-Apr-94 20-0ct-96 10-Sep-95 03-Sep-95 13-Nov-96 28-Aug-95 17-0ct-95 t3-0ct-96 07-Sep-95 16-0ct-97 21-Dec-95 01-Jun-95 14-Nov-97 30-Mar-95 16-Mar-97 11-0ct-97 31-0ct-96 20-Mar-95 30-0ct-97 10-Jan-97 23-0ct-96 21-Feb-95 02-Nov-95 16-0ct-96 18-Sep-96 02-Nov-96 20-0ct-96 02-Nov-96 20-0ct-96 30-Nov-96 12-Oct-96 13-Noy-96 05-Sep-96 14-Sep-96 17-0ct-95 26-Sep-96 11-0ct-97 20-Oct-96 24-May-96 19-0ct-96 01-Mar-95 30-Noy-97 14-0ct-96 14-Mar-95 30-Noy-96 14-0ct-96 15-Sep-96 25-Apr-95 30-Nov-96 18-0ct-96 11-Oct-97 08~Apr-96 24-Apr-96 17-Apr-96 C 02-Oct-96 Y 03-Sep-96 Y Age 4 2 2 2 C C 2 2 2 2 2 2 2 C Y C 2 2 2 3 2 2 2 Y 3 Y C 3 C C 3 2 C 3 2 2 C Y 2 2 2 2 2 2 2 2 2 2 2 Y 2 3 2 Y 2 C 2 2 C Y 2 2 C 2 Y 2 C C !~~~3)2L~~ _____ ~~ ___~ ____ ~ ____ ~___ Cause of Death & Code Number Legal kill second rifle season-47 Legal kill third rifle season-48 Legal kill archery season-33 Legal kill first rifle season-46 Mountain lion predation-3 Unknown-suspect predation-30 Disappear first rifLe season-40 Legal kill first rifle season-46 Wounding loss second rifle season-44 Legal kill second rifle season-s? 'Legal kill archery season-33 Disappear first rifle season-40 Legal kill first rifle season-46 Malnutrition-6 Wounding loss archery season-50 Malnutrition-6 Legal kilL second rifLe season-47 Legal kill archery season-33 Legal kiLL archery season-33 Legal kill third rifle season-48 Legal kiLL archery season-33 Legal kill first rifle season-46 Legal' kill first rifle season-46 Legal kiLL archery season-33 Wounding loss first rifle season-43 Unknown-11 Unknown-suspect predation-30 Wounding loss third rifLe season-45 Unknown-suspect predation-30 Malnutrition-6 Legal kill first rifle season-46 Legal kiLL first rifle season-46 Unknown-suspect maLnutrition-31 Legal kill second rifle season-47 LegaL kill late rifle season-29 Legal kill second rifle season-47 Mountain lion predation-3 Illegal kill second rifle season-50 Legal kill first rifle season-46 Legal kill archery season-33 Legal ki II third riHe season-48 Legal kill second rifle season-47 Legal kill third rifle season-48 Legal kill second rifle season-47 Disappear archery/muzzLe season-21 Legal kill first rifle season-47 ILlegal kiLL rifle season-9 Legal kill archery season-33 Legal kilL muzzleloading season-34 Illegal kill first rifLe season-49 Wounding loss archery/muzzle-24 Legal kill first rifle season-46 Legal kill second rifle season-47 Unknown-suspect predation-30 Legal kilL second rifle season-47 Mountain lion predation-3 Wounding loss rifle season-25 Legal kill first rifle season-46 Mountai'n lion predation-3 Illegal kill third rifle season-51 Legal kill first rifle season-46 Legal kill muzzleloading season-34 Mountain lion predation-3 Disappear second rifle season-41 Illegal kilL first rifle season-49 Legal,kill first rifle season-46 Unknown-suspect malnutrition-31 Mountain lion predation-3 Mountain lion predation-3 Wounding Loss archery season-52 Legal kill archery season-33 lI~~~~:?~ ______ u_n!~2~JP~~~!~~:? _________________________________ : �206 Appendix I. (continued) Frequency 101 Ie!!!:! Year Captured Site Zone 174.349/95 MD E 174.360/95 MD E 174.401/95 AP D 174.420/95 AP D \JI) 174.478/95 C 174.491195 lB C 174.500/95 lB C 174.520/95 KR B 174.520/96 GM A 174.560/95 Bl A 174.609/95 GB B 174.629/95 MD E 174.639/95 MD E 174.679/95 HG E 174.689/95 AP D 174.689/96 EW G 174.700/95 AP 0 174.710/95 AP 0 VM 0 174.729/95 VM 174.740/95 0 VM 174.750/95 0 174.770/95 WD C WD C 174.780/95 174.789/95 WD C 174.800/96 BG E 174.809/95 WD C 174.820/95 WD C 174.830/95 lB C 174.851/95 lB c 174.861/95 KR B lB c 174.870/95 KR B 174.880/95 174.889/95 we G Bl A 174.899/95 lM 0 174.910/96 Be c 175.059/96 175.130/96 GM A lM 0 175.170/96 [1g!!!1:! Sex F F F F F F F F F F F M M M M M M M M M M M M M M M M M M M M M M M F F Age 2 Y F c M 2 2 2 2 C Y C y' C 2 2 Y C C 2 2 Y 2 2 2 2 C C Y 2 2 2 Y 2 2 2 2 c c c Date 13-0ct-97 22-Apr-97 22-Sep-96 11-0ct-97 13-Sep-97 10-Sep-97 16-Apr-96 21-Sep-96 25-Apr-97 14-May-97 '15-Apr-96 11-0ct-97 21-0ct-97 13-Nov-96 05-Feb-96 14-May-97 16-0ct-97 15-0ct-97 17-0ct-96 08-Nov-97 05-Nov-97 16-0ct-97 11-0ct-97 22-May-96 09-Apr-97 22-Apr-97 14-0ct-97 13-0ct-97 22-0ct-97 31-0ct-96 30-0ct-97 11-0ct-97 20-0ct-97 30-0ct-97 27-Feb-97 13-Feb-97 24-Mar-97 26-Mar-97 Cause of Death & Code Number legal kill first rifle season·46 Unknown-suspect predation-30 legal kill muzzleloading season·34 legal kill first rifle season-46 legal kill muzzleloading season-34 Wounding loss archery season-52 Unknown-suspect predation-30 legal kill muzzleloading season·34 Mountain lion predation-3 Illegal kill-7 Unknown-suspect predation-30 legal kill first rifle season-46 legal kill second rifle season-47 Illegal kill second rifle season-50 Mountain lion predation-3 Unknown-suspect malnutrition-31 Wounding loss first rifle season-43 legal kill first rifle season-46 Illegal kill first rifle season-49 legal kill third rifle season-48 legal kill third rifle season-48 Disappear first rifle season-40 legal kill first rifle season-46 Unknown-suspect predation-30 Mountain lion predation-3 Accident, fell-10 legal kill first rifle season-46 legal kill first rifle season-46 Illegal kill second rifle season-50 Illegal kill second rifle seasonc50 Wounding loss second rifle season·44 legal kill first rifle season-46 legal kill second rifle season-47 Wounding loss second rifle season·44 Unknown-suspect predation·30 Unknown-11 Mountain lion predation·3 Unknown-suspect malnutrition-31 �172 �171 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT Smteof ~C~o~lo~r~ad~o~ _ Mammals Research Project No. ---'W.:.,.--=1...:,5;::;..3-..:.R::....-=12=--_ Elk Investigations Work Package __ --=3::...:0:;,,::0:,:2'-_ Task No. ---=-1 _ Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size Period Covered: July 1, 1998 - June 30, 1999 Author: D. 1. Freddy Personnel: R. Adams; T. Beck J. Broderick, G. Byrne, D. Crane, R. Del Piccolo, J. Ellenberger, V. Graham, D. Homan, R. Kahn, K. Madariaga, D. Masden, C. Mehaffy, P. Neil, J. Olterman.J, Thompson, P. Will, K. Wright, S. Yamashita, D. Younkin, CD OW; D. Bowden, G. White.T, Gross, M. Kneeland, W. Andelt, CSU; D. Ouren, D. Schneider, T. Fancher USGS-BRD, BLM Glenwood Springs, CO, USFS Rifle, CO, Rocky Mountain Elk Foundation, cooperating. ABSTRACT We monitored survival and movements of 169 previously radio-collared elk composed of 136 adult females and 33 adult males from 1 July 1998 through 30 June 1999. Survival of adult females during summer-fall was 0.77 ± 0.07 (n = 136) inclusive of hunting deaths and 1.00 (n = 105) with hunting deaths censored while survival during winter-spring was 0.98 0.03 (n = 103). The 2 deaths of adult females during winter-spring were attributed to accident and malnutrition. Survival of adult males during summer-fall was 0.34 0.17 (n = 32) inclusive of hunting deaths and 1.00 (n = 11) with hunting deaths censored while survival during winter-spring was 1.00 (n = 11). A combination of unlimited either-sex elk hunting licenses and high numbers of antlerless elk hunting permits during rifle hunting seasons in 1998 contributed to removing 23% of the adult females which was sufficient to temper population growth. Progress continues towards developing habitat use models to predict areas important to managing elk. Draft manuscripts on elk survival rates and techniques to estimate population size are progressing. ± ± �173 ESTIMATING SURVIVAL RATES OF ELK AND DEVELOPING ESTIMATE POPULATION SIZE TECHNIQUES TO David 1. Freddy P. N. OBJECTIVE Estimate survival rates of adult female, adult male, and calf elk and develop techniques to estimate population size. SEGMENT OBJECTIVES 1. Estimate winter, summer, and annual survival rates of adult female and male elk from fates of previously radio-collared elk. 2. Develop an initial habitat use prediction model for elk inhabiting oakbrush dominated habitats based upon locations of radio-collared elk obtained from 1993 -98. 3. Analyze data, summarize annually in Federal Aid Job Progress Report, and prepare draft manuscripts regarding elk survival rates and techniques to estimate population size. INTRODUCTION Our objectives are to provide reliable estimates of survival rates for calves during winter and for adult females and males throughout the year and to develop and test a system to estimate elk densities on winter ranges. Estimates of calf survival were obtained during winters 1993-94 through 1996-97 and summarized in Freddy (1997). We are continuing to obtain estimates of survival for adult males and females. For adults, we are interested in survival rates inclusive of hunting mortalities to document human-induced rates of survival and exclusive of hunting mortalities to estimate natural rates of survival. We are evaluating a system for estimating population size or density that incorporates estimates of sighting bias in conjunction with random sampling of search quadrats as sample units. Our winter study area encompasses about 324 rnf (839 knr') in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado. This area is part of the Grand Mesa Elk Data Analysis Unit E-14. Elk winter habitats include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnifolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields below elevations of9,800 ft. In summer, elk use oakbrush-mountain shrub, aspen, and subalpine fir-Engelmann spruce (Abies lasiocarpa-Picea engelmannii) meadow systems throughout the Grand Mesa region up to elevations of 12,000 ft. (Freddy 1993). METHODS We placed radio collars (172-176MHz) having mortality sensors on elk calves age 6 months and adults age 2:18 months during December 1993-1996 (Freddy 1997). Elk were captured using helicopter net-gunning and portable corral traps (Freddy 1997). During 1998-99, we monitored 169 adult elk, 136 females and 33 males, having functioning radios as of July 1998. Collars were white and had black identification symbols on dorsal surfaces of collars to allow visual identification of individual elk. �174 Estimating Elk Survival Rates We monitored survival of radioed elk with aerial surveys using a Cessna 185 at 2-4 week intervals from December 1993 to June 1999 and with daily ground surveys from December-April each year from 1993-94 to 1996-97. Survival rates (S) of radioed elk were calculated using the binomial estimator with a variance, V AR(S) = S(I-S)/n collars (White and Garrott 1990). Survival rates are expressed as the mean estimate the 95% confidence interval. We used x2-contingency tests to compare survival rates between sexes and among time intervals (pROC FREQ, SAS 1988). Sample sizes refer to numbers of individual radioed elk. We defined 3 major time intervals for survival analyses: winter-spring was 1 December to 14 June, summer-fall was 15 June to 30 November, and annual was 1 December to 30 November to coincide with timing of capture and collaring. For adult elk during these time intervals, we calculated survival rates inclusive of natural and hunting-related mortalities, exclusive of hunting mortalities, and exclusive of natural mortalities. Excluding, or censoring hunting mortalities, provided estimates of natural survival rates. Excluding natural mortalities but including hunting mortalities provided estimates of hunting removal rates. Censoring elk associated with categories of mortalities reduced sample sizes used to estimate survival rates. Elk were also censored ifradios failed or if their life/death status was unknown after an extended period of time. Archery, muzzleloading, and rifle hunting seasons occurred from about 1 September to 15 November each year during the summer-fall time interval. Late-rifle seasons occurred in some years . and restricted hunters to taking only antlerless elk from about 25 November-31 January which included portions of the summer-fall and winter-spring time intervals. Yearling spike-antlered males were generally not legal quarry in most areas frequented by radioed elk. Male elk were legal quarry when branch-antlered usually at age 2 years. Cause of death of radioed elk recovered in the field was estimated from presence or absence of gunshot wounds or bite wounds on carcass, predator tracks or scat at carcass site, physical positioning of carcass remains whether buried, covered, scattered, or consolidated (Wade and Browns 1982, Halfpenny and Biesiot 1986), relative amount of internal fat and marrow fat if present with carcass, and results of histopathology and marrow fat analyses. Fat content (percent dry matter) of bone marrow and estimates of age based on dental cementum were obtained for dead elk by the Colorado Division of Wildlife Laboratory while histopathology analyses were provided by the Colorado State University Veterinary Diagnostic Laboratory. Photographs were taken of nearly all mortalities so that physical evidence could be reviewed and judged by outside experts (pers. comm. T. Beck, W. Andelt). ± Elk Movements and Habitat Use Models We continued to precisely locate selected radioed elk at least once per month since their capture to document seasonal movements using a Cessna 185. These elk were originally selected at random from within trap zones and equalized by age class in January 1994. Elk from the original sample that died were replaced each subsequent January with randomly selected elk that were usually of the same sex, age class, and trap zone as elk that died. All replacement elk in January 1999 were ;:::2-years old. As of 1 January 1999, these 43 elk were classified as 32 adult females and 11 adult males males. During June 1999, we again located an additional 28 adult females that were originally selected at random in 1995 to document their locations during the calving period. Females from the original 1995 sample that died were replaced each subsequent June with adult females randomly selected from the same trap zones of elk that died. As needed, we located other elk to document unusual movements. We continue to cooperate with the USGS-BRD, USFS, and BLM with the support of the Rocky Mountain Elk Foundation to create a GIS database allowing analyses relating elk locations, movements, and home ranges to habitat components with the intent of developing a predictive habitat use model. During 1998, initial efforts were undertaken to develop a model with Dr. 1. Gross at the Natural Resource Ecology Laboratory at Colorado State University. �175 Elk habitat models are being developed by using a staged process. Major stages included initial data analysis and reduction, development of predictive variables (i.e., GIS coverages), and . development and statistical analysis of alternative habitat models. Initial data analysis included an extensive process to locate and correct errors in the data set, create new variables (e.g., age, class, season), and to subset the data so that analyses included only the animals of interest. This first stage of this process was accomplished by developing a database application in MicroSoft Access© that validated data records and produced new tables with the data needed for further analysis. The entire data set consisted of 5,321 elk locations. We reduced the data set to include only data from elk that were randomly selected and systematically located during years 1993-1998. This reduced total elk locations to 2,888. Locations were subset into groups by sex, age (calf, yearling, adult), and season. Seasons were biologically defined as spring (1 April- 30 May), summer (1 June - 31 August), fall (1 September - 30 November), and winter (1 December - 31 March). Using ArcInfo© and Ar~VieW©, we linked each location to GIS coverages for elevation, slope, aspect (EW and NS), distance to a road, and to tasselcap indices for brightness, greenness, and wetness. To evaluate the ability of these variables to predict elk observations, we used ordinary least squares (Upton and Fingleton 1985) to identify significant relationships arid coefficients that were used for logistic regression. RESULTS AND DISCUSSION Between 1 December 1993 and 14 June 1999,235 radioed elk died of which 31 were calves 611 months old and 204 were adults ~12 months old (Table 1, Appendix I). Calves died of natural causes (Freddy 1997) while for adults hunting accounted for 93% of 204 deaths. Hunting accounted for 98% of 102 deaths for adult males and 88% of 102 deaths for adult females. . Survival Estimates Adult Females Summer-Fall Survival during summer-fall 1998 for adult females all age 2:.24 months was 0.77 ± 0.07 (n = 136) inclusive of hunting deaths and 1.00 (n = 105) with hunting deaths censored (Table 6). Net survival in 1998 was the lowest measured during 5 summer-fall periods due to increased hunting deaths that resulted in a hunting removal rate of 23%. Reduced survival due to hunting in 1998 was evident in all cohorts offemales (Tables 2-5,7,8). Natural survival rates remained >0.99 during all 5 years (Table 6). Increased hunting removal rates were caused by a combination of increased numbers of limitedentry rifle antlerless permits and first-time use of unlimited over-the-counter rifle either-sex permits. Unlimited either-sex permits were valid in Game Management Units (GMUs) 43,52, and 521 during the second and third rifle seasons while limited antIerless permits were available for GMUs 42 and 421 for the first, second, and third rifle seasons. These GMUs collectively encompassed the area inhabited by radioed female elk. Approximate locations of each radioed female were obtained prior to each season, each elk was assigned to a GMU, and life/death status of each elk was known prior to and following each season. During the second rifle season, adult female removal rates were greater in areas having unlimited either-sex permits (26%) than in areas having limited antIerless permits (6%) (P=O.OOI, X2 =10.7, dJ=I). During third rifle season, removal rates were not different between types of permits (P=0.53, X2 =0.39, dJ=I)(Table 10). Removal rates with antlerless permits were consistent between seasons while removal rates with either-sex permits declined drastically during the third season (Table 10). In this geographic area, unlimited either-sex permits provided a burst of female removal only during the second season. �178 Prepared by _ David J. Freddy Life/Science Researcher Table l. Causes of deaths in radio-collared elk between 1 December 1993 and 14 June 1999. Calves (M=male, F=female) were age 6-11 months and collared at age 6 months. Yearling males and females .were age 12-17 months and juvenile males and females were age 18-23 months and all were collared at age 6 months. Adult males and females were age >24 months at time of death. Elk Age/Sex Class at Death Adult Total Cause of Death Calves Yearling Juvenile M F M All and -Code M F M F M F F Natural Causes 0 3 Malnutrition-6 2 0 0 0 2 5 2 0 Unknown-Suspect Malnutrition-31 0 0 3 1 3 1 0 0 0 0 4 Predation-Lion-3 0 0 1 8 5 13 8 4 0 0 0 0 Predation-Bear- 35 0 0 0 0 0 0 0 0 0 0 0 0 0 Unknown Predator-5 0 0 0 0 0 1 1 1 Unknown-Suspect 0 Predation-30 2 1 1 2 3 8 11 5 0 0 Accident-Birthing-32 0 0 0 2 0 2 0 0 0 0 2 Accident-Fell-IO 0 1 0 0 2 2 0 0 0 1 3 Unknown Cause-l l 2 0 0 2 4 1 0 0 1 2 6 Subtotals 10 26 45 14 Q Q Q £ £ 12 11 Le~1 Hunting Arc ery-33 0 0 0 0 9 3 9 5 0 2 14 ·4 Muzzleloading-34 0 0 0 0 8 2 8 12 0 2 0 0 0 0 0 1 0 1 0 0 1 Arch~lMuzzle-27 28 28 Rifle- irst-46 0 0 0 0 0 0 11 11 39 15 15 17 Rifle-Second-47 0 0 0 0 0 17 32 0 0 0 9 12 9 12 Rifle- Third-48 0 0 0 0 21 0 0 0 0 0 6 6 6 Rifle-Late-29 0 0 0 69 52 56 69 125 Subtotals Q Q Q Q Q 1. Wound~Loss 0 2 2 2 Archery uzzle-24 0 0 0 0 0 2 4 0 0 0 1 1 2 3 Archery-52 0 0 1 1 0 0 1 3 1 Rifle-First-43 0 0 0 0 3 4 Rifle-Second-a-t 0 0 0 0 0 4 10 4 10 14 0 2 2 Rifle- Third-45 0 0 0 0 0 1 1 3 0 0 r 1 Rifle-Unk.Reg.-25 0 0 0 0 0 0 0 1 0 0 0 Rifle-Late-26 0 0 0 0 0 3 3 3 10 20 Subtotals 32 Q Q Q Q 11 £1 1 1 Illegal Hunting 0 5 Rifle-First-49 0 5 0 0 0 0 5 0 0 6 Rifle-Second-50 0 5 0 0 I 0 0 6 0 0 -. 0 0 Rifle-Third-51 1 0 0 0 0 1 0 1 0 0 0 1 0 0 Rifle-Unk.Reg.-9 0 0 0 0 1 1 0 I 0 0 0 0 1 0 1 Archery Season-8 0 0 Out-of-Season-7 0 0 0 1 0 2 0 3 3 0 0 0 12" Subtotals }. Q Q Q 11 1 £ £ 11 Presumed Hunting" Missing-ArchMuzz-21 0 0 1 0 0 0 0 0 0 1 1 3 3 Missing-Rifle Ist-40 0 0 0 0 0 0 3 3 6 Missing-Rifle 2nd-41 0 0 0 2 6 2 7 0 1 0 9 Missing-Rifle 3rd-42 0 0 0 0 0 0 0 0 0 0 0 Subtotals 10 16 Q Q Q Q .2 Q .2 .2 1 Totals 17 14 13 6 2 3 87 93 119 116 235 • These elk were illegally shot as spike-antlered yearling males: (173.190/93) (173.232/93) (173.309/93) (173.320/93) (173.919194) (174.059/94) (174.140/95) (174.200/95) (174.679/95) (174.729195) (174.861195) (173.210/96). (173.309/93) disappeared in 1994 during first rifle season when spike-antlered yearling males were not legal and was assumed to have been taken illegally. All other illegal deaths were confirmed. b These elk disappeared during hunting seasons and remained missing for several months and are assumed dead and legally harvested: (172.207193) (172.269193) (172.308193) (172.498193) (172.649/93) (172.800/93) (172.961/93) (172.991193) (173.390/93) (173.439193) (173.760/94) (174.001/94) (174.181/94) (174.770195) (174.929/96) (175.199/96). �Table 2. Survival rates, inclusive ofnonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 1999 for the cohort of calves age 6 months radio-collared in December 1993. Survival rate for male and female calves pooled when age 6-11 months was 0.92 (95% CI 0.86-0.98, n=73). Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(1-S)/n collars. Elk Elk Age (months) and Time Period (WS or SF dates) 6-11 (mos) 12-17 18-23 24-29 30-35 36-41 42-47 48-53 54-59 60-65 66-71 6-71 WS SF WS SF WS SF WS SF WS SF WS ALL 1993-94 1994 .1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1998 1998-99 1993-99 0.88 0.78 0.99 32 0 4b 0 4 1.00 0.76 0.99 28 0 0 0 0 0.21 1.00 0.06 0.37 4 0 0 0 0 0.50 0.00 0.00 4 22 0 2 1.00 0.00 1.00 2r 0 0 0 0 0.00 0.97 0.87 1.00 35 0 1.00 0.92 1.00 34 0 0 0 0 0.97 0.91 1.00 33 0 1 0 1 0.84 0.91 1.00 32 0 5 0 5 1.00 0.71 0.97 27 0 0 0 0 0.89 MALES Survival 0.89 L 95%CI U 95%CI n collars 36 Censored" Died 4 Nonhunt 4 Hoot 0 28< 0 224 0 22 1 0 1 0 1 0.00 33 1& 3-'& 33 4 29 FEMALES Survival 0.95 L95%CI U95%CI n collars 37 Censored" Died 2 Nonhunt 2 Hoot 0 Ih 0 1 0.97 34 0 1 0 1 27 0 31 0 3 0.96 0.76 1.00 24 0 1 1 0 0.87 0.87 1.00 23 0 31 0 3 1.00 0.72 1.00 18 0 0 0 0 0.51 0.34 0.69 35 21t 17 '3 14 2 • Censored denotes collar failure and/or animallifeldeath status not known. b Collar (173.309/93) disappeared 1994 hunting seasons and assumed dead. e Includes (173.241193) collar failure August 1995 but seen January 1996. d Collars (173.390/93),(173.439/93) disappeared 1995 hunting seasons and assumed dead. • Censored elk; (173.241193) failed August 1995, (173.381193) slipped collar December 1995. r Includes (173.340/93) alive May 1997. I Censored elk (173.249/93) slipped collar September 1997. k Collar (172.800/93) disappeared 1994 hunting seasons and assumed dead. i Collar (172.961193) disappeared 1997 hunting seasons and assumed dead. j Collar (172.991193) disappeared 1998 hunting seasons and assumed dead. k Censored elk (172.849/93) failed May 1999, (173.151193) failed February 1999. ..... .....) \0 �Table 3. Survival rates, inclusive ofnonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1994-14 June 1999 for the cohort of calves age 6 months radio-collared in December 1994. Survival rate for male and female calves pooled when age 6-11 months was 0.90 (95% CI 0.83-0.97, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(1-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 6-11 (mos) 12-17 WS SF 1994-95 1995 0.91 0.81 1.00 33b 0 3 3 0 0.90 0.79 1.00 30b 0 .0.97 0.78 0.99 32 0 1 0 1 0.97 0.91 1.00 30 0 1 1 0 18-23 ./ 24-29 30-35 36-41 42-47 48-53 54-59 6-59 WS SF WS SF WS SF WS ALL 1995-96 1996 1996-97 1997 1997-98 1998 1997-98 1994-98 0.96 0.88 1.00 26 1c 1 1 0 0.08 0.00 0.19 25 0 23 0 23 1.00 1.00 0.00 0.00 2d 0 0 0 0 0.50 0.00 1.00 2 0 1 0 1 1 0 0 0 0 0 18 0 0 0 31 2 31 4 27 0.93 0.90 1.00 29 0.96 0.83 1.00 27 0 1 0 1 0.85 0.89 1.00 26 0 4 0 ·4 1.00 0.70 0.99 22 0 0 0 0 0.64 1.00 0.42 0.85 14 0 0 0 0 MALES Survival L 95%CI U 95%CI n collars Censored" Died Nonhunt Hunt 3 0 3 FEMALES Survival 0.89 L 95%CI U 95%CI n collars 36 Censored" Died 4 Nonhunt 4 Hunt 0 I" 2 0 2 • Censored denotes collar failure and/or animallifeldeath status not known. Includes (173.949194) collar failure December 1994 but seen January 1996 • Censored elk:(173.949194) collar failure, which was killed in fJISt rifle season 1996. d Includes (174.030/94) alive June 1997. • Censored elk: (173.719194) slipped collar May 1996. f Collar (173.760/94) disappeared 1998 hunting seasons and assumed dead. • Censored elk: (174.030/94) slipped collar September 1998. b 22 0 gf 0 8 0.40 0.23 0.57 35 0 21 5 16 •...• 00 0 �Table 4. Survival rates, inclusive ofnonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1995-14 June 1999 for the cohort of calves age 6 months radio-collared in December 1995. Survival rate for male and female calves pooled when age 6-11 months was 0.88 in 1995 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance of S(I-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 24-29 36-41 18-23 30-35 SF WS SF WS 1996-97 1997 1997-98 1998 6-11(mos} WS 1995-96 12-17 SF 19.96 MALES Survival L 95%CI U 95%CI n collars Censored" Died Nonhunt Hunt 0.86 0.74 0.98 35 2b 5 5 0 0.83 0.68 0.97 29 1c 5 0 5 0.96 0.87 1.00 24 0 1 1 0 0.23 0.04 0.41 22 4 Id I' 17 0 17 0 0 0 FEMALES Survival L 95%CI U 95%CI n collars Censored' Died Nonhunt Hunt 0.91 0.81 1.00 34 0 3 3 0 0.87 0.75 0.99 31 0 4 0 0.93 0.82 1.00 27 0 2 1 1 0.83 0.66 0.99 23 2f 4 0 4 1.00 4 1.00 18 I' 0 0 0 0.25 0.00 0.86 4 0 3 0 3 0.89 0.73 1.00 18 0 2 0 ·2 42-47 WS 1998-99 1.00 1 0 0 0 0 1.00 16 0 0 0 0 6-47 ALL 1995-99 0.03 0.00 0.10 32 5 31 6 25 0.52 0.33 0.70 .31 3 15 4 11 • Censored denotes collar failure and/or animal life/death status not known. Censored elk (174.619/95) slipped collar May 1996, (174.800/95) capture mortality. • Censored elk (174.660/95) slipped collar July 1996. d Censored elk (174.671195) likely collar failure July 1997. • Censored elk (174.190/95) slipped collar May 1998. r Censored elk (174.441195) slipped collar August 1997 and (174.580/95) collar failure July 1997. I Censored elk (174.470195) collar failure December 1997. . b .... 00 .... �Table 5. Survival rates, inclusive ofnonhunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 1999 for the cohort of calves age 6 months radio-collared in December 1996. Survival rate for male and female calves pooled when age 6-11 months was 0.86 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance ofS(I-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 6-11 (mos) 12-17 18-23 24-29 30-35 6-35 WS SF WS SF WS ALL 1996-97 1997 1997-98 1998 1998-99 1996-98 0.85 0.73 0.98 34 0.97 0.90 1.00 29 0 1 0 1 1.00 1.00 28 0 0 0 0 0.36 0.17 0.54 28 0 184 0 18 0.29 0.14 0.45 34 1 24 1.00 0.80 MALES Survival L 95%CI U 95%CI n collars Censored' Died Nonhunt HWlt Ib 5 5 0 10 0 0 0 0 5 19 FEMALES Survival 0.86 L 95%CI U 95%CI n collars 35 Censored' Died 5 Nonhunt 5 Hunt 0 1.00 0.74 0.98 30 0 0 0 0 30 0 0 0 0 30 0 6< 0 6 • Censored denotes collar failure and/or animallifeldeath status not known. Censored elk. (174.619/96) capture mortality. C Collar (174.929/96) disappeared 1998 hunting seasons and assumed dead. d Collar (175.199/96) disappeared 1998 hunting seasons and assumed dead. b 1.00 0.65 0.95 24 0 0 0 0 0.69 0.53 0.85 35 0 11 5 6 o •... 00 N �Table 6. Survival rates, inclusive ofnonhunting and hunting mortalities, for winter-spring (WS 1 December-14 June) and summer-fall (SF, 15 June30 November) time periods from 1 December 1993 - 14 June 1999 for all radio-collared adult female elk age 2:,12months. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(1-S)/n collars. Adult WS Adult SF Adult WS Elk Age and Time Period (WS or SF dates) Adult Adult Adult Adult Adult SF WS SF WS SF 1993-94 1994 1994-95 1995 1995-96 1996 1996-97 0.94 0.90 0.98 129bh 0 8d 0 8 0.94 0.90 0.98 119i 2) 7 4 3 0.89 0.84 0.94 1431: 0 16 1 15 0.98 0.95 1.00 1271 0 3 1 2 .1 Survival L 95%CI U 9S%CI n collars Censored" Died Nonhunt Hunt 0.96 0.91 1.00 68b• 0 0.87 0.80 0.94 100bf 0 3 13< 1 2 I 12 0.96 0.92 1.00 9Sbl 0 4 1 3 • Censored denotes collar failure or life/death status unknown. b Includes (172.011/93) collar failure April 1994, seen January 1996 , Collars (172.800/93,172.649/93) disappeared 1994 hunt seasons. d Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead. • Composed of 6-18+ and 62-30+ months old females. f Composed of35-12+, 6-24+, and 59-36+ months old females. • Composed of34-18+ and 61-30+ months old females. b Composed of32-12+, 34-24+, and 63-36+ months old females. I Composed of30-18+ and 89-30+ months old females. J Censored elk (172.011/93) failure and (173.719/94) slipped collar. k Composed of31-12+, 29-24+, and 83-36+ months old females. Adult WS Adult SF Adult WS 1997 1997-98 1998 1998-99 0.91· 0.87 0.96 152m 2D 13 0 13 0.99 0.97 1.00 138· IP 2 1 1 0.77 0.70 0.84 136<1 0 31' 0 31 0.98 0.95 1.00 103' 21 2 2 0 I Composed of27-18+ and 100-30+ month old females . ••Composed of30-12+, 23-24+, and 99-36+ months old females. • Censored elk (174.441/95) slipped collar August 1997 and (174.S80/95) likely failure June 1997. • Composed of30-18+ and 108-30+ months old females . P Censored elk (174.470/95) likely collar failure August 1997. q Composed of30-24+ and 106-36+ months old females. r Collars (172.269/93,172.308/93,172.498/93,172.991/93, 173,760/94, 174.929/96) disappeared 1998 hunt seasons and assumed dead. • Composed of24-30+ and 81-42+ months old females. I Censored elk (172.849/93, 173.151/93) failed collars. ,_. OQ W �186 APPENDIX I. Mortalities of235 radio-collared elk from 1 December 1993 through 14 June 1999. Age is aQQfoximate age in ~ears of elk at death: C=calf age 6-11 monthsz Y=yearling age 12-23 months. Frequency ID! Death TraQ Year caEtured Site Zone Sex Age Date Cause of death & code number 172.030/93 172.050/93 172.039/93 172.070/93 172.080/93 172.090/93 172.090/94 172.101193 172.128/93 172.139/93 172.160/93 172.181193 172.201193 172.207/93 172.229/93 172.258/93 172.269/93 172.277/93 172.290/93 172.290/94 172.300193 172.308/93 172.369/93 172.369/94 172.409/93 172.448/93 172.459/93 172.498/93 172.509/93 172.519/93 172.530/93 172.542/93 172.542/94 172.549/93 172.570/93 172.581193 172.581194 172.590/93 172.610/93 172.620/93 172.639/93 172.649/93 172.658/93 172.670/93 172.678/93 172.690/93 172.699/93 172.730/95 172.749/95 172.758/95 172.800/93 172.821/93 172.890/93 172.899/93 172.950/93 172.961193 172.991193 173.000/93 BR EG GR BR GM GR SM SR GC BC CC MC GS SG MC HY MC GS SG SM AC GH AC FM AC ·MH MH FS FS FS FS FS FM PG PG PG FM PG PG PG PG PG PG PG PG FM FM LS LS LS SR EG BC BC GH MG SG WM A B B A A B D B B C C C C D C C C C D D E D E B E E E H H H H H B H H H B H H H H H H H H B B H H H B B C C D D D G F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F F 5 12 4 11 6 11 11 8 8 17 3 3 3 4 8 3 12 3 6 4 8 8 3 4 8 12 8 12 3 6 8 6 15 7 16 3 3 5 3 5 16 2 5 4 9 8 7 19 11 15 Y 3 3 C 2 4 5 C 27-Oct-95 31-Oct-98 14-Jun-95 12-Feb-96 05-Nov-94 16-Jan-94 12-Oct-98 14-Oct-96 31-Oct-96 19-Oct-95 23-Oct-94 03-Nov-94 15-Nov-94 30-Nov-95 29-Oct-98 04-0ct-94 29-Oct-98 O4-Oct-94 23-Oct-94 16-Sep-96 30-0ct-97 29-Oct-98 18~94 14-Jan-96 29-Dec-94 . 01-Nov-98 24-Oct-96 15-Oct-98 21-Oct-95 12-Oct-98 29-Oct-98 01-Feb-94 06-Jan-99 28-Nov-95 03-Nov-94 17-Oct-94 08-Dec-95 i4-Apr-96 O4-Oct-94 04-Nov-98 14-Jun-96 30-Nov-94 02-Nov-97 16-Jan-95 22-Dec-94 24-Jan-94 05-Nov-95 05-May-99 07-Aug-96 28-Oct-98 30-Nov-94 08-Sep-96 06-Nov-96 18-Mar-94 18-Oct-95 30-Oct-97 29-Oct-98 25-Apr-94 Legal kill second rifle season-47 Legal kill third rifle season-48 Unknown-suspect predation-30 Unknown-l l Legal kill third rifle ~n-48 Wounding loss late rifle season-26 Legal kill first rifle season-46 Legal kill first rifle season-46 Wounding loss second rifle season-44 Wounding loss first rifle season-43 Legal kill second rifle season-47 Wounding loss second rifle season-44 Wounding loss second rifle season-44 Disappear first rifle season-40 Legal kill second rifle season-47 Legal kill archerylmuzzle season-27 Disappear second rifle season-41 Wounding loss archery/muzzle-24 Legal kill second rifle season-47 Legal kill muzzleloading season-34 Wounding loss second rifle season-44 Disappear second rifle season-41 Legal kill archery season-33 Legal kill late rifle season-29 Wounding loss late rifle season-26 Legal kill third rifle season-48 Legal kill second rifle season-47 Disappear [JISt rifle season-40 Legal kill second rifle season-47 Legal kill first rifle season-46 Wounding loss second rifle season-44 Mountain lion predation-3 Accident-irrigation ditch-If Legal kill late rifle season-29 Wounding loss second rifle season-44 Legal kill first rifle season-46 Legal kill late rifle season-29 Unknown-11 Accident. birthinglca1ving-32 Legal kill third rifle season-48 Accident. birthinglca1ving-32 Disappear first rifle season-40 Legal kill third rifle season-48 Legal kill late rifle season-29 Wounding loss late rifle season-26 megal kill-7 Legal kill third rifle season-48 Malnutrition-6 Unknown-suspect predation-30 Wounding loss second rifle season-44 Disappear second rifle season-41 Legal kill archery season-33 Legal kill third rifle season-48 Mountain lion predation-3 Legal kill first rifle season-46 Disappear second rifle season-41 Disappear second rifle season-41 . MaInutrition-6 --------------------------------------------------------------------------------------------- �187 Appendix I. (continued) Frequency IDI Trap Year captured Site Zone 173.000/94 173.010/93 173.041193 173.050/93 173.060/93 173.070/93 173.081193 173.090/93 173.100/93 173.120/93 173.140/93 173.160/93 173.171193 173.190/93 173.190/96 173.201193 173.210/93 173.210/96 173.219/93 173.219/96 . 173.232/93 173.232/96 173.262193 173.262/94 173.269/93 . .173.279/93 173.289/93 173.289/94 173.300/93 173.300/96 173.309/93 173.320/93 173.320/94 173.332/93 173.332/96 173.340/93 173.351193 173.351196 173.359/93 173.359/96 173.370/93 173.370/96 173.381196 173.390/93 173.402/93 173.410/93 173.410/96 173.420/93 173.429/93 173.439/93 173.450/93 173.461/93 173.461194 173.461196 173.469/93 173.469/94 173.479/93 173.479/96 173.492/93 HM WM GM MH MH MH FS FS FS GM PG FS FM BC BC GR GC LM BC CG BR BC BC HM MC MC MC PR GS MC HY HY HM GH BC SG SG BG AC MC MH RG RG MG MG WM EW WM MH PG PG PG CM GM FS PR FS RG FS B G A E E E H H H A H H B C C B B D C D AMY C C B C C C A C C C C B D C D D E E C E E E D D G G G E H H H AMY A H A H E H Death Sex· Age F F M F F F F F F M F F F M M M M M M M 4 4 2 5 2 5 3 4 4 2 3 3 5 Y 2 2 2 2 2 2 M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M 2 C 2 2 3 C 2 2 2 Y Y 2 2 2 4 2 2 2 2 2 C C 2 2 2 1 2 2 2 2 C M M M M M M 2 C 2 2 2 2 Date 31-Oct-98 07-Jan-98 19-Oct-95 31-Oct-98 27-Dec-95 03-Mar-98 22-Oct-96 24-Oct-97 30-0ct-97 14-Oct-95 31-Oct-96 13-Nov-96 10-Oct-98 29-Oct-94 1O-Oct-98 30-Nov-95 19-Oct-95 30-Oct-97 06-Nov-95 21-Oct-98 15-Nov-94 31-Oct-98 18-Mar-94 12-Oct-96 06-Nov-95 12-Oct-96 22-Mar-94 18-Sep-96 24-Oct-95 10-Oct-98 30-Nov-94 20-Oct-94 14-Sep-96 12-Sep-95 10-Oct-98 20-Oct-97 05-Nov-95 27-Oct-98 06-Sep-95 09-Nov-98 08-Nov-95 08-Jan-97 19-Feb-97 30-Nov-95 18-Oct-95 02-Nov-95 29-Sep-98 24-Oct-95 14-Sep-95 30-Nov-95 15-Oct-95 07-Feb-94 19-5ep-95 22-Oct-98 25-Apr-94 20-Oct-96 1O-Sep-95 l7-Oct-98 03-Sep-95 Cause of death & code number Legalkill third rifle season-48 Accident-fell-l0 Legalkill first rifle season-46 Legalkill third rifle season-48 Legalkill late rifle season-29 Illegalkill-7 Legalkill secondrifle season-47 Legalkill secondrifle season-47 Legalkill secondrifle season-47 Legalkill first rifle season-46 WOWldinglosssecondrifleseason-44 Legalkill third rifle season-48 Legalkill first rifle season-46 megal kill secondrifle season-50 Legalkill first rifle season-46 Woundingloss third rifle season-45 Legalkill first rifle season-46 Illegalkill archery/muzz.season-8 Legalkill third rifle season-48 Legalkill secondrifle season-47 illegal kill secondrifle season-50 Legalkill third rifle season-48 Unknown-ll Legalkill first rifle season-46 Legalkill third rifle season-48 Legalkill first rifle season-46 Unknown-ll Legalkill muzzleloadingseason-34 Legalkill secondrifle season-47 Legalkill first rifle season-46 Illegalkill first rifle season-49 megal kill first rifle season-49 Legalkill archeryseason-33 Legalkill muzzleloadingseason-34 Legalkill first rifle season-46 Legalkill secondrifle season-47 Legalkill third rifle season-48 Legalkill secondrifle season-47 Legalkill archeryseason-33 Woundingloss third rifle season-45 Legalkill first rifle season-46 Mountainlion predation-3 Unknown-suspectpredation-30 Disappearfirst rifle season-40 Legalkill first rifle season-46 Woundingloss secondrifle season-44 Woundingloss archery/muzzleseasons-24 Legalkill secondrifle season-47 Legalkill archeryseason-33 Disappearfirst rifle season-40 Legalkill first rifle season-46 Malnutrition-6 Woundingloss archeryseason-50 Legalkill secondrifle season-47 Malnutrition-6 Legalkill secondrifle season-47 Legalkill archeryseason-33 Legalkill secondrifle season-47 Legalkill archeryseason-33 !~~~~~~]--------~~-----~-------~----]----7--]]~~~!:?~-~g~!~~E:~~~~:_~~~~ _ �188 Appendix I. (continued) Frequency ID! Year Captured Trap. Site Zone Death Sex Age 173.510/93 FM FM FM M M F M F F F F F F F F 2 2 7 2 Y 3 Y C 3 C C 3 F F F F F F F F F F F F F M M M M M M M M M M M M M M M M M M 4 2 2 4 4 4 C 3 2 4 4 2 C Y 2 2 2 2 2 2 2 2 2 2 2 Y 2 3 2 Y 2 M M 2 2 M M M M M M M M Y 2 2 C 2 2 Y 2 173.521193 173.530/94 173.540/94 173.549/94 173.569/94 173.580/94 173.589/94 173.610/94 173.640/94 173.640/96 173.649/94 173.659/94 173.679/94 173.689/94 173.719/96 173.739/94 173.750/94 173.760194 173.789/94 173.819/94 173.829/94 173.840/94 173.849194 173.859/94 173.870/94 173.919/94 173.929/94 173.939/94 173.959/94 173.970/94 173.981/94 173.990/94 174.001194 174.009194 174.019/94 174.039/94 174.049194 174.059/94 174.069/94 174.080/94 174.090/94 174.101/94 174.109/94 174.119/94 174.119/95 174.129/94 174.140194 174.140/95 174.150/94 174.160/94 174.170/94 174.170/96 174.181194 174.200/95 174.210/95 174.220/95 174.230/95 174.230/96 00 HM PR PR 00 BC MC GM BC MC MP BG MC BG BG MR MR MM MM MM SM SM SM BC BC BC BC MC MP BC BG BG BG MR MM MR BG MR MR MM MM MM GB MM MM GB MM MM FM MC FM MS MS MS MS EW ~~~~~~2~ ~ B B B B B A A B C C A C CF4 D E C E E E E F F F D D D C C C C C D C E E E E F E E E E F F FMC B F FMC B F F B C B F F FMC FMC G M ~ ~ Date Cause of Death & Code Number 2 28-Aug-95 17-Oct-95 31-Oct-98 13-Oct-% 07-Sep-95 l6-Oct-97 21-Dec-95 01-Jun-95 14-Nov-97 30-Mar-95 16-Mar-97 1l-Oct-97 25-Oct-98 29-Oct-98 31-Oct-% 03-Nov-98 29-Oct-98 18-Oct-98 29-Oct-98 20-Mar-95 30-Oct-97 IO-Jan-97 29-Sep-98 20-Oct-98 23-Oct-96 21-Feb-95 02-Nov-95 l6-Oct-96 18-Sep-96 02-Nov-96 20-Oct-96 02-Nov-96 20-Oct-96 30-Nov-% 12-Oct-96 13-Nov-96 05-Sep-96 14-Sep-96 17-Oct-95 26-Sep-96 ll-Oct-97 20-Oct-96 24-May-96 19-Oct-96 01-Mar-95 30-Nov-97 14-Oct-96 14-Mar-95 30-Nov-96 14-Oct-96 15-Sep-96 25-Apr-95 10-Oct-98 30-Nov-96 18-Oct-96 ll-Oct-97 08-Apr-96 24-Apr-96 l3-Oct-98 Legal kill archeryseason-33 Legal kill first rifle season-46 Legal kill third rifle season-48 Legal kill first rifle season-46 Legal kill archeryseason-33 Woundingloss first rifle season-43 Unknown-ll Unknown-suspectpredation-30 Woundingloss third rifle season-45 Unknown-suspectpredation-30 Malnutrition-6 Legal kill first rifle season-46 Legal kill secondrifle season-47 Woundingloss first rifle season-43 Legalkillfrrstrifleseason-46 Legal kill third rifle season-48 Woundingloss secondrifle season-44 . Legal kill secondrifle season-47 Disappear secondrifle season-41 Unknown-suspectmalnutrition-31 Legal kill secondrifle season-47 Legal kill late rifle season-29 Woundingloss archery/muzzleseasons-24 Legal kill secondrifle season-47 Legal kill secondrifle season-47 Mountain lion predation-3 illegal kill secondrifle season-50 Legal kill first rifle season-46 Legal kill archeryseason-33 Legal kill third rifle season-48 Legal kill secondrifle season-47 Legal kill third rifle season-48 Legal kill secondrifle season-47 Disappeararchery/muzzleseason-21 Legal kill first rifle season-47 illegaI kill rifle season-9 Legal kill archeryseason-33 Legal kill muzzleloadingseason-34 illegal kill first rifle season-49 Woundingloss archery/muzzle-24 Legal kill first rifle season-46 Legal kill secondrifle season-47 Unknown-suspectpredation-30 Legal kill secondrifle season-47 Mountain lion predation-3 Woundingloss rifle season-25 Legal kill first rifle season-46 Mountainlionpredation-3 llIegalkillthirdrifleseason-51 Legal kill first rifle season-46 Legal kill muzzleloadingseason-34 Mountain lion predation-3 Legal kill first rifle season-46 Disappear secondrifle season-41 llIegaIkill first rifle season-49 Legal kill first rifle season-46 Unknown-suspectmalnutrition-31 Mountain lion predation-3 Legal kill first rifle season-46 ~ ~I:~~~~~ ~~~~~~~~P!~~~:~ _ �189 AEEendix I. {continued} Frequency ID! Tral! Site Zone Year caEtured 174.240/96 SR B MD 174.301195 E MS 174.319/95 F MD 174.329/95 E MD 174.339/95 E 174.349/95 MD E 174.360/95 MD E 174.401/95 AP D 174.420/95 AP D 174.478/95 WD e 174.491195 LB e 174.500/95 LB e 174.520/95 KR B 174.520/96 GM A 174.551/95 we G 174.560/95 BL A 174.609/95 GB B MD 174.629/95 E 174.639/95 MD E 174.650/95 HG E 174.679/95 HG E 174.689/95 AP D 174.689/96 EW G 174.700/95 AP D 174.710/95 AP D 174.729/95 VM D 174.740/95 VM D 174.750/95 VM D 174.760/95 VM D 174.770/95 WD e 174.780/95 WD e 174.789/95 WD e 174.789/96 EW G 174.800/96 BG E WD 174.809/95 e 174.820/95 WD e 174.830/95 LB e 174.841195 LB e 174.851195 LB e 174.861195 KR B 174.870/95 LB e 174.880/95 KR B 174.889/95 we G 174.899/95 BL A 174.910/96 LM D 174.929/96 LM D 174.959/96 LM D 174.998/96 BG E 175.059/96 Be e 175.130196 GM A 175.139/96 GM A 175.149/96 SR B 175.160/96 Be e 175.170196 LM D 175.189/96 RG E EW 175.199/96 G 175.209/96 MS F END Death Sex Age M 2 F 3 F Y F Y F e 2 F F Y F 2 F 2 2 F 2 F e F F Y F e 3 F F Y e F 2 M M 2 M 3 M Y e M e M M 2 M 2 M Y M 2 M 2 M 3 M 2 2 M e M 2 M M e y M 2 M M 2 3 M M 2 Y M M 2 2 M 2 M 2 M F e 2 F F 2 F 2 F e F e 2 F 2 F 2 M e M 2 M M 2 2 M Date 12-Sep-98 20-Sep-98 02-Oct-% 03-Sep-96 27-Mar-96 l3-Oct-97 22-Apr-97 22-Sep-% 1l-Oct-97 13-Sep-97 10-Sep-97 16-Apr-96 21-Sep-96 25-Apr-97 14-Oct-98 14-May-97 15-Apr-96 11-Oct-97 21-Oct-97 14-Sep-98 13-Nov-96 05-Feb-96 14-May-97 16-Oct-97 15-Oct-97 17-Oct-% 08-Nov-97 05-Nov-97 15-Sep-98 16-Oct-97 II-Oct-97 22-May-96 28-Oct-98 09-Apr-97 22-Apr-97 14-Oct-97 l3-Oct-97 12-Sep-98 22-Oct-97 31-Oct-96 30-Oct-97 11-Oct-97 20-Oct-97 30-Oct-97 27-Feb-97 29-Oct-98 29-Oct-98 21-Oct-98 13-Feb-97 24-Mar-97 28-Oct-98 19-Oct-98 17-Sep-98 26-Mar-97 l3-Oct-98 29-Oct-98 24-Oct-98 Cause of death & code number Legal kill muzzleloading season-34 Legal kill archery season-33 Wounding loss archery season-52 Legal kill archery season-33 Unknown predator-S Legal kill first rifle Season-46 Unknown-suspect predation-30 Legal kill muzzleloading season-34 Legal kill first rifle season-46 Legal kill muzzleloading season-34 Wounding loss archery season-52 Unknown-suspect predation-30 Legal kill muzzleloading season-34 Mountain lion predation-3 Legal kill first rifle season-46 Illegal kill-7 Unknown-suspect predation-30 Legal kill first rifle season-46 Legal kill second rifle season-47 Legal kill muzzleloading season-34 Illegal kill second rifle season-50 .Mountain lion predation-3 Unknown-suspect maInutrition-31 Wounding loss first rifle season-43 Legal kill first rifle season-46 Illegal kill first rifle season-49 Legal kill third rifle season-48 Legal kill third rifle season-48 Legal kill archery season-33 Disappear first rifle season-40 Legal kill first rifle season-46 Unknown-suspect predation-30 Wounding loss second rifle season-44 Mountain lion predation-S Accident, fell-lO Legal kill first rifle season-46 Legal kill first rifle season-46 Legal kill muzzleloading season-34 Illegal kill second rifle season-50 Illegal kill second rifle season-50 Wounding loss second rifle season-44 Legal kill first rifle season-46 Legal kill second rifle season-47 Wounding loss second rifle season-44 Unknown-suspect predation-30 Disappear second rifle season-41 Wounding loss second rifle season-44 Legal kill second rifle season-47 Unknown-l l Mountain lion predation-3 Legal kill second rifle season-47 Legal kill second rifle season-47 Legal kill muzzleloading season-34 Unknown-suspect maInutrition-31 Legal kill first rifle season-46 Disappear second rifle season-41 Legal kill second rifle season-47 �190 Appendix Il, Abstract from paper presented at Western States and Provinces Elk and Mule Deer Workshop, Salt Lake City, Utah, March 1999. ESTIMATING ELK DENSITIES IN COLORADO: PROGRESS WITH PERPLEXITIES DAVID J. FREDDY, Colorado Division of Wildlife, Research Center, 317 West Prospect Road, Fort Collins, CO, USA 80526 DAVID C. BOWDEN, Department of Statistics, Colorado State University, Fort Collins, CO 80523 USA GARY C. WIllTE, Department of Fishery and Wildlife Biology, Colorado State Univeristy, Fort Collins, CO 80523 USA Abstract: During winters 1994-1998, we evaluated helicopter survey methodologies to estimate elk densities injuniper-pinyon (Juniperus osteosperma-Pinus edulis) and oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnifolia) habitats. We developed sighting bias correction models to correct for groups of elk not observed when counting elk on 2.59-km2 (l-mf) quadrats. Within a 350-km2 area, we compared elk densities obtained from a stratified random quadrat sampling system corrected for sighting bias with independent estimates of densities obtained from mark-resight models using known numbers of radio-collared elk (120-137 elk) within the quadrat survey area. Although observers detected about 80% of the elk groups on quadrats during sighting bias trials and resulting sighting bias models increased estimated elk densities on quadrats by 10-12%, quadrat densities were 2:,25%lower than mark-resight densities. Estimated densities of elk ranged from 6-10 elk/krrr', We propose that errors in counting numbers of elk in a group may contribute more to underestimating elk densities than errors in detecting groups of elk. �239 Colorado Division of Wildlife Wildlife Research Report July 2000 JOB FINAL REPORT Smreof ~C~m~o~rnrl~o~ _ Cost Center 3430 Project No. W~-1=5=3__=-R:..:.-"""'1=_3 _ Manunals Research Work Package -=3...:::;0=02=-- _ Task No. --=2'-- _ Elk Management Estimating Survival Rates of Elk and Developing Techniques to Estimate Population Size Period Covered: July 1, 1999 - June 30,2000 Author: D. J. Freddy \ ) Personnel: T. Beck, J. Broderick, G. Byrne, D. Crane, R Del Piccolo, J. Ellenberger, V. Graham, D. Homan, R. Kahn, K. Madariaga, D. Masden, C. Mehaffy, P. Neil, J. alterman, P. Will, K. Wright, S. Yamashita, D. Younkin, CDOW; D. Bowden, M. Conner, M. Kneeland, G. White, CSU; D. Ouren, D. Schneider, T. Fancher, R. Waltermeir, USGS-BRD, BLM Glenwood Springs, CO, USFS Rifle, CO, Rocky Mountain Elk Foundation, cooperating. ABSTRACT We monitored survival and movements of 112 previously radio-collared elk composed of 101 adult females and 11 adult males from 1 July 1999 through 30 June 2000. Survival of adult females during summer-fall was 0.89 ± 0.06 (n = 101) inclusive of hunting deaths and 1.00 (n = 90) with hunting deaths censored while survival during winter-spring was 0.98 ± 0.03 (n = 88) inclusive of hunting "deaths and 0.99 ± 0.02 with hunting deaths censored. The 1 non-hunting death of an adult female during winter-spring was attributed . to mountain lion predation. Survival of adult males during summer-fall was 0.27 ± 0.30 (n = 11) inclusive of hunting deaths and 1.00 (n = 3) with hunting deaths censored while survival during winter-spring was 1.00 (n = 3); With hunting deaths censored, annual survival rates during winter-spring were 2: 0.97 for adult females and 2: 0.96 for adult males during 7 consecutive winters while annual survival rates during summer-full were 2: 0.99 for both adult females and males during 6 consecutive summers. High adult survival and high over-winter calf survival (0.89 ± 0.04) allow this population to potentially increase> 15% annually in the absence of hunting antlerless elk. Hunting related mortalities were the primary cause of death for adult male and female elk. During 6 years, 98% of all adult male deaths and 89% of all adult female deaths were related to hunting. Hunting annually removed 76% of the adult branch-antlered males and 13% of the adult females. Annual wounding losses averaged 15% for adult males and 30% for adult females while 11% of yearling spike-antlered males were illegally harvested. Sighting bias corrections for counting elk on l-mf quadrats were developed and evaluated as a method to estimate elk densities. We found counts of elk on quadrats corrected for sighting bias associated with detection of elk groups .---.---ro rnvwLDL11i1llrilil~~llljilrnl BDOW016789 �240 continued to under-estimate true numbers of elk present. Evidence indicates under-counting numbers of elk in groups also contributes to underestimating true numbers of elk present. If a quadrat sampling system is employed to estimate densities of elk, counts of elk would need to be increased by 1.3x to approximate true numbers of elk present. Progress continues towards developing habitat use models to predict areas important to managing elk Several manuscripts on elk survival rates, techniques to estimate population size, and habitat use are progressing. �241 ESTIMATING SURVIVAL JOB FINAL REPORT RATES OF ELK AND DEVELOPING ESTIMATE POPULATION SIZE TECHNIQUES TO David J. Freddy P. N. OBJECTIVE Estimate survival rates of adult female, adult male, and calf elk and develop techniques to estimate population size. SEGMENT OBJECTIVES 1. Analyze data concerning estimates of elk survival rates and experiments to estimate elk numbers. 2. Prepare Job Final Report 3. Prepare a manuscript for submission to a scientific journal which describes and summarizes research results. INTRODUCTION Our objectives are to provide reliable estimates of survival rates for calves during winter and for adult females and males throughout the year and to develop and test a system to estimate elk densities on winter . ranges. Estimates of calf survival were obtained during winters 1993-94 through 1996-97 and summarized in Freddy (1997). We continue to obtain estimates of survival for adult males and females. For adults, we are interested in survival rates inclusive of hunting mortalities to document human-induced rates of survival and exclusive of hunting mortalities to estimate natural rates of survival. We are evaluating a system for estimating population size or density that incorporates estimates of sighting bias in conjunction with random sampling of search quadrats as sample units. Our winter study area encompasses about 324 mi2 (839 knr') in the eastern half of Game Management Unit 42 south and east of Rifle, Colorado. This area is part of the Grand Mesa Elk: Data Analysis Unit E-14. Elk winter habitats include juniper-pinyon woodland (Juniperus osteosperma-Pinus edulis), oakbrush-mountain shrub (Quercus gambelii-Amelanchier alnifolia), aspen (Populus tremuloides), sagebrush (Artemisia tridentata), and agricultural fields below elevations of 9,800 ft. In summer, elk:use oakbrush-mountain shrub, aspen, and subalpine fir-Engelmann spruce (Abies lasiocarpa-Picea engelmannii) meadow systems throughout the Grand Mesa region up to elevations of 12,000 ft. (Freddy 1993). METHODS We placed radio collars (l72-176MHz) having mortality sensors on elk calves age 6 months and adults age :::18 months during December 1993-1996 (Freddy 1997). Elk: were captured using helicopter net-gunning and portable corral traps (Freddy 1997). During 1999-00, we monitored 112 adult elk, 101 females and 11 males, having functioning radios as of July 1999. Collars were white and had black identification symbols on dorsal surfaces of collars to allow visual identification of individual elk. Estimating Elk Survival Rates During 1999-2000, we monitored survival of radioed elk with limited aerial surveys using a Cessna 185 and with opportunistic ground surveys. Extreme reductions in operating budgets during 1999-2000 �242 prevented following survey protocols used in previous years. Survival rates (S) of radioed elk were calculated using the binomial estimator with a variance, VAR(S) = S( I-S)/n collars (White and Garrott 1990). Survival rates are expressed as the mean estimate ± the 95% confidence interval. Sample sizes refer to numbers of individual radioed elk. Elk were censored if radios failed or if their life/death status was unknown after an extended period of time We defined 3 major time intervals for survival analyses: winter-spring was 1 December to 14 June, summer-fall was 15 June to 30 November, and annual was 1 December to 30 November to coincide with timing of capture and collaring. For adult elk during these time intervals, we calculated survival rates inclusive of natural and hunting-related mortalities, exclusive of hunting mortalities, and exclusive of natural mortalities. Excluding, or censoring hunting mortalities, provided estimates of natural survival rates. Excluding natural mortalities but including hunting mortalities provided estimates of hunting removal rates. Censoring elk associated with categories of mortalities reduced sample sizes used to estimate survival rates .. Archery, muzzleloading, and rifle hunting seasons occurred from about 1 September to 15 November each year during the summer-fall time interval. Late-rifle seasons occurred in some years and restricted hunters to taking only antlerless elk from about 25 November-31 January which included portions of the summerfall and winter-spring time intervals. Yearling spike-antlered males were generally not legal quarry in most areas frequented by radioed elk. Male elk were legal quarry when branch-antlered usually at age 2 years. Cause of death of radioed elk recovered in the field was estimated from presence or absence of gunshot wounds or bite wounds on carcass, predator tracks or scat at carcass site, physical positioning of carcass remains whether buried, covered, scattered, or consolidated (Wade and Browns 1982, Halfpenny and Biesiot 1986), relative amount of internal fat and marrow fat if present with carcass, and results of histopathology and marrow fat analyses. Fat content (percent dry matter) of bone marrow and estimates of age based on dental cementum were obtained for dead elk by the Colorado Division of Wildlife Laboratory while histopathology analyses were provided by the Colorado State University Veterinary Diagnostic Laboratory. Photographs were taken of nearly all mortalities so that physical evidence could be reviewed and judged by outside experts. Population Estimation Development of sighting bias corrections (Samuel et al. 1987) for aerial quadrat sampling systems to estimate elk densities terminated after winter 1998. We have continued to analyze existing data to evaluate and sources of negative bias associated with sighting.bias corrected counts of elk on quadrat sample units. Elk Movements and Habitat Use Models Aerial surveys to precisely locate radioed elk were terminated after June 1999 and development of habitat use predictive models were hampered by reduced budgets in 1999-2000. However, we continued an extensive process of database refinement and reduction. Using ArcInfo© and ArcVieW©, we linked all elk locations to GIS coverages for elevation, slope, aspect (EW and NS), land ownership, private land density, road density, hydrologic density, distance to private land, distance to roads, and distance to water. The entire data set consisted of 5,164 elk locations representing 365 individual elk. For developing predictive use models, we will use only data from elk that were randomly selected and systematically located during years 1993-1999 which represented 2,900 locations representing 140 individual elk. All locations were subset into groups by sex, age, (calf, yearling, adult) and season. Seasons were biologically defined as spring (1 April- 30 May), summer (1 June- 31 August), fall (1 September - 30 November) and winter (1 December - 31 March). �243 We also embarked on developing a supervised habitat type GIS coverage using ERDAS Imagine© and a thematic mapper image from June 1993. We had anticipated obtaining this data from another source during the last 3 years but such information did not become available. RESUL TS AND DISCUSSION Between 1 December 1993 and 14 June 2000, 256 radioed elk died of which 31 were calves 6-11 months old and 225 were adults ~12 months old (fable 1, Appendix I). Calves died of natural causes (Freddy 1997) while hunting accounted for 93% of 225 adult deaths. Hunting caused 98% of 110 adult male deaths and 89% of 115 adult female deaths. Survival Estimates Adult Females Summer-Fall Survival during summer-fall 1999 for adult females all age ~24 months was 0.89 ± 0.06 (n = 101) inclusive of hunting deaths and 1.00 (n = 90) with hunting deaths censored (fable 6). Survival rates for adult females during summer-fall with hunting deaths censored remained >0.99 during 6 consecutive years, 1994-1999 (fables 6-8) .. Net summer-fall survival increased to 0.89 in 1999 from a low of 0.77 in 1998 (fable 6). An increase in net survival was evident in nearly all cohorts of females (fables 2-8). Increased survival likely reflected the return to using traditional limited antlerless permits during the 1999 hunting seasons compared to using unlimited either-sex permits during portions of 1998 hunting seasons (Freddy 1999). Adult Females Winter-Spring Survival during winter-spring 1999-00 for adult females all age ~24 months was 0.98 ± 0.03 (n = 88) inclusive of hunting deaths and 0.99 ± 0.02 (n = 87) with hunting deaths censored (fable 6). The 1 natural death involved a female age 6 years that was killed by a mountain lion. Survival rates for adult females during winter-spring with hunting deaths censored remained ~0.97 for 7 consecutive winters, 1993-941999-00 (fables 6-8). Adult Females-Annual Annual survival from 1 December 1998 to November 30 1999 was 0.83 ± 0.16 (n = 24) inclusive of hunting deaths and 1.00 (n = 20) with hunting deaths censored for the 1993 cohort of radioed older adult females (fable 9). Annual survival among years for this cohort ranged from 0.71 to 0.94 and from 0.92 to 1.00, inclusive and exclusive of hunting mortalities, respectively. Adult Males Summer-Fall Survival during summer-fall 1999 for adult males all age ~36 months was 0.27 ± 0.30 (n = 11) inclusive of hunting deaths and 1.00 (n = 3) with hunting deaths censored (fable 11). With the unlimited branchantlered male hunting system used in the project area, the probability of a male living from age 6-months to 48-months was 5% (7 of 138 males, Tables 2-5). Adult Males Winter-Spring Survival during winter-spring 1999-00 for adult males all age ~42 months was 1.00 (n = 3)(fable 5). There have been only 2 non-hunting deaths of males age ~12-months during 6 years and both occurred during winter-spring and were attributed to an accidental fall and predation (fable 1). Wounding Loss Wounding loss during archery, muzzleloading, and rifle seasons in 1999 was 33% for adult males and 33% for adult females. This compares to 1994-99 averages of 15% for adult males and 30% for adult females. Wounding loss is defined as wounded / legal kill (Freddy 1997). �244 Removal Rates During the summer-fall period, hunting removal rates (1 - survival rate) averaged 0.76 for adult branchantlered males and 0.13 for adult females (Tables 10, 11). Peak removal rates of 0.92 for 24 month-old males and 0.86 for all adult males occurred in 1996 while minimum removal rates of 0.64 and 0.65 for these groups of males occurred in 1998. Peak removal rate of 0.23 occurred for adult females in 1998. Removal rates in 1998 were associated with unlimited numbers of either-sex hunting permits during portions of the 1998 seasons. These permits appeared to reduce hunting mortality on males and increase hunting mortality on females. During those years when cohorts of yearling (12-17 months old) and adult females (>24 months old) were available, removal rates for yearling females tended to be lower than adult females (Table 11). Radio Collar Status As of July 2000, 89 adult elk (3 males, 86 females) were alive with functioning radio collars and remained in the project area. Many of these collars should be subject to electronic failure soon. Quality radio collars (Lotek, Inc) with very low electronic failure rates allowed obtaining accurate survival rates on elk for 6.5 years. Collars having 1 D-celilithium battery remained functional for up to 78 consecutive months. Population Estimation Continuing analyses strongly indicate that under-counting numbers of elk in groups is an important source of error, or negative bias, and may be equivalent in magnitude to negative bias associated with missing entire groups of elk.. Thus, errors in detecting groups and in counting elk within groups contribute to underestimates of true numbers of elk present. The assessment of negative bias was possible because of independently obtained mark-resight estimates of elk numbers that provided robust estimates of true numbers of elk. Elk Movements and Habitat Models Spatial plots of elk distribution, movements, and seasonal ranges were completed. All outputs were prepared for color reproduction, and as such, are not suitable to reproduce in this report. Further statistical assessment of predictive habitat use variables is ongoing. We anticipate completion and evaluation of the habitat type coverage during Fall 2000. Once the vegetation coverage is completed, analyses of habitat use can proceed towards completion. Manuscripts The following manuscripts are in various stages of progress. ESTIMATING ERROR ASSOCIATED WITH AERIAL TELEMETRY LOCATIONS OF ELK ON GRAND MESA, COLORADO. Projected outlet is CDOW technical series publication. SPATIAL DISTRIBUTION OF ELK ON GRAND MESA, COLORADO. Projected outlet is CDOW technical series publication in cooperation with USGS-BRD with financial support from the Rocky Mountain Elk Foundation. SURVNAL OF ELK CALVES DURING WINTER ON GRAND MESA, COLORADO. outlet is Journal of Wildlife Management. SURVNAL OF ADULT ELK ON GRAND MESA, COLORADO. Management. Projected Projected outlet is Journal of Wildlife ESTIMATING ELK DENSITIES ON GRAND MESA, COLORADO. Wildlife Management. Projected outlet is Journal of �245 Additional publications regarding effects of helicopter net-gunning capture protocols on elk calves and refinements to portable elk corral traps are planned. CONCLUSIONS With hunting deaths censored, annual survival rates during winter-spring were 2: 0.97 for adult females and 2: 0.96 for adult males during 7 consecutive winters while annual survival rates during summer-fall were 2: 0.99 for both adult females and males during 6 consecutive summers. High adult survival in conjunction with high over-winter calf survival (0.89 ± 0.04) allows this population to potentially increase> 15% annually in the absence of hunting antlerless elk. Hunting related mortalities were the primary cause of death for adult male and female elk. During 6 years, 98% of all adult male deaths and 89% of all adult female deaths were related to hunting. Hunting annually removed 76% of the adult branch-antlered males and 13% of the adult females. Wounding losses averaged 15% for adult males and 30% for adult females while 11% of yearling spike-antlered males were illegally harvested. We found counts of elk on quadrats corrected for sighting bias associated with detection of elk groups continued to under-estimate true numbers of elk present. Evidence indicates under-counting numbers of elk in groups also contributes to underestimating true numbers of elk present. If a quadrat sampling system is employed to estimate densities of elk, counts of elk on quadrats would need to be increased by l.3x to approximate true numbers of elk present. LITERATURE CITED Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Game Research Report. July: 83-117 .. Freddy, D. 1. 1997. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Game Research Report. July: 47-73. Freddy, D. 1. 1999. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Game Research Report. July: In press .. Halfpenny,1. C., and E. A Biesiot. 1986. A field guide to mammal tracking in North America. Johnson Books, Boulder, Colorado, USA. Samuel, M.D., RO. Garton, M.W. Schlegel, and RG. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. journal of Wildlife Management 51 :622-630. Wade, D. A, and J. E. Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas Agricultural. Experiment Station Publication B-1429. White, G. C., and R A Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego, California USA. Prepared by _ David 1. Freddy Life/Science Researcher �246 Table 1. Causes of death for radio-collared elk between I December 1993 and 14 June 2000. Calves (M=male, F=female) were age 6-11 months and collared at age 6 months. Yearling males and females were age 12-17 months and juvenile males and females were age 18-23 months and all were collared at age 6 months. Adult males and females were age >24 months at time of death. Elk Age/Sex Class at Death Cause of Death Calves Yearling Juvenile Adult Total and -Code All M F M F M F M F M F Natural Causes Malnutrition-6 2 2 0 0 1 2 3 5 0 0 0 Unknown-Suspect Malnutrition-31 0 0 3 4 3 1 0 0 0 1 0 O· 2 Predation-Lion- 3 8 4 0 0 8 6 14 0 0 Predation-Bear-35 0 0 0 0 0 0 0 0 0 0 0 Unknown Predator-5 0 1 0 1 0 0 0 0 1 0 0 Unknown-Suspect Predation-30 2 5 0 3 8 0 1 1 2 11 0 Accident -Birthing- 32 0 0 0 0 2 2 0 0 0 0 2 Accident-FeU-I0 0 0 0 0 2 1 2 0 0 1 3 Unknown Cause-l l 2 0 2 4 1 0 0 0 1 2 6 Subtotals 17 14 19 27 46 Q 11 Q Q ~ ~ Legal Hunting Archery-33 0 0 0 9 5 9 7 16 0 2 0 Muzzleloading-34 0 0 8 2 8 4 12 0 2 0 0 ArcherylMuzzle-27 0 0 0 0 0 1 0 1 1 0 0 Rifle-First-46 0 0 33 33 13 46 0 0 0 0 13 Rifle-Second-47 0 0 0 0 16 19 16 19 35 0 0 Rifle- Third-48 0 9 13 22 0 0 0 0 9 13 0 Rifle-Late-29 0 0 0 0 0 7 0 7 7 0 0 Rifle-Unk.Reg-28 0 0 0 0 0 0 0 1 1 1 0 Subtotals 75 75 65 61 140 Q Q Q Q Q 1 I Wound~Loss Archery uzzle-24 0 0 2 2 2 2 4 0 0 0 0 0 0 0 1 2 Archery-52 1 0 0 1 3 1 Rifle-Flrst-43 0 0 1 0 0 0 1 3 3 4 0 Rifle-Second-44 0 0 0 4 4 11 15 0 0 0 11 Riflc- Third-45 0 0 0 0 3 1 3 1 4 0 0 Rifle-Unk.Reg. -25 2 2 4 0 0 0 0 0 2 2 0 Rifle-Late-26 0 0 0 3 0 3 3 0 0 0 0 Subtotals 12 23 13 24 37 Q Q Q Q ! ! Illegal Hunting Rifle-First-49 0 0 0 5 5 0 0 0 0 5 0 Rifle-Second-50 6 0 0 5 0 0 1 0 0 6 0 Rifle- Third-51 0 0 0 0 0 0 1 0 1 1 0 Rifle-Unk.Reg, -9 0 0 0 0 1 0 1 0 1 0 0 Archery Season-S 0 0 0 0 0 0 1 0 1 0 1 Out -of-Season-? 0 0 0 0 2 0 3 3 0 0 1 Subtotals 12" 14 17 Q Q Q Q ! ~ ~ 2 Presumed Hunting" Missing-ArchMuzz-21 0 0 0 0 1 0 1 0 1 0 0 Missing-Rifle Ist-40 0 0 3 3 3 6 0 0 0 0 3 Missing-Rifle 2nd-41 0 0 2 0 0 0 6 2 7 9 1 Missing-Rifle 3rd-42 0 0 0 0 0 0 0 0 0 0 0 Subtotals 0 16 .Q .Q ...!.Q Q Q Q Q .2 ! Totals 17 14 13 6 2 3 95 106 127129 256 • These elk were illegally shot as spike-antlered yearling males: (173.190/93) (173.232/93) (173.309/93) (173.320/93) (173.919/94) (174.059/94) (174.140/95) (174.200/95) (174.679/95) (174.729/95) (174.861/95) (173.210/96). (173.309/93) disappeared in 1994 during first rifle season when spike-antlered yearling males were not legal and was assumed to have been taken illegally. All other illegal deaths were confirmed. b These elk disappeared during hunting seasons and remained missing for several months and are assumed dead and legally harvested: (172.207/93) (172.269/93) (172.308193) (172.498/93) (172.649193) (172.800/93) (172.961/93) (172.991193) (173.390/93) (173.439/93) (173.760/94) (174.001194) (174.181/94) (174.770/95) (174.929/96) (175.199/96). �247 Table 2. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 2000 for the cohort of calves age 6 months radio-collared in December 1993. Survival rate for male and female calves pooled when age 6-11 months was 0.92 (95% CI 0.86-0.98, n~73). Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S(1-S)/n collars. Elk Age (months) and Time Period (WS or SF dates) 6-83 6-1l(mos) 12-17 18-23 24-29 30-35 36-41 42-47 48-53 54-59 60-65 66-71 72-77 78-83 SF WS SF WS SF WS SF WS SF WS SF WS ALL WS 1993-94 1994 1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1998 1998-99 1999 1999-00 1993-00 MALES 0.00 0.88 1.00 Survival 0.89 0.21 1.00 0.50 1.00 0.00 L95%CI 0.78 0.76 0.06 0.00 0.00 U95%CI 0.99 0.99 0.37 0.00 1.00 4 2f 33 32 28 n collars 36 28c 4 1& 3"& o 0 Censored" 0 o 0 o 2" 22d 0 Died 4 33 4b 0 2 0 1 4 o 0 o 0 Nonhunt 4 o 0 o 29 4 Hunt 0 0 22 0 2 0 1 FEMALES Survival L 95%CI U 95% CI n collars Censored" Died Nonhunt Hunt 0.95 0.87 1.00 37 0 0.97 0.92 1.00 35 o 34 0 2 Ih 0 1 1 5 2 () o 0 0 o 0 o 1 If 5 1 1.00 0.97 0.91 1.00 34 0.97 0.91 1.00 33 0.84 0.71 0.97 32 o 0 o 1.00 27 0 0 0 0 0.87 0.72 1.00 23 o 0.96 0.87 1.00 24 0 1 1 3 0 3 0.89 0.76 1.00 27 o i 3 • Censored denotes collar failure and/or animal life/death status not known. b Collar (173.309/93) disappeared 1994 hunting seasons and assumed dead. c Includes (173.241193) collar failure August 1995 but seen January 1996. • Collars (173.390/93),(173.439/93) disappeared 1995 hunting seasons and assumed dead . • Censored elk; (173.241/93) failed August 1995, (173.381/93) slipped collar December 1995. f Includes (173.340/93) alive May 1997. , Censored elk: (173.249/93) slipped collar September 1997. k Collar (172.800/93) disappeared 1994 hunting seasons and assumed dead. i Collar (172.961193) disappeared 1997 hunting seasons and assumed dead. j Collar (172.991193) disappeared 1998 hunting seasons and assumed dead. k Censored elk: (172.849/93) failed May 1999, (173.151193) failed February 1999. 1.00 18 0.89 0.73 1.00 18 0.94 0.81 1.00 16 0.43 0.26 0.60 35 0 21;: 1 20 4 16 o 21;: o Ji 0 2 o 0 0 o 1 2 0 �248 Table 3. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1994 -14 June 2000 for the cohort of calves age 6 months radio-collared in December 1994. Survival rate fot male and female calves pooled when age 6-11 months was 0.90 (95% CI 0.83-0.97, n=69). Survival rates (S) calculated as a mean estimate of ~alive2/~alive + dead2 and variance Sp-S2/n collars. Elk Ase {months~and Time Period {WS or SF dates} 6-11(mos} 12-17 18-23 24-29 30-35 54-59 60-65 66-71 36-41 42-47 48-53 6-71 . SF WS ALL SF WS WS WS WS WS SF SF SF 1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1998 1998-99 1999 1999-00 1994-00 MALES 0.91 0.90 0.00 Survival 0.96 0.08 1.00 0.50 1.00 0.00 0.81 0.79 L 95%CI 0.88 0.00 0.00 1.00 U 95% CI 1.00 1.00 1.00 0.19 2d n collars 33b 30b 31 26 25 2 1 0 2C.~ 1c 1~ Censored' 0 0 0 0 0 0 3 3 31 Died 0 0 0 1 23 1 Nonhunt 3 0 0 4 1 0 0 0 0 0 3 27 HWlt 0 23 0 0 0 1 FEMALES Survival L 95% CI U95%CI n collars Censored' Died Nonhunt Hunt 0.89 0.78 0.99 36 0 4 4 0 0.97 0.91 1.00 32 0 1 0 1 0.97 0.90 1.00 30 1· 1 1 0 0.93 0.83 1.00 29 0 2 0 2 I 0.96 0.89 1.00 27 0 1 0 0.85 0.70 0.99 26 0 4 0 4 1.00 22 0 0 0 0 • Censored denotes collar failure and/or animal life/death status not known. Includes (173.949/94) collar failure December 1994 but seen January 1996 • Censored elk (173.949/94) collar failure, which was killed in first rifle season 1996. d Includes (174.030/94) alive June 1997. • Censored elk (173.719/94) slipped collar May 1996. f Collar (173.760/94) disappeared 1998 hunting seasons and assumed dead. • Censored elk (174.030/94) slipped collar September 1998. b Censored elk (173.799/94) collar failure February 2000. b 0.64 0.42 0.85 22 0 8f 0 8 1.00 14 0 0 ·0 0 0.86 0.66 1.00 14 0 2 0 2 0.91 0.72 1.00 11 Ih 1 0 1 0.29 0.14 0.45 34 2·,h 24 5 19 �249 Table 4. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1995-14 June 2000 for the cohort of calves age 6 months radio-collared in December 1995. Survival rate for male and female calves pooled when age 6-11 months was 0.88 in 1995 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of ~alivel/~alive+deadl and variance of Sp-S2/n collars. Elk Ag_e(months) and Time Period (WS or SF dates) 48-53 54-59 6-59 6-11 (mos) 12-17 18-23 30-35 36-41 42-47 24-29 ALL SF WS WS SF SF WS SF WS WS 1995-96 1996 1996-97 1999 1999-00 1995-00 1997 1997-98 1998 1998-99 MALES 0.00 Survival 0.86 0.83 0.96 0.23 1.00 0.25 1.00 0.00 0.74 L 95%CI 0.68 0.87 0.04 0.00 0.98 U95%CI 0.97 1.00 0.41 0.86 n collars 35 32 29 24 22 4 4 1 1 5b,C,d,. 2b Ie Id 1· 0 0 0 0 Censored" 5 5 1 32 Died 1 17 0 3 0 5 6 Nonhunt 0 0 0 0 0 0 1 0 5 0 17 0 1 26 Hunt 0 3 FEMALES Survival L95%CI U95%CI n collars Censored" Died Nonhunt Hunt • Censored Censored e Censored d Censored • Censored t Censored • Censored b 0.91 0.81 1.00 34 0 3 3 0 0.87 0.75 0.99 31 0 4 0 4 0.93 0.82 1.00 27 0 2 1 1 I 0.83 0.66 0.99 23 2f 1.00 Ig 4 0 4 0 0 0 18 0.89 0.73 1.00 18 0 2 0 2 1.00 16 0 0 0 0 denotes collar failure and/or animallifeldeath status not known. elk (174.619/95) slipped collar May 1996, (174.800/95) capture mortality. elk (174.660/95) slipped collar July 1996. elk (174.671/95) likely collar failure July 1997. elk (174.190/95) slipped collar May 1998. elk (174.441/95) slipped collar August 1997 and (174.580/95) collar failure July 1997. elk (174.470/95) collar failure December 1997. 0.88 0.70 1.00 16 0 2 0 2 1.00 14 0 0 0 0 0.36 0.18 0.53 31 3 17 4 13 �250 Table 5. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993-14 June 2000 for the cohort of calves age 6 months radio-collared in December 1996. Survival rate for male and female calves pooled when age 6-11 months was 0.86 (95% CI 0.81-0.96, n=69). Survival rates (S) calculated as a mean estimate of ~alive~/~alive+dead~ and variance of Sp-S~/n collars. Elk A~e (months2 and Time Period (WS or SF dates) 6-47 6-11 (mos) 36-41 42-47 12-17 24-29 30-35 18-23 ALL SF SF WS WS SF WS WS 1996-00 1999-00 1996-97 1997 1997-98 1998-99 1999 1998 MALES 1.00 0.09 0.85 0.97 1.00 0.30 Survival 1.00 0.36 0.00 L 95%CI 0.73 0.90 0.00 0.17 0.98 1.00 0.63 0.19 U 95% CI 0.54 n collars 34 10 3 34 29 28 28 10 1b 1b Censored" 0 0 0 0 0 0 0 Died Nonhunt Hunt 5 5 0 1 0 1 0 0 0 18d 0 18 0 0 0 7 0 7 0 0 FEMALES Survival L 95% CI U95%CI n collars Censored" Died Nonhunt Hunt 0.86 0.74 0.98 35 0 5 5 0 1.00 1.00 1.00 1.00 1.00 30 0 0 0 0 30 0 0 0 0 0.80 0.65 0.95 30 0 6C 0 6 24 0 0 0 0 24 0 0 0 0 24 0 0 0 0 • Censored denotes collar failure and/or animallifeldeath status not known. b Censored elk (174.619/96) capture mortality. c Collar (174.929/96) disappeared 1998 hunting seasons and assumed dead. d Collar (175.199196) disappeared 1998 hunting seasons and assumed dead. 31 5 26 0.69 0.53 0.85 35 0 11 5 6 �251 Table 6. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 2000 for all radio-collared adult female elk age :::12 months. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead2 and variance S{I-S2/n collars. Elk A8e and Time Period (WS or SF dates 2 Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult WS WS SF WS SF WS SF WS WS WS SF SF SF 1993-94 1994 1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1998 1998-99 1999 1999-00 0.99 0.77 0.98 0.98 Survival 0.96 0.87 0.96 0.94 0.91 0.89 0.94 0.89 0.98 0.70 0.95 L95%CI 0.91 0.80 0.90 0.87 0.97 0.83 0.95 0.92 0.90 0.84 0.95 1.00 0.84 1.00 U95%CI 0.94 1.00 0.98 1.00 0.96 1.00 1.00 0.95 0.98 0.94 100b[ 95b& 68b• 1431< 1271 152m ncollars 129bh ll~ 138° 136q 103' 101ft 88v 2ft 2i Censored" IP 0 2' 0 2'" 0 0 0 0 0 0 c 4 Died 13 3 4 8 7 13 2 31r 2 11 2 16 3 Nonhunt 0 1 1 1 0 4 0 2 0 1 1 1 Hunt 13 2 12 8 31 0 11 1 3 3 15 2 • Censored denotes collar failure or life/death status unknown. e Collars (172.800/93,172.649/93) disappeared 1994 hunt seasons. • Composed of6-18+ and 62-30+ months old females. I Composed of34-18+ and 61-30+ months old females. ; Composed of 30-18+ and 89-30+ months old females. k Composed of31-12+, 29-24+, and 83-36+ months old females. • Composed of30-12+, 23-24+, and 99-36+ months old females. • Censored elk: (174.441/95) slipped collar August 1997 and (174.580/95) likely failure June 1997 P Censored elk: (174.470/95) likely collar failure August 1997. 'Collars (172.269/93, 172.308/93, 172.498/93, 172.991/93, 173,760/94, 174.929/96) disappeared 1998 hunt seIjSOns and assumed dead. • Composed of 24-36+ and 77-48+ months old females W Censored elk: (172.418/93 April 2000, 173.799/94 Feb.2000) Includes (172.011/93) collar failure April 1994, seen January 1996 Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead. f Composed of35-12+, 6-24+, and 59-36+ months old females. k Composed of32-12+, 34-24+, and 63-36+ months old females. j Censored elk: (172.011/93) failure and (173.719/94) slipped collar. I Composed of27-18+ and 100-30+ month old females. b d o Composed of30-18+ and 108-30+ months old females. Composed of30-24+ and 106-36+ months old females. • Composed of 24-30+ and 81-42+ months old females. q I V Censored elk: (172.849/93, 173.151/93) failed collars. Composed of24-42+ and 66-54+ months old females �252 Table 7. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 2000 for radiocollared adult female elk age :::24 months. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) and variance S{l-S~/n collars. Elk Ase and Time Period (WS or SF dates2 Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult WS WS SF WS SF WS WS SF WS SF SF WS SF 1993-94 1994 1994-95 1995 1995-96 1996 1996-97 1997 1997-98 1998 1998-99 1999 1999-00 Survival 0.77 0.89 0.98 0.95 0.82 0.93 0.93 0.89 0.89 0.98 0.98 0.93 0.99 L 95%CI 0.72 0.84 0.70 0.95 0.83 0.95 0.90 0.87 0.88 0.84 0.96 0.88 0.97 0.84 1.00 U 95% CI 1.00 1.00 1.00 1.00 0.95 0.91 0.99 0.98 0.99 0.95 0.95 n collars 136 103 101 62 65 97 100 122 108 88 61 89 112 Ib Id 2f 2< Censored" 2· 0 0 0 0 0 0 0 0 Died 3 12 7 31 11 4 6 12 13 2 2 2 1 Nonhunt 1 0 0 0 1 1 3 0 1 2 1 1 0 Hunt 2 11 7 13 31 3 3 11 1 0 11 1 1 • Censoreddenotescollarfailureor life/deathstatusunknown. Censoredelk (174.441/95)(174.580/95) e Censoredelk (172.849/93,173.151193) e Censoredelk (172.011/93) Censoredelk (174.470195) fCensored elk (172.418/93,173.799/94) B d Table 8. Survival rates, inclusive of non-hunting and hunting mortalities, for winter-spring (WS, 1 December-14 June) and summer-fall (SF, 15 June-30 November) time periods from 1 December 1993 - 14 June 2000 for the group of adult female elk age :::18 months when radio-collared in December 1993. Survival rates (S) calculated as a mean estimate of (alive)/(alive + dead) an? variance S(l-S)/n collars. Elk Ase and Time Period (WS or SF dates2 Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult Adult SF WS WS SF WS SF WS SF WS SF WS SF WS 1993-94 1994 1994-95 1995 1995-96 1996 1996-97· 1997 1997-98 1998 1998-99 1999 1999-00 Survival 1.00 1.00 0.73 0.83 0.96 0.82 0.93 0.88 0.93 0.92 1.00 0.94 0.97 0.57 0.68 L95%CI 0.72 0.78 0.85 0.84 0.87 0.92 0.91 0.85 0.99 U95%CI 0.88 1.00 0.91 0.99 0.97 1.00 1.00 1.00 1.00 331: II)l 241: 241 68b• 34i 3~ 36i 36i n collars 65bf 53bf 49bh 42h o o Censored" 0 o 0 0 0 o 0 0 0 l' 12< Died 3 0 2 1 9 o 4 3 6d 4 3 o o Nonhunt o 0 0 0 o 1 1 0 3 1 Hunt 9 o 4 2 11 6 3 0 2 1 3 0 • Censored denotes collar failure or Iifcldcalh status unknown • CoDar (172.649/93) disappeared 1994 hunt seasons. • Composed of 6-18+ and 62-30+ month old females. • Censored (172.011/93) coDar failure Apri11994. i Composed of 100% females 48+ months old. • Composed of 100% females 72+ months old - Censored elk (172.418/93) collar failure Apri12000. • Includes (172.011/93) collar failure Apri11994 but seen Jan. 1996. • CoDar (172.207/93) disappeared 1995 hunt eeasons and assumed dead. r Composed of l000A. females 24+ months old. • Composed of 100% females 36+ months old. ; Composed of 100% females 60+ months old. , Composed of l000A. females 84+ months old �253 Table 9. Annual survival rates from 1 December-30 November each year 1993-94 - 1998-99 inclusive of nonhunting and hunting mortalities and overall survival through Novemeber 1999 for the group of adult female elk age ~18 months when radio-collared in December 1993. Survival rates (S) calculated as a mean estimate of (alive)/(alive+dead) and variance S(1-S)/n collars. Elk Age and Time Period (dates) Adult Adult Adult Adult Adult Adult Adult 19931994199519961997199819931994 1995 1996 1997 1998 1999 1999 Survival 0.78 0.84 0.86 0.94 0.71 0.83 0.30 L 95%CI 0.68 0.75 0.75 0.87 0.55 0.68 0.19 U 95% CI 0.88 0.93 0.97 1.00 0.86 0.99 0.41 68b,. 53b.f 34) 24k n collars 42g 36i 67 Ib Ib Censored" 0 0 0 0 0 d Died 15° 10 6 2 10 47 4 Nonhunt 2 1 3 0 0 6 0 Hunt 13 9 41 3 2 10 4 • Censored denotes collar failure or life/death status unknown b Includes collar (172.011193) failed 4/1994 seen alive 111996 d Collar (172.207/93) disappeared 1995 hunt seasons, assumed dead. t Composed of 100% females 24+ months old. ~ Censored (172.011193) failure 4/1996. j Composed of 60+ months old females. c Collar (172.649/93) disappeared 1994 hunt seasons • Composed of 6-18+ and 62-30+ months old females • Composed of36+ months old females I Composed of 48+ months old females k Composed of72+ months old females Table 10. Survival rates for adult male elk during summer-fall, 15 June-30 November, 1995-1999. All deaths due to hunting. Survival rates (S) calculated as 11 mean estimate of (alive)/(alive + dead) and variance S(I-S)/n collars. Removal rate = (1-S). All males radio-collared as 6-month old calves in December 1993-1996. Summer-Fall Time Period Year All Years 1995 1999 1996 1997 1998 MALES (age 24-29 months) Survival 0.21 0.22 0.08 0.23 0.35 L 95%CI 0.06 0.00 0.14 0.04 0.17 U95%CI 0.37 0.19 0.30 0.41 0.54 n collars 28 103 25 22 28 Died Hunting 80 22 23 17 18 Removal Rate 0.79 0.78 0.92 0.77 0.65 MALES (age 24-53 months) Survival 0.21 L 95% CI 0.06 U95%CI 0.37 n collars 28 Died Hunting 22 Removal Rate 0.79 0.14 0.01 0.27 29 25 0.86 0.24 0.06 0.42 25 19 0.76 0.33 0.17 0.50 33 21 0.64 0.27 0.00 0.57 11 8 0.73 0.24 0.17 0.32 126 95 0.76 �254 Table 11. Survival rates for adult female elk during summer-fall, 15 June-30 November, 1994-1999. For adult females, 2 natural deaths occurred during summer-fall in these 6 years and these 2 elk were censored from survival calculations. All deaths shown were due to hunting. Survival rates (S) calculated as a mean estimate of (alive) / (alive + dead) and variance of S(I-S) / n collars. Removal rate = (l -S). Females radio-collared as adults in 1993 or as 6-month calves in December 1993-1996. Summer-Fall Time Period Year 1994 1999 1995 1996 1997 1998 All Years FEMALES (age> 24 months) Survival 0.83 0.89 0.77 0.89 0.93 0.91 0.87 L 95% CI 0.73 0.70 0.83 0.88 0.85 0.84 0.84 U95%CI 0.92 0.98 0.95 0.84 0.95 0.89 0.96 n collars 64 110 122 136 99 628 97 Died Hunting 11 11 7 10 13 31 83 Removal Rate 0.17 0.11 0.07 0.09 0.11 0.23 0.13 FEMALES (age 12-17 months) 0.97 Survival L95% CI 0.92 U95%CI 1.00 n collars 35 Died Hunting 1 Removal Rate 0.03 0.97 0.91 1.00 32 1 0.03 0.87 0.75 0.99 31 4 0.13 1.00 30 0 0.00 0.95 0.92 0.99 128 6 0.05 �255 Appendi x I. MortaLities of 256 radio-coLLared eLk from 1 December 1993 through 14 June 2000. Age is aE2roximate a2e in ~ears of eLk at death: C=caLf a2e 6-11 months, Y=~earLin2 a2e 12-23 months. Death Frequency 101 Tra!;! Cause of Death & Code Number Date Age Zone Sex Year Ca~tured Site legaL kiLL second rifLe season-47 19-Oct-99 B 9 SR F 172.019/93 legaL kiLL second rifLe season-47 27-Oct-95 5 BR A F 172.030/93 legaL kiLL third rifLe season-48 31-Oct-98 F 12 EG B 172.050/93 Unknown-suspect predation-30 14-Jun-95 B F 4 GR 172.039/93 Unknown-11 12-Feb-96 F 11 BR A 172.070/93 legaL kiLL third rifLe season-48 05-Nov-94 6 GM A F 172.080/93 Wounding Loss late rifle season-26 16-Jan-94 F 11 GR B 172.090/93 legaL kiLL first rifLe season-46 12-Oct-98 0 F 11 SM 172.090/94 legaL kiLL first rifLe season-46 14-Oct-96 8 B F 172.101/93 SR Wounding Loss second rifLe season-44 31-Oct-96 8 B F GC 172.128/93 Wounding loss first rifLe season-43 19-0ct-95 17 BC C F 172.139/93 legaL kiLL second rifLe season-47 23-0ct-94 C F 3 CC 172.160/93 Wounding Loss second rifle season-44 03-Nov-94 3 MC C F 172.181/93 Wounding Loss second rifle season-44 15-Nov-94 3 GS C F 172.201/93 Disappear first rifle season-40 30-Nov-95 4 SG 0 F 172.207193 legaL kiLL rifle season-28 30-Nov-99 0 F 8 GH 172.219/93 legaL kiLL second rifle season-47 29-Oct-98 8 MC C F 172.229/93 legaL kiLL archery/muzzLe season-27 04-Oct-94 3 HY C F 172.258/93 Disappear second rifLe season-41 29-0ct-98 C F 12 MC 172.269/93 Wounding loss archerY/muzzLe-24 04-Oct-94 3 GS C F 172.277/93 legal kiLL second rifle season-47 23-0ct-94 D 6 SG F 172.290/93 legal kilL muzzleloading season-34 16-Sep-96 SM D F 4 172.290/94 Wounding loss second rifLe season-44 30-0ct-97 E 8 AC F 172.300/93 Disappear second rifle season-41 29-Oct-98 8 GH D F 172.308/93 legal kiLL first rifle season-46 10-Oct-99 D 11 SG F 172.330/93 legaL kiLL second rifle season-47 19-Oct-99 SG D F 11 172.358/93 legaL kiLL archery season-33 18-Sep-94 3 AC E F 172.369/93 legaL kiLL Late rifLe season-29 14-Jan-96 FM B F 4 172.369/94 Wounding Loss Late rifLe season-26 29-Dec-94 8 AC E F 172.409/93 legaL kiLL third rifle season-48 01-Nov-98 MH E F 172.448/93 I12 legaL kiLL second rifle season-47 24-0ct-96 E 8 MH F 172.459/93 Disappear first rifle season-40 15-0ct-98 12 FS H F 172.498/93 legaL kiLL second rifle season-47 21-0ct-95 3 FS H F 172.509/93 legaL kiLL first rifLe season-46 12-0ct-98 6 FS H F 172.519/93 Wounding Loss second rifLe season-44 29-Oct-98 8 FS H F 172.530/93 Mountain lion predation-3 01-Feb-94 6 FS H F 172.542193 Accident-irrigation ditch-10 06-Jan-99 15 FM B F 172.542/94 legaL kill late rifle season-29 28-Nov-95 7 PG H F 172.549/93 Wounding loss second rifle season-44 03-Nov-94 16 PG H F 172.570/93 legaL kiLL first rifLe season-46 17-Oct-94 PG H F 3 172.581/93 legal kill late rifle season-29 08-Dec-95 3 FM B F 172.581/94 Unknown-11 24-Apr-96 5 PG H F 172.590/93 Accident, birthing/calving-32 04-0ct-94 PG F 3 H 172.610/93 legaL kiLL third rifLe season-48 04-Nov-98 H F 5 PG 172.620/93 Accident, birthing/calving-32 14-Jun-96 16 PG H F 172.639/93 Disappear first rifle season-40 30-Nov-94 H F 2 172.649/93 PG legal kiLL third rifle season-48 02-Nov-97 H F 5 PG 172.658/93 legal kiLL late rifle season-29 16-Jan-95 4 PG H F 172.670/93 Wounding loss late rifle season-26 22-Dec-94 PG H F 9 1'72.678/93 Illegal kit l-7 24-Jan-94 B F 8 172.690/93 FM legaL kiLL third rifLe season-48 05-Nov-95 B 7 FM F 172.699/93 MaLnutrition-6 05-May-99 19 lS H F 172.730/95 Unknown-suspect predation-30 07-Aug-96 lS H F 11 172.749/95 Wounding Loss second rifLe season-44 28-Oct-98 15 lS H F 172.758/95 Wounding Loss second rifLe season-44 16-Oct-99 F 6 lS H 172.769/95 Mountain Lion predation-3 31-Dec-99 6 SR B F 172.790/93 Disappear second rifLe season-41 30-Nov-94 SR B F Y 172.800/93 legal kilL archery season-33 05-Sep-99 6 EG B F 172.810/93 legaL kilL archery season-33 08-S.ep-96 3 EG B F 172.821/93 legaL kilL third rifLe season-48 Q6-Nov-96 3 BC C F 172.890/93 Mountain Lion predation-3 18-Mar-94 BC C F C 172.899/93 legaL kiLL first rifLe season-46 18-0ct-95 GH D F 2 172.950/93 Disappear 'second rifLe season-41 30-Oct-97 MG D F 4 172.961/93 Disappear second rifLe season-41 29-0ct-98 D 5 SG F 172.991/93 Malnutrition-6 25-Apr-94 WM C 173.000/93 G F legaL kill third rifLe season-48 31-Oct-98 F 4 173.000/94 HM B Accident-feLL-10 07-Jan-98 WM 4 G F 173.010/93 legal kiLL first rifLe season-46 19-Oct-95 2 GM A M 173.041/93 �256 Appendix 1. (continued) Frequency ID/ Tral2 Year Captured Site Zone 173.050/93 MH E 173.060/93 MH E 173.070/93 E MH 173.081/93 FS H 173.090/93 FS H 173.100/93 FS H 173.120/93 GM A 173.140/93 PG H 173.160/93 FS H 173.180/93 PG H 173.171/93 FM B 173.190/93 BC C 173.190/96 BC C 173.201/93 GR B 173.210/93 GC B 173.210/96 LM D 173.219/93 BC C 173.219/96 CG D 173.232/93 BR A 173.232196 BC C 173.262/93 BC C 173.262/94 HM B 173.269/93 MC C 173.279/93 C MC 173.289/93 MC C 173.289/94 PR A 173.300/93 C GS 173.300/96 MC C 173.309/93 HY C 173.320/93 HY C 173.320/94 HM B 173.332/93 GH D 173.332/96 BC C 173.340/93 SG D 173.351/93 SG D 173.351/96 BG E 173.359/93 AC E 173.359/96 C MC 173.370/93 MH E 173.370/96 RG E RG' 173.381/96 E 173.390/93 MG D 173.402/93 MG D 173.410/93 WM G 173.410/96 EW G 173.420/93 WM G 173.429/93 MH E 173.429/96 G EW 173.439/93 PG H 173.450/93 PG H 173.450/96 EW G 173.461/93 PG H 173.461/94 CM A 173.461/96 GM A 173.469/93 FS H 173.469/94 PR A 173.479/93 FS H 173.479/96 RG E 173.492/93 FS H 173.492196 GM A 173.502/93 FS H 173.510/93 FM B 173.521/93 FM B 173.530/94 FM B 173.540/94 OG B 173.549/94 B HM 173.559/94 PR A 173.569/94 PR A 173.580/94 PR A Death Sex F F F F F F M F F F F M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M F M F F F F Age 5 2 5 3 4 4 2 3 3 6 5 Y 2 2 2 2 2 2 Y 2 C 2 2 3 C 2 2 2 Y Y ,2 2 2 4 2 2 2 2 2 C C 2 2 2 1 2 2 3 2 2 3 C Y 2 C 2 2 2 2 3 3 2 2 7 2 Y 5 3 Y Date 31-Oct·98 27-Dec-95 03-Mar-98 22-OCt-96 24-Oct-97 30-Oct-97 14-OCt-95 31-Oct-96 13-Noy-96 10-OCt-99 10-OCt-98 29-OCt-94 10-OCt-98 30-Noy-95 19-0ct-95 30-OCt-97 06-Noy-95 21-Oct-98 15-Noy-94 31-OCt-98 18-Mar-94 12-Oct-96 06-Noy-95 12-Oct-96 22-Mar-94 18-Sep-96 24-Oct-95 10-OCt-98 30-Noy-94 20-Oct-94 14-Sep-96 12-Sep-95 10-0ct-98 20-0ct-97 05-Noy-95 27-Oct-98 06-Sep-95 09-Noy-98 08-Noy-95 08-Jan-97 19-Feb-97 30-Noy-95 18-0ct-95 02-Noy-95 29-Sep-98 24-0ct-95 14-Sep-95 10-0ct-99 30-Noy-95 15-Oct-95 21-Oct-99 07-Feb-94 19-5ep-95 22-OCt-98 25-Apr-94 20-OCt-96 10-Sep-95 17-0ct-98 03-Sep-95 11-0ct-99 13-Noy-96 28-Aug-95 17-0ct-95 31-OCt-98 13-0ct-96 07-Sep-95 30-Oct-99 16-Oct-97 21-Dec-95 Cause of Death & Code Number Legal kill third rifle season-48 Legal kill late rifle season-29 Illegal kill-7 Legal kill second rifle season-47 Legal kill second rifle season-47 Legal kill second rifle season-47 Legal kill first rifle season-46 Wounding loss second rifle season-44 Legal kill third rifle season-48 Legal kill first rifle season-46 Legal kill first rifle season-46 Illegal kill second rifle season-50 Legal kill first rifle season-46 Wounding loss third rifle season-45 Legal kill first rifle season-46 Illegal kill archery/muzz. season-8 Legal kill third rifle season-48 Legal kill second rifle season-47 Illegal kill second rifle season-50 Legal kill third rifle season-48 Unknown-11 Legal ki II first rifle season-46 Legal k i II third rifLe season-48 LegaL kill first rifLe season-46 Unknown-11 LegaL kiLL muzzLeLoading season-34 LegaL kill second rifLe season-47 LegaL kiLL first rifle season-46 ILlegal kiLL first rifle season-49 Illegal kill first rifle season-49 LegaL kill archery season-33 LegaL kill muzzleloading season-34 Legal kiLL first rifle season-46 LegaL kill second rifLe season-47 Legal kill third rifle season-48 Legal kill second rifle season-47 Legal kill archery season-33 Wounding loss third rifle season-45 Legal kill first rifLe season-46 Mountain lion predation-3 Unknown-suspect predation-30 Disappear first rifle season-40 Legal kill first rifle season-46 Wounding (oss second rifle season-44 Wounding Loss archery/muzzle seasons-24 Legal kill second rifle season-47 Legal kill archery season-33 Legal kill first rifLe season-46 Disappear first rifLe season-40 Legal kill first rifle season-46 Legal kill second rifle season-47 Malnutrition-6 Wounding loss archery season-50 LegaL kill second rifLe season-47 MaLnutrition-6 Legal kill second rifle season-47 Legal kill archery season-33 LegaL kill second rifle season-47 Legal kiLL archery season-33 Legal kill first rifle season-46 LegaL kill third rifLe season-48 Legal kill archery season-33 LegaL kill first rifle season-46 Legal kill third rifle season-48 Legal kill first rifle season-46 Legal kill archery season-33 Legal kill third rifle season-48 Wounding loss first rifle season-43 Unknown-11 �257 A~ndix I. (continued) Frequency 10/ Tra!:! Zone Year Ca~tured Site 173.589/94 OG B 173.610/94 C BC 173.640/94 C MC 173.640/96 GM A 173.649/94 BC C 173.659/94 C MC 173.679/94 MP D 173.689/94 BG E 173.699/94 E BG 173.719/96 MC C 173.739/94 BG E 173.750/94 E BG 173.760/94 E MR 173.779/94 MR E 173.789/94 MR E 173.819/94 MM F 173.829/94 MM F 173.840/94 MM F 173.849/94 SM D 173.859/94 SM D 173.870/94 SM D 173.919/94 BC C C 173.929/94 BC 173.939/94 C BC 173.959/94 BC C 173.970/94 MC C 173.981/94 D MP 173.990/94 C BC 174.001/94 BG E 174.009/94 BG E 174.019/94 E BG 174.039/94 MR E 174.049/94 F MM 174.059/94 E MR 174.069/94 BG E 174.080/94 E MR 174.090/94 MR E 174.101/94 MM F 174.101/96 E~ G 174.109/94 MM F 174.119/94 MM F 174.119/95 GB B 174.129/94 MM F 174.140/94 F MM 174.140/95 GB B 174.150/94 MM F 174.160/94 MM F 174.170/94 FM B 174.170/96 C MC 174.181/94 FM B 174.200/95 MS F 174.210/95 MS F 174.220/95 MS F 174.220/96 F MS 174.230/95 MS F 174.230/96 G E~ 174.240/95 E MD 174.240/96 SR B 174.301/95 MD E 174.319/95 MS F 174.329/95 E MD 174.339/95 MD E 174.349/95 E MD 174.360/95 MD E 174.370/95 HG E 174.380/95 AP D 174.401/95 AP D 174.420/95 AP D 174.478/95 W C Death Sex F F F F F F F F F F F F F F F F F F F F F M M M M M M M M M M M M M M M M M M M M M M M M F F F F F F F F F F F Age C 3 C C 3 4 it 2 5 2 4 4 4 5 C 3 2 4 4 2 C Y 2 2 2 2 2 2 2 2 12 2 2 Y 2 3 2 Y 3 2 C 2 2 C Y 2 2 C 2 2 Y 2 C 3 C 2 C 2 3 Y Y C 2 Y 4 4 2 2 2 Date 01-Jun-95 14-Nov-97 30-Mar-95 16-Mar-97 11-0ct-97 25-0ct-98 29-Oct-98 31-Oct-96 30-Nov-99 03-Nov-98 29-Oct-98 18-Oct-98 29-Oct-98 31-Dec-99 20-Mar-95 30-Oct-97 10-Jan-97 29-Sep-98 20-Oct-98 23-0ct-96 21-Feb-95 02-Nov-95 16-Oct-96 18-Sep-96 02-Nov-96 20-Oct-96 02-Nov-96 20-Oct-96 30-Nov-96 12-0ct-96 13-Nov-96 05-Sep-96 14-Sep-96 17-0ct-95 26-Sep-96 11-0ct-97 20-Oct-96 24-May-96 10-0ct-99 19-Oct-96 01-Mar-95 30-Nov-97 14-0ct-96 14-Mar-95 30-Nov-96 14-0ct-96 15-Sep-96 25-Apr-95 10-0ct-98 30-Nov-96 18-0ct-96 11-0ct-97 08-Apr-96 11-0ct-99 24-Apr-96 13-0ct-98 17-Apr-96 12-Sep-98 20-Sep-98 02-Oct-96 03-Sep-96 27-Mar-96 13-Oct-97 22-Apr-97 30-Nov-99 30-Aug-99 22-Sep-96 11-Oct-97 13-Sep-97 Cause of Death & Code Number Unknown-suspect predation-30 ~ounding loss third rifle season-45 Unknown-suspect predation-30 Malnutrition-6 legal kill first rifle season-46 legal kill second rifle season-47 Wounding loss first rifle season-43 legal kill first rifle season-46 ~ounding loss rifle season-25 legal kill thi~d rifle season-48 ~ounding loss second rifle season-44 legal kill second rifle season-47 Disappear second rifle season-41 legal kill late rifle season-29 Unknown-suspect malnutrition-31 legal kill second rifle season-47 legal kill late rifle season-29 ~ounding loss archery/muzzle seasons-24 legal kill second rifle season-47 legal kill second rifle season-47 Mountain lion predation-3 Illegal kill second rifle season-50 legal kill first rifle season-46 legal kill archery season-33 legal kill third rifle season-48 legal kill second rifle season-47 legal kill third rifle season-48 legal kill second rifle season-47 Disappear archery/muzzle season-21 legal kill first rifle season-47 Illegal kill rifle season-9 legal kill archery season-33 legal kill muzzleloading season-34 Illegal kill first rifle season-49 ~ounding loss archery/muzzle-24 legal kill first rifle season-46 legal kill second rifle season-47 Unknown-suspect predation-30 legal kill first rifle season-46 legal kill second rifle season-47 Mountain lion predation-3 ~ounding loss rifle season-25 legal .ki ll first rifle season-46 Mountain lion predation-3 Illegal kill third rifle season-51 legal kill first rifle season-46 legal kill muzzleloading season-34 Mountain lion predation-3 legal kill first rifle season-46 Disappear second rifle season-41 Illegal kill first rifle season-49 legal kill first rifle season-46 Unknown-suspect malnutrition-31 legal kill first rifle season-46 Mountain lion predation-3 legal kill first rifle season-46 Mountain lion predation-3 legal kill muzzleloading season-34 legal kill archery season-33 ~ounding loss archery season-52 legal kill archery season-33 Unknown predator-5 legal kill first rifle season-46 Unknown-suspect predation-30 ~ounding loss rifle season-25 legal kill archery season-33 legal kill muzzleloading season-34 legal kill first rifle season-46 legal kill muzzleloading season-34 �258 Apeendix I. (continued) Frequency 10/ Tral;! Year Captured Site Zone 174.491/95 lB e 174.500/95 e lB 174.520/95 KR B 174.520/96 A GM 174.551/95 \Ie G 174.560/95 A Bl 174.609/95 GB B 174.629/95 E MD 174.639/95 MD E 174.650/95 HG E 174.660/96 B SR 174.679/95 E HG 174.689/95 D AP 174.689/96 G EW 174.700/95 0 AP 174.710/95 0 AP 174.719/95 VM 0 174.729/95 D VM 174.740/95 D VM 174.750/95 D VM 174.760/95 VM D 174.770/95 e W 174.780/95 e W 174.789/95 e W 174.789/96 G EW 174.800/96 E BG 174.809/95 W C 174.820/95 W C 174.830/95 lB e 174.841/95 e LB 174.851/95 e lB 174.861/95 KR B 174.870/95 e lB 174.880/95 B KR 174.889/95 G we 174.899/95 Bl A 174.910/96 LM D 174.929/96 D lM 174.959/96 lM 0 174.998/96 BG E 175.059/96 BC C 175.130/96 GM A 175.139/96 GM A 175.149/96 SR B 175.160/96 c Be 175.170/96 0 lM 175.180/96 E RG 175.189/96 RG E 175.199/96 EW G 175.209/96 MS F Oeath Sex F F F F F F F M M M M M M M M M M M M M M M M M M M M M M M M M M M M M F F F F F F F F M M M M M M Age 2 e Y e 3 Y e 2 2 3 3 Y e e 2 2 4 Y 2 2 3 2 2 e 2 e Y 2 2 3 12 Y 2 2 2 2 e 2 2 2 C C 2 2 2 C 3 2 2 2 Oate 10-Sep-97 16-Apr-96 21-Sep-96 25-Apr-97 14-Oct-98 14-May-97 15-Apr-96 11-Oct-97 21-0ct-97 14-Sep-98 07-Nov-99 13-Nov-96 05-Feb-96 14-May-97 16-Oct-97 15-0ct-97 10-0ct-99 17-0ct-96 08-Nov-97 05-Nov-97 15-Sep-98 16-Oct-97 11-0ct-97 22-May-96 28-0ct-98 09-Apr-97 22-Apr-97 14-Oct-97 13-0ct-97 12-Sep-98 22-0ct-97 31-0ct-96 30-0ct-97 11-0ct-97 20-0ct-97 30-0ct-97 27-Feb-97 29-Oct-98 29-0ct-98 21-0ct-98 13-Feb-97 24-Mar-97 28-0ct-98 19-0ct-98 17-Sep-98 26-Mar-97 30-Nov-99 13-0ct-98 29-0ct-98 24-0ct-98 Cause of Oeath & Code Number Wounding loss archery season-52 Unknown-suspect predation-30 legal kilL IlUzzleloading season-34 Mountain lion predation-3 legal kill first rifle season-46 Illegal kill-7 Unknown-suspect predation-30 legal kill first rifle season-46 legal kill second rifle season-47 legal kill IlUzzleloading season-34 Wounding loss third rifle season-45 Illegal kill second rifle season-50 Mountain lion predation-3 Unknown-suspect malnutrition-31 Wounding loss first rifle season-43 legal kill first rifle season-46 Legal kill first rifle season-46 Illegal kill first rifle season-49 Legal kill third rifle season-48 legal kill third rifle season-48 Legal kill archery season-33 Disapeear first rifle season-40 legal kill first rifle season-46 Unknown-suspect predation-30 Wounding loss second rifle season-44 Mountain lion predation-3 Accident, fell-10 legal kill first rifle season-46 legal kill first rifle season-46 Legal kill IlUzzleloading season-34 Illegal kill second rifle season-50 Illegal k ill second rifle season-50 Wounding loss second rifle season-44 legal kill first rifle season-46 legal kill second rifle season-47 Wounding loss second rifle season-44 Unknown-suspect predation-30 Disapeear second rifle season-41 Wounding loss second rifle season-44 legal kill second rifle season-47 Unknown-11 Mountain lion predation-3 legal kill second rifle season-47 legal kill second rifle season-47 legal kill IlUzzleloading season-34 Unknown-suspect malnutrition-31 Wounding loss rifle season-25 . legal kill first rifle season-46 Oisapeear second rifle season-41 Legal kill second rifle season-47 � https://cpw.cvlcollections.org/files/original/a2fae5d7a4eef8e55dda4123ea65bc20.pdf b5871955c8ba4bae18ec79e90191b315 PDF Text Text 207 Colorado Division of Wildlife Wildlife Research Report July 1998 Job Progress Report State of Colorado Cost center 3430 Project No. W-153-R-11 Mammals Program Project No. 3002 Elk conservation Work Program No. - - ~ L - - - - - - - Elk Movements in Response to Early season Hunting in the White River Area Period Covered: July 1, 1997 - June 30, 1998 Author: Mary Conner Personnel: Dave Freddy, Gary White, Rick Kahn, John Ellenberger, Jim Lipscomb, Bruce Gill, Jeff Madison ABSTRACT The effects of early hunting seasons on the movements and distribution of elk remains controversial. Those who hunt the regular rifle seasons claim that archery and muzzle loading rifle seasons drive elk off of public lands and onto private land refuges before the regular rifle season begins, making them unavailable to most who hunt in the regular rifle season.· Landowners complain that elk responses to early hunting seasons cause elk to spend longer periods on private property at the expense of the landowner. Beginning in 1996, the Colorado Division of Wildlife sponsored a management experiment designed to test the effects of early hunting on the movements and distribution of elk residing in and around the White River plateau. Four primary conclusions emerged from a preliminary analysis of 2 years of data: (1) In both 1996 and 1997, between 22-37% of the elk were on private land before mid-July. By mid-October, between 65-85% of the elk were on private land. The proportion of elk on private land was positively correlated with date; there was a 28-60% increase of elk on private land during the study period. (2-) The mean date of movement from public (non-refuge) to private land was not significantly different between treatments in the crossover analysis. Mean date of movement was different between treatments for 1997 but not for 1996. Mean date of movement was different between treatments for elk on the north half of the study area, but not found different for elk on the south half. The difference between late minus early date of movement was 6 days for elk receiving both treatments. �208 (3) Differences between elk on the north area and elk on the south area showed in responses of mean date of movement and proportion of elk on refuge areas. Mean date of movement between treatments was significantly different for elk on the north area but not for elk on the south area. The difference in proportion of elk on refuge areas between treatments was greater for elk on the north area than for elk on the south area. (4) Although all elk were captured on national forest land, some elk immediately moved to private land in 1996, and some elk were never located on public land during 1997 flights. "Manageable" elk include only those elk that are on public land within a month of early-season opening date. "Unmanageable• elk are those not on public land within a month of early-season opening date and are, therefore, not likely to be affected by changes in hunting patterns on public land. Between 39-64% of elk on public land one month before early-season opening date (unmanageable elk) moved to private land, and the mean date of movement including opening date in 3 of 4 cases. However, the elk that moved represent 31-41% of the entire herd (unmanageable and manageable elk). Therefore, any management decisions regarding hunter numbers is likely to affect at most 41%, and possibly less, of the White River elk. �209 ELK MOVEMENT IN RESPONSE TO EARLY SEASON IIUHTING IN THE WHITE RIVER AREA Mary Conner P.H. OBJECTIVE Test whether early-season hunting season causes movement of elk from areas of heavy hunting pressure to areas of lighter hunting pressure. SEGMENT OBJECTIVES 1. Estimate the mean date of movement of elk from non-refuge to refuge areas, and determine whether the timing is equivalent to the opening of archery season. 2. Evaluate alternative hypotheses about causes of elk movement such as livestock grazing, woodcutting, recreationalists, weather, or forage quality. 3. Publish analyses of elk movement in response to archery hunting in peerreviewed scientific journals. Preparation of manuscripts will begin during 1997-98. METHODS ARD MATERIALS Methods and materials used in this investigation are described in the detailed study plan reported in Conner 1996. RESULTS ARD DISCUSSIQH Preliminary analyses, results and conclusions of the 2-year study of the effects of early hunting seasons on the movements and distribution of elk in the White River area are summarized in Attachment 1 to this report. LITERATURE CITED Conner, M. 1996. Elk movements in response to early season hunting in the White River area. Colorado Division of Wildlife. Wildlife Research Report. July 1996 Part 1. Pp. 43-86. Prepared by Graduate Research Assistant ��211 Attachment 1 ELK MOVEMENTS IN RESPONSE TO EARLY-SEASON HUNTING IN 11IE WlilTE RIVER AREA: 1997 PRELIMINARY RESULTS Mary Conner March 31, 1998 EXECUTIVE SUMMARY This year was the second and final year of an experiment designed to determine if elk movements in the White River area were caused by early-season (archery and muzzleloading) hunting. The goal of this report is to present 1997 results in a timely manner. This interim report provides information for those involved with the White River elk to make relevant management decisions. Analyses that are more extensive will be included in my dissertation, which will be completed late spring or early summer 1998. Three main conclusions emerged from preliminary analyses of data from both years: (1) the proportion of elk located on private land (refuge) increased between July 15th - October 13th, (2) the timing of these movements weakly corresponded to the opening date of archery season, (3) elk on the north area had a stronger response to changes in archery-season opening date than elk on the south area, and (4) it is not clear how many elk in the White River area would be affected by management actions such as a reduction of archery hunting licenses. Conclusion (1): In both 1996 and 1997 between 22-37% of the elk were on private land before midJuly. By mid-October, between 65-85% of the elk were on private land. The proportion of elk on private land was positively correlated with date; there was a 28-60% increase of elk on private land during the study period. Conclusion (2): The mean date of movement from public (non-refuge) to private land was not significantly different between treatments in the crossover analysis. Mean date of movement was different between treatments for 1997 but not for 1996. Mean date of movement was different between treatments for elk on the north half of the study area but not found different for the south half elk. The difference between late minus early date of movement was 6 days for elk receiving both treatments. Conclusion (3): Differences between elk on the north area and elk on the south area showed in responses of mean date of movement and proportion of elk on refuge areas. Mean date of movement between treatments was significantly different for elk on the north area but not for elk on the south area. The difference in proportion of elk on refuge areas between treatments was greater for elk on the north area than for elk on the south area. Conclusion (4): Although all elk were captured on national forest land, some elk immediately moved to private land in 1996, and some elk were never located on public land during the 1997 flights. "Manageable" elk include only those elk that are on public land within a month of early-season opening date. "Unmanageable" elk are those elk not on public land within a month of early-season opening date and t rtherefore, not likely to be affected by changes in hunting patterns on public land. Between 39-64% of elk on public land a month before early-season opening date (manageable elk) moved to private land, and the mean date of movement included opening date in 3 of 4 cases. However, the elk that moved represent 3141 % of the entire herd (manageable and unmanageable elk). Therefore, any management decisions regarding hunter nwnbers are likely to affect at most 41 %, and possibly less, of the White River elk. INTRODUCTION As with the 1996 analyses, the treatment was difference in opening date of archery season and the primary response variables were mean date of movement and proportion of elk that move from public to private land I repeated all 1996 analyses for area x year to evaluate effects of archery hunting on elk that were on public land within a month of opening date and to compare to pilot study results (Appendix A: Methods). Because there are now 2 years of data, overall analyses including year and area effects were done to evaluate effects of changes in opening date of archery hunting. To evaluate treatment effects on mean date of movement, I did the crossover analysis described in my study plan (Appendix A: Methods). To evaluate �212 treatment effects on proportion of elk moving to refuge areas, I included area and year effects in the logistic regression model used in 1996 to predict the proportion of elk on refuge areas (Appendix A: Methods). Data from the entire 3-month study period were used in the crossover and logistic regression analyses. PRELIMINARY RESULTS Area x Year Analyses The timing of elk movements from non-refuge to refuge areas on the early- and late-opening treatments is presented for 1996 and 1997 (Fig. IA, B). Only elk moving within a month of opening date were used for within-treatment analyses to represent effects on manageable elk.Figure 1. Histograms of number of elk moving from public (non-refuge) to private (refuge) land with respect to archery-season opening date on the early-opening (A) and late opening (B) treatments; White River elk herd, 1996 and 1997. B A 1996 south side 1996 north side 4 4 Mun date of movemant8/26 CD Hlstortcal opening data .E 3 ~ ~3 E E .:.=: ='GI 2 ::, 0 !E 1 ::, 1 z z 0 0 IIIIIIIIIIIIIIIII Early opening: 8/24 § 1997 north side Mun Date of MovenwntB/18 1997 south side Hlstortcal opening data 4-r-----------------, 3 .:.=: 'ii 2 !E 1 0 1 ::, z Historical opening date CD C 1 ::, IIII~ IIIIIIIIIIII Late opening: 9/14 4 -r-----------------, !E Historical opening date ~2 0 !E Mean Date of Movement: 1115 CD C Mean Data of Movemant 916 z ~ ; IIt IIIIIIIIIIII Early opening: 8/23 I ; IIi IIIIIII IIIIIII Late opening 9/13 For elk moving from non-refuge to refuge areas, mean date of movement was tested under the null hypothesis that the mean date of movement was not different from opening date (Table 1). Between 39-64% of elk on non-refuge areas one month before opening date moved to refuge areas within a month of opening date (Table 2). The probability that classifications are independent of opening date (Table 2) evaluated the effect archery hunting has on elk location by testing whether movements between classifications occurred independently before and after opening of archery hunting. �213 Table 1. Mean dates of movement of elk moving from non-refuge to refuge areas. opening dates of archery season, and P-values from a t-test for differences between opening date and mean date of movement for earlyand late-opening treatments; White River study area. 1996 and 1997. Early opening Late opening Mean date of movement 95% Confidence interval 26 August 17 August- 18 August 11 August- 5 September 30 August- 6 September 26 August- Opening date of early-season 24 August 23 August 14 September 13 September P = 0.578 P = 0.178 P = 0.014 P = 0.131 - Ho: d _ = onenin2' date Table 2. Movements ofradio-collared elk between refuge and non-refuge areas with respect to opening date. early-and late opening treatments; White River study area. 1996 and 1997. Movement Combinations: Early opening Late opening Pre-opening -> post-opening YEAR 1 - South YEAR 2 - North YEAR 1 - North YEAR 2 - South Refuge -> refuge 11 8 4 11 Refuge -> non-refuge 5 0 2 2 Non-refuge-> refuge 12 18 15 14 Non-refuge -> non-refuge 19 10 20 15 Sample size 47 36 41 42 P= 0.047 P= 0.280 P=0.027 Probability movement combinations P=0.051 Overall Analyses on Mean Date of Movement The time frame for between-treatment analyses is the 3-month study period of July 15 th - October th 13 . Results from the crossover analysis on mean date of movement indicated no area (P = 0.138) or year effect (P = 0.644); however, there was a significant random effect of elk in area (P = 0.025). There was not a significant treatment effect (P = 0.159) on the mean date of elk movement from non-refuge to refuge areas (Table 3). Sequence effect refers to the fact that each elk received either a late-early or early-late sequence of treatments. Elk on the north half received the late-early treatment sequence. while elk on the south half received the early-late treatment sequence. Area effects and sequence effects were confounded. That is. it is impossible to determine if a sequence effect is really a difference due to the fact that the north side is different from the south side because of location of private-land refuges, topogQlphy, etc., or due to the fact that elk getting a late-opening treatment the first year followed by an early-opening treatment the second year will behave differently than elk getting the early-late sequence. I will refer to an area effect for clarity in the remainder of the paper. There appeared to be a treatment x year and treatment x area interaction in the crossover analysis that clouded the results. In a post hoc analysis, I found that there was a difference in mean date of movement between treatments for elk moving from non-refuge to refuge areas in 1997 but not in 1996 (Fig. 2 and Table 4). �214 Table 3. Least square mean differences in days between mean dates of movement for effects specified in the crossover analysis with their 95% confidence intervals; White River elk herd 1996 and 1997. No. of days difference No. of days difference No. of days difference between areas: ok between treatments: a; between years: Pi 7±9 2±7 6±8 Figure 2. Mean date of movement, 95% confidence interval, and archery opening date for elk on early-and late opening treatments, 1996 (A) and 1997 (B), White River elk herd. A 1996 Early open: South Mean date of movement: Late open: North Aug 26 Aug 31 Sept14 Aug 24 Opening Date: B 1997 Late open: South Early open: North Mean date of movement: Aug 18 Sept3 ~ IIII Aug 23 Opening Date: I Sept 13 Table 4. Differences between opening dates and mean dates of movement between early- and late-treatments, 95% confidence interval, and P-value for test of differences between mean opening dates 1996 and 1997; White River elk herd Year Days between .. 1996 1997 . dates 20 20 Days between mean p dates of movement 5± 11 16± 12 0.371 0.010 �215 I also did a post-hoc analysis to evaluate the treabnent effect by area, as it appeared that elk on the north area were moving to private land more readily than elk on the south area. There was a difference in mean date of movement between treabnents for elk on the north area but not for elk on the south area (Table 5). Table.5. Differences between opening dates and mean dates of movement between early- and late-treabnents for north- and south-side elk, 95% confidence interval, and P-value for test of differences between mean opening dates; White River elk herd 1996 and 1997. Area Days between Days between mean dates p North side ooenine: dates 20 of movement 13 ± 10 0.009 20 8 ± 14 0.267 (late-early treabnent) South side (earlv-late treabnent) I then analyzed date of movement only for individual elk that received both the early and late treabnent. Only 16 elk received both treabnents because some elk were not on public land for one year and some changed side of study area between years. For the elk getting both treabnents, I subtracted their early date of movement from their late date of movement to account for the fact that this was a repeated measurement on the elk. I tested the hull hypothesis that: Ho: Difference in date of movement for late treabnent • early treabnent = 0 Ha: Difference in date of movement for late treabnent - early treabnent > 0 . The difference in mean date of movement was 6 ± 7 days (p = 0.065). The distribution of differences in date of movement was not normal (Fig. 3); 12 of the 16 elk had a positive difference for date of movement. If movements were random, then there would be an equal number of positive and neg~tive differences. There was a greater count of positive differences than expected if date of movement was random with respect to treabnent (p = 0.038). Overall Analyses on Proportion of elk on Refuge Akaike's Information Criteria (AIC) was used to choose a model to predict the proportion of elk on refuge areas from a combination oftreabnent, area, year, and date effects (Fig. 4A, B). All models accounted for the repeated measurements taken on individual elk between treabnents. For the lowest AIC model, the logistic regression parameters for treabnent (P = 0.032), area (P < 0.001), year (P < 0.001), date (P < 0.001), and area x date (P < 0.00 I) were significantly different from z.ero. When these factors were controlled for there was a treabnent x date (P < 0.082) effect (Table 6). The borderline treabnent x date effect indicated that the slope, or rate of change in proportion of elk on refuge areas, was different for the 2 treabnent areas (Fig. 5). The significance of the area~ date parameter indicates that the slope, or rate of change in proportion of elk on refuge areas, was greater for elk on the north side (late-early sequence) compared to elk on the south side (early-late sequence; Fig. 6). Elk on the north area showed a greater response in proportion of elk on refuge area by treabnent compared to elk on the south area (Fig. 7A, B). The fitted proportion of elk on refuge for each area x year category and the corresponding predicted proportion of elk on refuge for the opposite treabnent was calculated to evaluate the effect of changing archery season opening date (Fig 8A, B, C,D). �216 Figure 3. Distribution of differences in date of movement between late and early treatments for elk experiencing both treatments; White River elk herd 1996 and 1997. ntlQUDiCT 7 6 4 3 2 1 -35 -25 -15 -5 5 15 Di t f•r•nce aovea•nt d.a.t• 25 35 (Late-early) Figure 4. Proportion of elk on refuge areas with respect to archery-season opening date, on early- and lateopening treatments for 1996 (A) and 1997 (B); White River elk herd. 1996 A Q) - 0.9 O> :::, 0.8 Q) L. C 0 ~ 0.7 0.6 Q) 0.5 0 0.4 ... , ,. ... C 0 :.::; 0L. 0.2 0L. 0.1 a. Cl.. Late treatment North side 0.0 (D 0) io ..r-- -- ~ N C:! r-- (D e? 0) C:! r-- ~ !Q a:) ~ (D ~ (D 0) (D ~ (D 0) (D 0) (D 0) -- t; ..... C:! ~ -- ..... ----' date: Early opening date: Late opening N ..... CD e? 0) (0 CD CD Aug24 O> e? 0) O> (0 O> Sept 14 C'5 C:! O> 0 (') O> 0 �217 Figure 4. (Continued) 1997 B Cl) 0.9 - . - - - - - - - - - - - - - - - - - - - - - - - - - , g> 0.8 e 0.1 ~ oC 0.6 ~ "a; 0.5 O C 0.4 j 0.3 [ 0.2 0 (l'. 0.1 ... ... ,, ,, 'Early treatment North side 0.0 +---r-,........,,.......,.---,---,---,--,--.-it-r--.,....-..--,........,--,--t,---,---,---,-~-,--....-....--1 i ~ .... ~ ~ ~.... Si....;::: co co ~ .... ~ ~ .... e.... 55 Early opening date: Aug23 .... I .... ~ .... a; .... ..,~ e.... ~ c3 .... I.... Late opening date: Sept 13 Table 6. Parameter estimates for logistic regression model used to predict the proportion of elk on refuge areas; White River elk herd 1996 and 1997. INTERCEPT SEQUENCE TREAT JULDAY YR JULDAY*TREAT -7.2244 4.2030 1.2382 0.0305 -0.2395 -0.0041 0.5082 0.5757 0.5684 0.0021 0.0606 0.0023 0.0001 0.0001 0.0323 0.0001 0.0001 0.0821 �218 Figure 5. Treatment r date effect for elk on early- and late-opening treatments 1996 and 1997; White River elk herd. Treatment Effect Q) C) .2 ! C 0 ~ Q) '5 C 0 :e0 a. e a. 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 •• • •• Early opening ~ • • • ••• • • I • • • • • • • • • . • • ~ • • • • • • • • • ••• Late opening • Early opening Late opening ■ 7/8 7/22 8/5 8/19 9/2 Date 9/16 9/30 10/14 Figure 6. Area x date effect for elk given the early-late or the late-early treatment sequence during 1996 and 1997; White River elk herd. Area Effect Q) C) :::, ! C 0 ~ Q) 0 C 0 :e0 a. e a. 0.9 0.8 early-late treatment 0.7 0.6 0.5 0.4 0.3 • •• • •• South side elk • • • • • • 0.2 0.1 0 ■. late-early treatment 7/8 7/22 8/5 8/19 9/2 Date ■ • South-side elk • North-side elk 9/16 9/30 10/14 �219 Figure 7. Fitted curves of proportion of elk on refuge areas by treatment from logistic regression analysis for elk on the north area (A) and elk on the south area (B); White River elk herd 1996 and 1997. (A) North Area: Elk movement to refuge by treatment 0.9 a, C> 0.8 .2 0.7 C 0.6 e 0 -a; ~ - 0.5 0 0.4 :e0 0.3 e 0.2 C 0 C. a. -North ear1y opening -fitted cutve 0.1 - North late opening - fitted cuive 0.0 7/8 7/28 9/6. 8/17 9/26 10/16 Date (B) South Area: Elk movement to refuge by treatment 0.9 a, C> 0.8 .2 0.7 C 0.6 ! ~- 0 ~ - 0.5 :e0 0.3 e 0.2 a, 0 C 0 C. a. ~ 0.4 -South ear1y opening- fitted cuive 0.1 - South late opening - fitted cutve 0.0 7/8 7/28 9/6 ,. 8/17 Date 9/26 10/16 �220 Figure 8. Fitted curves and predicted curves for reversed treatments, early treatment on south area 1996 (A), late treatment on north area 1996 (B), early treatment on north area 1997 (C), and late treatment on south area 1997 (D); White River elk herd. (A) (C) South Side - early treatmert 1996 North Side - early treatmert 1997 0.9 0.9 ., 0.8 a, 0.8 ,2 0.7 §, 0.7 C 0.6 l! 0.6 .>t! 0.5 .>t! I!! 0 .; 0 15 0.5 0.4 a; '5 0.4 .Q t: 0.3 -~ 0.3 e 0.2 C 8. n. J l===~I 0.1 0.0 718 7/28 8117 9/6 9/26 0.2 1-Filled early - Predicted late 0.1 0.0 718 10/16 7/28 8/17 Date C 0 .>t! ., 0.8 0.7 ,2 0.6 C 1-Filled late I a, I!! 0 0.7 0.6 .>t! 0.5 0 C 0.4 .Q t: 0.3 8. 0.9 0.8 .; e n. 10/16 South Side - late treatment 1997 0.9 I!! 9/26 (D) North Side - late treatment 1996 ,2 9/6 Date (B) .,a, I .; 0 C .Q t: 8. 0.2 e n. -Fitted late 0.1 - Predicted earty 0.0 0.5 0.4 0.3 0.2 0.1 - Predicted ea~y 0.0 718 7/28 8117 9/6 9/26 Date 10/16 718 7128 8/17 9/6 9/26 10/16 Date DISCUSSION AND FUTURE WORK Although all elk were captured on national forest land, some elk moved to private land early in the summer before the ±1 month time frame used for within-half analyses, and some elk were never located on public land during the 1997 flights. "Manageable" elk are the proportion of the herd on public land within a month of early-season opening date. "Unmanageable" elk are the proportion of the herd not on public land within a month of early-season opening date and are, therefore, not likely to be affected by changes in hunting patterns on public land. In determining effects of archery hunting activity on elk movement, two types of effects were examined; the effects on manageable elk, and the effects on total herd (manageable plus unmanageable elk). Between 39-64% of the manageable elk moved to private land within a month of archery-season opening date. For the manageable elk, confidence intervals on mean date of movement included opening date in 3 of 4 cases, and movements of elk between refuge and non-refuge areas was not independent of opening date in 3 of 4 cases. North-side elk experiencing the late-opening treatment were the exception in the tests, possibly due to several early movers that attenuated the treatment effect. In general, it appears that early season hunting activity has an effect on the manageable elk. �221 The effects of the manipulation of archery-season opening date on elk movements on the entire herd was evaluated by responses in mean date of movement and proportion of elk on refuge. The strongest test is the crossover analysis because it controls for external sources of variation when testing for treatment effects. The lack of a treatment effect in the crossover analysis is evidence that early-season hunting is not affecting the timing of elk movements from refuge to non-refuge areas. However, because there appeared to be interactions between treatment x area and treatment x year, post hoc analyses were done which reveled several pieces of evidence indicating that early-season hunting activity altered elk movements: (I) mean date of movement was different between treatments for elk on the north area, (2) mean date of movement was different between treatments for 1997, (3) for elk getting late and early treatments, there was a 6 day difference in late minus early date of movement, and (4) there was a significantly greater count of positive late minus early date of movement differences than expected if date of movement was random with respect to treatment. Also, from the logistic regression analysis of proportion of elk on refuge, the rate at which elk move from public land to private land refuge areas was borderline different for early- and late-opening treatments. Part of the ambiguity in evaluating the effects of archery hunting on elk movements may result from differences in movement patterns of elk on the north side versus elk on the south side of the study area. The steeper slope, or faster gain in proportion of elk on refuge areas over time for the north-side elk (Fig. 6) suggests that north-side elk move to private land more readily than south-side elk. This was surprising as south-side elk, which experienced the early-opening treatment the first year, were expected to move more readily the second year. Similarly, north-side elk, which experienced the late-opening treatment the first year would be taken by surprise by an early opening the second year, and were expected to move less readily. In addition to moving more readily, elk on the north area were more responsive to changes in opening of archery season. The timing of the movements of north-side elk was affected by archery season opening date, as indicated by the significant difference in mean date of movement betw~n treatments. South-side elk did not have as wide a spread in their mean date of movement between treatments and there was not a significant difference in mean date of movement between treatments. Also, the proportion of elk on refuge was greater during the early treatment compared to the late treatment for elk on the north area (Fig. 7A). For elk on the south area, the proportion of elk on refuges was similar for early and late treatments (Fig. 7B). It may be that the north-side elk move more readily due to the presence of a large private-land refuge adjacent to national forest land. Between 39-64% of the manageable elk moved to private land within a month of early-season opening date. However, the elk that moved represent 31-41 % of the entire herd. Hence, any management decisions regarding hunter numbers are likely to affect at most 41 %, and possibly less, of the White River elk. The question remains as to what percentage of the manageable elk would still move if hunting were reduced or eliminated. These results are not complete; I still need to analyre 1997 hunter survey data, test for elk avoidance of livestock, and calculate daily distances moved and elevational shifts with respect to early-season hunting activity. Additionally, I need to reclassify refuge areas; there needs to be a third land classification for habitat refuges. Habitat refuges will be defined as topographically steep areas where changes in elevation per linear distance are greater than some threshold (to be determined). Elk locations will be reclassified as public, private, or habitat refuge, and reanalyred in a multinomial model. Although it appears that north-side elk move more readily than south-side elk, results may change when habitat refuge areas are included in analyses. South-side elk may not need to move to private land because they move into habitat refuges. It may be that elk with available habitat refuges are of little management concern with respect to private-land problems. These results will be incorporated and discussed in my dissertation. ��223 APPENDIX A Methods METHODS The study area was split roughly east-west by the White River and North Fork of the White River into 2 halves for application of early- or late-opening treatments during 1996 and 1997. Game Management Unit (GMU) 12 and part of GMUs 23 and 24 comprised the north half, while GMU 33 and part of GMUs 23 and 24 comprised the south half. There was a 3-week difference in opening dates; archery hunting opened early, August 24th, on the south half, and late, September 14th, on the north half during 1996. Treatments were reversed in 1997; archery hunting opened late, September 13th on the north half, and early, August 23 rd , on the south half. Although data were collected on each elk from July 15 - October 13 for both years, withintreatment analyses were restricted to locations collected within a month of opening date (i.e. July 23 September 24 for early-opening treatment, and August 13 - October 13 for the late-opening treatment). The ±I-month interval allows evaluation of treatment effect on manageable elk and allowed for comparison to pilot study results. All other analyses were done over the 3-month study period for valid comparison of between-treatments effects on the entire herd (manageable plus unmanageable elk). The primary response variables were mean date of movement and proportion of elk that change classification (non-refuge ->refuge/ public ->private). All locations were labeled as either refuge or nonrefuge based on land ownership or management, and not on topographical considerations. That is, the Flat Tops Wilderness Area and all private land were labeled as refuge, while all National Forest, State Wildlife, and BLM lands were labeled as non-refuge. Area x Year Analyses This is a geographically nested design. with 2 levels of analysis. One level of analysis is within half, where the treatment is location on non-refuge or refuge areas. The time frame for within treatment analyses is ±1 month of opening date. The ±1 month interval allows evaluation of treatment effect on manageable elk. If hunting has no effect on elk movements, then elk movements from hunted non-refuge areas should not correlate with opening date. The primary hypothesis tested were: 1. Ho: Mean date of movement from non-refuge to refuge areas = opening date. Ha: Mean date of movement from non-refuge to refuge areas * opening date. 2. Ho: Location of elk on non-refuge and refuge areas was independent of the opening of archery hunting. Ha: Location of elk on non-refuge and refuge areas was not independent of the opening of archery hunting. These were the same hypotheses tested for the 1992,..1995 pilot study data; they were tested separately for both north and south halves of the study area. Differences in time of movement were tested with a one sample t-test. •Hypothesis 2 evaluated the effect archery hunting had on elk movements by testing whether changes in classifications (refuge->refuge, refuge->non-refuge, non-refuge->refuge, and non-refuge->nonrefuge) were independent of the presence of archery hunting. If archery hunting had no effect, then there should be no difference in elk locations before or after the opening of archery season. A chi-square test was used to evaluate if movement of elk between non-refuge and refuge areas was independent of being before or after opening date. �224 Overall Analyses on Mean Date of Movement The experimental unit is north or south half of the study area, the sampling unit is individual elk, and the treatment is early or late opening of archery season in this 2-period crossover design. The time frame for all overall analyses is the 3-month study period of July 15th -October 15th; the 3-month interval allows valid comparison between treatments for the entire herd (manageable and unmanageable elk). The crossover analysis used data from both years of the study to test the effects of early-season hunting on the mean date of elk movement from non-refuge to refuge areas (see methods: Elk movements in response to early-season hunting in the White River area: study plan). If hunting had no effect on elk movements, then there should be no difference between the mean date of movement to refuge areas between treatments. To test for a treatment effect on mean date of movement, the area (sequence) in which the treatments were applied,-the year, and the random effect of the individual sample elk must be accounted for. The corresponding analysis of variance model is: YiJ1d = µ + O.t + "1(1c) + (X; + A + &i11d, where: yij1d µ = date of movement for the fl' elk, in area k, treatment i, and year j = overall mean date of movement (for all elk, both years) bi = fixed effects due to area k (either north or south) = random effects due individual elk / in area k = fixed effects due to treatment i (early or late opening) = fixed effects due to year j (year I or year 2). tri(k) a; /3j Specific questions tested in the crossover ANOVA model were: 1. Mean date of movement for north-side elk (early-late treatment sequence)= mean date of movement for south-side elk (late-early treatment sequence), Ok= 0. 2. Elk randomly chosen from the south side (early-late sequence) were the same as elk randomly chosen from the north side (late-early sequence); 7rJ(k)-= 0. 3. Mean date of elk movement for early- opening treatment = mean date of elk movement for late opening treatment; a; = 0. 4. Mean date of elk movement of elk for year I of experiment= mean date of elk movement of elk for year 2; Pj = 0. Hypothesis 3 is the experimental hypothesis; hypotheses 1, 2, and 4 are needed to account for other sources of variation. Overall Analyses on Proportion of elk on Refuge The logistic regression model used in 1996 to test for treatment and date effects on the proportion of elk located on refuge areas (p): logit(p) =Po + P1(date)+ P2 (treatment)+ P3 (treatmentx.date) + e, was expanded to include area and year effects. Various combinations of treatment, area, year, and date were modeled. Akaike's Information Criterion (AIC) was used to select the best model given the precision and bias tradeoff. The DSCALE option was used in this analysis to account for the repeated measures on the individual elk and allow for inference to the entire herd. The model with the lowest AIC was: logit(p) = Po + P1 (area)+ P2 (year)+ p 3 (date)+ P4 (treatmemt) + Ps (treatment xdate) + P6 (areaxdate) + e. �225 From this model the following hypotheses were tested: 1: 2: 3: 4: 5: 6: Proportion of elk on refuges was independent of the area, given date, treatment, and year differences were controlled for; p, = 0. Proportion of elk on refuge areas was independent of year, given date, treatment, and area differences were controlled for; P2 = 0. Proportion of elk on refuge areas was independent of date, given area, year, and treatment differences were controlled for; P1 = 0. Proportion of elk on refuge areas was independent of treatment, given area, year, and date · differences were controlled for; p,;= 0. Early and late treatment had the same slope, that is, elk moved from non-refuge to refuge areas at the same rate on early- and late-treatment areas; PJ= 0. The south and north side had the same slope, that is, elk moved to refuge areas at the same rate whether they were on the south side (early-late treatment sequence) or on the north side (late-early treatment sequence); p6= 0. Hypotheses 5 is the experimental hypotheses. Hypothesis 5 was a test of proportion on refuge and timing of movement to refuge; that is, if archery hunting had no effect, then elk would be expected to move to refuge areas at the same rate for early- or late-opening treatments. A likelihood ratio test of the area x date effect (/J,) was an overall test of archery effects, given that elk would move the same on the 2 areas otherwise. Hypotheses 1-4 allow for accounting of additional sources of variation. Hypothesis 6 tested whether the rate of movement to refuge areas was different by area. This test was more biologically interesting than testing for a difference in the proportion of elk on refuge between areas. For example, a difference between areas may only indicate that more elk happened to begin on refuge areas on the north or south side, which is irrelevant to archery hunting activity. However, if elk on the south side receiving the early-treatment the first year were more wary the second year, then the south side elk should show a greater rate of movement than the north side (late-early sequence) elk. This effect was tested by the inclusion of the area x date interaction term in the logistic model. ��191 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB FINAL REPORT State of _ _ _ _--=C...,o=lo=r=ad=o,.___ _ _ __ Project No. ------=-W_,__-..:;.1=53=--=R=--=-=12=-----Work Package _~3-0~02~-----Task No. 2 ------'------------- Cost Center 3430 Mammals Research Elk Conservation Elk Movements in Response to Early-season Hunting in the White River Area • Period Covered: July 1, 1998 - June 30, 1999 Author: M. M. Conner Personnel: G. White, D. Freddy, R Kahn, J. Maddison, J. Ellenberger ABSTRACT Understanding causes of elk movement to private land is important to wildlife managers who use hunting on public land as a population management tool. In the White River area of northwest Colorado, late-summer elk movements onto private lands made it difficult to harvest enough elk to maintain specified population levels. I conducted a 2-year field experiment to determine if early-season hunting (archery and muzzleloading) caused elk movement to private land during late summer. The study area was split into north and south treatment areas: each area received both an early- and lateopening treatment. Early-opening treatment was archery season that opened 1 week earlier than the historical opening, and late-opening treatment was an archery season that opened 2 weeks later, yielding a 23-week difference in opening dates. The 80-88 adult female elk used in this study were captured from random locations throughout the study area I relocated radiocollared elk approximately 2 times per week for a 3-month period surrounding early- and late-opening dates each year. Using a Geographical Information System (GIS) generated map, I classified each elk location as being on public or private land. Elk receiving the late-opening treatment moved 10 days later than elk receiving the early treatment (P = 0.013, one sided ANOVA). Because there appeared to be an interaction between area and treatment, I performed a post hoc analysis separately by area In the north area, elk receiving the late-opening treatment moved 14 days later than elk receiving the early treatment (P + 0.006), one sided t-test), compared to a 6-day difference for elk in the south area (P = 0.218). Approximately twice as many radiocollared elk moved to private land on the north area (44%) compared to the south area (23%). The experimental effect on the number of elk directly influenced by early-season hunting can be estimated by the abrupt increase in the proportion of elk moving to private land when hunting opened. Proportion of elk on private land increased 8-18% at the opening of early season. The greater response of elk to hunter activity on the north area may be due to topographical and migration differences between areas. The south area had densely forested canyons and cliffs, inaccessible to motor vehicles, which provided elk good refuge from hunters on public land. In �192 contrast, the north area offered less shelter on public land, but had refuge in large private-land tracts that bordered the area During the study period, elk moving to private land in the north were just beginning their fall migration, whereas elk in the south area were completing their migration by moving to private land. Elk on the north area that move onto private land do not risk depleting their winter forage, while elk on the south area may degrade their winter range by grazing an extra couple of months on their wintering grounds. Colorado Division of Wildlife.surveyed 34% and 37% of hunters using the study area during a post-hunt telephone survey in 1996 and 1997 to estimate the number of hunters afield per day with a maximum 95% CI of ±150 hunters. Daily use varied between 115-1,130 hunters per treatment area, with corresponding hunter densities of0.006-0.51 hunters/km2. The proportion of elk on private land was not strongly affected by hunter density. • Domestic sheep were accused of causing elk movements to private land during early-season hunting. I collected a location for at least one band of sheep per flight. From this data, I used nonparametric statistics and bootstrapping techniques to calculate the probability that elk avoided sheep at 3 spatial scales. Locations of elk were random with respect to sheep when all elk were used in analyses (P > 0.342), and when only elk within 1 km of a sheep band were used (P > 0.912). Although elk may avoid sheep at <l km, it is unlikely that they avoid sheep at large enou.gh distances to cause widespread elk movements to private land. Although early-season opening may not be the sole cause of elk movements to private land, the experimental results show that early-season hunting caused some elk to move to private land, especially on the north area The increase of elk on private land directly attributable_ to opening of hunting was 8-18%. Hence, the CDOW can reduce, at most, approximately 20% of elk movement to private land by manipulating early-season hunting. However, if elk movements are concentrated in problem areas, then manipulation of opening date may result in a proportionally higher reduction of elk movements in those areas. Managers concerned with reducing elk movement to private land should consider the public and private land refuges available to elk, as well as historical elk migration patterns. �193 ELK MOVEMENT IN RESPONSE TO EARLY-SEASON HUNTING IN THE WHITE RIVER AREA Mary M. Conner P. N. OBJECTIVES I. Test whether early-season hunting causes movement of elk from areas of heavy hunting pressure to areas of lower hunting pressure. SEGMENT NARRATIVES I. Estimate the mean date of movement of elk from non-refuge areas, and determine whether the timing is equivalent to the opening of archery season. 2. Evaluate alternative hypotheses about causes of elk movement such as livestock grazing, woodcutting, recreationalists, weather or forage quality. •• 3. Publish analyses of elk movement in response to archery hunting in peer-reviewed scientific journals. INTRODUCTION Following is the most recent available draft of the Ph.D. Thesis summarizing results of research activities directed toward accomplishment of Program Narrative and Segment Narrative Objectives. ��195 DISSERTATION ELK MOVEMENT IN RESPONSE TO EARLY-SEASON HUNTING IN THE WHITE RIVER AREA, COLORADO Submitted by Mary M. Conner Department of Fishery and Wildlife Biology In partial fulfillment of the requirements for the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Fall 1999 �196 COLORADO STAIB UNIVERSITY June 28, 1999 WE HEREBY RECOMMEND THAT THE DISSERTATION PREPARED UNDER OUR SUPERVISION BY MARY M. CONNER ENTITLED ELK MOVEMENTS IN RESPONSE TO EARLY-SEASON HUNTING IN THE WHITE RIVER AREA BE ACCEPIBD AS FULFILLING IN PART REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHIT.,OSOPHY. Committee on Graduate Work Advisor Department Head �197 ABSTRACT OF DISSERTATION ELK MOVEMENT IN RESPONSE TO EARLY-SEASON HUNTING IN THE WHITE RIVER AREA, COLORADO Understanding causes of elk movement to private land is important to wildlife managers who use hunting on public land as a population management tool. During the 1980s, late-summer elk movements onto private land in the White River area of northwest Colorado made it difficult to harvest enough elk to maintain specified population levels. I conducted a 2-year field experiment to determine if early-season hunting (archery and muzzleloading) caused elk movement to private land during late summer. The study area was split into north and south treatment areas; each area received both an early- and late-opening treatment. Early-opening treatment was an archery season that opened 1 week earlier than the historical opening, and late-opening treatment was an archery season that opened 2 weeks later, yielding a 3-week difference in opening dates. The 80-88 adult female elk used in this study were captured from random locations throughout the study area. I relocated radiocollared elk approximately 2 times per week for a 3-month period surrounding early- and late-opening dates each year. Using a Geographical Information System (GIS) generated map, I classified each elk location as being on public or private land. Elk receiving the late-opening treatment moved 10 days later than elk receiving the early treatment (P = 0.013, one-sided ANOVA). Because elk on the north area appeared to respond differently to treatment than elk on the south area, I performed a post hoc analysis separately by area. In the north area, elk receiving the lateopening treatment moved 14 days later than elk receiving the early treatment (P = 0.006, one-sided I-test), compared to a 6-day difference for elk in the south area (P = 0.218). Approximately twice as many radiocollared elk moved to private land on the north area (44%) compared to the south area (23%). The experimental effect on the number of elk directly influenced by early-season hunting can be estimated by the abrupt increase in the proportion of elk moving to private land when hunting opened. Proportion of elk on private land increased 8-18% at the opening of early season. The greater response of elk to hunter activity on the north area may be due to topographical and migration differences between areas. The south area had densely forested canyons and cliffs, inaccessible to motor vehicles, which provided elk good refuge from hunters on public land. In contrast, the north area offered less shelter on public land, but had refuge in large private-land tracts that bordered the area. During the study period, elk moving to private land in the north area were just beginning their fall migration, whereas elk in the south area were completing their migration by moving to private land. Elk on the north area that move onto private land do not risk depleting their winter forage, while elk on the south area may degrade their winter range by grazing an extra couple months on their wintering grounds. Colorado Division of Wildlife surveyed 34% and 37% of early-season hunters using the study area during a post-hunt telephone survey in 1996 and 1997. The goal was to survey enough hunters to estimate, during the study period, the number of hunters afield per day with a maximum width 95% CI of ±150 hunters. Daily use varied between 115-1, 130 hunters per treatment area, with corresponding hunter densities of 0.06-0.51 hunters/km2• The proportion of elk on private land was not affected by hunter density. Elk in the White River area responded more to the opening of hunting season than to hunter density. It may be that hunter density must surpass or drop below a threshold before elk begin to respond directly to hunters, and hunter densities did not cross any threshold during the study. If hunter density continues to be a suspected cause of increased elk movement to private land, then an experiment manipulating hunter density should be conducted. Domestic sheep also were considered to cause elk movements to pmrate land ,dwing early-season hunting. I collected a location for at least one band of sheep per flight. From these data, I used non-parametric statistics and randomization techniques to calculate the probability that elk avoided sheep at 3 spatial scales. Locations of elk were random with respect to sheep when all elk were used in analyses (P= 0.737 in 1996, P = 0.199 in 1997), when only elk within 5 km of a sheep band were used (P = 0.342 in 1996, P = 0.990 in 1997), and when only elk within I km ofa sheep band were used (P> 0.969 in 1996, P= 0.912 in 1997). Although elk may avoid sheep at �198 < I km, it is unlikely that they avoid sheep at large enough distances to cause widespread elk movements to private land. Although early-season opening may not be the sole cause of elk movements to private land, the experimental results show that early-season hunting caused some elk to move to private land, especially on the north area. The direct effect of hunting season is reflected in the 8-18% increase in proportion of elk on private land that occurred on opening day. Hence, in the White River area, the CDOW can reduce, at most, approximately 20% of elk movement to private land by manipulating early-season hunting. However, if elk movements are concentrated in problem areas, then manipulation of opening date may result in a proportionally higher reduction of elk movements in those areas. The elk not affected by opening of hunting season may be elk for which private land is enroute to their wintering area. Late summer movement onto private land may have become part of a learned migration behavior, changing hunt season opening and/or hunter density may have little effect on these elk. Future experiments and management actions should consider an early hunting season on private land, where problems occur, to retain elk on public land during late summer. Mazy M. Conner Department of Fishery and Wildlife Biology Colorado State University Fort Collins, CO 80523 Fall 1999 �199 TABLE OF CONTENTS ABSTRACT OF DISSERTATION ........................................................ . ACKN"OWLEDGMENTS ............................................................... . INTRODUCTION ..................................................................... . ELK MOVEMENTS IN RESPONSE TO DISTURBANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elk Movement in Response to Human Activities , ........................................... . Elk Movement in Response to Hunting ................................................... . PROJECT OVERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LITERATURE CITED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FIGURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CHAPTER 1: ELK MOVEMENT IN RESPONSE TO EARLY-SEASON HUNTING IN NORTHWEST COLORADO ......................................................................... . INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . STUDY AREA ......................................................................... . METIIODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experimental design ................................................................. . Data collection .................................................. ;· .................. . Data analysis ...................................................................... . REsULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MANAGEMENT IMPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LITERATURE CITED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CHAPTER 2: EFFECT OF HUNTER DENSITY ON ELK MOVEMENT TO PRIVATE LAND IN NORTHWEST COLORADO ............................................................ . INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . STUDY AREA ......................................................................... . METIIODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radio-telemetry Data Collection ........................................................ . Hunter Survey Data Collection ......................................................... . Estimating Number ofHunters ......................................................... . Estimating Number ofHunters Afield per Day . ............................................. . Estimating Mean Number ofDays per Hunter and Hunter-days ................................ . Elk Movement versus Hunter Density .................................................... . RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hunter Survey Data .................................................................. . Elk Movement versus Hunter Density .................................................... . DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MANAGEMENT IMPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LITERATURE CITED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,. CHAPTER 3: ELK LOCATIONS IN RELATION TO DOMESTIC SHEEP BANDS AND A METHOD TO TESTFORAVOIDANCE OR ATTRACTION BETWEEN ANIMALS ........................... . INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . STUDY AREA ......................................................................... . METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data Collection ..................................................................... . Data Analysis ...................................................................... . �200 RESULTS DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experimental Results ................................................................. . Methodology for Determining Attraction and Avoidance ...................................... . MANAGEMENT IMPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LITERATURE CITED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . APPENDIX 1: SAMPLE SIZE CALCULATION FOR HUNTER SURVEY ....................... . APPENDIX 2: STANDARD ERRORS FOR DAILY GMUESTIMATES OF HUNTERS AND ATVS AFIELD APPENDIX 3: MAPS OF ELK AND DOMESTIC SHEEP LOCATIONS ON SELECTED FLIGHTS ... ACKNOWLEDGMENTS ri .:1: Funding was provided by Colorado Division of Wildlife (CDOW). Colorado Habitat Partners Program in the Northwest Region provided funding for flights to collect elk locations. I greatly appreciate the financial support. From the CDOW, I would like to extend a special thanks to Dave Freddy for his insightful elk discussions, reviews, and helping to procure financial support. A second special thanks to Dick Bartmann; without his help, organization, funding procurement, and common sense I would have struggled with all the logistics of collaring and tracking over 80 elk. Also from the CDOW, thanks to Jeff Madison for all his help with obtaining funding from Colorado Habitat Partners Program. My major professor, Dr. Gary White, has been quite an inspiration to me. What can I say, he is one of the smartest people I know and I have been lucky to study with such an adept thinker. My committee member, Dr. Ken Burnham, has always been a great help with statistical and mathematical issues that were difficult for me, and never missed a detail in my dissertation work. His help greatly improved my dissertation. Dr. Bill Alldredge always had the common elk-sense aspect and practical questions. Without him, I might have forgotten the most important issues about elk in their natural environment Finally, Dr. Bruce Wunder provided me with the interesting big picture questions that I would not have considered with out him. Thank you to all my committee; I enjoyed and benefitted from your input and help tremendously. The proximate reasons that I was able to complete this academic endeavor were excellent academic advising and a good funding source, but the ultimate reason is the relationships that have nourished me since • childhood. Primarily, my parents are the reason I have been able to start and complete my doctorate. My mother, who importuned me to ''finish what you begin", and my dear father, with his natural Buddhist nature, both allowed me and encouraged me to do whatever it is to which I set out. Additionally, their financial support during graduate school kept me out of the poorhouse and kept my car out of the junkyard. I must thank my sister, who rolled her eyes and told me to "get a grip" many times during my graduate studies. I then thank my extended family, the cast of characters to whom I am related. They make me laugh and somehow think that I could do anything if that's the stock from which I originate. To my long time friends who work hard, but certainly expect to vacation well, and have little tolerance of any stupid, wimpy PhD excuses, thank you. My friends M. Kiuchi, P. Kurz, M. Zimmer, E. Soderstrom, A. Peet, D. Yonenaka, N. Larsen, M. Riker, T. Howe, A. Bruno, and T. Weller deserve special acknowledgements. Of the mentors from my academic career, I would like to thank and acknowledge Sister Rita Basta, Dr. Mike Jaeger, Dr. Dale McCullough, and Dr. Wayne Getz. Wayne, a special thanks to you, although you will never know how much you inspired me. I would also like to thank and acknowledge the iny:riad of graduate students who have made my life bright and graduate school stimulating. Most importantly, infinite thanks to my dear husband, John Shivik. He has been a stalwart support, fellow adventurer, paper reviewer, research partner, coffeemaker, cocktail alchemist, bad joke teller, and all round husband extrodinaire. Thank you, thank you, thank you all. I hope you like what you've been so instrumental in producing -this one's for you. �201 INTRODUCTION ELK MOVEMENTS IN RESPONSE TO DISTURBANCE Migration between high-elevation summer range and low-elevation winter range is common among Rocky Mountain elk (Cervus e/aphus ne/soni) in mountainous regions (Adams 1982). High-elevation ranges provide high levels of nutrition during the summer, but snow makes forage inaccessible during the winter. Fall migrations typically take place before the snow becomes too deep for animals to forage. In the White River area of Colorado, elk migrate between summer range, located in high-elevation national forest and wilderness areas, and lowelevation wintering grounds, located as near as the base of the summer range or as far as 80 km away. Historically, fall elk migration took place in December (Boyd 1970), but since the 1980s, fall movements have apparently advanced into August and September (Gray et al. 1994). During the development of the 1994 elk management plan for the White River herd, early elk movement from summer ranges onto public land was the most common complaint (Gray et al. 1994). In response to complaints. Colorado Division of Wildlife (CDOW) conducted a pilot study on 20 radiocollared cow elk from 1992-1995 to determine if and when elk were moving onto private land. Results from the pilot study indicated a correlation between early-season hunting activity and elk movement to private lands. However, it did not establish a causal relationship. Before instituting any management changes, COOW needed an experiment to determine whether early-season hunting activity was causing latesummer elk movements. I designed and conducted such an experiment in 1996-1997, and that experiment is the topic of my dissertation. In this introduction, I present background material on elk responses to an array of human activities in general and to hunting in particular. I intend this background material to provide a framework for understanding my experiment to determine the cause oflate-summer elk movements in the White River area. Elk Movement in Response to Human Activities Elk responses to recreational activities such as hiking, cross-counl:Iy skiing, and automobile driving depend on habituation to humans and on the presence of hunting. In Rocky Mountain National Park, where elk were accustomed to people and were not hunted, elk showed little response to approaches of people in automobiles or on foot, day or night (Schultz and Bailey 1978). In a study of another unhunted elk population in Yellowstone National Park, elk response to cross-counl:Iy skiers depended on how accustomed elk were to people. In areas of low human activity during the winter, elk responded with flight distances of 125-1,700 m, while in an area of high human activity, the flight distance was considerably shorter, ranging from Oto 300 m (Cassirer et al. 1992). Interestingly, elk in the area of high human activity showed a three-fold increase in flight distance when they were disturbed outside the area where people were present 24 hours a day (Cassirer et al. 1992). Thus, even habituated elk appear to flee human activity in areas where they do not expect such activity. Besides habituating to humans, elk may learn to differentiate between dangerous and benign situations with respect to road avoidance. In Rocky Mountain National Park, where elk were not hunted and traffic volume was high, Schultz and Bailey (1978) found that none of their 14 delineated elk behaviors changed with traffic volume, and there was little or no avoidance of the roads in winter. In contrast, in Roosevelt National Forest, which is adjacent to Rocky Mountain National Park, Rost (1975) found that a population of hunted elk avoided roads in winter. Wright (1983) found that mean distance ofradiocollared elk to jeep trails more than doubled, increasing from 800 m to 2, I 00 m when hunting season opened. In addition to danger level, the level of road activity also affected elk movements. After roads were closed in an experimental treatment, Cole et al. (1997) found a reduction in daily movement, home range size, and core area, all measures of elk movement Czech (1991) found a significant increase in mean elk distances to a road after it was opened to the general public with a corresponding increase in traffic. Elk also cross heavily traveled roads less often than lightly traveled roads (Hershey and Legee 1982). A third factor, cover, may also determine the degree,of elk response to disturbance. Logging disturbances changed normal elk movements (Edge and Marcun'i 1985): elk moved significantly longer distances away from logging areas than toward them. But both distance from disturbances, and areas of high elk use, were correlated to the amount of cover in the area (Edge and Marcum 1985). Similarly, Czech (1991) found that elk tolerance of logging operations was correlated positively with proximity to hiding cover. In one of the few manipulative experiments on elk movements. elk calves subjected to simulated surface-mining activities sought coniferous forest significantly more often than undisturbed calves (Kuck et al. 1985). Oil drilling has the same effect as mining: elk increased their use of forested habitats during drilling and post-drilling periods, compared with pre-drilling periods (Van Dyke and Klein 1996). Collectively, these disturbance experiments build a strong case for a relationship between elk movement and availability of cover. �202 All studies that evaluated elk movements after the disturbance ended found displacement to be a temporary condition in most situations. The Yellowstone elk displaced by cross-country skiers typically returned close to their original locations after people left the area (Cassirer et al. 1992). Road proximity resumed pre-hunting distances after hunting season closed (Wright 1983), and mean distance to roads decreased soon after the roads were closed for the season (Hershey and Legee 1982). During weekends, and immediately following the end oflogging activities, elk moved back into logged areas (Ward 1976, Edge and Marcum 1985). ;;a, Elk Movement in Response to Hunting Documented responses of elk to hunting include movement away from hunters or heavily hunted areas, increased movement, movement to thick cover, shifts in circadian patterns, and elevation shifts. Most responses seem to occur before winter migration, but some studies attribute changes in migration patterns to hunting pressures. For example, Knight (1970) and Morgantini and Hudson (1979) found a reversal of the normal downward autumn migration of elk, coinciding with the opening of the hunting season. Responses of elk to hunting activity may depend on the amount, location and quality of hiding cover, as well as the topography of the area. Altmann (1956) described an evasive "migration" of elk hunted adjacent to Yellowstone National Park. With the opening of hunting season, movements of these elk became relatively long (513 km), and the elk ceased long movements only when they reached the sanctuary of the Park. Similarly, Martinka ( 1969) found that 12 marked elk, which were in the National Elk Refuge just prior to hunting season, moved between 8 and 22 Ian, to areas closed to hunting in Grand Teton National Park. Other studies have found lessdramatic movement to refuge areas. With opening of hunting season, elk moved to densely forested (Irwin and Peek 1979) or shrubby (Morgantini and Hudson 1979) areas adjacent to their typical areas of activity, which provided refuge from hunting. Unpublished data for 1992-1995 from a pilot study on elk in the White River area (M. M. Conner, Colorado State University, unpublished data) found that distance moved around opening date(± 1 week from opening date) differed depending on habitat cover in the vicinity. Elk located in rugged and relatively inaccessible areas with access to thick timber and rough terrain (n = 11) moved an average of858 m/day (95% CI= 602, 1113). In contrast, elk located in road-accessible areas (n = 15), with little access to vegetative and topographic cover, moved an average of 1258 m/day (95% CI= 1011, 1505) to refuge on private land. Thus, elk without access to nearby habitat refuges moved significantly farther (401 m/day: 95% CI= 45, 756) than elk with access (P = 0.014, I-sided). Areas of rough topography and dense timber may serve as refuge; if such refuge is available, elk may not move far even when subject to high hunting pressure. Elk may respond to hunting method or density of hunters. Wright (1983) examined elk response to different hunting seasons: archery and muzzleloading, rifle-special elk, rifle-special deer, and deer and elk rifle. The greatest density of elk hunters was during the rifle-special elk season, and distances traveled by elk were also greatest during that season. Elk traveled three to four times farther during this season than during archery and muzzleloading season. Wright (1983) concluded that archery and muzzleloading hunters did not change the behavior of radiocollared cow elk. However, this result might be explained by low hunter densities (0.13 archery and muzzleloading hunters/km2, compared to 1.42 rifle hunterslkm2) rather than by the hunting method. In a 1985 study in the White River area, Consolidation Coal Company radiocollared 23 elk to evaluate their movement onto the company's protected land during early-season hunting. Eighty-seven percent of the elk were still found on National Forest lands midway through archery and muzzleloading seasons (Camp Dresser and McKee, Inc. 1986). But the lack of movement may be explained by a 63% reduction in archery hunters from 1984 to 1985, due to a change in hunting regulations (Gray et al. 1994). z.abn (1974), Lemke (1975), and Hershey and Legee (1982) noticed an increase in movements during the first 10-12 days of hunting season, followed by normal movement during the remainder of the season. These authors noted that hunting pressure was heavy during the first 10-12 days of hunting and relatively light for the remainder of the season. These studies of hunting suggest that elk behavior may change only when the density of hunters reaches a critical threshold. While some elk appear to have learned to move to refuge areas, elk already in refuges may learn to remain there in response to hunting pressure. In Jackson Hole, both resident and migratory elk use the National Elk Refuge for their winter range (Martinka 1969). Of the 183 marked elk in the study, resident elk were defined as elk found at any time from July through August within 15 km of the winter range, while migratory elk were defined as all other elk. In the fall, both resident and migratory elk had to cross hunting areas to move to their winter range in the National Elk Refuge. Resident elk were sensitive to hunter presence and tended to hang back in areas closed to hunting, while migratory elk were less hesitant to move through hunting areas to the winter range. These studies of elk moving to, or staying in, refuge areas support the theory that elk are responding, possibly with learned behavior, to hunting pressure. �203 Other studies found evidence to indicate that elk are not responding to hunting pressure, but are being differentially removed from heavily hunted areas. In Wyoming, hunting pressure focused on a resident population of elk just east of Yellowstone National Park, drastically reducing their numbers (Rudd et al. 1983 ). Like the Jackson Hole herd, migratory elk that summered in protected areas of Yellowstone National Park wintered with resident elk in unprotected range just outside of the park. Hunting in the unprotected range occurred before the migratory elk arrived from the park, drastically reducing the herd of resident elk (Rudd et al. 1983). The proportion of migratory to resident elk increased in the unprotected range, apparently due to hunting itself and not to huntinginduced shifts in elk behavior. Boyce (1991) noted that migration of elk wintering in the National Elk Preseive in Jackson Hole changed dramatically between the 1950s and 1980s. The primary migration routes shifted from openhunting national forest lands to routes through Grand Teton National Park, where hunting was more restricted. Between 1950 and 1954, 22% of the migrating elk were estimated to have moved through Grand Teton National Parle; by 1980-1984 the figure was 51%. Boyce (1991) hypothesized that this change maybe due to differential haIVest of the migrating animals and not due to shifts in elk behavior. However, there has been no experiment to test whether the cause of migration changes is differential removal or learned response. Similar to results from non-lethal disturbance studies, z.ahn (1974), Lemke (1975), and Hershey and Legee (1982) found that elk response to hunter disturbance was short-lived. These studies noted that elk movements return to normal after the initial 10-12 days of opening day, and that hunting is most intense during those initial days. Elk not only discontinued their erratic and increased movements, but also returned to their pre-season activity areas, indicating that hunting activity was a temporary disturbance. In conclusion, elk show highly plastic responses to human activity, habituating to people in areas where there is no hunting, but actively avoiding hunters. Elk response to human activity depends on the amount of, and the danger of, contact with humans. For example, avoidance of roads varies with the amount of human use and the danger level. The presence of dense cover for hiding seems to attenuate responses to human activity. Finally, elk responses to human activity do not seem to persist after the activity subsides. All studies of elk responses to hunting have been obseivational and any causal relationship between hunting and elk movements remains untested. PROJECT OVERVIEW Game Management Units (GMUs) 12, 23, 24, and 33 in northwestern Colorado compose the majority of the area of the White River elk herd. The White River herd has been one of the most heavily hunted, managed, and documented elk herds in Colorado (Boyd 1970, Freddy 1987, Gray et al. 1994). Like all elk herds in Colorado, the White River herd was decimated during the late 1800s, eventually being reduced to a few hundred elk (Bryant and Maser 1982). Since regulated hunting began in 1929, the population has been growing and was estimated to be 31,000 in 1993, the upper bound for COOW management objectives (Gray et al. 1994). The number of hunters using the area has grown along with the elk herd, with especially significant increases in the number of early-season hunters (archery and muzzleloading) between 1984 and 1992 (Fig. I.I). In the White River area, summer range is high-elevation public forest, and winter range is lower-elevation private land. Historically, the main White River elk migration from summer to winter ranges took place between late November and early January (Boyd 1970). However, Freddy (1987) noted that elk were beginning to be found in lower elevations, characteristically winter range, during the September and October hunting seasons, which was uncommon in the 1960s. Furthermore, there is now evidence that elk are moving in August and early September, during early-season archery hunting (Gray et al. 1994). Typically, early-season hunters did not hunt private lands; thus, private lands provided elk a refuge during early-season hunts. Late-summer elk movements to private land have led to complaints by local private landowners and resource managers (Gray et al. 1994). For private landowners, complaints focused on crop damage. For COOW, the primacy problem is herd size: because hunters have limited access to private lands, it is difficult for COOW to maintain or reduce herd size via haIVest (J. Madison and C. Reichert, COOW, personal communication). Hunter equity is a third issue: if a large proportion of elk are on private land, then the best hunting will be monopolized by those with enough money to buy trespass pennits (J. Madison and C. Reichert, COOW;' personal communication). Complaints about late-summer elk movement during the mid- to late-1980s prompted the CDOW to conduct a prelimiruuy study on late-summer elk movement to private land in the White River area. In 1992 the COOW trapped and radiocollared 20 adult female elk. A 4-year pilot study from 1992 to 1995 was conducted on 14 to 20 of these radiocollared elk from GMUs 12, 23, 24, and 33. During the study, 70-100% ofradiocollared elk located on public land areas moved to private or wilderness areas, and the mean day of movement was not different from opening day of early-season hunting. For elk moving from public to private land (n = 29) during the 4- year pilot study, the mean date of movement was 3 days (95% CI= -4, 11) from opening date (M. Conner, Colorado �204 State University, unpublished data). Although it did not establish a causal relationship, this study provided strong evidence of a correlation between elk movements and the opening of early-season hunting. To determine if archery and muzzleloading hunting caused elk movements in the White River area in the White River area, I conducted a 2-year experiment. In the White River area, other factors that may contribute to elk movement include historical movement patterns, long-term, learned movement responses, recreational activity, wood cutting, and livestock activity. Any or all of these factors may contribute to elk movement from July through October. However, because the pilot study identified archery hunting as the prime suspect for late-summer movements, and because the CDOW was interested in manageable rather than academic issues, this study focused on the effects of archery hunting on elk movement. In Chapter 1, I report on the field experiment designed to determine whether archery hunting causes elk movement: this experiment compares the timing of elk movements, and the proportion of elk on or moving to private land, with the opening date of archery season. In Chapter 2, I estimate daily hunter densities and compare elk movement to private lands with hunter density. In Chapter 3, I discuss the impact of domestic sheep grazing on elk movement. Each chapter is written to stand alone for publication and follows manuscript guidelines for The Journal of Wildlife Management. LITERATURE CITED Adams, A. W. 1982. Migration. Pages 301-321 in J. W. Thomas and D.E. Toweill, editors. Elk of North America: ecology and management. Stackpole Books, Harrisburg, Pennsylvania, USA. Altmann, M 1956. Patterns of herd behavior in free-ranging elk of Wyoming, Cervus_canadensis ne/soni. Zoologica 41:65-71. Boyce, M S. 1991. Migratory behavior and management of elk (Cervus e/aphus). Applied Animal Behaviour Science 29:239-250. Boyd, R J. 1970. Elk of the White River Plateau, Colorado. Colorado Division of Game, Fish and Parks Technical Publication 25, Fort Collins, Colorado, USA. Bryant, L. D., and C. Maser. 1982. Classification and Distribution. Pages 1-59 in J. W. Thomas and D.E. Toweill, editors. Elk of North America: ecology and management. Stackpole Books, Harrisburg, Pennsylvania, USA. Camp Dresser and McKee, Inc. 1986. Meeker PRLA elk migration study: monitoring report, volume 2. Prepared for Consolidation Coal Company. Camp Dresser and McKee, Inc., Denver, Colorado, USA. Cassirer, E. F., D. J. Freddy, and E. D. Ables. 1992. Elk responses to distwbances by cross-country skiers in Yellowstone National Park. Wildlife Society Bulletin 20:375-381. Cole, E. K., MD. Pope, and R G. Anthony. 1997. Effects of road management on movement and survival of Roosevelt elk. Journal of Wildlife Management 61: 1115-1126. Craighead, J. J., G. Atwell, and B. W. O'Gara. 1972. Elk migrations in and near Yellowstone National Park. Wildlife Monographs 29. Czech, B. 1991. Elk behavior in response to human distwbance at Mount St. Helens National Volcanic Monument. Applied Animal Behaviour Science 29:269-277. Edge, W. D., and C. L. Marcum. 1985. Movements of elk in reaction to logging distwbances. Journal of Wildlife Management 49:926-930. Freddy, D. J. 1987. The White River elk herd: A perspective, 1960-85. Colorado Division of Wildlife Technical Publication 37 Fort Collins, Colorado, USA. Gray, J. P., G. Byrne, and J. Madison. 1994. White River elk data analysis unit plan: game management units: 11,211,12,13,131,231,23,24,25,26,33. Colorado Division of Wildlife Internal Report, Grand Junction, Colorado, USA. Hershey, T. J., and T. A. Leege. 1982. Elk movements and habitat use on a managed forest in north-central Idaho. Idaho Department of Fish and Game Wildlife Bulletin 10, Boise, Idaho, USA. Irwin, L. L., and J. M. Peek. 1979. Relationships between road closures and elk behavior in northern Idaho. Pages 199-204 in M. S. Boyce and L. D. Hayden-Wing, editors. North American elk: ecology, behavior, and 'management University of Wyoming, Laramie, Wyoming, USA. it Knight, RR 1970. The Sun River elk herd Wildlife Monographs 23. Kuck, L., G. L. Hompland, and E. H. Merrill. 1985. Elk calf response to simulated distwbance in southeast Idaho. Journal of Wildlife Management 49:751-757. Lemke, T. 0. 1975. Movement and seasonal ranges of the Burdette Creek elk herd, and an investigation of sport hunting. Montana Fish and Game Department Job Final Report 32.01, Job No. BG-3.15, Missoula, Montana, USA. �205 Martinka. C. J. 1969. Population ecology of summer resident elk in Jackson Hole, Wyoming. Journal of Wildlife Management 33:465-481. Morgantini, L. E., and R J. Hudson. 1979. Human distribution and habitat selection by elk. Pages l32-l39 in M. S. Boyce and L. D. Hayden-Wing, editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA Rost, G. R 1975. Responses of deer and elk to roads. Thesis, Colorado State University, Fort Collins, Colorado, USA. Rudd, W. J., AL. Ward, and L. L. Irwin. 1983. Do split hunting seasons influence elk migrations from Yellowstone National Park? Wildlife Society Bulletin 11:328-331. Schultz, R D., and J. A. Bailey. 1978. Responses of national park elk to human activity. Journal of Wildlife Management 42:91-100. Van Dyke, F., and W. C. Klein. 1996. Response of elk to installation of oil wells. Journal ofManunalogy 77:1028-1041. Ward, A L. 1976. Elk behavior in relation to timber harvest operations and traffic on Medicine Bow Range in south-central Wyoming. Pages 32-43 in S. Hieb, editor. Proceedings of the Elk-Logging-Roads Symposium. University ofldaho, Moscow, Idaho, USA Wright, K. L. 1983. Elk movements, habitat use, and the effects of hunting activity on elk behavior near Gunnison, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. z.abn, H. M. 1974. Seasonal movements of the Burdette Creek elk herd. Montana Fish and Game Department Job Final Report 32.01, Job BG-3.13, Missoula, Montana, USA 7000 - - - - - - - - - - - - - - - - ~ ~ ~ 6000 ::::J .c. C 0 95% Cl - .., . , ~-------., I ,. 5000 ,,. - -- _, ,. - , , - • •111, ' 111, ' " ... ' ' (/J m4000 ~ ai 3000 CD ~ 2000 CD .0 ~ 1000 z 0 -+----..---.------,------,.-----.----.----,------.---.----1 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 Year * Variance estimates not available 1984-1987. Figure I. 1. Number of archery and muzzleloading hunters using GMUs 12, 23, 24, and 33 in northwest Colorado, 1984-1994. Data from Deer, Elk, and Antelope Management (DEAMAN) database and software, Colorado Division of Wildlife, unpublished data. �206 �207 CHAPTER 1: ELK MOVEMENT IN RESPONSE TO EARLY-SEASON HUNTING IN NORTHWEST COLORADO INTRODUCTION Since the early 1900s, Rocky Mountain elk (Cervus elaphus nelsoni) populations have expanded their range from remote areas to much of the Rocky Mountain States (Bryant and Maser 1982). As elk range expanded, so too did elk contact with humans and human disturbances. Elk responses to hunting, road traffic, hikers, cross country skiers, snowmobiles, logging, mining, and oil drilling have been studied in order to reduce elk-human conflicts. Problems with elk responding to hunting center around elk moving onto hunting refuges, which are areas with no or low levels of hunting such as private land, national parks, or densely forested areas. Documented responses of elk to hunting include movement away from hunters or heavily hunted areas (Altmann 1956, Martinka 1969, Wright 1983), increased movement (Zahn 1974, Lemke 1975, Hershey and Legee 1982, Wright 1983), movement to dense vegetative cover (Irwin and Peek 1979, Morgantini and Hudson 1979), movement to private land (Wright 1983) or national parks (Altmann 1956, Martinka 1969), shifts in circadian patterns (Strohmeyer and Peek 1996), and elevation shifts in migration patterns (Knight 1970, Morgantini and Hudson 1979). Most responses to hunting occur before migration to winter range, but some studies have noted changes in migration patterns that were attributed to hunting pressures (Martinka 1969, Boyce 1991). All previous studies of elk responses to hunting have been observational, there have been·no experiments designed to test whether hunting activity causes elk movements. Elk inhabiting the White River area of northwest Colorado are no exception to the pattern of increased range expansion and increased conflict with humans. Prior to 1960, the fall migration of White River elk from high elevation public land, summer range, to lower elevation private land, winter range, (Fig 1.1) occurred during the month of December (Boyd 1970). However, Freddy (1987) noted that elk were beginning to be found in lower elevations during the September and October hunting seasons, which was an uncommon occurrence in the 1960s. Since the 1980s, fall movements have apparently advanced into August and September (Gray et al. 1994). Archery and muzzleloading hunting (early-season hunting) opens on the third Saturday of August in the White River area; around the time of the alleged elk movements onto private land. Since the 1960s, the number of earlyseason hunters using the White River area has grown, with especially significant increases between 1984 and 1992 (Fig. 1.2). Typically, archery hunters did not hunt private lands; thus, private lands provided elk a refuge during early-season hunts. As archery and muzzleloading hunter numbers increased, so too did complaints about early elk movements onto private land. For the private landowner, complaints about early elk movements focused on crop damage. For the Colorado Division of Wildlife (CDOW), the primary problem was herd size: it was difficult for CDOW to maintain or reduce herd size via harvest because hunters have limited access to private lands, (J. Madison and C. Reichert, Colorado Division of Wildlife, personal communication). Because of complaints during the mid- to late 1980s, CDOW conducted a preliminary study on late summer elk movement to private land in the White River area. From 1992 to 1995, 20 radiocollared elk were intensively monitored during August and September, approximately one month before and one month after opening day of archery hunting. Although the proportion and date of elk moving indicated a correlation between elk movement and opening of early-season hunting, a causal relationship was not established. Before instituting any management changes, the CDOW required. an experiment to determine if early-season hunting activity was causing late summer elk movements. My objective was to determine if archery hunting caused elk movement to private land during late summer. Specifically, I conducted a 2-year field experiment in :which_opening date of archery hunting was manipulated in a crossover design. The study area was split into 2 treatment areas; each area received an earlyand late-opening treatment. I tested the null hypotheses that; (1) the mean date of movement to private land was not different between early and late treatments, and (2) the proportion of elk on private land was not affected by the opening of archery hunting. �208 STUDY AREA The White River area of northwestern Colorado covered approximately 4,540 km2 and was composed of Game Management Units (GMUs) 12, 23, 24, and 33. In Colorado, GMUs were delineated to distribute hunters through allocation of hunting licenses. White River area land ownership was 34% private land and 66% public land (Fig 1.1), with 82% of public land being United States Forest Service (USFS). USFS land was mostly at high elevation and toward the center of the study area, with some Bureau of Land Management (BLM) areas at lower elevations in the southern sections of the study area. Private land was lower in elevation and comprised mainly ranches and coal mines. Topography, climate, and vegetation varied widely throughout the study area. Elevation ranged from 1,629 to 3,700 m. The central part of the study area was high elevation public land, split by the White River valley. The high elevation areas dropped off to lower elevations to the north, south, and western edges of the study area. Higher elevations had severe winters with heavy snowfall, while lower elevations had comparatively mild winters. Mean annual precipitation at 3,000 m in the National Forest areas was about 100 cm, compared with about 30 cm at lower elevations of <2,000 m. Vegetation types at elevations >2,600 m were in the montane/subalpine zone and included groves of aspen (Popu/us tremu/oides), Engelmann spruce (Picea enge/manni), and alpine fir (Abies /asiocarpa) interspersed with grassy meadows. Middle elevations (1,9802,600 m) were a transitional zone that consisted primarily of pinion pine (Pinus edu/is),jumper (Juniperus scopulorum), and big sagebrush (Artemisia tridentata). Lower elevations (<2,000 m) in the southern and northern parts of the study area were in the Great Basin zone with sage grasslands. Oakbrush patches were found at the middle and lower elevations with major shrubs that included Gambel's oak (Quercus gambe/ii), serviceberry (Amelanchier alnifo/ia), mountain mahogany (Cercocarpus montanus), chokecherry (Prunus virginiana), snowberry (Symphoricarpos utahensis), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus nauseosus). Higher and middle elevation areas provided summer and fall forage for elk, while lower elevations were typically used by elk during winter. Boyd (1970) provides a detailed description of the study area. Hunting for elk was economically important to local residents in the study area (Gray et al. 1994). Guides, outfitters, local service sectors, and private landowners (who sell trespass permits) made a large proportion of their annual income during the elk and deer hunting seasons, with most hunting revenues accrued during rifle hunting seasons. MEmODS Experimental design The White River and North Fork of the White River divided the study area roughly east-west into 2 halves (Fig. 1.3). GMU 12 and parts of GMUs 23 and 24 composed the north treatment area, while GMU 33 and parts of GMUs 23 and 24 composed the south treatment area. Because only 2 elk moved from one side of the White River to the other within a year during the 4-year pilot study (M. Conner, Colorado State University, unpublished data), I felt there would be little interchange between treatment areas. Two treatments were applied: an archery season that opened 1 week earlier, and another that opened 2 weeks later than normal, yielding a 3week difference in opening dates. During the first year of the study, the early-opening treatment was randomly assigned to the south treatment area. Treatments were reversed the second year of the study. Thus, in 1996, archery hunting opened early, 24 August, in the south area, and late, 14 September, in the north area. When treatments were reversed in 1997, archery hunting opened early, 23 August, in the north area, and late, 13 September, in the south area The number of archery and muzzleloading licenses issued for elk and deer during the study,:'were based on the mean number per year calculated for 1990-1994 (4,985; Colorado Division of ,· •1 Wildlife unpublished data), with licenses allocated approximately 50% per treatment area. Restricting licenses kept hunter density consistent during the study and consistent with years of high elk movement complaints. Sample size for number of collared elk was based on the primary response variable, mean date of movement, for the following parameters; Cl= 0.05, ~ = 90%, effect siz.e = 7-day difference in mean date of movement between treatments, and estimated variance = 22. 7 days. The variance was based on pilot study data (M. Conner, Colorado State University, unpublished data). For these parameters, 36 cows per treatment area • �209 were required. To allow for some telemetry failures or erratic elk movements off the study area, extra cows were collared. Thus, 40 cows per treatment area were collared for the study. Elk capture locations were randomly picked from a uniform distribution by a computer. Random Universal Transverse Mercator (UTM) coordinates were generated until 80 points lay within the study area's national forest boundaries. Elk were captured by helicopter netgunning (Barrett et al. 1982) during mid-July in 1996 and 1997. Elk were captured on their summer range to assure a random sample for the July-October study period. The helicopter pilot flew to each randomly selected location and captured the first adult female elk found near that location. Although it was not practical to capture exactly as dictated by a random number algorithm, due to constraints on private land access and time, a reasonably representative sample was obtained with 2 elk being captured at some locations (Fig. 1.3). In addition to the 80 elk captured in 1996, 8 radiocollared elk from the pilot study were used in 1996 analyses. In 1997, 10 additional elk were captured to replace animals that died, bringing the total number of collared animals back to 80, with 40 per treatment area. Colorado State University Institutional Animal Care and Use Committee approved the capture and handling methods (protocol 95-180A-0l). Each elk was fitted with a 148-152 MHz radio collar with a mortality sensor. A high percentage of bulls are lost to hunting, which could reduce sample size below levels required to maintain the power of the hypothesis tests. Because this study was to take place during a hunting season, when bulls are desirable game, I wished to collar only adult females to minimize loss of sample size. During fall rutting season, August-October, there is a high degree of association (97%) between male and female elk (Franklin and Lieb 1979). I collared only adult female elk to represent the movement patterns of both sexes and maintain the power of the hypothesis tests. Data collection The relevant time frame for determining elk movement in response to archery hunting was defined as ±1 month of opening day. Because early treatment opening was 23-24 August and late treatment opening was 13-14 September, I collected locations 20 July- IO October. The study period ended slightly less than a month after late treatment opening date to avoid confounding elk movements due to archery hunting with effects due to rifle hunting, which opened 13-14 October. All analyses were done on data collected over the entire 3-month study period. I relocated radiocollared elk between 0700-1500 hr using a Cessna 182 or 185 fixed-wing aircraft with a 2-element Yagi antenna mounted to each strut of the airplane. For each elk relocation, UTM coordinates were recorded with a Global Positioning System that was not differentially corrected. I collected elk locations 2 times a week with 2-4 days between collections. A Geographical Information System (GIS) map was used to record elk locations, land ownership, and treatment boundaries. The GIS map was digitized from a United States Geological Survey map at a scale of 1:100,000. For each location of a telemetered cow, a 0 was assigned if the location was on public land (e.g. Flat Tops Wilderness Area, USFS, State Wildlife, and BLM lands) and a I was assigned if the location was on private land. Because I was interested in gross classifications of elk locations (public land versus private land), I did not do a formal check of the telemetry error. However, I did a cursory check of telemetry error when picking up collars from a different study in the area. The mean error on the collars I collected was 333 m (n = 24, 95% CI= 265, 40 I), with a range of 117-683 m. Data analysis The primary response variables were mean date of movement for elk that changed classification (occupying public and moving to private land) and proportion of elk on private land. I calculated th~ date of movement for each elk using logistic regression oflocation on public (y = 0) and private land (y = 1) versus date. The date of movement was defined as the date at which the logistic curve crossed 0.5 on the y-axis, indicating an equal probability of being on public or private land. Only dates of movement from public to private land during the study period were included in analyses of mean date of movement. If hunting had no effect on elk movements, then there should be no difference between the mean date of movement to private land between early- and late-opening date treatments. To test for a treatment effect on mean date of movement, I accounted for treatment, area, and year effects. The corresponding ANOVA model was: �210 where: yyu = date of movement for the ff' radiocollared elk, receiving treatment i, in year j and in area k, µ = overall mean date of movement (for all elk, both years), a., = fixed effects due to treatment i (early or late opening), 131 = fixed effects due to yearj (year 1 or year 2), ok = fixed effects due to area k (either north or south), and &yu = random error for the /'1' radiocollared elk. Specific hypotheses tested were: Ho 1: Mean date of elk movement for early-opening treatment = mean date of elk movement for late-opening treatment; a., ~ 0; HA1: Mean date of elk movement for early-opening treatment < mean date of elk movement for late-opening treatment; a., < 0; ffm: Mean date of elk movement for year 1 of experiment = mean date of elk movement for year 2; f31 = 0; HA2: Mean date of elk movement for year 1 of experiment :t:. mean date of elk movement for year 2; 131 -:#- 0; Hen: Mean date of movement for north-area elk = mean date of movement for south-area elk, ok= 0; HAJ: Mean date of movement for north-area elk mean date of movement for south-area elk, ok:t:. 0. * Hypothesis l was the experimental hypothesis; hypotheses 2 and 3 accounted for other sources of variation. I used PROC GLM (SAS Institute 1990) to estimate and test differences in mean date of movement by area, treatment, and year. Type m sum of squares were used for hypothesis tests. To determine whether elk receiving both early and late treatments on public land, regardless of area or year, were affected by opening date, I used a paired I-test blocked on individual elk. This individual blocking reduced confounding effects and better accounted for repeated measures taken on animals receiving both treatments; thus, the analysis was limited to those individuals that received both early- and late-opening date treatments. Fewer elk received both treatments than received a single treatment because some elk died after the first study period, some elk were on public land only one year (they stayed on private land the other year), and some changed treatment areas between years. For the elk getting both treatments, I subtracted their early date of movement from their late date of movement to account for the fact that this was a repeated measurement on the elk. I tested the null hypothesis: Ho: Difference in date of movement for late treatment - early treatment <= 0; HA: Difference in date of movement for late treatment - early treatment> 0. I used logistic regression models to predict the proportion of elk on private land on day i (j, i) from elk location data (public or private land). Models included date as a covariate, and hunting season, area and year effects as categorical variables. Julian date was used to model date effects so that year effects could be considered separately from study period date. Hunting season referred to the period before opening of archery season (hunting season= 0) and after opening (hunting season= 1). I began with a global model, which included date, hunting season, area, year, plus all 2-, 3- and 4-way interactions of date, hunting season, area, and year (fable 1.1, Model 1). I then developed 9 additional a priori hypothetical models for proportion of elk on private land (fable 1.1, Models 2-10). After analyzing the a priori models, I built 3 additional models to see if a better model could be built (fable 1.1, Models 11-13). �211 I followed the methodology of Burnham and Anderson ( 1998) to select an appropriate model. I used Akaike's Information Criterion (Akaike 1973), adjusted for overdispersion and corrected for small sample bias (QAICc), as the basis for objectively ranking models and selecting an appropriate "best approximating" model (Burnham et al. 1995). QAICc was defined as: QAICc =- 2{lni) +2K + 2K(K +I) n-K -l ' c where In .e is the natural logarithm of the likelihood function evaluated at the maximum likelihood estimates for a c given model, K is the number of estimable parameters from that model, n is sample size, and is the estimated overdispersion factor. QAICc was used instead of AICc because repeated measurements were taken on radiocollared elk. Lack of independence in the data, in this case repeated measures on elk, may lead to overdispersion or "extra-binomial variation" (Burnham and Anderson 1988). I estimated the overdispersion parameter ( c) from the global model, and then used this estimate to adjust (inflate) the variance estimates of model parameters and predicted values, and to calculate QAICc for all models (Burnham and Anderson 1998). Parameter estimates, c, and QAICc values were calculated using PROC GENMOD (SAS Institute 1993). The sample size, n, was the number of elk locations collected during the study period. The best approximating model was selected based on minimum QAICc. Models were ranked and compared using DQSAICc (Leberton et al. 1992, Burnham and Anderson 1998) and normalized QAICc weights (Buckland et al. 1997, Burnham and Anderson 1998). For the suite of models being compared, AQAICc was computed for each model as: AQAICc,,, = QAICc,,, - QAICc.,,n , where QAICc,,, was the QAICc value for the mth model and QAICc.,,n was the minimum QAICc among the suite models being compared. Essentially, AQAICc,., is an estimate of the distance between the best approximating model and model m. Normalized AICc weights (w.,) were estimated for each mth model: _ _!.~QAICc w m- e 2 ~> R "' l --~QAICc 2 , r r=l where R refers to the R models chosen for evaluation. AQAICc and normalized QAICc weights were used to address model selection uncertainty. Generally, models within 1-2 QAICc units of the selected model were considered competing models for explaining elk movements to private land. Another element of uncertainty in estimates of model precision is selection of the appropriate model (Buckland et al. 1997). If several sets of data, generated from the same underlying process, were evaluated using AICc, there would be some variation in the selected best model (Burnham and Anderson 1998). Estimates of precision from any one best model do not include model selection variance and may be biased low. Therefore, after model selection, I used model averaging to better estimate the precision of the estimates of daily proportion of elk on private land from all the models I developed. Average estimates of the daily proportion of elk on private land were calculated for each day i across all models considered. Because all models were logit models, modelaveraged daily proportion of elk on public land, P;, and var(p;) were calculated in the logit scale and backtransformed to calculate the appropriate confidence interval, which was slightly asymmetric. The transfomation used was: logit(J\) = 1n[ I - R !fa;]. logit(p;) = L Wm logit(P;m), and m=l �212 where wm is the normalized AICc weight. The variance of the model-averaged estimates, which included conditional sampling variance and model uncertainty was estimated: where M,,, is the mth model. The 95% confidence interval for the daily estimated proportion of elk on private land was calculated as: +95%CI(p;) e +9S%Cl~ogit(fa1)] - - - - - - - , and I +e +9S%CI~ogit(fa,)] -95%Cl(p;)= e -9S%CI[logit(fa1)] _ I +e -9S%CI~ogit(j,1)] To estimate the effect of hunting season on the proportion of elk on private land, I estimated the difference between the proportion of elk on private land immediately before and after opening date: e logit(fab) l +elogit(j,b) ' pa p where and b are the model-averaged proportion of elk on private land after and before opening date. The variance in estimated proportion of elk on private land before and after opening of archery hunting was calculated: �213 Procedures for estimating covariance of model-averaged values are in the development stage and untested (K. Burnham, Colorado Cooperative Fish and Wildlife Research Unit, personal communication). Thus, I assumed the covariance to be z.ero. This omission may result in a slightly inflated variance, and a possibility of not detecting a true effect of hunting season. The variance of the model-averaged estimated proportion of elk on private land was calculated using the delta method (Seber 1982): ~i, Let u =logit(pa), then var(pa) =v:J and "l1+e" A • ~ 2 du du du =-=viir(u )-=- =(-=-) viir(u) =[ A viir(p a) dfaa dfaa dfaa ]2 e" A A (l+e") 2 viir(u) • Substituting logit(p a) back in for u: 2 _ elogit(it> var(_p a) = _ _ [ 2 ( 1+ elogit(faa)) _ _ var[logit(p a)]= [fa a (l - pa) f var[logit(pa)]. - 1 The var(pb) was calculated similarly. The 95% CI was calculated: - - - - I\_ 95%Cl(p0 - Pb)~ (Pa - fib)± l.96se(p0 - Pb)· Because previous studies used changes in daily distances moved and elevation shifts to evaluate elk responses to disturbance, I calculated these metrics for comparison. Mean daily distances moved and mean daily elevations during the study period were calculated from the 80-radiocollared elk. Distances were calculated from consecutive UTM locations for each elk as straight-line distances. Because elk were not located at fixed time �214 intervals, distances between locations were expressed per day by dividing the distances moved by the number of days between locations. Daily distances were not absolute measures of distance moved, rather they were indices of movement. Elevations for each elk location came from a statewide I: l 00,000-scale elevation map. RESULTS Results from the ANOVA on mean date of elk movement indicated a treatment effect (P = 0.013, one sided), but no area or year effects (P > 0.100; Table 1.2). However, north- and south-area elk showed different responses to opening of archery hunting. To evaluate this apparent difference, I preformed a post hoc analysis separately by area. This analysis revealed a 14-day difference (P = 0.006, one sided) in mean date of movement between treatments for elk in the north area, versus a 6-day difference (P = 0.218, one sided) between treatments for elk in the south area (Table 1.3). Area and year were confounded within sequence of treatments this study. That is, elk in the north area received the late-early treatment sequence, while elk in the south area received the early-late treatment sequence. Thus, it was impossible to determine whether a sequence effect was really a difference resulting from (1) a difference between treatment areas because oflocation of private-land refuges, topography, etc., or (2) elk receiving a late-opening treatment the first year followed by an early-opening treatment the second year behave differently than elk receiving the early-late sequence. I reference this confounded effect as an area effect, which I will discuss later. Sixteen of the 80-radiocollared elk received both early and late treatments and moved from public to private land during the study period. That is, there were 32 paired movements (16 elk receiving 2 treatments and moving form public to private both years) compared to 60 unpaired movements (elk receiving treatments and moving from public to private land at least 1 year). Some elk moved to private land immediately after capture in 1996, and some elk never returned to public land in 1997, thus fewer than 80 elk were available for treatment each year. The difference between the paired and unpaired movements occurred because 4 elk moved the first year but died before the second year, 3 elk were collared in 1997 and moved only the second year, 11 elk only moved one year because they were on public land one year and private land the other year, 1 elk changed treatment areas and received late-late treatments (counting as 2 unpaired movements), and 8 elk moved from public to private land one year only. The difference in mean date of movement for the 16 elk receiving both early and late treatments was 5 days (95% CI= -3, 13; P = 0.091 one sided). Using model-averaged values, I generated predicted curves of proportion of elk on private land versus Julian day, hunt season, area, and year (Fig. 1.4 and 1.5). All logistic models to estimate the daily proportion of elk on private land had a significant positive date effect indicating that proportion of elk on private land increased from 19 July-10 October both years of the study (Fig. 1.4 and 1.5). The logistic regression model with the lowest AICc (Table 1. 1, model 13) was: logit(f,;) = --4.715-1.294(area) +4.987(hunt season)+ 0.015(Julian day)+ 0.009(area x Julian day) -0.018(hunt season xJulian day) , where f,; is the predicted proportion of elk on private land on Julian day i. The top 2 models, both post hoc models, (Table 1.1, models 13 and 12) were 1.85 AICc units from each other, while the remaining 11 models were over 3 AICc units greater than model 13 (Table 1.4). Hence, I considered models 13 and 12 as competing models. Model 12, the second model, was identical to model 13 except for an additional area x hunt season interaction. Thus, area, hunt season, Julian date,,;u-ea x Julian day, hunt season x Julian day, and area x hunt season may be important predictors of the proportion of elk on private land. The area effect arose from a higher proportion of elk on private land, in general, on the north area versus the south area, the hunt season effect arose from a higher proportion of elk on private land after hunting opened versus before, and the Julian date effect arose from the increase in elk on private land through time (the study period). The area x Julian day interaction arose from the steeper slope for the north area versus the south area, and the hunt season x Julian day interaction arose from the steeper slope before hunting season opened versus after it opened. �215 The experimental effect on the number of elk directly influenced by early-season hunting can be estimated by the abrupt increase in proportion of elk moving to private land when hunting opened. I used the difference in the model-averaged predicted proportion of elk on private land immediately before and immediately after opening day to estimate the direct effect of opening of hunting. Elk on private land increased 8-18% at the opening of early-season hunting (Table 1.5). During the study period, a significantly higher proportion of radiocollared elk moved to private land in the north treatment area compared to south area (P = 0.035; Table 1.6). On average, elk moved 613 m/day (95% CI= 594,632). The mean daily distance moved by elk before hunting season opened was 651 m/day (95% CI= 619, 683) and 575 m/day (95% CI= 540,610) after opening (Fig. 1.6 and 1. 7). During the study, the mean elevation of elk changed by -2.1 m/day (95% CI = -2.3, -1.9). Elk moved down in elevation an average of-2.4 m/day (95% CI= -2.9, -1.9) before hunting season opened and down -0.7 m/day (95% CI= -1.2, -0.2) after opening (Fig. 1.8 and 1.9). DISCUSSION Experimental ResulJs Although elk movements in the White River area may not be solely caused by archery hunting activity, the experimental results show that archery hunting activity has an effect on elk movements despite other factors, especially in the northern treatment area. The strength of a 2 x 2 crossover design is that it blocks or controls for two sources of external variation, allowing for much stronger inference of cause and effect than the same design without a strict crossover (Ratti and Garton 1994). The crossover is also more efficient than a randomiz.ed design (Ott 1993); that is, a randomiz.ed design requires a larger sample size. In this experiment, area and year were the external sources of variation controlled for by the crossover design, and opening date of archery hunting was the treatment Any factor that occurred on both halves of the study area, such as recreational activity, grazing, weather, forage phenology etc., that also caused elk to move, would lessen detection of an effect due to hunting activity. For example, if recreational activity caused some elk movement during the study period, then these recreationally induced movements would be unaffected by opening date of archery hunting and would serve to attenuate detection of archery hunting effects. If no elk were responding to archery hunting activity, either because they moved in response to another factor or they did not move at all, then I would fail to reject the null hypothesis and would conclude that archery hunting was not affecting elk movement. In the White River elk population, some elk may move regardless of what happens with archery hunting, because their movement was a response to some other factor; some elk may not move; and some elk may move due to changes in archery hunting activity. In the north treatment area, elk receiving the early treatment moved 14 days earlier than elk receiving the late treatment, indicating that some elk moved in response to archery season. Similarly, the effects of archery hunting on the daily proportion of elk on private land can also be distinguished from other effects. The positive slope for proportion of elk on private land resulted from steady movement of elk to private land during the study period and suggested that factors other than archery hunting may have affected elk movements. However, some of the movement to private land was directly attributable to hunting. That is, 23-44% of the radiocollared elk moved to private land during the study period, and 8-18% of this movement occurred at the opening of archery season. The significant jump in proportion of elk on private land at archery opening, beyond the steady increase, indicates that archery hunting activity did affect movement beyond that caused by other factors on both the north and south treatment areas. Sequence or carry-over effects can dilute detection of treatment effects in this type of study. A carryover effect occurs when the sequence of treatments affects responses to treatments (Ott 1993). In the case of White River elk, a carry-over effect would exist if south-area elk, receiving the early-opening treatment the first year, moved early the second year, before the late-opening date. A carry-over effect would be manifest on the north area if elk receiving the late-opening treatment the first year, moved late the second year, after the earlyopening date. In this experiment, elk on the north area moved slightly before opening date both years, while elk on the south area moved in accordance with opening date. Thus, I concluded that there was no carry-over effect due to the sequence of the treatments. I attributed differences in movements to area rather than sequence effects. A post hoc analyses on mean date of movement and daily proportion of elk on private land revealed that treatment effects were greater in the north area. When designing the study, I assumed that the north and south �216 areas were similar and would serve as controls for each other. Alleged elk movements to private land were perceived to be similar problem on both areas. The differences may have occurred because habitat, cover, topography, or any other area factors important to elk movement were different on the two treatment areas. Fortunately, each area received both treatments, so I could look at each area as its own control and evaluate each area separately. In the north treatment area there was a significant 14-day difference in mean date of movement between early and late treatments, while in the south treatment area there was a non-significant 6-day difference. In the north treatment area, about twice as many elk moved to private land ( 44%) compared to elk in the south area (23%). The difference in treatment response in the north and south areas may be due to cover and refuge configuration. In general, animals must balance the tradeoff between feeding and danger (Krebs and Davies 1993); elk may reduce use of open areas and use cover more frequently in times of perceived or real danger. Elk calves subjected to simulated surface-mining activities used coniferous forest significantly more often compared to undisturbed calves (Kuck et al. 1985). Similarly, elk subjected to oil drilling significantly increased use of forested habitats during drilling and post drilling periods, compared with the pre-drilling period (Van Dyke and Klein 1996). Where logging activities disturbed elk, areas of high elk use were negatively correlated to the amount of cover in the area (Edge and Marcum 1985, Edge et al. 1985, Czech 1991). In the White River area, the north area was rolling, with open parks interspersed with a few high peaks, while the higher elevation south area was essentially a plateau cut by steep narrow canyons and with steep, densely forested cliffs defining the plateau. These densely forested canyons and cliffs, inaccessible to motor vehicles, offered good refuge from hunters on public land. In contrast, the north area offered less shelter on public land, but had refuge in large private-land tracts that bordered the area. The south treatment area had less private land adjacent to public land, as BLM land was abundant at lower elevations. It may be that elk in the south area moved into forest refuges on public land after archery hunting opened, while elk in the north area moved to private-land refuges. More generally, elk movements during hunting seem to depend on location and quality of hiding cover. Elk decreased their daily movements after attaining sanctuary from hunting in national parks (Altmann 1956, Martinka 1969) or thick vegetation inaccessible to most hunters (Lemke 1975, Irwin and Peek 1979, Morgantini and Hudson 1979). I found a similar general pattern; elk on the north and south areas reduced their daily movements an average of 76 m/day after hunting season opened and they attained refuge from hunting on private land or in thick vegetation. a Scale Issues Three main issues became evident during the course of the study that fall under the rubric of large-scale field experiments: (1) a difference between movement responses for elk in the north and south areas, (2) a difference in the experimental results compared to pilot study results, and (3) failure of many elk to receive both treatments. As discussed, I think the difference in treatment responses between north and south elk were due to proximity of cover and private land hunting sanctuary. Additionally, I speculate that differences in wintering grounds and migration routes between the two treatment areas also affected movement responses. In the south treatment area, wintering grounds were at the south end of the study area. Southern elk were impaired from migrating beyond the study area by barriers created by Interstate 70 and the Colorado River. In the north treatment area, although private-land refuge was adjacent to the study area, wintering grounds were 30-80 km west of the study area During the study period, elk moving to private land in the north area were just beginning their fall migration, whereas elk in the south area were completing their migration by moving to private land. It may be that there was no energetic cost to northern elk to move to private land in late summer, while southern elk would risk depleting their winter forage by moving to private land in late summer. There was less movement during..the ex~ent than I expected based on pilot study data. During the experiment, 21-48% of elk moved to private land compared to 70-100% during the pilot study. I think this disparity arose because the pilot study lacked a random sample from the entire area. Pilot study animals were collared primarily in areas with perceived movement problems. When the spatial scope of sampling expanded such that the entire study area was randomly sampled, many elk were collared in areas with no previous record of movement Corresponding to the increased spatial variability in elk capture location was an increased variability in elk movement responses: elk in some areas did not move. The pilot study animals were not representatives of the entire study area, rather they represented areas with movement problems. �217 I designed this experiment with the intent that it be a crossover experiment, which used a crossover AN OVA model to test whether the mean date of elk movement from public land to private land was different between treatments. Exposure by each animal to both treatments was a requirement of the crossover analysis, and this requirement was impossible to implement in this large-scale field experiment. I did not have the control to ensure that each animal received both treatments; therefore, I analyzed the data as paired and unpaired data. Interpretation of mean date of movement results would have been more robust if all elk received both treatments. Mean date of movement between treatments was less dramatic for the paired analysis (5 days) compared to the unpaired analysis (10 days), though the difference was not significant. This difference may represent sampling variance; the small size of the paired sample makes this possibility likely. MANAGEMENT IMPLICATIONS Although there was a statistically significant effect of archery hunting on timing and number of elk moving to private land in the north treatment area, the question remains as to whether this effect was significant to elk management. The experimental effect on number of elk moving can be estimated by the abrupt increase in proportion of elk moving to private land when hunting opened. This jump was 8-18%; hence, the CDOW can reduce, at most, approximately 20% of the elk movement to private lands by manipulating archery hunting activity. However, 20% of a herd may represent a large enough number of animals to make management changes worthwhile. Additionally, if elk movements are concentrated in problem areas, then manipulation of opening date may result in a proportionally higher reduction of elk movements in those areas. Managers must decide whether the contribution of archery hunting activity to elk movement is large enough to warrant management action. Elk responded to archery hunting activity differently in north and south treatment areas; I concluded that archery hunting activity had little or no effect in the south area, but had a statistically significant effect on timing and proportion moving in the north area. Thus, managers concerned with elk movement need to be cautious if citing White River results as a reason for management actions; elk movement was dependent on the habitat and topography of an area, and these factors must be considered in any plan to reduce elk movements. Furthermore, because this study manipulated opening date of hunting activity but kept hunter numbers constant, the question remains of what percentage of the elk would still move if hunting were reduced or eliminated. Managers may also want to consider the time needed to make permanent changes in elk movement patterns. Elk responses to disturbance may be long- or short-lived depending on the type of disturbance and the type of elk response. For example, studies that evaluated elk movements after disturbances ceased found that displacement appears to be temporary in most situations. Elk displaced by cross-country skiers returned to their original locations after people left the area (Cassirer et al. 1992). During weekends, and immediately following the end oflogging activities, elk moved back into logged areas (Ward 1976, Edge and Marcum 1985). Even for more potentially lethal hunting disturbances, mean distances to roads returned to pre-hunting distances after hunting season closed (Hershey and Legee 1982, Wright 1983). Zahn (1974), Lemke (1975), and Hershey and Legee (1982) also found that elk response to hunter disturbance was short-lived. In the White River area, this short-lived response seems to characterize south-area elk. In 1996, hunting season opened early, 24 August, in the south area, and closed 14 September. A drop in the proportion of elk on private land occurred after closing date (Fig. 1.4a), indicating that some elk moved back to public land after hunting season closed. This was also seen in elevation shifts of south-area elk: after hunting season closed in 1996, mean daily elevations increased (Fig 1.9a), indicating that elk moved back up to public land after the disturbance ended. Elk in the south treatment area seem to exhibit a short-term response to hunting disturbances. On the other hand, if the elk response to disturbance was a migration shift, then the movement response may last longer. Elk that have learned to move to unhunted refuges and choose migration routes through lightly hunted areas (Altmann 1956, Martinka 1969) may continue these patterns ifno cost was incurred by the change. In the north area, the steady movement may be only partially a direct effect of hunting season. Some elk may learn to move to private land as a conditioned response to avoid hunting danger, and this movement may have become paired with some unconditioned stimuli, such as shortening day length. Because movement in the north area is the beginning of migration, and because timing of migration is thought to be stimulated by daylight cues (Krebs and Davies 1993), north-area elk may now move when the days begin to shorten in addition to the stimulus of hunter activity. As older cow elk have been found to assume leadership roles within a group (Franklin and Lieb 1979), �218 social learning may pass on this pattern to future generations. Thus, elk on the north area may move to private land in response to direct cues of hunter activity and indirect cues of day length. When considering elk movements in response to hunting activity, wildlife managers should consider the type of movements being exhibited by the elk as well as the refuge configuration in the area. Although reducing hunter numbers may reduce movement where elk responses to disturbance are short lived (probably short movements to habitat refuges), different management practices may be needed where migration patterns have become a fixed behavior. If elk have established a migration pattern onto private land, private land hunts, on lands to which elk move, may be a good solution to break the migration pattern and deter early elk movements onto private land. LITERATURE CITED Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. Pages 267-281 in B. N. Petran and F. Csak:i, editors. International symposium on information theory. Second edition. Akademiai Kiadi, Budapest, Hungary. Altmann, M. 1956. Patterns of herd behavior in free-ranging elk of Wyoming, Cervus canadensis ne/soni. Zoologica 41 :65-71. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net gun to capture large mammals. Wildlife Society Bulletin 10:108-114. .. Boyce, M S. 1991. Migratory behavior and management of elk (Cervus elaphus). Applied Animal Behavioral Science 29:239-250. Boyd, R J. 1970. Elk of the White River Plateau, Colorado. Colorado Division of Game, Fish and Parks Technical Publication 25, Fort Collins, Colorado, USA. Buckland, S. T., K.. P. Burnham, and N. H. Augustin. 1997. Model selection: an integral part of inference. Biometrics 53:603-618. Burnham, K.. P., D. R Anderson, and G. C. White. 1995. Model selection strategy in the analysis ofcapturerecapture data. Biometrics 51 :888-898. Burnham, K.. P., and D. R Anderson. 1998. Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New Yorlc, USA. Bryant, L. D., and C. Maser. 1982. Classification and Distribution. Pages 1-59 in J. W. Thomas and D. E. Toweill, editors. Elk of North America: ecology and management Stackpole Books, Harrisburg, Pennsylvania, USA. Cassirer, E. F., D. J. Freddy, and E. D. Ables. 1992. Elk responses to disturbances by cross-country skiers in Yellowstone National Park. Wildlife Society Bulletin 20:375-381. Czech, B. 1991. Elk behavior in response to human disturbance at Mount St Helens National Volcanic Monument. Applied Animal Behavioral Science 29:269-277. Edge, W. D., and C. L. Marcum. 1985. Movements of elk in reaction to logging disturbances. Journal of Wildlife Management 49:926-930. Edge, W. D., C. L. Marcum, and S. L. Olson. 1985. Effects oflogging activities on home-range fidelity of elk. Journal of Wildlife Management 49:741-744. Franklin, W. L., and J. W. Lieb. 1979. The social organization ofa sedentary population of North American elk: a model for understanding other populations. Pages 185-198 in M. S. Boyce and L. D. Hayden-Wing editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA. Freddy, D. J. 1987. The White River elk herd: A perspective, 1960-85. Colorado Division of Wildlife Technical Publication 37, Fort Collins, Colorado, USA. Gray, J.P., G. Byrne, and J. Madison. 1994. White River elk data analysis unit plan: game management units: ll,211,12,13,i31,231,23,24,25,26,33. Colorado Division of Wildlife Internal Report, Grand Junction, Colorado, USA. .. Hershey, T. J., and T. A. Leege. 1982. Elk movements and habitat use on a managed forest in north-central Idaho. Idaho Department of Fish and Game Wildlife Bulletin 10, Boise, Idaho, USA. Irwin, L. L., and J.M. Peek. 1979. Relationships between road closures and elk behavior in northern Idaho. Pages 199-204 in M. S. Boyce and L. D. Hayden-Wing editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA. Knight, RR 1970. The Sun River elk herd. Wildlife Monographs 23. Krebs, J. R, and N. B. Davies. 1993. An introduction to behavioural ecology. Third edition. Blackwell Science Ltd., Oxford, England. �219 Kuck, L., G. L. Hompland, and E. H. Merrill. 1985. Elk calf response to simulated disturbance in southeast Idaho. Journal of Wildlife Management 49:751-757. Leberton, J-D., K. P. Burnham, J. Clobert, and D. R Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological Monographs 62:67-118. Lemke, T. 0. 1975. Movement and seasonal ranges of the Burdette Creek elk herd, and an investigation of sport hunting. Montana Fish and Game Department Final Report 32.01, Job Number BG-3.15, Missoula, Montana, USA. Martinka, C. J. 1969. Population ecology of summer resident elk in Jackson Hole, Wyoming. Journal of Wildlife Management 33:465-481. Morgantini, L. E., and R J. Hudson. 1979. Human distribution and habitat selection by elk. Pages 132-139 in M. S. Boyce and L. D. Hayden-Wing editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA. Ott, R L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth, Inc., Belmont, California, USA. Ratti, J. T., and E. 0. Garton. 1994. Research and experimental design. Pages 1-23 in S. Hieb, editor. Research and management techniques for wildlife and habitats. Fifth edition. The Wildlife Society, Bethesda, Maryland, USA. SAS Institute. 1990. SAS/STAT® user's guide, version 6.0. Fourth edition. SAS Institute, Inc., Cacy, North Carolina, USA. SAS Institute. 1993. SAS/STAT® software: The GENMOD procedure, release 6.09. SAS® Technical ReportP243, SAS Institute, Inc., Cacy, North Carolina, USA. .. Seber, G. A. F. 1982. The estimation of animal abundance and related parameters. Second edition. Edward Arnold, London, England. Strohmeyer, D. C., and J. M Peek. 1996. Wapiti home range and movement patterns in a sagebrush desert. Northwest Science 70:79-87. Van Dyke, F., and W. C. Klein. 1996. Response of elk to installation of oil wells. Journal ofMammalogy 77:1028-1041. Ward, A. L. 1976. Elk behavior in relation to timber harvest operations and traffic on Medicine Bow Range in south-central Wyoming. Pages 32-43 in S. Hieb, editor. Proceedings of the Elk-Logging-Roads Symposium. University of Idaho, Moscow, Idaho, USA. Wright, K. L. 1983. Elk movements, habitat use, and the effects of hunting activity on elk behavior near Gunnison, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Zahn, ll M. 1974. Seasonal movements of the Burdette Creek elk herd. Montana Fish and Game Department Final Report 32.01, Job Number BG-3.13, Missoula, Montana, USA. �220 Table 1.1. Description and representation of a priori (models 1-12) and post hoc (models 11-13) models relating effects of year, area. opening of archery hunting season. and Julian date to daily proportion of radiocollared elk found on private land (p,) from 20 July to 10 October in the White River area. Colorado, 1996-1997. 1. HyPOthesis Global model: year, area. opening of archery hunting, Julian day, and all possible interactions 2. No year x date interactions 3. No year x main effects (A and S) interactions 4. No year effects 5. No area x date interactions 6. No area x main effects (Y and S) interactions 7. No area effects 8. No hunt season x date interactions 9. No hunt season x main effects (A and Y) interactions 10. No hunt season effects 11. Only hunt season effects 12. Only hunt season and area effects 13. Only hunt season and area effects with no S x A interaction Model structure • f3o+f31 (Y)+f32(A)+f3iS)+f3iD)+f3s(YxA)+f36(YxS) +f37CY xD )+f3s(Ax S)+f39(AxD)+f3 10(SxD) +f3 11 (YxAxS)+f3 12(YxAxD)+f3 13(YxSxD) +f3 14(AxSxD)+f3 15(YxAxSxD) f3o+f31 (Y)+f3iA)+f3 3(S)+f3iD)+f35(YxA)+f36(Y xS) +f3i{AxS)+f3s(AxD)+f39(SxD)+f3 10(YxAxS) +f3 11 (AxSxD) f3o+f31(Y)+f32(A)+f33(S)+f3iD)+f3 5(YxD) +f36(AxS)+f3i{AxD)+f3s(SxD)+f39(AxSxD) f3o+f3,(A)+f32(S)+f3iD)+f3 4(AxS)+f35(AxD) +f3iSxD)+f3i{AxSxD) f3o+f31 (Y)+f32(A)+f3iS)+f3iD)+f3s(YxA)+f36(YxS) +f37CY"xD)+f3s(AxS)+f3 9(SxD) +f3 10(YxAxS)+f3 11 (YxSxD) .. f3o+f31(Y)+f32(A)+f33(S)+f34(D)+f3 5(YxS)+f3~xD) +f3i{AxD)+f3s(SxD)+f39(YxSxD) f3o+f3,(Y)+f32(S)+f33(D)+f34(YxS)+f3 5(YxD) +f3iSxD)+f37CYxHxD) f3o+f3, (Y)+f32(A)+f3iS)+f34(D)+f3s(YxA)+f36(Y xS) +f37CY'xD)+f38(AxS)+f3 9(AxD)+f3 10(YxAxS) +f3 11 (YxAxD) f3o+f3,(Y)+f32(A)+f33(S)+f34(D)+f3s(YxA)+f36(YxD) +f3i{AxD )+f3s(SxD)+f39(YxAxD) f3o+f3,(A)+f32(Y)+f33(D)+f3iAxY)+f3 5(AxD) +f36(YxD)+f3i{Ax YxD) f3o+f3,(S)+f32(D)+f3iSxD) f3 0+f3 1(A)+f3iS)+f33(D)+f3iAxS)+f3 5(AxD)+f36(SxD) f30+f3 1(A)+f3 2(S)+f33(D)+f3 4(AxD)+f3 5(SxD) • Y represents year with 1996 = 0 and 1997 = 1, A represents treatment area with south area = 0 and north area = I, S represents archery hunting season with O= before opening and 1 = after opening, and D represents the covariate date, which is Julian day. The dependent variable (p,) was in logit scale. �221 Table 1.2. Days between opening dates, least-square mean differences with ±95% CI, and P-value for the null hypothesis of no difference between mean date of movement by treatment, year, and area for radiocollared elk in the White River study area, Colorado 1996-1997. Days between opening dates Treatment effect: (late treatment - early treatment) Year effect: (1997 - 1996) Area effect: (south area - north area) Days between mean dates of movement p 20 10±9 1 0 4±9 7±8 0.013• 0.346 0.100 • One-sided test Table 1.3. Differences between opening dates, least square mean differences with ±95% CI. and one-sided P-value for the null hypothesis of no difference between mean date of movement for radiocollared elk in the White River study area, Colorado 1996-1997. Treatment area North South Days between Opening dates 20 20 Days between mean dates of movement (late treatment - early treatment) p 14 ± 10 6 ± 15 0.006 0.218 �222 Table 1.4. Ranking of a priori (models 1-12) and post hoc (models 11-13) hypothesized models relating effects of year, area, opening of archery hunting season, and Julian day to daily proportion of radiocollared elk found on private land (p,) from 20 July to 10 October in the White River area, Colorado, 1996-1997. Models were ranked by QAICc values and normalized QAICc weights ( wm ). Model number b Kc QAICc AQAICc Wm 13o+13,(A)+l3i(S)+l3iD)+l3iAxD)+l3lSxD) 13 6 4718.68 0.00 0.495 13o+l31(A)+l32(S)+l3J(D)+l3iAxS)+l3£AxD) +l3 6(SxD) 12 7 4720.53 1.85 0.196 13o+l31(Y)+l3i(A)+l3J(S)+l3iD)+l3£YxA) +l3 6(YxD)+l3-;(AxD)+l3s(SxD)+l3g(YxAxD) 9 10 4721.92 3.24 0.098 13o+l3i(A)+l3i(S)+l33(D)+l3iAxS)+l3lAxD)+l3iSxD) +l3-;(AxSxD) 4 8 4722.42 3.74 0.076 13o+l31(Y)+l3i(A)+l3iS)+l34(D)+l3£YxS) +l3 6(YxD)+l3-;(AxD)+l3s(SxD)+l39 (YxSxD) 6 10 4723.37 4.69 0.048 13o+l3,(Y)+l3i(A)+l3iS)+l34(D)+l3£YxA) +l3 6(YxS)+l3-;(AxS)+l3s(AxD)+l3g(SxD) +l3 10(YxAxS)+l3 11 (AxSxD) 2 12 4723.57 4.90 0.043 13o+l3,(Y)+l3i(A)+l3iS)+l34(D)+l3iYxD) +l3iAxS)+l3-;(AxD)+l3 8(SxD)+l3lAxSxD) 3 10 4724.11 5.43 0.033 13o+l3,(Y)+l3i(A)+l3iS)+l34(D)+l35(YxA)+l3 6(YxS) +l3-;(YxD)+l3s(AxS)+l3g(SxD)+l3 10(Y xAxS) +l3 11 (YxSxD) 5 12 4726.6 7.92 0.009 1 13o+l31(Y)+l3i(A)+l3JCS)+l34(D)+l35(YxA)+l3 6(YxS) +l3-;(YxD)+l3s(AxS)+l3iAxD)+l3 10(SxD)+l3 11 (YxAxS) +l3 12(YxAxD)+l3 13(Y xSxD)+l3,◄<AxSxD) +l3 15(YxAxSxD) 8 130+131 (Y)+f3i(A)+l3J(S)+l34(D)+l3 5(YxA)+l3 6(Y x S) +l3-;(YxD)+l3s(AxS)+l3iAxD)+l3 10(Y xAx S) +l3 11 (YxAxD) 16 4730.41 11.74 0.001 12 4733.36 14.68 0.000 Model structure • 130+131 (A)+l32(Y)+f3 3(D)+13 i Ax Y)+l3£AxD) +l3 6(YxD)+l3-;(Ax Y xD) 10 8 4745.57 26.89 0.000 13o+l31(Y)+f3i(S)+l33(D)+l34(YxS)+l3 5(Y xD)+l3 6 (SxD) +l3-;(SxYxD) 7 8 4845.74 127.07 0.000 4855.07 136.39 11 4 0.000 13o+l3i(S)+l32(D)+l3J(SxD) • Y represents year with 1996 = 0 and 1997 = 1, A represents treatment area with south area= 0 and north area= 1, S represents archery hunting season with 0 = before opening and 1 = after opening, and D represents the covariate date, which is Julian day. The dependent variable (p,) was in logit scale. b Numbers correspond to those in Table 1.1 c Number of estimable parameters. �223 Table 1.5. Model-averaged estimates of hunt season effect represented by the difference of proportion of radiocollared elk on private land immediately before and after opening day and 95% confidence intervals; White River area, Colorado, 1996-1997. rrreatment Area 1997: North -early 1996: North - late 1996: South - early 1997: South - late Estimated oronortion of elk on orivate land Immediately Immediately Difference 95%CI after oneninv; of difference before oneninv; 0.095-0.257 0.408 0.584 0.176 -0.001-0.158 0.542 0.621 0.078 0.089-0.231 0.256 0.416 0.160 0.317 0.416 0.099 0.028-0.170 Table 1.6. Mean proportion ofradiocollared elk on private land during 1996-1997 for each treatment area in the White River area, Colorado, at the beginning (19 July) and end (10 October) of the stud.y period. Mean proportion of elk on private land 1996-1997 Treatment area North South July 19 0.200 0.161 October 10 0.636 0.393 Change 0.436 0.232 95% CI of change 0.296-0.577 0.105-0.360 �224 t N km 0 .~ ra........ . ... I 10 20 BLM Land Flat Tops Wilderness GMU Boundaries J$ State Wildlife Land D study Area Boundary II Forest Service Land White River .• Towns Colorado Figure 1.1. Alleged elk movements from high elevation public land to lower elevation private land, and land ownership in the White River study area, Colorado. 7000 - 6000 C 5000 ~ (I) C ,,. - . -.... :::, .c 0 ' u, cu (1) u, 4000 I >, "C cu 3000 0 2000 (1) L.. (1) .a § 1000 z 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 Year * Variance estimates not available 1984-1987. Figure 1.2. Number of archery and muzzleloading hunters using GMUs 12, 23, 24, and 33 in northwest Colorado, 1984-1994. Data from Deer, Elk, and Antelope Management (DEAMAN) database and software, Colorado Division of Wildlife, unpublished data. �225 t N .I! BLM Land fiffl Flat Tops WIiderness ~ State WIidiife Land D Study Area Boundary km 0 10 20 ■· Forest Service Land • Elk Capture Locations •· Towns Figure 1.3. North and south treabnent areas and July 1996 elk capture locations in the White River study area, Colorado. �226 Early Opening Late Opening a C 0.9 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 "'C C ca Q.) ca > ·c: 'J••--- •• ! -~- ·······-··· .'!.------------- ♦----- •.•. South 96 <X) ~ ;::: C. C !12 Opening date 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Opening date ~ ~ cc ~ North 97 Cl) II) ~ ;:::: 0 ~ Q) 0 C 0 :e0 C. e a.. b d 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Opening date North 96 Cl) Opening dale ------♦-- ......... -----·-•-·-•·· South 97 Cl) I() I() ;:::: ~ ~ i:: ~ ♦ Raw data Predicted --•95%CI Figure 1.4. Model averaged predicted values, 95% CI, and raw data of proportion ofradiocollared elk on private land versus date for (a) early treatment on the south area 1996, (b) early treatment on the north area 1997, (c) late treatment on the north area 1996, and (d) late treatment on the south area 1997, July-October in the White River study area, Colorado. �227 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 a Earl!' opening filled curve\ ■ •••• ■ ~ • ■ • I .I:. ■ •••• • ■ ■ •■ ~- -■•• • -■ ■ ■ ■ ii Late opening • Early opening Late opening fitted curv ----CX) IC) T"" CX) IC) T"" N CX) CX) T"" ...... ...... 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 CX) N --- 0) ~ ~ CX) CX) IC) N 0) T"" T"" 0) 0) co 0) - <-> 0 0 ~ 0) T"" 0 T"" T"" Date b ■ Late opening • Early opening Early opening fitted curve ■ • CX) IC) T"" ~ j:::: • • ••• ■ • ■ •• ■ .. - T"" CX) CX) a> IC) T"" CX) ■ N •• ■ - -- ■ ■ ■ • ■ ■ - -■ - •• ■ \ Late opening filled curve 0) !!? 0) ~ ~ Date -N 0) T"" T"" 0) 0) co ~ 0) <-> 0 T"" 0 T"" 0 T"" Figure 1.5. Model averaged predicted values and raw data of proportion of radiocollared elk on private land versus date for (a) north-treatment area and (b) south-treatment area during July-October 1996-1997 in the White River study area, Colorado. 1600 ~ - - - - - - - - - - - - - - - - - - - ~ -Soulh early 1996 Early opening Late opening -c. ._as 1400 --North early 1997 E ·-····· South late 1997 >- -c 1200 CD ~ 1000 (I) g 800 (ti .., -~ "'C ~ 'iii "'C C (ti (I) 600 400 200 :::E 0 co ..... ..... ,..._ I() ('.I ..... ,..._ ..... ..... co co ..... co I() ..... ..... co as ('.I ..... oi 0) ..... ..... 0) (0 ~ ~ 0 ..... 0 ..... 0 ..... Date Figure l.6. Mean distance moved per day by radiocollared elk during July-October 1996-1997 in the White River study area, Colorado. �230 �231 CHAPTER 2: EFFECT OF HUNTER DENSITY ON ELK MOVEMENT TO PRIVATE LAND IN NORTHWEST COLORADO INTRODUCTION Animals may modulate their response to stimuli depending on the quality, quantity, context, and intensity of the stimuli. Prey species, such as elk (Cervus elaphus), may show responses to varying densities of predators, such as hunters. Elk may increase their use of a refuge to avoid hunters; that is, as the density of predators increases, so too does the probability that elk are found in a refuge area. Or, elk may ignore hunters at low densities, and move to refuge areas only when hunter densities increase above some tolerance and danger threshold. To avoid hunters, elk have moved to refuges in national parks (Altmann 1956, Martinka 1969), private land (Wright 1983, Chapter 1), or densely vegetated areas (Irwin and Peek 1979, Morgantini and Hudson 1979) adjacent to their typical areas of activity. However, little research as been done on general elk responses to differing levels of hunter pressure, and no research has directly evaluated the effects of hunter density on elk use of refuge. Since the 1960s, the number of early-season (archery and muzzleloading) hunters using the White River area of northwest Colorado has grown, with especially significant increases between 1984 and 1992 (Fig. 2.1, DEAMAN, Colorado Division of Wildlife, unpublished data). Typically, archery hunters did not hunt private lands; thus, private lands provided elk a refuge during early-season hunts. As archery and muzzleloading hunter numbers increased, so too did complaints about early elk movements onto private land. For the Colorado Division of Wildlife (CDOW), the primary problem was herd size: it was difficult for CDOW to maintain or reduce herd size via harvest because hunters have limited access to private lands, (J. Madison and C. Reichert, Colorado Division of Wildlife, personal communication). Managers hypothesized that reduction of early-season hunter pressure, achievable through limiting licenses, would reduce movement onto private land. As part of an experiment about elk movement in response to early-season hunting activity, CDOW conducted an intensive hunter survey in the fall of 1996 and 1997. The study area was split into 2 treatment areas. A telephone survey of early-season hunters was conducted to estimate the daily number of hunters using each treatment area with a 95% confidence interval of ±150 hunters (total confidence interval of300 hunters). I used these data, along with elk location data, to determine how the density of early-season hunters affected elk movement to private land. My objectives were to: (1) summarize hunter survey data and provide estimates of hunter numbers, hunter-days, and mean days hunted per hunter by treatment area, Game Management Unit (GMU), hunt code, and day, (2) compute these estimates for hunters using ATVs, and (3) evaluate the relationship between hunter density and elk movement to private land. I used logistic regression and Akaike's Information Criteria (AIC) model selection (Burnham and Anderson 1998) to evaluate the relationship between hunter density and elk movement to private land. STUDY.AREA The White River area of northwestern Colorado covered approximately 4,540 km2 and was composed of Game Management Units (GMUs) 12, 23, 24, and 33. In Colorado, GMUs were delineated to distribute hunters through allocation of hunting licenses. White River area land ownership was 34% private land and 66% public land (Fig 2.2), with 82% of public land being United States Forest Service (USFS). USFS land was mostly at high elevation and toward the center of the study area, with some Bureau of Land Management (BLM) areas at lower elevations in the southern sections of the study area. Private land was lower in elevation and comprised mainly ranches and coal mines. Topography, climate, and vegetation varied widely throughout the study area. Elevation ranged from 1,629 to 3,700 m. The central part of the study area was high elevation public land, split by the White River valley. The high elevation areas dropped off to lower elevations to the north, south, and western edges of the study area. Higher elevations had severe winters with heavy snowfall, while lower elevations had comparatively mild winters. Mean annual precipitation at 3,000 min the National Forest areas was about 100 cm, compared �232 with about 30 cm at lower elevations of <2,000 m. Vegetation types at elevations >2,600 m were in the montane/subalpine zone and included groves of aspen (Populus tremuloides), Engelmann spruce (Picea engelmanni), and alpine fir (Abies lasiocarpa) interspersed with grassy meadows. Middle elevations (1,9802,600 m) were a transitional zone that consisted primarily of pinion pine (Pinus edu/is),juniper (Juniperos scopu/orum), and big sagebrush (Artemisia tridentata). Lower elevations (<2,000 m) in the southern and northern parts of the study area were in the Great Basin zone with sage grasslands. Oakbrush patches were found at the middle and lower elevations with major shrubs that included Gambel's oak (Quercus gambelii), servicebeny (Amelanchier alnifolia), mountain mahogany (Cercocarpus montanus), chokecherry (Prunus virginiana), snowberry (Symphoricarpos utahensis), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus nauseosus). Higher and middle elevation areas provided summer and fall forage for elk, while lower elevations were typically used by elk during winter. Boyd (1970) provides a detailed description of the study area Hunting for large game was economically important to local residents in the study area (Gray et al. 1994). Guides, outfitters, local service sectors, and private landowners (who sell trespass perm.its) made a large proportion of their annual income during the elk and deer hunting seasons, with most hunting revenues accrued during rifle hunting season METHODS Radio-telemetry Data Collection As part of a study on effects of early-season opening date on elk movements to private land, the study area was divided roughly east-west into 2 halves along the White River and North Fork of the White River (Fig. 2.2). GMU 12 and parts of GMUs 23 and 24 composed the north treatment area, while GMU 33 and parts of GMUs 23 and 24 composed the south treatment area. Two treatments were applied: an archery season that opened 1 week earlier, and another that opened 2 weeks later than normal, yielding a 3-week difference in opening dates. Each area received both an early- and late-opening treatment During the first year of the study, the early-opening treatment was randomly assigned to the south treatment area. Treatments were reversed the second year of the study. Thus, in 1996, archery hunting opened early, 24 August, in the south area, and late, 14 September, in the north area. When treatments were reversed in 1997, archery hunting opened early, 23 August, in the north area, and late, 13 September, in the south area. Archery season was 4 weeks long during the earlyopening treatment and 3 weeks long during the late-opening treatment. Muzzleloading season was 1 week long and nested within archery season. Opening of muzzleloading season coincided with opening of archery season for the late-opening treatment, and occurred on the third weekend during the early-opening treatment. The 80 adult female elk used in this study were captured from random locations throughout the study area. Chapter 1 describes capture and collaring procedures in detail. Elk locations were collected 20 July-10 October 1996-1997. I relocated radiocollared elk between 0700-1500 hr using a Cessna 182 or 185 fixed-wing aircraft with a 2-element Yagi antenna mounted to each strut of the airplane. For each elk relocation, Universal Transverse Mercator (UTM) coordinates were recorded with a Global Positioning System that was not differentially corrected. During the early-season hunt, I collected elk locations 2 times a week with 2-4 days between collections. A Geographical Information System (GIS) map was used to record elk locations, land ownership, and treatment boundaries. The GIS map was digitized from a United States Geological Survey map at a scale of 1:100,000. For each location of a telemetered cow, a Owas assigned if the location was on public land (e.g. Flat Tops Wilderness Area, USFS, State Wildlife, and BLM lands) and a 1 was assigned if the location was on private land. Hunter Survey Data Collection Number of archery and muzzleloading hunting licenses for elk and deer in 1996 were based on the mean number calculated from 1990 - 1994 (4,985; Colorado Division of Wildlife unpublished data). Restricting licenses kept hunter density consistent during the study and consistent with years of high elk movement complaints. In the fall of 1996 and 1997, after archery and muzzleloading season ended, CDOW conducted a �233 telephone survey with a goal of sampling enough hunters to estimate the number of hunters afield on any day with a 95% confidence interval of ±150 hunters (total confidence interval width= 300 hunters; Appendix 1). Sample size was based on the binomial distribution and was conservative. That is, the maximum variance occurs when 50% of the license holders hunt, and enough license holders were surveyed to meet the ±150 hunters confidence interval under this condition. CDOW conducted the telephone survey following protocols typically used to collect hunter data. The sample was a simple random sample. The initial sample size was larger than required, with an expectation that 70-90% of hunters called will respond with a complete survey. If this requirement was not met, then additional hunters were again randomly chosen from those not sampled the first time. The survey began as soon as the hunting season closed, and continued for approximately 4 months. Telephone surveys have been found to provide valid estimates of harvest and days hunted (White 1993, Steinert et al. 1994). Hunt codes: D-E-012-01-A E-E-012-01-A E-F-012-01-M E-M-012-01-M D-M-012-01-M D-E-033-01-A E-E-033-01-A E-F-033-01-M E-M-033-01-M D-M-033-01-M - archery deer, either sex, on north area, - archery elk, either sex, on north area, - muzzleloading elk, cow, on north area, - muzzleloading elk, bull, on north area, - muzzleloading deer, buck, on north area, - archery deer, either sex, on south area, - archery elk, either sex, on south area, - muzzleloading elk, cow, on south area, - muzzleloading elk, bull, on south area, and - muzzleloading deer, buck, on south area, were surveyed. Hunters that purchased two licenses on the same treatment half (e.g. D-E-012-01-A and E-E012-01-A) were counted as one hunter and were proportionally assigned to hunt-code groups. The number of individuals purchasing licenses was the size of the statistical population sampled for estimates, and was used in all estimates of hunter number, hunter-days, and average days/hunter. Hunters were asked: 1. 2. 3. 4. 5. 6. 7. License identification number, Hunt code; If they hunted or did not hunt; In which GMUs they hunted; How many days they hunted per unit; If they hunted on day I, on day 2, on day 3, etc. of the 7season; and If they used an ATV. From these data, 3 categories of information were estimated for hunt-code group, treatment area, and GMU: Number of hunters that hunted and number of hunters that used ATVs; Number of hunters afield per day, and number of hunters with ATVs afield per day; and Number of hunter-days and average number of days in the field per hunter and per hunter using an ATV. The following notation is used in estimator formulas, with i, j, k, /, and m indexing the group for which the estimator is being used: i .. .., . j k I m - - day (day I is opening day, day 2 is 2nd day of the season etc.), "."' hunt code group (north treatment area contained hunt code groups: DE01201A, DM01201M, EE01201A, EF01201M, EM01201M; south treatment area contained hunt code groups: DE03301A, DM03301M, EE03301A, EF03301M, EM03301M), GMU (12, 23, 24, or 33), individual hunter, and treatment area (north or south half of study area). �234 For example, H;m is the estimated number of hunters afield on day i in treatment m, H;1cm is the estimated number of hunters afield on day i in GMU k, treatment area m, H1an is the estimated number of hunters that hunted in GMU k, treatment area m, etc. Additional notation is: N - N' - n I n - a - Number of individuals purchasing licenses, Number of licenses sold, Number of license holders surveyed who responded with at least partial infonnation, Number of license holders surveyed who reported hunting, fr - Number of license holders surveyed who reported hunting with an ATV, Estimated number of hunters, Estimated number of hunters using ATVs, Number of hunter-days reported for surveyed hunters, Number of hunter-days reported for surveyed hunters using ATVs, Number of hunter-days reported for surveyed hunters in a particular GMU, Estimated number of hunter-days, .. . Estimated number of hunter-days for hunters using A TVs, d f p - Mean number of days afield per hunter, Mean number of days afield per_ hunter using an A TV. Estimated probability that a license holder hunted, and r - Estimated probability that a license holder hunted with an A TV. H A d f u - D - Day i, hunter/, and A TV use were entere~ as~ or I. For example,. if a surveyed license holder hunted, then a I was entered, or, if they did not hunt, then a 0 was entered. Similarly, if a hunter hunted on.day i, then a I was entered, or, if the hunter did not hunt, then a 0 was entered for that day. If a hunter used an ATV . . .. then a I was entered, and the hunter was assumed to use the A TV every day hunting. The finite correction fact?r, (N~~ n) , was used for all estimates. N~te that N' was used in the finite correction because each - license, and not individual, was randomly sampled. Thus, a license holder purchasing 2 licenses could be interviewed for 0, I, or 2 of the licenses. The number of licenses sold varied between I 50-1,219 by hunt code and the finite correction factor varied between 0.45-0.72 (Table 2.4 and 2.5). The 95% confidence intervals were constructed similarly for all variables, e.g.: ii ±t.96.Jvar<.il> , or, where sample sizes were <100, the appropriate t-statistic was used in lieu of 1.96: Estimating Number of Hunters Estimates of number of hunters (if) and their associated variances were calculated for each hunt code group (J) separately, then summed over hunt~ode groups{/) for treatment (m) or GMU (k). The number of hunters from hunt code group (j) that hunted in treatment area (m) was estimated: �235 5 ii m = L ii J , and J=I 5 var(ilm) = L var(il1). J=I Similarly, the number of hunters using ATVs (A) from hunt code group (J) that hunted treatment area (m) was estimated: .~pf;·>= ""'' 1 (N'- -n-) r-(l-r-) J J J J N' ' ni J 5 Am= 2..,A1, and J=l 5 var(Am) = 2.., var(AJ). J=l The number of hunters (ii) from hunt code (J) that hunted in GMU (k) and treatment area (m) was estimated: " n'.k J PJk = - , ni :;...1· Va,.\Pjk ) = (N'-J -n J·) p" J·k(l-p"J-k) , N1 5 ii km = "I.., ii Jk , and J=I n1 �236 s L var(H jk). var(H km)= j=I Similarly, the number of hunters with AlVs (A) from hunt code (j) that hunted in GMU (k) and treatment area (m) was estimated: :;.~A Vcu\rjk ) = (N'-J -nJ·) r-k(l-r-k) J J I Nj nj s A1an = LAjk , and j=I var(Akm) = s L var(A jk). j=I Estimating Number of Hunters Afield per Day Estimates of total number of hunters (if) afield per day(,) and their associated daily variances were calculated for each hunt code group(/) separately, then summed over hunt code groups (j) for treatment (m) . . . . or GMU (k). The number of hunters afield on day (,) within treatment (m) was estimated: A s A H;m = LHij, and j=I var(H;m) = s L va.r(H ij). j=I Similarly, the number of hunters afield using AlVs ( A ) on day(,) within treatment area (m) was estimated: �237 a-I] r.--=1] , A nj var(r--) = (N'- -n -) r--(1-r--) J ~ J I] N'- IJ J I] nJ 5 ~ Aim= LAij ,and j=l 5 var(A;m) =}:: var(Aij). j=l The number of hunters(/) afield (ii) on day(,) in GMU (k), treatment area (m) was estimated: n.::.. i:.Pijkl l=l Pijk = - ' - - - - ' - - nj var(H ijk) = var(N j Pijk) = NJ var(Pijk), ~ 5 ~ Hil,m = L Hijk, and j=l 5 var(Hikm) = L var(H ijk). j=l Similarly, the number of hunters (l) using ATVs ( A ) afield on day (I) in GMU (k), treatment area (m) was estimated: �238 A A;1cm = 5 L Aiik , and A j=l s var(A;km) = L var(Aijk) j=l Estimating Mean Number ofDays per Hunter and Hunter-days - A Estimates of mean days afield per hunter ( d ) and total hunter-days ( D ), and their associated variances were calculated for each hunt code group (j) separately. For each hunt code group (J), mean days afjeld per hunter ( J ) was assumed to be independent of the proportion of license holders that hunted ( p). Estimates of mean days afield per hunter by treatment and GMU were calculated directly, and associated variances were summed over hunt code groups (j) for treatment (m) or GMU (k). The mean days afield per hunter and total number of hunter-days were estimated for hunters (l) from hunt code group (j) that hunted treatment area (m): nm Ldml -dm_-l=l --,-, nm - var(d m) = Ls var(d- j), J=l �239 5 A A Dm=L,Dj,and j=l 5 r, var(i> j). var(i>m) = j=l Similarly, for each hunt code group (j), mean days afield per hunter using an ATV ( j) was assumed to be independent of the proportion of license holders that hunted (; ). The mean days afield per hunter using an ATV ( j ) and total number of hunter-days with ATVs (ft) were estimated for hunters ({) from hunt code group (J) that hunted treatment area (m): F'_j =Ajfj =N/j/j, var(Fj) = var(N j1'j - var(/m) = 7j) = NJ f/ var{] j)+ 7/ var(rj )-(var(rj)var(/ ))], L5 var(/- j) , j=I A 5 A Fm= LFj ,and j=l 5 var(Fm) = L var(Fj) . j=l For each hunt code group (J), mean days afield per hunter ( d ) was assumed to be independent of the proportion of license holders that hunted ( p ). Mean days afield per hunter ( d) and total number of hunter-days ( D) were estimated for hunters ({) from hunt code group (J) that hunted GMU (k) and treatment area (m): �240 - 5 ~ var(d Jan)=}: var(djk), j=I 5 D1an = I, b jk , and j=I 5 var(D1an) = L var(D jk). j=I Similarly, for each hunt code group(/), mean days afield per hunter using an ATV(]) was assumed to be independent of the proportion of license holders that hunted ( r ). Mean days afield per hunter([) using an A TV ( J) and number of hunter-days using ATVs (fr) were estimated for hunters that hunted GMU (k) and treabnent area (m): ijk/ = fjl Pk/, �241 5 A Ljjkajk j=I ~ f1an=--s-"'iajk j=I s A var<}Jan)= A L var<}jk) · j=I s F1an = Iftjk , and j=I s var(F1cm)= Ivar<ftjk)j=I �242 Elk Movement versus Hunter Density I used logistic regression models to evaluate the effects of hunter density on elk movement to private land. The response variable representing elk movement to private land, proportion of elk on private land on day ; (v;), was calculated from elk location data (each elk location was classified as public or private land). Hunter density was the estimated density of hunters afield on day;, in hunters/km2 . Hunter density was not an exact measurement, rather it was an estimate with an error term. Typically, using a predictor variable with an error term results in the regression coefficient biased toward z.ero (Fuller 1987). That is, I would be less likely to detect an effect of hunter density than actually existed. However, if the variance of the predictor variable (hunter density) is large compared to the variance of the estimates, then the effect of the error in the predictor variable can be effectively ignored during regression analysis (Draper and Smith 1966). The variance of hunter density (0.0098) was large compared to the variance of the estimates (maximum variance= 0.0002); hence I ignored the error in hunter density. Because this experiment was not designed to manipulate hunter density, I used model selection to evaluate the effect of hunter density beyond other possible confounding factors. I previously built an extensive suite of models to evaluate the effects of hunt season opening on elk movement to private land (Chapter 1, Table 1.1 ). Instead of generating another long list of models, I began with the 2 best models from the existing set (Chapter 1, Table 1.4, Models 12 and 13); these 2 models were <2 QAICc units from each other and were competing models (Table 2.1, Models 1 and 2). My main goal was to evaluate the effect of hunter density on elk movement to private land, and compare this effect to hunt season opening. I replaced Julian day with hunter density to evaluate whether hunter density was a better predictor of elk on private land on day i than Julian day (Table 2.1, Models 3 and 4). To evaluate the importance of hunt season opening compared to hunter density, I first removed hunt season from Model 3, and then removed hunter density (Table 2.1, Models 5 and 6). Although treatment models did not work well predicting the proportion of elk on private land in the study manipulating opening date, I hypothesized that treatment may provide more information when hunter density was included in a model because hunter density patterns varied between earlyand late-opening treatments. To evaluate this idea, I added treatment to the best model that included hunter density (Table 2.1, Model 7), and replaced area with treatment (Table 2.1, Model 8). Finally, evaluate whether the cumulative interaction with hunters caused elk to move to private land, I replaced hunter density with cumulative hunter density in the best model that included hunter density (Table 2.1, Model 9). Note that none of these models were strictly a priori because I began with previously run best models and built from these best models. I followed the methodology of Burnham and Anderson (1998) to select an appropriate model. I used Akaike's Information Criterion (Akaike 1973), adjusted for overdispersion and corrected for small sample bias (QAICc), as the basis for objectively ranking models and selecting an appropria~l'best approximating" model (Burnham and Anderson 1998). QAICc was defined as: QAICc =- 2~l) + 2K + 2K(K +1), c n-K-1 where In l is the natural logarithm of the likelihood function evaluated at the maximum likelihood estimates for a given model, K is the number of estimable parameters from that model, n is sample siz.e, and cis the estimated overdispersion factor. QAICc was used instead of AICc because repeated measurements were taken on radiocollared elk. Lack of independence in the data, in this case repeated measures on elk, may lead to rr.,, overdispersion or "extra-binomial variation" (Burnham and Anderson 1988). I estimated the overdispel'$.ion ,, ,~ parameter ( c) from the global model, and then used this estimate to adjust (inflate) the variance estimates of model parameters and predicted values, and to calculate QAICc for all the models (Burnham and Anderson 1998). Parameter estimates, c, and QAICc values were calculated using PROC GENMOD (SAS Institute 1993). The sample siz.e, n, was the number of elk locations collected during the study period. �243 The best approximating model was selected based on minimum QAIO::. Models were ranked and compared using AQAIO:: (Leberton et al. 1992, Burnham and Anderson 1998) and normaliz.ed QAIO:: weights (Buckland et al. 1997, Burnham and Anderson 1998). For the suite of models being compared, AQAIO:: was computed for each model as: AQAICc., = QAICc., - QAICc.,,n . where QAIO::. was the QAIO:: value for the mth model and QAIO::""" was the minimum QAIO:: among the suite models being compared. Essentially, AQAIO::,.. is an estimate of the distance between the best approximating model and model m. Normaliz.ed QAIO:: weights (w.) were estimated for each mth model: __!_ An AICc A e 2"""'< - Wm = - - - 1- - - , R --AQAICc I;e 2 r r=l where R refers to the R models chosen for evaluation. AQAIO:: and normaliz.ed QAICc weights were used to· address model selection uncertainty. Generally, models within l-2 QAIO:: units of the selected model were considered competing models for explaining elk movements to private land. RESULTS Hunter Survey Data CDOW surveyed 35-36% of early-season hunters using the study area in 1996 and 1997. Early-season hunters were 77% archers and 23% muzzleloaders. Estimates of hunter use with and without ATVs are provided by treatment (fable 2.2) and GMU (fable 2.3). Estimates are provided by hunt code for 1996 (fable 2.4) and 1997 (fable 2.5). The estimated number of hunters afield per day and number of hunters using ATVs are shown with their 95% confidence intervals by treatment (Fig. 2.3) and GMU (Fig. 2.4). In 1996, daily information was collected for 23 days for each hunter, although hunting season extended 30 days during the early-opening treatment Therefore, 1996 graphs of the south area, where hunting opened early, show only the first 23 days of the season. In 1997, the survey was changed to collect information on hunter use for the entire 30-day season. Appendix 2 contains confidence intervals for daily GMU data. Elle Movement versus Hunter Density The best logistic regression model with the lowest QAIO:: value (fable 2.6, Model 1) was: This was the best model from the manipulative experiment and did not have a hunter density covariate. In fact, the first model with a hunter density covariate was 35.2 QAIO:: units from the top model (fable 2.6, Model .9), and the hunter density regression coefficient was not significantly different than zero in any of the models in which it was included. Model 9, with cumulative hunter density preformed similarly (AQAIO:: < 2) to its counterpart, Model 6 with straight hunter density (Table 2.6). Model 5, with hunter density, preformed poorly (AQAIO:: >> 2) compared to its counterpart, Model 6, with hunt season replacing hunter density (fable 2.6). �244 DISCUSSION By design, hunter use of the study area was constant from year to year and between treabnent areas. However, the daily pattern of use was different for early- and late-opening treabnents. When hunting opened early, hunter use was relatively constant. There were several small peaks coinciding with each weekend during the season, and one larger peak coinciding with the opening of muzzleloading season. When hunting opened late, there was a large peak on opening weekend, partially because muzzleloading season opened with archery season. The late treabnent peaked at higher densities of hunters (0.44-0.50 hunters/km2) compared to the early treabnent (0.28-0.36 hunters/km2). Several hunting studies indirectly provide insight about elk responses to different levels of hunting pressure. Wright (1983) examined elk response to different hunting seasons: archery and muzzleloading, versus 3 different types of rifle hunting seasons. Distances traveled by elk increased with hunter density, and were lowest during archery and muzzleloading season when hunter densities were the lowest. Although hunting method and hunter density were confounded, elk response to hunter density remains a possible explanation for increased elk movements. An earlier study in the White River area, designed to evaluate elk movement onto a coal company's protected land during early-season hunting, found that 13% of the radiocollared elk were on private lands midway through archery and muzzleloading seasons (Camp Dresser and McKee, Inc. 1986). During this study, 50% and 53% of the radiocollared elk were on private land on the same day during 1996 and 1997 respectively. The lack of movement onto private land in the earlier study may be explained by a 63% reduction in archery hunters for that year because of a change in hunting regulations (Gray et al. 1994). Thus, elk movement to private land may decrease when hunting pressure drops. Finally, Zahn (1974), Lemke (1975), and Hershey and Legee (1982) noticed an increase in distances moved by elk during the first 10-12 days of hunting season, followed by normal movement during the remainder of the season. These authors noted that hunting pressure was heavy during the initial 10-12 day of hunting, and relatively light for the remainder of the season. Although all these hunting studies are observational, taken together a pattern emerges; at high hunter densities elk increase their movements to refuge, and at low densities they decrease their movements to refuge. However, there is a confounding between the effects of hunter density and the opening of hunting season opening. That is, the increase in distances moved by elk during the initial 10-12 days of hunting season (Zahn 1974, Lemke 1975, Legee 1982) could be due to high densities of hunters or to the opening of hunting season itself. Elk in the White River area seemed to respond more to the opening of hunting season than to hunter density. That is, models that included a hunt season effect did significantly better than models without hunt season effect (Chapter 1). In contrast, models with a Julian day covariate (fable 2.6, Models 1 and 2) preformed far better than models with a hunter density covariate (fable 2.6, Models 3-5 and Models 7-9). In fact, hunter density can not be considered as a predictor of proportion of elk on private land because models with hunter density were a minimum of35.2 AQAICc units from the top model. Additionally, at the opening of earlyseason hunting, 8-18% of the study elk moved to private land (Chapter 1), while after opening, elk movement to private land was not related to hunter density (Fig. 2.5). Thus, hunter density had no effect on elk movements to private land in the White River area. It may be that hunter density must exceed a threshold before elk begin to respond directly to hunters, and hunter densities did not surpass this threshold during the study. MANAGEMENT IMPLICATIONS If hunter density continues to be a suspected cause of increased elk movement to private land, then an experiment manipulating hunter density should be conducted. Managers concerned with reducing elk movements to private land have an opportunity to evaluate effects of hunting pressure when setting license numbers for a particular area. Additionally, increasing hunter density on private land where problems are occurring may be the most direct strategy to retain elk on public land during late summer. Whatever the management strategy, manipulation of hunter density offers managers a good opportunity to conduct an adaptive management experiment to increase information regarding the management of elk movements to private land. �245 LITERATURE CITED Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. Pages 267-281 in B. N. Petran and F. Csaki, editors. International symposium on information theory. Second edition. Akademiai Kiadi, Budapest, Hungary. Altmann, M. 1956. Patterns of herd behavior in free-ranging elk of Wyoming, Cervus canadensis nelsoni. Zoologica 41 :65-71. Boyd, R J. 1970. Elk of the White River Plateau, Colorado. Colorado Division of Game, Fish and Parks Technical Publication 25, Fort Collins, Colorado, USA Buckland, S. T., K. P. Burnham, and N. H. Augustin. 1997. Model selection: an integral part of inference. Biometrics 53:603-618. Burnham, K. P., and D. R Anderson. 1998. Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New York, USA Camp Dresser and McKee, Inc. 1986. Meeker PRLA elk migration study: monitoring report, volume 2. Prepared for Consolidation Coal Company. Camp Dresser and McKee, Inc., Denver, Colorado, USA. Draper, N. Rand H. Smith Jr. 1966. Applied regression analysis. Second edition. John Wiley and Sons, New York, New York, USA Fuller, W. A 1987. Measurement error models. John Wiley and Sons, New York, New York, USA Gray, J.P.; G. Byrne, and J. Madison. 1994. White River elk data analysis unit plan: game management units: l l,21 l,12,13,13 l,231,23,24,25,26,33. Colorado Division of Wildlife Internal Report, Grand Junction, Colorado, USA Hershey, T. J., and T. A Leege. 1982. Elk movements and habitat use on a managed forest in north-central Idaho. Idaho Department of Fish and Game Wildlife Bulletin 10, Boise; Idaho, USA Irwin, L. L., and J.M. Peek. 1979. Relationships between road closures and elk behavior in northern Idaho. Pages 199-204 in M. S. Boyce and L. D. Hayden-Wing, editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA Leberton, J-D., K. P. Burnham, J. Clobert, and D. R Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological Monographs 62:67118. Lemke, T. 0. 1975. Movement and seasonal ranges of the Burdette Creek elk herd, and an investigation of sport hunting. Montana Fish and Game Department Job Final Report 32.01, Job Number BG-3.15, Missoula, Montana, USA Martinka, C. J. 1969. Population ecology of summer resident elk in Jackson Hole, Wyoming. Journal of Wildlife Management 33:465-481. Morgantini, L. E., and R J. Hudson. 1979. Human distribution and habitat selection by elk. Pages 132-139 in M. S. Boyce and L. D. Hayden-Wing, editors. North American elk: ecology, behavior, and management. University of Wyoming, Laramie, Wyoming, USA SAS Institute. 1993. SAS/STAT® software: The GENMOD procedure, release 6.09. SAS® Technical Report P-243, SAS Institute, Inc., Caty, North Carolina, USA Steinert, S. F., H. D. Riffel, and G. C. White. 1994. Comparisons of big game harvest estimates from check stations and telephone surveys. Journal of Wildlife Management 58:335-340. White, G. C. 1993. Precision of harvest estimates obtained from incomplete responses. Journal of Wildlife Management 57:129-134. Wright, K. L. 1983. Elk movements, habitat use, and the effects of hunting activity on elk behavior near Gunnison, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Zahn, H. M. 1974. Seasonal movements of the Burdette Creek elk herd. Montana Fish and Game Department Job Final Report 32.01, Job BG-3.13, Missoula, Montana, USA. �246 Table 2.1. Description and representation of models relating effects of area, treatment, hunt season opening, hunter density, and Julian date to daily proportion ofradiocollared elk found on private land (v,) from 20 July-10 October in the White River area, Colorado, 1996-1997. Hypothesis Model structure • I. Lowest AICc model from the experimental manipulation of early-season opening date b 2. Second lowest AICc model from the experimental f3 0+f3 1 (A)+f32(S)+f3iD)+f3◄(AxD)+f3 5 (SxD) manipulation of early-season opening date b +f3iAxS) 3. Hunter density is a better predictor than Julian day - Model f3o+f3 1(A)+f3 2(S)+f3J(H)+f3.(AxH) I with hunter density replacing the Julian day covariate • 4. Hunter density is a better predictor than Julian day - Model f3o+f3 1 (A)+f32(S)+f3 3(H)+f3◄(AxH)+f3s(AxS) 2 with hunter density replacing the Julian day covariate • 5. Hunter density is a better predictor than hunt season hunter density and area effects only 6. Hunt season is a better predictor than hunter density - hunt season and area effects only 7. Treatment is an important effect when hunter density is a covariate - add treatment to best model with hunter density 8. Treatment is an important effect when hunter density is a covariate - replace area with treatment 9. Cumulative hunter density better predicts elk movement to private land - use best model that includes hunter density and replace the hunter density covariate with a cumulative hunter density covariate • A represents treatment area with south area= 0 and north area = I, S represents archery hunting season with O = before opening and I = after opening, D represents the covariate date, which is Julian day, and H represents the covariate hunter density on day i in hunters/km2• The dependent variable (v,) was in logit scale. b See Chapter I, Table 1.4. • SxH cannot be estimated because hunter density= 0 before hunt season opening. �247 Table 2.2. Number of licenses sold (N), percent surveyed (s), estimates of hunter numbers ( ii ), hunter-days ( f> ), mean days hunted/hunter ( J ), hunters using ATVs (A), hunter-days with ATVs (ft), and mean number of days/hunter using an ATV ( ] ), by treatment area during archery and muzzleloading season in the White River area l 996-1997. The half-width of the 95% confidence interval is shown for all estimates. fl b Dc 37.2 36.9 1,362 ± 25 1,786 ± 20 8,999 ± 390 10, 716 ±426 6.4 ± I.I 6.0 ±0.8 35.1 1,715 ± 30 10,920 ±455 6.2 ± 1.0 Area Year N• s North 1996 1997 1,711 2,170 1996 2,253 South d A F 209 ± 34 1,555 ± 314 7.2 ±4.1 329 ± 45 2,134 ±392 6.4 ± 2.1 f 300 ±40 2,205 ± 380 7.1 ±2.8 1997 2,090 33.2 1,679 ± 26 11,128 ± 419 6.4 ± 0.9 258 ±40 2,083 ±408 7.6 ± 2.5 • Because some individuals purchased 2 licenses, the number of individuals purchasing licenses, which was used in all estimates, was slightly less than the number of licenses sold. b The estimated number of hunters is lower than the number oflicenses sold because some hunters purchasing licenses did not hunt and because some hunters purchased 2 licenses. c Estimated number of hunter-days and hunter-days with AlVs are sums of estimated hunter-days by hunt code (fables 2.4 and 2.5), and not the direct product of estimated number of hwiters x mean number of days/hunter. Table 2.3. Estimates of hunter numbers (fl), hunter-days (D ), mean days hunted/hunter (d), hunters using ATVs (A), hunter-days with ATVs (F), and mean number of days/hunter using an ATV(]), by GMU during archery and muzzleloading season in the White River area 1996-1997. The half-width of the 95% confidence interval is shown for all estimates. fl• Db F Year Area GMU J A Jc North 12 22 23 773 ±48 1,014 ± 58 437 ± 44 533 ± 52 291 ± 38 426 ±49 4,842 ± 441 6,295 ±484 2,653 ± 355 3,274 ± 483 1,504 ± 277 2,425 ± 401 6.0± 1.8 6.0± 1.2 5.8± 2.0 5.9± 2.2 5.0±2.5 5.3 ± 1.8 74 ±22 117 ± 30 104 ± 25 162 ± 33 75 ±21 102 ± 26 480 ± 181 571 ± 173 676 ±212 1,092 ±333 399 ± 154 643 ±296 6.3 ±7.1 5.0 ±3.1 6.3 ±4.7 6.3 ±3.5 5.3 ±7.5 5.8 ±3.9 1996 3,893 ±409 151 ± 30 890 ±235 5.7 ±3.6 715 ± 53 5.3± 1.8 1997 700 ±201 6.0 ±2.6 494 ± 51 2,770 ±358 5.5 ± 1.9 111 ±28 4.5 ±4.5 23 1996 342 ± 170 3,272 ± 375 5.4± 2.0 75 ±21 600 ± 51 1997 8.5 ± 7.4 577 ± 53 3,514 ±417 5.9±2.4 21 ± 12 195 ± 308 1996 5.7±2.0 132 ± 28 974 ±287 6.9 ±4.8 33 638 ± 52 3,735 ±456 1997 143 ± 31 1,188 ±302 8.0 ±3.1 746 ± 56 4,843 ±452 6.3± 1.4 • All GMU estimates are slightly greater than treatment or hunt code estimates because some hunters hunted in more than oneGMU. b Estimated number of hunter-days and hunter-days with AlVs are sums of estimated hunter-days by hunt code, and not the direct product of estimated number ofhunters x mean number of days/hunter. c Because of the small sample sizes, a log-based confidence interval should be used in some cases so that values for the 95% CI of ] are >O. South 22 1996 1997 1996 1997 1996 1997 �Table 2.4. Estimates of hunter numbers (H ), hunter-days (D ), mean days hunted/hunter (d ), hunters using ATVs (A), hunter-days with ATVs (fr), and mean number of day0iunter using an ATV (] ), by hunt code during archery and muzzleloading season in the White River area 1996. The half-width of the 95% confidence interval is shown for all estimates. Percent of Number of NORTH AREA fr b H d A f licenses sold • hunters surveyed 241 32.0 D-E-012-01-A 663 ± 83 94 ±7 7.1 ± 0.7 18±8 139 ±67 7.6 ±2.0 32.5 E-E-012-01-A 973 874 ± 22 6,368 ± 367 7.3 ± 0.4 149 ± 31 1,198 ± 302 8.1 ± 1.1 51.5 165 E-F-012-01-M 647 ± 69 5.1 ± 0.4 126 ± 8 12 ±6 66±43 5.3 ±2.7 178 48.9 E-M-012-01-M 808 ± 61 4.8 ± 0.4 167 ± 3 21 ±9 103 ± 48 4.8 ± 1.3 46.8 D-M-012-01-M 154 513 ± 59 101 ± 7 5.1±0.4 8±5 50 ±38 6.0 ± 3.2 SOUTH AREA 30.6 526 380 ± 128 D-E-033-01-A 292 ± 13 1,849 ± 187 6.3 ±0.6 59 ± 16 6.4 ± 1.3 1,219 32.0 7,184 ± 400 E-E-33-01-A 1,056 ± 23 6.8 ± 0.4 194 ± 35 1,579 ± 352 8.1 ± 1.1 49.3 150 581 ± 55 16 ±7 E-F-033-01-M 4.8 ± 0.4 86 ±41 5.3 ± 1.0 122 ± 6 47.5 160 5,8 ± 0.4 E-M-033-01-M, 140 ±6 817 ± 70 16±8 93 ±50 5.9 ± 1.6 45.5 198 490 ±77 4.7 ±0.5 14±7 4.9 ± 1.9 D-M-033-01-M 105 ± 12 68±41 • Because some individuals purchases 2 licenses, the number of individual purchasing licenses was slightly less the number of licenses sold. The number of individuals purchasing licenses was used for all estimates. Table 2.5. Estimates of hunter numbers (H ), hunter-days (D ), mean days hunted/hunter (d ), hunters using ATVs (A), hunter-days with ATVs (fr), and mean number of days/hunter using an ATV (] ), by hunt code during archery and muzzleloading season in the White River area 1997. The half-width of the 95% confidence interval is shown for all estimates. Percent of Number of NORTH AREA fr b H "J A ] licenses sold • hunters surveyed 402 54.7 D-E-012-01-A 1,243 ± 63 205 ±5 6.1 ± 0.3 41 ±8 253 ± 57 6.3 ±0.8 1,277 27.9 E-E-012-01-A 1,193±16 7,456 ± 407 6.3 ± 0.3 1,540 ± 377 233 ± 42 6.6 ± 1.1 166 43.4 E-F-012-01-M 134 ± 8 686 ± 70 5.1 ± 0.4 31 ± 11 193 ± 73 6.1±1.0 180 48.3 E-M-012-01-M 850 ± 63 5;3 ± 0.4 160 ± 5 21 ±9 131 ± 60 6.2 ± 1.4 145 45.5 D-M-012-01-M 480 ± 53 94 ±6 5.1 ± 0.5 16 ± 17 5.0 ±0.0 3±3 SOUTH AREA 30.0 D-E-033-01-A 416 223±7 1,503 ± 119 6.8±0.5 43 ± 13 330 ± 118 7.7 ± 1.4 28.4 1,185 E-E-33-01-A 1,058 ±23 7,640 ± 388 7.2±0.3 166 ± 34 1,516 ± 386 7.1±1.2 147 48.3 E-F-033-01-M 121 ±6 584±56 4.8 ±0.4 17 ±7 73 ±34 4.3 ±0.6 155 49.0 E-M-033-01-M 139±4 711 ±57 5.1 ±0.4 55 ± 34 11 ±6 4.8 ± 1.6 D-M-033-01-M 187 46.0 138 ±7 689 ± 63 5,0·± 0,4 21 ±8 109 ±4 9 5, 1 ± 1.2 • Because some individuals purchases 2 licenses, the number of individual purchasing licenses was slightly less the number of licenses sold. The number of individuals purchasing licenses was used for all estimates. N +'- 00 �249 Table 2.6. Ranking of models relating effects of area, treatment, hunt season opening, hunter density, cumulative hunter density, and Julian day to daily proportion ofradiocollared elk found on private land (v,) from 20 July-10 October in the White River area, Colorado, 1996-1997. Models were ranked by QAICc values and normalized QAICc weights ( ww ). Model number b Kc QAICc AQAICc wm f3 0+f3 1(A)+f3 2(S)+f33(D)+f3.(AxD)+f3s(SxD) +f3iAxS) 1 2 6 7 3760.28 3762.26 0.00 1.97 0.729 0.271 f3o+f31(A)+f32(S)+f3iC)+f3.(AxC) +f3s(AxS) 9 6 3795.45 35.17 f3o+f31(A)+f32(S)+f33(Ax S) f3o+f31(A)+f32(S)+f3iH)+f3.(AxH) +f3s(AxS) 6 4 3 7 4 6 3796.29 3798.59 36.01 38.31 40.13 0.000 0.000 0.000 Model structure • f3 0+f3 1(A)+f3 2(S)+f3 3(D)+f3.(AxD)+f3s(SxD) 5 3800.41 0.000 3802.34 8 42.06 0.000 4 5 3867.39 107.11 0.000 f3o+f31(A)+f32(D)+f3 3(Ax D) 3897.96 8 6 137.68 0.000 f3o+f31m+f32(S)+f33(H}+f34(fxH) +f3s(fxS) • A represents treabnent area with south area= 0 and north area= 1, S represents archeiy hunting season opening with before opening= 0 and after opening= 1, T represents treabnent with early opening= 0 and late opening= 1, D represents the covariate date, which is Julian day, H represents the covariate hunter density on day i in hunters/km2, and C represents the covariate cumulative hunter density on day i in hunters/km2. The dependent variable (v,) was in logit scale. b Numbers correspond to those in Table 2.1 c Number of estimable parameters. f3o+f3.(A)+f32(S)+f3iH)+f3.(AxH) f3o+f31(A)+f3 2(S)+f3iH)+f3 4(f)+f3s(AxH) +f3iAxS) +(3-ifxH) - 7000 f! Q) ______ , C 6000 . ~ .c. C 0 5000 U) co Q) C{) 4000 >, 1a 3000 Q) 0 2000 L- Q) .c ~ z 1000 0 1984 1985 1986 1987 1988 1989 1990 199119921993 1994 Year * Variance estimates not available 1984-1987. Figure 2.1. Number of archery and muzzleloading hwiters using GMUs 12, 23, 24, and 33 in Colorado, 19841994. Data from Deer, Elk, and Antelope Management (DEAMAN) database and software, Colorado Division of Wildlife wipublished data. �250 11· BLMLand llJ: Flat Tops Wilderness a. 0 10 State Wildlife Area □ Treatment Area Boundary Km 20 -II Forest Service Land Figure 2.2. North and south treatment areas and land ownership in the White River study area, Colorado. �251 a C Early Opening 1,200 Late Opening 1,200 Opening of muzzleloading End of muzzleloading 1,000 1,000 800 -- "'C ai ii: cu 600 800 South 1996 1 ~ 600 400 ~ 400 Cl) .c 200 :::s 0 E C "'C scu ...,. ~ m .... ~ ....a;...,. ~ 0 .... a1 b .. _ -- -- -- -- -- .... a1 ....a;...,. m a1 ....~ ,.._ a.... d 1,200 1,000 1,000 w -- - - . - 200 •- ---- ·-·- ·------- --••••·- ::::::::::-- -- = - = , , ~ E 1,200 .....u, ·- North 1996 800 .. 600 800 North 1997 600 400 400 200 200 ------ ---- ---· ··-- ---- ·- 0 C') N cc "'• •'"' •• •• ------ -- ·· -- ....a; C') ....a; C') 0 a1 0 a1 a1 Date LEGEND Hunters Hunters using A TVs •••••••••••• 95%CI Figure 2.3. Estimated daily number of hunters and hunters using A TVs in the (a) south treatment area 1996, (b) north treatment area 1997, ( c) north treatment area 1996, and (d} south treatment area 1997, during archery and muzzleloading season in the White River area, Colorado. The first date is opening date. Each date shown represents a Saturday. 1 There is a break in estimates for the south area in 1996 because survey data were only collected for 23 out of the 3'0 days of the early treatment. The survey was extended to 30 days in 1997. ,.": �252 a 1,000 1.000 "O B 1 A 800 co ii= 1997 C 1996 600 600 400 400 .0 200 200 ::l 0 ...cu (1) E C - ... - - ..... ~ ~ Cl) "O ..... I::: oi 0 - Cl) !!! ~ ~ CJI C B C ~ d 1,000 A B 1 C A 800 I I 600 400 400 200 200 0 B 0 a, E 600 .., ~ a Jg b cu 1,000 800 A 800 C ·- ... --.... :.-:, ··--•.• ···~-~-::,... -.r CJI 0 a, ~ "' 0 .., ~ ---- .. a t! ID Date LEGEND -GMU12 ......... GMU 23 --GMU24 -GMU33 A Opening date of archery season on early-treatment B Opening date of muzzleloading season and archery season on late treatment. C Closing date of muzzleloading season. Figure 2.4. Estimated daily number of (a) hunters 1996, (b) hunters using ATVs in 1996, (c) hunters 1997, and (d) hunters using A TVs 1997, during archery and muzzleloading season in the White River area, Colorado. Each date shown represents a ~aturday. 1 There is a break in estimates for GMU 23, 24, and 33 in 1996 because survey data were only collected for 23 out of the 30 days of the early treatment. The survey was extended to 30 days in 1997. �253 CHAPTER 3: ELK LOCATIONS IN RELATION TO DOMESTIC SHEEP BANDS AND A METHOD TO TEST FOR AVOIDANCE OR ATTRACTION BE1WEEN ANIMALS INTRODUCTION Hearsay, accusation, tall tales, and rumor dominate the discussion about Rocky Mountain elk (Cervus elaphus nelsoni) movements in response to domestic sheep (Ovis aries). Elk movement responses to sheep are a concern of hunters, who feel that livestock grazing on public land is a disturbance that elk avoid Hunters claim that domestic sheep force elk away from public hunting areas and onto private land, but there is little documentation of elk responses to domestic sheep. In one study of elk and livestock grazing, Clegg (1994) found that elk densities decreased rapidly after introduction of sheep, herders, and dogs. However, the distance of impact was not recorded making it difficult to assess whether sheep could move elk away from public hunting areas. Most studies of elk and sheep have originated from livestock concerns and concentrated on dietary overlaps and forage competition (Pickford and Reid 1943, Nichols 1957, Stevens 1966, Olsen and Hansen 1977, MacCracken and Hansen 1981, Beck et al. 1996). In the White River area, elk and domestic sheep graz.e high mountain meadows. Approximately 26 bands of domestic sheep used the study area between May and October. Early-season hunting (archery and muzzleloading), which occurs between late August and mid-October, overlaps with sheep grazing. During meetings about elk movements in response to early-season hunting, archery hunters expressed concern that domestic sheep cause elk to move off public land to private land during the early season. As part of the stakeholder process, CDOW agreed to collect locations of sheep bands in the area when collecting locations of 80 radiocollared elk for an archery hunting study. My objectives were to (1) determine if elk avoided sheep at several spatial scales and (2) develop a methodology applicable to radio-telemetry data to evaluate attraction or avoidance between animals. I used location data from radiocollared elk and visual locations of sheep bands from the summer and fall of 1996 and 1997. The null hypothesis was that elk locations were random with respect to sheep locations. I used nonparametric statistics and randomization techniques to calculate, under the null hypothesis, the probability that elk avoided sheep. STUDY .AREA The White River area of northwestern Colorado covered approximately 4,540 km2 and was composed of Game Management Units (GMUs) 12, 23, 24, and 33. In Colorado, GMUs were delineated to distribute hunters through allocation of hunting licenses. White River area land ownership was 34% private land and 66% public land (Fig. 3.1), with 82% of public land being United States Forest Service (USFS). USFS land was mostly at high elevation and toward the center of the study area, with some Bureau of Land Management (BLM) areas at lower elevations in the southern sections of the study area. Private land was lower in elevation and comprised mainly ranches and coal mines. Topography, climate, and vegetation varied widely throughout the study area. Elevation ranged from 1,629 to 3,700 m. The central part of the study area was high elevation public land, split by the White River valley. The high elevation areas dropped off to lower elevations to the north, south, and western edges of the study area. Higher elevations had severe winters with heavy snowfall, while lower elevations had comparatively mild winters. Mean annual precipitation at 3,000 min the National Forest areas was about 100 cm, compared with about 30 cm at lower elevations of <2,000 m. Vegetation types at elevations >2,600 m were in the montane/subalpine zone and included groves of aspen (Popu/us tremuloides), Engelmann spruce (Picea enge/manni), and alpine fir (Abies lasiocarpa) interspersed with grassy meadows. Middle elevations (l,9802,600 m) were a transitional zone that consisted primarily of pinion pine (Pinus edu/is),juniper (Juniperus scopulorom), and big sagebrush (Artemisia tridentata). Lower elevations (<2,000 m) in the southern and northern parts of the study area were in the Great Basin zone with sage grasslands. Oak.brush patches were found at the middle and lower elevations with major shrubs that included Gambel's oak (Quercus gambelii), serviceberry (Amelanchier alnifo/ia), mountain mahogany (Cercocarpus montanus), chokecherry (Prunus �254 virginiana), snowbcrry (Symphoricarpos utahensis), bittcrbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus nauseosus). Higher and middle elevation areas provided summer and fall forage for elk, while lower elevations were typically used by elk during winter. Boyd (1970) provides a detailed description of the study area. USFS issued permits for sheep grazing on national forest lands on the study area. During the study period, approximately 26 bands of domestic sheep used the study area. Each band was assigned to a particular area called an allotment. Bands ranged in size from 750-1,350 sheep, and averaged approximately 1,043 sheep (95% CI= 981, 1,106; USFS unpublished data from 1992-1995). Band sizes are approximate because actual numbers were often less than permitted numbers (Mary Massey, United States Forest Service, Meeker Colorado, personal communication). Sheep arrived on the study area 16 June-I I July, and left 10 September-15 October. Herders and dogs stayed with the sheep bands and moved them through their allotment area. METHODS Data Collection The adult female elk used in this study were captured from randomly selected locations throughout the study area. Capture and collaring procedures are descried in detail in Chapter 1. Elk and sheep locations were collected 20 July-10 October 1996-1997. I relocated radiocollared elk between 0700-1~00 hr using a fixed-wing aircraft with a 2-element Yagi antenna mounted to each strut of the airplane. For each elk relocation, Universal Transverse Mercator (U1M) coordinates were recorded with a Global Positioning System. I collected elk locations 2 times a week with 2-4 days between collections. During each flight, the position of at least 1 sheep band was recorded. Because elk-sheep interactions were not the focus of the study, locations of sheep bands were opportunistically chosen. That is, I typically recorded the location of only one band of sheep seen and did not record any other bands, although up to 3 bands per day were sometimes seen. Thus, each band location was a sample of the population of 26 bands. Because I did not collect locations in a specific route each flight, the daily sample of sheep bands was fairly random (Fig. 3.1). Once a sheep band was seen, I flew over the band and recorded lITM coordinates at the approximate center of the band Data Analysis ·r r· All analyses were computed separately for each year. Distances between elk and sheep bands were calculated from UTM coordinates as straight-line distances. For each day a sheep band was located, I calculated the distance between the band and every radiocollared elk located that day. I called these paired distances because they were paired in time (same day). I then calculated the distance between the location of the sheep band, located that day, and the locations of each radiocollared elk located every other day. I called these unpaired distances because they were temporally unpaired During the study period, 20-23 locations were collected on each elk per year. Thus, for each elk, there was I paired distance and 19-22 unpaired distances for each day locations were collected. Note that there was no way to compute the variance on I measurement; hence paired and unpaired distances could not be compared using parametric methods. However, a rank representing the paired distance compared to the unpaired distances, between 1 elk and I sheep band, represents I sample. Thus, I used a ranking method to evaluate avoidance between elk and sheep bands. For each elk and each day locations were collected, I ordered distances, paired and unpaired, from smallest to largest, and assigned a ranking to each distance. That is, the smallest distance between a sheep band and an elk was assigned a 1, the next smallest distance a 2 and so on. Thus, for each elk and each day data were collected, there was a ranking of I to number of distances collected on that elk (Fig. 3.2). If elk were located randomly with respect to sheep bands, then paired distances·would be equal to unpaired distances, and the mean rank of paired distances would be equal to the mean rank unpaired rankings. If elk avoided sheep, then paired distances would be farther from sheep, on average, than unpaired distances, and the mean rank of paired distances would be significantly greater than the mean rank of unpaired rankings. Conversely, if elk were attracted to the sheep, then paired distances would be closer to sheep, on average, than unpaired distances, and the mean rank of paired distances would be significantly less than the mean rank of unpaired rankings (Fig. 3.3). This assumes that elk do not avoid an area where sheep were located after the sheep leave the area. �255 For each year, I extracted the rank of the paired distances for each elk and day that both the elk and sheep band were located, and calculated the mean ranking of the paired distances. The statistical expressions of the null and alternative hypothesis were: Ho: The mean rank of paired distances = the expected mean rank of unpaired ranks, and HA: The mean rank of paired distances> the expected mean rank of unpaired ranks, which tested the study hypothesis: Ho: Locations of elk were random with respect to locations of sheep; elk did not avoid sheep, and HA: Locations of elk were father to sheep than expected at random; elk avoided sheep. Note that it was possible that elk were attracted to sheep because sheep are graz.ed in areas preferred by elk for grazing, but this was not the question of interest. In order to evaluate the probability of the observed paired rank, I generated the distribution of paired ranks under the null hypothesis that elk and sheep were located randomly with respect to each other. To develop the null distribution, I randomiz.ed on sheep bands. That is, I randomly assigned a day to each sheep band. For example, a sheep band located on day 2, may be randomly assigned to day 6. After randomly assigning a day to each sheep band, paired and unpaired distances were calculated as described for the observed data. From each sample, I extracted the ranks of the randomly "paired" rank. From the collection of samples via the randomization procedure, I generated the distribution of mean ranks for paired elk and sheep locations that were random, and created a null distribution representing no avoidance (or attraction) between elk and sheep. For each randomiz.ed sample, the mean rank was saved and the randomization was re-run until there were 999 mean rankings. The mean of the 999 randomiz.ed mean ranks was the expected mean rank. The observed mean rank was merged with the randomiz.ed mean ranks, and the mean ranks were ordered from largest to smallest. The percentile of the observed sample was the P-value of the hypothesis test; that is, the probability of observing the rank of the sample or a larger rank under the null hypothesis that elk are located randomly with respect to sheep (Mooney and Duval 1993). Spatial scale may influence the ability to detect avoidance or attraction between animals (Doncaster 1990, Turchin 1998). That is, 'if elk were> 10 km from a particular sheep band, then it was not likely that there was any interaction between those elk and the sheep band. To include only elk close enough to interact with the sheep bands, I repeated this analysis at 2 other spatial scales. First, I re-analyz.ed the data using elk and sheep bands that were <5 km from each other on any day. Finally, I re-analyz.ed the data using elk and sheep bands that were < l km of each other. I did not examine closer spatial scales because sample sizes became too small. RESULTS The observed ranks were distributed without any apparent attraction or avoidance for 1996 (Fig. 3.4) and 1997 (Fig. 3.5). For all elk, elk <5 km from a sheep band, and elk <1 km ofa sheep band, the observed mean rank was not significantly greater than the expected mean rank under the null hypothesis that locations of elk were random with respect to sheep (Table 3.1). Thus, elk did not avoid sheep at the 3 spatial scales examined. For all spatial scales, the randomized mean rank remained constant (Table 3.1). In 1996, when approximately 22 locations were collected per elk, the randomized mean rank was 11.48-11.49 for the 3 spatial scales. In 1997, when approximately 23 locations were collected per elk, the randomized mean rank was 11.9311. 97 for the 3 spatial scales. Maps of elk and domestic sheep locations on several flights are presented in Appendix 3. DISUCSSION Experimental Results Elk did not appear to avoid sheep at any of the spatial scales I examined. Elk may avoid sheep at <l km, but I lacked sample sires needed for finer scale detection of avoidance. However, because elk did not avoid �256 sheep at > I km, it is extremely unlikely that domestic sheep caused any large scale movements of elk from public to private lands. Additionally, it may be that elk avoided the area used by sheep following sheep occupation. If this effect lasted for a long period of time, then the rank method used would be biased because would not detect this avoidance. If there is concern about elk avoidance of sheep at <l km, or elk avoidance of an area after sheep occupation, then a study designed to answer these questions is needed. Although there is little documentation of elk response to domestic sheep disturbances, studies have been conducted on other, similar, non-lethal disturbances. Elk responses to recreationalists, cross country skiers, cattle, and roads may illuminate possible elk responses to domestic sheep. In areas of continuous human presence, such as Rocky Mountain Park, elk showed little response to approaches of people in automobiles or on foot, day or night (Schultz and Bailey 1978). However, in the less intensely used Medicine Bow National Forest, Ward et al. (1973) found that elk avoided recreationalists (campers, fishermen, and picnickers) at <800 m. Elk Response to cross country skiers depended on the habituation of elk; in areas of high human activity elk moved short distances away from skiers, while in areas of low human activity, elk movement away from skiers was over 3 times greater than that of habituated elk (Cassirer et al. 1992). With respect to cattle, elk showed no movement responses to cattle grazing at> 100 m (Ward et al. 1973, Clegg 1994). In addition to habituating to non-lethal disturbances, elk may learn to distinguish between dangerous and harmless disturbances. In Rocky M01mtain National Parle, where elk were not hunted, Schultz and Bailey (1978) found no avoidance of roads in winter. In contrast, in Roosevelt National Forest, which is adjacent to Rocky Mo1D1tain National Parle, Rost (1975) found that a population ofh1D1ted elk avoided roads in winter. Wright (1983).found that mean distance to dirt roads more than doubled when hunting season opened. In the White River area, where sheep have been grazed for the past l 00 years, elk may have learned that sheep pose no threat, and like elk exposed to other nonlethal human activities, the White River elk may have habituated to sheep activities and ceased to avoid sheep. Methodology for Determining Attraction and Avoidance One of the difficulties in studying behavioral interactions between animals with radio telemetry data is lack of quantitative methods to determine if one animal's movements or locations are related to another animal's (White and Garrott 1990). Historically, radio-telemetry location data has been used to descn"be the size and shape of an animal's home range. Most studies collecting these type of data do not take into account the temporal information available in the telemetry data (White and Garrott 1990). This temporal information can be used to describe social interactions, such as avoidance or attraction, between animals. Two general approaches have been used to descn"be animal interaction. The first, static territorial overlap, describes the overlap of home ranges (Webster and Brooks 1981, Minta 1992) as an indication of attraction or avoidance. The second method, temporal or dynamic interactions, uses distance expectations based on expected home range use to test for attraction or avoidance (Dunn 1979, Macdonald et al. 1980, Doncaster 1990, Minta 1992). Both static and parametric temporal methods of testing for avoidance between animals require knowledge of home range siz.e or use. There are difficulties in estimating the mean area and variance of a home range, even if estimation procedures are accurate (Worton 1987). Additionally, home range statistics vary depending on the method of estimation (White and Garrott 1990). Parametric methods that test for temporal interaction assume that home range use follows a bivariate normal distribution (Jennrich and Turner 1969, Dunn 1979). It is unlikely that animals use space in a bivariate normal manner because resources, mates, and cover are all likely to be clumped and non-normal in distribution. To combat unlikely representations of home range siz.e of use, Doncaster (1990) suggests a nonparametric approach based on differences between observed and theoretical distributions of separation distances between 2 animals. All temporally paired distances and unpaired distances between 2 animals are calculated, and a critical distance is chosen for analysis of temporal interaction. Using this distance, data can be placed in a 2 x 2 contingency table showing frequen_cies of Pa.ii"~ and unpaired distances closer and farther than this critical distance. If distances are closer than expected, then the animals are attracted to each other; if distances are farther than expected, then the animals are avoiding each other. The rank method presented here is similar to Doncaster's (1990) nonparametric test for attractions and avoidance. Both methods have the advantage of not requiring assumptions about home range size or use compared to the static and parametric dynamic methods. However, there are 2 main advantages of the rank method over Doncaster's (1990) nonparametric approach. First, the rank method requires no arbitrary critical distance to evaluate attraction or avoidance. Although it may appear that the various spatial scales I used are similar to a critical distance, they are not. This study was not originally designed to test for attraction and �257 avoidance between elk and sheep, and the spatial scale over which I collected data (4,540 lan.2) was too large for accurate testing of attraction and avoidance between animals. Because of the large scale, I examined various spatial scales to subset out animals close enough to sense each other. Studies designed to test for avoidance or attraction interactions would not be at such a large scale and would not need to subset out animals close to each other. Additionally, at any scale examined, I did not set any critical distance at which attraction or avoidance was to occur. Second, Doncaster's (1990) method uses a chi-square test statistic, which works best when expected cell counts are ~5. The chi-square would not have worked well in this study because there was only 1 paired distance, which results in a count of 1 and O in cells containing the number of paired distances closer and farther than the critical distance. The chi-square test may not work well for any study with low sample sizes or unbalanced data (more locations on one animal than another). However, this problem is attenuated if a Fisher's exact test is used to evaluate the 2-way contingency table of paired and unpaired distances. MANAGEMENT IMPLICATIONS This study suggests that elk do not avoid domestic sheep at distances great enough to cause elk movements off public hunting grounds to private land. If concern about elk avoidance of sheep at distances of <1 km becomes serious, a more complete study, with radiocollared sheep from each band and a design tailored to the avoidance question, should be performed. The rank method used to test for elk avoidance of sheep could be used in many radio-telemetry data sets to evaluate attraction or avoidance between animals. The rank method, using a randomization procedure to generate the null distribution, is a flexible, powerful, and assumption reduced approach to test for attraction or avoidance behaviors between animals. The main requirement of the method is that simultaneous locations are taken on all animals in the study. LITERATURE CITED Beck, J. L., J. T. Flinders, D. R Nelson, and C. L. Clyde. 1996. Dietary overlap and preference of elk and domestic sheep in aspen-dominated habitats in north-central Utah. Pages 81-85 in K. E. Evans, compiler. Sharing common ground on western rangeland: proceedings of a livestock/big game symposium. U.S. Forest Service, Intermountain Research Station, Ogden, Utah, USA. Boyd, R J. 1970. Elk of the White River Plateau, Colorado. Colorado Division of Game, Fish and Parks Technical Publication 25, Fort Collins, Colorado, USA. Cassirer, E. F., D. J. Freddy, and E. D. Ables. 1992. Elk responses to disturbances by cross-country skiers in Yellowstone National Park. Wildlife Society Bulletin 20:375-381. Clegg, K. 1994. Density and feeding habits of elk and deer in relation to livestock disturbance. Thesis, Utah State University, Logan, Utah, USA. Doncaster, C. P. 1990. Nonparametric estimates of interaction from radio-tracking data. Journal of Theoretical Biology 143:431-443. Dunn, J.E. 1979. A complete test for dynamic territorial interaction. Pages 159-169 in F. M. Long, editor. Proceedings for the second international conference on wildlife biotelemetry. University of Wyoming, Laramie, Wyoming, USA. Jennrich, RI., and F. B. Turner. 1969. Measurement of non-circular home range. Journal of Theoretical Biology 22:227-237. MacCracken, J. G., and R M. Hansen. 1981. Diets of domestic sheep and other large herbivores in south central Colorado. Journal of Range Management 34:242-243. Macdonald, D. W., F. G. Ball, and N. G. Hough. J:980. The e¥aluation of home range size and configuration using radio tracking data. Pages 405-424 in C. J. Amlaner, Jr. and D. W. Macdonald, editors. A handbook on biotelemetry and radio tracking. Pergamon Press, Oxford, England. Minta, S. C. 1992. Tests of spatial and temporal interaction among animals. Ecological Applications 2:178204. Mooney, C. Z., and RD. Duval. 1993. Bootstrapping: a nonparametric approach to statistical inference. Sage Publishing Inc., Newbury Park, California, USA. �258 Nichols, L. Jr. 1957. Forage utilization by elk and domestic sheep in the White River National Forest. Thesis, Colorado State University, Fort Collins, Colorado, USA. Olsen, F. W., and R. M. Hansen. 1977. Food relationships of wild free-roaming horses to livestock and big game, Red Desert, Wyoming. Journal of Range Management 30: 17-20. Pickford, G. D. and E. H. Reid. 1943. Competition of elk and domestic livestock for summer range forage. Journal of Range Management 7:328-332. Rost, G. R. 1975. Responses of deer and elk to roads. Thesis, Colorado State University, Fort Collins, Colorado, USA. Schultz, R. D., and J. A. Bailey. 1978. Responses of national park elk to human activity. Journal of Wildlife Management 42:91-100. Stevens, D. R. 1966. Range relationships of elk and livestock, Crow Creek drainage, Montana. Journal of Wildlife Management 30:349-363. Turchin, P. 1998. Quantitative analysis of movement: measuring and modeling population redistribution in animals and plants. Sinauer, Sunderland, Massachusetts, USA. Ward, A. L., J. J. Cupel, A. L. Lea, C. Z. Oakeley, and R. W. Weeks. 1973. Elk behavior in relation to cattle grazing, forest recreation, and traffic. Transcripts from the 38th American Wildlife Natural Resource Conference 38:327-337. Webster, B. A, and R. J. Brooks. 1981. Social behavior ofMicrotus pennsylvanicus in relation to seasonal changes in demography. Journal ofMammalogy 64:738-751, White, G. C., and R. A. Garrott. 1990. Analysis of radio-tracking data. Academic Press, San Diego, California, USA Wright, K. L. 1983. Elk movements, habitat use, and the effects of hunting activity on elk behavior near Gunnison, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA Worton, B. J. 1987. A review of models of home range for animal movement Ecological Modeling 38:277298. Table 3.1. Paired mean rank, randomiz.edmean rank, 95% confidence interval of the randomu:ed mean rank, and the probability of observing the sample rank or greater under the null hypothesis that elk locations are random with respect to sheep locations. Paired mean rank is the observed rank of temporally paired observations, and randomized mean rank is the expected rank of the temporally paired observations if elk are located randomly with respect to sheep. Num.berof observed rankings Paired mean rank Randomi7.ed meanraok Randomu:ed 95%CI 11.34 12.14 11.48 11.97 [11.47, 11.49] [11.96, 11.98] 0.737 0.199 11.71 10.59 11.48 11.93 [11.45, 11.52] [11.89, 11.96] 0.342 0.990.:. 9.09 9.84 11.49 12.00 [11.41, 11.57] [I 1.90, 12.10) 0.969 0.912 All elk 1,844 1996 1997 1,790 All e//c <5 km ofa sheep band on any day 1996 150 124' 1997 All elk <l km of a sheep band on any day 1996 34 1997 19 �259 t N Meeker Glenwood Springs • Rifle km 0 10 20 BLM Land Flat Tops Wilderness State Wildlife Land Study Area Boundary Forest Service Land Sheep Locations 1996 Sheep Locations 1997 Towns a ~ ..lo. * ■ Figure 3.1. Sheep bands located during flights 20 July-IO October 1996-1997, and land ownership in the White River Area, Colorado. Note that all white area (blank area) is private land. �260 Elk Day Sheep Band i 2 3 Temporally paired and unpaired distances PAIRED unpaired unpaired Rank 21 4 11 22 1 2 1 3 PAIRED unpaired 17 1 22 unpaired 3 Unpalied 2 . 2 unpaired 3 unpaired 21 15 7 PAIRED 20 I 1 22 2 i PAIRED I 2 2 2 21 3 unpaired oopalred 2 2 22 unpaired 2 2 9 15 7 2 3 2 . 22 uupalied .j 1 . PAIRED unpaired 21 22 • unpaired 2 2 2 2 unpaired unpaired 22 4 2 22 22 PAIRED 11 88 88 1 1 3 PAIRED unpaired unpaired 18 2 88 2 . 3 . 88 88 88 22 88 88 1 7 oopalred 2 Ot' l' e<l p .fl'RED 8 21 3 unpaired 1 22 unpaired 3 I 2 2 Figure 3.2. Representation of temporally paired and unpaired distances between elk and sheep. Only I sheep band was l~ted per day, therefore sheep band I was located on day 1, sheep band 2 was located on day 2 9tf. Ranks were randomly assigned as an example. Ranks of the temporally paired distances were extracted to • calculate the paired mean rank for a given year and spatial scale. �261 a -----·------------ Paired mean rank= 7.1 200 Expected mean rank= 5.5 >- 150 u C GI 6- 100 e u. 1 2 3 4 5 6 Rank 7 8 9 10 b 200 Paired mean rank= 3.9 Expected mean rank = 5.5 >- 150 u C GI 6- 100 e u. 50 I 0 ..µ,....._.....,......_,....u1•..,....11.,,l~'~r.....,L,-. 1 2 3 4 5 6 Rank 7 8 9. 10 9 10 C Paired mean rank= 5.5 200 Expected mean rank= 5.5 >-150 u . C a, ::, ec-100 u. 50 0 1 2 3 4 5 6 Rank 7 8 Figure 3.3. Theoretical distribution of paired ranks and paired mean rank under the expectation that (a) elk avoid domestic sheep, (b) elk are attracted to domestic sheep, or (c) elk are located rando!llly with respect to domestic sheep. Paired mean rank is the observed rank of temporally paired observations, and expected mean rank is the mean rank of all observations (temporally paired and unpaired) if elk are located randomly with respect to sheep. �262 a 120 - r - - - - - - - - - - - - : - - - - : - : - = - : - - - - - - - - , Paired mean rank= 11.34 100 Expected mean rank= 11.48 ~80 C CD 5-60 Kt40 20 0 ---..-.--..-.--..-. 1 3 5 7 9 11 13 15 17 19 21 23 Rank b 15 - r - - - - - - - - - - - - - - - - , Paired mean rank-= 11.71 Expected mean rank"" 11.48 >40 -CJ C CD ::s CJ" f5 IL 1 3 5 7 9 11 13 15 17 19 21 23 Rank C &~-------------------, 5 Paired mean rank= 9.09 Expected mean rank= 11.49 1 0 - . - . . - - -........-...---.......-.--.-...........,-,.-----1 1 3 5 7 9 11 13 15 17 19 21 23 Rank Figure 3.4. Observed distribution of paired ranks and paired mean rank for (a) all elk, (b) elk <5 km of a sheep band, and (c) elk <I km ofa sheep band, 20 July-IO October 1996 in the White River area, Colorado. Paired mean rank was the observed rank of temporally paired observations. Expected mean rank was the mean rank of all observations (temporally paired and unpaired) if elk were located randomly with respect to sheep, and was calculated from 999 samples that randomized on locations of sheep bands~ �263 a 120 ~ - - - -Paired - -mean - -rank - -c -----, 12.14 100 Expected mean rank = 11.97 ('; 80 C ~ 60 O" Cl) ~ 40 20 0 -flil,,...,....,....-,...,...,..,-,..,.....-,.,..,...,..,..,....,..,-.,.....,...,_,-i 1 3 5 7 9 11 13 15 17 19 21 23 Rank b 15 ~ - - - - - - - - - - - - - - - - - . Paired mean rank-= 10.69 Expected mean rank c 11.93 ~10 C G> ::s er e u. 5 1 3 5 7 9 11 13 15 17 19 21 23 Rank C 6~---------------~ Paired mean rank .. 9.84 5· Expected mean rank .. 12.00 1 0 -t-.,-,..-.-'r-T-.-...-,--.-,---+--,-..,-,--......,......-.........~ 1 3 5 7 9 11 13 15 17 19 21 23 Rank Figure 3.5. Observed distribution of paired ranks and paired mean rank for (a) all elk, (b) elk <5 km ofa sheep band, and (c) elk <l km ofa sheep band, 20 July-IO October 1997 in the White River area, Colorado. Paired mean rank was the observed rank of temporally paired observations. Expected mean rank was t;he mean rank of all observations (temporally paired and unpaired) if elk were located randomly with respect to sheep, and was calculated from 999 samples that randomized on locations of sheep bands. �264 �265 APPENDIX 1: SAMPLE SIZE CALCULATION FOR HUNTER SURVEY Note, G. White (Colorado State University, personal communication) derived this sample siz.e calculation. Hunt codes D-E-012-01-A. E-E-012-01-A. E-F-012-01-M, E-M-012-01-M, D-M-012-01-M, D-E-033-01-A. E-E033-01-A. E-F-033-01-M, E-M-033-01-M, and D-M-033-01-M used the study area during the study. To estimate total number of hunters on any day with a 95% confidence interval within ±150 hunters, the binomial distribution and proportion of licenses holders was used to derive the number of license holder to be surveyed, where: N Number of licenses holders (number of individuals purchasing licenses), p Estimated proportion of hunters hunting, n Number of licenses holders sampled/surveyed, H Estimated num.ber of hunters hunting, N-n N Finite population correction factor, H=pN,and N -n ~rt A)_ N -n N2 p(l- p) vaAr(HA)- - N2 v... \p - - -------'--. N N n The maximum variance will occur if 50% of the license holders hunt (i.e., p = 0.5), with the variance decreasing for larger or smaller percentages. For N license holders, the sample size (n) required to obtain a 95% confidence interval of ±150 with a= 0.05 and p = 0.5 is: On most days, the confidence interval will be less than ±150 because not exactly 50% of the hunters will be hunting. For example, if80% oflicense holders are hunting, then the variance of p is reduced from 0.25/n to 0.16/n (without the finite population correction factor). Thus, the confidence interval will be considerably smaller than ±150 hunters. �266 �267 APPENDIX 2: STANDARD ERRORS FOR DAILY GMU ESTIMATES OF HUNTERS AND ATVS AFIELD Estimated number of hunters afield per day by GMU and standard enors of the estimates for 1996. Stanoaro error of estimates Est1matoo fiunters af1elo DATE 8!:M/96 8/25/96 8/26/96 8/27/96 8/28/96 8/29/96 8/30/96 8/31/96 9/1/96 9/2/96 9/3/96 9/4/96 9/5196 9/6/96 9nl96 9/8/96 919196 9/10/96 9/11/96 9/12/96 9/13/96 9/14/96 9/15/96 9/16/96 9/17/96 9/18/96 9/19/96 9/20/96 9/21/96 9/22/96 9/23/96 9/24/96 9/25/96 9/26/96 9/27/96 9/28/96 9/29/96 9130196 10/1/96 10/2/96 10/3/96 10/4/96 10/5/96 10/6/96 Rl2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 568 551 498 460 410 362 314 282 209 155 124 111 91 80 80 74 73 70 64 61 63 66 51 H23 210 211 176 157 151 122 124 154 150 118 109 112 106 116 161 147 120 115 113 109 103 526 531 381 343 296 241 211 186 113 77 72 62 50 43 75 64 37 33 33 38 39 46 42 R2:il 127 135 129 119 106 85 84 121 132 126 105 105 94 88 119 118 116 114 113 112 113 421 400 265 243 197 163 133 117 47 30 32 25 22 28 36 33 26 29 3"1 31 25 19 21 R:33 218 226 185 176 152 129 130 177 175 151 133 119 112 118 163 146 74 69 65 71 74 211 213 94 78 52 43 39 34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Rl2SE 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 23 23 22 21 21 20 19 18 16 14 14 12 12 12 11 11 11 11 10 11 11 10 1-12:JSE 17 17 16 15 ·15 14 14 15 15 14 13 13 13 14 16 15 14 14 H24SE 14 14 14 14 13 II 11 14 14 14 13 13 13 12 14 14 14 14 14 13 13 25 25 20 20 19 17 16 15 13 II II IO 9 9 13 II 11 8 8 8 8 8 9 9 14 14 22 22 16 16 15 14 13 12 9 7 7 6 6 7 8 7 7 7 7 7 7 6 6 H33SE 18 18 17 16 15 14 14 16 16 15 15 14 13 14 16 15 11 11 10 11 11 16 16 8 8 6 6 6 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Note: H12 represents estimated number of hunter afield in GMU 12, H23 represents estimated number of hunter afield in GMU 23, etc. Hl2SE represents the standard error of the estimated number of hunters in GMUI2, Hl2SE represents the standard error of the estimated number of hunters in GMU23, etc. �268 Estimated number of hunters using ATVs afield per day by GMU and standard errors of the estimates for 1996. DATE 8724796 8/25/96 8/26/96 8/27/96 8/28/96 8/29/96 8/30/96 8/31/96 9/1/96 9/2/96 9/3/96 9/4/96 9/5/96 9/6/96 9nt96 9/8/96 9/9/96 9/10/96 9/11/96 9/12/96 9/13/96 9/14/96 9/15/96 9/16/96 9/17/96 9/18/96 9/19/96 9/20/96 9/21/96 9/22/96 9/23/96 9/24/96 9/25/96 9/26/96 9/27/96 9/28/96 9/29/96 9/30/96 10/1/96 10/2/96 10/3/96 10/4/96 10/5/96 10/6/96 Stanaaro error of estimates Esf1matea liunters usmg A I Qs af1elo HA12 HA23 HA24 HA'.33 HAl2SE HA23SE HA24SE HADSE 48 0 2o 0 9 6 51 9 6" 0 47 20 52 0 9 9 44 0 41 17 0 8 5 9 0 41 16 43 0 8 5 9 4 0 40 13 41 0 8 8 4 0 36 12 41 0 8 8 4 0 36 12 36 8 0 8 0 29 7 4 13 55 0 IO 4 7 0 26 13 51 0 9 17 5 0 11 50 0 4 IO 0 17 14 47 5 5 0 9 0 17 5 14 36 0 5 8 0 16 8 5 3 35 0 8 0 32 7 8 33 0 3 8 0 49 7 57 9 3 0 IO 0 46 6 48 0 9 3 9 0 40 8 6 26 0 3 7 0 8 39 7 23 3 0 7 0 8 39 7 23 0 3 7 0 33 8 2 5 18 0 6 28 7 0 11 4 15 0 5 14 50 139 77 45 9 IO 8 50 136 14 77 42 9 IO 8 47 90 II 59 13 9 9 3 46 85 11 8 12 9 55 3 37 77 46 12 8 IO 8 3 36 56 39 8 8 9 7 2 35 50 34 6 8 9 7 2 40 33 27 6 8 7 6 2 31 20 9 7 6 4 0 0 22 16 2 0 6 1 5 0 17 17 4 6 2 0 6 0 15 12 4 0 5 4 2 0 12 12 4 4 0 4 2 0 9 15 7 0 4 5 3 0 9 24 9 4 0 7 4 0 6 19 9 0 4 3 6 0 2 IO 8 0 I 4 4 0 2 4 8 0 0 3 4 2 4 8 0 0 3 4 4 2 8 0 0 4 3 0 7 6 0 0 0 3 3 3 10 0 2 0 0 4 0 3 7 0 0 0 2 3 0 Note: Hl2 represents estimated number of hunter afield in GMU 12, H23 represents estimated number of hunter afield in GMU 23, etc. Hl2SE represents the standard error of the estimated number of hunters in GMU12, Hl2SE represents the standard error of the estimated number of hunters in GMU23, etc. �269 Estimated number of hunters afield per day by GMU and standard errors of the estimates for 1997. Stanaara error of estimates H23SE H24SE H12SE DATE Eshmatoo liunfers af1ela H23 RI2 R24 H33 8723797 328 178 124 0 23 17 15 0 8/24/97 8/25/97 8/26/97 8/27/97 8/28/97 8/29/97 8/30/97 8/31/97 9/1/97 9/2/97 9/3/97 9/4/97 9/5/97 9/6/97 9nl97 9/8/97 9/9/97 9/10/97 9/11/97 9/12/97 9/13/97 9/14/97 9/15/97 9/16/97 9/17/97 9/18/97 9/19/97 9/20/97 9/21/97 9/22/97 9/23/97 9/24/97 9/25/97 9/26/97 9/27/97 9/28/97 9/29/97 9/30/97 10/1/97 10/2/97 10/3/97 10/4/97 10/5/97 314 282 252 226 206 191 220 211 191 151 139 115 107 130 168 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 22 21 20 19 19 20 20 19 17 17 15 15 16 17 ·11 17 15 14 14 13 13 14 14 14 13 13 13 12. 14 13 11 12 12 15 15 14 13 12 11 11 II 12 12 10 10 10 11 11 12 12 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 483 477 401 403 379. 317 249 275 240 17 23 22 21 21 20 161 148 0 0 -0 0 0 0 0 0 0 0 0 0 0 0 141 132 120 112 122 142 416 391 364 345 300 205 172 160 112 0 0 0 0 0 0 0 0 0 0 0 0 0 0 98 119 117 109 100 82 66 67 64 81 77 56 96 49 87 51 62 61 63 66 67 60 61 477 470 462 409 399 307 242 224 207 135 123 115 114 105 81 73 75 72 71 67 51 34 24 138 123 115 109 92 115 110 119 97 IOI 87 65 67 68 68 71 484 483 449 442 404 309 275. 223 149 57 50 53 52 50 46 50 44 50 39 37 37 40 45 .o 127 126 130 142 137 79 77 87 91 98 111 105 16 15 16 18 17 16 14 ii 11 11 26 26 25 25 24 22 21 19 16 10 10 10 10 10 9 IO IO IO 8 8 8 9 9 12 26 26 26 24 24 22 20 20 19 16 15 15 15 14 13 12 12 12 12 12 10 8 7 H33SE () 0 0 0 0 0 25 25 23 23 23 22 20 21 20 18 17 15 15 16 16 16 13 12 13 14 14 15 14 Note: Hl2 represents estimated number of hunter afield in GMU 12, H23 represents estimated number of hunter afield in GMU 23, etc. HI 2SE represents the standard error of the estimated number of hunters in GMU 12, Hl2SE represents the standard error of the estimated number of hunters in GMU23, etc. �270 Estimated number of hunters using ATVs afield per day by GMU and standard errors of the estimates for 1997. DATE 8723797 8/24/97 8(25/97 8(26/97 8f27/97 8(28/97 8/29/97 8/30/97 8/3 l/97 9/1/97 9f2/97 9/3/97 9/4/97 9/5/97 9/6/97 9nl91 9/8/97 9/9/97 9/10/97 9/l l/97 9/12/97 9/13/97 9/14/97 9/15/97 9/16/97 9/17/97 9/18/97 9/19/97 9f10l91 9fll/91 9(22/97 9(23/97 9f24/97 9f15l97 9f16l91 9(27/97 9(18/97 9/29/97 9/30/97 10/1/97 I0/2/97 10/3/97 I0/4/97 10/5/97 Estimatea nunters af1ela HA[2 HA23 HA24 43 70 34 39 36 70 32. 56 39 35 30 48 30 48 40 45 30 33 25 30 26 21 27 30 28 18 27 24 31 16 18 36 18 18 36 12 15 33 12 8 29 9 7 IO 34 5 30 8 12 30 8 30 8 5 2 8 30 28 3 5 7 21 5 110 29 50 32 110 50 112 51 30 20 113 48 22 106 48 81 ll 39 IO 77 33 52 7 30 7 19 35 14 0 7 0 14 7 0 8 7 8 0 7 0 8 7 0 15 3 0 19 3 0 19 3 0 19 3 0 19 3 0 19 3 0 19 3 0 12 3 0 12 3 HA33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 99 IOI 94 85 78 63 56 64 58 54 40 37 35 42 48 39 29 22 24 22 34 34 34 Stanaara error of estimates HAl2SE HA23SE HA24SE HA33SE 12 8 9 0 12 9 8 0 IO 9 8 0 9 8 0 8 9 9 8 0 8 8 9 0 8 7 0 7 7 8 8 0 8 6 0 8 8 5 7 0 8 6 6 0 8 6 5 0 8 5 5 0 7 3 4 0 8 3 4 0 8 4 3 0 8 4 5 0 8 4 3 0 8 4 0 8 3 0 3 4 7 3 0 8 14 13 7 14 8 13 8 8 13 14 8 8 12 14 6 14 8 12 6 12 8 11 5 12 8 10 4 8 11 3 IO 6 11 3 8 4 11 6 0 0 6 4 9 4 0 4 9 4 0 4 9 4 4 9 0 6 3 IO 0 0 6 3 9 8 6 3 0 7 6 3 0 7 6 3 0 7 6 3 0 9 3 0 6 9 3 0 5 9 0 5 3 Note: Hl2 represents estimated number of hunter afield in GMU 12, H23 represents estimated number of hunter afield in GMU 23, etc. Hl2SE represents the standard error of the estimated number of hunters in GMUI2, H 12SE represents the standard error of the estimated number of hunters in GMU23, etc. �:.!__; l White River Elk Movement Study White River Elk Movement Study Elk and Shee~ Locations on July 19, 1996 Elk and Sheep Locations on July 24, 1996 Hamilton Km 20 z t:I ~ !-:I Hamilton 0 ~ ~ l'1!j ~ 40 en 0 ',ij l'1!j ~ ~ t:I t:I 0 ~ l'1!j en -i ~ n en = l'1!j l'1!j ~ I:"" 0 n > -i Rio Blanco ~ 0 z en 0 z en LEGEND BLM Land Flat Tops WIiderness State Wildlife Land Study Area Boundary White River National Forest Springs ■ * A ■ ..., White River Elk Location Sheep Location Towns l'1!j I:"" l'1!j n -i Springs ■ l'1!j t:I ',ij I:"" ~ (;') = -i en N -.J �White River Elk Movement Study White River Elk Movement Study Elk and Sheep Locations on July 31, 1996 Elk and Sheep Locations on August 4, 1996 Hamilton Hamilton Krn 0 20 40 LEGEND Springs • .BLM Land Flat Tops WIiderness State Wildlife Land Study Area Boundary White River National Forest - White River • Elk Location Sheep Location ■ Towns !* -------- Springs ■ �White River Elk Movement Study White River Elk Movement Study Elk and Sheep Locations on August 14, 1996 Elk and Sheep Locations on August 28, 1996 Hamilton Hamilton Km 0 20 40 Rio 81anco LEGEND Springs ■ * • ■ BLM Land Flat Tops Wilderness State Wildlife Land Study Area Boundary White River National Forest White River Elk Location Sheep Location Towns ts) ...J \.,.) �N -.I White River Elk Movement Study White River Elk Movement Study Elk and Sheep Locations on August 20, 1997 Elk and Sheep Locations on September 6, 1997 Hamilton Hamilton Km 20 0 LEGEND BLM Land Flat Tops WIiderness State Wildlife Land Study Area Boundary White River National Forest !* - White River • ■ Elk Location Sheep Location Towns 40 00 �White River Elk Movement Study White River Elk Movement Study Elk and Sheep Locations on September 17, 1997 Elk and Sheep Locations on Septermber 24, 1997 Hamilton Km 0 20 40 LEGEND BLM Land Flat Tops Wilderness State Wildlife Land Study Area Boundary White River National Forest - White River • Elk Location Sheep Location. ■ Towns !* N --.J '° �White River Elk Movement Study White River Elk Movement Study ~:~ c:-:c S:;ee:::: ~oc:::~:o~s 0:1 Cctober 1, ~ 997 Elk and '":,he::>~, Lr;r,rJ;:r:;n~: on October 5, 1997 Hamilton Hamilton Km 0 • 20 LEGEND BLM Land Flat Tops Wilderness Area State Wildlife Area Study Area Boundary White River National Forest - White River • Elk Location Sheep Location ■ Towns !* 40 � https://cpw.cvlcollections.org/files/original/0a33e58ed066698d08f7ebee6435722d.pdf 6733fc151d4a614da8db27b829c5bcab PDF Text Text 227 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT State of Colorado cost center 3430 Project No. W-153-R-11 Mammals Program Work Package No. ___3_0_0-2______ Task No. _______.._______ Elk conservation : Monitoring and Managing-Chronic wasting Disease in Elk Period Covered: July 1, 1997 - June 30, 1998 w. Miller Authors: M. Personnel: s. Berry, K. Larsen, K. I. O'Rourke, T. R. Spraker, Wheeler, M.A. Wild, and E. S. Williams s. Tracy, E. ABSTRACT Elk from throughout Colorado were examined for occurrence of chronic wasting disease using a combination of targeted surveys and harvest or road-kill surveys. We continued to develop and modify a statewide targeted surveillance program for acquiring, examining, and reporting on CWD suspects submitted from Colorado. Between June 1997 and May 1998, 2 chronic wasting disease (CWD) cases were diagnosed among 6 •suspect• elk submitted from endemic game management units (GMUs) in northeastern Colorado; CWD was not diagnosed in any of 6 additional "suspect• elk submitted from elsewhere in Colorado. Harvest surveys were used to estimate CWD prevalence in enzootic management units. About 0.21 of elk harvested in Larimer County data analysis units (DAUs) (E4 or E9) tested positive for CWD via immunostaining; CWD was not detected in any of the harvested elk submitted from outside Larimer county. Requiring hunters to participate in harvest surveys continued to increase the number of samples submitted for CWD examination. Data from both targeted surveillance and surveys indicate that Larimer county remains the only focus of CWD in Colorado elk, although some undetected natural spread may be occurring. Compared to deer, however, CWD is a relatively rare disease in free-ranging elk in northcentral Colorado. Targeted surveillance of clinical suspects appears to be the most sensitive approach for initially detecting CWD in elk populations throughout Colorado, and will be continued statewide. Based on low prevalence detected in 1995-1997 surveys, future harvest and road-kill surveys will be conducted at about 5-yr intervals to estimate prevalence, monitor trends, and compare rates among endemic elk DAUS. ��229 MONITORING ARD MANAGING CHRONIC WASTING DISEASE IN ELK M.w. Miller P, H, OBJECTIVES (1) Design, conduct, and report results of: (a) targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWD) in free-ranging elk populations; and (b) harvest or road-kill surveys to estimate and detect changes in prevalence of CWD in enzootic elk populations. (2) Design, conduct, and report results of experimental studies using captive elk naturally or experimentally infected with CWD. SEGMEHT OBJECTIVES (1) Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWD in free-ranging elk populations statewide. (2) Conduct and report results of harvest surveys to estimate prevalence of CWD in DAUS E4 and E9. (3) Observe epizootiological features of naturally-occurring CWD in captive elk. IHTRQDUCTIQH Chronic wasting disease (CWD) is a disease of native deer and elk characterized by behavioral changes and progressive loss of body condition that invariably lead to the death of affected animals (Williams and Young 1992). Neither the causative agent nor its mode of transmission have been identified. There are no tests currently available for diagnosing CWD in live animals, and postmortem tests require microscopic examination of brain tissue. There are no known treatments for CWD. Previous attempts to eradicate CWD from research facilities failed on at least 2 occasions (Williams and Young 1992). Although similar in some respects to other transmissible spongiform encephalopathies that affect domestic sheep (scrapie) and cattle (bovine spongiform encephalopathy; BSE; "mad cow disease"), there is no evidence suggesting CWD can be naturally transmitted to domestic livestock, or that scrapie or BSE can be transmitted to native cervids. Moreover, there is no evidence suggesting that CWD presents a threat toLhuman health. "Chronic wasting disease" was first recognized by biologists in the 1960's as a disease syndrome of captive deer held in wildlife research facilities in Ft. Collins, co, and was subsequently recognized in captive deer, and later in captive elk, in wildlife research facilities near Ft. Collins, Kremmling, and Meeker, co and Wheatland, WY (Williams and Young 1980, 1982). Since 1981, 74 cases of CWD have also been diagnosed in free-ranging mule deer, white-tailed deer, and elk from northeastern Colorado; most of these diagnoses have been made since 1990 (Spraker et al. 1997; M. w. Miller, unpubl. data). At present, the known world-wide distribution of CWD in wild cervids appears to �230 be limited to northeastern Colorado and southeastern Wyoming. Although CWD was first diagnosed in captive cervids, the original source of CWD in either captive cervids or free-ranging cervids is unknown; whether CWD in captive cervids really preceded CWD in wild cervids, or vice versa, is equally uncertain (Spraker et al. 1997). In Colorado, free-ranging CWD cases in elk have all originated from along the northern Front Range. Game Management Units (GMUs) yielding infected elk include 7, 9, 19, 191, and 20. All clinical elk cases have come from two Data Analysis Units (DAUs)(E4, E9). To date, examinations of elk from other parts of Colorado have not detected CWD. Preliminary data from hunter-killed deer indicate that even in enzootic areas CWD is relatively rare: it probably affects $l.5% of the elk in E4 and E9. No real trend in prevalence (increasing or decreasing) can be discerned from data available to date. In the absence of historical (20-30 years ago) prevalence data or reliable estimates of transmission rates, it is also unclear whether incidence of CWD in northcentral Colorado DAUs is stable or increasing, or whether short-term observations can accurately forecast long-term trends. The significance of CWD and its impacts on native elk populations are unclear. Preliminary results of simulation modeling to predict dynamics and impacts of CWD on affected deer populations suggest that, sustained at current prevalence (about 6.5% in deer), CWD could impact wild deer herds and lead to population declines (M. w. Miller and c. w. McCarty, unpubl. data). Although CWD prevalence is lower in elk than in deer in enzootic DAUs, it is conceivable that impacts could occur if prevalence were allowed to increase. Clearly, reliable estimates of CWD prevalence in wild elk populations are needed to guide policy decisions and monitor efficacy of management efforts. In the absence of data to the contrary, and considering the difficulties inherent in eliminating CWD from captive or wild cervid populations once established, it seems most prudent to assume CWD could adversely affect native deer or elk populations and manage to reduce its occurrence and prevent its further spread. Consequently, the Colorado Division of Wildlife needs to undertake a variety of actions to further understanding about CWD and its management through surveillance and experimental research in order to reduce the occurrence of CWD and minimize the risk of its spread to other native deer or elk populations in Colorado. MATERIALS AND METHODS Surveillance We monitored elk populations throughout Colorado for occurrence of CWD using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: Targeted(= clinical disease) surveillance: Elk showing clinical signs consist~nt with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. The "suspect casen profile was defined as follows: • • • Species: Age: Signs: elk ~ 18 months emaciated and abnormal behavior &/or indifference to human activity &/or �231 increased salivation &/or tremor, stumbling, incoordination &/or difficulty or inefficiency in chewing/swallowing &/or increased drinking and urination Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (Williams and Young 1993) was used to diagnose CWD; in some cases, immunohistochemistry or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: In order to obtain reliable estimates of CWD prevalence that will serve as a basis for monitoring responses to management interventions, we continued conducting harvest surveys on select deer populations. During the 1997-1998 hunting seasons, fresh brain and select lymphatic tissues were collected from endemic and nonendemic GMUs. Brain tissues were examined at the Colorado State University Diagnostic Laboratory for histopathological lesions (Williams and Young, 1993)or anti-PrP immunostaining reactions (O'Rourke et al., 1998) consistent with CWD infection. Because sample sizes for most individual GMUs were too small to provide reliable prevalence estimates by GMO, we pooled data by DAU for comparisons within and among species. Small sample sizes also precluded meaningful analysis of data from deer or elk harvested outside known enzootic areas. Epizootiological Studies cwo Epidemiology of naturally-occurring in captive elk (Miller and Wild): we observed captive adult elk (n = 19) held at CDOW's Foothills Wildlife Research Facility for clinical signs of CWD and submitted all mortalities for complete necropsy and histopathological examination. A manuscript describing CWD epidemiology in captive elk (Miller et al., 1998) was revised and accepted for publication. RESULTS AND DISCUSSION Surveillance Targeted(= clinical disease) surveillance: Between June 1997 and May 1998, 2 chronic wasting disease (CWD) cases were diagnosed among 6 "suspect" elk submitted from endemic game management units (GMUs) in northeastern Colorado; CWD was not diagnosed in any of 6 additional "suspect" elk submitted from elsewhere in Colorado. Harvest surveys; During the 1997-1998 hunting seasons, fresh brain and select lymphatic tissues were collected from 653 elk harvested in enzootic GMUs • (Table l); 103 elk harvested or culled in other GMUs throughout Colorado were also sampled as negative controls. Estimated prevalence among harvested elk did not differ (P = 1.0) between E4 (0.2%) and E9 (0%). As in 1996, overall CWD prevalence among elk harvested in Larimer County was lower (P < 0.009) than in sympatric deer populations (see Miller, 1998). Even the foregoing prevalence estimates may be somewhat liberal because the definition of "positive" included subclinical cases where either histopathological lesions or anti-PrP immunostaining reactions in brain tissue were observed. The elk case identified in 1997, as well as all 4 elk cases in 1996, were classified as positive solely on the basis of immunostaining reactions. Although no known "false positives" were identified among the 103 elk examined from outside known enzootic DAUs in 1997, further evaluation of �232 both sensitivity and specificity of existing diagnostic techniques still appears warranted. During the 1997-1998 rifle seasons, harvest survey participation was required of successful elk hunters in both E4 and E9. In E4, 454 successful elk hunters submitted heads in 1997, compared to only 81 voluntary submissions in 1996. These observations reemphasize previous observations (Miller, 1997) that compelling participation in harvest surveys via regulation is the single most effective method for increasing sample sizes. Data from both targeted surveillance and surveys indicate that Larimer County remains the only focus of CWD in Colorado elk, although some undetected natural spread may be occurring. Compared to deer, however, CWD is a relatively rare disease in free-ranging elk in northcentral Colorado. Targeted surveillance of clinical suspects appears to be the most sensitive approach for initially detecting CWD in elk populations throughout Colorado, and will be continued statewide. Based on low prevalence detected in 1995-1997 surveys, future harvest and road-kill surveys will be conducted at about 5-yr intervals to estimate prevalence, monitor trends, and compare rates among endemic elk DAUs. Epizootiological Studies Epidemiology of naturally-occurring cwp in captive elk (Miller and Wild): None of the 19 captive adult elk held at CDOW's Foothills Wildlife Research Facility developed clinical CWD during June 1997-May 1998; one female (G86) that died showed no histological evidence of ewe. We will continue to monitor this naturally-infected captive herd and examine all mortalities for evidence of ewe. A manuscript describing CWD epidemiology in captive elk (Miller et al., 1998) was accepted for publication. Judging from requests for prepublication copies, this manuscript appears to be of considerable interest to those investigating and managing recently recognized foci of CWD in privately-owned captive elk throughout the us and Canada. ACKHQWLEDGMEHTS The statewide CWD monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those regional and area biologists, district and area wildlife managers, volunteers, deer and elk hunters, and others who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. LITERATURE CITED Miller, M. w. 1997. Monitoring and managing wildlife chronic wasting disease in Colorado. in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-10, WP2, Jl7. Colorado Division of Wildlife, Fort Collins, Colorado, USA, pp. 37-46. �233 1998. Monitoring and managing wildlife chronic wasting disease in deer. in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-11, WP3001, T3. Colorado Division of Wildlife, Fort Collins, Colorado, USA, in press. ___ ,M.A. Wild, and E. s. Williams. 1998. Epizootiology of chronic wasting disease in captive Rocky Montain elk. J. Wildl. Dis. 34: 532538. O'Rourke, K. I., T. v. Baszler, J.M. Miller, T. R. Spraker, I. SadlerRiggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.1.5 defines a conserved epitope on the ruminant prion protein. J. Clin. Microbiol. 36: 1750-1755. Spraker, T. R., M. W. Miller, E. S. Williams, D. M. Getzy, W. J. Adrian, G. G. Schoonveld, R. A. Spowart, K. I. O'Rourke, J.M. Miller, and P.A. Merz. 1997. Spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus ·elaphus nelsoni) in northcentral Colorado. J. Wildl. Dis. 33:1-6. Williams, E. s., ands. Young. 1980. Chronic Wasting disease of captive mule deer: A spongiform encephalopathy. Journal of Wildlife Diseases 16: 8998. ___ ,and___ 1982. Spongiform encephalopathy of Rocky Mountain elk. Journal of Wildlife Diseases 18: 465-471. ___ ,and___ 1992. Spongiform encephalopathies in Cervidae. Revue Scientifique et Technique Office International des Epizooties 11: 551567. ___ ,and___ 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. C Wildlife Research Veterinarian �234 Table 1. Results of 1997 CWD harvest surveys -- archery, muzzleloader, & rifle seasons. ELK DAU GMU # Examined # Positive E4 7 104 0 8 184 0 191 30 0 9 9 0 19 127 1 Total 454 1 20 199 0 Total 199 0 E9 Prevalence (95% Cl) 0.002 (0.0001-0.012) 0 (0-0.019) �281 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT State of - - - - ~ " ' " " "Colorado -"'""""''-=-------Project No. _ _ _. . _W.:. . --=1=5;:;.. 3--=-R-=--=12;___ _ _ __ Work Package No. -~3....0___0=2_ _ _ _ _ __ Task No. _ _ _ _ _........;::3;,.____ _ _ _ __ Cost Center 3430 Mammals Program Elk Management Monitoring and Managing Chronic Wasting Disease in Elk Period Covered: July 1, 1998 -June 30, 1999 Authors: M. W. Miller and C. T. Larsen Personnel: K. I. O'Rourke, T. R Spraker, E. Wheeler, M.A. Wild, and E. S. Williams ABSTRACT Elk from throughout Colorado were examined for occurrence of chronic wasting disease using targeted surveillance. Between June 1998 and May 1999, 7 chronic wasting disease (CWD) cases were diagnosed . from among 12 "suspect" elk submitted from endemic game management units (GMUs) in northeastern Colorado. CWD was not diagnosed in any of 4 additional "suspect" elk submitted from elsewhere in Colorado. No cases ofCWD occurred among 23 adult elk held at CDOW's Foothills Wildlife Research Facility. �282 �283 MONITORING AND MANAGING CHRONIC WASTING DISEASE IN ELK M. W. Miller and C. T. Larsen P. N. OBJECTIVES (I) Design, conduct, and report results of: (a) targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWD) in free-ranging elk populations; and (b) harvest or road-kill surveys to estimate and detect changes in prevalence of CWD in enzootic elk populations. (2) Design, conduct, and report results of experimental studies using captive elk naturally or experimentally infected with CWD. AGREEMENT OBJECTIVES (1) Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWD in free-ranging elk populations statewide. ( 2 ) Observe epizootiological features of naturally-occurring CWD in captive elk. MATERIALS AND METHODS Surveillance We monitored elk populations throughout Colorado for occurrence of CWD using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: Targeted(= clinical disease) surveillance: Elk showing clinical signs consistent with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. Toe "suspect case" profile was defined as follows: • Species: elk • Age: 2: 18 months • Signs: emaciated and abnormal behavior &/or indifference to human activity &/or increased salivation &/or tremor, stumbling, incoordination &/or difficulty or inefficiency in chewing/swallowing &/or increased drinking and urination Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (W"tlliams �284 and Young 1993) was used to diagnose CWD; in some cases, immunohistochemistry (O'Rourke et al., 1998) or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: No elk harvest surveys were planned for this segment. Epizootiological Studies Epidemiology of naturally-occurring CWD in captive elk (Miller and Wild): We observed captive adult elk (n = 23) held at CDOW's Foothills Wildlife Research Facility for clinical signs ofCWD and submitted all mortalities for complete necropsy and histopathological examination. RESULTS AND DISCUSSION Surveillance Targeted(= clinical disease) surveillance: Between June 1998 and May 1999, 7 chronic wasting disease (CWD) cases were diagnosed among 12 "suspect" elk submitted from endemic game management units (GMUs) in northeastern Colorado; CWD was not diagnosed in any of 4 additional "suspect" elk submitted from elsewhere in Colorado. Since 1981, 23 clinical CWD cases have been diagnosed in elk from Larimer County GMUs (Fig. I). Harvest surveys: No elk harvest surveys were conducted in this segment, and none are planned for 1999-2000. Epizootiological Studies Epidemiology of naturally-occurring CWD in captive elk (Miller and Wild): None of the 23 captive adult elk held at CDOW's Foothills Wildlife Research Facility developed clinical CWD during June 1998-May 1999; 3 female elk that died during that period were not infected. We will continue to monitor this naturally-infected captive herd and examine all mortalities for evidence of CWD. A manuscript describing CWD epidemiology in captive elk during 1986-1997 was published in July (Miller et al., 1998). ACKNOWLEDGMENTS The statewide CWD monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those regional and area biologists, district and area wildlife managers, volunteers, elk hlfflters, and .others 'Who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. �285 LITERATURE CITED Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epizootiology of chronic wasting disease in captive Rocky Montain elk. J. Wildl. Dis. 34: 532-538. O'Rourke, K. I., T. V. Baszler, J. M. Miller, T. R. Spraker, I. Sadler-Riggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.1.5 defines a conserved epitope on the ruminant prion protein. J. Clin. Microbiol. 36: 1750-1755. Williams, E. S., and S. Young. 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. Prepared by _ _ _ _ _ _ _ _ _ _ __ Michael W. Miller Wildlife Research Veterinarian oCheyenne: South Platte River River 50 100 _ ___.__ _...____ km Figure 1. Between March 1981 and June 1999, 23 clinical CWD cases have been diagnosed in elk from GMUs in Larimer County, Colorado. �286 �233 L Colorado Division of Wildlife Wild)ife Research Report July 2000 JOB PROGRESS REPORT Stateof _ _ _ _ _ _C=o=l=orad==o_ _ _ __ Cost Center 3430 Project No. _ _ _ _ _W~-1=5___3___ -R___-=13=------ Mammals Program Work Package No. _____3---00=2.___ _ __ Elk Management Task No. 1 ---------------- Monitoring and Managing Chronic Wasting Disease in Elk Period Covered: July 1, 1999 - June 30, 2000 Authors: M. W. Miller and C. T. Larsen Personnel: K. I. O'Rourke, T. R Spraker, E. Wheeler, M.A. Wild, and E. S. Williams \ . ) ABSTRACT Elk from throughout Colorado were examined for occurrence of chronic wasting disease using targeted surveillance. Between June 1999 and May 2000, 5 chronic wasting disease (CWD) suspect elk were submitted from endemic game management units (GMUs) in northeastern Colorado; none of those suspects were infected :with CWD. In addition, CWD was not diagnosed in any of 7 other suspect elk submitted from elsewhere in Colorado. Locoism was diagnosed in 5 suspect elk (all from Jefferson County), and cause of emaciation could not be determined in 5 cases (including 4 from endemic GMUs). One case ofCWD occurred among 23 adult elk held at CDOW's Foothills Wildlife Research Facility. The last case in this herd occurred nearly 5 years ago. Exposure to run-off from pens holding CWD-infected deer was the most likely source of infection. BDOW016787 ��235 MONITORING AND MANAGING CHRONIC WASTING DISEASE IN ELK M. W. Miller and C. T. Larsen P. N. OBJECTIVES (I) Design, conduct, and report results of: (a) targeted surveillance to estimate and detect changes in distribution of chronic wasting disease (CWD) in free-ranging elk populations; and (b) harvest or road-kill surveys to estimate and detect changes in prevalence of CWD in enzootic elk populations. (2) Design, conduct, and report results of experimental studies using captive elk naturally or experimentally infected with CWD. AGREEMENT OBJECTIVES (I) Conduct and report results of targeted surveillance to estimate and detect changes in distribution of CWD in free-ranging elk populations statewide. f (2) Observe epizootiological features of naturally-occurring CWD in captive elk. MATERIALS AND METHODS Surveillance We monitored elk populations throughout Colorado for occurrence of CWD using a combination of targeted surveillance and harvest or road-kill surveys. These were organized and conducted as follows: Targeted(= clinical disease) surveillance: Elk showing clinical signs consistent with those seen in chronic wasting disease were collected by field personnel statewide and brain tissues examined for evidence of spongiform encephalopathy. The "suspect case" profile was defined as follows: • Species: elk • Age: ::::, 18 months • Signs: emaciated and abnormal behavior &/or indifference to human activity &/or increased salivation &/or tremor, stumbling, incoordination &/or difficulty or inefficiency in chewing/swallowing &/or increased drinking and urination �236 Where possible, submissions were subjected to complete necropsy; in some situations, only heads were available for examination and sampling. In all cases, histopathology of brain tissue (Williams and Young 1993) was used to diagnose CWD; in some cases, immunohistochemistry (O'Rourke et al., 1998) or other ancillary tests were used to confirm or support diagnoses. Harvest surveys: No elk harvest surveys were planned for this segment. Epizootiological Studies Epidemiology of naturally-occurring CWD in captive elk (Miller and Wild): We observed captive adult elk (n = 23) held at CDOW's Foothills Wildlife Research Facility for clinical signs ofCWD and submitted all mortalities for complete necropsy and histopathological examination. RESULTS AND DISCUSSION Surveillance Targeted(= clinical disease) surveillance: Between June 1999 and May 2000, no chronic wasting disease (CWD) cases were diagnosed among 5 "suspect" elk submitted from endemic game management units (GMUs) in northeastern Colorado; CWD was not diagnosed in any of 7 additional "suspect" elk submitted from elsewhere in Colorado. Since 1981, 23 clinical CWD cases have been diagnosed in elk from Larimer County GMUs (Fig. I). Harvest surveys: No elk harvest surveys were conducted in this segment, and none are planned for 20002001. Epizootiological Studies Epidemiology of naturally-occurring CWD in captive elk (Miller and Wild): One of the 23 captive adult elk held at CDOW's Foothills Wildlife Research Facility developed clinical CWD during June 1999-May 2000. The last case in this herd had occurred nearly 5 years earlier (February, 1995; Miller et al. 1998). Exposure to run-off from pens holding CWD-infected deer was the most likely source of infection. We will continue to monitor this naturally-infected captive herd and examine all mortalities for evidence of CWD. ACKNOWLEDGMENTS The statewide CWD monitoring and surveillance program described here relies heavily on efforts of dedicated field personnel throughout the Colorado Division of Wildlife, and truly represents a division-wide effort to improve our understanding and management of this important disease problems. In addition to those specifically listed, we collectively thank all of those regional and area biologists, district and area wildlife managers, volunteers, elk hunters, and others who assisted by submitting suspect cases, harvested animals, or road-killed animals throughout the year. �237 Number of cllnlcal cases per MU In elk I Lara RI River Cache la Pou River 50 100 - ~ ~ ~1~ - k m Figure 1. Between March 1981 and May 2000, 23 clinical CWD cases have been diagnosed in elk from GMUs in Larimer County, Colorado. Cases reported in Wyoming are also shown to provide context on overall geographic distribution of CWD in free-ranging elk. Figure modified from Miller et al. (2000). LITERATURE CITED Miller, M. W., M. A. Wild, and E. S. Williams. 1998. Epizootiology of chronic wasting disease in captive Rocky Montain elk. J. Wildl. Dis. 34: 532-538. Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. J. Kreeger, C. T. Larsen, and E. T. Thome. 2000. Epizootiology of chronic wasting disease in free-ranging cervids in Colorado and Wyoming. Journal of Wildlife Diseases 38: 676-690. O'Rourke, K. I., T. V. Baszler, J.M. Miller, T. R. Spraker, I. Sadler-Riggleman, and D. P. Knowles. 1998. Monoclonal antibody F89/160.1.5 defines a conserved epitope on the ruminant prion protein. J. Clin. Microbiol. 36: 1750-1755. Williams, E. S., and S. Young. 1993. Neuropathology of chronic wasting disease in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Veterinary Pathology 30: 36-45. Prepared by _ _ _ _ _ _ _ _ _ _ _ __ Michael W. Miller Wildlife Research Veterinarian � https://cpw.cvlcollections.org/files/original/c68d6536d44147a37876d9868aa2aac0.pdf 1b145e1e8eea81ec415403a31aaeb1ae PDF Text Text 273 Colorado Division of Wildlife Wildlife Research Report July2000 JOB PROGRESS REPORT State of Colorado Cost Center 3430 Project No. W-153-R-13 Mammals Research Program Work Package No. ----"'3--=-0.a.;03"--------- Carnivorous Mammals Conservation Study No. 1 Black bear muscle physiology Period Covered: July 1, 1999-June 30, 2000 Author: T.D.I. Beck Personnel: T. Beck, R. Firth, CDOW; H. Harlow, M. Hooker, T. Lohuis, L. Willmarth, U. of Wyoming \ ) ABSTRACT In 1999 10 black bears were captured in Grand County for studies on muscle disuse atrophy. Fat and muscle biopsies and blood samples were obtained from all ten bears. No direct in vivo measurements of hind limb muscle strength were obtained because of problems with electrical and computer equipment. Eight radio-collared bears were selected for study in December 1999. Direct muscle strength measurements, fat biopsies, muscle biopsies and blood samples were obtained from all. Six of these 8 bears were re-sampled successfully during the late-den period (March 2000). The other 2 bolted from their dens early and were not captured. Five of the bears handled in March 2000 were equipped with knockdown collars to facilitate recapture in June 2000. None of these collars worked as designed and could not be triggered to inject the immobilizing drug. Conventional trapping produced 6 bears for the comparative summer sample. Two of the ATS knock-down collars have been·retrieved and were submitted for examination to determine cause of failure. Data summary and analyses are still being conducted by U. of Wyoming personnel as the,major part of a Ph.D. dissertation. Final reports will be in the next segment. ) �275 BLACK BEAR MUSCLE PHYSIOLOGY Thomas D. I. Beck SEGMENT OBJECTIVES I. Obtain early-denning and late-denning comparative measurements of muscle strength, morphology, and protein metabolism in order to accurately describe the lack of muscle disuse atrophy. METHODS AND MATERIALS Black bears (Ursus americanus) were captured in cage traps throughout Grand County, Colorado during July 1999 and June 2000. All bears estimated to be adults were instrumented with standard VHF radio transmitter collars. Bears were located by aerial telemetry during the early-denning period ofmidNovember to December. Ground-based telemetry confirmed den entry. The early-season den work was begun as soon as all study bears had denned. Aerial tracking was used in early March to determine if bears had changed dens. All late-denning season work began in mid-March. The primary purpose of this project was to provide study bears for physiological research that is being funded through the Univ. of Wyoming under a National Science Foundation grant. This collaboration has been a joint undertaking since 1993. During den handlings, all bears were initially immobilized with Telazol administered by jab stick at the dosage rate of 7 mg/kg. Following imrilobiliz.ation, bears were removed from the den and placed on a foam pad which was on a tarp for insulation. When precipitation seemed likely, an overhead tarp was erected to keep rain/snow off bear. A sterile opthalmic ointment was placed in each eye and a stocking mask placed on the bear to shield the eyes. Each bear was then weighed. Whole body fat content was measured using bioelectrical impedence (Baumgartner et al. 1990). In vivo muscle strength of the hind limb was measured using a force transducer apparatus modified from a design used for human clinical research by one of the project collaborators (P. Iazzo, U. of Minn.). Electrical stimulation of the perinea! nerve caused the tibialis anterior to contract. This contraction was measured on a force plate. Using sterile surgical techniques, a 1-2 gm muscle biopsy was removed from the vastus Iateralis of the quadraceps. This sample was equally divided into 3 subsamples for later analyses for total protein content, total nitrogen content, RNA content, DNA content, muscle morphometry and fiber type, ubiquitin concentration, and in vitro muscle strength. A small fat sample was also removed from subcutaneous fat reserves for identification of fatty acid profiles. A 15-ml blood sample was obtained by venipuncture in the inguinal region. Blood samples were analyzed for key amino acid levels of activity, ubiquitin messenger RNA, and a general chemistry screen. All of the surgical procedures and laboratory -analyses were conducted by Dr. Henry Harlow and graduate student Tom Lohuis of the Univ. of Wyoming under a joint NSF grant. During the early-denning sample period, all biopsies were taken from the left hind limb while during the late-denning sample period the right hind limb was used. The in vivo muscle strength measurements were taken on the left hind limb in both periods. Following the work-up, all bears were placed back in their dens and the den entrances covered. In addition, 5 of the black bears handled in March 2000 were instrumented with knock-down collars manufactured by Advanced Telemetry Systems. These collars held syringes loaded with ketamine/xylazine �276 which could be activated by radio transmitter. The plan was to obtain the same data as collected in winter during the summer from the identical study bears. As a back-up to this system, traditional trapping protocols with cage traps would be implemented if needed to obtain a summer cohort of bears. Bears captured in June 2000 for this project were not radio instrumented and radio collars were removed from . any bears handled in June 2000. RESULTS AND DISCUSSION During July 1999 IO black bears were captured and collared. In vivo strength measurements were not obtained on any of these bears because of problems in both software and electrical hardware needed. The equipment had been modified to reduce the weight and volume of equipment. Bench tests of the equipment had been successful but we were unable to make the needed corrections once the field problems occurred during July 1999. The equipment was corrected before the den seasons. However, muscle and fat biopsies were obtained from all ten (9 males, 1 female) bears. During the early denning period (Nov-Dec 1999) 7 of these bears were located as well as 8 bears collared in previous years. From this group, a subset of 8 (7 females, 1 male) were selected for denning studies. Criteria for selection were primarily gender (females move less than males) and ease of den access based on topography, avalanche danger, and land ownership. Muscle and fat biopsies, blood samples, and in vivo muscle strength measurements were obtained for all 8 bears. Sampling was repeated in March 2000 on 6 of these 8 bears. All samples and measurements were successfully obtained on these six. One 1female black bear exited her den unusually early (early March) and did not return while another female exited her den upon the approach of the field crew. Neither of these bears re-denned so could not be captured. Five of these bears (4 females, 1 male) were fitted with the ATS knock-down collars while the remainder had a conventional radio collar. During June 2000, 4 of the 5 bears equipped with ATS knock-down collars were located via aerial and ground telemetry. Numerous attempts were made to activate the syringes on the collars for each of the 4 bears. None worked. Conventional trapping resulted in a total of 6 bears captured. One recapture had an ATS knock-down collar on while another recapture had a conventional collar. Additionally, a male equipped with the ATS knock-down collar was struck by a vehicle and killed. Thus we obtained 2 of the collars for analysis of the malfunctions. The 6 bears captured in June 2000 (5 males, 1 female) provided muscle biopsies, blood samples, and measurements of muscle strength. All laboratory analyses have been conducted by collaborators at University of Wyoming. However, data analysis has not been completed but should be in final form and will be the major portion of the Ph.D. dissertation of Tom Lohuis (expected completion Spring 2001). All surgical incisions were carefully examined during subsequent handlings. All healed without problems. No further data will be collected for these studies in the next segment. Analyses will be completed and an effort will be made in December 2000 to locate collared bears and remove as many collars as is feasible. LITERATURE CITED Baumgartner, R. N., W. C. Chumlea, and A. F. Roche. 1990. Bioelectrical impedance for body composition. Exercise and Sport Reviews 18:193-224. � https://cpw.cvlcollections.org/files/original/5e679ecf369ff3b260c49cfba6dcf0ab.pdf 96582220480cfba835ae39a0e0992563 PDF Text Text 235 Colorado Divison of Wildlife Wildlife Research Report July 1998 JOB FIHAL REPORT state of Colorado cost center 3430 Project No. W-153-R-11 Mammals Program Work Package No. _ _,,3~P~P~3_ _ _ __ Predatory Mammals Management Task No. Use of Sport Hunting to Reduce Puma Depredation on sheep Period Covered: July 1, 1997 - June 30, 1998 Author: Thomas D. I. Beck Personnel: T. Beck, J. Madison, J. Wallace; CDOW ABSTRACT A puma density sampling protocol was prepared based on probability sampling along line transects. A prototype sampling unit was designated. However, the appropriate snow conditions did not occur in Jan.-Mar., 1998 to allow for sampling. An evaluation of the logistical constraints on the technique, along with loss of management authority, resulted in the termination of the study. �237 Use of Sport Bunting to Reduce Puma Depredation to Sheep P.H. objectives 1. Evaluate the efficacy of liberal sport hunting quotas to reduce the density of puma. 2. Investigate the relationship of puma density to depredation levels on domestic sheep. segment Objectives 1. Compile historic data on sport kill of puma and puma depredation on sheep in DAU L-7. 2. Prepare detailed protocol on transect sampling and puma density estimation. 3. Conduct puma density estimation transects on 2 study areas. METHODS AND MATERIALS Kill of puma (.E.e.l..i.a. concolor) by hunters was tabulated from mandatory check files for the years 1988-1997 for DAU L-7. The frequency distribution of kill by time was calculated in one-week intervals in hopes of identifying periods where sampling would have minimal impact on hunting activities. Based on location of historic kills and terrain considerations, a pilot study site of approximately 400 Jan2 was delineated in the Piceance creek drainage. A detailed sampling protocol was prepared based on the techniques described by Becker (1991) and Van Sickle and Lindsey (1991). RESULTS AND DISCUSSION Hunter kill of puma increased from 12 in 1988 to 80 in 1997 in DAU L-7. The marked increase in kill began in 1993 and was the result of greater quotas allocated in hopes of reducing puma depredation on domestic sheep. During the period 1995-1997 a total of 209 puma were taken by hunters and an additional 30 were taken by either landowners or predator control agents in DAU L-7. Game damage payments for puma depredation statewide varied from $46,000 to $60,000 per year during 1988-1991. Since 1992 the annual payments have varied from $93,000-$132,000. The relative importance of possible causative factors is unknown. Approximately 50% of the statewide puma damage payments are made in DAU L-7. A detailed sampling protocol was prepared (Appendix A) but never implemented. During the January-March 1998 sampling period adequate snow cover did not exist in the sampling block. In trying to implement the sampling scheme several serious logistical impediments became apparent. Scheduling of helicopter time was problematic because of restrictions with state contracts and the higher priority status of ungulate census and survival work. The puma census would have to compete with other on-going work for both helicopter and personnel time. �238 The logistical impediments, along with the changed management status of puma in Colorado (shared authority with Colorado Dept. of Agriculture), make the successful completion of this job improbable. Thus it was decided by participants to cease the effort at density estimation for future years. �239 Appendix A PROTOCOL FOR PROBABILITY SAMPLING OF PUMA DEIISITY SAMPLING AREA: Area should be a rectangle of at least 390 km 2 , and must be at least 13 km wide on the shortest axis (baseline axis). The long axis (transect axis, 30 km) should be perpendicular to the majority of the major drainages in the area. You must delineate a specific rectangular area in order to make inclusion judgments. TRANSECTS: At least 3 transects should be flown in a straight line along the long axis for the entire 30 km length. Transect 1 should be randomly selected to start within the first 3 kms of the baseline axis. The remaining transects should be spaced 4 km distant (Example: Transect 1 begins at baseline point of 2 km, No. 2 at 6 km, No. 3 at 10 km). Flight time will be about 60 minutes to fly a 30 km transect plus about 10 minutes of search time per puma track set. MODIFICATIONS: If a 30 km transect cannot be fitted into the areas of concern, the long axis can be shortened. However, total area should remain at least 400 km2 and transects should be separated by at least 4 km. Thus a 20X20 km area would have 5 transects flown, of 20 km each. Long (30 km) transects are more efficient in terms of flight time. SURVEY PERIOD: The helicopter surveys should be flown 2-3 days following a snowfall which is sufficiently deep as to not melt out within 48 hours and completely cover old tracks (about 8 cm). Very deep snows (>20 cm) restrict puma movement and are to be avoided. Optimum snow depth would be 8-12 cm. There must be at least one complete night for movement following the snow. A 2-night period is better unless very high winds are occurring; however, more than 2 nights creates difficulty because of other animal tracks and wind-blown snow. PROCEDURE: Surveys should be conducted by a crew consisting of a trained observer and a navigator. The navigator should have detailed knowledge of the terrain. While biologists may be excellent observers, we should try to utilize experienced puma hunters for observers as they will more easily detect the track patterns of puma. All locations should be recorded by UTM. Fly a straight line along Transect 1 until a puma track is encountered. Record location. Fly the backtrack until you find where puma started moving following snowfall; record the location of the point where the track is farthest from the transect. Fly the front track until you locate puma (often you will not see animal but will see where tracks end in heavy cover); record location of the point where the track is farthest from the transect. Because of the non-linear nature of travel, the beginning and ending points may not be the farthest distance traveled parallel to the baseline axis. Record the extreme distances from the transect. Return to original transect line at the point where track was located. Continue along the line until the next puma track is encountered. Repeat the process to estimate travel distance for each set of tracks. The objective is to obtain a straight-line distance of travel parallel to the base-transect. At the end of transect 1, move 4 Jans along the baseline and return along transect 2, which parallels transect 1. Multiple puma tracks traveling together (female w/kittens or male-female pair) should only be counted as 1 track set. However, make a notation of the group size. There are separate analysis procedures which can be used if this is a common occurrence. �240 Do not count kitten tracks traveling separate from the mother. This is an unlikely occurrence and distinguishing from bobcat tracks while airborne is quite problematic. Kill sites will be characterized by lots of tracks in the near vicinity of the kill. Estimate the diameter of the circle which would include all the tracks. This diameter will be used as the travel distance. Most straight-line travel distances will be less than 3 km. However, in the event that a puma track crosses 2 transects, it should be separately recorded for each transect. Data to be recorded: location of each puma track along each transect; location of farthest points of travel of puma perpendicular to the transect; all in UTM's. Data to be calculated: straight-line distance parallel to baseline moved by each puma, in km's. Data for any puma where >50% of the travel distance was outside the designated rectangular survey area will not be used in the calculations. ANALYSIS: Population size is estimated from the following equations, from Becker (1991) and Van Sickle and Lindzey (1991): P;=x/(D/q) ½=L (lip;) where Pi= probability that the ith puma i sample; xi= distance, parallel to the baseltoetatnedeledtb~ Yhb aystpmaalcD = length of baseline; q = number of transects per systematic sample; and Tj = population estimate for the jth systmatic sample. since we will not be flying replicate samples for an area, variance of the estimate will be estimated using jackknife procedures and dividing the transects into segments (McDonald and Manly 1989). This will be done by a contract statistician. While replication is the preferred methodology, helicopter costs make this prohibitive. ASSUMPTIONS FOR PROBABILITY SAMPLING PROCEDURE: 1. 2. 3. 4. 5. 6. 7. 8. All animals move during the survey period. Puma tracks are readily recognizable. All animal tracks are continuous. Animal movements are independent of the sampling process. Post-snowstorm tracks can be distinguished. All puma tracks crossing a transect will be observed. Study area is rectangular in shape. All the transects are oriented perpendicular to the baseline axis. LITERATURE CITED Becker, E. F. 1991. A terrestrial furbearer estimator based on probability sampling. J. Wildl. Manage. 55(4):730-737. Van Sickle, w. D. and F. G. Lindzey. 1991. Evaluation of a cougar population estimator based on probability sampling. J. Wildl. Manage. 55(4):738743. � https://cpw.cvlcollections.org/files/original/06dc6b096d152e191d3c010703b1a9b0.pdf 95f42b9124861b075e9f8e6280eb7479 PDF Text Text 245 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT State of Colorado cost center 3430 Project No. W-153-R-ll Mammals Program Work Plan No. 3004 Management of other ungulates Task No. Strategies for Managing Pasteurellosis in Mountain Sheep Populations Period Covered: July 1, 1997 - June 30, 1998 Authors: M. W. Miller and H.J. McNeil Personnel: s. Berry, J. George, K. Larsen, J. Vayhinger, T. Verry ABSTRACT We continued investigations of multivalent Pasteurella haemolytica supernatant vaccines in captive bighorn sheep (Ovis canadensis). A vaccine lot(PhSV lot #970520) that combined bighorn and domestic strains appears to contain antigenicity comparable to that of the original multivalent vaccine, and was selected for use in future laboratory and field studies. To evaluate vaccine delivery options, 30 captive bighorns were divided into 3 groups of 10 based on vaccine history and baseline P. haemolytica leukotoxin neutralizing antibody titers; treatment groups included hand injection, biobullet implantation and oral gavage of PhSV. Serum leukotoxin-neutralizing antibody titers differed among delivery treatments (P = 0.009). Neutralizing titers were highest among hand-injected bighorns; no serum antibody response was detected among bighorns vaccinated orally. Although neutralizing titers were lower among implanted bighorns than in the hand injected controls (P < 0.021), seroconversion rates did not differ (implantation= 6/10, hand injection= 9/10; P = 0.303). Although our data demonstrated that handinjection elicits higher absolute titers than either biobullet implantation or oral vaccination, biobullet implantation may also stimulate effective antibody responses to P. haemolytica supernatant vaccines. Further evaluation of biobullet vaccination against pneumonic pasteurellosis in free-ranging populations of wild bighorn sheep appears warranted. A total of 110 free-ranging bighorn sheep from 4 different herd units. in central Colorado were vaccinated with PhSV during January-March 1998. No adverse reactions or mortalities were detected among vaccinated bighorns through June 1998. Ongoing monitoring in the Tarryall-Kenosha herd complex will provide additional data on efficacy of vaccination to protect freeranging bighorns from pasteurellosis under field conditions. �247 EXPERIMENTS TO IDENTIFY AND MANAGE STRESS IN MOUNTAIN SHEEP POPULATIONS M. W. Miller and H.J. McNeil P, H, OBJECTIVES 1. Design, conduct, and report on experiments evaluating Pasteurella haemolytica vaccines and vaccine delivery systems and identify those with potential application in managing free-ranging bighorn populations. 2. Design, conduct, and report on field experiments evaluating management strategies for preventing pasteurellosis epizootics in bighorn populations SEGMENT OBJECTIVES 1. Conduct and report results of an experiment evaluating options for delivering a multivalent Pasteurella haemolytica supernatant vaccine to bighorn sheep. 2. Provide multivalent Pasteurella haemolytica supernatant vaccine for use in select bighorn sheep management activities statewide. STRATEGIES FOR MANAGING PASTEURELLOSIS IN MOUNTAIN SHEEP POPULATIONS Inability to control infectious disease outbreaks and subsequent mortality in mountain sheep populations represents a significant obstacle to long-term success in their management. Although the "bighorn pneumonia complex" has been studied intensively for over 3 decades, little is known about many aspects of its etiology and epizootiology. Moreover, management interventions recommended for preventing or controlling this problem remain untested. Although viral, bacterial, and parasitic agents have all been incriminated in these outbreaks, Pasteurella spp. are perhaps the most common pathogens associated with bronchopneumonia in bighorns. Two species, P. haemolytica and P. multocida, and several biotypes and/or serotypes within those species, have been isolated from bighorns during epizootics. Unfortunately, despite extensive diagnostic and experimental investigation, the epizootiology of pasteurellosis in wild bighorn populations is poorly understood. In the absence of knowledge about the epizootiology of pasteurellosis, effective strategies for managing pneumonia in bighorn populations have not emerged. Here, we report on a series of ongoing research studies designed to improve knowledge about various aspects of pasteurellosis epizootiology and management in bighorn sheep. METHODS ARD MATERIALS Refinement of experimental Pasteurella haemolytica supernatant vaccine (McNeil, Miller, and Shewen): A rabbit study was previously conducted with Pasteurella haemolytica supernatant vaccine (PhSV) lot #970520 (Miller and McNeil, 1997). Rabbits were exsanguinated after receiving three 0.5 ml doses �248 of vaccine at 2-wk intervals. All rabbits responded to vaccination by producing anti-leukotoxin antibodies. Protein profiles from Western blots (blotted with vaccinated rabbit serum) transferred from 12% precast PAGE gels containing the vaccine components of both PhSV lot #970520 and multivalent vaccine lot# 940902 (Miller et al., 1997) also showed strong vaccine-induced antibody reactivity. Based on these findings, a small pilot study in bighorn sheep was conducted. Six captive Rocky Mountain bighorn sheep were used. Sheep were paired on the basis of age and vaccination history. One bighorn from each pair received 2 ml PhSV lot #970520 intramuscularly; the other animals received 1 ml PhSV lot #970520 and 1 ml Presponsee mixed in the same syringe, delivered intramuscularly. (Presponsee is a commercially available supernatant vaccine of Pasteurella haemolytica Al.) We used this approach to establish whether the presence of P. haemolytica serotype Al was necessary to drive the marked increase in leukotoxin neutralizing titer seen in previous studies (Miller et al., 1997; Kraabel et al., 1998). Animals were bled prior to vaccination and again at day 7 and day 14. Serum leukotoxin neutralizing antibody titers stimulated by the two treatments were measured and compared using methods described by Miller et al. (1997). Delivery of Pasteurella haemolytica supernatant vaccine to bighorn sheep (McNeil and Miller): Thirty captive bighorn sheep were used in this study. Animals were divided into three groups of ten based on their vaccine history and baseline neutralizing titers. The three treatment groups included hand injection, biobullet implantation and oral gavage of vaccine. Four additional animals were intramuscularly injected with saline to monitor for changes in antibody titers unrelated to vaccination during the study period. PhSV lot #970520 was used for all treatments. Vaccine was lyophilized for use in biobullets and microspheres. The standard dose for intramuscular injection, 2 ml (Miller et al., 1997; Kraabel et al., 1998), yielded about 0.025 g lyophilized vaccine. Biobullets were packed with about 0.030 g lyophilized vaccine, then filled with methylcellulose filler for remote delivery. Lyophilized vaccine was also sent to Dr. Harm HogenEsch of Purdue University for encapsulation in alginate microspheres; 5 ml of alginate microsphere suspension was recommended as equivalent to a 2 ml dose of vaccine. The hand injection group received 2 ml PhSV injected intramuscularly into the left haunch. The biobullet group were vaccinated with the use of a specialized biobullet rifle from a distance of approximately 4 meters. Animals in this group had a small area on their left hindquarters shaved to facilitate confirming implantation. Animals receiving vaccine orally were dosed with the aid of a small stainless steel gavage tube. The tube was inserted into the animal's mouth and laid along the teeth; 5 ml of vaccine was then squirted into the sheep's mouth and subsequently swallowed. Animals were bled prior to vaccination and again at 1, 2, 4, 8 and 12 weeks postvaccination. Sera were collected and used to assess serological responses. Titers were measured using a leukotoxin neutralization assay, along with three separate direct agglutination assays that incorporated formanilized Pasteurella haemolytica serotypes Al, A2 or Tl0 as antigen (Miller et al., 1997; Kraabel et al., 1998). use of Pasteurella haemolytica supernatant vaccine in free-ranging bighorn .ab.e,ep (Miller, George, and Vayhinger): A total of 110 free-ranging bighorn sheep from 4 different herd units in central Colorado were vaccinated with �249 PhSV during January-March 1998 (Table 1). Bighorns from Georgetown herd unit were vaccinated just prior to translocation to the Arkansas River canyon for release; nearby resident bighorn populations appear to have recurrent problems with respiratory disease in this area, and translocated bighorns were considered potentially at risk. Bighorns in the Black Canyon and Twin Eagles herd units of the Tarryall-Kenosha complex were vaccinated in an attempt to prevent spread and/or minimize impacts of a pasteurellosis epidemic that started in the Sugarloaf herd unit in December 1997 (see WP7610-T4 for details); a few sheep in the Sugarloaf herd also were vaccinated in an attempt to enhance postepidemic survival in that subpopulation. Survival of vaccinated and unvaccinated individuals was compared opportunistically in conjunction with ongoing field studies. RESULTS AHD DISCUSSION Refinement of experimental Pasteurella haemolytica supernatant vaccine (McNeil, Miller, and Shewen): We observed no adverse effects in bighorns receiving PhSV lot #970520. All vaccinated bighorns responded with an increase in leukotoxin neutralizing titer. Based on these results, PhSV lot #970520 was judged an appropriate vaccine for use in the delivery experiment and in field applications. Delivery of Pasteurella haemolytica supernatant vaccine to bighorn sheep (McNeil and Miller): other than a mild transient lameness in animals vaccinated intramuscularly or remotely, no adverse reactions were observed following vaccination. Serum neutralizing antibody titers to P. haemolycica leukotoxin differed among delivery treatments (P=0.009) as well as among baseline titer/vaccination history groups (P=0.013). Neutralizing titers were highest among hand-injected bighorns; no serum antibody response was detected among bighorns vaccinated orally. Although neutralizing titers were lower among implanted bighorns than in the hand injected controls for ~2 weeks post vaccination (P < 0.021), seroconversion rates (defined as a ~2 log 2 increase in titers) in response to implantation (6/10) and hand injection (9/10) did not differ (P=0.303). Agglutinating antibody titers to Tl0 were high and did not differ over time or between delivery treatments. In addition, agglutinating antibody titers to Al did not vary over time or between groups. Agglutinating antibody titers to A2 were higher in the hand injected group than the orally vaccinated sheep during the time period between 2 and 4 weeks post vaccination (P < 0.026); A2 agglutinating titers in hand-injected and implanted sheep did not differ during the same time period (P = 0.07). Vaccination history/baseline titer categorization affected responses to serotype A2 surface antigens (P = 0.0001). our data support previous observations (Miller et al., 1997; Kraabel et al., 1998) that hand-injected P. haemolycica supernatant vaccines stimulate marked antibody responses in bighorn sheep; it follows that delivery via projectile syringe should stimulate similar antibody responses. Although our data demonstrate that hand-injection elicits higher absolute titers than either biobullet implantation or oral vaccination, biobullet implantation may also stimulate effective antibody responses to P. haemolycica supernatant vaccines. Whether lack of serum antibody response to oral vaccination truly reflects failure to stimulate immunity remains undetermined. Further evaluation of biobullet vaccination against pneumonic pasteurellosis in free-ranging populations of wild bighorn sheep appears warranted. �250 use of Pasteurella haemolytica supernatant vaccine in free-ranging bighorn Jlhe8l2 (Miller, George, and Vayhinger): As with previous captive animal studies (Miller et al., 1997; Kraabel et al., 1998; McNeil and Miller, above), no adverse effects were observed in free-ranging bighorns that received PhSV via hand-injection, projectile syringe, or biobullet implant. No mortality was been detected among vaccinated bighorns in the 4-6 mo after vaccination; however, little or no mortality occurred among unvaccinated bighorns in these populations during that time. We will continue to monitor survival rates among vaccinated and unvaccinated bighorns in the Tarryall and Kenosha subpopulations in conjunction with other ongoing studies. These data should be useful in evaluating efficacy of vaccination in protecting freeranging bighorns from pasteurellosis under field conditions. Kraabel, B. J., and M. W. Miller, J. A. Conlon, and H.J. McNeil. 1998. Evaluation of a multivalent Pasceurella haemolytica vaccine in bighorn sheep: Protection from experimental challenge. Journal of Wildlife Diseases 34: 325-333. Miller, M. W., J. A. COnlon, H.J. McNeil, J.M. Bulgin, and A. C. S. Ward. 1997. Evaluation of a multivalent Pasceurella haemolycica vaccine in bighorn sheep: Safety and serologic responses. Journal of Wildlife Diseases 33: 738-748 . ....._.L.-..lH.cer Wildlife Research Veterinarian Table 1. Free-ranging bighorn sheep treated with multivalent Pasceurella haemolycica supernatant vaccine during Jan-Mar 1998. Population (Herd Unit) Delivery Status Band Dart Biobullet healthy -translocated to Arkansas R. 25 0 0 healthy, future exposure likely 35 4 5 (Twin Eagles) healthy, future exposure likely 21 6 3 (Sugarloaf) pasteurellosis epidemic (12/97) 11 0 0 Georgetown (Georgetown) Tarryall-Kenosha (Black Canyon) �287 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB PROGRESS REPORT -------~-~---- State of Colorado Project No. --------'W-'--.....1=5"-3--=-R"---=12=-----.........,. ___________ Work Plan No. 3004 Task No. 3 ____ ------------- Cost Center 3430 Mammals Program Management of Other Ungulates Strategies for Managing Pasteurellosis in Mountain Sheep Populations Period Covered: July I, 1998 -June 30, 1999 Authors: M. W. Miller, H.J. McNeil, and J. L. George Personnel: K. Larsen, S. Berry, J. Vayhinger ABSTRACT A pasteurellosis epidemic that began in the Sugarloaf Mountain subpopulation of the Tarryall-Kenosha bighorn herd complex extended to two adjacent subpopulations (Black Canyon, Twin Eagles) during winter 1998-1999. Sick and dead bighorns were found in the Twin Eagles subpopulation by December 1998, and in the Black Canyon subpopulation by January 1999. Based on preliminary data, vaccination with PhSV 911 mo earlier did noi appear to improve bighorn survival during subsequent epidemics. A group of bighorns translocated from Dome Rock to the Holy Cross Wilderness received PhSV during winter 1998-1999. No adverse effects have been observed in free-ranging bighorns that received PhSV last winter, or during 1997-1998. We began developing and evaluating a modified-live P. haemolytica vaccine. Using polymerase chain reaction (PCR) techniques, we screened candidate carrier strains and further characterized bacterial genomes linked to leukotoxin production. Leukotoxin A (//eta) gene of P. haemolytica TIO Eco. 100 was successfully amplified, and subsequent sequencing revealed that the I/eta gene ofthis bighorn-derived strain was approximately homologous to the published //eta gene of P. haemo/ytica TIO. We successfully ligated 123 and 1767 bp gene fragments. Initiaj. attempts to use PCR to increase yields for cloning failed, but such efforts continue. Plasmid transfers of I/eta are planned for next segment. �288 �289 EXPERIMENTS TO IDENTIFY AND MANAGE STRESS IN MOUNTAIN SHEEP POPULATIONS M. W. Miller, H.J. McNeil, and J. L. George P. N. OBJECTIVES 1. Design, conduct, and report on experiments evaluating Pasteurella haemolytica vaccines and vaccine delivery systems and identify those with potential application in managing free-ranging bighorn populations. 2. Design, conduct, and report on field experiments evaluating management strategies for preventing pasteurellosis epizootics in bighorn populations SEGMENT OBJECTIVES 1. Report results of an experiment evaluating options for delivering a multivalent Pasteurella haemolytica supernatant vaccine to bighorn sheep. 2. Provide multivalent Pasteurella haemolytica supernatant vaccine for use in select bighorn sheep management activities statewide. 3. Begin development and evaluation of a modified-live Pasteurella haemolytica vaccine for use in bighorn sheep. STRATEGIES FOR MANAGING PASTEURELLOSIS IN MOUNTAIN SHEEP POPULATIONS Inability to control infectious disease outbreaks and subsequent mortality in mountain sheep populations represents a significant obstacle to long-term success in their management. Although the "bighorn pneumonia complex" has been studied intensively for over 3 decades, little is known about many aspects of its etiology and epizootiology. Moreover, management interventions recommended for preventing or controlling this problem remain untested. Although viral, bacterial, and parasitic agents have all been incriminated in these outbreaks, Pasteurella spp. are perhaps the most common pathogens associated with bronchopneumonia in bighorns (Miller, 1999). Two species, P. haemolytica and P. multocida, and several biotypes and/or serotypes within those species, have been isolated from bighorns during epizootics. Unfortunately, despite extensive diagnostic and experimental investigation, the epizootiology of pasteurellosis in wild bighorn populations is poorly understood. In the absence of knowledge about the epizootiology ofpasteurellosis, effective strategies for managing pneumonia iif bighorn populations have not emerged. Here, we report on a series of ongoing research studies designed to improve knowledge about various aspects of pasteurellosis epizootiology and management in bighorn sheep. �290 METHODS AND MATERIALS Delivery of Pasteurella haemolytica supernatant vaccine to bighorn sheep (McNeil and Miller): Last segment we conducted an experiment evaluating options for delivering a multivalent Pasteurella haemolytica supernatant vaccine (PhSV) to bighorn sheep. A draft manuscript describing that research was accepted for publication in the Journal of Wildlife Diseases (see abstract, Appendix A). Use of Pasteurella haemolytica supernatant vaccine in free-ranging bighorn sheep (Miller, George, and Vayhinger): We continued evaluating survival of free-ranging bighorn sheep vaccinated with PhSV in the face of a pneumonia epidemic during winter 1997-1998 by comparing survival rates of vaccinated bighorns to those of unvaccinated individuals. Our evaluation was conducted in conjunction with other ongoing studies of the Tarryall-Kenosha bighorn herd complex. In addition, PhSV was used in select field operations during the winter of 1998-1999 (Table 2). We also continued exploring ways of adding Pasteurella multocida antigens to our vaccine formulation. Development of a modified-live Pasteurella haemolytica vaccine for bighorn sheep (McNeil, Lo, and Miller): We prepared a study plan and began developing and evaluating a modified-live Pasteurella haemolytica vaccine. Highlights of preliminary laboratory technique development and evaluations are reported. Bacteria: Pasteurella haemolytica TIO <Ea,_100) was obtained from a bighorn sheep that died during a pasteurellosis epidemic in southcentral Colorado in 1990 (Kraabel et al., 1997). Bacterial stocks were kept frozen at -70° C in Brain Heart Infusion Broth (BHIB) with 15 % glycerol. Thawed stock was used to inoculate blood agar plates incubated at 37° C overnight (0/N). A small volume (50 ml in a 175 ml Erlenmeyer flask) ofBHIB was inoculated with a single colony from the 0/N agar plate and incubated at 37° C, 120 rpm 0/N. The resulting culture was used to extract DNA for use in polymerase chain reactions (PCR). Preparation ofgenomic DNA: Two commercial kits were used to extract maximum amounts of genomic DNA fromP. haemolytica TIO <Eco.100). A QIAGEN Genomic-tip® (QIAGEN Inc., Mississauga, ON, Canada) was used and DNA was extracted according to the Bacterial DNA Isolation Protocol in the QIAGEN Genomic DNA Handbook. A PUREGENE® genomic DNA isolation kit (Gentra Systems, MN, USA) was also used to improve yields. Genomic DNA was used as template for subsequent PCR. PCR: PCR was utilized to amplify the leukotoxin A gene (lkta) of P. haemolytica TIO <Ea,_100). Many different primers and conditions were assessed. The gene was successfully amplified using primers based on the published P. haemolytica TIO Ieukotoxin A gene sequence (Genbank Accession Z26247). 5'-ATGGGAACTAAACTAACCCT-3' 5'-TAAGCTGCTCTAGCAAATTG-3' Conditions were optimized at 3.5 mM [Mg++] using the genomic DNA prepared by the PUREGENE® method as template. The thermal cycler (Perkin Elmer-,Cetus, NoFWalk, Connecticut, USA) was programmed for 94 C for 30 seconds, 51 C for 30 seconds, 72 C for 3 minutes and 30 seconds. This was repeated for 30 cycles. Two sections of the lkta gene also were amplified via PCR for use in subsequent ligation. Similarities between the sequence of the lkta gene for Eco. 100 and P. haemolytica Al (Genbank Accession M20730) were considered. Previous work in our laboratory (R. Lo, unpubl. data) used two existing Nael sites on the �291 lkta gene to delete a section of the gene and ligate the smaller fragments together to form a truncated gene. Although the Nae! sites on the lkta Eco.ioo were not a perfect match, using primer design, two sections were amplified. These sections incorporated exact Nae! restriction sites. The 123 base pair segment from the 5' end of the gene was amplified using the following primers: 5'-GGATCCCTIATGGGAACTAAAC-3' 5'-0TCTGGCCGGCTIGGGTIAA-3' The 1767 base pair segment from the 3' end of the gene was amplified using the following primers: 5'-TGCCGCCGGCTCTGTGGTI-3' 5'-CGAAACAATCTAGAGTIGCCAATC-3' Conditions were optimized at 3.5 mM [Mg++] using the genomic DNA prepared by the PUREGENE~ method as template. The thermal cycler was programmed for 94 C for 30 seconds, 59 C for 30 seconds, 72 C for 3 minutes and 30 seconds. This was repeated for 30 cycles. PCR was also used to try to increase the amount of ligated product. The following primers were used: 5'-GGATCCCTTATGGGAACTAAAC-3' 5'-CGAAACAATCTAGAGTTGCCAATC-3' Conditions were optimized at 3.5 mM [Mg++] using gel purified ligated product as the template. The thermal cycler was programmed for 94 C for 30 seconds, 64 C for 30 seconds, 72 C for 3 minutes and 30 seconds. This was repeated for 30 cycles. All PCR products were run on 0.75 % agarose gels (85 V for 23-45 minutes) and stained with ethidiurn bromide. Bands were visualized using ultra-violet (UV) light and the image captured by a GelDoc 1000 machine (Bio-Rad Laboratories, Mississauga, ON, Canada). PCR Product Purification: PCR products to be sequenced or used for further manipulation were purified using a QIAGEN QIAquick PCR purification kit~. Purified product was run on gels as before purification to ensure that the band in question was still visible. In instances where extraneous bands were visible, gel extraction was used to isolate the desired product. A low melting point 1.0% agarose gel was loaded with product and run at low voltage overnight (8-9 V, 1216 hours). The gel was then stained with ethidiurn bromide and visualized using UV light on a transillurninator. The desired band was cut out using a sterile scalpel blade and put into a tube. The tube was heated to melt the agar. This material was then purified in the same manner as the non-gel purified PCR products. Restriction Enzyme Digestion: Purified 123 bp and 1767 bp fragments were digested using Nae! (Promega 'Corporation, Madison, WI, USA ) with the recommended buffer for 1 hour at 37 C. The enzyme was then inactivated at 60 C for 15 minutes. A 1 µI aliquot was run on a 0.75% agarose gel to ensure product integrity. These products were to be ligated together. Restriction enzyme digestion was also used for mapping the ligated product_ Digestions were performed using Nae!, Apa! (Promega Corporation, Madison, WI, USA) and Sacl (New England Biolabs Ltd., �294 APPENDIX A EFFECTS OF DELIVERY METHOD ON SEROLOGICAL RESPONSES OF BIGHORN SHEEP TO A MULTIVALENT PASTEURELLA HAEMOLYTICA SUPERNATANT VACCINE Heather J. McNeil,1 Michael W. Miller,2 Jennifer A. Conlon,3 Ian K. Barker,1 and Patrica E. Shewen1 1 Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, Ontario, NlG 2Wl, Canada 2 Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect Road, Fort Collins, Colorado 80526-2097, USA 3 Merial Incorporated, 115 Transtech Drive, Athens, Georgia, 30601-1649, USA ABSTRACT: The efficacy and safety of a multivalent Pasteurella haemolytica supernatant vaccine (serotypes A2 and TIO) using different delivery systems were examined in captive Rocky Mountain bighorn sheep (Ovis canadensis canadensis). Twenty bighorn sheep were grouped according to baseline leukotoxin neutralizing antibody titers (~2 or >2 log/) and vaccination history (previously vaccinated or unvaccinated). Within these groups, animals were randomly assigned to one of two delivery treatments: hand injection (control) or biobullet implantation. All bighorns received a single dose from the same lot of vaccine (n = IO/treatment); four additional animals were injected intramuscularly with 0.9% saline as unvaccinated sentinels. Mild, transient lameness one day after hand injection or biobullet implantation was the only adverse effect. Serum neutralizing antibody titers to P. haemolytica leukotoxin differed among delivery treatments (P = 0.009) and among baseline titer/vaccination history groups (P = 0.013). Neutralizing titers were highest among hand-injected bighorns. Although neutralizing titers were lower among implanted bighorns than hand-injected controls at 1 wk (P = 0.002) and 2 wk (P = 0.021) after vaccination, seroconversion rates in response to implantation (6/10) and hand injection (9/10) did not differ (P = 0.303). Agglutinating antibody titers to TIO were high and did not vary over time or between delivery treatments. Agglutinating antibody titers to A2 in the hand-injected controls were not different (P £ 0.07) than those in bighorns vaccinated with biobullet implantation. These data demonstrate that although hand injection elicits higher absolute titers, biobullet implantation may also stimulate effective antibody responses to P. haemolytica supernatant vaccine. Further evaluation of biobullet vaccination against pneumonic pasteurellosis in free-ranging populations of wild bighorn sheep is warranted. Key words: Bighorn sheep, Ovis canadensis, Pasteurella haemolytica, pasteurellosis, vaccine delivery, vaccination. �277 \ Colorado Division of Wildlife Wildlife Research· Report July 2000 JOB PROGRESS REPORT State of _ _ _ _ _.... C=o=lo=rad=o'------- Cost Center 3430 Project No. -----'W;.;.....:-1=5=3--=R....--=-1=-3_ _ _ __ Mammals Program Work Plan No. ___................. 3004 ______ Task No. _ _ _ _ __.:.,1_ _ _ _ __ Management of Other Ungulates Strategies for Managing Pasteurellosis in Mountain Sheep Populations Period Covered: July 1, 1999 - June 30, 2000 Authors: M. W. Miller, R E. Briggs, and H. J. McNeil Personnel: K. Larsen, S. Berry, J. George, J. Vayhinger \ / I ABSTRACT We continued developing and evaluating modified-live Pasteurella spp. va~ines for use in bighorn sheep mangement. Based on preliminary successes in protecting both cattle and domestic sheep from experimental pasteurellosis, we began a pilot study to evaluate a genetically-modified live P. haemolytica vaccine (GMLPhV)in captive bighorns. Vaccine was supplied by USDA/ARS/NADC in Ames, IA. Of3 bighorns receiving about 7 x 108 colony forming units (CFUs) ofGMLPhV, 1 died about 3 days after vaccination and another showed signs of moderately severe respiratory disease from days 2-10 postinoculation (Pl); the GMLPhV strain was most likely responsible for morbidity and mortality in . vaccinated bighorns. Two previously unvaccinated bighorns housed with the 2 surviving vaccinates ·beginning 2 weeks PI seroconverted to P. haemolytica serotype 2 2-3 weeks later, suggesting colonization of these in-contact animals by GMLPhV strain despite failure to actually isolate GMLPhV strain from either in-contact bighorn. Both in-contact bighorns remanied healthy through 7 weeks postexposure. Ability of GMLPhV to protect bighorns from pasteurellosis will be evaluated via experimental challenge in early July. Further evaluation of this or a similar GMLPhV strain hinges on the vaccine's ability to prc!ect bighorns from expennental challenge. ) We also continued attempts to engineer an antigenic but nonpathogenic P. trehalosi strain for use as a modified-live vaccine in bighorns. Recent ligation attempts yielded a product of appropriate size, and restriction enzyme mapping indicated ligation was successful. As before, attempts to use polymerase chain reaction (PCR) to increase yields for cloning were disappointing, insofar as there were extraneous bands. However, we used gel purification to prepare concentrated ligated product to use in the subsequent insertplasmid ligation in E. coli. Several recipient colonies were recovered. A small number were screened and carried a plasmid of appropriate size (~ 7Kb). Restriction mapping results were encouraging. One cloned �278 construct (D22) showed favorable and consistent results. When used as a PCR template, plasmid from this clone produced a single, clear, 1889 bp band. Attempts to amplify the gfp gene using PCR were successful. A single band of appropriate size was visualized. Unfortunately, attempts to insert the gfp into the p2 l 76 containing the modified leukotoxin gene (referred to as D22) have been, as yet, unsuccessful. Short-term plans for continuing this work include PCR to amplify the green fluorescent pigment (gfp) gene with constructed blunt end restriction enzyme sites on each end. We hope to successfully clone this gene into the Nael site on the plasmid carried in D22. We then will electroporate the plasmid into P. trehalosi serotype 10 <Eco. 100) and replace the existing lktA with our LJ/ktA-gfp. We anticipate having a P. treha/osi vaccine strain available for testing in captive bighorn sheep sometime in the 00/01 segment. �279 EXPERIMENTS TO IDENTIFY AND MANAGE STRESS IN MOUNTAIN SHEEP POPULATIONS M. W. Miller, R. E. Briggs, and H. J. McNeil P. N. OBJECTIVES I. Design, conduct, and report on experiments evaluating Pasteurella haemolytica vaccines and vaccine delivery systems and identify those with potential application in managing free-ranging bighorn populations. 2. Design, conduct, and report on field experiments evaluating management strategies for preventing pasteurellosis epizootics in bighorn populations SEGMENT OBJECTIVES I. Continue development and evaluation of a modified-live Pasteurella haemolytica vaccine for use in bighorn sheep. STRATEGIES FOR MANAGING PASTEURELLOSIS IN MOUNTAIN SHEEP POPULATIONS Inability to control infectious disease outbreaks and subsequent mortality in mountain sheep populations represents a significant obstacle to Iong-tenn success in their management. Although the "bighorn pneumonia complex" has been studied intensively for over 3 decades, little is known about many aspects of its etiology and epizootiology. Moreover, management interventions recommended for preventing or controlling this problem remain untested. Although viral, bacterial, and parasitic agents have all been incriminated in these outbreaks, Pasteurella spp. are perhaps the most common pathogens associated with bronchopneumonia in bighorns (Miller 2000). Three species, P. haemolytica, P. trehalosi, and P. multocida, and several biotypes and/or serotypes within those species, have been isolated from bighorns during epidemics. Unfortunately, despite extensive diagnostic and experimental investigation, the epidemiology of pasteurellosis in wild bighorn populations is poorly understood. In the absence of knowledge about the epidemiology of pasteurellosis, effective strategies for managing pneumonia in bighorn populations have not emerged. Here, we report on a series of ongoing research studies designed to improve knowledge about various aspects of pasteurellosis epidemiology and management in bighorn sheep. METHODS AND MATERIALS Evaluation of a genetically-modified live Pasteurella haemolytica vaccine in bighorn sheep (Miller and Briggs): Based on preliminary successes in protecting both cattle and domestic sheep from experimental pasteurellosis (Briggs and Tatum, 1999), we began a pilot study to evaluate a genetically-modified live P. haemolytica vaccine (GMLPhV)in captive bighorns. The experimental GMLPhV strain ("Pasteurella haemolytica St2, Foreyt delta 3) was derived from a hemolytic, serotype 2 P. haemolytica strain (WSU-1) originally recovered from bighorn sheep cohoused �280 with domestic sheep (Foreyt 1989). The original strain was highly pathogenic in bighorns (Foreyt 1989, Foreyt et al. 1994, Foreyt and Silflow 1996), produced leukotoxin (Foreyt et al. 1994, Kraabel and Miller 1997) and carried a naturally-occurring leukotoxin gene (Green et al. 1999). Methods for genetic modifications used to produce vaccine strain are proprietary (R. Briggs, USDNARS). The candidate vaccine strain had not been tested previously in bighorn sheep. However, parallel pilot studies on safety and efficacy this vaccine strain via pareneteral delivery are underway in Pullman, WA, and other geneticallymodified P. haemolytica strains (Al from cattle and A5/6 from domestic sheep) already have been demonstrated as both safe and effective in respective domestic host species (Briggs and Tatum 1999, R. Briggs unpubl. data). Vaccinated bighorns received about 7 x 108 colony forming units (CFUs) of GMLPhV, sprayed intranasally, on 25 April 2000. Our pilot study focussed on safety, immunogenicity, transmissibility, and efficacy ofGMLPhV. To evaluate safety and immunogenicity, we used three pairs of previously unvaccinated captive bighorn sheep (4 males, 2 females). One bighorn from each pair was randomly assigned to one of two groups: intranasal vaccination with GMLPhV (n=3) or intranasal phosphate-buffered saline solution (PBS) in volumes equivalent to vaccine doses (control; n=3). Vaccinated and control groups were housed in separate I 00 m2 isolation pens. After a 2-wk acclimation period, respective vaccine and control treatments were administered as described(= wk 0). Blood for serology and pharyngeal swabs for bacteriology will be collected at wk-2, 0, 1, and 2. Safety and immunogenicity were evaluated by comparing morbidity, mortality, strain-specific P. haemolytica colonization rates, and humoral immune responses between groups over a 2-wk period. We used 4 captive bighorns from the safety study to evaluate vaccine transmissibility. Bighorns from the intranasal vaccination(= surviving prirrtiuy vaccinates; n=2) and control(= secondary vaccinates; n=2) groups were housed together in a single 200 m2 isolation pen immediately after sampling at wk 2 of the safety pilot. Additional blood for serology and nasal and pharyngeal swabs for bacteriology were collected at wk 3, 4, 5, 7, and I 0. Safety, immunogenicity, and transmissibility were evaluated by further monitoring of morbidity, mortality, strain-specific P. haemolytica colonization rates, and humoral immune responses between groups over an 8-wk period. We plan to use the four vaccinated bighorns (2 primary vaccinates, 2 secondary vaccinates) from the foregoing pilot studies and a fifth unvaccinated male bighorn to evaluate vaccine efficacy. After challenge, all five bighorns wiU be housed together in a single 200 m2 isolation pen. Subject bighorns will be challenged at 10 wk after vaccination of primary vaccinates. For challenge, we will use about 1 x 107 CFU of serotype 2 P. haemolytica strain (WSU-1) sprayed intranasally.Vaccine efficacy will be evaluated by comparing morbidity, mortality, strain-specific P. haemolytica colonization rates, and humoral immune responses of vaccinated bigho_rns to the control and to results from a previous study (Kraabel et al. 1998) . Development of a modified-live Pasteurella trehalosi vaccine for bighorn sheep (McNeil, Lo, and Miller): We continued developing and evaluating a modified-live Pasteurella trehalosi serotype 10 vaccine strain for use in bighorn sheep. Highlights of ongoing laboratory technique development and evaluations are reported. Polymerase chain reaction: We used polymerase chain reaction (PCR) techniques to amplify a 122 base pair segment from the 5' end of the leukotoxin gene, as previously described; using the following primers: 5'-GAAITCCCITATGGGAACTAAAC-3' 5'-GTCTGGCCGGCITGGGITAA-3' �281 Conditions were optimized at 3.5 rnM [Mg++] using genomic DNA prepared by the PUREGENE® method as template. The thermal cycler was programmed for 94 C for 30 seconds, 59 C for 30 seconds, 72 C for 3 minutes and 30 seconds. lbis was repeated for 30 cycles. PCR was also utilized to try to increase the amount of ligated product. The following primers were used: 5'-GAATICCCTIATGGGAACTAAAC-3' 5'-CGAAACAATCTAGAGTIGCCAATC-3' Conditions were optimized at 3.5 rnM [Mg++] using gel purified ligated product as the template. The thermal cycler was programmed for 94 C for 30 seconds, 64 C for 30 seconds, 72 C for 3 minutes and 30 seconds. This was repeated for 30 cycles. The above primers (used to amplify the ligated product) were also used to amplify the ligated product once it had been inserted into the plasmid p2176, as a means of mapping and confirmation. All PCR products were run on 0. 75 % agarose gels (85 V for 23-45 minutes) and stained with ethidiwn bromide. Bands were visualized using ultra-violet (UV) light and the image captured by a GelDoc I 000 machine (Bio-Rad Laboratories, Mississauga, ON, Canada). PCR Product Purification: We purified PCR products to be sequenced or used for further manipulation using a QIAGEN QIAquick PCR purification kit®. Purified product was run on gels as before purification to ensure that the band in question was still visible. I In instances where extraneous bands were visible, gel extraction was used to isolate the desired product. A low melting point 1.0 % agarose gel was loaded with product and run at low voltage overnight (8-9 V, 1216 hours). The gel was then stained with ethidiwn bromide and visualized using UV light on a transillwninator. The desired band was cut out using a sterile scalpel blade and put into a tube. The tube was heated to melt the agar. lbis material was then purified in the same manner as the non-gel purified PCR products. Restriction Enzyme Digestion: Purified 122 hp fragment was digested using Nae! (Promega Corporation, Madison, WI, USA) with the recommended buffer for I hour at 37 C. The enzyme was then inactivated at 60 C for 15 minutes. This product was ligated to the 1767 hp fragment described previously. Restriction enzyme digestion was also used for mapping the ligated product. Digestions were performed using Nae!, Apa! (Promega Corporation, Madison, WI, USA) and Sad (New England Biolabs Ltd., Mississauga, ON, Canada). Appropriate buffers were used for each reaction which was carried out at 37 C for I hour. Reactions were terminated by heat inactivation at 60 C for 15 minutes. A sample of product was run on a 0.75% agarose gel, stained with ethidiwn bromide and photographed. Restriction enzyme digestion was also used for mapping the plasmid construct (containing the 1889 hp insert). Digestions were performed using Nae!, Apa!, Sac!, EcoRI, Xbal, San and C/al. Enzymes are from Amersham Pharmacia Biotech, Baie d'Urfe, Quebec, Canada, unless otherwise indicated previously. The commercially available plasmid pBluescriptll (Stratagene, Aurora, ON, Canada) was used to troubleshoot digestion problems. Blunt End Ligation: Equal volwnes of the fragments to be ligated were mixed with T4 DNA ligase buffer (Gibco, Burlington, ON, Canada) according to manufacturer's instructions. Ligase (10% final volwne) �282 was then added and mixed thoroughly. The reaction was left at 16 C O/N. The ligated product was then run on a gel for visualization as well as used as template in further PCR. The product was then gel purified as previously described and used as template in further PCR. Blunt end ligation was also used in the preparation of the construct. Different ratios ofvector:insert were used to maximize the opportunities for ligation. Conditions were the same as above. Construct: Plasmid p2176 was digested with EcoRl andXbal in a double digest for I hour at 37 C. The ligated 1889 hp product was also double digested with the same two enzymes to prepare for ligation with the plasmid. After the digestion, enzymes were heat-inactivated for 15 minutes at 65 C. The plasmid digest mixture was then treated with calf intestinal alkaline phosphatase to minimiz.e the chances of recirculariz.ation. The reactions were then purified and concentrated using GENECLEAN® (BiolOI-Inc, from BioCan Scientific). These concentrated products were used in a blunt end ligation as reported above. Following ligation, the plasmid was transformed into competent E. coli cells (HB IO I) as described below. Preparing Competent E.coli Cells by CaC/2: A single colony of E.coli HBIOI was used to inoculate 3 ml of LT broth and incubated at 37 C O/N with shaking. This culture was then subcultured 1/40 in LT broth and incubated with the same conditions for I hour and 15 minutes. This culture was then put on ice for 40 minutes. After centrifugation (5000 rpm) for 5 minutes, the pellet was resuspended in ½ volume of cold, sterile 50mM CaC12 . This mixture was left on ice for I hour. After centrifugation, the pellet was resuspended in 1/10 volume of cold, sterile 50mM CaC12• These cells were used after 24 hours at 4 C, at which time maximum competency for foreign DNA uptake is expected. Transformation: In small glass tubes, 0.2 ml of competent cell suspension was mixed with IO µl of potentially ligated insert-plasmid and put on ice for I hour. This was followed by a 2 minute heat-shock at 42 C. Each tube was then supplemented with 0.3 ml of LT broth and left to "recover" at 37 C for 15 minutes. These cells were then plated onto LT agar plates containing ampicillin. The plasmid p2 l 76 carries an ampicillin resistance gene. Negative controls containing no insert DNA (digested plasmid only) as well as control cells containing no foreign DNA were used. Plates were incubated O/N at 37 C. Visible colonies were re-plated and screened by plasmid preparation and restriction enzyme mapping. Plasmid Preparations: Plasmid preparations were made by growing the colony to be screened O/N in 20 mis of LT broth containing ampicillin in a 125 ml erlenmyer flask. To incr~e plasmid yield (p2176 is a low copy plasmid), spectinomycin was added (50 µg/ml final concentration). Plasmid was then purified using Qiagen's QuickSpin® columns. Plasmid was then run on agarose gels to look for a product of expected size. Those which were of the expected size were further examined using restriction enzyme mapping. RESULTS AND DISCUSSION Evaluation of a genetically-modified live Pasteurella haemolytica vaccine in bighorn sheep (Miller and Briggs): Of3 bighorns receiving about 7 x 108 colony forming units (CFUs) ofGMLPhV, I died about 3 days after vaccination and another showed signs of moderately severe respiratory disease from days 2-10 postinoculation (PQ. Although bacteriology results were somewhat confounded by the reported isolation of a hemolytic P. haemolytica strain from lung tissue, the GMLPhV strain was most likely responsible for �283 morbidity and mortality in vaccinated bighorns. The sick bighorn recovered without medical intervention, and both surviving primary vaccinates showed strong elevations in both agglutinating and leukotoxin neutralizing antibody titers in response to vaccination (Fig. I). Two previously unvaccinated bighorns housed with the 2 surviving vaccinates beginning at wk 2 (2 weeks Pl) seroconverted to P. haemolytica serotype 2 2-3 weeks later (Fig. I), suggesting colonization of these incontact animals by GMLPhV strain despite failure to actually isolate GMLPhV strain from either incontact bighorn. Agglutinating antibody responses appeared to be less that those stimulated by primary vaccination (Fig. IA), and leukotoxin neutralizing antibody responses in secondary vaccinates were negligible (Fig. 1B). Both in-contact bighorns remanied healthy through 7 weeks postexposure (= wk 9). Ability of GMLPhV to protect bighorns from pasteurellosis will be evaluated via experimental challenge beginning in early July. Further evaluation of this or a similar GMLPhV strain hinges on the vaccine's ability to protect bighorns from expermental challenge, as well as the need for further modifications to improve vaccine strain safety in bighorn sheep. Development of a modified-live Pasteurella haemo/ytica vaccine for bighorn sheep (McNeil, Lo, and Miller):' Failed attempts to insert the ligated 123 bp-1767 bp fragment into p2176 led to the discovery of an error that was easily rectified. A different short fragment ( 122 bp) was prepared in the same way and ligated to the 1767 bp incorporating a different restriction enzyme on the 5'-end. Ligation of the 122 bp fragment to the 1767 bp fragment appears to have been successful. The product is the appropriate size, and restriction enzyme mapping supported our conclusion of successful ligation. As before, attempts to use PCR to increase yields for cloning were disappointing, insofar as there were extraneous bands. However, gel purification was used to prepare a high concentration of ligated product to use in the subsequent insert-plasmid ligation. Weeks postinoa.llation Figure 1. Serological responses of captive bighorn sheep to GMLPhV. A Agglutination titers rose in both primary (solid lines) and secondary (dashed lines) vaccinates after direct or indirect vaccination. B. Leukotoxin neutralizing (LN) titers showed marked elevation in primaryvaccinates; in contrast, LN titer responses were relatively weak in secondary vaccinates. An unvaccinated control showed no change in titers. Different symbols represent different individual bighorn sheep. Several recipient E. coli colonies were recovered. A small nwnber were screened and carried a plasmid of the appropriate size (~7Kb). Restriction mapping has been encouraging. One cloned construct (022) shows the most favourable and consistent results. When plasmid from this �284 clone is used as template in a PCR (using the 5'-primer used to make 122 bp fragment and the 3'-primer made to use the 1767 bp fragment) a single, very clear band of appropriate size ( 1889 bp) is visualized. We were concerned about the failure of Nae I digestion to create a single linearized band of 7 Kb, as expected. However, NaeI also failed to properly digest pBluescriptll, a commercially available plasmid vector with a single NaeI site. We concluded that the problem lies with either the enzyme or the digestion technique rather than with the insert in p2 l 76. It is important to sort out the problem with the Nae I because that is the proposed site for cloning the green fluorescent protein (gfp) gene. Other workers at the University of Guelph have shown that gfp can be expressed in P. haemolyti(!a. Short-term plans for continuing this work include PCR to amplify the gfp gene with constructed blunt end restriction enzyme sites on each end. We hope to successfully clone this gene into the NaeI site on the plasmid carried in D22. We then will electroporate the plasmid into P. haemolytica TIO CEco. 100) and replace the existing lktA with our .dlktA-gfp. We anticipate having a vaccine strain available for testing in captive bighorn sheep sometime in the 00/01 segment. LITERATURE CITED Briggs, R. E., and F. M. Tatum. 1999. New mucosal vaccine in beef cattle imparts rapid resistance to pneumonic pasteurellosis after mass-medicating on feed. USDA, REE, ARS, NADC, Ames IA. Unpublished report presented at USAHA, San Diego, CA, October 1999, 4 pp. Foreyt, W.J. 1989. Fatal Pasteurella haemolytica pneumonia in bighorn sheep after direct contact with clinically normal domestic sheep. Am. J. Vet. Res. 50:341-343. Foreyt, W.J. and R. M. Silflow. 1996. 1Attempted protection of bighorn sheep (Ovis canadensis) from pneumonia using a nonlethal cytotoxic strain of Pasteurella haemolytica, biotype A, serotype 11. J. Wildl. Dis. 32:315-321. Foreyt, W.J., K.P. Snipes, and R. W. Kasten. 1994. Fatal pneumonia following inoculation of healthy bighorn sheep withPasteurella haemolytica from healthy domestic sheep. J. Wildl. Dis. 30:137-145. Green, A. L., N. M. DuTeau, M. W. Miller, J. Triantis, and M. D. Salman. 1999. Polymerase chain reaction techniques for differentiating cytotoxic and noncytotoxic Pasteurella trehalosi from Rocky Mountain bighorn sheep. American Journal of Veterinary Research 60:583-588. Kraabel, B.J., and M.W. Miller. 1997. Effect of simulated stress on susceptibility of bighorn sheep neutrophils to Pasteurella haemolytica leukotoxin. J. Wildl. Dis. 33:558-566. Kraabel, B.J., M.W. Miller, J.A. Conlon, and H. McNeil. 1998. Evaluation ofa multivalent Pasteurella haemolytica vaccine in bighorn sheep: Protection from experimental challenge. J. Wildl. Dis. 34:325-333. Miller, M. W. 2000. Pasteurellosis. In Infectious Diseases of Wild Mammals, 3rd edition, E. S. Williams and I. K. Barker, eds. Iowa State University Press, Ames, Iowa, in press. Miller, M. W., J. A. Conlon, H.J. McNeil, J.M. Bulgin, and A. C. S. Ward. 1997. Evaluation of a multivalent Pasteurella haemolytica vaccine in bighorn sheep: safety and serologic responses. J. Wildl. Dis. 33: 738-748. Silflow, RM., Foreyt, W.J., and R.W. Leid. 1993. Pasteurella haemolytica cytotoxin dependant killing of neutrophils from bighorn and domestic sheep. J. Wildl. Dis. 29:30-35. Prepared by _ _ _ _ _ _ _ _ _ _ __ Michael W. Miller Wildlife Research Veterinarian � https://cpw.cvlcollections.org/files/original/a437c3334ab93087aef88d9389bef4d1.pdf 85cff8767672b5d1c03cbca0fbb0631b PDF Text Text 241 Colorado Division of Wildlife Wildlife Research Report July 1998 JOB PROGRESS REPORT state of Colorado cost center 3430 Project No. W-153-R-11 Mammals Program 3004 Work Package No. Task No. 1 Period covered: Author: &2 : Management of other ungulates Pronghorn Data Analysis_and Reporting July 1, 1997 - June 30, 1998 T.M. Pojar Abstract A herd structure estimate was made on the Middle Park pronghorn population during August, 1997 amd the total winter population estimate was made during January 1998. This information, along with like information since 1986 was incorporated into a spreadsheet population model. This model was provided to management personnel for.projecting effects of various management options. It was also used in public meetings for exploring public opinion of the proposed options. A manuscript was prepared summarizing the results of experiments in pronghorn inventory methods. It was submitted to the Journal of Wildlife Management and rejected on the basis that the topic addressed a relatively narrow issue. The manuscript will be modified and submitted either to the Wildlife Society Bulletin or the African Journal of Wildlife Management. The abstract is included in the results section. �243 PRONGHORN DATA ANALYSIS AND REPORTING Thomas M. Pojar P,H,QBJECTIYES Task 1 Test for density dependence in Middle Park population parameters and summarize the findings in manuscript format suitable for submission to a professional wildlife management or ecological journal. Task 2 Analyze and summarize the results of experiments in pronghorn inventory methods and report the findings in manuscript format suitable for submission to a professional wildlife management journal. SEGMENT OBJECTIVES Task 1 Test for density dependence in Middle Park population parameters and summarize the findings in manuscript format suitable for submission to a professional wildlife management or ecological journal. Task 2 Analyze and summarize the results of experiments in pronghorn inventory methods and report the findings in manuscript format suitable for submission RESULTS Task 1 Key population information in the form of herd structure estimates and a count of the wintering population was collected. This was included in the population data set that began in 1986 and used to build a spreadsheet population model. This model was used to project population responses to proposed management options and was provided to managment personnel. The overall objective of Task 1 was not fulfilled during this segment. Task 2 A manuscript was prepared that analyzed and summarized the results of experiment in pronghorn invenorty methods. It was rejected by the Journal of Wildlife Management as having too narrow a focus. The manuscript will be modified and sumbitted either to the Wildlife Society Bulletin or the African Journal of Wildlife. The following is the abstract for this article. PRONGBORH DENSITY ESTIMATES: HELICOPTER QUADRAT SURVEYS COMPARISON OF FIXED-WING LIRE TRANSECT ARD THOMAS M. POJAR1 , Colorado Division of Wildlife, 317 w. Prospect Road, Fort Collins, CO 80526, USA DAVID c. BOWDEN, Department of Statistics, Colorado State University, Fort Collins, CO 80523, USA JEFF D. MADISON, Colorado Division of Wildlife, P.O. Box 1181, Meeker, CO 81641, USA Estimates of pronghorn (Antilocapra americana) density in northwest Colorado sagebrush (Artemisia spp.) steppe habitat were compared using fixedwing line transect and helicopter quadrat surveys. Fixed-wing line transects offer wildlife managers a survey method that is both economical and statistically valid but this technique has not been evaluated with a standard or known density for pronghorn. We used the helicopter quadrat survey method as the standard and compare density estimates to fixed-wing line transect Abstract: �244 surveys. Fixed-wing line transect estimates were always less than quadrat estimates (t=0.682, P = 0.050) and were 83%, 69%, and 83% of the quadrat estimates respectively, for 3 years data. In addition, we analyzed the first and second line transect intervals as narrow strips of 50 m and 100 m, respectively. The narrow strips were not different from either the quadrats or lines (P > 0.070) and may offer managers a method that combines the economy of line transects with the analysis simplicity of quadrat data. We conclude that line transect density estimates should be adjusted upward by considering them approximately 0.78 (SE= 6.32) of quadrat estimates. At the density of pronghorn encountered in this study (approximately 5/km'), the cost of fixedwing line transect sampling for large scale management application is about 510% of the cost of helicopter quadrats for similar precision. Prepared Wildlife Researcher � https://cpw.cvlcollections.org/files/original/385b1830d75fd77330072f041e83d500.pdf 7bc75debf6db24d3492aef8e4a87d438 PDF Text Text 295 Colorado Division of Wildlife Wildlife Research Report July 1999 JOB FINAL REPORT State of _ _ _ _ _ _C=o=l=o=rad=o_ _ _ __ Project No. ----~W'-'---......1....5___ 3-___R___--=12"---_ __ Work Plan No. 3004 Job No. - - - - - - - - ' 4 ' - - - - - - - ----~~----- Mammals Research Mountain Goat Investigations Mountain goat numbers, distribution, and dispersal in the northern Collegiate range. Period Covered: July 1, 1998 - June 30, 1999 Author: D. F. Reed ABSTRACT A manuscript titled "Mark-resight population estimates of mountain goats in Colorado" (Reed and Vayhinger [in preparation]) was prepared. Additionally, a manuscript titled "A conceptual interference competition model for introduced mountain goats" was prepared and submitted to the Journal of Wildlife Management (Reed [in review]) and collaboration with Natural Resources Ecology Laboratory (NREL) occurred to extent and refine some of the Mt Evans data. �296 �297 MOUNTAIN GOAT NUMBERS, DISTRJBUTION, AND DISPERSAL IN THE NORTHERN COLLEGIATE RANGE Dale F. Reed P.N. OBJECTIVE To improve estimates of mountain goat populations by mark-resight methodology, to determine distribution, and to estimate dispersal rates in an increasing mountain goat population. SEGMENT OBJECTIVE I. Analyze data and prepare manuscripts. STUDY AREA The study area is described in the Program Narrative (Reed 1995). ME1HODS AND MATERIALS The methods are outlined in the Program Narrative and 1995 and 1996 progress reports (Appendix A in Reed 1995, Reed 1996). RESULTS Results have been reported in Reed ( 1996), Reed ( 1997), and in a manuscript titled "Mark-resight population estimates of mountain goats in Colorado" (Reed and Vayhinger [in preparation]. Additionally, a manuscript titled "A conceptual interference competition model for introduced mountain goats" was prepared and submitted to the Journal of Wildlife Management (Reed [in review]) and collaboration with NREL (ref Rocky Mountain National. Park contract) occurred to extent and refine some of the Mt Evans data by evaluating spatial distribution, habitat segregation, and implications of competitive displacement. LITERATURE CITED Reed, D. F. 1995. Mountain goat numbers, distribution, and dispersal in the northern Collegiate range. Colo. Div. Wildl. Res. Rep. July, 223-234pp. Reed, D. F. 1996. Mountain goat numbers, distribution, and dispersal in the northern Collegiate range. Colo. Div. Wildl. Res. Rep. July, 255-263pp. ; .· Reed, D. F. 1997. Mountain goat numbers, distribution, and dispersal in the northern Collegiate range. Colo. Div. Wildl. Res. Rep. July, 165-167pp. Prepared by _ _ _ _ _ __ DaleF. Reed � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mammals research pdfs Description An account of the resource Pdfs of mammals research projects by title . Pdfs are linked from this page. Includes federal aid progress reports and non federal aid progress reports. If reports cover more than one year they are combined into one pdf. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. 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