https://cpw.cvlcollections.org/files/original/402b1e7ff9c5fa1a5309cb2080e8660b.pdf d5c955a9e8f9867f14717d551f2af146 PDF Text Text Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Density, demography, and seasonal movements of snowshoe hares in central Colorado. Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: G. White, T. Shenk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT To improve understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares (Lepus americanus) and lynx (Lynx canadensis) in Colorado, we estimated snowshoe hare density, survival, recruitment, and movement in west-central Colorado, USA from July 2006−March 2009. We sampled 3 types of forest stands that purportedly provide good habitat for hares: 1) mature Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), 2) early seral, even-aged lodgepole pine (Pinus contorta), and 3) mid-seral, even-aged lodgepole pine that had been pre-commercially thinned. In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central 40 �Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. We used simulation to compare relative performance of the method we developed to estimate density for this project (TELEM) to other contemporary methods that are widely used (i.e., spatially explicit capture-recapture (SECR), and mean maximum distance moved (MMDM)). We evaluated performance (percent error) under all combinations of 3 levels of detection probability (0.2, 0.4, 0.6), 3 levels of occasions (5, 7, 10), and 3 levels of abundance (10, 20, 40 animals). We also tested each estimator using 5 different models for animal home ranges. TELEM performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. SECR outperformed MMDM estimators in nearly all comparisons and may be preferable to TELEM at low capture probabilities, but performance varied with home range configuration. MMDM estimators exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. 41 �WILDLIFE RESEARCH REPORT DENSITY, DEMOGRAPY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN CENTRAL COLORADO JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 stand types (mature spruce/fir, early seral lodgepole pine, and thinned, midseral lodgepole pine) that purportedly provide high quality hare habitat by estimating density, survival, recruitment, and movements of hares in such stands during summer and winter. SEGMENT OBJECTIVES 1. Publish manuscripts in peer-reviewed scientific journals. INTRODUCTION Snowshoe hares (Lepus americanus), their famous 10-year population cycle, and close association with Canada lynx (Lynx canadensis) have been well-studied in boreal Canada for decades. Snowshoe hare range, however, extends south into the Sierra Nevada, Southern Rockies, upper Lake States, and Appalachian Mountains. Ecology of snowshoe hares in these more southerly regions is not as well understood, though hare research in the U.S. Rocky Mountains has accelerated over the past decade. Through this recent work, biologists have identified stands of young, densely-stocked conifers and those of mature, uneven-aged conifers as primary hare habitat in the region. Both stand types are characterized by dense understory vegetation that provides both browse and protection from elements and predators. From 1999 to 2006, Canada lynx were reintroduced into Colorado in an effort to restore a viable population to the southern portion of their former range. Snow tracking of released individuals and their progeny indicated that the majority of lynx winter diet in Colorado was comprised of snowshoe hares. Thus, long-term success of the lynx reintroduction effort hinges, at least partly, on maintaining adequate and widespread populations of snowshoe hares in the state. To improve our understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares and lynx in Colorado, we conducted an observational study to evaluate purported primary hare habitat in the state. Specifically, we estimated snowshoe hare density, survival, recruitment, and movement indices in mature, uneven-aged spruce/fir (Picea engelmannii/Abies lasiocarpa) and 2 classes of young, even-aged lodgepole pine: 1) “small” lodgepole pine (Pinus contorta) stands, which were clear cut 20−25 years prior to this study and had regenerated into densely stocked stands with trees 2.54−12.69 cm in diameter, and 2) “medium” lodgepole pine stands (tree diameter = 12.70−22.85 cm) which were clear cut 40-60 years prior to this study and pre-commercially thinned ~20 years prior. Animal density is one of the most common and fundamental parameters in wildlife ecology and was the first metric we used to evaluate the stand types. However, density can be difficult to estimate from mark-recapture data because animals move on and off of a trapping grid during a sampling session (i.e., lack of geographic closure). Thus, we first developed a density estimator that uses ancillary radio telemetry locations, in addition to mark-recapture information, to account for lack of geographic closure resulting in relatively unbiased estimates of density. We also completed a series of simulations to test the performance of this “telemetry” estimator over a range of sampling parameters (i.e., capture probabilities, sampling occasions, densities, and home range configurations) likely to be encountered in the field, and 42 �compared its performance to two other commonly used, contemporary estimators: spatially explicit capture-recapture (SECR), and mean maximum distance moved (MMDM). STUDY AREA The study area encompassed roughly 1200 km2 around Taylor Park and Pitkin, Colorado, USA (39°50'N, 106°34'W; Figure 1), and included a portion of the “Core Reintroduction Area” occupied by reintroduced Canada lynx (Shenk 2009). Open sagebrush (Artemisia tridentata) parks dissected by narrow riparian zones of willow (Salix spp.) and potentilla (Potentilla spp.) dominated the relatively low elevation (~2800−3000 m) parts of the study area. Extensive stands of lodgepole pine occupied low and mid-elevation slopes (~3000−3300 m), giving way to narrow bands of Engelmann spruce/subalpine fir in the sub-alpine zone (~3200−3600 m). Alpine tundra topped the highest parts of the study area (~3300−4200 m). Moist spruce-fir forests also occurred on north-facing slopes at mid-elevations. Climate was typical of continental, high-elevation zones with relatively short, mild summers and long, harsh winters. Mean July temperature was 14 °C; mean January temperature was −11 °C (Ivan 2011). Maximum snow depth on the study area averaged 80 cm but ranged from 22−163 cm depending on year, elevation, and aspect (Ivan 2011). Snowpack generally persisted from November through May (low elevations) or June (high elevations and north-facing slopes). Some human habitation occurred in the study area, mostly in the form of seasonal residences. Considerable recreational use occurred during summer in the form of dispersed camping and off-highway vehicle traffic. A suite of native predators were present within the study area including lynx, cougar (Puma concolor), coyote (Canis latrans), red fox (Vulpes vulpes), pine marten (Martes Americana), Great Horned Owl (Bubo virginianus) and Northern Goshawk (Accipiter gentilis). METHODS Refer to Ivan (2011) for methods associated with fieldwork conducted during 2006–2009 and subsequent statistical analyses. During fiscal year 2011–2012 we completed work on 2 manuscripts submitted as a pair to the journal Ecology. The first of these manuscripts lays out an approach to estimating animal density using auxiliary telemetry information to improve estimates. The second manuscript uses simulation to compare performance of this new estimator to other contemporary estimators. We have just completed what we believe to be final revisions to these papers. Additionally, we spent much of year combining the demography and movement chapters of the primary author’s dissertation into a single, comprehensive treatment of snowshoe hare ecology in central Colorado that includes analyses on hare density, survival, recruitment, and movement. This manuscript was recently submitted to the Journal of Wildlife Management for consideration as either a research article or monograph. RESULTS AND DISCUSSION A comprehensive treatment of the results is widely available in dissertation form (Ivan 2011), so we do not repeat that here. We are currently in the process of publishing results in the peer-reviewed literature. Below is list of manuscripts that have been submitted for publication (abstracts are provided in Appendix I): Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Using auxiliary telemetry information to estimate animal density from capture-recapture data. Ecology. 43 �Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Using simulation to compare methods for estimating density from capture-recapture data. Ecology. Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Density, Demography, and Seasonal Movements of Snowshoe Hares in Central Colorado. Journal of Wildlife Management. SUMMARY In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. The estimator we developed is based on a modified Huggins closed capture estimator. It directly accounts for lack of geographic closure (animals moving on and off of the sampling grid during the sampling period) using telemetry data, and this auxiliary information is used to compute estimates of density. Contrary to other approaches, this method is free from assumptions regarding the distribution of animals on the landscape, the stationarity of their home ranges, and biases induced by abnormal movements in response to baited detectors. The estimator is freely available in Program MARK. We found that our approach performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. Spatially explicit capture-recapture methods outperformed “mean maximum distance moved” (MMDM) estimators in nearly all comparisons and may be preferable to our telemetry estimator at low capture probabilities, but performance varied with home range configuration. MMDM estimators exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. LITERATURE CITED Ivan, J. S. 2011. Density, demography, and seasonal movement of snowshoe hares in central Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Prepared by ___________________________ Jacob S. Ivan 44 �Figure 1. Study area near Taylor Park and Pitkin, central Colorado. We estimated snowshoe density, demography, and movement in 3 late-seral Engelmann spruce/subalpine fir stands (circles), 3 mid-seral lodgepole stands (squares), and 6 early-seral lodgepole stands (triangles) from summer 2006 through winter 2009. 45 �APPENDIX I PROJECT PAPERS The following manuscript (referenced here by abstract) is currently in review at the journal Ecology. USING AUXILIARY TELEMETRY INFORMATION TO ESTIMATE ANIMAL DENSITY FROM CAPTURE-RECAPTURE DATA JACOB S. IVAN, GARY C. WHITE, AND TANYA M. SHENK ABSTRACT Estimation of animal density is fundamental to ecology, and ecologists often pursue density estimates using grids of detectors (e.g., cameras, traps, hair snags) to sample animals. However, under such a framework, reliable estimates can be difficult to obtain because animals move on and off of the study site during the sampling session (i.e., the site is not closed geographically). Generally, practioners address lack of geographic closure by a) inflating the area sampled by the detectors based on the mean distance individuals moved between trapping events, or b) invoking hierarchical models in which animal density is assumed to be a spatial point process, and detection is modeled as a declining function of distance to a detector. We provide an alternative in which lack of geographic closure is sampled directly using telemetry, and this auxiliary information is used to compute estimates of density based on a modified Huggins closed capture estimator. Contrary to other approaches, this method is free from assumptions regarding the distribution of animals on the landscape, the stationarity of their home ranges, and biases induced by abnormal movements in response to baited detectors. The estimator is freely available in Program MARK. The following manuscript (referenced here by abstract) is currently in review at the journal Ecology. USING SIMULATION TO COMPARE METHODS FOR ESTIMATING DENSITY FROM CAPTURE-RECAPTURE DATA JACOB S. IVAN, GARY C. WHITE, TANYA M. SHENK Estimation of animal density is fundamental to wildlife research and management, but estimation is often complicated by lack of geographic closure of sampling grids. Contemporary methods for estimating density using mark–recapture data include: 1) approximating the effective area sampled by an array of detectors based on the mean maximum distance moved (MMDM) by animals during the sampling session, 2) spatially explicit capture–recapture (SECR) methods that formulate the problem hierarchically with a process model for animal density and an observation model in which detection probability declines with distance from a detector, and 3) a telemetry estimator (TELEM) that uses auxiliary telemetry information to estimate the proportion of animals on the study site. We used simulation to compare relative performance (percent error) of these methods under all combinations of 3 levels of detection probability (0.2, 0.4, 0.6), 3 levels of occasions (5, 7, 10), and 3 levels of abundance (10, 20, 40 animals). We also tested each estimator using 5 different models for animal home ranges. TELEM performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. SECR outperformed MMDM estimators in nearly all comparisons and may be preferable to TELEM at low capture probabilities, but performance varied with home range configuration. MMDM estimators 46 �exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. The following manuscript (referenced here by abstract) is currently in review at the Journal of Wildlife Management. Density, Demography, and Seasonal Movements of Snowshoe Hares in Central Colorado JACOB S. IVAN, GARY C. WHITE, TANYA M. SHENK ABSTRACT To improve understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares (Lepus americanus) and lynx (Lynx canadensis) in Colorado, we estimated snowshoe hare density, survival, recruitment, and movement in west-central Colorado, USA from July 2006−March 2009. We sampled 3 types of forest stands that purportedly provide good habitat for hares: 1) mature Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), 2) early seral, even-aged lodgepole pine (Pinus contorta), and 3) mid-seral, even-aged lodgepole pine that had been pre-commercially thinned. In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. 47 � https://cpw.cvlcollections.org/files/original/fdd7b337777b6314a495e4b9bcef9686.pdf 4cce56f36148ff392817e671352029e8 PDF Text Text Colorado Division of Parks and Wildlife July 2010–June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Monitoring Canada Lynx in Colorado Using Occupancy Estimation: Initial Implementation in the Core Lynx Research Area Period Covered: July 1, 2010 – June 30, 2011 Author: J. S. Ivan Personnel: T. Shenk, G. Merrill, E. Newkirk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established. The purpose of this project was to develop a scientifically rigorous statewide plan to monitor this newly established population. Occupancy estimation, the use of presence/absence data to estimate the proportion of sample units used by a species within a study area, is appropriate for such a program. To evaluate this approach and provide initial estimates of occupancy and detection probability for planning purposes, we conducted a pilot occupancy estimation project in the core reintroduction area in the San Juan Mountains of southwestern Colorado. Lynx habitat in the study area was divided into 75−km2 sample units (8.66 km x 8.66 km cells), and we stratified the units into those accessible for snow tracking and “inaccessible” units which were sampled via remote cameras. We randomly sampled 30 units from each stratum. Sampling consisted of making multiple visits to each selected unit. We covered 2,178 km during our snow tracking effort (min= 1.4, max = 81.7 per visit) and detected lynx on 12 of the 30 sample units. Estimates of occupancy and detection probability from the top model were 0.62 and 0.37-0.43, respectively. Of the 120 cameras we deployed in late fall to survey the 30 inaccessible units, 113 were still operational when retrieved in early summer; 6 had memory cards that reached capacity in either May or June; 1 was stolen. We obtained 151,191 photos (min = 90, max = 6,948 per camera) from this effort. Work to assign species for each photo is ongoing. These pilot data will be used to conduct simulations and power analyses to determine how many sample units will be required to detect a statewide decline in Canada lynx, assuming that a decline in the actual population will be tied to a decline in the proportion of sample units used by lynx. 11 �WILDLIFE RESEARCH REPORT MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA JACOB S. IVAN P. N. OBJECTIVE Assess the use of occupancy estimation as a means of monitoring Canada lynx in Colorado using the Core Research Area in the San Juan Mountains as a test site. 1. Obtain initial estimates of occupancy and detection probability based on pilot work. 2. Conduct power analyses using initial estimates to determine the number of sample units, number of visits, and periodicity of sampling required to detect declines of interest in the statewide lynx population. 3. Develop a standardized, statistically rigorous monitoring protocol for estimating the distribution, stability and persistence of Canada lynx in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. Assess and suggest modifications to survey protocols. Construct database to store and query survey information. Obtain initial estimates of occupancy and detection probability based on pilot work. Determine covariates and covariate structures that will be most useful for modeling occupancy and detection probability in the future. 5. Determine the efficacy of collecting lynx scat during occupancy surveys and whether such collections can be helpful in identification of putative lynx tracks and/or individuals. INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple human-associated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) considered reintroduction as the best option to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, and 218 lynx were released into Colorado from 1999 – 2006 (Devineau et al. 2010). The goal of the Colorado lynx reintroduction program was to establish a selfsustaining, viable population of lynx. Progress toward this goal was tracked via evaluation of critical criteria related to lynx survival, fidelity, and recruitment. Recently, CPW determined that the criteria had been met and a viable Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). In order to track the distribution, stability, and persistence of this new lynx population, a minimally-invasive, long-term, statewide monitoring program is required. Abundance estimation is not 12 �feasible logistically and presents statistical difficulties even when field logistics can be managed. However, occupancy estimation, which uses detection/non-detection survey data to estimate the proportion of area occupied in a study area, is appropriate and feasible. In short, such a monitoring scheme requires multiple visits to a sample of survey units, and on each visit observers record whether a lynx was detected or not. Such information can be used to compute the probability of detecting a lynx given that it is present on a unit, which can in turn be used to estimate the proportion (ψ) of all survey units that are occupied. This metric can be tracked through time and is assumed to be closely tied to the size and extent of the lynx population. That is, if the proportion of survey units occupied by lynx declines through time, we assume this is due to a decline in the lynx population itself. Additionally, occupancy surveys can provide information relative to the distribution of lynx in the state. CPW initiated work to evaluate detection methods for occupancy estimation in 2009-2010 (Shenk 2009). Three methods of detecting lynx were tested in sample units where lynx were known to occur: snow tracking surveys, remote camera surveillance, and hair snags. The best method for detecting lynx was snow-tracking (daily detection probability = 0.70). Camera surveillance was far less efficient (daily detection probability = 0.085), and hair snares were ineffective (daily detection probability = 0.0; Ivan and Shenk 2010). Snow tracking, however, requires safe and extensive access to a survey unit via truck and/or snowmobile. Therefore, it cannot be used in roadless or wilderness areas, which may provide important lynx habitat. Here we build on this work to test occupancy estimation on a large scale using snow tracking where accessibility permitted it, and remote cameras in areas that were not accessible. METHODS Study Area The study area consisted of the 20,684 km2 “Lynx Core Research Area” in southwest Colorado. The Core Research Area is defined as areas >2591 m (>8500 ft) in elevation within the area bounded by New Mexico to the south, Taylor Mesa to the west, and Monarch Pass on the north and east (Figure 1). Topography in this area is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce (Picea engelmanii) − subalpine fir (Abies lasiocarpa) is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m, 8500-11,000 ft). Sampling The study area was divided into 75 km2 (8.66 km × 8.66 km) sample units, which reflects the mean annual home range size of reproducing lynx in Colorado (Shenk 2007) and Montana (Squires and Laurion 1999). Sample units that did not meet the following criteria were discarded as they did not represent potential lynx habitat that could be surveyed. ≥ 50 % of the cell contained conifer or montane/alpine habitat, as identified by the SWReGAP LandCover Dataset ( http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf) and 2. ≥ 50 % of the cell was located on public land (tribal, NGO and city and county lands are considered private) as determined by COMaP (Theobald, D.M., G. Wilcox, S.E. Linn, N. Peterson, and M. Lineal. 2008. Colorado Ownership, Management, and Protection v7 database. Human Dimensions of Natural Resources and Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, www.nrel.colostate.edu/projects/comap). 1. Each of the remaining sample units was assigned a random number resulting from a spatially balanced sampling scheme (RRQRR; Theobald et al. 2007) and units were stratified by accessibility for snow tracking or camera surveys. The cells with the lowest 30 random numbers for each stratum were 13 �selected for sampling during the pilot work. A few cells in both strata were discarded once field work began due to access issues and these were replaced with cells 31, 32, etc. Snow tracking Surveys Teams of 2 observers generally searched for lynx tracks within a sample unit using snowmobiles, although portions of some units were surveyed via truck or snowshoe. An effort was made to survey all portions of each unit as access allowed. Each of the 30 units selected for sampling was visited 3 times − roughly once per month from January through March. Occasionally a “visit” actually took place over consecutive days as some units could not be covered completely from a single access point. Once tracks were detected in a unit, that visit was considered complete and no further surveying occurred until the next visit. However, observers forward and back-tracked to find a scat sample. For each visit, observers recorded number of kilometers surveyed, tracking conditions (poor, fair, good, excellent), other species detected, location of lynx tracks, and time/distance to scat discovery. Camera Surveys Four remote camera sets (RECONYX RapidFireTM Professional PC85) were placed within each selected “inaccessible” sample unit during September and October. Placement of camera sets was not random within the unit; they were placed strategically on the landscape to maximize coverage of the sample unit and exploit microsites most likely to be used by lynx. Camera sets consisted of 1) a remote camera mounted to a tree using a Master Lock TM PythonTM cable lock, 2) a target tree at which the camera was pointed, generally about 5-10m away, 3) a compact disc strung from a nearby branch to visually attract lynx from a distance, 4) 2 feathers strung up in such a manner as to entice lynx to walk between the camera and the target tree, and 5) wool soaked in commercial scent lure that was packed into the bark of the target tree to hold lynx in front of the camera (Figure 2). Cameras were placed higher than usual, about head-height, and pointed slightly downward at the target tree so photos could be obtained during both snow-free periods and during periods of accumulating snow. Cameras were collected during June and July at which time the number of photos, percent of memory card used, percent battery life remaining, and condition of visual/scent lures was recorded. Analysis Assumptions inherent in occupancy estimation are 1) surveyed sites are either occupied or not occupied by the species of interest throughout the duration of the study; no sites change status during the survey period (i.e., the system is closed), 2) the probability of occupancy is constant across sites or can be modeled using covariates, 3) the probability of detection is constant across sites or can be modeled using site-specific covariates, and 4) species detection at a site is assumed to be independent of species detection at other sites (MacKenzie et al. 2006). Sampling mobile carnivores such as lynx presents a clear violation of the first assumption as individuals undoubtedly move into and out of sample units routinely. Fortunately, estimation can proceed, but the quantities estimated are different from traditional occupancy estimation. Rather than estimating the probability that a unit is occupied by lynx, we now estimate the probability that a sample unit is used by lynx. Also, the estimated detection parameter is not the probability of detection given a site is occupied, it is the product of a) the probability of detection given the species is available for detection, and b) the probability that the species was available. These subtleties aside, the procedure still gives a metric (use) that can be monitored through time to detect trends. We used the “Occupancy Estimation” data type in Program MARK to produce initial estimates of occupancy (i.e., use, ψ) and detection probability (p) for the snow tracking stratum. We hypothesized that some metric of the number of kilometers surveyed, or number that could be surveyed, would be important in explaining variation in detection probability as it should be an indicator of the amount of access to a unit. Surveys on units with more access should stand a better chance of detecting lynx if they are present. We further hypothesized that tracking conditions during a given visit should have an effect on detection 14 �probability. Finally, we did not expect differences among survey teams as both teams were experienced, but we wanted to test that assumption. Therefore, we considered 5 covariates that may explain variation in p: 1) total road length available for surveying in each sampled unit, 2) Kilometers surveyed during each visit, 3) maximum number of kilometers surveyed during any visit to a given unit, 4) tracking conditions during each visit, and 5) observer effect. We hypothesized that the proportion of spruce/fir cover in each unit may affect the probability of use, as might proportion of willow (Salix spp.), and subalpine/alpine meadow. Thus, we considered those 3 covariates as potentially important for explaining variability in ψ. As this analysis is exploratory, we held ψ constant and built an additive model for each detection covariate (one at a time) to determine the best structure for p. Similarly, we held p constant and fit additive models using the 3 covariates for ψ. We combined the best structure as determined by AICc (Burnham and Anderson 2002) for each parameter and used results from that single model to produce initial estimates of p and ψ. We also ran a model where both p and ψ were held constant as a baseline for comparison. Occupancy estimation for the camera stratum will proceed in a similar fashion as above, but data from the photos is incomplete at this time. Photos will be grouped by month (November to March) for each sample unit such that encounter histories will have 5 “visits” rather than 3. Due to this grouping, there are no meaningful covariates for p. Individual cameras recorded moon phase and temperature for each photo, but aggregated over a month, these data are not helpful. Some camera sets used different scent lures than others, but aggregating by unit negates the utility of this information as well. We will consider the same covariates on ψ as listed above. RESULTS On average, we covered 24.71 km per visit to each accessible sample unit (min = 1.40 km, max = 81.67 km) for a total of 2,184 km surveyed. We detected 20 lynx tracks in 12 of the 30 units sampled (i.e., tracks were detected on multiple visits to some units; Figure 1). We were able to collect scat from 13 of the 20 tracks, and mean forward/backtracking distance to scat discovery was 0.65 km (min = 0.05, max = 1.60). According to AICc, the best structures for p and ψ were “kilometers surveyed per visit” and “proportion spruce-fir,” respectively (Table 1). No other structure for either parameter resulted in improvement over constant p and ψ with the exception of modeling ψ as a function of “proportion willow.” In fact, this was the AICc top structure, but the parameters could not be estimated so it was dropped from the model set. Estimates (SE) from the model that combined the best structures were ψ = 0.62 (0.25), p1= 0.37 (0.10), p2= 0.37 (0.10), and p3 = 0.43 (0.10) where pi is the detection probability for visit I (i.e., p1 is the estimated detection probability for January, p2 = February, p3 = March) . As expected, the slope of the spruce-fir effect was highly positive. Probability of use was 0.5 when proportion spruce-fir approached 0.35, and probability of use went to 1.0 when proportion sprucefir approached 0.6 (Figure 3). The relationships between “proportion meadow” and ψ and “proportion willow” and ψ were also positive, but the relationships were weaker as confidence intervals for these slopes covered zero. The relationship between p and kilometers surveyed was negative. Similarly, the relationship between p and visit condition was opposite of our hypothesis (as visit conditions improved, detection probability declined). There was no relationship between “total road length” or “maximum kilometers surveyed” and detection probability. We did not detect differences between teams of observers. 15 �Genetic analysis of scat samples is ongoing. By December 2010, we should be able to assess whether scats were of high enough quality to confirm species and/or individual identification. Of the 120 cameras deployed during Fall 2010, 113 were still operational when retrieved in Summer 2011 after 234-309 days of deployment. Six had memory cards that reached capacity in either May or June, and one camera was stolen. On average, we obtained 1,260 photos per camera (min = 90, max = 6,948) for a total of 151,191 photos. At the time of retrieval, compact discs were still operational for 46% of camera sets, feathers were operational at 64% of sets, and remnants of scent lure were detected at 55% of sets. DISCUSSION Initial results indicate that occupancy (use) can be adequately modeled using data collected via snow tracking. Precision on estimates of ψ and p was relatively poor, but this can be addressed by sampling more units and/or making more visits. Modeling p as a function of the “kilometers surveyed per visit” was a better fit for the data than modeling it as a function of either “total road length within a unit” or “visit conditions.” However, we recommend continuing to record “total road length” and “visit conditions” in future surveys as it seems reasonable that these covariates should impact detection probability, and their effects may show through as sample size increases. Similarly, we recommend retaining all covariates on ψ to assess their performance with a larger dataset. The relationship between p and “kilometers surveyed per visit” was negative, which is likely an artifact of how the units were sampled – when lynx were detected, surveying stopped, so detection probability was higher for visits with few kilometers surveyed. The relationship between p and “visit condition” was opposite of our hypothesis (as visit conditions improved, detection probability declined). Our condition criteria were based largely on the freshness of the snow and degree of melting/crusting where fresh snow was assigned the best condition, and older, crusted snow was assigned the worst. Functionally, this index is an inverse of “time-since-snowfall.” Therefore, it is sensible that “poor” condition indices resulted in higher detection probabilities. While the immediate conditions were poor for tracking, significant time had passed in which lynx could move around and leave tracks to be discovered. We estimated that lynx used approximately 62% of the sample units available in the Core Research Area. However, for this pilot study, lynx habitat was coarsely defined as units with >50% spruce/fir and >50% public land. In several cases, sampled units met these criteria, but field crews that actually made visits indicated these units did not appear to include much lynx habitat. CPW is currently finishing an analysis to produce a map of predicted lynx habitat throughout the state. In the future, we expect to use this map to frame the population of units to sample for lynx monitoring. This more refined population of sample units should reduce time wasted surveying units that do not include good lynx habitat, and will result in an increased estimate of probability of use. Photos from cameras deployed to sample the inaccessible stratum have not been fully processed, therefore we cannot determine whether that portion of the study worked well enough to be included in any future monitoring effort. Roughly half of the visual attractants we used did not operate through the entirety of the study. These attractants are important for drawing lynx to the set from a distance and their failure diminishes the utility of the cameras for detecting lynx. If cameras are to be used in the future, design changes will be necessary to ensure that most of these visual attractants operate throughout the sampling season. 16 �ACKNOWLEDGMENTS We thank Britta Schielke, Cate Brown, Wendy Lanier, Joan Meiners, Shane McKenzie, Nick Burgmeier, Doug Clark, Bob Peterson, Tim Hanks, Kei Yasuda, Ashley Bies, Tyler Kelly, Alyssa Winkler, and Carolyn Shores for their efforts in the field. Dale Gomez and Rhandy Ghormley (USFS) graciously coordinated housing for seasonal crews. We thank various personnel from both the Rio Grande and San Juan National Forests for logistical help in the field. Funding was provided by a U.S. Fish and Wildlife Service Section 6 Grant. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A practical information-theoretic approach. Springer, New York, New York, USA. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Ivan, J. S., and T. M. Shenk. 2010. Estimating the Extent, Stability and Potential Distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press, Oxford, UK. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Shenk, T. M. 2005. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Shenk, T.M., and R. H. Kahn. 2003. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2010. The Colorado lynx reintroduction program. Report to the Colorado Division of Wildlife, Fort Collins, Colorado. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. Theobald, D.M., D.L. Stevens, Jr., D. White, N.S. Urquhart, A.R. Olsen, and J.B. Norman. 2007. Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management 40(1): 134-146. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 17 �Table 1. Model selection results for estimating occupancy of sample units by Canada Lynx (Lynx canadensis) in the Core Research Area, San Juan Mountains, Colorado, Winter 2010-2011. Model AICc ΔAICc AICc Wt Num Par p(KmSurveyPerVisit)ψ(SprFir) 81.25 0.00 0.78 4 p(.)ψ(SprFir) 84.23 2.98 0.17 3 p(KmSurveyPerVisit)ψ(.) 88.60 7.35 0.02 3 p(.)ψ(.) 89.95 8.70 0.01 2 p(TtlRoadLen)ψ(.) 90.29 9.04 0.01 3 p(.)ψ(Meadow) 91.25 9.99 0.01 3 p(Observer)ψ(.) 92.10 10.85 0.00 3 p(MaxKmSurv)ψ(.) 92.42 11.17 0.00 3 p(VisitCond)ψ(.) 97.77 16.52 0.00 5 Figure 1. Canada lynx Core Research Area in southwest Colorado. Squares are 75km2 sample units available for occupancy surveys. Blue represents the sample of 30 “accessible” units selected for snow tracking surveys. Orange are “inaccessible” units selected for surveys using remote cameras. Crosshatching indicates accessible units where lynx were detected. The data from inaccessible units has not been fully processed and units where lynx were detected are not shown. 18 �Target tree (scern t lure) Feather/wings (visua 11 u re) co (visual lure) Feather/wings (visual lure) Python cable Figure 2. General configuration of remote camera sets for detecting Canada lynx. Four such sets were deployed in each of 30 inaccessible sample units from Fall 2010 to Summer 2011. 19 �1 ➔ -; 0.8 - -- --(/) ::::I 0 -~ 0.6 .c C'O .c 0 o.. 0.4 "C (1) +-' C'O E ',i:i (/) 0.2 w 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0 .7 Proportion spruce/fir in Sample Unit Figure 3. Estimated probability of use (ψ) and 95% confidence intervals plotted against proportion spruce/fir in a sample unit. Relationship is based on snow tracking occupancy surveys completed in southwest Colorado, Winter 2010-2011. 20 0.8 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Monitoring Canada Lynx in Colorado Using Occupancy Estimation: Initial Implementation in the Core Lynx Research Area Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: T. Shenk, G. Merrill, E. Newkirk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, selfsustaining population of Canada lynx had been established. The purpose of this project was to develop a scientifically rigorous statewide plan to monitor this newly established population. Occupancy estimation, the use of presence/absence data to estimate the proportion of sample units used by a species within a study area, is appropriate for such a program. To evaluate this approach and provide initial estimates of occupancy and detection probability for planning purposes, we conducted a pilot occupancy estimation project in the core reintroduction area in the San Juan Mountains of southwestern Colorado. Lynx habitat in the study area was divided into 75-km2 sample units (8.66 km x 8.66 km cells), and we stratified the units into those accessible for snow tracking and “inaccessible” units, which were sampled via remote cameras. We randomly sampled 30 units from each stratum. A summary of snow tracking results can be found in Ivan (2011). Of the 120 cameras we deployed in late fall to survey the 30 inaccessible units, 113 were still operational when retrieved in early summer; 6 had memory cards that reached capacity in either May or June; 1 was stolen. We obtained 151,191 photos (min = 90, max = 6,948 per camera) from this effort. We determined species for each photo and checked our work using multiple observers. Average agreement between observers was 96%. We estimated that approximately 25% of inaccessible cells were used by lynx. Detection probability was 0.43. These pilot data are currently being used to conduct simulations and power analyses to determine how many sample units will be required to detect population changes of interest in Colorado. 26 �WILDLIFE RESEARCH REPORT MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA JACOB S. IVAN P. N. OBJECTIVE Assess the use of occupancy estimation as a means of monitoring Canada lynx in Colorado using the Core Research Area in the San Juan Mountains as a test site. SEGMENT OBJECTIVES 1. Obtain initial estimates of occupancy and detection probability from units where remote cameras were the primary detection method. 2. Determine covariates and covariate structures that will be most useful for modeling occupancy and detection probability for camera surveys. 3. Combine these results with those obtained via previous work (snow tracking) to inform simulation work aimed at determining the number of sample units, and visits to each unit, required to detect changes of interest in the lynx population in Colorado. INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple human-associated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) considered reintroduction as the best option to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, and 218 lynx were released into Colorado from 1999 – 2006 (Devineau et al. 2010). The goal of the Colorado lynx reintroduction program was to establish a selfsustaining, viable population of lynx. Progress toward this goal was tracked via evaluation of critical criteria related to lynx survival, fidelity, and recruitment. Recently, CPW determined that the criteria had been met and a viable Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). In order to track the distribution, stability, and persistence of this new lynx population, a minimally-invasive, long-term, statewide monitoring program is required. Abundance estimation is not feasible logistically and presents statistical difficulties even when field logistics can be managed. However, occupancy estimation, which uses detection/non-detection survey data to estimate the proportion of area occupied in a study area, is appropriate and feasible. In short, such a monitoring scheme requires multiple visits to a sample of survey units, and on each visit observers record whether a lynx was detected or not. Such information can be used to compute the probability of detecting a lynx given that it is present on a unit, which can in turn be used to estimate the proportion (ψ) of all survey units that are occupied. This metric can be tracked through time and is assumed to be closely tied to the 27 �size and extent of the lynx population. That is, if the proportion of survey units occupied by lynx declines through time, we assume this is due to a decline in the lynx population itself. Additionally, occupancy surveys can provide information relative to the distribution of lynx in the state. CPW initiated work to evaluate detection methods for occupancy estimation in 2009-2010 (Shenk 2009). Three methods of detecting lynx were tested in sample units where lynx were known to occur: snow tracking surveys, remote camera surveillance, and hair snags. The best method for detecting lynx was snow-tracking (daily detection probability = 0.70). Camera surveillance was far less efficient (daily detection probability = 0.085), and hair snares were ineffective (daily detection probability = 0.0; Ivan and Shenk 2010). Snow tracking, however, requires safe and extensive access to a survey unit via truck and/or snowmobile. Therefore, it cannot be used in roadless or wilderness areas, which may provide important lynx habitat. Here we build on this work to test occupancy estimation on a large scale using snow tracking where accessibility permitted it, and remote cameras in areas that were not accessible. METHODS Study Area The study area consisted of the 20,684 km2 “Lynx Core Research Area” in southwest Colorado. The Core Research Area is defined as areas >2591 m (>8500 ft) in elevation within the area bounded by New Mexico to the south, Taylor Mesa to the west, and Monarch Pass on the north and east (Figure 1). Topography in this area is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce (Picea engelmanii) - subalpine fir (Abies lasiocarpa) is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m, 8500-11,000 ft). Sampling The study area was divided into 75 km2 (8.66 km × 8.66 km) sample units, which reflects the mean annual home range size of reproductively active female lynx in Colorado (Shenk 2007) and Montana (Squires and Laurion 1999). Sample units that did not meet the following criteria were discarded as they did not represent potential lynx habitat that could be surveyed. ≥50 % of the cell contained conifer or montane/alpine habitat, as identified by the SWReGAP LandCover Dataset ( http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf) and 2. ≥ 50 % of the cell was located on public land (tribal, NGO, city, and county lands were considered private) as determined by COMaP (Theobald, D.M., G. Wilcox, S.E. Linn, N. Peterson, and M. Lineal. 2008. Colorado Ownership, Management, and Protection v7 database. Human Dimensions of Natural Resources and Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, www.nrel.colostate.edu/projects/comap). 1. Each of the remaining sample units was assigned a random number resulting from a spatially balanced sampling scheme (RRQRR; Theobald et al. 2007) and units were stratified by accessibility for snow tracking or camera surveys. The cells with the lowest 30 random numbers for each stratum were selected for sampling during the pilot work. A few cells in both strata were discarded once field work began due to access issues and these were replaced with cells 31, 32, etc. 28 �Snow tracking Surveys A detailed discussion of the methods and results associated with snow tracking surveys appears in Ivan (2011). We do not repeat that discussion here. Instead we focus on methods and results from the remote cameras, as those data were unavailable for the 2011 report. Camera Surveys Four remote camera sets (RECONYX RapidFireTM Professional PC85) were placed within each selected “inaccessible” sample unit during September and October. Placement of camera sets was not random within the unit; they were placed strategically on the landscape to maximize coverage of the sample unit and exploit microsites most likely to be used by lynx. Camera sets consisted of 1) a remote camera mounted to a tree using a Master Lock TM PythonTM cable lock, 2) a target tree at which the camera was pointed, generally about 5–10m away, 3) a compact disc strung from a nearby branch to visually attract lynx from a distance, 4) 2 feathers strung up in such a manner as to entice lynx to walk between the camera and the target tree, and 5) wool soaked in commercial scent lure that was packed into the bark of the target tree to hold lynx in front of the camera (Figure 2). Cameras were placed higher than usual, about head-height, and pointed slightly downward at the target tree so photos could be obtained during both snow-free periods and during periods of accumulating snow. Cameras were collected during June and July at which time the number of photos, percent of memory card used, percent battery life remaining, and condition of visual/scent lures was recorded. All photo attributes were imported into a database and species was assessed for each photo based on review by at least 2 observers. Analysis Assumptions inherent in occupancy estimation are 1) surveyed sites are either occupied or not occupied by the species of interest throughout the duration of the study; no sites change status during the survey period (i.e., the system is closed), 2) the probability of occupancy is constant across sites or can be modeled using covariates, 3) the probability of detection is constant across sites or can be modeled using site-specific covariates, and 4) species detection at a site is assumed to be independent of species detection at other sites (MacKenzie et al. 2006). Sampling mobile carnivores such as lynx presents a clear violation of the first assumption as individuals undoubtedly move into and out of sample units routinely. Fortunately, estimation can proceed, but the quantities estimated are different from traditional occupancy estimation. Rather than estimating the probability that a unit is occupied by lynx, we now estimate the probability that a sample unit is used by lynx. Also, the estimated detection parameter is not the probability of detection given a site is occupied, it is the product of a) the probability of detection given the species is available for detection, and b) the probability that the species was available. These subtleties aside, the procedure still gives a metric (use) that can be monitored through time to detect trends. We used the “Occupancy Estimation” data type in Program MARK to produce initial estimates of occupancy (i.e., use, ψ) and detection probability (p) for the camera stratum. Photos were grouped by month (November to March) for each sample unit such that encounter histories included 5 “visits.” Due to this grouping, there were no meaningful covariates for p. Individual cameras recorded moon phase and temperature for each photo, but aggregated over a month, these data were not helpful. Some camera sets used different scent lures than others, but aggregating by unit negates the utility of this information as well. We hypothesized that the proportion of spruce/fir and/or willow (Salix spp.) cover in each unit may affect the probability of use and/or probability of detection. Thus, we considered these covariates as potentially important for explaining variability in ψ and p. We held ψ constant and built an additive model for each detection covariate (one at a time) to determine the best structure for p. We then held p at the best structure as determined by AICc (Burnham and Anderson 2002) and fit additive models using the 29 �covariates for ψ. We also ran a model where both p and ψ were held constant as a baseline for comparison. We report estimates of p and ψ from the AICc top model. RESULTS Of the 120 cameras deployed during Fall 2010, 113 were still operational when retrieved in Summer 2011 after 234-309 days of deployment. Six had memory cards that reached capacity in either May or June, and one camera was stolen. On average, we obtained 1,260 photos per camera (min = 90, max = 6,948) for a total of 151,191 photos. At the time of retrieval, compact discs were still operational for 46% of camera sets, feathers were operational at 64% of sets, and remnants of scent lure were detected at 55% of sets. We obtained 445 photos of lynx and detected them in 7 of the 30 units sampled (Figure 1). Average agreement between photo reviewers was 96%. Of the model structures we fit, none was clearly better than the others as AICc weight was distributed fairly evenly (Table 1). Beta estimates for fitted models suggested that ψ was positively associated with both percent spruce/fir and percent willow in a given unit. Spruce/fir was also positively associated with detection probability, whereas willow was negative associated with detection probability. However none of these models were as well supported by the data as the null model in which ψ and p were considered constant across cells. Thus, results generally followed our expectations, but the null model came out on top likely due to sparse data and small samples in this pilot study. Model-averaged estimates for ψ and p were 0.25 and 0.42, respectively. Detection probability using cameras was about the same as for snowtracking (Ivan 2011), but estimated probability of use for inaccessible sampling units was about half that estimated for accessible cells sampled via snow tracking. DISCUSSION Initial results indicate that occupancy (use) can be adequately modeled using data collected via snow tracking. Precision on estimates of ψ and p was relatively poor, but this can be addressed by sampling more units and/or making more visits. Modeling p and ψ as functions of the covariates (spruce/fir and willow) was not as well supported as specifying them to be constant across units. However, we recommend continuing to record and use these covariates and others in future surveys as it seems reasonable that these covariates should impact detection probability and/or use, and their effects may be important as sample size increases. We estimated that lynx used approximately 25% of the sample units available in the Core Research Area. However, for this pilot study, lynx habitat was coarsely defined as units with >50% conifer and/or montane cover and >50% public land. In several cases, sampled units met these criteria, but field crews that actually made visits indicated these units did not appear to include much lynx habitat. CPW recently finished an analysis to produce a map of predicted lynx habitat throughout the state. In the future, we expect to use this map to frame the population of units to sample for lynx monitoring. This more refined population of sample units should reduce time wasted surveying units that do not include good lynx habitat, and will result in an increased estimate of probability of use. Indeed, re-running the analysis using only those cells (n = 24) within the top 40% of predicted lynx habitat in the state increased the occupancy estimate to 0.31. Roughly half of the visual attractants we used did not operate through the entirety of the study. These attractants are important for drawing lynx to the set from a distance and their failure diminishes the utility of the cameras for detecting lynx. If cameras are to be used in the future, design changes will be necessary to ensure that most of these visual attractants operate throughout the sampling season. We suggest that attractants be attached via wire rather than fishing line. We also suggest that auditory 30 �attractants may be helpful. In a recent study on cougars (Puma concolor) in the Front Range of Colorado, visitation rates at camera sites increased dramatically when auditory attractants were used in addition to scent lures and visual attractants (Kirstie Yeager, personal communication). ACKNOWLEDGMENTS We thank Britta Schielke, Cate Brown, Wendy Lanier, Joan Meiners, Shane McKenzie, Nick Burgmeier, Doug Clark, Bob Peterson, Tim Hanks, Kei Yasuda, Ashley Bies, Tyler Kelly, Alyssa Winkler, and Carolyn Shores for their efforts in the field. Dale Gomez and Rhandy Ghormley (USFS) graciously coordinated housing for seasonal crews. We thank various personnel from both the Rio Grande and San Juan National Forests for logistical help in the field. Funding was provided by a U.S. Fish and Wildlife Service Section 6 Grant. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A practical information-theoretic approach. Springer, New York, New York, USA. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524–531. Ivan, J. S., and T. M. Shenk. 2010. Estimating the Extent, Stability and Potential Distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Ivan, J. S. 2011. Monitoring Canada lynx in Colorado using occupancy estimation: Initial implementation in the Core Lynx Research Area. Wildlife Research Report. Colorado Division of Parks and Wildlife, Fort Collins, CO, USA. Pages 11–20. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press, Oxford, UK. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Shenk, T. M. 2005. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Shenk, T.M., and R. H. Kahn. 2003. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2010. The Colorado lynx reintroduction program. Report to the Colorado Division of Wildlife, Fort Collins, Colorado. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337–349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. 31 �Theobald, D.M., D.L. Stevens, Jr., D. White, N.S. Urquhart, A.R. Olsen, and J.B. Norman. 2007. Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management 40(1): 134–146. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Prepared by ___________________________ Jacob S. Ivan 32 �Table 1. Model selection results for estimating lynx occupancy of sample units surveyed via remote camera in the Core Research Area, San Juan Mountains, Colorado, Winter 2010–2011. Model ψ(.)p(.) ψ(.)p(willow) ψ(.)p(SprFir) ψ(SprFir)p(.) ψ(willow)p(.) AICc 84.54 85.06 85.37 85.73 85.92 ΔAICc 0.00 0.52 0.83 1.19 1.38 AICc Wt 0.29 0.22 0.19 0.16 0.14 Num Par 2 3 3 3 3 SnowTra Lynx Delee Figure 1. Canada lynx Core Research Area in southwest Colorado. Squares are 75km2 sample units available for occupancy surveys. Blue represents the sample of 30 “accessible” units selected for snow tracking surveys. Orange are “inaccessible” units selected for surveys using remote cameras. Crosshatching indicates units where lynx were detected. 33 �Target tree (scern t lure) Feather/wings (visua 11 u re) co (visual lure) Feather/wings (visual lure) Python cable Figure 2. General configuration of remote camera sets for detecting Canada lynx. Four such sets were deployed in each of 30 inaccessible sample units from Fall 2010 to Summer 2011. 34 � https://cpw.cvlcollections.org/files/original/921c5283d5df51faccf544bbaaddc42d.pdf d07d87bd0ade9817d706c87afe4ae252 PDF Text Text Colorado Parks and Wildlife July 2012–June 2013 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Statewide Monitoring of Canada Lynx in Colorado: Evaluation of options Period Covered: July 1, 2012 – June 30, 2013 Author: J. Ivan Personnel: M. Ellis, Alaska Department of Fish and Game, M. Schwartz, U.S. Forest Service Rocky Mountain Research Station All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. Here we evaluate options for monitoring the long-term success of the reintroduction effort using noninvasive techniques to assess species status and distribution. Ideally, this could be accomplished by estimating abundance of lynx in the state on a recurring basis. However, abundance estimation can be difficult for rare, wide-ranging carnivores because such efforts typically require multiple encounters with a number of individuals. Occupancy estimation may be a useful alternative as sampling under this framework requires only detection or non-detection information at the species level rather than multiple encounters with individuals. Models are fit to the detection data, collected over multiple visits to sampling units, to estimate the proportion of sample units used by the focal species within a study area. The monitoring objective may be to simply track this proportion (ψ) through time. However, ψ and abundance are clearly related; when abundance is zero, ψ is zero, and when the landscape is saturated with animals, ψ = 1.0. Thus, an alternative objective may be to use estimated ψ as a surrogate for abundance, and thus track abundance through time using occupancy estimation. We used a series of simulations based on pilot data to assess the effort required to detect declines (or increases) of interest in abundance and ψ of lynx in Colorado using occupancy estimation. We found that small changes could not be detected even with an enormous amount of effort. Even 50% declines or increases in abundance or ψ would require substantial effort and coordination to implement on a statewide basis. Tracking abundance through time using occupancy required relatively more effort than simply tracking a similar decline in ψ itself. Given these results, perhaps a scaled down approach is most practical. That is, CPW could implement a rigorous occupancy estimation program to track abundance, but only in a portion of the state. Elsewhere, rudimentary presence/absence surveys (i.e., surveys 15 �conducted without repeat visits, and probably on a rotating basis so any given mountain range is only visited every ~5 years) could be conducted to ascertain the distribution of lynx among the major mountain ranges and this distribution would tracked through time as a secondary measure of population performance. WILDLIFE RESEARCH REPORT STATEWIDE MONITORING OF CANADA LYNX IN COLORADO: EVALUATION OF OPTIONS JACOB S. IVAN PROJECT NARRATIVE OBJECTIVE Use simulation to assess occupancy estimation as a means of monitoring Canada lynx in Colorado. SEGMENT OBJECTIVES 1. Complete simulations to assess the effort required to track various declines (or increases) in abundance of lynx using occupancy estimation. 2. Complete simulations to assess the effort required to track various declines (or increases) in occupancy of lynx using occupancy estimation. INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U.S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state (U.S. Fish and Wildlife Service 2000). However, lynx were extirpated, or reduced to a few animals, in Colorado by the late 1970’s, (U.S. Fish and Wildlife Service 2000) most likely due to multiple human-associated factors including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) considered reintroduction as the best option to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, and 218 lynx were released into Colorado from 1999 – 2006 (Devineau et al. 2010). The goal of the Colorado lynx reintroduction program was to establish a self-sustaining population of lynx. Progress toward this goal was tracked via evaluation of criteria related to lynx survival, fidelity, and recruitment. Recently, CPW determined that the criteria had been met and an apparently viable Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. Ideally, this could be accomplished by estimating abundance of lynx in the state on a recurring basis. However, abundance estimation using traditional mark-recapture methods is difficult for rare, wide-ranging carnivores because such it typically requires multiple encounters with a number of individuals (Lukacs 2013). New advances in spatially explicit capture-recapture (Efford et al. 2009, Royle et al. 2009), use of multiple data sources (Sollmann et al. 2013a), and implementation of mark-resight approaches (Sollmann et al. 2013b) make 16 �the problem more tractable as these approaches generally require less intensive capture efforts than traditional mark-recapture. However, they still require some of this work, which can be both difficult and invasive. Alternatively, occupancy estimation may be a useful approach for monitoring lynx (MacKenzie et al. 2006). Such an approach requires several visits to a set of sampling units, but the data collected for each visit is simply detection or non-detection of the focal species (MacKenzie et al. 2003). There is no need for marking or tallying individuals. The detection information is used to estimate the proportion (ψ) of sample units used by the focal species (i.e., “occupancy”) which can then be monitored through time. The advantage in such an approach is that no individual identification is necessary and the information gathered during sampling is generally easier to obtain, especially for rare carnivores. The disadvantage is that information obtained about the population of interest is less resolute (i.e., knowing the proportion of the landscape used by a species is less informative than knowing the number of individuals within it). Finally, monitoring might be accomplished by simply documenting distribution of lynx in the state. Under this approach, the metric of interest to be tracked through time would be the number of mountain ranges (of the 6−8 main ranges) with evidence of use by lynx. Currently lynx are known to be present in the San Juan, Sawatch, and Elk Mountains where the reintroduction and/or associated research occurred. Expansion into other ranges over the long-term could be considered evidence of a successful reintroduction; recession into only 1 range, or none would indicate failure. Monitoring distribution is the least costly approach considered here, but also the least informative and least rigorous. We assume that estimation of abundance is not a viable option due to cost, although this assumption should be formally tested, especially as new statistical techniques arise. We further assume that documenting distribution is the least costly option and is thus logistically feasible. However, there is no power analysis or other statistical considerations associated with this option. Thus, from here forward, we focus on using simulation to assess the feasibility of using occupancy for monitoring lynx in Colorado. Under an occupancy framework, the monitoring objective may be to declare ψ as the metric of interest and simply track it through time as a means of monitoring the lynx population in a coarse sense. However, ψ is clearly related to abundance; when abundance is zero, ψ = 0, and when the landscape is saturated with animals, ψ = 1. Thus, an alternative objective may be to use estimated ψ as a surrogate for abundance, and thus attempt to track abundance through time using occupancy estimation. This may be a preferable approach because abundance is ultimately the quantity of interest. The utility of this idea relies on the strength of the relationship between ψ and abundance, which is partially dependent on sampling effort and partially dependent on the characteristics of the system under study. That is, if home range size and territorial tendencies of the focal species result in an average of 1 individual per sample unit, then ψ can be expected to mirror abundance quite well. However, if the interaction of these characteristics leads to multiple individuals using a sample unit (on average), then ψ and abundance will be relatively decoupled. Abundance could decline fairly significantly before precipitating any change in ψ. We conducted a series of simulations to assess the effort required for using occupancy estimation to detect declines (or increases) of interest in abundance or ψ of lynx in Colorado. Our simulations were calibrated to reflect estimates of ψ and detection probability (p) collected from pilot work in the state. We compare the various alternatives available for monitoring lynx in Colorado and discuss trade-offs associated with each. 17 �METHODS Pilot Work CPW initiated work to evaluate methods for detecting lynx during winter 2009−2010 (Shenk 2009, Ivan and Shenk 2010). Similar to Squires et al. (2012), the pilot study area was divided into 75km2 sample units (roughly the size of a female home range) and 3 methods of detecting lynx were tested in 6 sample units where lynx were known to occur: snow tracking surveys, remote camera surveillance, and hair snags. The daily probability of detecting a lynx given their presence in the unit was 0.70, 0.09, and 0.00 for snow tracking, remote cameras, and hair snares, respectively (Ivan 2011). During winter 2010−2011, pilot work was expanded to include 30 wilderness sample units surveyed via remote camera and 30 accessible units surveyed via snow-tracking. The status of lynx (present or not) in these randomly selected units was unknown. We fit single-season occupancy models to data from each stratum and found ψ = 0.33 and p = 0.40 for wilderness units (Ivan 2012; camera data were collapsed by month into 5 occasions, p = 0.40 for each occasion), and ψ = 0.65 and p = 0.37−0.43 for accessible units (Ivan 2011; based on 3 occasions of snow-tracking surveys). Thus, overall, ψ ≈ 0.50 and p ≈ 0.40 for the pilot study area. Assessment of using occupancy estimation to track changes in ψ To assess the effort required to detect declines or increases of interest in ψ using an occupancy estimation framework, we conducted a series of analyses using the simulation function in Program MARK (White and Burnham 1999). Within the “robust design occupancy” data type (i.e., multi-season occupancy, MacKenzie et al. 2006), we set up a simulation model in which ψ = 0.5 for year 1 and p = 0.4, thus matching estimates derived from pilot work. We then specified linear declines in ψ to 0.45 (10% decline), 0.40 (20% decline), or 0.25 (50% decline) over a 10-year period. We also specified an increase in ψ to 0.75 (50% increase) over a 10-year period. We generated data from each simulation model for 2, 3, 4, or 5 occasions and N = 25, 50, 75, 100, 125, and 150 units sampled. We also considered that sampling may occur annually or only in alternate years. Thus, there were 192 possible combinations of parameters specifying the simulation model (4 levels of change in ψ, 4 levels of occasions, 6 levels of sample size, 2 levels specifying the survey interval), and we generated 1000 simulated datasets for each of the 192 combinations. To each of the 192,000 data sets, we fit 2 estimation models. The first fixed ψ to be constant across the 10 years represented in each data set. The second specified a linear trend in estimated ψ. The true, data-generating model always included a trend of some type. Thus we defined “power” as the proportion of simulations in which Akaike’s Information Criterion (adjusted for small sample size; AICc) selected the correct (second) model by at least 2 AICc units (Burnham and Anderson 2002). In general, given sparse data (such as that generated from only a few occasions and/or for a small number of sample units) AICc will select the constant model as the one that fits the data best because there is not enough information to support anything but the simplest model. As the data become richer (i.e., more occasions and/or larger sample size), AICc will begin to pick the correct model more often. We adopted the conventional benchmark of 0.8 as a cutoff for adequately identifying declines or increases of interest. That is, combinations of sample size and occasions that resulted in power = 0.80 were deemed adequate to confidently detect declines or increases under consideration. Assessment of using occupancy estimation to track changes in abundance To assess the effort required to detect declines or increases in abundance using an occupancy estimation framework, we conducted a series of analysis using the R (R Development Team 2013) package SPACE (Ellis et al. 2013). Specifically, we provided the package with spatially referenced data representing predicted lynx habitat in Colorado (Ivan et al. 2011). The package then randomly assigned home range centers for 125 males and 125 females on this landscape. Home range centers were only 18 �allowed to occur in cells that had reasonable probability of being lynx habitat. To mimic territoriality, males were not allowed to have a home range center within 6 km of another male; females could not be assigned a home range center within 5 km of another female. Males and females could be any distance from each other. Once home range centers were assigned for all 250 lynx, each individual was temporarily assigned a bivariate normal utilization distribution (i.e., the probability of occurrence for each individual was highest at its home range center and dissipated equally in all directions) appropriately sized for each sex. This simplistic utilization distribution was then weighted by the underlying map of predicted lynx habitat to produce an irregular, realistic utilization distribution that was unique to each individual. Thus, following this first step, a realistic number of virtual lynx were distributed across the state and assigned reasonable utilization distributions that governed their movement across the landscape. We then specified declines (50%, 20%, 10%), and increases (50%) in abundance over a decade by randomly removing or adding the appropriate number of individuals at each of 10 time steps. Next, simulated landscapes were overlaid with a sampling grid consisting of 75-km2 sample units. This was done for each of the 10 time steps. Based on utilization distributions assigned to each individual, SPACE computed the probability of at least 1 animal being present in each unit during each time step (i.e., sampling occasion). It then applied the detection probability specified for the simulation to generate detection/non-detection data for each unit. We generated data sets for a variable number of occasions and sample sizes similar to that described above. As before, each simulated dataset was fitted with 2 competing models, one in which the estimated ψ was fixed to be constant throughout the 10-year period, and second in which it followed a linear trend. We again defined power as the proportion of simulations in which AICc selected the correct model. We also considered the impact of sampling every other year by removing data from even years. On average, estimates of ψ and p for the first year of each simulation were 0.50 and 0.34 respectively, which is close to the values observed from the pilot work. Thus, the model was well calibrated to the field. Sampling Details For each of the monitoring metrics, ψ and abundance, we identified the most plausible scenario that could be implemented in the field by CPW personnel, and further detailed the effort required to complete a survey by selecting a mock sample. To accomplish this, we first defined the population of sample units of interest by overlaying a grid of 75-km2 cells on the predicted lynx habitat layer for Colorado (Ivan et al. 2011). We identified cells as potential sample units if at least 50% of the lynx habitat pixels within them had probability values ≥0.60 (See Ivan et al. 2011 for detailed discussion of these probability values). This resulted in a population of 475 cells from which to draw a sample (Fig. 3). Next, we used the R (R Development Team 2013) package ‘spsurvey’ (Kincaid 2013) to enumerate each sample unit in a spatially balanced random fashion such that a valid sample of any size could be selected by simply ordering the cells by their randomly assigned number and selecting the 1st N cells. For each scenario of interest, we selected an appropriate sample, then summarized the effort required to complete the sample by CPW Area. We assumed 6 person-days would be required to sample each non-wilderness unit and 10 person-days would be required to sample each wilderness unit. These estimates were based on pilot work and assume that for snow-tracking surveys (non-wilderness units), personnel would work in pairs and complete 3 visits per sample unit. For wilderness units, we assumed personnel would work in pairs over 2.5 days to set 4 cameras in each selected unit, then work another 2.5 days per unit to retrieve the cameras after sampling. These represent minimum estimates of cost as any survey effort would also require personnel time to maintain snowmobiles and cameras, enter data, and complete analyses and reports. 19 �RESULTS Regardless of whether the objective was to use occupancy estimation to detect declines in ψ or abundance, power was low (≤ 0.40) for all but the most drastic changes in the lynx population, even with significant survey effort (e.g., N = 125−150; Fig. 1, 2). Fifty percent declines or increases in ψ over a decade could be adequately detected (power = 0.80) with 3 visits to each of 75 sample units if sampling occurred on an annual basis (Fig. 1). Reducing sampling effort to every other year did not impart dramatic changes to the sample size needed to maintain power. In contrast, annual surveys comprising 3 visits to 125 sample units were required to adequately detect 50% declines or increases in abundance over the same time span (Fig. 2). Also, in the case of abundance, reducing survey effort to every other year required ~250 units in order to maintain power. Power curves in the panels representing results for 20% and 10% declines in abundance (Fig. 2) were relatively high at very small sample sizes, then declined with increasing sample size before increasing again at large sample sizes. These counterintuitive results are likely artifacts of fitting models to sparse data. When data are sparse, parameters may not be estimated well and the model may return values at a boundary (i.e., ψ will be estimated as either 0 or 1). If the estimates of ψ near the beginning and/or end of the time series are returned as 0 or 1, then a trend may be detected. In an actual analysis with a single data set, such a phenomenon is easy to diagnose and alternatives are available to tweak the model and prevent this from happening. However, when thousands of datasets and model fits are involved, such tweaking is impossible. Thus, these high initial values and subsequent declines should be ignored. Power to detect trends across this range of sample sizes is likely very low. The most plausible scenarios for monitoring either ψ or abundance were those aimed at detecting a 50% change in either metric. Selection of an actual sample revealed that in both cases, the number of person-hours involved to carry out the sampling was substantial (Fig. 4, 5). For example, the scenario intended to provide an 80% chance of detecting a 50% decline in abundance over 10 years would require making 3 visits to each of 125 sample units on an annual basis. Assuming 2 Biologists, 2 District Wildlife Managers and 2 USFS Biologists were willing the carry out the work in each area, monitoring lynx under this scheme would require on average about 10 days worth of work per person per Area (Fig. 4; on average 64 person-days would be required per area; 64 person-days/6 people ≈10 days). Some Areas would require nearly 3 times that effort (Fig. 4; maximum estimated effort was 184 person-days; 184 person-days/6 people ≈ 30 days of work per person). The scenario intended to provide an 80% chance of detecting a 50% decline in ψ over 10 years was projected to require an average of 38 personhours to complete per Area, or ~6 days per person if the same set of biologists and managers participated. Again, effort in some Areas would be nearly 3 times higher. DISCUSSION We rigorously tested the power to detect various changes in population status of Canada lynx in Colorado using occupancy estimation. Small changes (10% or 20% declines) could not be detected with any reasonable amount of effort. Detection of large changes (50% declines or increases in either abundance or ψ) may be possible but would require considerable investment and coordination among management entities. This was especially true for the scenarios aimed at detecting changes in abundance, which is the more preferable approach as it would be most informative. Detecting large changes in ψ over a 10-year period required just more than half of the effort required to detect the same change in abundance, thus making it more feasible. However, this level of effort would still be costly and the information gained would be of low resolution. That is, by the time ψ declines by 50%, a significant number of individuals would be lost from the landscape, and it may be too late for any action to counter the decline. Monitoring distribution rather than abundance or occupancy would likely be the most 20 �affordable option but it is also least informative and least rigorous. In fact, it was not evaluated in this report because it is completely absent of any statistical underpinnings. Furthermore, the distribution approach provides little opportunity to learn why changes are happening. The multi-season occupancy models employed here to track abundance or ψ include extinction and colonization parameters (which we have largely ignored for the purposes of simulation). Modeling these parameters may provide an opportunity to associate changes on the landscape (e.g., bark beetle outbreaks, wildfire, timber harvest) with changes in ψ, thus providing an opportunity to learn why changes are occurring. Clearly trade-offs exist between containing costs and implementing a program that is meaningful, rigorous, and provides opportunities for continued learning. Perhaps the most practical way forward is a hybrid approach in which CPW implements a rigorous occupancy estimation program to track abundance, but only in a portion of the state, while simultaneously implementing the relatively less rigorous distributional approach statewide. Such an approach would provide detailed information about a (hopefully) representative subpopulation of lynx, but would be easier to implement as it would take less effort it would only be implemented in a portion of the state. Additionally, CPW would still obtain useful information regarding the statewide distribution of animals. If CPW were to adopt such a strategy, we suggest that the rigorous portion of the effort focus on the San Juan Range in the southwest as it provides the bulk of the lynx habitat and has long been considered a core stronghold for the species. Thus, it could be considered a “sentinel” area such that increases in the lynx population there probably bode well for the rest of the state, and declines there probably bode poorly. ACKNOWLEDGMENTS We thank Eric Odell, Gary White, Larissa Bailey, Paul Lukacs, and Fred Allendorf for initial and ongoing discussions relative to monitoring rare carnivores in general and lynx in particular. We thank the Rocky Mountain Research Station and a PECASE award to Mike Schwartz for initial funding toward simulation work. Funding specific to simulations regarding lynx in Colorado was provided by a U.S. Fish and Wildlife Service Section 6 Grant to Colorado Parks and Wildlife. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty, P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Efford, M. G., D. L. Borchers, and A. E. Byrom. 2009. Density estimation by spatially explicit capturerecapture: likelihood based methods. Pages 255-269 in G. P. Patil, D. L. Thomson, E. G. Cooch, andM. J. Conroy, editors. Modeling Demographic Processes in Marked Populations. Springer Science, Boston, Massachusetts, USA. Ellis, M. M., J. S. Ivan, and M. K. Schwartz. 2013. Spatially explicit power analyses for occupancy-based monitoring of wolverine in the U.S. Rocky Mountains. Conservation Biology In Press:xxx-xxx. Ivan, J. S. 2011. Monitoring Canada lynx in Colorado using occupancy estimation: Initial implementation in the Core Lynx Research Area. Colorado Division of Parks and Wildlife. Ivan, J. S. 2012. Monitoring Canada lynx in Colorado using occupancy estimation: Initial implementation in the Core Lynx Research Area. Colorado Division of Parks and Wildlife. Ivan, J. S., M. Rice, P. M. Lukacs, T. M. Shenk, D. M. Theobald, and E. Odell. 2011. Predicted lynx habitat in Colorado. Colorado Division of Parks and Wildlife. Ivan, J. S., and T. M. Shenk. 2010. Estimating the extent, stability and potential distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area. Colorado Division of Wildlife. 21 �Kincaid, T. 2013. R package 'spsurvey'. Version 2.5:http://www.epa.gov/nheerl/arm/. Lukacs, P. M. 2013. Closed population capture-recapture models. Pages 14.11 - 14.39 in E. Cooch, andG. C. White, editors. Program MARK: A Gentle Introduction MacKenzie, D., J. D. Nichols, J. E. Hines, M. G. Knutson, and A. B. Franklin. 2003. Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology 84:2200-2207. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. Meaney, C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20th century. Colorado Department of Transportation Report. Royle, J. A., J. D. Nichols, K. U. Karanth, and A. M. Gopalaswamy. 2009. A hierarchical model for estimating density in camera-trap studies. Journal of Applied Ecology 46:118-127. Service, U. S. F. a. W. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U. S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. Shenk, T. M. 2009. Post-Release Monitoring of Lynx Reintroduced to Southwestern Colorado. Colorado Division of Wildlife. Shenk, T. M., and R. H. Kahn. 2010. The Colorado lynx reintroduction program. Colorado Division of Wildlife. Sollmann, R., B. Gardner, R. B. Chandler, D. B. Shindle, D. P. Onorato, J. A. Royle, and A. F. O'Connell. 2013a. Using multiple data sources provides density estimates for endangered Florida panther. Journal of Applied Ecology 00:000-000. Sollmann, R., B. Gardner, A. W. Parsons, J. J. Stocking, B. T. McClintock, T. R. Simons, K. H. Pollock, and A. F. O'Connell. 2013b. A spatial mark–resight model augmented with telemetry data. Ecology 94:553-559. Squires, J. R., L. E. Olson, D. L. Turner, N. J. DeCesare, and J. A. Kolbe. 2012. Estimating detection probability for Canada lynx, Lynx canadensis, using snow-track surveys in the northern Rocky Mountains, Montana, USA. Wildlife Biology 18:215-224. Team, R. D. C. 2013. R Foundation for Statistical Computing, Vienna, Austria. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Jake Ivan, Wildlife Researcher 22 �en 50%_ Decline C 20%_Decline 10%_Decline 50%_Increase 2 1.0 0 0.8 ~ _2l 0.6 - Visits 50 4 - E 02 -0 - 2 ~ 10 ]j 0.8 - - 3 - 4 ~ 06 - - s a, ~ 04 - u 0.2 ~ 0 U I I I 25 50 75 I I I I 100 125 15025 I I 50 ~ I 1001~1~~ ~ ~ I I I I 1001~1~~ I I ~ ~ I I I 1001~1~ Number of cells sampled Figure 1. Power to detect various changes in the proportion (ψ) of sample sites used by lynx in Colorado using occupancy estimation. Changes were assumed to occur over a 10-year period. Power is shown for scenarios in which sample units were sampled annually (top panels) and when sampling occurred only in alternate years (bottom panels). “Visits” corresponds to the number of times selected units would be searched to collect detection/non-detection data. Visits could represent days for units surveyed via snow tracking, or they may represent blocks of time into which continuously collected camera data could be binned (e.g., 1 visit = 1 month of camera sampling). 23 �50% Decline 20% Decline 10% Decline 50% Increase Annual Alternate I I I t I I I I t t I I I I I I I I I 250 500 750 1000 250 500 750 1000 250 500 750 1000 250 500 750 1000 - a.a #visits - 2 3 4 Number of cells sampled Figure 2. Power to detect various changes in abundance of lynx in Colorado using occupancy estimation. Changes were assumed to occur over a 10-year period. Power is shown for scenarios in which cells are sampled annually (top panels) and when sampling occurs only in alternate years (lower panels). “Visits” corresponds to the number of times selected units would be searched to collect detection/non-detection data. Visits could represent days for units surveyed via snow tracking, or they may represent blocks of time into which continuously collected camera data could be binned (e.g., 1 visit = 1 month of camera sampling). 24 �Figure 3. Predicted lynx habitat (red pixels = good, blue pixels = poor) in Colorado overlaid with 75-km2 sample units (black squares, N = 475) from which to select a sample for monitoring declines or increases of interest in ψ or abundance. Only units where at least half of the lynx habitat pixels within them had probability values ≥0.60 were included in the population to sample from. See Ivan et al. (2011) for details regarding construction of the predicted lynx habitat map and interpretation of pixels that comprise it. 25 �Region Northeast Northwest Southeast Southwest Total Area 1 2 6 7 8 9 10 11 13 14 15 16 17 18 #Sample Units 6 1 2 1 13 3 2 1 4 1 8 12 18 3 75 Effort (person-days) 44 10 16 6 102 18 12 6 28 6 52 76 128 22 526 Figure 4. Map and tabular summary of a spatially balanced random sample of N = 75 cells selected for monitoring a 50% decline or increase in ψ over a 10-year period in Colorado, USA using a combination of snow-track surveys and remote camera surveys. Estimated effort accounts for the differential time required to sample wilderness (cameras) and non-wilderness (snow-tracking) units. 26 �Region Northeast Northwest Southeast Southwest Area #Sample Units Effort (person-days) 11 3 3 3 17 5 5 4 6 2 17 19 26 4 125 82 26 22 18 134 30 34 24 44 12 122 130 184 28 890 1 2 6 7 8 9 10 11 13 14 15 16 17 18 Total Figure 5. Map and tabular summary of a spatially balanced random sample of N = 125 cells selected for monitoring a 50% decline or increase in abundance of lynx over a 10-year period in Colorado, USA using a combination of snow-track surveys and remote camera surveys. Estimated effort accounts for the differential time required to sample wilderness (cameras) and non-wilderness (snow-tracking) units. 27 � https://cpw.cvlcollections.org/files/original/0481b19251749efd65d4fa09f8e61bff.pdf 2e369aa296f0897661166329223aaeb4 PDF Text Text Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3001 : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Assessment of survival and optimal harvest Strategies of adult male mule deer in Middle Park, Colorado W-185-R Period Covered: July 1, 2010 - June 30, 2011 Author: E.J. Bergman; Project Cooperators; C.J. Bishop, K. Oldham, and L. Sidener Personnel: G. Abram, G. Birch, J. Broderick, M. Crosby, B. Davies, T. Elm, D. Gillham, K. Holinka, A. Holland P. Lukacs, B. Manly, S. Murdoch, S. Schwab, S. Shepherd Colorado Division Parks and Wildlife R. Swisher, S. Swisher, T. McKendrick Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We developed a study plan and initiated field work on a study designed to assess the survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Three years of baseline survival data for adult (≥ 1 yr. old) male deer will be collected before implementing a harvest management action that will redistribute hunters within DAU-9. One hundred adult (1.5 years old and older) male deer were captured and radio collared. The survival rate for these deer was estimated at 0.879 (SE = 0.0326) for the first survival period (January through July). 97 �WILDLIFE RESEARCH REPORT ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO ERIC J. BERGMAN P.N. OBJECTIVES SEGMENT OBJECTIVES 1. Develop a project study plan to address the lack of knowledge regarding survival and harvest strategies of adult mule deer. 2. Initiate field work in the form of capturing and radio collaring animals. 3. Collect survival data on radio collared deer and provide preliminary survival estimates for adult male mule deer. INTRODUCTION Historically, management of big game species has focused on the performance of adult females and the young of the year segments of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important because it takes few males to provide adequate breeding coverage for the population, and historic harvest management objectives were set to maximize hunting opportunities. As long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has shifted from the objective of providing maximal opportunity towards providing higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, increased potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999 Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest estimates, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Only rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and adult male survival rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of 98 �males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004b, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). These studies also suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management scenarios and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. An additional need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of changes in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as Data Analysis Units (DAUs) reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, these assumptions are not biologically realistic. It is possible that herds with large post-hunt populations of adult males experience higher levels of non-harvest mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. STUDY AREA This study is taking place in Middle Park, Colorado (see Appendix I for discussion of criteria for study area selection). Under the current management structure, Middle Park falls within DAU D-9. Within D-9 are 6 Game Management Units (27,181, 18, 37, 371, and 28; Fig. 1). Due to the geologic and topographical landscape in Middle Park, this area is conducive to splitting the DAU into experimental units (see Appendix I for experimental design). Additionally, from a management perspective, D-9 is 99 �currently managed for 35 adult males per 100 adult females. This ratio objective represents an average “quality” management objective in Colorado (i.e., DAUs with higher or lower objectives exist, thus data from D-9 will be the most universally applicable). Finally, the topography and landscape of Middle Park also makes it prone to periodic, harsh winters. This variability is fundamental to attaining reasonable estimates of process variation in adult male survival. METHODS Capture of adult male deer was initiated in January of 2011. Capture was conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 1994, Barrett et al. 1982). All captures occurred after the completion of the 4th rifle hunting season, eliminating conflicts between capture efforts and hunting. Due to the need to generate survival estimates linked to animals of known age, all animals were handled by CPW personnel for aging purposes. Field aging of animals was done by visual inspection of tooth wear patterns (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). Colorado Parks and Wildlife researchers/biologists were ferried to the general area in which capture was occurring and subsequently ferried the short distance to each capture location after individual animals were captured. Prior to release, all animals had their antlers removed via handsaw to minimize the potential risk of injury as the animal was released. All captures occurred after annual mule deer classification flights had been conducted, alleviating the potential for misclassification of antlerless males as females. All deer were fitted with expandable radio collars (see Appendix I for discussion of radio collar development). All radio collars were equipped with mortality sensors that doubled in pulse rate after remaining motionless for 4 hours. Between the time of capture and mid-June, we used ground based monitoring to determine the live/dead status of deer 3-4 times per week. Additionally, every 5-10 days we conducted a telemetry flight to hear any animals that hadn’t been heard from the ground during the preceding week. A general location was collected for each radio marked deer in early-March to determine if it had departed the GMU in which it had originally been captured. From mid-June through remainder of the summer, deer were monitored from the ground weekly and from the air once per month. When detected, all mortalities were investigated as quickly as possible to determine cause of death and to get an accurate estimate of the date of death. To help evaluate the effects of a changing sex ratio on hunter harvest, we are currently preparing to sample successful hunters to acquire an age of animals harvested in D-9. Ages will be estimated via the cementum aging process of incisors (Hamlin et al. 2000). When possible, a lower incisor was also collected from each radio collared deer that died in order to validate animal ages of captured animals. To acquire teeth for aging purposes, all hunters who have licenses to hunt in any GMU in D-9 will be contacted via mail. Each hunter will be provided with a sampling kit, a pre-posted return envelope and detailed directions on how to extract teeth for aging purposes. These data will help inform terrestrial biologists and wildlife managers if changes in the age of animals harvested occur as populations shift up or down in age structure as sex ratios are increased or decreased. RESULTS AND DISCUSSION In January, 100 deer were captured, aged, weighed, radio collared and released during a 3½ day period. On one occasion, the skull plate of an animal was fractured immediately anterior to the animal’s antler pedestals while being captured. This animal was immediately euthanized via gunshot to the head. No other capture related injuries or mortalities occurred. With the exception of animals falling in the 2 youngest age classes (1½ years old (yearlings) and 2½ years old), the age distribution of captured animals followed the expected age distribution of the 100 �population (Fig. 2). In the case of the 2 youngest age classes, we captured more 2½ year old animals than yearlings. We believe this result was primarily due to misidentification of yearlings as part of the capture process. Small yearlings and particularly those with small antler morphometry had a greater probability of being skipped by the capture crew as they flew over groups of deer. In future years we will make a more concerted effort to increase the number of yearlings in the sample. The mass of adult male deer ranged between 52.3 kg and 106.8 kg, with the average mass being 82.2 kg (Fig. 3). Observationally, the largest animals appeared to be captured in areas in close proximity to irrigated agricultural fields. Survival of adult male deer between the time of capture and the end of July was high. Combined survival for the northern and southern halves of D-9 was 0.879 (SE = 0.0326). When separated, the survival rates for the northern and southern halves of D-9, for the same time period, were 0.858 (SE = 0.0495) and 0.900 (SE = 0.0495). Of the 12 mortalities that occurred, a suite of causes were observed. Six mortalities were attributed to predation (4 coyote, 2 mountain lion), 1 was attributed to starvation, 1 to disease (conjunctivitis that blinded the animal), and 2 were attributed to vehicular collisions (1 automobile and 1 train). The cause of mortality could not be determined for 2 deer. Survival patterns during the winter months during the first year did not demonstrate dramatic swings or mortality pulses during which several animals died. Rather, mortalities tended to occur at a relatively constant interval of approximately 2-3 mortalities per month. However, with the exception of the animal killed by a train, mortalities during the summer months (June and July) were not observed. SUMMARY Project efforts were successful during the first year of the study. Capture and handling of animals was efficient, cost effective and mortality/injury rates were low. The survival rate of adult male mule deer was high. Baseline data collection will continue for 2 additional winters before implementation of the harvest management experiment. LITERATURE CITED 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., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender, L.C., J.C. Lewis and D.P. Anderson. 2004a. Population ecology of Columbian black-tailed deer in Urban Vancouver, Washington. Northwestern Naturalist 85:53-59. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004b. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management. In Review. Bishop, C.J., J.W. Unsworth and E.O. Garton. 2005a. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. Bishop, C.J., G.C. White, D.J. Freddy and B.E. Watkins. 2005b. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins, and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1-28. Bleich, V.C., B.M. Pierce, J.L. Jones and R.T. Bowyer. 2006. Variance in survival of young mule deer in the Sierra Nevada, California. California Fish and Game. 92:24-38. 101 �Hamlin, K.L., D.F. Pac, C.A. Sime, R.M. DeSimone, and G.L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management. 64:441449. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. Robinette, W.L., J.S. Gashwiler, D.A. Jones, and H.S. Crane. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153. Severinghaus, C.W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195-216. Underwood, A.J. 1994. On beyond BACI-sampling designs that might reliably detect environmental disturbances. Ecological Applications. 4:3-15. 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. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by Eric J. Bergman, Wildlife Researcher 102 �Figure 1. Data Analysis Unit 9 (D-9) encompasses the Middle Park area of central Colorado. D-9 includes 6 Game Management Units (27, 181 and 18 on the northern half and 37, 371 and 28 on the southern). Current management sex ratio management objectives for D-9 are consistent across GMUs with an overall post hunt objective of 35 adult males per 100 adult females. 103 �30 ... 25 ...,,, 20 u ... "C (I) ::i CL (I) (I) -... Cl 15 0 (I) .0 10 E ::i z 5 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5+ Estimated Age of DeerCaptured Figure 2. Frequency of ages of 100 adult male mule deer captured in January (2011) in Middle Park, Colorado. Future capture efforts will be made to increase the frequency of 1½ year old males to accommodate for an expected underrepresentation in the current sample as well as for aging of radio collared animals throughout the study. 16 14 "O 12 ...:::, 10 ..... (1) C. n, u ... (1) (1) 0 8 6 :i:t 4 2 0 so so- s'l> 'o,.. 'o'o 10 10- 1'l> ~,.. ~'o '!Jo '!Jc- C!J'b "01- \.o'o \.\.o Mass(kg) Figure 3. Frequency of masses of 100 adult male mule deer captured in January (2011) in Middle Park, Colorado. Ages of deer captured ranged between 1½ years old and in excess of 9½ years old. 104 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 – FY 2015-16 State of: Cost Center: Work Package: Task No. Federal Aid Project No. Colorado 3430 3001 : : : : : Division of Wildlife Mammals Research Deer Conservation Assessment of Survival and Optimal Harvest Strategies of Adult Male Mule Deer in Middle Park, Colorado. W-185-R Assessment of Survival and Optimal Harvest Strategies of Adult Male Mule Deer in Middle Park, Colorado Principal Investigators Eric J. Bergman, Mammals Researcher, Colorado Parks and Wildlife Chad J. Bishop, Mammals Researcher Leader, Colorado Parks and Wildlife Kirk Oldham, Terrestrial Biologist, Colorado Parks and Wildlife Lyle Sidener, Area Wildlife Manager, Colorado Parks and Wildlife Cooperators Andy Holland, Big Game Coordinator, Colorado Parks and Wildlife John Broderick, Terrestrial Management Leader, Colorado Parks and Wildlife Area 9 Personnel, Colorado Parks and Wildlife STUDY PLAN APPROVAL Prepared by: Eric J. Bergman Date: Nov. 2010 Submitted by: Eric J. Bergman Date: Nov. 2010 Reviewed by: Chuck Anderson Date: Nov. 2010 Mike Phillips Date: Biometrician: Paul Lukacs Date: Nov. 2010 Approved by: Chad Bishop Mammals Research Leader Date: Nov. 2010 105 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO A Study Plan Proposal Submitted by: Eric J. Bergman, Mammals Researcher, Colorado Parks and Wildlife Chad J. Bishop, Mammals Research Leader, Colorado Parks and Wildlife Kirk Oldham, Terrestrial Biologist, Colorado Parks and Wildlife Lyle Sidener, Area Wildlife Manager, Colorado Parks and Wildlife Andy Holland, Big Game Coordinator, Colorado Parks and Wildlife John Broderick, Terrestrial Management Leader, Colorado Parks and Wildlife A. Need Historically, management of big game species has focused on the performance of the female and the young of the year components of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important, primarily due to the fact that it takes relatively few males to provide adequate breeding potential for the population. Additionally, historic harvest management objectives were set to maximize hunting opportunities. Thus, as long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has started to shift away from the objective of providing maximal opportunity towards providing fewer but higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, and the potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to greatly reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999, a few marked changes in Colorado’s deer herd have occurred. First, due to reduced harvest an overall increase in deer numbers has been observed (Fig. 1). Second, because the reduction in harvest was primarily focused on adult males, a subsequent increase in the ratio of adult males to adult females has resulted (Fig. 2) (Bergman et al. 2010). Stemming from this shift in harvest management and the subsequent changes in herd size and structure, a gap in biological information has been identified. Specifically, Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must further reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. 106 �700000 C: 0 'Z 650000 ..!!! ::::s a. ~ ... 600000 QJ QJ .... 550000 C 0 QJ N 500000 vi "'C ....ro 450000 'Z V'I 400000 QJ E w ..,,_q<o1 ..,,_q<oq ..,,_qq\. ..,,_qq, ..,,_qq? ..,,_qq1 ..,,_q'?>q ,,.oo\. ,_oo, ,,.o o? Year Figure 1. Colorado’s statewide deer herd estimate covering the past 2+ decades. Between 1998 and 1999 CPW implemented a statewide limitation process on the number of deer licenses sold. Since that time, a marked reversal in population trajectory has occurred, largely due to the increase in survival of adult males from reduced hunting license allocation. 80 • .,., 70 • • .!!! ro E 60 • QJ LL ±! ::::s 50 0 0 .... 40 ~ 30 "'i'ii • • "'C <( I • • •• I • • • • ••• •• • • • I •• • • I • • I •• • • • •• •• • • • •• • • • • I I I • .... 20 "'C <( 10 • • 0 1980 I •• I • •• ••• • • •• ~ :i • I I •• •I •• •• • I • I 1984 1988 • • 1992 1996 2000 2004 Year Figure 2. Estimates of adult male: adult female ratios, collected via aerial survey, in the DAUs in western Colorado during the past three decades. Of note, between 1998 and 1999, CPW implemented a statewide limitation on the number of deer hunting licenses sold. The harvest management action brought about a marked increase in estimates of the ratio of adult males to adult females. 107 �Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Very rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004b, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). However, rates of adult male survival reported in the literature are often linked to unique management situations such as variation in harvest structure (Pac and White 2007, Bender et al. 2004b), urban settings (Miller et al. 2008, Bender et al. 2004a) or disease management scenarios (Conner and Miller 2004, Miller et al. 2008). Similarly, most of these studies have been constrained by relatively small sample sizes and were of short duration, making the estimation of the process variation of adult male survival unreliable. However, available data suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management objectives and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. A different, but not unrelated need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of the change in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW still maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as DAUs reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer will remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, this is biologically not realistic. It is very likely that herds with large post-hunt populations of adult males experience higher levels of 108 �mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. B. Objectives Our study objective is two-fold. First, we wish to assess annual survival of adult male mule deer. We wish to establish baseline survival and variance estimates for different age classes of deer. Second, we wish to manipulate hunting license allocation within the Game Management Units (GMUs) of D-9 such that adult male: adult female ratios become measurably different between the northern and southern halves of the DAU. Accordingly, we wish to measure and correlate changes in natural survival of adult male deer with this management action. Similarly, as part of this second objective, we will determine if changes in the age structure of harvested animals occur as the sex ratio and age structure of the hunted population changes. While not a direct objective of the study, we will also be able to learn if increasing adult male: adult female ratios causes an increase in the emigration rate of animals from populations composed of a greater proportion of adult male deer. C. Expected Results or Benefits Data and information generated from this study will have immediate use to terrestrial biologists and wildlife managers across the state of Colorado. Survival estimates of adult male deer will be immediately incorporated in the annual population modeling process. As measurements are repeated over years, estimates of process variation will be generated, allowing a refinement of how adult male survival is incorporated into the modeling process. From a general ecology perspective, we will measure the direct and indirect effects of a concerted management action on the male component of the deer population. We expect to detect differences in the harvest rates of radio-collared deer under different hunter/license allocation strategies. We also expect to detect differences in the harvest rate of radio collared deer based on age and antler morphometry. Similarly, we expect to detect a difference in natural survival/mortality rates of deer under differing levels of harvest. Ultimately this will provide information about the additive/compensatory relationship of adult male deer, adult female deer and mule deer fawn survival in Colorado. This information will allow us to directly inform tradeoff decisions between hunting opportunity and hunter desires for various quality standards. Additionally, these data will allow us to identify thresholds where further license restrictions would fail to result in more adult males in the population and fail to increase the mean age or antler structure of males harvested. D. Approach 1. Radio Collar Development Radio collars deployed as part of this project will be permanent (i.e., they will not be fitted with any sort of release mechanism). However, utilizing traditional radio collars with a fixed diameter is not ideal due to the seasonal variation in the size of adult male mule deer necks; as adult male deer enter the breeding period, neck swelling occurs. Researchers have historically addressed this issue with several different approaches. The use of loosely-fitted, fixed diameter radio collars has occurred on several hundred white-tailed deer in Texas with no known incidence of mortality or injury (K. VerCauteren – personal communication). It is unknown if a similar result could be expected for mule deer in Colorado. Researchers in Montana used an expandable radio collar that was made of tubular aircraft grade bungee material to measure survival of 136 adult male mule deer (Pac and White 2007, D. Pac – personal communication). When this research was conducted, expandable radio collars were not commercially 109 �available, so the expansion design was developed and installed on a traditional VHF collar that was produced by Telonics, Inc (Mesa, AZ, USA). This radio collar design alleviated concerns over neck constriction during the breeding period and it sufficiently contracted as neck swelling reduced after the breeding period. However, in a few instances (1%-2% of radio collared population) it was documented that deer were able to get a front hoof/leg between the collar and neck (D. Pac – personal communication). On these occasions, deer were either recaptured or euthanized if recapture was not possible. Researchers in Idaho as well as Colorado used a different expandable collar design, fitted with an expansion device that was made of flat elastic encased in Cordura™ to measure survival of 70 (Idaho) and ~100 (Colorado) adult male mule deer, respectively (Bishop et al. 2005a, Conner and Miller 2004). This collar was also made by Telonics, Inc. This design also alleviated constriction around the neck as deer entered the breeding period, but the contraction properties of the elastic were such that as neck diameter reduced as deer exited the breeding period the collar did not adequately contract to the prebreeding period diameter. This was not ideal as loosely fitting collars had a propensity to slide on the necks of animals and to cause hair loss. Additionally, researchers had concerns over the potential for deer to get hooves caught between the collars and their necks. This event occurred on one occasion with a fawn during the Idaho study (subsequently resulting in the animal’s mortality) and on two occasions in Colorado (both animals were recaptured and collars were removed during the Colorado study). To address the issue of expansion collars failing to contract back to pre-breeding period diameters, a third generation expansion collar was developed by CPW (M. Sirochman – personal communication). This new design incorporated nylon sleeved springs as the expansion device. As was the case in Montana, the spring based expansion collar adequately expanded and contracted through the initial breeding periods. However, on a few occasions the springs in these collars did eventually expand beyond their critical limit and ultimately failed to contract after having been deployed. On these occasions, it appeared that springs had snagged on external features, thereby reducing the integrity of the spring itself. Outside of these external factors, resilience of the spring appeared to be sound. The occurrence of deer getting their hooves caught between the collars and their necks was also documented in this study, but due to the tractability of animals, all were recaptured and radio collars were safely removed (M. Sirochman – personal communication). One additional downfall of the spring based expansion collar was that irritation caused by the pressure of the springs on the dorsal portion of the neck was documented in a few cases. While the irritation did not appear to jeopardize the health of the animal, it was undesirable. For our study, what can be considered a fourth generation expandable radio collar has been designed in collaboration with Advanced Telemetry Systems, Inc. (Isanti, MN, USA) (Figs. 3a and 3b). This newly designed collar closely resembles the earlier generation collars that incorporated flat elastic material. The elastic based expansion collar had fairly high success because only on a single occasion was it documented that a deer had its hoof caught between the collar and its neck. The primary weakness of this design was that the contraction properties of the elastic expansion material were inadequate. This new design incorporates a more robust, high quality, flat bungee material that is sheathed between traditional nylon belting material on the outside and nylon webbing on the inside (Fig. 3b). Due to the sheathing design, only a small portion of the bungee material is exposed, reflecting the desired qualities of the elastic based expansion collar and retaining the reduced potential for deer to get hooves caught in the collar. The higher quality bungee is expected to maintain contraction properties far longer than elastic and thus the potential for loose fitting collars during the later years of the study is reduced, minimizing the opportunity for hair breakage. This new collar design was scrutinized by the researchers who represent the bulk of knowledge on the subject of radio collaring adult male mule deer (D. Pac - retired, MT Fish, Wildlife and Parks; C. Bishop, M. Miller, M. Sirochman and L. Wolfe, CPW). The only additional concern pertained to the orientation and potential wear/irritation of the collar on the dorsal portion of deer necks during the breeding period. However, due to the width of the bungee material, it is expected to be less than that of the spring based expansion design. Concern over the orientation of the collar will be addressed by testing the collar design on a captive animal at CPW wildlife health research facility. 110 �Figure 3a. Figure 3b. Figures 3a and 3b. The newly designed, expandable, VHF radio-collar that will be utilized on adult male mule deer during this study. Collars were designed to meet CPW specifications by Advanced Telemetry Systems, INC. (Isanti, MN, USA). The blue banding material seen in figures 3a and 3b is nylon coated bungee that will allow expansion and contraction, as needed, during the breeding period. To allow 111 �maximal expansion, but to help prevent the opportunity for deer to get hooves and legs caught between the neck and collar, the bungee material is sleeved in nylon webbing (red material visible in figure 3a). 2. Capture Capture of adult male deer for this project will be conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 1994, Barrett et al. 1982). All captures will occur after the completion of the 4th rifle hunting season, eliminating potential conflicts between capture efforts and hunting. Typically capture will occur between mid-December and mid-January. Exact timing of capture each year will be dependent on availability of the helicopter net-gunning crew. Due to the need to have survival estimates linked to animals of known age, all animals will be handled by CPW personnel for aging purposes. Depending on situation, captured animals will be handled in one of two ways. When feasible, captured deer will be ferried to a processing area staffed by CPW researchers/biologists who are qualified to age animals according to tooth wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). Deer will subsequently be returned to the capture site for release. In situations when capture locations are too far from processing areas to efficiently ferry animals, CPW researchers/biologists will be ferried to the general area in which capture is occurring and subsequently be ferried the short distance to each capture location to process animals at that site. Regardless of situation, it is possible that a single person will be responsible for collaring, aging and releasing animals. As such, prior to release, all animals will have their antlers removed via handsaw to minimize the potential risk of injury as the animal is released. The removal of antlers from animals at this time of year should have no negative impact on survival as all captures will occur post-rut. Similarly, all legal harvest of animals will have occurred and negative response of hunters should not occur. The only exception to the antler removal process will be if post-hunt sex/age class survey flights have not yet occurred and if the captured animal is located near a survey quadrat. If a deer is captured near a survey quadrat, prior to deer classification flights having been conducted and it is still deemed necessary to remove antlers, these deer will be temporarily marked with livestock marking paint on the back and neck. Marking deer in such a manner will allow biologists to accurately classify those individual deer as adult males, thereby removing any potential bias that may stem from capturing deer prior to classification flights. Whenever possible, capture will be conducted after classification flights to alleviate this problem. All deer will be fitted with expandable radio collars (discussed above). All radio collars will be equipped with mortality sensors which will double in pulse rate after remaining motionless for 4 hours. The desired sample size for each year of this study will be a total of 220 adult ( ≥ 1.5 years old) male deer. One hundred deer will be captured and radio collared during the first year of the study as a pilot assessment of the radio collar design and to test underlying assumptions about deer movement (discussed below). During the second year of the study, 120 additional deer, as well replacements for any deer that die during the first year will be captured and radio collared. Thus, not until the second winter of the study will the full sample size be achieved. For every year thereafter, only enough deer to maintain the 220 animal sample size will be captured. The 220 deer sample will be distributed such that 110 of the radio collared deer are located in the northern half and 110 are located in the southern half of the DAU. 3. Survival/Location Monitoring The primary objective of this study is to generate annual natural survival estimates and harvest rates for adult male deer. While most mortality is expected to occur via rifle harvest between October and November, the bulk of natural mortality is expected to occur between December and May of each year. In order to minimize bias of survival estimates during these periods, we will attempt to monitor the live/dead status of each animal 3-4 times per week. Each year, prior to the start of the archery hunting season, all deer will be located to asses in which half (northern versus southern) of the DAU each animal is located. A similar set of locations will be collected after the 4th rifle hunting season. Between each hunting season, a live/dead flight will be conducted to determine if any animals have disappeared, and subsequently assumed to have been harvested, without having been reported to CPW. Once all hunting 112 �seasons have been completed, we will revert to a weekly flight schedule to assess live/dead status of all animals. A field technician will check live/dead status 2-3 times for each animal between flights. All animals will be located 1 additional time during the winter to confirm that animals have not left the DAU and to determine if any animals have switched between the northern and southern halves of the DAU. Based on historical location data for adult female and fawn mule deer, approximately 10% of deer are expected to cross between northern and southern halves of the DAU (K. Oldham – unpublished data). Any animals switching between halves of the DAU will be censored from the optimal harvest management portion of the analysis. During periods when survival is expected to be higher and less dynamic (June through September), the level of effort of to determine live/dead status will be reduced. Flights to determine live/dead status will occur approximately every 14 days and efforts to hear animals from the ground will occur as time allows. A single location will be collected for each animal after it has arrived on summer range (between late-June and late-July). While not ideal, weekly survival estimates for summer months can be computed from bi-monthly estimates via the delta method (Powell 2007). This approach to survival monitoring will allow us to minimize bias but also minimize costs associated with aircraft and temporary personnel. 4. Harvest Management Experiment We will implement a management experiment to evaluate adult male survival rates under different harvest management strategies. Hunting management in Colorado is partitioned into DAUs. The boundaries of DAUs are intended to reflect the biological boundaries of deer such that deer movement between DAUs is non-existent or infrequent enough to be biologically insignificant. Within DAUs are GMUs. GMU boundaries tend to be highly permeable to deer, but serve to partition DAUs for human oriented management purposes such as survey work and hunter distribution. Typically all GMUs within a DAU have the same management objective. However, this study will deviate from this trend by establishing two different harvest objectives within a single DAU. This approach will help ensure that all deer in the study will experience similar environmental conditions and limiting factors except for different harvest objectives. Thus, any survival differences we observe are likely to be a result of differential harvest as opposed to some other factor. This study will take place in Middle Park, Colorado (see below for rationale). Under the current management structure, Middle Park falls within DAU D-9. Within D-9 are 6 GMUs (27,181, 18, 37, 371, and 28; Fig. 4). D-9 is managed for an adult male: adult female ratio of 35 adult males per 100 adult females. As part of this study, the management of D-9 will be temporarily altered such that it will be viewed as two separate populations (one population will be composed of the northern 3 GMUs (27, 181 and 18) and the other population will be the southern 3 GMUs (37, 371 and 28)). During the 4th-7th years of this study we will redistribute hunters within the DAU via hunting license allocation. During the 1st-3rd years of the study we will monitor survival across the DAU to provide baseline data (Fig. 5). The objective behind the redistribution of hunters will be to increase adult male: adult female ratios in one half of D-9 and to decrease adult male: adult female ratios in the other half of D-9. The current DAU objective of 35 adult males: 100 adult females will not change, but one half of the DAU will be managed for 25 adult males: 100 adult females and the other half will be managed for 45 adult males: 100 adult females. The determination of which half of D-9 will experience higher harvest and which half will experience lower harvest has not yet been made. This decision will ultimately be made by Area 9 and Northwest Region personnel. In the event that there are no overwhelming management concerns about this selection process, the selection will be random. 5. Age at Harvest To help evaluate the effects of a changing sex ratio on hunter harvest, we will attempt to acquire an age for animals harvested in D-9 for years 2-7 of the study. Ages will be estimated via the cementum 113 �aging process of incisors (Hamlin et al. 2000). To acquire teeth for aging purposes, all hunters who have licenses to hunt in any GMU in D-9 will be contacted prior to the archery season via mail. Each hunter will be provided with a sampling kit, a pre-posted return envelope and detailed directions on how to extract teeth for aging purposes. These data will help inform terrestrial biologists and wildlife managers if changes in the age of animals harvested occur as populations shift up or down in age structure as sex ratios are increased or decreased. Figure 4. Data Analysis Unit 9 (D-9) encompasses the Middle Park area of central Colorado. D-9 includes 6 Game Management Units (27, 181 and 18 on the northern half and 37, 371 and 28 on the southern). Current management sex ratio management objectives for D-9 are consistent across GMUs with an overall post hunt objective of 35 adult males per 100 adult females. 6. Data Analysis This study can be structured as a multi-state study (Fig. 6). We are primarily interested in deer that exist in three different states: 1) deer that survive, 2) deer that are harvested, and 3) deer that die due to non-harvest causes. While most multi-state studies include survival, detection and transition probabilities for different states, this study is purely focused on the transition probability of deer that transition from the living state to either one of the two non-living states, or back into the living state. Due to the relatively safe assumptions that deer will not leave study area, that use of radio-telemetry is essentially always detectable and the fates of deer can be readily identified, detection probabilities can be fixed at 1.0 and survival can be artificially set at 1.0. Thus, the transition probabilities between states 114 �becomes a surrogate for survival, thereby allowing us to distinguish and easily measure differences between causes of mortality. Figure 5. For this study, the northern and southern halves of D-9 will managed under different harvest management objectives during years 3-7. One half will be managed under less restrictive objectives, with a post hunt sex ratio objective of 25 adult males per 100 adult females. The other half of the DAU will be managed under more restrictive conditions with a post hunt sex ratio objective of 45 adult males per 100 adult females. For this study, we will have numerous response variables of interest. The basic analysis of this study will follow a before-after-control-impact (BACI) design (Green 1979, Hurlbert 1984, Underwood 1994 and Conner et al. 2007) (Fig. 7). Overall, survival of adult male deer will be analyzed using known-fate models in program MARK (White and Burnham 1999). Survival will be modeled using age of deer, GMU/DAU, year and trophy score. For the purposes of this study, we are primarily interested in weekly survival rates throughout the year. Cause specific mortality will be analyzed under a multi-state modeling framework in which detection probabilities will be fixed to 1.0 based on the known-fate properties of the data for the BACI analysis. We will use mixed models to assess the impact of manipulating harvest management. For the mixed model analyses, we will use adult male: adult female ratio as the response variable for one analysis and hunter success as the response variable in a second analysis. 115 �Survive 4'AB=Natural Mortality Rate 4' AB=Harvest Rate Non-Harvest Mortality Harvest Figure 6. Assessment of survival and mortality causes can be conceptualized as a multi-state analysis with transition rates from the surviving state to the harvest state or the non-harvest related mortality state being the parameters of interest. In this case, transitions represented by black arrows can be estimated via radio collared deer. Transitions represented by gray arrows are not biologically feasible. Deer that are harvested cannot return to the survival state, nor can they enter the non-harvest related mortality. Similarly, deer dying to non-harvest related causes cannot simultaneously survive or be harvested. Under this multi-state framework, all other parameters of interest will be fixed at 1.0. 7. Sample Size Sample size estimates for this study are based on the desire to detect a difference in the nonharvest mortality rates of deer under different harvest management regimes. Best estimates of harvest mortality rates, natural survival rates and the associated variance of each were based on the work published by Pac and White (2007). For our power calculations, baseline/ control harvest rates were set at 0.21 and the associated natural survival was 0.72. For high harvest areas, we set harvest at 0.37 and the associated natural survival at 0.77. For low harvest areas, we set harvest at 0.06 and subsequent natural survival at 0.67. Thus, our power calculation was set up to detect a 10% difference in natural survival under different harvest management regimes. For sample size estimation we chose to fix the number of radio collared deer entering the study each winter at ~200 (~100 animals per area) and then used simulation models to determine the number of releases (i.e., number of winters in the study) that would be needed to detect our desired effect size. Simulations were set up to test the differences in natural survival by comparing survival rates as beta offsets from the expected survival rates under normal conditions (Fig. 8). 116 �Half Sample Full Sampl e Full Sampl e Full Sampl e Full Sampl e Full Sample Full Sample Half Sampl e Full Sampl e Full Sampl e Full Sampl e Full Sampl e Full Sample Full Sample if1:., ., " -~ct 0, .:i: ti "~ ~ I <( ~ 0 ...J Control Period (Years 1-3) Impact Period (Years 4-7) Figure 7. The Before-After-Control-Impact design for this study is based on 6 years of a full sample of deer, with an initial build up year to help offset logistic and financial constraints associated with capturing 220 deer for the full sample (110/area). The control period will experience no change to harvest management, whereas the impact period with experience a concerted effort to redistribute hunters across the DAU to impact post hunt sex ratios. Based on these initial conditions, it appears that 6 winters with a full sample of deer will be needed to reliable detect a 10% difference in natural survival rates. Due to the estimated censoring of 10% of the radio-collared deer, due to movement between the northern and southern halves of the study area, we will inflate the total sample size from 100 animals per area to 110 animals for years 2-7 of the study. Duration of the study was determined by comparison of 95% confidence intervals surrounding the expected difference in natural survival (Fig. 9). Confidence intervals that included 0 were indicative of not enough statistical power to detect a difference. While 5 years may adequately meet the needs of the study, our results indicate that 6 years with a full sample of deer will be substantially more robust. E. Location This work will be conducted in Middle Park, Colorado. Middle Park was selected for this work based on several criteria. First, Middle Park is one of CPW’s mule deer winter survival monitoring areas and has ongoing monitoring of the survival of adult females and fawns. Adding estimates of adult male survival in this area will allow us to compute correlation and covariance between the different sexes through time. Similarly, in the event that changing adult male: adult female ratios affects survival of adult females or fawns, we will have all relevant sex and age classes marked and should be able to detect any changes. Additionally, geological and topographical structure of Middle Park is conducive to splitting the DAU into halves such that few deer migrate from one half to the other during the annual movement cycle. Existing data indicate that 10%-15% of deer cross between halves. As such, the number of deer needing to be censored from the management experiment portion of this study should be minimized. 117 �~ > C: --------------------------------------------------------------- Bo+B2 :::, (.I) ~ t - - - - - - - - - - - - - - - - - - - - - - - - Bo I,,. :::, ~ z Time Figure 8. Non-harvest survival will be analyzed using the log scale comparison of beta estimates. The control period will be the baseline survival estimate (ß0) to which natural survival under differing harvest management efforts will be compared (solid black line). Non-harvest related survival in restrictive harvest units (ß1) is expected to be lower than estimates for both the control phase and more liberal harvest units (long dashed line). Non-harvest related survival in liberal harvest units (ß2) is expected to be higher than estimates for both the control phase and more conservative harvest units (short dashed line). 0 "iii > -~ -0.2 :::, V'I ...:::, "iii - -0.4 ·=u -0.6 ra z Cl) ---------- - -------- · C: ... Cl) Cl) := -0.8 0 -1 5 4 6 Nmnher of Years Figure 9. Power calculation set up to determine the number of years necessary to detect a 10% difference in non-harvest related moratality rates under differing harvest management regimes. Solid lines depict 95% confidence intervals. Adequate power is achieved once 95% confidence interval estimates do not include 0. While statistical power may be adequate after 5 years, addition of a 6th year will make the study more robust to violations or deviations from the underlying parameter estimates used to structure the analysis. 118 �From a management perspective, D-9 is currently managed for 35 adult males per 100 adult females. The management experiment portion of this study will allow the DAU to be split with half of the DAU being managed for 25 adult males per 100 females and the other half being managed for 45 adult males per 100 females. These ratios are largely representative of objectives throughout the state (i.e., management is not purely trophy or opportunity driven) and should allow adequate inference to be drawn. By not altering the overall DAU population objectives, implementing this research will not require that the D-9 management plan be rewritten. Additionally, Middle Park has historically been prone to periodic, harsh winters which are fundamental to getting reasonable estimates of process variation. Lastly, Middle Park has also been the site of numerous deer research and concerted management efforts over the past several decades. Knowledge and information from these past efforts have greatly facilitated the design of this study and historical data are readily available should refinement of study design or objectives become necessary. F. Schedule Of Work Activity Date Design and Purchase Expandable Radio Collars June 2010−Nov 2010 Purchase Field Supplies June 2010−Nov 2010 Capture ½ of initial sample of deer Dec 2010-Jan 2011 Monitor Survival and Movement of Deer Dec 2010−June 2017 Capture remaining sample of deer Dec 2011−Jan 2012 Capture deer to bring sample back to full size Dec 2012−Jan 2013 Implement change in hunter distribution within DAU Feb 2013-Feb 2016 Capture deer to bring sample back to full size Dec 2013−Jan 2014 Capture deer to bring sample back to full size Dec 2014−Jan 2015 Capture deer to bring sample back to full size Dec 2015−Jan 2016 G. Estimated Costs Category Item or Position FY 10-11 Personnel Eric Bergman 0.25 PFTE Chad Bishop 0.25 PFTE Kirk Oldham 0.05 PFTE Lyle Sidener 0.00 PFTE Field Equipment and Capture $100,000 Operating 119 �H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS) and state lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited 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., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender, L.C., J.C. Lewis and D.P. Anderson. 2004a. Population ecology of Columbian black-tailed deer in Urban Vancouver, Washington. Northwestern Naturalist 85:53-59. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004b. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. 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A meta-BACI approach for evaluating management intervention on chronic wasting disease in mule deer. Ecological Applications 17:140-153. Green, R.H. 1979. Sampling design and statistical methods for environmental biologists. Wiley Interscience, Chichester, England. Hamlin, K.L., D.F. Pac, C.A. Sime, R.M. DeSimone, and G.L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management. 64:441449. Hurlbert, S.H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187-211. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. Powell, L.A. 2007. Approximating variance of demographic parameters using the delta method: a reference for avian biologists. Condor 109:949-954. 120 �Robinette, W.L., J.S. Gashwiler, D.A. Jones, and H.S. Crane. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153. Severinghaus, C.W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195-216. Underwood, A.J. 1994. On beyond BACI-sampling designs that might reliably detect environmental disturbances. Ecological Applications. 4:3-15. 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. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and K.P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46:120-139. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. 121 �Colorado Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3001 : : : : Parks and Wildlife Mammals Research Deer Conservation Assessment of survival and optimal harvest Strategies of adult male mule deer in Middle Park, Colorado W-185-R Period Covered: July 1, 2011 - June 30, 2012 Author: E.J. Bergman; Project Cooperators; C.J. Bishop, K. Oldham, and L. Sidener Personnel: G. Abram, G. Birch, J. Broderick, M. Crosby, B. Davies, T. Elm, D. Gillham, K. Holinka, A. Holland P. Lukacs, B. Manly, S. Murdoch, S. Schwab, S. Shepherd Colorado Parks and Wildlife R. Swisher, S. Swisher, T. McKendrick Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued field work on a study designed to assess the survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Two years of baseline survival data for adult (≥ 1 yr. old) male deer were collected prior to termination of this project. During December (2011), 49 additional adult (≥ 1.5 years old) male deer were captured and radio collared, returning the radio collared sample to 100 animals at the start of the 2012 calendar year. The natural, annual survival rate for all deer for the period ending on the 14th of December (2011) was estimated at 0.820 (SE = 0.0394). From the 15th of December (2011) through the 31st of July (2012), survival was estimated at 0.919 (SE = 0.0275). Due to consternation expressed by a very select group of trophy hunters, the project was terminated in July of 2012. 94 �WILDLIFE RESEARCH REPORT ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO ERIC J. BERGMAN P.N. OBJECTIVES SEGMENT OBJECTIVES 1. Continue field work in the form of capturing and radio collaring animals. 2. Collect survival data on radio collared deer and provide preliminary survival estimates for adult male mule deer. INTRODUCTION Historically, management of big game species has focused on the performance of adult females and the young of the year segments of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important because it takes few males to provide adequate breeding coverage for the population, and historic harvest management objectives were set to maximize hunting opportunities. As long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has shifted from the objective of providing maximal opportunity towards providing higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, increased potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to reduce total hunter numbers and to control the distribution of hunters throughout the state. Since 1999 Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must reflect a balance between meeting DAU population performance objectives, and maximizing hunter opportunity. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest estimates, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Only rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and adult male survival rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of 95 �population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). These studies also suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management scenarios and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. An additional need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of changes in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as Data Analysis Units (DAUs) reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, these assumptions are not biologically realistic. It is possible that herds with large post-hunt populations of adult males experience higher levels of non-harvest mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. STUDY AREA This study took place in Middle Park, Colorado, within DAU D-9. Within D-9 are 6 Game Management Units (27,181, 18, 37, 371, and 28; Fig. 1). METHODS Capture of adult male deer was conducted in January and December of 2011. Capture was conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 96 �1994, Barrett et al. 1982). All captures occurred after the completion of the 4th rifle hunting season, eliminating conflicts between capture efforts and hunting. All deer were fitted with expandable radio collars. All radio collars were equipped with mortality sensors that doubled in pulse rate after remaining motionless for 4 hours. Between the time of capture and mid-June, we used ground-based monitoring to determine the live/dead status of deer 3-4 times per week. Additionally, every 5-10 days we conducted a telemetry flight to detect any animals that hadn’t been heard from the ground during the preceding week. A general location was collected for each radio marked deer in early-March to determine if it had departed the GMU in which it had originally been captured. From mid-June through remainder of the summer, deer were monitored from the ground weekly and from the air once per month. When detected, all mortalities were investigated as quickly as possible to determine cause of death and to get an accurate estimate of the date of death. RESULTS AND DISCUSSION In December (2011), 49 deer were captured and radio collared. On one occasion, an animal suffered a fractured leg as part of the capture process and was subsequently euthanized at the capture site via gunshot to the head. No other capture related injuries or mortalities occurred, although one animal was killed via vehicular collision 2 days post capture. This animal was subsequently censored from survival analysis due to uncertainty if stress related to the capture process had influenced its fate. Survival of adult male deer between January 2011 and the 14th of December (2011) was estimated to be 0.820 (SE = 0.0394). There was no apparent difference between the north half the D-9 and the south half of D-9 (Table 1), validating the assumptions of the original study plan design. During the 2011 hunting seasons, a total of 31 radio collared bucks were harvested (Fig. 1). Due to mild winter conditions, survival from the 15th of December (2011) through the 31st of July (2012) was very high (0.909, SE = 0.0275). SUMMARY Project efforts were successful during the first two years of the study, although local resistance to the project remained high. Based on public meetings, the majority of hunters in the Middle Park area supported the project, although a very select group of trophy hunters remained opposed. Ultimately, CPW leadership determined that it “could not overcome the current opposition” and the study should not proceed. Thus, this research project has been terminated as of 7/12/2012. LITERATURE CITED 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., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management. In Review. Bishop, C.J., J.W. Unsworth and E.O. Garton. 2005a. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. Bishop, C.J., G.C. White, D.J. Freddy and B.E. Watkins. 2005b. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. 97 �Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins, and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1-28. Bleich, V.C., B.M. Pierce, J.L. Jones and R.T. Bowyer. 2006. Variance in survival of young mule deer in the Sierra Nevada, California. California Fish and Game. 92:24-38. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. 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. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by Eric J. Bergman, Wildlife Researcher 98 �Table 1. Model results for known-fate survival models based on mule deer buck data collected in Middle Park, Colorado. Model comparison is made via Akaike’s Information Criterion corrected for small sample size (AICc). Of interest to the original study design, there was no strong evidence that there was a difference in survival between the northern and southern halves (Area) of the study area. Model ∆AICc AICc Weight Likelihood Parameters Ŝ (Constant) 0.00 0.69 1.00 1 Ŝ (Area) 1.56 0.31 0.46 2 Ŝ (Week) 49.77 0.00 0.00 48 Ŝ (Area + Week) 51.37 0.00 0.00 49 Ŝ (Area*Week) 131.16 0.00 0.00 96 Figure 1. Fate and associated cause of death of 100 mule deer bucks between January 2011 and December 2011 in Middle Park, Colorado. □ Poachin g (n =2) ■ Wounding Loss (11 =1) Coyote (n =2) Survived (n = 53) □ Mt.Lion (n =l) D Unk. Predation (n =3) D Di sease/S tarvat ion (n =2) D Road/Tra in Kill (n =2) D Unknow n (n =3) 99 � https://cpw.cvlcollections.org/files/original/d771b319e26a9695ad1e3481df65876c.pdf c8f4617fa5e0ed7a51399e9f7d22fceb PDF Text Text Colorado Division of Parks and Wildlife July 1, 2010 − June 30, 2011 PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R JULY 2006 – JUNE 2011 State of Colorado Cost Center 3430 Work Package 3001 Federal Aid Project W-185-R : Division of Parks and Wildlife : Mammals Research : Deer Conservation Research : Period Covered: July 1, 2006 – June 30, 2011 Authors: Chad J. Bishop, Charles R. Anderson, Jr., and Eric J. Bergman Principal Investigators: M. W. Alldredge, C. R. Anderson, E. J. Bergman, C. J. Bishop, D. J. Freddy, P. M. Lukacs, D. P. Walsh, and B. E. Watkins. Colorado Division of Wildlife; P. F. Doherty and G. C. White, Colorado State University ABSTRACT This report highlights the accomplishments of mule deer research and associated activities conducted by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) with the funding support of Federal Aid Grant W-185-R during the 5-year grant segment, July 2006-June 2011. Two major multi-year research projects addressing mule deer population limiting factors and habitat enhancements were completed and reported upon during this segment. Two other major multi-year research projects were designed and implemented during this period. One project is comprehensively addressing approaches to mitigate the impacts of natural gas development on mule deer. The other project is evaluating survival rates and harvest management of adult male mule deer. Several other smaller research projects were designed and implemented, addressing mule deer-elk-cougar interactions and development of techniques for marking and monitoring mule deer. Additionally, funding provided scientific and technical expertise for mule deer population monitoring and analysis. Research experiments provided strong evidence that habitat nutritional quality had a greater impact on net productivity of mule deer than did existing levels of coyote, cougar, and black bear predation and that mechanical habitat treatments in senescent pinyon-juniper winter ranges were an effective strategy for increasing deer survival by increasing the amount of higher-quality forage. These research results provided wildlife managers support and direction for managing pinyon-juniper habitat across western Colorado. These research results also framed the experimental design for evaluating approaches to mitigate impacts of natural gas development on deer. Specifically, a large field experiment was initiated in northwest Colorado to evaluate effectiveness of habitat treatments in late-seral pinyon juniper and mountain shrub habitats that are experiencing high-intensity and low-intensity energy development. From activities supported by this Grant during this segment, principal investigators published 13 peer-reviewed scientific articles for prominent wildlife research journals, provided 21 annual CPW Wildlife Research Reports summarizing yearly progress of projects, provided 34 presentations at professional meetings or workshops, and initiated 2 graduate student projects. The cumulative impact of 37 �this programmatic effort provides Colorado the basis to progress and proactively sustain the mule deer resource in an increasingly complex landscape. The relative success of mule deer management in Colorado reflects the positive synergy between the terrestrial research and management sections in sharing expertise, financial resources, staffing, and common goals. 38 �PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R JULY 2006 – JUNE 2011 CHAD J. BISHOP, CHARLES R. ANDERSON, JR., AND ERIC J. BERGMAN PROGRAM NEED During the late 1990s, CPW was challenged by sportsmen and other stakeholders to investigate potential causes of declining numbers of mule deer in Colorado. The concerns of stakeholders gained the attention of the Colorado Legislature which directed CPW to prepare a document to address causes of the mule deer decline and outline a plan of action to reverse the perceived trend in mule deer populations. That document was prepared for the legislature in 1999 (Gill et al. 2001) and established the direction and objectives for mule deer management and research beginning in 1999. At the same time, the Colorado Wildlife Commission approved statewide limitations on hunting licenses for mule deer, which significantly reduced the number of deer harvested annually in Colorado. Several years later, a sudden and significant increase in natural gas development in the Piceance Basin of northwest Colorado prompted mule deer researchers and managers to initiate a comprehensive effort to mitigate development impacts on deer. The research projects conducted during this 5-year grant period directly or indirectly addressed these various management issues and concerns. This report highlights the accomplishments of research efforts conducted by CPW from July 1, 2006 through June 30, 2011 that were wholly or partially supported by Federal Aid Grant funds. PROGRAM NARRATIVE OBJECTIVES The primary Program Narrative research objectives were divided into two broad categories: 1) managing factors limiting mule deer populations, and 2) monitoring mule deer populations. The specific project objectives were: Managing Factors Limiting Mule Deer Populations Project 1 Objective. Evaluate the impacts of prescribed landscape habitat manipulations in senescent pinyon-juniper habitats on behavior and demographics (survival, reproduction, densities) of mule deer populations. Project 2 Objective. Evaluate approaches to mitigate the impacts of natural gas resource extraction and other related human-caused developments on mule deer habitats and population demographics. Project 3 Objective. Investigate behavioral and spatial relationships between mule deer and elk, and among mule deer, elk, and cougar as these species simultaneously utilize prescribed landscape habitat manipulations. Monitoring Mule Deer Populations Project 4 Objective. Evaluate the technical quality and applications of statewide mule deer research and management systems. Project 5 Objective. Evaluate new approaches to monitoring mule deer population demographics and habitat conditions. 39 �Project 6 Objective. Evaluate hunting systems that could maintain a balance between hunter opportunity and the quality of hunting experience. RESULTS Objective 1. Evaluate the impacts of prescribed landscape habitat manipulations in senescent pinyon-juniper habitats on behavior and demographics (survival, reproduction, densities) of mule deer populations. Project Objective 1 was formulated in response to field research conducted during the previous 5year grant cycle, which indicated that habitat quality was ultimately limiting mule deer population growth in western Colorado. Final data analyses and preparation of publications from this research was completed during 2006-2008, and therefore, are reported here as part of this project objective. We evaluated the effect of enhanced nutrition of deer during winter and spring on fecundity and survival rates of free-ranging mule deer on the Uncompahgre Plateau in southwest Colorado. The treatment represented an instantaneous increase in nutritional carrying capacity of a pinyon (Pinus edulis)−Utah juniper (Juniperus osteosperma) winter range and was intended to simulate optimum habitat quality. Prior studies on the Uncompahgre Plateau indicated predation and disease were the most common proximate causes of deer mortality. By manipulating nutrition and leaving natural predation unaltered, we determined whether habitat quality was ultimately a critical factor limiting the deer population. We measured annual survival and fecundity of adult females and survival of fawns, then estimated population rate of change as a function of enhanced nutrition. Our estimate of the population rate of change was 1.165 (SE = 0.036) for deer receiving the nutrition treatment and 1.033 (SE = 0.038) for control deer. We documented food limitation in the Uncompahgre deer population because survival of fawns and adult females increased considerably in response to enhanced nutrition. We found strong evidence that enhanced nutrition of deer reduced coyote (Canis latrans) and mountain lion (Puma concolor) predation rates of ≥6-month-old fawns and adult females. We concluded that winter-range habitat quality was a limiting factor of the Uncompahgre Plateau mule deer population. We, therefore, recommended evaluating habitat treatments for deer that were designed to set-back succession and increase productivity of late-seral pinyon-juniper habitats that presently dominate the winter range. Pinyon-juniper habitats across western Colorado have been exposed to minimal natural disturbance during recent decades. In particular, the natural role of fire in these systems has been significantly altered through aggressive efforts to extinguish fires ignited by lightning strikes. Fire suppression has become necessary because human dwellings are scattered across pinyon-juniper habitat throughout much of western Colorado. This has caused many mule deer winter ranges to become dominated by late-seral pinyon-juniper, which is unproductive for mule deer. Collaborative management efforts among state and federal agencies, NGOs, and private citizens have been initiated to incorporate disturbance into pinyon-juniper systems through the use of prescribed fire and mechanical treatments that remove or mulch pinyon and juniper trees. We evaluated the effectiveness of these types of habitat treatments on mule deer body condition, survival, and density. Peer-Reviewed Publications: Watkins, B. E., C. J. Bishop, E. J. Bergman, A. Bronson, B. Hale, B. F. Wakeling, L. H. Carpenter, and D. W. Lutz. 2007. Habitat guidelines for mule deer: Colorado Plateau shrubland and forest ecoregion. Mule Deer Working Group, Western Association of Fish and Wildlife Agencies. Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533−537. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. 40 �Bishop, C. J., B. E. Watkins, L. L. Wolfe, D. J. Freddy, and G. C. White. 2009. Evaluating mule deer body condition using serum thyroid hormone concentrations. Journal of Wildlife Management 73:462−467. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Annual Wildlife Research Reports: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2007. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 59-71. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2007. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 73-96. Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2008. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 39-51. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 53-62. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 101-110. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2010. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 81-91. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2011. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2006. Effect of enhanced nutrition of freeranging mule deer on population performance. The Wildlife Society 13th Annual Conference, September 23−27, Anchorage, Alaska, USA. Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2007. Effect of enhanced nutrition of freeranging mule deer on population performance and effectiveness of vaginal implant transmitters. Colorado State University Student Chapter of The Wildlife Society, February 26, Fort Collins, Colorado, USA. Bishop, C. J. 2007. Capture techniques and radio-telemetry used in wildlife research and management, and an example of technique application using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 26−30, Fort Collins, CO, USA. Bishop, C. J., and E. J. Bergman. 2007. Status of big game habitats and implications for wildlife within the Colorado Plateau. Plant Community Restoration Workshop, September 5−7, Grand Junction, Colorado, USA. Bishop, C. J., G. C. White, and P. M. Lukacs. 2007. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. The Wildlife Society 14th Annual Conference, September 22−26, Tucson, Arizona, USA. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Colorado Chapter of The Wildlife Society Annual Meeting, January 23−25, Denver, Colorado, USA. 41 �Bishop, C. J. 2008. Capture techniques and radio-telemetry used in wildlife research and management, and an example of technique application using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, April 1, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife Research Review, August 20-21, Denver, CO, USA. Bergman, E. J. 2009. Monitoring habitat for deer. Joint Meeting of Colorado’s Habitat Partnership Program and the Colorado Chapter of The Wildlife Society, February 5, Grand Junction, CO, USA. Bishop, C. J. 2009. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 31, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado State University Student Chapter of The Wildlife Society, April, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. 2009 Western States and Provinces Deer and Elk Workshop, May, Spokane, Washington, USA. Bishop, C. J. 2010. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 30, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2010. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Joint Meeting of Colorado’s Habitat Partnership Program and the Colorado Section of the Society of Range Management, December 1, Grand Junction, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2011. Evaluation of winter range habitat treatments on overwinter survival of mule deer. Northwest Region Biology Days, January 19, Glenwood Springs, CO, USA. Bishop, C. J. 2011. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 29, Fort Collins, CO, USA. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2011. Effect of enhanced nutrition of free-ranging mule deer on population performance. 2011 Western States and Provinces Deer and Elk Workshop, May 17, Santa Ana Pueblo, New Mexico, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2011. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. 2011 Western States and Provinces Deer and Elk Workshop, May 17, Santa Ana Pueblo, New Mexico, USA. Objective 2. Evaluate approaches to mitigate the impacts of natural gas resource extraction and other related human-caused developments on mule deer habitats and population demographics. We designed and implemented a project to experimentally evaluate habitat treatments and human-activity management alternatives (i.e., best management practices; BMPs) that may benefit mule deer exposed to extensive energy development. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. This project was initiated in 2007 and is expected to go to 2016 at a minimum and ideally to 2019. The project timeline was recently extended by 1 year due to a delay in implementing habitat mitigation treatments. The Piceance Basin in northwest Colorado supports one of the largest migratory mule deer populations in North America and also exhibits one of the highest natural gas reserves in North America. 42 �Public stakeholders and CPW are concerned that the cumulative impacts of natural gas extraction will negatively affect mule deer and other wildlife resources in the region. Concern is particularly high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas is directly affecting the potential suitability of the landscape for mule deer by converting native habitat vegetation to drill pads, roads, and noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction is indirectly affecting deer by increasing the human work-force population of the region and the subsequent need for developing additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads is raising the potential for direct mortality from vehicle-animal collisions. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. Impacts of natural gas development may be most effectively mitigated for mule deer by restoring or enhancing habitat conditions on or adjacent to disturbed sites and by modifying development practices. However, we presently lack information to appropriately guide the expenditure of mitigation dollars to offset or lessen impacts. The purpose of this project is to address these mitigation questions so that dollars are spent wisely. For example, it remains unknown whether we can effectively mitigate impacts of natural gas development by treating habitat within a developing area. Results from this study will indicate whether mitigation dollars would be better spent enhancing/restoring habitat on-site or enhancing habitat in adjacent, undeveloped areas. Although not hypothesized, there is also the possibility that efforts to enhance habitat within heavily developed areas have a negative impact on deer and other species by causing further disturbance. Thus, this project will scientifically assess approaches for mitigating effects of natural gas development on mule deer to guide future management decisions. From December 2007 to present, we gathered baseline demographic and habitat utilization data from radio-collared deer across the Piceance Basin to allow assessment of mitigation approaches that are presently being implemented. We selected 5 winter range study areas representing varying levels of development to serve as treatment and control sites and recorded habitat use and movement patterns using GPS collars. We also estimated winter fawn survival and annual adult female survival, late winter body condition of adult females using ultrasonography, and deer abundance using helicopter mark-resight surveys. We started with 5 study sites to allow flexibility to respond to changing energy development plans, which can directly affect experimental design. In 2009, we refined our study design using our baseline deer data and current energy development plans of the major companies operating in Piceance Basin. We also eliminated a study site to reduce the annual project budget to the minimum necessary to meet the original research objectives. During December 2010-January 2011, we implemented 100 acres of habitat treatments as a pilot effort to evaluate logistics and effectiveness of habitat treatment strategies. We will implement an additional 1,100 acres of habitat treatments across two of our study sites as a mitigation strategy during 2011-13. ExxonMobil Corporation is directly funding all habitat treatments in this research as part of an agreed-upon mitigation plan with CPW. One study site receiving habitat treatments has undergone extensive energy development whereas the other site receiving treatments is experiencing modest development. We will continue to collect the various population and habitat use data across all study sites in order to evaluate the effectiveness of the habitat treatments. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less-impacted areas. We may also find that habitat mitigation efforts are not effective in developed areas at all, suggesting that habitat enhancement efforts may be only effective in areas that are not impacted by development. In 2010, we initiated a PhD project 43 �in collaboration with Colorado State University and ExxonMobil to evaluate deer behavioral responses to varying levels of development activity and habitat mitigation treatments. ExxonMobil is funding this project via a cooperative funding agreement with Colorado State University and CPW. This will allow us to assess the effectiveness of certain BMPs and habitat manipulations for reducing disturbance to deer. We also initiated a Masters project in collaboration with CSU and funded by ExxonMobil to evaluate vegetation responses to the habitat treatments described above. Danielle Johnston in the Avian Research Section is taking the lead on this project, working in collaboration with Chuck Anderson. Last, we plan to initiate a PhD project in collaboration with CSU during FY 11-12 to measure neonatal deer survival, also funded by ExxonMobil. Through combined funding from Federal Aid and energy companies, we are comprehensively evaluating effects of natural gas development on deer and associated mitigation strategies. Annual Wildlife Research Reports: Anderson, C. R., and D. J. Freddy. 2007. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 103-110. Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Stage I, Objective 5: patterns of mule deer distribution and movements. Colorado Division of Wildlife, Wildlife Research Report July: 63-86. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 111-124. Anderson, C. R., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 47-62. Anderson, C. R., and C. J. Bishop. 2011. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Tri-state energy meeting addressing wildlife management in relation to energy development activities, Parachute, CO, USA. Anderson, C. R. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Graduate-Faculty Seminar Series, Colorado State University, September 18, Fort Collins, CO, USA. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2010. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Faculty-Student Seminar, Western State College, Gunnison, CO, USA. 44 �Anderson, C. R., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2010. Piceance Basin mule deer and energy development: improving winter range habitat as mitigation. Joint Meeting of Colorado’s Habitat Partnership Program and Colorado Section of the Society for Range Management, December 1, Grand Junction, CO, USA. Anderson, C. R. 2011. Piceance Basin mule deer and energy development: improving winter range habitat as mitigation. Northwest Region Biology Training, January 19, Glenwood Springs, CO, USA. Anderson, C. R., and C. J. Bishop. 2011. Current understanding of mule deer-energy development interactions in the western United States. Northwest Region Biology Training, January 19, Glenwood Springs, CO, USA. Northrup, J., G. Wittemyer, and C. R. Anderson. 2011. Behavioral response of mule deer to energy development activities in the Piceance Basin, Colorado. Colorado Chapter of The Wildlife Society Annual Meeting, February 25, Fort Collins, CO, USA. Objective 3. Investigate behavioral and spatial relationships between mule deer and elk, and among mule deer, elk, and cougar as these species simultaneously utilize prescribed landscape habitat manipulations. We capitalized on an opportunity to simultaneously monitor spatial movements and predator-prey dynamics of radio-collared mule deer, elk, and cougars on the Uncompahgre Plateau. Mule deer were marked as part of ongoing research described above under Objective 1. Elk were marked as part of a pilot study to monitor spatial movements of deer and elk on the Uncompahgre Plateau, and cougars were marked with GPS collars as part of a long-term research study (not funded by Federal Aid) evaluating the effects of harvest on cougar populations and the assumptions used by CPW to manage cougar populations. Our primary goal was to improve understanding of cougar-prey dynamics. We investigated GPS location clusters for cougars and assessed if a predation event occurred and what species of prey was involved. Locations of predation events were assessed in relation to vegetation treatments applied to the landscape to benefit mule deer and elk. As predicted, cougar kill sites were associated with deer and elk distribution. The greatest density of kill sites occurred across mid-upper elevation deer winter range where overlap of wintering elk and deer was greatest. We investigated 462 clusters during this pilot study. Kill probability increased as cluster size increased. Kill probability exceeded 0.9 with ≥ 10 locations/cluster and approached 1 with ≥ 15 locations/cluster. The probability of a kill was high if a cougar spent >2 days in the same general area, and a kill was essentially certain if a cougar spent >3 days in the same general area. There was some probability of a kill at clusters that comprised only 1 location, indicating that isolated cougar locations may periodically be associated with kills and should not be ruled out when using GPS location data to address cougar prey utilization. Our estimates of kill probability are conservative because the estimates assume prey detection probability was 1, which is unlikely. Cougars killed adult deer, fawn deer, adult elk, and calf elk in roughly equal proportions. Each prey class comprised 0.22−0.24 of the total kill. Kill composition varied as a function of percent vegetative cover and elevation. In FY 09-10, for logistical and study design reasons, we transitioned all research on this objective to a non-Federal Aid cougar project along the Front Range of Colorado. Annual Wildlife Research Reports: Alldredge, M. W., E. J. Bergman, C. J. Bishop, K. A. Logan, and D. J. Freddy. 2008. Pilot evaluation of predator-prey dynamics on the Uncompahgre Plateau. Colorado Division of Wildlife, Wildlife Research Report July: 87-104. 45 �Objective 4. Evaluate the technical quality and applications of statewide mule deer research and management systems. Considerable progress has been made during recent decades in developing and implementing quality mule deer research and management programs within CPW by enlisting the biostatistical support of faculty at Colorado State University (CSU). This objective has been attained for many years via annual contract for professional services with individual faculty at CSU. Federal Aid grant funding has routinely been used to help fund this contract to support mule deer management and research. Other funds (non-Federal Aid) have also supported this contract, which permits biostatistical support of other research and management functions in CPW as well. During 2006-07, Gary White (CSU faculty) provided support to CPW biologists on designing and implementing harvest surveys, terrestrial inventory systems, and population modeling procedures. Ongoing support was also provided for CPW’s DEAMAN software package, which was used by staff for the storage, summary, and analysis of mule deer and other big game population and harvest data. In July 2007, CPW terminated the annual contract with faculty at CSU after hiring a permanent biometrician within CPW to provide these same services in-house. Peer-Reviewed Publications: McClintock, B. T., G. C. White, and K. P. Burnham. 2006. A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities. Journal of Agricultural, Biological, and Ecological Statistics 11:231-248. Martin, D. J., G. C. White, and F. M. Pusateri. 2007. Occupancy rates by swift foxes (Vulpes velox) in eastern Colorado. Southwestern Naturalist 52:541-551. White, G. C. 2008. Closed population estimation models and their extensions in Program MARK. Environmental and Ecological Statistics 15:89-99. Odell, E. A., F. M. Pusateri, and G. C. White. 2008. Estimation of occupied and unoccupied black-tailed prairie dog colony acreage in Colorado. Journal of Wildlife Management 72:1311-1317. Conn, P. B., D. R. Diefenbach, J. L. Laake, M. A. Ternent, and G. C. White. 2008. Bayesian analysis of wildlife age-at-harvest data. Biometrics 64:1170-1177. Annual Wildlife Research Reports: White, G. C. 2007. Multispecies investigations consulting services for mark-recapture analysis. Colorado Division of Wildlife, Wildlife Research Report July: 97-101. Objective 5. Evaluate new approaches to monitoring mule deer population demographics and habitat conditions. We conducted two separate research projects focused on the development and evaluation of new approaches to enhance monitoring of mule deer populations for research and management: 1) modification and evaluation of vaginal implant transmitters in deer, and 2) development of an automated collaring device for mule deer. Redesigned Vaginal Implant Transmitters Our understanding of factors that limit mule deer populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The only viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not possible previously; however, VITs are often expelled from adult females prepartum, which limits their utility. During the previous 5-year Federal Aid Grant Segment, we evaluated effectiveness of VITs in mule deer. Based on this research, during the current grant segment, we redesigned an existing vaginal implant transmitter (VIT) manufactured by Advanced 46 �Telemetry Systems (ATS) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates to increase likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In our earlier study using the original VIT wings, the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. Automated Collaring Device for Deer We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique significantly reduces stress that is typically associated with capture and handling and should eliminate capture-related mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fully-functional prototype of the device. We conducted an extensive field evaluation of the device with free-ranging mule deer during winter 2010-11. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range. Collars were purposefully made to shed from deer within several weeks or months of being captured. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. Certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We identified a series of device modifications that would be necessary to address these various issues. We will modify the device accordingly and conduct a follow-up field evaluation during 2011-12. Peer-Reviewed Publications: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., C. R. Anderson, Jr., D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2011. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Journal of Wildlife Management 75:1797−1806. Annual Wildlife Research Reports: Bishop, C. J., D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. 2009. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Wildlife, Wildlife Research Report July: 55-67. 47 �Bishop, C. J., C. R. Anderson, D. P. Walsh, P. Kuechle, J. Roth, and E. J. Bergman. 2009. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 69-99. Bishop, C. J., C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2010. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 63-80. Bishop, C. J., D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. 2010. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Wildlife, Wildlife Research Report July: 93-100. Bishop, C. J., C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2011. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Bishop, C. J., M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. 2011. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Colorado Chapter of The Wildlife Society Annual Meeting, January 17−19, Glenwood Springs, Colorado, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. 7th Western States and Provinces Deer and Elk Workshop, May 13−16, Estes Park, Colorado, USA. Bishop, C. J., M. W. Alldredge, D. P. Walsh, E. J. Bergman, and D. Kilpatrick. 2011. Automated collaring device for mule deer. Colorado Chapter of The Wildlife Society Annual Meeting, February 25, Fort Collins, CO, USA. Objective 6. Evaluate hunting systems that could maintain a balance between hunter opportunity and the quality of hunting experience. Historically, management of big game species has focused on the performance of the female and young of the year components of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important, primarily due to the fact that it takes relatively few males to provide adequate breeding potential for the population. Additionally, harvest management objectives were to provide maximal hunting opportunity for hunters. Thus, as long as there were adequate numbers of males to breed females there was no need to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has started to shift away from the objective of providing maximal opportunity towards providing fewer but higher quality opportunities. High quality opportunities are typically defined by hunters as a combination of the opportunity to see a greater number of male deer during the hunt, the potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, in 1999 CPW implemented a statewide limitation in deer hunting. This statewide limitation gave the CPW the ability to greatly reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999, a few marked changes in Colorado’s deer herd have occurred. First, due to reduced harvest an overall increase in deer numbers has been observed. Second, because the reduction in harvest was primarily focused on adult males, a subsequent increase in the ratio of adult males to adult females has occurred. Stemming from this shift in harvest management and the subsequent changes in herd size and structure, a gap in biological information has been identified. Specifically, Colorado’s deer herds have 48 �become composed of a greater number of males, yet little biological data on them exist. Also stemming from the change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so). The decision of how many licenses to make available did not need to be considered. Since 1999, the CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must further reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Very rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and rates have been assumed to not be different from the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. A different, but not unrelated need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of the change in harvest management that occurred between 1998 and 1999. Overall, this shift has been viewed as positive by both the CPW as well as the public. However, the CPW still maintains the responsibility of optimally managing the deer of Colorado and providing the maximal amount of hunting opportunity under this new set of constraints. To date, the CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as DAUs reach and surpass their adult male: adult female ratio objectives, the CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition. If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer will remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, this is biologically not realistic. It is very likely that herds with large post-hunt populations of adult males experience higher levels of mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The simplest way to learn about the mortality process is via manipulative experimentation. Our study objective is two-fold. First, we wish to assess annual survival of adult male mule deer. We wish to establish baseline survival estimates, and related estimates of variance, for different age classes of deer. Second, we wish to manipulate hunting license allocation within the Game Management Units (GMUs) of a single DAU such that adult male: adult female ratios become measurably different between two halves of the DAU. Accordingly, we wish to measure and correlate changes in natural survival of adult male deer with this management action. Similarly, as part of this second objective, we will determine if changes in the age structure of harvested animals occur as the sex ratio and age structure of the hunted population changes. We designed the study and wrote a study plan during 2009-10 and initiated field work during 2010-11. 49 �Peer-Reviewed Publications: Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2011. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management 75:1443−1452. Annual Wildlife Research Reports: Bergman, E. J., C. J. Bishop, K. Oldham, and L. Sidener. 2011. Assessment of survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2007. Biological, social, and economic effects of totally limited deer licenses in Colorado. 7th Western States and Provinces Deer and Elk Workshop, May 13−16, Estes Park, Colorado, USA. Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2008. Biological, social, and economic effects of totally limited deer licenses in Colorado. Colorado Chapter of The Wildlife Society Annual Meeting, January 25, Denver, Colorado, USA. Bergman, E. J., C. J. Bishop, L. Sidener, and K. Oldham. 2011. Survival and optimal harvest management of mule deer bucks in Middle Park, CO. Presentation to the Colorado Wildlife Commission, April 7, Meeker, CO, USA. SUMMARY We conducted work on seven research projects addressing mule deer limiting factors, habitat enhancement, mitigation of natural gas development impacts, predator-prey dynamics, buck harvest management, and technique developments. Additionally, funding provided biostatistical support for implementing or maintaining statewide deer harvest surveys, population databases, aerial surveys, population modeling, and research projects. From activities supported by this Grant during this segment, principal investigators published 13 peer-reviewed scientific articles for prominent wildlife research journals, provided 21 annual CPW Wildlife Research Reports summarizing yearly progress of projects, provided 34 presentations at professional meetings, workshops, or symposia, and initiated 2 graduate student projects. The cumulative impact of this programmatic effort provides Colorado the basis to progress and proactively sustain the mule deer resource in an increasingly complex landscape. The relative success of mule deer management in Colorado reflects the positive synergy between the terrestrial research and management sections in sharing expertise, financial resources, staffing, and common goals. LITERATURE CITED 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. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report 77. Fort Collins, Colorado, USA. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by ______________________________________ Chad J. Bishop, Mammals Research Leader 50 � https://cpw.cvlcollections.org/files/original/dd84b6ce08e6e3f362fcbeb51c265a5c.pdf c7f2cfcb97d2c58d8dfc8f796f9ef2c5 https://cpw.cvlcollections.org/files/original/365a0eac97ef867b3fbb52c0addf3fe8.pdf 40caf868430af28c09c0218f01f383a6 PDF Text Text Colorado Division of Wildlife July 2008 − June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2008 − June 30, 2009 Authors: C. J. Bishop, D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We initiated an effort to design, produce, and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. A passive collaring device would allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. Such a technique would significantly reduce stress that is typically associated with capture and handling and would eliminate capture-related mortality. We wrote a study plan (Appendix I) and collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University in an attempt to produce a prototype device. We evaluated device components in phases throughout the year using captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. The students did a good job with the mechanical aspects of the design when developing a prototype, but the electrical controls to run the device were too advanced for them. Although the prototype lacked several key components, we were able to evaluate various aspects of the device to guide further development. We tested the device at FWRF and then conducted a field evaluation with free-ranging deer during April and May, 2009. The latter provided extensive information on how deer interacted with the device. Most importantly, we could have collared free-ranging deer without handling them had the device been fully automated. To produce a fully functional device, we are pursuing a contract with a professional engineering firm capable of meeting our detailed device specifications. 55 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, DANIEL P. WALSH, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, AND CHUCK R. ANDERSON P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Write a study plan to guide development and evaluation of the automated collaring device. 2. Produce a prototype device and conduct a preliminary field evaluation with mule deer. INTRODUCTION The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., $3,000−5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. 56 �A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. STUDY AREA We conducted all evaluations with captive deer at the FWRF in Fort Collins, Colorado. We conducted limited evaluations with free-ranging deer near Fort Collins in north-central Colorado. We plan to conduct extensive field evaluations in the Piceance Basin in northwest Colorado once a fullyfunctioning device is produced. METHODS We wrote a study plan and identified detailed device specifications to guide development of the automated collaring device (Appendix I). We approached Colorado State University’s Mechanical Engineering Department to discuss their interest in helping design such a device. In result, the collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with free-ranging deer near the end of the year. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. RESULTS AND DISCUSSION We completed the study plan and detailed device specifications (Appendix I). The student engineers did a good job with the mechanical aspects of the design, but the electrical controls to run the device were too advanced for them. The students therefore approached a private electrical engineering design firm located in Fort Collins – Dynamic Group Circuit Design (DGCD). DGCD donated many hours to the project to help the students produce a prototype. By spring 2009, we were interacting directly with DGCD in an attempt to make the prototype device function. Although the device lacked several key components, a number of aspects were ready for evaluation. We therefore tested the device at FWRF and then conducted a field evaluation with free-ranging deer during April and May, 2009. The latter provided extensive information on how deer interacted with the device. Most importantly, we could have collared free-ranging deer without handling them had the device been fully automated. In order to produce a fully functional device, we are presently pursuing a contract with DGCD because of their capability to incorporate our complete set of design specifications into the device. SUMMARY We made significant progress toward developing an automated collaring device for mule deer. We now depend on services of professional engineers to complete prototype development and evaluation. If we are successful, the automated collaring device would allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling would be required and deer could be collared at any time. Primary time commitments would include baiting sites, 57 �moving device(s) among sites, and adding collars to the devices. Once design work is completed, the current estimate for producing one fully functional collaring device is $7,000. At the current net-gunning rate of roughly $550/deer, an individual collaring device would be paid off after 13 deer were collared. Over time, as an individual biologist or researcher accumulated several of these devices, it is reasonable to assume they could collar 25-35 deer with a few weeks of limited effort, amounting to a savings of roughly $14,000-$20,000 per study per year once the devices were paid off. The collaring device would also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. The collaring device would significantly reduce stress that is typically associated with capture and handling and there should be no capture-related mortality. We also have designed the collaring device so that it should be relatively easy to adjust to target adult deer and other ungulate species. Last, the collaring device would have wide applicability for ungulate researchers and managers beyond Colorado. LITERATURE CITED 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by Chad J. Bishop, Wildlife Researcher 58 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2008-09 – FY 2009-10 State of: Cost Center: Work Package: Task No. Colorado 3430 3001 8 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS Principal Investigators Chad J. Bishop, Mammals Researcher, Colorado Division of Wildlife Daniel P. Walsh, Wildlife Health Researcher, Colorado Division of Wildlife Eric J. Bergman, Mammals Researcher, Colorado Division of Wildlife Mathew W. Alldredge, Mammals Researcher, Colorado Division of Wildlife Chuck R. Anderson, Mammals Researcher, Colorado Division of Wildlife Cooperators Mechanical Engineering Department, Colorado State University Michael Sirochman, Veterinarian Technician, Colorado Division of Wildlife John Broderick, Senior Terrestrial Biologist, Colorado Division of Wildlife Lisa L. Wolfe, Veterinarian, Colorado Division of Wildlife Michael W. Miller, Wildlife Health Leader, Colorado Division of Wildlife Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center STUDY PLAN APPROVAL Prepared by: Chad J. Bishop Date: Nov 2008 Submitted by: Chad J. Bishop Date: Nov 2008 Reviewed by: Date: Date: Biometrician: Approved by: Date: Michael W. Miller Mammals Research Leader, Acting 59 Date: �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS A Study Plan Proposal Submitted by: Chad J. Bishop, Mammals Researcher, Colorado Division of Wildlife Daniel P. Walsh, Wildlife Health Researcher, Colorado Division of Wildlife Eric J. Bergman, Mammals Researcher, Colorado Division of Wildlife Mathew W. Alldredge, Mammals Researcher, Colorado Division of Wildlife Chuck R. Anderson, Mammals Researcher, Colorado Division of Wildlife A. Need The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., $3,000−5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. 60 �B. Objectives Our study objective is to develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. C. Expected Results or Benefits A passive collaring device, as described above, would allow biologists and researchers to radiocollar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. Such a technique would significantly reduce stress that is typically associated with capture and handling and would eliminate capture-related mortality. We do not expect our collaring device to replace other capture techniques. Rather, we expect the device to provide biologists and researchers with an efficient, cost-effective technique to mark a portion of their targeted fawn samples, thereby keeping helicopter net-gunning requirements and associated costs at viable levels. D. Approach 1. Device Specifications We identified an array of specifications to guide design of the automated collaring device, which we divided into 3 categories: 1) collaring device, 2) radio collar, and 3) controls. Collaring device refers to the overall trap-like device and its various components. Our radio collar specifications reflect 6month-old fawn radio collars that are currently used by CDOW. Our intent was to avoid design of a more costly radio collar and to ensure that biologists and researchers could use radio collars readily available on the market without making substantive changes. If radio collar costs increased significantly, the automated collaring device would fail to be cost-effective and have much less utility to biologists and researchers accustomed to using helicopter net-gunning. We were less concerned about cost of the collaring device because it would be a one-time expense that would support repeated fawn captures. Our third specification category, controls, refers to those aspects of the device requiring automation. Collaring Device 1. Device remotely attaches radio collar around the neck of a ≥6-month-old deer fawn; most ≥6month-old fawns range in size from 50−100 lbs. 2. Device deters adult deer or other larger animals from entering but does not deter entry of fawns. 3. Device allows fawns to easily exit in multiple directions at any time. 4. Device must not cause injury to animals. 5. Device incorporates a place for bait, which will lure the animals to the device. 6. The collapsed device should fit in the back of a typical full-size pickup truck. 7. Device should be of a generalized design that could be modified in the future to target different ages and species of animals (e.g., adult deer, calf elk, adult elk, lamb sheep, adult sheep, etc.) Radio collar 1. Collar accommodates fawn neck sizes ranging from 11 to 16 inches in circumference. 2. Width of collar neckband ranges from 0.5 to 3 inches. 3. Collar sheds from the deer 6−12 months after being placed on the animal using surgical tubing or comparable mechanism that does not increase the overall cost of a radio collar. 4. Use existing radio transmitters that are presently available on the market. Controls 1. Restrict collaring to animals that weigh 47−103 lbs (i.e., guarantee that only fawns receive radio collars). 2. Prevent the same fawn from being collared more than once. 3. Measure and record animal weight. 4. Measure and record animal sex. a. Fawn deer sexing options include: 61 �i. Gonads (most reliable) ii. Antler stubs (less reliable) 5. Obtain photo of captured animal. 2. Device Design Working with engineering students and faculty at Colorado State University, we designed the device in stages using a series of prototypes. For example, we initially constructed the device frame out of cheap material and evaluated it using captive deer at the Foothills Wildlife Research Facility in Fort Collins, CO. We observed deer interactions with the prototype to evaluate device dimensions and placement of the radio collar within the device (Figs. 1, 2). We then modified the prototype accordingly and reevaluated until we were comfortable the dimensions were adequate. Once staged prototype testing was completed, we constructed the various device components using materials we believed were suitable for employing the device in winter field conditions. The device frame was constructed from steel and coated to prevent rust and to lessen wear and tear (Fig. 3). The sides of the device comprise one-gay gates, which prevent entry from outside the device yet allow deer to exit the device at any point they choose. The one-way gates were constructed from aluminum and are being mounted with hinges and springs to allow one-way movement. Deer will enter the device through a 14” x 32” opening in the front of the device; entry dimensions were derived from experience feeding deer fawns in Idaho (G. Scholten, Idaho Department of Fish and Game - retired, personal communication). The radio collar and collaring mechanism will be positioned at the rear of the device and in front of the bait compartment (Fig. 4). To access the bait, a deer will be required to extend its head and neck through an expandable collar in the fully expanded position (Fig. 5). The radio collar was made expandable using springs, which was patterned after an expandable adult buck collar designed by Michael Sirochman (Colorado Division of Wildlife, personal communication). The springs prevent the collar from being too loose on a small fawn while not being too tight on a large fawn. Expandable fawn collars are not a new concept and have been commonly used elsewhere on 6-month-old fawns and are sold by telemetry companies. The floor of the device will comprise a scale to estimate the animal’s weight. The animal’s weight will be correctly recorded no matter where the animal stands within the device. A door will close and prevent access to the collaring mechanism/bait compartment if an animal is heavier than 103 lbs, which will allow us to target fawns and prevent older deer from sticking their head through the expanded collar. To be collared, a deer must extend its head through the collar and nudge a joystick positioned in the center of the bait container. The collar will not release unless an animal is heavier than 43 lbs (and less than 103 lbs), which will prevent small animals that may access the bait from triggering the collar. When the joystick is moved and the animal is in the correct weight range, a solenoid will be activated that causes the collar to release around the deer’s neck (Fig. 5). To prevent double-collaring, radio frequency identification (RFID) tags will be attached to all fawn collars. An antenna will be positioned around the opening of the device and connected to an RFID reader. When a previously collared fawn enters the device, the RFID reader will detect the tag and cause the door to the collaring mechanism/bait compartment to close. Digital cameras will be positioned in several locations in the device to photograph the animal when the collar is released. We are currently in the process of assembling the various device components. Once fully assembled and operational, we will evaluate the device with captive deer at FWRF. As necessary, we will make modifications or adjustments to the device until it meets all of our specifications listed above. 62 �3. Field Testing We will evaluate the device with free-ranging deer after we have confirmed the device is working correctly with captive deer. Initially, we will evaluate the device under close supervision in the Fort Collins area to record deer interactions with the trap and to document any problems we may have failed to anticipate. We will be on-site during this initial field testing and we will secure the device entry to prevent access when we’re not present. This will allow us to directly observe how animals interact with the device and to free any animals if there is a problem. If there is a problem, we will use a pole or rod to simultaneously pull back the bars forming the one-way gates on the sides of the trap to encourage the animal to exit and/or to assist the animal with exiting. In the unlikely event we were to seriously injure an animal or kill an animal, we would cease the field study and go back to the design phase to address the problem that caused the animal harm. Animals will be released from the device with functioning radio collars and will be monitored one week post-collaring and every few weeks thereafter. Collars will have surgical tubing between the transmitter and the springs, thereby allowing the collar to drop-off when the surgical tubing degrades. We are using surgical tubing because it is the standard technique used to collar 6-month-old fawns in Colorado, and thus we want to test deployment of collars that will actually be used with this device. However, we will use a knife to make small cuts in the surgical tubing to cause the collars to shed from the animals within a few months of being deployed. Once we have radio-collared several fawns successively without incident and confirmed the device is working correctly, we will begin more widespread testing. During November-December 2009, we will employ ≥1 devices on mule deer winter range to capture fawns as part of ongoing research (Anderson and Freddy 2008). We will document whether the collars cause any ill effects to fawns during the field evaluations by following up on fawns and evaluating whether any mortalities might be related to collaring. We will record numbers of fawns successfully radio-collared and measured relative to personhours expended setting and moving the device. We will then contrast costs and efficiency with other fawn capture techniques. Finally, we will project the cost-savings over a 10-year period associated with using the device for 3 weeks on each deer research and management study in Colorado. It is highly unlikely that an animal would require euthanasia in this study because we will not restrain animals and animals will be able to readily exit the collaring device in any of 3 directions. However, if a deer were to suffer a broken leg, back, neck, pelvis, or other similar wound, it will be euthanized by deep anesthesia with the drug combination of ketamine or Telazol© and xylazine (IV or IM) with dosage based on estimated weight, followed by intravenous administration of KCl (~350 mg KCl/ml sterile water, dosed at >50 mg KCl/kg estimated body mass). In situations where administration of KCl is not feasible, then euthanasia will be performed via a gunshot to the head. E. Location We will conduct all evaluations with captive deer at the FWRF in Fort Collins, CO. We will conduct limited evaluations with free-ranging deer near Fort Collins in north-central Colorado and extensive field evaluations in the Piceance Basin in northwest Colorado. Anderson and Freddy (2008) provided a detailed description of winter range study sites where 6-month-old fawn mule deer will be captured in the Piceance Basin. 63 �F. Schedule Of Work Activity Date Complete Initial Device Specifications Design and Evaluate Prototypes of Device Components Assemble and Evaluate Prototype Device with Captive Deer Initial Evaluation of Device with Free-Ranging Deer Set up Contract with Professional Engineering Firm Complete Design Requirements and Fabricate Working Device Extensive Evaluation of Device with Free-Ranging Deer Prepare Final Report Submit Manuscript to JWM for Publication Sept 2008 Sept 2008−Feb 2009 Mar 2009 Mar−Apr 2009 July−Aug 2009 Sept−Dec 2009 Dec 2009−Feb 2010 Mar−Apr 2010 May−July 2010 G. Estimated Costs Category Item or Position FY 08-09 FY 09-10 Personnel Chad Bishop 0.06 PFTE 0.06 PFTE Dan Walsh 0.06 PFTE 0.04 PFTE Mat Alldredge 0.03 PFTE 0.01 PFTE Eric Bergman 0.03 PFTE 0.01 PFTE Chuck Anderson 0.00 PFTE 0.03 PFTE Device Design and Fabrication $9,000 $22,000 Field Evaluations $1,000 $3,000 Operating H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS) and state lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. 64 �van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Figure 1. Prototype evaluation of collar and bait placement, and validation that a deer would extend its head and neck through an expanded collar to access the bait. 65 �Figure 2. Prototype evaluation of entrance and cage dimensions with captive deer. Figure 3. Device frame. The sides of the device will comprise one-way gates that prevent entry to the device yet allow animal to easily exit once inside. Animals will be required to enter the device through a 14” x 32” opening in the front. The rear portion of the device is a bait compartment fabricated from steel. A door on the rear of the bait compartment will allow biologists to easily add bait in the field. 66 �Figure 4. The bait compartment. Deer will be required to extend their head and neck through an outstretched expandable radio collar in order to reach the bait. Figure 5. Radio collar in fully expanded position situated at the entry to the bait compartment. Clear plexi-glass will be placed on either side of the collar to prevent deer from accessing the bait from the side yet will allow visibility. When activated, a solenoid positioned at the top of the collaring device pushes a lever that releases the collar. 67 �Colorado Division of Wildlife July 2009 − June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2009 − June 30, 2010 Authors: C. J. Bishop, D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We will conduct an extensive field evaluation of the device with freeranging mule deer during 2010-11. 93 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, DANIEL P. WALSH, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, AND CHUCK R. ANDERSON P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Work with a professional engineering firm to produce a fully-functional prototype of an automated collaring device for ≥6-month-old mule deer fawns. INTRODUCTION The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described 94 �above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. Therefore, our objective is to design, produce, and evaluate a fully-functional prototype of an automated collaring device for ≥6-month-old mule deer fawns. STUDY AREA We conducted all evaluations with captive deer at the FWRF in Fort Collins, Colorado. We conducted limited evaluations with free-ranging deer near Fort Collins in north-central Colorado. We plan to conduct extensive field evaluations with free-ranging deer in north-central Colorado and elsewhere in Colorado once a fully-functioning device is produced. METHODS We initially wrote a study plan and identified detailed device specifications to guide development of the automated collaring device. We approached Colorado State University’s Mechanical Engineering Department to discuss their interest in helping design such a device. In result, the collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with free-ranging deer near the end of the year. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), located in Fort Collins, Colorado, to produce a fully-functional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during the course of the year. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. RESULTS AND DISCUSSION We produced a fully-functional prototype device that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment. Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 1). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to 95 �target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again ready to fire and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 2 and 3). The collar is then situated around the deer’s neck. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a closeup photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We will evaluate effectiveness of the device in the field during 2010-11. Initially, we will only set the device with a collar when we are present and able to directly observe deer interactions with the device. After collaring 5-10 animals in this manner and troubleshooting any problems with the device, we will set the device to operate remotely without an observer on-site, which is how it is intended to be used. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving device(s) among sites, and adding collars to the devices. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. The collaring device should significantly reduce stress that is typically associated with capture and handling and there should be no capture-related mortality. We also have designed the collaring device so that it should be relatively easy to adjust to target adult deer and other ungulate species. Last, the collaring device should have wide applicability for ungulate researchers and managers beyond Colorado. We will be evaluating the device in the field with free-ranging mule deer during the coming year and making additional modifications as necessary. 96 �LITERATURE CITED 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 97 �Figure 1. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 98 �Figure 2. View of the collar release mechanism in an automated collaring device for mule deer. 99 �Figure 3. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. The prototype device will be evaluated extensively in the field with free-ranging deer during 2010-11. 100 �Colorado Division of Parks and Wildlife July 2010 − June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2010 − June 30, 2011 Authors: C. J. Bishop, M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We conducted an extensive field evaluation of the device with freeranging mule deer during winter 2010-11. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range. Collars were purposefully made to shed from deer within several weeks or months of being collared. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. Certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We identified a series of device modifications that would be necessary to address these various issues. During 2011-12, we will modify the device accordingly and conduct a follow-up field evaluation. 85 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, MATHEW W. ALLDREDGE, DANIEL P. WALSH, ERIC J. BERGMAN, AND CHARLES R. ANDERSON, JR. P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that will automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 7. Evaluate effectiveness and functionality of an automated collaring device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. INTRODUCTION Colorado Parks and Wildlife (CPW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240−300 deer fawns are captured annually to monitor survival among 4−5 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CPW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CPW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described 86 �above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CPW’s operating expenses and improve animal welfare. Therefore, we designed, produced, and evaluated an automated device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. STUDY AREA We conducted all evaluations with captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. We conducted field evaluations with free-ranging deer at 5 sites along Colorado’s northern Front Range: 1) Horsetooth Reservoir, west of Fort Collins, private land 2) Masonville, southwest of Fort Collins, private land, 3) Red Feather, northwest of Fort Collins, private land, 4) Hall Ranch, west of Lyons, Boulder County Parks and Open Space, and 5) Heil Valley Ranch, southwest of Lyons, Boulder County Parks and Open Space. We plan to conduct additional field evaluations with free-ranging deer in northwest Colorado during 2011-12. METHODS We identified detailed specifications to guide the design and development of an automated collaring device and sought assistance from Colorado State University’s Mechanical Engineering Department. The collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with freeranging deer during spring 2009. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), located in Fort Collins, Colorado, to produce a fully-functional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during 2009-10. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. Working with DGCD, we produced a fully-functional prototype device in 2010 that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment (Fig. 1). Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 2). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to 87 �target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again able to be released (when triggered) and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 3 and 4). The collar is then situated around the deer’s neck. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a closeup photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We evaluated effectiveness of the device in the field during winter 2010-11. Initially, we only set the device with a collar in place when we were present and able to directly observe deer interactions with the device. After collaring several animals in this manner and troubleshooting problems with the device, we set the device to operate remotely without an observer on-site, which is how it was intended to be used. RESULTS AND DISCUSSION We began baiting sites at Horsetooth Reservoir and Masonville on October 21, 2010, to attract deer for evaluating the device. We baited sites with alfalfa hay, apple pulp, dried fruit, and cereal. We baited several other sites briefly but discontinued baiting due to lack of deer use. Deer immediately responded to bait at Horsetooth Reservoir and began accessing the bait daily. On October 26, we placed the collaring device on site and began encouraging deer to walk into the device by placing bait on the scale inside the cage. On October 29, we documented a deer accessing the bait pan within the bait compartment for the first time. In the following weeks, we continued to periodically document deer entering the device and accessing the bait pan, although malfunctioning of the device prevented deer from being collared. One malfunction occurred because an electrical signal emitted from a camera placed at the entry of the device interfered with the RFID reader, which ultimately prevented fawns from being collared. It took roughly a week to diagnose the problem, which was corrected by simply removing the camera from the entry of the device. This particular camera was not wired into the device and was not critical to device functioning. We deemed that this camera was unnecessary and would be more useful if placed approximately 5 meters away from the trap to better document deer use and behavior. A second malfunction occurred because the scale did not have adequate support underneath and touched the 88 �ground, thereby giving inaccurate weight readings, which also prevented deer from being collared. We corrected this particular problem by welding an aluminum frame to better support the scale. Once these problems were corrected and other adjustments were made, we remotely collared our first fawn (female) on November 17, 2010. The fawn showed little reaction to the collaring event, calmly exiting the trap shortly after receiving the collar. The fawn’s weight and sex were successfully recorded. Sex was positively confirmed based on a photograph of the fawn’s head taken by the camera positioned in the bait compartment. We continued to monitor the device at Horsetooth Reservoir because there were adequate numbers of uncollared fawns in the area. However, we continued to encounter various problems with the device that affected functionality. Most notably, the collar release mechanism began failing to release the collar when a fawn was in position. We quickly determined that device controls were working properly and that an electrical signal was successfully being sent to the solenoid when an uncollared fawn was in the proper position accessing the bait. The source of the problem was a mechanical failing associated with the release mechanism itself. When an expanded collar was in place (i.e., in a fully-expanded state), the tension of the collar sometimes prevented the release lever from moving enough to release the aluminum plates holding the collar in position. Once aware of the problem, we began making adjustments to the release mechanism to improve its functionality. Another problem we identified was that fawns were placing their front hooves on a piece of metal trim at the front of the cage when accessing the bait, which led to inaccurate weight readings and missed opportunities to collar fawns. We corrected this problem by placing a plastic shield above the metal trim so that deer could no longer place hooves on the metal trim. Following this modification, the entire floor surface of the cage comprised only the scale. We also noted that small fawns accessing the bait sometimes failed to break the infrared beam extending across the center of the bait pan, thereby failing to be collared. Thus, we adjusted the positioning of the bait pan to make sure that fawns successfully broke the infrared beam when accessing the bait, regardless of size. Once these changes were made, we successfully collared two more fawns (1 male and 1 female) on successive days, December 13 and 14, 2010. Also, the female fawn that was collared on November 17 shed its collar on December 13 and was successfully recollared on December 20. On December 21, the actuator that opens and closes the bait door short-circuited in response to cold, snowy weather and damaged the circuit board that controls operation of the device. The actuator was positioned such that moisture could enter it. The moisture, in combination with cold temperatures, caused the failure. It became evident at this point that future device modifications would likely require a heavier-duty actuator. However, until a new actuator could be researched, tested, and installed, DGCD used the same actuator and positioned it differently so that it was less likely to take on moisture. DGCD also replaced the circuit board to restore functionality of the collaring device. Several weeks were required to make these modifications, causing the device to be inoperable from December 21, 2010, through January 15, 2011. On January 20, we recollared the female fawn that was initially collared on December 14 (it shed the first collar on January 13). We then moved the device to the Masonville bait site on January 21, after documenting 5 successful collaring events at Horsetooth Reservoir. The Masonville bait site was regularly visited by 4 bucks, 3 does, and 2 fawns. The fawns were aggressively chased by the 4 bucks once we put the collaring device in place and restricted the amount of bait available outside of the collaring device. We solved this problem by creating a separate bait site for the bucks a short distance away. It took one week before the fawns at Masonville became comfortable entering the collaring device and accessing the bait in the bait pan. We did not put a collar in place initially because we speculated that the fawns would be more likely to access the bait pan for the first time if they were not required to extend their head through the collar. Once one of the fawns became acclimated and we put a collar in the device, the bait door/actuator began malfunctioning again, preventing the fawn from being collared. The malfunctioning was apparently related to cold temperatures. The bait door/actuator began functioning correctly again several days later and we collared 89 �a male fawn on February 4, 2011. The only other fawn on site showed no interest in accessing the bait in the bait pan during the ensuing week. Thus, we stopped baiting the site on February 12 and moved the device to the Red Feather site on February 14. Several of the gate arms that prevent deer entry into the sides of the device had been damaged by deer over the course of the winter. During February 14−20, as deer became accustomed to the collaring device, we replaced all gate arms with a new, more durable hinge system. We then resumed normal operations and collared our 7th fawn (female) on February 27, 2011. Unfortunately, the RFID reader failed to detect this collared fawn the following day, allowing the fawn to receive a second collar on February 28. We suspended collaring efforts for several days evaluating the RFID failure. It became evident that if a collared fawn entered the device quickly, it could go undetected by the RFID reader. This issue was already understood as a potential problem, but this was the first time a fawn was actually double-collared. We documented no ill effects of the second collar on the fawn. Realizing the odds of a double-collaring event were low, we resumed collaring efforts on approximately March 6. Incidentally, the odds of the double-collared fawn receiving a third collar were essentially zero because the fawn now had two RFID transponders. We made note that the RFID problem would need to be resolved with a device modification during the following year. The other couple of fawns routinely visiting the site were reluctant to access the bait pan. On March 17, we moved the collaring device to the Heil Valley Ranch site on Boulder County Parks and Open Space land. Deer regularly visiting the Heil site included 4 bucks, 2 does, and 1 fawn. We were unable to keep the bucks from being aggressive toward the does and fawn around the collaring device, which prevented the fawn from entering the device. In response, we moved the device to the Hall Ranch bait site on March 24, 2011, where 3-4 bucks, 2-3 does, and 1-3 fawns were using the site. Deer acclimated quickly to the collaring device and we collared our 8th fawn on March 28th, immediately after placing the collar in the device. A few days later we concluded the field evaluation because weather was turning warm, green forage was abundant, and bears were coming out of hibernation. During our field evaluation, we documented a number of issues with the collaring device that need resolved in subsequent design modifications: • The solenoid release mechanism occasionally failed to release the collar even when the solenoid was triggered. We plan to evaluate an alternative release mechanism that uses an archery caliper release instead of the existing metal, latch system. • We documented several scenarios that could allow a fawn to receive a second collar. First, if a collared fawn extends its head through the entry to the device and is detected by the RFID reader but fails to move forward onto the scale for ≥30 seconds, the bait door will move back into the open position. Second, if a collared fawn is on the scale for >15 minutes (i.e., beds down on the scale), the scale will rezero and the door will move back into the open position. At this point another fawn could step into the device, which would indicate a correct weight range, and the collared fawn could receive a second collar if it then accessed the bait. Third, as we directly witnessed, if a collared fawn enters the device quickly, it is possible the RFID reader could fail to detect the RFID transponder in the fawn’s collar. These scenarios, albeit unlikely, can be corrected by changing the device programming and increasing sensitivity of the RFID reader/antenna. • The actuator that controls the bait door commonly malfunctioned in cold temperatures (i.e., ≤ −12 °C). We intend for the device to be fully functional at −32 °C. We plan to research other actuators and evaluate them under controlled temperature settings. A number of actuators are available on the market that meet our temperature specifications, but they range in cost from <$100 to >$1000. The actuator we evaluated was the cheapest available and did not meet its 90 �• stated specifications. Our intent is to find the cheapest actuator that will hold up under field conditions. The camera mounted on the floor of the device commonly failed to provide useful images for identifying sex. We therefore plan to remove the floor-mounted camera. In contrast, the camera in the bait compartment positioned to take pictures of a fawn’s head provided conclusive evidence of sex. The only needed adjustment is to more securely attach the “head camera” to the bait compartment. Working with DGCD, we will research and implement the necessary device modifications to address these issues. We plan to incorporate the design modifications during summer-fall 2011 and conduct a follow-up field evaluation during winter 2011-12. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving device(s) among sites, and adding collars to the devices. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. We successfully collared 6 different fawns during Nov−Mar, 2011−12, along Colorado’s northern Front Range. We recollared 2 of these fawns after they shed their initial collars, resulting in 8 successful collaring events. Fawns generally showed minimal reaction to being collared. It was evident that fawns did not experience the type of stress that is associated with typical capture and handling techniques. We documented a number of functional issues with the collaring device, which we plan to resolve through design modifications during summer-fall 2011. We then plan to conduct a follow-up field evaluation during winter 2011-12. LITERATURE CITED 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 91 �Figure 1. Automated collaring device for mule deer, comprising an aluminum cage and a bait compartment. Deer become collared by entering the cage and extending their head through an expanded radio collar when accessing bait. 92 �Figure 2. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 93 �Figure 3. View of the collar release mechanism in an automated collaring device for mule deer. 94 �Figure 4. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. 95 �Colorado Division of Parks and Wildlife July 2011 − June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2011 − June 30, 2012 Authors: C. J. Bishop, M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We conducted an extensive field evaluation of the device with freeranging mule deer during October-March, 2010-11, and January-March, 2012. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range during winter 2010-11. Collars were purposefully made to shed from deer within several weeks or months of being collared. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns in 2010-11. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. We successfully collared, weighed, and identified sex of 2 different mule deer fawns in the Piceance Basin of northwest Colorado during February-March 2012. We collared fewer fawns in winter 2011-12 than the previous winter in part because of a shortened evaluation period (i.e., 3 instead of 6 months). Winter conditions were mild overall during 2011-12, which likely contributed to the lower collaring rate since deer had ample foraging options and may not have been as strongly attracted to bait. During 2010-11, certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We incorporated a series of device modifications during summer-fall 2011 necessary to address these various issues. The device functioned well under field 80 �conditions during January-March 2012, indicating the modifications were effective. Our automated collaring device allowed mule deer fawns to be remotely collared, weighed, and sexed with minimal or no stress to the animals. However, fawns typically required one or more weeks of exposure to the device before they entered and accessed the bait. This slow acclimation period limited utility of the device when compared to traditional capture techniques used to collar fawns. Future work will focus on additional device modifications and altered baiting strategies that decrease fawn acclimation period, and in turn, increase collaring rates. 81 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, DANIEL P. WALSH, AND CHARLES R. ANDERSON, JR. P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that will automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Evaluate effectiveness and functionality of an automated collaring device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. INTRODUCTION Colorado Parks and Wildlife (CPW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240−300 fawns are captured annually to monitor survival among 4−5 populations distributed across western Colorado and an additional 100−350 fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CPW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CPW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should not cause capture-related mortality. The large-mammal capture techniques described above place 82 �considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CPW’s operating expenses and improve animal welfare. Therefore, we designed, produced, and evaluated an automated device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. STUDY AREA We worked with captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado, when designing the device and evaluating initial prototypes. We conducted subsequent evaluations of the collaring device with free-ranging deer in various field locations. During 2010-11, we conducted field evaluations with free-ranging deer at 5 sites along Colorado’s northern Front Range: 1) Horsetooth Reservoir, west of Fort Collins, private land 2) Masonville, southwest of Fort Collins, private land, 3) Red Feather, northwest of Fort Collins, private land, 4) Hall Ranch, west of Lyons, Boulder County Parks and Open Space, and 5) Heil Valley Ranch, southwest of Lyons, Boulder County Parks and Open Space. During 2012, we conducted field evaluations with free-ranging deer at Hall Ranch (Jan) and in the Piceance Basin southwest of Meeker, Colorado (Feb-Mar). METHODS We identified detailed specifications to guide the design and development of an automated collaring device and sought assistance from Colorado State University’s Mechanical Engineering Department. The collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with freeranging deer during spring 2009. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), Fort Collins, Colorado, to produce a fullyfunctional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during 2009-10. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. Working with DGCD, we produced a fully-functional prototype device in 2010 that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment (Fig. 1). Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 2). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal 83 �outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again able to be released (when triggered) and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever or trigger that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 3 and 4). The collar is then situated around the deer’s neck. In 2011, we replaced the release lever with an archery caliper release in an attempt to improve the release mechanism. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a close-up photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. In 2011, we removed the floor camera after determining it was not necessary or effective for identifying deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We evaluated effectiveness of the device in the field during October-March 2010-11 and JanuaryMarch 2012. Initially, we only set the device with a collar in place when we were present and able to directly observe deer interactions with the device. After collaring several animals in this manner and troubleshooting problems with the device, we set the device to operate remotely without an observer onsite, which is how it was intended to be used. RESULTS AND DISCUSSION 2010-2011 Field Evaluation We began baiting sites at Horsetooth Reservoir and Masonville on October 21, 2010, to attract deer for evaluating the device. We baited sites with alfalfa hay, apple pulp, dried fruit, and cereal. We baited several other sites briefly but discontinued baiting due to lack of deer use. Deer immediately responded to bait at Horsetooth Reservoir and began accessing the bait daily. On October 26, we placed the collaring device on site and began encouraging deer to walk into the device by placing bait on the scale inside the cage. On October 29, we documented a deer accessing the bait pan within the bait compartment for the first time. In the following weeks, we continued to periodically document deer entering the device and accessing the bait pan, although malfunctioning of the device prevented deer from being collared. One malfunction occurred because an electrical signal emitted from a camera placed at the entry of the device interfered with the RFID reader, which ultimately prevented fawns from being 84 �collared. It took roughly a week to diagnose the problem, which was corrected by simply removing the camera from the entry of the device. This particular camera was not wired into the device and was not critical to device functioning. We deemed that this camera was unnecessary and would be more useful if placed approximately 5 meters away from the trap to better document deer use and behavior. A second malfunction occurred because the scale did not have adequate support underneath and touched the ground, thereby giving inaccurate weight readings, which also prevented deer from being collared. We corrected this particular problem by welding an aluminum frame to better support the scale. Once these problems were corrected and other adjustments were made, we remotely collared our first fawn (female) on November 17, 2010. The fawn showed little reaction to the collaring event, calmly exiting the trap shortly after receiving the collar. The fawn’s weight and sex were successfully recorded. Sex was positively confirmed based on a photograph of the fawn’s head taken by the camera positioned in the bait compartment. We continued to monitor the device at Horsetooth Reservoir because there were adequate numbers of uncollared fawns in the area. However, we continued to encounter various problems with the device that affected functionality. Most notably, the collar release mechanism began failing to release the collar when a fawn was in position. We quickly determined that device controls were working properly and that an electrical signal was successfully being sent to the solenoid when an uncollared fawn was in position accessing the bait. The source of the problem was a mechanical failing associated with the release mechanism itself. When an expanded collar was in place (i.e., in a fully-expanded state), the tension of the collar sometimes prevented the release lever from moving enough to release the aluminum plates holding the collar in position. Once aware of the problem, we began making adjustments to the release mechanism to improve its functionality. Another problem we identified was that fawns were placing their front hooves on a piece of metal trim at the front of the cage when accessing the bait, which led to inaccurate weight readings and missed opportunities to collar fawns. We corrected this problem by placing a plastic shield above the metal trim so that deer could no longer place hooves on the metal trim. Following this modification, the entire floor surface of the cage comprised only the scale. We also noted that small fawns accessing the bait sometimes failed to break the infrared beam extending across the center of the bait pan, thereby failing to be collared. Thus, we adjusted the positioning of the bait pan to make sure that fawns successfully broke the infrared beam when accessing the bait, regardless of size. Once these changes were made, we successfully collared two more fawns (1 male and 1 female) on successive days, December 13 and 14, 2010. Also, the female fawn that was collared on November 17 shed its collar on December 13 and was successfully recollared on December 20. On December 21, the actuator that opens and closes the bait door short-circuited in response to cold, snowy weather and damaged the circuit board that controls operation of the device. The actuator was positioned such that moisture could enter it. The moisture, in combination with cold temperatures, caused the failure. It became evident at this point that future device modifications would likely require a heavier-duty actuator. However, until a new actuator could be researched, tested, and installed, DGCD used the same actuator and positioned it differently so that it was less likely to take on moisture. DGCD also replaced the circuit board to restore functionality of the collaring device. Several weeks were required to make these modifications, causing the device to be inoperable from December 21, 2010, through January 15, 2011. On January 20, we recollared the female fawn that was initially collared on December 14 (it shed the first collar on January 13). We then moved the device to the Masonville bait site on January 21, after documenting 5 successful collaring events at Horsetooth Reservoir. The Masonville bait site was regularly visited by 4 bucks, 3 does, and 2 fawns. The fawns were aggressively chased by the 4 bucks once we put the collaring device in place and restricted the amount of bait available outside of the collaring device. We solved this problem by creating a separate bait site for the bucks a short distance away. It took one week before the fawns at Masonville became comfortable entering the collaring device and accessing the bait in the bait pan. We did not put a collar in place 85 �initially because we speculated that the fawns would be more likely to access the bait pan for the first time if they were not required to extend their head through the collar. Once one of the fawns became acclimated and we put a collar in the device, the bait door/actuator began malfunctioning again, preventing the fawn from being collared. The malfunctioning was apparently related to cold temperatures. The bait door/actuator began functioning correctly again several days later and we collared a male fawn on February 4, 2011. The only other fawn on site showed no interest in accessing the bait in the bait pan during the ensuing week. Thus, we stopped baiting the site on February 12 and moved the device to the Red Feather site on February 14. Several of the gate arms that prevent deer entry into the sides of the device had been damaged by deer over the course of the winter. During February 14−20, as deer became accustomed to the collaring device, we replaced all gate arms with a new, more durable hinge system. We then resumed normal operations and collared our 7th fawn (female) on February 27, 2011. Unfortunately, the RFID reader failed to detect this collared fawn the following day, allowing the fawn to receive a second collar on February 28. We suspended collaring efforts for several days evaluating the RFID failure. It became evident that if a collared fawn entered the device quickly, it could go undetected by the RFID reader. We were aware of this potential problem, but this was the first time it actually occurred. We documented no ill effects of the second collar on the fawn. Realizing the odds of a double-collaring event were low, we resumed collaring efforts on approximately March 6. Incidentally, the odds of the double-collared fawn receiving a third collar were essentially zero because the fawn now had two RFID transponders. We made note that the RFID problem would need to be resolved with a device modification during the following year. The other couple of fawns routinely visiting the site were reluctant to access the bait pan. On March 17, we moved the collaring device to the Heil Valley Ranch site on Boulder County Parks and Open Space land. Deer regularly visiting the Heil site included 4 bucks, 2 does, and 1 fawn. We were unable to keep the bucks from being aggressive toward the does and fawn around the collaring device, which prevented the fawn from entering the device. In response, we moved the device to the Hall Ranch bait site on March 24, 2011, where 3-4 bucks, 2-3 does, and 1-3 fawns were using the site. Deer acclimated quickly to the collaring device and we collared our 8th fawn on March 28th, immediately after placing the collar in the device. A few days later we concluded the field evaluation because weather was turning warm, green forage was abundant, and bears were coming out of hibernation. 2011 Device Modifications During our 2010-11 winter field evaluation, we documented a number of issues with the collaring device that needed resolved. During summer-fall 2011, working with DGCD, we made several modifications to the device to address these issues. • Issue: The solenoid release mechanism occasionally failed to release the collar even when the solenoid was triggered. Modification: We evaluated and incorporated an alternative release mechanism that used an archery caliper release instead of the existing metal, latch system. • Issue: We documented several scenarios that could allow a fawn to receive a second collar. First, if a collared fawn extended its head through the entry to the device and was detected by the RFID reader but failed to move forward onto the scale for ≥30 seconds, the bait door moved back into the open position. Second, if a collared fawn was on the scale for >15 minutes (i.e., bedded down on the scale), the scale re-zeroed and the door moved back into the open position. At this point another fawn could step into the device, which would indicate a correct weight range, and the collared fawn could receive a second collar if it then accessed the bait. Third, as we directly witnessed, if a collared fawn entered the device quickly, the RFID reader sometimes failed to detect the RFID transponder in the fawn’s collar. Modifications: We resolved these issues by reprogramming the device and increasing sensitivity of the RFID reader/antenna. 86 �• • Issue: The actuator that controls the bait door commonly malfunctioned in cold temperatures (i.e., ≤ −12 °C). We intend for the device to be fully functional at −32 °C. Modification: We researched other actuators and selected a higher quality unit that would be more likely to perform adequately under the desired conditions. We then evaluated the actuator under controlled temperature settings in a freezer to confirm functionality before installation in the collaring device. Issue: The camera mounted on the floor of the device commonly failed to provide useful images for identifying sex. The camera in the bait compartment positioned to take pictures of a fawn’s head provided conclusive evidence of sex, indicating the floor camera was unnecessary. Modification: We removed the floor-mounted camera from the device and eliminated the associated wiring and programming. 2012 Field Evaluation We made considerable progress evaluating and subsequently modifying the collaring device during 2010-2011, and therefore, we believed that a 3-month evaluation period during January-March 2012 would be sufficient for a follow-up field evaluation. We initially evaluated the collaring device during January 2012 at Hall Ranch near Lyons, Colorado. We began evaluating the collaring device on January 10. Unfortunately, the bait sites were visited primarily by adult males, limiting any opportunities to collar fawns. These adult males also appeared to prevent regular attendance at the bait site/collaring device by adult females and fawns that were in the area. The problem of adult males dominating a bait site is not unique to this study and has been documented over time when attempting to capture fawns where bait is used to attract animals to a trap (Colorado Parks and Wildlife, unpublished data). Given the challenges posed by adult males near Lyons, we moved the collaring device at the end of January to Piceance Basin, southwest of Meeker, Colorado, where a separate deer study was underway and could benefit from additional collared fawns. We also believed deer densities would be higher near our bait sites in Piceance Basin than our sites along Colorado’s northern Front Range, potentially offering more opportunities to collar fawns. We initiated our evaluation of the collaring device in Piceance Basin on February 5, 2012. We were unable to monitor the collaring device in the field on a daily basis given the distance from the original study area along the northern Front Range. Our first monitoring period occurred during February 5-10. We collared a male fawn weighing 66 lbs on February 7 during early evening. During February 1118, we baited the collaring device but did not monitor deer activity on site. We resumed direct field monitoring of the device during February 19-24. During this time, we consistently observed a mixture of does, fawns, and bucks on site but did not successfully collar a fawn. The previously collared fawn was routinely on site and often entered the collaring device. During February 25-March 3, we again baited the collaring device but did not conduct field observations. We resumed field monitoring during March 4-9. Deer consistently accessed the bait site during this period, typically with a group size of 6-7 deer that included 3-4 fawns. On March 9, we collared a female fawn weighing 63 lbs. We once again ceased direct field monitoring during March 10-18 and completed our final monitoring period during March 1921. Deer were active on site during this final evaluation period, including the previously collared fawns, although we were unable to collar any new fawns. We then ceased our evaluation of the collaring device for 2012, having collared 2 fawns during an approximately 1.5-month evaluation period in Piceance Basin. Our modifications to the collaring device in 2011 appeared to have improved functionality of the device. The only problem we documented during our field evaluation in 2012 was that the bait door often remained open when the first collared fawn reentered the device on subsequent occasions. While initially of concern, the bait door always closed when tested with other collars. Additionally, the bait door closed each time the second collared fawn reentered the device after having been collared. Thus, we concluded 87 �there was a problem with the RFID transponder placed in the first collar rather than a problem with the collaring device itself. Although the device functioned well, the rate at which deer were collared was particularly slow. Our field observations indicate that fawns typically required one or more weeks of exposure before they entered the device and accessed the bait in the bait pan. Some fawns were reluctant to enter the device even after days or weeks of exposure. We tried various baiting strategies in an attempt to maximally encourage fawns to enter the device to access bait in the bait pan. If bait were only placed in the bait pan inside the device, deer groups were not attracted and retained at the site, and therefore, no fawns were present. If too much bait were placed outside the device, there was no incentive for fawns to enter the device and extend their head through the expanded collar to access bait in the bait pan. Generally speaking, we learned that some bait has to be placed outside the device to attract deer groups to the site and that some bait should be placed on the floor/scale to lure fawns into the device. We also tried placing all bait external to the device in buckets to limit the number of animals accessing bait at any given time and to make them more accustomed to placing their heads in an enclosed area to obtain the bait. However, our observations did not suggest this technique was any more effective at encouraging fawns to enter the device and extend their heads through the expanded collar to access bait in the pan. Winter weather conditions were overall mild during our study, particularly during winter 2011-12, which may partly explain the slow rate at which fawns were collared. During winter conditions exhibiting greater snow depths and lower temperatures with less forage available, we would expect fawns to have greater incentive to enter the device and extend their head through the expanded collar to access bait. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving the device(s) among sites, and adding collars to the device. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. We successfully collared 6 different fawns during Nov−Mar, 2011−12, along Colorado’s northern Front Range. We recollared 2 of these fawns after they shed their initial collars, resulting in 8 successful collaring events. Fawns generally showed minimal reaction to being collared. It was evident that fawns did not experience the type of stress that is associated with typical capture and handling techniques. We documented a number of functional issues with the collaring device in 2010-11, which we resolved through design modifications during summer-fall 2011. We conducted a follow-up field evaluation during January-March 2012 and collared 2 additional fawns during February and March in Piceance Basin. The largest drawback of the collaring device is the slow rate at which fawns were collared. Fawns typically required one or more weeks of exposure to the device before fully entering the device and extending their head through the expanded collar to access bait in the bait pan. This slow acclimation period limited utility of the device when compared to traditional capture techniques used to collar fawns. In the future, additional design modifications or more clever baiting strategies will be necessary to improve collaring rates. We also plan to evaluate placement of ≥2 collaring devices at the same site once a second collaring device is produced. With more collaring devices, potentially less bait would need to be placed external to the devices and deer might be more inclined to access bait in the bait pans within the collaring devices. 88 �LITERATURE CITED 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 89 �Figure 1. Automated collaring device for mule deer, comprising an aluminum cage and a bait compartment. Deer become collared by entering the cage and extending their head through an expanded radio collar when accessing bait. 90 �Figure 2. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 91 �Figure 3. View of the collar release mechanism in an automated collaring device for mule deer. 92 �Figure 4. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. 93 �Colorado Parks and Wildlife July 2012 – June 2013 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3001 8 Federal Aid Project No. W-185-R : : : : : Parks and Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2012 – June 30, 2013 Authors: C. J. Bishop, M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. Cooperators: Mechanical Engineering Department, Colorado State University, Michael Sirochman, Veterinarian Technician, Colorado Parks and Wildlife, John Broderick, Senior Terrestrial Biologist, Colorado Parks and Wildlife. Lisa L. Wolfe, Veterinarian, Colorado Parks and Wildlife, Michael W. Miller, Wildlife Health Leader, Colorado Parks and Wildlife, Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We conducted an extensive field evaluation of the device with free-ranging mule deer during OctoberMarch, 2010-11, and January-March, 2012. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range during winter 2010-11. Collars were purposefully made to shed from deer within several weeks or months of being collared. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns in 2010-11. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. We successfully collared, weighed, and identified sex of 2 different mule deer fawns in the Piceance Basin of northwest Colorado during February-March 2012. We collared fewer fawns in winter 2011-12 than the 57 �previous winter in part because of a shortened evaluation period (i.e., 3 instead of 6 months). Winter conditions were mild overall during 2011-12, which likely contributed to the lower collaring rate since deer had ample foraging options and may not have been as strongly attracted to bait. During 2010-11, certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We incorporated a series of device modifications during summer-fall 2011 necessary to address these various issues. The device functioned well under field conditions during January-March 2012, indicating the modifications were effective. Our automated collaring device allowed mule deer fawns to be remotely collared, weighed, and sexed with minimal or no stress to the animals. However, fawns typically required one or more weeks of exposure to the device before they entered and accessed the bait. This slow acclimation period limited utility of the device when compared to traditional capture techniques used to collar fawns. During 2012-13, focus was on additional device modifications and altered baiting strategies that decrease fawn acclimation period, and in turn, increase collaring rates. 58 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, DANIEL P. WALSH, AND CHARLES R. ANDERSON, JR. OBJECTIVE Colorado Parks and Wildlife (CPW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CPW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., $3,000−5,000 ea.) would reduce CPW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CPW’s operating expenses and improve animal welfare. Our study objective is to develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. 59 �STUDY AREA We conducted field evaluations with free-ranging deer along Colorado’s Front Range between Boulder and Fort Collins, in the Piceance Basin in northwest Colorado, and on the Uncompahgre Plateau in western Colorado. METHOD Device Specifications We identified an array of specifications to guide design of the automated collaring device, which we divided into 3 categories: 1) collaring device, 2) radio collar, and 3) controls. Collaring device refers to the overall trap-like device and its various components. Our radio collar specifications reflect 6month-old fawn radio collars that are currently used by CPW. Our intent was to avoid design of a more costly radio collar and to ensure that biologists and researchers could use radio collars readily available on the market without making substantive changes. If radio collar costs increased significantly, the automated collaring device would fail to be cost-effective and have much less utility to biologists and researchers accustomed to using helicopter net-gunning. We were less concerned about cost of the collaring device because it would be a one-time expense that would support repeated fawn captures. Our third specification category, controls, refers to those aspects of the device requiring automation. Collaring Device 1. Device remotely attaches radio collar around the neck of a ≥6-month-old deer fawn; most ≥6month-old fawns range in size from 50−100 lbs. 2. Device deters adult deer or other larger animals from entering but does not deter entry of fawns. 3. Device allows fawns to easily exit in multiple directions at any time. 4. Device must not cause injury to animals. 5. Device incorporates a place for bait, which will lure the animals to the device. 6. The collapsed device should fit in the back of a typical full-size pickup truck. 7. Device should be of a generalized design that could be modified in the future to target different ages and species of animals (e.g., adult deer, calf elk, adult elk, lamb sheep, adult sheep, etc.) Radio collar 1. Collar accommodates fawn neck sizes ranging from 11 to 16 inches in circumference. 2. Width of collar neckband ranges from 0.5 to 3 inches. 3. Collar sheds from the deer 6−12 months after being placed on the animal using surgical tubing or comparable mechanism that does not increase the overall cost of a radio collar. 4. Use existing radio transmitters that are presently available on the market. Controls 1. Restrict collaring to animals that weigh 47−103 lbs (i.e., guarantee that only fawns receive radio collars). 2. Prevent the same fawn from being collared more than once. 3. Measure and record animal weight. 4. Measure and record animal sex. a. Fawn deer sexing options include: i. Gonads (most reliable) ii. Antler stubs (less reliable) 5. Obtain photo of captured animal. Device Design Working with engineering students and faculty at Colorado State University, we designed the device in stages using a series of prototypes. For example, we initially constructed the device frame out of cheap material and evaluated it using captive deer at the Foothills Wildlife Research Facility in Fort 60 �Collins, CO. We observed deer interactions with the prototype to evaluate device dimensions and placement of the radio collar within the device (Figs. 1, 2). We then modified the prototype accordingly and reevaluated until we were comfortable the dimensions were adequate. Once staged prototype testing was completed, we constructed the various device components using materials we believed were suitable for employing the device in winter field conditions. The initial device frame was constructed from steel and coated to prevent rust and to lessen wear and tear. We later changed the device frame to aluminum (Fig. 3). The sides of the device comprise one-gay gates, which prevent entry from outside the device yet allow deer to exit the device at any point they choose. The one-way gates were constructed from aluminum and are being mounted with hinges and springs to allow one-way movement. Deer will enter the device through a 14” x 32” opening in the front of the device; entry dimensions were derived from experience feeding deer fawns in Idaho (G. Scholten, Idaho Department of Fish and Game - retired, personal communication). The radio collar and collaring mechanism will be positioned at the rear of the device and in front of the bait compartment. To access the bait, a deer will be required to extend its head and neck through an expandable collar in the fully expanded position (Fig. 4). The radio collar was made expandable using springs, which was patterned after an expandable adult buck collar designed by Michael Sirochman (Colorado Parks and Wildlife, personal communication). The springs prevent the collar from being too loose on a small fawn while not being too tight on a large fawn. Expandable fawn collars are not a new concept and have been commonly used elsewhere on 6-month-old fawns and are sold by telemetry companies. The floor of the device will comprise a scale to estimate the animal’s weight. The animal’s weight will be correctly recorded no matter where the animal stands within the device. A door will close and prevent access to the collaring mechanism/bait compartment if an animal is heavier than 103 lbs, which will allow us to target fawns and prevent older deer from sticking their head through the expanded collar. To be collared, a deer must extend its head through the collar and break an infrared beam positioned immediately above the bait container. The collar will not release unless an animal is heavier than 43 lbs (and less than 103 lbs), which will prevent small animals that may access the bait from triggering the collar. When the IR beam is broken and the animal is in the correct weight range, a solenoid will be activated that causes the collar to release around the deer’s neck (Fig. 4). To prevent double-collaring, radio frequency identification (RFID) tags will be attached to all fawn collars. An antenna will be positioned around the opening of the device and connected to an RFID reader. When a previously collared fawn enters the device, the RFID reader will detect the tag and cause the door to the collaring mechanism/bait compartment to close. Digital cameras will be positioned in several locations in the device to photograph the animal when the collar is released. RESULTS AND BENEFITS A passive collaring device, as described above, would allow biologists and researchers to radiocollar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. Such a technique would significantly reduce stress that is typically associated with capture and handling and would eliminate capture-related mortality. We do not expect our collaring device to replace other capture techniques. Rather, we expect the device to provide biologists and researchers with an efficient, cost-effective technique to mark a portion of their targeted fawn samples, thereby keeping helicopter net-gunning requirements and associated costs at viable levels. In winter 2011-12 we completed a second year of field evaluation of a fully-functional prototype device (Figs. 5, 6). During this evaluation, we accumulated hundreds of hours of field observation of mule deer interacting with the device and we noted device components that warranted modification for optimal performance. We incorporated these modifications and conducted a follow-up field evaluation 61 �with free-ranging deer during winter 2012-13 on the Uncompahgre Plateau. We also constructed a second prototype for field testing based on the final design of the first prototype. All animals were released from the device with functioning radio collars and were monitored one week post-collaring and every few weeks thereafter. Collars had surgical tubing between the transmitter and the springs, thereby allowing the collar to drop-off when the surgical tubing degraded. We used surgical tubing because it is the standard technique used to collar 6-month-old fawns in Colorado, and thus we wanted to test deployment of collars that would actually be used with this device. However, we did make small cuts in the surgical tubing to cause the collars to shed from the animals within a few months of being deployed. We designed and fabricated the collaring device in such a manner as to prevent inadvertent collaring of non-target species, thereby preventing any possibility that a threatened, endangered, or candidate species could be harmed. The floor of the collaring device is a scale that continuously records weight and informs the device. The collar can only be released when an appropriately-sized animal is in the device. Animals are attracted to the device with bait, contained in a separate compartment at one end of the device. To access the bait, animals must extend their head and neck through an expanded collar into the bait compartment. The collar can only be released when an animal is accessing the bait, thereby breaking an infrared beam, which further informs the device. We are not familiar with any animals in these study areas that fit the weight range of a deer and could simultaneously access the bait. The only possible animal is a black bear, although it is unlikely the bear could access the bait. However, black bears will be hibernating during the winter months when the collaring device will be employed. Finally, even if a non-target animal accessed the device, there is ample opportunity for the animal to leave the device without being harmed. The sides of the device consist of one-way gates, such that an animal in the device can exit at any time through the entrance or sides. Finally, in the extreme unlikely event that a non-target animal were radio-collared, the expandable collar does not pose a threat to any animal that can fit its head through the expanded collar. The device, therefore, poses no threat to non-target species, including threatened, endangered, and candidate species listed under the Endangered Species Act because none are similar in size or behavior to deer. Also, all travel will occur on established roads throughout the study areas, preventing any chance of damaging a listed plant species. SUMMARY As part of our field evaluation, we recorded numbers of fawns successfully radio-collared and measured relative to person-hours expended setting and moving the device. We planned to contrast costs and efficiency with other fawn capture techniques. However, successful capture of fawns was extremely limited, so at this point other capture techniques would be more efficient. During the final winter of investigation no fawns were collared and only a few actually entered the device. This concludes this project. LITERATURE CITED Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, 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. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. 62 �Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 63 �Figure 1. Prototype evaluation of collar and bait placement, and validation that a deer would extend its head and neck through an expanded collar to access the bait. Figure 2. Prototype evaluation of entrance and cage dimensions with captive deer. 64 �Figure 3. Device frame. The sides of the device comprise one-way gates that prevent entry to the device yet allow animals to easily exit once inside. Animals will be required to enter the device through a 14” x 32” opening in the front, which is adjustable. The rear portion of the device is a bait compartment fabricated from aluminum. A door on the rear of the bait compartment will allow biologists to easily add bait in the field and access controls. Figure 4. The bait compartment. Deer will be required to extend their head and neck through an outstretched expandable radio collar in order to reach the bait. 65 �Figure 5. Mule deer fawn in process of being collared. Figure 6. Mule deer fawn at the moment of the collar being released. 66 � https://cpw.cvlcollections.org/files/original/a917e885d25f935ada35f4868554e1d2.pdf 29d9ebae18e5cd8e0d93069e7080e872 PDF Text Text Colorado Division of Wildlife July 2008 − June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2008 − June 30, 2009 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, P. Kuechle, J. Roth, and E. J. Bergman. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our understanding of factors that limit mule deer populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The only viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not possible previously; however, VITs are often expelled from adult females prepartum, which limits their utility. We redesigned an existing vaginal implant transmitter (VIT) manufactured by Advanced Telemetry Systems (ATS) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates to increase likelihood of locating birth sites and newborn fawns. We placed VITs with modified wings in 59 adult female mule deer and evaluated probability of retention to parturition and probability of locating newborn fawns. Probability of a VIT being expelled during parturition (i.e., success) was 0.766 (SE = 0.0605) and probability of a VIT being expelled ≤3 days prepartum (i.e., partial success) was 0.128 (SE = 0.0477). Thus, probability of a VIT being at least partially successful was 0.894 (SE = 0.0441). Probability of locating at least 1 neonate from successful or partially successful VITs was 0.952 (SE = 0.0333) and probability of locating both fawns from twin litters was 0.588 (SE = 0.0857). We expended approximately 12 person-hours per detected neonate. Our modifications to VIT wings effectively increased VIT retention in mule deer, allowing more neonate fawns to be located per unit cost and effort. Researchers employing VITs with modified wings should require minimal oversampling to offset failures caused by early expulsion. To aid researchers in planning future studies, we developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival. 69 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHUCK R. ANDERSON, DANIEL P. WALSH, PETER KUECHLE, JOHN ROTH, AND ERIC J. BERGMAN P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 1. Redesign and manufacture the silicone-covered plastic wings used to retain VITs in deer. 2. Evaluate rates of VIT retention to parturition and fawn capture success using the newly-designed wings in free-ranging mule deer. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radio-locate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. hemionus), black-tailed deer (O. hemionus columbianus), and mule deer have been moderately successful (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Bishop et al. 2007). Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sample bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, road densities, fawn ages, and stages of fawning. When using VITs, neonate captures should be more random as long as VIT signals are monitored with equal intensity during fawning, and assuming the sample of radio-collared does was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT 70 �design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although capture success was high when VITs shed only 1−3 days prepartum. More importantly, Bishop et al. (2007) found that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling would be required in the design of future projects to achieve a target sample size of fawns. Oversampling is not desirable from an animal care and use perspective or from a cost perspective. Thus, the plastic-silicone retention wings of VITs need to be redesigned to allow maximum retention in deer. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used to produce VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used to produce VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs and with antennas cut to the appropriate length, S. P. Haskell (Texas Tech University, unpublished data) reported that 81% of VITs (n = 21) in deer were retained until parturition. Although retention improved, this aftermarket modification was not ideal. The modified wing tips were hard because of the resin addition and thus not ideal for placement in the vaginal canal. Also, there remained a need to further increase retention rate. We therefore developed a study plan (Appendix A), redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as Magnolia, Story-Sprague, Ryan Gulch, and Yellow Creek (Fig. 2). These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). Winter range habitat comprised predominantly pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) and secondarily big sagebrush (Artemisia tridentata), serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus spp.). Drainage bottoms were characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainage bottoms having been converted to irrigated, grass hay fields. Elevations ranged from 1860 m at Piceance Creek in Ryan Gulch to 2280 m in Yellow Creek and Story-Sprague. Our summer range study area comprised roughly 1700 km2 across the Roan Plateau and Piceance Basin (Fig. 1). Principal summer range habitat types included aspen (Populus tremuloides), mountain shrub, oakbrush (Quercus gambellii), big sagebrush, and pinyon-juniper. Serviceberry, snowberry (Symphoricarpos spp.), and chokecherry (Prunus virginiana) were common species in mountain shrub communities. Elevation ranged from 2000 m in Piceance Creek at the mouth of Story Gulch to 2600 m on Roan Plateau. 71 �METHODS VIT Modification We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the way in which wings are attached to the transmitter body. Specifically, we extended the length and width of the retention wings and added ridges to the wing surface, both of which were intended to increase probability of retention to parturition (Fig. 3). The wings were made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold, which met our target specifications and therefore was deemed acceptable. We then manufactured a production mold, necessary to produce a large number of the wings. We incorporated ejector pins into the VIT design that allow wings to be attached to the VIT transmitter body in the field. In the original design, wings were permanently affixed to the transmitter body during the VIT assembly process. Although we only used one wing size in this study, field-attachment will allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. Deer Capture and VIT Insertion During late February and early March, 2009, we captured 59 adult female deer utilizing helicopter net guns (Barrett et al. 1982, van Reenen 1982) in conjunction with ongoing research addressing other objectives (Anderson and Freddy 2008). We captured 20 deer in Ryan Gulch, 19 deer in Yellow Creek, and 10 deer each in South Magnolia and Story-Sprague study units. Captured deer were hobbled, blind-folded, and ferried ≤5 km by helicopter to a central handling location. For each captured deer, we used transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop et al. 2007, Bishop et al. 2009). We shaved the left caudal abdomen from the last rib and applied lubricant to facilitate transabdominal scanning using a 3-MHz linear transducer. We fitted each pregnant deer with a VIT and a radiocollar equipped with a mortality sensor and store-on-board global position system (GPS). The mortality sensor was programmed to switch signal transmission from a slow pulse to a fast pulse after remaining motionless for 4 hours. We also measured mass, chest girth, and hind foot length of each deer and estimated age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). We performed the ultrasound and VIT insertion procedures in a wall-frame tent to minimize disturbance from helicopter rotor wash and adverse weather conditions and to create a dim environment to facilitate ultrasonography. We sterilized VITs in a chlorhexidine solution prior to insertion in the field. We inserted VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope was 15.2 cm long with a 1.59 cm internal diameter and had a smoothed end to minimize vaginal trauma. We placed vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and used a new pair of surgical gloves to handle the vaginoscope and VIT for each deer, and we applied a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we folded the wings together and placed the VIT into the end of the vaginoscope. We liberally applied sterile KY Jelly to the scope and inserted it into the vaginal canal until the tip of the VIT antenna was approximately flush with the vulva. We used previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We extended alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope was pulled out from the vagina. Each VIT had a temperature-sensitive switch and a pre-cut antenna (6 cm in length) with antenna 72 �tip encapsulated in a resin bead to eliminate sharp edges. The temperature-sensitive switch caused the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature dropped below 32° C. A temperature drop below 32° C was indicative of the VIT being expelled from the deer. VIT Monitoring and Success Evaluation We monitored live-dead status and general location of all radiocollared adult females daily from the ground and biweekly from the air during winter and spring. During each morning of June we checked VIT signal status by aerially locating each radio-collared doe having a VIT, weather permitting. We began flights at approximately 0630 hours and completed them by 0900–1100 hours. Early flights were necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceeded 32° C by mid-day, which caused VITs to switch back to a slow (i.e., prepartum) pulse. When we detected a fast (i.e., postpartum) pulse rate, we used very high frequency (VHF) receivers and directional antennae from the ground to simultaneously locate the VIT and radiocollared doe. We attempted to observe behavior of the collared adult female, establish whether the VIT was shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moved away from the VIT (i.e., >200 m), we located the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) were present and subsequently located the collared dam to search for fawns at her location. We attempted to account for each dam’s fetus(es) as live or stillborn. We typically worked in pairs, which allowed us to effectively partition effort across the study area while maintaining reasonable efficiency when searching for neonates (i.e., two people were more effective locating a hidden neonate than one person). We described effort associated with locating fawns by calculating the number of person-hours per fawn. We also quantified cost per fawn by considering all operating and personnel expenses, including capture and VIT costs for adult females. We assigned the fate of each VIT to one of 4 categories: 1) success (i.e., VIT expelled during parturition), 2) partial success (i.e., VIT expelled ≤3 days prepartum), 3) failure (i.e., VIT expelled >3 days prepartum), or 4) censor. We considered a VIT successful if it was expelled at or near a birth site in conjunction with parturition. For most success events, we located VITs at birth sites and located neonates near the VITs or in close proximity to their dams. In other success cases, we did not locate VITs at birth sites yet we found neonate(s) in close proximity to the dam, sometimes at a birth site a short distance from the expelled VIT. In these cases, we considered a VIT successful if we documented <1-day-old fawn(s) <24 hours after the VIT was expelled. Last, on two occasions, we considered a VIT successful because it was located at an evident birth site even though we could not locate fawns. Birth sites appeared as atypically large deer beds with soil appearing damp and with forbs and grasses flattened and radiating outward, consistent with a deer licking the site clean. On some occasions, fawns and/or placental remains were still present at birth sites when we arrived, providing positive confirmation of birth site characteristics. We considered VITs expelled within 3 days of parturition as partial successes because they provided useful information for locating fawns, consistent with Bishop et al. (2007). We documented such cases by locating a dam’s neonates one or more days after the VIT was expelled and comparing neonate age to VIT expulsion date. We censored VITs when adult females died prior to parturition and when adult females were located on private land that we did not have permission to access. In either case, we were unable to evaluate VIT effectiveness. All females dying prior to parturition were still carrying the VITs upon death. Analysis We modeled VIT success probability using a generalized logits model (i.e., multinomial logistic regression) in PROC LOGISTIC in SAS (SAS Institute, Cary, NC). We considered 3 levels of success consistent with our description above (success, partial success, failure) and we removed all censors from the dataset prior to analysis. We modeled VIT success as a function of adult female age (yr), mass (kg), hind foot length (cm), chest girth (cm), body fat (%), vegetative cover at VIT expulsion site, and study site. The latter two variables were included to evaluate whether locating fawns, and hence VIT success, 73 �was influenced by habitat characteristics. We expressed vegetative cover categorically as low, medium, or high. Low cover class was characterized by limited understory and overstory vegetation with minimal visual obstruction at ground level (e.g., sparsely-vegetated grass, sagebrush, or mountain shrub slopes). Medium cover class was characterized by moderate to heavy vegetative cover within 1 m of the ground but limited cover above 1 m (e.g., typical sagebrush, mountain shrub sites). High cover class comprised moderate to heavy vegetative cover from ground level up to > 1 m with nearly complete visual obstruction (e.g., oakbrush, aspen-mountain shrub, dense serviceberry). We selected among models using Akaike’s information criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We then estimated the probability of locating ≥ 1 fawn, probability of locating both fawns from twin litters, and probability of locating complete litters from adult females with successful or partially successful VITs. Finally, we developed an equation for determining number of VITs necessary to achieve a specified sample of neonates for planning of future neonatal studies. RESULTS AND DISCUSSION We observed 9 adult female mortalities during winter and spring, which was much higher than expected. There was no evidence to suggest VITs were related to the mortality events. Several of the mortalities occurred within 1 week of capture and were likely capture-related. We were unable to groundmonitor 2 other adult females during the fawning period because they were located on private land that we did not have permission to access. One other adult female was inadvertently deleted from the aerial monitoring list due to miscommunication. We censored these 12 deer because they did not permit evaluation of VIT effectiveness, resulting in a sample size of 47 deer. The model of VIT success probability with the lowest AICc included only the intercept (no. parameters = 2, AICc wt = 0.271; Table 1). Probability of a VIT being expelled during parturition (i.e., success) was 0.766 (SE = 0.0605) and probability of a VIT being expelled ≤3 days prepartum (i.e., partial success) was 0.128 (SE = 0.0477). Thus, probability of a VIT being at least partially successful was 0.894 (SE = 0.0441). For comparison, using the original VIT wing design, Bishop et al. (2007) found that probability of VIT expulsion during parturition was 0.447 (SE = 0.0468), and probability of VIT expulsion during parturition or ≤3 days prepartum was 0.623 (SE = 0.0456). We employed the same methodology as Bishop et al. (2007), except for the wing modification. Assuming the 2 studies are comparable, our wing modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). High VIT success probability may largely explain why VIT retention did not vary as a function of any covariates we evaluated. Bishop et al. (2007) found that larger deer were more likely to expel VITs prematurely, which was the basis for modifying VIT wings. Our results suggest the wing modifications effectively reduced premature expulsion in larger deer. We located 58 neonates and 2 stillborns from 42 adult females with successful or partially successful VITs. For these 42 females, probability of locating at least 1 neonate was 0.952 (SE = 0.0333), probability of locating complete litters was 0.667 (SE = 0.0745), and probability of locating both fawns from twin litters was 0.588 (SE = 0.0857). Fawn location success did not differ between successful and partially successful VITs. Our probability estimate of locating twins is conservative because we did not place radio collars on fawns, and therefore, we could not relocate radiocollared fawns to search for their siblings. The technique of relocating a radiocollared fawn to locate its sibling was found to be successful in a previous study in Colorado (Bishop et al. 2009). During this earlier study, when a dam was known to have twin fetuses yet only one fawn was located and radiocollared during the initial capture attempt, the sibling fawn was found 45% of the time (10/22) by relocating the initial radiocollared fawn 1−2 days post-capture (C. J. Bishop, CDOW, unpublished data). Based on this rate, we would expect our probability of locating both fawns from twin litters to be roughly 0.77 had we radiocollared fawns during our study. 74 �On average, we located 1.3 neonates per VIT excluding censors and 1.0 neonate per VIT including censors. Censors need to be considered when planning VIT sample sizes for neonatal studies. Censored VITs represent the reduction in VIT sample size caused by prepartum mortality of adult females or any factor preventing access to adult females during the fawning period. We developed the following equation for determining the expected number of neonates to be encountered from a sample of VITs: , where = targeted neonate sample size. n N~, = sample size of adult females with VITs. nvns = probability adult female survives to parturition and is accessible. SAdF = probability of VIT retention to within 3 days of parturition. RvIT = probability of detecting ≥1 fawn. 'PPa w-r. = probability adult female has twin fetuses. 1'.4dF PTwms = probability of detecting twin neonates given an adult female has twin fetuses. The purpose of the above equation is to allow determination of VIT sample size once a target neonate sample size has been identified. Thus, it makes more sense to rearrange the equation as: Incorporating our estimates of retention and detection probabilities, we recommend use of the following equation to plan neonatal studies incorporating VITs with our modified wing design: nvrr, = (o.Rs)s [1 + (o.sg )r.◄dF J , AdF We expended roughly 700 person-hours during the fawning period to locate 58 neonates and 2 stillborns, or approximately 12 person-hours per fawn located. This estimate includes hours spent searching for fawns from adult females with failed VITs, although we were never successful in these attempts. Bishop et al. (2007) expended 7 person-hours per captured fawn from adult females with successful VITs, 16 person-hours per fawn from females with partially successful VITs, and 42 personhours per fawn from females with failed VITs and females not receiving VITs. Given their observed VIT success rates, Bishop et al. (2007) would have required approximately 1,315 person-hours to locate 60 neonates, or 22 person-hours per fawn. Assuming these studies are comparable, increased VIT success associated with our modified wing design resulted in a 45% reduction in labor required to locate a fawn from a radiocollared adult female. We expended $31,000 to net-gun our sample of adult females, $15,000 on VITs, $10,000 on fixed wing monitoring, and $20,000 on personnel. Thus, we expended approximately $1,267 per neonate located. We did not include adult female radio collars in our cost estimate because we used GPS collars to meet other research objectives, yet VHF collars would have sufficed for locating neonates. Assuming VHF collars were used on adult females at a rate of $250 per collar, our cost estimate becomes $1,520 per fawn. The VIT technique is therefore effective but expensive to employ. Actual cost of the technique depends on what costs are already incurred to meet other research objectives. For example, in Colorado and elsewhere, researchers have begun estimating late-winter deer body condition as a response variable to accompany survival estimates. In these cases, adult female capture and radio collar costs are already accounted for in the base study, and thus, incorporation of VITs to facilitate neonate capture becomes much more cost-effective. In our study, where adult female capture and collar costs were covered by ongoing research efforts, the added cost of incorporating VITs and neonate capture was $750 per fawn. 75 �SUMMARY Use of VITs in well-designed field studies will increase our understanding of deer limiting factors and population limitation by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. Improved VIT effectiveness facilitates increased detection of twins, and therefore, increased likelihood of radio-collaring complete litters. Determining fates of complete litters improves our ecological understanding of fawn production and recruitment and allows assessment of individual reproductive fitness if the same females are captured across years. However, it is not reasonable to assume neonatal twins are independent sample units when analyzing survival. A technique is available to quantify the amount of sibling dependence in a sample of radio-collared fawns comprising siblings to correctly estimate variance of survival rates and to improve understanding of sibling relationships (Bishop et al. 2008). Although we significantly increased VIT retention, we cannot explain why 10% of adult females expelled VITs several days or weeks prepartum. These individuals were not older or larger than other deer in our sample, making it difficult to recommend future VIT modifications to further improve retention. We speculate that individual behavior may largely explain early VIT expulsion in this study. That is, some deer may be more inclined to attempt to remove VITs than others, making it difficult to eliminate prepartum shedding altogether without dramatically changing how VITs are retained. LITERATURE CITED Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. 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. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer-Verlag, New York, New York, USA. 76 �Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Hamlin, K. L., D. F. Pac, C. A. Sime, R. M. DeSimone, and G. L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management 64:441−449. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. 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. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. 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 Chad J. Bishop, Wildlife Researcher 77 �Figure 1. Location of winter and summer range study areas in Piceance Basin and on Roan Plateau, northwest Colorado. 78 �Figure 2. Location of winter range study units where we captured and radio-marked mule deer in Piceance Basin, northwest Colorado. These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). 79 �I -,i 8 \''¼;_ , ~ ii ~ _J 8 SECTION B·B SCALE 2 · 1 • ~TUBlf:~OINl!ll'-.!:OtfttWll'QCJfr"'£/foltW,O,f"2l ~Sm'E'JS,..,_.~t~ ;: 1!1",TE.~fOB!PCl..'110fE>!i• FW'..J,EITl04,IIO~A t•ti01l(;p~ ~a>1!CU\folii.Blf~CWC'U,tlll) l oo..otrtJBE T,IINl9...l,.(:el7 ~ ;•::-=~~l'WE~~Na.£10111£ • m.O'f',"~.:c.•~•roc.,r,r:A(·•~,.. to•lle"r:I • _.,-IPGIIIC]~-C<NlCC,,111'.JftSTIJllt.~II• ~ Q P • t ~ . . •"V'll ...."11 '4'11 ••41.111 "'"J~•-._....,,,., t •~s, ~(MIA ' ~• t•C..-M~l'(JrNi~fW"1<ilV,.IAA. ~ ~•~ ,-;,o.ac io◄ a flC.:rwr.. :n,~• SECTION A-A SCALE 2 · 1 Figure 3. Design and dimensions of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions include a nylon core with an elastomeric overmold that protects deer from any sharp or rigid edges. 80 �APPENDIX A PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2007-08 – FY 2009-10 State of: Cost Center: Work Package: Task No. Colorado 3430 3001 7 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES Principal Investigators Chad J. Bishop, Wildlife Researcher, Mammals Research Chuck R. Anderson, Wildlife Researcher, Mammals Research Daniel P. Walsh, Wildlife Researcher, Wildlife Health Eric J. Bergman, Wildlife Researcher, Mammals Research Peter Kuechle, President, Advanced Telemetry Systems John Roth, Product Consultant, Advanced Telemetry Systems David J. Freddy, Wildlife Research Leader, Mammals Research Cooperators Lisa L. Wolfe, Veterinarian, Colorado Division of Wildlife Darby Finley, Terrestrial Biologist, Colorado Division of Wildlife Jamin Grigg, Terrestrial Biologist, Colorado Division of Wildlife STUDY PLAN APPROVAL Prepared by: Chad J. Bishop Date: July 2008 Submitted by: Chad J. Bishop Date: July 2008 Reviewed by: Danny Martin Date: 11/24/2008 Jon Runge Date: 11/13/2008 Date: Biometrician Review: Paul Lukacs Date: 11/4/2008 Approved by: David J. Freddy Date: Dec. 2008 Mammals Research Leader 81 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES. A Study Plan Proposal Submitted by: Chad J. Bishop, Wildlife Researcher, Mammals Research Chuck R. Anderson, Wildlife Researcher, Mammals Research Daniel P. Walsh, Wildlife Researcher, Wildlife Health Eric J. Bergman, Wildlife Researcher, Mammals Research Peter Kuechle, President, Advanced Telemetry Systems John Roth, Product Consultant, Advanced Telemetry Systems David J. Freddy, Wildlife Research Leader, Mammals Research A. Need Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radio-locate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. hemionus), black-tailed deer (O. hemionus columbianus), and mule deer have been moderately successful (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Bishop et al. 2007). Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality is known to occur (Bishop 2007, Bishop et al. 2007, Bishop et al. 2008). An additional advantage of using VITs to capture neonates may be a reduction in sample bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, road densities, fawn ages, and stages of fawning. When using VITs, neonate captures should be more random as long as VIT signals are monitored with equal intensity during fawning, and assuming the sample of radio-collared does was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked does. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). The VIT has flexible, plastic wings coated with silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although capture success was high when VITs shed only 1−3 days prepartum. More importantly, Bishop et al. (2007) found that 25% (SE = 4.1) of VITs shed >3 82 �days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling would be required in the design of future projects to achieve a target sample size of fawns. Oversampling is not desirable from an animal care and use perspective or from a cost perspective. Application of VITs in mule deer costs roughly $1,325 per captured fawn given current rates of premature expulsion (Bishop et al. 2007). Thus, the plastic-silicone retention wings of VITs need to be redesigned to allow maximum retention in deer. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactures 1 large wing and 1 small wing; the former has been used to produce VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used to produce VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs and with antennas cut to the appropriate length, S. P. Haskell (Texas Tech University, unpublished data) reported that 81% of VITs (n = 21) in deer were retained until parturition. Although retention improved, this aftermarket modification is not ideal. The modified wing tips are hard because of the resin addition and thus not ideal for placement in the vaginal canal. Also, we desire a VIT design that will provide >0.9 retention rates to parturition. Ideally, any modification to the VIT wings should be incorporated into the manufacturing process. The silicone-covered plastic wings must be manufactured using a production mold that costs roughly $15,000 to fabricate. To date, this cost has deterred design modifications to VIT wings. There is no economic incentive for a company to fabricate wing production molds exclusively for use in wildlife research given the high manufacturing costs and low anticipated return. However, the opportunity exists to redesign VIT retention wings with suitable funding. We propose to redesign the silicone-covered plastic wings, fabricate a new production mold, and conduct a field evaluation. B. Objectives Our study objectives are to (1) redesign and manufacture the silicone-covered plastic wings used to retain VITs in deer, and (2) evaluate rates of VIT retention to parturition and fawn capture rates using the newly designed wings in free-ranging mule deer. C. Expected Results or Benefits A redesigned VIT allowing high rates of retention to parturition (i.e., >0.9) would enable researchers to cost-effectively address complex problems associated with deer reproductive ecology, population productivity, and disease transmission in field studies. This field technique would then be efficacious and directly applicable to research evaluating effects of energy development and associated mitigation strategies, which is presently the highest priority facing Colorado Division of Wildlife and several other state wildlife agencies in the West. D. Approach 1. Hypotheses 1) Redesigned VITs will be retained until parturition in >90% of adult female mule deer. • Redesigning VITs by lengthening and widening the retention wings is expected to increase retention rates based on past research (Bishop et al. 2007; S. P. Haskell, Texas Tech University, unpublished data). 2) Stillborn or neonatal fawns will be located from >85% of adult female mule deer that receive redesigned VITs. • Bishop et al. (2007) captured fawns from 92% (SE = 3.7) of adult female mule deer that retained VITs to parturition. 83 �2. Experimental Design Our study design requires 2 key elements: 1) a minimum sample size of 60 adult female mule deer to guarantee suitable precision of VIT retention estimates, and 2) capture of adult female deer during mid-late winter to facilitate in utero fetus detection and to ensure VIT batteries will be operational throughout the fawning period (i.e., through early July). We will augment existing research efforts by placing VITs in adult female mule deer that will be captured in the Piceance Basin to meet other study objectives (Anderson and Freddy 2008). During 2009−2010, we will place VITs in 60 adult female mule deer each year during late February through early March in the Piceance Basin in northwest Colorado. The adult females will be captured across the Piceance Basin (Anderson and Freddy 2008) and are expected to cover an extensive area during summer (i.e., roughly 3000−4000 mi2) based on past research in this area (White et al. 1987, Bartmann et al. 1992). Assuming a VIT retention rate of 0.9 (i.e., 90% of VITs shed at birth sites), 60 adult females would allow us to estimate a yearly retention rate with a 95% confidence interval (CI) of 0.79−0.96, or a coefficient of variation (CV) of 4.3%. Following the 2-year study, we will be able to estimate retention rate with a 95% CI of 0.83−0.95 (i.e., CV = 3.1%), if there is no significant year effect. If we observe a year effect, we may be able to identify factor(s) that were potentially responsible and improve our understanding of VIT retention. Also, if we experience a problem in the first year, we may be able to correct it prior to the second year. If we experience high success during the first year (e.g., >0.9 retention to parturition), the second year may become part of a biological study to evaluate effects of energy development on fawn production and neonatal survival. 3. Procedures We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the way in which wings are attached to the transmitter body. Specifically, we extended the length and width of the retention wings and added ridges to the wing surface, both of which should increase probability of retention to parturition (Figs. 1, 2). The wings are made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold (i.e., $1,200). The prototype was acceptable. We will therefore manufacture a production mold (i.e., ~$15,000), which will allow a large number of the wings to be produced. The wings will be inexpensive to manufacture once the production mold is available. We will incorporate ejector pins into the VIT design that will allow wings to be attached to the VIT transmitter body in the field. Previously, wings were permanently affixed to the transmitter body during the VIT assembly process. Field-attachment would allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. In late February or early March each year of study, we will capture a total of 60 adult female deer utilizing helicopter net guns (Barrett et al. 1982, van Reenen 1982) in conjunction with ongoing research (Anderson and Freddy 2008). Captured deer will be hobbled, blind-folded, and ferried ≤3.5 km by helicopter to a central handling location. For each captured deer, we will use transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop 2007, Bishop et al. 2007). We will shave the left caudal abdomen from the last rib and apply lubricant to facilitate transabdominal scanning using a 3-MHz linear transducer. We will fit each pregnant deer with a VIT and a radiocollar equipped with a mortality sensor, which will activate after remaining motionless for 4 hours. 84 �We will also measure mass, chest girth, and hind foot length of each deer and estimate age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). We will perform the ultrasound and VIT insertion procedures in a wall-frame tent or other structure to minimize disturbance from helicopter rotor wash and adverse weather conditions and to create a dim environment to facilitate ultrasonography. We will sterilize VITs in a chlorhexidine solution prior to insertion in the field. We will insert VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope is 15.2 cm long with a 1.59 cm internal diameter and has a smoothed end to minimize vaginal trauma. We will place vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and use a new pair of nitrile surgical gloves to handle the vaginoscope and VIT for each deer, and we will apply a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we will fold the silicone wings together and place the VIT into the end of the vaginoscope. We will liberally apply sterile KY Jelly to the scope and insert it into the vaginal canal until the tip of the VIT antenna is approximately flush with the vulva. We will use previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We will extend alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope is pulled out from the vagina. Each VIT will have a temperature-sensitive switch, pre-cut antenna (~6 cm in length) with antenna tip encapsulated in a resin bead to eliminate sharp edges, and a 12-hour on-off duty cycle to extend battery life (Bishop et al. 2007). The temperature-sensitive switch will cause the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature drops below 32° C. A temperature drop below 32° C will be indicative of the VIT being expelled from the deer. We will regularly monitor live-dead status and general location of all radiocollared adult females during winter and spring. During each morning of June we will check VIT signal status by aerially locating each radio-collared doe having a VIT, weather permitting. We will begin flights at approximately 0530 hours and complete them by approximately 1000–1100 hours. Early flights will be necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceed 32° C by mid-day, which will cause VITs to switch back to a slow (i.e., prepartum) pulse (Bishop et al. 2007). When we detect a fast (i.e., postpartum) pulse rate, we will use very high frequency (VHF) receivers and directional antennae from the ground to simultaneously locate the VIT and radiocollared doe. We will attempt to observe behavior of the collared adult female, establish whether the VIT is shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moves away from the VIT (i.e., >200 m), we will locate the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) are present and subsequently locate the collared dam to search for fawns at her location. We will attempt to account for each dam’s fetus(es) as live or stillborn, which is fundamental to estimating fetal survival (Bishop et al. 2007, 2008). We will wear surgical gloves when handling fawns to help minimize transfer of human scent. We will work in pairs and partition the study area into segments, whereby each 2-person team is responsible for one segment. We anticipate needing 4−5 teams given the expanse of the study area (Fig. 3). We will assign the fate of each VIT to one of 6 categories: 1) parturition shed, 2) late prepartum shed (i.e., ≤3 days prepartum), 3) early prepartum shed (i.e., >3 days prepartum), 4) battery or transmitter failure, 5) migration loss, or 6) censor (Bishop et al. 2007). We will identify parturition sheds based on identification of a birth site where the VIT is shed or location of <1-day-old fawn(s) <24 hours after a VIT is shed. The latter criterion is useful because not all birth sites can be positively identified once the dam has cleaned up afterbirth and moved the fawns. Although our primary objective is to quantify the proportion of VITs shed at parturition, the remaining VIT fate categories will be useful for understanding why VITs failed and should aid additional technique refinements. We will distinguish between early 85 �prepartum sheds and late prepartum sheds because the latter provides useful information for capturing fawns. Neonate capture success rate was 0.792 (SE = 0.0847, n = 24) for dams with VITs shed late prepartum on the Uncompahgre Plateau during 2002−2004 (Bishop et al. 2007). We will document battery failures based on the disappearance of a doe’s VIT signal after having consistently heard the signal on a daily basis. Migration losses refer to any VIT signals that disappear during spring migration. These failures are presumably caused by battery failures or early prepartum sheds between winter and summer range, yet the specific cause cannot be determined (Bishop et al. 2007). We will censor VITs associated with prepartum doe mortalities and missing does (i.e., unable to detect radiocollar signal) because these deer will not provide an adequate test of VIT effectiveness (i.e., the failure is independent of VIT technology). We will quantify the proportion of successful fawn captures associated with VITs shed at parturition as well as those shed ≤3 days prepartum. We will also determine whether we account for the entire litter by comparing the number of fawns located in June to the in utero fetal counts obtained in February−March. We will describe effort associated with fawn capture by calculating the number of person-hours per captured fawn. We will also quantify cost per captured fawn by considering all operating and personnel expenses, including capture and transmitter costs for adult does. 4. Data Analysis Procedures We will use a straight-forward binomial model to estimate the probability of VIT retention until parturition in adult female mule deer. We will contrast this estimate with a previous retention probability estimate (0.447, SE = 0.0468, Bishop et al. 2007) to evaluate the likely effect of our VIT modification. The estimates are not directly comparable because they will not have been measured simultaneously. However, the initial retention estimate measured by Bishop et al. (2007) provides a baseline for evaluating whether our VIT modifications had a positive effect. Ultimately, we will evaluate our retention probability estimate relative to our hypothesized retention rate of 0.9. We will model VIT retention as a function of adult female individual covariates (i.e., age, mass, chest girth, hind foot length) using logistic regression in SAS (SAS Institute, Cary, North Carolina) to improve our understanding of factors related to retention, which will be particularly useful if retention is < 0.9. We will select among models using Akaike’s information criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We will also estimate fawn detection probability associated with adult females receiving VITs. Specifically, we will estimate separate detection probabilities for adult females that shed VITs prepartum and adult females that shed VITs at parturition. We will then use the detection probabilities to estimate the probability of capturing the complete litter for different sized litters. E. Location The proposed research will take place in the vicinity of Piceance Basin and the White River National Forest in northwest Colorado (Fig. 3). Anderson and Freddy (2008) provided a detailed description of winter range study sites where adult female mule deer will be captured. The winter range study area is located primarily within CDOW Game Management Unit (GMU) 22. Summer range will be defined by the movements of the radiocollared adult females captured on winter range. We anticipate the summer range study area will include portions of GMUs 11, 211, 12, 22, 23, 24, 31, 32, and 33 (Fig. 3). 86 �F. Schedule Of Work Activity Complete Initial Draft of Study Plan Manufacture VIT Retention Wing Production Mold Finalize Study Plan and Submit to ACUC Order VITs and Purchase Associated Field Equipment Capture Deer and Insert VITs Periodically Monitor Radiocollared Deer Monitor VITs Daily, Locate Shed VITs, and Conduct Fawn Searches Analyze Data and Prepare Progress Report Analyze Data and Prepare Final Report Submit VIT Techniques Manuscript for Publication Date April−May 2008 May−June 2008 August−October 2008 November 2008−2009 February−March 2009−2010 March−May 2009−2010 June 2009−2010 July−August 2009 July−August 2010 December 2010 G. Estimated Costsa Category Item or Position FY 07-08 FY 08-09 FY 09-10 Personnel Chad Bishop 0.20 PFTE 0.40 PFTE 0.40 PFTE Chuck Anderson 0 0.05 PFTE 0.05 PFTE Eric Bergman 0 0.05 PFTE 0.05 PFTE Dan Walsh 0.05 PFTE 0.05 PFTE 0.05 PFTE 0 6.5 Mo. - $17,186 7.0 Mo. - $18,760 VIT Prototype $2,500 0 0 VIT Production Mold $18,500 0 0 Fixed-wing Monitoring (June) 0 $14,875 $15,750 Field Supplies 0 $5,000 $4,000 60 VITs 0 $13,800 $13,800 Telemetry Equipment 0 $3,000 $1,500 TFTE Operating Total Cost $21,000 $53,861 $53,810 a Study costs were minimized by leveraging existing mule deer capture efforts within the ongoing Piceance Basin deer study (Anderson and Freddy 2008). H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS), state, and private lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. 87 �Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. 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., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1−39. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer-Verlag, New York, New York, USA. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Hamlin, K. L., D. F. Pac, C. A. Sime, R. M. DeSimone, and G. L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management 64:441−449. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. 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. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. 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., 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. 88 �J. Figures And Tables D C E 7 B AL("_ - ~ ---J_:_:._JA B ~-.ff -.:::-·:::::::ri::j-• _j _j ---,"C"".. C .. " -~ fll_J\llf.!1 ,.- D '"'.,.,,... . ~f'il;I I I ~ ~,.. ' 'PO'l;rt1- 1,, -I - ,~ ,-- ! ; 2!tJtOH'JC~ _::1 i E - ~Pt "' I ~1:a +- ~ ' 'I ' ,..m-, •~I SECTION C-C SCALE 2 : 1 - .,.,111~, ll'l(krc=,- SECTION D-D SCALE 2 1 SECTION E-E SCALE 2 1 m V --...:: ~ 1N , v- { _,,, / '...-=,. f - O)_ ..,.. ,.. \ Plltlf1 ""' ':I ~ I? ~ •1'1':11:1 ,.,,. W.~IAJ...":)~J#f\.0-.1.-, OCl5UOAtD ,llfE-El~ltlF-BnM'.: J O ~ Wll 7Fl'll •1 Je,,;.~ CD.OA'TOFIE"Qfl.iQJ..:;W,.,W. •1.H;~~F~r...11AJT"1..r...iTOS T«f• I~ ""''" ~ ~~~~J~::t~~~=~FV' CN'ID,111 ... ntnicoa- ~ Dl'l(jQ1D)FtAJM~~l ~1:.S"I ~"Ekl ""' ... ,h, ~ L 1..Qtt..CH>I~ ~Yil• 11~~ SECTION 8-B SCALE 2 : 1 , SECT ION A-A SCALE 2 1 Figure 1. Modified design of the nylon core of retention wings used to retain vaginal implant transmitters in adult female mule deer. We modified the original design by lengthening and widening the wings and modifying the shape. We also incorporated an ejector pin to facilitate attachment of different-sized wings in the field. 89 �/ 8 7 ! -:,- i- \, \, ! : ~-~ _! 8 SECTION B•B SCALE 2 · 1 ...... • ~Tl1111:-...tlcDll\lB1A!:OtEU:'Nl".:..:J,t~-M«:le:I lEI.BiET,o'Si'Sl'U.ISF¥fHJMB' 15f0.I' : ~ c : : ~ = ~ • . w ~ ~ & G I E A T<a!KP~ l.:o.atl'D!!EPl,-,~IT t .L ~"' ~-~;~'} 1 1~-~? \ U~ffl p.- '°'>#IN."""'-LTWOltE:!iS -OBE D,l';I'' ~ ~"~':~~RW'E?"'K-ffU ~ " ' ~ ,oec ___ ,..,_ _ _ _ ,,. _ _ • ~ ~ . . . . -... - ~ , tO 5>,lm'/r.-' ...,., tO• ~ r ~~~~::+t~.~~"r.:,~".'f,=::.i_, S2- 11;.I \ • =;: ,.... J...,_i'.i I \ '~ ,-~~~ SECTION A-A SCALE 2 • 1 ••..,.. ~~.:w flrlf!.'toY'IO,,(W.,.'(UAllt,, ~ ~•-111,10.lilC~ .. fl(,"'1•)1')<1WI. ~ liio!:_ __ ;:o ~nod~~[(,.,;~ ...,~ "154Qe Figure 2. Design and dimensions of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions include the nylon core (Figure 1) with an elastomeric overmold that protects deer from any sharp or rigid edges. 90 �Figure 3. Location of winter range and summer range study areas in the vicinity of Piceance Basin and White River National Forest in northwest Colorado, where we will evaluate the effectiveness of modified vaginal implant transmitters (VITs). Winter and summer range study areas are outlined in white. Mule deer winter range is denoted with dark shading and USFS lands are outlined in black. 91 �K. Appendices APPENDIX I HELICOPTER NET-GUN CAPTURE AND HANDLING PROTOCOL FOR MULE DEER Helicopter net-gunning is a well-established procedure for capturing ungulates (Barrett et al. 1982, van Reenen 1982). Large samples of mule deer and white-tailed deer have been captured using helicopter net-guns with ≤ 1% capture-related mortality (Potvin and Breton 1998, White and Bartmann 1994, Webb et al. 2008). The protocol described below is nearly identical to net-gun protocols approved previously by CDOW’s ACUC (CDOW ACUC Project Protocols 11−2000, 10−2005, 15−2007). Capture-related mortality rates in these projects have ranged from 0 to 3.5%, which includes all animals dying ≤1 week post-capture regardless of cause. A capture mortality rate of 3.5% is higher than the preferred rate of 2% (Spraker 1993) but much lower than what has commonly been experienced in the field using other methods to capture deer (Conner et al. 1987, DelGiudice et al. 2005). The 3.5% capturerelated mortality rate occurred on the Uncompahgre Plateau when large samples of mule deer were captured within small study sites, creating challenging conditions for helicopter net-gunning (Bishop 2007). The overall capture mortality rate in this study was 2% because a majority of deer were captured with drop nets, where capture mortality was 1%. In other recent studies, capture-related mortality rates associated with helicopter net-gunning have been ≤ 2% (Anderson and Freddy 2008; Bergman et al. 2006, 2007, 2008). Net-gunning will be performed by Quicksilver Air, Inc., or other qualified vendor selected by the Colorado Division of Wildlife (CDOW) through a request-for-proposal (RFP) process, which is the required procedure for selecting vendors to conduct helicopter work for CDOW. Quicksilver Air, Inc., has captured large samples of deer in Colorado during the past few years with capture-related mortality rates generally ≤ 2% (Anderson and Freddy 2008; Bergman et al. 2006, 2007, 2008; B. E. Watkins, CDOW, personal communication). Capture and Transport Methods: Wild mule deer will be pursued and netted by the helicopter net-gunning crew. The crew will consist of one pilot, one net-gunner, and ≤2 handlers. Netted animals will immediately be blind-folded and hobbled and transported by the helicopter to a nearby handling site. Deer will be placed inside the helicopter or slung underneath the helicopter during transport. At the handling site, CDOW personnel (i.e., handling crew) will record measurements, affix transmitters, and release each captured deer. Mule deer will be captured within 1−2 miles of the handling site to minimize the distance deer are transported. The handling crew will be ferried to appropriate handling sites by the helicopter pilot if vehicle access is limited in an area. Mule deer will be captured with net-guns in late February or early March in Game Management Unit (GMU) 22 in the Piceance Basin. In Meeker, Colorado, mid-late winter snow depths average roughly 12 cm, and rarely exceed 35 cm, where deer will be captured, and mean daily temperatures during late February have averaged –1 °C (30 °F) during recent decades. Under these conditions, mule deer can be captured safely without undue risk of hyperthermia. Maximum allowable pursuit time, or time necessary to chase and net a target animal, will vary given existing weather conditions and animal behavior. For example, in warmer conditions (e.g. >4°C), pursuit times will be minimized, particularly if unfavorable snow conditions are present. Total pursuit time will not exceed 8−10 minutes regardless of conditions, and will generally be less than 5 minutes. Individual deer will not be repeatedly chased. Large deer groups typically fracture upon the initial pursuit, thereby preventing the need to repeatedly chase the same individuals while still allowing the capture of >1 deer from the initial group. 92 �The helicopter pilot, fuel truck driver, and handling crew will be in radio contact with one another. In the event of an accident, the Meeker CDOW office will be contacted by radio, and necessary emergency services will be sent to the site. The ground crew will have direct radio access to the Rio Blanco County Sheriffs Office, Colorado State Patrol, and other emergency law enforcement channels. Training and Personnel: The helicopter net-gunning crew will be instructed as to procedures for minimizing stress and injury to the animals. Specifically, they will be instructed on pursuit times, transport distances, and safe handling procedures. The handling crew, comprised of CDOW personnel, will be instructed on proper care and handling procedures to minimize stress and risk of injury to the captured deer. Chad Bishop and Chuck Anderson will be ultimately responsible for all animal care and handling during the capture operation. Procedures and Manipulations of Animals: As stated above, netted animals will immediately be blind-folded, hobbled, and transported to the handling site. At the handling site, deer will be removed from the net and/or transport bag if present, and the blind-fold and hobbles will be checked. Deer will be radiocollared and aged by qualitatively evaluating height and wear of incisors and premolars. Radio collars will be of fixed-size and individually fitted to each animal. The following samples will be obtained from each deer: blood, hind foot length, chest girth, and weight. Blood samples will be collected using routine venipuncture for evaluating serum thyroid hormone concentrations and disease serology. Pregnancy status, number of fetuses, and body condition will also be determined using ultrasonography. Please refer to Appendix II for detailed handling procedures (Appendix II. Use of Ultrasonography and Vaginal Implant Transmitters in Adult Female Mule Deer to Capture Neonatal Fawns). If a captured deer suffers a broken leg, back, neck, pelvis, or other similar wound, it will be euthanized by deep anesthesia with the drug combination of ketamine or Telazol© and xylazine (IV or IM) with dosage based on estimated weight, followed by intravenous administration of KCl (~350 mg KCl/ml sterile water, dosed at >50 mg KCl/kg estimated body mass). In situations where administration of KCl is not feasible, then euthanasia will be performed via a gunshot to the head. Radiocollared mule deer will not be handled following capture, although they will be radiomonitored from both the ground and air on a routine basis. Except during the fawning period, deer will not be routinely relocated from the ground using VHF telemetry and therefore will not be regularly disturbed. During fawning in June, deer will be radiomonitored daily to determine when vaginal implant trasmitters are shed (see Appendix II. Use of Ultrasonography and Vaginal Implant Transmitters in Adult Female Mule Deer to Locate Neonatal Fawns). Literature Cited: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, 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. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2006. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2007. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. 93 �Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Conner, M. C., E. C. Soutiere, and R. A. Lancia. 1987. Drop-netting deer: costs and incidence of capture myopathy. Wildlife Society Bulletin 15:434−438. DelGiudice, G. D., B. A. Sampson, D. W. Kuehn, M. Carstensen Powell, and J. Fieberg. 2005. Understanding margins of safe capture, chemical immobilization, and handling of free-ranging white-tailed deer. Wildlife Society Bulletin 33:677−687. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer Odocoileus virginianus on Anticosti Island, Quebec. The Canadian Field Naturalist 102:697−700. Spraker, T. R. 1993. Stress and capture myopathy in artiodactylids. Pages 481−488 in M. E. Fowler, editor. Zoo and wild animal medicine: current therapy 3. W. B. Saunders, Philadelphia, Pennsylvania, USA. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. White, G. C., and R. M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248−252. 94 �APPENDIX II ULTRASONOGRAPHY AND VAGINAL IMPLANT TRANSMITTER PROTOCOLS FOR ADULT FEMALE MULE DEER AND NEONATAL FAWNS Background: For some time, radio-transmitter implants in the vaginas of deer have been considered as a technique for locating and capturing newborn fawns from radio-collared does immediately following parturition. Early attempts to employ this technique were largely unsuccessful in terms of both effectiveness and animal welfare (Garrott and Bartmann 1984, Giessman and Dalton 1984, Nelson 1984). This early technique used sutures to partially close the vulva in order to retain the transmitter in the vagina. Later, Bowman and Jacobsen (1998) developed and employed a modified vaginal implant transmitter (VIT) for white-tailed deer, with better success. This transmitter had plastic wings encased in silicone to retain the transmitter in the vagina until parturition; thus, no sutures were used. They found no indications that animals were negatively impacted by the newly designed VIT. Recent studies employing VITs have not identified any negative impacts to animals receiving VITs (Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007), including a VIT study on elk focused exclusively on animal welfare (Johnson et al. 2006). Also, these studies do not indicate that VITs cause major problems with in utero fetus survival or birthing, particularly given the success of researchers at finding birth sites and fawns, occasionally from the same adult females over consecutive years. Furthermore, farmed deer in New Zealand with vaginal hormone implants with a similar design have not had any major reproduction problems (Asher and Smith 1987, Asher et al. 1988, Mylrea et al. 1992). Although the current VIT design apparently causes no harm to the animal, animals often expel VITs prior to parturition, which greatly reduces their utility. Thus, to achieve target sample sizes of newborn fawns, investigators must oversample adult females, causing excess animals to be captured, handled, and implanted with VITs. To reduce premature VIT expulsion, Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, lengthened the retention wings in 2004 from 58 mm to 68 mm by adding hard resin to the wing tips, which significantly improved VIT retention (S. P. Haskell, Texas Tech University, unpublished data). Since 2004, researchers employing VITs with the longer wings have not documented any ill effects in deer (ATS, unpublished data). Although retention improved and no ill effects have been observed, this aftermarket modification is not ideal. The modified wing tips are hard because of the resin addition and thus not ideal for placement in the vaginal canal. Ideally, any modification to the VIT wings should be incorporated into the manufacturing process. The retention wings must be manufactured using a production mold that costs a minimum of $15,000 to fabricate. We therefore obtained suitable funding and redesigned the VIT production mold. We lengthened the wing mold from 58 mm to 68 mm, consistent with the aftermarket modifications made to VIT wings beginning in 2004. We also widened the wings from 9 mm to 14 mm to increase the contact surface with the vaginal wall. During spring-summer 2008, we placed 6 prototypes of our newly-manufactured VITs in bighorn sheep ewes at the Foothills Wildlife Research Facility in Fort Collins, CO, where the penned sheep could be closely monitored. We documented no ill effects and all pregnant sheep retained their VITs until parturition. We do not anticipate that our VIT design modifications will pose a risk to animal welfare considering our pilot evaluation in sheep and recent deer studies that employed VITs with aftermarket alterations. In fact, the motivation for developing a new production mold was to improve animal welfare by eliminating the need for aftermarket alterations that create particularly hard wing surfaces. We will monitor fetal survival and neonatal production of all adult female deer receiving VITs to help document whether the newly designed VITs cause any negative effects. We will also monitor survival of the adult females and conduct a thorough necropsy of any deer that die. 95 �Aside from the VIT modifications, the protocols described herein are nearly identical to a protocol approved in the past (CDOW ACUC Project Protocol 1−2002). In this earlier study, we did not document any negative effects to deer associated with ultrasonography or VIT procedures. Also, neonatal fawn survival was higher among fawns captured from adult does that received VITs than fawns captured opportunistically from adult does that did not have VITs (Bishop et al. 2007). Vaginal implants allowed us to remotely monitor adult doe birthing status. If a VIT functioned correctly, we were generally able to capture the adult doe’s fawn(s) with only one disturbance event. In the absence of a VIT, when attempting to capture fawns from a targeted adult doe, we typically had to repeatedly locate and disturb the adult doe during the fawning period to capture her fawn(s). Capture and Transport Technique: Adult female mule deer will be captured in late February and/or early March via helicopter netgunning (Barrett et al. 1982, van Reenen 1982). Please refer to Appendix I. for a detailed helicopter netgunning capture protocol (Appendix I. Helicopter Net-gunning Capture and Handling Protocol for Mule Deer). Net-gunned deer will be blind-folded, hobbled, and ferried a short distance to a handling site. Procedures and Manipulations of Animals: We will use ultrasonography to determine pregnancy status (yes/no), fetal count (# fetuses), and body condition (see below). Additionally, we will measure weight, chest girth, hind foot length, and age (based on tooth replacement and wear). We will collect a blood sample using routine venipuncture. If an adult female is pregnant, we will place a nylon radio-collar around the neck and insert a VIT in the vagina posterior to the cervix. Vaginal implant insertion procedures are explained in detail below. Total handling time for an individual deer will typically be ~15 minutes and will not exceed 25 minutes. We will cease manipulations/data collection at any point the welfare of the deer is in question and immediately begin administering fluids, oxygen, or any other warranted procedure under the guidance of CDOW’s attending veterinarian. Ultrasonography: We will use ultrasonography to determine body condition, diagnose pregnancy, and quantify fetal numbers of each mule deer. Body condition will be measured to meet other research objectives (Anderson and Freddy 2008). Body condition methods are briefly repeated here for completeness. We will measure maximum subcutaneous fat thickness on the rump and thickness of the longissimus dorsi muscle of each doe using a SonoVet 2000 portable ultrasound unit (Universal Medical Systems, Bedford Hills, NY) with a 5 MHz linear transducer (Stephenson et al. 1998, 2002; Cook et al. 2001; Bishop 2007). A small area of hair will be plucked at each measurement point and lubricant will be used to enhance contact between the transducer and skin. The 2 plucked areas will be ≤15 cm long by ≤5 cm wide. We will determine a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001, 2007). We will combine ultrasound measurements with the BCS score to estimate body fat of each deer (Cook et al. 2007). We will quantify reproductive status using a SonoVet 2000 portable ultrasound unit (Universal Medical Systems, Bedford Hills, NY) with a 3 MHz linear transducer. We will shave the left side of the abdomen and apply lubricant to facilitate transabdominal scanning (Stephenson et al. 1995, Bishop 2007, Bishop et al. 2007). Specifically, we will shave an area covering the haired portion of the left ventral abdomen that is 20 cm wide; the area is bounded by the caudal rib cranially, the inguinal fold caudally, and the ventral midline. Both uterine horns will be systematically scanned to identify fetal numbers ranging from 0 to 3. 96 �Vaginal Implant Transmitter (VIT) and Insertion Technique: Refer to the attached study plan for detailed specifications of VITs to be used in this study. Prior to insertion, we will sterilize VITs in a chlorhexidine solution, rinse them with sterile saline solution, allow them to air-dry, and seal them in air- and water-tight pouches. This will guarantee cleanliness of VITs up until the moment they are placed in deer. We will insert VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope is 15.2 cm long with a 1.59 cm internal diameter and has a smoothed end to minimize vaginal trauma. We will gauge approximate insertion distance from extensive experience gained on the Uncompahgre Plateau (Bishop et al. 2007). We will place vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and use a new pair of nitrile surgical gloves to handle the vaginoscope and VIT for each deer, and we will apply a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we will fold the silicone wings together and place the VIT into the end of the vaginoscope. We will liberally apply sterile KY Jelly to the scope and insert it into the vaginal canal until the tip of the VIT antenna is approximately flush with the vulva. We will use the alligator forceps, which extend through the vaginoscope, to firmly hold the VIT in place while the scope is pulled out from the vagina. The tip of the antenna, which may protrude up to 1.5 cm past the vulva, is encapsulated is a resin bead to protect the deer from its sharp edge. Post-Implantation Monitoring: From March through May, we will regularly monitor the radio collar and VIT signals of the adult does in our sample. Monitoring will allow us to document any VITs that shed early and the opportunity to perform a necropsy on mortalities. The latter will allow us to evaluate whether VITs caused any tissue irritation or other impact to the adult doe. Fetus Survival and Neonate Capture: During each morning of June we will check VIT signal status by aerially locating each radiocollared doe having a VIT, weather permitting. We will also radiomonitor VIT signals from the ground as logistically feasible. When we detect a fast (i.e., postpartum) pulse rate, we will use VHF receivers and directional antennae from the ground to simultaneously locate the VIT and radio-collared doe, which should be in proximity to one another. We will attempt to observe behavior of the collared doe, establish whether the VIT is shed at a birth site, and search for fawns in the vicinity of the doe and expelled VIT. If the doe has moved away from the VIT (i.e., >200 m), we will locate the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) were present and subsequently locate the collared doe to search for fawns at her location. We will attempt to account for each doe’s fetus(es) measured in February as live or stillborn fawns. We will not radiocollar or handle newborn fawns. Thus, once a neonate is located, we will back away and leave the neonate undisturbed. If a VIT is shed prior to parturition, we will radiolocate the adult doe no more than once per day on each successive day and search for fawns in an attempt to determine approximately when the doe actually gives birth. This will allow us to determine how many days a VIT shed prematurely. Neonate searches will typically last up to 30−45 minutes and will not exceed 1 hour. Past deer neonatal studies have reported minimal or no abandonment as a result of neonate capture, handling, and marking (Carstensen et al. 2003, Pojar and Bowden 2004, Bishop 2007). Powell et al. (2005) found no evidence of markinginduced abandonment, and they found that handling time and age-at-capture had no impact on neonatal survival. We therefore do not anticipate that our neonate searches will cause any direct or indirect harm to the neonates or their dams, particularly since we will not be handling fawns. 97 �Literature Cited: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. Asher, G. W., and J. F. Smith. 1987. Induction of oestrus and ovulation in farmed fallow deer (Dama dama) by using progesterone and PMSG treatment. Journal of Reproduction and Fertility 81:113−118. Asher, G. W., J. L. Adam, R. W. James, and D. Barnes. 1988. Artificial insemination of farmed fallow deer (Dama dama): fixed-time insemination at a synchronized oestrus. Animal Production 47:487−492. 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. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for Rocky Mountain Elk. Journal of Wildlife Management 65:973−987. Cook, R. C., T. R. Stephenson, W. L. Myers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934−1943. Garrott, R. A, and R. M. Bartmann. 1984. Evaluation of vaginal implants for mule deer. Journal of Wildlife Management 48:646−648. Giessman, N. F., and C. J. Dalton. 1984. White-tailed deer fawn mortality in the southeastern Missouri Ozarks. Missouri Department of Conservation, Jefferson City, Pittman-Robertson Project W-13R-35. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Mylrea, G. E., A. W., English, R. C. Mulley, and G. Evans. 1992. Artificial insemination of farmed chital deer. Pages 334−337 in R. D. Brown, editor. The Biology of Deer. Springer-Verlag, New York, New York, USA. Nelson, T. A. 1984. Production and survival of white-tailed deer fawns on Crab Orchard National Wildlife Refuge. Thesis, Southern Illinois University, Carbondale, IL, USA. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Powell, M. C., G. D. DelGiudice, and B. A. Sampson. 2005. Low risk of marking-induced abandonment in free-ranging white-tailed deer neonates. Wildlife Society Bulletin 33:643−655. 98 �Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557−564. Stephenson, T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717−722. 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. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. 99 �Colorado Division of Wildlife July 2009 − June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2009 − June 30, 2010 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our understanding of factors that limit mule deer (Odocoileus hemionus) populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The most viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not previously possible; however, VITs are often expelled from adult females prepartum, which limits their effectiveness. We redesigned an existing VIT manufactured by Advanced Telemetry Systems (ATS; Isanti, MN) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates and thereby increase likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. We also developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In a similar study using the original VIT wings (Bishop et al. 2007), the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). We expended approximately 12 personhours per detected neonate. As a guide for researchers planning future studies, we found that VIT sample size should approximately equal the targeted neonate sample size. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. 63 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHUCK R. ANDERSON, DANIEL P. WALSH, ERIC J. BERGMAN, PETER KUECHLE, AND JOHN ROTH P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 1. Evaluate rates of VIT retention to parturition and fawn capture success using the newly-designed wings in free-ranging mule deer. 2. Publish findings in Journal of Wildlife Management. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radiolocate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. virginianus; Carstensen et al. 2003, Haskell et al. 2007, Saalfeld and Ditchkoff 2007), black-tailed deer (O. hemionus columbianus; Pamplin 2003), mule deer (Bishop et al. 2007, Haskell et al. 2007), and elk (Cervus elaphus; Johnson et al. 2006, Barbknecht et al. 2009) have been moderately successful. Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sampling bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, distances to roads, fawn ages, and stages of fawning. For example, if roads are used to conduct opportunistic searches, fawn capture probability will decline with increasing distance from a road and neonates will be disproportionately sampled in areas with high road densities. When using VITs, the distribution of radio-marked adult females carrying VITs determines where neonates are sampled. Inferences will be less biased with VITs than with opportunistic capture techniques if all VITs are monitored with equal intensity during fawning and the sample of radio-marked adult females was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. 64 �The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns, especially in mule deer (Johnstone-Yellin et al. 2006, Bishop et al. 2007, Haskell et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although the probability of capturing ≥1 fawn was relatively high (0.792, SE = 0.0847) when VITs shed only 1–3 days prepartum. They noted that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling of adult females would be required in the design of future projects to achieve a target sample size of fawns. That is, extra adult females would need to be sampled to offset those adult females that shed VITs prematurely. Oversampling, in this instance, is undesirable from an animal care and use perspective and unnecessarily expensive. Thus, our objective was to redesign the plastic-silicone retention wings of VITs to allow maximum retention in larger deer species. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used in production of VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used in production of VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs with antennas cut to the appropriate length, Haskell et al. (2007) reported that 81% of VITs (n = 21) in deer were retained until parturition. Retention improved but the aftermarket wing-modification was problematic because the wing tips were hard and thus not ideal for placement in the vaginal canal. That study provided justification to pursue further wing development. We therefore redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on the Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as South Magnolia, StorySprague, Ryan Gulch, and Yellow Creek (Fig. 1). These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). Winter range habitat comprised predominantly pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) and secondarily big sagebrush (Artemisia tridentata), serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus spp.). Drainage bottoms were characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainage bottoms having been converted to irrigated, grass hay fields. Elevations ranged from 1,860 m at Piceance Creek in Ryan Gulch to 2,280 m in Yellow Creek and Story-Sprague study units. Our summer range study area comprised roughly 1,700 km2 across the Roan Plateau and Piceance Basin (Fig. 1). Principal summer range habitat types included aspen (Populus tremuloides), mountain shrub, oakbrush (Quercus gambellii), big sagebrush, and pinyon-juniper. Serviceberry, snowberry (Symphoricarpos spp.), and chokecherry (Prunus virginiana) were common species in mountain shrub communities. Elevation ranged from 2,000 m in Piceance Creek at the mouth of Story Gulch to 2,600 m on Roan Plateau. 65 �METHODS We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the means by which they are attached to the transmitter body (Fig. 2). Specifically, we modified dimensions of the retention wings by lengthening them from 57 mm to 68 mm and widening them from 9 mm to 13 mm. We also added ridges to the wing surface as means to increase probability of retention to parturition. The wings were made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold, which met our target specifications and therefore was deemed acceptable. We then manufactured a production mold, necessary to produce a large number of the wings. We incorporated ejector pins into the VIT design that allow wings to be attached to the VIT transmitter body in the field. In the original design, wings were permanently affixed to the transmitter body during the VIT assembly process. Although we only used one wing size in this study, field-attachment will allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. During late February and early March, 2009, we captured 60 adult female deer utilizing helicopter net guns (Barrett et al. 1982, Krausman et al. 1985, White and Bartmann 1994) in conjunction with ongoing research addressing other objectives (Anderson and Freddy 2008). We captured 20 deer each in Ryan Gulch and Yellow Creek, and 10 deer each in South Magnolia and Story-Sprague study units (Fig. 1). Captured deer were hobbled, blind-folded, and ferried ≤5 km by helicopter to a central handling location. For each captured deer, we used transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop et al. 2007, Bishop et al. 2009). We also measured rump fat depth of each deer using ultrasonography and estimated a body condition score using palpation to estimate percent body fat (Stephenson et al. 2002, Cook et al. 2007). We measured mass by placing each deer on a stretcher and attaching the stretcher to a scale supported by a steel frame. We measured chest girth by placing a cloth tape around the chest immediately posterior to the front shoulders and recording measurement when deer exhaled. Last, we measured hind foot length of each deer and estimated age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957). This aging technique is susceptible to measurement error (Hamlin et al. 2000). However, two trained observers, each with experience aging >1,000 deer in the field, estimated age of all deer in this study to minimize error and to insure that relative age differences across all deer in our sample were correctly captured in the data. We performed handling procedures in a wall-frame tent to create a dim environment for viewing ultrasound imagery. We fitted each pregnant deer with a radiocollar and VIT. Collar transmitters were turned off on Saturdays and Mondays to extend battery life for meeting other research objectives (Anderson and Freddy 2008). Each collar was equipped with a mortality sensor and store-on-board global positioning system (GPS). Mortality sensors were programmed to switch signal transmission from 60 pulses to 120 pulses per minute after remaining motionless for 8 hours. Each VIT had a temperature-sensitive switch and a pre-cut antenna (6 cm in length) with antenna tip encapsulated in a resin bead to eliminate sharp edges. The temperature-sensitive switch caused the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature dropped below 32° C, which was indicative of VIT expulsion. We sterilized VITs in a chlorhexidine solution prior to insertion in the field. We inserted VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The 66 �vaginoscope was 15.2 cm long with a 1.59 cm internal diameter and had a smoothed end to minimize vaginal trauma. We placed vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and used a new pair of surgical gloves to handle the vaginoscope and VIT for each deer, and we applied lidocaine topically to the deer’s vagina to minimize irritation during VIT insertion. To insert a VIT, we folded the wings together and placed the VIT into the end of the vaginoscope. We liberally applied sterile KY Jelly to the scope and inserted it into the vaginal canal until the tip of the VIT antenna was approximately flush with the vulva. We used previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We extended alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope was pulled out from the vagina. During winter and spring, we monitored live-dead status and general location of radiocollared adult females daily from the ground, except when collars were inactive, and biweekly from the air via fixed-wing aircraft. During June, we checked VIT signal status each morning of the week that radiocollars were active by aerially locating each radiocollared doe carrying a VIT. We began flights at approximately 0630 hours and completed them by 0900–1100 hours. Early flights were necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceeded 32° C by mid-day, which caused VITs to switch back to a slow (i.e., prepartum) pulse (Newbolt and Ditchkoff 2009). When we detected a fast (i.e., postpartum) pulse rate, we ground-located the VIT and radiocollared doe in ≤3 hours using very high frequency (VHF) receivers and directional antennae. We attempted to observe behavior of the collared adult female, establish whether the VIT was shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moved away from the VIT (i.e., >200 m), we located the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawns were present and subsequently located the collared dam to search for fawns at her location. We attempted to account for each dam’s fetus(es) as live or stillborn. We typically worked in pairs, which allowed us to effectively partition effort across the study area while maintaining efficiency when searching for neonates (i.e., two people were more effective locating a hidden neonate than one person). We described effort associated with locating fawns by calculating the number of person-hours per fawn. We also quantified cost per fawn by considering all operating and personnel expenses, including capture and VIT costs for adult females. All deer capture and handling procedures and use of VITs were approved by Colorado Division of Wildlife’s (CDOW) Institutional Animal Care and Use Committee (Project # 17-2008). We assigned the fate of each VIT to one of 4 categories: 1) retained (i.e., VIT expelled during parturition), 2) nearly-retained (i.e., VIT expelled ≤3 days prepartum), 3) not retained (i.e., VIT expelled >3 days prepartum), or 4) censored. We considered a VIT to be retained if it was expelled at or near a birth site in conjunction with parturition. For 75% of retention events, we located the VIT at a birth site and located neonate(s) near the VIT or in close proximity to the dam. In other cases, the VIT was not at a birth site but we readily found the dam and her newborn fawn(s) nearby, sometimes at a birth site 10−100 m from the VIT. In these situations, we considered a VIT retained if we documented <1-day-old fawn(s) <24 hours after the VIT was expelled. Finally, on two occasions, we considered a VIT retained because it was located at an evident birth site even though we could not locate fawns. Birth sites appeared as atypically large deer beds with soil appearing damp and with forbs and grasses flattened and radiating outward, consistent with a deer licking the site clean. On some occasions, fawns and/or placental remains were still present at birth sites when we arrived, providing positive confirmation of birth site characteristics. We distinguished VITs expelled ≤3 days prepartum as nearly-retained because they provided useful information for locating fawns, consistent with Bishop et al. (2007). We documented such cases by locating a dam’s neonate(s) one or more days after the VIT was expelled and comparing neonate age to VIT expulsion date. We estimated neonate age using hoof characteristics, condition of the umbilical cord, pelage, and behavior (Haugen and Speake 1958, Robinette et al. 1973, Sams et al. 1996, 67 �Pojar and Bowden 2004). We assumed a VIT was shed >3 days prepartum if the VIT was not at an evident birth site and we documented ≥2 of the following characteristics: 1) the adult female was located with other deer during repeated relocations for >3 days after the VIT was shed, 2) the adult female exhibited no behavioral cues indicating she had a fawn, 3) the adult female was noticeably still pregnant, and 4) we failed to locate a neonate following repeated searches for ≥1 week after the VIT was shed. We censored VITs from our retention analysis when adult females died prior to parturition or when adult females were located on private land that we did not have permission to access. In either case, we were unable to evaluate VIT retention to parturition. All females dying prior to parturition were still carrying the VITs upon death. We modeled VIT retention probability using a generalized logits model (i.e., multinomial logistic regression) in PROC LOGISTIC in SAS (SAS Institute, Cary, NC). We evaluated goodness-of-fit of the global model (i.e., model containing each predictor variable) by dividing model deviance by its degrees of freedom. We considered 3 levels of retention consistent with our description above (i.e., retained, nearlyretained, not retained) and we removed all censors from the dataset prior to analysis. Our primary purpose for this analysis was to evaluate whether our VIT design modifications increased VIT retention probability in larger deer. Our design modifications were based on the observation by Bishop et al. (2007) that VIT retention probability declined as deer body size increased. We modeled VIT retention as a function of mass (kg), hind foot length (cm), chest girth (cm), adult female age (yr), and body fat (%). We considered only linear models because we lacked a rationale for evaluating higher-order polynomial functions. Several of the variables we considered in our analysis were likely correlated because they represented different ways of expressing deer body size. We did not expect models comprising each of these variables to receive more support than simpler models. Thus, we focused our candidate model set on models with one or two variables. We evaluated all single-variable models plus we evaluated twovariable models that included age with each other variable. Age partially related to deer body size but age also related to number of times a female had previously given birth and possibly to behavioral differences among deer, either of which could have influenced retention probability. Thus, age tested hypotheses about retention probability that were not just related to body size or condition. We also considered several models with ≥3 variables to determine whether there was any support for models with higher numbers of parameters. We evaluated 13 models in total and we selected among models using Akaike’s Information Criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We modelaveraged beta parameter estimates to incorporate model selection uncertainty when evaluating whether VIT retention probability varied as a function of the variables in our analysis. We did not model-average real parameter estimates because each of our predictor variables was continuous. We modeled fawn detection probability based on adult females that retained or nearly retained VITs. We planned to conduct separate analyses for singleton and twin litters, but we achieved perfect detection with singleton litters. We therefore modeled fawn detection probability considering only females with twin fetuses using a generalized logits model in SAS, and we evaluated goodness-of-fit by dividing model deviance by its degrees of freedom. We used 3 detection levels (0, 1, 2 fawns) and we modeled detection as a function of VIT retention status (retained vs. nearly-retained), VIT shed-day, adult female age, and vegetative cover at VIT expulsion site. Shed-day distinguished between VITs detected on fast pulse on Sundays and Tuesdays (dummy code = 1) and VITs detected on fast pulse during Wednesday−Friday (dummy code = 0). We used the shed-day variable to evaluate whether delayed response time, caused by our inability to monitor deer on Saturdays and Mondays, influenced our ability to detect fawns. We included adult female age in our analysis to evaluate if older females may have been more experienced at hiding fawns. Last, we used vegetative cover to evaluate if fawns were more difficult to detect in heavier cover. We expressed vegetative cover categorically as low, medium, or high based on a visual assessment at the site. Low cover class was characterized by limited understory and overstory vegetation with minimal visual obstruction at ground level (e.g., sparsely-vegetated grass, sagebrush, or mountain shrub slopes). Medium cover class was characterized by moderate to heavy 68 �vegetative cover within 1 m of the ground but limited cover above 1 m (e.g., typical sagebrush, mountain shrub sites). High cover class comprised moderate to heavy vegetative cover from ground level up to > 1 m with nearly complete visual obstruction (e.g., oakbrush, aspen-mountain shrub, dense serviceberry). We evaluated all single-variable models in addition to 4 models with ≥2 variables to determine whether there was any support for models with higher numbers of parameters. We evaluated 9 models in total and we selected among models using Akaike’s Information Criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We did not model-average parameter estimates because it would have resulted in 10 different estimates of each level of fawn detection probability for a total of 30 probability estimates. These differences were not supported by the model selection results. We used our VIT retention and fawn detection probabilities to guide calculation of VIT sample sizes for planning future neonatal studies. We expressed the expected number of neonates to be encountered from a sample of VITs as: , where n N ,30 n v1r s SAdF RvlT TAdF P 1 1r1.vins P21r ,.vms P1 1Si ngl. = neonate sample size. = sample size of adult females with VITs. = probability an adult female survives to parturition and is accessible. = probability an adult female retains her VIT to within 3 days of parturition given she survives to parturition and is accessible (i.e., VIT is retained or nearly retained). = probability adult female has twin fetuses. = probability 1 fawn is detected given an adult female retains her VIT and has twin fetuses. = probability 2 fawns are detected given an adult female retains her VIT and has twin fetuses. = probability 1 fawn is detected given an adult female retains her VIT and has one fetus. Since we had perfect detection with singleton litters and observed a high probability of detecting at least 1 fawn from twin litters, we simplified the above equation to: where is the probability of detecting at least 1 fawn, irrespective of litter size. Thus, given a targeted sample size of neonates, the estimated number of VITs required can be calculated as: We incorporated our estimates into the above equation to provide guidance for planning future studies. RESULTS AND DISCUSSION A retention wing of 1 VIT snapped at its base when the wings were squeezed together for placement into a vaginoscope, prior to insertion into a deer. No other retention wings exhibited any 69 �cracking or weakness when squeezed together, even after VITs were recovered from animals during spring and summer. Thus, we found this to be an isolated incident, and our resulting sample size was 59 deer with VITs. The probability that an adult female receiving a VIT in winter survived to parturition and was accessible (SAdF) was 0.797 (SE = 0.0529). We observed 9 adult female mortalities during winter and spring, and there was no evidence to suggest VITs were related to the mortality events. Four of the mortalities occurred within 1 week of capture and were likely capture-related. We were unable to groundmonitor 2 other adult females during the fawning period because they were located on private land that we did not have permission to access. One other adult female was inadvertently deleted from the aerial monitoring list due to miscommunication. We censored these 12 deer from our analysis of VIT retention because they did not permit evaluation of VIT retention to parturition, resulting in a sample size of 47 deer. Our global model of VIT retention probability (k = 12) adequately fit the data (deviance/df = 0.670, P = 0.991). The model of VIT retention probability with the lowest AICc included only the intercept (k = 2, ∆AICc = 0.00, wi = 0.331), although the model with deer age received some support (k = 4, ∆AICc = 1.42, wi = 0.163; Table 1). There was slight evidence that retention probability was lower in older deer ( = 0.169, SE = 0.256; Fig. 3). Also, there was slight evidence that retention probability was lower in larger deer ( = 0.086, SE = 0.171; Table 1). Based on the intercept-only model, the probability of a VIT being expelled during parturition (i.e., retained) was 0.766 (SE = 0.0605) and the probability of a VIT being expelled ≤3 days prepartum (i.e., nearly-retained) was 0.128 (SE = 0.0477). Thus, the probability of a VIT being retained to within 3 days of parturition (RVIT) was 0.894 (SE = 0.0441). Our global model of fawn detection probability (k = 12) adequately fit the data (deviance/df = 0.846, P = 0.730). The model of fawn detection probability with the lowest AICc included only the intercept (k = 2, ∆AICc = 0.00, wi = 0.600), whereas the model with the next lowest AICc included the VIT shed-day variable (k = 4, ∆AICc = 1.80, wi = 0.244; Table 2). Thus, we observed some evidence that fawn detection probability was influenced by our inability to monitor deer 2 days of the week (f1sh ,3d - da y,si n9 l ,3ron = 0.537, SE = 0.738). The probability of detecting twins was 0.688 (SE = 0.114) when we located adult females <24 hours after their VITs switched to fast pulse, whereas twin detection probability was 0.500 (SE = 0.115) when our response time was delayed due to irregular monitoring. There was no evidence that probability of fawn detection was influenced by dam age or vegetative cover. Also, fawn detection probability did not meaningfully differ between females with retained and nearlyretained VITs. We detected 58 neonates and 2 stillborns from 42 adult females (1.4 neonates/female) that retained or nearly retained VITs. We detected a neonate from each adult female that had 1 fetus (P11Singl. = 1.0 , n = 8). For adult females with twin fetuses (n = 34), based on the intercept-only model, the probability of detecting 1 neonate (P 1 1Tw i n.s) was 0.353 (SE = 0.0803) and the probability of detecting twins (P21T 1,vin.s) was 0.588 (SE = 0.0827). Combining litter sizes, the probability of detecting at least 1 ) was 0.952 (SE = 0.0334). The probability of an adult female having twin fetuses (TAdF) neonate ( was 0.810 (SE = 0.0613). On average, we located one neonate or stillborn per VIT in our initial sample (nNeo = 60, nVITs = 59). Thus, inputting our estimates into our sample size equation, we found that VIT sample size should roughly equal the targeted neonate sample size: E [n N. ol E [n N. ol n vir , = (0.80 )(0.89) [0.95 + (0.81)(0.59)] = 1.02 70 �We expended roughly 700 person-hours during the fawning period to locate 58 neonates and 2 stillborns, or approximately 12 person-hours per fawn located. This estimate includes hours spent searching for fawns from adult females that expelled VITs >3 days prepartum, although we were never successful in these attempts. We expended $31,000 to net-gun our sample of adult females, $15,000 on VITs, $10,000 on fixed wing monitoring, and $20,000 on personnel. Thus, we expended approximately $1,267 per neonate located. We did not include adult female radio collars in this cost estimate because we used GPS collars to meet other research objectives, yet VHF collars would have sufficed for locating neonates. Assuming VHF collars were used on adult females at a rate of $250 per collar, our cost estimate is approximately $1,520 per fawn. Our wing modification increased VIT retention in adult female mule deer. Our results are consistent with Haskell et al. (2007), who observed 81% retention (17/21) in the final year of their study after lengthening VIT wings and preventing antennas from protruding >1 cm past the vulva. Our study expanded on Haskell et al. (2007) by incorporating VIT wing modifications into the manufacturing process and conducting a focused field evaluation of those modifications. Investigators using the original VIT wing design in mule deer observed much lower rates of retention than we observed (Johnstone-Yellin et al. 2006, Bishop et al. 2007, Haskell et al. 2007). Using the original design, Bishop et al. (2007) found that the probability of VIT expulsion during parturition was 0.447 (SE = 0.0468), and the probability of VIT expulsion during parturition or ≤3 days prepartum was 0.623 (SE = 0.0456). We employed the same methodology as Bishop et al. (2007), except for the wing modification. Our study area was 100 km north of where Bishop et al. (2007) conducted their study. Assuming the 2 studies are comparable, our wing modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). The intercept-only model of VIT retention probability received the most Akaike weight, which is partly a reflection of our limited sample size. However, overall high rates of retention likely explain why we did not observe any strong relationships between VIT retention and deer body size. Bishop et al. (2007) found that larger deer were more likely to expel VITs prematurely, which was our basis for modifying VIT wings and conducting this study. Our results suggest the wing modifications effectively reduced premature expulsion, particularly in larger deer (Fig. 4). We documented a high probability of detecting at least 1 fawn from adult females that retained or nearly retained VITs, regardless of litter size. When a VIT was shed and evidence suggested the adult female was near parturition or had already given birth, we conducted intense searches up to 1 hour in length for successive days until a fawn was found. Thus, irrespective of vegetative cover or other covariates we assessed, we usually found a fawn when a VIT was adequately retained because it focused our search effort. Our likelihood of detecting twins was somewhat lower, in part because of our irregular monitoring schedule. However, other factors explain why twin detection probability was lower. First, our search intensity decreased when searching for a second fawn. For example, if we had searched most of an hour before detecting the first fawn, we typically limited our search time for a second fawn to minimize our disturbance to the adult female. Second, we did not place radio collars on fawns, and therefore, we could not relocate radiocollared fawns to search for their siblings. The technique of relocating a radiocollared fawn to locate its sibling was found to be successful in a previous study in Colorado (Bishop et al. 2009). During this earlier study, when a dam was known to have twin fetuses yet only one fawn was located and radiocollared during the initial capture attempt, the sibling fawn was found 45% of the time (10/22) by relocating the initial radiocollared fawn 1−2 days post-capture (C. J. Bishop, CDOW, unpublished data). Based on this rate, we would expect our probability of detecting both fawns from twin litters to be roughly 0.77 had we radiocollared fawns during our study. We found that our sample size of detected neonates roughly equaled our sample size of VITs, which provides a useful guide for planning future research using our modified wing design. However, 71 �this recommendation may overestimate VIT sample size because of our lower rate of twin detection and because adult female survival was lower than we anticipated. Fortunately, accessibility of adult females was higher than expected considering we lacked permission to access a large tract of land in the middle of summer range. Bishop et al. (2007) observed 0.97 survival of adult females to parturition and 0.99 were accessible during fawning (SAdF = 0.95). Adult female survival and accessibility is specific to study area. Twinning probability may also vary regionally. We therefore recommend use of the following equation for planning VIT sample size that incorporates information specific to the study area or region of interest: E[n Naol Bishop et al. (2007) expended 7 person-hours per captured fawn from adult females with successful VITs, 16 person-hours per fawn from females with partially successful VITs, and 42 personhours per fawn from females with failed VITs and females not receiving VITs. Given their observed VIT success rates, Bishop et al. (2007) would have required approximately 1,315 person-hours to locate 60 neonates, or 22 person-hours per fawn. Assuming these studies are comparable, increased VIT success associated with our modified wing design resulted in a 45% reduction in labor required to locate a fawn from a radiocollared adult female. The VIT technique is effective but expensive to employ. Actual cost of the technique, however, depends on what costs are already incurred to meet other research objectives. For example, in Colorado and elsewhere, researchers have begun estimating late-winter deer body condition as a response variable to accompany survival estimates. In these cases, adult female capture and radio collar costs are already accounted for in the base study, and thus, incorporation of VITs to facilitate neonate capture becomes much more cost-effective. In our study, where adult female capture and collar costs were covered by ongoing research efforts, the added cost of incorporating VITs and neonate capture was $750 per fawn. SUMMARY Use of VITs in well-designed field studies should increase our understanding of factors limiting deer populations by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. The question remains as to whether premature expulsion of VITs can be eliminated in mule deer. We observed modest evidence that deer expelling VITs >3 days prepartum were older and larger than deer that retained or nearly-retained VITs. We therefore recommend manufacturing slightly larger wings for large, older mule deer (e.g., >65 kg and >5 yrs old) as a possible strategy to further investigate VIT retention. LITERATURE CITED Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. 72 �Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. Barbknecht, A. E., W. S. Fairbanks, J. D. Rogerson, E. J. Maichak, and L. L. Meadows. 2009. Effectiveness of vaginal-implant transmitters for locating elk parturition sites. Journal of Wildlife Management 73:144−148. 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. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. 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Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71−73. Newbolt, C. H., and S. S. Ditchkoff. 2009. Effects of environmental conditions on performance of vaginal implant transmitters. Journal of Wildlife Management 73:303−305. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., C. H. Baer, R. E. Pillmore, and C. E. Knittle. 1973. Effects of nutritional change on captive mule deer. Journal of Wildlife Management 37:312−326. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. 73 �Saalfeld, S. T., and S. S. Ditchkoff. 2007. Survival of neonatal white-tailed deer in an exurban population. Journal of Wildlife Management 71:940−944. Sams, M. G., R. L. Lochmiller, E. C. Hellgren, W. D. Warde, and L. W. Varner. 1996. Morphometric predictors of neonatal age for white-tailed deer. Wildlife Society Bulletin 24:53−57. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557−564. 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. White, G. C., and R. M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248−252. 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 _______________________ Chad J. Bishop, Mammals Research Leader 74 �Figure 1. Location of winter and summer range study areas in Piceance Basin and Roan Plateau, northwest Colorado. Winter range study units where we captured and radio-marked mule deer are noted as: YC = Yellow Creek, RG = Ryan Gulch, SM = South Magnolia, and SS = Story-Sprague. 75 �A B 60° (2) R 278 (2) - - - - 1.000 - - --, ,871 0 .581 2'18 (2) ORE 040 ,640 (2) NOMI NAL 743 (2) I R 139 (2) 1 740 :21 17 ~ - - - - - - - - - 2.67-3 f68 ITT[Jlj - - - - - - - - ---1 Figure 2. Three-dimensional view (A) and dimensions (B) of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions at bottom include a nylon core with an elastomeric overmold that protects deer from any sharp or rigid edges. 76 �- - - - - - - - - - -- --- - - - - ----' 1 0.9 C 0 0.8 ' ' +"' C QJ 0.7 +"' QJ I,.. I- 0.6 > 0.5 0 > +"' 0.4 .c re .c 0.3 0 I,.. c.. ' ' ' '' '' 0.2 0.1 '' '' 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 '' 8.5 Deer age (yr) Figure 3. Estimated probability and 95% confidence interval of adult female mule deer retaining vaginal implant transmitters (VITs) to within 3 days of parturition as a function of deer age in northwest Colorado. 77 9.5 �--- - ----------------~- _______ ... -------- 1 0.9 0.8 - - - -..... ..... ..... C: .2 +C: 0.7 ' ' Q) +- ... Q) 0.6 I- > 0.5 0 >, :!::: .c ('Cl .c ...0 a. 0.4 0.3 0.2 0.1 0 50 55 65 60 70 75 80 Deer body mass (kg) Figure 4. Estimated probabilities and 95% confidence intervals of adult female mule deer retaining vaginal implant transmitters (VITs) to within 3 days of parturition as a function of deer body mass in Colorado using original (solid line, Bishop et al. 2007) and modified (dashed line, this study) VIT retention wings. 78 �Table 1. Model selection results, based on Akaike’s Information Criterion with small sample size correction (AICc), from an analysis of vaginal implant transmitter (VIT) retention in adult female mule deer as a function of adult female age (yr), mass (kg), hind foot length (cm), chest girth (cm), and body fat (%) in northwest Colorado, USA, 2009. Model k AICc ∆AICc wi Intercept only 2 70.58 0.00 0.331 Age 4 72.00 1.42 0.163 Foot length 4 72.88 2.30 0.105 Age, fat 6 72.96 2.39 0.100 Mass 4 73.57 2.99 0.074 Fat 4 73.66 3.08 0.071 Chest girth 4 73.79 3.21 0.066 Age, chest girth 6 75.10 4.52 0.035 Age, foot length 6 75.45 4.88 0.029 Age, mass 6 76.32 5.74 0.019 Age, foot length, chest girth 8 78.53 7.95 0.006 79 �Table 2. Model selection results, based on Akaike’s Information Criterion with small sample size correction (AICc), from an analysis of fawn detection probability associated with adult females that retained or nearly-retained vaginal implant transmitters (VITs) in northwest Colorado, 2009. We modeled detection probability as a function of VIT retention status (retained vs. nearly-retained), adult female age (yr), the day of the week VITs were shed (i.e., shed-day), and amount of vegetative cover at VIT shed sites. We evaluated detection probability relative to shed day because we were unable to monitor radio signals on Saturdays and Mondays. Model k AICc ∆AICc wi Intercept only 2 61.94 0.00 0.600 Shed-day 4 63.74 1.80 0.244 Retention status 4 66.07 4.13 0.076 Age 4 66.26 4.32 0.069 Cover 6 70.46 8.52 0.008 Shed-day, cover 8 73.22 11.28 0.002 Shed-day, cover, retention status 10 79.53 17.59 0.000 Age, shed-day, cover 10 80.24 18.30 0.000 80 �Colorado Division of Parks and Wildlife July 2010 − June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2010 − June 30, 2011 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed all field work on this project and prepared draft manuscripts for publication prior to FY 10-11. As explained in our Segment Narrative for FY 10-11, our final objective for this project was to publish results of the study in Journal of Wildlife Management (JWM). Our manuscript was accepted for publication in JWM on March 23, 2011. The manuscript will be published in the November 2011 issue of JWM. 71 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHARLES R. ANDERSON, JR., DANIEL P. WALSH, ERIC J. BERGMAN, PETER KUECHLE, AND JOHN ROTH P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 6. Publish findings in Journal of Wildlife Management. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radiolocate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. virginianus; Carstensen et al. 2003, Haskell et al. 2007, Saalfeld and Ditchkoff 2007), black-tailed deer (O. hemionus columbianus; Pamplin 2003), mule deer (Bishop et al. 2007, Haskell et al. 2007), and elk (Cervus elaphus; Johnson et al. 2006, Barbknecht et al. 2009) have been moderately successful. Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sampling bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, distances to roads, fawn ages, and stages of fawning. For example, if roads are used to conduct opportunistic searches, fawn capture probability will decline with increasing distance from a road and neonates will be disproportionately sampled in areas with high road densities. When using VITs, the distribution of radio-marked adult females carrying VITs determines where neonates are sampled. Inferences will be less biased with VITs than with opportunistic capture techniques if all VITs are monitored with equal intensity during fawning and the sample of radio-marked adult females was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns, especially in mule deer (Johnstone-Yellin et al. 2006, 72 �Bishop et al. 2007, Haskell et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although the probability of capturing ≥1 fawn was relatively high (0.792, SE = 0.0847) when VITs shed only 1–3 days prepartum. They noted that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling of adult females would be required in the design of future projects to achieve a target sample size of fawns. That is, extra adult females would need to be sampled to offset those adult females that shed VITs prematurely. Oversampling, in this instance, is undesirable from an animal care and use perspective and unnecessarily expensive. Thus, our objective was to redesign the plastic-silicone retention wings of VITs to allow maximum retention in larger deer species. Prior to our study, the wings used to retain VITs had been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used in production of VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used in production of VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs with antennas cut to the appropriate length, Haskell et al. (2007) reported that 81% of VITs (n = 21) in deer were retained until parturition. Retention improved but the aftermarket wingmodification was problematic because the wing tips were hard and thus not ideal for placement in the vaginal canal. That study provided justification to pursue further wing development. We therefore redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on the Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as South Magnolia, StorySprague, Ryan Gulch, and Yellow Creek (Fig. 1). METHODS We prepared and submitted a draft manuscript to Journal of Wildlife Management (JWM). Initial reviews were favorable, and thus, we were invited to submit a revised manuscript for further consideration. We prepared a revised manuscript based on comments submitted by peer reviewers and the associate editor. RESULTS AND DISCUSSION Our revised manuscript was accepted for publication on March 23, 2011. The manuscript will be published in the November 2011 issue of JWM. The abstract from this publication follows: Our understanding of factors that limit mule deer (Odocoileus hemionus) populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The most viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant 73 �transmitters (VITs). To date, VITs have allowed research opportunities that were not previously possible; however, VITs are often expelled from adult females prepartum, which limits their effectiveness. We redesigned an existing VIT manufactured by Advanced Telemetry Systems (ATS; Isanti, MN) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates and thereby increase the likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. We also developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In a similar study using the original VIT wings (Bishop et al. 2007), the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). We expended approximately 12 personhours per detected neonate. As a guide for researchers planning future studies, we found that VIT sample size should approximately equal the targeted neonate sample size. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. The full text publication can be obtained electronically or in hard copy through JWM and WileyBlackwell Publishers. SUMMARY Use of VITs in well-designed field studies should increase our understanding of factors limiting deer populations by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. The question remains as to whether premature expulsion of VITs can be eliminated in mule deer. We observed modest evidence that deer expelling VITs >3 days prepartum were older and larger than deer that retained or nearly-retained VITs. We therefore recommend manufacturing slightly larger wings for large, older mule deer (e.g., >65 kg and >5 yrs old) as a possible strategy to further investigate VIT retention. An article documenting our research findings will be published in the November 2011 issue of JWM. 74 �LITERATURE CITED Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. Barbknecht, A. E., W. S. Fairbanks, J. D. Rogerson, E. J. Maichak, and L. L. Meadows. 2009. Effectiveness of vaginal-implant transmitters for locating elk parturition sites. Journal of Wildlife Management 73:144−148. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Haskell, S. P., W. B. Ballard, D. A. Butler, N. M. Tatman, M. C. Wallace, C. O. Kochanny, and O. J. Alcumbrac. 2007. Observations on capturing and aging deer fawns. Journal of Mammalogy 88:1482−1487. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Saalfeld, S. T., and S. S. Ditchkoff. 2007. Survival of neonatal white-tailed deer in an exurban population. Journal of Wildlife Management 71:940−944. 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 _______________________ Chad J. Bishop, Mammals Research Leader 75 �Figure 1. Location of winter and summer range study areas in Piceance Basin and Roan Plateau, northwest Colorado. Winter range study units where we captured and radio-marked mule deer are noted as: YC = Yellow Creek, RG = Ryan Gulch, SM = South Magnolia, and SS = Story-Sprague. 76 � https://cpw.cvlcollections.org/files/original/7275825e22516664628adf03224d1631.pdf 551222294d28fd64eab2f0081020dea7 PDF Text Text Colorado Division of Parks and Wildlife July 2016 - June 2017 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3002 1 W-242-R2 : : : : : : Division of Parks and Wildlife Mammals Research Pilot Study—Elk Recruitment and Habitat Use in Colorado Period Covered: July 1, 2016 - June 30, 2017 Author: M.W. Alldredge, B. Banulis, and A. Vitt Personnel: R. DeVergie, L. Snobl, T. Stratman, A. Orlando, W. Hiler, A. Meyer, N. Collier, B. Hoffman, K. Botzet, S. Stevens, L. Sweanor, T. Verzuh All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our principal research objective was to assess elk recruitment rates in southern Colorado, where declining December calf:cow ratios have been observed since the early 2000’s. We initiated this study this year in elk Data Analysis Units (DAUs) E-20 and E-33 as these areas consistently had the lowest calf:cow ratios. Our objective is to determine major factors that may be contributing to low recruitment in order to direct future research activities. Therefore, we are examining this from both the cow productivity standpoint and in terms of calf mortality. In February and March, 2017, 30 adult cow elk were captured in each area (23 collared), to assess pregnancy rates and body condition. Starting in May, 2017, we also captured and fitted at least 40 neonate elk in each study area with GPS collars to assess cause specific mortality rates and recruitment to the yearling age class. Body condition in both study areas was reasonable given the time of year and pregnancy rates were 78.1% in E-20 and 90.0% in E-33. By June 20, 2017, a total of 40 calves had been captured in E-20 and 55 in E-33. 1 �WILDLIFE RESEARCH REPORT PILOT STUDY—ELK RECRUITMENT AND HABITAT USE IN COLORADO MATHEW W. ALLDREDGE PROJECT NARRITIVE OBJECTIVES 1. To assess adult cow elk (Cervus canadensis) body condition and pregnancy rates in two different elk populations, DAUs E-20 and E-33, in southern Colorado. 2. Assess cause specific calf mortality and recruitment into the yearling age class for two different elk populations, E-20 and E-33, in southern Colorado. 3. Assess cow and calf habitat use in relation to body condition and survival. SEGMENT OBJECTIVES Elk Recruitment 1. Measure body condition, pregnancy and fetal rates for cow elk within each study area. 2. Measure calf elk weight at parturition and relate this to the dam’s body condition and whether she had a calf the previous year. 3. Determine cause specific mortality for elk calves from birth to age one. 4. Examine cow elk habitat use, including use of habitat treatments in the study area. ELK RECRUITMENT BY M. ALLDREDGE INTRODUCTION Rocky Mountain Elk (Cervus elaphus) is an iconic species throughout western North America and especially in Colorado, with a high recreational value to hunters, photographers, artists and wildlife enthusiasts in general. Elk populations are known to fluctuate greatly following habitat succession, especially following historic wildfires. Human exploitation, habitat loss, predation and disease are all factors that can lead to population declines. In order to maintain healthy populations, managers must understand these factors and use their best knowledge to set herd objectives, harvest strategies and monitoring programs. Population dynamics of ungulates, including elk, are generally characterized by relatively constant adult survival and variable recruitment (Gaillard et al. 1998, Garrott et al. 2003, White et al. 2010, Proffitt et al. 2014). Eberhardt (2002), when examining large herbivore populations, suggested that juvenile survival is the first parameter expected to change as populations decline. Variability in recruitment rates can manifest in a variety of ways, including pregnancy rates, intra-uterine survival, neonate survival and over-winter survival (Proffitt et al. 2014). Pregnancy rates can be a function of environmental conditions or nutrition and its influence on body condition (Cook et al. 2004). Survival of neonates can be affected by summer temperature, precipitation, predation, population density (White et al. 2010, Griffin et al. 2011) and human disturbance (Phillips and Alldredge 2000). Malnutrition is also a factor that contributes to over-winter mortality (Proffitt et al. 2014). 2 �Concerns about elk calf ratios have been expressed for about a decade, but factors influencing local populations remain largely unknown. During the 1990’s and early 2000’s, elk herds were above objective and efforts were made to reduce elk populations. Calf ratios started declining in the early 2000’s while herds were generally still above objective. Many studies have been conducted to investigate environmental influences on elk, many of which center around juvenile recruitment (Alldredge and Phillips 2000, White et al. 2010, Sargeant et al. 2011, Cook et al. 2013, Proffitt et al. 2014). Colorado is no exception, in many parts of the state recruitment rates are low and declining, which will have long term ramifications on elk populations across the state. Colorado Parks and Wildlife (CPW) has defined numerous elk data analysis units (DAUs) across the state delineating specific elk populations for management objectives and monitoring purposes (Figure 1). Early winter surveys are conducted within each DAU annually in order to obtain population parameters, such as cow:calf:bull ratios, in order to model population size. In general, these data are showing lower and declining cow:calf ratios in the southern portion of the state compared to the northern part of the state since 1994 and especially since the early 2000s (Figures 2 and 3). Annual variation in cow:calf ratios exists but a steady decline for the southern DAUs is also evident with current ratios approaching or below 30 calves per 100 cows (Figure 2). Similar annual variability exists in the northern DAUs, but the declining pattern is not evident and cow:calf ratios are higher, currently above 50 calves per 100 cows in the DAUs presented. Low recruitment rates for elk across the state and potential long term population level ramifications are of great concern to CPW wildlife managers and biologists. If the trend of low recruitment rates continues, resulting declining elk populations will significantly impact both recreational opportunity and economics in Colorado and for CPW. Furthermore, CPW has a statutory responsibility to manage elk. However, very little is known as to the factors driving declining recruitment rates. Research on this topic is vital. A recent study on mule deer (Odocoileus hemionus) has demonstrated a paradigm shift in causes of low recruitment for this species from the historical research demonstrating low over-winter survival (Bartmann et al. 1992) to recent developments suggesting low neonatal survival (Anderson 2015). It is imperative that CPW conduct similar investigations on elk to gain information on factors affecting low recruitment across the state and develop management strategies to mitigate these factors. Because little is known about the factors affecting elk recruitment in the state, we proposed a pilot study designed to identify primary factors. Given that this low recruitment is occurring across a broad spatial scale we also proposed that this work be conducted in multiple study areas exhibiting low recruitment and one study area with higher recruitment as a reference area. The intent of this 2 year pilot study is to determine pregnancy rates, fetal counts, and cause specific mortality of calf elk from birth to age 1. Additional data on cow body condition, birth weights and consecutive year reproduction will allow determination of potential causes of low elk recruitment. Measuring individual body condition of cow elk in the study and then ascertaining the fate of each cow’s calf will provide valuable insights regarding nutritional influences on both calf survival and future pregnancy rates. Examinations of cow elk habitat use will also be conducted, including use of habitat treatments that exist on the landscape, to determine differences in habitat use and the impact that has on pregnancy rates and calf survival. Information from this pilot study will provide insights into factors that are affecting elk recruitment throughout Colorado and potentially throughout many western states. This information will be used to direct future research and management implementation to mitigate factors contributing to low elk recruitment. These factors may include but are not limited to; habitat quality and poor nutrition, neonate predation, disease and/or human disturbance. The results from this pilot project will direct future hypotheses regarding declining calf ratios and future direction of work, such as: 3 �High pregnancy rates: indicates high dam nutrition and reduces evidence of nutritional stress Hypothesis: Poor neonate survival. Low pregnancy rates and poor body condition: indicates nutritional stress for dam, reduced evidence that calf survival is limiting. Hypothesis: Summer nutrition is limiting herd productivity. Low neonatal survival and low predator specific mortality: indicates habitat limitation. Hypothesis: Poor neonate survival is caused by habitat limitation. Low neonatal survival and high predator specific mortality: indicates predator limitation. Hypothesis: High neonatal predation is limiting populations. Results indicating habitat limitations could lead to future studies that examine habitat manipulations/improvement and/or studies that examine reductions in herd size. Results indicating poor neonate survival could lead to studies that will examine cause specific mortality to determine the drivers of low calf survival. If predation appears to be a limiting factor then future studies could examine the effects of predator manipulations on neonate survival. If other factors are limiting calf survival then specific studies will be designed to examine these limitations (disease, habitat, etc.) and what manipulations can be done to improve neonate survival. STUDY AREA This project is designed to examine low elk recruitment issues statewide. Given the broad scale issue, two study areas with low elk recruitment were selected and, if funding permits, one area will be selected as a reference area where elk recruitment is high following the 2-year pilot phase. In conjunction with other work in the state, pregnancy rates are being monitored in areas where recruitment is high. The two study areas in the southern part of the state with low recruitment rates targeted during the pilot phase are DAUs E-20 and E-33. E-20 E-20 is the Uncompahgre Plateau area with game management units (GMU) 61 and 62. These GMUs are in Montrose, Mesa, Delta, San Miguel and Ouray counties encompassing 2,262 square miles. Elevations range from 4,600 feet to 10,300 feet. The area is characterized by flat mesas and deep rugged canyons. Vegetation includes grassland, shrub, pinon/juniper, pine, aspen, and spruce/fir. Land ownership includes private, BLM, US Forest Service and state. E-33 E-33 is the La Veta/Trinidad area with game management units (GMU) 140, 85, and 851. GMU 140 is in Las Animas County on the New Mexico border. Elevations range from 5,414 to 9,544 feet. The area is characterized by gently rolling hills, steep canyons and mesas. Vegetation includes shortgrass prairie, pinion pine, oak and spruce/fir. Approximately 99% of the land is privately owned. GMU 85 is located in Huerfano and Las Animas counties. Elevations range from 6,025 feet to 13,518 feet. The area is characterized by flat valley bottoms, foothills and steep mountains. Vegetation includes grassland, pinon/juniper, pine/oak, spruce/fir, and alpine. Approximately 75% of the area is privately owned. GMU 851 is in Las Animas county and is bordered on the south by New Mexico. Elevations range from 6,025 to 14,000 feet. The area is characterized foothills and steep mountains. Vegetation includes grassland, pine, spruce/fir, aspen, and alpine. Approximately 98% of the area is privately owned. 4 �METHODS Cow Capture and Sampling Cow elk will be captured in January using clover traps, free-range darting, and helicopter net gunning following approved elk capture and handling guidelines (CPW ACUC #09-2008) (Appendix I). Darting and clover traps will be used initially to capture elk and net gunning will be used if necessary to complete the sample of at least 20 collared cow elk per study area and body condition on 30 elk per study area. Fetal counts and body condition will be assessed for all collared elk using ultrasound. Multiple bait sites will be placed within each study area to attract elk prior to capture. Elk will be darted or clover trapped at these sites. Only 2 to 3 elk will be collared at each bait site. Additional animals will be eartagged and blood will be drawn to estimate pregnancy rates before release. Pregnant females equipped with telemetry collars on winter range will also be equipped with vaginal implant transmitters (VITs; Neolink-ITX, Advanced Telemetry Systems, Isanti, MN, USA) to facilitate spring neonate capture and collaring efforts following birth on summer range. Neonate Capture GPS collars on cow elk will send an alert and a location when a VIT is expelled. Once expelled, field crews will be directed to birth site locations to locate and capture newborn calves. In order to minimize human disturbance, neonate searches will typically last 3045 minutes and will not exceed 1 hour. Uncollared pregnant cows will also be observed in an attempt to opportunistically locate and collar additional calves. Each neonate will be handled with sterile nitrile latex gloves to minimize the transfer of human scent, blindfolded, and placed in a cloth bag to measure body mass. Hind foot length, chest girth, age (days), and gender will also be recorded. Each neonate will be fitted with an expandable GPScollar (Wildlink-GTX Globalstar GPS Collar, ATS, Isanti MN, USA) with a 4 hour mortality sensor that is designed to drop off after 12 months. Handling time will be ≤ 5 minutes and neonates will be placed in the precise location where they were located to minimize abandonment. Neonate telemetry signals will be monitored daily using GPS satellite communication. Continuous monitoring will afford us the ability to detect mortalities and assess cause specific mortality within 24 hours. Monitoring of neonate signals will continue throughout the year or until mortality occurs. Once a mortality is detected, neonates and/or collars will be located from the ground and if any part of a carcass is present a thorough field necropsy will be conducted to determine cause of death. Data Analysis Pregnancy rates will be compared among study areas, years and possibly to historic data using a binomial variance. Body condition and age class will be treated as covariates in the analysis. Longitudinal data will also be examined to determine the affects of previous years’ pregnancy status on pregnancy rate, body condition and birth weights. We will also use individual body condition to estimate the animal indicated carrying capacity following Monteith et al. (2014). Low pregnancy rates and/or poor body condition will lead us to consider future habitat manipulations or elk population reductions as a means to improve herd productivity. Pregnancy rates from blood samples of captured cows in the NW, where recruitment is higher, were estimated at 0.92 in December 2015. The binomial power to detect a decrease from this baseline rate of 0.15, using a sample size of 30, is 0.78. A minimum of 20 animals is necessary to detect a 1.5% difference in total body fat based on mule deer with a power of 0.70 (Anderson 2008). Therefore, 30 animals in each study area should give reasonable power to detect differences in body condition between pregnant and non-pregnant cow elk. Neonate survival estimates will be obtained using the Kaplan-Meier (Pollock et al. 1989) approach and examined for seasonal patterns. Cause specific mortality estimates will be examined with 5 �competing risks models using Cox proportional hazards (Heisey and Patterson 2006). These models will include seasonal effects, individual effects (birth weight, gender) and environmental effects to obtain detailed information on the drivers of cause specific neonate mortality. If neonate survival is low then future work will be directed at improving calf survival. This could take the form of predator manipulations if predation rates are high or habitat manipulations if habitat appears to impact calf survival. Bishop et al. (2009) suggested that a sample size of 40 neonates per group per year provided power of 0.81 to detect a difference of 0.15 in survival. Analysis of cause specific mortality of 40 neonates per area over 2 years results in mortality estimates with cv’s less than 0.14, which is sufficient to assess mortality and direct future research efforts. We recognize that cause specific mortality may represent the proximate cause and that the ultimate cause may not be detected as it relates to disease or malnutrition. We will attempt to assess this as well and, when possible, bring calf mortalities to the lab for a more thorough necropsy. Movement models will also be utilized to examine potential drivers of movement for cow elk, including seasonal patterns and responses to environmental variables. Continuous-time-discrete-space models (Hanks et al. 2015) will be used to analyze movement data and RSFs will be used to examine the relationship between resource selection and body condition. Specifically we will use these models to examine animal movement relative to nutritional/energetic demands, response to environmental conditions, seasonal patterns and response to human activity. These movement patterns directly relate to an individual’s resource selection strategy, which are likely to have implications for elk recruitment. These analyses may provide important detail on how elk are utilizing their habitat and what limitations this creates. Additional analyses are currently underway to examine correlations between environmental variables (temperature, moisture) and calf ratios. These data will only provide correlations but will help identify how environmental influences are driving calf ratios on a yearly basis. These data can then be incorporated with data collected in this pilot effort to determine potential interactions among environmental factors and pregnancy rates, body condition, and calf survival. Combining these data will be important to determining the direction of future work. RESULTS AND DISCUSSION Cow elk capture was initiated in late February, 2017, in E-20 and E-33. Weather was hot and dry so baiting elk had limited success as natural forage was starting to develop. A total of 8 elk were caught in E-20 and 5 in E-33 using clover traps. The remaining elk were caught in early March using helicopter net gunning. Body condition was estimated for 32 and 29 elk in E-20 and E-33 respectively and 23 were GPS collared in each area. Body condition of elk, based on loin thickness, rump fat and a body condition score was reasonably good in both study areas (Table 1). Vaginal implant transmitters (VITs) were placed in pregnant elk. Pregnancy rates were 78.1% and 90.0% in E-20 and E-33 respectively (Table 1). Calf capture began in the middle of May. Only 2 of 40 VITs worked so capture was primarily opportunistic. A total of 40 and 55 calves were caught in E-20 and E-33, respectively (Table 2). Average age at capture was estimated at just over 2 days old, although some older calves were caught at a week old. Average capture weight was 17.3 kg for both areas. Collar retention is an issue as numerous collars have been found near fences and the collar belting appears to have broken after getting snagged in the fence. As this is the first year of the study and data is just starting to be collected, no factors have been identified as potentially contributing to low recruitment rates for these elk herds. In the southwest corner of E-20, pregnancy rates were very low. Of the 8 cows captured there, only 4 were pregnant. However, 6 �pregnancy rates in the rest of this unit were high. This may be of interest for further investigation to determine if there are localized low pregnancy rates in this area. Beyond this, the project is on schedule and proceeding as planned. SUMMARY The elk recruitment study was initiated this year in E-20 and E-33. Approximately 30 cow elk were captured in each study area using clover traps and helicopter net gunning and 23 were GPS collared in each study area. Body condition and pregnancy rates were reasonable in both study areas. Calf capture began in May and a total of 40 and 55 calves were captured and collared in E-20 and E-33 respectively. Calf capture concluded at the end of June so no data is available to assess calf survival or cause specific mortality at this time. LITERATURE CITED Anderson, C. R. Jr. 2015. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid Project No. W-185-R Annual Report, Colorado Parks and Wildlife, Fort Collins, USA. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs No. 121. Cook, J.G., B.K. Johnson, R.C. Cook, R.A. Riggs, T. Delcurto, L.D. Bryant, and L.L. Irwin. 2004. Effects of summer-autumn nutrition and parturition data on reproduction and survival of elk. Wildlife Monographs 155:1-61. Cook, R.C., J.G. Cook, D.J. Vales, B.K. Johnson, S.M. McCorquodale, L.A. Shipley, R.A. Riggs, L.L. Irwin, S.L. Murphie, K.A. Schoenecker, F. Geyer, P.B. Hall, R.D. Spencer, D.A. Immell, D.H. Jackson, B.L. Tiller, P.J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1-44. Eberhardt, L.L. 2002. A paradigm for population analysis of long-lived vertebrates. Ecology 83:28412854. Gaillard, J.M., M. Festa-Bianchet, and N.G. Yoccoz. 1998. Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends in Ecology and Evolution. 13:58-63. Garrott, R.A., L.L. Eberhardt, P.J. White, and J. Rotella. 2003 Climate-induced variation in vital rates of an unharvested large-herbivore population. Canadian Journal of Zoology. 81:33-45. Griffin, K.A., M. Hebblewhite, H.S. Robinson, P. Zager, S.M. Barber-Meyer, D. Christianson, S. Creel, N.C. Harris, M.A. Hurley, D.H. Jackson, B.K. Johnson, W.L. Meyers, J.D. Raithel, M. Schlegel, B.L. Smith, C. White, and P.J. White. 2011. Neonatal mortality of elk drivien by climate, predator phenology and predator community composition. Journal of Animal Ecology 80:12461257. Hanks, E.M., M.B. Hooten, and M.W. Alldredge. 2015. Continuous-time discrete-space models for animal movement. The Annals of Applied Statistics. 9:145-165. 7 �Heisey, D.M. and B.R. Patterson. 2006. A review of methods to estimate cause-specific mortality in presence of competing risks. Journal of Wildlife Management. 70:1544-1555. Monteith, K.L., V.C. Bleich, T.R. Stephenson, B.M. Pierce, M.M. Conner, J.G. Kie, and R.T. Bowyer. 2014. Life-history characteristics of mule deer: effects of nutrition in a variable environment. Wildlife Monographs. Phillips, G.E and A.W. Alldredge. 2000. Reproductive success of elk following disturbance by humans during calving season. Journal of Wildlife Management. 64:521-530. Pollock, K.H., S.R. Winterstein, C.M. Bunck, and P.D. Curtis. 1989. Survival analysis in telemetry studies: The staggered entry design. Journal of Wildlife Management. 53:7-15. Proffitt, K.M., J.A. Conningham, K.L. Hamlin, and R.A. Garrott. 2014. Bottom-up and top-down influences on pregnancy rates and recruitment of northern Yellowstone elk. Journal of Wildlife Management 78:1383-1393. Sargeant, G.A., D. C. Weber, and D. E. Roddy. 2011. Implications of chronic wasting disease, cougar predation, and reduced recruitment of elk management. Journal of Wildlife Management 75:171177. White, C.G., P. Zager, and M. W. Gratson. 2010. Influence of predator harvest, biological factors, and landscape on elk calf survival in Idaho. Journal of Wildlife Management 74:355-369. White, P.J., R.A. Garrott, K.L. Hamlin, R.C. Cook, J.G. Cook, and J.A. Cunningham. 2011. Body condition and pregnancy in northern Yellowstone elk: evidence for predation risk effects? Ecological Applications 21:3-8. Prepared by Mathew W. Alldredge, Wildlife Researcher 8 �Table 1: Cow capture statistics for E-20 and E-33. Loin thickness (mm), rump fat thickness (mm), body condition score (BCS) and percent pregnant by year and location. E-20 E-33 Year n Loin Rump BCS % Pregnant 2017 32 48.7 7.1 3.4 78.1 2017 29 52.0 5.7 3.4 90.0 Table 2: Calf capture summary for E-20 and E-33. Sex ratio (female:male), estimated capture age (days) and capture weight (kg). E-20 E-33 Year n F:M Age Weight 2017 40 20:20 2.3 17.3 2017 55 29:26 2.6 17.3 �Figure 1: Colorado’s elk data analysis units (DAUs) used for management and monitoring of elk populations. COLORADO PARKS AND WILDLIFE - Elk DAUs April2015 • �Figure 2: Selected southern Colorado DAUs showing declining calf:cow ratios from 1994 to present. Declining elk calf ratios 1994 - 2014 70 60 [2 -+- r l4 n~ I !; I . . - en [1 S - 111,..n IF1111 u ~ fl :UI 1 J . 11 ar tl U I �Figure 3: Two northern Colorado DAUs showing increasing or slightly decreasing calf:cow ratios from 1994 to present. St bl to Iner fl I ,,, ng elk c If r tios �Colorado Division of Parks and Wildlife July 2017 - June 2018 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3002 1 : : : : : Division of Parks and Wildlife Mammals Research Pilot Study—Elk Recruitment and Habitat Use in Colorado W-242-R2 Period Covered: July 1, 2017 - June 30, 2018 Author: M.W. Alldredge, N. Rayl, B. Banulis, and A. Vitt Personnel: R. DeVergie, L. Snobl, T. Stratman, A. Orlando, W. Hiler, A. Meyer, N. Collier, B. Hoffman, K. Botzet, S. Stevens, L. Sweanor, T. Verzuh, A. Tuck, J. Stanton, A, Kirby, S. Boyle, C. Wallace, A. Hart, A. Larson, R. Coleman, J. Kelley, L. Temple, M. Montoya, K. Logan All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our principal research objective was to assess elk recruitment rates in southern Colorado, where declining December calf:cow ratios have been observed since the early 2000’s. We initiated this study in 2016 in elk Data Analysis Units (DAUs) E-20 and E-33 as these areas consistently had the lowest calf:cow ratios in the state. Our objective is to determine major factors that may be contributing to low recruitment in order to direct future research activities. Therefore, we are examining this from both the cow productivity standpoint and in terms of calf mortality. In February and March, 2017 and 2018, 30 adult cow elk were captured in each area (approximately 20 collared), to assess pregnancy rates and body condition. Starting in May, 2017 and 2018, we also captured and fitted at least 40 neonate elk in each study area with global positioning system (GPS) collars to assess cause specific mortality rates and recruitment to the yearling age class. Body condition in both study areas was reasonable given the time of year and pregnancy rates have ranged between 77% and 97.0% in E-33. Because a large portion of calf collars fell off prematurely due to manufacture related issued associated with new technology, no calf recruitment estimates were possible for year one and year two estimates are still pending. 1 �WILDLIFE RESEARCH REPORT PILOT STUDY—ELK RECRUITMENT AND HABITAT USE IN COLORADO MATHEW W. ALLDREDGE NATHANIEL RAYL PROJECT NARRITIVE OBJECTIVES 1. To assess adult cow elk (Cervus canadensis) body condition and pregnancy rates in two different elk populations, DAUs E-20 and E-33, in southern Colorado. 2. To assess cause specific calf mortality and recruitment into the yearling age class for two different elk populations, E-20 and E-33, in southern Colorado. 3. To assess cow and calf habitat use in relation to body condition and survival. SEGMENT OBJECTIVES Elk Recruitment 1. Measure body condition, pregnancy and fetal rates for cow elk within each study area. 2. Measure calf elk weight at parturition and relate this to the dam’s body condition. 3. Determine cause specific mortality for elk calves from birth to age one. 4. Examine cow elk habitat use, including use of habitat treatments in the study area. INTRODUCTION Rocky Mountain Elk (Cervus elaphus) is an iconic species throughout western North America and especially in Colorado, with a high recreational value to hunters, photographers, artists and wildlife enthusiasts in general. Elk populations are known to fluctuate greatly following habitat succession, especially following historic wildfires. Human exploitation, habitat loss, predation and disease are all factors that can lead to population declines. In order to maintain healthy populations, managers must understand these factors and use their best knowledge to set herd objectives, harvest strategies and monitoring programs. Population dynamics of ungulates, including elk, are generally characterized by relatively constant adult survival and variable recruitment (Gaillard et al. 1998, Garrott et al. 2003, White et al. 2010, Proffitt et al. 2014). Eberhardt (2002), when examining large herbivore populations, suggested that juvenile survival is the first parameter expected to change as populations decline. Variability in recruitment rates can manifest in a variety of ways, including pregnancy rates, intra-uterine survival, neonate survival and overwinter survival (Proffitt et al. 2014). Pregnancy rates can be a function of environmental conditions or nutrition and its influence on body condition (Cook et al. 2004). Survival of neonates can be affected by summer temperature, precipitation, predation, population density (White et al. 2010, Griffin et al. 2011) and human disturbance (Phillips and Alldredge 2000). Malnutrition is also a factor that contributes to over-winter mortality (Proffitt et al. 2014). Concerns about elk calf ratios have been expressed for about a decade, but factors influencing local populations remain largely unknown. During the 1990’s and early 2000’s, elk herds were above objective and efforts were made to reduce elk populations. Calf ratios started declining in the early 2000’s while herds were generally still above objective. Many studies have been conducted to investigate environmental influences on elk, many of which center around juvenile recruitment (Phillips and Alldredge2000, White et al. 2010, Sargeant et al. 2011, Cook et al. 2013, Proffitt et al. 2014). Colorado is 2 �no exception, in many parts of the state recruitment rates are low and declining, which will have long term ramifications on elk populations across the state. Colorado Parks and Wildlife (CPW) has defined numerous elk data analysis units (DAUs) across the state delineating specific elk populations for management objectives and monitoring purposes (Figure 1). Early winter surveys are conducted within each DAU annually in order to obtain population parameters, such as cow:calf:bull ratios, in order to model population size. In general, these data are showing lower and declining cow:calf ratios in the southern portion of the state compared to the northern part of the state since 1994 and especially since the early 2000s (Figures 2 and 3). Annual variation in cow:calf ratios exists but a steady decline for the southern DAUs is also evident with current ratios approaching or below 30 calves per 100 cows (Figure 2). Similar annual variability exists in the northern DAUs, but the declining pattern is not evident and cow:calf ratios are higher, currently above 50 calves per 100 cows in the DAUs presented. Low recruitment rates for elk across the state and potential long term population level ramifications are of great concern to CPW wildlife managers and biologists. If the trend of low recruitment rates continues, resulting declining elk populations will significantly impact both recreational opportunity and economics in Colorado and for CPW. Furthermore, CPW has a statutory responsibility to manage elk. However, very little is known as to the factors driving declining recruitment rates. Research on this topic is vital. A recent study on mule deer (Odocoileus hemionus) has demonstrated a paradigm shift in causes of low recruitment for this species from the historical research demonstrating low over-winter survival (Bartmann et al. 1992) to recent developments suggesting low neonatal survival (Anderson 2015). It is imperative that CPW conduct similar investigations on elk to gain information on factors affecting low recruitment across the state and develop management strategies to mitigate these factors. Because little is known about the factors affecting elk recruitment in the state, we proposed a pilot study designed to identify primary factors. Given that this low recruitment is occurring across a broad spatial scale we also proposed that this work be conducted in multiple study areas exhibiting low recruitment and one study area with higher recruitment as a reference area. The intent of this 2 year pilot study is to determine pregnancy rates, fetal counts, and cause specific mortality of calf elk from birth to age 1. Additional data on cow body condition, birth weights and consecutive year reproduction will allow determination of potential causes of low elk recruitment. Measuring individual body condition of cow elk in the study and then ascertaining the fate of each cow’s calf will provide valuable insights regarding nutritional influences on both calf survival and future pregnancy rates. Examinations of cow elk habitat use will also be conducted, including use of habitat treatments that exist on the landscape, to determine differences in habitat use and the impact that has on pregnancy rates and calf survival. Information from this pilot study will provide insights into factors that are affecting elk recruitment throughout Colorado and potentially throughout many western states. This information will be used to direct future research and management implementation to mitigate factors contributing to low elk recruitment. These factors may include but are not limited to; habitat quality and poor nutrition, neonate predation, disease and/or human disturbance. The results from this pilot project will direct future hypotheses regarding declining calf ratios and future direction of work, such as: High pregnancy rates: indicates high dam nutrition and reduces evidence of nutritional stress Hypothesis: Poor neonate survival. Low pregnancy rates and poor body condition: indicates nutritional stress for dam, reduced evidence that calf survival is limiting. Hypothesis: Summer nutrition is limiting herd productivity. Low neonatal survival and low predator specific mortality: indicates habitat limitation. Hypothesis: Poor neonate survival is caused by habitat limitation. 3 �Low neonatal survival and high predator specific mortality: indicates predator limitation. Hypothesis: High neonatal predation is limiting populations. Results indicating habitat limitations could lead to future studies that examine habitat manipulations/improvement and/or studies that examine reductions in herd size. Results indicating poor neonate survival could lead to studies that will examine cause specific mortality to determine the drivers of low calf survival. If predation appears to be a limiting factor then future studies could examine the effects of predator manipulations on neonate survival. If other factors are limiting calf survival then specific studies will be designed to examine these limitations (disease, habitat, etc.) and what manipulations can be done to improve neonate survival. STUDY AREA This project is designed to examine low elk recruitment issues statewide. Given the broad scale issue, two study areas with low elk recruitment were selected and, if funding permits, one area will be selected as a reference area where elk recruitment is high following the 2-year pilot phase. In conjunction with other work in the state, pregnancy rates are being monitored in areas where recruitment is high. The two study areas in the southern part of the state with low recruitment rates targeted during the pilot phase are DAUs E-20 and E-33. E-20 E-20 is the Uncompahgre Plateau area with game management units (GMU) 61 and 62. These GMUs are in Montrose, Mesa, Delta, San Miguel and Ouray counties encompassing 2,262 square miles. Elevations range from 4,600 feet to 10,300 feet. The area is characterized by flat mesas and deep rugged canyons. Vegetation includes grassland, shrub, pinon/juniper, pine, aspen, and spruce/fir. Land ownership includes private, BLM, US Forest Service and state. E-33 E-33 is the La Veta/Trinidad area with game management units (GMU) 140, 85, and 851. GMU 140 is in Las Animas County on the New Mexico border. Elevations range from 5,414 to 9,544 feet. The area is characterized by gently rolling hills, steep canyons and mesas. Vegetation includes shortgrass prairie, pinion pine, oak and spruce/fir. Approximately 99% of the land is privately owned. GMU 85 is located in Huerfano and Las Animas counties. Elevations range from 6,025 feet to 13,518 feet. The area is characterized by flat valley bottoms, foothills and steep mountains. Vegetation includes grassland, pinon/juniper, pine/oak, spruce/fir, and alpine. Approximately 75% of the area is privately owned. GMU 851 is in Las Animas county and is bordered on the south by New Mexico. Elevations range from 6,025 to 14,000 feet. The area is characterized foothills and steep mountains. Vegetation includes grassland, pine, spruce/fir, aspen, and alpine. Approximately 98% of the area is privately owned. METHODS Cow Capture and Sampling Cow elk were captured in late February and early March using clover traps and helicopter net gunning following approved elk capture and handling guidelines (CPW ACUC #09-2008) (Appendix I). Clover traps were used for some elk capture in 2017 but was not efficient because of mild winter conditions. The majority of elk in 2017 and all elk in 2018 were captured via net gunning. In this initial phase of the study a target of 20 collared cow elk per study area and body condition on 30 elk per study area was established. Fetal counts and body condition was assessed for all collared elk using ultrasound. Pregnant females equipped with telemetry collars on winter range will also be equipped with vaginal implant transmitters (VITs;) to facilitate spring neonate capture and collaring efforts following birth on summer 4 �range. VITs failed to communicate birth events during the first year of the study, but did reveal that the use of VITs is critical to capturing elk calves at birth and estimating early mortality. Neonate Capture GPS collars on cow elk will send an alert and a location when a VIT is expelled. Once expelled, field crews will be directed to birth site locations to locate and capture newborn calves. In order to minimize human disturbance, neonate searches will typically last 3045 minutes and will not exceed 1 hour. Uncollared pregnant cows will also be observed in an attempt to opportunistically locate and collar additional calves. Each neonate will be handled with sterile nitrile latex gloves to minimize the transfer of human scent, blindfolded, and placed in a cloth bag to measure body mass. Hind foot length, chest girth, age (days), and gender will also be recorded. Each neonate will be fitted with an expandable GPScollar (Wildlink-GTX Globalstar GPS Collar, ATS, Isanti MN, USA) with a 4 hour mortality sensor that is designed to drop off after 12 months. Handling time will be ≤ 5 minutes and neonates will be placed in the precise location where they were located to minimize abandonment. Neonate telemetry signals will be monitored daily using GPS satellite communication. Continuous monitoring will afford us the ability to detect mortalities and assess cause specific mortality within 24 hours. Monitoring of neonate signals will continue throughout the year or until mortality occurs. Once a mortality is detected, neonates and/or collars will be located from the ground and if any part of a carcass is present a thorough field necropsy will be conducted to determine cause of death. Data Analysis Pregnancy rates will be compared among study areas, years and possibly to historic data using a binomial variance. Body condition and age class will be treated as covariates in the analysis. We will also use individual body condition to estimate the animal indicated carrying capacity following Monteith et al. (2014). Low pregnancy rates and/or poor body condition will lead us to consider future habitat manipulations or elk population reductions as a means to improve herd productivity. Pregnancy rates from blood samples of captured cows in the NW, where recruitment is higher, were estimated at 0.91 in December 2015. The binomial power to detect a decrease from this baseline rate of 0.15, using a sample size of 30, is 0.78. A minimum of 20 animals is necessary to detect a 1.5% difference in total body fat based on mule deer with a power of 0.70 (Anderson 2008). Therefore, 30 animals in each study area should give reasonable power to detect differences in body condition between pregnant and non-pregnant cow elk. Neonate survival estimates will be obtained using the Kaplan-Meier (Pollock et al. 1989) approach and examined for seasonal patterns. Cause specific mortality estimates will be examined with competing risks models using Cox proportional hazards (Heisey and Patterson 2006). These models will include seasonal effects, individual effects (birth weight, gender) and environmental effects to obtain detailed information on the drivers of cause specific neonate mortality. If neonate survival is low then future work will be directed at improving calf survival. Bishop et al. (2009) suggested that a sample size of 40 neonates per group per year provided power of 0.81 to detect a difference of 0.15 in survival. Analysis of cause specific mortality of 40 neonates per area over 2 years results in mortality estimates with cv’s less than 0.14, which is sufficient to assess mortality and direct future research efforts. We recognize that cause specific mortality may represent the proximate cause and that the ultimate cause may not be detected as it relates to disease or malnutrition. We will attempt to assess this as well and, when possible, bring calf mortalities to the lab for a more thorough necropsy. Movement models will also be utilized to examine potential drivers of movement for cow elk, including seasonal patterns and responses to environmental variables. Continuous-time-discrete-space models (Hanks et al. 2015) will be used to analyze movement data and resource selection functions (RSFs) will 5 �be used to examine the relationship between resource selection and body condition. Specifically we will use these models to examine animal movement relative to nutritional/energetic demands, response to environmental conditions, seasonal patterns and response to human activity. These movement patterns directly relate to an individual’s resource selection strategy, which are likely to have implications for elk recruitment. These analyses may provide important detail on how elk are utilizing their habitat and what limitations this creates. Additional analyses are currently underway to examine correlations between environmental variables (temperature, moisture) and calf ratios. These data will only provide correlations but will help identify how environmental influences are driving calf ratios on a yearly basis. These data can then be incorporated with data collected in this pilot effort to determine potential interactions among environmental factors and pregnancy rates, body condition, and calf survival. Combining these data will be important to determining the direction of future work. RESULTS AND DISCUSSION Cow elk capture was initiated in late February, 2017, in E-20 and E-33. Weather was hot and dry so baiting elk had limited success as natural forage was starting to develop. A total of 8 elk were caught in E-20 and 5 in E-33 using clover traps. The remaining elk were caught in early March using helicopter net gunning. Body condition was estimated for 32 and 29 elk in E-20 and E-33 respectively and 23 were GPS collared in each area. Body condition of elk, based on loin thickness, rump fat and a body condition score was reasonably good in both study areas (Table 1). Vaginal implant transmitters (VITs) were placed in pregnant elk. Pregnancy rates were 77.4% and 79.3% in E-20 and E-33 respectively (Figure 4). In late February 2018, cow elk capture was conducted for the second year in E-20 and E-33. All capture was conducted using helicopter net gunning. Weather conditions and mechanical issues for the E-20 efforts extended capture over two weeks, but capture in E-33 was done in 3 days. One capture related mortality occurred in each area. Body condition was estimated for 30 elk in E-20 and 31 elk in E-33 and 20 were collared with VITS in each area. Body condition scores, loin thickness and rump fat were measured for all captured elk (Table 1). Ingesta-free body fat was estimated from these measures for each study area and year with an average near 7.5% each year (Figure 5). Pregnancy rates were higher in 2018 at 96.7% and 87.1% in E-20 and E-33 respectively (Table 1). Calf capture began in the middle of May, 2017. Only 2 of 40 VITs worked so capture was primarily opportunistic. A total of 40 and 55 calves were caught in E-20 and E-33, respectively (Table 2). Average age at capture was estimated at just over 2 days old, although some older calves were caught at a week old. Average capture weight was 17.3 kg for both areas. Collar retention was an issue as numerous collars were found near fences and the collar belting appeared to have been broken after getting snagged in the fence. Calf capture was again initiated in the middle of May for the 2018 season. VITs worked reliably this year allowing for numerous captures shortly after parturition for calves from collared cows. Additional calves were also captured opportunistically. A total of 47 and 54 calves were captured in E-20 and E-33 respectively (Table 2). Average age at capture was 1.6 and 2.2 in E-20 and E-33, slightly younger than the previous year because of the use of VITs. The slightly higher age in E-33 is likely due to a greater number of opportunistic captures. Average capture weight was similar across years. Retention issues for calf collars during the first year of the study limits the results for assessing recruitment. Mortality during the first few months (prior to collar retention issues) indicated 10% known predation mortality in E-20 and 27% known predation mortality in E-33. There was an additional mortality from malnutrition and one unknown cause in E-20 and 2 unknown mortalities in E-33. In E-33, 6 �26% of the calf mortality was attributed to bears and 32% to cougars. As of June 30, 2018, similar patterns were being observed during this second year with potentially higher bear predation in E-33, but this only represents a few weeks of data for this year. SUMMARY The elk recruitment study initiated in 2017 continued this year in E-20 and E-33. Approximately 30 cow elk were captured in each study area using helicopter net gunning and 20 were GPS collared in each study area. Body condition was reasonable, although lactation status was unknown so interpretation is limited and pregnancy rates were slightly low in both study areas. Calf capture began in May and a total of 47 and 54 calves were captured and collared in E-20 and E-33 respectively. Calf capture concluded at the end of June so no data are available to assess calf survival or cause specific mortality for 2018. Information on calf recruitment is limited from 2017 efforts because of collar issues, but there is some indication that early mortality from predators does play a significant role in documented December calf:cow ratios. LITERATURE CITED Anderson, C. R. Jr. 2015. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid Project No. W-185-R Annual Report, Colorado Parks and Wildlife, Fort Collins, USA. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs No. 121. Cook, J.G., B.K. Johnson, R.C. Cook, R.A. Riggs, T. Delcurto, L.D. Bryant, and L.L. Irwin. 2004. Effects of summer-autumn nutrition and parturition data on reproduction and survival of elk. Wildlife Monographs 155:1-61. Cook, R.C., J.G. Cook, D.J. Vales, B.K. Johnson, S.M. McCorquodale, L.A. Shipley, R.A. Riggs, L.L. Irwin, S.L. Murphie, K.A. Schoenecker, F. Geyer, P.B. Hall, R.D. Spencer, D.A. Immell, D.H. Jackson, B.L. Tiller, P.J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1-44. Eberhardt, L.L. 2002. A paradigm for population analysis of long-lived vertebrates. Ecology 83:28412854. Gaillard, J.M., M. Festa-Bianchet, and N.G. Yoccoz. 1998. Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends in Ecology and Evolution. 13:58-63. Garrott, R.A., L.L. Eberhardt, P.J. White, and J. Rotella. 2003 Climate-induced variation in vital rates of an unharvested large-herbivore population. Canadian Journal of Zoology. 81:33-45. Griffin, K.A., M. Hebblewhite, H.S. Robinson, P. Zager, S.M. Barber-Meyer, D. Christianson, S. Creel, N.C. Harris, M.A. Hurley, D.H. Jackson, B.K. Johnson, W.L. Meyers, J.D. Raithel, M. Schlegel, B.L. Smith, C. White, and P.J. White. 2011. Neonatal mortality of elk drivien by climate, predator phenology and predator community composition. Journal of Animal Ecology 80:1246-1257. 7 �Hanks, E.M., M.B. Hooten, and M.W. Alldredge. 2015. Continuous-time discrete-space models for animal movement. The Annals of Applied Statistics. 9:145-165. Heisey, D.M. and B.R. Patterson. 2006. A review of methods to estimate cause-specific mortality in presence of competing risks. Journal of Wildlife Management. 70:1544-1555. Monteith, K.L., V.C. Bleich, T.R. Stephenson, B.M. Pierce, M.M. Conner, J.G. Kie, and R.T. Bowyer. 2014. Life-history characteristics of mule deer: effects of nutrition in a variable environment. Wildlife Monographs. Phillips, G.E and A.W. Alldredge. 2000. Reproductive success of elk following disturbance by humans during calving season. Journal of Wildlife Management. 64:521-530. Pollock, K.H., S.R. Winterstein, C.M. Bunck, and P.D. Curtis. 1989. Survival analysis in telemetry studies: The staggered entry design. Journal of Wildlife Management. 53:7-15. Proffitt, K.M., J.A. Conningham, K.L. Hamlin, and R.A. Garrott. 2014. Bottom-up and top-down influences on pregnancy rates and recruitment of northern Yellowstone elk. Journal of Wildlife Management 78:1383-1393. Sargeant, G.A., D. C. Weber, and D. E. Roddy. 2011. Implications of chronic wasting disease, cougar predation, and reduced recruitment of elk management. Journal of Wildlife Management 75:171-177. White, C.G., P. Zager, and M. W. Gratson. 2010. Influence of predator harvest, biological factors, and landscape on elk calf survival in Idaho. Journal of Wildlife Management 74:355-369. White, P.J., R.A. Garrott, K.L. Hamlin, R.C. Cook, J.G. Cook, and J.A. Cunningham. 2011. Body condition and pregnancy in northern Yellowstone elk: evidence for predation risk effects? Ecological Applications 21:3-8. Prepared by Mathew W. Alldredge, Wildlife Researcher 8 �Table 1: Cow elk capture statistics for E-20 and E-33. Loin thickness (mm), rump fat thickness (mm), body condition score (BCS) and percent pregnant by year and location. E-20 E-33 Year 2017 2018 2017 2018 n 32 30 29 31 Loin 48.7 53.7 52.0 51.4 Rump 7.1 7.1 5.7 5.2 BCS 3.4 3.9 3.4 3.2 % Pregnant 77.4 96.7 79.3 87.1 Table 2: Calf elk capture summary for E-20 and E-33. Sex ratio (female:male), mean estimated capture age (days) and weight (kg). E-20 E-33 Year 2017 2018 2017 2018 n 40 47 55 54 F:M 20:20 24:23 29:26 25:29 Age 2.3 1.6 2.6 2.2 Weight 17.3 17.9 17.3 18.7 �Figure 1: Colorado’s elk data analysis units (DAUs) used for management and monitoring of elk populations. COLORADO PARKS AND WILDLIFE - Elk DAUs April 2il 15 • �Figure 2: Selected southern Colorado DAUs showing declining calf:cow ratios from 1994 to present. Declining elk calf ratios 1994 - 2014 80.0 70.0 60.0 50.0 - E20 ~ E24 ; - - E34 8 ....._ E33 0 ~ 40.0 .,;,;> -+- E15 - - Linear (E20) "ii u 30.0 - - Unear (E24) - - Linear (E34 ) - - Linear (E33) 20.0 10.0 0.0 - - Linear (E1 5) �Figure 3: Two northern Colorado DAUs showing increasing or slightly decreasing calf:cow ratios from 1994 to present. Stable to increasing elk calf ratios 80.00 70.00 60.00 50.00 ;: 8 -+- E2 0 ~ 40.00 ~ ~ - - - EB - - linear (E2) ;; u - - Lin ear (E13) 30.00 20.00 10.00 0.00 �Figure 4: Pregnancy rates for cow elk in E-20 (Uncompahgre) and E-33 (Trinchera) estimated from late February capture during 2017 and 2018. The sample size is given at the top of the 95% binomial confidence intervals (black lines). 1.0 0.9 29 31 30 31 ,+-,I ffi 0.8 C 0)0.7 Q) c.0.6 Trinchera Uncompahgre 5 0.5 to 0.4 Cl. e o.3 a_ 0.2 0.1 0.0 2017 2018 Year �Figure 5: Ingesta-free body fat for cow elk in E-20 (Uncompahgre) and E-33 (Trinchera) calculated from body condition scores, rump fat, and loin thickness for 2017 and 2018 late February captures. $ Trinchera • ~ 15.0- C)' ._., ..., ~ 12 •5 ~ Uncompahgre • • •• • ""O 0 ..c ID 10.0ID "- '+I .ffi 7.5 - ID 0) C 5.0 - I I 2017 2018 Year I � https://cpw.cvlcollections.org/files/original/35b4be52a8bb45f0431d770854aac773.pdf b0d26be47dac90c63127c16f3862a99c PDF Text Text Colorado Division of Wildlife June 2004 – July 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 : : : : Federal Aid Project: N/A : Division of Wildlife Mammals Research Predatory Mammals Conservation Puma Population Structure And Vital Rates On The Uncompahgre Plateau, Colorado Period covered: July 1, 2004―June 30, 2005 Author: K. A. Logan. Personnel: S. Waters, T. Murphy, K. Crane, T. Mathieson, M. Caddy, and T. Smith of CDOW, J. Bauer of Colorado Cooperative Fishery and Wildlife Research Unit, J. Kane of U.S.D.A. Wildlife Services, volunteers, cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks, with project support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT To begin conducting research on puma population characteristics and dynamics on the Uncompahgre Plateau, public meetings were held, puma hunting regulations were altered for an experimental design, and a study plan was developed and approved along with animal care and handling procedures. Field research began on December 2, 2004. From December 2, 2004 to July 22, 2005 fifteen puma were captured, sampled, tagged and released, including 7 adult pumas (3 males, 4 females) and 8 cubs (3 males, 5 females). Three other pumas were captured with the aid of dogs, but were released without sampling or tagging for safety reasons. One adult female puma was hit and killed by a car on highway 62 at the southern boundary of the study area. The 7 adult pumas wore GPS collars that yielded 355 to 779 locations per puma. GPS locations indicated 139 clusters that were investigated. Prey use was found at 112 clusters, with mule deer (n = 61) and elk (n = 48) comprising the most important items. Tissue samples collected from all puma handled will be used for proposed research on laboratory and field methods to estimate puma numbers using DNA mark-recapture methods. Puma GPS locations will also be used in proposed efforts to develop and test puma habitat suitability models and maps. Information on evaluations of the GPS collar technology and findings at GPS clusters will be used to develop proposed research on puma-prey relationships on the Uncompahgre Plateau. 105 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing puma in Colorado. SEGMENT OBJECTIVES 1. Hold public meetings and contact individuals to inform citizens in the area of Uncompahgre Plateau about the CDOW desires to conduct the puma research. 2. Obtain needed regulations from the Wildlife Commission for experimental research on the study area. 3. Develop a peer-reviewed study plan that is authorized by the Leader of Mammals Research in the CDOW. Develop proper procedures for the capture, restraint, handling, and sampling of puma for research which are authorized by the CDOW Animal Care and Use Committee. 4. Begin quantifying puma population sex and age structure. 5. Begin process of estimating female puma reproduction rates. 6. Begin process of estimating puma sex and age-stage survival rates. 7. Begin process of estimating agent-specific mortality rates. 8. Begin gathering quantitative data on puma movements for the development of sampling methods for direct and DNA-genotype mark-recapture population estimates. Begin gathering puma tissue samples for individual puma genotyping procedures. 9. Evaluate other data sources that could come from this research that might be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma-prey interactions. Staff on the Front Range placed greater emphasis on puma-human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified 106 �by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. 107 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ); for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, age-specific natality, sexand age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥50% lower, λ≤1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ=0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 108 �2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. 109 �STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-mark- 110 �recapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma-prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large 111 �majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. 112 �Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System, and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female puma will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male puma will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those puma on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode 113 �set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark puma prior to performing capture-recapture occasions using houndsmen teams. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to analyze survival rates in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates will be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of 114 �puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ=Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. 115 �Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 The Division of Wildlife held public meetings in Redvale (August 23, 2004) and Montrose (August 30, 2004) where DOW staff informed attendees from the Uncompahgre Plateau area about the puma research project and addressed their questions. Meetings were held with over 70 private landowners, ranchers, hunters, outfitters, and guides that live and operate on the Uncompahgre Plateau to inform them about the puma research, address questions, and request permission to access private lands for puma research activities. Additional meetings were with representatives of the U.S. Forest Service, Bureau of Land Management, National Park Service, and Colorado State Parks who were also informed about the puma research. Segment Objective 2 The Wildlife Commission passed regulations allowing for the experimental design of this puma research. Their decision resulted in a closure to puma sport-hunting for the first 5-years of the research (Nov. 11, 2004 to Mar. 31, 2009) on the study area. In addition, the Commission allowed the creation of a buffer zone during the same time period comprised of the remaining parts of Game Management Units 61 and 62 north of the 25 Mesa Road (i.e., north of the study area) where pumas tagged on the study area can not be legally taken by puma sport-hunters. The buffer zone is intended to protect puma that are originally captured and sampled in the study area and that range to the north so that pumas in the study population will express life history traits not affected by sport-hunting off-take. A larger buffer zone to protect pumas tagged on the study area was requested of the CDOW Regulations Review Committee. That buffer zone would have protected all puma tagged in the study area even if they ranged off the study area but were west of the continental divide in Colorado. However, that request was denied by the Regulations Review Committee. Segment Objective 3 A study plan was developed, peer-reviewed, modified with the peers’ recommendations (Logan 2004), and then initiated to begin the long-term, experimental research on puma population dynamics on the Uncompahgre Plateau. Procedures for the capture, restraint, handling, and sampling of pumas for this research were reviewed and approved (file #08-2004) by the Colorado Division of Wildlife Animal Care and Use Committee. 116 �Segment Objectives 4―7 Field research to begin quantifying puma population structure, vital rates, and causes of mortality began on Dec. 2, 2004. From December 2, 2004 to May 12, 2005, trained dogs were used as our main method to capture, sample, and mark pumas. Our search efforts on the east slope of the study area were from 25 Mesa Road south to Fisher Creek. On the west slope, our efforts were from the 25 Mesa Road south to Goodenough Gulch. Those efforts resulted in 78 search days, 109 puma tracks, 35 pursuits, and the capture of 14 pumas (Table 1). Eight of those pumas were restrained, sampled, tagged, and released (Table 2). Puma M1 was unintentionally recaptured when we thought we were pursuing an unmarked puma. Puma F3 was recaptured during our effort to capture her male offspring M5 for the first time. Pumas were bayed in trees by dogs on 4 other occasions, but we did not attempt to anesthetize the puma because of concern for the pumas safety on 3 occasions, and concern for the puma’s and the researchers’ safety on one occasion (Table 3). In those cases, a puma was treed in cliffs at night, and on 3 occasions the pumas were bayed in trees too dangerous for researchers to attempt to safely dart the pumas and then climb the trees to retrieve the cats. These pumas included 1 large adult female that was probably caught twice, 1 adult male, and 1 puma that was either a large cub or a subadult (sex undetermined). A summary of capture efforts with dogs is in Table 4. We attempted to capture a female puma on Ridgeway State Park on April 1, 2005. The puma killed an adult mule deer doe, and had begun to eat the deer on the sidewalk beside the Fishing Pond at Pa-Co-Chu-Puk Campground. This location was about 520 m east of where our trained dogs treed, but we could not handle a large female puma on February 1, 2005. We used a cage trap designed for black bears to attempt to capture the puma, but the bear trap was not sufficient. The puma entered the trap, but apparently the cage door did not latch because the puma’s tail was caught in the door jam. The puma did not return to cage trap. We did not pursue the puma with dogs because of the close proximity of highway 550 and private lands directly north and east of the park. We captured 8 cubs from 4 litters born to GPS-collared female pumas. Two litters were born in May, 1 litter was born in June, and 1 litter was born in August. There were 3 males and 5 females (Table 5). One puma death was detected on July 28, 2005. A female, about 49 months old, was hit and killed by a car between 06:00―08:00 on state highway 62 about 10.4 km west of Ridgeway in lower Cottonwood Creek. This location was on the southern boundary of the study area. A necropsy showed that the puma appeared to be in excellent physical condition prior to its death. Her mass was 46 kg; she apparently was not pregnant; and her mammary glands were not producing milk. Segment Objectives 8―9 Seven adult pumas were fit with Lotek 4400S GPS collars programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 355 to 779 (Table 6). Because none of the puma have yet been monitored for a complete year and the sample is small, annual and seasonal home ranges sizes were not estimated for this report. However, we estimated the activity areas used by the 7 GPS-collared adult pumas (Table 6) during the monitoring periods and overlaid 100% Minimum Convex Polygons on a map of the study area (Fig. 2). In addition, we are collaborating with colleagues at Colorado State University― Dr. K. Crooks, Dr. D. Theobald, and Dr. K. Wilson― to develop a proposal and funding that would allow us to develop and validate puma habitat suitability models and maps for Colorado in which these puma GPS location data will be used. Tissue samples from all of the captured pumas and the unmarked female puma hit and killed by a car have been archived with geneticist Dr. M. Douglas. We are currently collaborating with Dr. Douglas to develop a study plan and funding for the development and assessment of laboratory and field methods 117 �for genotyping pumas and for estimating puma abundance in the wild using DNA mark-recapture techniques. We conducted a preliminary assessment of the usefulness of GPS-collar technology for investigations of puma-prey relationships. The average GPS location fix rate for the 7 GPS-collared pumas was 70.7% (range = 54―87%) (Table 6). We investigated 139 GPS location clusters for 7 adult pumas where individual GPS-collared pumas spent ≥1 day during the span December 26, 2004 to July 31, 2005. The estimated error between 101 collar-fixed GPS locations and prey remains found on the ground averaged 3.2 m (range = 0―50 m, SE = 0.6). Prey remains were found at 112 of the 139 clusters, with mule deer and elk comprising 54% and 43%, respectively (Table 7). The sex and age stage structure of 60 mule deer and 48 elk used by puma at GPS clusters is in Table 8. On average, puma spent 2.3 days on mule deer (range = 1―6, SE = 0.2) and 2.9 days on elk (range = 1―10, SE = 0.3). Ungulate use rates by the GPS-collared pumas estimated from these data are in Table 9. Evidence that black bears (Ursus Americana) used portions of the same ungulates used by GPS-collared pumas was found at remains of 7 mule deer and 10 elk. Evidence that coyotes (Canis latrans) used portions of the same ungulates used by GPS-collared pumas was found at remains of 7 mule deer and 14 elk. We are currently assessing how this GPS-collar capability could be used to structure research on puma-ungulate relationships on the Uncompahgre Plateau and the additional funding and personnel needed to thoroughly execute the research. SUMMARY Experimental, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. From December 2004 to July 2005 fifteen pumas were captured, sampled, marked, and released. The number of pumas handled is partially contingent upon effort, the number of pumas present on the study area, and safety concerns. Individual pumas sampled in the population provide quantitative information on population structure, vital rates, and dynamics over time in reference and treatment periods to improve the CDOW’s puma management. All pumas were sampled as part of developing research for genotype mark-recapture procedures. Seven adult puma were fit with GPS collars, yielding 487―779 locations. Puma GPS location data will be used to: design enumeration methods in the field, develop and test puma habitat suitability models and maps, and develop potential research on puma-ungulate relationships on the Uncompahgre Plateau contingent upon funding and support. Research efforts for year 2 will focus on increasing numbers and distribution of sampled, marked, and GPS/radio-collared puma on the study area for data to address the objectives, management assumptions, and hypotheses in the study plan. 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LOGAN, J. W. BAUER, B. MILSAP, AND W. M. BOYCE. 2005 in review. Pumahuman relationships in Cuyamaca Rancho State Park, California. Wildlife Society Bulletin. VAN BALLENBERGHE, V. 1983. Rage of increasse of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 120 �Table 1. Puma capture efforts with dogs from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Month No. No. & type of puma No. & type of pumas No. & I.D. or type of Search tracks founda pursued pumas captured Days December 19 20 tracks: 11 male, 9 4 pursuits: 3 males, 1 2 pumas captured: female female M1, 1 female not handled January 15 26 tracks: 9 male, 15 8 pursuits: 4 males, 4 4 pumas captured: female, 2 cub females M1 recaptured, F2, F3, M4 February 17 22-23 tracks: 5 male, 11 pursuits: 2 males, 7 6 pumas captured: 14 female, 2-4 cubs, females, 2 cubs, or 1 1 female not handled, or 2-3 cubs & 1 cub & 1 subadult F3 recaptured, cub subadult M5, M6, 1 cub or subadult, F7 March 11 17 tracks: 8-9 male or 2 pursuits: 2 females 1 puma captured: F8 1 large cub, 7 female, 1 unspecified sex April 9 13 tracks: 10 male, 3 2 pursuits: 2 males 1 puma captured: female 1 male not handled May 7 10 tracks: 4 male, 6 8 pursuits: 3 males, 5 0 pumas captured female females 78 109 tracks found: 47- 35 pursuits: 14 males, 14 captures: (6 males, TOTALS 48 male, 54 female, 19 females, 1 male 6 females, 1 male cub, 4-6 cub or 0-1 cub, 1 cub (unknown 1 cub (unknown sex) subadult, 1 sex) or 1 subadult or 1 subadult unspecified (unknown sex) (unknown sex) a Puma hind-foot tracks with plantar pad widths >52 mm wide are assumed to be male; ≤52 mm are assumed to be female. Table 2. Pumas that were captured with aid of dogs, sampled, tagged, and released from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Puma Sex Estimated Mass Capture Location I.D. Age (mo.) (kg) date M1 male 33 68 12-08-04 Shavano Valley M4 male 25-33 65 01-28-05 McKenzie Butte Mesa M5 male 6 12 02-04-05 Spring Creek M6 male 33 59 02-18-05 Happy Canyon F2 female 49 43 01-07-05 Dolores Canyon F3 female 41 40 01-21-05 Spring Creek F7 female 56-64 32 02-24-05 Dolores Canyon F8 female 21 30 03-21-05 Cottonwood Creek (W) 121 �Table 3. Pumas that were captured with aid of dogs, but were not handled for safety reasons, from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Puma sex Age Capture Location Comments stage date Female adult 12-23-05 McKenzie Butte Mesa Large female. Female adult 02-01-05 South McKenzie Butte Mesa This puma probably same animal caught 12-23-05. Unspecified cub or 02-24-05 Dolores Canyon This puma apparently in subadult association with F7 at an elk kill. Possibly F7’s offspring or an unrelated subadult. Male adult 04-05-05 Horsefly Canyon (E) This puma, or another male, was pursued on 4 other occasions in the San Miguel River-toCottonwood Creek area. Table 4. Summary of puma capture efforts with dogs, December 2004 to May 2005, Uncompahgre Plateau, Colorado. Period Track Pursuit effort Puma capture Effort to capture a detection effort puma for the first time effort 11 pumas captured for 14/78 = 0.18 Dec. 2, 109/78 = 1.40 35/78 = 0.45 first time (minus M1, F3, capture/day 2004 tracks/day pursuit/day & large female) to 78/14 = 5.57 11/78 = 0.14 capture/day 78/35 = 2.23 May 12, day/capture day/pursuit 2005 78/11 = 7.09 day/capture Table 5. Puma cubs sampled on the Uncompahgre Plateau Puma Study area, 2004 to 2005. Cub Sex Estimated Estimated age Mass Mother Estimated age of I.D. birth date at capture (kg) mother at birth of this litter (mo) a M5 male August 2004 6 months 12 F3 36 F9 female May 28, 2005b 31 days 2.27 F2 44 F10 female May 28, 2005b 31 days 2.04 “ “ M11 male May 28, 2005b 31 days 2.27 “ “ 42 days 2.63 F7 59-67 F12 female May 19, 2005b F13 female May 19, 2005b 42 days 1.72 “ “ F14 female June 26, 2005b 26 days 1.90 F8 24 26 days 2.0 “ “ M15 male June 26, 2005b a Estimated age of M5 was based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data). b Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. 122 �Table 6. Numbers of GPS locations for adult puma on the Uncompahgre Plateau, Colorado, December 2004 to August 2005. Puma I.D. Sex Age Dates monitored a No. Acquisition rate Use areas estimated (km2) b stage locations average, range, n with 100% Minimum Convex Polygonc M1 male adult 12-08-04 to 08-19-05 779 76, 73―83, 5 815 M4 male adult 01-28-05 to 07-25-05 487 73, 57―84, 5 254 M6 male adult 02-18-05 to 07-25-05 543 87, 82―93, 5 552 F2 female adult 01-07-05 to 08-10-05 565 65, 43―82, 7 120 F3 female adult 01-21-05 to 08-02-05 586 76, 67―85, 6 174 F7 female adult 02-24-05 to 07-26-05 362 54, 26―78, 5 94 F8 female adult 03-21-05 to 08-08-05 355 64, 48―78, 4 245 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored is for the last location from the last GPS data download for an individual puma for this report. b n = number of remote downloads. c Polygons for individual GPS-collared puma are overlaid on a study area map in Figure 2. Table 7. Observations at GPS location clusters for 7 GPS-collared puma on the Uncompahgre Plateau, Colorado, December 2004 to July 2005. Puma No. Dates of GPS clusters Mule Elk Porcupine Beaver Puma Only Only Nothing No. GPS I.D. GPS that were deer scavenge Puma Black bear found clusters clusters investigated or sharea signb signc not visitedd M1 23 12-26-04 to 07-10-05 4 14 1 4 2 M4 16 02-03-05 to 07-12-05 4 7 1 4 2 M6 17 02-18-05 to 07-07-05 3 11 2 1 0 4 F2 26 01-12-05 to 07-26-05 12 9 2 2 1 0 1 F3 27 01-27-05 to 07-31-05 22 5 0 0 F7 18 03-08-05 to 07-22-05 9 1 5 1 2 0 F8 11 03-23-05 to 07-03-05 7 2 1 1 1 0 139 61 48 2 1 4 10 2 11 9 Total a A GPS-collared puma either shared a prey item with another GPS-collared puma (2 instances), or a GPS-collared puma scavenged on remains of prey previously used by another GPS-collared puma (2 instances). b Only puma tracks, feces, and/or beds were found at the GPS cluster. c Only black bear sign (e.g., feces) was found at the puma GPS cluster. d Some puma GPS clusters were not investigated because clusters fell on small private land holdings where we did not have permission for access at the time, or other principal objectives of our research were priority. 123 �Table 8. Sex and age structure of mule deer and elk found at GPS location clusters for 7 GPS-collared adult puma on the Uncompahgre Plateau, Colorado, December 2004 to August 2005. Sex No. Fawn/Calf Yearling 2+ years Unknown age Mule deer Female 26 2 2 20 2 Male 10 0 3 7 0 Unknown 25 13 3 3 6 Total 61 15 8 29 8 Elk Female Male Unknown Total 25 5 18 48 12 0 16 28 1 0 0 1 12 5 1 18 0 0 1 1 Table 9. Estimated ungulate use rates of adult GPS-collared pumas on the Uncompahgre Plateau, Colorado, December 2004 to July 2005. Puma Dates starting with & No. days inclusive in No. Estimated No. I.D. ending with ungulate use date span ungulates ungulates used used per yeara M1 12-26-04 to 07-10-05 196 18 33.5 M4 02-03-05 to 07-04-05 152 11 26.4 M6 02-18-05 to 07-07-05 140 14 36.5 F2 01-12-05 to 07-26-05 195 21 39.3 F3 01-27-05 to 07-31-05 185 27 53.3 F7 03-08-05 to 07-16-05 131 9 25.1 F8 03-23-05 to 07-03-05 103 9 31.9 a Estimated ungulate use rates per year are based on the key assumption that the individual puma would use ungulates throughout the year equal to the same rate recorded during the monitoring span in Dates starting with & ending with ungulate use. This assumption is probably not reliable especially for adult female pumas, because their reproductive status, and thus energetic needs vary throughout the year. For example, F3 was raising cubs born in August 2004; yet, F2, F7, and F8 started raising cubs born in May, May, and June of 2005, respectively. In addition, not all GPS clusters were investigated for M1, M4, M6, and F2 (see Table 7). 124 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population G h Vulnerability to Harvest Puma Habitat Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Deer, Elk, Other Natural Prey & Species of Concern Domestic Animals Puma― Human Relationships Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report and the puma management goal (at top). 125 �![ ![ ![ Delta M1 ![ Olathe ![ Montrose F8 F3 ![ Nucla F7 ![ Naturita M4 F2 Norwood ![ M6 L ![ Ridgeway ![ ![ Legend CJ County Boundaries D 0 5 10 20 Kilometers Study Area . Figure 2. The Uncompahgre Plateau Puma Study Area with activity areas of adult GPS-collared pumas depicted with 100% Minimum Convex Polygons, December 2004 to August 2005. 126 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Puma Population Structure and Vital Rates on the Uncompahgre Plateau : Period covered: July 1, 2005―June 30, 2006 Author: K. A. Logan. Personnel: K. Logan, S. Waters, B. Bavin, B. Simpson, K. Crane, T. Mathieson, M. Caddy, and T. Smith of CDOW, J. Bauer of Colorado Cooperative Fishery and Wildlife Research Unit, J. Kane, V. Johnson, S. Young, and J. McNamara of U.S.D.A. Wildlife Services, volunteers, cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks, with financial support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. Puma capture efforts resulted in a total of 36 puma captures (14 adults [1 adult female captured twice], 4 subadults, 14 cubs, and 2 adult or subadult males [1 captured twice] but not handled) with 20 radio-collared pumas within the study area as of July 2006. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 21, 2005 to May 26, 2006. This resulted in 14 puma captures, including 1 adult female, 1 subadult female, 2 adult males, and 1 subadult or adult male captured and processed for the first time. Two other males were captured (one of them twice), but were not handled for safety reasons. The remainder was recaptures of previously marked pumas, including 2 adult females (1 recaptured twice), 1 adult male, 1 subadult male, and 1 male cub. We substantially increased puma capture efforts with ungulate carcasses to bait pumas into cage traps. From August 2, 2005 to June 27, 2006, we used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 23 different sites. This resulted in 11 puma captures, including 4 adult females, 1 adult male, and 1 male cub captured and processed for the first time, and 3 adult females, 1 subadult male, and 1 male cub that were recaptured. Eleven other puma cubs (4 males, 7 females) from 4 litters were captured by hand at nurseries and processed for the first time. We investigated 4 puma mortalities: one adult male was killed by another male puma, 2 cubs (1 male, 1 female) were killed and eaten by other pumas, and 1 female cub died due to the expandable radiocollar she was wearing. To date, 14 pumas (5 males, 9 females) have been monitored with GPS collars, yielding 113 to 1,784 locations per puma, and a total of 13,139 GPS locations. We began quantifying the frequency that puma mothers are away from their cubs during the Colorado puma hunting season (Nov. through Mar.) as a preliminary assessment of potential vulnerability of mothers to harvest. Radio-collared members (mothers and cubs) of 5 families were located 79 times during fixed-wing flights from November 9, 2005 to March 29, 2006. Mothers 95 �were apart from their cubs >600 m during 12 of those occasions (15.2%). Preliminary comparisons between our current puma research on the Uncompahgre Plateau (~21 months duration) and results of the Anderson et al. (1992) puma research on the plateau (~7 years duration 1981-1988) are made where appropriate. We collaborated with colleagues to develop 3 proposals to contribute to the Colorado puma management program. Proposed work includes: testing genetic techniques for non-invasive methods to estimate puma numbers using mark-recapture methods and models, developing state-wide puma habitat models and maps, and assessing puma health. In addition, we will resume quantifying puma use frequencies of ungulates, and considering how research of pumas on developed areas on the Uncompahgre Plateau can contribute to the CDOW’s efforts to study puma-human interactions on the Colorado Front Range. 96 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Continue gathering data on puma movements for the development of sampling methods for markresight or recapture population estimates that might involve sampling puma DNA-genotypes, trail cameras, or direct observations. 6. Begin gathering data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma-prey interactions. Staff on the Front Range placed greater emphasis on puma-human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): 97 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual 98 �population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ ; for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, agespecific natality, sex- and age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥ 50% lower, λ ≤ 1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ = 0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, 99 �mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. 100 �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. 101 �The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma-prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements 102 �recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤ 1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤ 2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤ 10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). 103 �Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤ 10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥ 11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). 104 �Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using using methods such as houndsmen teams or trail cameras. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥ 24 months old, or younger breeders), subadults (young puma independent of mothers, < 24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the binomial survival model (Williams et al. 2001:343-344) or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤ 1 year. Thus, the sampling unit is the individual independent puma (~≥ 1 yr. old). General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture 105 �occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ = Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype or other mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank 106 �correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2005 to July 2006. Our searches to detect puma presence covered the entire study area, but, we allocated most of our effort in areas where we consistently found tracks that we thought were of unmarked pumas. Less effort was allocated to the northeast and southwest areas where we found little or no evidence of pumas. We made 36 puma captures during the period (10 adult females [1 adult female captured twice], 4 adult males, 1 subadult female, 2 subadult males, 14 cubs, and 3 adult or subadult males [1 captured twice] but not handled). As our main method to capture, sample, and mark adult and subadult pumas, we used trained dogs from November 21, 2005 to May 26, 2006. Those efforts resulted in 82 search days, 149 puma tracks detected, 43 pursuits, and 14 puma captures (Table 1). Puma capture efforts with dogs in this period was similar to our efforts in the last (first) report period (Table 2). Only the number of pumas captured for the first time is lower in this period (7 vs. 11). These included 2 males (1 of them captured twice) that could not be handled for safety reasons (Table 3). It is possible that we captured 1 or both of those male pumas in subsequent capture efforts. Moreover, we substantially increased our puma capture efforts by using ungulate carcasses and cage traps from August 2005 to June 2006. We used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 23 sites to capture pumas 11 times (Tables 4, 5, 6). Pumas scavenged 16 of 80 (20%) of the roadkilled ungulate carcasses we used for bait. A total of 11 pumas were captured, sampled, and marked for the first time by using dogs and cage traps, (Table 5), including 1 cub caught with its mother in a cage trap (Table 7). Eleven recaptures of 10 marked pumas were made with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). We captured, sampled, and marked 11 other cubs in 4 litters that were captured by hand at nurseries (Table 7). Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study as it is in this current study. Although our current puma research on the Uncompahgre Plateau has been underway for only about 21 months (compared to 7 years of Anderson et al. 1992), there might be some useful preliminary comparisons between the 2 efforts that we can begin to make in this annual report. As our current effort results in larger samples and progresses in time through the Reference and Treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should become robust, and illuminate new knowledge for pumas in Colorado. In the first 2 winters of puma capture efforts with dogs (1981-82 and 1983), Anderson et al. (1992:33) attempted to capture pumas in 32 and 59 days, respectively, compared to our efforts of 78 and 82 days (2004-05 and 2005-06). In the first winter, they captured 3 female pumas for the first time with an effort of 10.6 days per capture, compared to our 11 pumas (5 males, 6 females) captured for the first time, and an effort of 7.1 days per capture. In the second winter, they captured 7 pumas (4 males, 3 females) for the first time with an effort of 8.4 days per capture, compared to our 7 pumas (5 males, 2 females) captured for the first time with an effort of 11.7 days per capture. In the 7 winters of the 107 �Anderson et al. (1992) study, the average effort was 91.1 days per winter (range = 32 to 136) resulting in average capture effort of 13.9 days per capture. Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not attempt to capture pumas using cage traps or at nurseries like we are (e.g., in about the first 25 months, Anderson et al. captured 11 pumas; we captured 37 pumas in about 20 months). Puma mass recorded by Anderson et al. (1992:86) for puma having an estimated age ≥ 24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in the current study, mass for pumas ≥ 24 months old averaged 59.3 kg for 7 males (SD = 9.3, range 40 to 68 kg) and 39.7 kg for 8 females (SD = 4.8, range = 32 to 46). Sexual dimorphism has been described for puma throughout the species range (Young and Goldman 1946) and has been explained as the result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 We observed 12 puma cubs produced by 5 females (Table 7). Eleven of the cubs were examined at nurseries when the cubs were 29 to 37 days old; the sexes were 4 males and 7 females. A twelfth cub was caught in a cage trap when he was about 183 days (~6 mo.) old. No evidence of siblings was found during that event. The 5 litters were born in May (1), June (1), August (1), and September (2). Puma F3 has produced 2 litters; 1 in August 2005 and 1 in September 2006; for a birth interval of 13 months. Puma M6 is a candidate sire of F3’s September 2006 litter; he and F3 consorted during June 22―24, 2005 (based on their joint GPS location data). From those consorting dates to the estimated birth date, the estimated gestation period for F3’s litter was 93―95 days. Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4)”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al (1992:48). So far in our current research, for 7 postnatal litters about 26 to 42 days old from 7 individual females, the mean (±SD) and extremes of litter sizes were 2.57 ± 0.79, 2 to 4. Sexes of the 18 cubs we examined in 7 litters aged about 26 to 42 days old were 6 males and 12 females. Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. So far, the monthly distribution of puma births we have observed in the current study is: May (3), June (2), August (2), September (2). Considering an average 92-day gestation period (Anderson 1983:33, Logan and Sweanor 2001), breeding of pumas that produced these litters occurred from February through June. Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) compares with our sole observation of a 13-month birth interval for F3 (above). Segment Objective 3 & 4 From December 2, 2004 (start of our research) to June 30, 2006, we monitored 7 adult male and 10 adult female pumas to quantify survival and agent-specific mortality rates (Table 8). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 2 adult males; 1 due to GPS/VHF collar failure (M6). Evidence in the field suggests that M6 might still be alive. The other male (M31) was classified as an adult at first capture because his estimated age was 25 months. However, he might still be in the latter part of the subadult stage and could have moved away from the study area. Our radiotelemetry flights beyond the boundaries of the study area have yet to locate him. All adult female pumas have survived. Adult pumas with which we have lost contact might be recaptured on the study area as our research efforts continue. 108 �Twenty puma cubs (8 males, 12 females) have been monitored by radiotelemetry (Table 10). Two males (M5, M11) are known to have survived to the subadult stage. Two cubs (F13, M22) were killed and eaten by other pumas. F35 died 1 week after we marked her probably as a result of starvation caused when the radiocollar transmitter box got caught in her mouth. We lost contact with 9 cubs (5 females, 4 males) because they shed their expandable radiocollars. Of those 9, three females (F10, F12, F14) subsequently disappeared from the family groups (i.e., we were unable to find tracks of them with other family members) and are believed to have died. As this study proceeds, some cubs with which we have lost contact will probably be re-captured or re-observed, and thus, provide more complete survival information. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 < 24 months old, 10 ≥ 24 months old) from a total of 49 in the previous study where pumas were not hunted. Yet, 19 of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agentspecific survival rates from our current effort will be compared with the Anderson et al. (1992) data set at a later date when we have greater samples, duration in research time, and more complete fate data (i.e., pumas currently without functional collars) to make such comparisons meaningful. Differences might be illuminated. For example, research of a puma population in New Mexico that was not hunted for 10 years indicated that the major cause of death for both sexes and all age stages of pumas was intraspecifies strife, cannibalism, and infanticide (Logan and Sweanor 2001). We have monitored the fates of 3 subadult pumas so far (Table 9). Males M5 and M11 were born on the study area, entered the subadult stage at about 13 months old, and have dispersed from their natal areas. F23 was captured as a subadult, survived to the adult stage, and has given birth to her first litter. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Although we have observed 2 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson’s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and thus expressed in puma populations at different times and different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. Segment Objective 5 Fourteen adult pumas (5 males, 9 females) were fit with Lotek 4400S GPS collars since field research began in December 2004. The collars are programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 113―1,784 (Table 11). Activity areas for GPS-collared pumas during this report period were estimated (Table 12) with fixed kernel and minimum convex polygon home range estimators (ArcView 3.2 Animal Movement Extension), and mapped (Fig. 2). In addition, 1 adult female (F30), 1adult male (M32), and 1 independent male (M31, i.e., subadult or adult) were monitored with VHF radiocollars. The number of locations for those 3 pumas were not sufficient to estimate the size of activity areas (Table 13), however, their activity areas or locations are mapped on Fig. 2. 109 �Anderson et al. (1992) provided an exhaustive analysis of seasonal puma home ranges and movements using data collected from VHF-collared animals during 1982 to 1988. We have not yet conducted an exhaustive analysis of adult puma home ranges and movements with the GPS data from our current puma research efforts in the past 21 months. Instead, we provide only limited descriptive information in Table 13 and Fig. 2. Given the different types of location data and analytical methods, only broad descriptive comparisons might be made between the 2 studies at this time. Elemental similarities in home range attributes of pumas in the Anderson et al. (1992) research and our current effort, include: current home ranges of some puma overlap extensively with home ranges of puma documented by Anderson et al (1992), home ranges of male and female pumas are large, male home ranges are larger that female home ranges, male home ranges overlap multiple female home ranges, female home ranges overlap other female home ranges sometimes extensively, male home ranges overlap other male home ranges to a lesser extent than female home ranges. These characteristics are generally similar for pumas in other populations that have been studied with adequate intensity and duration (Beier and Barrett 1993, Logan and Sweanor 2001), and reflect behavioral tactics of male and female pumas that might contribute to individual survival and reproductive success (Logan and Sweanor 2001). Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we started gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fare game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that ≤ 6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). From November 9, 2005 to March 29, 2006 we located 4 to 5 radio-collared families of puma mothers and cubs from fixed-wing aircraft 79 times (Table 14).To assess whether mothers were apart or in close association with cubs, we needed to consider error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and fixed with GPS and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Sixty-seven (84.8%) of observations located mothers and cubs ≤ 500 m apart, within the extreme margin of location error. Mothers were ≥ 650 m from their cubs during 12 (15.2%) of the observations (mean distance = 1,060 m, SD = 325.99, range = 650 to 1,600). Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Three proposals were developed with colleagues in the CDOW and Colorado State University to meet some of the objectives of the Uncompahgre Plateau puma population research and to enhance the state-wide puma management program. CDOW and our CSU colleagues are currently seeking funding to support the proposals. A proposal titled: A Non-invasive Method to Estimate Puma Populations based on DNA Genotype Mark-recapture, was developed in collaboration with geneticist Dr. Marlis Douglas (CSU). We propose to use the intensively studied puma population on the Uncompahgre Plateau for gathering genetic material to develop and test molecular techniques as a means of individually genotyping puma. If successful, the methods will be used in the field and laboratory to estimate the puma population on the 110 �Uncompahgre Plateau study area. As part of our current puma capture protocol, we collect puma tissues (i.e., integument, blood, feces, hair) and archive them with Dr. Douglas, who will lead the genetics research. We developed a proposal titled: Colorado Puma Habitat Models and Maps in collaboration with Dr. Kevin Crooks, Dr. Dave Theobald, and Dr. Ken Wilson (CSU) to develop puma habitat models and maps for the entire state of Colorado. Furthermore, we are collaborating with Dr. Crooks to assess if the GPS data currently available on pumas from this project can be used to develop a graduate degree program that investigates puma habitat use on the Uncompahgre Plateau. We collaborated with Dr. Sue VandeWoude (CSU) to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to her laboratory for pending analysis. Intensive effort to quantify puma use rates on ungulates by investigating puma GPS clusters was suspended in this report period, because we discovered in our work last year that such effort was time consuming and distracted some members of our research team from our principal objectives pertaining to puma population dynamics. Yet, our work last year proved the reliability of the GPS technology to allow us to gather quantitative information on ungulate prey use rates by pumas. In that effort, 7 GPS-collared adult pumas (3 males, 4 females) used 61 mule deer and 48 elk at 139 puma GPS clusters we investigated. In contrast, when Anderson et al. (1992) studied the pumas during 1981 to 1988, they found 68 mule deer and 3 elk used by pumas. These differences might reflect a greater number and distribution of elk currently on the Uncompahgre Plateau (~1,500 elk in GMU 62 vs. 9,663 elk in E20, sources Anderson et al. 1992:15, CDOW unpubl. 2004 post-hunt elk estimate, respectively), and poses new questions about the impact of puma predation on mule deer as a function of greater availability of elk. Consequently, the CDOW has provided additional support for a 6-month temporary technician to gather such data during the next year. An assessment will be made at the end of that work on whether we should expand the effort to investigate year-round puma use rates of ungulates on the Uncompahgre Plateau. We will evaluate the potential for collaborative research on puma-human relationships on the Uncompahgre Plateau with the developing CDOW puma-human research on the Colorado Front Range. To date, we have gathered location data on 6 (4 adult females, 2 adult males) GPS-collared pumas that have activity areas on the developed southeast portion of our study area, which includes: Fairway Pines, Loghill Village, and Fisher Creek subdivisions, numerous other private homes, Fairway Pines golf course and driving range, all adjacent to Ridgeway State Park (Fig. 3). This is the same area that Anderson et al. (1992:80) received 17 useable questionnaires on puma observations from residents, and also had some radio-collared puma frequenting these same developments. Linking puma-human research on the Uncompahgre Plateau and Front Range provides opportunities for increasing sample size (i.e., puma numbers, study sites) and observing variation in puma-human relationships. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 20 months of effort, 36 pumas (14 adults, 3 subadults, 19 cubs) have been captured, sampled, marked, radio-collared and released to quantify vital rates and puma population dynamics in a reference situation (i.e., without sport-hunting off-take). Data on research efforts and puma capture, fates, reproduction, and activity areas are presented. As of July 2006, 20 radio-collared puma are within the study area. Fourteen adult pumas were fit with GPS collars, yielding 113 to 1,784 locations per puma. We started investigating the potential vulnerability of puma mothers to capture by hunters while away from their cubs. Preliminary comparisons of aspects of puma biology and ecology were made between our new research effort on the Uncompahgre 111 �Plateau and that of Anderson et al. (1992) in GMU 62 during 1981 to 1988. Research efforts for year 3 will focus on increasing numbers and distribution of sampled, marked, and GPS/radio-collared pumas on the study area, especially in the northeast and southwest portions of the study area where we have been finding relatively little evidence of pumas, possibly due to low density. Efforts will resume to estimate frequency of puma use of mule deer and elk on the Uncompahgre Plateau. Puma GPS location data will be used to: design enumeration methods in the field, develop and test puma habitat models and maps, and develop research on puma-ungulate relationships on the Uncompahgre Plateau contingent upon funding and support. We will increase our efforts to obtain outside funding for other projects we have proposed on puma genetics, puma habitat use, modeling, and mapping, and puma diseases. We will consider incorporating pumas on the Uncompahgre Plateau to address questions pertaining to research on pumahuman relationships on the Colorado Front Range. 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Okarma, and P. R. Sievert, editors. Wildlife, land, and people: priorities for the 21st century. Proceedings of the Second International Wildlife Management Congress. The Wildlife Society, Bethesda, Maryland, USA. KOLOSKI, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. KREEGER, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. LAUNDRE, J. W., L. HERNANDEZ, D. STREUBEL, K. ALTENDORF, AND C. L. LOPEZ GONZALEZ. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. LOGAN, K. A., E. T. THORNE, L. L. IRWIN, AND R. SKINNER. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. 112 �_____, L. L. SWEANOR, J. F. SMITH, AND M. G. HORNOCKER. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, AND L. L. SWEANOR. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2004. Colorado puma research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center, Ft. Collins. MURPHY, K., M. CULVER, M. MENOTTI-RAYMOND, V. DAVID, M. G. HORNOCKER, AND S. J. O’BRIEN. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. OTIS, D. L., K. P. BURNHAM, G. C. WHITE, AND D. R. ANDERSON. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. OTT, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. PIERCE, B. K., V. C. BLEICH, AND R. T. BOWYER. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. POLLOCK, K. H., S. R. WINTERSTEIN, C. M. BUNCK, AND P. D. CURTIS. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. WINTERSTEIN, AND M. J. CONROY. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. NICHOLS, C. BROWNIE, AND J. E. HINES. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. ROSS, P. I., AND M. G. JALKOTZY. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. STONER, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. SWEANOR, L. L., K. A. LOGAN, AND M. G. HORNOCKER. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. LOGAN, J. W. BAUER, W. M. BOYCE, AND B. MILSAP. 2006 in review. Puma-human relationships in a California, USA state park. Biological Conservation. VAN BALLENBERGHE, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. YOUNG, S. P. AND E. A. GOLDMAN. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: Kenneth A. Logan, Wildlife Researcher 113 �Table 1. Summary of puma capture efforts with dogs from November 21, 2005 to May 26, 2006, Uncompahgre Plateau, Colorado. Month November No. Search Days 4 December 18 January No. & type of puma tracks founda No. & type of pumas pursued No. & I.D. or type of pumas captured 12 tracks: 2 male, 9 female, 1 unspecified sex 16 tracks: 10 male, 4 female, 2 unspecified sex 0 pursuits 0 captures 5 pursuits: 4 males, 1 female 19 50 tracks: 15 male, 23 female, 12 cub 11 pursuits: 4 males, 4 females, 3 cubs February 19 9 pursuits: 2 males, 3 females, 4 cubs March 7 39 tracks: 11 male, 14 female, 9 cub, 5 unspecified sex 11 tracks: 2 male, 5 female, 4 cub 11 tracks: 3 male, 5 female, 3 cub 2 pumas captured 3 times: M5 recaptured, 1 male captured twice but not handledb 3 pumas captured: F23, F24, 1 male not handled 1 puma captured: F8 recaptured 7 pursuits: 1 male, 3 females, 3 cubs 9 pursuits: 3 males, 4 females, 2 cubs 2 pumas captured: M27, F8 recaptured April 7 3 puma captured: M29 & M31 captured, M15 recaptured 2 pursuits: 1 male, 1 female 2 pumas captured: F24 May 8 10 tracks: 5 male, 5 female recaptured, M1 recaptured 82 149 tracks found: 48 male, 43 pursuits: 15 males, 16 14 captures: 3 males & 2 TOTALS females, 12 cubs females captured for the 1st 65 female, 28 cub, 8 time, 2 different males unspecified sex captured 3 times but not handled, 1 male recaptured, 2 females recaptured 3 times, 1 subadult male recaptured, 1 subadult or adult male recaptured, 1 male cub recaptured a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female. b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. Table 2. Summary of puma capture efforts with dogs, December 2004 to May 2006, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Track detection effort 109/78 = 1.40 tracks/day 149/82 = 1.82 tracks/day Pursuit effort 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 82/43 = 1.91 day/pursuit 82/14 = 5.86 day/capture 114 Effort to capture a puma for the first time 11 pumas captured for first time (minus M1, F3, & large female) 11/78 = 0.14 capture/day 78/11 = 7.09 day/capture 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture �Table 3. Pumas that were captured with aid of dogs, but were not handled for safety reasons, from December 2005 to January 2006, Uncompahgre Plateau, Colorado. Puma sex Age stage Capture date 12-04-05 Male subadult or adult Male Male Location Roatcap Mesa subadult or adult 12-05-05 Cushman Creek adult 01-22-06 San Miguel River Canyon Comments Puma climbed to top of huge Ponderosa pine tree. This puma might be M32. This puma was the same animal caught 12-04-05. Climbed tall spruce tree on a ledge. Puma climbed Ponderosa pine tree beside the river. This puma might be M29. Table 4. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 2, 2005 to June 27, 2006, Uncompahgre Plateau, Colorado.a Month August No. of Sites 4 Puma activity & capture effort results Male puma scavenged a mule deer on 8-20-05. Cage trap set 8-20 & 8-21-05; puma did not return. September 7 Male puma scavenged a mule deer on 9-16-05; subadult M5 was recaptured there and was fit with a VHF collar (he had shed the expandable collar he wore as a cub). October 10 Puma F16 captured 10-11-05 at an elk kill. Puma scavenged mule deer on 10-17-05. Cage trap set 10-18 and 10-19-05; puma did not return. November 12 Puma F16 recaptured 11-1-05 at a mule deer kill; her faulty GPS collar was replaced. Puma F16 scavenged a mule deer on 11-27-05. No attempt to recapture her. December 1 No puma activity detected. January 2 No puma activity detected. February 9 Puma F25 and cub M26 captured 2-8-06 at a mule deer kill. Puma F7 scavenged a mule deer on 2-26 & 2-17-06. No attempt to recapture her. Puma F3 scavenged a mule deer on 2-26-06. No attempt to recapture her. March 11 Male puma completely scavenged a mule deer over the weekend of 3-18 & 1906. Female puma completely scavenged a mule deer over the weekend of 3-18 & 19-06. Female puma scavenged a mule deer 3-21 to 3-23-06; puma F28 was captured there 3-23-06. Pumas F3 & cub F21 scavenged a mule deer 3-23 to 3-27-06. No attempt was made to recapture the pumas. Female puma completely scavenged a mule deer over the weekend of 3-25 & 26-06. Puma F7 was recaptured at a mule deer she scavenged on 3-30-06; her GPS collar was replaced. April 11 Puma F30 captured 4-15-06 at a mule deer kill. Male puma scavenged a mule deer on 4-20-06. Cage trap was set 4-20 & 4-2106; puma did not return. Male puma scavenged the same mule deer on 4-26-06; M32 was captured there on 4-26-06. Puma F2 and cubs F9 & M11 scavenged a mule deer on 4-2-06. Cub M11 was recaptured on 4-2-06 and fit with a VHF collar. F2 was recaptured there 4-3-06 and her GPS collar was replaced. May 0 No fresh road-killed ungulate carcasses were available. June 3 No puma activity. a We used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma-killed elk at 23 different sites. Of the road-killed ungulate baits, 16 of 80 (20.0%) were scavenged by pumas. 115 �Table 5. Adult and subadult pumas captured for the first time, sampled, tagged, and released from October 2005 to April 2006, Uncompahgre Plateau, Colorado. Puma I.D. Sex Estimated Age (mo.) Mass (kg) Capture date Capture method F16 F 33 42 10-11-05 Cage trap F23 F24 F25 M27 F28 M29 F30 M31 M32 F F F M F M F M M 17 57 80 55 33 80 33 25 56 42 38 46 61 43 65 34 40 57 01-04-06 01-17-06 02-08-06 03-10-06 03-23-06 04-14-06 04-15-06 04-19-06 04-26-06 Dogs Dogs Cage trap Dogs Cage trap Dogs Cage trap Dogs Cage trap Location Ridgeway Reservoir Dam, Ridgeway State Park San Miguel River Canyon Horsefly Creek (west) Loghill Mesa Big Bucktail Creek Big Bucktail Creek Big Bucktail Creek Wildcat Canyon Craig Draw Spring Creek Table 6. Pumas recaptured with dogs and cage traps, September 2005 to May 2006, Uncompahgre Plateau, Colorado. Puma I.D. Recapture date Mass kg Estimated Age (mo.) M5 F16 M5 F8 F8 F7 M11 F2 M15 F24 M1 09-16-05 11-01-05 12-30-05 02-07-06 03-21-06 03-30-06 04-02-06 04-03-06 04-13-06 05-17-06 05-26-06 39 42 Observed Observed Observed 35 32 43 23 Observed Observed 13 34 16 32 33 69-77 10 64 9.5 61 51 Capture Method Cage trap Cage trap Dogs Dogs Dogs Cage trap Cage trap Cage trap Dogs Dogs Dogs Process Re-collared Re-collared None None None Re-collared Re-collared Re-collared Re-collared None None Table 7. Puma cubs sampled August 2005 to June 2006 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) F17 F Sept. 22, 2005 34 2.5 F16 32 F18 F Sept. 22, 2005 34 2.0 “ “ M19 M Sept. 22, 2005 34 2.0 “ “ M20 M Sept. 22, 2005 34 2.1 “ “ F21b F Sept. 26, 2005 37 2.8 F3c 49 M Sept. 26, 2005 37 2.8 “ “ M22b M26d M Aug. 2005 183 12.0 F25 74 F33 F May 30, 2006 31 1.9 F23 21 F34 F May 30, 2006 31 1.9 “ “ F35 F May 30, 2006 31 2.2 “ “ F36 F June 9, 2006 29 1.9 F28 36 M37 M June 9, 2006 29 2.1 “ “ a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. b Puma M6 is a candidate sire of cubs F21 & M22; he consorted with F3 (based on their joint GPS location data) during June 22―24, 2005. This would indicate a gestation period of 93―95 days. c F3 gave birth to a previous litter in August 2004. From that litter, offspring M5 survived to independence. Birth interval is 13 months (Aug. 2004 to Sept. 2005). d Estimated age of M26 was based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data, i.e., ~6 mo. ≈183 days). He was initially captured in a cage trap with his mother F25 on Feb. 8, 2006. 116 �Table 8. Summary for individual adult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma I.D. Monitoring span No. days Status: Alive/Lost contact/Dead; Cause of death M1 12-08-04 to 06-30-06 569 Alive. M4 01-28-05 to 12-28-05 333 Dead; killed by a male puma.a M6 02-18-05 to 02-22-06 369 Lost contact― failed GPS/VHF collar. M27 03-10-06 to 06-30-06 112 Alive. M29 04-14-06 to 06-30-06 77 Alive. M31 04-19-06 to 04-26-06 7 Lost contact.b M32 04-26-06 to 06-30-06 65 Alive. F2 01-07-05 to 06-30-06 539 Alive. F3 01-21-05 to 06-30-06 525 Alive. F7 02-24-05 to 06-30-06 491 Alive. F8 03-21-05 to 06-30-06 466 Alive. F16 10-11-05 to 06-30-06 262 Alive. F23 02-05-06 to 06-30-06 146 Alive. F24 01-17-06 to 06-30-06 164 Alive. F25 02-08-06 to 06-30-06 142 Alive. F28 03-23-06 to 06-30-06 99 Alive. F30 04-15-06 to 06-30-06 76 Alive. a Puma M4 died at the estimated age of 37―45 months old. b Puma M31 estimated age at capture was 25 months, at the lower margin of puberty. But he might have been a dispersing subadult, instead of an adult. He may have moved away from the study area. No VHF signals have been received of M31 in the area surrounding the study area as of 07-29-06. Table 9. Summary of subadult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma Monitoring span No. Status: Alive/Survived to adult stage/ I.D. days Lost contact/Dead; Cause of death M5 09-16-05 to 06-30-06 287 Alive; dispersed from natal area. M11 06-21-06 to 06-30-06 7 Alive; dispersed from natal area. F23 01-04-06 to 02-04-06 31 Alive; survived to adult stage; gave birth to first litter at ~21 months old. 117 �Table 10. Summary for individual puma cub survival and mortality, December 2004 to July 2006, Uncompahgre Plateau, Colorado. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Age to last monitor date alive or at death Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/Dead; Cause of death Mother I.D. M5 183 02-04-05 to 06-30-06 22 mo. F3 F9 31 F10 31 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 329 days 207―246 days M11 31 06-27-05 to 07-11-06 14 mo. F12 42 07-01-05 to 12-08-05― 01-26-06 245―294 days F13 42 F14 26 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 100 days 226―257 days M15 26 F17 34 F18 34 M19 34 M20 34 F21 37 M22 37 07-22-05 to 06-06-06 10-26-05 to 06-06-06 10-26-05 to 06-30-06 10-26-05 to 07-27-06 10-26-05 to 05-24-06 11-02-05 to 06-30-06 11-02-05 to 12-21-05― 12-22-05 345 days 257 days 281 days 306 days 244 days 277 days 86―87 days Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 13 mo. old . Lost contact― shed radiocollar 04-1906―04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Lost contact― shed radiocollar 07-2805―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified). Lost contact― shed radiocollar 01-2006―01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-0606―06-14-06. Lost contact― shed radiocollar 06-0606―06-14-06. Alive. M26 183 F33 31 F34 31 F35 31 F36 29 M37 29 02-08-06 to 03-21-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 224 days 62 days 62 days 38 days 49 days 49 days Puma I.D. a F2 F2 F2 F7 F7 F8 F8 F16 F16 Lost contact― shed radiocollar 07-2706―08-02-06. Lost contact― shed radiocollar 05-2406―05-25-06. Alive. F16 Dead; killed and eaten by male puma 12-2105―12-22-05. F3 Lost contact― shed radiocollar 03-2106―03-24-06. Alive. F25 Alive. F23 Dead; research-related fatality.a F23 Alive. F28 Alive. F28 F16 F3 F23 Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. 118 �Table 11. Numbers of GPS locations for adult puma on the Uncompahgre Plateau, Colorado, December 2004 to June 2006. Puma I.D. M1 M4 M6 M27 M29 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a No. locations M M M M M F F F F F F Acquisition rate average, range, nb 77, 73―84, 13 70, 57―84, 10 84, 73―93, 9 77, 67―84, 3 68, 63―75, 3 75, 43―90, 18 76, 55―88, 17 67, 26―86, 17 70, 48―81, 14 76, 58―90, 10 79, 45―92, 6 adult 12-08-04 to 06-21-06 1,784 adult 01-28-05 to 12-28-05e 910 926 adult 02-18-05 to 11-23-05f adult 03-11-06 to 06-21-06 316 adult 04-14-06 to 07-27-06 287 1,664 adult 01-07-05 to 07-12-06 1,649 adult 01-21-05 to 07-26-06 1,423 adult 02-24-05 to 07-26-06 1,328 adult 03-21-05 to 07-05-06 833 adult 10-12-05 to 07-03-06 113 subadult, 01-04-06 to 02-04-06 02-05-06 to 07-17-06 511 adult 523 88, 86―93, 5 F24 F adult 01-17-06 to 06-14-06 551 78, 68―87, 5 F25 F adult 02-09-06 to 07-12-06 321 74, 61―89, 4 F28 F adult 03-24-06 to 07-07-06 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download for an individual puma in this report. b n = number of remote downloads. Table 12. Estimated use areas of GPS-collared pumas on the Uncompahgre Plateau, Colorado, 2005 to 2006.a Puma I.D. No. locations Time span No. months 95% Fixed kernel (km2) 50% Fixed kernel (km2) 100% Minimum convex polygon (km2) 1,129.0 318.5 542.0 504.0 288.3 183.0 194.0 139.0 215.0 74.3 226.0 111.7 115.9 114.8 M1 1,083 07-01-05 to 06-21-06 12 988.1 189.1 M4b 481 07-01-05 to 12-28-05 5 208.8 29.6 465 07-01-05 to 11-23-05 4.8 550.8 67.3 M6c M27 316 03-11-06 to 06-21-06 3.3 452.0 40.3 M29 220 04-14-06 to 06-30-06 2.5 276.1 14.0 F2 1,173 07-01-05 to 06-30-06 12 67.6 6.9 F3 1,079 07-01-05 to 06-30-06 12 84.3 11.7 F7 1,058 07-01-05 to 06-30-06 12 110.4 16.2 F8 1,043 07-01-05 to 06-30-06 12 84.1 7.7 F16 825 10-12-05 to 06-30-06 8.6 39.9 4.8 F23 566 01-04-06 to 06-30-06 5.9 109.2 13.0 F24 574 01-17-06 to 06-30-06 5.5 26.8 2.4 F25 453 02-09-06 to 06-30-06 4.7 105.5 16.1 F28 306 03-24-06 to 06-30-06 3.2 86.2 14.8 a Use areas were estimated by using the Animal Movement extension in ArcView 3.2. b Puma M4 died on 12-28-05; he was killed by a male puma. c Puma M6’s GPS collar malfunctioned on 11-23-05. His last VHF location was fixed on 02-22-06. The VHF beacon failed after that date. Table 13. VHF-radio-collared independent pumas on the Uncompahgre Plateau, Colorado, 2006. Puma I.D. F30 M31 Sex Age stage Dates monitored No. locations F M 04-15-06 to 06-28-06 04-09-06 to 04-26-06 11 2 M32 M Adult Adult or subadult Adult 04-26-06 to 06-28-06 6 119 �Table 14. Summary of puma mother and cub associations by distance (m) during fixed-wing flights, November 9, 2005 to March 29, 2006. Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with No. observations with mothers & cubs mothers & cubs ≤500 m >600 m apartb apart Nov. 3 4 2―6 10 2 Dec. 4 4 3―7 16 4 Jan. 5 4 4―8 16 4 Feb. 4 5 5―9 16 2 Mar. 2 5 6―10 9 0 Totals 18 4―5 2―10 67 12 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650―1,600. GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report for the puma management goal (at top). 120 �! ( ! ( ! ( ! ( ! ( Clifton County Boundary Highways Study Area ! ( ! ( ! ( ! ( ! ( Delta ! ( M1 ! ( ! ( M32 Montrose F8 M27 ( ! F23 ! ( ! ( F3 M31 M4 F7 F28 F24 F30 F2 M6 ( ! F16 F25 ! ( Ridgeway M29 ! ( Norwood ! ( ! ( 0 5 10 20 30 40 Kilometers ! ( Figure 2. The Uncompahgre Plateau Puma Study Area with activity areas of GPS- and VHF- radiocollared pumas depicted with 100% Minimum Convex Polygons (for ease of viewing), and 2 locations of one independent puma for which we lost contact (M31), 2005 to 2006. 121 �Figure 3. Locations of 6 GPS-collared pumas on the human-developed southeast portion of the Uncompahgre Plateau puma study area, 2005-2006, intended only to show potential for developing research on puma-human relationships on this study area and the Colorado Front Range. 122 �Colorado Division of Wildlife July 2006 – June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Puma Population Structure and Vital Rates on the Uncompahgre Plateau : Period covered: August 1, 2006―July 30, 2007 Author: K. A. Logan. Personnel: K. Logan, B. Bavin, B. Dunne, J. Mannas, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young, and J. McNamara of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks with financial support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. Puma capture efforts resulted in a total of 54 puma captures (9-10 adult females [1 female captured twice], 7 adult males [1 male probably captured 3 times, and another captured twice], 1 subadult female, 0-1 other subadults, and 30 cubs [4 captured twice each]). Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 13, 2006 to May 11, 2007. This resulted in 22 puma captures, including 1 adult female, 1 adult male, 2 adult males, and 2 male cubs captured and processed for the first time. One female (adult or subadult) and 2 cubs were not handled for safety reasons. Capture efforts with ungulate carcasses and cage traps resulted in 8 puma captures, including 4 adult females, 2 adult males, 1 subadult female, and 1 female cub. Of those animals, 1 adult female, 1 adult male, the subadult female, and the female cub were captured for the first time. Capture efforts during November 2006 through May 2007 enabled us to estimate a minimum count of 24 independent pumas detected on the Uncompahgre Plateau study area during that time. The count included 16 females and 8 males. We captured, sampled, and marked 26 puma cubs produced by 10 females. Twenty-three of the cubs were examined at 8 nurseries when the cubs were 29 to 41 days old. Since the start of this study, 38 cubs from 13 litters aged 29 to 42 days old had a sex ratio of 21 males:17 females. The mean (±SD) and extremes of litter sizes were 2.84 (±0.99), 1 to 4. Eight birth intervals for 7 different females averaged 14.99 months (SD = 3.40), and ranged from 11.7 to 20.5 months. Four gestation periods averaged 92.0 days (SD = 1.68). Of 9 adult males and 12 adult females radio-monitored to quantify survival and agentspecific mortality rates, 1 male and 1 female are known to have died from natural causes. Of 6 subadult pumas monitored via radio-telemetry, none died. Thirty-nine puma cubs (20 males, 19 females) have been monitored by radiotelemetry for varying durations. Among those, 12 deaths were documented, including 7 from intra-species strife, 1 killed by coyotes, 1 killed by a vehicle, and 3 died due to research activities. 111 �Twenty adult pumas (7 males, 13 females) fit with GPS collars since field research began in December 2004 have yielded 113 to 2,759 locations per individual puma. Winter activity areas were estimated for 12 (9 female, 3 male) GPS-collared adult pumas. As an index to the vulnerability of puma mothers to sportharvest we monitored mother-cub distances from an airplane during November to March. Puma mothers were ≥520 m from their cubs during 16.3% of the observations (mean distance = 1,120 m, SD = 1,214.40, range = 616 to 4,101). These results were similar to our results the previous winter (15.2%). A collaborative effort to investigate puma use of ungulates on the Uncompahgre Plateau resumed. GPS clusters were investigated for 13 GPS-collared adult pumas (8 female, 5 male). A total of 257 clusters were investigated. Mule deer and elk were about equally important to pumas as food. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (31 months duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Proposed work includes: continuing investigations of puma use of ungulates, developing and testing methods and models to estimate puma abundance, and collaborating with colleagues to assess puma health. In addition, we will consider how research of pumas on developed areas on the Uncompahgre Plateau can contribute to the CDOW’s efforts to study puma-human interactions on the Colorado Front Range. 112 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Continue gathering data on puma movements for the development of sampling methods for markresight or recapture population estimates that might involve sampling puma DNA-genotypes, trail cameras, or direct observations. 6. Begin gathering data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): 113 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 114 �1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ); for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, agespecific natality, sex- and age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥50% lower, λ ≤1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ = 0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those 115 �quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded 116 �by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using 117 �recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma―prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe 118 �physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are 119 �away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF 120 �collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using using methods such as houndsmen teams or trail cameras. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the binomial survival model (Williams et al. 2001:343-344) or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). 121 �General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ = Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype or other mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not 122 �linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2006 to July 2007. Our searches to detect puma presence covered the entire study area. We allocated most of our effort in areas where we consistently found tracks that we thought were of unmarked pumas, particularly in the northeast and southwest areas where we found little or no evidence of pumas during the previous 2 years. We made 54 puma captures during the period (9-10 adult females [1 adult female captured twice], 7 adult males [1 adult male probably captured 3 times, another captured twice], 1 subadult female, 0-1 other subadults, and 30 cubs [4 of them captured twice each]). As our main method to capture, sample, and mark adult and subadult pumas, we used trained dogs from November 13, 2006 to May 11, 2007. Those efforts resulted in 78 search days, 177-178 puma tracks detected, 45-47 pursuits, and 22 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was similar to our efforts in the 2 previous efforts (Table 2). But, the frequency of pursuits and puma captures has increased over the 2 previous periods. In addition, the number of adult and subadult pumas captured for the first time declined from 11 (Oct. 2005 to Apr. 2006) to 6 (this period). This included 1 adult female or subadult puma that could not be handled for safety reasons (see Tables 3 and 4). Of the pumas we captured, but could not handle, it is probable that we captured and marked 1 adult male (M51) and 1 adult female (F50) in subsequent capture efforts. Our puma capture efforts using ungulate carcasses and cage traps extended from August 2006 to July 2007. We used 64 road-killed mule deer, 7 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 26 sites to capture pumas 8 times (Tables 5). Pumas scavenged 16 of 71 (22.5%) of the roadkilled ungulate carcasses used for bait. This was similar to the results last years (16 of 80, 20%). Five pumas were captured, sampled, and marked for the first time by using dogs and cage traps, (Table 3). Fifteen recaptures of 13 marked pumas were made with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). We captured, sampled, and marked 26 cubs in 10 litters that were captured by hand at nurseries (Table 7). Search efforts throughout the study area also revealed the presence of at least 4 other independent females and 1 independent male. The tracks we found of those animals were too old to pursue (i.e., probability of capture with the dogs was negligible). We could separate the activity of those pumas from the GPS- and VHF- collared pumas in time and space. In addition, 2 of the females were in association with cubs. One female was followed by 2 cubs about 5 to 6 months old in December and January, when we captured but could not handle 1 or 2 of the cubs (Table 4). Another female was followed by 1 large cub (probably a male) likely 10 or more months old. And another female on the southwest portion of the 123 �study area might have been an adult if it were associated with a female cub (~6 mo. old) that was hit and killed by a vehicle on highway 62 on January 28, 2007. Our search and capture efforts during November 2006 through May 2007 enabled us to estimate a minimum count of 24 independent pumas detected on the Uncompahgre Plateau study area. The count included 16 females and 8 males. Of those, 12 adult females and 7 adult males were probably marked animals (79% of independent pumas detected). Of the remainder, 2 females were adults because they were followed by cubs, and 2 females and 1 male were of unknown independent status (i.e., either subadult or adult). Figure 2 indicates the estimated use areas of those independent pumas. Some of the animals range outside the borders of the study area, as indicated by movements of GPS- and VHFcollared pumas. There appears to be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 8 independent pumas (5 females― 4 marked, 1 unmarked; 3 males― 2 marked, 1 unmarked). The east slope count includes 16 independent pumas (11 females― 8 marked, 3 unmarked; 5 males― all marked). Female home ranges overlap other female home ranges extensively, and are overlapped by male home ranges. Male home ranges overlap multiple female home ranges, and overlap other male home ranges somewhat. Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study as it is in this study Reference Period. As our current effort results in larger samples and progresses in time through the Reference and Treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 2.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete, yet, our data set enables some preliminary comparisons with Anderson’s completed work (Anderson et al. 1992). In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). They captured 47 pumas for an average capture rate of 13.9 days per puma. Eight other pumas, all female cubs ≤7 months old, were caught in steel leg-hold traps by trappers, and were added to the study animal population. So far, in our 3 winters, the average effort is 79.3 days (range = 78 to 82). Of 123 pursuits, 50 (41%) were successful. We captured and GPS- or VHF-collared 25 pumas for the first time, yielding a capture rate of 10.0 days per capture. Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or at nurseries like we are. In their effort, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. In our current effort, we captured, sampled, and marked 68 pumas, of which 61 were radio-collared. Puma mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old averaged 59.8 kg for 9 males (SD = 8.1, range 40 to 68 kg) and 38.4 kg for 11 females (SD = 4.9, range = 31 to 46). Sexual dimorphism has been described for puma throughout the species range (Young and Goldman 1946) and has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 We captured, sampled, and marked 26 puma cubs produced by 10 females (Table 7). Twentythree of the cubs were examined at 8 nurseries when the cubs were 29 to 41 days old. The sexes were 17 124 �males and 6 females. Four other cubs, including 2 males and 2 females, were caught when they were about 158 to 215 day old. In addition to those offspring, 2 cubs, about 152 to 183 days old, were detected in association with an unmarked female that we pursued. One or 2 of those cubs were captured in different events; the female sex was determined for one of the cubs. But, neither cub could be handled safely for further sampling. The estimated birth month for the 10 litters were April (1), May (1), July (5), August (2), and September (1). During the past 27 months of this work we compiled data on puma reproduction that was heretofore not available for Colorado. We examined 38 cubs from 13 litters aged 29 to 42 days old where we were reasonably sure that we examined all the cubs at the nurseries. The sex ratio of the observed cubs was 21 males:17 females. The mean (±SD) and extremes of litter sizes were 2.84 (±0.99), 1 to 4. The distribution of puma births by month indicate puma births extending from March into September, with 18 of 20 births occurring May to September (Fig. 3). In addition, 8 birth intervals for 7 different female pumas averaged 14.99 months (SD = 3.40), and ranged from 11.7 to 20.5 months (Table 8). Based on observations (from GPS data) of associations between 4 mothers and putative sires, 4 gestation periods averaged 92.0 days (SD = 1.68), which is consistent with average puma gestation reported in literature (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al (1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 20 litters adds to Anderson’s data (Fig. 3), and indicates puma births in Colorado occurring in every month except January and November (so far). Our data suggests that the majority of puma breeding activity occurs February through June. Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (above). Segment Objective 3 & 4 From December 2, 2004 (start of our research) to July 31, 2007, we radio-monitored 9 adult male and 12 adult female pumas to quantify survival and agent-specific mortality rates (Table 9). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 3 adult males apparently due to GPS/VHF collar failure (M1, M6, M27). Evidence in the field suggests that all 3 males might still be alive. One adult female is known to have died. F50 was about 29 to 31 months old when she apparently died of natural causes (exact agent could not be identified). We have radio-monitored 6 subadult pumas (Table 10). None of those died while we were monitoring them. F23 has become a breeding adult on the study area. M5 dispersed from his natal area and the study area at about 13 months old and went to the northwest slope of the Uncompahgre Plateau where he has apparently established an adult territory. M49 was orphaned at 9 months old when his mother F50 died. He has since dispersed from his natal area and the study area to the northeast slope of the Uncompahgre Plateau. We continue to monitor his status. On the other hand, we have lost contact with 2 subadult males and 1 subadult female. Puma M11 became a subadult at 13 months old and dispersed from his natal area at 14 months old. He was last located in the Dolores River valley between Stapletone and Stoner, Colorado, on December 14, 2006. F52 dispersed from the study area before we lost track of her in the area of the Black Canyon of the Gunnison in mid-May 2007. We lost track of M31 seven days after he was captured. He might have dispersed from the study area. Efforts to locate him by 125 �flying over and around the study area have not been successful. Dispersal rates and distances will be reported after we have compiled more complete data. In addition to the subadults discussed above, a nonmarked female puma about 18 to 24 months old was killed by a vehicle November 4, 2006 on highway 550, which forms the southeast boundary of our study area. The female appeared to be in good health (41 kg), was not pregnant, and was not lactating. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). The current closure on sport-hunting on the study area and protection of marked pumas from sport-harvest on the buffer area on the northern portion of the Uncompahgre Plateau for the Reference Period appears to be operating, so far. None of the adult or subadult pumas wearing functional GPS- or VHF- collars have died due to human causes. This reference condition enables us to quantify puma survival rates and agent-specific mortality rates of adult and subadult pumas (i.e., harvest-age pumas) in the absence of direct human-caused mortality factors related to sport-hunting. So far, survival of radiomonitored adult and subadult pumas in the study and buffer areas appears to be high. In addition, the population sex and age structure can be examined in this reference condition. As indicated in Figure 4, the adult age structure appears to be indicative of high survival rates during the past 3 winters without sporthunting mortality. These data will be valuable in comparisons of sex and age structure during the Treatment Period and with the structure of harvested pumas in other regions of Colorado. But, we will wait for greater sample sizes (i.e., greater numbers of radio-monitored pumas and duration) before we develop more quantitative analyses of survival rates and agent-specific mortality rates and attendant inferences. Thirty-nine puma cubs (20 males, 19 females) have been monitored by radiotelemetry for varying durations (Table 11). Three males (M5, M11, M49) are known to have survived to the subadult or adult stages (Table 10). Seven cubs (F13, F18, M22, F33, F34, F36, and M37) were killed and eaten by other pumas. At least 4 of those were subjects of male-induced infanticide. Sex of the puma involved in each of the other cases could not be determined. In addition, cub F45 was apparently killed by coyotes when she was 280 to 283 days old. F45 was separated from her adopted mother, F2, and also appeared to be emaciated at the time of her death. Cub F17 was killed by a vehicle on highway 550 when she was about 330 days old. She was not radio-collared at the time, but GPS data from her mother, F16, showed her in the vicinity of her offspring. Thus, F17 was probably still dependent on F16. Three cub deaths were due to our research activities, namely problems with the expandable radiocollars. F35 died at 37 days old probably as a result of starvation caused when the transmitter box got caught in her mouth. M42 died at 106 days old apparently from complications of septicemia caused by an infection at the axis of the right foreleg. The cub put his right foreleg through the expandable collar and the collar material lacerated the right underarm as the animal grew, enabling the infection. M60 died at 49 days old, apparently from starvation. He apparently could not keep up with the movements of his mother, because he had put his right foreleg through the expandable collar, restricting his mobility. In addition to these deaths, 1 unmarked female cub (~6 mo. old) was killed by a vehicle on highway 62 on the southwest boundary of the study area on January 28, 2007 (mentioned earlier). We lost contact with a number of cubs because they shed their expandable radiocollars (Table 11). As this study proceeds, some cubs with which we have lost contact will be re-captured, re-observed, or harvested, and thus, provide more complete survival information. 126 �Clearly, data on cub survival and mortality are still preliminary. At this time, we can say that a minimum of 12 deaths occurred in 39 radio-collared cubs that we monitored for varying periods of time. This represents a minimum 0.31 mortality rate (12/39), including research-related causes. Subtracting the 3 research-related deaths, the minimum mortality rate is 0.25 (9/36). The main cause of death is being killed by another puma (0.78, 7/9). These rates should be interpreted as only rudimentary information. More complete data on cub survival and mortality will be forthcoming as our efforts continue. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 <24 months old, 10 ≥24 months old) from a total of 49 in the previous study where pumas were not hunted. Yet, 19 of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agentspecific survival rates from our current effort will be compared with the Anderson et al. (1992) data set at a later date when we have greater samples, duration in research time, and more complete fate data (i.e., pumas currently without functional collars) to make such comparisons meaningful. Differences might be illuminated. For example, research of a puma population in New Mexico that was not hunted for 10 years indicated that the major cause of death for both sexes and all age stages of pumas was intraspecifies strife, and male-induced infanticide (Logan and Sweanor 2001). Although we have observed 3 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson’s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations at different times and different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. Segment Objective 5 Twenty adult pumas (7 males, 13 females) were fit with Lotek 4400S GPS collars since field research began in December 2004. The collars are programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 113 to 2,759 (Table 12). Winter activity areas for GPS-collared pumas were estimated (Table 13) with fixed kernel and minimum convex polygon home range estimators (ArcView 3.2 Animal Movement Extension). These estimates are intended for use in developing the sampling frame for the puma population estimation pilot project (see Introduction). In addition, 5 adult and subadult pumas have been monitored with VHF radiocollars (Table 14). Anderson et al. (1992) provided an exhaustive analysis of seasonal puma home ranges and movements using data collected from VHF-collared animals during 1982 to 1988. We have not yet conducted an exhaustive analysis of adult puma home ranges and movements with the GPS data from our current puma research efforts. Instead, we provide only limited descriptive information in Tables 13, 14 and Fig. 2. Given the different types of location data and analytical methods, only broad descriptive comparisons might be made between the 2 studies at this time. Elemental similarities in home range attributes of pumas in the Anderson et al. (1992) research and our current effort, include: current home ranges of some puma overlap extensively with home ranges of puma documented by Anderson et al (1992), home ranges of male and female pumas are large, male home ranges are larger than female home ranges, male home ranges overlap multiple female home ranges, female home ranges overlap other female home ranges sometimes extensively, male home ranges overlap other male home ranges to a lesser 127 �extent than female home ranges. These characteristics are generally similar for pumas in other populations that have been studied with adequate intensity and duration (Beier and Barrett 1993, Logan and Sweanor 2001), and reflect behavioral strategies of male and female pumas that seem to contribute to individual survival and reproductive success (Logan and Sweanor 2001). Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that ≤6 months old could have a survival rate (to the subadult stage) of <0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). From November 7, 2006 to March 22, 2007 we located 1 to 4 radio-collared families of puma mothers and cubs from an airplane 49 times (Table 15).To assess whether mothers were apart or in close association with cubs, we needed to consider error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and fixed with GPS and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Forty-one (83.7%) of observations located mothers and cubs ≤500 m apart, within the extreme margin of location error. Mothers were ≥520 m from their cubs during 8 (16.3%) of the observations (mean distance = 1,120 m, SD = 1,214.40, range = 616 to 4,101). The results for last winter were similar to our results the previous winter (15.2% and 16.3%, Table 15). Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Intensive effort to quantify puma use rates on ungulates by investigating puma GPS clusters continued during this period as an expansion of our pilot effort in the first research year (Logan 2005). That work proved the reliability of the GPS technology to allow us to gather quantitative information on ungulate prey use rates by pumas. In summary, 7 GPS-collared adult pumas (3 males, 4 females) used 61 mule deer, 48 elk, 2 porcupines, and 1 beaver found at 139 puma GPS clusters we investigated. The current work is a collaborative effort among CDOW Mammals Researchers (M. Alldredge, E. Bergman, C. Bishop, D. Freddy, and K. Logan). This was another pilot effort because it involved the development and testing of clustering parameters, clustering routine, associated computer programs, and field investigation protocols. Here we report only the general summary of the pilot field investigations of puma GPS clusters from October 2006 to April 2007. Five types of puma GPS clusters (Bergman et al. 2006) were investigated for 13 GPS-collared adult pumas (8 female, 5 male). The sample unit was the individual puma. The field effort focused on investigating a sample of randomly chosen clusters from each cluster type. In addition, when other non-random S1 clusters (i.e., clusters with the highest probability of ungulate use detection) were conveniently located to random clusters targeted for investigation, field personnel would attempt to investigate those clusters, too. A total of 257 clusters were investigated, including 63 non-random S1 clusters, and 173 random clusters (S1, S2, S3, S4, S5). Mule deer and elk were about equally important to pumas as food (Tables 16, 17, 18). Other mammals were rarely found. The next step in this investigation involves examining the performance of all aspects of the GPS cluster investigations and modifying cluster parameters and field protocols to maximize the 128 �efficiency and reliability of our continuing efforts to quantify ungulate use by pumas on the Uncompahgre Plateau. We will make further progress to designing and implementing a pilot project to investigate puma population estimation methods on the Uncompahgre Plateau. CDOW personnel Mat Alldredge, Chad Bishop, Ken Logan (Mammals Research) and Paul Lukacs (Terrestrial) met with Dr. Gary White (Colorado State University) June 21, 2007 to discuss possible approaches to estimating puma numbers by using capture-recapture methods and models. Another method we will explore, with the collaboration Mammals Researcher Chuck Anderson, is helicopter-based puma track probability sampling. We will evaluate the potential for collaborative research on puma-human relationships on the Uncompahgre Plateau with the developing CDOW puma-human research on the Colorado Front Range. To date, we have gathered location data on 10 (7 adult females, 3 adult males) GPS-collared pumas with activity areas on the developed southeast portion of our study area, which includes: Fairway Pines, Loghill Village, and Fisher Creek subdivisions, numerous other private homes, Fairway Pines golf course and driving range, all adjacent to Ridgeway State Park (Fig. 2). In addition, 2 new subdivisions and golf courses are underdevelopment on the southeast quarter of the Uncompahgre Plateau. This is the same area that Anderson et al. (1992:80) received 17 useable questionnaires on puma observations from residents, and also had some radio-collared pumas frequenting these same developments. Linking puma-human research on the Uncompahgre Plateau and Front Range provides opportunities for increasing sample size (i.e., puma numbers, study sites) and observing variation in puma-human relationships. We collaborated with Dr. Sue VandeWoude (CSU) to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to her laboratory for analyses. That project will be expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of that project and preliminary results on infectious disease surveillance on 21 pumas (13 female, 8 male) sampled on the Uncompahgre Plateau are presented in Appendix I. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 31 months of effort, 68 pumas have been captured, sampled, marked, and released. Of those 61 were radio-collared. Age stages we have monitored have included 21 adults, 6 subadults, and 46 cubs. Data from the marked animals are used to quantify vital rates and puma population dynamics in a reference situation (i.e., without sport-hunting off-take). Data on research efforts and puma capture, fates, reproduction, and activity areas are presented. During November 2006 through May 2007 a minimum count of 24 independent pumas were detected on the Uncompahgre Plateau study area. The count included 16 females and 8 males. Of those, 12 adult females and 7 adult males were probably marked animals (79% of independent pumas detected). Our efforts to quantify reproduction are yielding reliable data for Colorado on puma litter sizes, offspring sex ratios, and birth intervals. In this reference period, survival of adult and subadult pumas appears to be high. So far, the main cause of death in puma cubs is infanticide by males. Twenty adult pumas (13 females, 7 males) have been fitted with GPS collars, yielding 113 to 2,759 locations per puma. Our evaluations on the frequency that puma mothers on the Uncompahgre Plateau are away from their cubs >520 meters during the Colorado hunting season is low (15.2 to 16.3%). Intensive efforts to quantify puma use of ungulates on the Uncompahgre Plateau continued. Mule deer and elk appeared to be about equally important as puma food. 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Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. OTT, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. PIERCE, B. K., V. C. BLEICH, AND R. T. BOWYER. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. POLLOCK, K. H., S. R. WINTERSTEIN, C. M. BUNCK, AND P. D. CURTIS. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. WINTERSTEIN, AND M. J. CONROY. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. NICHOLS, C. BROWNIE, AND J. E. HINES. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. ROSS, P. I., AND M. G. JALKOTZY. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. STONER, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. SWEANOR, L. L., K. A. LOGAN, AND M. G. HORNOCKER. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. LOGAN, J. W. BAUER, W. M. BOYCE, AND B. MILSAP. 2006 in review. Puma-human relationships in a California, USA state park. Biological Conservation. VAN BALLENBERGHE, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. YOUNG, S. P. AND E. A. GOLDMAN. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: __________________________________ Kenneth A. Logan, Wildlife Researcher 131 �Table 1. Summary of puma capture efforts with dogs from November 13, 2006 to May 11, 2007, Uncompahgre Plateau, Colorado. No. & type of No. & type of No. & I.D. or type of pumas Month No. puma tracks pumas pursued captured Search founda Days November 8 12 tracks: 3 male, 7 pursuits: 1 3 pumas captured 4 times: 1 male 7 female, 2 cub male, 4 females, (not handledb), F3 twice (not 2 cubs handled once), cub M42 (died) December 16 49 tracks: 7-8 13 pursuits: 3 5 pumas captured 6 times: 1 male male, 19-20 males, 4-5 (not handled), F50, 1 female or female, 22-23 females, 5-6 cubs subadult puma (not handled), cub cub M49 captured twice (not handled once), 1 cub (not handled) 3 pumas captured: 9-10 pursuits: 3 January 19 56-58 tracks: 19 males, 3 females, 1 male (not handled), M51, 1 male, 30 female, female cub (not handled) 3-4 cubs 7-9 cub February 8 4 tracks: 1 male, 3 pursuits: 1 2 pumas captured: 1 female, 2 cub female, 2 cubs cubs M44 & M56 March 14 31-33 tracks: 8 12 pursuits: 4 7 pumas captured: M29, F7, F23 male, 13 female, male, 5 females, (not handled), F24 (not handled), 10-12 cub 3 cubs cubs M43 (not handled), M56 (not handled), & 1 unmarked female cub (not handled) 1 pursuit: 1 male 0 puma captured April 11 23 tracks: 13-16 male, 5-8 female, 2 cub May 2 2 tracks: 2 female 1 pursuit: 1 0 pumas captured female 78 177-178 tracks: 45-47 pursuits: 22 captures of 16 individuals: 7 TOTALS 51-55 male, 7712 males, 18-19 pumas captured for the 1st time81 female, 45-50 females, 15-17 M49, F50, M51, M56, & 1 female cub cubs or subadult (not handled) & 2 female cubs (not handled), 1 adult male caught twice (not handled), 12 marked pumas were recaptured 15 times (including 4 caught for the 1st time this year). a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female. b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. 132 �Table 2. Summary of puma capture efforts with dogs, December 2004 to May 2007, Uncompahgre Plateau, Colorado. Pursuit effort Puma capture Effort to capture a puma for Period Track effort the first time detection effort Dec. 2, 109/78 = 1.40 35/78 = 0.45 14/78 = 0.18 11 pumas captured for first 2004 tracks/day pursuit/day capture/day time (minus M1, F3, & large to female) May 12, 78/35 = 2.23 78/14 = 5.57 11/78 = 0.14 capture/day 2005 day/pursuit day/capture 78/11 = 7.09 day/capture 7 pumas captured for first time 14/82 = 0.17 149/82 = 1.82 43/82 = 0.52 Nov. 21, 7/82 = 0.08 capture/day capture/day tracks/day pursuit/day 2005 to 82/7 = 11.71 day/capture 82/14 = 5.86 82/43 = 1.91 May 26, day/capture day/pursuit 2006 7 pumas captured for first time 22/78 = 0.28 45/78 to 47/78 177/78 to Nov. 13, 7/78 = 0.09 capture/day capture/day = 0.58-0.60 182/78 = 2.272006 pursuit/day 2.33 to tracks/day May 11, 78/7 = 11.14 day/capture 78/22 = 3.54 78/47 to 78/45 2007 day/capture = 1.66-1.73 day/pursuit Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2006 to January 2007, Uncompahgre Plateau, Colorado. Puma Sex Estimated Mass Capture Capture Location I.D. Age (mo.) (kg) date method F50 F 25-27 31 12-14-06 Dogs West Fork Dry Creek M51 M 44-49 61 01-07-07 Dogs Lindsay Canyon F52 F 18-20 38 01-10-07 Cage trap Paco-Chu-Puk Campground, Ridgway State Park F54 F 30 36 01-12-07 Cage trap Pleasant View, Pleasant Valley M55 M 24-36 62 01-21-07 Cage trap Dallas Creek, Pleasant Valley 133 �Table 4. Pumas that were captured with aid of dogs, but were not handled and marked at that time for either safety reasons or they escaped, November 2006 to May 2007, Uncompahgre Plateau, Colorado. Puma Age Capture Location Comments sex stage date Male adult 11-13-06 East Fork Unmarked puma climbed difficult spruce tree beside Dry Creek creek. This puma is probably M51 (captured & marked 01-07-07, identified with distinguishing notch in margin of right pinna). Female, adult 11-21-07 Dry Creek Puma F3 climbed dangerous tree adjacent to creek. F3 Basin Unknown cub 12-02-06 Dry Creek Unmarked cub was bayed on edge of high cliff. This sex Basin cub was member of family comprised of an adult female & 2 cubs, which was probably pursued again on 01-25-07. Unknown subadult 12-05-06 Dry Creek This unmarked puma was treed on the same day that Basin we captured & handled cub M49. This puma could sex male or have been M49’s mother or a subadult puma (sex female, uncertain). or adult female Male adult 12-18-06 Lower Unmarked puma climbed difficult fir tree on steep East Fork slope. This puma was probably M51 (captured & Dry Creek marked 01-07-07, identified with distinguishing notch in margin of right pinna). Female cub 01-25-07 Piney Unmarked cub climbed tree. Anesthesia was Creek attempted with pole syringe. Cub jumped from tree, apparently with subcutaneous injection. Cub was pursued unsuccessfully by researchers on foot. Dogs were not released on partially sedated cub for safety reasons. This cub was member of family comprised of an adult female & 2 cubs, which was initially pursued on 12-02-06. Female cub 03-01-07 Dolores Unmarked cub associated with puma F2; was Canyon probably her unmarked cub, sibling of M38. Cub climbed difficult spruce tree adjacent to creek. Female, adult 03-07-07 San Puma F23 climbed a cottonwood tree close to the F23 Miguel San Miguel River. We did not attempt to anesthetize River at F23 to replace her non-functional GPS collar for Pinyon safety reasons. 134 �Table 5. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 2, 2006 to July 26, 2007, Uncompahgre Plateau, Colorado.a Month No. of Puma activity & capture effort resultsb Sites August 5 Puma scavenged a mule deer carcass on 08-07-06. Cage trap set. Black bear caught & released. Puma F16 was in the area. Puma did not return. September 4 No puma activity detected. October 10 Male puma scavenged a mule deer carcass 10-27-06. Cage trap set & monitored 10-27 to 28-06. Puma did not return. November 12 Male puma scavenged a mule deer carcass on 11-06-06. Set & monitored cage trap 11-06 to 10-06. Puma F16 walked around cage trap, but did not enter on 11-09-06. January 3 Subadult female F52 captured at adult female mule deer she killed 01-10-07, Ridgway State Park. Adult female F54 and her cub F53 were captured at an adult female mule deer kill 01-12-07, Pleasant Valley. Adult male puma M55 was captured at a mule deer fawn kill 01-21-07, Dallas Creek. March 7 Adult male puma M29 was temporarily caught in cage trap set on an adult elk cow he had killed 03-15-07. But, M29 escaped out of back of the trap as researchers arrived. An ear-tagged male cub of puma F3 was observed feeding on a mule deer carcass 03-26-07; F3’s family was in the vicinity. Female puma scavenged on a mule deer carcass 03-29-07. Cage trap was set. Puma F30 was recaptured, and her VHF collar was changed to a GPS collar. April 7 Male puma, probably M29, scavenged a mule deer carcass ~04-01-07. Female puma walked by same carcass (as above) on ~04-02-07, but did not feed. During ~04-05 to 08-07 a puma completely scavenged the same mule deer carcass. Puma F3 and her cubs consumed a mule deer carcass 04-06 to 10-07. Puma F30 consumed a mule deer fawn carcass 04-08-07. Puma F30 consumed a mule deer carcass 04-24-07. Male puma scavenged on mule deer carcass 04-10-07. Cage trap set. Male puma M55 walked up to cage trap (GPS data), but did not enter. Pumas F30 & M55 fed on a mule deer carcass 04-17 to 20-07. Female puma scavenged a mule deer carcass 0423-07. Cage trap set. Puma F8 was recaptured; her non-functional GPS collar was replaced with a VHF collar. Male puma M55 scavenged a mule deer carcass 04-30-07. Female puma scavenged a mule deer carcass. 04-27-07. Cage trap set. Puma F16 recaptured, and her GPS collar was changed with a new GPS collar. May 6 Male puma M55 scavenged on a mule deer carcass 05-08-07. Female puma killed a mule deer doe 05-10-07. Cage trap set. Puma did not return or did not enter the trap. Male puma M55 scavenged a mule deer carcass 05-22-07. June 5 Male puma M55 scavenged on an elk carcass 06-06-07. July 4 No puma activity detected. a We used 64 road-killed mule deer, 7 road-killed elk, 3 puma-killed mule deer, and 1 puma-killed elk at 26 different sites. Of the road-killed ungulate baits, 16 of 71 (22.5%) were scavenged by pumas. b Eight pumas were captured, including: 2 adult males (M29, M55), 4 adult females (F54, F30, F8, F16), 1 subadult female (F52), and 1 female cub (F53). 135 �Table 6. Pumas recaptured with dogs and cage traps, November 2006 to April 2007, Uncompahgre Plateau, Colorado. Puma I.D. F3 F3 M42 Recapture date 11-21-06 11-22-06 11-27-06 M49 M44 M43 M56 F7 F23 M29 F24 M29 F30 F8 F16 Mass kg Observed 41 4.8 Estimated Age (mo.) 63 63 3.5 Capture Method Dogs Dogs Dogs 12-12-06 02-14-07 03-01-07 03-01-07 03-03-07 03-07-07 03-05-07 03-22-07 03-27-07 03-29-07 Observed Observed Observed Observed 33 Observed Observed Observed 60 37 5 6 6.5 6.5 88 31 91 71 91 44 Dogs Dogs Dogs Dogs Dogs Dogs Cage trap Dogs Dogs Cage trap 04-23-07 04-28-07 37 48 46 51 Cage trap Cage trap Process None Changed GPS collar Cub died due to infection & stress None None None None Changed GPS collar None None None Changed GPS collar Changed VHF collar to GPS collar Changed GPS collar Changed GPS collar Table 7. Puma cubs sampled July 2006 to August 2007 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M38 M July 29, 2006 41 2.9 F2 67 Unm.b F “ 215 Observed “ “ M39 M August 13, 2006 29 1.9 F8 37 F40 F “ “ 1.8 “ “ F41 F “ “ 1.3 “ “ M42 M “ “ 1.5 “ “ M43 M August 13, 2006 33 2.4 F7 82 M44 M “ “ 2.5 “ “ F45 F “ “ 1.7 “ “ M56c M “ 185 9.6 “ “ M46 M September 17, 2006 31 2.2 F3 61 M47 M “ “ 2.2 “ “ M48 M “ “ 2.5 “ “ M49c M July 1, 2006 158 10.0 F50 21 c F53 F July 1, 2006 196 15.0 F54 24 F57 F April 16, 2007 35 2.3 F25 94 M58 M May 24, 2007 34 2.3 F16 52 F59 F “ “ 2.2 “ “ M60 M “ “ 2.0 “ “ M61 M “ “ 1.7 “ “ M62 M July 14, 2007 34 1.8 F24 75 M63 M “ “ 2.1 “ “ M64 M “ “ 1.7 “ “ M65 M “ “ 1.9 “ “ F66 F July 17, 2007 37 2.1 F30 48 M67 M “ “ 3.0 “ “ M68 M “ “ 3.3 “ “ a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. b This unmarked female cub was captured on 03-01-07 in association with adult female puma F2. This cub could be the sibling of cub M38, offspring of F2, which we were not able to capture previously with M38 (its tracks were observed). c Estimated ages of M49 and F53 were based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data). 136 �Table 8. Puma reproduction, Uncompahgre Plateau, Colorado, 2004-2007. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) Dates pairs consortedb Estimated birth datec Estimated birth interval (mo.) Estimated gestation Observed number of cubsd F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F8 24 06/26/05 2 F8 37 08/13/06 13.4 4 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F23 21 05/30/06 3 F24 75 M29 92 04/12-15/07 07/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F28 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data. c Estimated birth dates were indicated by GPS data of mothers at nurseries. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 6 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. 137 �Table 9. Summary for individual adult puma survival and mortality, December 2004 to July 2007, Uncompahgre Plateau, Colorado. Puma I.D. M1 M4 M5 M6 M27 M29 M32 M51 M55 F2 F3 F7 F8 F16 F23 F24 F25 F28 F30 F50 F54 Monitoring span 12-08-04 to 08-1606 01-28-05 to 12-2805 08-01-06 to 07-3107 02-18-05 to 02-2206 03-10-06 to 07-0506 04-14-06 to 07-3107 04-26-06 to 07-3107 01-07-07 to 07-3107 01-21-07 to 07-3107 01-07-05 to 07-3107 01-21-05 to 07-3107 02-24-05 to 07-3107 03-21-05 to 07-3107 10-11-05 to 07-3107 02-05-06 to 03-0707 01-17-06 to 07-3107 02-08-06 to 07-3107 03-23-06 to 07-3107 04-15-06 to 07-3107 12-14-06 to 03-2607 01-12-07 to 07-3107 No. days 616 333 365 369 117 Status: Alive/Lost contact/Dead; Cause of death Lost contact― failed GPS/VHF collar. M1 ranged principally north of the study area. Dead; killed by a male puma. Estimated age at death 37―45 months. Alive. Born on study area; offspring of F3. He was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months. Lost contact― failed GPS/VHF collar. 473 Lost contact― failed GPS/VHF collar. M27 ranged principally north of the study area. Alive. 461 Alive. 205 Alive. 191 Alive. 935 Alive. 921 Alive. 887 Alive. 862 Alive. 658 Alive. 396 Lost contact― failed GPS/VHF collar. 560 Alive. 538 Alive. 495 Alive. 472 Alive. 102 Died of natural causes; exact agent unknown. 200 Alive. 138 �Table 10. Summary of subadult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma Monitoring No. days Status: Alive/Survived to adult stage/ Lost contact/Dead; I.D. span Cause of death M5 09-16-05 to 308 Alive; independent and dispersed from natal area at 13 06-30-06 months old. Established adult territory on northwest slope of Uncompahgre Plateau. M11 06-21-06 to 176 Lost contact. Independent at 13 months old. Dispersed from 12-14-06 natal area at 14 months old. Last location in Dolores River valley Dec. 14, 2006. F23 01-04-06 to 31 Alive; survived to adult stage; gave birth to first litter at ~21 02-04-06 months old. M31 04-19-06 to 7 Lost contact. Probable disperser. M31’s estimated age at 04-26-06 capture was 25 months, at the lower margin of puberty for puma. He may have been a dispersing subadult, and could have moved away from the study area. M49 03-26-07 to 127 M49 was orphaned at about 9 months old, when his mother 07-31-07 F50 died of natural causes. He dispersed from his natal area at about 10 months old and has been ranging on the northeast slope of the Uncompahgre Plateau. F52 01-10-07 to 125 Lost contact. Dispersed from study area as a subadult. F52’s 05-15-07 last location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon. 139 �Table 11. Summary for individual puma cub survival and mortality, December 2004 to 2007, Uncompahgre Plateau, Colorado. Status: Alive/Survived to subadult stage/ Lost Estimated survival Age to last Puma Estimated contact/Disappeared/ Dead; Cause of death span from 1st monitor date I.D. Age at alive or at capture capture to fate or death (days) (days) last monitor date M5 183 02-04-05 to 07-31-07 907 F9 F10 31 31 329 207-246 M11 31 06-27-05 to 4-19-06 06-27-05 to 11-2005― 12-29-05 06-27-05 to 12-14-06 F12 42 07-01-05 to 12-0805― 01-26-06 245-294 F13 F14 42 26 07-01-05 to 08-28-05 07-22-05 to 02-0706― 03-10-06 100 226-257 M15 F17 26 34 07-22-05 to 06-06-06 10-26-05 to 08-18-06 345 330 F18 34 301-308 M19 M20 F21 M22 34 34 37 37 M26 183 10-26-05 to 0720―27-06 10-26-05 to 07-27-06 10-26-05 to 05-24-06 11-02-05 to 06-30-06 11-02-05 to 12-2105― 12-22-05 02-08-06 to 03-21-06 Mother I.D. F3 306 244 277 86-87 Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old . Lost contact― shed radiocollar 04-19-06―04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified). Lost contact― shed radiocollar 01-20-06―01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 0207-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06―06-14-06. Dead. Lost contact― shed radiocollar 06-06-06―06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Born 9/22/05 Lost contact― shed radiocollar 07-27-06―08-02-06. Lost contact― shed radiocollar 05-24-06―05-25-06. Alive. Dead; killed and eaten by male puma 12-21-05―12-22-05. F16 F16 F3 F3 224 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 535 140 F2 F2 F2 F7 F7 F8 F8 F16 F16 �Puma I.D. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Age to last monitor date alive or at death (days) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death F33 31 06-30-06 to 07-31-06 62 F34 31 06-30-06 to 07-31-06 62 F35 F36 31 29 06-30-06 to 07-07-06 07-08-06 to 07-28-06 38 74 M37 29 07-08-06 to 07-28-06 74 M38 M39 41 29 165 9 226 M40 29 9 226 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 F41 29 09-08-06 to 02-20-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. 24 F8 M42 M43 M44 29 33 33 09-11-06 to 11-27-06 09-15-06 to 03-01-07 09-15-06 to 02-14-07 77 167 152 F45 33 09-15-06 to 5-20 to 23-07 280-283 M46 31 10-18-06 to 12-15-06 58 M47 31 10-18-06 to 12-15-06 58 M48 31 10-18-06 to 12-15-06 58 Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 10-13-06 (collar found). Dead; research-related fatality.b Treed, visually observed 03-01-07. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. 141 Mother I.D. F23 F23 F23 F28 F28 F2 F8 F8 F7 F7 F7 F3 F3 F3 �Puma I.D. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Age to last monitor date alive or at death (days) Mother I.D. M49 153 12-05-06 to 07-31-07 238 M49 was orphaned when his mother died on about 03-26-07. F50 F53 183 01-12-07 to 02-23-07 42 Lost contact― shed radiocollar 2-23-07. F54 M56c 183 02-14-07 to03-01-07 15 Lost contact― shed radiocollar 2-27-07. M56 observed 03-01-07. F7 (?) F57 35 05-21-07 to 06-06-07 16 Lost contact― shed radiocollar 06-07-07. Live mode 06-06-07. F25 M58 34 06-27-07 Not radio-collared. F16 F59 34 06-27-07 to 08-21-07 55 Alive. F16 M60 34 06-27-07 to 07-11-07 14 Dead; research-related mortality.d F16 F61 34 06-27-07 to 06-29-07 2 Radiocollar malfunction. F16 M62 34 08-17-07 Not radio-collared. F24 M63 34 08-17-07 Not radio-collared. F24 M64 34 08-17-07 Not radio-collared. F24 M65 34 08-17-07 Not radio-collared. F24 F66 37 08-23-07 Radio-collared. F30 M67 37 08-23-07 Not radio-collared. F30 M68 37 08-23-07 Not radio-collared. F30 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 142 �Table 12. Numbers of GPS locations for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2007. Puma I.D. M1 M4 M6 M27 M29 M51 M55 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a No. locations M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F F F F F F F adult adult adult adult adult adult adult adult adult adult adult adult subadult, adult adult adult adult adult adult subadult adult 12-08-04 to 07-20-06 01-28-05 to 12-28-05 02-18-05 to 11-23-05 03-11-06 to 06-21-06 04-14-06 to 07-30-07 01-07-07 to 07-30-07 01-21-07 to 07-22-07 01-07-05 to 07-11-07 01-21-05 to 07-30-07 02-24-05 to 07-30-07 03-21-05 to 10-04-06 10-12-05 to 06-12-07 01-04-06 to 02-04-06 02-05-06 to 07-17-06 01-17-06 to 07-25-07 02-09-06 to 07-02-07 03-24-06 to 07-11-07 03-30-07 to 07-25-07 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 07-20-07 1,864 910 926 316 1,165 630 558 2,759 2,474 2,401 1,516 1,797 113 511 1,816 1,408 1,394 381 361 383 615 Acquisition rate average, range, nb 76, 69―84, 14 70, 57―84, 10 84, 73―93, 9 77, 67―84, 3 69, 56―81,13 76, 66―87, 6 79, 68―91, 6 75, 43―91, 30 78, 55―90, 24 68, 26―92, 27 67, 41―81, 17 73, 41―90, 23 79, 45―92, 6 82, 65―93, 18 69, 55―87, 16 74, 53―89, 16 83, 58―94, 4 87, 76―94, 4 83, 70―92, 3 82, 77―86, 6 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download for an individual puma in this report. b n = number of remote downloads. Table 13. Estimated use areas of GPS-collared pumas during November through March, Uncompahgre Plateau, Colorado.a Puma I.D. No. locations Time span No. months 95% Fixed kernel (km2) 50% Fixed kernel (km2) F2 F3 F7 F8 F16 F24 F25 F28 F50 M1 M29 M51 151 130 114 147 144 150 147 146 103 149 97 85 11-01-06 to 03-31-07 11-22-06 to 03-31-07 11-01-06 to 03-31-07 11-01-05 to 03-31-06 11-01-06 to 03-31-07 11-01-06 to 03-31-07 11-01-06 to 03-31-07 11-01-06 to 03-31-07 12-14-06 to 03-26-07 11-01-05 to 03-31-06 11-01-06 to 03-31-07 01-07-07 to 03-31-07 5 4.3 3.9b 5 5 5 5 5 3.4 5 3.4c 2.8 78.6 138.9 66.7 33.7 53.6 117.7 52.0 61.8 70.0 1,132.7 349.1 231.0 13.3 12.2 10.6 5.4 7.0 18.9 6.5 6.3 15.8 302.3 25.0 31.0 a 100% Minimum convex polygon (km2) 102.3 164.0 66.8 43.3 59.9 148.9 79.8 105.4 91.2 779.8 379.0 281.2 Use areas were estimated by using the Animal Movement extension in ArcView 3.2. One location per day was randomly chosen from up to 4 locations fixed per day per puma to reduce autocorrelation. b Due to GPS collar failure, GPS locations were not fixed for F7 from 01-30 to 03-02-07. C Due to GPS collar failure, GPS locations were not fixed for M29 from 02-09 to 03-26-07. 143 �Table 14. VHF-radio-collared independent pumas on the Uncompahgre Plateau, Colorado, 2007. Puma I.D. M5 Sex Age stage Dates monitored No. locations M F8 F30 M31 M32 F F M M Subadult Adult Adult Adult Subadult Adult 09-16-05 to 07-31-06 08-01-06 to 07-30-07 04-23-07 to 07-30-07 04-15-06 to 03-29-07 04-09-06 to 04-26-06 04-26-06 to 07-30-07 36 37 14 43 2 50 Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, November through March each winter. Monitoring period Month Nov. 9, 2005 to March 29, 2006 Nov. Dec. Jan. Feb. Mar. Nov. 7, 2006 to March 22, 2007 Nov. Dec. Jan. Feb. Mar. Totals Totals No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs ≤520 m apart 3 4 5 4 2 18 4 4 5 4 3 20 4 4 4 5 5 4―5 4 4 3 4 1 1―4 2―6 3―7 4―8 5―9 6―10 2―10 2―3 2―5 4―6 5―7 8 2―8 10 16 16 16 9 67 10 11 9 9 2 41 No. observations with mothers & cubs >520 m apart 2 4 4 2 0 12b 1 1 3 2 1 8c a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650―1,600. C Mean = 1,120 m, SD = 1,214.40, range = 616―4,101. Table 16. General results of puma GPS cluster investigations pilot project, October 2006 to April 2007, Uncompahgre Plateau, Colorado. Cluster Types Investigated S1 Non-random S1 Random S2 Random S3 Random S4 Random S5 Random Totals No. 63 84 11 29 30 40 257 Animals found at all clusters Mule deer Elk Beaver Coyote Total 144 No. 63 58 1 2 124 Animals found at random clusters Mule deer Elk Coyote Total No. 33 31 2 66 �Table 17. Sex and age classes of mule deer found at puma GPS cluster investigations, October 2006 to April 2007, Uncompahgre Plateau, Colorado. Sex & age of mule deer Fawn Yearling 2+ year Unknown age 1+ yr. Unknown age Totals Female 0 1 6 1 0 8 All clusters Male Unknown 1 18 6 3 6 1 1 6 0 13 14 41 Female 0 1 5 1 0 7 Random clusters Male Unknown 1 10 3 2 1 1 1 4 0 3 6 20 Table 18. Sex and age classes of elk found at puma GPS cluster investigations, October 2006 to April 2007, Uncompahgre Plateau, Colorado. All clusters Random clusters Sex & age of elk Female Male Unknown Female Male Unknown Calf 3 1 18 1 0 10 Yearling 13 2 3 7 1 3 2+ year 4 3 4 1 2 3 Unknown age 1+ yr. 0 0 4 0 0 2 Unknown age 0 0 3 0 0 1 Totals 20 6 32 9 3 19 145 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Estimation Methods for Monitoring Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report for the puma management goal (at top). 146 �! ( ! ( ! ( ! ( ! ( Clifton County Boundary Highways Study Area ! ( ! ( ! ( ! ( ! ( Delta ! ( M1 ! ( UF UF M32 F50 ! ( UF Montrose F8 M27 M51 F3 F23 M29 ! ( ! ( F7 F28 F2 F24 F30 M6 M55 F16 F25 F54 ! ( Norwood ! ( Ridgeway UF ! ( UM ! ( 0 5 10 20 30 40 Kilometers ! ( Figure 2. Schematic of home ranges of GPS-collared (polygons) and non-collared (ellipses) independent pumas (adults and subadults), intended to show the minimum count and location of independent pumas detected on the study area during November to May period, 2006-2007, Uncompahgre Plateau, Colorado. M & F signify male & female, followed by the identification number of the puma. UF and UM signify uncollared and unsampled female and male pumas, respectively. 147 �5 No. Litters 4 3 - + - - - -- - - I - 2 - + - - - -- - - I 1 -+-------- ~ ~ -------, - - - ,~ --------I - - - r----- - - - - - - - ~- - - - - - , - - - - - - - -~ --I Ja n. Fe b. M ar . Ap r. M ay Ju ne Ju ly Au g. Se p. O ct . No v. De c. 0 I □ Births 2005-07 ■ Births 1983-87 Figure 3. Puma births (n = 20 litters) detected by month during the current research effort, 2005 to 2007, and during the earlier effort by Anderson et al. (1992), 1983 to 1987 (n = 10 litters). Age structure of adult pumas captured and sampled on the Uncompahgre Plateau, Colorado, to March 31, 2007. No. Puma 4 3 2 ~.- ~ 1 ~ - ~ Female ..... Male 0 ~ -~ ~ I ~ 11 I 2 to 3 >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 4 5 6 7 8 9 10 Age (Years) Figure 4. Age structure of adult pumas captured and sampled on the Uncompahgre Plateau, Colorado, on March 31, 2007, after 3 winters (Nov. through Mar., 2004-05 to 2006-07) of protection from sporthunting mortality. In addition, no other human-caused mortalities have been documented in the GPS/radio-collared sample of adults. This age structure assumes that puma M1, M6, and M27 (which had non-functional GPS collars) were alive. Evidence was found on the ground that indicated that all 3 of those males were alive. Pumas M1, M5, and M27 range north of the study area and were protected from legal sport-harvest. Mean ± SD of adult female and adult male ages, respectively: 4.90 ± 1.80 yr. (58.82 ± 21.62 mo.), 4.76 ± 1.62 yr. (57.12 ± 19.39 mo.). 148 �APPENDIX I COLLABORATIVE PROJECT ON DISEASE SURVEILLANCE IN WILD FELIDS. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 Attached please find the consolidated report on infectious disease surveillance for the mountain lion samples you have provided to our laboratory as an adjunct to your CDOW ongoing studies. Our laboratory has performed puma-lentivirus (PLV) antibody screening using a sensitive western blot assay developed in our laboratory and found 13 of 18 samples conclusively positive (72%), with two additional samples inconclusive and one not tested. Dr. Michael Lappin, a veterinary internal medicine specialist with expertise in feline infectious disease has tested a subset of 6 samples for antibodies to Feline Calicivirus (FCV), Feline Herpes Virus (FHV), Feline parvovirus (FPV), Toxoplasma gondii (IgM, indicating recent infection, IgG indicating past exposure), and Bartonella hensalae (the agent associated with cat scratch disease). At least one of six animals tested has been positive for each of these agents. Further results are pending from the remaining samples you have provided for these 5 assays. In addition, Dr. Martin Scriefer at Fort Collins CDC has also tested 6 animals for evidence of antibodies to the agent responsible for plague (Yersinia pestis). Interestingly, 3 of 6 animals demonstrate significant exposure to this agent as well. These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, “The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids”, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and inter-specific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that 149 �will be most valuable, and a draft of a ‘permissions’ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude THE EFFECTS OF URBAN FRAGMENTATION AND LANDSCAPE CONNECTIVITY ON DISEASE PREVALENCE AND TRANSMISSION IN NORTH AMERICAN FELIDS PROJECT SUMMARY Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species--ecologically pivotal organisms that are sensitive to human disturbances. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on large carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and post-graduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multidisciplinary collaborations. 150 �Table 1. Appendix I. Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado. Puma ID UPCO 3 UPCO 7 UPCO 7 UPCO 7 UPCO 8 UPCO 4 UPCO 5 UPCO 6 UPCO 25 UPCO 28 UPCO 29 UPCO 31 UPCO 23 UPCO 27 UPCO 30 UPCO 50 UPCO 51 UPCO 52 UPCO 54 UPCO 55 UPCO 24 T.g.e IgG B.h. Y.p. FPV T.g. e IgM f g + + - + - ++ + - - - + - +++ + Ph P P P P P P 13S, 247645, 4246097 Ih P P P P P P P 3/21/2005 12S, 727808, 4239029 I - - - - + - ++ M 1/28/2005 13S, 257565, 4239606 + - - - - + + I M 2/4/2005 13S, 240577, 4251037 - - + + - + - I M 2/18/2005 13S, 247399, 4254006 + - - - - + - I F 2/8/2006 13S, 258374, 4230480 + P P P P P P P F 3/23/2006 12S, 722868, 4240115 + P P P P P P P M 4/14/2006 12S, 723458, 4242340 + P P P P P P P M 4/19/2006 12S, 746919, 4225441 + P P P P P P P F 1/4/2006 12S, 730188, 4234861 - P P P P P P P M 3/10/2006 12S, 722339, 4245212 - P P P P P P P F 4/15/2006 13S, 248551, 4242095 - P P P P P P P F 12/14/2006 12S, 753639, 4260149 + P P P P P P P M 1/7/2007 13S, 238783, 4252390 + P P P P P P P F 1/10/2007 13S, 258058, 4236260 I P P P P P P P F 1/12/2007 13S, 252688, 4228050 + P P P P P P P M 1/21/2007 13S, 258133, 4228691 + P P P P P P P F 1/17/2006 12S, 737151, 4233273 % Seroprevalance = No. animals positive/Total animals tested * 100 + P P P P P P P 72 33 33 33 0 100 17 50 Sex Capture Date GPS NAD27 U.T.M.: Zone, E, N PLV FCV FHV F 1/21/2005 13S, 241606, 4251510 - +h F 2/24/2005 13S, 246328, 4244230 + F 3/30/2006 13S, 245901, 4247627 F 3/3/2007 F a a b PLV is Puma Lentivirus. b FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result). 151 c d �Colorado Division of Wildlife July 2007 −June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Predatory Mammals Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 1, 2007−June 30, 2008 Author: K. A. Logan. Personnel: K. Logan, B. Bavin, B. Dunne, J. Timmer, V. Yovovich, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young, and J. McNamara of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service, with supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. All capture efforts in 2007-08 resulted in a total of 41 puma captures (9 adult females [1 adult female captured 3 times], 6 adult males [1 adult male captured 2 times], 1 subadult male, and 21 cubs [4 of them captured twice each]). Two adults, 4 subadults, and 16 cubs were captured for the first time. As of July 2008, there were 18 adults, 1 subadult, and 4 cubs marked with active radio-collars. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 19, 2007 to April 24, 2008. Those efforts resulted in 77 search days, 217-218 puma tracks detected, 49 pursuits, and 20 puma captures. In 2007-08, capture efforts with ungulate carcasses and cage traps resulted in 1 adult male being captured twice. One cub was captured for the first time with dogs, and 15 cubs were caught the first time by hand. Capture and search efforts from November 2007 through March 2008 enabled us to estimate a minimum of 33 independent pumas detected on the Uncompahgre Plateau study area during that time, including 21 females and 12 males. Preliminary puma population parameters estimated during the past 3.7 years of research, included: population sex and age structure, reproduction rates, and survival rates. Data on puma reproduction rates included: average litter size = 2.810 ± 0.9808 SD, n = 21; average birth interval (mo.) = 17.969 ± 4.748 SD, n = 13; average proportion of adult females producing cubs each year = 0.65 ± 0.0586 SD, n = 12-13 females for 3 yr.; secondary sex ratio = 33:26, consistent with 1:1; and average gestation length (day) = 91.188 ± 2.3443 SD. Puma births occurred March through September. Survival rates for both adult and subadult pumas in this reference period appear to be high, and might reflect the relatively small samples of individual pumas in each age-stage and sex and years. Cub survival ranged from 0.50 (Kaplan-Meier procedure) to 0.56 (binomial model). The main cause of 105 �mortality in the adults and cubs is caused by male pumas. A puma population model was developed for researchers and wildlife managers to assess scenarios of puma harvest management strategies. Results from a set of scenarios and attendant models are presented. Only 1 puma family with a radio-collared mother and cub could be monitored during the winter to assess association distances during aerial locations. The aggregate data gathered during the past 3 winters generally indicate that mothers were usually within 520 m of their cubs during the day. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (3.7 years duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Proposed work includes: continuing to quantify puma population characteristics and vital rates, with an emphasis on increasing sample sizes on radio-monitored adults, subadults, and cubs, and developing a study plan for the next 6 years of research, which will include the treatment period. We will collaborate with colleagues to assess puma health and model and map puma habitat. 106 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; begin puma population modeling process; and plan for the remaining 6 years of the Uncompahgre Plateau Puma Project― all to improve the Colorado Division of Wildlife‘s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Develop a puma population model and parameter estimates useful for guiding decisions about the hunting treatment phase of this project, and for the Data Analysis Unit puma management planning process performed by CDOW biologists and managers. 6. Gather data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Develop a study plan for remaining 6 years of puma population research on the Uncompahgre Plateau Study Area. 8. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while ― achieving healthy, self-sustaining populations‖(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW‘s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado‘s puma research program, with multiple lines of inquiry (i.e., projects): 107 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage-specific survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW‘s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct mark-recapture, and DNA genotype capture-recapture. A descriptive study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population. 108 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft LDAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,}., = I. 15)  for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing  include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H1: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed = 1.15. 2. The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). H2: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a decline of the harvest-age segment of the population by the beginning of the next hunting season. 3. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H3: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). Considering limitations (i.e., methods, number of years, assumption violations) to the Colorado-specific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: 109 �H4: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (e.g., capture-mark-recapture) of known reliability will allow managers to ―g round truth‖ modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture, and assessments of harvest sex and age structure. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties. The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and 110 �domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will involve structured puma management strategies. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW‘s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW‘s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase and population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. For managers, demonstrating that they can manage puma populations with hunting and achieve the CDOW strategic objective of managing for a healthy, self- sustainable puma population state-wide is important. Dynamics of the puma population may be manipulated (i.e., increase and decline phases) to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative 111 �vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting), enumeration methods, and puma―prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when 112 �snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each 113 �pinna to facilitate individual identification during direct recaptures. Cubs 10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week (as flight schedules and weather allow) from light fixed-wing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using GIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for 3 to 24 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, ~50g, or Telonics, Inc., Mesa, Arizona MOD 210, ~100g,) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radio-collared cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using methods such as houndsmen teams. In addition, by marking puma before capturerecapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers‘ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is 114 �naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capturerecapture occasions to estimate the population of independent puma may not begin until we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989), binomial survival model (Williams et al. 2001:343-344), or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado‘s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). Basic assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike‘s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. 115 �Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of ≥0.4 for each animal per capture occasion (see Results and Discussion, Segment Objective 7). In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Nt+1/Nt) between consecutive years and Rate of Population Increase: Finite rates of increase ( average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination can be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman‘s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2007 to July 2008. Our searches to detect puma presence covered the entire study area. We made 41 puma captures during the period (9 adult females [1 adult female captured 3 times], 6 adult males [1 adult male captured 2 times], 1 subadult male, and 21 cubs [4 of them captured twice each]), resulting in 2 adults (1 female, 1 male), 4 subadults (2 females, 2 males), and 16 cubs (7 females, 9 males) captured for the first time in 2007-08. Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from November 19, 2007 to April 24, 2008. Those efforts resulted in 77 search days, 217-218 puma tracks detected, 49 pursuits, and 20 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was similar to our efforts in the 3 previous winters (Table 2). But, the frequency of tracks encountered and pursuits increased over the 3 previous periods. Our capture rate 116 �declined slightly probably due to our ability to identify radio-collared pumas associated with tracks (see later), thus, negating the need to capture the pumas directly with dogs. Seven adult and subadult pumas were captured for the first time (Table 3). This includes 1 adult female puma that could not be handled for safety reasons (Tables 4). One large cub, and 1 adult female were each recaptured twice, but could not be handled for safety reasons. One GPS-collared male puma was visually observed in association with an adult female puma we recaptured with dogs, but the male puma was not be bayed by the dogs (Table 4). The age structure of independent pumas captured for the first time continues to suggest that we have been studying a relatively young age-structured puma population that is increasing in the current reference period (Figure 2). Our puma capture efforts using ungulate carcasses and cage traps extended from August 7, 2007 to July 15, 2008. We used 59 road-killed mule deer, 1 road-killed elk, and 1 puma-killed mule deer as bait at 15 different sites to capture one adult male puma 2 times (Tables 5). The puma-killed deer was used as bait at another site after puma F30 abandoned the carcass after we set a camera trap at her cache to obtain photos of the number of marked cubs in her family to confirm survival data. Pumas scavenged 11 of 60 (18.3%) of the ungulate carcasses used for bait. This was slightly lower than results of the last 2 years (i.e., 20%, 22.5%). Other carnivores that used the ungulate baits included: black bear, coyote, and bobcat. Recaptures of 11 to 12 individual marked pumas were made 17 times with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). This included puma M27 (which wore a non-functional GPS collar) that was treed twice north of the study area by a puma hunter (Stan Garvey, Nucla) using dogs. The hunter reported the observation of the tagged animal (including, ear-tag number, and a visible hole in the GPS unit battery box), dates, and locations to principal investigator K. Logan. One recapture was of puma cub M44 (offspring of F7) made by Wildlife Services personnel responding to puma depredation on domestic sheep on the study area. The Wildlife Service houndsman released dogs on the puma tracks, and subsequently treed M44 and shot him to control the depredation. In another instance, a researcher visually observed a GPS-collared male puma in association with puma F23 as we pursued both pumas with dogs. Neither of the pumas had functioning GPS collars at the time. The GPS-collared male puma was either M27 or M29, as those 2 adult males were the only GPS-collared males that ranged in that area. The dogs treed F23, but they did not bay the male puma to enable us to obtain exact identity. We also captured 16 cubs (9 male:7 female) for the first time (Table 7). Seven cubs were radiocollared, including zero to 2 cubs collared in each of 7 litters (Appendix A). One 18 kg female cub was treed by our trained dogs, and immobilized with a pole syringe for safe handling. The other 15 cubs were handled without anesthetics at their nurseries when they were 28 to 40 days old. The litters were produced in May (3), June (2), and July (2). In addition to our direct puma captures, we identified 11 previously marked adult pumas that we detected 34 times initially by snow-tracking (Table 8). Upon detecting puma tracks that were roughly aged at 1 to 2 days old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be < 1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made in snow, then we ruled the data were confirmatory. A large majority (i.e., 70%) of confirmatory data is a combination of radio-telemetry and GPS data. One snow track was assigned to a male puma only using GPS data, apparently because he had moved sufficiently far enough away so we did not receive radio signals at the time we found his tracks. If the GPS data did not indicate movement through the area, but the puma probably had sufficient time between fixes to foray to the tracks from proximate GPS locations, then we decided the GPS data were inconclusive. None of the GPS data clearly indicated that an individual puma could not have been the one we initially identified by radio-telemetry. 117 �In one instance, principal investigator K. Logan visually observed puma F25 attack a mule deer after following up her tracks with radio-telemetry. If we could not identify a collared puma in association with 1-day-old puma tracks, then we released the dogs in attempt to capture the puma. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning radio- or GPS-collars. This approach would also be useful in a rigorous mark-recapture effort where radio-collared pumas are available. Our search efforts throughout the study area also revealed the presence of at least 9 other independent females and 1 independent male. We could separate the activity of these pumas from the GPS- and VHF- collared pumas in time and space. Moreover, females in association with cubs of different counts and sizes enabled us to separate 5 adult females followed by 1 to 3 medium-to-large-size cubs. One adult female with 1 large dependent cub was treed, but could not be handled safely. She initially treed, which provided us with an excellent visual observation; but, she left the tree and escaped into a system of sink holes that were too unstable (i.e., dangerous) for researchers to enter. Another adult female with 2 medium-size cubs was pursued with dogs, but was not captured. It was the same situation with another adult female with 2 to 3 medium-size cubs in a different area. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). Our search and capture efforts during November 2007 through April 2008 enabled us to estimate a minimum count of 33 independent pumas detected on the Uncompahgre Plateau study area, up from a minimum count of 24 independent pumas during the November 2006 to May 2007 period. This estimate was based on the number of known radio-collared pumas, the observation of one non-collared puma, and detection of tracks of suspected non-collared pumas on the study area (explained previously). In addition to the independent pumas, we also counted a minimum of 20 to 21 cubs. The sex and age structure of the minimum puma count is in Table 9. Of the 33 independent pumas, 23−24 (70−73%) were marked and 9−10 (27−30%) were assumed to be unmarked animals. Of the expected unmarked pumas, 8−9 were females and 1 was male, which might reflect lower detection rates of females. There appears to be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 12 independent pumas (8 females, 4 males). The east slope count includes 21 independent pumas (13 females, 8 males). We used the minimum puma count and population structure in an effort to develop puma population models to simulate expected puma population dynamics in the remainder of the reference period and expected results of harvest management for the treatment period on the Uncompahgre Plateau Puma Project. Moreover, the models can be used by CODOW wildlife managers and biologists as a tool to explore expected outcomes of puma harvest management strategies in Colorado (see Segment Objective 5). Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study to investigate an ― unexploited‖ puma population (Anderson et al. 1992:5). As our current effort results in larger samples and progresses in time through the reference and treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 3.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete because we are still in the intensive data-gathering phase, yet, our data allows some preliminary comparisons with Anderson‘s (1992) completed work. In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). Anderson et al. (1992) focused on capturing pumas >27 kg in body mass while avoiding pumas <27 kg in mass. They captured 47 pumas with dogs for an average capture rate of 13.9 days per puma. Eight other pumas, all 118 �female cubs ≤ 7 months old, were caught in steel leg-hold traps by trappers, and were added to the study animal population. Two other cubs were killed by the dogs. In total, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. So far, in our 4 winters, the average effort to capture pumas with dogs is 78.8 days (range = 77 to 82). Of 172 pursuits, 70 (41%) were successful. We captured 38 individual pumas their first time with dogs (i.e., does not include dog-aided recaptures), yielding an average capture rate of 8.3 days per capture (i.e., 315 days/38 captures). Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or capture cubs at nurseries like we are. In our current effort, we captured, sampled, and marked 90 pumas. Of those animals, 74 were radio-collared, allowing us to monitor fates of pumas in all sexes and age stages, including: 15 adult females, 11 adult males, 2 subadult females, 5 subadult males, 25 female cubs, 22 male cubs (some individuals occur in more than one age-stage). To date, this represents the largest number of individual pumas sampled for population data in Colorado. Mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old averaged 59.4 kg for 11 males (SD = 7.42, range 40 to 68 kg) and 38.4 kg for 14 females (SD = 4.29, range = 31 to 46). Sexual dimorphism is evident in pumas, and has been described for the species throughout its range (Young and Goldman 1946). Sexual dimorphism in puma has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 During the past 3.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. We examined 59 cubs from 21 litters aged 29 to 42 days old where we were reasonably sure that we counted all the cubs at the nurseries (Appendix A). The distribution of puma births by month indicate puma births extending from March into September, with 26 of 28 births occurring May through September (Fig. 3).The secondary sex ratio was 33:26 for 21 litters where all the cubs were sexed. This ratio was not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). An equal sex ratio at birth is characteristic of other puma populations in North America (Robinette et al. 1961, Logan and Sweanor 2001:69-70). The mean (±SD) and extremes of litter sizes were 2.810 (±0.9808), 1−4 (Table 10). In addition, 13 birth intervals for 8 different female pumas averaged 17.969 months (SD = 4.748), and ranged from 11.7 to 23.9 months (Table 10). During the past 3 biological years (i.e., 2005-06 to 2007-08) when we radio-monitored 12, 13, and 12 adult female pumas respectively, the proportion of adult females that produced cubs each year were 0.67, 0.69, and 0.58, with a mean ± SD of 0.65 ± 0.0586. Based on observations (from GPS and radio-telemetry data) of associations between 7 mothers and putative sires, 8 estimated gestation periods averaged 91.188 days (SD = 2.3443), which is consistent with average puma gestation reported in the technical literature on puma (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of ―1 7 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4‖. ―Because most postnatal young were not handled, their sex ratio is unknown‖ (Anderson et al.1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 28 litters adds to Anderson‘s data (Fig. 2), and indicates puma births in Colorado occurring in every 119 �month except January and November (so far). Our data suggests that the majority of puma breeding activity occurs February through June. Anderson‘s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (see previously). Segment Objective 3 & 4 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2008, we radio-monitored 11 adult male and 15 adult female pumas to quantify survival and agent-specific mortality rates (Table 11). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 3 adult males apparently due to GPS/VHF collar failure: M1, M27, and M29. Direct observations in the field during January 2008 indicated that M27 was alive, and M29 might also be alive. Three adult females are known to have died. F50 was about 29 to 31 months old when she died apparently of natural causes (exact agent could not be identified). Two adult females, F54 and F30, were killed by other pumas. F54 was killed at about 49 months old by a male puma on the southern boundary of the study area while apparently in direct competition for a fawn mule deer. F30 was apparently killed by a puma of unknown sex and for unknown circumstances when she was about 60 months old. Both females died as a result of fatal bites to the head. Preliminary estimates of adult puma survival rates indicate relatively high survival in this reference period (i.e., with no sport-hunting) (Table 12). Survival rates were estimated using the KaplanMeier procedure to staggered entry of animals (Pollock et al. 1989) for the past 2 annual and hunting season periods when samples were ≥ 5 animals in each sex category. The survival rates reflect zero male deaths, and all 3 adult females that occurred in those periods. We need to increase the number of radiomonitored adult males to obtain more realistic survival rates (i.e., other than 1.0). The adult age structure, as indicated in Figure 4, is indicative of high survival rates during the past 4 winters without sporthunting mortality. Research in New Mexico on a non-hunted puma population also indicated higher survival rates for adult male than adult female pumas, with the major cause of death being aggression by male pumas (n = 8 years; Logan and Sweanor 2001:127-138). We have radio-monitored 7 subadult pumas, 5 males and 2 females (Table 13). None of those died while we were monitoring them in the subadult age stage. F23 has become a breeding adult on the study area. M5 dispersed from his natal area and the study area at about 13 months old and went to the northwest slope of the Uncompahgre Plateau where he established an adult territory. M49 was orphaned at 9 months old when his mother F50 died. He dispersed from his natal area and the study area to the northeast slope of the Uncompahgre Plateau, but shed his expandable radio-collar at a fresh elk kill when he was about 15 months old. Puma M11 became a subadult at 13 months old and dispersed from his natal area at 14 months old. He moved to the Dolores River valley between Stapletone and Stoner, Colorado by December 14, 2006. He was legally killed by a puma hunter on December 12, 2007 when he was 30 months old, in the adult age-stage. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire more realistic estimates of their survival (i.e., other than 1.0). Contact was lost with 2 subadult males and 1 subadult female. F52 dispersed from the study area before we lost track of her in the area of the Black Canyon of the Gunnison in mid-May 2007. We lost track of M31 seven days after he was captured in April 2006. He might have dispersed from the study area. Efforts to locate him by flying over and around the study area have not been successful. M69 emigrated from the study area in spring 2008 when he was about 16 to 20 months old. We monitored him in the Beaton Creek area east of the Uncompahgre River for awhile until we lost contact with him in April 2008. In addition to the subadults discussed previously, a non-marked female puma about 18 to 24 months old was killed by a vehicle November 4, 2006 on highway 550 (between Colona and Ridgway), 120 �which forms the southeast boundary of our study area. The female appeared to be in good health (41 kg), was not pregnant, and was not lactating. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Although we have observed 3 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson‘s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations in different locations and at different times. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. A preliminary estimate of puma cub survival was made with 38 cubs (21 males, 17 females) that we marked (n = 31 were radio-collared) at nurseries when they were 26 to 42 days old. Only cubs that died of natural causes were used (i.e., 3 capture-related deaths were excluded). All cubs were born from May 2005 to July 2007. Cubs that died included 13 that were radio-collared at nurseries and 3 noncollared cubs that apparently disappeared from families because they were not subsequently observed or track counts indicated attrition in cubs. For the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989), the maximum survival period was assumed to be 365 days (i.e., 12 months) to coincide with the time that puma cubs would usually be expected to become independent from their mothers (Logan and Sweanor 2001). Otherwise, cubs were right censored if they reached independence, or we lost contact before then. Dates that bracketed the deaths or disappearances of cubs were used to estimate minim and maximum survival rates. Maximum estimated cub survival using the Kaplan-Meier procedure was 0.4998 (SE = 0.2499). The estimated minimum survival rate was practically the same, 0.4993 (SE = 0.2498). Cub survival estimated with a binomial model (Williams et al. 2001) was 0.5789 ± 0.1570 (95% C.I.). In order to improve the reliability of puma cub survival data, we will make an effort to increase the number of radio-collared cubs that are monitored. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by male pumas (Appendix A). Male-caused infanticide and cannibalism, along with aggression-caused mortality in adult (indicated previously) and subadult pumas (Logan and Sweanor 2001) has also been a dominant mortality factor in other puma populations in North America (Logan and Sweanor 2001:115-136). Such male puma behavior has been theorized for being a strong selective force in shaping the evolution of behavioral tactics and life history strategies in pumas (Logan and Sweanor 2001). The current closure on sport-hunting on the study area and protection of marked pumas from sport-harvest on the buffer area on the northern portion of the Uncompahgre Plateau for the reference period appears to be operating, so far. None of the adult or subadult pumas wearing functional GPS- or VHF-collars have died due to human causes. This reference condition enables us to quantify puma population structure, survival rates, and agent-specific mortality rates of pumas in the absence of direct 121 �human-caused mortality factors related to sport-hunting, and allow comparisons with the treatment period when hunting of pumas on the study area resumes. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 < 24 months old, 10 ≥ 24 months old) from a total of 49 in his previous study which was intended to ―a ssess the effects of sport-hunting on an unexploited population‖ (Anderson et al. 1992:5). They found 19 (90%) of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agent-specific mortality rates from our current effort cannot be clearly compared with the Anderson et al. (1992:53) data set because they pooled data for male and female pumas in seemingly arbitrary age stages that overlapped puma life history stages (i.e., cubs, subadults, adults). The Anderson et al. (1992:53) estimated survival rates with the Kaplan-Meier procedure (Pollock et al. 1989) for 20 male and 22 female pumas were: 1224 month old = 0.642; 24-36 months old = 0.692, 36 to 48 months old = 0.917, and 48-60 months old = 0.800. Actual sample sizes within each age-stage were not given. There were no quantitative data allowing estimation of survival and agent-specific mortality for cubs less than 12 months old. Segment Objective 5 Cumulative data gathered during the past 3.7 years on the Uncompahgre Plateau Puma Project allowed a minimum count of pumas on the Uncompahgre Plateau Study area, and attendant estimates of population structure, reproduction rates, and survival rates. Those data positioned this project to begin puma population modeling efforts. Such modeling processes are useful for CDOW Mammals Researchers to design the treatment phase of this research project and provide CDOW wildlife biologists and managers with tools to assess current puma harvest management assumptions (previously in Testing Assumptions and Hypotheses) and other conceptual and proposed puma management approaches. A deterministic, discrete time model was developed and created on Excel (Microsoft Office software 2007) by principal investigator K. Logan and CDOW Biometrician P. Lukacs. The model structure has 3 age stages recognized in puma population biology (Logan and Sweanor 2001)− adult, subadult, and juvenile− and which are consistent with parameters we are estimating in this research and available in the technical literature on puma populations: Adult: NAFt+1 = (SF*NAFt + SSF*NSFt)(1-HAFt+1) NAMt+1 = (SM*NAMt + SSM*NSMt)(1-HAMt+1) Subadult: NSFt+1 = ((rSJF*NJt)(1-HSFt+1))PIF/EF NSMt+1 = (((1-r)SJM*NJt)(1-HSMt+1))PIM/EM Juvenile: NJt+1 = RNAFt+1 The model terms are: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). PI/E = Ratio of progeny + immigrants/emigrants. R = Reproductive rate for adult females (i.e., average number of cubs per female per year). 122 �r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). These basic assumptions pertain to the use of this model. Expected puma population projections and annual rates of increase (i.e., lambda) generated by the model are conditional on the assigned puma population structure and demographic estimates that parameterize the model. The model structure does not include density dependence, and thus, should not be used to project population trends beyond 10 years. In reality, density dependence probably operates in puma population dynamics, with competition for food expected to regulate independent (i.e., adults and subadults) female density and competition for mates expected to regulate independent male density (Logan and Sweanor 2001). The model structure also assumes that puma harvest is strongly additive mortality, an assumption that is consistent with the current observed adult and subadult (i.e., harvest-age pumas) puma survival rates in the reference period and for adult pumas in other non-hunted puma populations (Logan and Sweanor 2001). We used this model to simulate puma population dynamics to examine a set of scenarios that pertain to current CDOW puma management assumptions and to consider the puma research and management direction for the treatment period. Furthermore, we modeled the potential population impact of the historical puma harvest on the study area prior to the current puma research (i.e., 1994-2003). We parameterized the model with data gathered on the pumas on the study area during the past 3.7 years. The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table 9). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radiocollared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table 14). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature (Table 14), because our current sample sizes (i.e., number of individuals and years) were not adequate for realistic estimates (i.e., estimates from our data were 1.0 for adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to emigrants as a model input was from the literature, because such data is scarce and does not exist for Colorado (all references in Table 14). We preferred using the population characteristics and parameter estimates gathered in the current study, because this is the puma population we intend to manipulate in the treatment period to test CDOW puma management strategies. Results of our modeling efforts are presented in Appendix B. This constitutes the first time that current CDOW puma harvest assumptions have been evaluated by using Colorado-specific population data, and thus, is considered to be preliminary. Expected estimates of population growth were generally consistent with the CDOW puma harvest management assumptions that were previously developed from data in the puma population literature to manage for a stable-to-increasing population and for a declining puma population. The results demonstrated the importance of female survival to population dynamics. As more quantitative population data is gathered and the puma population is manipulated during the treatment period, population dynamics can be evaluated further. Results from the model evaluating the historical puma mortality on the study area during 1994 to 2003 indicate the expected outcome is that the puma population on the study area would decline during the treatment years. Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away 123 �from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that 6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). We monitored only 1 puma family with a radio-collared mother and cub from November 13, 2007 to February 14, 2008 during 8 airplane flights (Table 16).To assess whether mothers were apart or in close association with cubs, we considered error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Five of 8 (62%) of the observations located the mother and cub :c::::500 m apart, within the extreme margin of location error. In aggregate, the data for the past 3 winters include 136 observations for 1−5 families per winter (Table 15), and generally indicate that puma mothers are more likely to be within 520 m of their cubs during the day in winter. An effort will be made to increase the number of radio-collared family members in subsequent winters. In addition, we will examine variation in mother-cub association distances on an individual female basis. Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Principal investigator K. Logan developed 6 drafts study plans pertaining to the next 6 years of puma research on the Uncompahgre Plateau. Three of the drafts were circulated for internal review to obtain comments from CDOW Mammals Research Leader D. Freddy, Carnivore Biologist J. Apker, Area 18 Biologist B. Banulis, Southwest Regional Biologist S. Wait, and Area 18 Wildlife Manager R. Del Piccolo. The planning process involved modeling puma population scenarios (previously in Segment Objective 5) and modeling mark-recapture scenarios in MARK (Cooch and White 2004) with CDOW Biometrician P. Lukacs. The mark-recapture modeling process enabled consideration of effects of puma population size and individual detection rates on the ability to detect changes in puma population abundance that might result from the hunting treatment. Results of the MARK simulations applied to a scenario with 3 capture occasions and puma population abundances that varied from 25 to 50 animals indicated that individual detection rates would need to be 0.4 or greater to be able to detect changes in puma abundance (Table 16). The study plan is expected to be completed in September 2008, with a decision on a course to proceed with the remainder of the research soon thereafter. Segment Objective 8 Data from 23 (7 male, 23 female) GPS-collared pumas, totaling over 31 thousand GPS locations (Table 17) are currently being used in a collaborative study of puma prey use on the Uncompahgre Plateau, carried out by CDOW Mammals Research staff. Plans to use these and other data subsequently gathered, include habitat modeling and mapping for pumas in the western U.S. in collaboration with colleagues at Colorado State University (CSU), and descriptive information on puma behavior in relation to human development on the Uncompahgre Plateau. We are currently collaborating with Dr. Sue VandeWoude and Dr. Kevin Crooks, and postdoctoral and graduate students at CSU to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to the Department of Microbiology, Immunology, and Pathology at CSU for analyses. That project will be expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of 124 �that project and incomplete results on infectious disease surveillance on 27 pumas (16 female, 11 male) sampled on the Uncompahgre Plateau are presented in Appendix C. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 3.7 years of effort, 90 pumas have been captured, sampled, marked, and released. Of those, 74 pumas were radiocollared, allowing us to monitor fates of pumas in sexes and age stages, including: 15 adult females, 11 adult males, 2 subadult females, 5 subadult males, 25 female cubs, 22 male cubs. As of July 2008, we were monitoring 18 adults, 1 subadult, and 4 cubs with active radio-collars. Data from the marked animals are used to quantify puma population characteristics and vital rates in a reference situation (i.e., without sport-hunting off-take). During November 2007 through March 2008 a minimum estimate of 33 independent pumas were detected on the Uncompahgre Plateau study area, up from 24 the previous winter, with estimates of sex and age structure. Our efforts to quantify puma population characteristics and vital rates positioned us to begin puma population model development, and to use modeling scenarios to assess potential directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools useful to CDOW wildlife biologists and managers for assessing effects of puma harvest strategies. A study plan for the remainder of the research has been in development and should be completed in September 2008. To improve data on puma population vital rates, attention will be given to increasing sample sizes on radio-collared adult males, subadults, and cubs. Furthermore, data from 23 GPS –collared pumas, totaling over 31 thousand GPS locations enables collaboration on investigations of puma use of prey, puma-human relations on the Uncompahgre Plateau, and puma habitat modeling and mapping with colleagues. All of these efforts should enhance the Colorado puma research and management programs. LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Beier, P., and R. H. Barrett. 1993. The cougar in the Santa Ana Mountain Range, California. Orange County Cooperative Mountain Lion Study Final Report. Bergman, E. J., M. W. Alldredge, K. A. Logan, M. Shuette, C. J. Bishop, and D. J. Freddy. 2007. Study Plan-Pilot evaluation of predator-prey dynamics on the Uncompahgre Plateau. Pages 83-96 in Bergman, E.J. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report July: 73-96. Colorado Division of Wildlife, Fort Collins. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Caughley, G. 1978. Analysis of vertebrate populations. John Wiley and Sons, New York. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. Colorado Division of Wildlife. 2007. Colorado mountain lion management data analysis unit revision and quota development process. Colorado Division of Wildlife, Denver. Conover, W. J. 1999. Practical nonparametric statistics. John Wiley & Sons, Inc., New York. Cooch, E., and G. White. 2004. Program MARK- a gentle introduction, 3rd edition. Colorado State University, Fort Collins. 125 �Culver, M., W. E. Johnson, J. Pecon-Slattery, and S. J. O‘Brien. 2000. Genomic ancestry of the American puma (Puma concolor). The Journal of Heredity 91:186-197. Currier, M. J. P., and K. R. Russell. 1977. Mountain lion population and harvest near Canon City, Colorado, 1974-1977. Colorado Division of Wildlife Special Report No. 42. Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and cause specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674. Kendall, W.L. 2001. The robust design for capture-recapture studies: analysis using program MARK. Pages 357-360 in R. Field, R. J. Warren, H. Okarma, and P. R. Sievert, editors. Wildlife, land, and people: priorities for the 21st century. Proceedings of the Second International Wildlife Management Congress. The Wildlife Society, Bethesda, Maryland, USA. Koloski, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2004. Colorado puma research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center, Ft. Collins. _____. 2005. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. July: 105-126, Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O‘Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Otis, D. L., K. P. Burnham, G. C. White, and D. R. Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. Winterstein, and M. J. Conroy. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. 126 �Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:1076-1084. Van Ballenberghe, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a re-evaluation. Journal of Wildlife Management 47:1245-1247. Watkins, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. Worton, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Young, S. P. and E. A. Goldman. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 127 �Table 1. Summary of puma capture efforts with dogs from November 19, 2007 to April 24, 2008, Uncompahgre Plateau, Colorado. Month November No. Search Days 5 December 18 January 18 69 tracks: 23-27 male, 22-26 female, 20 cub 5 pursuits: 2 males, 3 females February 20 64-65 tracks: 14-15 male, 30-31 female, 19-20 cub 21 pursuits: 9 males, 9 females, 3 cubs March 11 17 tracks: 5-6 male, 9-10 female, 2 cub April 5 15 tracks: 1 male, 6 female, 8 cub 217-218 tracks: 6573 male, 85-93 female, 59-60 cub 11 pursuits: 3-4 males, 4-5 females, 3 cubs 6 pursuits: 2 females, 4 cubs 49 pursuits: 16-17 males, 20-21 females, 12 cubs No. & type of pumas pursued 1 pursuit: 1 male 5 pursuits: 1 male, 2 females, 2 cubs No. & I.D. or type of pumas captured 1 puma recaptured: M55 (not handled). 4 pumas captured 5 times: M32 recaptured (not handled), F25 recaptured (faulty GPS collar changed), cub F57 recaptured twice (not handled), cub M44 recaptured by Wildlife Services & killed for depredation on domestic sheep. 5 pumas captured: M69 & M71 (handled & marked for the first time), F16 recaptured (faulty GPS collar changed), F2 recaptured (faulty GPS collar changed), F70 (handled & marked for the first time). 5 pumas captured 7 times: M73 (handled & marked for the first time), F23 recaptured 3 times (could not be handled safely first 2 times, faulty GPS collar changed the 3rd time), F72 (handled & marked for the first time), 1 radio-collared male puma was visually observed in association with F23 while pursuing a female & male puma with dogs on 2-25-08, but he could not be treed to handle (either M27 or M29, both with non-functional GPS collars), 1 unmarked adult female captured (could not be handled safely). 2 pumas captured: F74 (handled & marked for the first time), F75 (handled & marked for the first time). 0 pumas captured 20 captures of 17 individuals: 7 independent pumas and 1 cub were captured for the 1st time- M69, F70, M71, F72, M73, cub F74, F75, & 1 unmarked adult female (not handled). a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; 50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. TOTALS 77 No. & type of puma tracks founda 20 tracks: 9 male, 8 female, 3 cub 32 tracks: 13-15 male, 10-12 female, 7 cub 128 �Table 2. Summary of puma capture efforts with dogs, December 2004 to April 2008, Uncompahgre Plateau, Colorado. Period Track detection effort 109/78 = 1.40 tracks/day Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 77/49 = 1.57 day/pursuit 77/20 = 3.85 day/capture 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from January 2008 to March 2008, Uncompahgre Plateau, Colorado. Puma I.D. M69 F70 M71 F72 M73 F74 F75 Sex M F M F M F F Estimated Age (mo.) 14-18 33 24 24 49 8-9 41 Mass (kg) 42 39 55 43 60 18 39 Capture date 01-11-08 01-14-08 01-29-08 02-12-08 02-21-08 03-12-08 03-26-08 Capture method Dogs Dogs Dogs Dogs Dogs Dogs Dogs 129 Location Dolores Creek Dolores Creek East Fork Dry Creek Loghill Mesa North fork Cottonwood Creek North fork Cottonwood Creek Cottonwood Creek �Table 4. Pumas that were captured and observed with aid of dogs, but were not handled at that time for safety or other reasons, December 2007 to February 2008, Uncompahgre Plateau, Colorado. Puma sex Capture date Location Comments F57 Age stage or months 7 12-03-07 Caterwauler Canyon F57 8 12-19-07 Loghill Mesa Female adult 02-01-08 Cottonwood Canyon F23 49 02-19-08 F23 49 02-20-08 Big Bucktail Canyon San Miguel Canyon M27 or M29 78 107 02-25-08 F57 was previously marked at the nursery when about 35 days old; born ~April 16, 2007. F57 was recaptured high in a tree, too dangerous to attempt to handle her to fit an expandable radio-collar. F57 was recaptured in a tree that did not allow safe immobilization to handle her to fit an expandable radio-collar. Unmarked female was bayed high in a tree out of range of dart gun. The puma left the tree, but escaped into deep system of sink holes too unstable for any research team member to enter. F23 was recaptured in a tree too dangerous to handle her to change the non-functioning GPS collar she wore. F23 was recaptured again in a tree too dangerous to handle her to change the non-functioning GPS collar she wore. She was safely recaptured and handled on 02-25-08, and was fit with a new GPS collar. A radio-collared male puma was visually observed in association with puma F23 when she & a male puma were pursued with dogs. The male puma was either M27 or M29, both of which had over-lapping home ranges in that area, and both had non-functional GPS collars. But, the male puma could not be treed for absolute identity or for handling. Big Bucktail Canyon Table 5. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 7, 2007 to July 15, 2008, Uncompahgre Plateau, Colorado.a Carnivore activity & capture effort resultsb No puma activity detected. One deer carcass scavenged by a black bear. No puma activity detected. Deer carcasses scavenged by skunk, bobcat, & black bear. Deer carcasses scavenged by male pumas M55 (10-2 to 3-07) and M29 (10-19 to 22-07). Puma M51 walked ~4 m from a deer carcass, but did not feed. An unknown female puma scavenged on a deer carcass 10-16-07; two cage traps were set and monitored for 2 days, but puma did not return. Deer carcasses were also scavenged by bobcat, coyote, and black bear. November 3 An unknown female puma walked past a deer carcass on 11-1&2-07, but did not feed. An unknown female puma walked past another deer carcass on 11-4-07, but did not feed. An unknown male puma walked past a deer carcass on 11-14-07, but did not feed. Deer carcasses were scavenged by bobcat and coyote. December 2 No puma activity detected. March 3 Unknown male puma scavenged a deer carcass 3-15 to 17-08; two cage traps set and monitored 3-18 &19-08, but puma did not return. Unknown male puma (possibly same as above) scavenged deer carcass 3-23 to 24-08; cage trap set and monitored 3-25 to 27-08, but puma did not return. April 5 Male puma M6 recaptured 4-12-08. He had shed his non-functional GPS collar; we fit him with a new one. An unknown female puma scavenged a deer carcass on ~4-10-08, but did not return. A deer carcass was visited by unknown male & a female pumas; one or both scavenged 4-16-08. Two cage traps were set and monitored 4-17 to 19-08, but the pumas did not return. An unknown male puma scavenged a deer carcass 4-19 or 20-08. Cage trap set and monitored 4-21 to 25-08, but the puma did not return. An unknown female puma scavenged a deer carcass 4-23-08. Cage trap was set and monitored 4-23 to 25-08, but the puma did not return. Another unknown female puma walked past a deer carcass without feeding. July 1 Puma M6 was recaptured 7-15-08; his non-functional GPS collar was replaced with a VHF collar. This was the same bait site and cage trap where we recaptured M6 on 4-8-08. a We used 59 road-killed mule deer, 1 road-killed elk, and 1 puma-killed mule deer (abandoned by F30 and used as bait) at 15 different sites. Of the road-killed ungulate baits, 11 of 60 (18.3%) were scavenged by pumas. b One adult male puma, M6, was recaptured twice. Month August September October No. of Sites 3 4 12 130 �Table 6. Pumas recaptured with dogs, cage traps, or visually observed, November 2007 to July 2008, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date Estimated Age (mo.) 42 76 Capture Method Process 11-28-07 12-02-07 Mass (kg) Observed Observed M55 M27 Dogs Dogs F25 F57 M44 12-03-07 12-03-07 12-05-07 45 Observed 50 102 7.5 15.5 Dogs Dogs Dogs M32 F57 F16 F2 M27 12-12-07 12-19-07 01-01-08 01-08-08 01-22-08 Observed Observed 43 42 Observed 76 8 59 85 77 Dogs Dogs Dogs Dogs Dogs F25 01-26-08 Observed 103 F23 F23 F23 M27 or M29 02-19-08 02-20-08 02-25-08 02-25-08 Observed Observed Observed Observed 42 42 42 78 107 M6 M6 04-12-08 07-15-08 67 63 74 77 Visual observation of F25 attacking a mule deer after detecting tracks on snow, then snow& radio-tracking Dogs Dogs Dogs Visually observed while pursued by dogs Cage Cage None None, treed in E. fork Tabeguache Cr. by outfitter Stan Garvey, Nucla, CO Changed GPS collar None Shot by Wildlife Services for depredation on domestic sheep None None Changed GPS collar Changed GPS collar None, treed in Johnson Cr. by outfitter Stan Garvey, Nucla, CO None None None Changed GPS collar None GPS collar VHF collar Table 7. Puma cubs sampled June 2007 to August 2008 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) F74b F June 1, 2007 267 18 F75 32 M76 M May 19, 2008 30 2.0 F2 89 M77 M ― ― 2.3 ― ― F78 F ― ― 1.2 ― ― M79 M ― ― 2.2 ― ― F80 F May 23, 2008 40 1.1 F23 45 F81 F ― ― 2.8 ― ― M82 M May 29, 2008 37 2.8 F8 58 M83 M ― ― 2.5 ― ― M84 M June 5, 2008 36 2.6 F70 38 F85 F ― ― 1.8 ― ― F86 F ― ― 2.0 ― ― M87 M July 3, 2008 28 1.9 F3 83 M88 M ― ― 1.8 ― ― F89 F ― ― 1.7 ― ― M90 M July 9, 2008 36 2.1 F72 29 a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs with mother only with radio-telemetry. b This unmarked female cub was captured on 03-12-08 in association with an unmarked adult female puma. The adult female puma, F75, was captured and marked 03-26-08 with cub F74 in association. 131 �Table 8. Pumas detected by tracks and identified by radio-telemetry, GPS-collar fixes, and visual observation. Puma I.D.a Date detected Estimated Age of Tracks on Snow (days) Type of IdentificationRadio-telemetry (VHF) and/or GPS fixes, Visual Observation M55 12/2/07 2 GPS M51 12/3/07 1 VHF & GPS F3 12/6/07 1 VHF & GPS M55 12/15/07 1 VHF & GPS M55 12/18/07 1 VHF (GPS inconclusive) F7 12/28/07 1 VHF & GPS M51 12/28/07 1 VHF & GPS M51 1/3/08 1 VHF M51 1/10/08 1 VHF & GPS F2 1/11/08 1 VHF & GPS F16 & cubs 1/15/08 2 VHF & GPS M51 1/17/08 1 VHF & GPS F16 1/17/08 2 VHF & GPS F25 1/17/08 2 VHF & GPS F16 & cubs 1/18/08 1 VHF & GPS F25 & cub F57 1/18/08 1 VHF & GPS F16 & cubs 1/22/08 1 VHF & GPS F16 & cubs 1/24/08 1 VHF & GPS F25 & cub F57 1/26/08 1 VHF & GPS & visual of F25 F16 & cubs 1/26/08 1 VHF & GPS M55 1/26/08 1 VHF & GPS M32 & Unk.F 1/31/08 1 VHF (GPS NA)b M32 2/6/08 1 VHF (GPS NA) F25 & cub F57 2/12/08 2 VHF & GPS F16 & cubs 2/13/08 1 VHF & GPS F16 2/14/08 1 VHF & GPS F16 & 3 cubs 2/15/08 1 VHF & GPS F8 2/21/08 2 VHF (GPS NA) F23 2/28/08 1 VHF & GPS F23 3/12/08 2 VHF & GPS F8 3/12/08 1 VHF (GPS NA) F25 & cub F57 4/12/08 1 VHF (GPS inconclusive) F16 & 3 cubs 4/12/08 1 VHF (GPS inconclusive) F24 & 2 cubs 4/24/08 1 VHF (GPS NA) a Eleven individual adult radio- and/or GPS-collared pumas were first detected by tracks on snow, then identified by radio- and GPS data, including one visual observation, a total of 34 times. b GPS NA means the GPS instrument was non-functional, but the VHF beacon was working. 132 �Table 9. Minimum puma population estimate based on numbers of known radio-collared pumas and track counts of suspected unmarked pumas on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008. Adults Subadults Cubs Female Male Female Male Female Male Unknown sex 10 4 3 4 4 4 7 6 4 2 0 1 2 2-3 16 8 5 4 5 6 9-10 Total Independent Pumas = 33a,b a Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. b The unmarked independent pumas included: 1adult female with 2 large cubs in Happy Canyon, 1 adult female with 1 large cub in Potter Creek and 25-mile Mesa, 1 adult female with 2 large cubs in Monitor Creek, 1 adult female with 2 medium-size cubs in Potter Creek, 1 adult female with 2-3 cubs in San Miguel Canyon, and 1 female or F28 with a non-functional collar Big Bucktail Creek to San Miguel Canyon. Region East slope West slope Totals Table 10. Puma reproduction, Uncompahgre Plateau, Colorado, 2005-2008. Consort pairs and estimated agesa Female Age Male Age (mo.) (mo.) F2 F2 F2 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F16 F16 F23* F23 53 67 89 36 50 62 83 67 82 106 24 37 58 32 52 21 45 Dates pairs consortedb M6 37 06/22-24/05 M51 60 03/31/08 M73 M27 or M29f M29 49 78 02/28-29/08 02/19-25/08 Estimated birth datec 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 09/22/05 05/24/07 05/30/06 05/23/08 Estimated birth interval (mo.) Estimated gestation (days) 14.0 22.0 13.8 11.7 21.5 93-95 94 14.9 23.9 13.4 22.5 90-91 19.9 23.8 87-93 Observed number of cubsd 3 2 4 1 2 3 3 2 4 3 2 4 2 4 4 3 2 107 F24 75 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F72* 29 07/09/08 1 F75 32 06/01/07 1 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS and radio-telemetry data. c Estimated birth dates were indicated by GPS and radio-telemetry data of mothers at nurseries. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 6 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. 133 �Table 11. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2008, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 No. days 616 M4 M5 01-28-05 to 12-28-05 08-01-06 to 07-31-08 333 730 M6 M27 02-18-05 to 07-31-08 03-10-06 to 01-22-08 1259 683 M29 04-14-06 to 01-11-08 637 M32 M51 M55 M71 M73 F2 F3 F7 F8 F16 F23 F24 F25 F28 F30 04-26-06 to 07-31-08 01-07-07 to 07-31-08 01-21-07 to 07-31-08 01-29-08 to 07-31-08 02-21-08 to 07-31-08 01-07-05 to 07-31-08 01-21-05 to 07-31-08 02-24-05 to 07-31-08 03-21-05 to 07-31-08 10-11-05 to 07-31-08 02-05-06 to 07-31-08 01-17-06 to 07-31-08 02-08-06 to 07-31-08 03-23-06 to 09-25-07 04-15-06 to 07-29-08 827 571 557 184 161 1301 1287 1253 1228 1024 907 926 904 551 836 F50 12-14-06 to 03-26-07 102 F54 01-12-07 to 08-18-07 218 F70 F72 F75 01-14-08 to 07-31-08 02-12-08 to 07-31-08 03-26-08 to 07-31-08 199 170 127 Status: Alive/Lost contact/Dead; Cause of death Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area. Dead; killed by a male puma. Estimated age at death 37−45 months. Alive. Born on study area; offspring of F3. He was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months. Alive. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-2208 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Lost contact− failed GPS/VHF collar. Died; killed by another puma (sex of puma unknown). Estimated age at death 60 months. Died of natural causes; exact agent unknown. Estimated age at death 30 months. Died; killed by a male puma while in direct competition for prey (i.e., mule deer fawn). Estimated age at death 49 months. Alive. Alive. Alive. Table 12. Preliminary estimated survival rates (S) of adult-age pumas during the reference period (i.e., the study area is closed to puma hunting), Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31) and the hunting season period (November 1 through March 31). Survival rates were estimated only for periods when n ≥ 5 individuals. Period of interest Annual 8/1/2006 to 7/31/2007 Annual 8/1/2007 to 7/31/2008 Hunting season 11/1/2006 to 3/31/2007 Hunting season 11/1/2007 to 3/31/2008 S 0.909 Females SE 0.0867 n 11 S 1.000 Males SE 0.0000 n 5 0.825 0.1041 13 1.000 0.0000 9 0.909 0.0867 11 1.000 0.0000 5 1.000 0.0000 12 1.000 0.0000 9 134 �Table 13. Summary of subadult puma survival and mortality, December 2004 to June 2008, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span No. days 09-16-05 to 06-3006 308 M11 06-21-06 to 12-0207 529 F23 01-04-06 to 02-0406 04-19-06 to 04-2606 31 M49 03-26-07 to 10-0107 189 F52 01-10-07 to 05-1507 125 M69 01-11-08 to 04-0708 87 M31 7 Status: Alive/Survived to adult stage/ Lost contact/Dead; Cause of death Alive; independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau. Dead. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by Dec. 14, 2006. Killed by a puma hunter Dec. 12, 2007 when 30 months old. Alive. Captured on the study area when ~17 months old. Survived to adult stage; gave birth to first litter at ~21 months old. Lost contact. Probable disperser. M31‘s estimated age at capture was 25 months, at the lower margin of puberty for puma. He may have been a dispersing subadult, and could have moved away from the study area. Lost contact. M49 was orphaned at about 9 months old, when his mother F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was ~15 months old, he shed his expandable radio-collar on ~10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. Lost contact. Dispersed from study area as a subadult by Jan. 16, 2007. F52‘s last location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon. Lost contact. Captured on the study area when ~14-18 months old. Emigrated from the study area as subadult by Mar. 19, 2008. Last location was in Beaton Creek, east side of Uncompahgre River valley. 135 �Table 14. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the published literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Parameter Adult age Estimate 2+ years Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). Also see Robinette et al. 1961, Logan and Sweanor 2001:69-70. Proportion of adult females giving birth each year (n = 3 years for ns = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits /Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). 136 �Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, each winter, Uncompahgre Plateau, Colorado. Monitoring period Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs 520 m apart Nov. 9, 2005 to Nov. 3 4 2−6 10 Mar. 29, 2006 Dec. 4 4 3−7 16 Jan. 5 4 4−8 16 Feb. 4 5 5−9 16 Mar. 2 5 6−10 9 Totals 18 4−5 2−10 67 Nov. 7, 2006 to Nov. 4 4 2−3 10 Mar. 22, 2007 Dec. 4 4 2−5 11 Jan. 5 3 4−6 9 Feb. 4 4 5−7 9 Mar. 3 1 8 2 Totals 20 1−4 2−8 41 Nov. 13, 2007 to Nov. 2 1 6 1 Feb. 14, 2008 Dec. 0 1 7 NA Jan. 3 1 8 2 Feb. 3 1 9 2 Totals 8 1 6−9 5 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650−1,600. c Mean = 1,120 m, SD = 1,214.40, range = 616−4,101. d Mean = 1,317 m, SD = 530, range = 750−1,800. No. observations with mothers & cubs >520 m apart 2 4 4 2 0 12b 1 1 3 2 1 8c 1 NA 1 1 3d Table 16. Results of MARK (Cooch and White 2004) simulations to investigate precision as a function of individual capture probabilities and population size. Expected Standard Error Capture Probability (p) 0.2 0.3 0.4 0.5 Large Population (n = 50) 21 9.6 5.5 3.5 Small Population (n = 25) 13 7.8 4.2 2.5 Confidence Interval width Large Population (n = 50) 84 38.4 22 14 137 Small Population (n = 25) 52 31.2 16.8 10 Large Pop. Lower Bound Small Pop. Upper Bound 8 31 39 43 32 29 27 26 �Table 17. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2008. Puma I.D. M1 M4 M6 M27 M29 M51 M55 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 05-17-08 1,464 adult 01-21-07 to 05-01-08 1,334 adult 01-07-05 to 05-07-08 3,239 adult 01-21-05 to 04-01-08 3,205 adult 02-24-05 to 07-30-07 2,401 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 04-01-08 2,089 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 05-07-08 746 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 04-07-08 1,854 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-01-08 686 F70 F adult 01-14-08 to 07-31-08 685 F72 F adult 02-12-08 to 07-31-08 737 F75 F adult 03-26-08 to 07-02-08 287 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma in this report period. 138 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 139 �Age sh'ucture ofindeJJendent1mmas rn}Jtured and smnJJled for the first time from December 2004 to March 2008,Uncom}Jahgre Plateau. Colorndo. 7 6 5 ltl § 4 >- - - ~ ■ female ~ 0 0 3 >- -- 2 >- -- 1 >- - 0 >- __._______ Male z ~ I- - ' I 1 to 2 >2 lo 3 >3 to 4 -,4 lo 5 >5 to 6 >6 lo 7 >7 to 8 >8 to 9 Age ( years) >9 to 10 Figure 2. Age structure of independent pumas captured and sampled for the first time on the Uncompahgre Plateau, Colorado, December 2004 to March 2008. Puma births. Uncompabgre Plateau. Colorado 8 7 6 l:'.' 5 ':J ci 4 ~ z 3 2 1 'l 0 Jc1n. 11 I - -- ..,_ Feb. Mai. Apr. May June July ■ Bi rths 2005-2008 i: ~ l Aug. Sep. I Oct. Nov. Dec. Births 1983°1987 Figure 3. Puma births detected by month during the current research effort, 2005 to 2008 (n = 28 litters of 15 females), and during the earlier effort by Anderson et al. (1992; 1983 to 1987, n = 10 litters of 8 females), Uncompahgre Plateau, Colorado. 140 �3 Age sh·ucture of independent pumas in Manh 2008, of ~11rvivingpumas raptured ancl sam11Iecl from December 200-t to l\ifarch 2008. while protected from spoTt-lnmting since Ap1"il 2004. Uncompahgre Plateau, Colornclo ■ Fema·lt- 1 T 0 llol >2to3 Male,: Ir ----.- ?3 to4 >4to5 >5to6 >6to7 ?7to8 >8to9 >9to10 101 Age (years) Figure 4. Age structure of surviving independent pumas captured and sampled on the Uncompahgre Plateau, Colorado, in March 2008, and after protection from sport-hunting mortality since April 2004, which includes 4 hunting seasons (Nov. through Mar., 2004-05 to 2007-08). In addition, no other humancaused mortalities were documented in the radio- and GPS-collared sample of independent pumas. This age structure assumes that puma M27 and M29 were alive on March 31, 2008; they each had nonfunctional GPS collars, and were detected alive on 1-22-08 and 1-11-08, respectively. Pumas M5 and M27 range north of the study area and were protected from legal sport-harvest because they are visually tagged animals. Mean ± SD of adult female and adult male ages, respectively: 5.35 ± 2.11 yr. (64.23 ± 25.36 mo.); 4.79 ± 2.17 yr. (57.50 ± 26.06 mo.). 141 �Appendix A. Summary of individual puma cub survival and mortality, December 2004 to 2008, Uncompahgre Plateau, Colorado. Puma I.D. Est. Birth date Est. survival span from 1st capture to fate or last monitor date M5 Estimated Age at capture (days) 183 ~8-1-04 02-04-05 to 04-07-08 F9 31 5-28-05 F10 31 5-28-05 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 M11 31 5-28-05 06-27-05 to 12-2-07 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 F13 42 5-19-05 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 Age to last monitor date alive or at death (days, birth to fate) ~1,345 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Lost contact― shed radiocollar 04-19-06 to 04-26-06. F3 Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 1230-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7‘s tracks. Dead; killed and eaten by a puma (sex unspecified) about 8-28-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 0614-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 324 Lost contact; radiocollar quit. Last aerial location 8-1606, live signal. F3 326-333 176-215 918 203-252 101 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 142 F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma Estimated I.D. Age at capture (days) M22 37 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 9-26-05 M26 183 8-1-05 F33 31 5-30-06 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 F34 31 5-30-06 06-30-06 to 07-31-06 63-65 F35 31 5-30-06 38 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 M44 33 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 86-87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Dead; killed and eaten by male puma 12-21-05―12-2205. F3 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 63-65 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a F23 Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 7/16-17/07 at 352-353 days old. F28 F8 53-61 106 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 0425-07. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 0425-07. Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 10-13-06 (collar found); assumed dead. Dead; research-related fatality.b 200 Treed, visually observed 03-01-07. F7 F7 479 Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12/5/07, for killing 4 domestic sheep. 74 74 352-353 9 255 9 255 143 F23 F23 F28 F2 F8 F8 F8 �Appendix A continued Puma Estimated I.D. Age at capture (days) F45 33 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 8-13-06 09-15-06 to 5-20 to 23-07 M46 9-17-06 10-18-06 to 12-15-06 31 Age to last monitor date alive or at death (days, birth to fate) 280-283 89 360 M47 M48 M49 F53 31 31 153 183 9-17-06 9-17-06 7-1-06 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 89 360 89 360 12-05-06 to 07-31-07 to 01-01-07 01-12-07 to 02-23-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 ~456 42 ~428 subad. 200 52 324 434 144 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 1219 to 20-06. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. M49 was orphaned when his mother died on about 0326-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. F7 Lost contact― shed radiocollar 2-27-07. M56 observed 03-01-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-06-07. Not radio-collared. Tracks of 3 cubs observed with F16‘s tracks on 04-1208, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F3 F3 F3 F50 F54 F7 (?) F25 F16 �Appendix A continued Puma Estimated I.D. Age at capture (days) F59 34 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 5-24-07 06-27-07 to 08-21-07 Age to last monitor date alive or at death (days, birth to fate) 55 324 434 M60 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 F61 34 5-24-07 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 M65 34 7-14-07 08-17-07 F66 37 7-17-07 08-23-07 to 5-31 to 6-1-08 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 M77 30 30 5-19-08 5-19-08 03-12-08 to 07-09-08 06-18-08 06-18-08 48-49 324 434 262 262 282-283 403 145 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16‘s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16‘s tracks on 04-1208, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24‘s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24‘s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. One male cub might have died or was not observed. Radio-collared. Shed radiocollar between 7-9-08 and 715-08, probably while still dependent on mother F75. Not radio-collared. Not radio-collared. F16 F16 F24 F24 F24 F24 F30 F30 F30 F75 F2 F2 �Appendix A continued Puma Estimated I.D. Age at capture (days) F78 30 M79 30 F80 40 F81 40 M82 37 M83 37 M84 36 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 5-19-08 5-19-08 5-23-08 5-23-08 5-29-08 5-29-08 6-5-08 06-18-08 06-18-08 07-02-08 07-02-08 07-05-08 07-05-08 07-11-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. F2 Not radio-collared. F2 Not radio-collared. F23 Radio-collared. F23 Radio-collared. F8 Not radio-collared. F8 ~69 Radio-collared 7-11-08 to 7-22-08; collar removed F70 because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08; assuming M84 died, he probably died around 8-13-08 when cub F85 was located ~340m south of the eartag in the East fork Dolores Cyn. F85 36 6-5-08 07-11-08 Radio-collared. F70 F86 36 6-5-08 07-11-08 Radio-collared 7-22-08. F70 M87 28 7-3-08 07-31-08 Not radio-collared. F3 M88 28 7-3-08 07-31-08 Not radio-collared. F3 F89 28 7-3-08 07-31-08 Radio-collared F3 M90 36 7-9-08 08-14-08 Radio-collared F72 7MA 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 7MB 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 7FC 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 146 �Appendix B. Puma population models and simulation results as preliminary assessments of current CDOW puma management assumptions and population manipulations for the treatment period. Modeling Scenarios We modeled a set of scenarios that pertain to current CDOW puma management assumptions and to potential puma research direction on the Uncompahgre Plateau for the treatment period: 1) Puma population dynamics without hunting-caused mortality. 2) Puma harvest that would induce a stable (i.e., no growth) phase to identify a population tipping point induced by harvest mortality. 3) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population, with harvest apportioned equally among independent males and females. 4) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population, but with harvest comprised of 40% females and 60% males, which is consistent with the sex composition of puma harvest in Colorado. 5) Puma harvest at the upper limit (i.e., 28% of 16-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population, with harvest apportioned equally among independent males and females. 6) Puma harvest at the upper limit (i.e., 28% of >15-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population, but with harvest comprised of 40% females and 60% males, which is consistent with the sex composition of puma harvest in Colorado. 7) A harvest scenario applied the historic puma harvest on the study area. Puma mortality data for the study area during the 10 years previous (i.e., 1994-2003) to the beginning of the reference period was quantified after carefully geo-referencing mortality locations on the study area (see last table in Appendix B). Model parameters from those data include: mortality rate of 14.3 independent puma mortalities per year (rounded to 14/yr.), and sex proportions of 55% males and 45% females. No other puma population data or parameter estimates were available for the study area at that time. Therefore, the scenario that was modeled pertained to the expected impact of the average annual puma mortality of independent pumas (i.e., adults and subadults) if the hypothetical population was the same as the non-hunted minimum expected puma population in treatment period year 1 (i.e., TY1). A harvest of 14 pumas per year is a 26% harvest rate on the expected TY1 non-hunted minimum independent puma population (i.e., 14/53). Another way of stating this scenario is; what would occur if puma harvest was applied to the puma population on the study area during the treatment period at the average rate of puma mortality that was recorded during 1994 to 2003? Results of Puma Population Simulations The following tables contain the expected minimum population sizes for independent pumas and annual rates of population increase for independent pumas conditional upon the minimum number of independent pumas detected in Reference Year 4 (RY4) and the model input parameters and assumptions (Table 14, this report). Notes below each table explain how results may be interpreted relative to other research results on puma population dynamics and specific CDOW puma management assumptions. The harvest levels for each model are clearly stated in the left column of each table. Simulations involving harvest apply the harvest following reference year 5 (RY5) and starting with treatment year 1 (TY1). 147 �Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 23 14 8 8 42 53 1.14 TY2 27 17 11 10 49 64 1.18 TY3 32 22 12 11 58 77 1.17 TY4 38 27 15 14 69 92 1.17 TY5 44 32 17 16 81 110 1.16 Note: Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau approach the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4; r = 0.28, n = 4; r = 0.17, n = 4; r = 0.11, n = 7; Logan and Sweanor 2001:169-175). Puma population growth could be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater prey biomass), and if puma sources are nearby to the study area. Harvest Level No harvest. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 12 7 6 35 44 0.98 TY2 19 12 8 7 34 45 1.02 TY3 19 13 7 7 34 46 1.01 TY4 19 13 7 7 34 46 1.01 TY5 19 14 7 7 34 46 1.00 Note: The tipping point of population stability and decline is expected to be about 16% harvest of independent male and female pumas, consistent with current CDOW puma harvest assumptions. Harvest Level 16% of independent pumas, sexes are harvested equally; i.e., stable phase model. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 12 7 7 36 45 0.99 TY2 19 12 8 7 35 47 1.03 TY3 19 13 8 7 36 47 1.02 TY4 20 14 8 7 36 48 1.02 TY5 20 14 8 7 36 49 1.01 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with very slow growth attributed to equal harvest of females and males. Harvest Level 15% of independent pumas, sexes are harvested equally. 148 �Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 21 11 8 6 38 45 0.99 TY2 22 10 9 7 39 47 1.05 TY3 23 10 9 7 42 50 1.05 TY4 25 11 10 8 45 53 1.05 TY5 26 11 10 8 48 56 1.06 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with increased growth due to reduced female mortality. Harvest Level 15% of independent pumas, comprised of 40% females & 60% males. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 17 10 6 6 30 38 0.81 TY2 14 9 6 5 25 33 0.86 TY3 12 8 5 4 22 29 0.84 TY4 10 7 4 4 18 25 0.84 TY5 9 6 3 3 16 21 0.84 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population. Harvest Level 28% of independent pumas, sexes are harvested equally. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 8 7 4 34 38 0.81 TY2 18 6 7 5 32 35 0.92 TY3 17 5 7 4 31 33 0.93 TY4 16 4 6 4 30 31 0.95 TY5 16 4 6 4 29 30 0.95 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population even with harvest weighted toward males. Harvest Level 28% of independent pumas, comprised of 40% females & 60% males. Projected Minimum Puma Population Size Harvest Independent Pumas Adult Subadult Cub Level Year Female Male Female Male F&M Total Lambda 26% of RY4 16 8 5 4 20 33 independent RY5 18 10 9 8 33 45 1.27 pumas, TY1 18 9 7 6 33 41 0.89 comprised of TY2 17 8 7 6 31 39 0.94 45% females TY3 16 8 7 6 30 36 0.94 & 55% males; TY4 16 7 7 5 28 35 0.95 i.e. historical harvest model TY5 15 7 6 5 27 33 0.95 Note: Results of this model indicate that the expected outcome is that the puma population would decline. 149 �Appendix B (continued). Puma mortality data for portions of Game Management Units (GMUs) 61, 62, 70 that comprise the Uncompahgre Plateau Study Area, 1994-2003. GMU Year Adult Male Subadult Male Adult Female Subadult Female Subtotals 61 2003 4 2 3 0 9 62 2003 1 1 1 3 6 70 2003 0 0 0 0 0 61 2002 1 0 2 0 3 62 2002 0 0 3 1 4 70 2002 1 0 0 0 1 61 2001 4 0 5 0 9 62 2001 2 1 2 1 6 70 2001 1 0 1 0 2 61 2000 5 0 1 2 8 62 2000 0 0 0 0 0 70 2000 0 0 1 1 2 61 1999 3 1 3 0 7 62 1999 2 0 1 0 3 70 1999 2 0 1 0 3 61 1998 3 1 3 1 8 62 1998 3 1 0 0 4 70 1998 1 0 3 0 4 61 1997 5 1 1 0 7 62 1997 2 0 2 1 5 70 1997 1 0 0 0 1 61 1996 3 0 2 0 5 62 1996 2 1 3 0 6 70 1996 1 0 0 0 1 61 1995 6 1 4 0 11 62 1995 9 0 4 0 13 70 1995 1 0 0 0 1 61 1994 2 0 3 0 5 62 1994 3 1 4 0 8 70 1994 0 0 1 0 1 Subtotal 68 11 54 10 143 Total 79 males (55%) 64 females (45%) 14.3/yr. Note: Nine puma records did not designate adult or subadult age stages. Those data were determined with a cointoss for this table, resulting in 6 males designated as 3 adults and 3 subadults, and 3 females designated as 1 adult and 2 subadults. Three mortalities were recorded as ― road-kills‖ (1 subadult male, 2 subadult females). Two adult male deaths were recorded as ― other‖. Two adult male deaths were recorded as ― landowner‖. All other deaths were recorded as ― hunter harvest‖. Source of records: Colorado Division of Wildlife, 6060 Broadway, Denver, CO, and K. Crane, CDOW DWM, Ridgway. 150 �Appendix C. Collaborative project on disease surveillance in wild felids. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 Attached please find the consolidated report on infectious disease surveillance for the mountain lion samples you have provided to our laboratory as an adjunct to your CDOW ongoing studies. Our laboratory has performed puma-lentivirus (PLV) antibody screening using a sensitive western blot assay developed in our laboratory and found 13 of 18 samples conclusively positive (72%), with two additional samples inconclusive and one not tested. Dr. Michael Lappin, a veterinary internal medicine specialist with expertise in feline infectious disease has tested a subset of 6 samples for antibodies to Feline Calicivirus (FCV), Feline Herpes Virus (FHV), Feline parvovirus (FPV), Toxoplasma gondii (IgM, indicating recent infection, IgG indicating past exposure), and Bartonella hensalae (the agent associated with cat scratch disease). At least one of six animals tested has been positive for each of these agents. Further results are pending from the remaining samples you have provided for these 5 assays. In addition, Dr. Martin Scriefer at Fort Collins CDC has also tested 6 animals for evidence of antibodies to the agent responsible for plague (Yersinia pestis). Interestingly, 3 of 6 animals demonstrate significant exposure to this agent as well. These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, ― The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids‖, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Mr. Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. 151 �We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and inter-specific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that will be most valuable, and a draft of a ‗permissions‘ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids Project Summary Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in carnivore species. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and post-graduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multi-disciplinary collaborations. 152 �Appendix C (continued). Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado, 2005-2008. Puma ID UPCO2 UPCO3 UPCO7 UPCO7 UPCO7 UPCO8 UPCO4 UPCO5 UPCO6 UPCO6 UPCO23 UPCO25 UPCO28 UPCO29 UPCO31 UPCO23 UPCO27 UPCO30 UPCO50 UPCO51 UPCO52 UPCO54 UPCO55 UPCO24 UPCO69 UPCO70 UPCO71 UPCO72 UPCO73 UPCO74 UPCO75 a Sex F F F F F F M M M M F F F M M F M F F M F F M F M F M F F F F Capture Date 1/8/2008 1/21/2005 2/24/2005 3/30/2006 3/3/2007 3/21/2005 1/28/2005 2/4/2005 2/18/2005 4/12/2008 2/25/2008 2/8/2006 3/23/2006 4/14/2006 4/19/2006 1/4/2006 3/10/2006 4/15/2006 12/14/2006 1/7/2007 1/10/2007 1/12/2007 1/21/2007 1/17/2006 1/11/2008 1/20/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 3/26/2008 GPS NAD27 U.T.M.: Zone, E, N 13S, 245722, 4244166 13S, 241606, 4251510 13S, 246328, 4244230 13S, 245901, 4247627 13S, 247645, 4246097 12S, 727808, 4239029 13S, 257565, 4239606 13S, 240577, 4251037 13S, 247399, 4254006 13S, 257516, 4239696 12S, 723304, 4242231 13S, 258374, 4230480 12S, 722868, 4240115 12S, 723458, 4242340 12S, 746919, 4225441 12S, 730188, 4234861 12S, 722339, 4245212 13S, 248551, 4242095 12S, 753639, 4260149 13S, 238783, 4252390 13S, 258058, 4236260 13S, 252688, 4228050 13S, 258133, 4228691 12S, 737151, 4233273 13S, 248191, 4246810 13S, 247122, 4245760 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 12S, 732894, 4239423 PLV + + + Ih I + + P P + + + + + + I + + + + + P P P P P a FCV +h + Ph P P P P P P P P P P P P P P P P + + P P P P P b PLV is Puma Lentivirus. FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result). b 153 FHV + P P + P P P P P P P P P P P P P P P + + P P P P P c FPV + P P + P P P P P P P P P P P P P P P + + P P P P P d T.g. e IgM + P P P P P P P P P P P P P P P P P P P P P P T.g.e IgG + + P P + + + + P P P P P P P P P P P P P P P + + P P P P P B.h. Y.p. P P + P P P P P P P P P P P P P P P P P P P P + ++ +++ P P ++ I I I + + P P P P P P P P P P P P P + + + f g �Colorado Division of Wildlife July 2008 –July 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 31, 2008−July 31, 2009 Author: K. A. Logan. Personnel: K. Logan, B. Dunne, D. Ranglack, J. Timmer, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young and W. Wilson of U.S.D.A. Wildlife Services; houndmen R. Navarette and J. Knight; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT This report provides information in the fifth year of the reference period August 2008 through July 2009 on puma population characteristics and dynamics on the Uncompahgre Plateau. Field operations were impacted by a state government issued hiring freeze that did not allow full staffing of 2 puma capture teams during winter 2008-09. All capture efforts involving use of trained dogs, cage traps, and inspections at nurseries in 2008-09 resulted in a total of 37 puma captures (7 adult females [1 adult female captured 3 times, another captured twice], 4 adult males [1 adult male captured 3 times], 1 subadult female, and 18 cubs [2 of them captured twice each]). Five adults (4 females, 1 male) and 14 cubs were captured and marked for the first time. As of July 2009, there were 17 adults (11 females, 6 males), 1 subadult female, and 5 cubs (2 females, 3 males) with active radio-collars. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from December 9, 2008 to April 30, 2009. Those efforts resulted in 71 search days, 198-202 puma tracks detected, 75-78 pursuits, and 24 puma captures. In 2008-09, capture efforts with ungulate carcasses and cage traps resulted in captures of 2 adult females and 1 subadult female. Capture and search efforts from November 2008 through March 2009 enabled us to estimate a minimum of 37 independent pumas detected on the Uncompahgre Plateau study area during that time, including 26 females and 11 males. Preliminary puma population parameters estimated during the past 4.7 years of research, included: population sex and age structure, reproduction rates, and survival rates. Data on puma reproduction rates included: average litter size = 2.77 ± 0.9081 SD, n = 26; average birth interval (mo.) = 18.462 ± 4.6035 SD, n = 16; average proportion of adult females producing cubs each year = 0.598 ± 0.1094 SD, n = 11-13 females per yr. for 4 years; secondary sex ratio = 41:31, consistent with 1:1; and average gestation length (day) = 90.5-92.3(SD = 2.5495, 125 �2.1628, respectively). Puma births occurred March through September, with 24 of 27 occurring May through September. Majority of breeding activity was February through June. Preliminary estimates of survival rates for both adult and subadult pumas in this reference period were high, and may reflect the absence of puma sport-hunting as a mortality factor. An increasing age structure of independent pumas in the reference period reflects the high survival rates. Cub survival was about 0.53 (SE = 0.1623-0.1629; Kaplan-Meier procedure) and 0.58 (± 0.1610 95% CI; binomial model). The main cause of mortality in the adults and cubs was aggression by other pumas. Dispersal from the Uncompahgre Plateau study area was documented for 8 pumas (7 male, 1 female) that dispersed during the subadult stage and moved distances ranging from about 61 to 330 linear km. We monitored 7 puma families with a radio-collared mother and at least one radio-collared cub to assess association distances during aerial locations from November 6, 2008 to March 20, 2009. The aggregate data gathered during the past 4 winters generally indicate that mothers were usually within 660 m of their cubs during the day. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (4.7 years duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Data on puma population characteristics and dynamics gathered during the reference period was used for a preliminary assessment of population-based assumptions used by CDOW to guide puma hunting management and indicated that assumptions pertaining to puma population sex and age structure, density, and expected results from modeled harvest rates are biologically supported. The CDOW structured the puma hunting season for the treatment period. The first hunting season will begin midNovember 2009 and extend to January 31, 2010 unless the quota is filled earlier. The management objective will be to achieve a stable to increasing puma population. Population model simulations indicated a harvest quota of 8 independent pumas to achieve the objective. No limit of hunters on the study area is imposed, but each hunter is required to obtain a hunting permit for the study area. In addition, an effort will be made to survey each hunter obtaining a valid permit. All pumas harvested in and around the study area will be inspected by CDOW personnel. A study plan for the treatment period was submitted for internal review in the CDOW. The plan was substantially modified and received another internal review. That version will be modified and submitted to the Mammals Research leader in fall 2009. Continuing this research includes manipulating the puma population with sport-hunting in the treatment period while also estimating puma population characteristics and vital rates. We are continuing to collaborate with colleagues in Mammals Research and at Colorado State University to assess puma population dynamics and social structure, puma-human interactions, health, habitat use, and we will incorporate a pilot project to examine individual puma detection rates using a camera grid design. 126 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; and plan for the remaining 5 years of the Uncompahgre Plateau Puma Project― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. 6. 7. 8. 9. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data on agent-specific mortality. Gather data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. Use data on population dynamics for a preliminary evaluation of assumptions used by CDOW biologists and managers in the Data Analysis Unit puma management planning process. Work with CDOW biologists and managers to structure the puma hunting manipulation for the first year of the 5 year treatment phase. Develop a study plan for remaining 5 years of puma population research on the Uncompahgre Plateau Study Area. Collaborate with other researchers and evaluate other data sources that could be relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs 127 �identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. 128 �The treatment period will involve the use of controlled recreational hunting to manipulate the puma population. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the minimum puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-firstbreeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CDOW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). 129 �H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a decline of the harvest-age segment of the population by the beginning of the next hunting season. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. 130 �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates will be quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for the past 100 years. Hence, the reference period, years 1―5, would provide conditions where individual pumas in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and eartagged pumas that ranged in a buffer zone, that includes the northern halves of GMUs 61 and 62, were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CDOW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared pumas. For managers, demonstrating that they can manage puma populations with hunting and achieve the CDOW strategic objective of managing for a healthy, selfsustainable puma population state-wide is important to their mandated responsibility. Dynamics of the 131 �puma population will be manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a majority of independent pumas in the population should be marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was have a minimum of 6 puma in each of 6 categories (36 total) radiotagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Assuming that the puma population density on the study area was relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio was equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might have been 22 adults, 11 males and 11 females. Also assuming that the total population contained 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might have been 4 subadults and 13 cubs with equal sex ratios in a total population of 39 pumas. If we achieved our logistical aim, then we should be able to quantify population characteristics and vital rates of the puma population based on a sample that includes a majority of individuals in the population. Recognizing that the population may grow, we will build upon the tagged number in each subsequent year to maintain a high proportion of marked individuals in the population. Puma capture and handling procedures were approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) and when available fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, 132 �snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allowed researchers to be at the cage to handle captured pumas within 30 minutes. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating vital rates and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were eartagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas would provide precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPS-collars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). 133 �Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars are not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when puma was immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allow) from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). Aerial locations also provided simultaneous location data on mothers and cubs. GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, ~50g, or Telonics, Inc., Mesa, Arizona MOD 210, ~100g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg could wear these small expandable collars until they are over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the cub age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum 134 �number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed using SYSTAT, R, and MARK software. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2008 to July 2009. Our plan was to use 2 fully-staffed puma capture teams with dogs November through April, with each team operating on half the study area, with the intent of substantially boosting puma capture and sampling efforts. But, field operations were impacted by a state government mandated hiring freeze. We were limited to the principal investigator and 2 houndmen teams from October 2008 through April 2009. The principal investigator operated with the 2 houndmen teams for a single expanded moving search footprint and performed all immobilization and sampling procedures during winter and spring capture efforts. Our searches to detect puma presence covered the entire study area. By May 2009 technicians could be hired again and assisted in puma captures in cage traps and at nurseries. In addition, the Colorado State University bobcat research team facilitated the recapture of an adult female puma. We made 37 puma captures during the period (7 adult females [1 adult female captured 3 times, another captured twice], 4 adult males [1 adult male captured 3 times], 1 subadult female, and 18 cubs [2 of them captured twice each]). Five adults (4 females, 1 male) and 14 cubs were captured and marked for the first time in 2008-2009. One adult female and 2 cubs were visually observed at capture efforts, but could not be handled. A total of 39 pumas were monitored with radiotelemetry from August 2008 to July 2009 (some of these had been collared during previous years). Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from December 9, 2008 to April 30, 2009. Those efforts resulted in 71 search days, 198-202 puma tracks detected, 75-78 pursuits, and 24 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was slightly less than our efforts in the 4 previous winters (Table 2). But, the frequency of tracks encountered was about the same as the previous winter. The pursuits increased over the 4 previous periods, as did our capture rate. The later 2 statistics were probably the result of using 2 houndmen teams. Four adult and 7 cubs were captured for the first time by using dogs (Tables 1 and 3). 135 �This included 2 non-marked cubs that could not be handled for safety reasons. Three adult male pumas and 1 large male cub were captured with dogs but could not be handled for safety reasons, and 1 adult female and her cub were visually observed but could not be caught for marking and sampling (Table 4). Two adult females (1 recaptured twice) and an adult male were recaptured and observed, but there was no need to handle them (Table 5). Puma capture efforts using ungulate carcasses and cage traps extended from August 20, 2008 to July 20, 2009. We used 36 road-killed mule deer at 17 different sites to capture one adult female and one subadult female (Tables 6). In addition, the Colorado State University bobcat research team recaptured an adult female in a trap set for bobcats, thus, providing an opportunity to change a failing GPS collar. Pumas scavenged 7 of 36 (19.4%) of the ungulate carcasses used for bait. Percentages of puma scavenging ungulate carcasses in the previous 3 years were 20%, 22.5%, and 18.3%. Other carnivores that used the ungulate baits included: black bear, bobcat, gray fox, and domestic dogs. We captured 14 cubs (8 male:6 female) for the first time (Table 7), and fit 11 of them with radiocollars (Appendix A). Three cubs were not radio-collared. In 1 case the mother returned to the nursery while we were sampling the cubs so we quickly returned the cubs to the nursery, leaving 1 collared and 1 not collared. In the other case, 2 cubs in a litter of 3 were too small to wear the collar design. Three of the cubs were bayed by our dogs and were large enough to require anesthetics for safe handling. The other 11 cubs were handled without anesthetics at their nurseries when they were 34 to 38 days old. Litters bearing these cubs were produced in August (2), September (1), April (1), and May (3). In addition to our direct puma captures with dogs December through April, we detected 10 independent pumas that we were able to identify with GPS or VHF telemetry 12 times, thus, negating the need to capture those pumas directly with dogs (Table 1). Upon detecting puma tracks that were aged at 1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made, then we ruled the data were confirmatory. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with nonfunctioning GPS- or radiocollars. Our search efforts throughout the study area also revealed the presence of at least 14 other independent pumas, we classified as 12 females and 2 males. We could separate the activity of these pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females and males. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to separate 5 adult females followed by 1 to 3 medium-to-large-size cubs. One of the adult females was visually observed with 2 of her 3 cubs, 2 of which we captured and marked. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). It is also possible that 2 of the adult females were previously marked animals wearing non-functional GPS collars (Table 8). Our search and capture efforts during November 2008 through April 2009 enabled us to estimate a minimum count of 37 independent pumas detected on the Uncompahgre Plateau study area, up from a minimum count of 33 independent pumas during the November 2007 to March 2008 (Table 8). This estimate was based on the number of known radio-collared pumas, the observation of one non-collared female puma, and detection of tracks of suspected non-collared pumas or pumas with non-functional GPS collars on the study area (explained previously). In addition to the independent pumas, we also counted a minimum of 21 cubs. Of the 37 independent pumas, 23 to 25 (62-68%) were marked and 12 to 14 (32- 136 �38%) were assumed to be unmarked animals. Of the expected unmarked pumas, 12 were females and 2 were males, which might reflect lower detection rates of females, making it more difficult for us to capture and mark females. Although, we would have expected to capture, sample, and mark a larger portion of those animals had we fielded the 2 complete capture teams in winter 2008 to 2009 as previously planned. There may be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 16 independent pumas (11 females, 5 males). The east slope count includes 21 independent pumas (15 females, 6 males). We used the minimum puma counts in the past 2 periods, (i.e., 33 independent pumas for November 2007 to March 2008 and 37 independent pumas for November 2008 to April 2009) to calculate preliminary minimum densities for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area. The minimum densities ranged from 2.0 to 2.2 independent pumas/100 km2. Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study to investigate an “unexploited” puma population (Anderson et al. 1992:5). As our current effort results in larger samples and progresses in time through the reference and treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 4.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete because we are still in the intensive data-gathering phase, yet, our data allows some preliminary comparisons with Anderson’s (1992) completed work. In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). Anderson et al. (1992) focused on capturing pumas >27 kg in body mass while avoiding pumas <27 kg in mass. They captured 47 pumas with dogs for an average capture rate of 13.9 days per puma. Eight other pumas, all female cubs ≤7 months old, were caught in steel leg-hold traps by trappers in pursuit of furbearers, and were added to the study animal population. Two other cubs were killed by the dogs. In total, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. Anderson et al. (1992:49) estimated a minimum density of “resident” pumas (equivalent to our independent pumas) at 1.1 pumas/100 km2. This was practically half the density of our current preliminary minimum density estimates for independent pumas (see previously). So far, in our 5 winters, the average effort per winter to capture pumas with dogs is 77.2 days (range = 71 to 82). Of 247 pursuits, 94 (38%) were successful. We captured 41 individual pumas their first time with dogs (i.e., does not include dog-aided recaptures), yielding an average capture rate of 9.4 days per capture (i.e., 386 days/41 captures). Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or capture cubs at nurseries like we are. In our current effort, we captured, sampled, and marked 109 pumas. Of those animals, 91 were radiocollared, allowing us to monitor fates of pumas in all sexes and age stages, including: 19 adult females, 12 adult males, 4 subadult females, 5 subadult males, 30 female cubs, 30 male cubs (some individuals occur in more than one age-stage). To date, this represents the largest number of individual pumas sampled for population data in Colorado. Mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old and weighed for the first time averaged 61.3 kg for 10 males (SD = 3.72, range 55 to 68 kg) and 38.3 kg for 18 females (SD = 137 �4.01, range = 31 to 45). Sexual dimorphism is evident in pumas, and has been described for the species throughout its range (Young and Goldman 1946). Sexual dimorphism in the puma has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 During the past 4.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. We examined 72 cubs from 26 litters aged 26 to 42 days old where we were reasonably sure that we counted all the cubs at the nurseries (Table 9, Appendix A). Using those litters and 1 other litter confirmed by nursling cub tracks with a GPS-collared female (i.e., n = 27 litters with approximately known birth dates), the distribution of puma births by month indicate puma births extending from March into September, with 24 of 27 births occurring May through September (Fig. 4). Our data suggests that the majority of puma breeding activity occurs February through June. The secondary male:female sex ratio was 41:31 for 26 litters where all the cubs were sexed. This ratio was not significantly different from 1:1, (X2 = 1.389 < 3.841, α = 0.05, 1 d.f.). An equal sex ratio at birth is characteristic of other puma populations in North America (Robinette et al. 1961, Logan and Sweanor 2001:69-70). The mean (±SD) and extreme sizes of the 26 litters examined at nurseries were 2.77 (±0.9081), 1 to 4 (Table 9). In addition, 16 birth intervals for 9 different female pumas averaged 18.462 months (SD = 4.6035), and ranged from 11.7 to 23.9 months (Table 9). During the past 4 biological years (i.e., 2005-06 to 2008-09) when we radio-monitored 12, 13, 12, and 11 adult female pumas per year, respectively, the proportion of adult females that produced cubs each year were 0.67, 0.69, 0.58, 0.45 with a mean ± SD of 0.598 ± 0.1094. Based on observations (from GPS and radio-telemetry data) of associations between 9 mothers and putative sires (Table 9), 10 estimated gestation periods, considering a range of days for 7 observations, averaged 90.5 to 92.3 days (SD = 2.5495, 2.1628, respectively), which is consistent with average puma gestation reported in the technical literature on puma (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al.1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 27 litters adds to Anderson’s data (Fig. 4), and indicates puma births in Colorado occurring in every month except January and November (so far). Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (Table 9). Segment Objectives 3 & 4 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2009, we radio-monitored 12 adult male and 19 adult female pumas to quantify survival and agent-specific mortality rates (Table 10). One adult male is known to have died of natural causes. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. One adult male, M5, lived in the buffer zone north of the study area where all marked pumas were protected from sport-hunting. However, M5 was killed at 54 months old by a puma hunter when M5 left the buffer zone and ranged into eastern Utah. We lost contact with 3 adult males apparently due to GPS/VHF collar failure: M1, M27, and M29. Direct observations in the field indicated that M27 was alive on 05-07-09 (camera photo), and M29 was alive on 02-25-09 (recapture). Four adult females are known to have died of natural causes. F50 was about 29 to 31 months old when she died apparently of natural causes (exact agent could not be identified). Three adult females, F54, F30, and F2 were killed by other pumas. F54 was killed at about 49 months old by a male puma on the southern boundary of the 138 �study area while apparently in direct competition for a fawn mule deer. F30 was killed by a puma of unknown sex and for unknown circumstances when she was about 60 months old. F2 was killed when she was about 92 months old by a puma of unknown sex (but thought to be a male based on presence of 8 scrapes), as was at least one of her four 87-day-old cubs M79 (Appendix A). All 3 adult females appeared to have fatal bites to the head, with canine punctures that penetrated the skull. One adult female, F7, was killed for depredation control purposes when she was about 107 months old. Preliminary estimates of adult puma survival rates indicate relatively high survival in this reference period (i.e., with no sport-hunting) (Table 11). Survival rates were estimated using the KaplanMeier procedure to staggered entry of animals (Pollock et al. 1989) for the past 4 annual and hunting season periods when samples were ≥ 5 animals in each sex category. The survival rates reflect 1 male death and 4 adult female deaths from natural causes. Data on M5 (killed by a hunter) and F7 (killed for depredation control) were right censored after the date they died. In general, adult male puma survival is higher than adult female survival in this non-hunted population state. The adult age structure, as indicated in Figure 4, is indicative of high survival rates during the past 5 winters without sport-hunting mortality. Research in New Mexico on a non-hunted puma population also indicated high adult survival rates with survival rates of adult males higher than adult females and the major cause of death being aggression by male pumas (n = 8 years; Logan and Sweanor 2001:127-138). We have radio-monitored 9 pumas, 5 males and 4 females, in the subadult age-stage (independent pumas <24 months old) (Table 12). One of those, F66, died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Data from puma hunters provided additional information on fates of 8 pumas, 7 males and 1 female, initially captured and marked as cubs (5 males) or subadults (2 males, 1 female) on the Uncompahgre Plateau puma study area (Table 13). All 7 of the males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 66 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). The female (F52) was treed and released by hunters. These pumas represent dispersal moves from the Uncompahgre Plateau. All of the pumas, except for 1 (M68, 17 months old) had reached adult ages ranging from 24 to 54 months old. Our current research effort is still too short in duration and samples too small to make meaningful comparisons with evidence in the literature regarding puma offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations in different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to understand the significance of those parameters in our study population. A preliminary estimate of puma cub survival was made with 36 radio-collared cubs (16 males, 20 females) that we marked at nurseries when they were 26 to 42 days old. Only cubs that died of natural causes were used (i.e., 3 capture-related deaths were excluded). All cubs were born from May 2005 to July 2007. For the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989), the maximum survival period was assumed to be 365 days after capture (i.e., ~13-14 months old) to coincide with the age that puma cubs would normally be expected to become independent from their mothers (Logan and Sweanor 2001). In this preliminary estimate, observations of siblings are assumed to be 139 �independent (i.e., distribution of mortalities among litters is random), but that assumption might not be reliable (Bishop et al. 2008; an overdispersion parameter will need to be estimated). We omitted 3 radiocollared cubs that died as a result of the expandable radiocollars (Appendix A). Otherwise, cubs were right censored when they reached independence, or from the date after we lost contact. Dates that bracketed the deaths of cubs were used to estimate minimum and maximum survival rates. The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629). Cub survival estimated with a binomial model (Williams et al. 2001) for the same sample was 0.5833 ± 0.1610 (95% C.I.). In order to improve the reliability of puma cub survival data, we will make an effort to increase the number of radiocollared cubs that are monitored. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. We attributed 8 cub mortalities to infanticide, and it is probable that 5 other cubs died directly from infanticide or because their mother was killed when her 4 cubs were at an age (87 days) when they could not survive without her (Appendix A). Male-caused infanticide, along with aggression-caused mortality in adult (indicated previously) and subadult pumas (Logan and Sweanor 2001) has also been a dominant mortality factor in other puma populations in North America (Logan and Sweanor 2001:115-136). Such male puma behavior has been theorized for being a strong selective force in shaping the evolution of behavioral tactics, social structure, and life history strategies in pumas (Logan and Sweanor 2001). The closure on sport-hunting on the study area and protection of marked pumas from sportharvest on the buffer area on the northern portion of the Uncompahgre Plateau for the reference period operated as designed to remove sport-hunting as a cause of death in the study population. Of the adult and subadult pumas wearing a functional GPS/VHF-collar, only 1 adult puma died due to human causes on the study or buffer areas (F7 killed for depredation control, mentioned previously). This reference condition enabled us to quantify puma population structure, survival rates, and agent-specific mortality rates of pumas in the absence of direct human-caused mortality by sport-hunting, and will allow comparisons with the treatment period when puma hunting manipulates the puma population on the study area. Furthermore, we recorded deaths of 7 non-marked pumas that died since 2004, mainly from human causes (Table 14). Six non-marked pumas (2 males, 4 females) were struck by vehicles on highways or a county road along boundaries of the study area. In addition, 2 marked female cubs (mentioned previously) were killed in vehicle collisions on a highway. Both of those cubs were offspring of F16 which has a home range straddling highway 550 south of Montrose. Of the 8 pumas killed by vehicles, 5 were dependent cubs, 2 were probably subadults, and 1 was an adult female. A bizarre natural mortality case we documented was of a non-marked adult female found in Roubideau Canyon that was lodged in a narrow fork of an aspen tree and probably died of asphyxia due to compression of the thorax. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 pumas <24 months old, and 10 ≥ 24 months old) from a total of 49 in his previous study which was intended to “assess the effects of sport-hunting on an unexploited population” (Anderson et al. 1992:5). They found 19 of the 21 deaths (i.e., 90%) were due to human causes, attributed to: legal kill outside the study area (7), research capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agent-specific mortality rates from our current effort cannot be clearly compared with the Anderson et al. (1992:53) effort because they pooled data for male and female pumas in seemingly arbitrary age stages that overlapped puma life history stages (i.e., cubs, subadults, adults). The Anderson et al. (1992:53) estimated survival rates with the Kaplan-Meier procedure (Pollock et al. 1989) for 20 male and 22 female pumas were: 12-24 month old = 0.642; 24-36 months old = 0.692, 36 to 48 months old = 0.917, and 48- 140 �60 months old = 0.800. Actual sample sizes within each age category were not given. There were no quantitative data allowing estimation of survival and agent-specific mortality for cubs less than 12 months old. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Segment Objective 5 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that are ≤6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). We monitored 7 puma families with a radio-collared mother and at least 1 radio-collared cub from November 6, 2008 to March 20, 2009 during 11 airplane flights (Table 15). To assess whether mothers were apart or in close association with cubs, we considered error in aerial locations. We recovered 28 puma radiocollars (i.e., of dead pumas or shed collars from cubs) that we located from the airplane and then fixed the actual locations of collars on the ground with hand-held GPS receivers. Range of location error was 5 to 660 m (mean = 260, SD = 179.73). We used distances greater than the extreme high range of location error (660 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. In aggregate, the data for the past 4 winters include 171 observations for 1−7 families per winter (Table 15), and generally indicate that puma mothers are more likely (87% of observations) to be within 660 m of their cubs during the day in winter. An effort will be made to increase the number of radio-collared family members in subsequent winters. If the total sample size allows, we want to examine variation in mother-cub association distances on an individual female basis. Moreover, we will gather direct information on the frequency that cubs are orphaned and their survival during the treatment period when the pumas are hunted. Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 6 We used the data gathered so far in the reference period for a preliminary evaluation of 5 assumptions used by CDOW biologists and managers to manage puma populations with sport-hunting. Assumption 1: The CDOW assumes density ranges of 2.0 to 4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Assuming that on average 66% of the population is comprised of adults and subadults (previously), then the range of density for independent pumas would be 1.3 to 3.0/100 km2. The population sex and age structure is also assumed to be similar to puma populations described in the intensive studies in the literature on puma populations (CDOW 2007). 141 �H1: Puma densities during the reference period and the treatment period will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations studied intensively in Wyoming, Idaho, Alberta, and New Mexico (CDOW 2007). We have partially addressed H1 with a preliminary minimum estimated density of 2.0 to 2.2 independent pumas/100 km2 of estimated winter habitat on the Uncompahgre Plateau study area in RY4 (i.e., 33 minimum independent pumas/1,671 km2) and RY5 (i.e., 37 minimum independent pumas/1,671 km2). These minimum density estimates represent the mid-to-high range of density for independent resident pumas in some North American populations (i.e., range 0.3-2.2/100 km2, Logan and Sweanor 2001:167), but lower than higher estimates for independent pumas in more recent studies in Wyoming (3.4/100 km2, Anderson and Lindzey 2005) and Utah (3.2/100 km2, Choate et al. 2006). Moreover, the sex and age structure of the minimum population observed in winter of reference year 4 (i.e., RY4) is similar to descriptions of other puma populations in western states (Logan and Sweanor 2001:167). Assumption 2: The adult plus subadult (i.e., harvest-age pumas) segment of the population exhibit a moderate annual rate of growth of 15% (i.e., λ = 1.15, CDOW 2007). H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. Puma population modeling using population characteristics and vital rates from this current research effort supports this assumption (Appendix B). Expected lambda (i.e., finite rate of population change of independent pumas) ranges from 1.17 to 1.22 and an average of 1.20 ± 0.0182 SD (n = 5; TY1-TY5) for the no harvest model (Appendix B, Table B.7). Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau are consistent with the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4 yr.; r = 0.28, n = 4 yr.; r = 0.17, n = 4 yr.; r = 0.11, n = 7 yr.; Logan and Sweanor 2001:169-175). Puma population growth might be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater vulnerable prey biomass), and if puma sources are nearby to the study area which provide immigrants. Assumption 3: Puma harvest rate formulations for DAUs assume that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). Harvest is assumed to be additive to natural mortality. H3a: The puma population is not expected to decline, therefore, we should be observing puma population parameters characteristic of a stable or increasing hunted puma population. Preliminary modeling results with 15% and 16% mortality in the harvest-age population indicates expected stable or increase population phases, with additive harvest mortality (Appendix B, Tables B.3, B.4, B.5, B.8, B.9, Fig. B.2). H3b: Harvest mortality of 15% of the adults and subadults will be strongly additive to other natural causes of mortality. Preliminary survival rates for annual and shorter-term hunting season periods for adult-age pumas in the reference period indicate high survival (Table 11). Similarly, a course survival rate for 9 subadult radiocollared pumas in the reference period is also high (finite rate of survival during the subadult stage: 8/9 = 0.89). These rates partially support the assumption that additive mortality caused by hunting can be expected. A direct test of this assumption will develop in the treatment period. Assumption 4: To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality 142 �guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). Preliminary modeling results with 16% mortality or greater in the harvest-age population and with greater than 45% of the harvest comprised of females indicates expected puma population declines (Appendix B, Tables B.6, B.10, B.12−B.16, Figs. B.2−B.4). Assumption 5: The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Preliminary results as indicated by the age structure of independent pumas captured for the first time in 2004-05 (Logan 2005), at first capture (Fig. 3), and the age structure of the independent puma population in March 2009 (Fig. 5), and apparently high adult and subadult survival rates during the reference period support the hypothesis for a young age structure early in the reference period with an aging structure later at the end of the period. Segment Objective 7 Principal investigator K. Logan with CDOW biologists and managers developed by consensus a preliminary structure (i.e., official approval pending Wildlife Commission decision in September 2009) to manipulate the puma population with sport-hunting on the study area during the treatment period. The hunting season will begin in mid-November and extend to January 31, unless the last puma on the design quota is killed before January 31, which will effectively close the season on the study area. The harvest quota will be 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. The quota of 8 is based on the projected minimum number of independent pumas expected on the study area in winter 2009-10, modeled from a minimum count during winter 2007-08 (see Appendix B, Table B.7). No assumptions about additional pumas on the study area are made or contrived. The quota of 8 is expected to allow the population to achieve a stable or increase phase even if the quota is exceeded due to potential ideal snow-tracking conditions that could result in multiple pumas being killed within a mandatory 48-hour reporting period. Such an overharvest might be expected to reach 20 to 30% over the design harvest (in this case ~2 pumas killed over the harvest; J. Apker, Carnivore Biologist, CDOW, person. comm. June 8, 2009). The number of hunters on the study area at any particular time each hunting season will not be limited. However, each hunter on the study area will be required to obtain a hunting permit from the CDOW Montrose Service Center. Permits will be free and unlimited. Each permit will allow the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wish to continue hunting past the permit expiration date can request a new permit for another 14 days or until the hunting season on the study area closes due to the quota being reached or the end of the hunting season. (The number of pumas killed on the study area each winter will be regulated by the design quota, discussed previously.) This permit system is expected to allow the CDOW to monitor the number of hunters on the study area and to contact each hunter for survey information. All pumas harvested on the study area will be subject to the examination check and seal mandated by the State of Colorado. Hunters must report their puma kill to CDOW within 48 hours of harvest and 143 �present the puma carcass for inspection within 5 days of harvest. At the time of carcass check-in a biologist with the puma research team will inspect the puma to assist in recording information on the CDOW puma harvest data form and to collect an upper premolar tooth for aging (i.e., mandatory) and a tissue sample using a 6 mm biopsy punch (i.e., voluntary) for DNA genotyping. Each successful hunter will also be asked at that time to complete a one-page hunter survey form. All other hunters that do not report a puma kill on the study area will be contacted and asked to complete the survey. Hunter harvest will provide direct evidence of removal rates of marked puma for survival and agent-specific mortality data, and to help evaluate the relative vulnerability of pumas to harvest and potential for hunter selectivity. Hunter harvest will also reveal availability and sex and age classes of unmarked pumas on the study area. After the design quota is filled or January 31 (whichever comes first), puma research teams will immediately activate for capture operations with trained dogs. Two fully-staffed capture teams, one detailed on the east slope and one detailed on the west slope, will systematically and thoroughly search the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring when snow-tracking conditions can facilitate those efforts. These efforts are necessary to maintain samples to quantify population sex and age structure and estimate minimum population size and other population parameters. Segment Objective 8 Principal investigator K. Logan developed another draft study plan pertaining to the next 5 years of puma research on the Uncompahgre Plateau. The draft plan was subjected to an internal review by researchers and was circulated for review to Carnivore Biologist J. Apker, Area 18 Biologist B. Banulis, Southwest Regional Biologist S. Wait, and Area 18 Wildlife Manager R. Del Piccolo. Comments were incorporated into a substantially modified study plan which was reviewed by Mammals Researcher Dr. Chad Bishop (now the Mammals Research Leader). That study plan will be modified to address new considerations and will be submitted to Mammals Research Leader Chad Bishop in fall 2009. Segment Objective 9 Data from 26 (8 male, 18 female) GPS-collared pumas, totaling over 39 thousand GPS locations (Table 16) will be used to examine the social structure of the puma population on the Uncompahgre Plateau and to examine movements of pumas relative to Game and Data Analysis Unit boundaries. Those data will also be used in a set of collaborative projects, including: examination of puma behavior in relation to human development with Mammals Researcher Dr. Mat Alldredge, who is studying pumahuman interactions on the Colorado Front Range; modeling and mapping puma habitat in Colorado and other western states with Dr. Kevin Crooks and Dr. Chris Burdett (Department of Fish, Wildlife and Conservation Biology, Colorado State University- DFWCB, CSU); evaluation of puma detection rates using camera grids with Dr. Kevin Crooks and Ph.D. candidate Jesse Lewis (DFWCB, CSU). Furthermore, puma population and genetic data from the Uncompahgre Plateau can be used in collaboration with Dr. Alldredge’s puma research efforts on the Front Range to examine similarities or differences in puma population dynamics and social structure between the 2 environments. We are currently collaborating with Dr. Sue VandeWoude and Dr. Kevin Crooks, and postdoctoral and graduate students at the College of Veterinary Medicine and Biomedical Sciences, Department of Microbiology, Pathology, and Immunology, Colorado State University in a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to the DMIP for analyses. That project has been expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of that project and incomplete results on infectious disease surveillance on 35 individual pumas (22 independent 144 �females, 12 independent males, and 1 male cub) sampled on the Uncompahgre Plateau are presented in Appendix C. Those data contributed to a publication in Emerging Infectious Diseases (accepted), titled Plague and wild felids: zoonotic disease in the western US , a paper on seroprevalence in populations of pumas and bobcats in the western United States by collaborators: Sarah N. Bevins1, Jeff A. Tracey1, Sam P. Franklin1, Virginia L. Schmit1, Martha L. MacMillan1, Kenneth L. Gage2, Martin E. Schriefer2, Kenneth A. Logan3, Linda L. Sweanor1, Mat W. Alldredge3, Karoline Krumm1, Walter M. Boyce4, Winston Vickers4, Seth P.D. Riley5, Lisa M. Lyren6, Erin E. Boydston6, Melody E. Roelke7, Robert Fischer6, Kevin R. Crooks1, and Sue VandeWoude1 (1Colorado State University, USA; 2DVBID Centers for Disease Control, USA; 3Colorado Division of Wildlife, USA; 4University of California, Davis, USA; 5 National Park Service, USA; 6United States Geological Survey, USA; 7 National Cancer Institute, USA). SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 4.7 years of effort in a reference period, 109 pumas have been captured, sampled, marked, and released. Of those animals, 91 were radio-collared, allowing us to monitor fates of pumas in all sexes and age stages, including: 19 adult females, 12 adult males, 4 subadult females, 5 subadult males, 30 female cubs, 30 male cubs (some individuals occur in more than one age-stage). Data from the marked animals are used to quantify puma population characteristics and vital rates in a reference situation without sport-hunting off-take as a mortality factor. Our efforts to quantify puma population characteristics and vital rates in a reference condition positioned us to develop a puma population model, and to use the population data and modeling scenarios to conduct a preliminary assessment of CDOW puma management assumptions and to guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CDOW wildlife biologists and managers for assessing puma harvest strategies. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes on life stages and sexes. The treatment period, scheduled to begin winter 2009-10 and to extend the following 5 years, will be a population-wide evaluation of sport-hunting impacts on a puma population. 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Logan, Wildlife Researcher 147 �Table 1. Summary of puma capture efforts with dogs from December 9, 2008 to April 30, 2009, Uncompahgre Plateau, Colorado. Month No. Search Days 11 No. & type of puma tracks founda 16 tracks: 6 male, 6 female, 4 cub No. & type of pumas pursued 10 pursuits: 5 males, 5 females, 4 cubs No. & I.D. or type of pumas captured, observed, or identified December 6 pumas captured 8 times: M71 recaptured (not handled), M55 recaptured twice (not handled to change faulty GPS collar due to dangerous tree & cliffs), F93 captured twice- the first time, then with her 2 large cubs F95 and a male cub that could not be handled in a hole, F94 captured for the first time. In addition, male puma tracks found and attributed to M32 by VHF telemetry (no pursuit with hounds). January 17 38 tracks: 17 male, 17 pursuits: 6 males, 5 pumas captured 6 times: M55 (faulty GPS 10 female, 11 cub 4 females, 7 cubs collar changed), F93 recaptured while cub F95 and unmarked male cub escaped, F16 recaptured (faulty GPS collar changed) while M6 (consort) escaped, F96 captured for first time while 2 cubs escaped, F96 recaptured while 2 cubs escaped, cub M84 recaptured (handled to fit with new expandable cub collar). In addition, M6 and F16 were detected by tracks and identified with VHF telemetry on 2 other occasions. M51 was detected by tracks and identified with VHF telemetry and pursued, but was not caught to change his GPS collar on low battery. F93 and F95 were detected by tracks with non-marked cub and identified with VHF telemetry. February 15 64-65 tracks: 12-17 26 pursuits: 3-4 5 pumas captured: cub F97 captured for the first male, 26-31 female, males, 7-8 females, time while mother F23 & sibling F81 escaped. 24-27 cub 15 cubs Cub M82 recaptured and fit with new VHF collar, while mother F8 escaped and confirmed with VHF telemetry. Cub F98 captured for the first time; one of three cubs of an unmarked adult female puma visually observed with F98 on 217-09. M29 recaptured, but could not be handled in dangerous cliffs to replace faulty GPS collar. M99 captured for first time; sibling of F98. March 15 56 tracks: 24-26 15 pursuits: 4-5 4 pumas captured 5 times: F98 recaptured while male, 21-23 female, 9 males, 3-4 females, mother and 2 sibling cubs escaped, M99 cub 7 cubs captured for first time while mother and siblings F98 and non-marked cub escaped, M99 and nontagged cub visually observed, M100 captured for the first time. April 13 24-27 tracks: 17 0 pumas captured. One male pursued identified 7-10 pursuits: 4 male, 6 female, 1-4 males, 2 females, 1- as M55 with GPS data. Another male pursued cub identified as M100 with GPS data. Two females 4 cubs and their cubs pursued identified as F70 and F96 with 1-4 cubs with VHF telemetry. 71 198-202 tracks: 75-78 pursuits: 24 captures of 17 individuals: 4 independent TOTALS 76-83 male, 22-24 males, pumas (F93, F94, F96, M100) and 4 marked 69-76 female, 21-23 females, (F95, F97, F98, M99) and 2 non-marked cubs 49-55 cub 34-37 cubs were captured for the 1st time. 10 independent pumas were detected by tracks and identified with GPS/VHF telemetry 12 times: M6 (twice), F8, F16 (twice), M32, M51, M55, F70, F93, F96, M100. a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Pumas are not handled for a variety of safety reasons: tree too dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. 148 �Table 2. Summary of puma capture efforts with dogs, December 2004 to April 2009, Uncompahgre Plateau, Colorado. Period Track detection effort 109/78 = 1.40 tracks/day Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day 198/71 to 202/71 = 2.79-2.84 tracks/day Pursuit effort 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2008 to May 2009, Uncompahgre Plateau, Colorado. Puma I.D. F93 F94 F96 M100 Sex F F F M Estimated Age (mo.) 72 41 36 72 Mass (kg) Capture date 12-15-08 12-19-08 01-28-09 03-27-09 32 36 40 64-68 estimated* F104 F 96 40 05-21-09 *M100 could not be weighed by scale due to steepness of terrain. 149 Capture method Dogs Dogs Dogs Dogs Location Coal Bank Canyon Shavano Valley Dolores Canyon San Miguel Canyon Cage Trap Roubideau Canyon �Table 4. Pumas that were captured and observed with aid of dogs, or observed in association with another radio-collared puma, but were not handled at that time for safety or other reasons, December 2008 to March 2009, Uncompahgre Plateau, Colorado. Puma sex Capture date Location Comments M55 Age stage or months 42 12-12-08 Dolores Canyon M55 Male 42 16 12-21-08 12-29-08 Spring Creek Dry Creek Basin Female Unk. adult 02-19-09 San Miguel Canyon Unknown 5 02-19-09 San Miguel Canyon M29 129 02-25-09 Unknown 6 03-11-09 Big Bucktail Canyon San Miguel Canyon M55 bayed in a hole then climbed a tree too dangerous for handling to replace non-functioning GPS collar. M55 bayed on cliffs too dangerous for handling. Non-marked male cub of F93 and sibling of F95 took refuge in narrow hole; unable to handle him. Non-marked adult female puma was visually observed with radio-collared cub F98 and a non-marked cub (either M99 later marked or non-marked sibling below), but could not be caught with dogs. Non-marked cub was visually observed with radio-collared cub F98 and non-marked adult puma, but could not be caught with dogs. M29 bayed in cliffs too dangerous for handling. Non-marked cub- sibling of F98 & M99- visually observed with radio-collared cub M99, but could not be caught with dogs. Table 5. Pumas recaptured with dogs, cage traps, or visually observed, December 2008 to January 2009, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date 12-08-08 Mass (kg) Observed Estimated Age (mo.) 35 Capture Method/ Location Dogs/Shavano Mesa M71 F93 12-29-08 Observed 72 Dogs/Dry Creek Basin F93 01-08-09 Observed 72 Dogs/Shavano Valley F96 01-29-09 Observed 36 Dogs/Dolores Canyon 150 Process M71 wore a functioning vhf collar; no need to handle him. F93 wore a functioning GPS collar; no need to handle her. F93 wore a functioning GPS collar; no need to handle her. F96 wore a functioning GPS collar; no need to handle her. �Table 6. Summary of puma capture efforts with ungulate road-kill baits and cage traps from August 20, 2008 to July 20, 2009, Uncompahgre Plateau, Colorado.a Carnivore activity & capture effort resultsb No puma activity detected. One deer carcass scavenged by coyotes. Deer carcasses scavenged by male puma 9-14-08; likely M55 (trail camera photos). Set cage trap 9-15-08. Puma did not return. Bobcat fed on deer carcass in cage trap. A bobcat, a black bear and domestic dogs scavenged 3 different deer carcasses. October 3 Deer carcass scavenged by bobcat. November 6 Female puma scavenged a deer carcass 11-21 to 22-08. Cage trap set 11-23-08; but, female puma did not return. Male puma scavenged a deer carcass 11-24-08, and cage trap set 11-2408. The male puma returned, walked around the trap, but did not enter. Female puma and bobcat scavenged a carcass 11-24-08. Cage trap set 11-24-08. Bobcat captured and released 1124-08. Subadult female puma F66 recaptured and radio-collared 11-25-08. December 2 No puma activity detected. February 2 A female or small male puma walked ~20 m past a deer carcass but did not feed. Another deer carcass was scavenged by a bobcat. March 4 A male puma walked ~5 m past 2 different deer carcasses but did not feed. Three deer carcasses were scavenged by 2 gray foxes and 2 bobcats. April 1 Male puma M55 scavenged a deer carcass 5-6-09. No need to recapture him. May 4 Female puma fed on a deer carcass 5-8 to 10-09. Set cage trap 5-11-09. Female puma returned but did not enter cage trap. Set 2 cage traps 5-12-09; but female puma did not return. Female puma (possibly same as previous) scavenged deer carcass 5-21-09. Cage trap set 5-21-09. F104 captured. A black bear scavenged one deer carcass. July 2 Puma F72b was recaptured 7-20-09 in cage trap set for bobcat study. Her malfunctioning GPS collar was replaced. A non-marked puma was photographed at one deer bait 7-17-09; but it did not feed. Same deer bait was scavenged by ~5 different black bears. a We used 36 road-killed mule deer at 17 different sites. Of the road-killed ungulate baits, 7 of 36 (19.4%) were scavenged by pumas. b Adult female puma F72 was recaptured in a bobcat cage trap baited with a predator call box and visual attractant. Month August September No. of Sites 2 5 Table 7. Puma cubs sampled September 2008 to June 2009 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M91 M92 F95 F97 F98 M99 M101 M102 F103 M105 F106 M107 F108 M109 M M F F F M M M F M F M F M August 19, 2008 August 19, 2008 August 2007 May 23, 2008 Sep.-Oct. 2008 Sep.-Oct. 2008 April 15, 2009 April 15, 2009 April 15, 2009 May 7, 2009 May 7, 2009 May 25, 2009 May 25, 2009 May 25, 2009 35 35 488 257 122-152 152 35 35 35 38 38 34 34 34 2.5 2.8 33 20 9.5 13.6 2.8 2.5 2.1 2.6 2.6 2.0 1.75 1.75 F25 F25 F93 F23 Fb Fb F16 F16 F16 F75 F75 F94 F94 F94 110 110 56 45 Unk. Unk. 75 75 75 55 55 46 46 46 Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs with mother only with radio-telemetry. b F98 and M99 were captured in association with an non-marked adult female puma and another non-marked cub. 151 �Table 8. Minimum puma population estimate based on numbers of known radio-collared pumas, visual observations of non-marked pumas, and track counts of suspected non-marked pumas on the study area during the past 2 winters, November 2007 to March 2008 and November 2008 to April 2009, Uncompahgre Plateau study area, Colorado. Adults Winter & Region Nov.07-Mar.08 East slope West slope Totals Female Male Subadults Female Male 10 4 3 6 4 2 16 8 5 Total Independent Pumas = 33a,b 4 0 4 Nov.08-Apr.09 East slope West slope Totals Female Cubs Male Unknown sex 4 1 5 4 2 6 7 2-3 9-10 11-13 5-6 2-4 0-1 2 5 5 9-10 4 1-2 1 3 2 4 20-23 9-10 3-6 1-2 5 7 9 Total Independent Pumas = 37c,d a Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be non-marked, but some might have ear-tags, tattoos, or non-functional GPS/VHF collars. b The non-marked independent pumas included: 1adult female with 2 large cubs in Happy Canyon, 1 adult female with 1 large cub in Potter Creek and 25-mile Mesa, 1 adult female with 2 large cubs in Monitor Creek, 1 adult female with 2 medium-size cubs in Potter Creek, 1 adult female with 2-3 cubs in San Miguel Canyon, and 1 female or F28 with a non-functional collar Big Bucktail Creek to San Miguel Canyon. c Of the total, 23−25 (62−68%) independent pumas were marked and 12-14 (32−38%) were assumed to be non-collared, but some might have ear-tags, tattoos, or non-functional GPS/VHF collars. d The non-marked independent pumas included: 1 adult female with 2 cubs on N. McKenzie Mesa, 1 subadult or adult female in Linscott Creek, 1 adult female in Monitor Creek, 1 subadult or adult female in Roubideau Canyon, 1 subadult or adult male in Monitor Creek, 1 adult female with 3 cubs in San Miguel Canyon, 1 adult female with ≥1 cub or F28 with a non-functional GPS collar in Big Bucktail Canyon to N. Fork Cottonwood Creek, 1 adult female or F24 with non-functional GPS collar in Horsefly Creek to Dead Horse Mesa, 1 adult female or F28 with non-functional GPS collar in San Miguel Canyon W of Pinion, 1 adult female with ≥1 cub on Mailbox Park, 1 adult female with 1 cub from McKenzie Creek to Iron Springs Mesa. 1 subadult or adult female on Iron Springs Mesa, 1 subadult female in Big Bucktail Canyon to ridge E of Nucla, 1 subadult male from Pinion across Big Bucktail Canyon and ridge E of Nucla. 152 �Table 9. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2009. Consort pairs and estimated agesa Dates pairs Estimated Estimated Estimated Observed consortedb birth datec birth interval gestation number of Female Age Male Age (mo.) (days) cubsd (mo.) (mo.) F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F2 89 05/19/08 22.0 4 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F3 84 M51 60 03/31/08 07/03/08 21.5 94 3 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F7 106 07/10/08 23.9 3 F8*e 24 06/26/05 2 F8 37 08/13/06 13.4 4 F8 60 M73 49 02/28-29/08 05/29/08 22.5 90-91 2 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F16 75 M6 80 01/13-14/09 04/15/09 22.7 91-92 3 F23* 21 05/30/06 3 F23 45 M27 or 78 02/19-25/08 05/23/08 23.8 87-93 3 M29f 107 F24 75 M29 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F25 110 08/19/08 16.1 2 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F72* 28 07/09/08 1 F75 32 06/01/07 1 F75 55 M73 61 02/11/09 05/07/09 23 93 2 F93 56 08/07 2 F94* 46 05/27/09 3 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. 153 �Table 10. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2009, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 No. days 616 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 333 934 M6 M27 02-18-05 to 07-31-09 03-10-06 to 05-07-09 1,624 1,154 M29 04-14-06 to 02-25-09 1,048 M32 M51 M55 M71 M73 M100 F2 04-26-06 to 07-31-09 01-07-07 to 03-20-09 01-21-07 to 07-31-09 01-29-08 to 07-31-09 02-21-08 to 07-31-09 03-27-09 to 07-31-09 01-07-05 to 08-14-08 1,192 803 922 549 526 126 1,315 F3 F7 01-21-05 to 01-15-09 02-24-05 to 08-03-08 1,455 1,256 F8 F16 F23 F24 F25 F28 F30 03-21-05 to 07-31-09 10-11-05 to 07-31-09 02-05-06 to 07-31-09 01-17-06 to 09-03-08 02-08-06 to 07-31-09 03-23-06 to 09-25-07 04-15-06 to 07-29-08 1,593 1,389 1,272 960 1,269 551 836 F50 12-14-06 to 03-26-07 102 F54 01-12-07 to 08-18-07 218 F70 F72 F75 F93 F94 F96 F104 01-14-08 to 07-31-09 02-12-08 to 07-31-09 03-26-08 to 07-31-09 12-05-08 to 07-31-09 12-19-08 to 07-31-09 01-28-09 to 07-31-09 05-21-09 to 07-31-09 564 535 492 238 224 184 71 Status: Alive/Lost contact/Dead; Cause of death Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Alive. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-2208 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. Alive. Alive. Lost contact− failed GPS/VHF collar. Alive. Alive. Alive. Alive. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. Estimated age at death 92 months. Lost contact− failed GPS/VHF collar. Dead 08-03-08; killed by U.S., W.S. agent for predator control of depredation on domestic sheep. Estimated age at death 107 months. Alive. Alive. Alive. Lost contact− failed GPS/VHF collar. Alive. Lost contact− failed GPS/VHF collar. Dead; killed by another puma (sex of puma unknown) 07-29-08. Estimated age at death 60 months. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. Estimated age at death 30 months. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. Estimated age at death 49 months. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 154 �Table 11. Preliminary estimated survival rates (S) of adult-age pumas during the reference period (i.e., the study area is closed to puma hunting), Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31) and the hunting season period (November 1 through March 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma deaths in this analysis pertained only to pumas that died of natural causes. Pumas that were killed by people, a non-natural cause (i.e., F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. Period of interest Annual 8/1/2005 to 7/31/2006 Annual 8/1/2006 to 7/31/2007 Annual 8/1/2007 to 7/31/2008 Annual 8/1/2008 to 7/31/2009 Hunting season 11/1/2005 to 3/31/2006 Hunting season 11/1/2006 to 3/31/2007 Hunting season 11/1/2007 to 3/31/2008 Hunting season 11/1/2008 to 3/31/2009 S 1.000 Females SE 0.0000 n 10 S 0.667* Males SE 0.2222* n 6* 0.909 0.0867 11 1.000 0.0000 5 0.831 0.0986 14 1.000 0.0000 7 0.875 0.1031 13 1.000 0.0000 8 1.000 0.0000 6 na na 4 0.909 0.0867 11 1.000 0.0000 5 1.000 0.0000 12 1.000 0.0000 9 1.000 0.0000 11 1.000 0.0000 8 Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. 155 �Table 12. Summary of subadult puma survival and mortality, December 2004 to July 2009, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 7 190 M69 01-11-08 to 04-07-08 87 F95 12-29-08 to 07-31-09 214 Status M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. F52 dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adultstage home range. GPS collar nonfunctional. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-0608 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location). She has been ranging adjacent to and overlapping the northern portion of her natal area. 156 �Table 13. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2009. Puma I.D. 1st capture date on study area 1st capture location→kill or resite location (UTM, NAD27) M5 02-04-05 13S,240577Ex 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278Ex 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M43 09-15-06 12S,746919Ex 4225441N→ 13S,500000Ex 4050000N 12S,760177Ex 4242995N→ 12S,739859Ex 4308557N M49 12-05-06 12S,757241Ex 4258259N→ 12S,693350Ex 4274559N 66.1 M68 08-23-07 80.7 M69 01-11-08 13S,257371Ex 4235231N→ 12S,711262Ex 4198681N 13S,248191Ex 4246810N→ 13T,378900Ex 4591990N F52 01-10-07 13S,258058Ex 4236260N→ 13S,319217Ex 4240467N Estimated linear dispersal distance (km)* 102.2 68.6 369.6 61.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill or recapture site. 157 �Table 14. Recorded deaths of non-marked pumas and of marked pumas struck by vehicles, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2009. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870Ex4227520N Highway 62 east of Dallas divide 13S,250000Ex4222500N F F17 F 11 08-18-06 18-24 11-06-06 F 6 01-30-07 F 36 09-16-08 M 12-24 08-13-08 F F61 18 11-13-08 F 12 08-10-09 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown Good Good Vehicle collision Good 158 Highway 550 south of Colona 13S,257602Ex4242185N Highway 550 east of Ridgway State Park 13S,259843Ex4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718Ex4255277N Highway 145 west of Placerville 13S,756490Ex4212336N Highway 550 east of Ridgway State Park 13S,259843Ex4235985N Highway 145 east of Norwood 12S,745739Ex4222548N �Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, each winter, Uncompahgre Plateau, Colorado. Monitoring period Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs ≤660 m apart Nov. 9, 2005 to Nov. 3 4 2−6 9 Mar. 29, 2006 Dec. 4 4 3−7 16 Jan. 5 4 4−8 17 Feb. 4 5 5−9 16 Mar. 2 5 6−10 9 Totals 18 4−5 2−10 67 Nov. 7, 2006 to Nov. 4 4 2−3 11 Mar. 22, 2007 Dec. 4 4 2−5 11 Jan. 5 3 4−6 10 Feb. 4 4 5−7 10 Mar. 3 1 8 2 Totals 20 1−4 2−8 44 Nov. 13, 2007 to Nov. 2 1 6 1 Feb. 14, 2008 Dec. 0 1 7 NA Jan. 3 1 8 2 Feb. 3 1 9 2 Totals 8 1 6-9 5 Nov. 6, 2008 to Nov. 3 5 3-6 10 Mar. 20, 2009 Dec. 1 4 4-7 4 Jan. 2 6 5-17 8 Feb. 2 4 7-9 6 Mar. 3 2 7-10 5 Totals 11 2-6 3-17 33 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,097 m, SD = 313.95, range = 670−1,600. c Mean = 1,606 m, SD = 1,665.39, range = 678−4,101. d Mean = 1,341 m, SD = 542.34, range = 759−1,832. e Mean = 2,608 m, SD = 3,360.56, range = 799-7,641. 159 No. observations with mothers & cubs >660 m apart 2 4 3 2 0 11b 0 0 2 1 1 4c 1 NA 1 1 3d 0 0 3 0 1 4e �Table 16. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2009. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 04-22-09 1,887 adult 03-27-09 to 06-30-09 318 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 05-14-08 3,344 adult 02-24-05 to 08-03-08 3.922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 05-13-09 3,157 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 04-22-09 1,083 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 06-26-09 3,398 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 04-29-09 1,486 F72 F adult 02-12-08 to 06-23-09 1,186 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 04-29-09 235 F104 F adult 05-29-09 to 08-19-09 274 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 160 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Estimation Methods for Monitoring Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Grayshaded shapes identify areas of research addressed by puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 161 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Agt': :(U·nr:tnrt nf indtpnul,uttrnmas ('apnn·~d and ~•nn1ll~d fo1· the fil':(f. t.im~ from Det t.tnl>er 2tl04 fo Pvfa1·d1 20ftR. l :n tom)lahgl't': Plat.e~m, g Colnl'Mlo. 7 f, " s !: ~ a. 0 ■ ~@rn;ilf-: 4 .... ci 3 z 2 l 0 lto 2 >2to3 >3to 4 >4 to 5 >~ toG >Gto 7 >7 to8 >8 to9 >9 to Age {vears) 10+ :ID Figure 3. Age structure of independent pumas captured and sampled for the first time on the Uncompahgre Plateau, Colorado, December 2004 to May 2009. 162 �Puma births, Uncompahgre Plateau, Colorado 10 9 8 7 6 5 4 3 2 1 0 Jan . Feb. M ar. Apr. May June ■ Births 2005-2009 July Aug. Sep. Oct. Nov. Dec. ■ Births 1982-1987 Figure 4. Puma births detected by month during the reference period (i.e., no puma hunting), 2005 to 2009 (n = 27 litters of 14 females; 26 of the litters were examined at nurseries when cubs were 26-42 days old and 1 litter confirmed by tracks of ≥2 cubs following GPS-collared mother F28 when cubs were ~42 days old), and during the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1-8 months old), Uncompahgre Plateau, Colorado. Age structure of independent.pumas in March 2009, of surviving pumas captured and sampled from December 2004 , while protected from sport-hunting since April 2004, UncompahgrePlateau, Colorado. 4 ,,, 3 v> E ::i c.. 2 0 ■ Fema le ci z 1 ■ M ale 0 lto2 >2to 3 >3to 4 >4 to5 >5to6 >6to7 >7to8 >8to9 >9to10 10+ Age {years) Figure 5. Age structure of surviving independent pumas captured and sampled on the Uncompahgre Plateau, Colorado in March 2009, and after protection from sport-hunting mortality since April 2004, which includes 5 hunting seasons (Nov. through Mar., 2004-05 to 2008-09). One human-caused mortality (F7 killed for depredation control 08-03-08) was documented in the radio- and GPS-collared sample of independent pumas on the study area. This age structure assumes that pumas F3, M29, and M51 were alive on March 31, 2009; they each had non-functional GPS collars and were detected alive as late as 1-15-09, 02-25-09, and 03-20-09, respectively. Mean ± SD of adult female and adult male ages, respectively: 5.21 ± 2.29 yr. (62.54 ± 27.42 mo.); 6.31 ± 1.87 yr. (75.67 ± 22.45 mo.). 163 �APPENDIX A Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2009, Uncompahgre Plateau, Colorado. Puma I.D. Estimated Est. Est. survival span Age to last monitor date Status: Alive/Survived to subadult stage/ from 1st capture to Age at Birth alive or at death (days, Lost contact/Disappeared/ fate or last monitor capture date birth to fate) Dead; Cause of death (days) date M5 183 ~8-1-04 02-04-05 to ~1,345 Survived to subadult stage by 09-16-05; independent at ~13 04-07-08 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4 ½ years old. F9 31 5-28-05 06-27-05 to 326-333 Lost contact― shed radiocollar 04-19-06 to 04-26-06. 4-19-06 F10 31 5-28-05 06-27-05 to 176-215 Lost contact― shed radiocollar 11-20-05― 08-10-05; last tracks of F10 with mother F2 & siblings F9 & 12-29-05 M11 observed 11-20-05. F10 disappeared by 12-30-05. M11 31 5-28-05 06-27-05 to Survived to subadult stage by 12-2-07 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW 918 CO 12-2-07 at 918 days (30 mo.) old F12 42 5-19-05 07-01-05 to 203-252 Lost contact― shed radiocollar 07-28-05―08-01-05. 12-08-05― Tracks of F12 found in association with mother F7 on 1201-26-06 08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. F13 42 5-19-05 07-01-05 to 101 Dead; killed and eaten by a puma (sex unspecified) about 808-28-05 28-05. F14 26 6-26-05 07-22-05 to 226-257 Lost contact― shed radiocollar 01-20-06 to 01-25-06. 02-07-06― Tracks of F14 were observed with tracks of mother F8 & 03-10-06 sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. M15 26 6-26-05 07-22-05 to 345-353 Lost contact― shed radiocollar 06-06-06 to 06-14-06. 06-06 to 14-06 F17 34 9-22-05 10-26-05 to 330 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. 08-18-06 Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. F18 34 9-22-05 10-26-05 to 301-308 Dead; probably killed by another puma. Multiple bite 07-20 to 27-06 wounds to skull. 10 mo. old. M19 34 9-22-05 10-26-05 to 308-314 Lost contact― shed radiocollar 07-27-06 to 08-02-06. 07-27 to 08-02-06 M20 34 9-22-05 10-26-05 to 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. 05-24-06 F21 37 9-26-05 11-02-05 to 324 Lost contact; radiocollar quit. Last aerial location 8-16-06, 08-16-06 live signal. 164 Mother I.D. F3 F2 F2 F2 F7 F7 F8 F8 F16 F16 F16 F16 F3 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 165 Mother I.D. F23 F23 F28 F2 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed, visually observed 03-01-07. Killed by a puma hunter 01-2809 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. F7 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 ~456 42 ~428 subad. 200 52 166 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. F7 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. F7 (?) F7 F3 F3 F3 F50 F54 F25 �Appendix A continued Puma I.D. Estimated Age at capture (days) M58 34 Est. Birth date 5-24-07 Est. survival span from 1st capture to fate or last monitor date 06-27-07 Age to last monitor date alive or at death (days, birth to fate) 324 F59 34 5-24-07 06-27-07 to 08-21-07 434 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 167 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F16 Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F16 Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Killed by a puma hunter in Disappointment Valley, CO 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. 111 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 30 5-19-08 03-12-08 to 07-09-08 06-18-08 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 168 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 F23 �Appendix A continued Puma I.D. Estimated Age at capture (days) F81 40 F97 8 ½ mo. 5-23-08 5-23-08 M82 37 5-29-08 M83 37 M84 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-02-08 to 07-29-09 02-04-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 424 354 F23 F23 295-308 5-29-08 07-05-08 to 03-20-09 or 04-02-09 07-05-08 Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. F8 36 6-5-08 07-11-08 to 02-11-09 251 Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F85 36 6-5-08 07-11-08 F70 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 M87 M88 F89 M90 Male 7A 28 28 28 36 28-35 7-3-08 7-3-08 7-3-08 7-9-08 7-10-08 07-31-08 07-31-08 07-31-08 08-14-08 ~08-07-08 to 08-14-08 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Not radio-collared. Radio-collared Radio-collared Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. ~48-59 28 to 35 169 Mother I.D. F8 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 35 F95 16 mo. F98 4-5 mo. Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-29-08 09-29-08 12-29-08 2-12-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 8-19-08 Radio-collared. F25 8-19-08 Radio-collared. F25 June-07 Radio-collared. Survived to subadult stage. F93 Sep-Oct23-24 Radio-collared. Died, probably killed by male puma Unm.F 08 (infanticide). M99 5 mo. Sep-Oct2-27-09 Radio-collared. Last location 4-22-09 on Paterson Mt. Unm.F 08 M101 35 4-15-09 05-20-09 Radio-collared. F16 M102 35 4-15-09 05-20-09 Radio-collared. F16 F103 35 4-15-09 05-20-09 Radio-collared. F16 M105 38 5-7-09 06-14-09 Radio-collared F75 F106 38 5-7-09 06-14-09 Not radio-collared; F75 returned to nursery during handling. F75 M107 34 5-25-09 06-28-09 Not radio-collared; too small. F94 F108 34 5-25-09 06-28-09 Shed radiocollar; fastener failed. F94 M109 34 5-25-09 06-28-09 Not radio-collared; too small. F94 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 170 �APPENDIX B Puma Population Models and Simulations. Research on the Uncompahgre Plateau Puma Project from December 2004 to July 2009 provides estimates of puma population structure and parameters for a model-based approach developed by CDOW biometrician P. Lukacs and Mammals Researcher K. Logan to examine options for the design of the remainder of this research, and as a preliminary assessment of the CDOW puma management assumptions. Puma Population Modeling Our puma population projections for the study area involved an age-structured, deterministic, discrete time model. The additive puma population model structure is: Nt+1 = Adult Females = (SAF * NAFt + SSF * NSFt) * (1 – HAFt+1) + Adult Males = (SAM * NAMt + SSM * NSMt) * (1 – HAMt+1) + Subadult Females = ((r * SC * NCt) * (1 – HSFt+1)) * PISF/ESF + Subadult Males = (((1 − r) * SC * NCt) * (1 – HSMt+1)) * PISM/ESM + Cubs = Lỹ * AFR * NAFt+1 Terms: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). PI/E = Ratio of progeny + immigrants/emigrants. Lỹ = Average litter size. AFR = Proportion of adult females giving birth to new litters each year. Basic assumptions of the model include: 1) expected puma population projections and annual rates of increase (i.e., lambda) are conditional on the assigned puma population structure and demographic estimates, 2) no density dependent responses are built into the model. Density dependence might operate in puma population dynamics, with competition for food regulating adult female density and competition for mates regulating adult male density (Logan and Sweanor 2001), and 3) harvest is additive mortality. We parameterized the model with data gathered on the pumas on the study area during the first 3.7 years. (Data from this past year, 2008-09 could not be used because decisions about harvest structure for the treatment period needed to be made June of that biological year). The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table B.1). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radio-collared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table B.2). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature 171 �(Table B.2), because our current sample sizes (i.e., number of individuals and years) may not be adequate for realistic estimates (i.e., adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to emigrants as a model input was from the literature, because such data is scarce and does not exist for Colorado (all references in Table B.2). We preferred using the population characteristics and parameter estimates gathered in the current research effort, because this is the puma population we intend to manipulate to assess current CDOW puma management strategies. Table B.1. Minimum puma population count on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008 (RY4). The minimum count involves counting all radio- and GPS-collared pumas, all other marked pumas, and all presumably unmarked pumas detected on the study area during the period. Presumed unmarked pumas could be marked with ear-tags and tattoos. Their tracks and movements could be separated from movements of radio- and GPS-collared pumas. Or they exhibited evidence that could separate them from other local marked pumas from their tracks (i.e., distinguishable by sex, number of cubs and/or relative size of cubs varied). Region East slope West slope Totals Adults Subadults Female Male Female Male 10 4 3 4 6 4 2 0 16 8 5 4 Total Independent Pumas = 33a,b Female 4 1 5 Cubs Male 4 2 6 Unknown sex 7 2-3 20-21 Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. a 172 �Table B.2. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas of both sexes 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radiocollared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Parameter Adult age Estimate 2+ years Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). This result supported Logan and Sweanor 2001:69, n = 148). Proportion of adult females giving birth each year (n = 3 years for n = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits/Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). 173 �Puma Population Simulations We used this model to simulate puma population dynamics to examine a set of scenarios that pertain to current CDOW puma management assumptions and to the puma research and management direction on the Uncompahgre Plateau for the treatment period: 1) Puma population dynamics without hunting-caused mortality. 2) Puma harvest that would induce a stable (i.e., no growth) phase to identify a population tipping point induced by harvest mortality, expected to be 16% harvest of independent pumas. Various sex ratios of harvest composition were examined. 3) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population. Various sex ratios of harvest composition were examined. 4) Puma harvest at the upper limit (i.e., 28% of >15-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population. Various sex ratios of harvest composition were examined. 5) Puma harvest at a 20% harvest level intermediate to the 16% stable growth and 28% decline phase with varying female to male sex structure of the harvest. 6) Puma harvest at the historic harvest level of 26% and sex ratio of 45 females:55 males on the study area during 1994-2003. Results of Puma Population Simulations The following tables contain the expected minimum population sizes for independent pumas and annual rates of population increase conditional upon the minimum number of independent pumas detected in Reference Year 4 (RY4) and the model input parameters and assumptions (given in Tables B.1 and B.2). The total number of independent pumas is probably higher in any particular scenario because we probably did not detect all of the independent pumas in RY4. Simulations involving harvest apply the harvest following reference year 5 (RY5) and starting with treatment year 1 (TY1) to assess what might be expected to occur within the current research structure on the Uncompahgre Plateau. Our puma population simulation modeling suggest strategies to achieve increasing and declining puma populations contingent upon the set of assumptions and input demographic data. Moreover, results of this modeling effort constitute the first time that CDOW puma harvest assumptions have been evaluated by using Colorado-specific population data. Results could change as more quantitative population data are gathered and the puma population is manipulated during this research. Expected estimates of population growth were generally consistent with the current CDOW puma harvest management assumptions that were previously developed from data in the puma population literature to manage for a stable-to-increasing population, and for a declining puma population. The following series of tables (B.3 – B.16) indicate results of the individual models, followed by notes on how results may be interpreted relative to other research results on puma population dynamics and specific CDOW puma management assumptions. The harvest levels for each model are clearly stated in the left column of each table. 174 �Table B.3. Harvest Level 16% of independent pumas, sexes are harvested equally; i.e., stable phase model. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 12 7 6 19 12 8 7 19 13 7 7 19 13 7 7 19 14 7 7 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 35 34 34 34 34 Total 33 45 44 45 46 46 46 Lambda* 1.37 0.98 1.02 1.01 1.01 1.00 Note: The tipping point of population stability and decline is expected to be about 16% harvest of independent male and female pumas, consistent with current CDOW puma harvest assumptions. *Lambda is the finite rate of population growth (Williams et al. 2002:136): λ = 1 + (N t+1 – N t) / N t Expected Minimum No. Pumas 50 "'n:, 45 E 40 ::I c.. 35 C: 30 (IJ "C 25 C: (IJ C. 20 (IJ "C 15 -=ci 10 z 5 0 ... .,,, - - - 11;:: /' .,.. 33 RY4 RYS TYl TY2 TY3 TY4 TYS Year Figure B.1. Expected minimum number of independent pumas based on population simulations with 16% harvest of independent pumas comprised of 50% males and 50% females in the harvest in TY1 to TY5. Table B.4. Harvest Level 16% of independent pumas, harvest comprised of 40% females:60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 11 7 6 21 10 9 7 23 10 9 7 24 10 9 7 25 10 10 8 Note: The puma population is expected to increase. 175 Independent Pumas Cub 20 33 37 39 41 44 46 Total 33 45 44 46 48 51 53 Lambda 1.37 0.98 1.05 1.04 1.05 1.05 �Table B.5. Harvest Level 16% of independent pumas, harvest comprised of 45% females:55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 11 7 6 20 11 8 7 21 11 8 7 21 12 8 7 22 12 9 7 Independent Pumas Cub 20 33 36 37 38 39 40 Total 33 45 45 46 47 49 50 Lambda 1.37 0.98 1.04 1.03 1.03 1.03 Note: The puma population is expected to increase. Table B.6. Harvest Level 16% of independent pumas, harvest comprised of 55% females:45% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 12 7 7 17 13 7 7 17 14 6 6 16 14 6 6 15 15 6 6 Independent Pumas Cub 20 33 34 31 30 29 27 Total 33 45 44 44 43 42 41 Lambda 1.37 0.97 1.00 0.98 0.98 0.97 Note: The puma population is expected to decline slowly. Expected No. Independent Pumas at 16% harvest with varying female:male ratio 60 V, Ill - so E ::i c... .... 40 ~ QJ "ti ~ 30 / / F:M ratlo - 40:60 - 45 :55 50:50 QJ C. - QJ "ti -=ci z 20 55:45 10 0 RY4 RYS TY1 TY2 Ye ars TY3 TY4 TYS Figure B.2. Expected minimum number of independent pumas based on population simulations with 16% harvest of independent pumas comprised of varying female to male sex ratios in the harvest in TY1 to TY5. See tables B.3-6 (above) for quantities of results for each model. In reality, the ratio of females to males in the harvest may vary randomly on an annual basis, and the expected annual numbers of independent pumas may fall within the lower and upper population trend lines. 176 �Table B.7. Harvest Level No harvest. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Note: Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau are consistent with the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4 yr.; r = 0.28, n = 4 yr.; r = 0.17, n = 4 yr.; r = 0.11, n = 7 yr.; Logan and Sweanor 2001:169-175). Puma population growth could be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater vulnerable prey biomass), and if puma sources are nearby to the study area. Table B.8. Harvest Level 15% of independent pumas, sexes are harvested equally. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 12 7 7 19 12 8 7 19 13 8 7 20 14 8 7 20 14 8 7 Independent Pumas Cub 20 33 36 35 36 36 36 Total 33 45 45 47 47 48 49 Lambda 1.37 0.99 1.04 1.02 1.02 1.01 Note: This result is consistent with current the CDOW puma harvest assumption for a stable-to-increasing population, with slow growth attributed to equal harvest of females and males. Table B.9. Harvest Level 15% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 21 11 8 6 22 10 9 7 23 10 9 7 25 11 10 8 26 11 10 8 Independent Pumas Cub 20 33 38 39 42 45 48 Total 33 45 45 47 50 53 56 Lambda 1.37 0.99 1.06 1.05 1.06 1.06 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with increased growth due to reduced female mortality. 177 �Table B.10. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 50% females and 50% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 50% females & 50% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 11 7 6 17 11 7 6 16 11 6 6 15 11 6 6 15 11 6 5 Independent Pumas Cub 20 33 34 31 30 28 27 Total 33 45 42 41 40 38 36 Lambda* 1.37 0.93 0.97 0.96 0.96 0.96 Note: The puma population would be expected to decline. Table B.11. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 40% females and 60% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 10 7 5 20 8 8 6 21 8 8 6 21 8 8 6 22 7 9 6 Independent Pumas Cub 20 33 36 37 38 39 40 Total 33 45 42 42 43 43 44 Lambda 1.37 0.93 1.01 1.00 1.01 1.02 Note: The puma population would be expected to increase slowly. Table B.12. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 45% females and 55% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 45% females & 55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 10 7 6 19 10 7 6 19 10 7 6 18 9 7 6 18 9 7 6 Independent Pumas Cub 20 33 35 34 34 34 33 Total 33 45 42 42 41 41 40 Lambda 1.37 0.94 0.99 0.98 0.99 0.99 Note: The puma population would be expected to decline slowly. The ratio of 45% females and 55% males in the harvest is the average harvest sex ratio during 1994-2003. 178 �Table B.13. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 55% females and 45% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 55% females & 45% males. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 17 12 6 6 15 12 6 6 14 12 5 5 12 12 5 5 11 12 4 4 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 32 28 25 22 20 Total 33 45 42 40 37 34 31 Lambda 1.37 0.94 0.99 0.98 0.99 0.99 Note: The puma population would be expected to decline more rapidly. Expected No. Independent Pumas at 20% harvest with varying female:male ratio so 45 "'ro 40 ::I c.. 35 - 40:60 C: 30 - 45:55 "C 25 E ..... QJ C: 50:50 QJ Q. QJ "C -=ci z 20 - 15 55:45 10 5 0 RY4 RYS TYl TY2 TY3 TY4 TVS Years Figure B.3. A harvest level of 20% of independent pumas is expected to result in a declining population, except in the scenario consistently weighted heavily toward male harvest (i.e., 60%). Table B.14. Harvest Level 28% of independent pumas, sexes are harvested equally. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 17 10 6 6 14 9 6 5 12 8 5 4 10 7 4 4 9 6 3 3 Independent Pumas Cub 20 33 30 25 22 18 16 Total 33 45 38 33 29 25 21 Lambda 1.37 0.84 0.88 0.86 0.86 0.86 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population. 179 �Table B.15. Harvest Level 28% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 8 7 4 18 6 7 5 17 5 7 4 16 4 6 4 16 4 6 4 Independent Pumas Cub 20 33 34 32 31 30 29 Total 33 45 38 35 33 31 30 Lambda 1.37 0.84 0.93 0.93 0.95 0.95 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population even with harvest weighted toward males. Yet another harvest scenario to consider for the treatment period is application of the historic puma harvest on the study area. Puma mortality data for the study area during the 10 years previous 19942003 prior to the beginning of the study reference period was tabulated after carefully geo-referencing mortality locations on the study area (Logan 2008). Model parameters from those data include: mortality rate of 14.3 independent puma mortalities per year (rounded to 14/yr.), and sex proportions of 55% males and 45% females. No other puma population data or parameter estimates were available for the study area at that time. Therefore, the scenario that was modeled pertained to the expected impact of the average annual puma mortality of independent pumas (i.e., adults and subadults) if the hypothetical population was the same as the minimum expected puma population after year 5 of the reference period (i.e., RY5). A harvest of 14 pumas/yr. is a 26% harvest rate of the expected minimum independent puma population at the start of TY1. Table B.16. Harvest Level 26% of independent pumas at start of TY1, comprised of 45% females & 55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 9 7 5 17 8 7 5 15 7 6 5 14 6 6 5 13 6 5 4 Independent Pumas Cub 20 33 33 30 28 26 25 Total 33 45 39 36 34 31 29 Lambda 1.27 0.87 0.93 0.92 0.93 0.93 Note: As expected, results of this model indicate puma population decline. This simulation demonstrates the negative cost of uncertainty in puma management; in this case a puma population would decline where the intended management objective was for a stable-to-increasing population. 180 �Expected No. Independent Pumas 50 45 V, re 40 E 35 ::J c.. .... C: 30 29 Q) "C C: 25 Q) Q. Q) "C 20 -=ci 15 z 10 5 0 RY4 RYS TYl TY2 TY3 TY4 TVS Years Figure B.4. Expected dynamics of a puma population with the historical harvest (1994-2003) rate on the Uncompahgre Plateau study area of 26% of the independent puma and sex ratio of 45% females to 55% males (see Logan 2008 for historical harvest data on the study area). 181 �APPENDIX C Collaborative project on disease surveillance in wild felids with College of Veterinary Medicine and Biomedical Sciences, Department of Microbiology, Pathology, and Immunology, Colorado State University. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, “The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids”, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Mr. Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and interspecific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that will be most valuable, and a draft of a ‘permissions’ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude 182 �The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids Project Summary Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in carnivore species. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and postgraduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multidisciplinary collaborations. 183 �Appendix C (continued). Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado, 2005-2009. Puma ID UPCO2 UPCO3 UPCO7 UPCO7 UPCO7 UPCO8 UPCO4 UPCO5 UPCO6 UPCO6 UPCO23 UPCO25 UPCO28 UPCO29 UPCO31 UPCO23 UPCO27 UPCO30 UPCO50 UPCO51 UPCO52 UPCO54 UPCO55 UPCO24 UPCO69 UPCO70 UPCO71 UPCO72 UPCO73 UPCO74 UPCO75 UPCO72 Sex F F F F F F M M M M F F F M M F M F F M F F M F M F M F F F F F Capture Date 1/8/2008 1/21/2005 2/24/2005 3/30/2006 3/3/2007 3/21/2005 1/28/2005 2/4/2005 2/18/2005 4/12/2008 2/25/2008 2/8/2006 3/23/2006 4/14/2006 4/19/2006 1/4/2006 3/10/2006 4/15/2006 12/14/2006 1/7/2007 1/10/2007 1/12/2007 1/21/2007 1/17/2006 1/11/2008 1/20/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 3/26/2008 7/20/2009 UPCO104 UPCO55 UPCOF16 UPCO66 UPCO94 UPCO96 UPCO100 UPCO82 UPCO93 UPCO71 UPCO72 UPCO73 UPCO74 F M F F F F M M F M F F F 5/21/2009 1/5/2009 1/14/2009 11/25/2008 12/19/2008 1/28/2009 3/27/2009 2/10/2009 12/15/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 GPS NAD27 U.T.M.: Zone, E, N 13S, 245722, 4244166 13S, 241606, 4251510 13S, 246328, 4244230 13S, 245901, 4247627 13S, 247645, 4246097 12S, 727808, 4239029 13S, 257565, 4239606 13S, 240577, 4251037 13S, 247399, 4254006 13S, 257516, 4239696 12S, 723304, 4242231 13S, 258374, 4230480 12S, 722868, 4240115 12S, 723458, 4242340 12S, 746919, 4225441 12S, 730188, 4234861 12S, 722339, 4245212 13S, 248551, 4242095 12S, 753639, 4260149 13S, 238783, 4252390 13S, 258058, 4236260 13S, 252688, 4228050 13S, 258133, 4228691 12S, 737151, 4233273 13S, 248191, 4246810 13S, 247122, 4245760 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 12S, 732894, 4239423 13S, 255400, 4229658 12S, 745118, 4264721N 13S, 239076, 4248637 13S, 256528, 4235500 13S, 245901, 4247627 12S, 758531, 4259824 13S, 247764, 4246239 12S, 749832, 4217148 12S, 726732, 4243782 12S, 751445, 4265985 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 PLV + + + + I + + + + + + + + + + + + + + P P P P + P + P P P + P a a b FCV +h + + + + + + No swab - c FHV + + + + + + + No swab - FPV + + + NA NA + + + + + + + + NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA d T.g.e IgM + P - T.g.e IgG + + + + + + + + + + + + + + + + + + + + + + + + P + + B.h.f + + Y.p.g + ++ +++ ++ ++ ++ + + ++ + + + NA P + + + + + + + + + + + P + - NA NA NA NA NA NA NA NA NA + - PLV is Puma Lentivirus. FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result), NA (not applicable). b 184 �Colorado Division of Wildlife July 2009 –July 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 31, 2009−July 31, 2010 Author: K. A. Logan. Personnel: K. Logan, C. Burnett, B. Dunne, A. Greenleaf, J. Knight, R. Navarrete, J. Waddell, S. Waters, K. Crane, T. Mathieson, J. Koch, and T. Bonacquista of CDOW; S. Young and W. Wilson of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, yrs 1-5) and presence (treatment period, yrs 6-10) of hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Division of Wildlife’s model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report informs on the first year of the treatment period (TY1), August 2009 through July 2010, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sporthunting opened November 16 and closed December 11, 2009 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 9 pumas were killed: 2 adult females, 1 subadult female, 5 adult males, and 1 dependent cub. The harvest of 8 independent pumas represented 15% of the expected (i.e., modeled) 53 independent pumas and 14.5% of the minimum number of 55 independent pumas counted 2009-10. Independent females and males comprised 37.5% and 62.5% of the harvest, respectively. Four other radio-collared pumas, 1 adult female and 3 adult male, in the study area population were killed in GMUs adjacent to the study area. The total harvest of 12 independent pumas represented 21.8% of the minimum count of independent pumas. Eight independent pumas will be the harvest quota for the 2010-11 hunting season (TY2). Seventy-nine hunters requested mandatory permits with an attached voluntary hunter survey in TY1. Seventy-one of the hunters provided responses to written (n = 43) or telephone call follow-up contact (n = 28). An estimated 67 hunters 101 �actually hunted on the study area, of which 13% harvested pumas and 24% captured pumas (i.e., harvested plus treed and released). All hunters responded that they were selective hunters, and the capture and population data indicated that most successful hunters practiced selection. From August 2009 to July 2010 thirty-three individual pumas were captured 38 times. Two capture teams with dogs operated over 86 search days from December 2009 through April 2010 to find 266 puma tracks, pursue pumas 93 times, and capture 21 pumas 26 times. Capture efforts with cage traps resulted in the recapture of 2 adult pumas and 1 cub. Nine cubs were observed for the first time at nurseries. A total of 42 pumas were monitored by radiotelemetry. Search efforts also revealed the presence of at least 15 other independent pumas. Our minimum count of independent pumas from September 2009 to April 2010 was 55, including 31 females and 24 males. A preliminary minimum estimated density of independent pumas was 3.29/100 km2. The proportion of radio-collared adult females giving birth in the August 2009 to July 2010 biological year was 0.42 (8/19). Seven litters that could be dated to month of birth were produced in June (4), July (2), and August (1). We monitored 19 female and 8 male adult radio-collared pumas for survival and agentspecific mortality. Survival rates in TY1 with hunting were generally lower than in the reference period without hunting. Causes of mortality were vehicle strikes and hunting. In addition, all 5 adult males with malfunctional radiocollars since the beginning of this study were harvested by hunters in TY1. Two radiomonitored subadult males died apparently due to natural causes. Of 19 cubs monitored with radiotelemetry, 5 died, all associated with infanticide. A non-marked adult male was also killed by a vehicle on the boundary of the study area. Puma harvest data also provided information on dispersals of 12 male and 1 female puma initially marked on the study area. Those pumas moved from about 60 to 370 km from initial capture sites. A pilot study on detection probabilities of pumas using a camera grid for a mark-recapture design was conducted in collaboration with Colorado State University Researchers J. Lewis and K. Crooks as they studied bobcats on the east slope of our study area. Two camera grids, Area 1 and Area 2, were on the east slope of the study area. Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. Cameras operated for 108 days from August 21 to December 7, 2009. Detection probabilities for 4 adult radio-collared pumas on Area 1 and 5 adult pumas on Area 2 were 0.75 and 0.80, respectively. Those pumas were photographed a total of 51 times: 17 times in Area 1 and 34 times in Area 2. Males were detected more frequently than females. Four other marked pumas without functioning collars were also detected 7 times. Non-marked pumas were photographed 31 times, representing 2 to 4 individuals in Area 1 and 3 to 5 individuals in Area 2. The next step in this collaboration is to conduct an intensive evaluation of pilot study data to model detection probability, estimate precision, and define the survey area for a camera grid design specifically for puma. Data are continued to be gathered for other collaborative projects with Mammals Research and CSU investigators on puma behavior, social organization, population dynamics, and habitat use. 102 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Division of Wildlife (CDOW) puma management assumptions in the first year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CDOW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the first year of the five-year treatment period by working with CDOW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and age-stage survival rates. 5. Continue gathering data on agent-specific mortality. 6. Collaborate with Colorado State University (CSU) researchers on a pilot project to assess puma detection probability in a camera grid design. 7. Collaborate with other researchers involved with puma biology and ecology. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). 103 �● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the gray-shaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 will involve the use of controlled recreational hunting to manipulate the puma population. 104 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-firstbreeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CDOW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of 105 �greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested (with the use of hounds) is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CDOW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2008). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. We want to examine the usefulness of this approach in Colorado. CDOW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 106 �months old (Barnhurst 1982, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area highly accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates 107 �will be quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for at least the past 100 years. Hence, the reference period, years 1―5, provided conditions where individual pumas in this population (of estimated sex and age structure) expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CDOW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population will be manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the 108 �study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling 109 �processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when puma was immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they are over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). 110 �Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). 111 �RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2009 to July 2010, was the first year of the treatment period in this study of puma population dynamics on the Uncompahgre Plateau. Principal investigator K. Logan with CDOW biologists and managers developed a structure (i.e., officially approved by Wildlife Commission decision in September 2009) to manipulate the puma population with sport-hunting and to survey hunters. The hunting season on the study area began on November 16, 2009 and was scheduled to extend to January 31, 2010, unless the harvest quota was taken before then. The design harvest quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This design harvest tests the CDOW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-toincreasing puma population (Assumption and Hypothesis 3 p.5 this report). The quota of 8 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1). We relied on the count data from 2007-08 because that was the last year in the reference period in which a fully staffed research team was able to adequately survey the study area in winter capture operations. The next year, 2008-09 (i.e., the last year of the reference period), a state government-mandated hiring freeze contributed to subpar winter capture operations, and thus, an inadequate minimum count effort. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CDOW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CDOW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later). All pumas harvested on the study area were examined by principal investigator K. Logan and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CDOW within 48 hours of harvest. Upon inspection data was recorded on the puma harvested, including: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 16 to December 11, 2009, taking 26 days to fill the quota of 8 pumas. Nine pumas were killed, including: 2 adult females, 1 subadult female, 5 adult males, and 1 dependent male cub (Table 2). Three of the pumas were killed on the last day, resulting in the quota being exceeded by 1 puma. Of the harvested pumas, 3 were marked: dependent male cub M91 (offspring of F25), and 2 adult males M51 and M71. In addition to the pumas killed on the study area, 1 adult female (F110) and 3 adult males (M27, M29, M100) that had home ranges overlapping the study area were killed off the study area on adjoining GMUs (Table 3). The harvest of 8 independent pumas on the study area was 14.5% (8/55*100) of the minimum count of 55 independent pumas, including 31 females and 24 males, estimated by the research team 112 �during September 2009 to April 2010 (Table 4). Independent females and males comprised 37.5% (3/8*100) and 62.5% (5/8*100) of the harvest, respectively. This harvest structure was 9.7% (3/31*100) of the independent females and 20.8% (5/24*100) of the independent males. Considering the harvest of 4 other radio-collared adults (F110, M27, M29, M100) off the study area, which had home ranges overlapping on and off the study area, a harvest of 12 independent pumas was 21.8% (12/55*100) of the minimum number of independent pumas. The harvest composition of 4 females and 8 males was comprised of 33.3% (4/12*100) females and 66.7% (8/12*100) males. This harvest structure was 12.9% (4/31*100) of the independent females and 33.3% (8/24*100) of the independent males in the minimum count. The minimum count of independent pumas in 2009-10 was highly consistent with the expected number and sex structure of independent pumas projected by the deterministic, discrete time model (see Tables 1 and 4. Minimum count 2009-10 = 55 independent pumas, including 31 females, 24 males. Model projected independent pumas = 53, including 31 females, 22 males). Therefore, we used the model to guide the decision to manipulate the puma population with a harvest of 8 independent pumas in the 201011 hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population will probably be killed outside of the study area as in the 2009-10 hunting season (Fig. 3). The projected population trends are stable-to-increasing. Hunter permits and survey: Mandatory permits with the voluntary survey attached were requested by 79 individual hunters. Thirty-three of the hunters requested a second permit after the first one expired after 14 days. Seventy-one hunters (90%) provided responses to the voluntary survey either by turning in the survey (i.e., n = 43) or providing information during follow-up telephone calls (i.e., n = 28) by principal investigator K. Logan. The remaining 8 hunters could not be contacted, because either they did not have working phone numbers or they did not return calls. Of the respondents, 11 hunters indicated that they did not hunt on the study area. As a proportion of the 71 respondents, the number that hunted extrapolated to the total of 79 hunters (60/71 = 0.845) indicated that about 67 hunters took to the field for pumas on the study area during the 26-day hunting season. Considering that 67 hunters were estimated to be afield, then 13% harvested pumas (9/67*100) and 24% of individual hunters captured pumas (16/67*100; see captured and released pumas below and in Table 5). In response to the survey question, “Do you consider yourself a selective or non-selective hunter?” all the respondents that hunted on the study area indicated that they were selective hunters. (A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size.) Yet, selective hunter was indicated by the 3 hunters that killed a subadult female, a lactating female, and a dependent male cub, which may indicate that in fact not all the hunters are selective or some cannot distinguish types (i.e., sex, age stage) of pumas in the field to practice selection. On the other hand, hunter surveys also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 14 times, including 9 females and 5 males. All 9 females were described by the hunters as adult age; 2 males were described as adult age, and 3 males were described as subadults. Five of the treed pumas were marked, including adult female F8 treed twice, adult female F74, and 2 yellow ear-tagged subadult males (numbers could not be distinguished). Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex and size (Table 5). These preliminary survey and harvest data indicate independent females were probably captured slightly more frequently than independent males (i.e., ratio 12 females:10 males; females = 3 harvested + 9 captured and released; males = 5 harvested + 5 captured and released). This sex structure was consistent with the sex structure of the independent pumas in the minimum count (Table 4). Yet, the harvest was comprised of mostly males (3 females, 5 males). 113 �This preliminary assessment from TY1 puma harvest and hunter survey data suggests that most hunters that captured pumas were selective and influenced harvest sex and age composition. Segment Objective 2 After the design quota was filled, puma research teams immediately activated for capture operations with trained dogs. Two fully-staffed capture teams, one detailed on the east slope and one detailed on the west slope, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring 2009-10. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 34 puma captures of 28 individuals from August 2009 to July 2010 (Tables 6-11). Twenty-one individual pumas were captured with dogs 26 times. Three pumas were captured in cage traps. Cubs were captured at nurseries 5 times. A total of 42 pumas were monitored with radiotelemetry from August 2009 to July 2010 (some of these had been collared in previous years). In addition, 2 cubs were monitored from birth to death at the nursery by monitoring the GPS and VHF data of their mother. Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from December 15, 2009 to April 30, 2010. Those efforts resulted in 86 search days, 266 puma tracks detected, 93 pursuits, and 26 puma captures (Table 6). Search days with dogs in this period was greater than our efforts in the 4 previous winters by 4 to 15 days (Table 12). In addition, this was the first year we deployed 2 fully-staffed hound capture teams. The frequency of tracks (tracks/day) encountered was higher than the previous 5 winters. The pursuits increased over all previous years by 18 to 58, with the lowest number of pursuits occurring in the first year of this study (2004-05). The capture rate was also the highest by 2 to 12 captures. Increased capture efforts and captures were probably the result of using 2 fully-staffed houndsmen teams even though the puma population had been reduced due to harvest just before our capture operations. Researchers also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be pursued by houndsmen. The count was: 37 tracks of females, including 5 associated with cubs; 21 tracks of males; and 2 tracks of unspecified sex. The ratio of female to male tracks was consistent with the sex structure of independent pumas in our minimum count (Table 4). Puma capture efforts using ungulate carcasses and cage traps extended from September 11, 2009 to May 17, 2010 (Table 10). We used 21 road-killed mule deer at 17 different sites, but did not capture any pumas. However, 2 adult pumas (M55, F94) were each recaptured in cage traps at mule deer kills they made. Pumas scavenged at 3 of 17 (17.65%) sites where ungulate carcasses were used for bait. A bobcat trapper inadvertently caught male cub M112 (offspring of F70) in a cage trap. The trapper notified us, and we sampled, tagged, radio-collared, and released the cub. The cub successfully rejoined his family. We captured 5 cubs, all males for the first time (Table 11), and fit all with radio-collars (Appendix A). Two cubs of F3 were captured at nurseries, 2 were bayed by hounds (M115 of F28, M117 of F119), and 1 was caught in a bobcat cage trap (M112 of F70, see above). In addition, we found 2 male cubs (P1016, P1017) of F72 that were killed by male puma M32 on the day we investigated the nursery to sample and tag the cubs (see later). Two cubs of F93 were observed in the nursery at about 28 days old, but they could not be handled because the rock structure of the nursery afforded them complete protection from capture. 114 �In addition to our direct puma captures with dogs December through April, we detected 16 pumas that we were able to identify with GPS or VHF telemetry 38 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made, then we ruled the data were confirmatory. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with nonfunctioning GPS- or radiocollars. Our search efforts throughout the study area also revealed the presence of at least 15 other independent pumas, we classified as 9 females and 6 males. Two of the males were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 7). We could separate the activity of the other pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females and males. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to separate 2 adult females followed by 2 to 3 medium-to-large-size cubs. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). One of the adult females was likely F74, which was also treed and observed by a puma hunter on December 9, 2009. It is also possible that 1 of the adult females was previously marked animal F24 wearing non-functional GPS collar. Our search and capture efforts during September 2009 through April 2010 enabled us to quantify a minimum count of 55 independent pumas detected on the Uncompahgre Plateau study area, including 31 independent females and 24 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or treed and released by hunters on the study area, and fresh puma tracks (i.e., ≤ 1 days old) observed by researchers that could not be attributed to pumas with functioning radiocollars. The estimated age structure of independent pumas in November 2009 at the beginning of the puma hunting season in Treatment Year 1 (TY1) on the Uncompahgre Plateau study area is depicted in Figure 4. In addition to the independent pumas, we also counted a minimum of 20 to 25 cubs. Of the 55 independent pumas, 34 to 35 (62-64%) were marked and 20 to 21 (36-38%) were assumed to be unmarked animals. Of the expected unmarked pumas, 10 to 11 were females and 10 were males. The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 28 independent pumas (17 females, 11 males). The west slope count included 27 independent pumas (14 females, 13 males). Considering the minimum count of 55 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 3.29 independent pumas/100 km2. Segment Objective 3 During the past 5.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). We observed 6 litters born in June (3), July (2), and August (1) 2010, each with 1 to 3 cubs each, born to radio-collared females. We found sign (i.e., nurseries, tracks) of a fourth litter born in June to a GPS-collared female (F111); but, we could not catch the cubs before they developed well enough to escape us (about 6 weeks old). Data on reproduction observed in this first year of the treatment period were added to Table 13, but will not be summarized again until the end of the period. The proportion of radio-collared adult females giving birth from August 2009 to July 2010 biological year was 0.53 (8/15). 115 �Considering our 32 total observed litters and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females, all with cubs 26 to 42 days old, the distribution of puma births by month indicate births extending from March into September, with 24 of 34 births (70.6%) occurring May through July (Fig. 5). Our data suggests that the large majority of puma breeding activity occurred February through April. In contrast, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 34 litters added to Anderson’s data (Fig. 5), and indicated puma births on the Uncompahgre Plateau occurred in every month except January and November (so far). Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2010, we radio-monitored 14 adult male and 26 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting indicated relatively high survival, with adult male survival generally higher than adult female survival (Table 15). For this first year of the treatment period, we monitored 19 adult radio-collared females and 8 radio-collared adult males. The initial indication is that adult survival rates declined for adult females and males (Table 15). But, no conclusions should be drawn with only 1 year in the treatment period (TY1). The primary interest is the magnitude of reduction in survival, and the implications of those survival rates for population growth rate. This is what ultimately allows us to evaluate the effect of this harvest level for our population management assumptions when the goal is a stable to increasing population. Causes of mortality for adult pumas with functioning radiocollars in TY1 were due to vehicle strikes on roadways (2 females, 1 male) and hunting (1 female, 1 male). In addition, all 5 adult males which developed non-functional radiocollars (M1, M27, M29, M51; Table 3) or shed a collar (M71) since the beginning of this study were harvested by hunters in TY1. Inclusion of those adult males in the survival estimate indicated a substantially lower adult male survival rate in TY1 (Table 15). We have radio-monitored 11 pumas, 4 females and 7 males, in the subadult age-stage (independent pumas <24 months old) (Table 16). Three died before reaching adulthood, indicating a preliminary finite survival rate of 0.727. All 3 subadults apparently died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old due to unknown causes; but, punctures in the skull suggested strife with another puma. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Data from puma hunters provided additional information on fates of 13 pumas, 12 males and 1 female, initially captured and marked as cubs (10 males) or subadults (2 males, 1 female) on the Uncompahgre Plateau puma study area (Table 17). All 12 of the males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 60 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). The female (F52) was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she probably established an adult home range there. These pumas represent dispersal moves from the 116 �Uncompahgre Plateau. Eleven of the 13 pumas (except M68, 17 months old and M82, 19 months old) had reached adult ages ranging from 24 to 55 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009. In that summary 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old were used for a Kaplan Meier procedure cub survival estimate of about 0.53 to one year of age. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In this first year of the treatment period, we monitored the fates of 19 cubs (Appendix A). Five of the cubs were known to have died, all of them associated with infanticide. Two (M101, F103) were orphaned at 149 days old when their mother (F16) was hit by a vehicle on County Road 1 on September 11, 2009. The 2 cubs were killed and partially eaten by adult male puma M55 on September 17 and 19, 2009. Fate of their sibling M102 was unknown because of a failed radiocollar after September 4, 2009. But M102 probably would have died of starvation if he was not killed by M55. F72’s 2 male cubs were killed, and 1 partially eaten, by adult male puma M32 at the nursery when the cubs were 39 days old on July 21, 2010. Mother F72 was about 2 km away from the nursery at the time the cubs met their fate. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. In addition, a 2-year-old non-marked male puma was struck and killed by a vehicle on highway 62 in Leopard Creek on the south boundary of the study area on August 25, 2010. This mortality made the twelfth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 12 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Segment Objective 6 We wanted to enhance this project with reliable estimates of puma abundance and density (see Objective 5, page 4). Because a majority of independent pumas were individually marked on the study area, we decided to explore the potential of using a camera grid mark-recapture structure to derive puma abundance estimates by first examining detection probabilities in a pilot effort. This effort is an attempt to develop puma population monitoring methods (Fig. 1). A camera grid mark-recapture approach is a method for counting pumas independent from our main method of capturing pumas with searches on snow-covered routes and dogs and thus has the potential of providing unbiased estimates. For this pilot project, we collaborated with Colorado State University Researchers Jesse Lewis (Ph.D. candidate) and Dr. Kevin Crooks (Dep. of Fish, Wildlife, and Conservation Biology) who studied bobcat distribution, abundance, and behaviors on the eastern slope of our Uncompahgre Plateau puma study area. Because those researchers used a camera grid design for bobcats where we also had GPS/VHF- collared pumas, this gave our project an opportunity to evaluate puma detection probability on a small scale. This was a first step in considering the usefulness of a camera grid design for puma abundance estimates. We established 2 camera grids on the east slope of the study area (Fig. 6). Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. We searched each grid for potential camera sites with the intention to maximize the encounter of a puma or bobcat with a camera. We used our general knowledge about puma and bobcat behavior to place the cameras and did not use any GPS/VHF data on puma locations. Felid sign on the ground (i.e., tracks, feces, scrapes) helped to guide our camera placement. Initially we placed 1 Cuddeback Capture digital camera (Park Falls, WI) in each cell at the site we deemed best to intercept wild felids, and did not use scent or sight lures in an attempt to attract the felids. One alternate camera site was placed in Area 1 and 5 alternate camera sites were placed in Area 2 to increase the sample effort in canyon bottoms relative to canyon rims. All cameras were set at the highest design setting of 1 photo per 30 seconds if the passive infrared 117 �sensor were activated and serviced every 2 weeks to ensure operation and fresh batteries. Cameras operated for 108 days from August 21 to December 7, 2009. During the period that the cameras operated, 4 adult (2 females, 2 males) GPS/VHF-collared pumas ranged on Area 1 and 5 adult (3 females, 2 males) GPS/VHF-collared pumas ranged on Area 2. Those pumas were photographed a total of 51 times: 17 times in Area 1 and 34 times in Area 2. Three of 4 adult pumas (probability 0.75) on Area 1 and 4 of 5 adult pumas (probability 0.80) were detected 2 to 19 times each in the 108 day period. Daily detection rates ranged from 0.02 to 0.18 (Table 19). Detection rates varied among individuals, and were the highest for adult males. Both adult pumas that were not detected were females. One, F16, died on September 11, so was available for 21 days. The other, F70, had a new litter of cubs on August 31 at a nursery in a canyon between the 2 camera grids where she focused her activities. Then on September 23 her GPS collar quit functioning and we were unaware of her movements. In addition, 4 other marked pumas without functioning collars were detected by cameras a total of 7 times. Those pumas were: adult F3 (detected 3 times; non-functional GPS collar), adult M71 (detected twice; eartags, shed expandable VHF collar), a subadult female detected once (orange eartag right pinna), and a male cub detected once (yellow eartag left pinna). Non-marked pumas were photographed 31 times on the camera grids. In Area 1 non-marked pumas were photographed 20 times at primary cameras and once at the alternate camera. We estimated the photos represented 2 to 4 individual independent pumas. In Area 2 non-marked pumas were photographed 8 times at primary cameras and twice by alternate cameras. We estimated the photos represented 3 to 5 independent pumas. Any of the non-marked pumas could have ranged on both camera grid areas. Our next step in this collaborative process is to analyze the photographic data on the 2 grids, including modeling detection probabilities with landscape and puma covariates and to examine expected estimates of precision. We also will examine population closure and investigate methods for defining the survey area by using the GPS and VHF locations of pumas with functioning collars that used the camera grid areas. This information will be used to assess the feasibility of designing a camera grid specifically to obtain accurate and precise estimates of puma abundance and density on a portion of the Uncompahgre Plateau study area. This phase is expected to be completed by July 2011. Segment Objective 7 Data from 28 (8 male, 20 female) GPS-collared pumas, totaling over 48 thousand GPS locations (Table 20) will be used to examine behaviors and social structure of the puma population on the Uncompahgre Plateau, including movements of pumas relative to Game and Data Analysis Unit boundaries and vulnerability to hunter detection. Those data will also be used in a set of collaborative projects, including: examination of puma behavior in relation to human development with Mammals Researcher Dr. Mat Alldredge, who is studying puma-human interactions on the Colorado Front Range and modeling and mapping puma habitat in Colorado and other western states with Dr. Kevin Crooks and Dr. Chris Burdett (Department of Fish, Wildlife and Conservation Biology, Colorado State UniversityDFWCB, CSU). Furthermore, puma population and genetic data from the Uncompahgre Plateau can be used in collaboration with Dr. Alldredge’s puma research efforts on the Front Range to examine similarities or differences in puma population dynamics and behaviors between the 2 environments. 118 �SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 5.7 years of effort 125 pumas have been captured, sampled, marked, and released. Of those animals, 107 were radiomonitored, allowing us to monitor fates of pumas in all sexes and age stages, including: 25 adult females, 13 adult males, 4 subadult females, 7 subadult males, 32 female cubs, 39 male cubs (some individuals occur in more than one age-stage). Data from the marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CDOW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CDOW wildlife biologists and managers for assessing puma harvest strategies. The first year of the 5-year treatment period was August 2009 to July 2010 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CDOW puma management assumptions. The puma harvest quota for TY2 will be 8 independent pumas, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes on life stages and sexes. Furthermore, we will continue collaboration efforts with colleagues on investigations of puma population parameter estimation, pumahuman relations, puma habitat modeling and mapping, and individual puma detection rates in camera grid designs. All of these efforts should enhance the Colorado puma research and management programs. 119 �LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. Colorado Division of Wildlife. 2007. Colorado mountain lion management data analysis unit revision and quota development process. Colorado Division of Wildlife, Denver. Conover, W. J. 1999. Practical nonparametric statistics. John Wiley & Sons, Inc., New York. Cooch, E., and G. White. 2004. Program MARK- a gentle introduction, 3rd edition. Colorado State University, Fort Collins. Culver, M., W. E. Johnson, J. Pecon-Slattery, and S. J. O’Brien. 2000. Genomic ancestry of the American puma (Puma concolor). The Journal of Heredity 91:186-197. Currier, M. J. P., and K. R. Russell. 1977. Mountain lion population and harvest near Canon City, Colorado, 1974-1977. Colorado Division of Wildlife Special Report No. 42. Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and cause specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674. Karanth, K. U., and J. D. Nichols. 2002. Monitoring tigers and their prey: A manual for researchers, managers and conservationists in tropical Asia. Centre for Wildlife Studies, Bangalore, India. Koloski, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2009. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O’Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. 120 �Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 121 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Table 2. Pumas harvested by sport-hunters in Treatment Year 1 (TY1) on the Uncompahgre Plateau Study Area, Colorado, November 16 to December 11, 2009. Puma sex/age/mark M (cub of F25) M Age (yr.) 1.25 2-3 11/21/2009 F 4 12/9/2009 F 1.5-2 12/9/2009 M 4 M 4 12/9/2009 F (lactating) M 2 12/11/2009 M 2-3 7 Previous I.D. M91 M71 M51 Date of kill Location/UTM Hunter/status 11/17/2009 Pleasant Valley/ 13S,247640E,4228470N Little Bucktail Creek/ 12S,726165E,4240290N San Miguel Canyon/ 12S,732268E,4234711N Pinyon Ridge/ 13S,256380E,4241740N Spring Creek/ 12S,762033E,4248487N Horsefly Canyon (E)/ 13S,249114E,4240143N Roubideau Canyon/ 12S,746670E,4254762N Shavano Valley/ 12S,761117E,4256800N Mailbox Park/ 12S, 726524E,4234984N Jack Flowers/ Resident Ty Spangler/ Resident Larry McPeak/ Non-resident M. Ryan Hatter/ Resident Caleb Marquardt/ Resident Darren Reed/ Resident Brian Coe/ Non-resident Darrel Moberly/ Resident Donald Gambril/ Non-resident 12/9/2009 12/11/2009 12/11/2009 122 �Table 3. Five other independent pumas from the Uncompahgre Plateau Study Area killed by hunters off of the study area. Four adult pumas– F110, M27, M29, M100– were in the minimum count on the study area in winter 2009-10.a Adult male M1 probably no longer ranged on the study area. Puma sex/age/mark M29/adult Date of kill 11/16/2009 Place of kill/UTM Hunter/status Beaver Creek (GMU70east) Syver Bicknase/ 12S,745500E,4219660N Resident M27/adult 12/9/2009 N. Fork Mesa Creek (GMU61north) Kevin Thornton/ 12S,693422E,4266607N Non-resident M1/adult 1/2/2010 West Bang’s Canyon (GMU40) Outfitter Steve Biggerstaff 12S,710656E,4314243N M100/adult 1/16/2010 Naturita Canyon Outfitter Wade Wilson 12S,734604E,4216634N F110/adult 2/25/2010 Naturita Creek Alex Sokolik/ 12S,721010E,4230929N Resident a All five adult male pumas with non-functioning (4) or shed (1) radiocollars were killed during TY1 either on (M51, M71) or off (M1, M27, M29) of the UP Study Area. Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010, Uncompahgre Plateau study area, Colorado. Study Area Adults Subadults region Female Male Female Male East slope 16 10 1 1 West slope 14 10 0 3 subtotals 30 20 1 4 Total Independent Pumas = 55, including 31 females, 24 males Female 1 3 4 Cubs Male 4 3 7 Unknown sex 4-8* 5-6 9-14 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 123 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 1 (TY1) on the Uncompahgre Plateau Study Area, Colorado, November 16 to December 11, 2009. Data are from puma hunter responses in 71 voluntary surveys, including: 43 original surveys on mandatory permits and 28 telephone contacts with hunters that did not return surveys on permits. Total response rate from 79 individual hunters was 90% (71/79 = 0.899*100). Puma sex/age stage/mark F/adult/none Date of capture 12/1/2009 Capture location Hunter name Preston Joseph 12/8/2009 N. Fork Cottonwood Creek N. Fork Cottonwood Creek DeVinney Canyon F/adult/F8 collar & eartag M/subadult/ yellow eartags in both ears (numbers not distinguished) F/adult/F74 orange eartags 12/7/2009 12/9/2009 Cottonwood Creek 11/30 to 12/7/2009 11/30 to 12/7/2009 Loghill Mesa, Fisher Creek area Loghill Mesa, Fisher Creek area Larry McPeak, guided by Stan Garvey Zachary Prock & Dustin Braiser Zachary Prock F/adult/none M/subadult/none 12/11/2009 Big Bucktail Canyon Brian Hibbert F/adult/F8 collar & eartag 11/23 to 12/11/2009 N. Fork Cottonwood Creek Gerald Sickels, Jr. F/adult/none 11/23 to 12/11/2009 East of Nucla Gerald Sickels, Jr. F/adult/none 11/23 to 12/11/2009 Pinyon, Cottonwood Creek Gerald Sickels, Jr. M/subadult/yellow eartag 11/23 to 12/11/2009 San Miguel Canyon below Pinyon Gerald Sickels, Jr. M/adult/none 11/23 to 12/11/2009 Mailbox Park Gerald Sickels, Jr. M/adult/none 11/23 to 12/11/2009 Dead Horse Mesa Gerald Sickels, Jr. F/adult/none Late 11/2009 Pinyon Ridge Micah Brogden F/adult/none 124 Ryan Weimer Gary Gleason Reason for releasing the puma given by hunter Did not want to kill a female puma. Outfitter R. Weimer did not want hunter to kill a female puma. Did not want to kill a small male puma. Estimated ~125 lb. Did not want to kill a female. L. McPeak later in same day killed another adult female puma. Hunters will not kill a female puma.* Will not kill a female puma. *These 2 females treed ~4 days apart. One seemed younger than the other, so thought to be different females. But, could have been same puma. Did not want to kill a small male puma. B. Hibbert estimated puma about 1.5 years old. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a small male. Wants to kill a big male puma. Likes to look at the pumas and train his dogs. Does not want to kill an average male. Wants to kill a big male puma. Likes to look at the pumas and train his dogs. Does not want to kill an average male. Wants to kill a big male puma. Not interested in killing any puma. Likes to hunt pumas with dogs. �Table 6. Summary of puma capture efforts with dogs from December 15, 2009 to April 30, 2010, Uncompahgre Plateau, Colorado. Month December No. Search Days 10 No. & type of puma tracks founda,b 27 tracks: 12 male, 15 female, 0 cub Tracks ≤1 day old: 5 male, 8 female, 0 cub No. & type of pumas pursued 10 pursuits: 4 males, 6 females , 0 cubs January 20 80 tracks: 24 male, 35 female, 21 cub Tracks ≤1 day old: 11 male, 15 female, 10 cub 23 pursuits: 7 males, 10 females, 6 cubs February 22 77 tracks: 19-20 male, 36-37 female, 20 cub; 1 unknown sex Tracks ≤1 day old: 11 male, 24 female, 12 cub 36 pursuits: 7 males, 17 females, 12 cubs March 23 58 tracks: 16 male, 26 female, 16 cub Tracks ≤1 day old: 7 male, 14 female, 10 cub 18 pursuits: 4 males, 8 females, 6 cubs April 19 No. & I.D. or type of pumas captured, observed, or identified 2 pumas captured 3 times: F3 recaptured (nonfunctioning GPS collar replaced). One adult male puma ~2-3 yr. old captured twice, but not handled due to dangerous trees. In addition, adult F93 associated once with tracks by VHF telemetry (no pursuit with hounds). 6 pumas captured 9 times: M55 recaptured twice; F70 recaptured once; F111, F115, & F116 captured for first time. Then M115 & F116 recaptured. One adult male ~2-3 yr. old was captured, but not handled due to dangerous tree. In addition, 5 adult pumas were associated with tracks 6 times with VHF or GPS telemetry: M55 twice (VHF), F70 (GPS), F72 (GPS), F93 (VHF), F111 (GPS). 10 pumas captured 12 times: F23 recaptured 3 times, but in trees too dangerous for handling to replace her non-functional GPS collar. F28 recaptured in a tree too dangerous for handling to replace her non-functional GPS collar. M32 recaptured (VHF collar replaced). F72 recaptured (non-functional GPS collar replaced). Cubs F106, M107 & F108 recaptured (expandable radiocollars fitted on F106 & F108). M114, M117, F118 captured for the first time. In addition, 7 adult pumas were associated with tracks 9 times via VHF or GPS telemetry: M32 (VHF), F70 (GPS), F95 (VHF), F111 three times (GPS), F113 (VHF), F116 (VHF), F118 (VHF). 3 pumas captured: F96 and M115 recaptured. F119 captured for first time. In addition, 8 pumas were associated with tracks 16 times via VHF telemetry and/or GPS: F3 three times (GPS, VHF & GPS, VHF), M6 twice (VHF), M55 four times (VHF, GPS, VHF & GPS twice), F70 three times (VHF, GPS twice), cub M112 once (VHF), F93 once (VHF), F96 once (GPS), and cub M115 (VHF). 0 pumas captured physically, but F95 identified in one pursuit with VHF telemetry. In addition, 3 adult pumas associated with tracks with VHF telemetry: F93, F104, F118. 24 tracks: 11-12 male, 6 pursuits: 2-3 12-13 female, males, 3-4 females, 0 cub 0 cubs Tracks ≤1 day old: 3-4 male, 6-7 female, 0 cub 86 266 tracks: 93 pursuits: 21 individual pumas were captured 26 times with TOTALS 82-84 male, 24-24 males, aid of dogs. In addition, 16 radio-collared pumas 124-126 female, 44-45 females, were detected 38 times by tracks and identified 57 cub, 24 cubs with VHF and/or GPS telemetry. 1 unknown sex Tracks ≤1 day old: 37-38 male 67-68 female 32 cub a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day. The count was: 37 tracks of females, including 5 associated with cubs; 21 tracks of males; and 2 tracks of unspecified sex. 125 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2009 to April 2010, Uncompahgre Plateau, Colorado. Puma I.D. MA* MB* F111 M112 F113 M114 M115 F116 M117 F118 F119 Sex Estimated Age (mo.) 24-36 24-36 24-27 4.7 36 36 14 36-48 6 18-24 60-72 M M F M F M M F M F F Mass (kg) Unknown Unknown 35 10 47 63 39 49 12 38 46 Capture date 12-16-09 01-03-10 01-01-10 01/23/10 01/26/10 02-27-10 01-13-10 01-20-10 02-05-10 02-25-10 03-25-10 Capture method Dogs Dogs Dogs Cage trap Cage trap Dogs Dogs Dogs Dogs Dogs Dogs Location West Fork Dry Creek Basin East Fork Dry Creek Basin Cushman Canyon Horsefly Canyon (east slope) McKenzie Butte McKenzie Butte San Miguel Canyon San Miguel Canyon San Miguel Canyon Big Bucktail Canyon San Miguel Canyon * Pumas MA and MB were adult males that could not be handled because they climbed dangerous trees. Table 8. Pumas that were captured and observed with aid of dogs, or observed in association with another radio-collared puma, but were not handled at that time for safety reasons, December 2009 to April 2010, Uncompahgre Plateau, Colorado. Puma sex & I.D. Capture date Location Comments MA Age stage or months 24-36 12-16-09 West Fork Dry Creek Basin MB 24-36 01-03-10 East Fork Dry Creek Basin F23 72 02-23-10 San Miguel Canyon F23 72 02-24-10 Big Bucktail Creek F23 72 02-25-10 San Miguel Canyon F28 89 02-01-10 Tomcat Creek Puma climbed dangerous tree, not handled. No noticeable marks. Puma climbed dangerous tree, not handled. This puma obviously larger than MA (above). F23 climbed dangerous tree, not handled to change non-functional GPS collar. F23 climbed dangerous tree, not handled to change non-functional GPS collar. F23 climbed dangerous tree, not handled to change non-functional GPS collar. F28 climbed dangerous tree, not handled to change non-functional GPS collar. F28 was in association with M115, apparently her offspring. 126 �Table 9. Pumas recaptured with dogs, cage traps, or visually observed, November 2009 to May 2010, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date 12-23-09 Mass (kg) Not weighed Estimated Age (mo.) 101 M32 02-04-10 54 100 Capture Method/ Location Dogs/East Fork Dry Creek Basin Dogs/Dry Creek Basin F3 M55 11-06-09 70 66 Cage trap/Puma Canyon M55 01-07-10 Observed 68 Spring Creek Canyon M55 01-24-10 Observed 68 Linscott Canyon M67 02-24-10 73 31 Dogs/Tomcat Creek F70 01-19-10 Not weighed 63 F72 02-09-10 Observed 47 Dogs/Horsefly Canyon (east slope) Dogs/Loghill Mesa F94 05-13-10 Not weighed 58 F96 03-11-10 43 50 Cage trap/Pinyon Hills west of Happy Canyon Dogs/Happy Canyon F106 02-10-10 20 9 Dogs/Dry Park M107 02-24-10 Observed 9 Dogs/Spring Creek Canyon F108 02-24-10 20 9 Dogs/Spring Creek Canyon M115 01-21-10 Observed 14 Dogs/San Miguel Canyon M115 03-18-10 34 16 Dogs/North Fork Cottonwood Creek F116 01/21/10 Observed 36-48 Dogs/San Miguel Canyon 127 Process Non-functional GPS collar replaced. M32’s old VHF collar was replaced. M55’s old GPS collar was replaced. M55 was wearing a functional GPS collar. No need to handle. M55 was wearing a functional GPS collar. No need to handle. M67 fitted with VHF collar. Offspring of F30, born July 17, 2007. Non-functional GPS collar replaced. F72 wore functional GPS collar, no need to handle. F94’s VHF collar changed to GPS collar. F96’s old GPS collar was replaced. F106 fitted with expandable VHF collar. Offspring of F75, born May 7, 2009. M107 captured with sibling F108, offspring of F94, born May 25, 2009. F108 captured with sibling M107, offspring of F94, born May 25, 2009. F108 fitted with expandable VHF collar. Attempted to capture female puma with M115. Dogs got on M115’s tracks. M115 handled to examine draining wound to left foreleg that occurred about 1-2 weeks prior to this capture; cause unknown. Broken bone detected by palpation. Left ulna was broken (examined later at mortality 08/06/10). F116 wore functional VHF collar, no need to handle. �Table 10. Summary of puma capture efforts with cage traps from September 11, 2009 to May 17, 2010, Uncompahgre Plateau, Colorado.* Month September No. of Sites 2 Carnivore activity & capture effort results Set cage trap with mule deer and predator call box on east rim Roubideau Canyon 09-11-09 to 09-15-09. Adult female puma with 2 large cubs visited 09-13-09; clawed at deer carcass, but did not feed; clawed at call box. Puma family did not return. October 1 A non-collared puma (probably subadult or adult female) visited the fawn mule deer carcass 10-17-10, but did not feed (Reconyx camera photos). A black bear walked ~10 m from the carcass, but did not feed. Mule deer carcasses scavenged by bobcats and magpies. November 2 Cage trap set with catnip oil and K-9 call scent bait and predator call box and stuffed toy rabbit 11-03-09 to 11-06-09. Cage trap closed due to proximity of puma F72 to trap. Puma M55 was recaptured at a mule deer buck he killed 11-06-09. January 2 Set cage trap with mule deer buck killed by male puma 01-04 to 08-10. Male puma was treed by dogs on 01-03-10, but could not be safely handled in East Fork Dry Creek. Puma did not return to its deer kill and cage trap. Bobcat trapper inadvertently captured cub M112 in cage trap on west rim Horsefly Canyon 0123-10. M112 offspring of F70. February 2 A bobcat and Golden Eagle scavenged mule deer carcasses. March 12 Puma F94 and cubs walked with 10 m of a mule deer carcass with predator call box, but did not feed 03-29-10. A male puma walked by mule deer carcass with predator call box, but did not feed 03-18-10. A male puma scraped 2 m from mule deer carcass, but did not feed 03-2310. Puma F96 investigated a predator call box set about 10 m from a mule deer carcass and clawed the call box, but did not feed on the deer. April 6 Puma F94 and cubs M107, F108 consumed a mule deer carcass 04-03 to 07-10. A male puma scavenged a mule deer carcass sometime during 04-05 to 13-10, possibly M55. M55 scavenged from another mule deer carcass on 04-05-10. May 3 Cage trap set 05-13-10 with mule deer doe killed by a female puma in Pinyon Hills; recaptured F94. Tracks indicated a male puma walked ~15 m from 2 cage traps with call boxes and scent lures, but did not go to cage traps to investigate. * We used 21 road-killed mule deer at 17 different sites. Of the road-killed deer baits, 3 of 17 (17.65%) were scavenged by pumas. Table 11. Puma cubs sampled July 2009 to July 2010 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M112 M115 M117 M120 M121 P1016b P1017b M M M M M M M August 31, 2009 November 2008 August 2009 June 28, 2010 June 28, 2010 June 12, 2010 June 12, 2010 145 427 183 30 30 39 39 10 39 12 2.5 2.2 2.1 half eaten F70 F28 F119 F3 F3 F72 F72 52 68 66 107 107 51 51 Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Cubs P1016 and P1017 were monitored from birth via F72’s GPS data and visual of her nursery to the day of their death; but the cubs were not individually marked. Individual identification of non-marked pumas were designated with P one thousand series numbers (e.g., P1016). On the day we investigated F72’s nursery, male adult puma M32 was at the nursery; he had killed both cubs and half-consumed one about 3 to 6 hours before our arrival. 128 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2010, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Dec. 15, 2009 to April 30, 2010 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 86/93 = 0.92 day/pursuit 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/26 = 3.31 day/capture 86/9 = 9.56 day/capture 129 �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2010. Consort pairs and estimated agesa Dates pairs Estimated Estimated Estimated Observed consortedb birth datec birth interval gestation number of Female Age Male Age (mo.) (days) cubsd (mo.) (mo.) F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F2 89 05/19/08 22.0 4 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F3 84 M51 60 03/31/08 07/03/08 21.5 94 3 F3 107 M55 69 03/28-31/10 06/28/10 23.8 89-92 2 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F7 106 07/10/08 23.9 3 F8*e 24 06/26/05 2 F8 37 08/13/06 13.4 4 F8 60 M73 49 02/28-29/08 05/29/08 22.5 90-91 2 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F16 75 M6 80 01/13-14/09 04/15/09 22.7 91-92 3 F23* 21 05/30/06 3 F23 45 M27 or 78 02/19-25/08 05/23/08 23.8 87-93 3 M29f 107 F24 75 M29 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F25 110 08/19/08 16.1 2 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F28 68 11/08 1 F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F70 52 08/31/09 14.8 3 F72* 28 07/09/08 1 F72 51 06/12/10 23.1 2 F75 32 06/01/07 1 F75 55 M73 61 02/11/09 05/07/09 23.2 93 2 F93 56 08/07 2 F93 90 06/16/10 2 F94* 46 05/27/09 3 F94 60 M55 70 04/15/10 07/15/10 13.3 91 3 F104 110 07/08/10 1 F111* 32 06/16/10 ≥1 tracks F116g 36-48 2009 2 F119 66 08/09 2 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. 130 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2010, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 M51 04-26-06 to 07-31-10 01-07-07 to 03-20-09 M55 M67 M71 01-21-07 to 07-31-10 08-23-07 to 07-31-10 01-29-08 to 11-12-09 M73 M100 02-21-08 to 07-31-10 03-27-09 to 07-31-09 M114 02-27-10 to 06-23-10 F2 01-07-05 to 08-14-08 F3 F7 01-21-05 to 07-31-10 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-10 10-11-05 to 09-11-09 F23 02-05-06 to 02-25-10 F24 F25 01-17-06 to 09-03-08 02-08-06 to 09-04-09 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Alive. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Alive. Alive. M67 is offspring of F30. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-12-09. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Alive. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Lost contact– after 06-23-10. VHF collar may have failed or puma dispersed. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Lost contact− failed GPS/VHF collar. Dead. Killed by U.S. Wildlife Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Lost radio contact after12-02-09. Recaptured F23 on the study area 02-25-10, but could not be handled to replace non-functional GPS collar. Lost radio contact after 09-03-08− failed GPS/VHF collar. Lost radio contact after 09-04-09– failed GPS/VHF collar. 131 �Puma I.D. F28 Monitoring span 03-23-06 to 02-01-10 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 F72 F75 01-14-08 to 07-31-10 02-12-08 to 07-31-10 03-26-08 to 02-10-10 F93 F94 F95 F96 F104 F110 12-05-08 to 07-31-10 12-19-08 to 07-31-10 08-01-09 to 07-31-10 01-28-09 to 07-31-10 05-21-09 to 07-31-10 09-21-09 to 02-25-10 F111 F113 01-01-10 to 07-31-10 01-26-10 to 06-06-10 F116 F118 F119 01-20-10 to 07-31-10 02-25-10 to 07-31-10 03-25-10 to 07-31-10 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured on the study area 02-01-10, but could not be handled to replace nonfunctional GPS/VHF collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Alive. Alive. Lost radio contact after 09-29-09– failed GPS/VHF collar. F75 in association with her cubs M105 and F106 when F106 was recaptured on 02-10-10 on the study area. Alive. Alive. Alive. Alive. Alive. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Alive. Alive. Alive. 132 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 1 year in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Period of interest S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 8/1/2009 to 7/31/2010 Treatment Annualb 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. 133 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 7 190 M69 01-11-08 to 04-07-08 87 F95 12-29-08 to 07-31-09 214 M99 02-27-09 to 04-22-09 54 Status M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. F52 dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adultstage home range. GPS collar nonfunctional. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-0608 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. M99 died on unknown causes; but, possibly killed by another puma (holes in skull) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. 134 �Puma I.D. M115 Monitoring span 01-13-10 to 07-21-10 No. days 189 Table 16 continued. Status M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on Mar. 18, 2010, he had previously suffered a broken left ulna. M115 was probably independent by July15, 2010 when he was located outside of his natal area on a probably dispersal move. M115 died on about July 21, 2010 apparently from complications of his broken left foreleg; possibly not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. 135 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2010. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M39 09-11-06 M43 09-15-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 73.2 M65 08-17-07 M68 08-23-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,711262E, 4198681N Estimated linear dispersal distance (km)* 102.2 71.3 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 43 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61 North on 12-27-09 when he was 39 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a U.S. Wildlife Service agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 28 months old. 80.7 M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. 136 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M69 01-11-08 13S,248191E, 4246810N→ 13T,378900E, 4591990N M82 07-05-08 F52 01-10-07 12S,726901E, 4243463N→ 13S,255316E, 4216768N 13S,258058E, 4236260N→ 13S,319217E, 4240467N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 369.6 M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 60.5 M82 was offspring of F8, born May 2008. M82 was killed by a hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill or recapture site. 137 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2010. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 138 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N �Table 19. GPS- and VHF-collared pumas with functioning collars using two camera grids (Area 1Loghill, Area 2- Delores Creek to Spring Creek) during August 21 to December 7, 2009 (i.e., 108 days), Uncompahgre Plateau, Colorado. Area 1- Loghill Puma Sex Estimated Collar & Number of Capture rate per day for ID Age (mo.) data type detections by primary camera configuration Aug.-Dec. cameras in grid (photo per puma/no. days) 2009 primary/alternate cameraa F16 female 79-83 GPS 0 0 F72 female 41-45 GPS 4/0 4/108 = 0.04 M6 male 90-94 VHF 6/0 6/108 = 0.06 M55 male 50-54 GPS 7/0 7/108 = 0.06 Area 2- Delores Creek to Spring Creek Puma Sex Estimated Collar & Number of Capture rate per day for ID Age (mo.) data type detections by primary camera configuration Aug.-Nov. cameras in grid (photo per puma/no. days) 2009 primary/alternate camerab F70 female 52-56 GPS 0 0 F94 female 49-53 VHF 3/1 3/108 = 0.03 F96 female 43-49 GPS 2/0 2/108 = 0.02 M32 male 96-100 VHF 4/0 4/108 = 0.04 M55 male 50-54 GPS 19/5 19/108 = 0.18 a Aug. 21 to Nov. 2 (74 days) to detect 3 of 4 adult pumas with functioning collars for first time. Aug. 21 to Oct. 20 (61 days) to detect 4 of 5 adult pumas with functioning collars for first time. It took 88 days (Aug. 21 to Nov. 16) to also detect 2 adult pumas with non-functioning collars. b 139 �Table 20. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2010. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 08-09-10 3,226 adult 03-27-09 to 01-16-10 923 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 05-14-08 3,344 adult 02-24-05 to 08-03-08 3,922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 09-10-09 3,801 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 09-04-09 2,281 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 06-26-09 3,398 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 07-01-10 2,429 F72 F adult 02-12-08 to 07-07-10 2,842 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 08-08-10 1,061 F104 F adult 05-29-09 to 08-09-10 1,349 F111 F adult 01-01-10 to 08-02-10 488 F113 F adult 01-27-10 to 06-06-10 445 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 140 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Puma Habitat Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Methods for Monitoring Populations Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 141 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Expected No. Independent Pumas ~ 70 ml .i-0 "'E 40 :, "- 0 z .,n 20 In 0 RY4 T\'1 T\'2 T'/3 Year Figure 3. Expected (i.e., modeled) number of independent pumas on the Uncompahgre Plateau Study area after the harvest of 14.5% and 21.8% of independent pumas observed in the 2009-10 hunting season. The 14.5% harvest rate represents 8 independent pumas (3 females, 5 males) killed inside the study area. The 21.8% harvest represents 12 independent pumas (4 females, 8 males), including 4 pumas (1 female, 3 males) killed outside of the study area in addition to 8 killed inside the study area. The projected lines represent the expected population trends resulting from the observed harvest rates and sex structure. 142 �Age structure of independent pumas in November 2009 at beginning ofthe puma hunting season in Treatment Year 1, Uncompahgre Plateau, Colorado. 4 "' Ill E 3 ::J '.:: 2 0 1 0 z >--- - - - f- II 0 I ■ Female I ■ Male lto 2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age {years) Figure 4. Estimated age structure of independent pumas in November 2009 at the beginning of the puma hunting season in Treatment Year 1 (TY1) on the Uncompahgre Plateau, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 4.55 ± 2.11 yr. (54.63 ± 25.29 mo.), n = 19; 5.48 ± 2.57 yr. (65.71 ± 30.88 mo.), n = 14. Puma births, Uncompahgre Plateau, Colorado 10 9 8 7 6 5 4 3 2 - 1 11 0 Jan. I I Feb. M ar. Apr. - - - ~ f- M ay June July ■ Births 2005-2010 IT H1 Aug. Sep. Oct. 11 Nov. Dec. ■ Bi rths 1982-1987 Figure 5. Puma births (black bars) detected by month during 2005 to 2010 (n = 34 litters of 17 females; 32 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 143 �2 AREAS FOR CAMERA GRIDS Montrose N A 0 2.5 5 1O Kilometers Figure 6. Layout of 2 camera grids on the east slope of the Uncompaghre Plateau Puma Study Area. Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. Area 1 was the south grid that covered Loghill Mesa to upper Horsefly Canyon. Area 2 was the north grid that covered from Dolores Canyon to Spring Creek Canyon. 144 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death ~8-1-04 F9 31 5-28-05 F10 31 5-28-05 ~1,345 F3 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4.5 years old. Lost contact― shed radiocollar 04-19-06 to 04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified) about 828-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 M11 31 5-28-05 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 F13 42 5-19-05 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 F21 37 9-26-05 Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 176-215 918 203-252 101 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 324 145 Mother I.D. F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 Est. Birth date F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 43 months old. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed 0301-07. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 01-28-09 in GMU 41 when 29 months old. F7 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 146 Mother I.D. F23 F23 F28 F2 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 ~456 42 ~428 subad. 147 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61 when 39 months old. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61 N) 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. Mother I.D. F7 F7 F3 F3 F3 F50 F54 �Appendix A continued Puma I.D. Estimated Age at capture (days) M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 200 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F7 (?) Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 28 months old. F16 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 148 F25 F16 F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. 111 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 30 5-19-08 03-12-08 to 07-09-08 06-18-08 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 149 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 F23 �Appendix A continued Puma I.D. Estimated Age at capture (days) F81 40 F97 8 ½ mo. 5-23-08 5-23-08 M82 37 M83 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-02-08 to 07-29-09 02-04-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 424 354 F23 F23 5-29-08 07-05-08 to 03-20-09 or 04-02-09 295-308 37 5-29-08 07-05-08 M84 36 6-5-08 07-11-08 to 02-11-09 Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 19 months old. Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F85 36 6-5-08 07-11-08 F70 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 M87 M88 F89 M90 Male 7A 28 28 28 36 28-35 7-3-08 7-3-08 7-3-08 7-9-08 7-10-08 07-31-08 07-31-08 07-31-08 08-14-08 ~08-07-08 to 08-14-08 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Not radio-collared. Radio-collared Radio-collared Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. 251 ~48-59 28 to 35 150 Mother I.D. F8 F8 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 35 F95 16 mo. Est. Birth date Age to last monitor date alive or at death (days, birth to fate) 8-19-08 8-19-08 June-07 Est. survival span from 1st capture to fate or last monitor date 09-29-08 09-29-08 12-29-08 Sep-Oct08 Sep-Oct08 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 05-20-09 to 09-19-09 05-20-09 157 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 03-16-10 159 241 F98 4-5 mo. M99 5 mo. M101 35 4-15-09 M102 35 4-15-09 F103 35 4-15-09 M105 38 5-7-09 F106 38 5-7-09 M107 34 5-25-09 F108 34 5-25-09 M109 M112 34 145 5-25-09 8-31-09 06-28-09 to 02-24-10 06-28-09 to 03-05-10 06-28-09 05-04-10 M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 275 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 6-12-10 06-12-10 to 07-21-10 39 488 278 275 250 246 151 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Radio-collared. Radio-collared. Survived to adult stage. Established adult home range overlapping F93’s home range. Radio-collared. Died, probably killed by male puma (infanticide). Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Cause of death unknown, possibly killed by another puma. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 9-4-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 2-9-10 due to shed collar. F25 F25 F93 Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. Not radio-collared; too small. Recaptured 2-24-10; not collared. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. F75 Unm.F Unm.F F16 F16 F16 F75 F94 F94 F94 F70 F28 F119 F72 F72 �Appendix A continued Puma I.D. Estimated Est. Est. survival span Age to last monitor date Status: Alive/Survived to subadult stage/ Mother Age at Birth from 1st capture to alive or at death (days, Lost contact/Disappeared/ I.D. birth to fate) capture date fate or last monitor Dead; Cause of death (days) date M120 30 6-28-10 07-28-10 Radio-collared. F3 M121 30 6-28-10 07-28-10 Radio-collared. F3 M122 35 7-8-10 08-12-10 Radio-collared. F104 F123 29 7-15-10 08-13-10 Radio-collared. F94 F124 29 7-15-10 08-13-10 Radio-collared. F94 M125 29 7-15-10 08-13-10 Radio-collared. F94 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement 152 �Colorado Division of Parks and Wildlife July 2010 –June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Federal Aid Project No. Period covered: July 31, 2010−June 30, 2011 Author: K. A. Logan. Personnel: K. Logan, A. Butler, B. Dunne, W. Hollerman, C. Jacobs, W. Jesson, J. Knight, B. Nay, R. Navarrete, J. Waddell, S. Waters, T. Bonacquista, K. Crane, J. Koch, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, yrs 1-5) and presence (treatment period, yrs 6-10) of hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Parks and Wildlife’s model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report informs on the second year of the treatment period (TY2), August 2010 through July 2011, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 22 and closed December 12, 2010 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 8 pumas were killed: 2 subadult females, 5 adult males, and 1 subadult male. The harvest of 8 independent pumas represented 15.4% of the 52 independent pumas in our minimum count during November 2010 to April 2011. Independent females and males comprised 25.0% and 75.0% of the harvest, respectively. Three other radio-collared independent pumas in the study area population were killed during the Colorado puma hunting season; 2 adult females killed on the study area for depredation control and 1 adult male in a GMU adjacent to the study area. The total mortality of 11 independent pumas during the hunting season represented 21.2% of the minimum count of independent pumas. Eight independent pumas will be the harvest quota for the 2011-12 hunting season (TY3), based on an expectation of a stable-to-increasing population. Sixty-four hunters requested mandatory permits with an 177 �attached voluntary hunter survey in TY2. Fifty-four of the hunters provided responses to written (n = 42) or telephone call follow-up contact (n = 12). An estimated 42 hunters actually hunted on the study area, of which about 19% harvested pumas and 38% captured pumas (i.e., harvested plus treed and released). Thirty-three hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks < 1 day old encountered by hunters and pumas captured by hunters indicated that independent female pumas were more vulnerable than males to detection by hunters. From August 2010 to July 2011 54-55 individual pumas were captured 70 times. Two capture teams with dogs operated over 81 search days from November 16 and December 14, 2010 through April 22, 2011 to find 291 puma tracks, pursue pumas 99 times, and capture 36-37 pumas 52 times. Capture efforts with cage traps resulted in the capture of 1 adult male and 1 subadult male for the first time and the recapture of 2 adult female pumas. Fourteen cubs were observed for the first time at nurseries. A total of 53 pumas were monitored by radiotelemetry in TY2. Search efforts also revealed the presence of at least 15 other independent pumas. Our minimum count of independent pumas from November 2010 to April 2011 was 52, including 35 females and 17 males. A preliminary minimum estimated density of independent pumas was 3.11/100 km2. The proportion of radio-collared adult females giving birth in the August 2010 to July 2011 biological year was 0.56 (9/16). Six litters that could be dated to month of birth were produced in April (2), July (2), and August (2). Since 2005 a birth peak has occurred from May through August, involving 80% of nursling litters. We monitored 19 female and 9 male adult radio-collared pumas for survival and agent-specific mortality. Survival rates in TY2 for adult females were within the range during the reference period, but substantially lower for males. Causes of mortality were hunting and depredation control. One subadult female was killed and eaten by a male puma during competition for an elk carcass. Of 23 cubs monitored with radiotelemetry, 6 died, 3 from natural causes (including 2 infanticide and cannibalism) and 3 from depredation control. A non-marked female cub was also killed by a vehicle on the boundary of the study area. Puma harvest, capture, and radiotelemetry data provided information on dispersals of 26 pumas initially marked on the study area. Those pumas moved from about 20 to 370 km from initial capture sites. We explored the feasibility of attracting pumas to rub stations to obtain tissue non-invasively for potential use in a genotype markrecapture structure for estimating abundance. Nine sites with trail cameras, rub devices, and 6 scents produced 39 puma visit events. Puma behavior toward the scents was highly variable. Beaver castorium produced the highest maximum detection probability. Data continue to be gathered for other collaborative projects with Mammals Research and CSU investigators on puma behavior, social organization, population dynamics, and habitat use. 178 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the first year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the second year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and age-stage survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore feasibility of attracting pumas to a rub station and obtaining tissue for potential use in a noninvasive genotype mark-recapture structure. INTRODUCTION Colorado Parks and Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). 179 �● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the gray-shaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CPW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 will involve the use of controlled recreational hunting to manipulate the puma population. 180 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CPW 2007). H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of 181 �greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2008). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics relative to harvest. We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment 182 �period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1982, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area highly accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) 183 �involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for at least the past 100 years. Hence, the reference period, years 1―5, provided conditions where individual pumas in this population (of estimated sex and age structure) expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. 184 �Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were 185 �restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. 186 �We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s 187 �rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2010 to July 2011, was the second year of the treatment period (TY2) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 22, 2010 and was scheduled to extend to January 31, 2011, unless the harvest quota was taken before then. The design harvest quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This design harvest tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (Assumption and Hypothesis 3 p.5 this report). The initial quota of 8 pumas for TY1 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY2 was based on the observed minimum count of 55 independent pumas during September 2009 to April 2010 in TY1 and that approximately the same number of independent pumas were expected during the puma hunting season for TY2 (an expectation consistent with our observed minimum count of 52 independent pumas for TY2, see later in Segment Objective 2). The hunting structure in TY2 was the same as in TY1. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). All pumas harvested on the study area were examined by principal investigator K. Logan or a wildlife research technician and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon inspection data were recorded on the puma harvested, including: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 22 to December 12, 2010, taking 21 days to fill the quota of 8 pumas. This was 5 days less than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Eight pumas were killed, including: 2 subadult females, 5 adult males, and 1 subadult male (Table 2). Of the 8 harvested pumas, 4 were marked: M32, M55, M90, and F108. In addition to the pumas killed on the study area during the Colorado puma hunting season, adult 188 �male M133 was killed by a hunter in north GMU62 and adult females F25 and F94 were killed for depredation control reasons on the study area (Table 3). The harvest of 8 independent pumas on the study area was 15.4% (8/52*100) of the minimum count of 52 independent pumas, including 31 females and 24 males, determined by the research team during November 2010 to April 2011 (Table 4). Independent females and males comprised 25.0% (2/8*100) and 75.0% (6/8*100) of the harvest, respectively. This harvest structure was 5.7% (2/35*100) of the independent females and 35.3% (6/17*100) of the independent males. Considering the mortality of 3 other radio-collared adults (F25, F94, M133, Table 3), a harvest of 11 independent pumas was 21.2% (11/52*100) of the minimum number of independent pumas. The harvest composition of 4 females and 8 males was comprised of 36.4% (4/11*100) females and 63.6% (7/11*100) males. This harvest structure was 11.4% (4/35*100) of the independent females and 41.2% (7/17*100) of the independent males in the minimum count. The minimum count of 52 independent pumas in TY2 was slightly lower than the minimum count of 55 independent pumas in TY1 (Table 4). Minimum count TY2 = 52 independent pumas, including 35 females and 17 males. This count reflected the relatively high adult female survival rate and low adult male survival rate in TY1 (Logan 2010). Because the harvest quota of 8 independent pumas in TY1 resulted in a minimum count of 52 independent pumas in TY2 and is expected to result in a stable-toincreasing population trend, we decided to set the quota to harvest 8 independent pumas in the TY3 (2011-12) hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population might be killed outside of the study area as in the TY1 and TY2 hunting seasons (Fig. 3). It is still too early in this research to tell if this harvest structure is resulting in a declining, stable, or increasing population trend. Hunter permits and survey: In TY2 mandatory permits with the voluntary survey attached were requested by 64 individual hunters, down from 79 individual hunters in TY1. Seventeen of the hunters requested a second permit after the first one expired after 14 days. Fifty-four hunters (84.4%) provided responses to the voluntary survey either by turning in the printed survey (n = 42) or providing information during follow-up telephone calls (n = 12) by principal investigator K. Logan. The remaining 10 hunters could not be contacted because either they did not have working phone numbers or they did not return calls. Of the respondents, 19 hunters indicated that they did not hunt on the study area. The proportion of the 54 respondents that hunted extrapolated to the total of 64 hunters (35/54 = 0.648) indicated that about 42 hunters took to the field for pumas on the study area during the 21-day hunting season. This was down from 67 hunters that probably hunted in TY1 (Logan 2010). Considering that 42 hunters were estimated to be afield, then 19% of the hunters harvested pumas (8/42*100) and 38% of hunters captured pumas (16/42*100; see captured and released pumas below and in Table 5). The 42 puma hunters that turned in the written volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 33 respondents. Of the remaining 9 hunters, 5 did not answer the question because they indicated that they did not hunt on the study area and 1 was an outfitter that did not hunt on the study area for himself (i.e., he hunted for his clients). One hunter indicated he was nonselective, and he killed a subadult female puma. Another hunter that did not answer the question killed a subadult female puma, too. The volunteer hunter survey also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 8 times, including 7 females and 1 subadult male. Of the 7 females 6 were described as adult, including 1 with at 189 �least 1 cub. Two of the adult females were marked with GPS collars (F3, F96). One female was either an adult or subadult. Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex, reproductive status, and size (Table 5). In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to tracks that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters responses showed they encountered 30 puma tracks less than one day old. Of those, 20 tracks were of females, and 10 tracks were of males, indicating that during the hunting season females are more detectable than males by a ratio of 2:1, and similar to the sex structure of independent pumas in the minimum count on the study area which was 35 females and 17 males (ratio 2.06:1, Table 4). Of the female tracks, 3 female pumas were pursued by hunters with intent to harvest, of which 2 females were actually killed. Seventeen hunters indicated they did not pursue female tracks with intent to harvest; but, hunters captured and released 7 female pumas. Of the male tracks, 7 were pursued by hunters with intent to harvest, of which 6 were actually killed. Three hunters indicated they did not pursue to harvest 3 male tracks; but, 1 subadult male puma was captured and released. These preliminary survey and harvest data for TY2 indicate independent females were captured by hunters slightly more frequently than independent males by 9 to 7 (i.e., females = 2 harvested + 7 captured and released; males = 6 harvested + 1 captured and released). Moreover, hunters are choosing to kill males more frequently than females. This result is consistent with TY1 where hunters caught females slightly more frequently than males (i.e., 12 females, 10 males; females = 3 harvested + 9 captured and released; males = 5 harvested + 5 captured and released). Also in TY1, hunters indicated a preference to harvest males over females. This preliminary assessment from years TY1 and TY2 puma harvest and hunter survey data suggests that most hunters that captured pumas were selective and influenced harvest sex and age composition and that independent female pumas were detected by hunters at a higher rate than were independent male pumas. Segment Objective 2 After the design quota was filled, puma research teams immediately activated for capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring 2010-11. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 70 puma captures of 54 to 55 individuals from August 2010 to July 2011 (Tables 6-11); 36 to 37 individual pumas were captured with dogs 52 times. Four pumas were captured in cage traps. Cubs were captured at nurseries 14 times. A total of 53 pumas were monitored with radio-telemetry from August 2010 to July 2011 (some of these had been collared in previous years). Trained dogs were used as our main method to capture, sample, and mark pumas on November 16, 2010 and from December 14, 2010 to April 22, 2011. Those efforts resulted in 81 search days, 291 total puma tracks detected of which 157 were ≤1 day old, 99 pursuits, and a total of 52 puma captures of 36-37 individual pumas (Table 6). This was the second year we deployed 2 fully-staffed hound capture teams in the treatment period. Search days with dogs was similar in both TY1 (86) and TY2 (81; Table 12). The frequency of tracks (tracks/day) encountered was higher in TY2 than the previous 6 winters. 190 �Also, pursuits increased over all previous years by 6 to 58, with the lowest number of pursuits occurring in the first year of this study (2004-05) when the puma population was probably at its lowest abundance on the study area. The capture rate was also the highest by 26 to 38 captures. Increased capture efforts and captures were probably the result of using 2 fully-staffed relatively more efficient houndsmen teams in TY2 even though the puma population had been reduced due to harvest just before our capture operations. Researchers in the two hound capture teams on November 16, 2010 and from December 14, 2010 to April 22, 2011 also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected by houndsmen. The count was: 47 tracks of females, including 11 associated with cubs; 21 tracks of males; 4 tracks of cubs, and 1 track of unspecified sex. Except for 1 female and 1 male track ≤ 1 day old found on November 16, 2010, all other tracks ≤ 1 day old were found after the TY2 puma hunting season when 6 independent males and 2 independent females were harvested. Therefore, the harvested pumas were not present to make tracks for our researchers to observe. The loss of the 6 males and 2 females may reflect the slightly higher ratio of female:male tracks post-hunting season, 2.2:1 than was reported by hunters during the hunting season, 2:1 (previously, Segment Objective 1). Still, the ratios are similar and reflect the greater likelihood of encountering females than males. Puma capture efforts using ungulate carcasses and cage traps was sporadic from November 8, 2010 to April 18, 2011 (Table 10). We used 12 road-killed mule deer at 10 different sites. Two independent male pumas (M133, M153) were captured for the first time, and 2 adult females (F70, F137) were recaptured and re-collared. Pumas scavenged at 5 of 12 (41.66%) sites where deer carcasses were used for bait. We sampled 24 cubs, including 10 females and 14 males (Table 11). Nine females and 14 males were captured by us, of which 21 (7 females, 14 males) were radio-collared to monitor survival and agent-specific mortality (Appendix A). Female cub P1026 was sampled with a bio-dart only because she climbed a dangerous tree. Another female cub, P1030, was found dead, hit by a vehicle on state highway 62 in Leopard Creek. In addition to our direct puma captures with dogs November through April, we detected 18 radiocollared pumas that we were able to identify with GPS or VHF telemetry 28 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. Our search efforts throughout the study area from December 2010 to April 2011 also revealed the presence of at least 13 other independent pumas, which we classified as 9 females and 4 males. Three females and 2 males were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). Of those, 2 females and 2 males were sampled with biodarts to obtain a tissue sample for genotyping the individuals. We could separate the activity of the other pumas from the GPSand VHF- collared pumas in time, space, and track size differences between females and males. One puma might have been F75 with a non-functional GPS collar. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to distinguish 4 adult females followed by 1 to 2 medium-to-large-size cubs. Some tracks we found of these pumas were too old to pursue (i.e., 2+ days old; probability of capture with the dogs was negligible). 191 �Our search and capture efforts during November 2010 through April 2011 and information from the puma hunting season in TY2 enabled us to quantify a minimum count of 52 independent pumas detected on the Uncompahgre Plateau study area, including 35 independent females and 17 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or treed and released by hunters on the study area, and puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars. The estimated age structure of independent pumas in November 2010 at the beginning of the puma hunting season in TY2 on the Uncompahgre Plateau study area is depicted in Figure 4. In addition to the independent pumas, we also counted a minimum of 39 cubs. Of the 52 independent pumas, 36 to 37 (69-71%) were marked and 15 to 16 (29-31%) were assumed to be unmarked animals. The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 25 independent pumas (18 females, 7 males). The west slope count included 27 independent pumas (17 females, 10 males). Considering the minimum count of 52 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 3.11 independent pumas/100 km2. Segment Objective 3 During the past 6.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). In TY2 we directly observed 6 litters in nurseries which were born in April (2), July (2), and August (2) 2010, each with 1 to 4 cubs, born to radio-collared females. Data on reproduction we observed in TY1 and TY2 were added to Table 13 which gives the reproductive chronology and information on mates of reproducing females. But those data will not be summarized again until the end of the treatment period. The proportion of radio-collared adult females giving birth from August 2010 to July 2011 biological year (TY2) was 0.56 (9/16), similar to TY1 (0.53, 8/15). Considering our 38 total observed litters with cubs 26 to 42 days old and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females (the latter include F111’s cubs caught later when 8.5 months old) (Table 13), the distribution of puma births by month since 2005 indicate births extending from March into September (Fig. 5). Births peak during May, June, July, and August involving 80% of the births (Fig. 5). The data indicate that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 1982-1987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions in the reference and treatment periods separately. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2011, we radio-monitored 19 adult male and 30 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). Preliminary adult puma survival for TY1 and TY2 are also shown in Table 15. So far, adult male survival is substantially lower in the treatment period than in the reference period and adult female 192 �survival may be similar in both periods. These characteristics may be indicative of hunter selection for male pumas (previously in Segment Objective 1). But, no conclusions should be drawn with results from only 2 years in the treatment period. The primary research interests include how survival rates influence population growth rates and the strength of factors associated with survival and mortality. This is what ultimately allows us to evaluate the effect of a 15% harvest level on independent pumas for our population management assumptions when the goal is a stable to increasing population. Human-related causes of mortality dominated deaths of marked adult pumas in TY2, including: sport-hunting harvest (4 males- M32, M55, M90, M133) and depredation control (1 male- M134; 2 females- F25, F94) (Table 14). We have radio-monitored 19 pumas, including 6 females and 13 males, in the subadult age-stage (independent pumas <24 months old) (Table 16). Four died before reaching adulthood, indicating a preliminary finite survival rate of 0.789 (i.e., 15/19). All 4 subadults apparently died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old; punctures to his skull were consistent with canine bites from another puma and suggested intra-species strife as cause of death. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. F143 was killed and eaten by a male puma while in competition for an elk carcass that one of the pumas killed. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Harvest data along with our capture and radiotelemetry data provided additional information on fates of 26 marked pumas, 22 males and 4 females. Of those, 21 (2 females, 19 males) were initially captured and marked as cubs, and 5 (2 females, 3 males) were captured and marked as subadults on the Uncompahgre Plateau puma study area (Table 17). Twenty males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she probably established an adult home range there. Three males marked initially as cubs born on the study area (M67, M87, M92) dispersed from their natal ranges and were recaptured as adults on the study area. All were born on the east slope of the Uncompahgre Plateau and moved to the west slope. These pumas represent dispersal moves on and from the Uncompahgre Plateau. Eighteen of the 26 pumas had reached adult ages ranging from 24 to 55 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53.. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY2 we monitored the fates of 23 radio-collared cubs (Appendix A). Six of the cubs (3 females, 3 males) were known to have died. Three cubs with their mother F94 were killed for depredation control to protect a commercial domestic elk operation. Three other cubs died of natural causes. M130 died from a cause associated with injury to his right shoulder during the first move away from his nursery with F96 and 3 other siblings. Two cubs, M139 and F148 (offspring of F8), died of infanticide and cannibalism by a female or subadult male puma. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. 193 �In addition, a non-marked female puma cub was struck and killed by a vehicle on state highway 62 in Leopard Creek on the south boundary of the study area on February 16, 2011. This mortality made the thirteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 13 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Thirty-two adult pumas (23 females, 9 males) have worn GPS collars since this project began in 2004 (Table 19). Over 55 thousand GPS locations have been obtained for studies on puma behavior, social organization, population dynamics, movements, habitat use and puma-human relations in collaboration with colleagues in Mammals Research and Colorado State University. Segment Objective 6 As an extension of our pilot puma camera grid project in 2009 (Logan 2010), we decided to explore the feasibility of attracting wild pumas to a rub station to obtain tissue non-invasively for potential use in a genotype mark-recapture structure for estimating abundance. Our question was basic to such a structure. What might be expected detection probabilities for wild pumas at scent/rub stations? This work operated on minimal resources consisting of 9 trail cameras, opportunistically available scents, and the field work was done primarily by volunteer Linda Sweanor. Thus, we consider this work exploratory to inform how we might continue in future efforts. Our approach was simple, reflecting available resources. We placed cameras and scent stations with hair capture devices at sites where we thought we could maximize encounters with pumas. Cameras were Reconyx ™ with passive infrared motion detectors and night time infrared illumination each set to take photos each second after the camera was triggered. Our previous approach to locating stations using only trail cameras in a grid resulted in very high detection probabilities of marked pumas during our pilot camera grid project in 2009 (Logan 2010). This allowed us to photographically record behavior of pumas at scent/rub stations. Scents used included: beaver castorium, catnip oil, MT Lynx ™, Obsession for Men ™, Spotted Fever ™, and one combination of catnip oil and Spotted Fever™. Scent/rub stations, camera operation, and camera digital data were examined at approximately 2 to 4 week intervals. At those times, each rub pad (i.e., rub device and carpet swatch) was treated with a different available scent if a puma had visited the scent/rub station and regardless of the puma’s response to the scent/rub station. If no pumas visited the rub/scent station, then the carpet swatch was re-treated with the same scent used the previous weeks. Our aim was to expose as many individual pumas as possible to different scents and record their behaviors. We defined the sampled population of pumas to include only those pumas recorded by the cameras. All pumas photographed passed ≤5 m of the scent/rub station. We defined a maximum detection probability for a particular scent as the number of individual pumas that were photographically recorded at scent/rub stations with a particular scent that rubbed and deposited hair that could be collected divided by the total number of individual pumas that were photographically recorded at scent/rub stations with a particular scent. We did not have resources to attempt to assess quality of the DNA and individual puma genotype accuracy; thus, detection was considered to be maximum for this exploratory assessment only. In addition, this design did not consider other pumas in the environment that were not detected by the camera/scent/rub stations. Non-detected pumas in the area of the camera/scent/rub stations and DNA that provided inaccurate genotypes would lower the detection probability. Detailed notes were kept on visits and behaviors of all pumas and other wildlife that were recorded by cameras. Camera scent/rub stations were maintained from November 20, 2010 to August 14, 2011. A total of 9 stations were used. All information in Tables 20, 21 and Appendix B should be considered exploratory and preliminary. Thirty-nine puma visit events were photographed, including one family of 4 194 �pumas (i.e., mother with 3 cubs). Beaver castorium produced the highest maximum detection probability, 0.667, (Table 20). Detection was variable among the scents used and among pumas and appeared to be substantially lower for male than for female pumas (Table 21). These results indicate that more work needs to be done in a more structured manner to sample a greater number of known individual wild pumas, a variety of scents, and with an analysis of DNA quality and genotype accuracy. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 6.7 years of effort 153 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 30 adult females, 19 adult males, 6 subadult females, 12 subadult males, 39 female cubs, 53 male cubs (some individuals occur in more than one age-stage). Data from the marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CPW wildlife biologists and managers for assessing puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now 2 years of the treatment period are complete (TY1, TY2). Although some data support CPW puma management assumptions, it is still too early in this research to adequately test the assumptions and attendant hypotheses. Although the assumption and hypothesis on harvest structure and hunter selection is not supported with the first 2 years of data in the treatment period, this could change with a substantial change in abundance and sex structure of independent pumas available for hunting in TY3 to TY5. The puma harvest quota for TY3 will be 8 independent pumas, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes across the various life stages and sexes. We will continue to explore methods for estimating puma abundance with accurate and affordable methods. Furthermore, we will continue collaboration with colleagues on investigations of puma population parameter estimation, abundance estimation, puma movements, puma habitat modeling and mapping, and puma-human relations. All of these efforts should enhance the Colorado puma research and management programs. 195 �LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. Colorado Division of Wildlife. 2007. Colorado mountain lion management data analysis unit revision and quota development process. Colorado Division of Wildlife, Denver. Conover, W. J. 1999. Practical nonparametric statistics. John Wiley & Sons, Inc., New York. Cooch, E., and G. White. 2004. Program MARK- a gentle introduction, 3rd edition. Colorado State University, Fort Collins. Culver, M., W. E. Johnson, J. Pecon-Slattery, and S. J. O’Brien. 2000. Genomic ancestry of the American puma (Puma concolor). The Journal of Heredity 91:186-197. Currier, M. J. P., and K. R. Russell. 1977. Mountain lion population and harvest near Canon City, Colorado, 1974-1977. Colorado Division of Wildlife Special Report No. 42. Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and cause specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674. Karanth, K. U., and J. D. Nichols. 2002. Monitoring tigers and their prey: A manual for researchers, managers and conservationists in tropical Asia. Centre for Wildlife Studies, Bangalore, India. Koloski, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2009. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. _____. 2010. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O’Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. 196 �Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 197 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Table 2. Pumas harvested by sport-hunters in Treatment Year 2 (TY2) on the Uncompahgre Plateau Study Area, Colorado, November 22 to December 12, 2010. Puma sex Age (yr.) Date of kill Location/UTM 1.5 Previous M/F I.D. or specimen P no. if not marked P1020 F 11/22/2010 M 2.3 M90 11/23/2010 M 6.3 M55 11/25/2010 M 3.5 P1023 11/26/2010 F 1.5 F108 11/29/2010 M 3 P1032 12/1/2010 M 9.2 M32 12/2/2010 M 1.5 P1024 12/12/2010 McKenzie Butte/ 13S,255947E,4238054N McKenzie Creek/ 13S,257237E,4238244N Spring Creek Canyon/ 13S,239181E,4248300N San Miguel River Canyon/ 12S,736610E,4230762N Cushman Creek/ 12S,752013E,4263883N San Miguel Canyon (E)/ 12S,729439E,4236264N McKenzie Creek/ 13S,257722E,4239169N Tabeguache Creek/ 12S,735100E,4249600N 198 Hunter/status Micah Brogden/ Resident Jack Flowers/ Resident Dennis Rawley/ Non-resident Michael Compton/ Resident Richard Fischer/ Resident Nathan Nickle/ Non-resident Mat Iverson/ Resident Mark Puerschner/ Non-resident �Table 3. Three other independent GPS-collared adult pumas in the minimum count for the Uncompahgre Plateau Study Area that died during the 2010-11 Colorado puma hunting season. Puma sex (M or F) Date of kill Place of kill/UTM Hunter/status/other cause M133 Age (yr.) 3.5 12/1/2010 F94 5 2/1/2011 F25 10 2/5/2011 Dry Fork Escalante Canyon 12S,731720E,4278128N Happy Canyon 13S,246976E,4255108N Pleasant Valley 13S,252703E,4225101N Trent Schloegel/ Non-resident Killed by A.P.H.I.S.W.S. agent for depredation on domestic elk Killed by ranch-hand because puma was seen in vicinity of cattle Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1) and November 2010 to April 2011 (TY2), Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 Unknown sex 4-8* 5-6 9-14 7 9 16 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 199 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 2 (TY2) on the Uncompahgre Plateau Study Area, Colorado, November 22 to December 12, 2010. Data are from puma hunter responses in 54 voluntary surveys, including: 42 original surveys on printed voluntary permits and 12 telephone contacts with hunters that did not return printed surveys on permits. Total response rate from 64 individual hunters was 84.4% (54/64 = 0.894*100). Puma sex/age stage/mark F/adult/F3 by collar, no eartags, confirmed with GPS and VHF data F/adult/F96 by GPS collar, confirmed with GPS data F/adult/none Date of capture 11/25/2010 Capture location Hunter name Spring Creek Canyon Justin Hill 11/27/2010 Dolores Canyon Justin Hill Did not pursue the female puma with intent to harvest it. 11/23 to 27/2010 McKenzie Creek (west) Tommie Buckington guided by Ryan Weimer F /adult and cub/none F/adult or subadult/none 11/22 to 30/2010 11/30/2010 Dolores River Canyon Dolores Creek (east) Ryan Weimer Female puma with evidence of suckling on nipples. Did not want to kill a female puma with cubs. Cubs not actually seen. Not legal to kill a female puma with cubs. Did not pursue the female puma with intent to harvest it. F/adult/none 12/11/2010 F/adult/none 11/22 to 12/12/2010 11/22 to 12/12/2010 Sims Mesa to Happy Canyon Dry Park to Big Bucktail Creek San Miguel Canyon above Goodenough Gulch M/subadult/none John Akerberg & Kris Brown guided by Ben Harris Wade Wilson Sam Sickels Ty Sickels 200 Reason for releasing the puma given by hunter Did not pursue the female puma with intent to harvest it. Did not pursue the female puma with intent to harvest it. Did not pursue the female puma with intent to harvest it. Did not want to harvest a subadult male; guessed weight 125 lb. �Table 6. Summary of puma capture efforts with dogs from November 16, 2010 to April 22, 2011, Uncompahgre Plateau, Colorado. Month November No. Search Days 1 December 11 January 22 February 20 March 21 No. & type of puma tracks founda,b 2 tracks: 1 male, 1female, 0 cub Tracks ≤1 day old: 1 male, 1 female, 0 cub 35 tracks: 7 male, 17 female, 9 cub, 2 undetermined independent pumas Tracks ≤1 day old: 2 male, 3 female, 2 cub 109 tracks: 15 male, 60 female, 30 cub, 4 undetermined independent pumas Tracks ≤1 day old: 5 male, 25 female, 24 cub No. & type of pumas pursued 1 pursuits: 1 male, 0 female , 0 cub No. & I.D. or type of pumas captured, observed, or identified 1 puma captured: M90 recaptured and fit with adult-size VHF collar (cub collar had quit/shed a long time previously). 5 pursuits: 1 male, 3 female, 1 cub 3 pumas captured 3 times: AFP1025 (biodart, dangerous tree), Adult F (not handled due to dangerous tree), M134 cub. In addition, adult female F118, her 3 cubs M126, M127, M128, and adult male M67 were associated with tracks by VHF telemetry. 29 pursuits: 5 male, 14 female, 10 cub 65 tracks: 13 male, 28 female, 24 cub Tracks ≤1 day old: 10 male, 21 female, 22 cub 30 pursuits: 9 male, 11 female, 10 cub 18-19 pumas captured 20 times: F135, F104, AFP1029 (bio-darted, dangerous tree), F136, F137, F28, F23 captured twice, Sub./AMP1028 (possibly M138), M138, and cubs F111's two cubs (not handled, dangerous trees), M112, FP1026, MP1027, M134, M112, F140, M141, M142. In addition, adult females F111, F3 (twice), F96, F136, F116 (twice), and cubs F140, M141, M142 were associated with tracks by VHF telemetry. 14 pumas captured 15 times: F137, F70, F23, F143, adult F (not handled, dangerous tree), F24 (twice), independent M (not handled, dangerous tree), M138, M87, subMP1031 (bio-darted, dangerous tree), and cubs M150 (twice), P1026, M151. In addition, adult females F96, F70 (twice), F23, F118, F143, adult male M67, and cubs M141, M142 were associated with tracks by VHF telemetry. 7 pumas captured 7 times: F111, F3, F72, F145, F146, M144, and cub F152. In addition, subadults M144, F145, and cub M142 were associated with tracks by VHF telemetry. 5 pumas captured 5 times: F24, M92, and cubs F140, M141, F147. In addition, adult M67 was associated with tracks with VHF telemetry. 73 tracks: 26 male, 22 pursuits: 4 male, 30 female, 17 cub 11 female, 7 cub Tracks ≤1 day old: 9 male, 12 female, 7 cub April 6 16 tracks: 3 male, 12 pursuits: 6 female, 7 cub 2 male, 3 female, Tracks ≤1 day old: 7 cub 2 male, 4 female, 7 cub 81 300 tracks: 99 pursuits: 36 to 37 individual pumas were captured 52 TOTALS 65 male, 22 male, times with aid of dogs. In addition, 18 radio142 female, 42 female, collared pumas were detected 28 times by tracks 87 cub, 35 cub and identified with VHF telemetry ≤1 km from 6 undetermined the tracks. Tracks ≤1 day old: 29 male 68 female 62 cub a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day. The count was: 47 tracks of females, including 11 associated with cubs; 21 tracks of males; 4 tracks of cubs, and 1 track of undetermined sex. 201 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from November 2010 to April 2011, Uncompahgre Plateau, Colorado. Puma I.D. M133 F135 F136 F137 M138 F143 M144 F145 F146 M153 Sex M F F F M F M F F M Estimated Age (mo.) 42 27 30 24 18 24 18 18 18 18 Mass (kg) Capture date 11/12/2010 1/1/2011 1/20/2011 1/21/2011 1/26/2011 2/15/2011 3/7/2011 3/8/2011 3/8/2011 4/12/2011 70 38 41 35 50 45 63 42 36 55 Capture method Cage trap Dogs Dogs Dogs Dogs Dogs Dogs Dogs Dogs Cage trap Location Roubideau Canyon Dry Creek Basin McKenzie Creek (east) Dry Creek Basin Spring Creek Canyon San Miguel Canyon Little Big Bucktail Creek North Fork Cottonwood Creek Tomcat Creek McKenzie Mesa Table 8. Pumas that were captured and observed with aid of dogs, some of which were biopsy-darted and given specimen numbers (e.g., P1025), but were not handled at that time for safety reasons, December 2010 to April 2011, Uncompahgre Plateau, Colorado. Puma sex & I.D. F P1025 Age stage or months adult Capture date 12/14/2010 Location Comments Monitor Mesa, Roubideau Canyon Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Apparent mother of cub M134. Puma climbed dangerous tree momentarily, then left the tree and took refuge in a deep narrow hole where we could not gain access to her to change the non-functional GPS collar. Puma climbed dangerous tree. Cub of F111. Two cub tracks found; one was M151 marked 2/24/2011. Puma climbed dangerous tree. Cub of F111. Two cub tracks found; one was M151 marked 2/24/2011. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Probably offspring of F70; sibling of M112 and M150. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Probably M150, offspring of F70; sibling of M112 and P1026. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Possibly M138. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Puma climbed dangerous tree. Too high to biopsy dart. Puma climbed dangerous trees. Biopsy-darted to obtain tissue sample for genotype. First dart missed puma; puma left tree and evaded dogs on bare ground. Puma climbed dangerous tree. Identified by eartag. F28 adult 1/1/2011 San Miguel Canyon Unknown none cub 7 1/2/2011 Piney Creek Unknown none cub 7 1/2/2011 Piney Creek F P1026 cub 18 1/6/2011 Happy Canyon M P1027 cub 18 1/7/2011 Happy Canyon M P1028 F P1029 M none M P1031 F none M92 adult 1/12/2011 Roubideau Canyon adult 1/15/2011 Dolores Canyon (E) adult 2/3/2011 West Fork Dry Creek Basin subadult 2/17/2011 adult 2/21/2011 adult 4/22/2011 North Fork Cottonwood Creek San Miguel Canyon above Horsefly Creek McKenzie Canyon (W) 202 �Table 9. Pumas recaptured with dogs and cage traps January 2011 to April 2011, Uncompahgre Plateau, Colorado. Puma I.D. F28 Recapture Date 1/1/2011 Mass (kg) Observed Estimated Age (mo.) 94 Capture Method/ Location Dogs/East Fork Dry Creek Basin F23 1/6/2011 Observed 77 Dogs/San Miguel Canyon above Pinyon M112 1/6/2011 Observed 17 Dogs/Happy Canyon M134 F104 M112 1/8/2011 1/11/2011 1/24/2011 Observed 36 42 19 116 17 Dogs/Potter Basin Dogs/Roatcap Canyon Dogs/Horsefly Canyon F23 1/26/2011 45 77 F137 2/1/2011 Observed 25 F23 M87 2/8/2011 2/9/2011 Observed 65 78 31 M138 F70 2/9/2011 2/18/2011 Observed Observed 19 70 F70 2/21/2011 46 70 F24 2/22/2011 38 119 F24 2/24/2011 Observed 119 Dogs/San Miguel Canyon below Pinyon Dogs/East Fork Dry Creek Dogs/Tomcat Creek Dogs/Big Bucktail Creek Dogs/Roatcap Canyon Dogs/Spring Creek Canyon Cage trap/Pinyon Hills, Happy Canyon Dogs/Dry Park, Cottonwood Creek Dogs/San Miguel Canyon above Pinyon F111 3/4/2011 41 41 F3 3/15/2011 Observed 116 F72 3/18/2011 Observed 60 Dogs/Fisher Creek F140 4/1/2011 8 Dogs/Coal Canyon Dogs/Cushman Canyon Dogs/Spring Creek Canyon 22 M141 4/1/2011 Observed 8 Dogs/Coal Canyon F137 4/11/2011 42 27 F24 4/21/2011 Observed 121 Cage trap/Dry Creek Basin Dogs/McKenzie Canyon (west) M92 4/22/2011 Observed 32 Dogs/McKenzie Canyon (west) 203 Process F28 first climbed dangerous tree, left the tree, then entered deep narrow hole; could not be handled to replace non-functional GPS collar. F23 took refuge in elevated crevice on canyon wall; could not be handled to replace non-functional GPS collar. Observed puma bayed on the ground, fighting the dogs. Dogs caught and puma allowed to escape. Not handled. GPS collar replaced with VHF radiocollar. M112 fit with VHF radiocollar with expansion link. Replaced non-functional GPS collar with new VHF radiocollar. Observed and released. Observed and released. M87 fit with VHF radiocollar. Observed and released. F70 climbed dangerous tree; could not be handled. Old GPS collar replaced with new GPS collar. Replaced non-functional GPS collar with new VHF radiocollar. F24 observed and released. Effort to capture 2 cubs failed; lost tracks on bare ground in ledges. Old GPS collar replaced with new GPS collar. F3 climbed dangerous tree. Could not be handled to replace old, working GPS collar. F72 climbed dangerous tree. Could not be handled to replace non-functional GPS collar. Recollared with large expandable cub collar to replace the collar that was shed earlier. M141 left tree before we could handle him; escaped the dogs on bare ground. Replaced VHF radiocollar with GPS collar. F24 observed and released. Captured, sampled, and radio-collared cub F147 (one of two cubs). M92 climbed dangerous tree. Could not be handled to fit with radiocollar. �Table 10. Summary of puma capture efforts with cage traps from November 8, 2010 to April 18, 2011, Uncompahgre Plateau, Colorado.* Month November No. of Sites 6 Carnivore activity & capture effort results Captured adult male puma M133 that scavenged mule deer doe carcass in Roubideau Canyon 11/12/2010. Set cage trap in mouth Linscott Canyon on 11/18/2010 in effort to capture male puma that scavenged mule deer carcass; but, the male puma did not return. January 0 All capture efforts with dogs. February 1 Puma F70 was recaptured at a mule deer kill on 2/21/2011 on Pinyon Hills, Happy Canyon. March 3 No pumas scavenged the mule deer carcasses. April 4 Puma F137 was recaptured when she returned to scavenge on a mule deer buck carcass in Dry Creek Basin on 4/11/2011. Puma M153 was captured when he returned to scavenge a mule deer doe carcass on McKenzie Mesa on 4/12/2011. Puma F70 scavenged a mule deer buck carcass on 4/16-17/2011; no effort was made to recapture her. * We used 12 road-killed mule deer at 10 different sites. Of the road-killed deer baits, 5 of 12 (41.66%) were scavenged by pumas. Table 11. Puma cubs sampled August 2010 to July 2011 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M122b F123 F124 M125 M126 M127 M128 F129 M130 M131 F132 M134 M139 F148 F140 M141 M142 F147c F149 M150d P1026d M151e F152f P1030 M F M M M M M F M M F M M F F M M F F M F M F F 7/8/2010 7/15/2010 7/15/2010 7/15/2010 8/8/2010 8/8/2010 8/8/2010 8/21/2010 8/21/2010 8/21/2010 8/21/2010 6/2009 4/18/2011 4/18/2011 8/2010 8/2010 8/2010 9/2010 4/22/2011 8/31/2009 8/31/2009 6/16/2010 6/16/2010 8/2010 35 29 29 29 28 28 28 35 35 35 35 547 36 36 152 152 152 214 45 547 516 253 261 183 2.2 1.8 1.9 2.0 1.6 1.9 2.0 1.6 1.9 1.8 1.6 64 2.25 2.25 13 15 14 16 2.9 53 NH 23 25 21 F104 F94 F94 F94 F118 F118 F118 F96 F96 F96 F96 Unknown F8 F8 Unknown Unknown Unknown F24 F23 F70 F70 F111 F93 Unknown 110 60 60 60 27 27 27 55 55 55 55 Unknown 95 95 Unknown Unknown Unknown 114 80 52 52 32 90 Unknown Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Three sets of cub tracks (including M122) observed in association with F104 when she was recaptured 1/11/2011 in Roatcap Canyon. c Three sets of cub tracks (including F147) observed in association with F24. d Cubs M150 and P1026 are siblings of M112. F70 had at least 3 cubs in the litter. Birth date based on GPS data on F70’s collar. e Two cubs were observed in association of F111. f F93 had two cubs in this litter. 204 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2011, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 205 15 pumas captured for first time 15/81 = 0.18 capture/day 81/15 = 5.40 day/capture �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2011. Consort pairs and estimated agesa Female Age Male Age (mo.) (mo.) F2 53 F2 67 F2 89 F3 36 F3 50 M6 37 F3 62 F3 84 M51 60 F3 107 M55 69 F7 67 F7 82 F7 106 F8*e 24 F8 37 F8 60 M73 49 F8 95 F16 32 F16 52 F16 75 M6 80 F23* 21 F23 45 M27 or 78 M29f 107 F23 80 F24 75 M29 92 F24 114 F25 74 F25 94 F25 110 F25 129 F28* 36 F28 48 M29 88 F28 68 F30* 48 M55 34 F50 21 F54 24 F70* 38 M51 60 F70 52 F72* 28 F72 51 F75 32 F75 55 M73 61 F93 56 F93 90 F94* 46 F94 60 M55 70 F96 55 M55 71 F104 110 F111* 32 F116g 36-48 F118 27 F119 66 Dates pairs consortedb 06/22-24/05 03/31/08 03/28-31/10 02/28-29/08 01/13-14/09 02/19-25/08 04/12-15/07 12/27-29/06 04/16-20/07 03/10/08 02/11/09 04/15/10 05/21/10 Estimated birth datec 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 04/22/11 06/14/07 09/10 08/01/05 04/16/07 08/19/08 3/10 06/09/06 03/30/07 11/08 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 07/09/08 06/12/10 06/01/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 08/21/10 07/08/10 06/16/10 2009 08/08/10 08/09 a Estimated birth interval (mo.) Estimated gestation (days) 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 90-91 19.9 22.7 91-92 23.8 87-93 Non-funct.GPS 90-93 Non-funct.GPS 20.5 16.1 Non-funct.GPS 11.7 92-93 88-92 87 14.8 23.1 23.2 93 13.3 91 Observed number of cubsd 3 2 4 1 2 3 3 2 2 4 3 2 4 2 4 4 3 3 3 1 4 3 1 1 2 3 2 ≥2 tracks 1 3 1 1 3 3 1 2 1 2 2 2 3 3 4 3 2 2 3 2 Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. 206 �d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore nonfunctional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. 207 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2011, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 M71 08-23-07 to 07-31-11 01-29-08 to 11-12-09 M73 M87 M90 02-21-08 to 07-31-11 02-09-11 to 07-31-11 11-16-10 to 11-23-10 M100 03-27-09 to 07-31-09 M114 M133 02-27-10 to 06-23-10 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Alive. M67 is offspring of F30. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Alive. Alive. M87 is offspring of F3. Dead. M90 was killed by a hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Lost contact– after 06-23-10. VHF collar may have failed or puma dispersed. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. 208 �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 F2 07-01-11 to 07-31-11 01-07-05 to 08-14-08 F3 F7 01-21-05 to 07-31-10 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-11 10-11-05 to 09-11-09 F23 02-05-06 to 07-31-11 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 01-01-11 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 F72 01-14-08 to 07-31-11 02-12-08 to 03-18-11 F75 03-26-08 to 02-10-10 F93 F94 12-05-08 to 07-31-11 12-19-08 to 02-01-11 F95 F96 F104 F110 08-01-09 to 07-31-11 01-28-09 to 07-31-11 05-21-09 to 07-31-11 09-21-09 to 02-25-10 F111 01-01-10 to 07-31-11 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Alive. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Lost contact− failed GPS/VHF collar. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Alive. Lost radio contact after12-02-09. F23 recaptured on the study area 01-26-11; her non-functional GPS collar was replaced with a VHF radiocollar. Alive. Lost radio contact after 09-03-08− failed GPS/VHF collar. F24 recaptured on 0222-11; her non-functional GPS collar was replaced with a VHF radiocollar. Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area 02-01-10 and 01-01-11, but could not be handled to replace non-functional GPS collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Alive. Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Lost radio contact after 09-29-09– failed GPS/VHF collar. F75 in association with her cubs M105 and F106 when F106 was recaptured on 02-10-10 on the study area. Alive. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Alive. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. 209 �Puma I.D. F113 Monitoring span 01-26-10 to 06-06-10 F116 F118 F119 F135 F136 F137 F143 01-20-10 to 07-31-11 02-25-10 to 07-31-11 03-25-10 to 07-31-11 01-01-11 to 07-31-11 01-20-11 to 07-31-11 01-21-11 to 07-31-11 02-15-11 to 07-31-11 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 210 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 2 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 2 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 3 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 4 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 5 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annualb 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males 0.947c 0.0568 19 0.250 0.1082 9 Treatment Annual 2 8/1/2010 to 7/31/2011 a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a nonfunctional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. 211 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2011, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 M69 01-11-08 to 04-07-08 7 190 87 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. Dead. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 212 �Puma I.D. F95 Monitoring span 12-29-08 to 07-31-09 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 03-07-11 to 07-13-11 03-08-11 to 04-28-11 03-08-11 to 03-23-11 155 M150 03-28-11 to 04-11-11 14 M153 04-12-11 to 07-31-11 110 M144 F145 F146 128 51 15 Table 16 continued Status Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Dead. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. M112 was offspring of F70. Lost contact of M112 after 04-18-11; he may have dispersed or radiocollar quit. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-1811. Dead. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Alive on the study area. Entered adult life stage 07-01-11. Dispersed. Last contact on 07-13-11 in Blue Creek, northwest Uncompahgre Plateau. Dispersed. Last contact on 04-28-11 in UC Creek, Deep Canyon, northwest Uncompahgre Plateau. Dead. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Alive on the study area. 213 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2011. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 54 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 43 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61 North on 12-27-09 when he was 39 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 214 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 M83 07-05-08 M87 07-31-08 M88 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 42 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 28 months old. 57.7 80.7 369.6 12S,726901E, 4243463N→ 13S,255316E, 4216768N 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N 60.5 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N 21.9 M107 06-28-09 13S,242359E, 4252618N→ 12S,754886E, 4341330N 89.2 90.7 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 30 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is a resident adult on the west slope of the study area to 07-31-11. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a hunter in Dawson Creek, Disappointment Valley on 11-30-10 when he was 29 months old. M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 215 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M117 02-05-10 12S,731840E, 4232346N→ 12S,743909E, 4216633N M144 03-07-33 12S,727173E, 4242012N→ 12S,696439E, 4276888N F52 01-10-07 13S,258058E, 4236260N→ 13S,319217E, 4240467N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N F145 03-18-11 12S,727181E, 4241468N→ 12S,701196E, 4270127N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 19.7 M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. 46.6 M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area. Mother is unknown. He moved off the study area on 03-15-11. M144’s last aerial radio location was in Blue Creek on northwest Uncompahgre Plateau on 07-13-11; he was about 22 months old. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. F108 was offspring of F94, born May 25, 2009; sibling of M107 18.2 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a hunter on the study area on 11-29-10 when she was 17 months old. 38.6 F145 was originally captured in association of M144 and F146; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145’s last aerial radio location was in UC Creek, Deep Canyon, North Fork Mesa Creek on northwest Uncompahgre Plateau on 04-28-11. She was about 19 months old. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. 216 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2011. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision F 6 2/16/2011 Vehicle Good P1030c collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 217 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N �Table 19. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to August 2011. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 11-25-10 3,523 adult 03-27-09 to 01-16-10 923 adult 11-12-10 to 12-01-10 45 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 04-19-11 4,862 adult 02-24-05 to 08-03-08 3,922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 09-10-09 3,801 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 09-04-09 2,281 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 09-09-09 3,653 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 06-09-11 3,359 F72 F adult 02-12-08 to 07-07-10 2,842 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 04-20-11 1,619 F104 F adult 05-29-09 to 11-04-10 1,632 F111 F adult 01-01-10 to 07-12-11 1174 F113 F adult 01-27-10 to 06-06-10 445 F135 F adult 01-01-11 to 08-15-11 787 F136 F adult 01-20-11 to 08-08-11 649 F137 F adult 04-12-11 to 08-15-11 235 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 218 �Table 20. Summary results of exploratory use of scents and hair snags to detect individual wild pumas, November 2010 to August 2011, Uncompahgre Plateau, Colorado. Scent used No times scent used at 9 sites No. puma visits No. individual puma visits . No. times pumas rubbed Beaver castorium Catnip oil 16 8 5 5 2 0 Catnip/Spotted Fever MT Lynx 1 1 7 8 Obsession for Men 11 16 Spotted Fever 7 4 Totals 3 (Unm F, F72, F106) 2 (unm M, M153) 1 (unk sex & age) 4-5 (M153, 12 of unk sex & age, 2 unm M) 5-6 (F72, F106, F136, M153, unm M, unidentifiable) 4 (F3, F25 & 3 cubs, F96, M32) No. times hair was collected from device 5 No. individual pumas detected Max. detection probability (defined in text) 0 2 (Unm F, F106) 0 0.667 (2/3) 0.0 0 0 0 0.0 1 1 1 (unm, unk sex and age) 0.200-0.250 (1/5 to 1/4) 3 3 2(F106, F136) 0.333-0.400 (2/6 to 2/5) 1 1 1 (F25 & cubs) 0.250 (1/4) 39 10 10 Table 21. Variation in individual puma response to scents, November 2010 to August 2011, Uncompahgre Plateau, Colorado. Individual F3 F25 (& 3 cubs) F72 F72 F96 F106 F106 F136 Unmarked Female, unk age M32 M153 M153 M153 Unmarked Male, unk age Unmarked Male, unk age Unmarked Male, unk age Unmarked Male, unk age Unmarked, unk sex and age Unmarked, unk sex and age Unmarked, unk sex and age Unknown if marked, unk sex and age Scent Spotted Fever Spotted Fever Beaver Castorium Obsession for Men Spotted Fever Beaver Castorium Obsession for Men Obsession Beaver Castorium Spotted Fever Obsession for Men Catnip MT Lynx Obsession MT Lynx MT Lynx Catnip Spotted Fever & Catnip MT Lynx MT Lynx Obsession 219 No. times rubbed/ No. of visits 0/1 1/1 0/2 0/3 0/1 4/5 1/1 2/7 1/1 0/1 0/2 0/1 0/2 0/2 0/2 0/1 0/1 0/1 0/2 1/1 0/1 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Puma Habitat Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Methods for Monitoring Populations Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 220 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Puma Po11ulation Trend, U.P., CO ~ 60 "E so 40 ,,.," 30 ".,.,,,_ 20 4~ ~ :11 52 ,,4 43 41 1'(1 I Y2 ll. ~ ,, lO .!: 0 z 0 KY4 Years Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1 and 2 (TY1, TY2). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to 221 �count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. We made further team changes for TY2, which made our efforts more efficient and successful. Yet, in TY2 we counted slightly less (52) independent pumas than in TY1 (55). Post-harvest high trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 14.5% to 15.4% harvest of independent pumas. Post-harvest low trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting. The TY2 postharvest low also includes 2 adult female pumas killed February 1, 5, 2011 on the study area to protect livestock (F25 killed while seen by a ranch hand among cattle; F94 killed for preying on domestic elk). This trend line represents 21.2% to 21.8% harvest of independent pumas. Age structure of independent pumas in November 2010 at beginning of the puma hunting season in Treatment Year 2, Uncompahgre Plateau, Colorado. 7 6 f-f-- 1 0 f-- ~ f-- ~ f-- ~ ~ ~ I r1 11 11 11 ■ Female I 11 ■ Male lto2>2to >3to >4 to >S to >6to >7 to >8to >9to 10+ 3 4 5 6 7 8 9 10 Age(years) Figure 4. Estimated age structure of independent pumas in November 2010 at the beginning of the puma hunting season in Treatment Year 2 (TY2) on the Uncompahgre Plateau, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 4.87 ± 3.11 yr. (58.40 ± 37.26 mo.), n = 25; 3.51 ± 2.59 yr. (42.07 ± 31.08 mo.), n = 14. 222 �Puma births, Uncompahgre Plateau, Colorado. 10 9 "' ....a1 = z 0 8 7 6 5 4 3 2 1 0 I Ja n. 11 I I I I I I I l I H: I I I 11 I Feb. M ar. Apr. M ay June July Aug. Sep. Oct. Nov. Dec. ■ Bi1ths 2005-2011 ■ Bi1t hs 1982-1 987 Figure 5. Puma births (black bars) detected by month from May 19, 2005 to April 22, 2011 (n = 40 litters of 21 females; 38 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 223 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) 31 5-28-05 F10 31 5-28-05 M11 31 5-28-05 F12 42 F13 Mother I.D. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4.5 years old. Lost contact― shed radiocollar 04-19-06 to 04-26-06. F3 Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified) about 828-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 ~1,345 F9 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 324 224 F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 Est. Birth date F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 43 months old. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed 0301-07. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 01-28-09 in GMU 41 when 29 months old. F7 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 225 Mother I.D. F23 F23 F28 F2 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 ~456 42 ~428 subad. 226 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61 when 39 months old. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61 N) 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. Mother I.D. F7 F7 F3 F3 F3 F50 F54 �Appendix A continued Puma I.D. Estimated Age at capture (days) M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 200 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F7 (?) Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 28 months old. F16 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 227 F25 F16 F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau. Alive as of 07-31-11. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. 111 681 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 1475 532 F74 259 6-1-07 5-19-08 03-12-08 to 07-09-08 06-18-08 M76 30 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 228 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) F80 40 F81 F97 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) 5-23-08 Est. survival span from 1st capture to fate or last monitor date 07-02-08 40 8 ½ mo. 5-23-08 5-23-08 07-02-08 to 07-29-09 02-04-09 424 354 M82 37 5-29-08 07-05-08 to 03-20-09 or 04-02-09 295-308 M83 37 5-29-08 07-05-08 M84 36 6-5-08 07-11-08 to 02-11-09 F85 36 6-5-08 07-11-08 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 ~48-59 M87 28 7-3-08 07-31-08 1123 M88 F89 M90 28 28 36 7-3-08 7-3-08 7-9-08 07-31-08 07-31-08 08-14-08 251 867 229 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 19 months old. Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F23 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11. Alive as of 07-31-11. Not radio-collared. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. F70 F23 F23 F8 F8 F70 F70 F3 F3 F3 F72 �Appendix A continued Puma I.D. Estimated Age at capture (days) Male 7A 28-35 7-10-08 Male 7B 28-35 Female 7C Est. Birth date Est. survival span from 1st capture to fate or last monitor date ~08-07-08 to 08-14-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 28 to 35 F7 7-10-08 ~08-07-08 to 08-14-08 28 to 35 28-35 7-10-08 28 to 35 M91 M92 35 35 8-19-08 8-19-08 ~08-07-08 to 08-14-08 09-29-08 09-29-08 F95 16 mo. June-07 12-29-08 F98 4-5 mo. 5 mo. 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 M99 Sep-Oct08 Sep-Oct08 M101 35 4-15-09 157 M102 35 4-15-09 05-20-09 to 09-19-09 05-20-09 F103 35 4-15-09 159 M105 38 5-7-09 F106 38 5-7-09 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. Radio-collared. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. Radio-collared. Died, probably killed by male puma (infanticide). Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 9-4-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 2-9-10 due to shed collar. F75 M107 34 5-25-09 Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 2-24-10; not collared. 06-28-09 to 02-24-10 976 488 278 275 661 241 230 Mother I.D. F7 F7 F25 F25 F93 Unm.F Unm.F F16 F16 F16 F75 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) F108 34 Est. Birth date 5-25-09 Est. survival span from 1st capture to fate or last monitor date 06-28-09 to 03-05-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 275 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 6-12-10 06-12-10 to 07-21-10 39 M120 30 6-28-10 157 M121 30 6-28-10 273 Radio-collared. Lost radio contact after 03-28-11. F3 M122 35 7-8-10 07-28-10 to 12-02-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11; he may have dispersed or radiocollar quit. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. 274 F104 F123 29 7-15-10 F124 29 7-15-10 M125 29 7-15-10 M126 28 08-08-10 M127 28 08-08-10 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 528 595 08-13-10 to 02-17-11 08-13-10 to 02-16-11 08-13-10 to 02-01-11 09-05-10 to 03-17-11 09-05-10 to 07-01-11 217 216 201 221 327 231 F94 F94 F70 F28 F119 F72 F72 F3 F94 F94 F94 F118 F118 �Appendix A continued Puma I.D. Estimated Age at capture (days) M128 28 08-08-10 F129 35 08-21-10 M130 35 08-21-10 09-25-10 to 10-23-10 M131 35 08-21-10 F132 35 08-21-10 09-25-10 to 07-21-11 09-25-10 M134 ~18 mo. ~June-09 12-14-10 to 06-10-11 731 M139 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 F140 ~5 mo. ~Aug.10 01-02-11 to 04-18-11 258 M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 241 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 F149 45 04-22-11 M150 525 08-31-09 04-21-11 to 07-31-11 06-06-11 to 07-31-11 02-07-11 to 04-11-11 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-05-10 to 02-22-11 09-25-10 to 04-28-11 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 198 F118 315 Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Not radio-collared. Too small for collar design. Fate unknown. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. 100 Radio-collared. F23 588 Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. F70 250 63 334 35 183 232 F96 F96 F96 F96 Unm. F F8 F8 Unk./ F28? Unk./ F28? Unk./ F28? Unk. F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M151 253 06-16-10 F152 06-06-10 271 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-24-11 to 03-07-11 03-14-11 to 03-21-11 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 264 Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). Radio-collared. Lost contact after 03-21-11; shed collar. F111 271 a F93 Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. b 233 �Appendix B. Summary of exploratory use of scents and hair snags to detect individual pumas, 2010 to 2011, Uncompahgre Plateau, Colorado. Details on behaviors of pumas and other wildlife that visited the camera-scent stations are not included in this appendix, but are in original data file. Time puma was at site (min.) No. photos of puma Time lapse between scent treatment and puma visit (days) Scent type/name Closest puma distance estimate to scent pad-hair snag (m) Rub response by puma (yes, no) Date MS Time Puma Sex Age stage Female Reproductive Status HS01 11/27/2010 9:39 F96 F Adult Cubs 6 mo. old 1 2 7 Spotted Fever 0.3 no HS01 12/8/2010 16:40 unmarked F Adult Unk 5 114 2 Beaver Castor 0 yes HS02 11/29/2010 15:40 F3 F Adult Cubs 5 mo. old 1 6 9 Spotted Fever 0.6 no HS03 2/27/2011 6:10 F106 F Adult No cubs 3 95 12 Beaver Castor 0 yes yes HS03 2/27/2011 17:45 F106 F Adult No cubs 5 48 12 Beaver Castor 0 yes yes HS03 2/28/2011 18:38 F106 F Adult No cubs 74 572 13 Beaver Castor 0 yes yes HS03 3/1/2011 6:31 F106 F Adult No cubs 1 15 14 Beaver Castor 0 no HS03 3/2/2011 18:37 F106 F Adult No cubs 13 297 15 Beaver Castor 0 yes yes HS03 3/3/2011 18:23 F106 F Adult No cubs 4 107 16 Obsession 0 yes yes HS03 3/7/2011 20:26 F136 F Adult No cubs 1 18 4 Obsession 3 no HS03 3/11/2011 4:41 F136 F No cubs 5 54 8 Obsession 0 yes HS03 4/11/2011 0:31 unmarked M Adult 1 3 3 Catnip 1.5 no HS03 4/13/2011 22:18 M153 M Sub-adult 1 3 5 Catnip 0.6 no HS03 5/16/2011 21:54 unmarked Unk Unk 1 4 4 Catnip/Spotted Fever 0.6 no HS03 6/11/2011 22:56 unmarked M Adult 1 9 2 Obsession 0.3 no HS03 7/6/2011 17:59 unmarked Unk Unk 1 11 0 MT Lynx 0.1 no HSO4 11/22/2010 5:34 M32 M Adult 1 10 4 Spotted Fever 0.6 no HS04 12/3/2010 17:40 F25 & 3 cubs F Adult 7 243 3 Spotted Fever 0 yes Camera site I.D. Cubs 8-9 mo. old 234 Hair on snag collected yes yes yes �Appendix B continued. Time puma was at site (min.) Time lapse between scent treatment and puma visit (days) Closest puma distance estimate to scent pad-hair snag (m) Date MS Time Puma Sex Age stage Female Reproductive Status HS04 2/24/2011 16:04 F72 F Adult No cubs 3 44 9 Beaver Castor 0 no HS04 2/25/2011 15:36 F72 F Adult No cubs 1 15 10 Beaver Castor 0 no HS04 3/8/2011 6:33 F72 F Adult No cubs 1 21 5 Obsession 0 no HS04 3/8/2011 20:51 F72 F Adult No cubs 1 21 5 Obsession 3.5 no HS04 3/16/2011 3:29 F72 F Adult No cubs 1 13 Obsession 3.5 no HS04 3/18/2011 21:32 Not identifiable Unk Unk Unk 1 9 15 Obsession 3 no HS04 4/14/2011 2:03 F136 F Adult No cubs 1 9 6 Obsession 3.5 no HS04 4/15/2011 4:40 F136 F Adult No cubs 1 15 7 Obsession 0.3 no HS04 4/16/2011 4:40 F136 F Adult No cubs 1 6 8 Obsession 3 no HS04 4/18/2011 18:20 F136 F Adult Pregnant 1 15 10 Obsession 0 yes HS04 4/25/2011 23:52 M153 M Sub-adult 1 15 17 Obsession 0.3 no HS04 5/2/2011 19:31 unmarked M Adult 1 27 24 Obsession 0 no M Sub-adult 1 9 31 Obsession 3 no Adult 1 12 32 Obsession 2.3 no MT Lynx 1.5 no Camera site I.D. HS04 5/9/2011 15:36 VHF male 150 or M153 HS04 5/10/2011 1:07 F136 F HS04 7/15/2011 unmarked M HS06 6/29/2011 1:39 M153 M HS06 7/4/2011 18:21 unmarked HS06 7/15/2011 19:36 unmarked M HS07 7/8/2011 3:02 M153 M HS09 7/24/2011 21:01 unmarked Unk Pregnant No. photos of puma 4 Sub-adult Sub-adult Scent type/name Rub response by puma (yes, no) 1 33 7 MT Lynx 0.3 no 1 6 12 MT Lynx 0.3 no 1 3 23 MT Lynx 0.3 no 1 15 16 MT Lynx 0 no 1 9 25 MT Lynx 1.3 no 235 Hair on snag collected yes no �Appendix B continued. Camera site I.D. HS09 Date MS Time Puma Sex 8/6/2011 5:44 unmarked Unk Age stage Female Reproductive Status Time puma was at site (min.) No. photos of puma Time lapse between scent treatment and puma visit (days) 2 21 38 236 Scent type/name Closest puma distance estimate to scent pad-hair snag (m) Rub response by puma (yes, no) Hair on snag collected MT Lynx 0 yes yes �Colorado Division of Parks and Wildlife July 2011 –June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. W-204-R1 : : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates on the Uncompahgre Plateau Period covered: July 31, 2011−June 30, 2012 Author: Kenneth A. Logan. Personnel: K. Logan, S. Bard, B. Dunne, W. Hollerman, W. Jesson, R. Navarrete, B. Nay, H. Taylor, S. Waters, B. Banulis, T. Bonacquista, K. Crane, J. Koch, E. Phillips, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, Oklahoma State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, years 1-5) and presence (treatment period, years 6-10) of sport-hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Parks and Wildlife model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report provides information on the third year of the treatment period (TY3), August 2011 through July 2012, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 21 and closed December 23, 2011 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 8 pumas were killed: 3 adult females, 1 adult male, and 4 subadult males. The harvest of 8 independent pumas represented 16.7% of the 48 independent pumas in our minimum count during November 2011 to April 2012. Independent females and males comprised 37.5% and 62.5% of the harvest, respectively. Four other radio-collared independent pumas (2 adult females, 2 adult males) and 3 non-collared adults (1 female, 2 males) in the study area population died during the Colorado puma hunting season. Of those, 2 adult females died of natural causes and the remainder was killed by puma hunters in GMUs adjacent to 134 �the study area. The total mortality of 15 independent pumas during the TY3 hunting season represented 31.2% of the 48 minimum count of independent pumas on the study area. Seventy-four hunters requested mandatory permits with an attached voluntary hunter survey in TY3. Thirty-six of the hunters provided responses to written (n = 31) or telephone call follow-up contact (n = 5). An estimated 49 hunters actually hunted on the study area, of which about 16.3% harvested pumas and 26.5% captured pumas (i.e., harvested plus treed and released). Twenty-four of 26 answering hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks < 1 day old encountered by hunters and pumas captured by hunters indicated that independent female pumas were detected more frequently than males by hunters. From August 2011 to July 2012 twenty-eight individual pumas were captured 35 times by research teams. Two capture teams with dogs operated over 79 search days from December 27, 2011 through April 12, 2012 to find 268 puma tracks, pursue pumas 89 times, and capture 21 pumas 26 times. Capture efforts with cage traps resulted in the capture of 1 adult female for the first time. Nine new cubs were captured and radio-collared. A total of 42 pumas were monitored by radio-telemetry in TY3. Search efforts also revealed the presence of at least 26 other independent pumas. Our minimum count of 48 independent pumas from November 2011 to April 2012 included: 31 females and 17 males. The minimum count of 48 independent pumas in TY3 was lower than 52 in TY2 and 55 in TY1. A preliminary minimum estimated density of independent pumas was 2.87/100 km2. The proportion of radio-collared adult females giving birth in the August 2011 to July 2012 biological year was 0.19 (3/16). Three litters that could be dated to month of birth were produced in August. Since 2005 a birth peak has occurred from May through August, involving 86% of births. We monitored 20 female and 7 male adult radio-collared pumas for survival and agent-specific mortality. Survival rates in TY3 for adult females (0.548, SE=0.1063) and males (0.167, SE=0.1076) were lower than in TY1 and TY2. A preliminary assessment is that hunting mortality is additive to natural mortality. Of 12 cubs monitored with radiotelemetry in TY3, 6 died. Three died of starvation after their mothers were killed by puma hunters. Three others died of natural-related causes, including 2 that starved after their mother died of a natural cause. One non-marked male cub was struck and killed by a vehicle on state highway 62. Puma harvest, capture, and radio-telemetry data from the beginning of this study to the present provided information on dispersals of 33 pumas initially marked on the study area. Those pumas moved from about 18.2 to 370 km from initial capture sites. We investigated the prevalence of Trichinella spp. in pumas killed in southwest Colorado in collaboration with Dr. Mason Reichard, Oklahoma State University. Twelve of 14 (85.7%) puma tongues were infected with Trichinella. The apparent decline in the puma population on the study area during TY1 to TY3 necessitates a reduction in the harvest quota to continue to test the harvest assumption for a stable-to-increasing puma population. This change will be pursued for TY4 and the results of the harvest monitored through the end of the treatment period. 135 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction of females, stage-specific survival, and immigration and emigration; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the third year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the third year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and stage-specific survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore frequency of Trichinella ssp. in pumas harvested in southwest Colorado in collaboration with Dr. Mason Reichard, Veterinary Health Science, Oklahoma State University. INTRODUCTION Colorado Parks and Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of “achieving healthy, self-sustaining populations” through management (Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). 136 �● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the grayshaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas to investigate the effects of sport-hunting and other causes of mortality on puma population dynamics. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CPW’s puma model-based management and attendant assumptions with Coloradospecific data from objectives 1―3. Consider other useful models. Conduct a pilot study to develop methods that yield reliable estimates of puma population abundance. Investigate diseases in pumas. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 which involves the use of controlled recreational hunting to manipulate the puma population. 137 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all stage classes - adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). These objectives are expected to provide both the capacity for puma population resiliency to achieve a state-wide goal of a healthy, self-sustaining puma population while managing the puma population to provide sport-hunting opportunity and population control in some DAUs (even though puma population dynamics in any DAUs are not known). Basic model parameters are: puma population density, sex and age structure, annual population growth rate, and relative puma habitat quality and quantity. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. An assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ) Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). This assumption is 138 �vital to providing the capacity for resiliency in the state-wide puma population which is hunted by applying this assumption to about three-quarters of the puma GMUs in the state. H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). This assumption is applied to about one-quarter of the GMUs in the state. H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2007). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics relative to harvest. 139 �We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1986, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. Information which will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. People reside year-round along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of 140 �the plateau. A highly developed road system makes the study area easily accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma populations in western North America for at least the past 100 years. Hence, the reference period, years 1 to 5, provided conditions where individual pumas in this population expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6 to10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of 141 �the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were recorded via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and enabled dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snowmobiles, and on foot. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg based on estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). The immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers for capture were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage 142 �and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and movement across Data Analysis Unit boundaries). Adults, subadults, and cubs were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were identified about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using a hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around those locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes were recorded on standard forms. GPS and aerial locations were mapped using GIS software. 143 �We attempted to collar all cubs in observed litters. Cubs were fit with small VHF transmitters mounted on expandable collars that expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with the Colorado puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of 144 �the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2011 to July 2012, was the third year of the treatment period (TY3) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 21, 2011 and was scheduled to extend to January 31, 2011, unless the harvest quota was taken before then. The harvest design quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This harvest design tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (Assumption and Hypothesis 3 p.5-6 this report). The initial quota of 8 pumas for TY1 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY3 was based on the observed minimum count of 52 independent pumas during November 2010 to April 2011 in TY2 and that approximately the same number of independent pumas was expected during the puma hunting season for TY3. The hunting structure in TY3 was the same as in TY1 and TY2. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). All pumas harvested on the study area were examined by principal investigator K. Logan or a wildlife research technician and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon inspection, the following data were recorded: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 21 to December 23, 2011, taking 33 days to fill the quota of 8 pumas. This was 12 days more than it took to harvest 8 pumas in TY2 (i.e., 21 days, Nov. 22 to Dec. 12, 2010) and 7 more days than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Eight pumas were killed on the study area, including: 3 adult females, 1 adult male, and 4 subadult males (Table 2). Of the 8 harvested pumas, 6 were marked: F3, F70, F75, M120, M138, and M141. In addition to the pumas killed on the study area during the Colorado puma 145 �hunting season, adult males M67 and M87 were killed by hunters in north GMU61, and adult females F104 and F119 died of natural causes. In addition, 3 non-marked adult pumas that apparently ranged on the study area were killed by hunters (Table 3). Of those, one adult male was pursued across 25 Mesa Road, the north study area boundary, and killed in north GMU62; another adult male was snow-tracked across Colorado state highway 145, a south study area boundary, and was killed in east GMU70; and an adult female with a radio-collared cub that ranged on the study area was killed adjacent to the study area in north GMU61. All these pumas were included in the minimum count of pumas for TY3. The harvest of 8 independent pumas on the study area was 16.7% (8/48*100) of the minimum count of 48 independent pumas counted on the study area, including 31 females and 17 males, determined by the research team during November 2011 to April 2012 (Table 4). Independent females and males comprised 37.5% (3/8*100) and 62.5% (5/8*100) of the harvest, respectively. This harvest structure was 9.7% (3/31*100) of the independent females and 29.4% (5/17*100) of the independent males. Considering the mortality of 4 other radio-collared adults (F104, F119, M67, M87) and 3 noncollared adults (1 female, 2 males) (Table 3), the mortality of 15 independent pumas was 31.2% (15/48*100) of the minimum number of independent pumas. The mortality composition of 6 females and 9 males was comprised of 40.0% (6/15*100) females and 60.0% (9/15*100) males. This harvest structure was 19.4% (6/31*100) of the independent females and 52.9% (9/17*100) of the independent males in the minimum count. The minimum count of 48 independent pumas in TY3 was lower than the minimum count of 52 independent pumas in TY2 and 55 independent pumas in TY1 (Table 4, Fig.3.). Minimum count TY3 = 48 independent pumas, including 31 females and 17 males. This count reflected the relatively low adult female and low adult male survival rates (see Table 15, later). Because the harvest quota of 8 independent pumas in TY1 resulted in a minimum count of 52 independent pumas in TY2 and was expected to result in a stable-to-increasing population trend, we decided to set the quota to harvest 8 independent pumas in the TY3 (2011-12) hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population might be killed outside of the study area as in the TY1 and TY2 hunting seasons. However, the additional pumas killed by hunters outside of the study area and natural mortality occurring during the hunting season and other parts of the biological year has apparently resulted in a declining population trend (Fig. 3). Hunter permits and survey: In TY3 mandatory permits with the voluntary survey attached were requested by 74 individual puma hunters. This number is up from 64 hunters in TY2 and down from 79 individual hunters in TY1. Twenty-three of the hunters requested a second permit, 13 hunters requested a third permit, and one hunter requested a fourth permit after a previous permit expired after 14 days. Thirty-six hunters (48.6%) provided responses to the voluntary survey either by turning in the printed survey (n = 31) or providing information during follow-up telephone calls (n = 5) by principal investigator K. Logan. The remaining 38 hunters could not be contacted because either they did not have working phone numbers or they did not return calls. Of the respondents, 12 hunters indicated that they did not hunt on the study area. The proportion of the 36 respondents that hunted extrapolated to the total of 74 hunters (24/36 = 0.666) indicated that about 49 hunters took to the field for pumas on the study area during the 33-day TY3 hunting season. This was up from 42 hunters in TY2, but down from 67 hunters in TY1 (Logan 2010, 2011). Considering that 49 hunters were estimated to be afield, then 16.3% of the hunters harvested pumas (8/49*100) and 26.5% of hunters captured pumas (13/49*100; see captured and released pumas below and in Table 5). The 31 puma hunters that turned in the written volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting 146 �for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 24 respondents (92.3%; 24/26 = 0.923). Of the remaining 7 hunters, 2 indicated they were non-selective (7.7%), and 5 did not answer the question because they indicated that they did not hunt on the study area. The volunteer hunter survey also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 4 times and observed one, including 2 adult females (1 of them twice), 1 female of unspecified age-class, and 2 “young” males (1 male treed by 2 hunters). Two of the females were marked with collars and ear-tags. Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex, size, and one hunter did not want to kill a puma (Table 5). In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters and hunter selection to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to pumas that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters’ responses in TY3 showed they encountered 21 puma tracks less than one day old. Of those, 15 tracks were of females, and 6 tracks were of males, indicating that during the hunting season females are more detectable than males by a ratio of 2.5:1, consistent with the sex structure of independent pumas in the minimum count on the study area which was 31 females and 17 males (Table 4). Of the 15 female tracks, 1 female puma was pursued by a hunter with intent to harvest it, and that female was killed. Nine hunters indicated they observed female tracks as their first tracks <1day old, but did not pursue the puma with intent to harvest it. Another 4 hunters did not answer the question, “Did you pursue the lion to harvest it?” Six hunters indicated they observed male tracks as their first track <1 day old; 4 indicated they pursued the puma to harvest it, and 3 male pumas were killed. Two hunters indicated they did not pursue male pumas to harvest them. These preliminary survey and harvest data for TY3 indicate that hunters detect independent females more frequently than male pumas and females were captured by hunters slightly less than or about the same frequency as independent males by 6 to 7 (i.e., females = 3 harvested + 3 captured and released; males = 5 harvested + 2 captured and released). Moreover, hunters were choosing to kill males more frequently than females. Results in TY3 indicated selection for male pumas by hunters was consistent with TY1 and TY2 results where hunters caught females slightly more frequently than males, yet the males were selected for harvest. This preliminary assessment from years TY1, TY2, and TY3 puma harvest and hunter survey data suggests that female pumas were detected by hunters more frequently than male pumas, most puma hunters were selective, and hunter choices influenced harvest sex and age composition. Segment Objective 2 After the harvest quota was filled, puma research teams immediately initiated capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radio-collar pumas the remainder of winter and early spring 2011-12. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 35 puma captures of 28 individuals from August 2011 to July 2012 (Tables 6-11); 21 individual pumas were captured with dogs 26 times. One puma was captured in a cage trap. Six cubs were captured at nurseries by hand. A total of 42 individual pumas were monitored with radio-telemetry from 147 �August 2011 to July 2012 (some of these had been collared in previous years), representing sex and age classes including: 19 adult females, 7 adult males, 4 subadult females, 4 subadult males, and 12 cubs (i.e., 1 cub and 2 subadult males survived to older age classes during the biological year). Trained dogs were used as our main method to capture, sample, and mark pumas from December 27, 2011 to April 12, 2012. Those efforts resulted in 79 search days, 268 total puma tracks detected of which 138 were ≤1 day old, 89 pursuits, and a total of 26 puma captures of 21 individual pumas (Table 6). This was the third year we deployed 2 fully-staffed hound capture teams in the treatment period. Search days with dogs in TY3 (79 days) were similar to TY2 (81 days), but slightly lower than TY1 (86 days) (Table 12). The frequency of tracks (tracks/day) encountered in TY3 was slightly lower than TY2, but slightly higher than TY1. The number of pursuits in TY3 was 10 less than in TY2 and 4 less than in TY1. The capture rate in TY3 was less than half that in TY2, but similar to TY1. The number of new pumas captured for the first time in TY3 was 4 less than TY2, but 2 more than TY1 (Table 12). Researchers in the two hound capture teams from December 27, 2011 to April 12, 2012 also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected and pursued by puma hunters. The count was: 70 tracks of females, including 17 associated with cubs; 2 of 2 orphaned cubs; 12 tracks of males; and 2 tracks of unspecified sex. These tracks ≤ 1 day old were found after the TY3 puma hunting season when 3 independent females and 5 independent males were harvested (Table 2). Therefore, the harvested pumas were not present to make tracks for our researchers to observe. The loss of the 3females and 5 males may be reflected in the substantially higher ratio of female:male tracks post-hunting season. By comparison, the number of female to male tracks reported by puma hunters in TY3 was 15 females and 6 males (Segment Objective 1 above). Puma capture efforts using ungulate carcasses and cage traps was sporadic from October 5, 2011 to April 11, 2012 (Table 10). We used 21 road-killed mule deer at 18 different sites. One independent adult female puma, F172, was captured for the first time. Pumas scavenged at 3 of 21 (14.29%) sites where deer carcasses were used for bait. We sampled 9 new cubs, including 2 females and 7 males (Table 11). All were radio-collared to monitor survival and agent-specific mortality (Appendix A). In addition to our direct puma captures with dogs December through April, we detected 17 radiocollared pumas that we were able to identify with GPS or VHF telemetry 40 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. In addition to the harvest and capture data (previously), our search efforts also revealed the presence of at least 26 other pumas which we included in our minimum count November 2011 through April 2012 (Table 4). We classified those pumas as: 10 adult females, 4 adult males, 1 subadult female, 1 subadult male, and 10 cubs. Two adult females and 2 cubs were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). Of those, 2 adult females were sampled with biopsy darts to obtain a tissue sample for genotyping the individuals. We could separate the activity of the other pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females, males, and numbers of cubs with females. Moreover, of the 26, 4 non- 148 �marked independent pumas (3 females, 1 male) and 4 non-marked cubs were confirmed with photographs from digital trail cameras. Our search and capture efforts during December 2011 through April 2012 and information from the puma hunting season in TY3 enabled us to quantify a minimum count of 48 independent pumas detected on the Uncompahgre Plateau study area, including 31 independent females and 17 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or pursued, treed and released by hunters on and adjacent to the study area, and puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars. Of the 48 independent pumas, 27 (56%) were marked and 21 (44%) were assumed to be non-marked animals (i.e., some may have ear-tags and tattoos). The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 21 independent pumas (14 females, 7 males). The west slope count included 27 independent pumas (17 females, 10 males). A decline in the study area puma population is evident on the east slope. Considering the minimum count of 48 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 2.87 independent pumas/100 km2. The TY3 minimum count of 48 independent pumas is lower than the two previous treatment years TY1 and TY2 and appears to signal a declining trend in the puma population on the Uncompahgre Plateau study area (Fig. 3). The declining trend is further supported by declining survival rates of adult pumas on the study area (see Segment Objective 4&5 below). Taking into account the apparent declining trend in the number of independent pumas, a simple linear regression model of minimum counts of independent pumas in TY1, TY2, and TY3 on year projected that a minimum of 45 independent pumas could be expected in TY4 if the population decline continues. The recommended puma harvest for TY4 will be 5 pumas, representing 11.1% of the 45 expected number of independent pumas. This harvest rate is in the mid-range of the 8-15% test assumption for a stable to increasing population. The estimated age structure of independent pumas in November 2011 at the beginning of the puma hunting season in TY3 on the Uncompahgre Plateau study area is depicted in Figure 4. The male age structure has declined when compared with TY1 and TY2 (Logan 2010, 2011). The female age structure is more evenly distributed and does not yet reflect a decline in survival rates of adult females in TY3 (Logan 2010, 2011). In addition to the independent pumas, we counted a minimum of 19 cubs in TY3 (Table 4). Segment Objective 3 During the past 7.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). In TY3 we directly observed 4 litters in nurseries which were born in June 2012 (1; F118’s cub not marked), July 2011 (1) and August 2011 (2), each with 1 to 3 cubs born to radio-collared females. Data on reproduction we observed in TY1, TY2, and TY3 were added to Table 13 which gives the reproductive chronology and information on mates of reproducing females. But those data will not be summarized again until the end of the treatment period. The proportion of radio-collared adult females giving birth from August 2011 to July 2012 biological year (TY3) was 0.19 (3/16), substantially lower than TY1 (0.53, 8/15) and TY2 (0.56, 9/16), further evidence for a declining puma population. 149 �Considering our 46 total litters from 24 females, including 44 observed with cubs 26 to 42 days old and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females (the latter include F111’s cubs caught later when 8.5 months old) (Table 13), the distribution of puma births by month since 2005 indicate births extending from March into September (Fig. 5). Births are high in May and June, peak in July, and decline in August and September. Births during late spring to late summer (May to August) involve 86% of the births (Fig. 5). The data indicate that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 19821987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions of births in the reference and treatment periods separately for a treatment effect on timing of breeding and births. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2012, we radio-monitored 21 adult male and 34 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). We monitored 20 adult females and 7 adult males for annual survival and agent-specific mortality in TY3. Annual survival rate for adult females was 0.548 (SE=0.1063) and for males was 0.167 (SE=0.1076). Preliminary adult puma survival for TY1, TY2, and TY3 are also shown in Table 15. So far, adult male survival is substantially lower in the treatment period than in the reference period. Adult female survival is lower in TY1 and TY3, with marked decline in TY3. Yet, female survival is generally higher than male survival. These characteristics are probably indicative of hunter selection for male pumas (previously in Segment Objective 1). The lower adult puma survival rates were consistent with an observed decline in the puma population on the study area (see Segment Objective 2, previously). Human-related factors caused 8 deaths of radio-marked adult pumas in TY3, including: sporthunting harvest (3 males- M67, M87, M138; 3 females- F3, F70, F75), illegal shooting (M73), and depredation control (1 male- M153) (Tables 2, 3, 14). In addition, 6 adult female pumas died of natural causes: F23 and F24 were killed by a male puma; F104 apparently died of starvation associated with senescence; F116 apparently died of complications associated with pregnancy and parturition; F119 died of a ruptured uterus and internal bleeding associated with pregnancy, and F135 died of unknown natural cause (Table 14). The occurrence of an increasing frequency of natural deaths and declining adult survival rates in this hunted puma population suggests that sport-hunting causes additive mortality. We have radio-monitored 27 subadult pumas (i.e., independent pumas <24 months old), including 11 females and 16 males (Table 16). We lost contact with 2 males that probably dispersed from the study area unknown distances. Of the remaining 25 subadults (females and males combined), 6 (2 females, 4 males) died before reaching adulthood, indicating a preliminary binomial survival rate of 0.76 (i.e., 19/25). F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old; punctures to his skull were consistent with canine bites from another puma and suggested intra-species strife as cause of death. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. F143 was killed and eaten by a male puma while in competition for an elk carcass that one of the pumas killed. Two subadult males were killed by puma hunters. We 150 �need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Harvest data along with our capture and radiotelemetry data provided dispersal and fate information on 33 marked pumas, 25 males and 8 females. Of those, 25 (4 females, 21 males) were initially captured and marked as cubs, and 8 (4 females, 4 males) were captured and marked in the subadult life-stage on the Uncompahgre Plateau puma study area (Table 17). Twenty males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). Four females were killed by puma hunters; 3 off the study area ranging from 24.0 to 74.5 km from initial capture sites; 1 on the study area 18.2 km from her initial capture site. Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she established an adult home range there before she was killed by a puma hunter in that area on Jan. 9, 2012. Three males marked initially as cubs born on the study area (M67, M87, M92) dispersed from their natal ranges and were recaptured as adults on the study area. All were born on the east slope of the Uncompahgre Plateau and moved to the west slope. Twenty-three of the 33 pumas had reached adult ages ranging from 24 to 79 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53. [The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629).] The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY3 we monitored the fates of 12 radio-collared cubs (Appendix A). We lost contact with one (M156) after he shed his expandable radio-collar; he was 59 days old. Of the remaining 11 collared cubs, 6 died. Cubs M154 and M155 died probably of starvation after their mother died of an unknown natural cause; they were 77-81 days old. M159 died of an unknown natural cause when he was about 105 days old. His siblings F157 and F158 died of starvation after their mother F70 was killed by a puma hunter; they were 150 days old. M162 died of starvation after his mother was killed by a puma hunter; he was about 10.6 months old. Three other cubs that were orphaned at older ages survived to the subadult life stage. F147 was orphaned at 12 months old when her mother F24 was killed by a male puma. F147 continued to range on her natal area until her radiocollar quit functioning when she was 19 months old. Siblings F149 and M161 were orphaned at 13.5 months old when their mother F23 was killed by a male puma. Both siblings dispersed to the east slope of the study area when they were 14 to 15 months old. Another cub, F152, offspring of F93, survived to at least 25 month old in July 2012 and ranged on her natal area. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. In addition, a non-marked male puma cub was struck and killed by a vehicle on state highway 62 in Leopard Creek on the south boundary of the study area on October 7, 2011. This mortality made the fourteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 14 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Thirty-five adult pumas (26 females, 9 males) have worn GPS collars since this project began in 2004 (Table 19). Over 60 thousand GPS locations have been obtained and will be used for studies on 151 �puma behavior, social organization, population dynamics, movements, habitat use and puma-human relations in collaboration with colleagues in Mammals Research and Colorado State University. Segment Objective 6 A pilot survey of prevalence of Trichinella spp. in puma from southwest Colorado was initiated by Mammals Researcher Ken Logan and Dr. Mason Reichard of Center for Veterinary Health Science, Oklahoma State University, Stillwater, OK. Summary: The current pilot study documented the occurrence and high prevalence of Trichinella spp. in Puma concolor from Colorado. Twelve of 14 (85.7%) puma tongues were infected with Trichinella. The high prevalence of the zoonotic nematode in Colorado pumas justifies expansion of the sampling area to include pumas from a broader geographical scale. Background: Trichinella spp. are zoonotic nematodes capable of infecting humans and other animals. Wild animals and humans throughout the world become infected when they ingest infected tissue containing the parasite. Infection in humans of Trichinella spp. may result in nausea, diarrhea, vomiting, fatigue, fever, abdominal discomfort, headaches, chills, cough, eye swelling, and may even lead to heart and breathing problems. In severe cases, infection of Trichinella spp. may result in death. Hunting of pumas in Colorado has substantial historical, cultural, recreational, and economic importance. However, little current research and literature (either public or peer-reviewed) is available regarding the prevalence of Trichinella in Colorado puma and the potential for human infection. In 1995, an outbreak of trichinellosis in 10 people from Idaho County, Idaho was reported from the consumption of improperly prepared cougar jerky (Vollbrecht et al. 1996). The outbreak of trichinellosis in Idaho stresses the importance of wild carnivores as reservoirs of Trichinella spp. infections to humans (Kennedy et al. 2009). In addition to Idaho, pumas infected with Trichinella spp. have been reported from Montana (Worley et al. 1974; Winters 1969), Oregon (Rausch et al. 1983), Wyoming (Worley et al. 1974), and British Columbia, Canada (Gajadhar and Forbes 2010). The purpose of the current pilot study was to determine if puma from southwest Colorado were infected with Trichinella spp. The specific objectives were to: 1. Determine the prevalence of Trichinella spp. in P. concolor from southwest Colorado. 2. Determine which species of Trichinella is/are present in P. concolor from southwest Colorado. 3. Establish baseline data on the occurrence, prevalence, and distribution of Trichinella spp. in southwest Colorado. Pilot Project Design: Tongues from hunter-killed pumas were artificially digested to detect Trichinella spp. larvae. Infection with Trichinella spp. was assessed according to sex, age class, and geographic location of capture. Collection of Tissue from Pumas Tongues from dead pumas were collected by Mammals Researcher Ken Logan from pumas that were killed by sport-hunters (n = 12) and for depredation control (n = 2) in GMUs 61, 62, 64, 65, 66, and 521 representing Delta, Gunnison, Montrose, and Ouray counties in southwest Colorado. Jaws of the cats were opened, tongue firmly grasped, and pulled out of the mouth. One-half to three-quarters of the puma’s tongue was cut from the carcass using a clean knife or sterile scalpel. Excised tongues were placed in zip-top bags, labelled with sex, age estimate, and unique identifiers according to the host puma and location of where and when the sample was collected. Tongues samples were then frozen (-20 C) until they were shipped to Oklahoma State University for analysis. 152 �Determination of Trichinella Infection Infection with Trichinella sp. was determined by tissue digestion of tongues from puma (Webster et al., 2006). Puma tongues were weighed and homogenized in a Polytron (Kinematica GmbH, Kriens-Luzern, Switzerland). Ground samples were mixed with 10 ml of artificial digestive fluid (1% pepsin [1:3,000 IU] and 1% hydrochloric acid) per 1 gram of tissue. Digests were then mixed vigorously on magnetic stir plats at 37° C for 3 hours. Digests were allowed to settle for 20 min and the sediment containing Trichinella larvae were washed with tap water and enumerated under 40x magnification. Results were recorded as the number of larvae recovered per gram of tongue tissue digested. Results: Fourteen pumas were tested for infection with Trichinella. Twelve of the 14 (85.7%) were infected with Trichinella (Table 20). Because the prevalence of Trichinella infection was high and the sample size was relatively small, additional statistical comparisons of sex and age classes were not made as they were unlikely to yield useful information. Based on previously published data on the prevalence of Trichinella spp. in pumas from other locations (Winters 1969; Worley et al. 1974; Vollbrecht et al. 1996), we anticipated that approximately 50% of the pumas from southwest Colorado would have been infected. However, the prevalence of Trichinella in pumas was much higher than originally thought. The common occurrence of the zoonotic parasites in pumas from southwest Colorado coupled with the fact that consumption of improperly prepared meat from wild felids can infect humans (Vollbrecht et al. 1996) necessitates continued sampling from a broader geographical area in Colorado to determine infection risk to humans. Project Continuation: Trichinella larvae recovered from these twelve pumas will be submitted to the International Trichinella Reference Center (ITRC, www.iss.it/site/Trichinella/) in Rome, Italy for genotyping to identify the species of Trichinella. Individual Trichinella larvae will be identified by a multiplex PCR analysis following the protocol described by Zarlenga et al. (1999) and modified by Pozio and La Rosa (2003). Briefly, DNA will be extracted from individual worms and PCR will be performed using ExTaq DNA polymerase (Takara) in 50 ml containing 1.5 mM MgCl2, 200 mM dNTPs, 50 pmol of each primer and 0.5 unit of ExTaq DNA polymerase. The PCR-amplified fragments from purified DNA will be visualised by agarose gel electrophoresis (2.0% standard agarose). When Trichinella larvae were counted from infected pumas, we noticed that the majority of the worms were still alive after being frozen for at least 6 months or longer. The trait of freeze resistance suggests the Trichinella in pumas from southwestern Colorado are either T. nativa or Trichinella genotype T6 (i.e., the two freeze resistant species in North America). However, T. murrelli, not freeze resistant, is the species of Trichinella most commonly recovered from wild animals in temperate areas across North America. Fifteen additional puma tongues from southwest Colorado were collected to accumulate a larger sample size during the 2011 to 2012 puma hunting season. Those tissues will be analyzed for prevalence of Trichinella by Dr. Mason’s laboratory in 2013. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 7.7 years of effort 168 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 34 adult females, 21 adult males, 11 subadult females, 16 subadult males, 45 female cubs, 71 male cubs, and 1 cub of undetermined sex (some individuals occur in more than one stage class). Data from marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a 153 �reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CPW wildlife biologists and managers for assessing puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now 3 years of the treatment period are complete (TY1, TY2, TY3). Although data support some CPW puma management assumptions (e.g., population structure, density, how sport-harvest can cause population decline), it is still too early in this research to adequately test all the assumptions and attendant hypotheses. Although the assumption and hypothesis on harvest structure and hunter selection is not supported with the first 3 years of data in the treatment period, this could change with a substantial change in abundance and sex structure of independent pumas available for hunting in TY4 and TY5. The puma harvest quota for TY4 is recommended to be 5 independent pumas to align with the research design and harvest objective, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes across the various life stages and sexes. We will continue to explore methods for estimating puma abundance with accurate and affordable methods. 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Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Vollbrecht, A., D. Sokolowski, W. Hollipeter, R. Sigler, J. Greenblatt, D. E. Anderson, P. J. Tennican, H. R. Gamble, and D. Zarlenga. 1996. Oubreak of trichinellosis associated with eating cougar jerky – Idaho, 1995. Morbidity and Mortality Weekly Report 45: 205-206. Webster, P., C. Maddox-Hyttel, K. Nockler, A. Malajauskas, J. van der Giessen, E. Pozio, P. Boireau, C. M. O. Kapel. 2006. Meat inspection for Trichinella in pork, horsemeat and game within the EU: available technology and its present implementation. Eurosurveillance 11:50-55. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Winters, J. B. 1969. Trichiniasis in Montana mountain lions. Bulletin of the Wildlife Disease Association 5: 400. Worley, D. E., J. C. Fox, J. B. Winters, and K. R. Greer. 1974. Prevalence and distribution of Trichinella spiralis in carnivorous mammals in the United States northern Rocky Mountain region. Proceedings of the 3rd International Conference on Trichinellosis, Florida, USA, November 2-4, 1972. Zarlenga, D.S., Chute, M.B., Martin, A. and Kapel, C.M. 1999. A multiplex PCR for unequivocal differentiation of all encapsulated and nonencapsulated genotypes of Trichinella. International Journal for Parasitology 29:1859–1867. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 156 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Year RY4 RY5 TY1 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 Independent Pumas Cub 20 33 42 Total 33 45 53 Lambda 1.37 1.17 Table 2. Pumas harvested by sport-hunters in Treatment Year 3 (TY3) on the Uncompahgre Plateau Study Area, Colorado, November 21 to December 23, 2011. Puma sex Age (yr.) Date of kill Location/UTM NAD27 Zone, Easting, Northing 1.6 Previous M/F I.D. or specimen P no. if not marked P1038 M 12/5/2011 M 1.4 M120 12/6/2011 F 9.5 F3 12/11/2011 F 8 F75 12/14/2011 F 7 F70 12/22/2011 M 1.1 P1049 12/23/2011 M 2.5 M138 12/23/2011 M 1.3 M141 12/23/2011 Cottonwood Fork of Dry Creek 12, 756280, 4250547 Spring Creek 13, 238681, 4249866 Lindsay Creek 13, 238911, 4252542 Cottonwood Creek (W) 12, 732894, 4239423 Spring Creek, Puma Fork 13, 239323, 4243719 Hills west of Colona, CO 13, 256132, 4245751 Horsefly Creek (E) 13, 249592, 4240770 Little Bucktail Creek 12, 752201, 4239371 157 Hunter/status Ray David/resident Gary Gleason/resident Kari McClanahan/ resident Joe Gray/non-resident Dustin Gleason/resident Dawson Flowers/ resident Darren Reed/resident Kenneth Sowell/ resident �Table 3. Four other independent VHF/GPS-collared and 3 non-collared adult pumas in the minimum count for the Uncompahgre Plateau Study Area that died during the 2011-2012 Colorado puma hunting season. Puma sex (M or F) M87 Age (yr.) 3.4 Date of kill/death 12/6/2011 M67 4.4 12/18/2011 F119 7.5 1/28/2012 F104 11 1/31/2012 M 5.5 12/6/2011 M 3 1/17/2012 F 6 1/18/2012 Place of kill/UTM NAD27 Zone, Easting, Northing Forty-seven Canyon, Tabaguache Canyon 6.5 km N of study area Lower Tabaguache Canyon 12.61 km NW of study area 12, 707031, 4247827 Clay Creek 12, 743719, 4228535 Lower Roubideau Creek, died 1.73 km N of study area 12, 748282, 4288223 Cottonwood Creek north of Roubideau Canyon 0.66 km N of study area 12, 736764, 4274349 Specie Creek 1.65 km S of study area 12, 752861, 4211534 Pinto Mesa 1.02 km N of study area 12, 721658, 4247479 Hunter/status/other cause John Elmer/rresident/S. Garvey Outfitter Karl Red/resident Ruptured uterus and blood loss associated with pregnancy Starvation, probably associated with senescence Brett Merritt/non-resident Trailed from study area/R. Navarrete Outfitter Alan Hatfield/resident Trailed from study area James Williams/nonresident/S. Garvey Outfitter Radio-collared cub M162 ranged on study area Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1), November 2010 to April 2011 (TY2), and November 2011 to April 2012 (TY3) Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 TY3 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 2 West slope 14 5 3 5 1 2 subtotals 27 9 4 8 5 4 Total Independent Pumas = 48, including 31 females, 17 males. Cubs = 19 Unknown sex 4-8* 5-6 9-14 7 9 16 4 6 10 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 158 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 3 (TY3) on the Uncompahgre Plateau Study Area, Colorado, November 21 to December 23, 2011. Data are from puma hunter responses in 36 voluntary surveys, including: 31 original surveys on printed voluntary permits and 5 telephone contacts with hunters that did not return printed surveys on permits. Total response rate from 74 individual permitted hunters was 48.6 % (36/74 = 0.486*100). Puma sex/age stage/mark F/adult/collar/eartags Date of capture 12/4/2011 M/young/no marks 11/30/2011 to 12/5/2011 12/14 to 16/2011 F/adult/F75/ collar/eartags/caught twice M/young/no marks F/no marks 11/30/2011 to 12/5/2011 12/20 to 23/2011 Capture location Hunter name Transfer Rd., Roubideau Cyn. Dry Park. George Quintana Cottonwood Cr. Thomas Barnes Dry Park. Ross Ward Loghill Mesa Zachary Prock Eric Franklin 159 Reason for releasing the puma given by hunter Did not want to kill a female. Observed the puma on the road. Did not want to kill a small male. Caught F75 twice. Did not want to kill a puma. Wanted to take photos. Did not want to kill a small male. Same male caught with Eric Franklin (above). Did not want to kill a female. �Table 6. Summary of puma capture efforts with dogs from December 27, 2011 to April 12, 2012, Uncompahgre Plateau, Colorado. Month December No. Search Days 4 January 25 February 20 March 22 No. & type of puma tracks founda,b 16 tracks: 4 male, 10 female, 1 cub, 1 undetermined independent puma Tracks ≤1 day old: 2 male, 8 female, 0 cub 103 tracks: 12 male, 56 female, 31 cub, 4 undetermined independent pumas Tracks ≤1 day old: 4 male, 31 female, 23 cub, 1 undetermined 71 tracks: 9 male, 44 female, 17 cub, 1 undetermined independent puma Tracks ≤1 day old: 7 male, 26 female, 9 cub, 1 undetermined No. & type of pumas pursued 4 pursuits: 2 male, 2 female, 0 cub No. & I.D. or type of pumas captured, observed, or identified 2 pumas captured 2 times: adult female F137 and dependent young F152 (of F93). In addition, adult females F93 and F111 were associated with tracks by VHF telemetry. 39 pursuits: 3 male, 19 female, 16 cub, 1 undetermined 12 pumas captured 14 times: F93, F96, M170 (cub of F171), F171, cub (not handled, of F171), F8, F140, F149 (cub of F23), M160, M161 twice (cub of F23), F163 twice, M162 (orphaned cub). In addition, adult females F23 (3 times), F93 (2 times), F136, F137, F149 (2 times), F152 (2 times), M170, and F171 were located by VHF telemetry in association with tracks. 9 pumas captured 9 times: F28 (not handled in hole), F129 (not handled, dangerous tree), M131 (not handled, dangerous tree), F163, M164, M165, PF1051 (biodarted, not handled in dangerous tree), PF1052 (biodarted, not handled in dangerous tree), cub (not handled in dangerous tree, of non-marked female). In addition, adult females F23 (2 times), F93, F95, F96 (2 times), F136, F137, F171, adult male M164, subadult females F147 and F163 (3 times), and cubs F152 and M162 (2 times) were associated with tracks by VHF telemetry. 2 pumas captured 2 times: F149, M161. In addition, adult females F23, F95, F96, F171, subadult females F140 and F149, cubs M161 and M170 were associated with tracks by VHF telemetry. 27 pursuits: 6 male, 13 female, 8 cub 66 tracks: 12 male, 18 pursuits: 2 male, 39 female, 14 cub, 1 12 female, 4 cub undetermined independent puma Tracks ≤1 day old: 2 male, 16 female, 4 cub April 8 12 tracks: 6 male, 1 pursuit: 0 pumas captured. None associated with tracks 5 female, 1 cub 1 male with VHF telemetry. Tracks ≤1 day old: 1 male, 2 female, 1 cub 79 268 tracks: 89 pursuits: 21 individual pumas were captured 26 times with TOTALS 43 male, 14 male, aid of dogs. In addition, 17 radio-collared pumas 154 female, 46 female, were detected 40 times by tracks and identified 64 cub, 28 cub with VHF telemetry ≤1 km from the tracks. 7 undetermined 1 undetermined Tracks ≤1 day old: 16 male 83 female 37 cub 2 undetermined a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Each capture season researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day to gather data on vulnerability to detection using methods similar to puma hunters. For 2011-2012 (TY3) the count was: 70 tracks of females, including 17 of those associated with cubs; 2 tracks of 2 orphaned cubs; 12 tracks of males; and 2 tracks of undetermined sex. 160 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma I.D. M160 F163 M164 M165 F171 F172 Sex Estimated Age (mo.) 19 18 19 19 27 33 M F M M F F Mass (kg) 46 43 56 56 45 NM* Capture date 1/18/2012 1/26/2012 2/14/2012 2/24/2012 1/20/2012 3/28/2012 Capture method Dogs Dogs Dogs Dogs Dogs Cage trap Location Sanborn Park, head of Albin Draw San Miguel Canyon E of Pinyon Pinto Mesa, moved from Big Bucktail Canyon Head of Coal Canyon McKenzie Butte Monitor Canyon, Roubideau Canyon *Not measured. Table 8. Pumas that were captured and observed with aid of dogs, some of which were biopsy-darted and given specimen numbers (e.g., P1051), but were not handled at that time for safety reasons, and a puma killed for depredation control, December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma sex & I.D. F P1035 F P1051 Age stage or months 18 Capture date 10/22/2011 adult 2/13/2012 F P1052 Unknown none Unknown none adult 2/29/2012 cub 4 to 5 cub 8 to 10 1/12/2012 2/29/2012 Location Comments Dallas Creek, Pleasant Valley. Potter Canyon, Roubideau Canyon. Puma killed by Wildlife Services agent for killing a domestic llama. Puma not previously marked. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. In association with a single cub about 8 to 10 months old, which also could not be handled due to dangerous tree. Puma climbed dangerous tree Biopsy-darted to obtain tissue sample for genotype. Puma cub climbed high in dangerous tree. Probably 1 of 2 cubs of F171. Puma cub climbed high in dangerous tree. Not handled. In association with P1051 above. Monitor Canyon, Roubideau Canyon. E Loghill Mesa. Monitor Canyon, Roubideau Canyon. Table 9. Pumas recaptured with dogs (none in cage traps) December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma I.D. F152 Recapture Date 12/27/2011 Mass (kg) Observed Estimated Age (mo.) 18 Capture Method/ Location Dogs/Dry Cr. Basin F137 F96 F140 F93 12/28/2011 1/9/2012 1/13/2012 1/17/2012 Observed 44 47 Observed 35 72 17 109 F8 F152 F149 M161 F163 F129 1/17/2012 1/18/2012 1/24/2012 1/24/2012 1/27/2012 2/2/2012 Observed 43 Observed Observed Observed Observed 104 19 9 9 18 18 Dogs/W Fk. Dry Cr. Dogs/lower Delores Cr. Dogs/Tomcat Cr. Dogs/Lower Linscott Cyn. Dogs/Coal Canyon Dogs/Shavano Mesa Dogs/Big Bucktail Cyn. Dogs/Big Bucktail Cyn. Dogs/Maverick Draw Dogs/Dolores Cyn. M131 2/2/2012 Observed 18 Dogs/Dolores Cyn. F163 F28 2/9/2012 2/16/2012 Observed Observed 19 107 Dogs/San Miguel Cyn. Dogs/San Miguel Cyn. F149 M161 3/5/2012 3/5/2012 29 Observed 11 11 Dogs/Tomcat Cr. Dogs/Tomcat Cr. 161 Process F152 climbed dangerous tree. Could not be handled to fit with radiocollar. None. Replaced faulty GPS collar. Fitted with VHF collar. None. None. Fitted with GPS collar. None. None. None. F129 climbed dangerous tree. Could not be handled to fit with radiocollar. M131 climbed dangerous tree. Could not be handled to fit with radiocollar. None. F28 took refuge in hole. Could not be handled. Replaced VHF collar on F149. None. �Table 10. Summary of puma capture efforts with cage traps from October 5, 2011 to April 11, 2012, Uncompahgre Plateau, Colorado.* Month October November No. of Sites 6 7 March 2 April 5 Carnivore activity & capture effort results No pumas scavenged 7 mule deer carcasses used at the sites. Unknown male puma scavenged deer carcass on SE Loghill Rim 11/9/2011; attempted capture with cage trap; male puma did not return. Unknown male puma walked ~100 m from deer carcass at same bait site above 11/22/2011, but did not scavenge the bait. Unknown male puma walked ~1.5 m from a deer carcass at same bait site as above 11/29/2012, but did not scavenge the bait. Puma F172 captured in cage trap baited with mule deer carcass 3/28/2012. Unknown female puma and lone cub scavenged mule deer carcass at another bait site 4/68/2012. The pumas were pursued with dogs on 4/9/2012, but were not captured. No pumas scavenged 5 mule deer carcasses used at the sites. * We used 21 road-killed mule deer at 18 different sites. Of the road-killed deer baits, 3 of 21 (14.29%) were scavenged by pumas. Table 11. Puma cubs sampled August 2011 to July 2012 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M154 M155 M156b F157 F158 M159 M161c M162d M170e M M M F F M M M M 7/6/2011 7/6/2011 8/20/2011 8/18/2011 8/18/2011 8/18/2011 4/22/2011 7/2011 8/2011 42 42 43 40 40 40 276 183 137 2.6 3.0 3.25 2.5 2.5 2.5 24 12 9 F135 F135 F137 F70 F70 F70 F23 Nonmarked F171 33 33 30 76 76 76 80 Adult 22 a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Probably more than one cub in F137’s litter; others probably hiding in a hole at the nursery. c M161 is sibling of F149; birth date known from radio-telemetry on mother F23. d M162 was observed with one non-marked sibling on 2/7/2012. Both cubs were orphans; their mother non-marked mother apparently killed by a hunter on 1/18/ 2012 on Pinto Mesa. e M170 was observed with one sibling on 1/12,13/2012. Mother F171 was captured for first time on 1/20/2012. 162 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2012, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day Dec. 27, 2011 To April 12, 2012 268/79 = 3.39 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 81/15 = 5.40 day/capture 89/79 = 1.13 pursuit/day 26/79 = 0.28 capture/day 11 pumas captured for first time 11/79 = 0.14 capture/day 79/89 = 0.89 day/pursuit 79/26 = 3.04 day/capture 79/11 = 7.18 day/capture 163 15 pumas captured for first time 15/81 = 0.18 capture/day �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2012. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) F2 F2 F2 F3 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F8 F16 F16 F16 F23* F23 53 67 89 36 50 62 84 107 67 82 106 24 37 60 95 32 52 75 21 45 F23 80 F24 F24 75 114 F25 F25 F25 F25 74 94 110 129 F28* F28 F28 F30* F50 F54 F70* F70 F70 F72* F72 F72 36 48 68 48 21 24 38 52 76 28 51 64 F75 F75 F93 F93 F94* F94 F96 F104 F111* F116g 32 55 56 90 46 60 55 110 32 36 Dates pairs consortedb Estimated birth datec M73 49 02/28-29/08 M6 80 01/13-14/09 M27 or M29f M67 78 107 53 02/19-25/08 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 01/28-31/11 04/22/11 M29 92 04/12-15/07 06/14/07 09/10 M6 37 06/22-24/05 M51 M55 60 69 03/31/08 03/28-31/10 08/01/05 04/16/07 08/19/08 3/10 M29 88 12/27-29/06 M55 34 04/16-20/07 M51 60 03/10/08 M73 61 02/11/09 M55 M55 70 71 04/15/10 05/21/10 164 06/09/06 03/30/07 11/08 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 08/18/11 07/09/08 06/12/10 07/15/11 06/01/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 08/21/10 07/08/10 06/16/10 2009 Estimated birth interval (mo.) Estimated gestation (days) Observed number of cubsd 19.9 22.7 91-92 23.8 87-93 3 2 4 1 2 3 3 2 2 4 3 2 4 2 2 4 4 3 3 3 Nonfunct.GPS 84-86 2 90-93 4 3 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 90-91 Nonfunct.GPS 1 1 2 3 20.5 16.1 Nonfunct.GPS 11.7 92-93 88-92 87 14.8 23.6 23.1 13 23.2 93 13.3 91 2 ≥2 tracks 1 3 1 1 3 3 3 1 2 3 photographed 1 2 2 2 3 3 4 3 2 2 �Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) Table 13 continued. Dates pairs Estimated consortedb birth datec Estimated birth interval (mo.) 23 Estimated gestation (days) Observed number of cubsd ≥1 observed F119 66 08/09 2 F119i 96 02/12 29 1 plus 1-2 expected expected expected uterine scars F135 33 07/06/11 2 F136j 39 07/10/11 ≥1 remains F136 51 07/05/12 12 2 F137 30 07/08/11 ≥1 F171 22 08/11 2 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. h One cub observed with F118 in Maverick Draw 7/19/2012. i F119 died of a ruptured uterus and internal bleeding on 1/28/12. Cub in uterus in third trimester; 1-2 uterine scars indicated expulsion of 1-2 fetuses. j Remains of F136’s cubs found 8/9/11. Cause of death predation by puma or black bear. F118h 50 06/20/2012 165 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2012, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 08-23-07 to 12-18-11 M71 01-29-08 to 11-12-09 M73 02-21-08 to 10-26-11 M87 02-09-11 to 12-06-11 M90 11-16-10 to 11-23-10 M100 03-27-09 to 07-31-09 M114 02-27-10 to 03-10-12 M133 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Dead. M67 is offspring of F30. Dispersed natal area. Established territory on W side U.P. study area. Killed by a puma hunter in Tabaguache Creek 12-18-2011 at age 52.9 months. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Dead. Illegally killed 10-26-2011 in Bear Pen Gulch, upper East Fork Escalante Canyon; shot through abdomen during second rifle season. M73 was about 80 months old at death. Dead. M87 is offspring of F3. Dispersed from natal area. Established territory on W side of U.P. study area. Killed by a puma hunter in 47 Canyon, Tabaguache Canyon 12-06-2011. M87 was 41 months old at death. Dead. M90 was killed by a hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Dispersed from U.P. study area after 06-23-10. Killed by a puma hunter in Beaver Creek, NE of Canyon City, GMU59, 03-10-12. M114 was about 55 months old at death. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. 166 �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 07-01-11 to 12-23-11 M144 09-01-11 to 07-31-12 M153 M165 09-01-11 to 09-13-11 07-01-12 to 07-31-12 F2 01-07-05 to 08-14-08 F3 01-21-05 to 12-11-11 F7 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-12 10-11-05 to 09-11-09 F23 02-05-06 to 06-06-12 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 02-16-12 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 01-14-08 to 12-22-11 F72 02-12-08 to 12-21-11 F75 03-26-08 to 12-13-11 F93 F94 12-05-08 to 07-31-12 12-19-08 to 02-01-11 F95 F96 F104 08-01-09 to 07-31-12 01-28-09 to 07-31-12 05-21-09 to 01-31-12 Table 14. Continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Dead. Killed by a puma hunter in Horsefly Canyon (E) 12/23/11. M138 was about 29 months old at death. Alive. Initially captured as 18 mo. old subadult on W side U.P. study area 03-07-11. Established adult territory on NW U.P. Dead. Killed for depredation control; killed an alpaca in Pleasant Valley 09-13-11. Alive. Initially captured as 19 mo. old subadult on W side U.P. study area 02-24-12. Moved to Escalante Creek drainage by adult age 07-31-12. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Dead. Killed by a puma hunter in Lindsay Creek 12-11-11. F3 was about 120 months old at death. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Dead. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. F23 may have attempted to defend 2 cubs (F149, M161; 13.5 months old) and/or calf elk kill. Dead. Killed by a male puma in Logging Camp Draw about 09-16-11. F24 was about 126 months old at death. F24 may have attempted to defend ≥2 cubs (F147, nonmarked siblings; 12 mo. old). Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area 02-01-10 and 01-01-11 and 02-16-12, but could not be handled to replace non-functional GPS collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Dead. Killed by a puma hunter Spring Creek 12-22-11. F70 was 80 months old at death. Her death orphaned 2 cubs, F157 and F158, at 4 months old; both starved to death about 01-15-12 at about 5 months old. Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Photographed on Miller Mesa S of U.P. study area on 12-18 to 21-11 with 3 new cubs born about July 2012. Dead. Killed by a puma hunter in North Fork Cottonwood Creek 12-13-11. F75 was about 98 months old at death. Alive. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Dead. Died probably of starvation associated with senescence in lower Roubideau Creek 01-31-12. F104 was about 132 months old at death. 167 �Puma I.D. F110 Monitoring span 09-21-09 to 02-25-10 F111 F113 01-01-10 to 07-31-12 01-26-10 to 06-06-10 F116 01-20-10 to 09-20-11 F118 F119 02-25-10 to 07-31-12 03-25-10 to 01-28-12 F135 01-01-11 to 09-20-11 F136 F137 F143 F152 F163 F171 F172 01-20-11 to 07-31-12 01-21-11 to 07-31-12 02-15-11 to 07-31-12 06-16-12 to 07-31-12 07-01-12 to 07-31-12 01-20-12 to 07-31-12 03-28-12 to 07-31-12 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Dead. Died about 09-20-11 of unknown natural cause associated with pregnancy and birth of new litter of cubs. F116 was about 60 months old at death. Alive. Dead. Died of ruptured uterus and internal bleeding associated with pregnancy in Clay Creek Canyon 01-28-12. F119 was about 95 months old at death. Dead. Died of unknown natural cause in E Fork Dry Creek 09-20-11. Her death orphaned cubs M154 and M155 at 76 days old; both died of starvation or disease when 77 (M154) and 81 (M155) days old. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 168 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 2 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 2 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 3 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 4 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 5 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annual 1b 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males 0.947c 0.0568 19 0.250 0.1082 9 Treatment Annual 2 8/1/2010 to 7/31/2011 0.548d 0.1063 20 0.167 0.1076 7d Treatment Annual 3 8/1/2011 to 7/31/2012 a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a nonfunctional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. d Sample includes M144, ranges on NW Uncompahgre Plateau N of the study area but not on the U.P. study area, vulnerable to annual hunting. 169 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2012, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 31 M31 04-19-06 to 04-26-06 7 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Survived to adult stage. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. M69 01-11-08 to 04-07-08 190 87 Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. Died in subadult stage. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. Mother F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 170 �Puma I.D. F95 Monitoring span 12-29-08 to 07-31-12 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M120 12-06-12 1 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 155 F140 01-13-12 to 07- 31-12 200 M141 12-23-11 1 M144 03-07-11 to 09-08-11 185 F145 03-08-11 to 09-08-11 184 F146 03-08-11 to 03-23-11 15 F147 09-16-11 to 04-12-12 209 Table 16 continued Status Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Died in subadult stage. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. M112 was offspring of F70. Lost contact of M112 after 04-18-11; he may have dispersed or radiocollar quit. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-1811. Died in subadult stage. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. Died in subadult stage. M120 was offspring of F3. M120 was killed by a puma hunter 12-06-12 in his natal area in Spring Creek. He was 17 months old at death. Survived to adult stage (barely). M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Survived to adult stage. Entered adult life stage 07-01-11. Killed by a puma hunter 12-23-11 in Horsefly Canyon. M138 was about 29 months old at death. Survived to late subadult stage. Will turn adult in Aug. 2012. Probably offspring of F28. Has established a home range adjacent to natal area where she was initially captured at 5 months old on 01-02-11. Died in subadult stage. M141 was killed by a puma hunter on 12-23-11 in Little Bucktail Creek. He was 16 months old at death. Survived to adult stage. Emigrated from U.P. study area. Established adult territory on northwest Uncompahgre Plateau. M144 is sibling of F145 below. Survived to adult stage. Emigrated from U.P. study area and to Colorado Mesa. Killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. Died in subadult stage. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Lost contact; radiocollar quit after 04-12-12. F147 orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-1611. 171 �Puma I.D. F149 Monitoring span 06-06-12 to 07-31-12 No. days 55 M150 03-28-11 to 04-11-11 14 F152 05-04-12 to 06-16-12 44 M153 04-12-11 to 09-06-11 147 M161 06-06-12 to 07-31-12 55 F163 01-26-12 to 07-01-12 157 Table 16 continued. Status F149 (sibling of M161 below) was orphaned at 13.5 months old when her mother F23 was killed by a male puma. F149 dispersed from the natal area by 07-16-12 to E side U.P. study area when she was 14.8 months old. Dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Survived to adult stage. F152 was independent from her mother F93 by 05-04-12 when about 23 months old. She ranged as a subadult and adult on the natal area (07-31-12). Survived to adult stage. Consorted with F137 when 23 months old on 09-07-2011. Killed by Wildlife Services agent for depredation on an alpaca in Dallas Creek on 09-13-11. M153 was 23 months old at death. M161 (sibling of F149 above) was orphaned at 13.5 months old when his mother F23 was killed by a male puma. M161 dispersed from the natal area by 06-29-12 to E side U.P. study area when he was 14 months old. F163 was captured at about 18 months old on the study area. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (07-16-12 most recent location). 172 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2012. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a puma hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 53.2 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 42.8 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29.5 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61N on 1227-09 when he was 38.9 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek GMU 61N in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 173 �Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a puma hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 41.5 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 27.8 months old. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 12S,726901E, 4243463N→ 13S,255316E, 4216768N 60.5 M83 07-05-08 90.7 M87 07-31-08 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N M88 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N 21.9 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N 57.7 80.7 369.6 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a puma hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a puma hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 30 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is was resident adult on the west slope of the study area. He was killed by a puma hunter on 12-06-11 at 41 months old north of the study area. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a puma hunter in Dawson Creek, Disappointment Valley on 11-3010 when he was 29 months old. M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. 174 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M107 06-28-09 M114 02-27-10 M117 02-05-10 13S,242359E, 4252618N→ 12S,754886E, 4341330N 13S,256933E, 4237862N→ 13S,492615E, 4266192N 12S,731840E, 4232346N→ 12S,743909E, 4216633N M126 09-05-10 M144 03-07-33 M161 01-23-12 F52 01-10-07 F97 02-04-09 12S,727529E, 4237648N→ 12S,705930E, 4227299N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N 12S,734503E, 4224636N→ 12S, 710850E, 4239350N 12S,727173E, 4242012N→ 12S,696439E, 4276888N 12S,727932E, 4239430N→ 12S,750473E, 4247250N 13S,258058E, 4236260N→ 13S,319217E, 4240467N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 89.2 M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 237.5 M114 was initially captured at about 30 months old. Emigrated from the U.P. study area. He was killed by a puma hunter on 0310-12 in Beaver Creek, GMU59. He was about 55 months old at death. 19.7 M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. 27.7 M126 was offspring of F118, born Aug. 8, 2010. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. 46.6 M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area. Mother is unknown. He moved off the study area on 03-15-11. M144’s last aerial radio location was in Blue Creek on northwest Uncompahgre Plateau on 07-13-11; he was about 22 months old. M144 established his adult territory on northwest Uncompahgre Plateau and upper Unaweep Canyon from Sep. 2011 to July 2012. 23.9 M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old and moved to the east slope of the U.P. study area. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. 24.0 F97 was offspring of F23, born May 23, 2008. She was radiocollared at 8.5 month old in San Miguel Canyon; but, lost contact on 05-12-09 after F97 shed the radiocollar at an elk cache. F97 dispersed from the U.P. study area. She was killed by a puma hunter on 01-22-12 in Dry Creek west of the U.P. study area when she was 43.9 months old. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. 175 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N F143 02-15-11 F145 03-18-11 12S,723748E, 4238579N→ 12S,721795, 4264246 12S,727181E, 4241468N→ 12S,705833E, 4312909N F149 06-06-11 F163 01-26-12 12S,729993E, 4242329N→ 12S,715551E, 4285489N 12S,732153E, 4232452N→ 12S,695407E, 4280753N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 18.2 F108 was offspring of F94, born May 25, 2009; sibling of M107 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a puma hunter on the study area on 11-29-10 when she was 17 months old. 25.7 F143 was captured on the study area when about 24 months old. Dispersed N on the Uncompahgre Plateau and established an adult home range on the NW portion of the Uncompahgre Plateau (most recent location 07-16-12). 74.5 F145 was originally captured in association of M144 and F146; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145 emigrated to Colorado Mesa. She was killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. 45.5 F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old and moved to the NE Uncompahgre Plateau. 60.7 F163 was initially captured at about 18 months old. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (0716-12 most recent location). *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. 176 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2012. Puma sex & ID if marked M Estimated age (mo.) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision F 6 02-16-11 Vehicle Good P1030c collision M 4 10-07-11 Vehicle Fair P1034 collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 177 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N Highway 62 Leopard Creek 12S,762806E,4219531N �Table 19. Pumas monitored with GPS collars on the Uncompahgre Plateau, Colorado, December 2004 to July 2012. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 F2 F3 F7 F8 F16 F23 Sex M M M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F70 F72 F75 F96 F104 F111 F113 F135 F136 F137 F152 F F F F F F F F F F F F F F F F F F F171 F172 F F Age stage adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult adult adult subadult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult Dates monitored 12-08-04 to 07-20-06 01-28-05 to 01-14-06 02-18-05 to 05-14-08 03-12-06 to 06-21-06 04-14-06 to 01-01-08 01-07-07 to 07-15-08 01-21-07 to 11-25-10 03-27-09 to 01-16-10 11-12-10 to 12-01-10 01-07-05 to 08-14-08 01-21-05 to 12-11-11 02-24-05 to 08-03-08 03-21-05 to 10-10-06 10-12-05 to 09-10-09 01-04-06 to 02-04-06 02-05-06 to 09-04-09 01-17-06 to 07-25-07 02-09-06 to 09-09-09 03-24-06 to 08-15-07 03-30-07 to 02-22-08 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 08-18-08 01-14-08 to 12-22-11 02-12-08 to 07-07-10 03-26-08 to 06-03-09 01-28-09 to 07-31-12 05-29-09 to 01-31-12 01-01-10 to 07-31-12 01-27-10 to 06-06-10 01-01-11 to 09-20-11 01-20-11 to 07-31-12 04-12-11 to 07-31-12 01-18-12 to 06-15-12 06-16-12 to 07-31-12 01-20-12 to 07-31-12 03-28-12 to 07-31-12 178 �Table 20. Number of Trichinella larvae recovered from puma tongues, southwest Colorado, 2010-2011. Puma Seal Sex and/or I.D. Estimate Date Location: UTM Trichinella Larvae d Age collected NAD27 Per Gram (LPG) of Zone, Easting, Tongue Tissue (years) Number Northing F94 F 5 2/1/2011 13S,246976E,4255108N 1.2 12301 M 1.5 12/12/2010 12S,735100E,4249600N 5.1 6266 F 11-12 2/3/2011 13S,252703E,4225101N 0.4 (F25) 12039 F 4-5 11/22/2010 13S,283349E,4234088N 2.0 12042 M 3-4 11/26/2010 12S,736610E,4230762N 3.2 12045 M 2-3 12/1/2010 13S,283888E,4310965N 8.4 12046 M 3 12/1/2010 12S,729439E,4236264N 5.4 12047 M 9-10 12/2/2010 13S,257722E,4239169N 12048 M 2 12/3/2010 13S,261946E,4241911N 7.6 12302 M 2.5 12/17/2010 13S,316520E,4228320N 5.1 12314 F 5 1/13/2011 13S,305193E,4247057N 1.4 12317 M 1.5 1/17/2011 12044 F 1.5 11/29/2010 12S,752013E,4263883N M 6-7 11/25/2010 13S,239181E,4248300N (M32) 2.8 (F108) 12041 1.0 (M55) 179 0.0 0.0 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Puma Habitat Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Methods for Monitoring Populations Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 180 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Pun1a Population Trend, U. P., CO 60 0 RY4 IY.! I Yl YEARS - - \ i ir. imum Cour t - -Post Ha·vest Lov,.r - Post harv<::st Hi~n Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1, 2, and 3 (TY1, TY2, TY3). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected nonmarked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the state government hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 181 �independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. Post-harvest high trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 14.5% to 16.7% harvest of independent pumas. Post-harvest low trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting and other mortalities are subtracted from the minimum count. TY1 post-harvest low includes 1 adult female and 3 adult males killed off the study area. The TY2 post- harvest low includes 1 adult male killed off the study area and 2 adult female pumas killed in February 2011 on the study area to protect livestock. The TY3 post-harvest low includes 1 adult female and 4 adult males harvested off the study area and 2 adult females that died of natural causes on the study area. This trend line represents 21.2% to 31.2% harvest of independent pumas. Age structure of independent pumas in November 2011 at beginning of the puma hunting season in Treatment Year 3, Uncompahgre Plateau, Colorado. 8 7 ~ 6 8 s .... ~ 4 0 3 0 ■ Female Z 2 ■ Ma l e 1 0 lto 2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age (years) Figure 4. Estimated age structure of independent pumas in November 2011 at the beginning of the puma hunting season in Treatment Year 3 (TY3) on the Uncompahgre Plateau study area, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 5.85 ± 3.05 yr. (70.19 ± 36.57 mo.), n = 16; 2.25 ± 1.58 yr. (27.00 ± 18.95 mo.), n = 10. 182 �Puma births, Uncompahgre Plateau, Colorado. 14 12 10 ""~ ..,; ..,; 8 ;:i 0 z 6 4 ■ 7 2 0 I Jan. n ■ I I I I I I 17 11 11 I I I I I n I Feb. M ar. Apr. M ay Ju ne July Au g. Sep. Oct. Nov. Dec. ■ Bi1ths 2005-2012 ■ Births 1982-1 987 Figure 5. Puma births (black bars) detected by month from May 19, 2005 to July 5, 2012 (n = 46 litters of 24 females; 44 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 183 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2012, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) ~1,664 F9 31 5-28-05 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 F10 31 5-28-05 M11 31 5-28-05 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 F13 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 54.6 months old. Radio-collared. Shed radiocollar 04-19-06 to 04-26-06. F3 Radio-collared. Dhed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-2005. F10 disappeared by 12-30-05. Radio-collared. Shed collar 10-24 to 11-08-05. Recollared on 04-02-06. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 0711-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Radio-collared. Shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Radio-collared. Killed and eaten by a puma possibly M5 (13 mo. old) about 08-28-05. Radio-collared. Shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. F2 F2 F2 F7 F7 F8 F8 F16 308-314 Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Died at 10.8 months old Radio-collared. Probably killed by another puma. Multiple bite wounds to skull. Died at 10 months old. Radio-collared. Shed radiocollar 07-27-06 to 08-02-06. 244-245 Radio-collared. Shed radiocollar 05-24-06―05-25-06. F16 324 Radio-collared. Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 184 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 F35 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Radio-collared. Killed and eaten by male puma 12-21-05 to 12-22-05. F3 ~232-235 Radio-collared. Shed radiocollar 03-21-06 to 03-24-06. F25 63-65 F23 5-30-06 06-30-06 to 07-31-06 63-65 31 5-30-06 38 F36 29 6-9-06 29 6-9-06 M38 41 7-29-06 Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. Killed by puma hunter 01-07-11 in GMU40 Ladder Creek when he was 53.2 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 42.8 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F28 M37 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Radio-collared. Assumed dead. Shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Radio-collared. Shed radiocollar by 11-7 to 17-06. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO GMU41 at 29.5 months old. F7 74 74 352-353 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 1623 9 255 1307 9 Mother I.D. F23 F23 F28 F2 F8 F8 255 53-61 106 200 899 185 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 to 12-27-09 89 360 89 360 1187 12-05-06 to 07-31-07 to 01-01-07 ~456 186 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Radio-collared. Shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. M44 killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. He was 15.7 months old. Radio-collared. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Died 05-20 to 23-07 when she was 9.2 months old. Radio-collared. Shed collar by 12-14-06. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed collar . Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61N when 38.9 months old. Radio-collared. M49 was orphaned when his mother died on about 03-26-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61N) 01-24-09 when ~29 months old. Mother I.D. F7 F7 F3 F3 F3 F50 �Appendix A continued Puma I.D. Estimated Age at capture (days) F53 183 Est. Birth date 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. survival span from 1st capture to fate or last monitor date 01-12-07 to 02-23-07 to 09-02-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 42 Radio-collared. Shed radiocollar 02-23-07. F53 visually observed by P. & F. Star (Loghill Mesa), on 09-02-07, when F53 was ~14 months old and an independent subadult. F54 Radio-collared. Shed radiocollar 2-27-07. M56 observed 0301-07. Radio-collared. Shed radiocollar 06-07-07. Live mode 0606-07. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Radio-collared. Shed collar about 02-14-08. Observed with 11-20-07 with F16, but without siblings M58 and F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. Three cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F7 (?) Radio-collared. Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11-13-08. Not radio-collared. Not radio-collared. Dispersed from study area. Killed by a puma hunter 01-01-11 in Calamity Creek, GMU61N when he was 41.5 months old. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 ~428 subad. 200 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 to 01-01-11 1267 08-17-07 262 187 Mother I.D. F25 F16 F16 F16 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M65 34 Est. Birth date 7-14-07 Est. survival span from 1st capture to fate or last monitor date 08-17-07 to 11-07-09 Age to last monitor date alive or at death (days, birth to fate) Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 27.8 months old. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau. Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17.5 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. 262 847 F66 37 7-17-07 08-23-07 to 11-05-07 111 681 M67 37 7-17-07 08-23-07 to 12-18-11 M68 37 7-17-07 08-23-07 to 12-30-08 1615 532 F74 259 6-1-07 5-19-08 03-12-08 to 07-09-08 06-18-08 M76 30 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 188 Mother I.D. F24 F30 F30 F30 F75 F2 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) M79 30 5-19-08 Est. survival span from 1st capture to fate or last monitor date 06-18-08 F80 40 5-23-08 07-02-08 F81 40 5-23-08 F97 257 5-23-08 07-02-08 to 07-29-09 02-04-09 to 01-22-12 M82 37 5-29-08 07-05-08 to 12-10-09 560 M83 37 5-29-08 07-05-08 to 01-18-11 964 M84 36 6-5-08 07-11-08 to 02-11-09 251 F85 36 6-5-08 07-11-08 to 10-01-08 118 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 87 Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 08/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 02-04-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. 424 1339 Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Dispersed from study area. Killed by a puma hunter 01-22-12 in Dry Creek when 43.9 months old. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 18.4 months old. Not radio-collared. Survived; dispersed from study area. Killed by a puma hunter 01-18-11 on Glade Park, GMU40. He was 31.6 months old. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located her on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 0214-09. Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill at age 3.9 months. 189 Mother I.D. F2 F23 F23 F23 F8 F8 F70 F70 �Appendix A continued Puma I.D. Estimated Age at capture (days) F86 36 6-5-08 M87 28 M88 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-11-08 to 07-23 to 08-03-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death ~48-59 7-3-08 07-31-08 to 12-06-11 1251 28 7-3-08 07-31-08 to 11-30-10 880 F89 M90 28 36 7-3-08 7-9-08 07-31-08 08-14-08 Male 7A 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 28 to 35 M91 35 8-19-08 ~08-07-08 to 08-14-08 09-29-08 M92 35 8-19-08 09-29-08 976 F95 16 mo. June-07 12-29-08 F98 4-5 mo. Sep-Oct08 02-12-09 to 03-08-09 Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11. Alive as of 07-31-11. Killed by puma hunter on 12-06-11 at 41 months old north of the study area. Not radio-collared. Dispersed. Killed by a puma hunter in Disappointment Valley, GMU711 on 11-30-10 when 28.9 months old. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. Radio-collared. Killed by a puma hunter on study area during TY1 as dependent cub on 11-17-09 at age 14.9 months. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. To date, July 2012, F95’s home range mainly adjacent to N side of natal area. Radio-collared. Died; probably killed by male puma (infanticide). 867 455 146-176 190 Mother I.D. F70 F3 F3 F3 F72 F7 F7 F7 F25 F25 F93 Unm.F �Appendix A continued Puma I.D. Estimated Age at capture (days) M99 5 mo. Est. Birth date Sep-Oct08 M101 35 4-15-09 M102 35 4-15-09 F103 35 4-15-09 M105 38 5-7-09 F106 38 5-7-09 M107 34 5-25-09 F108 34 5-25-09 Est. survival span from 1st capture to fate or last monitor date 2-27-09 to 01-2010 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 488 Unm.F 05-20-09 to 09-19-09 05-20-09 157 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 159 Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma. Radio-collared. Died; killed by puma M55 after he was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 09-04-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after she was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 02-09-10 due to shed collar. Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 2-24-10; not collared. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11 at 18.1 months old. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11; he may have dispersed or radiocollar quit. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Killed by a puma hunter on the natal area in Beaver Creek, off the U.P. study area on 01-01-11 when he was 17 months old. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. 06-28-09 to 02-24-10 06-28-09 to 03-05-10 278 275 661 241 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 528 595 M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 to 01-01-11 518 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 191 F16 F16 F16 F75 F75 F94 F94 F94 F70 F28 F119 F72 �Appendix A continued Puma I.D. Estimated Age at capture (days) P1017(M) 39 6-12-10 M120 30 M121 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 06-12-10 to 07-21-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 39 F72 6-28-10 07-28-10 to 12-02-10 526 30 6-28-10 273 M122 35 7-8-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. Killed by a puma hunter on his natal area on 12-06-11 when he was 17.2 months old. Radio-collared. Lost radio contact after 03-28-11. F104 F123 29 7-15-10 217 F124 29 7-15-10 M125 29 7-15-10 M126 28 08-08-10 08-13-10 to 02-17-11 08-13-10 to 02-16-11 08-13-10 to 02-01-11 09-05-10 to 01-08-12 M127 28 08-08-10 09-05-10 to 09-10-11 398 M128 28 08-08-10 198 F129 35 08-21-10 09-05-10 to 02-22-11 09-25-10 to 02-02-12 M130 35 08-21-10 09-25-10 to 02-02-12 M131 35 08-21-10 09-25-10 to 07-21-11 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. Found dead 09-14-11 on natal area; killed by another puma on about 09-10-11 at age 13 months. Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Survived to recapture on 02-02-12 at 17.4 months old, with sibling M131; neither handled due to dangerous trees. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-0212 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. 274 216 201 221 530 530 334 192 Mother I.D. F3 F3 F94 F94 F94 F118 F118 F118 F96 F96 F96 �Appendix A continued Puma I.D. Estimated Age at capture (days) F132 35 08-21-10 M134 ~18 mo. M139 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-25-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 35 ~June-09 12-14-10 to 06-10-11 731 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 F140 ~5 mo. ~Aug.10 01-02-11 to 04-18-11 258 M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 241 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 04-21-11 to 07-31-11 315 F149 45 04-22-11 06-06-11 to 07-16-12 451 M150 525 08-31-09 02-07-11 to 04-11-11 588 M151 253 06-16-10 02-24-11 to 03-07-11 264 Not radio-collared. Too small for collar design. Fate unknown. Apparently died; not with F96 and siblings F129 and M130 on 02-02-12. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Recaptured and re-collared 01-12-12 as 17-month-old subadult on natal range. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. Orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-16-11. She ranged in her natal area until her radiocollar quit after 0412-12. Radio-collared. F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old. Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). 183 193 Mother I.D. F96 Unm. F F8 F8 Unk./ F28? Unk./ F28? Unk./ F28? Unk. F24 F23 F70 F111 �Appendix A continued Puma I.D. Estimated Age at capture (days) F152 271 06-16-10 M154 42 07-06-11 M155 42 07-06-11 M156 43 07-08-11 F157 40 08-18-11 F158 40 08-18-11 09-27-11 to 01-15-12 150 M159 40 08-18-11 09-27-11 to 12-01-11 105 M161 276 04-22-11 01-23-12 to 07-16-12 451 M162 183 07-25-11 01-25-12 to 06-11-12 322 M170 137 08-29-11 01-13-12 to 03-12-12 199 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 03-14-11 to 07-31-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 776 08-16-11 to 09-21-11 08-16-11 to 09-25-11 08-20-11 to 09-05-11 09-27-11 to 01-15-12 77 Radio-collared. Lost contact after 03-21-11; shed collar. Recaptured 01-18-12; fit with GPS collar at 19 months old; currently (July 31, 2012) a 25-month-old adult ranging on her natal area (philopatric). Radio-collared. M154 probably died of starvation following natural death of his mother F135. Sibling M155 also died. Radio-collared. M155 died of starvation following death of his mother F135. Sibling M154 also died. Radio-collared. M156 shed the collar about 09-05-11. He was 59 days old. F157 with sibling F158 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. F158 with sibling F157 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. M159 probably died about 12-01-11 when he was located with his family (F70, siblings F157, F158). He was not located with them on 12-12-11 and was not observed with them on 12-13-11. He was 105 days old on 12-01-11. M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 0629-12 when he was 14 months old. M162 probably was orphaned cub of non-marked adult female puma killed on Pinto Mesa 01-18-12. M162 died of starvation on 06-11-12 when he was 322 days (10.6 mo.) old. M170 died about 03-15-12 of unknown natural cause. He was 199 days (6.5 mo.) old. 81 56 150 194 Mother I.D. F93 F135 F135 F137 F70 F70 F70 F23 F171 �Appendix A continued Puma I.D. Estimated Age at capture (days) P1033 22 Est. Birth date 07-10-11 Est. survival span from 1st capture to fate or last monitor date NA Age to last monitor date alive or at death (days, birth to fate) 22 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Cub P1033 was offspring of F136. It died of predation, F136 probably killed by a puma or black bear in the nursery when about 22 days old, before researchers could examine the entire litter to sample and mark the cubs. a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. 195 � https://cpw.cvlcollections.org/files/original/bc30ee992c3291ecd16386953db83616.pdf 59e0ab0a34962daefadfa42d0affc1cd PDF Text Text Colorado Division of Parks and Wildlife July 2012 –June 2013 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project: W-204-R1 : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates on the Uncompahgre Plateau : Period covered: July 31, 2012−June 30, 2013 Author: Kenneth A. Logan. Personnel: K. Logan, R. Alonso, C. Anton, S. Bard, B. Dunne, W. Hollerman, W. Jesson, R. Navarrete, B. Nay, H. Taylor, S. Waters, B. Banulis, T. Bonacquista, K. Crane, J. Koch, E. Phillips, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation, Safari Club International Foundation, and The Summerlee Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Parks and Wildlife (CPW) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, years 1-5) and presence (treatment period, years 6-10) of sport-hunting. The purpose of the study is to evaluate assumptions underlying the CPW model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report provides information on the fourth year of the treatment period (TY4), August 2012 through July 2013, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 19 and closed December 29, 2012 after a quota of 5 independent pumas was harvested. The harvest was designed to test the management assumption that an 8-15% harvest of independent pumas results in a stable-to-increasing population. The decline in the puma population on the study area during TY1 to TY3 necessitated a reduction in the harvest quota from 8 to 5 to continue to test the harvest assumption for a stable-to-increasing puma population. A total of 5 pumas were killed: 2 adult females, 2 adult males, and 1 subadult male. The harvest of 5 independent pumas represented 11.9% of the 42 independent pumas in our minimum count during November 2012 to April 2013. Independent females and males comprised 40.0% and 60.0% of the harvest, respectively. Four other radio-collared independent pumas (3 adult females, 1 adult male) in the study area population died during the Colorado puma hunting season. Of those, 1 adult female died of natural cause and the remainder was killed by puma hunters in GMUs adjacent to the study area. The total mortality of 9 independent pumas during the TY4 hunting season represented 21.4% of the 42 minimum count of independent pumas on the study area. �Seventy hunters requested mandatory permits with an attached voluntary hunter survey in TY4. Forty-two of the hunters provided written responses on the surveys. An estimated 40 hunters actually hunted on the study area, of which about 12.5% harvested pumas and 15.0% captured pumas (i.e., harvested plus treed and released). Twenty of 24 answering hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks < 1 day old encountered by hunters and pumas captured by hunters indicated that independent male pumas were detected more frequently than females in TY4. Researchers captured forty-nine individual pumas captured 62 times from August 2012 to July 2013. Two capture teams with dogs operated over 74 search days from January 1, 2013 through April 18, 2013 to find 229 puma tracks, pursue pumas 82 times, and capture 29 pumas 42 times. Capture efforts with cage traps resulted in the capture of 4 independent pumas and 1 cub for the first time, and the recapture of 2 adult females. Twenty-one new cubs were captured and radio-collared. A total of 55 pumas were monitored by radio-telemetry in TY4. Search efforts also revealed the presence of at least 8 other independent pumas. Our minimum count of 42 independent pumas from November 2012 to April 2013 included: 31 females and 11 males. The minimum count of 42 independent pumas in TY4 was lower than 48 in TY3, 52 in TY2 and 55 in TY1, indicating a steadily declining population. A preliminary minimum estimated density of independent pumas was 2.51/100 km2. The proportion of radio-collared adult females giving birth in the August 2012 to July 2013 biological year was 0.60 (9/15). Since 2005 a birth peak has occurred from May through August, involving 84.9% of births. We monitored 19 female and 8 male adult radio-collared pumas for survival and agent-specific mortality. Adult puma survival rates in TY4 for adult females and males were 0.819 (SE=0.0931) and 0.188 (SE=0.0845), respectively. Sporthunting mortality was the major cause of death. Of 21 cubs monitored with radio-telemetry in TY4, 7 died and 1 orphaned cub was removed from the wild. Six died of infanticide and cannibalism by male pumas and 1 was killed by puma hunting dogs. One subadult male was killed by a hunter, and 1 subadult male was struck and killed by a vehicle on state highway 62. Puma harvest, capture, and radio-telemetry data from the beginning of this study to the present provided information on dispersals of 38 pumas initially marked on the study area. Those pumas moved from about 18 to 370 km from initial capture sites. Since the start of this study 45 adult pumas have been monitored with GPS collars and have yielded over 70,000 locations. Efforts to develop and test puma population survey methods continued with a collaborative effort with M.S. student K. Yeager and Mammals Researcher Dr. Mat Alldredge. This involved 54 sites in randomly selected cells in a grid system with predator call boxes, digital cameras, and hair gathering devices from December 2012 to March 2013. Pumas were photographed at the sites 18 times with all the photos depicting GPS/VHF-collared pumas. Seven of 11 collared pumas that used the grid were detected by photographs (p = 0.64). Six hair samples were acquired from 4 to 5 individual pumas. The quality of the hair samples for accurate genotypes has yet to be analyzed. �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN PROJECT NARRATIVE OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction of females, stage-specific survival, and immigration and emigration; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the third year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the fourth year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and stage-specific survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore non-invasive methods for sampling pumas to estimate abundance in collaboration with Dr. Mat Alldredge (Mammals Researcher, CPW) and Master of Science graduate student Kirstie Yeager, Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University. INTRODUCTION Colorado Parks and Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of “achieving healthy, self-sustaining populations” through management (Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma−prey interactions. Staff on the Front Range placed greater emphasis on puma−human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). �● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the grayshaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas to investigate the effects of sport-hunting and other causes of mortality on puma population dynamics. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CPW’s puma model-based management and attendant assumptions with Coloradospecific data from objectives 1−3. Consider other useful models. 5. Conduct a pilot study to develop methods that yield reliable estimates of puma population abundance. 6. Investigate diseases in pumas. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 which involves the use of controlled recreational hunting to manipulate the puma population. �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1−5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992), and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all stage classes - adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to provide allowable harvest quotas in an effort to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). These objectives are expected to provide both the capacity for puma population resiliency to achieve a state-wide goal of a healthy, self-sustaining puma population while managing the puma population to provide sport-hunting opportunity and population control in some DAUs (even though puma population dynamics in any DAUs are not known). Basic model parameters assigned to the model are: puma population density, sex and age structure, annual population growth rate, and relative puma habitat quality and quantity. Parameter quantities are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. An assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assume that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus �subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). This assumption is vital to providing the capacity for resiliency in the state-wide puma population which is hunted by applying this assumption to about three-quarters of the puma GMUs in the state. H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). This assumption is applied to about one-quarter of the GMUs in the state. H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. 6. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2007). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate �during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics relative to harvest. We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1986, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. Information which will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. People reside year-round along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area easily accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma populations in western North America for at least the past 100 years. Hence, the reference period, years 1 to 5, provided conditions where individual pumas in this population expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6 to10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e., effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to �hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were recorded via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and enabled dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snowmobiles, and on foot. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg based on estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). The immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers for capture were released without handling, or we encourage �the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and movement across Data Analysis Unit boundaries). Adults, subadults, and cubs were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHF- �collared pumas were identified about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using a hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around those locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes were recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters. Cubs were fit with small VHF transmitters mounted on expandable collars that expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3−11 kg (5−25 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with the Colorado puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). �Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2012 to July 2013, was the fourth year of the treatment period (TY4) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 19, 2012 and was scheduled to extend to January 31, 2013, unless the harvest quota was taken before then. The harvest design quota was 5 pumas. This represented an 11.1% harvest of the projected minimum number of 45 independent pumas expected on the study area during November through March in TY4 (Logan 2012). The expected number of 45 was derived with a simple linear model that regressed the number of independent pumas observed in TY1 (55), TY2 (52, and TY3 (48) on year and projected to TY4 (i.e., 45 expected). We reduced the harvest rate because the population of independent pumas was declining during TY1 to TY3, contrary to the expected population trend in this research project and the realization that the population would probably continue to decline with a 15% harvest rate. This harvest design still tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-toincreasing puma population (Assumption and Hypothesis 3 p.5-6 this report). The 11% harvest in TY4 is in the middle of the 8 to 15% harvest range we are testing. The initial quota of 8 pumas for TY1, TY2, and TY3 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY3 was based on the observed minimum count of 52 independent pumas during November 2010 to April 2011 in TY2 and that approximately the same number of independent pumas was expected during the puma hunting season for TY3. The hunting structure in TY4 was the same as in TY1 to TY3, except for the reduction in quota (see above). The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). All pumas harvested on the study area were examined by principal investigator K. Logan or a wildlife research technician and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon �inspection, the following data were recorded: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. The puma hunting season occurred on the study area from November 19 to December 29, 2012, taking 41 days to fill the quota of 5 pumas; the longest hunting season yet on the study area during this treatment period. This was 8 more days than it took to harvest 8 pumas in TY3 (i.e., 33 days, Nov. 21 to Dec. 23, 2011), 20 days more than it took to harvest 8 pumas in TY2 (i.e., 21 days, Nov. 22 to Dec. 12, 2010) and 15 more days than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Five pumas were killed on the study area, including: 2 adult females, 2 adult males, and 1 subadult male (Table 2). Of the 5 harvested pumas, 3 were marked: F152, M156 and M179. In addition to the pumas killed on the study area during the Colorado puma hunting season, 4 other marked independent pumas died (Table 3): adult female F93 was killed by another puma on the study area, and 3 pumas were killed by hunters on adjacent GMUs, including subadult female F149 (GMU 70), adult female F177 (GMU 65) and adult male M178 (GMU 65). All these pumas were included in the minimum count of pumas for TY4 because they were initially captured on the study area and were present in the population during the TY4 survey period (Nov.–Apr.). The harvest of 5 independent pumas on the study area was 11.9% (5/42*100) of the minimum count of 42 independent pumas counted on the study area, including 31 females and 11 males, determined by the research team during November 2012 to April 2013 (Table 4). Independent females and males comprised 40.0% (2/5*100) and 60.0% (3/5*100) of the harvest, respectively. This harvest structure was 6.4% (2/31*100) of the independent females and 27.3% (3/11*100) of the independent males. Considering the mortality of 4 other radio-collared independent pumas (F93, F149, F177, M178; Table 3), the mortality of 9 independent pumas was 21.4% (9/42*100) of the minimum number of 42 independent pumas. The mortality composition of 5 females and 4 males was comprised of 55.6% (5/9*100) females and 44.4% (4/9*100) males. This harvest structure was 16.1% (5/31*100) of the independent females and 36.4% (4/11*100) of the independent males in the minimum count. The minimum count of 42 independent pumas in TY4 was lower than the minimum count of 48 independent pumas in TY3, 52 independent pumas in TY2, and 55 in TY1 (Table 4) and indicates a consistently declining population (Fig.3.). The population decline is explained mainly by the declining number of independent male pumas (Table 4) and the relatively low adult male survival rates (see Table 15, later). The number of adult females have also declined, but to a lesser extent (Table 4). Hunter permits and survey: In TY4 mandatory permits with the voluntary survey attached were requested by 70 individual puma hunters. This number is slightly down from 74 in TY3, up from 64 hunters in TY2, and down from 79 hunters in TY1. Twenty-three of the hunters requested a second permit, 7 hunters requested a third permit, and zero hunters requested a fourth permit after a previous permit expired after 14 days. Forty-two hunters (60.0%; 42/70*100) provided responses to the voluntary survey by turning in the printed survey. Of the respondents, 18 hunters indicated that they did not hunt on the study area. The proportion of the 42 respondents that hunted extrapolated to the total of 70 hunters (24/42 = 0.571) indicated that about 40 hunters took to the field for pumas on the study area during the 41-day TY4 hunting season. This was down from 49 hunters in TY3, 42 hunters in TY2 and 67 hunters in TY1 (Logan 2010, 2011). Considering that 40 hunters were estimated to be afield, then 12.5% of the hunters harvested pumas (5/40*100) and 15.0% of hunters captured pumas (6/40*100; see captured and released pumas below and in Table 5). �The 42 puma hunters that turned in the written volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 20 respondents that answered the question (83.3%; 20/24 = 0.833). Of the remaining hunters, 4 indicated they were non-selective (16.7%). Eighteen hunters that returned surveys did not answer the question. The voluntary hunter survey also revealed that one hunter treed a puma on the study area, but chose not to kill it (Table 5). The hunter reported he treed a puma he believed to be a female. But his description of a yellow ear-tag in the puma indicated that it was instead a subadult male. The hunter’s reason for not wanting to kill the puma was he did not want to kill a female puma. In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters and hunter selection to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to pumas that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters’ responses in TY4 showed they encountered 19 puma tracks less than one day old. Of those, 8 tracks were of females, and 11 tracks were of males, indicating that during the TY4 hunting season males were more detectable than females even though independent females outnumbered independent males by 31 females and 11 males based on the minimum count (Table 4). In comparison with the previous 2 treatment years (these data were not gathered in the survey for TY1) tracks < 1 day old reported by puma hunters consistently favored females (TY2: 20 female, 10 male; TY3: 15 female, 6 male). Of the 8 female tracks less than one day old, 7 hunters that encountered them said they had no intent to harvest the puma and one hunter did not indicate his intent. Of the 11 male tracks less than one day old, 10 of the hunters that encountered them indicated intent to harvest the pumas and in fact did harvest 3 of them. One hunter did not pursue the male puma with intent to harvest it. These preliminary survey and harvest data for TY4 indicate that hunters detected independent male pumas more frequently than females and males were captured by hunters more frequently than females by 2 to 1 (i.e., males = 3 harvested + 1 captured and released; females = 2 harvested). Moreover, hunters were choosing to kill males more frequently than females. Results in TY4 indicated selection for male pumas by hunters was consistent with TY1, TY2, and TY3 results, except in those 3 previous treatment years hunters caught females slightly more frequently than males, and males were selected for harvest. This preliminary assessment from years TY1, TY2, TY3, and TY4 puma harvest and hunter survey data suggests that female pumas were detected by hunters more frequently than male pumas, except for TY4, the large majority of puma hunters were selective, and hunter choices influenced harvest sex and age composition. Segment Objective 2 After the harvest quota was filled, puma research teams immediately initiated capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes of the study area, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radio-collar pumas the remainder of winter and early spring 2012-13. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area during November to April. �We made 62 puma captures of 49 individuals from August 2012 to July 2013 (Tables 6-11); 29 individual pumas were captured with dogs 42 times. Seven pumas were captured in cage traps. Thirteen cubs were captured at nurseries by hand. A total of 55 individual pumas were monitored with radiotelemetry from August 2012 to July 2013 (some of these had been collared in previous years), representing sex and age classes including: 19 adult females, 8 adult males, 5 subadult females, 2 subadult males, and 21 cubs (i.e., the 2 subadult males survived to adult age during the biological year). Trained dogs were used as our main method to capture, sample, and mark pumas from January 1, 2013 to April 18, 2013. Those efforts resulted in 74 search days, 229 total puma tracks detected of which 125 were ≤1 day old, 82 pursuits, and a total of 42 puma captures of 29 individual pumas (Table 6). Search days with dogs in TY4 (74) were slightly lower than TY3 (79 days) and lower than TY1 (86 days) and TY2 (81 days)(Table 12). The frequency of tracks (tracks/day) encountered in TY4 was equivalent to TY1 and lower than TY2 and TY3. The number of pursuits in TY4 was 7 less than TY3 was 17 less than in TY2 and 11 less than in TY1. The capture rate in TY4 was substantially higher than TY1 and TY3 but somewhat less than TY2. The number of new pumas captured for the first time in TY4 was 3 higher than TY1, 3 lower than TY2 and 1 more than TY3 (Table 12). Researchers in the two hound capture teams also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected and pursued by puma hunters. The count was: 46 tracks of females, including 9 associated with cubs; 23 tracks of males; and 1 track of unspecified sex. These tracks ≤ 1 day old were found after the TY4 puma hunting season when 4 independent females and 4 independent males were harvested (Tables 2 and 3). Therefore, the harvested pumas were not present to make tracks for our researchers to observe. By comparison, the number of first tracks <1 day hunters reported by puma hunters in TY4 was 8 females and 11 males (Segment Objective 1 above). Puma capture efforts using ungulate carcasses and cage traps occurred from September 18, 2012 to May 22, 2013 with the main efforts in the fall and spring (Table 10). We used 50 road-killed mule deer and one road-killed elk at 28 different sites. Two adult females (F176, F177), 2 adult males (M178, M179, 1 subadult female (F186), and 1 cub (F186 were captured for the first time. Two adult females (F93, F95) were recaptured and re-collared. Pumas scavenged at 12 of 51 (23.53%) of the ungulate carcasses used for bait. Pumas sometimes walked past the ungulate baits but did not feed (Table 10). We sampled 23 new cubs, including 12 females and 11 males (Table 11). All except 2 were radio-collared to monitor survival and agent-specific mortality (Appendix A). One non-marked female cub (PF1062) climbed an electrical utility pole and was electrocuted on 12/18/2012. A previously nonmarked cub (PM1068) was found dead, killed and partially consumed by a male puma; the same fate that befell his sibling M191. Besides our direct puma captures with dogs January through April, we detected 10 radio-collared pumas that we were able to identify with GPS or VHF telemetry 12 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. In addition to the harvest and capture data (previously), our search efforts revealed the presence of at least 22 other pumas which we included in our minimum count November 2012 through April 2013 (Table 4). We classified those pumas as: 7 adult females, 2 adult males, 1 subadult female, and 12 cubs. �Three adult females, 1 adult male and 1 cub were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). Four of those were bio-darted for genotyping. Also, 1 cub jumped from a tree and was briefly caught by dogs (P1073). We collected a hair sample from it. We collected tissue samples from 1 cub that was electrocuted (previously), 1 cub killed and partially eaten by a male puma, and 1 subadult female shot by a bobcat hunter (Table 8). We could separate the activity of the other pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females, males, and numbers of cubs with females. Also, 1 non-marked adult male was photographed by a digital trail camera while consorting with 2 adult GPS-collared females (F136, F182) at the same time. Our search and capture efforts during January through April 2013 and information from the puma hunting season in TY4 enabled us to quantify a minimum count of 42 independent pumas detected on the Uncompahgre Plateau study area, including 31 independent females and 11 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas killed by hunters on the study area, observations of marked and non-marked pumas observed by researchers or pursued, treed and released by hunters on the study area, and puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars. Of the 42 independent pumas, 29 (69.0%) were marked and 13 (31.0%) were assumed to be non-marked animals (i.e., some may have ear-tags and tattoos). Our observed minimum count of 42 independent pumas for TY4 was close to the expected model projected 45 independent pumas that we used to reset the harvest quota for TY4 (see Segment Objective 1, Puma harvest). The abundance was higher on the east slope of the study area compared to the west slope. But the sex structure of independent pumas on the east and west slopes was similar. The east slope count included 24 independent pumas (18 females, 6 males). The west slope count included 18 independent pumas (13 females, 5 males). A decline in the study area puma population was most evident on the west slope. Considering the minimum count of 42 independent pumas in TY4, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 2.51 independent pumas/100 km2. The TY4 minimum count of 42 independent pumas is lower than the 3 previous treatment years TY1, TY2, and TY3, which indicated a steadily declining trend in the puma population on the Uncompahgre Plateau study area (Fig. 3). The declining trend was further reflected by declining survival rates of adult pumas on the study area (see Segment Objective 4&5 below). The major cause of death in the independent pumas was sport-hunting mortality (Logan 2010, 2011, 2012, this report). The estimated age structure of independent pumas in November 2012 at the beginning of the puma hunting season in TY4 on the Uncompahgre Plateau study area is depicted in Figure 4. The male age structure has declined when compared with TY1, TY2, and TY3 (Logan 2010, 2011, 2012) with the oldest males about 4 years old. The female age structure is also distributed to the younger ages with a few reaching 9 or 10 years (Logan 2010, 2011). In addition to the independent pumas, we counted a minimum of 24 cubs in TY4 (Table 4). Segment Objective 3 During the past 8.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). In TY4 we directly observed 6 litters in nurseries of which 1 was born in May, 2 in June, 2 in July, and 1 in August (Table 11), each with 1 to 3 cubs born to radio-collared females. Data on reproduction we observed in TY1, TY2, TY3, and TY4 were added to Table 13 which gives the reproductive chronology and information on mates (if known) of reproducing females. Those �data will not be summarized again until the end of the treatment period. The proportion of radio-collared adult females giving birth from August 2012 to July 2013 biological year (TY4) was 0.53 (8/15). For the previous 3 treatment years the proportion was TY1=0.53 (8/15), TY2=0.53 (9/17), and TY3=0.29 (5/17). Considering our 53 total litters from 27 females, including 51 observed with cubs 26 to 42 days old and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females (the latter include F111’s cubs caught later when 8.5 months old) (Table 13), the distribution of puma births by month from 2005 to 2013 indicate births extending from March into September (Fig. 5). Births are high in May and June, peak in July, high in August and decline in September. Births during late spring to late summer (May to August) involve 84.9% (45/53*100) of the births (Fig. 5). The data indicate that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 1982-1987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions of births in the reference and treatment periods separately for a treatment effect on timing of breeding and births. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2013, we radio-monitored 28 adult male and 42 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). We monitored 19 adult females and 8 adult males for annual survival and agent-specific mortality in TY4. Annual survival rate for adult females was 0.819 (SE=0.0931) and for males was 0.188 (SE=0.0845). Preliminary adult puma survival for TY1, TY2, and TY3 are also shown in Table 15. So far, adult male survival is substantially lower in the treatment period than in the reference period. Adult female survival is lower in TY1 and TY3, with marked decline in TY3. Yet, female survival is generally higher than male survival. These characteristics are indicative of hunter selection for male pumas (previously in Segment Objective 1). The lower adult puma survival rates, particularly of males, were consistent with an observed decline in the puma population on the study area (see Segment Objective 2, previously). Human-related factors caused 4 deaths of radio-marked adult pumas in TY4, including: sporthunting harvest (2 males- M178, M179; 2 females- F152, F177) (Tables 2, 3, 14). In addition, 1 adult female puma died of natural causes: F93 was killed by another puma (Table 14). We have information on 35 subadult pumas (i.e., independent pumas <24 months old), including 14 females and 21 males (Table 16). We lost radio contact with 2 male and 2 females that probably dispersed from the study area unknown distances. Of the remaining 31 subadults (females and males combined), 8 (3 females, 5 males) died before reaching adulthood, indicating a rough preliminary binomial survival rate of 0.74 (i.e., 23/31) for subadults surviving to the adult age stage (i.e., 24 mo. old). Of the 8 subadults that died, 4 deaths were from natural causes, 3 were from sport-hunting, and 1 was from a vehicle strike (Table 16).We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire more reliable estimates of their survival. �Harvest data along with our capture and radiotelemetry data provided dispersal and fate information on 38 marked pumas, 29 males and 9 females. Of those, 28 (4 females, 24 males) were initially captured and marked as cubs, and 10 (5 females, 5 males) were captured and marked in the subadult life-stage on the Uncompahgre Plateau puma study area (Table 17). Twenty-three males were killed by hunters away from the study area at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). One male was killed by a hunter on the study area 12.9 km from his original capture site. Four females were killed by puma hunters off the study area ranging from 20.7 to 74.5 km from initial capture sites. One female was killed by a hunter on the study area 18.2 km from her initial capture site. Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she established an adult home range there before she was killed by a puma hunter in that area on Jan. 9, 2012. Three males (M67, M87, M92) that were marked initially as cubs born on the east slope of the study area, dispersed from their natal ranges and were recaptured as adults on the west slope of the study area. Two of those (M67, M87) were killed on their adult territories by hunters. One (M92) is of unknown fate as of July 2013. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53. [The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629).] The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY4 we monitored the fates of 21 radio-collared cubs (Table 11, Appendix A). We lost contact with 2 (F185, F195) after they shed their expandable radio-collars prematurely. Of the remaining 19 collared cubs, 7 died and 1 was orphaned and removed from the wild to be rehabilitated to the subadult stage. One non-marked cub in association with a radio-collared cub was also found dead. Eight cubs from 3 litters (1 of those litters with the radio-collared and a non-collared cub) died from infanticide and cannibalism by male pumas. One cub (M175) died when it was apparently mauled by puma-hunting dogs. Later his mother (F152) was killed by a puma hunter. Her death orphaned the remaining cub (M174) and he was recaptured and removed from the wild to be rehabilitated at the CPW Wildlife Rehabilitation Center in Del Norte, Colorado. Of the 11 remaining live radio-collared cubs 4 survived to the subadult stage and 7 were being monitored in association with their mothers as of July 31, 2013. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. Subadult male puma M161 was struck and killed by a vehicle on state highway 62 at Dallas Divide on the south boundary of the study area in October 2012 (Tables 17, 18, Appendix A). This mortality made the fifteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Six of the 15 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Forty-five adult pumas (33 females, 12 males) have worn GPS collars since this project began in 2004 (Table 19). Over 70 thousand GPS locations have been obtained and will be used for studies on puma behavior, social organization, population dynamics, population genetics, movements, population survey methods, habitat use and puma-human relations in collaboration with colleagues in Mammals Research, Colorado State University, and Arizona State University. �Segment Objective 6 We continued to explore non-invasive methods for sampling pumas to estimate abundance by collaborating with Dr. Mat Alldredge (Mammals Researcher, CPW) and Master of Science graduate student Kirstie Yeager, Colorado Cooperative Fish and Wildlife Research Unit and Colorado State University. Here only a brief summary will be presented. M.S. student Kirstie Yeager is currently in the process of analyzing data. For a detailed report refer to Yeager (2013). A grid of 2 km x 2 km (4 sq. km) cells was established on the east slope of the Uncompahgre Plateau study area (Fig. 6). Eighteen cells were identified randomly for each of 3 survey periods each lasting about 28 days. A total of 54 random cells were surveyed during December 2012 to March 2013. Within each random cell M.S. student Kirstie Yeager subjectively chose the “best” site to attract pumas by using vocal baits each consisting of a Fur-Finder ® (Magna, UT) electronic predator call of a distressed deer fawn. Each site also had a Reconyx ® (Holmen, WI) PC900 Hyperfire camera to record animal activity and hair-sampling devices (i.e., barbed-wire strands, sticky rollers) to attempt to acquire hair. This was an effort to evaluate these methods for a non-invasive survey of puma abundance by using tissue to genetically identify individuals in a mark-recapture structure. During the survey spanning December 2012 to March 2013 eleven GPS and VHF collared pumas were known to use the survey grid for varying amounts of time, including 7 adult females, 1 subadult female, 2 adult males, and 1 subadult male. During the survey a total of 18 photographs of pumas visiting the sites were acquired, and all 18 of the photographs depicted GPS or VHF collared pumas. No noncollared pumas were photographed. Of the 11 collared pumas known to use the grid, at least 7 of them were photographed 1 to 4 times each, including 5 adult females, 1 subadult female, and 1 subadult male. Probability of detecting the 11 collared pumas available during the entire survey time was 0.64 (p = 7/11). Six hair samples were acquired from 4 to 5 individual pumas. The quality of the tissues for accurate genotypes of the individual will be determined by K. Yeager later by comparing with genotypes derived from skin and hair samples acquired from the individual pumas at capture and handling events. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 8.7 years of effort 202 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 42 adult females, 28 adult males, 14 subadult females, 21 subadult males, 56 female cubs, 82 male cubs, and 1 cub of undetermined sex (some individuals occur in more than one stage class). Data from marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CPW wildlife biologists and managers for assessing puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now 4 years of the treatment period are complete (TY1, TY2, TY3, TY4). Although data support some CPW puma management assumptions (e.g., population structure, density, how sport-harvest can cause population decline), it is still too early in this research to adequately test all the assumptions and attendant hypotheses. Although the assumption and hypothesis on harvest structure and hunter selection is not supported with the first 4 years of data in the treatment period, this could change with a substantial change in abundance and sex structure of independent pumas available for hunting in TY5. The puma harvest quota for TY5 is recommended to be 5 independent pumas to align with the research design and �harvest objective, and the hunters will be surveyed again. Since the beginning of this study 2 efforts have been made to develop and test non-invasive methods for estimating puma abundance. These efforts were in collaboration with Colorado State University in a Ph.D. program (Jesse Lewis) and a M.S. program (Kirstie Yeager). To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes across the various life stages and sexes. Furthermore, we will continue collaboration with colleagues on investigations of puma population parameter estimation, population genetics, puma movements, puma habitat modeling and mapping, puma-human relations, and disease prevalence. All of these efforts should enhance the Colorado puma research and management programs. LITERATURE CITED Anderson, A. E, D. C. Bowden, and D. M. Kattner. 1992. 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Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Pozio, E., and G. La Rosa. 2003. PCR-derived methods for the identification of Trichinella parasites from animal and human samples. Methods in Molecular and Cellular Biology 216: 299-309. Rausch, R. L., C. Maser, and E. P. Hoberg. 1983. Gastrointestinal helminths of the cougar, Felis concolor L. in northeastern Oregon. Journal of Wildlife Diseases 19: 14-19. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Vollbrecht, A., D. Sokolowski, W. Hollipeter, R. Sigler, J. Greenblatt, D. E. Anderson, P. J. Tennican, H. R. Gamble, and D. Zarlenga. 1996. Oubreak of trichinellosis associated with eating cougar jerky – Idaho, 1995. Morbidity and Mortality Weekly Report 45: 205-206. Webster, P., C. Maddox-Hyttel, K. Nockler, A. Malajauskas, J. van der Giessen, E. Pozio, P. Boireau, C. M. O. Kapel. 2006. Meat inspection for Trichinella in pork, horsemeat and game within the EU: available technology and its present implementation. Eurosurveillance 11:50-55. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Winters, J. B. 1969. Trichiniasis in Montana mountain lions. Bulletin of the Wildlife Disease Association 5: 400. Worley, D. E., J. C. Fox, J. B. Winters, and K. R. Greer. 1974. Prevalence and distribution of Trichinella spiralis in carnivorous mammals in the United States northern Rocky Mountain region. Proceedings of the 3rd International Conference on Trichinellosis, Florida, USA, November 2-4, 1972. �Yeager, K., B. Kendall, M. Alldredge. 2013. The Use of Lures, Hair Snares, and Snow Tracking as NonInvasive Sampling Techniques to Detect and Identify Cougars. Colorado Cooperative Fish and Wildlife Research Unit, Ft. Collins. Zarlenga, D.S., Chute, M.B., Martin, A. and Kapel, C.M. 1999. A multiplex PCR for unequivocal differentiation of all encapsulated and nonencapsulated genotypes of Trichinella. International Journal for Parasitology 29:1859–1867. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Year RY4 RY5 TY1 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 Independent Pumas Cub 20 33 42 Total 33 45 53 Lambda 1.37 1.17 Table 2. Pumas harvested by sport-hunters in Treatment Year 4 (TY4) on the Uncompahgre Plateau Study Area, Colorado, November 19 to December 29, 2012. Puma sex Age (yr.) F M M F M 2.5 1.5 2.5 2.5 2.5 Previous M/F I.D. or specimen P no. if not marked P1058 M156 P1066 F152 M179 Date of kill Location/UTM NAD27 Zone, Easting, Northing 12/10/2012 12/10/2012 12/21/2012 12/23/2012 12/29/2012 12, 756299, 4250598 12, 753851, 4249709 12, 741039, 4236392 13, 239123, 4248299 12, 759988, 4250158 Hunter/status Mark Rackay/resident Dustin Gleason/resident Mia Enstrom/resident Jared Roberts/resident Gary Gleason/resident Table 3. Four other independent VHF/GPS-collared pumas in the minimum count November 2012 to April 2013 (TY4) for the Uncompahgre Plateau Study Area that also died during November to April 2012-2013 period coinciding with the Colorado puma hunting season. Puma sex (M or F) F93 Age (yr.) 11 Date of kill/death 11/11/2012 F149 1.7 12/31/2012 F177 2.5 12/10/2012 M178 3 12/11/2012 Place of kill/UTM NAD27 Zone, Easting, Northing Linscott Canyon on study area 12, 761904, 4253939 GMU 70W, Dry Creek, south of Naturita, CO 12, 713658, 4229703 GMU 65, Tommy Creek fork of Cow Creek, 13, 263944, 4233691 GMU 65, Uncompahgre River, trailed off of study area at McKenzie Buttes, 13, 258413, 4239129 Hunter/status/other cause Killed by another puma Duane Pool/nonresident/Bobby Starks Outfitter Scott Hill/resident/Matt Iverson Outfitter Michael Delfino/nonresident/Ben Harris-Needle Rock Outfitter �Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1), November 2010 to April 2011 (TY2), November 2011 to April 2012 (TY3), and November 2012 to April 2013 (TY4), Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 TY3 TY4 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 2 West slope 14 5 3 5 1 2 subtotals 27 9 4 8 5 4 Total Independent Pumas = 48, including 31 females, 17 males. Cubs = 19 East slope 15 4 3 2 4 4 West slope 10 5 3 0 2 5 subtotals 25 9 6 2 6 9 Total Independent Pumas = 42, including 31 females, 11 males. Cubs = 24 Unknown sex 4-8* 5-6 9-14 7 9 16 4 6 10 3 6 9 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. Table 5. Pumas captured and released by sport-hunters in Treatment Year 4 (TY4) on the Uncompahgre Plateau Study Area, Colorado, November 19 to December 29, 2012. Data are from puma hunter responses in 42 original voluntary surveys on printed permits. Total response rate from 70 individual permitted hunters was 60% (42/70 = 0.60*100). Puma sex/age stage/mark M/subadult/ eartags Date of capture 12/23/2012 Capture location Hunter name Sim’s Mesa Jeremiah Wheeler Reason for releasing the puma given by hunter Hunter thought the puma was a female. Yellow ear-tag indicated male puma. Number on ear-tag not noted by hunter. �Table 6. Summary of puma capture efforts with dogs from January 1, 2013 to April 18, 2013, Uncompahgre Plateau, Colorado. Month January No. Search Days 23 No. & type of puma tracks founda,b 93 tracks: 13 male, 50 female, 19 cub, 11 undetermined independent pumas Tracks ≤1 day old: 5 male, 22 female, 10 cub No. & type of pumas pursued 32 pursuits: 5 male, 18 female, 9 cub February 23 69 tracks: 15 male, 34 female, 14 cub, 6 undetermined independent puma Tracks ≤1 day old: 12 male, 27 female, 14 cub, 2 undetermined independent puma 29 pursuits: 9 male, 11 female, 7 cub, 2 undetermined independent puma March 21 No. & I.D. or type of pumas captured, observed, or identified 12 pumas captured 19 times: M180, M190 (twice), F129, F181, F136 (twice), F137 (4 times), F194, F74 (twice), PM1067 (twice; cub of F171; bio-darted; not handled in dangerous trees), M191 (probably cub of F28), M192 and M193 (cubs of F118). In addition, adult females F74 , F136, F137, F171 and subadult female F194 were associated with tracks by VHF telemetry. 13 pumas captured 13 times: M183, M196, PM1072 (bio-darted; not handled in dangerous trees), F182, PF1070 (bio-darted; not handled in dangerous trees), PF1071 (bio-darted; not handled in dangerous trees), cub unknown sex of PF1071 bayed on dangerous ledge but could not be handled safely, F136, F171, F197, F28 (nonfunctional collar; bio-darted; not handled in dangerous trees), F195 (cub of F118), M192 (cub of F118). In addition, adult females F140 (2 times), F74, F111 and subadult female F181 were associated with tracks by VHF telemetry. 4 pumas captured 4 times: PM1072 (not handled in dangerous trees), F137, F28 (non-functional collar; not handled in dangerous trees) F184 (cub of F111), P1073 (sex undetermined; hair collected, escaped). In addition, adult male M190 was associated with tracks by VHF telemetry. 4 pumas captured 5 times: F111, PF1074 (biodarted; not handled in dangerous trees), M198 (twice; cub of PF1074), F199 (cub of PF1074). In addition, subadult female F186 was associated with tracks by VHF telemetry. 29 individual pumas were captured 42 times with aid of dogs. In addition, 10 radio-collared pumas were detected 12 times by tracks and identified with VHF telemetry ≤1 km from the tracks. 12 independent pumas (adults, subadults) were captured with dogs for the first time (refer to Tables 7 and 8). 48 tracks: 12 male, 11 pursuits: 4 male, 24 female, 11 cub, 1 4 female, 3 cub undetermined independent puma Tracks ≤1 day old: 5 male, 7 female, 3 cub April 7 19 tracks: 1 male, 10 pursuits: 8 female, 10 cub 4 female, 6 cub Tracks ≤1 day old: 0 male, 8 female, 10 cub 74 229 tracks: 82 pursuits: TOTALS 41 male, 18 male, 116 female, 37 female, 54 cub, 25 cub 18 undetermined 2 undetermined Tracks ≤1 day old: 23 male 64 female 37 cub 2 undetermined a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Each capture season researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day to gather data on vulnerability to detection using methods similar to puma hunters. For 2012-2013 (TY4) the count was: 46 tracks of females, including 9 of those associated with cubs; 23 tracks of males; and 1 track of undetermined sex. �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from October 2012 to April 2013, Uncompahgre Plateau, Colorado. Puma I.D. F176 F177 M178 M179 M180 F181 F182 M183 F186 M190 F194 M196 F197 Sex Estimated Age (mo.) 27 28 29 25 18 21 48 54 29 36 26 45 18 F F M M M F F M F M F M F Mass (kg) 42 44 65 54 45 36 55 72 38 57 40 78 49 Capture date 10/17/2012 10/27/2012 11/13/2012 11/18/2012 1/1/2013 1/15/2013 2/4/2013 2/14/2013 3/30/2013 1/1/2013 1/29/2013 2/5/2013 2/14/2013 Capture method Cage trap Cage trap Cage trap Cage trap Dogs Dogs Dogs Dogs Cage trap Dogs Dogs Dogs Dogs Location North of Norwood Hill, San Miguel Canyon North McKenzie Mesa North McKenzie Mesa East rim Dry Creek Basin Dolores Creek Happy Creek Fisher Canyon Roubideau Canyon 7N Mesa, Roubideau Canyon San Miguel Canyon San Miguel Canyon San Miguel Canyon San Miguel Canyon Table 8. Pumas that were captured and observed with aid of dogs, some of which were biopsy-darted or hair was collected and given specimen numbers (e.g., PM1067, M for male, F for female), but were not handled at that time for safety reasons, and a puma killed by a bobcat hunter, January 2013 to March 2013, Uncompahgre Plateau, Colorado. Puma sex & I.D. PM1067 PF1069 Age stage or months 17 18 Capture date 1/25/2013 1/11/2013 PF1070 Adult 2/11/2013 PF1071 Adult 2/25/2013 PM1072 Adult 2/27/2013 P1073 6 3/15/2013 PF1074 Adult 4/12/2013 Location Horsefly Creek Lower Maverick Draw North Fork Cottonwood Creek Potter Creek, Roubideau Canyon North Fork Cottonwood Creek Monitor Creek, Roubideau Canyon Craig Draw Comments Cub of F171, sibling of M170. Puma shot by a bobcat hunter that thought the cat was a bobcat. Puma not previously marked. Mother of 3 cubs ~5-6 mo. old; one of which was bayed on a ledge but not handled. Mother of 1 male cub ~18 mo. old (not handled). Puma naturally marked with abbreviated right pinna with 2 notches and left nostril pad removed. Puma cub was mauled by dogs and escaped. Hair left at scene was collected. Mother of cubs M198, F199. �Table 9. Pumas recaptured October 2012 to April 2013, Uncompahgre Plateau, Colorado. Puma I.D. F93 Recapture Date 10/3/2012 Mass (kg) 39 Estimated Age (mo.) 132 Capture Method/ Location Cage trap/Happy Canyon Dogs/Horsefly Creek Dogs/McKenzie Creek F129 1/2/2013 1/17/2013 43 Observed 28 53 F136 1/18/2013 Observed 53 2/7/2013 50 54 1/4/2013 Observed 48 1/9/2013 Observed 48 Dogs/Caterwauler Canyon, SE Loghill Mesa Dogs/south rim Loghill Mesa Dogs/West Fork Dry Creek Dogs/Piney Creek 1/13/2013 Observed 48 Dogs/Dry Creek Forks 1/31/2013 Observed 48 Dogs/Dry Creek 3/6/2013 Observed 48 Dogs/Lower Dry Creek 1/15/2013 34 65 1/30/2013 Observed 65 2/5/2013 2/21/2013 Observed Observed 43 120 3/1/2013 Observed 121 Dogs/Lower Clay Creek Dogs/Lower Cottonwood Creek Dogs/Horsefly Creek Dogs/East Fork Big Bucktail Canyon Dogs/North Fork Cottonwood Creek F95 3/14/2013 40 67 F111 M190 4/12/2013 1/1/2013 35 Observed 60 36 PM1067 1/29/2013 Observed 17 M192 PM1072 2/1/2013 3/12/2013 Observed Observed 7 Adult M198 4/18/2013 Observed 9 F137 F74 F171 F28 Cage trap/Roubideau Canyon Dogs/Piney Creek Dogs/San Miguel Canyon Dogs/Horsefly Creek Dogs/Mailbox Park Dogs/Big Bucktail Canyon Dogs/upper Horsefly Creek Process Replaced VHF collar with GPS collar. Fit with GPS collar. F136 climbed dangerous trees; not handled. F136 climbed dangerous trees; not handled. Replaced non-functional GPS collar with a new one. F137 climbed dangerous tree; not handled. F137 climbed dangerous tree; not handled. F137 climbed dangerous tree; not handled. F137 climbed dangerous tree; not handled. F137 climbed dangerous tree; bio-darted for tissue sample, but not handled. F74 fit with new radiocollar. None. None. F28 climbed dangerous tree; not handled to replace non-functional GPS collar. F28 climbed dangerous tree; bio-darted for tissue sample, but not handled to replace non-functional GPS collar. Replaced VHF collar with GPS collar. Replaced GPS collar. M190 took refuge in dangerous ledges; not handled. PM1067 climbed dangerous tree; not handled. None. PM1072 climbed dangerous tree; not handled. None. �Table 10. Summary of puma capture efforts with cage traps from September 18, 2012 to May 22, 2013, Uncompahgre Plateau, Colorado.* Month September No. of Sites 4 Carnivore activity & capture effort results Female puma walked ~5-10 m from mule deer bait 6 days old, but did not feed, East McKenzie Mesa bait site. Black bears, bobcats, coyotes scavenged some mule deer carcasses. October 13 Adult puma F93 recaptured in cage trap baited with mule deer 10/3/2012. Adult puma F176 captured for the first time in cage trap baited with mule deer 10/17/2012. Adult puma F177 captured for first time in cage trap baited with mule deer 10/27/2012. Non-marked female puma scavenged mule deer bait at SE Loghill Mesa rim 10/30/2012; set cage trap; but, puma did not return. Adult puma F136 walked past same mule deer bait, 8 days old, at SE Loghill Mesa Rim on 10/31/2012, but did not feed. Unknown puma walked past mule deer bait in mouth of Clay Creek, but did not feed. Bobcats and gray foxes scavenged from some of the mule deer carcasses. November 7 Adult puma M178 captured for first time in cage trap baited with mule deer 11/13/2012. Adult puma M179 captured for first time in cage trap baited with mule deer 11/18/2012. Non-marked female puma scavenged mule deer bait at SE Loghill Mesa rim 11/5/2012; set cage trap; but, puma did not return (probably same as in October). Puma M178 walked by mule deer bait 5 days old on SE Loghill Mesa 11/10/2012, but did not feed. March 14 Adult puma F95 recaptured in cage trap baited with mule deer 3/14/2013. Puma cub F185 captured for the first time in cage trap baited with mule deer 3/23/2013. Subadult puma F186 captured for the first time in a cage trap baited with mule deer 3/30/2013. Puma, probably F95, fed on mule deer bait on east Roubideau Canyon rim, cage trap set; puma did not return. Adult puma M183 visited mule deer bait on 7N Mesa, but did not feed. Female puma, probably F118, walked ~3 m from mule deer bait on N Norwood Hill, but did not feed. Coyotes, bobcats and black bear scavenged some of the mule deer carcasses. April 3 Adult F171 fed on elk bait at Horsefly Canyon on 4/23/2013; no capture effort needed. Black bears and coyotes scavenged on elk bait. May 2 Black bears scavenged mule deer baits. * We used 50 road-killed mule deer and 1 road-killed elk at 28 different sites. Of the road-killed baits, 12 of 51 (23.53%) were scavenged by pumas. Table 11. Puma cubs sampled August 2012 to July 2013 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) PF1062 F 6/2012 183 13.5 Nonmarked Adult M166 M 7/5/2012 33 2.2 F136 51 M167 M 7/5/2012 33 2.1 M168 M 7/27/2012 37 2.3 F169 F 7/27/2012 37 2.2 F96 78 F173 F 7/27/2012 37 2.5 M174 M 8/8/2012 32 1.9 F152 25.7 M175 M 8/8/2012 32 1.8 F184 F 8/25/2012 208 13.0 F111 58 F185 F 9/2012 183 12.0 Nonmarked Adult F187 F 5/14/2013 31 2.3 F96 88 F188 F 5/14/2013 31 2.5 b M191 M 7/2012 183 14.0 F28 probably 112 PM1068 M 7/2012 183 Unknown M192 M 6/20/2012 199 21.0 M193 M 6/20/2012 199 20.0 F118 50 F195 F 6/20/2012 227 20.0 M198 M 6/2012 274 30 PF1074 Adult F199 F 6/2012 282 25 F189 F 6/18/2013 38 2.6 F200 F 6/18/2013 38 2.6 F136 62 M201 M 6/18/2013 38 2.8 F202 F 6/25/2013 35 2.5 F172 48 a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b F28 had a non-functional GPS collar, but recapture sites and tracked travel routes were consistent with associations with cubs M191 and PM1068. Another non-marked cub was in association, making the total number of cubs = 3. �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2013, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day Dec. 27, 2011 to April 12, 2012 268/79 = 3.39 tracks/day Jan. 1, 2013 to April 18, 2013 229/74 = 3.09 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 81/15 = 5.40 day/capture 89/79 = 1.13 pursuit/day 26/79 = 0.28 capture/day 11 pumas captured for first time 11/79 = 0.14 capture/day 79/89 = 0.89 day/pursuit 79/26 = 3.04 day/capture 79/11 = 7.18 day/capture 82/74 = 1.11 pursuit/day 42/74 = 0.57 capture/day 12 pumas captured for the first time 12/74 = 0.16 capture/day 74/82 = 0.90 day/pursuit 74/42 = 1.76 day/capture 74/12 = 6.17 day/capture 15 pumas captured for first time 15/81 = 0.18 capture/day �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2013. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) F2 F2 F2 F3 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F8 F16 F16 F16 F23* F23 53 67 89 36 50 62 84 107 67 82 106 24 37 60 95 32 52 75 21 45 F23 80 F24 F24 75 114 F25 F25 F25 F25 74 94 110 129 F28* F28 F28 F28 F30* F50 F54 F70* F70 F70 F72* F72 F72 36 48 68 112 48 21 24 38 52 76 28 51 64 F75 F75 F93 F93 F94* F94 F96 F96 F96 32 55 56 90 46 60 55 78 88 Dates pairs consortedb Estimated birth datec M73 49 02/28-29/08 M6 80 01/13-14/09 M27 or M29f M67 78 107 53 02/19-25/08 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 01/28-31/11 04/22/11 M29 92 04/12-15/07 06/14/07 09/10 M6 37 06/22-24/05 M51 M55 60 69 03/31/08 03/28-31/10 08/01/05 04/16/07 08/19/08 3/10 M29 88 12/27-29/06 M55 34 04/16-20/07 M51 60 03/10/08 M73 61 02/11/09 M55 M55 70 71 04/15/10 05/21/10 06/09/06 03/30/07 11/08 07/12 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 08/18/11 07/09/08 06/12/10 07/15/11 08/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 08/21/10 07/27/12 05/14/13 Estimated birth interval (mo.) Estimated gestation (days) Observed number of cubsd 19.9 22.7 91-92 23.8 87-93 3 2 4 1 2 3 3 2 2 4 3 2 4 2 2 4 4 3 3 3 Nonfunct.GPS 84-86 2 90-93 4 3 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 90-91 Nonfunct.GPS 1 1 2 3 20.5 16.1 Nonfunct.GPS 11.7 92-93 88-92 87 14.8 23.6 23.1 13 23.2 93 13.3 91 23.2 9.6 2 ≥2 tracks 1 3 3 1 1 3 3 3 1 2 3 photographed 1 2 2 2 3 3 4 3 2 �Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) Table 13 continued. Dates pairs Estimated consortedb birth datec Estimated birth interval (mo.) F104 F111* F111 F116g F118 F118h F119 F119i 110 32 58 36 27 50 66 96 expected 07/08/10 06/16/10 08/25/12 2009 08/08/10 06/20/2012 08/09 02/12 expected 29 expected F135 F136j F136 F136 33 39 51 62 07/06/11 07/10/11 07/05/12 06/18/13 12 11 Nonmarkedl Unk. 03/19/13 Estimated gestation (days) Observed number of cubsd 92 3 2 2k 2 3 3 2 1 plus 1-2 uterine scars 2 ≥1 remains 2 3 26.3 22.4 F137 30 07/08/11 ≥1 F137 54 07/12/2013 3 F152* 25.7 08/08/2012 2 F171 22 08/11 2 F171 45 07/31/2013 4 F172 48 06/25/2013 1 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on known history or nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. h Two cubs observed with F118 south of Norwood 9/24/2012. i F119 died of a ruptured uterus and internal bleeding on 1/28/12. Cub in uterus in third trimester; 1-2 uterine scars indicated expulsion of 1-2 fetuses. j Remains of F136’s cubs found 8/9/11. Cause of death predation by puma or black bear. k Tracks evidence of one other cub in association with F111 and cub F184, but not captured and marked. l A non-marked adult male puma was photographed consorting with adult female pumas F136 and F182 at the same time on the NE rim of Loghill Mesa on 03/19-20/13. �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2013, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 08-23-07 to 12-18-11 M71 01-29-08 to 11-12-09 M73 02-21-08 to 10-26-11 M87 02-09-11 to 12-06-11 M90 11-16-10 to 11-23-10 M100 03-27-09 to 07-31-09 M114 02-27-10 to 03-10-12 M133 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Dead. M67 is offspring of F30. Dispersed natal area. Established territory on W side U.P. study area. Killed by a puma hunter in Tabaguache Creek 12-18-2011 at age 52.9 months. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Dead. Illegally killed 10-26-2011 in Bear Pen Gulch, upper East Fork Escalante Canyon; shot through abdomen during second rifle season. M73 was about 80 months old at death. Dead. M87 is offspring of F3. Dispersed from natal area. Established territory on W side of U.P. study area. Killed by a puma hunter in 47 Canyon, Tabaguache Canyon 12-06-2011. M87 was 41 months old at death. Dead. M90 was killed by a hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Dispersed from U.P. study area after 06-23-10. Killed by a puma hunter in Beaver Creek, NE of Canyon City, GMU59, 03-10-12. M114 was about 55 months old at death. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 07-01-11 to 12-23-11 M144 09-01-11 to 02-25-13 M153 M165 09-01-11 to 09-13-11 07-01-12 to 02-17-12 M178 11-13-12 to 12-11-12 M179 M180 M183 M190 M196 F2 11-18-12 to 12-29-12 07-01-13 to 07-31-13 02-14-13 to 07-31-13 01-02-13 to 07-31-13 02-05-13 to 07-31-13 01-07-05 to 08-14-08 F3 01-21-05 to 12-11-11 F7 02-24-05 to 08-03-08 F8 03-21-05 to 12-17-12 F16 10-11-05 to 09-11-09 F23 02-05-06 to 06-06-12 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 02-16-12 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 01-14-08 to 12-22-11 F72 02-12-08 to 12-21-11 F74 01-15-13 to 5-16-13 Table 14. Continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Dead. Killed by a puma hunter in Horsefly Canyon (E) 12/23/11. M138 was about 29 months old at death. Dead. Initially captured as 18 mo. old subadult on W side U.P. study area 03-07-11. Dispersed from study area. Established adult territory on NW U.P. Killed by puma hunter 2-25-2013 in GMU 40, North Fork West Creek, Unaweep Canyon. Dead. Killed for depredation control; killed an alpaca in Pleasant Valley 09-13-11. Alive. Initially captured as 19 mo. old subadult on W side U.P. study area 02-24-12. Moved to Escalante Creek drainage by adult age 07-31-12. Killed by puma hunter 1217-2012 in GMU 62N, Dry Fork Escalante Canyon. Dead. Originally captured on the study area 11-13-12. Killed by puma hunter 12-1112 after tracking M178 off the study area and onto adjacent GMU 65. Dead. Killed by puma hunter on study area 12-29-12. Alive. Alive. Alive. Alive. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Dead. Killed by a puma hunter in Lindsay Creek 12-11-11. F3 was about 120 months old at death. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Lost radio contact. Last live signal heard 12/17/2012 in Big Bucktail Canyon on study area. Fate unknown; was not recaptured on study area Jan. to April 2013. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Dead. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. F23 may have attempted to defend 2 cubs (F149, M161; 13.5 months old) and/or calf elk kill. Dead. Killed by a male puma in Logging Camp Draw about 09-16-11. F24 was about 126 months old at death. F24 may have attempted to defend ≥2 cubs (F147, nonmarked siblings; 12 mo. old). Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area 02-01-10 and 01-01-11 and 02-16-12, but could not be handled to replace non-functional GPS collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Dead. Killed by a puma hunter Spring Creek 12-22-11. F70 was 80 months old at death. Her death orphaned 2 cubs, F157 and F158, at 4 months old; both starved to death about 01-15-12 at about 5 months old. Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Photographed on Miller Mesa S of U.P. study area on 12-18 to 21-11 with 3 new cubs born about July 2012. Lost radio contact after 5-16-13; radiocollar fell off after canvas breakaway tab broke; detected 6-10-13. �Puma I.D. F75 Monitoring span 03-26-08 to 12-13-11 F93 F94 12-05-08 to 11-11-12 12-19-08 to 02-01-11 F95 F96 F104 08-01-09 to 07-31-13 01-28-09 to 07-31-13 05-21-09 to 01-31-12 F110 09-21-09 to 02-25-10 F111 F113 01-01-10 to 07-31-13 01-26-10 to 06-06-10 F116 01-20-10 to 09-20-11 F118 F119 02-25-10 to 07-31-13 03-25-10 to 01-28-12 F135 01-01-11 to 09-20-11 F136 F137 F140 F143 F152 F163 F171 F172 F176 F177 F181 F182 F186 F194 01-20-11 to 07-31-13 01-21-11 to 07-31-13 08-01-12 to 07-31-13 02-15-11 to 07-31-13 06-16-12 to 12-23-12 07-01-12 to 07-31-13 01-20-12 to 07-31-13 03-28-12 to 07-31-13 10-17-12 to 07-31-13 10-27-12 to 12-10-12 04-01-13 to 07-31-13 02-04-13 to 07-31-13 03-30-13 to 07-31-13 01-29-13 to 06-17-13 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. Killed by a puma hunter in North Fork Cottonwood Creek 12-13-11. F75 was about 98 months old at death. Dead. Killed by another puma 11-11-12. Fatal bite wounds to the skull. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Dead. Died probably of starvation associated with senescence in lower Roubideau Creek 01-31-12. F104 was about 132 months old at death. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Dead. Died about 09-20-11 of unknown natural cause associated with pregnancy and birth of new litter of cubs. F116 was about 60 months old at death. Alive. Dead. Died of ruptured uterus and internal bleeding associated with pregnancy in Clay Creek Canyon 01-28-12. F119 was about 95 months old at death. Dead. Died of unknown natural cause in E Fork Dry Creek 09-20-11. Her death orphaned cubs M154 and M155 at 76 days old; both died of starvation or disease when 77 (M154) and 81 (M155) days old. Alive. Alive. Alive. Alive. Dead. Killed by puma hunter on study area, Spring Creek Canyon. Alive. Alive. Alive. Alive. Dead. Killed by puma hunter 12-10-12 in GMU 65 adjacent to study area. Alive. Alive. Alive. Dispersed, exhibited subadult behavior. Fate unknown. Censor. �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 4 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year Reference Annual 2 8/1/2005 to 7/31/2006 Reference Annual 3 8/1/2006 to 7/31/2007 Reference Annual 4 8/1/2007 to 7/31/2008 Reference Annual 5 8/1/2008 to 7/31/2009 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annual 1b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males Treatment Annual 2 8/1/2010 to 7/31/2011 Treatment Annual 3 8/1/2011 to 7/31/2012 Treatment Annual 4 8/1/2012 to 7/31/2013 a S 1.000 Females SE 0.0000 n 10 S 0.667a Males SE 0.2222a n 6a 0.909 0.0867 11 1.000 0.0000 5 0.831 0.0986 14 1.000 0.0000 7 0.875 0.1031 13 1.000 0.0000 8 0.784 0.1011 19 0.667 0.1924 8 NA (see rates above) NA NA 0.333b 0.1361b 12b 0.947c 0.0568 19 0.250 0.1082 9 0.548d 0.1063 20 0.167 0.1076 7d 0.819 0.0931 19 0.188 0.0845 8e Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHFmonitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a non-functional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. d Sample included F143, F163, M144, ranged on NW Uncompahgre Plateau N of the study area but not on the U.P. study area, vulnerable to annual hunting. e Sample includes F143, F163, M144, M165 that ranged on north half of the Uncompahgre Plateau north of the study area (not on the study area) and were at risk to annual sport-hunting mortality. �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2013, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 31 M31 04-19-06 to 04-26-06 7 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Survived to adult stage. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. M69 01-11-08 to 04-07-08 190 87 Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. Died in subadult stage. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. Mother F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. �Table 16 continued Puma I.D. F95 Monitoring span 12-29-08 to 07-31-12 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M120 12-06-11 1 M122 08-12-10 to 04-18-11 250 M131 09-25-10 to 04-18-11 206 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 155 F140 01-13-12 to 07- 31-12 200 M141 12-23-11 1 M144 03-07-11 to 09-08-11 185 F145 03-08-11 to 09-08-11 184 Status Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Died in subadult stage. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. M112 was offspring of F70 born August 2009. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-18-11. Lost contact of M112 after 04-18-11. Dispersed. M112 was killed by a puma hunter 01-06-2013, GMU 73, SE of Dolores, CO; UTM: 12S, 732863E, 4146772N; age 41 months, adult stage. Died in subadult stage. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. Died in subadult stage. M120 was offspring of F3. M120 was killed by a puma hunter 12-06-11 in his natal area in Spring Creek. He was 17 months old at death. M122 was offspring of F104, born 07-08-10. Lost contact after 04-1811 when radio-collar malfunctioned. Dispersed. Killed by puma hunter in GMU 62, Tatum Draw, Dry Fork Escalante Creek, N of natal area 01-23-13; UTM: 12S, 735353E, 4283455N; age 30 months, adult stage. M131 was offspring of F96, born 08-21-10. Lost contact after 04-18-11 when collar malfunctioned. Dispersed. Killed by puma hunter in GMU 60, Lion Creek, extreme W CO 01-17-13; UTM: 12S, 670829E, 4246980N; age 29 months old, adult stage. Survived to adult stage (barely). M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Survived to adult stage. Entered adult life stage 07-01-11. Killed by a puma hunter 12-23-11 in Horsefly Canyon. M138 was about 29 months old at death. Survived to adult stage. Turned adult in Aug. 2012. Probably offspring of F28. Has established a home range adjacent to natal area where she was initially captured at 5 months old on 01-02-11. Died in subadult stage. M141 was killed by a puma hunter on 12-23-11 in Little Bucktail Creek. He was 16 months old at death. Survived to adult stage. Emigrated from U.P. study area. Established adult territory on northwest Uncompahgre Plateau. M144 is sibling of F145 below. Killed by puma hunter 2/25/2013 at ~41 mo. old. Survived to adult stage. Emigrated from U.P. study area and to Colorado Mesa. Killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. �Table 16 continued Puma I.D. F146 Monitoring span 03-08-11 to 03-23-11 No. days 15 F147 09-16-11 to 04-12-12 209 F149 06-06-11 to 12-31-12 575 M150 03-28-11 to 04-11-11 14 F152 05-04-12 to 06-16-12 44 M153 04-12-11 to 09-06-11 147 M161 06-06-12 to 08-03-12 59 F163 01-26-12 to 07-01-12 157 M164 02-14-12 to 02-26-12 02-24-12 to 12-17-12 12 M165 M180 F181 F194 F197 01-01-13 to 07-01-13 01-15-13 to 07-01-13 01-29-13 to 6-17-13 02-13-13 to 07-01-13 298 182 Status Died in subadult stage. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Lost contact; radiocollar quit after 04-12-12. F147 orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-1611. Died in subadult stage. F149 was offspring of F23, born 04-22-11. F149 (sibling of M161 below) was orphaned at 13.5 months old when her mother F23 was killed by a male puma. F149 dispersed from the natal area by 07-16-12 to E side U.P. study area when she was 14.8 months old; onto Bostwick Park, then W to Dry Creek. Killed by a puma hunter 12-31-12 in GMU 70W, Dry Creek; UTM: 12S, 713658E, 4229703N; age 20 months. Dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Survived to adult stage. F152 was independent from her mother F93 by 05-04-12 when about 23 months old. She ranged as a subadult and adult on the natal area (07-31-12). Survived to adult stage. Consorted with F137 when 23 months old on 09-07-2011. Killed by Wildlife Services agent for depredation on an alpaca in Dallas Creek on 09-13-11. M153 was 23 months old at death. Died in subadult stage. M161 (sibling of F149 above) was orphaned at 13.5 months old when his mother F23 was killed by a male puma. M161 dispersed from the natal area by 06-29-12 to E side U.P. study area when he was 14 months old. He shed his expandable cub collar about 08-03-12. M161 was struck and killed by a vehicle on Dallas Divide, HWY 62 in October 2012 when he was 18 months old. Survived to adult stage. F163 was captured at about 18 months old on the study area. She emigrated from the study area and established an adult home range on the NW Uncompahgre Plateau as of July 2012 (0716-12 location). Lost contact after 02-26-12. M164 may have dispersed a long distance. Fate unknown. M165 moved from W to E side of the study area. Appeared to establish adult home range on NE Uncompahgre Plateau. Killed by a puma hunter 12-17-12 in GMU 62N, Dry Fork Escalante Creek; UTM: 12S, 730184E, 4272500N; age about 29 months, adult stage. M181 moved to NE Uncompahgre Plateau, ranging N of the study area. Turned to adult age (24 mo.) July 2013. 168 F181 moved from E to W side of study area. Turned to adult age (24 mo.) April 2013. 140 Lost contact after 06-17-13. F194 dispersed S, last location on North Mt., head of Naturita Creek. Estimated age 30 months in June 2013. 139 F197 ranges on W side of the study area. Turns to adult age (24 mo.) August 2013. �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2013. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a puma hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 53.2 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 42.8 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29.5 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61N on 1227-09 when he was 38.9 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek GMU 61N in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. �Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a puma hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 41.5 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 27.8 months old. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 12S,726901E, 4243463N→ 13S,255316E, 4216768N 60.5 M83 07-05-08 90.7 M87 07-31-08 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N M88 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N 21.9 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N 57.7 80.7 369.6 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a puma hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a puma hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 31.6 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is was resident adult on the west slope of the study area. He was killed by a puma hunter on 12-06-11 at 41 months old north of the study area. M88 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a puma hunter in Dawson Creek, Disappointment Valley on 11-3010 when he was 29 months old. M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M107 06-28-09 M112 01-23-10 13S,242359E, 4252618N→ 12S,754886E, 4341330N 13S,248567E, 4240108N→ 12S,732863E, 4146772N M114 02-27-10 M117 02-05-10 M126 09-05-10 M144 03-07-33 M161 01-23-12 Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 89.2 M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 102.5 M112 was initially captured 4.7 mo. old in his natal area while dependent on his mother F70 on 01-23-10. He was recaptured 0124-11 in the natal area at 17 months old, independent of F70. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-18-11 when he was 18-20 mo. old. Lost contact of M112 after 04-18-11. Dispersed and emigrated from the U.P. study area. M112 was killed by a puma hunter 01-06-2013, GMU 73, SE of Dolores, CO; UTM: 12S, 732863E, 4146772N; age 41 months. 13S,256933E, 4237862N→ 13S,492615E, 4266192N 12S,731840E, 4232346N→ 12S,743909E, 4216633N 237.5 12S,734503E, 4224636N→ 12S, 710850E, 4239350N 12S,727173E, 4242012N→ 12S,696439E, 4276888N 27.7 12S,727932E, 4239430N→ 13S,247567E, 4220129N 49.2 19.7 46.6 M114 was initially captured at about 30 months old. Emigrated from the U.P. study area. He was killed by a puma hunter on 0310-12 in Beaver Creek, GMU59. He was about 55 months old at death. M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. M126 was offspring of F118, born Aug. 8, 2010. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area. Mother is unknown. He moved off the study area on 03-15-11. M144 established his adult territory on northwest Uncompahgre Plateau and upper Unaweep Canyon from Sep. 2011 to 02-25-13. M144 was killed by a puma hunter 02-25-13 in GMU 40, North Fork West Creek, Unaweep Canyon. M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old and moved to the east slope of the U.P. study area. M161 shed his expandable cub collar about Aug. 3, 2012 in head of E Fk. Dry Creek. He was struck and killed by a vehicle on highway 62 at Dallas Divide in October 2012; he was 18 mo. old. �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) F52 01-10-07 13S,258058E, 4236260N→ 13S,319217E, 4240467N F97 02-04-09 12S,727529E, 4237648N→ 12S,705930E, 4227299N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N M122 08-12-2010 M131 09-25-10 12S,746164E, 4276613N→ 12S,735353E, 4283455N 12S,760695E, 4243505N→ 12S,670829E, 4246980N F143 02-15-11 F145 03-18-11 12S,723748E, 4238579N→ 12S,721795, 4264246 12S,727181E, 4241468N→ 12S,705833E, 4312909N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. 24.0 F97 was offspring of F23, born May 23, 2008. She was radiocollared at 8.5 month old in San Miguel Canyon; but, lost contact on 05-12-09 after F97 shed the radiocollar at an elk cache. F97 dispersed from the U.P. study area. She was killed by a puma hunter on 01-22-12 in Dry Creek west of the U.P. study area when she was 43.9 months old. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. 18.2 F108 was offspring of F94, born May 25, 2009; sibling of M107 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a puma hunter on the study area on 11-29-10 when she was 17 months old. 12.9 M122 was offspring of F104, born July 8, 2010. Fitted with expandable cub collar 08-12-10. Lost contact 04-28-11 due to transmitter malfunction. Killed by puma hunter N of natal area 01-23-13 at 30 mo. old. 90.1 M131 was offspring of F96, born August 21, 2010. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-02-12 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. Emigrated from U.P. study area. Killed by a puma hunter 01-17-13 at 29 mo. old in GMU 60 in western Colorado near border with Utah. 25.7 F143 was captured on the study area when about 24 months old. Dispersed N on the Uncompahgre Plateau and established an adult home range on the NW portion of the Uncompahgre Plateau (most recent location 07-16-12). 74.5 F145 was originally captured in association of M144 and F146; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145 emigrated to Colorado Mesa. She was killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) F149 06-06-11 12S,729993E, 4242329N→ 12S,713658E, 4229703N F163 01-26-12 M165 02-24-12 12S,732153E, 4232452N→ 12S,695407E, 4280753N 12S,722816E, 4246926N→ 12S,730814E, 4272500N F194 01-29-13 12S,742443E, 4225259N→ 12S,729101E, 4201962N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 20.7 F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old and moved to the NE Uncompahgre Plateau, onto Bostwick Park, then back across Uncompahgre Plateau. She emigrated from the U.P. study area and was killed by a puma hunter 12-31-12 at 20 mo. old 60.7 F163 was initially captured at about 18 months old. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (0716-12 most recent location). 26.9 M165 was first captured 02-24-12 at ~19 mo. old. His origin unknown. He moved from the west slope of the U.P. study area to the east slope of the U.P. north of the study area between 05-042012 and 06-15-12. He was killed by a puma hunter in GMU 62N on 12-17-12 when he was ~29 mo. old. 26.9 F194 was first captured at ~24 mo. old on W slope of U.P. study area on 01-29-13. Her origin unknown. She emigrated from the U.P. study area heading S. Her last aerial location was 06-17-13 on North Mt. in the SW head of Naturita Creek. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2012. Puma sex & ID if marked M Estimated age (mo.) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 M P1018c F P1030c M P1034 M161 24 08-25-10 6 02-16-11 4 10-07-11 18 06-17-13 a Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating Excellent Good Fair Unknown, decomposed Subadult marked (i.e., tattoos, eartags), but not radio-collared. Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. b Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N Highway 62 Leopard Creek 12S,762806E,4219531N Highway 62 Dallas Divide 13S,2475674220129 �Table 19. Pumas monitored with GPS collars on the Uncompahgre Plateau, Colorado, December 2004 to July 2013. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 M178 M179 M183 F2 F3 F7 F8 F16 F23 Sex M M M M M M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F70 F72 F75 F93 F95 F96 F104 F111 F113 F129 F135 F136 F137 F152 F F F F F F F F F F F F F F F F F F F F F F171 F172 F177 F181 F F F F F182 F186 F F Age stage adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult adult adult subadult adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult subadult adult adult adult Dates monitored 12-08-04 to 07-20-06 01-28-05 to 01-14-06 02-18-05 to 05-14-08 03-12-06 to 06-21-06 04-14-06 to 01-01-08 01-07-07 to 07-15-08 01-21-07 to 11-25-10 03-27-09 to 01-16-10 11-12-10 to 12-01-10 11-13-12 to 12-11-12 11-18-12 to 12-29-12 02-14-13 to 07-31-13 01-07-05 to 08-14-08 01-21-05 to 12-11-11 02-24-05 to 08-03-08 03-21-05 to 10-10-06 10-12-05 to 09-10-09 01-04-06 to 02-04-06 02-05-06 to 09-04-09 01-17-06 to 07-25-07 02-09-06 to 09-09-09 03-24-06 to 08-15-07 03-30-07 to 02-22-08 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 08-18-08 01-14-08 to 12-22-11 02-12-08 to 07-07-10 03-26-08 to 06-03-09 10-03-12 to 11-11-12 03-14-13 to 07-31-13 01-28-09 to 07-31-12 05-29-09 to 01-31-12 01-01-10 to 07-31-13 01-27-10 to 06-06-10 01-02-13 to 07-31-13 01-01-11 to 09-20-11 01-20-11 to 07-31-13 04-12-11 to 07-31-13 01-18-12 to 06-15-12 06-16-12 to 12-23-12 01-20-12 to 07-31-13 03-28-12 to 07-31-13 10-27-12 to 12-10-12 01-15-13 to 04-15-13 04-16-13 to 07-31-13 02-04-13 to 07-31-13 03-30-13 to 07-31-13 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Methods for Monitoring Populations Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Puma Population Trend, U.P., CO GO 47 0 IY2 IYl YEARS Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1, 2, 3, and 4 (TY1, TY2, TY3, TY4). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected �non-marked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the state government hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. Post-harvest high trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 11.9% to 16.7% harvest of independent pumas. Post-harvest low trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting and other mortalities are subtracted from the minimum count. TY1 post-harvest low includes 1 adult female and 3 adult males killed off the study area. The TY2 post- harvest low includes 1 adult male killed off the study area and 2 adult female pumas killed in February 2011 on the study area to protect livestock. The TY3 post-harvest low includes 1 adult female and 4 adult males harvested off the study area and 2 adult females that died of natural causes on the study area. The TY4 post-harvest low includes 1 adult female and 1 adult male harvested off the study area and 1 adult female that died of natural cause. This trend line represents 21.2% to 31.2% harvest of independent pumas. Age structure of independent pumas in November 2012 at beginning of puma hunting season in Treatment Year 4, Uncompahgre Plateau, Colorado. 8 7 ~ 6 55 ....if 4 0 ■ Female 0 3 Z 2 ■ Male 1 0 lto 2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age (.y ears) Figure 4. Estimated age structure of independent pumas in November 2012 at the beginning of the puma hunting season in Treatment Year 4 (TY4) on the Uncompahgre Plateau study area, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of independent female and male ages, respectively: 4.29 ± 2.69 yr. (51.48 ± 32.29 mo.), n = 21; 2.51 ± 0.86 yr. (30.12 ± 10.37 mo.), n = 8. �Puma births, Uncompahgre Plateau, Colorado. 16 14 12 ........"'~ 10 8 ;:i 0 z 6 4 17 2 0 I n ■ I ■ j I I I I I 17 I II Jan. Feb. Mar. Apr. May June Ju ly Aug. Sep. ■ Births 2005-2013 I 11 I I n I Oct. Nov. Dec. ■ Births 1982-1987 Figure 5. Puma births (black bars) detected by month from May 19, 2005 to July 31, 2013 (n = 53 litters of 27 females; 51 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. �UP Study Area_ Period 1 Locations ~ N BlM SOR coow CITY COl»ITY FWS lNCJTRIJST NPS """"TE USFS- GMUG U SFS - s.-.N JIJ,,Vf 0 3.75 7.5 15 Kilometers Figure 6. The grid on the east slope of the Uncompahgre Plateau Puma Project study area indicating the 18 camera/call box sites (red dots) in sample period 1. A total of 3 sample periods were used, each 28 days long and each with 18 sites, for a total of 54 random cells surveyed December 2012 to March 2013 to test non-invasive survey methods. Image by M.S. student Kirstie Yeager. �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2013, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 02-20-09 Age to last monitor date alive or at death (days, birth to fate) ~1,664 F9 31 5-28-05 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-02-07 326-333 F10 31 5-28-05 M11 31 5-28-05 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 F13 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 301-308 330 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 54.6 months old. Radio-collared. Shed radiocollar 04-19-06 to 04-26-06. F3 Radio-collared. Dhed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-2005. F10 disappeared by 12-30-05. Radio-collared. Shed collar 10-24 to 11-08-05. Recollared on 04-02-06. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 0711-06 at 14 mo. old. Moved to Dolores River valley in SW CO by 12-14-06. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Radio-collared. Shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Radio-collared. Killed and eaten by a puma possibly M5 (13 mo. old) about 08-28-05. Radio-collared. Shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. F2 F2 F2 F7 F7 F8 F8 308-314 Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Died at 10.8 months old Radio-collared. Probably killed by another puma. Multiple bite wounds to skull. Died at 10 months old. Radio-collared. Shed radiocollar 07-27-06 to 08-02-06. F16 F16 244-245 Radio-collared. Shed radiocollar 05-24-06―05-25-06. F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) F21 37 9-26-05 M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 F35 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 08-16-06 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 324 Radio-collared. Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. Radio-collared. Killed and eaten by male puma 12-21-05 to 12-22-05. F3 ~232-235 Radio-collared. Shed radiocollar 03-21-06 to 03-24-06. F25 63-65 F23 5-30-06 06-30-06 to 07-31-06 63-65 31 5-30-06 38 F36 29 6-9-06 29 6-9-06 M38 41 7-29-06 Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. Dispersed. Killed by puma hunter 01-07-11 in GMU40 Ladder Creek, SW of Grand Junction, CO when he was 53.2 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Dispersed. Killed by a puma hunter 03-12-10 in GMU 40, Bangs Canyon, when 42.8 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F28 M37 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Radio-collared. Assumed dead. Shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 86-87 74 74 352-353 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 1623 9 255 1307 9 Mother I.D. F3 F23 F23 F28 F2 F8 F8 255 53-61 106 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M43 33 8-13-06 M44 8-13-06 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-15-06 03-01-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 200 Radio-collared. Shed radiocollar by 11-7 to 17-06. Dispersed. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO GMU41 at 29.5 months old. Radio-collared. Shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. M44 killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. He was 15.7 months old. Radio-collared. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Died 05-20 to 23-07 when she was 9.2 months old. Radio-collared. Shed collar by 12-14-06. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed collar . Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Dispersed. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in Tabaguache Creek, GMU 61N when 38.9 months old. Radio-collared. M49 was orphaned when his mother died on about 03-26-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Dispersed from natal area. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61N) 01-2409 when ~29 months old. 899 33 09-15-06 to 02-14-07 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 to 12-27-09 89 360 89 360 1187 12-05-06 to 07-31-07 to 01-24-09 939 Mother I.D. F7 F7 F7 F3 F3 F3 F50 �Appendix A continued Puma I.D. Estimated Age at capture (days) F53 183 Est. Birth date 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. survival span from 1st capture to fate or last monitor date 01-12-07 to 02-23-07 to 09-02-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 42 Radio-collared. Shed radiocollar 02-23-07. F53 visually observed by P. & F. Star (Loghill Mesa), on 09-02-07, when F53 was ~14 months old and an independent subadult. F54 Radio-collared. Shed radiocollar 2-27-07. M56 observed 0301-07. Radio-collared. Shed radiocollar 06-07-07. Live mode 0606-07. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dispersed. Survived to adult stage. Killed by a puma hunter 12-27-09 in GMU 521, North Fork Gunnison River, when 31 months old. Radio-collared. Shed collar about 02-14-08. Observed with 11-20-07 with F16, but without siblings M58 and F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. Three cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F7 (?) Radio-collared. Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11-13-08. Not radio-collared. Not radio-collared. Dispersed from study area. Killed by a puma hunter 01-01-11 in Calamity Creek, GMU61N when he was 41.5 months old. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 ~428 subad. 200 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 to 01-01-11 1267 08-17-07 262 Mother I.D. F25 F16 F16 F16 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M65 34 Est. Birth date 7-14-07 Est. survival span from 1st capture to fate or last monitor date 08-17-07 to 11-07-09 Age to last monitor date alive or at death (days, birth to fate) 262 847 F66 37 7-17-07 08-23-07 to 05-28-09 M67 37 7-17-07 08-23-07 to 12-18-11 M68 37 7-17-07 08-23-07 to 12-30-08 682 1615 532 F74 259 6-1-07 5-19-08 03-12-08 to 07-09-08 06-18-08 M76 30 M77 30 403 ~87 5-19-08 06-18-08 ~87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 04-01-08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Dispersed. Survived to adult stage. Killed by Wildlife Services for depredation control for predation on llamas in Little Dolores River, on 11-07-09 when 27.8 months old. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Her range overlapped her natal area. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau study area. Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage. Dispersed. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17.5 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Mother I.D. F24 F30 F30 F30 F75 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) F78 30 M79 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 5-19-08 Est. survival span from 1st capture to fate or last monitor date 06-18-08 ~87 F2 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 F81 40 5-23-08 F95 ~488 ~Aug. 2007 07-02-08 to 07-29-09 12-29-08 to 07-31-13 Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 08/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 02-04-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. F93 F97 257 5-23-08 02-04-09 to 01-22-12 1339 M82 37 5-29-08 07-05-08 to 12-10-09 560 M83 37 5-29-08 07-05-08 to 01-18-11 964 Radio-collared. F95 was offspring of F93. She survived the subadult stage and into the adult stage. Her home range overlapped her natal area. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Dispersed from study area. Killed by a puma hunter 01-22-12 in Dry Creek when 43.9 months old. Radio-collared. Shed radiocollar after 03-20-09. Survived to subadult stage. Dispersed. Killed by a puma hunter in 1210-09 GMU 65, Beaver Creek fork of East Dallas Creek, when 18.4 months old. Not radio-collared. Survived; dispersed from study area. Killed by a puma hunter 01-18-11 in Coates Creek west of Glade Park, GMU40. He was 31.6 months old. 424 2,196 Mother I.D. F2 F23 F23 F23 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M84 36 6-5-08 F85 36 F86 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-11-08 to 02-11-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 251 6-5-08 07-11-08 to 10-01-08 118 36 6-5-08 07-11-08 to 07-23 to 08-03-08 ~48-59 M87 28 7-3-08 07-31-08 to 12-06-11 1251 M88 28 7-3-08 07-31-08 to 11-30-10 880 F89 M90 28 36 7-3-08 7-9-08 07-31-08 08-14-08 Male 7A 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located her on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 0214-09. Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill at age 3.9 months. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11 at 31 months old. Killed by puma hunter on 12-06-11 at 41 months old in GMU61N north of the study area. Not radio-collared. Dispersed. Killed by a puma hunter in Dawson Creek, Disappointment Valley, GMU711 on 11-3010 when 28.9 months old. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. 867 Mother I.D. F70 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 8-19-08 Est. survival span from 1st capture to fate or last monitor date 09-29-08 455 35 8-19-08 09-29-08 976 F95 16 mo. June-07 12-29-08 F98 4-5 mo. 158 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 M99 Sep-Oct08 Sep-Oct08 M101 35 4-15-09 157 M102 35 4-15-09 05-20-09 to 09-19-09 05-20-09 F103 35 4-15-09 159 M105 38 5-7-09 F106 38 5-7-09 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 M107 34 5-25-09 Radio-collared. Killed by a puma hunter on study area during TY1 as dependent cub on 11-17-09 at age 14.9 months. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Due to dangerous tree, could not handle him safely to fit new radiocollar. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. To date, July 2012, F95’s home range mainly adjacent to N side of natal area. Radio-collared. Died; probably killed by male puma (infanticide). Radio-collared. Offspring of non-marked female. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma; apparent canine punctures to braincase. Radio-collared. Died; killed by puma M55 after he was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 09-04-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after she was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 02-09-10 due to shed collar. Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 02-24-10; not collared. Dispersed. Killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 06-28-09 to 02-24-10 488 278 275 661 241 Mother I.D. F25 F25 F93 Unm.F Unm.F F16 F16 F16 F75 F75 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) F108 34 Est. Birth date 5-25-09 Est. survival span from 1st capture to fate or last monitor date 06-28-09 to 03-05-10 Age to last monitor date alive or at death (days, birth to fate) 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 to 01-06-13 1,225 M115 427 Nov.-08 07-21-10 610 M117 193 Aug.-09 02-05-10 to 01-01-11 518 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 06-12-10 06-12-10 to 07-21-10 39 M120 30 06-28-10 07-28-10 to 12-02-10 526 M121 30 06-28-10 273 M122 35 07-8-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 F123 29 07-15-10 217 F124 29 07-15-10 08-13-10 to 02-17-11 08-13-10 to 02-16-11 931 216 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11 at 18.1 months old. Not radio-collared; too small. Radio-collared. Lost contact after 05-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11. Dispersed. Killed by a puma hunter 01-06-13 in GMU73 SE of Dolores, CO; age 41 months. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Killed by a puma hunter on the natal area in Beaver Creek, GMU70E, off the U.P. study area on 01-01-11 when he was 17 months old. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. Killed by a puma hunter on his natal area on 12-06-11 when he was 17.2 months old. Radio-collared. Lost radio contact after 03-28-11. F94 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). M122 killed by a puma hunter in Tatum Draw, Dry Fk. Escalante Cr., GMU62N, 01-23-13; age 30 months. Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. F104 F94 F70 F28 F119 F72 F72 F3 F3 F94 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) M125 29 07-15-10 M126 28 08-08-10 M127 28 M128 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 08-13-10 to 02-01-11 09-05-10 to 01-08-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 201 08-08-10 09-05-10 to 09-10-11 398 28 08-08-10 198 F129 35 08-21-10 09-05-10 to 02-22-11 09-25-10 to 02-02-12 M130 35 08-21-10 09-25-10 to 02-02-12 M131 35 08-21-10 09-25-10 to 07-21-11 F132 35 08-21-10 09-25-10 35 M134 ~18 mo. ~June-09 12-14-10 to 06-10-11 740 M139 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO, GMU61N, as 17-month-old subadult. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. Found dead 09-14-11 on natal area; killed by another puma on about 09-10-11 at age 13 months. Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Survived to recapture on 02-02-12 at 17.4 months old, with sibling M131; neither handled due to dangerous trees. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-0212 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. Dispersed. Killed by a puma hunter in Lion Cr., extreme western CO, GMU60; age 29 months. Not radio-collared. Too small for collar design. Fate unknown. Apparently died; not with F96 and siblings F129 and M130 on 02-02-12. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. He was about 24 mo. old Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. 221 530 530 334 Mother I.D. F94 F118 F118 F118 F96 F96 F96 F96 Unm. F F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) F140 ~5 mo. Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. ~Aug.10 Est. survival span from 1st capture to fate or last monitor date 01-02-11 to 07-31-13 1,096 Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Recaptured and re-collared 01-12-12 as 17-month-old subadult on natal range. Survived to adult stage. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Killed by a puma hunter on 12-23-11 in his natal area; age 16 months. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. Orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-16-11. She ranged in her natal area until her radiocollar quit after 0412-12. Radio-collared. F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old. Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). Radio-collared. Lost contact after 03-21-11; shed collar. Recaptured 01-18-12; fit with GPS collar at 19 months old. Ranged on natal area as adult (philopatric). First litter on 0808-12 at 26 mo. old. Killed by puma hunter on 12/23/12. Radio-collared. M154 probably died of starvation following natural death of his mother F135. Sibling M155 also died. Radio-collared. M155 died of starvation following death of his mother F135. Sibling M154 also died. Radio-collared. M156 shed the collar about 09-05-11. He was 59 days old. Unk./ F28? M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 509 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 04-21-11 to 07-31-11 315 F149 45 04-22-11 06-06-11 to 07-16-12 451 M150 525 08-31-09 02-07-11 to 04-11-11 588 M151 253 06-16-10 264 F152 271 06-16-10 02-24-11 to 03-07-11 03-14-11 to 12-23-12 M154 42 07-06-11 77 M155 42 07-06-11 M156 43 07-08-11 08-16-11 to 09-21-11 08-16-11 to 09-25-11 08-20-11 to 09-05-11 183 776 81 56 Unk./ F28? Unk./ F28? Unk. F24 F23 F70 F111 F93 F135 F135 F137 �Appendix A continued Puma I.D. Estimated Age at capture (days) F157 40 08-18-11 F158 40 M159 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-27-11 to 01-15-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 150 08-18-11 09-27-11 to 01-15-12 150 40 08-18-11 09-27-11 to 12-01-11 105 M161 276 04-22-11 01-23-12 to 10-15-12 543 M162 183 07-25-11 01-25-12 to 06-11-12 322 M168 37 07-27-12 09-02-12 to 09-12-12 47 F169 37 07-27-12 09-02-12 to 09-12-12 47 M170 137 08-29-11 199 P1033 22 07-10-11 01-13-12 to 03-12-12 NA Radio-collared. F157 with sibling F158 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. Radio-collared. F158 with sibling F157 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. Radio-collared. M159 probably died about 12-01-11 when he was located with his family (F70, siblings F157, F158). He was not located with them on 12-12-11 and was not observed with them on 12-13-11. He was 105 days old on 12-01-11. Radio-collared. M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old. Shed his expandable collar about 08-03-12. Was struck and killed by a vehicle on Dallas Divide, Hwy 62 in October 2012 when 18 mo. old. Radio-collared. M162 probably was orphaned cub of nonmarked adult female puma killed on Pinto Mesa 01-18-12. M162 died of starvation on 06-11-12 when he was 322 days (10.6 mo.) old. Radio-collared. Cub M168 was offspring of F96; sibling of F169 & F173. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. Cub F169 was offspring of F96; sibling of M168 & F173. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. M170 died about 03-15-12 of unknown natural cause. He was 199 days (6.5 mo.) old. Radio-collared. Cub P1033 was offspring of F136. It died of predation, probably killed by a puma or black bear in the nursery when about 22 days old, before researchers could examine the entire litter to sample and mark the cubs. 22 Mother I.D. F70 F70 F70 F23 Unm.F F96 F96 F171 F136 �Appendix A continued Puma I.D. Estimated Age at capture (days) F173 37 07-27-12 M174 32 M175 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-02-12 to 09-12-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 47 08-08-12 09-11-12 to 03-10-13 181 32 08-08-12 09-11-12 to 12-11-12 126 F184 208 08-25-12 03-20-13 to 07-29-13 339 F185 ~183 ~Oct.2012 03-23-12 to 03-27-13 190 F187 31 05-14-13 77 F188 31 05-14-13 F189 38 06-18-13 M191 ~183 ~July 2012 06-14-13 to 07-29-13 06-14-13 to 07-29-13 07-26-13 to 07-31-13 01-03-13 to 01-20-13 PM1068 ~183 ~July 2012 01-03-13 to 01-20-13 ~210 M192 199 06-20-12 01-04-13 to 07-01-13 376 Radio-collared. Cub F173 was offspring of F96; sibling of M168 & F169. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. Cub M174 was offspring of F152; sibling of M175. He was orphaned after his mother was killed by a hunter on 12-23-12. He was 137 days old. M174 was recaptured at 181 days old and removed from the wild to be rehabilitated at the CPW Del Norte wildlife center for rerelease to the wild at a later date. Radio-collared. Cub M175 was offspring of F152; sibling of M174. He was mauled to death probably by puma hunting dogs on about 12-11-12 when he was 126 days old. Radio-collared. Cub F184 was offspring of F111; one other sibling track was observed, but the puma was not captured. F184 still dependent on F111 on 07-29-13. Radio-collared. Cub F185 was offspring of a non-marked female puma in Roubideau Cyn. F185 shed her expandable collar about 7 days after initial capture. Lost contact. Fate unknown. Radio-collared. Cub F187 was offspring of F96; sibling of F188. Radio-collared. Cub F188 was offspring of F96; sibling of F187. Radio-collared. Cub F189 was offspring of F136; sibling of F200 and M201. Radio-collared. Cub M191 apparently was offspring of F28 (with non-functional GPS collar). He was sibling of PM1068 and one other non-marked cub. M191 was killed by a non-marked male puma on about 01-20-13 along with PM1068. PM1068 was not captured and tagged. It was apparently offspring of F28; sibling of M191 and one other nonmarked cub. PM1068 was killed and partially eaten by a non-marked male puma. Radio-collared. M192 was offspring of F118; sibling of M193 & F195. M192 was independent of F118 at ~11.7 mo. old. He shed his expandable collar at a mule deer kill after 07-01-13. 77 44 ~210 Mother I.D. F96 F152 F152 F111 Unm.F F96 F96 F136 F28 F28 F118 �Appendix A continued Puma I.D. Estimated Age at capture (days) M193 199 Est. Birth date 06-20-12 Est. survival span from 1st capture to fate or last monitor date 01-04-13 to 07-01-13 Age to last monitor date alive or at death (days, birth to fate) 376 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. M193 was offspring of F118; sibling of F118 M192 & F195. M192 was independent of F118 at ~11.7 mo. old. He shed his expandable collar at a mule deer kill after 07-01-13 like sibling M192, but the siblings were not associating (kills were at different locations). F195 227 06-20-12 02-01-13 to 258 Radio-collared. F195 was offspring of F118; sibling of F118 03-04-13 M192 & M193. F195 shed her expandable radiocollar at an elk kill on about 03-04-13; contact lost afterwards. M198 274 ~June 04-10-13 to 417 Radio-collared. M198 was offspring of non-marked female PF1074 2012 07-31-13 PF1074 (sampled by bio-dart). He was sibling of F199. F199 292 ~June 04-18-13 to 417 Radio-collared. F199 was offspring of non-marked female PF1074 2012 07-31-13 PF1074 (sampled by bio-dart). She was sibling of M198. F200 38 06-18-13 07-26-13 to 44 Radio-collared. Cub F200 was offspring of F136; sibling of F136 07-31-13 F189 and M201. M201 38 06-18-13 07-26-13 to 44 Radio-collared. Cub M201 was offspring of F136; sibling of F136 07-31-13 F189 and F200. F202 35 06-25-13 07-30-13 to 36 Radio-collared. Cub F202 was offspring of F172. No F172 07-31-13 siblings were observed at the nursery; but some could have hidden. a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. �Colorado Division of Parks and Wildlife July 2013 –June 2014 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project: W-204-R1 : : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates on the Uncompahgre Plateau Period covered: July 31, 2013−June 30, 2014 Author: Kenneth A. Logan. Personnel: K. Logan, R. Alonso, S. Bard, Yasaman Shakeri, W. Hollerman, W. Jesson, R. Navarrete, B. Nay, S. Waters, B. Banulis, T. Bonacquista, M. Caddy, K. Crane, E. Phillips, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation, Safari Club International Foundation, and The Summerlee Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Parks and Wildlife (CPW) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, years 1-5) and presence (treatment period, years 6-10) of sport-hunting. The purpose of the study is to evaluate the assumptions underlying the CPW puma management program with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for research purposes on the Uncompahgre Plateau (Logan 2009). This report provides information on the fifth year of the treatment period (TY5), August 2013 through July 2014, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 18, 2013 and closed January 10, 2014 after a quota of 5 independent pumas were killed. The harvest was designed to test the management assumption that an 815% harvest of independent pumas results in a stable-to-increasing population. The decline in the puma population on the study area during TY1 to TY3 necessitated a reduction in the harvest quota from 8 to 5 to continue to test the harvest assumption for a stable-to-increasing puma population. The five pumas killed included, 1 adult female, 3 adult males, and 1 subadult male. The harvest of five independent pumas represented 11.4% of the 44 independent pumas in our minimum count during November 2013 to April 2014. Independent females and males comprised 20.0% and 80.0% of the harvest, respectively. One other radio-collared adult female in the study area population died of natural cause in November 2013. The total mortality of 6 independent pumas during the TY5 minimum population count (November through April) represented 13.6% of the 44 minimum count of independent pumas on the study area. Sixty-five hunters requested mandatory permits with an attached voluntary hunter survey in TY5. Forty-four of the hunters provided responses on the surveys. An estimated 37 hunters actually hunted on the study area, of which about 13.5% harvested pumas and 27.0% captured pumas (i.e., harvested plus 1 �treed and released). Twenty-seven of 29 answering hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks <1 day old encountered by hunters and pumas captured by hunters indicated that independent female pumas were detected more frequently than males in TY5. Researchers captured 38 individual pumas 43 times from August 2013 to July 2014. Two capture teams with dogs operated during 75 search days from January 9, 2014 through April 24, 2014 to find 361 puma tracks, pursue pumas 82 times, and capture 24 pumas 29 times. Capture efforts with cage traps resulted in the capture of 2 independent pumas for the first time, and the recapture of 1 adult male. Twelve new cubs were captured and marked. A total of 56 pumas were monitored by radio-telemetry in TY5. Search efforts also revealed the presence of at least 13 other independent pumas. Our minimum count of 44 independent pumas from November 2013 to April 2014 included: 27 females and 17 males. A preliminary minimum estimated density of independent pumas was 2.63/100 km2. The TY5 minimum count of 44 was up slightly from 42 in TY4 and could be attributed partially to the reduction in harvest from 15% to 11% in TY4 and to immigration especially of subadult male pumas on the east slope of the study area. The proportion of radio-collared adult females giving birth in the August 2012 to July 2013 biological year was 0.33 (5/15). Since 2005 puma births occurred mainly from May through August, involving 86% of births. We monitored 22 female and 7 male adult radio-collared pumas for survival and agent-specific mortality. Adult puma survival rates in TY5 for adult females and males were 0.678 (SE=0.0934) and 0.667 (SE=0.1721), respectively. Sport-hunting mortality was the major cause of death. One adult female was struck and killed by a vehicle on state highway 550. One adult female was killed for depredation control. Of 21 radio-collared cubs in TY5, 14 were monitored continuously. Of those 14, six died. Causes of death included: starvation (3), infanticide or predation (1), and unknown natural causes (2). Puma harvest, capture, and radio-telemetry data from the beginning of this study to the present provided information on dispersals of 41 pumas initially marked on the study area. Those pumas moved from about 18 to 370 km from initial capture sites. Since the start of this study 48 adult pumas have been monitored with GPS collars and have yielded over 70,000 locations. In addition, 45 subadult pumas have been monitored for survival and fate data. Efforts to develop and test puma population survey methods continued with a pilot project started in June 2014. We are evaluating the use of temporary foot-hold devices and break-away neck snares as passive devices that non-invasively collect puma hair for DNA genotyping and mark-recapture population estimation methods. Those efforts will continue into November 2014. 2 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN PROJECT NARRATIVE OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction of females, stage-specific survival, and immigration and emigration; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the fifth year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the fifth year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and stage-specific survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore non-invasive methods for sampling pumas to estimate abundance. INTRODUCTION Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of “achieving healthy, self-sustaining populations” through management (Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been conducted in Colorado since the early 1970s and puma harvest data is compiled annually, additional information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is needed. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in pumaprey interactions. Staff on the Front Range placed greater emphasis on pumahuman interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). 3 �● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the grayshaded components on the left side of the conceptual model in Figure 1 that pertain to the puma population, including: effects of harvest and other mortality, movements and corridors, population dynamics, vulnerability to harvest, population models, and methods for monitoring populations. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas to investigate the effects of sport-hunting and other causes of mortality on puma population dynamics. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CPW’s puma model-based management and attendant assumptions with Coloradospecific data from objectives 13. Consider other useful models. 5. Conduct a pilot study to develop methods that yield reliable estimates of puma population abundance. 6. Investigate diseases in pumas. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 which involves the use of controlled recreational hunting to manipulate the puma population. 4 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 15 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992), and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age classes - adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to provide allowable harvest quotas in an effort to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). These objectives are expected to provide both the capacity for puma population resiliency to achieve a state-wide goal of a healthy, self-sustaining puma population while managing the puma population to provide sport-hunting opportunity and population control in some DAUs (even though puma population dynamics in any DAUs are not known). Basic model parameters assigned to the model are: puma population density, sex and age structure, annual population growth rate, and relative puma habitat quality and quantity. Parameter quantities are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing  include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed  = 1.15. 3. An assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and Puma harvest rate formulations for DAUs assume that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus 5 �subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). This assumption is vital to providing the capacity for resiliency in the state-wide puma population which is hunted by applying this assumption to about three-quarters of the puma GMUs in the state. H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). This assumption is applied to about one-quarter of the GMUs in the state. H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. 6. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2007). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest as predicated by puma movement patterns. It was assumed that pumas that traveled longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 5 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will 6 �investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics by using harvest composition as an indicator. We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1986, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. Information which will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. 7 �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. People reside year-round along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area easily accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma populations in western North America for at least the past 100 years. Hence, the reference period, years 1 to 5, provided conditions where individual pumas in this population expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6 to10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e., effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to 8 �hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were recorded via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and enabled dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snowmobiles, and on foot. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg based on estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). The immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers for capture were released without handling, or we encourage 9 �the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and movement across Data Analysis Unit boundaries). Adults, subadults, and cubs were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs 10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHF10 �collared pumas were identified about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using a hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around those locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes were recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters. Cubs were fit with small VHF transmitters mounted on expandable collars that expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.311 kg (525 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with the Colorado puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. This minimum count is achieved by very intensive field operations and should be considered close to a complete enumeration of independent pumas counted during our annual November to April search period. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). 11 �Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2013 to July 2014, was the fifth year of the treatment period (TY5) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 18, 2013 and was scheduled to extend to January 31, 2014, unless the harvest quota was taken before then. The harvest design quota was 5 pumas, the same as in TY4 in an effort see if the lower harvest rate of about 11% (reduced from a desired 15%) would result in a stable or increased number of independent pumas (Logan 2013). We reduced the harvest rate because the population of independent pumas was declining during TY1 to TY3, contrary to the expected population trend in this research project and the realization that the population would probably continue to decline with a 15% harvest rate. This harvest design still tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (Assumption and Hypothesis 3 p.5-6 this report). The 11% harvest is in the middle of the 8 to 15% harvest range we are testing. The initial quota of 8 pumas for TY1, TY2, and TY3 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY3 was based on the observed minimum count of 52 independent pumas during November 2010 to April 2011 in TY2 and that approximately the same number of independent pumas was expected during the puma hunting season for TY3. The hunting structure in TY5 was the same as in TY1 to TY4, except for the reduction in quota (see above). The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). 12 �All pumas harvested on the study area were examined by principal investigator K. Logan and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon inspection, the following data were recorded: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. The puma hunting season occurred on the study area from November 18, 2013 to January 10, 2014, taking 54 days to fill the quota of 5 pumas; the longest hunting season yet on the study area during this treatment period. This was 13 more days than it took to harvest 5 pumas in TY4 (i.e., 41 days, Nov. 19 to Dec. 29, 2012), 21 more days than it took to harvest 8 pumas in TY3 (i.e., 33 days, Nov. 21 to Dec. 23, 2011), 33 days more than it took to harvest 8 pumas in TY2 (i.e., 21 days, Nov. 22 to Dec. 12, 2010) and 28 more days than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Five pumas were killed on the study area, including: 1 adult female, 3 adult males, and 1 subadult male (Table 2). Of the 5 harvested pumas, 3 were marked: F111, M92 and M180. In addition to the pumas killed on the study area during the Colorado puma hunting season, 1 other marked adult female puma died during November 3 to 5, 2013 (Table 3). Adult female F140 died from an unknown natural cause. This puma was included in the minimum count of pumas for TY5 because she was initially captured on the study area and was present in the population during the TY5 survey period (Nov.–Apr.). The harvest of 5 independent pumas on the study area was 11.4% (5/44*100) of the minimum count of 44 independent pumas counted on the study area, including 27 females and 17 males, determined by intensive searches of the research team during November 2013 to April 2014 (Table 4). Independent females and males comprised 20.0% (1/5*100) and 80.0% (4/5*100) of the harvest, respectively. This harvest structure was 3.7% (1/27*100) of the independent females and 23.5% (4/17*100) of the independent males. Considering the mortality of 1 other radio-collared independent puma (F140; Table 3), the mortality of 6 independent pumas was 13.6% (6/44*100) of the minimum number of 44 independent pumas. The mortality composition of 2 females and 4 males was comprised of 33.3% (2/6*100) females and 66.7% (4/6*100) males. This mortality structure was 7.4% (2/27*100) of the independent females and 23.5% (4/17*100) of the independent males in the minimum count. The minimum count of 44 independent pumas in TY5 was slightly higher than the 42 minimum count in TY4, but was lower than the minimum count of 48 independent pumas in TY3, 52 independent pumas in TY2, and 55 in TY1 (Table 4). The slightly higher number of independent pumas in TY5 compared to TY4 suggests that the puma population responded in a positive way to the lower harvest rate (11%) applied in TY4 (Fig.3.) and to immigration of subadults. Nevertheless, the population decline caused by the higher harvest rate during TY1 to TY3 was still evident in a low population phase, and was particularly represented in losses to the adult female and adult male segments (Table 4, Segment Objectives 4 & 5 below). Hunter permits and survey: In TY5 mandatory permits with the voluntary survey attached were requested by 65 individual puma hunters. This number is lower than 70 hunters in TY4, and continued a downward trend from 74 hunters in TY3. It was close to 64 hunters in TY2, yet down substantially from 79 hunters in TY1. Thirteen of the hunters requested a second permit (after 14 days of the first permit had expired). Eleven hunters requested three permits, and one hunter requested four permits. Forty-four individual hunters (67.7%; 44/65*100) provided responses to the voluntary survey by turning in the 13 �printed survey. Of the respondents, 19 hunters indicated that they did not hunt on the study area. Twentyfive hunters indicated they did hunt at least one day. The proportion of the 44 respondents that hunted (25/44 = 0.568) extrapolated to the total of 65 hunters (0.568*65) indicated that about 37 hunters took to the field for pumas on the study area during the 54-day TY5 hunting season. This was down from 40 hunters in TY4, 49 hunters in TY3, 42 hunters in TY2 and 67 hunters in TY1 (Logan 2010, 2011, Logan 2012, Logan 2013). Considering that 37 hunters were estimated to be afield, then 13.5% of the hunters harvested pumas (5/37*100) and 27.0% of hunters captured pumas (10/37*100; see captured and released pumas below and in Table 5). The 44 puma hunters that turned in the volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 27 respondents that answered the question (93.1%; 27/29 = 0.931). Of the remaining hunters, 2 indicated they were non-selective (6.9%). Fifteen hunters that returned surveys did not answer the question. The voluntary hunter survey also revealed that four hunters treed other pumas on the study area, but chose not to kill them (Table 5). The hunters’ reasons for not wanting to kill the pumas included they were not legal game (2 cubs), the size was too small to harvest (1 subadult males, 1 adult male). No reason was given for not harvesting one other subadult male. In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters and hunter selection to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to pumas that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters’ responses in TY5 showed they encountered 17 puma tracks less than one day old. Of those, 11 tracks were of females, and 6 tracks were of males, indicating that during the TY5 hunting season females were more detectable than males. These data from TY5 were consistent with data from two previous treatment years TY2 and TY3 (these data were not gathered in the survey for TY1) where tracks less than 1 day old reported by puma hunters consistently favored females (TY2: 20 female, 10 male; TY3: 15 female, 6 male). But, they were at variance with TY4 (8 female, 11 male). Of the 11 female tracks less than one day old, 10 hunters that encountered them said they had no intent to harvest the puma and one hunter did not indicate his intent. However, one of those hunters killed adult female F111 because he could not clearly sex the puma and thought it was a male. Of the 6 male tracks less than one day old, 3 of the hunters that encountered them indicated intent to harvest the pumas and in fact they did harvest 2 of them. One hunter that encountered both male and female tracks together did not intend to harvest the pumas he pursued. Two other hunters that encountered male tracks did not indicate their intent to harvest them. These preliminary survey and harvest data for TY5 indicate that hunters detected independent female pumas more frequently than males and males were captured by hunters more frequently than females by 7 to 1 (i.e., males = 4 harvested + 3 captured and released; females = 1 harvested). Moreover, hunters chose to kill males instead of females. Results in TY5 indicated selection for male pumas by hunters were consistent with TY1, TY2, TY3 and TY4 results. In addition, hunters in TY1, TY2, and TY3 treatment years caught females slightly more frequently than males, and males were selected for harvest. But, in TY4 hunters said they detected independent male pumas more frequently than females, and males were captured by hunters more frequently than females (Logan 2013). This preliminary assessment from the treatment period (i.e., TY1-TY5) puma harvest and hunter survey data suggests that generally female pumas were detected by hunters more frequently than male pumas, except for TY4, the 14 �large majority of puma hunters were selective, and hunter choices influenced harvest sex and age composition. Harvest composition was not simply determined by hunter detections of pumas as determined by puma movement patterns (Hypothesis 6, previously). These results do not support assumptions in Hypothesis 6. Independent male pumas on our study area were more vulnerable to harvest mainly due to hunter selection (not to greater detection), while independent female pumas were more detectable. In addition, the puma population declined even though independent male pumas dominated the harvest all 5 treatment years, with percentages in harvest ranging from 60% in TY4 to 75% in TY2 during the decline years, to 80% in TY5 when the population was still in low phase. Moreover, adult males dominated the harvest in TY1 (62.5%) when the population was highest, in TY2 (62.5%) as the population declined, and in TY5 (60%) when the puma population was still in low phase, contrary to predictions. Subadult males comprised a large percentage of the harvest (50%) only in TY3 when the population was well into a decline phase. Segment Objective 2 After the harvest quota was filled, puma research teams immediately initiated capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes of the study area, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radio-collar pumas the remainder of winter and early spring 2013-14. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area during November to April. We made 43 captures of 38 individual pumas from August 2013 to July 2014 (Tables 6-11); 24 individual pumas were captured with dogs 29 times, including one that was originally captured in a cage trap earlier. Three pumas were captured in cage traps. Twelve cubs were captured at nurseries by hand. A total of 56 individual pumas were monitored with radio-telemetry from August 2013 to July 2014 (some of these had been collared in previous years), representing sex and age classes including: 23 adult females, 7 adult males, 4 subadult females, 5 subadult males, and 21 cubs (13 female, 8 male). Three subadult females and 2 subadult males that were monitored survived to adult age during the biological year. Trained dogs were used as our main method to capture, sample, and mark pumas from January 9, 2014 to April 24, 2014. Those efforts resulted in 75 search days, 361 total puma tracks detected of which 109 were ≤1 day old, 82 pursuits, and a total of 29 puma captures of 24 individual pumas (Table 6). Search days with dogs in TY5 (75) was almost equal to TY4 (74), slightly lower than TY3 (79 days) and lower than TY1 (86 days) and TY2 (81 days) (Table 12). The frequency of tracks (tracks/day) encountered in TY5 was the highest of all the treatment years (Table 12). The capture rate (capture/day) in TY5 fell at the mid-range of the capture rates for TY1 to TY5 (Table 12). The number of new pumas captured for the first time in TY5 was the second lowest, exceeding only TY1 (Table 12). Researchers in the two hound capture teams also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected and pursued by puma hunters. The count was: 37 tracks of females, including 10 associated with cubs; 11 tracks of males; 1 track of a lone cub; and 3 track of unspecified sex. These tracks ≤ 1 day old were found by the researchers after the TY5 puma hunting season when one independent female and four independent males were harvested and one adult female died natural causes earlier in November (Tables 2 and 3). Therefore, those dead pumas were not present to make tracks for our researchers to observe. By comparison, the number of first tracks <1 day reported by puma hunters in TY5 was 11 females and 6 males (Segment Objective 1 above). 15 �Puma capture efforts using ungulate carcasses and cage traps occurred from October 8, 2013 to July 21, 2014 with the main efforts in the fall and spring (Table 10). We used 50 road-killed mule deer and one road-killed elk at 24 different sites. One subadult female (F210) and 1 adult male (M211) were captured for the first time. One adult male (M196) was recaptured and re-collared. Pumas scavenged at 11 of 51 (21.6%) of the ungulate carcasses used for bait. We sampled 12 new cubs, including 5 females and 7 males (Table 11). All except 1 were radiocollared to monitor survival and agent-specific mortality (Appendix A). One other non-marked female cub (PF1094; offspring of F176) was mauled to death by our dogs on 2/4/2014 when the cub was about 7 months old. Besides our direct puma captures with dogs January through April, we detected 13 radio-collared pumas that we were able to identify with GPS or VHF telemetry 18 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. In addition to the harvest and capture data (previously), our search efforts revealed the presence of at least 26 to 28 non-marked pumas which we included in our minimum count November 2013 through April 2014 (Table 4). We classified those pumas as: 6 adult females, 4 adult males, 3 subadult males, and 13 to 15 cubs. Of these pumas, one adult female and one adult male were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). In addition, one cub was mauled to death by our dogs (PF1094, previously). The two adults were bio-darted for genotyping and we collected tissue from the dead cub. We could separate the activity of these other pumas from the GPSand VHF- collared pumas in time, space, track size differences between females and males, and by the numbers of cubs following females. Also, one non-marked adult male was photographed by a digital trail camera with two notches in his right pinna that distinguished him from M211 caught for the first time. An adult female was photographed by a trail camera while associating with M196. A subadult male was photographed twice while scavenging on mule deer bait. Our intensive search and capture efforts during January through April 2014, information from pumas previously marked and GPS/VHF-monitored pumas, and information from the puma hunting season in TY5 enabled us to quantify a minimum count of 44 independent pumas detected on the Uncompahgre Plateau study area, including 27 independent females and 17 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas killed by hunters on the study area, observations of marked and non-marked pumas observed by researchers or pursued, treed and released by hunters on the study area, puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars, and distinctive pumas photographed by trail cameras. Of the 44 independent pumas, 31 (70.5%) were marked and 13 (29.5%) were non-marked animals (i.e., some may have ear-tags and tattoos). The abundance of independent pumas in TY5 on the east slope (25; 13 females, 12 males) was greater than the west slope (19; 14 females, 5 males) of the study area. The largest difference was the higher number of subadult males detected on the east slope (Table 4). Otherwise, the sex structure of adult pumas on the east and west slopes was similar, with substantially more females than males. The slight increase in independent pumas in TY5 compared to TY4 was attributed to the addition of one adult male and an increase in subadult males. Considering the minimum count of 44 independent pumas in TY5, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the 16 �Uncompahgre Plateau study area was 2.63 independent pumas/100 km2. The adult puma density was 1.97 adult pumas/100 km2. These preliminary densities contrast with the highest densities for the study area in TY1, in which there were 3.29 independent pumas/100 km2 and 2.99 adult pumas/100 km2. The TY5 minimum count of 44 independent pumas was a slight increase over 42 minimum independent pumas counted in TY4 (Table 4). This signaled stabilization if not slight increase in the puma population compared to the steady decline phase that occurred during the 4 previous treatment years TY1 to TY4; however, the population was still in low phase (Fig. 3). A stabilization or slight increase can be attributed to the lower harvest rate in TY4 (Fig. 3) in which the harvest rate was reduced from a designed 15% to 11% of independent pumas (i.e., quota reduced from 8 to 5 pumas) and to immigration of subadults (Table 4). Clearly, a 15% harvest rate of independent pumas on the Uncompahgre Plateau study area, in addition to other sources of mortality, reduced the abundance of independent and adult pumas (Fig. 3, Table 4). Between TY1 and TY5 minimum counts indicated that the adult female segment of the population had declined from 30 to 23 females, a 23% decline. During this decline the percent of adult females in the study area sport harvest ranged from zero to 40%, with zero adult females killed in TY2, and 25% in TY1, 37.5% in TY3, 40% in TY4, and 20% in TY5. The percent of independent females (adults plus subadults) in the harvest ranged from 20% (TY5) to 37.5% (TY1 and TY3). The puma population declined with 25% to 37.5% independent females in the harvest from TY1 to TY3. The adult male segment had declined from 20 to 10 adults, a 50% decline which is indicative of the strong hunter selection for male pumas (previously in Segment Objective 1). The number of independent pumas (adults and subadults) declined from 55 to 44 pumas, a 20% decline. The largest decline in the number of independent pumas occurred between TY1 and TY4 after three years of an intended 15% harvest rate of independent pumas and before the harvest rate was reduced to 11%. The independent pumas declined from 55 to 42, a 24% decline. These results from this population test do not support Hypothesis 3 (previously). The estimated age structure of independent pumas in November 2013 at the beginning of the puma hunting season in TY5 on the Uncompahgre Plateau study area is depicted in Figure 4. The male age structure is young and declined primarily due to harvest during TY1, TY2, TY3, and TY4 (Logan 2010, 2011, 2012, 2013) and immigration of subadults with the oldest males about 4.75 years old. The female age structure was also distributed mainly to the younger ages but with several distributed among the older ages, including two aged 10+ years. This age structure is a characteristic of the decline in the puma population from TY1 to TY5 (Fig. 3) and attendant with reduced adult annual survival rates, especially of males, when compared with the reference period (Table 15). Segment Objective 3 During the past 9.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). In TY5 we directly observed four litters in nurseries and inferred the birth of one other litter from the GPS data of the mother (F129). In the latter case lack of private land access impeded our ability to observe the litter. Of those 5 litters, four were born in August 2013 and one was born in June 2014 (Table 11, Table 13). In addition, one litter identified by one observed male cub that was captured and marked (M225) was born to an unmarked female in September 2013. Data on reproduction we observed in TY1, TY2, TY3, TY4 and TY5 were added to Table 13 which gives the reproductive chronology and information on mates (if known) of reproducing females. The proportion of radio-collared adult females giving birth from August 2013 to July 2014 biological year (TY5) was 0.33 (5/15). For the previous 4 treatment years the proportion was TY1=0.53 (8/15), TY2=0.53 (9/17), TY3=0.29 (5/17), TY4=0.67 (10/15). 17 �Considering our 57 total litters from 31 females, including 53 observed with cubs 25 to 45 days old and 4 other litters confirmed by nurseries and ≥1 nursling cub tracks or dead cub remains with GPScollared females (Table 13), the distribution of puma births by month from 2005 to 2014 indicate births extending from March into September (Fig. 5). Births began in spring and were high in May through August with a peak in July. Our data from the past 10 years indicated no observed live births from October through February. Births during late spring to late summer (May to August) involved 86% (49/57*100) of the births (Fig. 5). The data indicated that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 19821987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions of births in the reference and treatment periods separately for a treatment effect on timing of breeding and births. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2014, we monitored 31 adult male and 47 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). Annual survival rates for adult pumas generally declined during the treatment period (Table 15), with the exception of adult females in TY2. Otherwise, adult puma survival rates declined substantially in the treatment period and the greater mortality was associated with the population to decline (Table 4, Fig. 3). The major cause of mortality was sport-hunting (Table 14). In TY5 we monitored 22 adult females and 7 adult males for annual survival and agent-specific mortality in TY5. Annual survival rate for adult females was 0.678 (SE=0.0934) and for males was 0.667(SE=0.1721). Sport-hunting was the only cause of death for adult males. However, one adult female was killed by a hunter, two died of other human causes, and one died of natural cause. Adult F182 was struck and killed by a vehicle on highway 550 August 25, 2013. She was about 48 months old at death and was pregnant with two fetuses that probably would have been born in September. This mortality made the sixteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Seven of the 16 pumas were marked, including 4 adults with GPS/VHF collars. Adult F136 was shot on September 30, 2013 by a U.S.D.A., A.P.H.I.S.,Wildlife Services agent because she killed a domestic goat. Her three 3.4 month-old cubs (F189, F200, M201) starved to death about 20 to 23 days later. F136 was about 65 months old at death. We recorded two natural deaths of adult female pumas, exact causes unknown. Adult F140 died on November 4, 2013. F140 was found laying in a space under a boulder over-hang, completely intact, no visible injuries, but dehydrated and emaciated. Enlarged nipples, red-stained hair around the nipples, and uterine scars indicated that F140 probably had recently given birth to cubs. GPS location data on F140 indicated the probable birth date of the cubs was June 25, 2013. Fate of the cubs was unknown. F140 was 39 months old at death. Adult F171 died on June 1, 2014 according to GPS data. Her death orphaned 3 cubs (M206, F207, F208) when they were 10 months old. We have information on 45 subadult pumas (i.e., independent pumas <24 months old), including 19 females and 26 males (Table 16). We lost radio contact with 4 male and 2 female that probably dispersed from the study area unknown distances. The fate subadult M198 is currently unknown. His 18 �radiocollar was detected on mortality mode on July 30, 2014; but, we could not investigate the fate of M198 because the collar was in dangerous cliffs. Of the remaining 38 subadults (females and males combined), 8 (3 females, 5 males) died before reaching adult stage, indicating a rough preliminary binomial survival rate of 0.79 (i.e., 30/38) for subadults surviving to the adult age stage (i.e., 24 mo. old). Of the eight subadults that died, four deaths were from natural causes (1 trampled by elk, 2 killed by other pumas, 1 broken leg), three were from sport-hunting, and one was from a vehicle strike (Table 16). Harvest data along with our capture and radiotelemetry data provided dispersal and fate information on 41 marked pumas, 30 males and 11 females. Of those, 30 (5 females, 25 males) were initially captured and marked as cubs, and 11 (5 females, 6 males) were captured and marked in the subadult life-stage on the Uncompahgre Plateau puma study area (Table 17). Twenty-three males were killed by hunters away from the study area at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). Two males were killed by a hunter on the study area 12.9 and 21.9 km from their original capture sites. Four females were killed by puma hunters off the study area ranging from 20.7 to 74.5 km from initial capture sites. One female was killed by a hunter on the study area 18.2 km from her initial capture site. Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she established an adult home range there before she was killed by a puma hunter in that area on Jan. 9, 2012. Three males (M67, M87, M92) that were marked initially as cubs born on the east slope of the study area, dispersed from their natal ranges and were recaptured as adults on the west slope of the study area. All three of the males were killed by hunters on their adult territories. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53. [The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629).] The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY5 we monitored the fates of 21 radio-collared cubs (Table 11, Appendix A). We lost contact with 7 (F184, F187, F188, F203, F204, F208, M221) after radiocollars apparently quit operating and one collar was shed prematurely. However, one of those, F184, was later recaptured as a subadult. Of the remaining 14 collared cubs, 6 died. Three siblings (F189, F200, M201) died of starvation at 93 to 96 days old after their mother F136 was killed for depredation control purposes (i.e., she killed a goat). One cub (F202) died from predation or infanticide at about 59 days old. One cub (M205) died of an unknown natural cause when about 190 days old. One cub, F207, died an unknown natural cause when about 330 days old and about 24 days after her mother F171 died of an unknown natural cause. F207 had numerous porcupine quills stuck in her face, mouth, left shoulder, and both hind feet. F207 also had suffered a broken left humerus earlier in life, which had mended. Of the 8 remaining live radio-collared cubs 3 survived to the subadult stage, including one, M206, that was orphaned at 10 months old (sibling of F207). Five dependent cubs were being monitored as of July 31, 2014. Two non-marked cubs also died. Nursling P1076 was found dead and mostly consumed due to infanticide or predation in the nursery of F181. PF1094 was killed by our hunting dogs during a capture effort. Forty-eight adult pumas (35 females, 13 males) have worn GPS collars since this project began in 2004 (Table 19). Over 70 thousand GPS locations have been obtained and will be used for studies on puma behavior, social organization, population dynamics, population genetics, movements, population 19 �survey methods, habitat use and puma-human relations in collaboration with colleagues in Mammals Research, Colorado State University, and Arizona State University. Segment Objective 6 We continued to explore non-invasive methods for sampling pumas to estimate abundance. We began a pilot project in June 2014 to evaluate modified foot-hold devices and break-away neck snares as passive devices to snag hair from passing pumas. Hair obtained from the pumas will be tested to determine the quality of the DNA for genotyping individuals for mark-recapture methods for estimating abundance. This effort will continue into early November 2014. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 9.7 years of effort 224 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 47 adult females, 31 adult males, 19 subadult females, 26 subadult males, 62 female cubs, 90 male cubs, and 2 cubs of undetermined sex (some individuals occur in more than one age stage). Data from marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools for CPW wildlife biologists and managers to assess puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now almost 5 years of the treatment period are complete. The data support some CPW puma management assumptions, such as expected population structure and density ranges, and sport-hunting can cause population decline. Other assumptions are being challenged, such as 15% harvest rate with 35 to 45% females in the harvest can result in population stability or growth (15% harvest with 25-40% females caused population decline), male pumas are more detectable by hunters (females were more detectable), and puma harvest composition is not influenced by hunter selection (hunter selection strongly influenced harvest composition). Another underlying assumption of the GMU structure is that pumas assumed to occupy a GMU are only subject to harvest within that GMU. The data indicated that assumption to be unreliable. Pumas moved among adjacent GMUs and were at risk to harvest after the study area GMU was closed (i.e., the quota was filled) even though the study area GMU is among the largest in the state. The additional mortality that occurred contributed to population decline. Since the beginning of this study 2 previous efforts have been made to develop and test non-invasive methods for estimating puma abundance. These efforts were in collaboration with Colorado State University in a Ph.D. program (Jesse Lewis) and a M.S. program (Kirstie Yeager). A third pilot effort was begun in June 2014 and will go to November 2014. Monitoring of the radio-collared pumas will continue through December 2014 to gather data on puma reproduction, survival and causes of mortality. In January 2015, the principal investigator will start an intensive, thorough data analysis, modeling, and writing phase. Furthermore, we will continue collaboration with colleagues on investigations of puma population parameter estimation, population genetics, puma movements, puma habitat modeling and mapping, puma-human relations, and disease prevalence. All of these efforts should enhance the Colorado puma research and management programs. LITERATURE CITED Anderson, A. E, D. C. Bowden, and D. 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Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2008. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. _____. 2009. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. _____. 2010. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. _____. 2011. 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Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. 21 �Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Rausch, R. L., C. Maser, and E. P. Hoberg. 1983. Gastrointestinal helminths of the cougar, Felis concolor L. in northeastern Oregon. Journal of Wildlife Diseases 19: 14-19. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 22 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Year RY4 RY5 TY1 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 Independent Pumas Cub 20 33 42 Total 33 45 53 Lambda 1.37 1.17 Table 2. Pumas harvested by sport-hunters in Treatment Year 5 (TY5) on the Uncompahgre Plateau Study Area, Colorado, November 18, 2013 to January 10, 2014 (54 days). Puma sex Age (yr.) Date of kill Location/UTM NAD27 Zone, Easting, Northing Hunter/status 1.5 Previous M/F I.D. or specimen P no. if not marked PM1080 M 11/29/2013 13S, 239533, 4249632 M M 3.5 2.5 PM1089 M180 12/14/2013 12/16/2013 12S, 755418, 425910 12S, 737774, 4271802 F M 6.5 5.4 F111 M92 12/21/2013 1/10/2014 12S, 750802, 4261687 12S, 736233, 4238645 Brandon Owens/ Resident Shamus Howe/Resident John Watson/Nonresident Jacob Owens/Resident Gary Heubel/Nonresident Table 3. One other independent VHF-collared puma in the minimum count November 2013 to April 2014 (TY5) for the Uncompahgre Plateau Study Area that also died during November to April 2013-2014 period coinciding with the Colorado puma hunting season. Puma sex (M or F) F140 Age (yr.) 3.25 Date of kill/death 11/3-5/2013 Place of kill/UTM NAD27 Zone, Easting, Northing Study Area, San Miguel River Canyon 12S, 719342, 4236621 23 Hunter/status/other cause Unknown natural cause �Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1), November 2010 to April 2011 (TY2), November 2011 to April 2012 (TY3), November 2012 to April 2013 (TY4), and November 2013 to April 2014 (TY5), Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 TY3 TY4 TY5 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 2 West slope 14 5 3 5 1 2 subtotals 27 9 4 8 5 4 Total Independent Pumas = 48, including 31 females, 17 males. Cubs = 19 East slope 15 4 3 2 4 4 West slope 10 5 3 0 2 5 subtotals 25 9 6 2 6 9 Total Independent Pumas = 42, including 31 females, 11 males. Cubs = 24 East slope 10 6 3 6 6-7 2 West slope 13 4 1 1 1 3 subtotals 23 10 4 7 7-8 5 Total Independent Pumas = 44, including 27 females, 17 males. Cubs = 25-28 Unknown sex 4-8* 5-6 9-14 7 9 16 4 6 10 3 6 9 2 11-13 13-15 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. Table 5. Pumas captured and released by sport-hunters in Treatment Year 5 (TY5) on the Uncompahgre Plateau Study Area, Colorado, November 18, 2013 to January 10, 2014. Data are from puma hunter responses in 44 original voluntary surveys on printed permits. Total response rate from 65 individual permitted hunters was 68% (44/65 = 0.68*100). Puma sex/age stage/mark M/subadult/ no tags 2 M/cubs/no tags M/subadult/no tags M/adult/no tags Date of capture 11/26/2013 11/28 or 12/13/2013 12/7,8,14,15/2013 12/7,8,14,15/2013 Capture location Sim’s Mesa San Miguel River Sim’s Mesa Sim’s Mesa Hunter name Chad Black John Martinez & Gerald Sickels, Jr. Jeremy Wheeler Jeremy Wheeler 24 Reason for releasing the puma given by hunter None given. Cubs. Too small to harvest. Too small to harvest. �Table 6. Summary of puma capture efforts with dogs from January 9, 2014 to April 24, 2014, Uncompahgre Plateau, Colorado. Month No. Search Days 16 No. & type of puma No. & type of No. & I.D. or type of pumas captured, tracks founda,b pumas pursued observed, or identified January 95 tracks: 14 male, 19 pursuits: 4 male, 7 pumas captured 7 times: F95, F118, F171, 51 female, 19 cub, 10 female, 5 cub M211, F212, M220, M221 (cub of F197). In 11 undetermined addition, adult females F137, F171, F176, F181, independent pumas F197, subadult male M220, and cubs F203, F204 Tracks ≤1 day old: and M206 were associated with tracks by VHF 4 male, 14 female, telemetry. 7 cub, 1 undetermined independent puma February 23 144 tracks: 27 male, 41 pursuits: 7 male, 12 pumas captured 16 times: F8, F28, F176, 71 female, 38 cub, 19 female, 13 cub, F184 (2 times), M213 (3 times), F214, F222, 8 undetermined 2 undetermined M223 (cub of F28), F224, PM1095 (2 times; bioindependent puma independent puma darted; not handled due to dangerous trees), Tracks ≤1 day old: PF1094 (cub of F176; killed by dogs). In 9 male, 26 female, addition, adult females F95, F118, and cub M223 16 cub, 2 (2 times) were associated with tracks by VHF undetermined telemetry, and adult M211 and subadult M220 independent puma were identified with tracks at trail cameras. March 19 78 tracks: 23 male, 16 pursuits: 2 male, 4 pumas captured 4 times: M215, M223 (cub of 29 female, 24 cub, 7 female, 7 cub F28), M225 (cub of unidentified female), M226. 2 undetermined In addition, adult female F176 and adult male independent puma M196 were associated with tracks by VHF Tracks ≤1 day old: telemetry. 3 male, 8 female, 8 cub April 17 44 tracks: 10 male, 6 pursuits: 3 pumas captured 3 times: F96, F186 and F188 24 female, 10 cub 3 female, 3 cub (cub of F96). In addition, adult F118 and adult Tracks ≤1 day old: M196 (2 times) were associated with tracks by 2 male, 4 female, VHF telemetry, and adult M190 was identified at 3 cub a trail camera. 75 361 tracks: 82 pursuits: 24 individual pumas were captured 29 times with TOTALS 74 male, 13 male, aid of dogs. In addition, 13 radio-collared pumas 175 female, 39 female, were detected 18 times by tracks and identified 91 cub, 28 cub with VHF telemetry ≤1 km from the tracks and 3 21 undetermined 2 undetermined marked pumas were identified at trail cameras. Tracks ≤1 day old: 10 independent pumas (adults, subadults) were 18 male captured with dogs for the first time (refer to 52 female Tables 7 and 8). 34 cub 5 undetermined a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; 50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Each capture season project researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day to gather data on vulnerability to detection using methods similar to puma hunters (i.e., using roads, twotracks, ATV trails, searching canyon rims on snow). For 2013-2014 (TY5) the count was: 37 tracks of females, including 10 of those associated with cubs; 11 tracks of males; 1 track of a lone cub; and 3 tracks of undetermined sex. 25 �Table 7. Adult and subadult pumas captured for the first time, marked, collared (with canvass breakaways), and released from November 2013 to March 2014, Uncompahgre Plateau, Colorado. Puma I.D. F210 M211 F212 M213 F214 M215 M220 F222 F224 M226 Sex F M F M F M M F F M Estimated Age (mo.) 16 45 35 17 17 19 20 69 20 20 Mass (kg) 38 65 53 45 32 61 57 46 40 68 est.* Capture date 11/14/2013 1/3/2014 1/23/2014 2/5/2014 2/20/2014 3/8/2014 1/16/2014 2/1/2014 2/12/2014 3/8/2014 Capture method Cage trap Cage trap Dogs Dogs Dogs Dogs Dogs Dogs Dogs Dogs *Mass was estimated. Scales not available. Location Loghill Mesa Loghill Mesa Roubideau Canyon Cushman Creek Loghill Mesa McKenzie Mesa San Miguel Canyon Big Bucktail Canyon San Miguel Canyon Uncompahgre River Canyon Table 8. Pumas that were captured and observed with aid of dogs, biopsy-darted and given specimen numbers (e.g., PM1067, M for male, F for female), but were not handled at that time for safety reasons, February 2014, Uncompahgre Plateau, Colorado. Puma sex & I.D. PF1093 Age stage or months Adult Capture date 2/1/2014 PM1095 Adult 2/11/2014 Location Comments Monitor Creek of Roubideau Creek Spring Creek Notch in apex of left pinna. Estimated mass 41kg. Probable abdominal hernia. Recaptured 2/12/214 and could not be handled due to dangerous tree. 26 �Table 9. Pumas recaptured January 2014 to March 2014, Uncompahgre Plateau, Colorado. Puma I.D. F171 Recapture Date 1/14/2014 Mass (kg) 41 Estimated Age (mo.) 54 Capture Method/ Location Dogs/Dolores Canyon F95 1/24/2014 43 77 Dogs/Shavano Valley F118 1/24/2014 44 69 M211 F176 1/29/2014 2/4/2014 Observed Observed 45 43 2/5/2014 Observed 17 Dogs/San Miguel Canyon Dogs/Loghill Mesa Dogs/Horsefly Canyon (West) Dogs/Cushman Creek 2/8/2014 Observed 17 Dogs/Dry Creek Basin F28 2/8/2014 2/28/2014 2/11/2014 Observed Observed Observed 17 18 132 Dogs/Dry Creek Basin Dogs/Piney Creek Dogs/Tomcat Creek PM1095 2/12/2014 Observed Adult Dogs/Spring Creek F8 2/20/2014 44 129 M220 2/27/2014 Observed 21 M223 3/13/2014 Observed 9 M196 3/27/2014 71 58 Dogs/Big Bucktail Creek Dogs-Photo/Big Bucktail Creek Dogs/San Miguel Canyon Cage trap/Clay Creek F96 4/3/2014 45 99 Dogs/Dolores Canyon F188 4/3/2014 Observed 11 Dogs/Dolores Canyon F186 4/11/2014 Observed 42 Dogs/McKenzie Canyon (West) F184 M213 27 Process Replaced GPS collar and inserted canvass break-away. Inserted canvass break-away on GPS collar. Replaced VHF collar and inserted canvass break-away. None. F176 climbed dangerous tree; not handled. F118 climbed dangerous tree; not handled. Could not change nonfunctional expandable cub collar. F118 climbed dangerous tree; not handled. Could not change nonfunctional expandable cub collar. None. None. F28 climbed dangerous tree: not handled to replace her non-functional GPS collar. PM1095 climbed dangerous tree; not handled. Non-functional VHF collar replaced and canvass break-away inserted. Trail camera identified the male puma we pursued as M220. None. Replaced VHF collar and inserted canvass break-away. Replaced non-functional GPS collar and inserted canvass break-away. F188 climbed a dangerous tree; not handled. Cub of F96. Tracks of sibling F187 also in association with F96 and F188, but was not captured. F186 climbed a dangerous tree; not handled. �Table 10. Summary of puma capture efforts with cage traps from October 8, 2013 to July 21, 2014, Uncompahgre Plateau, Colorado.* Month October No. of Sites 4 Carnivore activity & capture effort results Unknown puma scavenged mule deer bait on east rim Dry Creek Basin site 11/2/2013. Nonmarked male puma passed by mule deer bait at southeast Loghill Mesa site 10/19-20/2013 (possibly M211, captured 1/3/2013). Bobcats and coyotes scavenged from some of the mule deer carcasses. November 7 Subadult puma F210 captured for first time in cage trap baited with mule deer at southeast Loghill Mesa site 11/14/2013. Non-marked male puma walked past mule deer bait at southeast Loghill Mesa site 11/14/2013 (possibly M211, captured 1/3/2013). Non-marked male puma scavenged mule deer bait at southeast Loghill Mesa site 11/16/2013; set cage trap and monitored it 11/16-17/2013; but, puma did not return (possibly M211, captured 1/3/2013). Bobcats, coyotes, and a bear scavenged from some of the mule deer carcasses. December 1 Bobcat scavenged the mule deer carcass. January 1 Adult male puma M211 captured for the first time in cage trap baited with mule deer at southeast Loghill Mesa site 1/3/2014. F210 scavenged mule deer bait at southeast Loghill Mesa site 1/13/2014. Non-collared female puma scavenged mule deer bait at southeast Loghill Mesa site 1/13-14/2014 (probably F214 captured with dogs on southeast Loghill Mesa 2/20/2014). February 1 No puma visits. March 11 Adult male puma M196 recaptured in cage trap baited with mule deer at north rim Clay Creek site 3/27/2014. A subadult male puma was photographed scavenging on a mule deer carcass on McKenzie Mesa on 3/9/2014. An unknown male puma walked about 10 m from a mule deer bait at the Monitor Mesa Rim site on 3/11/2014. April 8 Subadult female F214 fed on mule deer bait and was photographed at east rim McKenzie Mesa site on 4/19 and 21/2014; no capture effort needed. Adult male M196 associated with a nonmarked female puma at an elk carcass on Iron Springs Mesa. A subadult male puma was photographed scavenging on a mule deer carcass on McKenzie Mesa on 4/4/2014. Black bears scavenged on elk bait. July 1 No puma or other carnivore visits. * We used 50 road-killed mule deer and 1 road-killed elk (at 2 sites) at 24 different sites. Of the road-killed baits, 11 of 51 (21.6%) were scavenged by pumas. Table 11. Puma cubs sampled August 2013 to July 2014 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) F203 F204 M205 M206 F207 F208 F209b M216 M217 M221 M223 M225 F F M M F F F M M M M M 7/12/2013 7/12/2013 7/12/2013 7/31/2013 7/31/2013 7/31/2013 7/31/2013 6/12/2014 6/12/2014 8/2013 6/2013 9/2013 35 35 35 28 28 28 28 25 25 167 244 183 1.95 2.2 2.5 1.8 1.7 1.7 1.5 1.9 1.75 11.0 32 12 Mother Estimated age of mother at birth of this litter (mo) F137 54 F171 45 F210c F197 F28 Not captured 23 24 123 Adult Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Cub F209 was tattooed and ear-tagged, but was not radio-collared. c A third cub was in F210’s litter, sibling of M216 and M217, but it could not be handled (crawled into a hole). 28 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2014, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Track detection effort 109/78 = 1.40 tracks/day Pursuit effort 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 217/77 to 218/77 = 2.82-2.83 tracks/day 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day Dec. 27, 2011 to April 12, 2012 268/79 = 3.39 tracks/day Jan. 1, 2013 to April 18, 2013 229/74 = 3.09 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 81/15 = 5.40 day/capture 89/79 = 1.13 pursuit/day 26/79 = 0.28 capture/day 11 pumas captured for first time 11/79 = 0.14 capture/day 79/89 = 0.89 day/pursuit 79/26 = 3.04 day/capture 79/11 = 7.18 day/capture 82/74 = 1.11 pursuit/day 42/74 = 0.57 capture/day 12 pumas captured for the first time 12/74 = 0.16 capture/day 74/82 = 0.90 day/pursuit 74/42 = 1.76 day/capture 74/12 = 6.17 day/capture 29 15 pumas captured for first time 15/81 = 0.18 capture/day �Table 12. continued. Period Track detection effort Pursuit effort Puma capture effort Effort to capture an independent puma for the first time Jan. 9, 2014 To April 31, 2014 361/75 = 4.81 tracks/day 82/75 = 1.09 pursuit/day 29/75 = 0.39 capture/day 10 pumas captured for the first time 10/75 = 0.13 capture/day 75/82 = 0.91 day/pursuit 75/29 = 2.59 day/capture 75/10 = 7.50 day/capture 30 �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2014. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) F2 F2 F2 F3 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F8 F16 F16 F16 F23* F23 53 67 89 36 50 62 84 107 67 82 106 24 37 60 95 32 52 75 21 45 F23 80 F24 F24 75 114 F25 F25 F25 F25 74 94 110 129 F28* F28 F28 F28 F28 F30* F50 F54 F70* F70 F70 F72* F72 F72 36 48 68 112 123 48 21 24 38 52 76 28 51 64 F75 F75 F93 F93 F94* F94 F95 32 55 56 90 46 60 58 Dates pairs consortedb Estimated birth datec M73 49 02/28-29/08 M6 80 01/13-14/09 M27 or M29f M67 78 107 53 02/19-25/08 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 01/28-31/11 04/22/11 M29 92 04/12-15/07 06/14/07 09/10 M6 37 06/22-24/05 M51 M55 60 69 03/31/08 03/28-31/10 08/01/05 04/16/07 08/19/08 3/10 M29 88 12/27-29/06 M55 34 04/16-20/07 M51 60 03/10/08 M73 61 02/11/09 M55 70 04/15/10 31 06/09/06 03/30/07 11/08 07/12 06/13 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 08/18/11 07/09/08 06/12/10 07/15/11 08/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 06/17/13 Estimated birth interval (mo.) Estimated gestation (days) Observed number of cubsd 19.9 22.7 91-92 23.8 87-93 3 2 4 1 2 3 3 2 2 4 3 2 4 2 2 4 4 3 3 3 Nonfunct.GPS 84-86 2 90-93 4 3 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 Nonfunct.GPS 90-91 1 1 2 3 20.5 16.1 Nonfunct.GPS 11.7 92-93 88-92 14.8 23.6 87 23.1 13 23.2 93 13.3 91 2 ≥2 tracks 1 3m 2 3 1 1 3 3 3 1 2 3 photographed 1 2 2 2 3 3 Tracks/GPSn �Table 13 continued. Dates pairs Estimated consortedb birth datec Consort pairs and estimated agesa F96 F96 F96 F104 F111* F111 F116g F118 F118h F118 F119 F119i 55 78 88 110 32 58 36 27 50 64 66 96 expected F129* F135 F136j F136 F136 23.4 33 39 51 62 F137 F137 F140* 30 54 34 M55 Nonmarkedl 71 Unk. 05/21/10 03/19/13 08/21/10 07/27/12 05/14/13 07/08/10 06/16/10 08/25/12 2009 08/08/10 06/20/12 08/05/13 08/09 02/12 expected 08/03/13 07/06/11 07/10/11 07/05/12 06/18/13 07/08/11 07/12/13 06/25/13 Estimated birth interval (mo.) Estimated gestation (days) Observed number of cubsd 92 4 3 2 3 2 2k 2 3 3 1 2 1 plus 1-2 uterine scars GPS datap 2 ≥1 remains 2 3 23.2 9.6 26.3 22.4 13.5 29 expected 12 11 ≥1 3 GPS data, uterine scarsq F152* 25.7 08/08/12 2 F171 22 08/11 2 F171 45 07/31/13 4 F172 48 06/25/13 1 F176 35 06/13 3 F181* 28 08/05/13 ≥1o F197* 24 08/13/13 2 F210* 23 06/12/13 3 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on known history or nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. h Two cubs observed with F118 south of Norwood 9/24/2012. i F119 died of a ruptured uterus and internal bleeding on 1/28/12. Cub in uterus in third trimester; 1-2 uterine scars indicated expulsion of 1-2 fetuses. j Remains of F136’s cubs found 8/9/11. Cause of death predation by puma or black bear. k Tracks evidence of one other cub in association with F111 and cub F184, but not captured and marked; probably M213. l A non-marked adult male puma was photographed consorting with adult female pumas F136 and F182 at the same time on the NE rim of Loghill Mesa on 03/19-20/13. m F28 entire litter lost winter 2012-13; two were killed by a male puma (infanticide). n GPS data and tracks at a nursery site indicated that F95 had a litter of cubs on 6/17/13. The entire litter of cubs was apparently lost (died) by January 2014 (no evidence of cubs were found in association with F95 during winter capture efforts). 32 �o F181 had her first litter on 8/5/13 based on GPS data. When we investigated the nursery on 9/6/13, we found one cub that died of predation or infanticide. No evidence of additional cubs were found; but, they may have been completely consumed. P GPS data indicated F129 probably had her first litter of cubs on 08/03/ 13. But we could not investigate due to private land restrictions to access. F129 apparently lost the entire litter by 11/02/13. This data point is not used in Fig. 5. q We could not view F140’s cubs. But uterine scars present on F140 during necropsy and GPS location data indicated that F140 had give birth to cubs on 06/25/2013. Fate of the cubs was unknown. This data point not used in Fig. 5. 33 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2014, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 08-23-07 to 12-18-11 M71 01-29-08 to 11-12-09 M73 02-21-08 to 10-26-11 M87 02-09-11 to 12-06-11 M90 11-16-10 to 11-23-10 M92 04-22-11 to 01-10-14 M100 03-27-09 to 07-31-09 M114 02-27-10 to 03-10-12 M133 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Dead. M67 is offspring of F30. Dispersed natal area. Established territory on W side U.P. study area. Killed by a puma hunter in Tabaguache Creek 12-18-2011 at age 52.9 months. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Dead. Illegally killed 10-26-2011 in Bear Pen Gulch, upper East Fork Escalante Canyon; shot through abdomen during second rifle season. M73 was about 80 months old at death. Dead. M87 is offspring of F3. Dispersed from natal area. Established territory on W side of U.P. study area. Killed by a puma hunter in 47 Canyon, Tabaguache Canyon 12-06-2011. M87 was 41 months old at death. Dead. M90 was killed by a puma hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M92 was killed by a puma hunter on 01-10-14 on the study area in upper Cottonwood Creek, near Ute. He was 65 months old. M92 was the offspring of F25, born on 08-19-08 in Pleasant Valley Canyon. He dispersed to the west side of the study area and was recaptured there on 04-22-11 when 32 months old. M92 was recaptured 2 more times on the west slope of the study area on 02-27-13 and 03-12-13; but, we could not handle him to radio-collar him because he climbed dangerous tree. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Dispersed from U.P. study area after 06-23-10. Killed by a puma hunter in Beaver Creek, NE of Canyon City, GMU59, 03-10-12. M114 was about 55 months old at death. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. 34 �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 07-01-11 to 12-23-11 M144 09-01-11 to 02-25-13 M165 07-01-12 to 12-17-12 M178 11-13-12 to 12-11-12 M179 M180 11-18-12 to 12-29-12 07-01-13 to 12-16-13 M183 02-14-13 to 11-11-13 M190 M196 M211 M220 M226 F2 01-02-13 to 07-31-13 02-05-13 to 07-31-13 01-03-14 to 07-31-14 05-01-14 to 07-31-14 07-01-14 07-31-14 01-07-05 to 08-14-08 F3 01-21-05 to 12-11-11 F7 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-14 10-11-05 to 09-11-09 F23 02-05-06 to 06-06-12 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 08-08-14 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 01-14-08 to 12-22-11 Table 14. Continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Dead. Killed by a puma hunter in Horsefly Canyon (E) 12/23/11. M138 was about 29 months old at death. Dead. Initially captured as 18 mo. old subadult on W side U.P. study area 03-07-11. Dispersed from study area. Established adult territory on NW U.P. Killed by puma hunter 2-25-2013 in GMU 40, North Fork West Creek, Unaweep Canyon. Dead. Initially captured as 19 mo. old subadult on W side U.P. study area 02-24-12. Moved to Escalante Creek drainage by adult age 07-31-12. Killed by puma hunter 1217-2012 in GMU 62N, Dry Fork Escalante Canyon. Dead. Originally captured on the study area 11-13-12. Killed by puma hunter 12-1112 after tracking M178 off the study area and onto adjacent GMU 65. Dead. Killed by puma hunter on study area 12-29-12 at about 30 months old. Dead. Killed by a puma hunter on the study area in Monitor Creek on 12-16-13 at about 30 months old. Lost radio contact. Unknown status. GPS collar may have malfunctioned. Last live radio signal on the study area in Spring Creek on 11-11-13. Alive. Alive. Alive. Alive. M220 originally captured as a subadult male about 20 months old on 01-16-14. Alive. M226 originally captured as a subadult male about 20 months old on 03-08-14. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Dead. Killed by a puma hunter in Lindsay Creek 12-11-11. F3 was about 120 months old at death. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Dead. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. F23 may have attempted to defend 2 cubs (F149, M161; 13.5 months old) and/or calf elk kill. Dead. Killed by a male puma in Logging Camp Draw about 09-16-11. F24 was about 126 months old at death. F24 may have attempted to defend ≥2 cubs (F147, nonmarked siblings; 12 mo. old). Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Alive as of 08-08-14. Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area on 02-11-14, but could not be handled to replace non-functional GPS collar and on 08-08-14 photographed on trail camera (P. Joseph, Nucla). Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Dead. Killed by a puma hunter Spring Creek 12-22-11. F70 was 80 months old at death. Her death orphaned 2 cubs, F157 and F158, at 4 months old; both starved to death about 01-15-12 at about 5 months old. 35 �Puma I.D. F72 Monitoring span 02-12-08 to 12-21-11 F74 01-15-13 to 5-16-13 F75 03-26-08 to 12-13-11 F93 F94 12-05-08 to 11-11-12 12-19-08 to 02-01-11 F95 F96 F104 08-01-09 to 07-31-14 01-28-09 to 07-31-14 05-21-09 to 01-31-12 F110 09-21-09 to 02-25-10 F111 01-01-10 to 12-21-13 F113 01-26-10 to 06-06-10 F116 01-20-10 to 09-20-11 F118 F119 02-25-10 to 07-31-13 03-25-10 to 01-28-12 F135 01-01-11 to 09-20-11 F136 01-20-11 to 09-30-13 F137 F140 01-21-11 to 01-09-14 08-01-12 to 11-04-13 F143 F152 F163 F171 02-15-11 to 07-31-14 06-16-12 to 12-23-12 07-01-12 to 07-31-14 01-20-12 to 06-01-14 F172 03-28-12 to 02-08-14 F176 F177 F181 F182 10-17-12 to 07-31-14 10-27-12 to 12-10-12 04-01-13 to 07-31-14 02-04-13 to 08-25-13 F186 F194 F197 03-30-13 to 07-31-14 01-29-13 to 06-17-13 08-01-13 to 07-31-14 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Photographed on Miller Mesa S of U.P. study area on 12-18 to 21-11 with 3 new cubs born about July 2012. Lost radio contact after 5-16-13; radiocollar fell off after canvas breakaway tab broke; detected 6-10-13. Dead. Killed by a puma hunter in North Fork Cottonwood Creek 12-13-11. F75 was about 98 months old at death. Dead. Killed by another puma 11-11-12. Fatal bite wounds to the skull. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Dead. Died probably of starvation associated with senescence in lower Roubideau Creek 01-31-12. F104 was about 132 months old at death. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Dead. Killed by a puma hunter on12-21-13 on the study area in Cushman Creek. F111 was about 74 months old at death. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Dead. Died about 09-20-11 of unknown natural cause associated with pregnancy and birth of new litter of cubs. F116 was about 60 months old at death. Alive. Dead. Died of ruptured uterus and internal bleeding associated with pregnancy in Clay Creek Canyon 01-28-12. F119 was about 95 months old at death. Dead. Died of unknown natural cause in E Fork Dry Creek 09-20-11. Her death orphaned cubs M154 and M155 at 76 days old; both died of starvation or disease when 77 (M154) and 81 (M155) days old. Dead. F136 was killed by A.P.H.I.S., Wildlife Services Agent for depredation control. She killed one goat. F136 was about 65 months old at death. Lost radio contact. Unknown status. GPS collar malfunctioned after 01-09-13. Dead. F140 died on an unknown natural cause on the study area in lower San Miguel Canyon. She was 39 months old known age. Alive. Dead. Killed by puma hunter on study area, Spring Creek Canyon. Alive. Dead. F171 died probably of an unknown natural cause on 06-01-14. She was about 56 months old at death. Dead. Killed by a puma hunter on 02-08-14 off the study area on Dry Fork Escalante Creek. She was about 56 months old at death. Alive. Dead. Killed by puma hunter 12-10-12 in GMU 65 adjacent to study area. Alive. Dead. Killed by a vehicle on highway 550 on 08-25-13. She was about 48 months old at death. F182 was pregnant with 2 fetuses; projected birth September 2013. Alive. Dispersed, exhibited subadult behavior. Fate unknown. Censor. Alive. F197 was originally captured on the study area as a subadult about 18 months old on 02-14-03. 36 �Puma I.D. F199 Monitoring span 06-01-14 to 07-31-14 F210 03-01-14 to 07-31-14 F212 F222 F224 01-23-04 to 07-31-14 02-01-14 to 07-31-14 06-1-14 to 07-31-14 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Alive. F199 was originally captured on the study area as a cub (born June 2012) of PF1074, and is sibling of M198. F199 separated from M198 by July 29, 2013 when 13 months old, and dispersed from her natal area by August 14, 2013 when 14 months old. She established a home range in upper Dallas Creek-to-Miller Mesa area. Alive. F210 was originally captured on the study area as a subadult about 16 months old. She was impregnated in March 2014 at 20 months old and had her first litter on 06-12-14 at 23 months old. Alive. Alive. Alive. F224 was originally captured as a subadult about 20 months old on 02-12-14. 37 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 5 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year a Reference Annual 2 8/1/2005 to 7/31/2006 Reference Annual 3 8/1/2006 to 7/31/2007 Reference Annual 4 8/1/2007 to 7/31/2008 Reference Annual 5 8/1/2008 to 7/31/2009 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annual 1b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males Treatment Annual 2 8/1/2010 to 7/31/2011 Treatment Annual 3 8/1/2011 to 7/31/2012 Treatment Annual 4 8/1/2012 to 7/31/2013 Treatment Annual 5 8/1/2013 to 7/31/2014 S 1.000 Females SE 0.0000 n 10 S 0.667a Males SE 0.2222a n 6a 0.909 0.0867 11 1.000 0.0000 5 0.831 0.0986 14 1.000 0.0000 7 0.875 0.1031 13 1.000 0.0000 8 0.784 0.1011 19 0.667 0.1924 8 NA (see rates above) NA NA 0.333b 0.1361b 12b 0.947c 0.0568 19 0.250 0.1082 9 0.548d 0.1063 20 0.167 0.1076 7d 0.819 0.0931 19e 0.188 0.0845 8e 0.678 0.0934 22f 0.667 0.1721 7 Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had nonfunctional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a non-functional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. d Sample included F143, F163, M144, ranged on NW Uncompahgre Plateau N of the study area but not on the U.P. study area, vulnerable to annual hunting. e Sample includes F143, F163, M144, M165 that ranged on north half of the Uncompahgre Plateau north of the study area (not on the study area) and were at risk to annual sport-hunting mortality. f Sample includes F143, F163, F172 that ranged on north half of the Uncompahgre Plateau north of the study area (not on the study area) and were at risk to annual sport-hunting mortality. 38 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2014, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 31 M31 04-19-06 to 04-26-06 7 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M69 01-11-08 to 04-07-08 190 87 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Survived to adult stage. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. Died in subadult stage. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. Mother F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 39 �Puma I.D. F95 Monitoring span 12-29-08 to 07-31-12 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M120 12-06-11 1 M122 08-12-10 to 04-18-11 250 M131 09-25-10 to 04-18-11 206 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 155 F140 01-13-12 to 07- 31-12 200 M141 12-23-11 1 M144 03-07-11 to 09-08-11 185 Table 16 continued Status Survived to adult stage. Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Died in subadult stage. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. Survived to adult stage. M112 was offspring of F70 born August 2009. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-18-11. Lost contact of M112 after 04-1811. Dispersed. M112 was killed by a puma hunter 01-06-2013, GMU 73, SE of Dolores, CO; UTM: 12S, 732863E, 4146772N; age 41 months. Died in subadult stage. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. Died in subadult stage. M120 was offspring of F3. M120 was killed by a puma hunter 12-06-11 in his natal area in Spring Creek. He was 17 months old at death. Survived to adult stage. M122 was offspring of F104, born 07-08-10. Lost contact after 04-18-11 when radio-collar malfunctioned. Dispersed. Killed by puma hunter in GMU 62, Tatum Draw, Dry Fork Escalante Creek, N of natal area 01-23-13; UTM: 12S, 735353E, 4283455N; age 30 months. Survived to adult stage. M131 was offspring of F96, born 08-21-10. Lost contact after 04-18-11 when collar malfunctioned. Dispersed. Killed by puma hunter in GMU 60, Lion Creek, extreme W CO 01-1713; UTM: 12S, 670829E, 4246980N; age 29 months old. Survived to adult stage (barely). M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Survived to adult stage. Entered adult life stage 07-01-11. Killed by a puma hunter 12-23-11 in Horsefly Canyon. M138 was about 29 months old at death. Survived to adult stage. Turned adult in Aug. 2012. Probably offspring of F28. Has established a home range adjacent to natal area where she was initially captured at 5 months old on 01-02-11. Died in subadult stage. M141 was killed by a puma hunter on 12-23-11 in Little Bucktail Creek. He was 16 months old at death. Survived to adult stage. Emigrated from U.P. study area. Established adult territory on northwest Uncompahgre Plateau. M144 is sibling of F145 below. Killed by puma hunter 2/25/2013 at ~41 mo. old. 40 �Puma I.D. F145 Monitoring span 03-08-11 to 09-08-11 No. days 184 F146 03-08-11 to 03-23-11 15 F147 09-16-11 to 04-12-12 209 F149 06-06-11 to 12-31-12 575 M150 03-28-11 to 04-11-11 14 F152 05-04-12 to 06-16-12 44 M153 04-12-11 to 09-06-11 147 M161 06-06-12 to 08-03-12 59 F163 01-26-12 to 07-01-12 157 M164 02-14-12 to 02-26-12 02-24-12 to 12-17-12 12 M165 M180 01-01-13 to 07-01-13 298 182 Table 16 continued Status Survived to adult stage. Emigrated from U.P. study area and to Colorado Mesa. Killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. Died in subadult stage. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Lost contact; radiocollar quit after 04-12-12. F147 orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-1611. Died in subadult stage. F149 was offspring of F23, born 04-22-11. F149 (sibling of M161 below) was orphaned at 13.5 months old when her mother F23 was killed by a male puma. F149 dispersed from the natal area by 07-16-12 to E side U.P. study area when she was 14.8 months old; onto Bostwick Park, then W to Dry Creek. Killed by a puma hunter 12-31-12 in GMU 70W, Dry Creek; UTM: 12S, 713658E, 4229703N; age 20 months. Lost contact; probably dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Survived to adult stage. F152 was independent from her mother F93 by 05-04-12 when about 23 months old. She ranged as a subadult and adult on the natal area (07-31-12). Survived to adult stage. Associated with F137 when 23 months old on 09-07-2011. Killed by Wildlife Services agent for depredation on an alpaca in Dallas Creek on 09-13-11. M153 was 23 months old at death. Died in subadult stage. M161 (sibling of F149 above) was orphaned at 13.5 months old when his mother F23 was killed by a male puma. M161 dispersed from the natal area by 06-29-12 to E side U.P. study area when he was 14 months old. He shed his expandable cub collar about 08-03-12. M161 was struck and killed by a vehicle on Dallas Divide, HWY 62 in October 2012 when he was 18 months old. Survived to adult stage. F163 was captured at about 18 months old on the study area. She emigrated from the study area and established an adult home range on the NW Uncompahgre Plateau as of July 2012 (0716-12 location). Lost contact after 02-26-12. M164 may have dispersed a long distance. Fate unknown. Survived to adult stage. M165 moved from W to E side of the study area. Appeared to establish adult home range on NE Uncompahgre Plateau. Killed by a puma hunter 12-17-12 in GMU 62N, Dry Fork Escalante Creek; UTM: 12S, 730184E, 4272500N; age about 29 months, adult stage. Survived to adult stage. M180 moved to NE Uncompahgre Plateau, ranging N of the study area. Turned to adult age (24 mo.) July 2013. Killed by a puma hunter on the study area 12-16-13 when 29 mo. old adult. 41 �Puma I.D. F181 Monitoring span 01-15-13 to 04-01-13 ~12-21-13, 02-05-14, 02-08-14 07-09-14 No. days 168 F194 01-29-13 to 6-17-13 140 F197 02-13-13 to 08-01-13 07-29-13 to 06-01-2014 171 F199 07-29-13 to 06-01-2014 308 F210 11-14-13 to 03-12-14 02-05-14 to 07-31-14 122 02-20-14 to 07-31-14 03-08-14 to 03-13-14 01-16-14 to 05-15-14 162 F184 M198 M213 F214 M215 M220 308 177 5 120 Table 16 continued Status Survived to adult stage. F181 moved from E to W side of study area. Turned to adult age (24 mo.) April 2013. Had first litter 08-05-13 at 28 mo. old. Lost contact. F184, offspring of F111, born 08-25-12. Probably was orphaned and became independent subadult when mother F111 was killed by a puma hunter on 12-21-13. Previous radio signal with F111 was on 10-10-13, before F184’s collar malfunctioned. F184 recaptured with subadult M213 (probably sibling) on 02-05-14 and 02-08-14. F184 probably photographed by trail camera on Horsefly Creek on 07-09-14 (dispersed from natal area). Survived to adult stage. F194 dispersed S to North Mt., head of Naturita Creek by 06-17-13. Estimated age 30 months in June 2013. Located again 03-31-14 on Hamilton Mesa, head of Hamilton Creek. Probably established adult home range there. Survived to adult stage. F197 ranges on W side of the study area. Turned to adult age (24 mo.) August 2013. Had her first litter 08-13-13 when 24 mo. old. Fate unknown. M198 was originally captured on the study area as a cub on 04-18-2013 (born June 2012) of PF1074, and is sibling of F199. M198 separated from F199 by 07-29-13 when 13 months old, and dispersed from his natal area and the study area by 10-23-13 when 15 months old. His radio-collar was located on mortality mode on 07-30-14 in Bear Creek San Miguel River above Sawpit. Field investigation indicated that the collar is in very steep cliffs and site could not be examined due to danger. M198 was 25 months old. Survived to adult stage. Alive. F199 was originally captured on the study area as a cub on 04-18-2013 (born June 2012) of PF1074, and is sibling of M198. F199 separated from M198 by 07-29-13 when 13 months old, and dispersed from her natal area by 08-14-13 when 14 months old. She established a home range in upper Dallas Creek-toMiller Mesa area. Survived to adult stage. F210 was first captured at about 16 mo. old on 11-14-13. Turned adult age by 20 mo. old, when she was impregnated. F210 gave birth to her first litter on about 06-12-14. Lost contact. M213 was captured on 02-05-14 in the company of subadult female F184, offspring of F111 when F184 was 17.3 mo. old. M213 probably sibling of F111 (we previously captured one, F184, of 2 cubs in the litter). If so, M213 will reach adult age (24 mo.) on 08-2514, birthday of the F111’s litter. Dispersed north of suspected natal area by 05-27-14 at age 21 months. Lost contact after 06-09-14; probably dispersed. Alive. F214 was captured on 02-20-14 at about 17 mo. old. She will turn adult age (24 mo.) in September 2014. Lost contact. M215 was captured on 03-08-14 at about 19 mo. old. Last radio location was on 03-14-14. He apparently dispersed from the study area and surrounding area. Survived to adult stage. M220 was captured on 01-16-14 at about 20 mo. old. He turned adult age (24 mo.) by about 05-01-14 and is an adult male on the study area. 42 �Puma I.D. F224 Monitoring span 02-12-14 to 06-01-14 No. days 110 M226 03-08-14 to 07-01-14 116 Table 16 continued Status Survived to adult stage. F224 was captured on 02-12-14 at about 20 mo. old. She dispersed from the southwest of the study area by 03-31-14, and since has ranged south of the study area. F224 turned adult age (24 mo.) by about 06-01-14 and has an early adult home range from Mud Spring Draw to Naturita Creek. Survived to adult stage. M226 was captured 03-08-14 at about 20 mo. old. He turned adult age (24 mo.) by about 07-01-14. He has an adult home range on the study area. 43 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2014. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a puma hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 53.2 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 42.8 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29.5 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61N on 1227-09 when he was 38.9 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek GMU 61N in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 44 �Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a puma hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 41.5 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 27.8 months old. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 12S,726901E, 4243463N→ 13S,255316E, 4216768N 60.5 M83 07-05-08 90.7 M87 07-31-08 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N M88 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N 57.7 80.7 369.6 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a puma hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a puma hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 31.6 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is was resident adult on the west slope of the study area. He was killed by a puma hunter on 12-06-11 at 41 months old in GMU 61N north of the study area. M88 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a puma hunter in Dawson Creek, Disappointment Valley on 11-3010 when he was 29 months old. 45 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N M107 06-28-09 M112 01-23-10 13S,242359E, 4252618N→ 12S,754886E, 4341330N 13S,248567E, 4240108N→ 12S,732863E, 4146772N M114 02-27-10 M117 02-05-10 M126 09-05-10 M144 03-07-33 13S,256933E, 4237862N→ 13S,492615E, 4266192N 12S,731840E, 4232346N→ 12S,743909E, 4216633N 12S,734503E, 4224636N→ 12S, 710850E, 4239350N 12S,727173E, 4242012N→ 12S,696439E, 4276888N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 21.9 M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. He was recaptured twice more on 02-27-13 and 03-12-13 also on the SW side of the study area, but could not be collared because he climbed dangerous trees. M92 was killed by a puma hunter on 01-10-14 in upper Cottonwood Creek; he was 65 mo. old. M92 had established an adult territory on the SW side of the study area. 89.2 M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 102.5 M112 was initially captured 4.7 mo. old in his natal area while dependent on his mother F70 on 01-23-10. He was recaptured 0124-11 in the natal area at 17 months old, independent of F70. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-18-11 when he was 18-20 mo. old. Lost contact of M112 after 04-18-11. Dispersed and emigrated from the U.P. study area. M112 was killed by a puma hunter 01-06-2013, GMU 73, SE of Dolores, CO; UTM: 12S, 732863E, 4146772N; age 41 months. 237.5 M114 was initially captured at about 30 months old. Emigrated from the U.P. study area. He was killed by a puma hunter on 0310-12 in Beaver Creek, GMU59. He was about 55 months old at death. 19.7 M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. 27.7 M126 was offspring of F118, born Aug. 8, 2010. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. 46.6 M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area when ~18 months old. Mother is unknown. He moved off the study area on 03-15-11. M144 established his adult territory on northwest Uncompahgre Plateau and upper Unaweep Canyon from Sep. 2011 to 02-25-13. M144 was killed by a puma hunter 02-25-13 in GMU 40, North Fork West Creek, Unaweep Canyon. 46 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M161 01-23-12 12S,727932E, 4239430N→ 13S,247567E, 4220129N F52 01-10-07 13S,258058E, 4236260N→ 13S,319217E, 4240467N F97 02-04-09 12S,727529E, 4237648N→ 12S,705930E, 4227299N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N M122 08-12-2010 M131 09-25-10 12S,746164E, 4276613N→ 12S,735353E, 4283455N 12S,760695E, 4243505N→ 12S,670829E, 4246980N F143 02-15-11 12S,723748E, 4238579N→ 12S,721795, 4264246 Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 49.2 M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old and moved to the east slope of the U.P. study area. M161 shed his expandable cub collar about Aug. 3, 2012 in head of E Fk. Dry Creek. He was struck and killed by a vehicle on highway 62 at Dallas Divide in October 2012; he was 18 mo. old. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. 24.0 F97 was offspring of F23, born May 23, 2008. She was radiocollared at 8.5 month old in San Miguel Canyon; but, lost contact on 05-12-09 after F97 shed the radiocollar at an elk cache. F97 dispersed from the U.P. study area. She was killed by a puma hunter on 01-22-12 in Dry Creek west of the U.P. study area when she was 43.9 months old. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. 18.2 F108 was offspring of F94, born May 25, 2009; sibling of M107 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a puma hunter on the study area on 11-29-10 when she was 17 months old. 12.9 M122 was offspring of F104, born July 8, 2010. Fitted with expandable cub collar 08-12-10. Lost contact 04-28-11 due to transmitter malfunction. Killed by puma hunter N of natal area 01-23-13 at 30 mo. old. 90.1 M131 was offspring of F96, born August 21, 2010. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-02-12 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. Emigrated from U.P. study area. Killed by a puma hunter 01-17-13 at 29 mo. old in GMU 60 in western Colorado near border with Utah. 25.7 F143 was captured on the study area when about 24 months old. Dispersed N on the Uncompahgre Plateau and established an adult home range on the NW portion of the Uncompahgre Plateau, GMU61N. 47 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) F145 03-18-11 12S,727181E, 4241468N→ 12S,705833E, 4312909N F149 06-06-11 12S,729993E, 4242329N→ 12S,713658E, 4229703N F163 01-26-12 M165 02-24-12 12S,732153E, 4232452N→ 12S,695407E, 4280753N 12S,722816E, 4246926N→ 12S,730814E, 4272500N F194 01-29-13 12S,742443E, 4225259N→ 12S,729101E, 4201962N M198 04-10-13 12S,749316, 4222763N→ 13S,238781E, 4204762N F199 04-10-13 12S,749316, 4222763N→ 13S,252306E, 4214655N F224 02-12-14 12S,722381E 4237049N→ 12S,733636E, 4218890N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 74.5 F145 was originally captured in association of M144 and F146 when ~18 months old; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145 emigrated to Colorado Mesa. She was killed by a puma hunter 0123-12 in West Bangs Canyon. F145 was 28 months old at death. 20.7 F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old and moved to the NE Uncompahgre Plateau, onto Bostwick Park, then back across Uncompahgre Plateau. She emigrated from the U.P. study area and was killed by a puma hunter 12-31-12 at 20 mo. old 60.7 F163 was initially captured at about 18 months old. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (0716-12 most recent location). 26.9 M165 was first captured 02-24-12 at ~19 mo. old. His origin unknown. He moved from the west slope of the U.P. study area to the east slope of the U.P. north of the study area between 05-042012 and 06-15-12. He was killed by a puma hunter in GMU 62N on 12-17-12 when he was ~29 mo. old. 26.9 F194 was first captured at ~24 mo. old on W slope of U.P. study area on 01-29-13. Her origin unknown. She emigrated from the U.P. study area heading S. An aerial location on 06-17-13 located her on North Mt. in the SW head of Naturita Creek. Another aerial location on 03-31-14 located her on Hamilton Mesa. F194 apparently has an adult home range in that area. 24.5 Fate unknown. M198 was originally captured on the study area as a cub on 04-18-2013 (born June 2012) of PF1074, and is sibling of F199. M198 separated from F199 by July 29, 2013 when 13 months old, and dispersed from his natal area and the study area by 10-23-13 when 15 months old. His radio-collar was located on mortality mode on 07-31-14 in Bear Creek San Miguel River above Sawpit. Field investigation indicated that the collar is in very steep cliffs and site could not be examined due to danger. 30.4 F199 was originally captured on the study area as a cub on 04-182013 (born June 2012) of PF1074, and is sibling of M198. F199 separated from M198 by July 29, 2013 when 13 months old, and dispersed from her natal area by August 14, 2013 when 14 months old. She established a home range in upper Dallas Creek-to-Miller Mesa area. 21.2 F224 was first captured at ~20 mo. old on the W slope of the U.P. study area on 02-12-14. She emigrated from the study area heading S by 03-31-14 when she was located in Hamilton Creek, N of Hamilton Mesa. She has ranged in that area and Naturita Creek up to 07-14-14. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. 48 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2013. Puma sex & ID if marked M Estimated age (mo.) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 M P1018c F P1030c M P1034 M161 24 08-25-10 6 02-16-11 4 10-07-11 18 06-17-13 F182 48 08-25-13 a Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating Excellent Good Fair Unknown, decomposed Fair, pregnant with 2 fetuses Subadult marked (i.e., tattoos, eartags), but not radio-collared. Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. b 49 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N Highway 62 Leopard Creek 12S,762806E,4219531N Highway 62 Dallas Divide 13S,2475674220129 Highway 550 Cow Creek 13S,258958E,4236541N �Table 19. Pumas monitored with GPS collars on the Uncompahgre Plateau, Colorado, December 2004 to July 2014. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 M178 M179 M183 M211 F2 F3 F7 F8 F16 F23 Sex M M M M M M M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F70 F72 F75 F93 F95 F96 F104 F111 F113 F129 F135 F136 F137 F152 F F F F F F F F F F F F F F F F F F F F F F171 F172 F177 F181 F F F F F182 F186 F210 F F F F214 F Age stage adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult adult adult subadult adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult subadult adult adult adult subadult adult subadult Dates monitored 12-08-04 to 07-20-06 01-28-05 to 01-14-06 02-18-05 to 05-14-08 03-12-06 to 06-21-06 04-14-06 to 01-01-08 01-07-07 to 07-15-08 01-21-07 to 11-25-10 03-27-09 to 01-16-10 11-12-10 to 12-01-10 11-13-12 to 12-11-12 11-18-12 to 12-29-12 02-14-13 to 11-11-13 01-03-14 to 07-31-14 01-07-05 to 08-14-08 01-21-05 to 12-11-11 02-24-05 to 08-03-08 03-21-05 to 10-10-06 10-12-05 to 09-10-09 01-04-06 to 02-04-06 02-05-06 to 09-04-09 01-17-06 to 07-25-07 02-09-06 to 09-09-09 03-24-06 to 08-15-07 03-30-07 to 02-22-08 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 08-18-08 01-14-08 to 12-22-11 02-12-08 to 07-07-10 03-26-08 to 06-03-09 10-03-12 to 11-11-12 03-14-13 to 07-31-14 01-28-09 to 07-31-14 05-29-09 to 01-31-12 01-01-10 to 12-21-13 01-27-10 to 06-06-10 01-02-13 to 07-31-14 01-01-11 to 09-20-11 01-20-11 to 09-30-13 04-12-11 to 01-09-13 01-18-12 to 06-15-12 06-16-12 to 12-23-12 01-20-12 to 06-01-14 03-28-12 to 02-08-14 10-27-12 to 12-10-12 01-15-13 to 04-15-13 04-16-13 to 07-31-14 02-04-13 to 08-25-13 03-30-13 to 07-31-14 11-14-13 to 03-01-14 03-01-14 to 07-31-14 02-20-14 to 07-31-14 50 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Puma Habitat Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Methods for Monitoring Populations Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 51 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. 52 �Puma Population Trend, Uncompahgre Plateau, Colorado ra "' E ~ ..., 40 + - - -~ ' - - - - - - - - -,.--,--- ------""'- -...-- -----"4 ~ - - - -------,,,,,-------- C QJ -0 ~ 30 c. + - - - - - - - - - - - - - - -~ ~- -~ ---- QJ -0 C ci z RY4 RYS TYl TY2 TY3 TY4 TYS YEARS ~ Minimum Count Harvest reduction - All mortalities reduction Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1, 2, 3, 4, and 5 (TY1, TY2, TY3, TY4, TY5). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the state government hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. Harvest reduction trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 11.4% to 16.7% harvest of independent pumas. All mortalities trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting 53 �and other mortalities are subtracted from the minimum count. TY1 datum includes 1 adult female and 3 adult males killed off the study area. The TY2 datum includes 1 adult male killed off the study area and 2 adult female pumas killed in February 2011 on the study area to protect livestock. The TY3 datum includes 1 adult female and 4 adult males harvested off the study area and 2 adult females that died of natural causes on the study area. The TY4 datum includes 1 adult female and 1 adult male harvested off the study area and 1 adult female that died of natural cause. The TY5 datum includes 1 adult female that died of natural cause on the study area. This trend line represents 13.6% to 31.2% harvest of independent pumas. Age structure of independent pmm1s in November 2013 at beginning of puma hunting season in Treatment Year 5. Uncompahgre Plateau. Coloi'aclo. 6 ---------------------- 5 "' 84 E 3 0 Female o2 z; ■ Ma le 1 0 1 to2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 Age(vears) 8 9 10 Figure 4. Estimated age structure of independent pumas in November 2013 at the beginning of the puma hunting season in Treatment Year 5 (TY5) on the Uncompahgre Plateau study area, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of independent female and male ages, respectively: 4.59 ± 2.85 yr. (55.11 ± 34.17 mo.), n = 18; 2.66 ± 1.40 yr. (31.91 ± 16.74 mo.), n = 11. 54 �Puma births by month, Uncolilpahgre Phlteau, Colorado. 16 14 12 "'a,; 10 :: ;:i 8 .....0 o 6 z. 4 2 0 - I r :-1· n Ji!in. Feb. M ai·. Apr. M ay Jun!:! July AL1g. Sep. Oct. Nov. Dec;. ■ Births 2005-1014 Births1 982-l 987 Figure 5. Puma births (black bars) detected by month from May 19, 2005 to July 31, 2014 (n = 57 litters of 31 females; 53 of the litters were examined at nurseries when cubs were 25-42 days old and 4 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28, F95 and F111 and VHF-collared mother F197 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 55 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2014, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 02-20-09 Age to last monitor date alive or at death (days, birth to fate) 31 5-28-05 F10 31 5-28-05 M11 31 5-28-05 F12 42 F13 Mother I.D. Radio-collared. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 54.6 months old. Radio-collared. Shed radiocollar 04-19-06 to 04-26-06. F3 Radio-collared. Dhed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-2005. F10 disappeared by 12-30-05. Radio-collared. Shed collar 10-24 to 11-08-05. Recollared on 04-02-06. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 0711-06 at 14 mo. old. Moved to Dolores River valley in SW CO by 12-14-06. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Radio-collared. Shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Radio-collared. Killed and eaten by a puma possibly M5 (13 mo. old) about 08-28-05. Radio-collared. Shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. F2 F16 308-314 Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Died at 10.8 months old Radio-collared. Probably killed by another puma. Multiple bite wounds to skull. Died at 10 months old. Radio-collared. Shed radiocollar 07-27-06 to 08-02-06. 244-245 Radio-collared. Shed radiocollar 05-24-06―05-25-06. F16 ~1,664 F9 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-02-07 326-333 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 301-308 330 56 F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) F21 37 9-26-05 M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 F35 Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 08-16-06 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 324 Radio-collared. Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. Radio-collared. Killed and eaten by male puma 12-21-05 to 12-22-05. F3 ~232-235 Radio-collared. Shed radiocollar 03-21-06 to 03-24-06. F25 63-65 F23 5-30-06 06-30-06 to 07-31-06 63-65 31 5-30-06 38 F36 29 6-9-06 29 6-9-06 M38 41 7-29-06 Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. Dispersed. Killed by puma hunter 01-07-11 in GMU40 Ladder Creek, SW of Grand Junction, CO when he was 53.2 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Dispersed. Killed by a puma hunter 03-12-10 in GMU 40, Bangs Canyon, when 42.8 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F28 M37 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Radio-collared. Assumed dead. Shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 M39 29 Est. Birth date 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 86-87 74 74 352-353 1623 9 255 1307 9 255 53-61 106 57 Mother I.D. F3 F23 F23 F28 F2 F8 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M43 33 8-13-06 M44 8-13-06 33 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-15-06 03-01-07 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 200 Radio-collared. Shed radiocollar by 11-7 to 17-06. Dispersed. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO GMU41 at 29.5 months old. Radio-collared. Shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. M44 killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. He was 15.7 months old. Radio-collared. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Died 05-20 to 23-07 when she was 9.2 months old. Radio-collared. Shed collar by 12-14-06. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed collar . Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Dispersed. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in Tabaguache Creek, GMU 61N when 38.9 months old. Radio-collared. M49 was orphaned when his mother died on about 03-26-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Dispersed from natal area. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61N) 01-2409 when ~29 months old. 899 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 to 12-27-09 89 360 89 360 1187 12-05-06 to 07-31-07 to 01-24-09 939 58 Mother I.D. F7 F7 F7 F3 F3 F3 F50 �Appendix A continued Puma I.D. Estimated Age at capture (days) F53 183 Est. Birth date 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. survival span from 1st capture to fate or last monitor date 01-12-07 to 02-23-07 to 09-02-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 42 Radio-collared. Shed radiocollar 02-23-07. F53 visually observed by P. & F. Star (Loghill Mesa), on 09-02-07, when F53 was ~14 months old and an independent subadult. F54 Radio-collared. Shed radiocollar 2-27-07. M56 observed 0301-07. Radio-collared. Shed radiocollar 06-07-07. Live mode 0606-07. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dispersed. Survived to adult stage. Killed by a puma hunter 12-27-09 in GMU 521, North Fork Gunnison River, when 31 months old. Radio-collared. Shed collar about 02-14-08. Observed with 11-20-07 with F16, but without siblings M58 and F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. Three cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F7 (?) Radio-collared. Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11-13-08. Not radio-collared. Not radio-collared. Dispersed from study area. Killed by a puma hunter 01-01-11 in Calamity Creek, GMU61N when he was 41.5 months old. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 ~428 subad. 200 52 324 434 F59 34 5-24-07 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 08-21-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 55 324 434 48-49 324 434 M62 M63 34 34 7-14-07 7-14-07 08-17-07 08-17-07 to 01-01-11 M64 34 7-14-07 08-17-07 538 1267 262 59 Mother I.D. F25 F16 F16 F16 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M65 34 Est. Birth date 7-14-07 Est. survival span from 1st capture to fate or last monitor date 08-17-07 to 11-07-09 Age to last monitor date alive or at death (days, birth to fate) Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 04-01-08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Dispersed. Survived to adult stage. Killed by Wildlife Services for depredation control for predation on llamas in Little Dolores River, on 11-07-09 when 27.8 months old. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Her range overlapped her natal area. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau study area. Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage. Dispersed. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17.5 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. 262 847 F66 37 7-17-07 08-23-07 to 05-28-09 M67 37 7-17-07 08-23-07 to 12-18-11 M68 37 7-17-07 08-23-07 to 12-30-08 F74 259 6-1-07 M76 30 M77 30 682 1615 532 5-19-08 03-12-08 to 07-09-08 06-18-08 ~87 5-19-08 06-18-08 ~87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 60 Mother I.D. F24 F30 F30 F30 F75 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) F78 30 M79 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 5-19-08 Est. survival span from 1st capture to fate or last monitor date 06-18-08 ~87 F2 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 F81 40 5-23-08 F95 ~488 ~Aug. 2007 07-02-08 to 07-29-09 12-29-08 to 07-31-13 Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 08/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 02-04-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. F93 F97 257 5-23-08 02-04-09 to 01-22-12 1339 M82 37 5-29-08 07-05-08 to 12-10-09 560 M83 37 5-29-08 07-05-08 to 01-18-11 964 Radio-collared. F95 was offspring of F93. She survived the subadult stage and into the adult stage. Her home range overlapped her natal area. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Dispersed from study area. Killed by a puma hunter 01-22-12 in Dry Creek when 43.9 months old. Radio-collared. Shed radiocollar after 03-20-09. Survived to subadult stage. Dispersed. Killed by a puma hunter in 1210-09 GMU 65, Beaver Creek fork of East Dallas Creek, when 18.4 months old. Not radio-collared. Survived; dispersed from study area. Killed by a puma hunter 01-18-11 in Coates Creek west of Glade Park, GMU40. He was 31.6 months old. 424 2,196 61 Mother I.D. F2 F23 F23 F23 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M84 36 6-5-08 F85 36 F86 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-11-08 to 02-11-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 251 6-5-08 07-11-08 to 10-01-08 118 36 6-5-08 07-11-08 to 07-23 to 08-03-08 ~48-59 M87 28 7-3-08 07-31-08 to 12-06-11 1251 M88 28 7-3-08 07-31-08 to 11-30-10 880 F89 M90 28 36 7-3-08 7-9-08 07-31-08 08-14-08 Male 7A 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located her on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 0214-09. Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill at age 3.9 months. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11 at 31 months old. Killed by puma hunter on 12-06-11 at 41 months old in GMU61N north of the study area. Not radio-collared. Dispersed. Killed by a puma hunter in Dawson Creek, Disappointment Valley, GMU711 on 11-3010 when 28.9 months old. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. 867 62 Mother I.D. F70 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 8-19-08 Est. survival span from 1st capture to fate or last monitor date 09-29-08 455 35 8-19-08 09-29-08 976 F95 16 mo. June-07 12-29-08 F98 4-5 mo. 158 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 M99 Sep-Oct08 Sep-Oct08 M101 35 4-15-09 157 M102 35 4-15-09 05-20-09 to 09-19-09 05-20-09 F103 35 4-15-09 159 M105 38 5-7-09 F106 38 5-7-09 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 M107 34 5-25-09 Radio-collared. Killed by a puma hunter on study area during TY1 as dependent cub on 11-17-09 at age 14.9 months. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Due to dangerous tree, could not handle him safely to fit new radiocollar. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. To date, July 2012, F95’s home range mainly adjacent to N side of natal area. Radio-collared. Died; probably killed by male puma (infanticide). Radio-collared. Offspring of non-marked female. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma; apparent canine punctures to braincase. Radio-collared. Died; killed by puma M55 after he was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 09-04-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after she was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 02-09-10 due to shed collar. Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 02-24-10; not collared. Dispersed. Killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 06-28-09 to 02-24-10 488 278 275 661 241 63 Mother I.D. F25 F25 F93 Unm.F Unm.F F16 F16 F16 F75 F75 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) F108 34 Est. Birth date 5-25-09 Est. survival span from 1st capture to fate or last monitor date 06-28-09 to 03-05-10 Age to last monitor date alive or at death (days, birth to fate) 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 to 01-06-13 1,225 M115 427 Nov.-08 07-21-10 610 M117 193 Aug.-09 02-05-10 to 01-01-11 518 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 06-12-10 06-12-10 to 07-21-10 39 M120 30 06-28-10 07-28-10 to 12-02-10 526 M121 30 06-28-10 273 M122 35 07-8-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 F123 29 07-15-10 217 F124 29 07-15-10 08-13-10 to 02-17-11 08-13-10 to 02-16-11 931 216 64 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11 at 18.1 months old. Not radio-collared; too small. Radio-collared. Lost contact after 05-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11. Dispersed. Killed by a puma hunter 01-06-13 in GMU73 SE of Dolores, CO; age 41 months. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Killed by a puma hunter on the natal area in Beaver Creek, GMU70E, off the U.P. study area on 01-01-11 when he was 17 months old. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. Killed by a puma hunter on his natal area on 12-06-11 when he was 17.2 months old. Radio-collared. Lost radio contact after 03-28-11. F94 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). M122 killed by a puma hunter in Tatum Draw, Dry Fk. Escalante Cr., GMU62N, 01-23-13; age 30 months. Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. F104 F94 F70 F28 F119 F72 F72 F3 F3 F94 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) M125 29 07-15-10 M126 28 08-08-10 M127 28 M128 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 08-13-10 to 02-01-11 09-05-10 to 01-08-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 201 08-08-10 09-05-10 to 09-10-11 398 28 08-08-10 198 F129 35 08-21-10 09-05-10 to 02-22-11 09-25-10 to 02-02-12 M130 35 08-21-10 09-25-10 to 02-02-12 M131 35 08-21-10 09-25-10 to 07-21-11 F132 35 08-21-10 09-25-10 35 M134 ~18 mo. ~June-09 12-14-10 to 06-10-11 740 M139 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO, GMU61N, as 17-month-old subadult. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. Found dead 09-14-11 on natal area; killed by another puma on about 09-10-11 at age 13 months. Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Survived to recapture on 02-02-12 at 17.4 months old, with sibling M131; neither handled due to dangerous trees. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-0212 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. Dispersed. Killed by a puma hunter in Lion Cr., extreme western CO, GMU60; age 29 months. Not radio-collared. Too small for collar design. Fate unknown. Apparently died; not with F96 and siblings F129 and M130 on 02-02-12. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. He was about 24 mo. old Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. 221 530 530 334 65 Mother I.D. F94 F118 F118 F118 F96 F96 F96 F96 Unm. F F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) F140 ~5 mo. Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. ~Aug.10 Est. survival span from 1st capture to fate or last monitor date 01-02-11 to 07-31-13 1,096 Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Recaptured and re-collared 01-12-12 as 17-month-old subadult on natal range. Survived to adult stage. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Killed by a puma hunter on 12-23-11 in his natal area; age 16 months. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. Orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-16-11. She ranged in her natal area until her radiocollar quit after 0412-12. Radio-collared. F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old. Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). Radio-collared. Lost contact after 03-21-11; shed collar. Recaptured 01-18-12; fit with GPS collar at 19 months old. Ranged on natal area as adult (philopatric). First litter on 0808-12 at 26 mo. old. Killed by puma hunter on 12/23/12. Radio-collared. M154 probably died of starvation following natural death of his mother F135. Sibling M155 also died. Radio-collared. M155 died of starvation following death of his mother F135. Sibling M154 also died. Radio-collared. M156 shed the collar about 09-05-11. He was 59 days old. Unk./ F28? M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 509 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 04-21-11 to 07-31-11 315 F149 45 04-22-11 06-06-11 to 07-16-12 451 M150 525 08-31-09 02-07-11 to 04-11-11 588 M151 253 06-16-10 264 F152 271 06-16-10 02-24-11 to 03-07-11 03-14-11 to 12-23-12 M154 42 07-06-11 77 M155 42 07-06-11 M156 43 07-08-11 08-16-11 to 09-21-11 08-16-11 to 09-25-11 08-20-11 to 09-05-11 183 776 81 56 66 Unk./ F28? Unk./ F28? Unk. F24 F23 F70 F111 F93 F135 F135 F137 �Appendix A continued Puma I.D. Estimated Age at capture (days) F157 40 08-18-11 F158 40 M159 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-27-11 to 01-15-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 150 08-18-11 09-27-11 to 01-15-12 150 40 08-18-11 09-27-11 to 12-01-11 105 M161 276 04-22-11 01-23-12 to 10-15-12 543 M162 183 07-25-11 01-25-12 to 06-11-12 322 M168 37 07-27-12 09-02-12 to 09-12-12 47 F169 37 07-27-12 09-02-12 to 09-12-12 47 M170 137 08-29-11 199 P1033 22 07-10-11 01-13-12 to 03-12-12 NA Radio-collared. F157 with sibling F158 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. Radio-collared. F158 with sibling F157 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. Radio-collared. M159 probably died about 12-01-11 when he was located with his family (F70, siblings F157, F158). He was not located with them on 12-12-11 and was not observed with them on 12-13-11. He was 105 days old on 12-01-11. Radio-collared. M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old. Shed his expandable collar about 08-03-12. Was struck and killed by a vehicle on Dallas Divide, Hwy 62 in October 2012 when 18 mo. old. Radio-collared. M162 probably was orphaned cub of nonmarked adult female puma killed on Pinto Mesa 01-18-12. M162 died of starvation on 06-11-12 when he was 322 days (10.6 mo.) old. Radio-collared. Cub M168 was offspring of F96; sibling of F169 & F173. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. Cub F169 was offspring of F96; sibling of M168 & F173. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. M170 died about 03-15-12 of unknown natural cause. He was 199 days (6.5 mo.) old. Radio-collared. Cub P1033 was offspring of F136. It died of predation, probably killed by a puma or black bear in the nursery when about 22 days old, before researchers could examine the entire litter to sample and mark the cubs. 22 67 Mother I.D. F70 F70 F70 F23 Unm.F F96 F96 F171 F136 �Appendix A continued Puma I.D. Estimated Age at capture (days) F173 37 07-27-12 M174 32 M175 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-02-12 to 09-12-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 47 08-08-12 09-11-12 to 03-10-13 181 32 08-08-12 09-11-12 to 12-11-12 126 F184 208 08-25-12 03-20-13 to 02-08-14 533 F185 ~183 ~Oct.2012 03-23-12 to 03-27-13 190 F187 31 05-14-13 06-14-13 to 04-03-14 325 F188 31 05-14-13 06-14-13 to 04-03-14 325 F189 38 06-18-13 07-26-13 to 10-19 to 20-13 93-94 Radio-collared. Cub F173 was offspring of F96; sibling of M168 & F169. It died of infanticide, probably of a male puma, based on track sizes (fhpw = 60 mm; hhpw = 50 mm). Radio-collared. Cub M174 was offspring of F152; sibling of M175. He was orphaned after his mother was killed by a hunter on 12-23-12. He was 137 days old. M174 was recaptured at 181 days old and removed from the wild and was rehabilitated at the CPW Del Norte wildlife center for re-release to the wild. He was released to the wild on NW Uncompahgre Plateau on 05-08-14 at 21 mo. old. He was shot for killing 2 domestic goats in Nucla, CO on 08-24-14. Radio-collared. Cub M175 was offspring of F152; sibling of M174. He was mauled to death probably by puma hunting dogs on about 12-11-12 when he was 126 days old. Radio-collared. Cub F184 was offspring of F111; one other sibling track was observed, but the puma was not captured (probably M213 captured with F184 02-05-14 and 02-0814. F184 still dependent on F111 on 10-10-13. F184 orphaned when mother F111 was killed by a hunter on 1221-13. F184 collar malfunctioned; lost contact. She was probably photographed on N rim Horsefly Canyon 07-09-14 and tissue sampled in Belisle device. Radio-collared. Cub F185 was offspring of a non-marked female puma in Roubideau Cyn. F185 shed her expandable collar about 7 days after initial capture. Lost contact. Fate unknown. Radio-collared. Cub F187 was offspring of F96; sibling of F188. Collar quit; but tracks of F187 present with F96 and sibling F188 when recaptured 04-03-14 at 10.5 months old. Radio-collared. Cub F188 was offspring of F96; sibling of F187. Collar quit; but F188 recaptured 04-03-14 at 10.5 mo. old. Radio-collared. Cub F189 was offspring of F136; sibling of F200 and M201. Died of starvation at 93-94 days old after F136 was killed for depredation control. 68 Mother I.D. F96 F152 F152 F111 Unm.F F96 F96 F136 �Appendix A continued Puma I.D. Estimated Age at capture (days) M191 ~183 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death ~July 2012 Est. survival span from 1st capture to fate or last monitor date 01-03-13 to 01-20-13 ~210 Radio-collared. Cub M191 apparently was offspring of F28 (with non-functional GPS collar). He was sibling of PM1068 and one other non-marked cub. M191 was killed by a non-marked male puma on about 01-20-13 along with PM1068. PM1068 was not captured and tagged. It was apparently offspring of F28; sibling of M191 and one other nonmarked cub. PM1068 was killed and partially eaten by a non-marked male puma. Radio-collared. M192 was offspring of F118; sibling of M193 & F195. M192 was independent of F118 at ~11.7 mo. old. He shed his expandable collar at a mule deer kill after 07-01-13. Radio-collared. M193 was offspring of F118; sibling of M192 & F195. M192 was independent of F118 at ~11.7 mo. old. He shed his expandable collar at a mule deer kill after 07-01-13 like sibling M192, but the siblings were not associating (kills were at different locations). Radio-collared. F195 was offspring of F118; sibling of M192 & M193. F195 shed her expandable radiocollar at an elk kill on about 03-04-13; contact lost afterwards. Radio-collared. M198 was offspring of non-marked female PF1074 (sampled by bio-dart). He was sibling of F199. Survived to subadult stage. Dispersed. Last live signal 1023-13 at 15 mo. old. Collar on mortality mode 07-31-14; fate undetermined/unknown; collar in dangerous cliffs. Radio-collared. F199 was offspring of non-marked female PF1074 (sampled by bio-dart). She was sibling of M198. Dispersed. Survived to subadult and adult stages. Radio-collared. Cub F200 was offspring of F136; sibling of F189 and M201. Died of starvation at 96 days old after F136 was killed for depredation control. Radio-collared. Cub M201 was offspring of F136; sibling of F189 and F200. Died of starvation at 93-94 days old after F136 was killed for depredation control. PM1068 ~183 ~July 2012 01-03-13 to 01-20-13 ~210 M192 199 06-20-12 01-04-13 to 07-01-13 376 M193 199 06-20-12 01-04-13 to 07-01-13 376 F195 227 06-20-12 02-01-13 to 03-04-13 258 M198 274 ~June 2012 04-10-13 to 10-23-13 ~510 F199 292 ~June 2012 04-18-13 to 07-31-14 ~790 F200 38 06-18-13 07-26-13 to 10-22-13 96 M201 38 06-18-13 07-26-13 to 10-19 to 20-13 93-94 69 Mother I.D. F28 F28 F118 F118 F118 PF1074 PF1074 F136 F136 �Appendix A continued Puma I.D. Estimated Age at capture (days) F202 35 06-25-13 F203 35 F204 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-30-13 to 08-22-13 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 59 F172 07-12-13 08-16-13 to 03-13-14 245 35 07-12-13 08-16-13 to 03-13-14 245 M205 35 07-12-13 08-16-13 to 01-17-14 190 M206 28 07-31-13 08-28-13 to 07-30-14 365 F207 28 07-31-13 08-28-13 to 06-25-14 330 F208 28 07-31-13 08-28-13 to 06-09-14 314 F209 28 07-31-13 08-28-13 1 Radio-collared. Cub F202 was offspring of F172. No siblings were observed at the nursery; but some could have hidden. Died of predation or infanticide about 08-22-13. Radio-collared. Cub F203 offspring of F137; sibling of F204, M205. Last live signal 03-13-14 in association with F204. Radiocollar probably quit after. Radio-collared. Cub F203 offspring of F137; sibling of F203, M205. Last live signal 03-13-14 in association with F203. Radiocollar probably quit after. Radio-collared. Cub M205 offspring of F137; sibling of F203, F204. Died apparently of natural cause when about 6.2 mo. old. Radio-collared. Cub M206 offspring of F171; sibling of F207, F208, F209. Orphaned at 10 mo. old when mother died of natural cause on 06-01-14. Separated from siblings. Dispersed from natal area. Alive on 07-30-14 in Uncompahgre River bottom between Colona and Billy Cr. Radio-collared. Cub F207 offspring of F171; sibling of M206, F208, F209. Orphaned at 10 mo. old when mother died of natural cause on 06-01-14. Separated from siblings. Died apparently of natural cause about 06-25-14 at 10.8 mo. old. Radio-collared. Cub F208 offspring of F171; sibling of M206, F207, F209. Orphaned at 10 mo. old when mother died of natural cause on 06-01-14. Separated from siblings. Lost contact; last live signal 06-09-14. Radiocollar may have quit. Fate unknown as of 07-23-14. Not radio-collared; too small. Cub F209 offspring of F171; sibling of M206, F207, F208. Fate unknown. 70 F137 F137 F137 F171 F171 F171 F171 �Appendix A continued Puma I.D. Estimated Age at capture (days) M213 550 Est. Birth date 08-25-12 Est. survival span from 1st capture to fate or last monitor date 02-05-14 to 06-09-14 Age to last monitor date alive or at death (days, birth to fate) 654 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Caught in association with subadult F184 on F111 02-05-14 and 02-08-14; probably her sibling, offspring of F111. Previously we had not captured the second cub in F111’s litter, of which F184 was one. Last live signal of M213 on 06-09-14, on NW edge of natal area. He probably dispersed. M216 25 06-12-14 07-08-14 to 49 Radio-collared. Offspring of F210; sibling of M217 and one F210 07-30-14 non-marked cub. Alive on 07-30-14. M217 25 06-12-14 07-08-14 to 49 Radio-collared. Offspring of F210; sibling of M216 and one F210 07-30-14 non-marked cub. Alive on 07-30-14. M221 168 08-13-13 01-27-14 to 18 Radio-collared. Offspring of F197; sibling of one other non- F197 02-13-14 marked cub. Shed expandable cub collar by 03-04-14 at bull elk cache. Last live signal 02-13-14. M223 244 June 02-05-14 to 425 Radio-collared. Radio-monitored in association with F28 at F28 2013 07-30-14 recapture 02-11-14. Alive on 07-30-14. M225 183 Sep. 03-05-14 to 333 Radio-collared. Offspring of non-marked adult female. Unm.F 2013 07-30-14 Possibly one sibling in association at capture 03-05-14. Alive on 07-30-14. P1076 30-31 08-05-13 30-31 30-31 Found dead and mostly consumed in the nursery. Cause F181 probably infanticide or predation. PF1094 214 July 02-04-13 1 Died; mauled by our capture dogs. Offspring of F176. Born F176 2013 in July 2014. Had 2 siblings; 3 cubs total. Other 2 cubs not captured and marked. a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. 71 � https://cpw.cvlcollections.org/files/original/4fc5497ee0d163186822c8afe502ebe8.pdf f8715034a7046db12521fe8b782b314e https://cpw.cvlcollections.org/files/original/4900dd59efbf86b63b17352444f5ce31.pdf e007376ef770594d046293b4ebaf3730 PDF Text Text Colorado Parks and Wildlife July 1, 2014  June 30, 2015 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 3 Federal Aid Project No. W-204-R4 : : : : : Parks and Wildlife Mammals Research Carnivore Conservation Assessing Effects of Hunting on a Puma Population on the Uncompahgre Plateau, Colorado Period Covered: July 1, 2014  June 30, 2015 Author: K. A. Logan Personnel: J. Runge, C. Anderson, Colorado Parks and Wildlife All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the authors. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Colorado Parks and Wildlife (CPW) conducted a 10-year (2004-2014) puma study on the Uncompahgre Plateau to quantify puma population dynamics in the absence (reference period, years 1-5) and presence (treatment period, years 6-10) of sport-hunting. The purpose of the study was to evaluate the assumptions underlying the CPW puma management program with sport-hunting in Colorado. The reference period began December 2004 and ended October 2009 and the treatment period began November 2009 and ended all data collection in December 2014. 109 pumas were captured and marked in the reference period and 115 pumas were captured and marked in the treatment period. Those animals produced known-fate data for 75 adults, 75 subadults, and 118 cubs. This report summarizes results of early preliminary stages of data analyses. In the absence of sport-hunting, the puma population increased and exhibited high survival rates and a high fecundity rate. There was a clear treatment effect with sporthunting. The puma population declined substantially after 3 hunting seasons at a 15% design harvest of independent pumas. An 11-12% design harvest of independent pumas was applied in the final 2 years of the treatment period. The treatment period puma population also exhibited substantially lower survival rates of adults, subadults, and cubs, and a lower fecundity rate. Data analyses are ongoing and will ultimately inform future puma management in Colorado. 1 �WILDLIFE RESEARCH REPORT ASSESSING EFFECTS OF HUNTING ON A PUMA POPULATION ON THE UNCOMPAHGRE PLATEAU, COLORADO Kenneth A. Logan PROJECT NARRATIVE OBJECTIVES 1. Gather data on puma population abundance, sex and age structure, vital rates (i.e., reproduction, age-stage survival rates, and emigration and immigration rates if possible), and agent-specific mortality in a non-hunted puma population phase and a hunted puma population phase for use in modeling puma population dynamics and evaluating and structuring puma harvest management and research approaches. 2. Test current CPW puma harvest-related assumptions that are applied to puma populations in DAUs, and arrive at acceptable harvest levels intended to achieve population objectives, including increases, stability, and reductions in the puma population. 3. Apply a hunting treatment to the puma population on the Uncompahgre Plateau study area designed to test CPW harvest-related assumptions and learn about impacts of hunting on pumas. 4. Develop methods that detect changes in puma population abundance on the Uncompahgre Plateau study area that might be useful for monitoring changes in puma abundance in other puma habitats. SEGMENT OBJECTIVES 1. Complete data collection of the fifth and final year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Complete gathering data on puma population sex and age structure. 3. Complete gathering data for estimates of puma reproduction rates. 4. Complete gathering data to estimate puma sex and stage-specific survival rates. 5. Complete gathering data on agent-specific mortality. 6. Begin data analysis phase working with CPW Biometrician, Jon Runge. Introduction Colorado Parks and Wildlife (CPW) managers need reliable information on puma population biology to develop sound management strategies that address diverse public values and the CPW objective of actively managing pumas while “achieving healthy, self-sustaining populations” (Colorado Division of Wildlife 2002-2007 Strategic Plan:9). Active management of pumas includes managing for sustained populations to provide sport-hunting opportunity, and reducing puma populations to suppress depredation on livestock, predation on mule deer, and enhance public safety. Thus, sport-hunting is intended as a tool for puma management in addition to recreation. Because sport-hunting is a major cause of death for pumas in hunted populations (Murphy 1983, Logan et al. 1986, Anderson et al. 1992, Ross and Jalkotzy 1992, Lambert et al. 2006, Stoner et al. 2006, Laundré et al. 2007), managers need information to better understand how hunting impacts puma populations and methods to monitor changes in puma abundance to assess how management actions are working to meet management objectives. To improve the biological basis for managing pumas, the CPW began a process in year 2000 to develop puma Data Analysis Unit (DAU) plans (Colorado Division of Wildlife 2007). The DAU plans 2 �involved a formulation or deductive model to project an expected number of pumas on available habitat and the level of sport-harvest deemed acceptable to achieve one of two management objectives for each DAU: 1) to maintain a stable or increasing puma population, or 2) to suppress the puma population. A series of “best judgments” and assumptions by CPW managers on puma populations in DAUs was necessary because reliable and affordable methods for estimating puma population abundance in habitat were not available, and there was no information on impacts of hunting on Colorado puma populations. Consequently, managers that developed DAU plans mostly used data from intensive puma population studies from other western states that were published in the literature and from information from studies of puma in Colorado (Anderson et al. 1992) as a guide. The information included estimates of puma population density, sex and age structure, population rates of increase, and expected impacts of harvest rates, and that information was extrapolated to expected puma habitat across Colorado. Current CPW (CDOW 2007) management assumptions include: 1) Puma densities range from 2.0−4.6 pumas/100 km2. 2) A moderate annual rate of growth of 15% (i.e., for the adult and subadult puma population. 3) For DAUs managed for a stable or increasing puma population, acceptable total mortality could fall in the range of 8 to 15% of the projected huntable population (i.e., adult plus subadult pumas). 4) In addition, for DAUs with a management objective for a stable-to-increasing puma population, acceptable female (i.e., adults and subadults) mortality could fall in the range of 35 to 45% of the total mortality. 5) For DAUs managed to suppress the puma population, total mortality could fall in the range of >15 to 28% of the projected huntable population of adult plus subadult pumas. Prior to the current puma research described in this report, none of these demographic prescriptions had been tested for their validity on a puma population in Colorado. Such testing is prudent because some biological judgments made for DAU management plans might be in error and cause unintended consequences to puma populations, such as cause puma populations to decline where the management objective is for stable or increasing puma populations- the critical component for providing resiliency in the puma population to effects of hunting mortality. Metrics from research in other western states support or are at variance with current CPW puma harvest guidelines for a stable to increasing population. Recent research in Wyoming indicated that a puma population could sustain a harvest comprised of 10 to 15% adult females, and population decline occurred when about 25% of adult females comprised the harvest (Anderson and Lindzey 2005:187). A Utah study found that a puma population declined when harvest exceeded 30% of the adults and subadults and comprised 42% females for 3 years (Choate et al. 2006). Another study in southern Idaho and northern Utah suggested that a harvest that included 15 to 20% of resident females probably would not reduce a puma population (Laundré et al. 2007). More recently, researchers in Washington modeled puma population dynamics and indicated that a 14% harvest of adult pumas was expected to result in a stable population and age structure (Beausoleil et al. 2013). Thus considering any of this information, if adult females comprise the majority of the current acceptable level of female harvest (i.e., 35-45%) in a Colorado DAU, and there is substantial error in the population projection, the puma population could decline. This result is possible because actual puma population estimates are not available for any DAUs, in fact numbers used are at best educated guesses or biological judgments extrapolated over huge nonsurveyed areas, and would be problematic if errors occurred for a substantial number of DAUs where the management objective is for a stable-to-increasing population. Thus, the state-wide strategic objective of managing for a healthy, self-sustaining puma population could be in jeopardy. This emphasizes the need to quantify impacts of puma harvest on population parameters to structure guidelines that will likely achieve population objectives. This current study serves as an empirical test of the more theoretical guidelines that could be derived from the literature (previously cited). To gauge the impact of management prescriptions on puma populations, wildlife managers need reliable, affordable methods to apply to representative DAUs. Already the CPW gathers information 3 �useful for guiding puma management through mandatory puma harvest reports and records on other detected mortality (e.g., road-kill, depredation control). Those data include sex, age-stage, location, and cause of death. In 2007, new efforts to improve the quality of the data included aging harvested pumas by tooth cementum-annuli and assessing population structure of pumas in Colorado using population genetics (J. Apker, Carnivore Management Coordinator, M. Alldredge, Mammals Researcher, personal commun.). Yet, the CPW needs to link those data to puma population dynamics influenced by harvest. To address information needs, the CPW began this research in 2004 on the Uncompahgre Plateau to better understand puma population dynamics and effects of sport-harvest. The study was designed in two 5-year periods: a reference period (years 1 to 5) and a treatment period (years 6 to 10). The reference period provided baseline estimates on puma population abundance, sex and age structure, reproduction, survival, agent-specific mortality, and dynamics in representative puma habitat in Colorado where sporthunting was not a cause of mortality. The treatment period occurred on the same study area and included manipulation of the puma population through the use of sport-hunting to provide information on the impact of hunting on a puma population and to evaluate methods intended to detect changes in the puma population. Study Area The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 1). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. This area comprised a Game Management Unit (GMU), the basic spatial unit used to manage pumas by CPW, for the purpose of this study on effects of sport-hunting on a puma population. The study area size represented the very largest GMUs for puma management in Colorado, therefore inferences from the study could be interpreted at the GMU population level. The study area was typical of puma habitat in Colorado that has vegetation cover varying from pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) were the most abundant wild ungulates available for puma prey. Cattle and domestic sheep were raised on summer ranges on the study area. People reside year-round along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area easily accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). 4 �Figure 1. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Expected Results Results of this study inform CPW biologists and managers about expected puma population dynamics and biological impacts of sport-hunting and other causes of mortality (e.g., intra-specific strife, disease, poaching, vehicle collisions, depredation control) on a puma population in Colorado. The study reveal puma life history traits and management effects useful for developing sound management strategies. Moreover, this study evaluated the current puma management structure and assumptions used in puma harvest management through the examination of data gathered directly from a population-level manipulation. This study also assessed one method to detect changes in puma populations on a local intensive scale and for potential application on large representative management areas in collaboration with Mammals Researcher Dr. Mat Alldredge and colleagues. This information should assist the CPW to improve puma management in Colorado. Approach The puma population on the Uncompahgre Plateau study area was studied during a 5-year reference period (i.e., reference period years RY1-RY5) and manipulated during a 5-year treatment period (i.e., treatment period years TY1-TY5). The reference period provided baseline data on puma population dynamics (i.e., abundance, sex and age structure, survival, reproduction, agent-specific mortality, immigration and emigration) without puma sport-hunting as a cause of mortality. The study area was closed to puma hunting from November 2004 to October 2009. In addition, any radio-collared or ear-tagged pumas in the two Game Management Units (GMUs 61 north, 62 north) adjacent to the study area to the north were also protected from sport-hunting. This was an unreplicated case study on one geographic area having a before and after treatment effect design. This effort represented the most pumas ever studied in a population in Colorado and an unprecedented opportunity for CPW to learn about puma population dynamics and effects of sport-hunting. 5 �Field Methods Puma Population Status Puma capture, marking, and sampling: The capture, marking, and GPS- or VHF- collaring of individual pumas and subsequent monitoring was essential to a number of project objectives, including obtaining: population counts, sex and age structure, estimates of vital rates, estimating detection probabilities per individual in camera grids, and movement data to evaluate emigration, vulnerability to hunters, and GMU and DAU boundaries. Pumas were captured year-round using 3 methods: trained dogs, cage traps, and by hand (for small cubs). All captured pumas were examined to ascertain sex and describe physical condition and diagnostic markings. Ages of adult puma were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma were estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Ages of nurslings were estimated from apparent birthing dates indicated by GPS- and VHF-location data of collared mothers. Metric scale body measurements were recorded for each puma included: mass (kg), pinna length, hind foot length, plantar pad dimensions, total length and tail length. Tissue collections of adult and subadult pumas included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) and hair for genotyping individuals, parentage and relatedness analyses, and disease screening. Only skin and hair samples were collected from cubs  10 weeks old. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). All pumas were handled in accordance with approved Animal Care and Use Committee (ACUC) capture and handling protocols in ACUC file #08-2004 (Appendix I) and ACUC protocol #03-2007 titled, Mountain Lion Capture and Handling Guidelines. Captured and handled adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHFcollar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into at least one pinna to facilitate individual identification during direct recaptures and when pumas were harvested. Pumas captured by dogs usually climbed trees to take refuge. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass. The drug was delivered into the caudal thigh or shoulder muscles via a Pneu-Dart® shot from a CO2-powered pistol (Pneu-Dart X-Caliber, Pneu-Dart Inc., Williamsburg, PA). A 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell. A researcher climbed the tree, fixed a rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once on the ground, the puma’s head was covered, its legs tethered, and vital signs monitored. (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). Treed pumas that could not be safely immobilized and handled were shot with a biopsy dart (8 mm long x 3 mm dia., Pneu-Dart Inc., Williamsburg, PA) fired from a CO2-powered pistol to obtain a skin sample from the caudal thigh or shoulder. This sample was used in a study of puma population genetics. Cage traps were used to capture adults, subadults, and large cubs. Pumas were lured into the trap using road-killed or puma-killed ungulates (Bauer et al. 2005, Sweanor et al. 2008). A cage trap was set only if a target puma (i.e., an unmarked puma, or a puma requiring a collar change) scavenged on the lure. Researchers continuously monitored the set cage trap from about 0.5 to 1 km distance by using VHF beacons on the cage and door. This allowed researchers to respond to the captured puma within 30 6 �minutes. Pumas were immobilized with Telazol injected into the caudal thigh or shoulder muscles with a pole or hand syringe. Immobilized pumas were restrained and monitored as described above. Small cubs (≤10 weeks old) were captured using our hands (covered with clean gloves) or with a catch pole. Cubs were restrained inside new burlap bags during the handling process and were not administered drugs. Cubs at nurseries were approached when mothers were away from nurseries as determined by radio-telemetry. Cubs captured at nurseries were removed from the nursery a distance of ~20-100 m to minimize disturbance and human scent at nurseries. Cubs were returned to the exact nurseries immediately after sampling processes were completed (Logan and Sweanor 2001). Adult and subadult pumas were fitted with GPS collars (approximately 400 g each) or VHF collars (approximately 300 g each (Lotek Wireless, Newmarket, Ontario, Canada). Budget constraints limited the number of GPS collars (~10-15) available annually. Therefore, GPS collars were fitted to primarily adult pumas. GPS collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). This schedule seems optimal for sampling different parts of the day and to extend battery life (~18 months). Other adult and subadult pumas were fitted with VHF collars. Our efforts were to locate all collared pumas once per week from fixed wing aircraft and as weather and scheduling conditions allowed, for data on survival, agent-specific mortality, and location. We checked the live signal/mortality signal status from collared pumas from the ground opportunistically when we operated within their home ranges. VHF and GPS collars had mortality modes set to alert researchers when puma were immobile for 3 hours (VHF collars) to 24 hours (GPS collars) so that dead pumas could be found for data on survival and agent-specific mortality. Because subadult male pumas were not fully grown, they also received leather expansion links in their collars. The expansion links added 10-12 cm when open to allow the collars to be worn safely into the adult stage. We attempted to collar all cubs in each observed litter with a small VHF transmitter mounted on an expandable collar (62 g, model 080, Telonics Inc., Mesa, AZ) when cubs weighed 1.3―10 kg. The collars were designed to operate for 10−12 months, and expanded to 54 cm circumference to accommodate growth. Cubs with mass ≥7 kg were fitted with a larger expandable collar (90 g, model 210, Telonics Inc., Mesa, AZ). The collars were designed to operate for 12−18 months and could expand to 54 cm circumference to accommodate growth. Cubs approaching the age of independence (~11−14 mo. old) were fitted with Lotek LMRT-3 VHF collars (~400 g) with leather expansion links that add 10−14 cm to the collar circumference to accommodate the adult puma neck size. These collars operated for 2−3 years. Cubs were recaptured when possible to replace collars as necessary. Monitoring collared cubs allowed quantification of survival rates and agent-specific mortality rates. Radio-collared offspring also provided information on movements, age of independence, recruitment, and emigration. Puma population sampling considerations: The puma is one of the most difficult large mammals to study in North America because of its relatively low abundance on the landscape and its highly cryptic behavior. These characteristics were expected to influence the ability to sample individuals in the study population. The most efficient technique for locating and capturing pumas is detecting their tracks in snow and using trained dogs to pursue and secure them for sampling purposes. Hunters use the same technique to harvest pumas, which creates potential for biased survival rate estimates if researchers and hunters use similar strategies to detect and capture pumas. That is, with similar sampling strategies, pumas that are most vulnerable to being captured and radio-collared might also be more vulnerable to harvest, resulting in survival rates that are biased low. Hunters’ detection of puma tracks is heavily influenced by road access. To minimize bias potential, we attempted to intensively search the entire study area for puma tracks, irrespective of road characteristics, thereby equally detecting puma with both higher and lower hunter-detection probabilities. Thus, our approach was to apply roughly equal (i.e., intensive, uniform) searching intensity across the study area and apply an alternative capture technique with bait and 7 �cage traps that did not rely on track detection to capture pumas, and attempt to directly monitor via VHF telemetry a large proportion of the population in the study area in order to reduce heterogeneity in sampling individuals. Capture efforts to sample the adult and subadult pumas (i.e., independent pumas) subject to sporthunting mortality in the study area population was conducted mainly during winter when snow cover maximized the detection and capture probability of pumas. Snow provided a continuous or almost continuous substrate that registered tracks of terrestrial mammals. Puma tracks were highly distinctive and at ground level could be accurately and consistently visually identified and distinguished from tracks of all other mammals by trained personnel in a variety of snow and weather conditions and in the variety of terrains and vegetation communities. This characteristic was the reason why most intensive puma population studies in the West have been conducted during winter- to maximize detection, quantification, classification and monitoring of animals in the populations (Hornocker 1970, Logan et al. 1986, Lindzey et al. 1992, Ross and Jalkotzy 1992, Spreadbury 1996, Anderson and Lindzey 2005, Lambert et al. 2006, Laundre et al. 2007, Cooley et al. 2008). Puma population research in winter also more directly linked the puma population investigated with animals killed during the hunting season, which in Colorado occurred annually during mid-November through March to facilitate the detection of pumas by hunters which mainly use trained dogs to capture the pumas. Snow also maximized the ability of trained dogs to follow scent in tracks and capture the pumas. In addition, during spring and fall and opportunistically in winter, we attempted to capture pumas in cage traps where pumas were attracted to road-killed deer baits, and puma prey kills. Individuals caught in cage traps were available to move about the study area during winter and be exposed to hunters. The Uncompahgre Plateau study area was highly roaded, and from those roads branched ATV trails that further facilitated thorough searches of the study area to detect pumas. Still, the road system was not uniform, with some areas densely roaded, others moderately roaded, and one area in particular that did not allow motorized vehicles. The area is the combined Camelback Wilderness Study Area (BLM portion) and Roubideau Special Management Area (U.S. Forest Service portion) in the main fork of Roubideau Canyon. That non-roaded area was about 109 km2 (42 mi.2). Yet a system of roads and trails we used surrounded this area. We routinely handled this area by hiking up the lower reaches of Roubideau Canyon and onto upper benches and canyons to search for puma tracks. A puma capture team, involving 4 people on separate search routes, was detailed to search this region on the surrounding roads, ATV/snowmobile trails, and hiking paths. By visiting this area repeatedly each winter we expected to detect some pumas that used the canyon and that might not have been detected in the canyon in other search days. Pumas were expected to move out of the non-roaded portion of the canyon periodically during the winter and be exposed by their movements. Thus, periodic searches of any of the search routes was expected to increase exposure of the pumas to detection. The study area was partitioned into search areas that a capture team could search within 1-2 days to detect puma tracks on snow within each area (Table 1). The intent was to structure a thorough, relatively uniform, systematic search effort across the study area and to repeat it multiple times during winter and spring. To cover the areas efficiently, we used four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue the puma to capture, sample, and mark it. When puma tracks 1-2 days old were detected, we searched in the direction of travel of the puma in an effort to find ≤ 1 day old tracks that would facilitate pursuit of the puma. This sometimes lengthened our search within any particular area by another 1-2 days. When a GPS/VHF-collared puma was detected with radiotelemetry within 1 km (usually < 0.5 km) of the tracks and the direction of the tracks indicate that the puma was likely the collared individual, then we directed our efforts away from those tracks to focus our efforts on non-collared (i.e., non-sampled) pumas in the population to use our time more efficiently. 8 �Table 1. Puma search areas on the Uncompahgre Plateau Study area. West Slope East Slope 25 Mesa Road to Cottonwood Creek and San 25 Mile Mesa Road to east rim of Roubideau Miguel Canyon (west reach) Canyon and Ben Lowe Mesa ---------------------------------------------------------------------------------------------------+-------------------------------Cottonwood Creek to Horsefly Canyon Roubideau Canyon to Transfer Road ---------------------------------------------------------------------------------------------------+-------------------------------San Miguel Canyon (mid reach) to Maverick Draw Transfer Road to east rim of Dry Creek Basin ---------------------------------------------------------------------------------------------------+-------------------------------Horsefly Canyon and San Miguel Canyon (mid East rim of Dry Creek Basin to east rim of Spring reach) to Clay Creek Canyon ---------------------------------------------------------------------------------------------------+-------------------------------Clay Creek and San Miguel Canyon (upper reach) Spring Canyon to Happy Canyon to McKenzie Creek ---------------------------------------------------------------------------------------------------+-------------------------------McKenzie Creek and San Miguel Canyon (upper Happy Canyon to Horsefly Canyon reach) to Leopard Creek ---------------------------------------------------------------------------------------------------+-------------------------------Horsefly Canyon to McKenzie Butte ---------------------------------------------------------------------------------------------------+-------------------------------McKenzie Butte to Loghill Mesa Reliability of population count methods: The approach described previously was expected to enable us to monitor a large proportion of the independent puma population on the study area in winter for reliable counts. On this point, we wanted direct evidence on the reliability of our field methods to study the puma population and make our winter counts. An opportunity for a one-time independent evaluation on the proportion of independent pumas on the study area that we might have marked was provided by an independent camera grid study conducted on our study area by Master of Science graduate student Kirsti Yeager (Colorado State Univ., Dep. of Fish, Wildlife, and Conservation Biology) and advisors Dr. William Kendall (Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University) and Dr. Mat Alldredge (Mammals Researcher, CPW). This collaboration was part of a larger CPW supported project on the Colorado Front Range that evaluated the use of a grid with cameras, predator call boxes and DNA collection methods as a noninvasive method to collect puma tissue for capture-recapture models for estimates of puma abundance (Yeager et al. 2013). A grid of 2 km x 2 km (4 sq. km) cells covering 540 km2 was established on the east slope of the Uncompahgre Plateau study area. Eighteen cells were identified randomly for each of 3 survey periods each lasting about 28 days. Therefore, a total of 54 random cells were surveyed during December 2012 to March 2013. This period was in treatment year 4 (TY4). Within each random cell K. Yeager subjectively chose the “best” site to attract pumas by using vocal baits each consisting of a Fur-Finder ® (Magna, UT) electronic predator call of a distressed deer fawn. Each site also had a Reconyx ® PC900 Hyperfire camera (Holmen, WI) to record animal activity and hair-sampling devices (i.e., barbed-wire strands, sticky rollers) to attempt to acquire hair. This effort evaluated these methods for a non-invasive survey of puma abundance by using tissue to genetically identify individuals in a capture-recapture structure (Yeager et al. in development). This also allowed us to evaluate our field methods and proportion of independent pumas that were marked in the population. Population Manipulation: The puma population on the Uncompahgre Plateau Study Area was manipulated by sport hunting after the 5-year reference period with no hunting. The hunting season was from mid-November and extended to January 31, unless the last puma on the design quota was killed before January 31, which effectively closed the season on the study area. The initial harvest quota was 8 pumas which represented a 15% harvest of the expected number of independent pumas in treatment year 1 (TY1). The predicted effect was that the 15% harvest of independent pumas would result in a stable or increasing population, an expectation that mangers used to guide puma harvest rates in Colorado. The quota of 8 was based on the projected number of 52 independent pumas expected on the study area in winter 2009-10 (TY1), modeled from count data in winter 2007-08 (RY4) (see Appendix II, Table AI.3). After it was evident that the number of independent pumas had declined during TY1 to TY3, we adjusted 9 �the harvest quota down to 5 pumas to represent an 11% harvest of the projected 45 independent pumas expected in TY4 in an effort to find a sustainable harvest rate useful to managers. The harvest quota of 5 was continued in TY5. The number of hunters on the study area each winter was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date could get a new permit for another 14 days or until the hunting season on the study area closed due to the quota being reached or the end of the hunting season. This permit system enabled CPW to estimate the number of hunters that actually hunted on the study area each season. In addition, a voluntary survey questionnaire (see Appendix III) was attached to each puma hunting permit issued to each hunter with a stamped envelope addressed to the CPW principal investigator. Hunters were asked to complete the survey as soon as possible for each hunting period associated with the permit in an effort to have hunters report the information while it was still fresh in their minds. All pumas harvested on the study area were visually examined and sealed by the principal investigator as mandated by CPW. Hunters reported their puma kill to CPW within 48 hours of harvest and presented the puma carcass for inspection within 5 days of harvest. At the time of carcass check-in a mandatory CPW harvest check form was completed. In addition, an upper premolar tooth (i.e., PM2) was extracted for aging by the cementum annuli method and a tissue sample was collected. Each successful hunter was asked to fill-out the one-page hunter survey form. All other hunters that did not report a puma kill on the study area were contacted by phone or in person and asked to complete the survey form as well. Many hunters returned the surveys on their own volition. Mandatory hunter harvest checks provided accurate data on pumas removed from the study population for estimates of survival and agent-specific mortality. Hunters also provided data to evaluate the relative vulnerability of pumas to harvest and potential for hunter selectivity. Hunter harvest and capture events also revealed availability and sex and age classes of unmarked pumas on the study area during the hunting season and before our capture teams operated after the season to quantify the population. After the design quota was filled and the study area closed to hunting, two puma research teams activated for capture operations with trained dogs and cage traps. One team operated on the east slope and one operated on the west slope of the study area to systematically and thoroughly search the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring. Population Monitoring: This monitoring plan enabled us to estimate the winter puma population abundance and sex and age structure each hunting season. Researchers monitored other population parameters, including: reproduction, survival and agent-specific mortality year-round. Movements of VHF- and GPS-collared pumas were also monitored. GPS- and VHF-collared pumas were fixed about once per week from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring enabled researchers to find GPS-collared pumas to acquire remote GPS location reports, monitor the status (i.e., live or dead) of individual pumas, and to locate carcasses for necropsy. Status of GPS- and VHF-collared pumas were monitored from the ground opportunistically using handheld yagi antenna. GPS-collared pumas were monitored for survival status daily by using GPS-data that attempt location fixes 4 times daily (00:00, 06:00, 12:00, and 19:00). Cessation of activity (i.e., due to death) around those times allow a more accurate identification of time of death. Puma births occurred from March through September, but potentially they could happen any month of the year (Anderson et al. 10 �1992, Laundre and Hernandez 2007, Logan 2008). Researchers estimated reproduction data on birth interval, litter size, sex ratio, survival, agent-specific mortality, and recruitment to later life stages (i.e., subadult, adult). Emigration was revealed with a sample of radio-collared or ear-tagged marked offspring that left the study area. Analytical methods: The population of interest to managers was the independent pumas (i.e., adults and subadults) in winter, which coincided with the puma hunting season in Colorado when snow cover maximized the vulnerability of pumas to hunting. As indicated previously, our winter research was designed to be thorough to search the study area to maximize the number of marked pumas while trying to reduce heterogeneity in sampling for population parameter estimation. This along with harvest statistics we attempted to obtain a complete count with attendant sex and age structure of the population that represented the Colorado hunting season from November through March. The counts consisted of the sum total of all known marked (i.e., radio-collared and ear-tagged) pumas on the study area, and non-marked harvested pumas plus any other pumas detected on the study area whose movements did not match movements of collared pumas and exhibited diagnostic characteristics of unique individuals (e.g., tracks distinguishing sex from hind-foot plantar pad measurements, counts of cub tracks with female tracks). In addition, we wanted to maximize the number of radio-collared pumas in all sex and age classes and to obtain a uniform distribution of those animals across the study area to represent animals in the population exposed to all causes of mortality. Puma Population Trends Puma population change was quantified by winter population counts. Data on agent-specific mortality, survival and reproduction rates were used to evaluate changes in population associated with the reference and treatment periods. Puma Survival and Mortality Analysis Adult puma survival and mortality was examined from data on radio-collared pumas that provided known-fate data (i.e., monitoring dates, estimated dates of death, cause of death). We used program MARK (White and Burnham 1999) (accessed January 12, 2015), the known fates data type and the logit link function to model survival rates with a candidate set of models structured to investigate factors that might explain variation in survival. MARK estimated survival rates, standard errors, and 95% confidence intervals for each model. Our main interest was the effect of the hunting treatment as partitioned among the reference and treatment periods on survival, because our research focus was to examine effects of sport-hunting on a puma population. Radio-location records for each adult puma were converted to monthly encounter histories. MARK estimated monthly survival rates using the modified Kaplan and Meier (1958) estimator that allowed staggered entry based on when we collared individuals and censoring of individuals if we lost contact with them (Pollock et al. 1989). We used data from year 2 of the reference (RY2) period to year 5 of the treatment period (TY5) (i.e., a 9 year span). We did not use data from reference year 1 (RY1) because we had just started the study and had collared only 7 adult pumas (3 males and 5 females). Encounter histories of individual adult pumas started on the day of capture, because no pumas died as a result of capture, or the beginning of RY2 (November 1, 2005). We censored individuals in the data if we did not receive its signal after the month of its last location. Individuals re-entered the data set if we recaptured them and fit them with a new collar. Death dates for puma were assigned to pumas with GPS collars based on the first day that GPS locations indicated that the pumas were immobile. Death dates for VHF-collared pumas were estimated based on previous live signal data and the mid-point of the span of days the puma was estimated to have died based on carcass decomposition. Causes of death were categorized to known human causes (e.g., harvest, depredation control, vehicle strike, poached), to known natural causes (e.g., intraspecific strife, injury), or to unknown natural causes. 11 �Subadults puma survival and mortality was estimated for all known radio-collared and ear-tagged and tattooed pumas with known fates that spanned a 12-month subadult stage from 13 months up to 24 months of age. We did not know with certainty when all of the pumas in this 12-month age stage became independent, therefore some of the pumas may have been dependent for a period of time. Encounter histories for the pumas started as marked pumas entered the age stage. Histories started on the first day of capture for subadults caught and marked for the first time, because no subadults died as a result of capture. All histories were converted to monthly encounter histories. Death dates were assigned to harvest, depredation control, and observed vehicle strike dates. For other VHF-collared pumas where dates were not observed, dates were estimated as the mid-point of the span of days the puma was estimated to have died based on previous live signal data and carcass decomposition. The encounter histories were treated as known-fate data and entered into program MARK to model subadult puma survival rates using a candidate set of models that might explain the variation in survival rates. Examining survival rates of adults and subadults, the legal harvest-age pumas, in the reference and treatment periods with contrasting models with and without the hunting treatment allowed us to assess changes in survival associated with the treatment effect. A treatment effect supported an inference that sport-hunting mortality was an important factor explaining the variation in puma survival and a factor that was largely additive if survival declined in association with the treatment. However, if models lacking the treatment effect received the most support, this would indicate that hunting mortality was primarily compensatory or that statistical power was insufficient to detect a treatment effect. If population growth of independent pumas also declined in association with treatment effect on survival, this change would further support that hunting-caused mortality was mostly an additive factor. Cub survival and mortality was estimated for all radio-collared pumas 1 month to 12 months of age representing a stage when the pumas were dependent on their mothers. The large majority of the cubs in this data set were initially radio-collared as nurslings 1-2 months old. But we also included cubs collared at older ages, because we entered data so MARK would estimate monthly survival rates. In this way, use of data on the older cubs only added to the sample of older cubs and did not bias estimates because older cubs have a tendency to exhibit higher survival (Logan and Sweanor 2001, Ruth et al. 2011). Encounter histories for the cubs started on the first day they were collared. Three nursling cubs that died as a result of malfunctions of the design of the expandable radiocollars early in the study in the reference period were removed from the analysis. After the collars were modified, no other cub mortalities from the collars occurred. Causes of cub deaths were assigned after dead cubs were examined directly. Dates of death were estimated as the mid-point of the span of days the puma was estimated to have died based on dates of previous live signal data and carcass decomposition. The assumption that each radio-collared cub was an independent random sample (i.e., distribution of mortalities among litters is random) may be violated because multiple cubs were often collared in litters and the fates of cubs within litters may be linked. For example, sometimes more than 1 or all cubs in a litter may die from the same proximate cause (e.g., infanticide by a male puma) or the survival of surviving cubs in a litter may be linked to death of siblings (e.g., resulting from greater individual maternal care ). Violation of the independence assumption can result in unbiased survival point estimates, however, sample variances are expected to be underestimated, (i.e., overdispersion, Bishop et al. 2008). Therefore, we will examine validity of the independence assumption in data by estimating an over dispersion parameter, c-hat (Cooch and White 2015). Model selection and parameter estimates The candidate models were considered in importance in an information-theoretic approach (Burnham and Anderson 1998) using Akaike’s Information Criterion adjusted for small sample sizes (AICc) to rank the models. We considered the models with the most support as those with the lowest AICc scores, high AICc weights (wi), and models with ∆AICc ≤2 as having similar support (Burnham and 12 �Anderson 2002). Survival estimates reported here were estimates in the top model and other supported models. Average monthly survival rates for adults were converted to annual survival rates (i.e., Saveragemonthly12), standard errors, and 95% confidence intervals. Stage survival parameters for subadults and cubs were derived estimates calculated in MARK from monthly survival rates that produced average stage (i.e., 12-month) survival rates, standard errors, and 95% confidence intervals. Reproduction Female pumas with GPS/VHF collars were monitored the year round. Data from those pumas provided information on fecundity (i.e., proportion of adult females giving birth each year), litter size, secondary sex ratio (i.e., sex ratio of cubs born), birth intervals, and age at first breeding. Reproduction was verified by direct observations of cubs in nurseries and in direct association of adult females during capture efforts. Fecundity, defined as the proportion of adult female pumas giving birth each year, was estimated annually from reference year 2 (RY2) to through treatment year 5 (TY5) when we had ≥12 adult females in annual samples (there were only 4 adult females in RY1). Data on each adult female each year was coded with the individual identification number and as producing a litter of cubs (1) or not producing a litter (0) and whether the individual female produced a litter each year in the reference period (1) or the treatment period (2). Because adult females comprising the samples within each year were not independent of other years (i.e., some of the same females were monitored in a series of years within and among periods) mean period fecundity rates were modeled by using the generalized linear mixed model procedure (PROC GLIMMIX) in SAS (Version 9.3, 2010, SAS Institute) where the period was the fixed effect and individual puma identification was the random effect. We used the binomial distribution and logit link. We also investigated all adult females that exhibited extremely constrained GPS and VHF location clusters or movements that might indicate the birth of a litter for data on numbers and gender of cubs. When the cubs were 25 to 45 days old we entered the nurseries when the mothers were absent to examine the cubs and to mark them (previously described). We coded the data with each adult female identification number, the period in which the litter was produced (reference=1, treatment=2) and the number of cubs observed in each litter (1, 2, 3, 4). Similarly, because adult females comprising the samples within each year were not independent of other years and some occurred in both periods, we modeled period mean litter size using the mixed linear model procedure (PROC MIXED) in SAS, where period was the fixed effect and individual puma identification was the random effect. The sex ratio of cubs produced in the reference and treatment periods was compared to an expected 1:1 sex ratio by using the Goodness of fit Chi-square procedure in Zar (1984). PRELIMINARY FINDINGS Puma Capture From December 2, 2004 to October 30, 2014 we captured ~256 individual pumas a total of 440 times on the Uncompahgre Plateau study area. None of the adult or subadult pumas died from capture procedures. However, 3 cubs died as a result of premature expansions of the radiocollars (indicated previously in Field Methods) and 1 cub was killed by our tracking dogs. We individually marked 226 pumas: 109 in the reference period and 115 in the treatment period. The number of radio-collared pumas monitored each year ranged from 16 to 56 and averaged 40. Marked pumas provided known-fate data on 75 adults, 75 subadults, and 118 cubs. About 30 individuals were captured with dogs, but were not handled due to dangerous positions in trees. Of those pumas not handled, 11 were captured in the reference period and 19 were captured in the treatment period. Six of 11 pumas not handled in the reference period were associated with marked family members (i.e., mothers, siblings, cubs). Likewise, 8 of 19 pumas not handled in the treatment period were associated with marked family members. Reliability of Population Count Methods The camera grid survey by K. Yeager in treatment year 4 (TY4) spanned 102 days from December 2012 to March 2013. The survey time overlapped 3 months of our capture efforts on the study 13 �area from January 1, 2013 to April 18, 2013. Eleven GPS and VHF collared pumas were known to use the survey grid for varying amounts of time, including 7 adult females, 1 subadult female, 2 adult males, and 1 subadult male. During the survey 18 photographs of pumas visiting the sites were acquired, and all 18 of the photographs depicted GPS or VHF collared pumas. The photographed pumas included 1 subadult female (captured 1/15/2013) and 1 subadult male (captured 1/1/2013) that we captured and marked during the camera survey for the first time before cameras subsequently detected them 5 and 3 times each, respectively. In addition, we captured and marked 1 adult male (2/14/2013) for the first time during the camera survey that was not detected by the cameras. Of the 11 collared pumas known to use the grid, 7 were photographed 1 to 5 times each, including 5 adult females, 1 subadult female, and 1 subadult male. Probability of detecting the 11 collared pumas available during the entire survey period was 0.64 (p= 7/11). Because no non-collared pumas were photographed and we detected, captured and marked 3 new pumas before the cameras detected them during the survey, the data indicated that our field methods produced reliable winter population counts. Puma Population Counts The number of days we spent each winter and early spring searching for pumas with dogs in each period was similar (reference mean=77.2, SD=4.0, range 71-82; treatment mean=79, SD=4.8, range 7486). We believe we had a thorough knowledge of the study area and search routes for reliable counts of the winter population of independent pumas on the study area by reference year 4 (RY4) and throughout the treatment period. However, in RY5 a state-mandated hiring freeze (in response to economic recession) resulted in insufficient personnel for thorough searches of the study area for a reliable winter count of independent pumas. Therefore, the count in RY5 is biased low, but is still larger than RY4 (Table 2, Fig. 2). Puma Population Trends The population of independent pumas increased during the reference period without hunting as a mortality factor and the population declined substantially during the treatment period when hunting was restored (Table 2, Fig. 2). The increasing population during the reference period was the first indication that hunting mortality might have a population affect. The highest number of independent pumas was counted in winter of treatment year 1 (TY1) which was preceded by 5 previous years without hunting. The hunting treatment during TY1 to TY3 consisted of a designed 15% harvest rate on the independent pumas with an expectation that the puma population would remain stable or increase. The quota to represent a 15% harvest was 8 pumas based on a model that projected 53 independent pumas expected in TY1 (Appendix II). However, the puma population declined, therefore, a 15% design harvest (actual harvest averaged 16.1% TY1-TY3, Table 3) of independent pumas was not supported for managing toward a stable or increasing population. Because the population declined with a 16.1% actual harvest rate, we wanted to find a harvest that might be sustainable. Therefore, in TY4 and TY5 the quota was reduced to 5 pumas constituting 11-12% design harvest of independent pumas. The population reached a minimum of 42 independent pumas in TY4, a 25% decline (Fig. 3), and was affected mainly by hunting mortality from TY1 to TY3. The population increased slightly in TY5 and was associated with the lower design harvest rate. During the hunting treatment the number of adult pumas declined to the lowest number in TY5, a 34% decline (Fig. 3). Puma Mortality The regulations implemented for eliminating sport-hunting as a mortality factor in pumas on the study area in the reference period were effective. Of the 32 (21 females, 11 males at risk) adult radiocollared pumas we monitored, 7 adult pumas died; but none from hunting (Table 4). Causes of death were attributed to: 5 natural causes (4 intraspecific strife, 1 unknown), 1 vehicle strike, and 1 depredation control. Of the 22 subadults (8 females, 14 males at risk) providing known-fate data in the reference period, 3 died. One male was killed by a hunter after he dispersed from the study area. The other causes of death in subadults were 1 natural cause (trampled by elk) and 1 vehicle strike. Of 55 radio-collared 14 �cubs (28 females, 27 males at risk) monitored in the reference period, 16 died. Causes included: 13 infanticide, 1 predation, 1 natural, and 1 vehicle strike. In the reference period natural causes dominated deaths of adults and cubs, but of the 3 subadult deaths 2 were from human-causes. In the treatment period a total of 35 pumas were killed by hunters on the study area (Table 3), including: 8 adult females (22.8%), 16 adult males (45.7%), 3 subadult females 8.6%, and 8 subadult males (22.9%). This harvest structure was associated with a declining puma population. The ratio of marked to non-marked pumas killed by hunters on the study area before we started our winter capture operations during the treatment period was 19:16. Moreover, another 12 radio-collared independent pumas that ranged on the study area were killed by hunters when those pumas moved onto adjacent GMUs open to puma hunting, including: 4 adult females, 7 adult males, and 1 subadult female. Sport-hunting in the treatment period changed mortality for independent pumas (Table 4). Of the 61 adults we monitored (39 females, 22 males at risk), 37 died. Hunting caused 21 adult deaths (14 males, 7 females). Other adult deaths were attributed to: 10 natural (7 unknown probably disease related, 3 strife), 3 vehicle strike, 2 depredation control, 1 illegal kill. Of the 53 subadults (19 females, 34 males at risk) providing known-fate data in the treatment period, 20 died. Eleven were killed by hunters. Other deaths in subadults were: 3 strife, 2 other natural, 1 vehicle strike, and 3 depredation control. Of the 63 radio-collared cubs (27 females, 36 males at risk), 27 died. Mortality causes in the cubs included: 8 infanticide, 4 other natural, 2 vehicle strike, 3 depredation control, and 9 starvation. The 9 cubs starved after the deaths of 5 mothers due to: hunting (2 mothers involving 3 cubs), depredation control (1 mother with 3 cubs), and natural causes (2 mothers involving 3 cubs). Human caused mortality, particularly from hunting, dominated adult and subadult puma deaths in the treatment period. Natural mortality comprised the majority of cubs deaths (15/27*100=55.6%). But, human-caused cub deaths in the treatment period increased to 44.4% (12/27*100=44.4%) from 6.2% in the reference period. In addition to these deaths revealed by the radio-collared cubs, we observed deaths of 4 entire litters on the day we entered nurseries to examine cubs for the first time. These cubs were not part of the radio-collared cub population used to model or estimate cub survival (see below in Puma Survival, Cubs). One litter of 3 nursling cubs starved to death in the reference period after the mother was killed for depredation control. In the treatment period, we observed that three entire litters died: one litter with 2 cubs and one litter with ≥1 cubs died of infanticide. A third litter with ≥1 cub died due to black bear predation. Puma Survival Adults Our adult survival sample included 75 radio-collared individuals, with 32 monitored in the reference period and 61 monitored in the treatment period. The most parsimonious survival model included gender interacting with period (i.e., reference, treatment periods, indicating a treatment effect) as factors that best explained variation in adult puma survival rates (Table 5). The evidence ratio using AICc weights (wi) indicated very strong support for the top model with 10.10 times the support of the secondranked model with gender in an additive effect with period. Moreover, >4 ∆AICc separated the top model from the second-ranked model. The remainder of the models in the 8 model candidate set had weak to no support. Clearly, hunting-caused mortality negatively affected adult male and female puma survival, and was particularly strong on adult males. Adult male survival declined from 0.96 in the reference period to 0.40 in the treatment period, and adult female survival declined from 0.86 to 0.74 in those respective periods (Table 6). 15 �Subadults Our subadult survival sample included 75 individuals with known-fates: 22 in the reference period and 53 in the treatment period. For subadult pumas the modeling results indicated period as an important factor influencing survival as indicated by the two top-ranked models ≤2 ∆AICc points (Table 7), which together accounted for 0.77 of the model weights (wi). Evidence ratios using AICc weights (wi) indicated the top-ranked model with interaction of gender with period had weak support for the best model with 1.7 times the support of the second-ranked model with period (i.e., genders combined). Subadult males were strongly negatively affected by hunting-caused mortality, similar to adult males. Subadult male survival declined from 0.92 in the reference period to 0.43 in the treatment period. However, subadult female survival indicated no substantial change from 0.63 to 0.70 with overlapping 95% CIs in those respective periods (Table 7). The second-ranked model Speriod (with genders combined) had reasonable support as the best model (i.e., 1.0567 ∆AICc, wi=0.28631) for explaining variation in subadult survival which declined from 0.84 (95% CI 0.60, 0.95) in the reference period to 0.52 (95% CI 0.37, 0.66) in the treatment period (Table 8). Independent pumas Hunting-caused mortality in the treatment period was the single-most important cause and it was strongly additive. Had hunting mortality been strongly compensatory, the population of independent pumas was expected to be relatively stable or increase (consistent with the reference period population trend), meaning hunting mortality would have compensated for other causes of mortality. Adequate immigration would have also compensated for some mortality. But, this was not the case. The number of independent pumas increased in the reference period without hunting mortality and it declined substantially in the treatment period in association with hunting as the major cause. Moreover, other independent pumas that ranged on and off the study area were killed by hunters and other causes of mortality continued to materialize in the treatment period, including natural and other human causes, all of which contributed to population decline. Cubs Our cub survival sample included 118 cubs: 55 cubs from 32 litters in the reference period, 63 cubs from 45 litters in the treatment period. Modeling results indicated that hunting treatment as a factor explaining puma cub survival variation was less conclusive. This age stage was not expected to be directly affected by hunting mortality because cubs were not legal game. The two top-ranked models indicated period as a factor that influenced cub survival (Table 9) and together accounted for 0.54 of the model weights (wi). Evidence ratios using AICc weights (wi) indicated the top-ranked model with an interaction of gender with period had weak support as the best model with 1.6 times the support of the second-ranked model with period. Moreover, the top model had 1.7 times the support of the third-ranked continuous survival model with no treatment effect. The top model was separated from the next two models by ≤1.0174 ∆AICc, and with the evidence ratios this indicated that all 3 models had substantial support as best models for explaining the variation in cub survival. The top model with gender interacting with period indicated no substantial change in female cub survival between the reference (0.34) and treatment (0.39) periods (Table 5). But male cub survival declined from 0.71 to 0.30 in those respective periods. The second-ranked model (Speriod) also had substantial support as the best model to explain changes in cub survival (females and males combined) which declined from 0.50 (95% CI 0.34, 0.66) in the reference period to 0.34 (95% CI 0.22, 0.48) in the treatment period (Table 10). The third-ranked model S(.) (i.e., no treatment effect, combined genders) estimated the cub survival rate 0.41 (95% CI 0.31, 0.52) for the entire study duration. Note: - - c-hat (i.e., over-dispersion parameter) has yet to be estimated for cub survival, and adjustments will be made if necessary. 16 �Puma Reproduction Adult female pumas on the Uncompahgre Plateau produced litters of cubs between the months of March to September, spanning the early spring to early fall seasons. Data on 66 birth dates revealed that births increased rapidly in May and June, peaked in July, followed by a slight decline in August and a rapid decline in September. No live births were detected in the months of October, November, December, January, or February (Fig. 4). Assuming a 92 day gestation period (Anderson 1983, Logan and Sweanor 2001, this study), the distribution of birth months indicated that puma breeding activity spanned the months of December to June, with a rapid increase in February and peaking March through May. We estimated gestation for 17 litters by 13 females based on GPS- or VHF- location data of females with prospective sires that produced minimum and maximum estimates. Gestation lengths averaged 90.4min-91.8max days (SDmin=2.6, 95% CImin 89.1, 91.6; SDmax=1.0, 95% CImax 90.7, 92.8). Birth intervals for 18 adult females that produced 33 litters averaged 18.5 months (SD=5.9, 95% CI 16.4, 24.4). We estimated the age of 13 adult females when they produced their first litters based on estimated ages (n=11) or known-ages (n=2) of pumas at previous captures and nipple characteristics (i.e., tiny, pink or white color) and associated reproduction histories. The average age at first litter was 32.2 months (SD=8.4, 95% CI 27.6, 36.8, range=21-48). This meant those females conceived at the average age of 29.2 months (SD=8.4, 95% CI 24.6, 33.8, range=18-45) assuming an average 92 day gestation period. Litter sizes were determined for 26 litters produced by 14 females in the reference period where we were reasonably certain we counted all the cubs in nurseries when the cubs were 26 to 42 days old. Likewise, we determined litter sizes for 21 litters of 16 females in the treatment period for nursling cubs 25 to 45 days old. Average litter sizes for each period estimated using linear mixed models were 2.76 (SE=0.1806, 95% CI 2.41, 3.12) for the reference period and 2.38 (SE=0.1972, 95% CI 1.99, 2.76) for the treatment period. Change in the average litter sizes in the two periods was small and the averages were not significantly different because the 95% confidence intervals on the slope for period included zero. The male:female sex ratio for 72 nursling cubs in the reference period was 41:31 and was not significantly different from an expected 1:1 ratio (χ2=1.388, 1 d.f., 0.10<P<0.25). Similarly, the 27:22 sex ratio for 49 nurslings in the treatment period was not significantly different from an expected 1:1 ratio (χ2=0.51, 1 d.f., 0.25<P<0.50). With all the cubs pooled from both periods, the sex ratio 68:53 was not significantly different from parity (χc2=1.860, 1 d.f., 0.10<P<0.25). Fecundity, defined here as the proportion of adult female pumas giving birth each year, was determined for reference period years 2 to 5 (i.e., RY2-RY5) when we radio-monitored 12 to 13 individual females per year and treatment period years 1 to 5 (i.e., TY1-TY5) when we radio-monitored 15 to 17 individual females per year. Average fecundity per year for each period estimated using generalized linear mixed models were 0.63 (SE=0.068, 95% CI 0.49, 0.75) for the reference period and 0.48 (SE=0.057, 95% CI 0.37, 0.59) for the treatment period. The average fecundity rates for the periods were not statistically different because the 95% confidence interval for the slope included zero. However, a lower average fecundity of 0.48 over 5 years was expected to produce a substantially lower population growth (~6% less per year) than an average fecundity of 0.63 in our deterministic discrete time model (Appendix II) with zero harvest and all other population parameters being equal. Therefore, decline in fecundity from the reference to treatment periods was biologically significant, especially because it occurred with lower survival rates. Management Implications 1) A 15% design harvest (actual harvest averaged ~16%) of independent pumas in this population manipulation was associated with a substantial population decline in 3 years. Up to ~12% harvest of independent pumas may be sustainable. 2) Human causes of mortality, especially hunting, affected survival of independent pumas in the treatment period. 17 �3) Natural causes of mortality were undetected by managers, as were some vehicle strikes and illegal killing. 4) The GMU puma management unit structure inadequately fitted the scale of hunting-caused mortality due to the movements of pumas beyond GMU boundaries. Literature Cited Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Special Report No. 54, Colorado Division of Wildlife, Ft. Collins. Anderson, A. E., D. C. Bowden, and D. M. Kattner. 1992. The puma on the Uncompahgre Plateau, Colorado. Colorado Division of Wildlife Technical Publication No. 40. Anderson, C. R., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Bauer, J. W., K. A. Logan, L. L. Sweanor, and W. M. Boyce. 2005. Scavenging behavior in puma. The Southwestern Naturalist 50:466-471. Beausoleil, R. A., G. M. Koehler, B. T. Maletzke, B. N. Kertson, and R. B. Wielgus. 2013. Research to regulation: cougar social behavior as a guide for management. Wildlife Society Bulletin 37:680688. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Choate, D. M., M. L. Wolfe, and D. C. Stoner. 2006. Evaluation of cougar population estimators in Utah. Wildlife Society Bulletin 34:782-799. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife, Denver. Colorado Division of Wildlife. 2007. Colorado mountain lion management data analysis unit revision and quota development process. Colorado Division of Wildlife, Denver. Cooch, E., and G. White. 2015. Program MARK- a gentle introduction, 14th edition. Colorado State University, Fort Collins. Cooley, H. S. 2008. Effects of hunting on cougar population demography. Ph.D. Dissertation. Washington State University, Pullman. Hornocker, M. G. 1970. An analysis of mountain lion predation upon mule deer and elk in the Idaho Primitive Area. Wildlife Monographs No. 21. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53:457-481. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Lambert, C. M. S., R. B. Wielgus, H. S. Robinson, D. D. Katnik, H. S. Cruickshank, R. Clarke, and J. Almack. 2006. Cougar population dynamics and viability in the Pacific Northwest. Journal of Wildlife Management 70:246-254. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Laundré, J. W., L. Hernández, and S. G. Clark. 2007. Numerical and demographic responses of lions to changes in prey abundance: Testing current predictions. Journal of Wildlife Management 71:345355. Laundré, J. W., and L. Hernández. 2007. Do female pumas (Puma concolor) exhibit a birth pulse? Journal of Mammalogy 88:1300-1304. Lindzey, F. G., W. D. Van Sickle, S. P. Laing, and C. S. Mecham. 1992. Cougar population response to manipulation in southern Utah. Wildlife Society Bulletin 20:224-227. Logan, K. A., L. L. Irwin, and R. Skinner. 1986. Characteristics of a hunted mountain lion population in Wyoming. Journal of Wildlife Management 50:648-654. 18 �Logan, K. A., and L. L. Sweanor. 2001. Desert puma: Evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D. C. Logan, K. A. 2004. Colorado lion research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center. Logan, K. A. 2008. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K. M. 1983. Relationships between a mountain lion population and hunting pressure in western Montana. Master’s Thesis, University of Montana. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Ruth, T. K., M. A. Haroldson, K. M. Murphy, P. C. Buotte, M. G. Hornocker, H. B. Quigley. 2011. Cougar survival and source-sink structure on Greater Yellowstone’s Northern Range. Journal of Wildlife Management 75:1381-1398. Spreadbury, B. R., K. Musil, J. Musil, C. Kaisner, and J. Kovak. 1996. Cougar population characteristics in southeastern British Columbia. Journal of Wildlife Management 60:962-969. Stoner, D. C., M. L. Wolfe, and D. M. Choate. 2006. Cougar exploitation levels in Utah: Implications for demographic structure, population recovery, and metapopulation dynamics. Journal of Wildlife Management 70:1588-1600. Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Yeager, K., B. Kendall, M. Alldredge. 2013. The Use of Lures, Hair Snares, and Snow Tracking as NonInvasive Sampling Techniques to Detect and Identify Cougars. Colorado Cooperative Fish and Wildlife Research Unit, Ft. Collins. Zar, J. H. 1984. Biostatistical analysis. Second edition. Prentice Hall, Englewood Cliffs, New Jersey. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 19 �Table 2. Count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during reference years 4 and 5 (RY4, RY5) and treatment years 1-5 (TY1-TY5). Also indicated * is the population projection for RY5 due to lack of a reliable count (see text), Uncompahgre Plateau study area, Colorado. Period & Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Study Area region Adults Female Male Subadults Female Male Female East slope 10 4 3 4 4 West slope 6 4 2 0 1 subtotals 16 8 5 4 5 Total Independent Pumas = 33: 21 females, 12 males. Cubs = 20-21 East slope 11-13 5-6 2-4 0-1 2 West slope 9-10 4 1-2 1 3 subtotals 20-23 9-10 3-6 1-2 5 Total Independent Pumas = 37, *45 East slope 16 10 1 2 1 West slope 14 10 0 3 3 subtotals 30 20 1 4 4 Total Independent Pumas = 56: 31 females, 25 males. Cubs = 19-24 East slope 15 5 3 2 7 West slope 15 7 2 3 2 subtotals 30 12 5 5 9 Total Independent Pumas = 52: 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 West slope 14 5 3 5 1 subtotals 27 9 4 8 5 Total Independent Pumas = 48: 31 females, 17 males. Cubs = 19 East slope 15 4 3 2 4 West slope 10 5 3 0 2 subtotals 25 9 6 2 6 Total Independent Pumas = 42: 31 females, 11 males. Cubs = 24 East slope 10 6 3 6 6-7 West slope 13 4 1 1 1 subtotals 23 10 4 7 7-8 Total Independent Pumas = 44: 27 females, 17 males. Cubs = 25-28 Cubs Male 4 2 6 Unknown sex 7 2-3 9-10 5 2 7 5 4 9 3 3 7 4-8* 5-6 9-14 9 5 14 7 9 16 2 2 4 4 6 10 4 5 9 3 6 9 2 3 5 2 11-13 13-15 Table 3. Pumas killed by hunters on the study area during the treatment period, Uncompahgre Plateau, Colorado. Actual No. of No. Independent Percent harvest of Treatment Adult Adult Subadult Subadult pumas pumas in Independent Period Year Female Male Female Male Quota killed count pumas 8 9 56 16.1 TY1 2 5 1 1 8 8 52 15.4 TY2 0 5 2 1 8 8 48 16.7 TY3 3 1 0 4 5 5 42 11.9 TY4 2 2 0 1 5 5 44 11.4 TY5 1 3 0 1 subtotals 8 16 3 8 20 �Table 4. Causes of death in adult, subadult, and cub pumas in the reference and treatment periods, Uncompahgre Plateau, Colorado. Reference Period Adults (21F,11M at Females Females Males Males Total Total risk Number Percent Number Percent Number Percent Strife 3 50 1 100 4 57 Other natural 1 16.7 0 0 1 14.3 Vehicle strike 1 16.7 0 0 1 14.3 Depredation control 1 16.7 0 0 1 14.3 Illegal kill 0 0 0 0 0 0 Hunting 0 0 0 0 0 0 Subadults (8F,14M at risk) Strife 0 0 0 0 0 0 Other natural 1 50 0 0 1 33.3 Vehicle strike 1 50 0 0 1 33.3 Depredation control 0 0 0 0 0 0 Illegal kill 0 0 0 0 0 0 Hunting 0 0 1 100 1 33.3 Cubs (28F,27M at risk) Infanticide 9 75 4 100 13 81.3 Predation 1 8.3 0 0 1 6.2 Other unknown natural 1 8.3 0 0 1 6.2 Starvation 0 0 0 0 0 0 Vehicle strike 1 8.3 0 0 1 6.2 Depredation control 0 0 0 0 0 0 Illegal kill 0 0 0 0 0 0 Hunting 0 0 0 0 0 0 21 �Table 4. Continued Adults (39F,22M at risk) Strife Other natural Vehicle strike Depredation control Illegal kill Hunting Subadults (19F,34M at risk) Strife Other natural Vehicle strike Depredation control Illegal kill Hunting Cubs (28F,36M at risk) Infanticide Predation Other unknown natural Starvation Vehicle strike Depredation control Illegal kill Hunting Mauled by dogs Treatment Period Females Females Males Number Percent Number 3 14.3 0 7 33 0 2 9.5 1 2 9.5 0 0 0 1 7 33 14 Males Percent 0 0 0 0 6.7 93.3 Total Number 3 7 3 2 1 21 Total Percent 8.1 18.9 8.1 5.4 2.7 56.8 1 0 0 1 0 2 25 0 0 25 0 50 2 2 1 2 0 9 12.5 12.5 6.2 12.5 0 56.2 3 2 1 3 0 11 15 10 5 15 0 55 3 0 0 5 0 2 0 0 0 30 0 0 50 0 20 0 0 0 5 0 4 4 2 1 0 0 1 29.4 0 23.5 23.5 11.8 5.9 0 0 5.9 8 0 4 9 2 3 0 0 1 29.6 0 14.8 33.3 7.4 11.1 0 0 3.7 22 �Table 5. Adult puma survival modeling results, Uncompahgre Plateau, Colorado. Model Number ∆ AICc AICc wi Likelihood Parameters Deviance Model AICc {S(gender*period)} 396.9874 0 0.84055 1 4 162.0375 {S(gender+period)} 401.613 4.6256 0.0832 0.099 3 168.6719 {Sgender*year} 402.1608 5.1734 0.06327 0.0753 14 147.0023 {S{period)} 405.339 8.3516 0.01291 0.0154 2 174.4044 {S(gender)} 416.7478 19.7604 0.00004 0 2 185.8131 {S(.))} 417.3778 20.3904 0.00003 0 1 188.4475 {S(month)} 509.8345 112.8471 0 0 108 53.2893 {S(gender*month)} 716.7591 319.7717 0 0 216 0 Table 6. Puma adult, subadult, and cub annual survival rates, estimated from top model Sgender*period for each stage, Uncompahgre Plateau, Colorado. Adults (≥24 months old) Period Gender Average annual Lower 95% CI Upper 95% CI Survival estimate Reference Female 0.8599 0.7153 0.9345 Male 0.9593 0.7459 0.9942 Treatment Female 0.7415 0.6324 0.8230 Male 0.3971 0.2232 0.5692 Subadults (13-24 months old) Period Gender Survival estimate Lower 95% CI Upper 95% CI Reference Female 0.6303 0.2320 0.9058 Male 0.9233 0.6106 0.9893 Treatment Female 0.7026 0.4247 0.8832 Male 0.4272 0.2651 0.6071 Cubs (1-12 months old) Period Gender Survival estimate Lower 95% CI Upper 95% CI Reference Female 0.3439 0.1727 0.5683 Male 0.7132 0.4393 0.8875 Treatment Female 0.3906 0.2048 0.6147 Male 0.3020 0.1606 0.4944 * Over-dispersion parameter c-hat has to be estimated for the cub survival data. Table 7. Subadult puma modeling results, Uncompahgre Plateau, Colorado. Model Number Model AICc ∆ AICc AICc wi Likelihood Parameters Deviance {Sgender*period} 190.0683 0 0.48562 1 4 39.4874 {Speriod} 191.125 1.0567 0.28631 0.5896 2 44.5933 {Sgender+period} 192.1299 2.0616 0.17323 0.3567 3 43.5771 {S.} 195.2243 5.156 0.03687 0.0759 1 50.7065 {Sgender} 196.6757 6.6074 0.01784 0.0367 2 50.1439 {Smonth*period} 206.5767 16.5084 0.00013 0.0003 24 13.888 {Smonth*period*gender} 266.4878 76.4195 0 0 48 0 23 �Table 8. Subadult puma survival rates estimated with second-ranked model Speriod, females and males combined, Uncompahgre Plateau, Colorado. Subadults (13-24 months old) Period Survival estimate Lower 95% CI Reference 0.8371 0.5991 Treatment 0.5152 0.3685 Upper 95% CI 0.9464 0.6594 Table 9. Cub puma modeling results, Uncompaghre Plateau, Colorado. Model Number Model AICc ∆ AICc AICc wi Likelihood Parameters Deviance {Sgender*period} 317.1119 0 0.3335 1 4 309.0458 {S{period} 318.0671 0.9552 0.20686 0.6203 2 314.0473 {S{.} 318.1293 1.0174 0.20053 0.6013 1 316.1227 {Sgender+period} 319.4672 2.3553 0.10272 0.308 3 313.4276 {S{gender} 319.6242 2.5123 0.09496 0.2847 2 315.6045 {S{gender+Birthmonth} 320.8604 3.7485 0.05118 0.1535 3 314.8208 {Sgender*period}+birthmonth} 324.8551 7.7432 0.00695 0.0208 5 314.7558 {Smonth*period} 326.3474 9.2355 0.00329 0.0099 24 276.2961 {Smonth*period*gender} 367.9388 50.8269 0 0 48 263.5538 Table 10. Cub puma survival rates estimated with second-ranked model Speriod, females and males combined, Uncompahgre Plateau, Colorado. Over-dispersion parameter c-hat has to be estimated for the cub survival data. Cubs (1-12 months old) Period Survival estimate Lower 95% CI Reference 0.4999 0.3363 Treatment 0.3392 0.2187 24 Upper 95% CI 0.6635 0.4849 �Independent Pumas 60 - - , - - - - - - - - -~ - -.....----- - - - - - - - 50 + - - - - - ---F-- --=--....a;;::. - ------,,.,---- ----44- :Q 40 E ~ 30 + - - - - - - - - - - - - - - - - - - - - - 10 - + - - - - - - - - - - - - - - - - - - - - 0 +-----~-----~--~--~-~ RY4 RYS TY2 TY1 TY4 TY3 TY5 Study Years Figure 2. Counts of independent pumas, Uncompahgre Plateau, Colorado. Counts in RY4 and TY1 to TY5 are from ground surveys and capture efforts. The count for RY5 is biased low because capture efforts were insufficient due to lack of personnel to thoroughly search the study area (see text). Change in Number of Pumas 60 50 ~ 44 40 E :::J 36 .... c.. 30 33 0 0 Z 20 10 0 TY1 TY2 TY3 TY4 Treatment Years - Independent Pumas ...,._Adult Pumas Figure 3. Change in numbers of independent and adult pumas, Uncompahgre Plateau, Colorado. 25 �20 18 16 1.4 ~ .~~10 .2-J 12 ,- I- - f-- f--- - 0 0 % 8 6 4 2 0 - - -,- Jan. Feb. Mar. Apr. May June July Aug, Sep. Oct. lfov. Dec. Figure 4. Puma births (black bars) detected by month from May 19, 2005 to September 30, 2014 (n = 66 litters of 33 females; 60 litters were examined at nurseries when cubs were 25-45 days old, 4 litters were confirmed by tracks of ≥1 cubs following GPS- and VHF-collared mothers and 2 litters by remains of cubs of 2 GPS-collared mothers when cubs were ≤45 days old, Uncompahgre Plateau, Colorado. 26 �APPENDICES Appendix I. ACUC Capture and Handling Forms and Protocols File # _________________ Revised Date ______________ (ACUC Secretary will supply) COLORADO PARKS AND WILDLIFE ANIMAL CARE AND USE COMMITTEE (CPW ACUC) FORM FOR REVIEW OF NEW RESEARCH PROJECTS 1. Principal Investigator (s): Dr. Kenneth A. Logan, Mammals Researcher, CPW. Phone: 970-252-6013(o) or 970-275-3227(c) E-mail: ken.logan@state.co.us 2. 3. All investigators (including all individuals involved in implementing research: Principal investigator Ken Logan (CPW), all CPW technicians and other houndsmen. Location of facility or study area: The study area is on the Uncompahgre Plateau in western 4. Beginning date: December 1, 2008. 5. Ending date: April 1, 2014. 6. Title of project: Assessing Effects of Hunting on a Puma Population on the Uncompahgre Plateau, Colorado. 7. Species of animal (s): Puma concolor 8. A study Plan or Prospectus describing each research or pilot project is required with this form. Is the Study Plan attached? Yes _X_ No ___ 9. Rationale for use of this animal model: a. Explain why other models (e.g. nonanimal models, in vitro techniques) are inappropriate. This study pertains specifically to puma population dynamics and attendant effects of hunting off-take. It is intended to provide wildlife managers with useful information for the management of pumas in Colorado. b. If not a species specific study, why is this the most appropriate species for this research? Colorado in areas west and southwest of Montrose. The study area is the South Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties). The study area includes about 2,200 km2 of the southern halves of GMUs 61 and 62, and about 155 km2 of the northern edge of GMU 70. The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. c. If capturing wild animals for pen research, why is this source most appropriate? 27 �10. 11. If the study will use wild animals, describe capture and transport methods: Please refer to the attached study plan Puma capture and marking (pages 13-15, 18, 24) and the Mountain Lion Capture and Handling Guidelines. Location of capture: Pumas will be captured on the study area described in question 3 above. 12. Indicate number of animals to be used _20-30 pumas/year_. Provide a brief justification (or page reference in Study Plan) for sample size selected: Please see study plan sections Puma capture and marking, Population monitoring, and Population Size (pages 13-19). 13. By signing this form, you are verifying that all persons involved in this project are adequately trained. Briefly describe the training process(es) and list personnel responsible for animal care and handling: K. Logan, S. Young, have all been trained in and have directly captured, immobilized, and sampled pumas. All new technicians and houndsmen will receive training on pumas by principal investigator Ken Logan. 14. Provide a detailed description of the procedures and manipulations of animals, including an end point (if necessary) at which animals will be removed from experiment or be euthanized. (If described in Study Plan or Prospectus, provide reference page numbers.) If administration of anesthesia and /or surgery is part of the procedure, identify who will perform these tasks: Please see study plan section Puma capture and marking (pages 13-19). 15. Are the levels of pain and suffering, stress, discomfort, deprivation, etc., to be experienced by experimental animals greater than normally associated with handling, administration of therapeutics by commonly used methods, or routine venipuncture? Yes __ No _X_ If answered yes, attach a detailed justification and indicate here the date of search, some of literature search, date range searched, and key words and combination of key words searched to document the lack of alternative methods: 16. 17. Will pain and suffering be controlled? Yes ____ No ____ N/A _X__ If answered no, attach a detailed justification. Describe how pain and suffering not associated with routine handling will be controlled. a. Methods and dosage of anesthesia to be used: N/A b. Methods and dosage of analgesia to be used: N/A c. Methods and dosage of tranquilization to be used: N/A The attending veterinarian must be consulted when planning projects where handling of any animal will occur. Do this prior to submitting this application. Date consulted_________ Does the proposed project include planned euthanasia of animals? Yes _____ No _X__ 28 �Signing below assures that all investigators have reviewed the CPW ACUC Euthanasia Guidelines and that investigators will use appropriate methods for humanely destroying animals involved in their study. Please indicate the criteria for and methods of euthanasia to be used in this study: Date: ________ 18. Signed: ___________________________________ Principal Investigator Signing below assures that the planned research does not unnecessarily duplicate previous research on the subject and species proposed for study. Date: ________ Signed: ___________________________________ Principal Investigator 29 �Appendix II. Puma Population Model and Simulations Research on the Uncompahgre Plateau Puma Project from December 2004 to July 2007 provided estimates of puma population structure and parameters for a model-based approach developed by CPW biometrician Dr. P. Lukacs and Mammals Researcher Dr. K. Logan to examine options for the design of the remainder of this research, and as a preliminary assessment of the CPW puma management assumptions. Puma Population Modeling Our puma population projections for the study area involved an age-structured, deterministic, discrete time model. The additive puma population model structure is: Nt+1 = Adult Females = (SAF * NAFt + SSF * NSFt) * (1 – HAFt+1) + Adult Males = (SAM * NAMt + SSM * NSMt) * (1 – HAMt+1) + Subadult Females = ((r * SC * NCt) * (1 – HSFt+1)) * PISF/ESF + Subadult Males = (((1 − r) * SC * NCt) * (1 – HSMt+1)) * PISM/ESM + Cubs = Lỹ * AFR * NAFt+1 Terms: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). PI/E = Ratio of progeny + immigrants/emigrants. Lỹ = Average litter size. AFR = Proportion of adult females giving birth to new litters each year. Basic assumptions of the model include: 1) expected puma population projections and annual rates of increase (i.e., lambda) are conditional on the assigned puma population structure and demographic estimates, and 2) no density dependent responses are built into the model. In reality, density dependence probably operates in puma population dynamics, with competition for food regulating adult female density and competition for mates regulating adult male density (Logan and Sweanor 2001). We parameterized the model with data gathered on the pumas on the study area during the previous 3.7 years. The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table AI.1). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radio-collared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table I.2). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature (Table 2), because our current sample sizes (i.e., number of individuals and years) were not adequate for realistic estimates (i.e., estimates from our data were 1.0 for adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to 30 �emigrants as a model input was from the literature, because such data were scarce and does not exist for Colorado (all references in Table AI.2). We preferred using the population characteristics and parameter estimates gathered in the current research effort, because this is the puma population we intend to manipulate to assess current CPW puma management strategies. Table AI.1. Minimum puma population count on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008 (RY4). The minimum count involves counting all radio- and GPS-collared pumas, all other marked pumas, and all presumably unmarked pumas detected on the study area during the period. Presumed unmarked pumas could be marked with ear-tags and tattoos. Their tracks and movements could be separated from movements of radio- and GPS-collared pumas. Or they exhibited evidence that could separate them from other local marked pumas from their tracks (i.e., distinguishable by sex, number of cubs and/or relative size of cubs varied). Region East slope West slope Totals a Adults Subadults Female Male Female Male 10 4 3 4 6 4 2 0 16 8 5 4 Total Independent Pumas = 33a,b Female 4 1 5 Cubs Male 4 2 6 Unknown sex 7 2-3 20-21 Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. Table AI.2. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Parameter Adult age Estimate 2+ years Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas of both sexes 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radiocollared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). 31 �Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). This result supported Logan and Sweanor 2001:69, n = 148). Proportion of adult females giving birth each year (n = 3 years for n = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits/Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). Results of Puma Population Simulations Expected minimum population sizes for independent pumas for RY5 and TY1 conditional upon the number of independent pumas counted in Reference Year 4 (RY4) and the model input parameters and assumptions (given in Tables AI.1 and AI.2). Table AI.3. Year RY4 RY5 TY1 Adult Female 16 18 23 Puma Population Size Subadult Male Female 8 5 10 9 14 8 Male 4 8 8 Cub 20 33 42 32 Independent Pumas Total 33 count 45 projected 53 projected �Appendix III. MOUNTAIN LION HUNTER SURVEY MOUNTAIN LION HUNTER SURVEY EXPERIMENTAL LION HARVEST UNCOMPAHGRE PLATEAU STUDY AREA- GMUs 61, 62, and 70 Hunter Name: ___ License No.: CID No.: 1. Please circle the days on which you hunted (please count partial days hunting as full days) November: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 December: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 January: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 2. Name the drainages and mesas where you hunted __________________________________________________ ____________________________________________________________________________________________ ____________________________________________________________________________________________ 3. Did you hunt with hounds? YES or NO (circle one) 4. Did you hunt with an outfitter? YES or NO (circle one) 5. Do you consider yourself to be a SELECTIVE hunter or a NON-SELECTIVE hunter? (read explanation below, then circle one) A SELECTIVE hunter is one that purposely is hunting for a specific type of legal lion, such as a male, large male, or large female, and therefore attempts to distinguish between male and female tracks, large and small males or females before taking the animal, and is willing to pass up lions that are detected from tracks or when treed. A NON-SELECTIVE hunter is one that intends to take whatever legal lion is first encountered or caught, with no desire for sex or size. 6. What was the sex of the lion that made the first set of tracks you encountered that were less than one day old? FEMALE  MALE  Did you pursue the lion to harvest it? YES  NO  NOTE: Adult & subadult male lions usually have hindfoot heel pad widths greater than or equal to 2 1/16 in. (52mm) wide. Adult & subadult female lions usually have hindfoot heel pad widths less than or equal to 1 15/16 in. (50 mm) wide. 7. Of the total tracks you encountered that were less than one day old, how many were male (_____) and female (_____) lions? (write number on the blank) 8. How many tracks were of females followed by cubs? _________ 9. How many times did you pursue lions with dogs? _________ 10. How many times did you tree or bay lions with dogs? _________ 11. How many of the lions treed and bayed were males (________), females (________), and cubs (________)? 12. Were any of the lions marked with a visible collar or ear-tags? YES or NO (circle one) If YES, describe the collar color, ear-tag color and number on each lion and its sex & age (i.e., male or female; adults ≥2 yrs. or subadults ~1-2 yrs.; indicate male or female and adult or subadult for each) ___________________________________________________________________________________________ 13. Describe the non-marked lions you caught (e.g., adult male, adult female, subadult male, subadult female) and list here: ___________________________________________________________________________________ 14. Did you harvest a lion? YES or NO (circle one) If YES, what was it? MALE or FEMALE (circle one). ADULT (≥2 yrs.) or SUBADULT (~1-2 yrs.) (circle one) 15. What was the seal number? ____________________ 16. Did marks (e.g., collar, ear-tag) on the lion influence your decision to harvest or not harvest the animal? (check one)  TO HARVEST  NOT TO HARVEST  NO INFLUENCE AT ALL 17. Did snow facilitate your harvest? YES if the puma was tracked on snow. NO if the puma was tracked on ground without snow. (circle one) 33 �Compliance Endangered Species Act This research will involve trapping mountain lions using hounds, cage traps and snares. It is extremely unlikely that any listed species under the Endangered Species Act will be inadvertently captured. However, in the unlikely event that a lynx or wolverine was captured, we will immediately release the animal unharmed. We will utilize existing roadways on public and private lands to access areas for running hounds and setting traps. Other field work on this project will comprise telemetry monitoring primarily from roads and fixed wing aircraft, minimizing potential for disturbing any listed species. No activities associated with this project pose a threat to the well-being of any listed species in Colorado. Animal Welfare Act The project is approved through Colorado Division of Wildlife’s Animal Care and Use Committee (Project #08-2004 and #03-2007). NEPA This research falls under a Categorical Exclusion as set forth in Title 40, Section 1508.4 of the Code of Federal Regulations (i.e., 40 CFR 1508.4) because the actions in this research do not involve significant environmental impacts. Other Landscape-Oriented Federal Acts This research will have no impact on the landscape, and therefore, will not violate provisions of other Federal Legislation governing floodplains and wetlands, historical sites, and prime and unique farmlands. Americans With Disabilities Act When hiring personnel as part of this project, qualified individuals will not be discriminated against based on disability. No structures or access points will be constructed as part of this research, and thus accessibility is not applicable. 34 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 3 Federal Aid Project No. W-204-R5 : : : : : Parks and Wildlife Mammals Research Carnivore Conservation Assessing Effects of Hunting on a Puma Population on the Uncompahgre Plateau, Colorado Period Covered: July 1, 2015  June 30, 2016 Mountain lion population responses to sport-hunting on the Uncompahgre Plateau, Colorado Principal Investigator: Kenneth A. Logan, Ken.Logan@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. Colorado Parks and Wildlife (CPW) conducted a 10-year (2004−2014) study on effects of sport-hunting on a mountain lion population on the Uncompahgre Plateau. The purpose was to examine effects of hunting on a lion population, to evaluate assumptions used by CPW in lion management, and learn how lion hunter behavior may influence harvest. This report summarizes the latest analysis of the effects of hunting and other causes of mortality on a lion population. Analyses are ongoing and are expected to provide reliable information for application in lion management in Colorado. The study was designed with a reference period (years 1−5, RY1−RY5) without mountain lion hunting, and a treatment period (years 6−10, TY1−TY5) with lion hunting. The reference period began December 2004 and ended October 2009. The treatment period began November 2009 and all data collection ended in December 2014. The study area was on the Uncompahgre Plateau in Mesa, Montrose, Ouray, and San Miguel Counties. The 2,996 km2 (1,157 mi.2) study area included the southern halves of Game Management Units (GMUs) 61 and 62, and the northern edge of GMU 70. The Uncompahgre Plateau Study Area GMU (UPSA from here on) was in the largest 8% of the 185 GMUs used to manage lions in Colorado (average = 1,457 km2, range = 71−4,460 km2). Because this study was designed to represent a lion population segment on a Colorado GMU scale, the study area was managed as its own GMU so that inferences from the study could be interpreted at the GMU scale. 1 �From December 2, 2004 to October 30, 2014 we captured about 256 individual lions a total of 440 times on the UPSA. We individually marked 226 lions: 109 in the reference period and 115 in the treatment period. Marked lions provided known-fate data on 75 adults, 75 subadults, and 118 cubs. In addition to the lions captured by our research team during the treatment period, lion hunters captured and killed a total of 35 lions, including 8 adult females, 16 adult males, 3 subadult females, and 8 subadult males. Lion hunters also reported having captured and released 30 independent lions, with their reported gender identification of 19 females and 11 males. During the reference period without sport-hunting as a mortality factor the population of independent lions comprised of adults and subadults increased from a low of 33 lions counted in RY4 to a high of 56 lions counted in TY1 (Fig. 1). This indicated that lion management on the study area before this study probably suppressed the lion population. Along with the population increase during the reference period, adult lion survival was high and the age structure of independent lions increased. In the reference period, of the 32 (21 females, 11 males) adult radio-collared lions we monitored 7 adult lions died but none from hunting. Causes of death were attributed to: 5 natural causes (4 intra-specific strife, 1 unknown), 1 vehicle strike, and 1 depredation control. Of the 22 subadults (8 females, 14 males) providing known-fate data, 3 died. One male that had dispersed from the study area was killed by a hunter that did not see the tags (tagged lions that ranged north of the study area were protected from hunting during the reference period). Other causes of death in subadults were 1 natural cause (trampled by elk) and 1 vehicle strike. Of 55 radiocollared cubs (28 females, 27 males) monitored in the reference period, 16 died. Causes included: 13 infanticide, 1 predation, 1 unknown natural, and 1 vehicle strike. In the reference period natural causes dominated deaths of adults and cubs (71.3% and 93.8%, respectively), but 2 of 3 subadult deaths were from human causes. The treatment period was managed with mountain lion sport-hunting. TY1 was the first year that hunting influenced the lion population after 5 years of no hunting, and it was marked with the highest count of independent lions (56) on the study area. TY1−TY3, the lion harvest rate was set with a design quota of 8 lions to test if a 15% harvest of independent lions with 35−45% independent females in the harvest would result in a stable-to-increasing population. However, the expectation that a 15% harvest results in a stable-to-increasing population was not supported as the population of independent lions declined steadily from 56 in TY1 to 42 by TY4 (Fig. 1). Results from TY1−TY4 indicated that reducing a lion population with hunting is achievable at a 15% harvest rate with other human-caused and natural mortality operating on the population. The lion population in the treatment period was expected to continue to decline if the quota remained at 8 lions. Therefore, in an effort to find a harvest rate useful to managers that might result in a stable-to-increasing population for the remainder of the study, the quota was reduced to 5 lions. This quota represented about 11−12% harvest rate of independent lions for TY4 and TY5. 2 �Sport-hunting was the most important cause of death for independent lions during the treatment period. Of the 61 adults (39 females, 22 males) we radio-monitored during the period, 37 died. Hunting caused 56.8% of adult deaths (n = 21: 14 males, 7 females), followed by natural causes (27%; n = 10: 7 unknown with 6 probably disease-related and 1 due to starvation with senescence, 3 intra-specific strife), and other human causes (16.2%; n = 6: 3 vehicle strike, 2 depredation control, and 1 illegal kill). Of the 53 subadults (19 females, 34 males) providing known-fate data, 20 died. Hunting caused 55% of the subadult deaths (n = 11: 9 males, 2 females). Natural mortality followed in importance with 25% (n = 5: 3 intra-specific strife, 2 other natural), then closely by 20% other human causes of death (n = 4: 3 depredation control, 1 vehicle strike). Combining adult and subadult lion deaths in the treatment period, human causes were 73.7 % (i.e., 42/57*100), of which hunting caused 76.2% (i.e., 32/42*100) and other human causes comprised 23.8% (10/42*100). Of the 63 radio-collared cubs (27 females, 36 males) monitored, 27 died. Mortality causes in the cubs included: 9 infanticide, 4 other natural, 2 vehicle strike, 3 depredation control, and 9 starvation. The 9 cubs starved after the deaths of 5 mothers due to: hunting (2 mothers involving 3 cubs), depredation control (1 mother with 3 cubs), and natural causes (2 mothers involving 3 cubs). Natural mortality comprised the majority of cubs deaths (15/27*100 = 55.6%). But, human-caused cub deaths in the treatment period increased to 44.4% (12/27*100 = 44.4%) from 6.2% in the reference period. In the treatment period, the population of independent lions declined from a total count of 56 in TY1 to a low of 42 in TY4, a 25% decline after three hunting seasons (Fig. 1). The abundance of adult females declined 23.3% by TY5. Adult males declined 55% by TY3 and TY4, and 50% by TY5. The percentage of females in the harvest TY1−TY5 was 31.6%; comprised of 23% adult females and 8.6% subadult females. The remainder of the harvest was comprised of adult males (45.7%) and subadult males (22.9%). After we reduced the quota to 5 for TY4 and TY5, the abundance of independent pumas seemed to stay in a low phase and may have slightly increased (Fig. 1). Hunting in surrounding GMUs also contributed to the decline in the abundance of independent lions on UPSA. Ten radio-collared independent lions (2 adult females, 7 adult males, 1 subadult female) included in treatment year winter counts were killed by hunters in adjoining GMUs 61 North, 62 North, 65, and 70 because those lions had home ranges that extended beyond the boundaries of UPSA. Those lions were counted in the hunting quota in the adjoining GMUs, not UPSA. Including these deaths off the study area, the percent of hunting kill from TY1−TY5 ranged from 11.4%−25% (average = 18.2%) of independent lions in winter counts on the UPSA. The actual hunter-kill of the number of independent lions during TY1−TY3 ranged from 17.3−25% (average = 21.8%), and was associated with the population decline phase. During TY4−TY5 the actual hunter-kill was 11.4−19.0% (average = 15.2%), and was associated with the low population phase. We used an information-theoretic approach and Akaike’s Information Criterion to rank survival models with and without the treatment effect for adults, subadults, and cubs. The hunting treatment was indicated as an important factor explaining variation in adult and subadult 3 �male lion survival rates. Average annual survival rates of adult male lions declined significantly from 0.96 in the reference period to 0.40 in the treatment period. Likewise, subadult male lion survival rates declined significantly from 0.92 in the reference period to 0.43 in the treatment period. Although average annual adult female lion survival in the reference period, 0.86, was not statistically different than in the treatment period, 0.74, the decline in the abundance of adult females by 23.3% from TY1−TY5 suggested that the lower survival rate during the treatment period was biologically significant. Subadult female survival in the reference period, 0.63, was not statistically different from survival in the treatment period, 0.70. For cubs, models indicated that whether the dam lived or died was the single most important factor affecting cub survival. For the entire study period, the rate of cub survival to the subadult stage was 0.45. Female cub survival, 0.42, was not statistically different than male cub survival, 0.48. Age structure of independent lions declined from TY1−TY5. After 5 years of no hunting, the younger and up to middle aged (i.e., 1−5 years old) lions comprised the majority of the population and with both adult females and males being represented up to the oldest ages (i.e., >5−10+ years old). After 5 years of hunting, adult males >5 years old were eliminated from the age structure. Average litter size in the reference period, 2.76, was not statistically different from the treatment period, 2.38. Likewise, parturition rate for adult females in the reference period, 0.63, was not statistically different from the treatment period, 0.48. Sex ratio of cubs born in the reference or treatment periods, and in the study overall was not statistically different from parity. Management Implications 1) In the GMU-based mountain lion management structure in Colorado, a design harvest of ≥15% of independent lions with an average of ≥20% adult (i.e., 2+ years old) females in the harvest, and with other human and natural causes of mortality operating on a relatively high density lion population, can cause population decline in as few as 3 years. Managers should consider accounting for all detectable (i.e., recorded) human-caused mortality in quotas when setting removal rates in respect to lion population management objectives. Other human causes of death comprised about 24% of the total human-caused mortality with the remaining 76% of deaths due to hunting in the treatment period on the UPSA GMU when the lion population declined and reached a low phase. 2) It can take up to 5 years for a lion population previously reduced to a low density to recover to a relatively high density after hunting has been eliminated. 3) Design harvests of up to 11−12% of independent lions with an average of <20% adult females in the harvest is expected to result in a stable, possibly increasing population, considering that other human- and natural-causes of mortality operate on the population. 4) Lion population segment management objectives and attendant harvest rates can affect lion abundance in the particular GMUs of interest and adjacent GMUs where lions have home ranges overlapping GMU boundaries because GMUs in connected lion habitat are not closed lion populations. 5) Lion harvest management structure which includes provisions for reducing lion population segments to achieve specified management objectives (e.g., reduce predation 4 �on livestock or mule deer populations) should also provide for lion population segments managed with conservative harvest rates to allow for stable or increasing lion population segments (i.e., source-sink management) to ensure overall lion population resiliency because of all the unknowns and uncertainties associated with lion population management, including lion abundance and effects of harvest and other human and natural causes of lion mortality in GMUs. 6) Management experiments and research involving lion population segments should consider potential effects of historical lion hunting on and around the study areas. When experimental designs require reference conditions, human-caused mortality to lions should be limited or eliminated if possible. Final publications from this work are in preparation and will be submitted to the USFWS Wildlife & Sport Fish Restoration Program upon completion. ~ 50 _ _ _ _ _ __ ,_:..___ _ _~ = --..-==--=--......,..,,..------- ~ ~ .......lo-'!!l~- · - 44 ~ 30 - -~ ----------------------- c... 40 - - -~ L -- - - - - - - - - - - - -~ ~---- ~ 4> Q. 4> -,::, 20 - - - - - - - - - - - - - - - - - - - - - - - - £ 0 z 10 - - - - - - - - - - - - - - - - - - - - - - - - 0 RY4 RY5 TY1 TY2 Study Year TY3 TY4 TY5 Figure 1. Trends in the population of independent mountain lions associated with no sporthunting in the reference period years 4 and 5 (RY4, RY5) and with sport-hunting in the treatment period years 1 through 5 (TY1−TY5), Uncompahgre Plateau, Colorado. The count data were gathered from November through April each winter in efforts to canvass the study area thoroughly to count the number of independent lions in addition to the lion harvest. These data represent the number of independent lions expected to have been at risk to hunting during the Colorado lion hunting season November through March each year. 5 �Colorado Parks and Wildlife July 1, 2016  June 30, 2017 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 3 Federal Aid Project No. W-204-R4 : : : : : Parks and Wildlife Mammals Research Carnivore Conservation Effects of Hunting on a Puma Population on the Uncompahgre Plateau, Colorado Period Covered: July 1, 2016  June 30, 2017 Author: K. A. Logan Personnel: J. Runge, Colorado Parks and Wildlife All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the authors. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Colorado Parks and Wildlife (CPW) conducted a 10-year (2004−2014) study on effects of sporthunting on a puma population on the Uncompahgre Plateau. The purpose was to examine effects of sporthunting on a puma population and evaluate assumptions used by CPW in puma management. The study design had a reference period (years 1−5) without puma hunting, and a treatment period (years 6−10) with puma hunting. The reference period began December 2004 and ended October 2009 and the treatment period began November 2009 and all data collection ended in December 2014. Counts of pumas in the study area population segment were made each winter coinciding with the Colorado puma hunting season from reference year 4 to treatment year 5. In the reference and treatment periods, 109 and 115 pumas were captured and marked, respectively. Those animals produced known-fate data for 75 adults, 75 subadults, and 118 cubs. Another 30 pumas were captured, but not handled for safety reasons. During the treatment period, hunters killed 35 independent pumas and captured and released 30 independent pumas. Responses of the puma population to sport-hunting and other causes of mortality were based on changes in four variables: 1) abundance of independent pumas, 2) survival of adult, subadult, and cub pumas, 3) reproduction rates, and 4) age structure of independent pumas. This report summarizes results of data analyses for use in puma management in Colorado and for preparation of manuscripts for publication on this research project. In the absence of sport-hunting in the reference period, the population of independent pumas increased by at least 70% and exhibited relatively high survival of independent pumas. There were clear effects of sport-hunting in the treatment period. Sporthunting was the major cause of death to independent pumas which added to other human-caused and natural mortality. The population of independent pumas on the study area declined 25% after the first 3 hunting seasons with a 15% design harvest of independent pumas on the study area. Actual harvests ranged from 15.4−16.7% of independent pumas and total independent puma mortality ranged from 16.1−20.8%. The sport-hunting harvest was reduced to 11−12% of independent pumas in the final two 1 �years of the treatment period with total independent puma mortality ranging 13.6−14.3% in which the population decline ceased and the population remained in a low phase. By the fifth year of the treatment period, the abundance of independent pumas had declined by 21%. The number of adult females and males declined by16.7% and 55%, respectively, by the fourth treatment year. By the the fifth year of the treatment period, the number of adult females and males had declined by 23.3% and 50%, respectively. The abundance of independent pumas on the study area was also influenced by sport-hunting off-take of pumas with home ranges that overlapped the study area and adjacent GMUs. During the treatment period, other human causes of death (excluding hunting) comprised about 24−29% of the total human-caused mortality (i.e., 74−81% of all deaths). Hunting comprised 71−76% of all human-caused deaths (depending on accounting method). Survival modeling results indicated that hunting was an important factor that explained adult and subadult male survival rates. The treatment period puma population exhibited statistically significant declines in survival rates of male adults (reference period S = 0.96 [95% CI = 0.746−0.994] , treatment period S = 0.40 [95% CI = 0.223−0.569]) and subadults (reference period S = 0.92 [95% CI = 0.611−0.989], treatment period S = 0.43 [95% CI = 0.265−0.607]). Changes in adult female (reference period S = 0.86 [95% CI = 0.715−0.935], treatment period S = 0.74 [95% CI = 0.632−0.823]) and subadult female (reference period S = 0.63 [95% CI = 0.232−0.906], treatment period S = 0.70 [95% CI = 0.425−0.883]) survival rates were not significantly different. However, the 23.3% decline in the abundance of adult females in the treatment period exhibited the biological significance of lower survival. The age structure for independent males declined in the treatment period, and reflected the lower survival and a selection of male pumas by hunters. There was no evidence of adequate compensatory immigration and local recruitment to offset mortalities of adult pumas. Puma cub survival was determined primarily by natural causes of mortality in the reference and treatment periods. The most important factor influencing cub survival was the fate of dams while cubs were dependent. Estimated probability of cub survival to the adult stage (i.e., 2 yr. old) in the reference period was 0.39. Estimated probability of cub survival to the adult stage in the treatment period was 0.22. Average litter sizes (reference period = 2.76 [SE = 0.1806, 95% CI = 2.41−3.12], treatment period = 2.38 [SE = 0.1972, 95% CI = 1.99−2.76]) and parturition rates (reference period = 0.63 [SE = 0.068, 95% CI = 0.49−0.75], treatment period = 0.48 [SE = 0.057, 95% CI 0.37−0.59]) were not statistically different in the reference and treatment periods. There was no evidence of compensatory reproduction in the treatment period. Therefore the most important factor associated with the decline in the abundance of independent pumas on the study area was hunting-caused mortality, which can be regulated by management. Management implications are listed at the end of this report to inform future puma management and research in Colorado. Final publications from this work are in preparation and peer-review and the final report will be submitted to the USFWS Wildlife & Sport Fish Restoration Program by the next reporting period. 2 �WILDLIFE RESEARCH REPORT EFFECTS OF HUNTING ON A PUMA POPULATION ON THE UNCOMPAHGRE PLATEAU, COLORADO Kenneth A. Logan PROJECT NARRATIVE OBJECTIVES 1. Gather data on puma population abundance, sex and age structure, vital rates (i.e., reproduction, age-stage survival rates, and emigration and immigration rates if possible), and agent-specific mortality in a non-hunted puma population phase and a hunted puma population phase for use in understanding puma population dynamics and evaluating and structuring puma harvest management and research approaches. 2. Test current CPW puma harvest-related assumptions that are applied to puma population segments in Colorado, and arrive at acceptable harvest levels intended to achieve population objectives, including increases, stability, and reductions in puma population segments. 3. Apply a hunting treatment to the puma population on the Uncompahgre Plateau study area designed to test CPW puma population management assumptions and learn about impacts of hunting on pumas. 4. Develop methods that detect changes in puma population abundance on the Uncompahgre Plateau study area that might be useful for monitoring changes in puma abundance in other puma habitats. SEGMENT OBJECTIVES 1. Arrange all the puma population data gathered during the 10-year study for data analysis. 2. Complete analysis of the puma population data and present it in written form for preparation for internal peer-review and for manuscripts submitted for publication. Introduction Colorado Parks and Wildlife (CPW) managers need reliable information on puma population biology to develop sound management strategies that address diverse public values and the CPW objective of actively managing pumas while “achieving healthy, self-sustaining populations” (Colorado Division of Wildlife 2002−2007 Strategic Plan:9). Moreover, the CPW 2015 Strategic Plan states Goal I to “Conserve wildlife and habitat to ensure healthy sustainable populations and ecosystems”. Active management of pumas includes managing for sustained populations to provide sport-hunting opportunity, and reducing puma populations to achieve specified management objectives, such as to reduce depredation on livestock and predation on mule deer, and to enhance public safety (Cooley et al. 2011). Thus, regulated sport-hunting is a main component of puma conservation and in addition to providing recreation it is intended to be used as a tool for managing pumas. Because sport-hunting is a major cause of death for pumas in hunted populations (Murphy 1983, Logan et al. 1986, Anderson et al. 1992, Ross and Jalkotzy 1992, Lambert et al. 2006, Stoner et al. 2006, Laundré et al. 2007), managers need information to better understand how hunting impacts puma populations to assess how management actions are working to meet management objectives. To improve the biological basis for managing pumas, the CPW began a process in 2000 to develop puma Data Analysis Unit (DAU) plans (Colorado Division of Wildlife 2007). DAUs are each comprised of several smaller Game Management Units (GMUs) and cover areas ranging 4,048−21,054 3 �km2. Conceptually, GMUs are the basic unit of puma harvest that is regulated with quotas on the number of pumas that are allowed to be killed by hunters each year and used to distribute harvest to achieve the management objective at the DAU level. The DAU plans involved a formulation to extrapolate an expected number of pumas on available habitat and the level of sport-harvest assumed to be acceptable to achieve one of two management objectives for each DAU: 1) to maintain a stable or increasing puma population, or 2) to suppress (i.e., reduce) the puma population. A series of “best biological judgments” and assumptions by CPW biologists on puma populations in DAUs was necessary because reliable and affordable methods for estimating puma population abundance in habitat were not available, and there was no information on impacts of hunting on Colorado puma populations. Consequently, biologists that developed DAU plans mostly used data from intensive puma population studies from other western states that were published in the literature and from information from studies of puma in Colorado (Anderson et al. 1992) as a guide. The information included estimates of puma population density, sex and age structure, population rates of increase, and expected impacts of harvest rates, and that information was extrapolated to expected puma habitat across Colorado. Colorado Parks and Wildlife (CDOW 2007) puma management assumptions included: 1) For areas managed for a stable or increasing puma population, acceptable total mortality (i.e., natural and human-caused) could fall in the range of 8 to 15% of the projected huntable population (i.e., adult plus subadult pumas) with female (i.e., adults and subadults) mortality in the range of 35 to 45% of the deaths. 2) For areas managed to suppress the puma population, total mortality could fall in the range of >15 to 28% of the projected huntable population with >45% of the deaths comprised of females. Other unknowns associated with these assumptions, in addition to the ones previously mentioned (i.e., puma abundance, effects of harvest) included undetected human-caused deaths and effects of natural mortality. All of these unknowns were consistently represented in the 19 puma DAU management plans developed by CPW biologists. The management objectives were to manage for stable or increasing puma populations in 17 of the 19 DAU plans. In plans with this objective, non-hunting mortality was assumed to be negligible, ranging from 0 to 7 pumas per year per DAU, with a median 0.5 pumas/year/DAU and an average 1.4 pumas/year/DAU for 17 of the 19 DAU plans that provided this information. Therefore, the total allowable mortality was generally considered to be comprised of sport-hunting off-take. Considering this, our focus was to investigate effects of sport-hunting off-take on a puma population when managed for a stable or increasing population. Specifically, we chose to investigate the effects that a 15% design harvest of independent pumas might have on a puma population, representing the maximum range of the assumption expected to result in a stable-to-increasing puma population (i.e., 8−15% harvest of the projected huntable population). Prior to the current puma research described in this report, none of the demographic prescriptions for management had been tested for their validity on a puma population segment at the GMU level in Colorado. Such testing is prudent because some assumptions made for management plans might be in error and cause puma populations to decline where the management objective is for stable or increasing puma populations. This objective is critical to providing resiliency in the puma population due to effects of hunting-caused mortality, which previous research has revealed was not compensatory (Cooley et al. 2009), and because other puma population segments would purposely be managed for suppression. Metrics from research in other western states support or are at variance with current CPW puma harvest guidelines for a stable to increasing population. Recent research in Wyoming indicated that a puma population could sustain a harvest comprised of 10 to 15% adult females, and population decline occurred when about 25% of adult females comprised the harvest (Anderson and Lindzey 2005:187). A Utah study found that a puma population declined when harvest exceeded 30% of the adults and subadults and comprised 42% females for 3 years (Choate et al. 2006). Another study in southern Idaho and 4 �northern Utah suggested that a harvest that included 15 to 20% of resident females probably would not reduce a puma population (Laundré et al. 2007). More recently, researchers in Washington modeled puma population dynamics and indicated that a 14% harvest of adult pumas was expected to result in a stable population and age structure (Beausoleil et al. 2013, Wielgus et al. 2013). A traditionally used reference claiming a sustainable puma harvest up to an extreme of 30% does not present any data to support that notion (Ashman et al. 1983). Another more recent reference has been used to support up to a 21.1% harvest rate on a puma population; but those authors clearly cautioned against using this metric because “potential effects of this harvest rate were offset by [three] interceding years when no cougars were shot. It is unknown what annual harvest rate could be sustained and still allow for stability or growth in the population size” (Ross and Jalkotzy 1992:424). Thus considering any of this information including our CPW assumptions, a population decline could occur if there is substantial over-projection error in the assumed puma abundance for an area and/or the applied harvest is excessive. This result is possible because actual puma population estimates are not available for any non-surveyed areas. In fact numbers used are at best educated guesses or biological judgments extrapolated over huge non-surveyed areas. This would be especially problematic if errors occurred for a substantial number of areas where the management objective is for a stable-to-increasing population. Thus, the state-wide strategic objective of managing for a healthy, self-sustaining puma population could be in jeopardy. This emphasized the need to quantify impacts of puma hunting on population parameters to structure guidelines that will likely achieve population objectives. Our current study serves as a field-based population-level test of the theoretical guidelines that could be derived from the literature and our management assumptions (previously cited). To address these information needs, CPW began this research in 2004 on the Uncompahgre Plateau to better understand puma population dynamics and effects of sport-hunting. The study was designed in two 5-year periods: a reference period (years 1−5) and a treatment period (years 6−10). The reference period provided baseline estimates on puma population abundance, sex and age structure, reproduction, survival, agent-specific mortality, and dynamics in representative puma habitat in Colorado where sport-hunting was not a cause of mortality. The treatment period occurred on the same study area and included manipulation of the puma population through the use of sport-hunting to provide information on the impact of hunting on a puma population. Study Area The study area for our puma research was on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties) in southwestern Colorado (Fig. 1). The 2,996 km2 (1,157 mi.2) study area included the southern halves of Game Management Units (GMUs) 61 and 62, and the northern edge of GMU 70. The Uncompahgre Plateau Study Area GMU (UPSA from here on) was in the largest 8% of the 185 GMUs used to manage pumas in Colorado (average = 1,457 km2, range = 71−4,460 km2). Because this study was designed to represent a puma population segment on a Colorado GMU scale, the study area was managed as its own GMU so that inferences from the study could be interpreted at the GMU scale. Highly developed road and all-terrain vehicle trail systems made the study area relatively highly accessible for puma research efforts. The UPSA was typical of puma habitat in Colorado. Vegetation cover transitioned from pinion-juniper (Pinus edulis-Juniperus spp.) covered foothills starting at about 1,700 m elevation to a Ponderosa pine (Pinus ponderosa) dominated woodland at mid-elevation, and up to the spruce-fir (Picea-Abies) and aspen (Populus tremuloides) forests at the highest elevations of 5 �about 3,000 m. Mid-elevation forests were interspersed with oak-serviceberry (Quercus spp.Amelancheir spp.) brushlands. Expansive sagebrush-steppe (Artemesia-grass) meadows and basins occupied mid-to-high-elevations, especially in the southern portion of the area. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) were the most abundant wild ungulates and were used as prey by pumas. Both mule deer and elk migrated from higher to lower elevations during winter due to deep snow at higher elevations. These deer also were subject to annual fall big game hunting seasons. Cattle and domestic sheep grazed on summer ranges and fed in low-elevation pastures in winter on UPSA. Sheep in particular were sometimes prey for pumas. People resided year-round along the eastern and western fringe of the area, and there was a growing residential presence especially on the southern end. Hobby animals kept by people, including alpacas, llamas, and goats, were also sometimes prey for pumas. Prior to our research, the puma population on the UPSA was subject to sport-hunting during a legal hunting season that extended from mid-November through March. The number of pumas allowed to be killed by hunters was limited by a quota. During the 5 previous years (1999-2003) an average of 12 independent pumas were reported killed by hunters on the study area (range = 9−17/yr.; unpublished puma mortality records, Colorado Parks and Wildlife, Denver). Based on the records of the gender and age stage (i.e., adults 2+ years old, subadults between 1−2 years old) of the pumas killed, 34% were classified as adult females; the rest were adult males and subadult females and males. During our research, portions of four abutting GMUs (61 North, 62 North, 65, and 70) were included in home ranges of adult radio-collared pumas that lived on the UPSA. Those GMUs also were subject to an annual puma sport-hunting season regulated by a quota. Consequently, those pumas with home ranges that overlapped the UPSA and adjacent GMUs were at risk of hunting mortality whether on or off the study area. As a result, some radiocollared pumas were killed off the study area during the treatment period (see later). During the 10 years of our research a total of 235 independent pumas were killed by hunters in those four surrounding GMUs, with a range of 14 to 29 pumas killed each year. As part of a puma management planning process in Colorado in 2004, the stated puma population management objectives were to manage for a stable puma population (i.e., not intended to increase or decline) in GMUs 61 North, 62 North, and 65, and a stable-to-increasing population in GMU 70 (Watkins 2004, Colorado Division of Wildlife 2004). Expected Results Information from our study will assist the Colorado Parks and Wildlife to improve puma management in Colorado. Results of the study will inform CPW biologists and managers about expected puma population dynamics and biological impacts of sport-hunting and other human-caused and natural mortality on a puma population in Colorado. The study also reveals puma life history traits and management effects useful for developing sound management strategies. Moreover, this study evaluated the current puma management structure and assumptions used in puma hunting management through the examination of data gathered directly from a GMU-level puma population manipulation. 6 �Approach The puma population on the Uncompahgre Plateau was studied for a total of 10 years divided into a 5-year reference period (i.e., reference years RY1−RY5) and a 5-year treatment period (i.e., treatment years TY1−TY5). In the reference period (November 2004 to October 2009) the study area was closed to puma hunting to provide baseline data on puma population dynamics without puma sport-hunting as a mortality factor, including: abundance, sex and age structure, survival, reproduction, agent-specific mortality, immigration and emigration. In addition, any radio-collared or ear-tagged pumas that ranged onto GMUs 61 North and 62 North (along the northwest boundary of the study area) were also protected from sport-hunting. The study area puma population was manipulated with sport-hunting during the treatment period (November 2009 to October 2014). This was an un-replicated case study on one geographic area having a before and after treatment effect design. This effort represented the largest number of pumas ever studied in a population segment in Colorado and an unprecedented opportunity for CPW to learn about puma population dynamics and effects of sport-hunting to apply to puma management. Field Methods Puma capture, marking, and sampling The capture, marking, and GPS- or VHF- collaring of individual pumas and subsequent monitoring was essential to a number of project objectives, including obtaining data on: population abundance, sex and age structure, vital rates, proportion of independent pumas marked in a camera grid, and puma movements to evaluate emigration and validity of GMUs. Pumas were captured year-round using 3 methods: trained dogs, cage traps, and by hand (for small cubs). All captured pumas were examined to ascertain gender and age, and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age pumas from New Mexico (Logan and Sweanor, unpubl. data) and later from known-age pumas in this study. Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas from New Mexico (Logan and Sweanor unpubl. data) and later from known-age pumas in this study. Ages of nurslings were estimated from apparent birthing dates indicated by GPS- and VHF-location data of collared mothers. Metric scale body measurements recorded for each puma included: mass (kg), pinna length, hind foot length, plantar pad dimensions, total length and tail length. Puma tissues were collected for genotyping individuals for parentage and relatedness analyses and disease screening, and included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), hair, and blood (30 ml from the saphenous or cephalic veins; only collected from pumas >10 weeks old). Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). All pumas were handled in accordance with approved Animal Care and Use Committee (ACUC) capture and handling protocols in ACUC file #08-2004 (Appendix I) and ACUC protocol #03-2007 titled, Mountain Lion Capture and Handling Guidelines. Captured and handled adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHFcollar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into at least one pinna to facilitate individual identification during direct recaptures and when retrieved dead pumas were inspected. We captured pumas with dogs trained by experienced houndsmen whose research activities were guided directly in the field by the principal investigator. During the reference period when no sporthunting was allowed, our capture team could operate usually from early snow accumulation in November 7 �until high temperatures and black bear emergence from hibernation impacted the dogs’ effectiveness in April or May. However, during the treatment period we inserted our dog-assisted capture operations after the UPSA puma-hunting quota was reached so as not to interfere with hunters’ activities, harvest preferences, and influence on the puma population. Our shorter capture time-span usually went from midDecember through April, but we made up for that by deploying two capture teams, one on the west-side and one on the east-side of the UPSA. None of the houndsmen involved in our capture teams were allowed to hunt pumas for sport on the UPSA during the treatment period. Pumas captured by dogs usually climbed trees to take refuge. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass. The drug was delivered into the caudal thigh or shoulder muscles via a Pneu-Dart® shot from a CO2-powered pistol (Pneu-Dart X-Caliber, Pneu-Dart Inc., Williamsburg, PA). A 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell. A researcher climbed the tree, fixed a rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once on the ground, the puma’s head was covered, its legs tethered, and vital signs monitored. Normal signs were considered: pulse ~70−80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95−104oF (Kreeger 1996). Treed pumas that could not be safely immobilized and handled were shot with a biopsy dart (8 mm long x 3 mm dia., Pneu-Dart Inc., Williamsburg, PA) fired from the CO2-powered pistol to obtain a skin sample from the caudal thigh or shoulder. These samples were used in a study of puma population genetics and genomics. Cage traps were used to capture adults, subadults, and large cubs. Pumas were lured into traps using road-killed or puma-killed ungulates (Bauer et al. 2005, Sweanor et al. 2008). A cage trap was set only if a target puma (i.e., an unmarked puma, or a puma requiring a collar change) scavenged on the lure. Researchers continuously monitored a set cage trap from about 0.5−1 km distance by using VHF beacons on the cage and door. This allowed researchers to respond to the captured puma within 30 minutes. Pumas were immobilized with Telazol injected into the caudal thigh or shoulder muscles with a pole or hand syringe. Immobilized pumas were restrained and monitored as described above. Small cubs (≤10 weeks old) were captured using our hands (covered with clean gloves) or with a catch pole. Cubs were restrained inside new burlap bags during the handling process and were not administered drugs. Cubs at nurseries were approached when mothers were away from nurseries as determined by radio-telemetry. Cubs captured at nurseries were removed from the nursery a distance of ~20–100 m to minimize disturbance and human scent at nurseries. Cubs were returned to the exact nurseries immediately after sampling processes were completed (Logan and Sweanor 2001). Adult and subadult pumas were fitted with GPS (approximately 400 g each) or VHF collars (approximately 300 g each (Lotek Wireless, Newmarket, Ontario, Canada). Budget constraints limited the number of GPS collars (~10−15) available annually. Therefore, GPS collars were fitted to primarily adult pumas. Other adult and subadult pumas were fitted with VHF collars. Our efforts were to locate all collared pumas once per week from fixed wing aircraft and as weather and scheduling conditions allowed for data on survival, agent-specific mortality, and location. We checked the live/dead signal status from collared pumas from the ground opportunistically when we operated within their home ranges. VHF and GPS collars had mortality modes set to alert researchers when pumas were immobile for 3 hours (VHF collars) to 24 hours (GPS collars) so that dead pumas could be found for data on survival and agentspecific mortality. Because subadult male pumas were not fully grown, they also received leather expansion links in their collars. The expansion links added 10−12 cm when open and allowed the collars to be worn safely into the adult stage. 8 �We attempted to collar all cubs in each observed litter with a small VHF transmitter mounted on an expandable collar (62 g, model 080, Telonics Inc., Mesa, AZ) when cubs weighed 1.3−10 kg. The collars were designed to operate for 10−12 months, and expanded to 54 cm circumference to accommodate growth. Cubs with mass ≥7 kg were fitted with a larger expandable collar (90 g, model 210, Telonics Inc., Mesa, AZ). The collars were designed to operate for 12−18 months and could expand to 54 cm circumference to accommodate growth. Cubs approaching the age of independence (~11−14 mo. old) were fitted with Lotek LMRT-3 VHF collars (~400 g) with leather expansion links that add 10−14 cm to the collar circumference to accommodate the adult puma neck size. These collars operated for 2−3 years. Cubs were recaptured when possible to replace collars as necessary. Puma population sampling considerations The puma is one of the most difficult large, North American mammals to study because of its relatively low abundance on the landscape and its highly cryptic behavior. These characteristics were expected to influence the ability to sample individuals in the study population. The most efficient technique for locating and capturing pumas is detecting their tracks in snow and using trained dogs to pursue and secure them for sampling purposes. Hunters use the same technique to harvest pumas, which creates potential for biased survival rate estimates if researchers and hunters use similar strategies to detect and capture pumas. That is, with similar sampling strategies, pumas that are most vulnerable to being captured and radio-collared might also be more vulnerable to harvest, resulting in survival rates that are biased low. Hunters’ detection of puma tracks is heavily influenced by road access. To minimize bias potential, we attempted to intensively search the entire study area for puma tracks, irrespective of road characteristics, thereby equally detecting puma with both higher and lower hunter-detection probabilities. Thus, our approach was to apply roughly equal (i.e., intensive, uniform) searching intensity across the study area and apply an alternative capture technique with bait and cage traps that did not rely on track detection to capture pumas, and attempt to directly monitor via VHF telemetry a large majority of the population in the study area. Capture efforts to sample the adult and subadult pumas (i.e., independent pumas) subject to sporthunting mortality in the UPSA population were conducted mainly during winter when snow cover maximized the detection and capture probability of pumas. Snow provided a continuous or almost continuous substrate that registered tracks of terrestrial mammals. Puma tracks were highly distinctive and at ground level could be accurately and consistently visually identified and distinguished from tracks of all other mammals by trained personnel in a variety of snow and weather conditions and in the variety of terrains and vegetation communities. This characteristic was the reason why most intensive puma population studies in western North America have been conducted during winter to maximize detection, quantification, classification and monitoring of animals in the populations (Hornocker 1970, Logan et al. 1986, Lindzey et al. 1992, Ross and Jalkotzy 1992, Spreadbury 1996, Anderson and Lindzey 2005, Lambert et al. 2006, Laundre et al. 2007, Cooley et al. 2008). Puma population research in winter also directly linked the puma population investigated with animals killed during the hunting season, which in Colorado occurred annually during mid-November through March when snow facilitated the detection of pumas by hunters and maximized the ability of their dogs to follow scent in tracks to capture the pumas. In addition, during spring and fall and opportunistically in winter, we attempted to capture pumas in cage traps. Individuals caught in cage traps were available to move about the study area during winter and be exposed to hunters. The Uncompahgre Plateau study area was highly roaded. From those roads branched ATV trails that further facilitated thorough searches of the study area to detect pumas (Fig. 2). Still, the road system was not uniform, with some areas densely roaded, others moderately roaded, and one area in particular that did not allow motorized vehicles−the combined Camelback Wilderness Study Area (BLM jurisdiction) and Roubideau Special Management Area (U.S. Forest Service jurisdiction) in the main fork of Roubideau Canyon. That non-roaded area was about 109 km2 (42 mi.2). Because a system of roads and 9 �trails surrounded this area we were able to address this problem by hiking up the lower reaches of Roubideau Canyon and onto upper benches and canyons to search for puma tracks. A puma capture team, involving 4 people on separate search routes, was detailed to search this region on the surrounding roads, ATV/snowmobile trails, and hiking paths. By visiting this area repeatedly each winter we expected to detect some pumas that used the canyon and that might not have been detected in the canyon in other search days. Pumas were expected to move out of the non-roaded portion of the canyon periodically during the winter and be exposed by their movements. Thus, periodic searches of any of the search routes were expected to increase exposure of the pumas to our detection. The UPSA was partitioned into smaller search areas that a capture team could cover within 1−2 days to detect puma tracks on snow within each area each winter to spring (Table 1). The West-side search area was about 721 sq. km and the East-side search area was about 980 sq. km, with each area limited at the higher elevations by deep snow and lack of puma activity during winter. However, search routes at higher elevations enabled us to explore areas until deep snow limited our mobility and absence of puma activity was apparent, usually by the end of December each year. By this time, pumas and their ungulate prey mule deer and elk were concentrated on their winter range. The intent was to structure a thorough, relatively uniform, systematic search effort across the study area and to repeat it multiple times each winter−spring. To cover the areas efficiently, we traveled by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and foot. When puma tracks ≤1 day old were detected, trained dogs were released to pursue the puma to capture, sample, and mark it. When puma tracks 1−2 days old were detected, we searched in the direction of travel of the puma in an effort to find ≤ 1 day old tracks that would facilitate pursuit of the puma. This sometimes lengthened our search within any particular area by another 1−2 days. When a GPS/VHF-collared puma was detected with radiotelemetry ≤1 km distance (usually <0.5 km) of the tracks and the direction of the tracks indicate that the puma was likely the collared individual, then we directed our efforts away from those tracks and redirected them to finding non-collared (i.e., non-sampled) pumas. Reliability of population count methods We expected the approach just described would enable us to monitor a large majority of the independent pumas on the UPSA from November through March and consequently gather reliable population data. The main way we indexed puma abundance was to count all the individual independent pumas we detected on the study area each winter. We were able to gauge the reliability of our field methods in Treatment Year 4 (TY4), when our resources allowed a one-time independent evaluation on the proportion of independent pumas on the study area that we captured and marked. This evaluation was provided by a camera grid study conducted by Colorado State University researcher K. Yeager (2016). K. Yeager established a 540 km2 grid comprised of 2 km x 2 km (4 sq. km) cells on the East-side of the UPSA. She randomly identified 18 cells for each of 3 survey periods, each lasting about 28 days during December 2012 to March 2013. Therefore, a total of 54 random cells were surveyed. Within each random cell Yeager subjectively chose the “best” site to attract pumas by using vocal baits each consisting of a Fur-Finder ® (Magna, UT) electronic recording of a distressed deer fawn. Each site also had a Reconyx ® PC900 Hyperfire camera (Holmen, WI) to record animal activity and hair-sampling devices (i.e., barbed-wire strands, sticky rollers) to attempt to acquire hair. This effort allowed us to evaluate our field methods intended to mark a large majority of independent pumas on the UPSA. Population Manipulation The puma population on the UPSA was manipulated by sport hunting after the 5-year reference period with no hunting. The hunting season was from mid-November to January 31, or until the last puma on the design quota was killed if it was before January 31. We initially tested the assumption that a 15% harvest of independent pumas comprised of 35−45% females would result in a stable-to-increasing population in the UPSA GMU. 10 �The initial harvest quota was 8 pumas which represented a 15% harvest of the expected number of independent pumas in treatment year 1 (TY1) on UPSA. Therefore, the predicted effect was that the 15% harvest of independent pumas would result in a stable or increasing population in subsequent years of the treatment period. The quota of 8 was based on the projected number of 52 independent pumas expected on the study area in winter 2009−10 (TY1), modeled from count data in winter 2007−08 (RY4) (see Appendix II, Table AI.3). After it was evident that the number of independent pumas had declined during TY1−TY3, we adjusted the harvest quota down to 5 pumas to represent an 11% harvest of the projected 45 independent pumas expected in TY4 in an effort to find a sustainable harvest rate useful to managers. The harvest quota of 5 was continued in TY5. The number of hunters on the study area each winter was not limited to be consistent with the Colorado puma hunting structure. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal Colorado puma hunting license to hunt in the UPSA for 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date could get serial 14-day permits until they harvested a puma or until the hunting season on the study area closed due to the quota being reached or the end of the hunting season. This permit system enabled CPW to estimate the number of hunters that actually hunted on the study area each season. In addition, a voluntary survey questionnaire (see Appendix III) was attached to each puma hunting permit issued to each hunter with a stamped envelope addressed to the CPW principal investigator. Hunters were asked to complete the survey as soon as possible for each hunting period associated with the permit in an effort to have hunters report the information while it was still fresh in their minds. All pumas harvested on the study area were visually examined and sealed by the principal investigator or project biologists just as is mandated by CPW for all pumas killed by hunters in Colorado. Hunters reported their puma kill to CPW within 48 hours of harvest and presented the puma carcass for inspection within 5 days of harvest. At the time of carcass check-in a mandatory CPW harvest check form was completed, which included gender, age estimate, and location of capture for each puma. Each successful hunter was asked to fill-out the one-page hunter survey form. Most other hunters either mailedin or handed-in their surveys on their own volition. If hunters did not respond, they were contacted by telephone or in person, if possible, and asked to complete the survey and return it. Mandatory hunter harvest checks provided accurate data on the gender and sex of pumas removed from the study population. Hunters also provided data to evaluate the relative vulnerability of pumas to harvest and potential for hunter selectivity. Hunter harvest and capture events also revealed availability and sex and age classes of non-marked pumas on the study area during the hunting season and before our capture teams operated after the season to quantify the population. Population Monitoring This monitoring plan enabled us to index the abundance of pumas with our counts and estimate the sex and age structure during each hunting season period November through March. Radio-collared pumas monitored year-round enabled us to gather population data, including: fecundity, birth interval, litter size, sex ratio, survival, agent-specific mortality, and recruitment to the adult stage. Emigration was revealed with a sample of radio-collared or ear-tagged marked offspring that left the study area. GPS- and VHF-collared pumas were located about once per week from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring enabled researchers to find GPS-collared pumas to acquire remote GPS location reports, monitor the status (i.e., live or dead) of individual pumas, and to locate carcasses for necropsy. Life status of GPS- and VHFcollared pumas were monitored from the ground opportunistically using hand-held yagi antenna. GPScollared pumas were monitored for survival status by using data from GPS collars. 11 �Analytical Methods Response variables We quantified and estimated responses of the puma population to sport-hunting and other causes of mortality based on changes in four variables: 1) abundance of independent pumas, 2) survival of adult, subadult, and cub pumas, 3) reproduction, including litter size and parturition rates, and 4) age structure of independent pumas. Puma population counts and trends The parameter of interest to managers was the abundance of independent pumas (i.e., adults and subadults) in winter, which coincided with the puma hunting season in Colorado when snow cover maximized the vulnerability of pumas to hunting. Our winter research effort was designed to be thorough to maximize the proportion of marked pumas in the population to sample for other parameter estimates, including survival, agent-specific mortality, reproduction rates, and age structure. Using this design, we attempted to obtain a reliable index to puma abundance with as complete of a count as we could achieve along with the attendant sex and age structure of the population that occurred from November through March (i.e., winter counts). We assumed the winter counts of adult and subadult pumas to be a census of the population without estimates of variance of independent pumas that used the UPSA each winter. We used the annual winter counts of independent pumas as one level of gauging effects of hunting and other causes of mortality at the population level. The winter counts consisted of the sum total of all known, marked (i.e., radio-collared and eartagged) pumas, non-marked pumas we captured but could not safely handle, non-marked harvested pumas and non-marked pumas reported captured and released by hunters on the UPSA. In addition, our counts included any other pumas detected by their tracks as recorded by our capture teams on the study area whose track locations and movements fit these criteria: 1) did not match known movements and locations of collared pumas, 2) exhibited diagnostic characteristics of unique individuals (e.g., tracks distinguishing sex from hind-foot plantar pad width measurements ≥52 mm classified as male, ≤50 mm classified as female; ≥2 mm difference in hind-foot plantar pad widths, 3) variation in counts of cub tracks with female tracks. We believe these counts accurately quantified puma abundance and sex and age structure. Yet, the counts may conservatively estimate population size due to a probability of us missing tracks of individuals and a probability that similar sized tracks may have been made by more than one individual. If our counts were conservative, then the design quotas we used and the observed mortality were a lower percentage of the actual population size. Puma density We used the winter population counts to calculate the density of independent pumas based on two methods of assessing area: 1) density based on the winter search areas, and 2) density based on mapped strata of winter puma habitat (December through February) as defined by a resource selection function (RSF) developed in 2015 by the CPW GIS Unit and the Avian Research, Mammals Research, and Terrestrial Sections (Colorado Parks and Wildlife 2015, Ft. Collins). The first approach made our density estimates comparable to other previous puma density estimates in western North America in the literature. The RSF approach allowed us to estimate puma density in a context of defined puma habitat that can be used by wildlife managers in Colorado. The RSF model was developed using 2,470 male and 1,603 female puma mortality locations documented in Colorado through mandatory checks. Validation of the model was assessed using 164 documented winter puma predation sites on radio-collared mule deer in Colorado, 14,793 winter GPS locations (i.e., Dec−Feb.) from 33 female and 9 male independent pumas on the Uncompahgre Plateau from 2004−2015, and 58,593 winter GPS locations from 45 female and 32 male pumas on the northern Colorado Front Range from 2007−2015. The assessment indicated that 86% of the puma locations on the Uncompahgre Plateau were within strata 3 and 4 of the model. 12 �Puma survival and mortality analysis Adult pumas participate in breeding behavior and were considered to be animals that were aged 2+ years old (Logan and Sweanor 2001:93-95, Lindzey et al. 1994). We chose 2+ years as the lower limit of age for adult pumas, because that age assignment was consistent with more complete data from New Mexico (Logan and Sweanor 2001:93-95) in which 12 known-age female pumas conceived successfully for the first time at an average age of 26.1 months old, which was close to the average age of 29.2 months (median = 27 months, range = 18−43 months) of first conception for a less-known sample of females in this study (see Puma reproduction section). Furthermore, Lindzey et al. (1994) estimated 23 months as the average age of first breeding for 6 known-age female pumas in Utah. Males in the New Mexico study were estimated to reach sexual maturity at about 24 months old. We did not have comparable data for this study. Adult puma survival and mortality was examined from data on radio-collared pumas that provided known-fate data (i.e., monitoring dates, estimated date of death, cause of death). We used program MARK (White and Burnham 1999) (accessed January 12, 2015), the known fates data type and the logit link function to model survival rates with a candidate set of models structured to investigate factors that might explain variation in survival. MARK estimated survival rates, standard errors, and 95% confidence intervals for each model. Our main interest was the effect of the hunting treatment as partitioned among the reference and treatment periods on survival, because our research focus was to examine effects of sport-hunting on a puma population. As such, our biological year spanned from November (the month that puma hunting seasons began) to October to encompass complete hunting seasons within each 12month period. Radio-location records for each adult puma were converted to monthly encounter histories. MARK estimated monthly survival rates using the modified Kaplan and Meier (1958) estimator that allowed staggered entry based on when we collared individuals and censoring of individuals if we lost contact with them (Pollock et al. 1989). We used data from year 2 of the reference (RY2) period to year 5 of the treatment period (TY5) (i.e., a 9 year span). We did not use data from reference year 1 (RY1) because we had just started the study and had collared only 7 adult pumas (3 males and 4 females). Encounter histories of individual adult pumas started on the day of capture because no pumas died as a result of capture, or the beginning of RY2 (November 1, 2005) for surviving pumas that were captured previous to that date. We censored individuals in the data if we did not receive its signal after the month of its last location. Individuals re-entered the data set if we recaptured them and fit them with a new collar. Death dates for puma were assigned to pumas with GPS collars based on the first day that GPS locations indicated that the pumas were immobile. Death dates for VHF-collared pumas were estimated based on previous live signal data and the mid-point of the span of days the puma was estimated to have died based on carcass decomposition. Death dates of hunter-killed pumas were reported by the hunters and recorded on mandatory check forms. Causes of death were categorized to known human causes (e.g., hunting, depredation control, vehicle strike, poached), to known natural causes (e.g., intraspecific strife, injury), or to unknown natural causes. Subadult pumas in our study were considered to be animals known or estimated to be 13−24 months old. This is a life stage where pumas are independent of their mothers and usually not participating in breeding behavior (Logan and Sweanor 2001:146). Subadult puma survival and mortality was estimated for all known radio-collared and ear-tagged and tattooed pumas with known fates that spanned the 12-month subadult stage. We did not know with certainty when all of the pumas in this stage became independent, therefore some of the pumas may have been dependent cubs for a period of time longer than 13 months. Furthermore, at the upper end of this stage we could not determine when most pumas were transitioning into adulthood. Encounter histories for the pumas started as marked pumas entered the stage and on the first day of capture for subadults caught and marked for the first time because no subadults died as a result of capture. All histories were converted to monthly encounter histories. Death dates were assigned to reported and observed harvest, depredation control, and vehicle strike dates. For VHF-collared pumas that died of natural causes where mortality dates were not observed, dates were 13 �estimated as the mid-point of the span of days the puma was estimated to have died based on previous radio-telemetry live signal data and carcass decomposition. The encounter histories were treated as known-fate data and entered into program MARK to model subadult puma survival rates using a candidate set of models that might explain the variation in survival rates. Cubs were dependent upon provisioning from their mothers. In our data set, these included animals between 1 to 12 months old. Survival and mortality was estimated for all radio-collared pumas in this stage. The large majority of the cubs in this data set were initially radio-collared as nurslings 1−2 months old. But we also included cubs collared at older ages, because we entered data to estimate monthly survival rates. In this way, use of data on the older cubs only added to the sample of older cubs and did not bias estimates because older cubs have a tendency to exhibit higher survival (Logan and Sweanor 2001, Ruth et al. 2011). Monthly survival rates were estimated using MARK and the known-fate data type. Encounter histories for the cubs started on the first day they were collared. Three nursling cubs that died as a result of malfunctions of the design of the expandable radiocollars early in the study in the reference period were removed from the analysis. After the collars were modified, no other cub mortalities from the collars occurred. Causes of cub deaths were assigned after dead cubs were physically examined. Dates of death were estimated as the mid-point of the span of days the puma was estimated to have died based on dates of previous radio-telemetry live signal data and carcass decomposition. The assumption that each radio-collared cub was an independent random sample (i.e., distribution of mortalities among litters is random) may be violated because we collared one-to-three cubs in litters, and often two-to-three siblings per litter, and the fates of siblings might be linked. For example, sometimes more than 1 or all cubs in a litter may die from the same proximate cause (e.g., infanticide by a male puma) or the survival of surviving cubs in a litter may be linked to death of siblings (i.e., resulting from greater individual maternal care). Violation of the independence assumption can result in unbiased survival point estimates, however, sample variances are expected to be underestimated. The data are said to be over-dispersed (Bishop et al. 2008). Therefore, we examined validity of the independence assumption in data by estimating an over dispersion parameter, c-hat (Cooch and White 2015). Covariate selection, model selection and inferences We developed sets of covariates that we hypothesized might affect survival of adult, subadult, and cub pumas. Because our research investigated effects of sport-hunting on a puma population which involved adult and subadult pumas as the huntable life stages, we developed models that included individual covariates for gender and period (i.e., reference and treatment periods). For adults, we also used a covariate for the abundance of mule deer and elk combined because these ungulates were the primary prey of puma on UPSA and because of a hypothesis that prey abundance ultimately limits puma populations (Pierce et al. 2000, Laundre et al. 2007, Logan and Sweanor 2010). Mule deer and elk abundance was indexed by modeled population estimates in December of each year that puma survival was assessed (Terrestrial Section, Colorado Parks and Wildlife, unpublished data). The mule deer and elk covariate was not used for subadult pumas because most of the subadults had dispersed from the UPSA in various directions and at varying distances when they were subject to hunting. Individual cub covariates included gender and period. We used a covariate to indicate if a cub’s dam lived or died during the 12month age stage of cub’s dependency. We used abundance of mule deer and elk combined as individual covariates to assess variation of key prey abundance to cub survival. We also explored whether birth month was associated with cub survival. We included time-varying models using year as a covariate for adults and month for subadults and cubs. We modeled puma survival for all three stages including constant (.) and additive (+) and interactive (*) combinations of covariates; for cubs we also included some quadratic terms. 14 �We evaluated the importance of candidate models in an information-theoretic approach (Burnham and Anderson 1998). For adults and subadults, we used Akaike’s Information Criterion adjusted for small sample sizes (AICc) to rank the models. We considered the models with the most support as those with the lowest AICc scores, high AICc weights (wi), and models with ∆AICc <2 as having similar support (Burnham and Anderson 2002). Survival estimates reported here were estimates in the top model and other supported models. Average monthly survival rates for adults were converted to annual survival rates (i.e., Saveragemonthly12), standard errors, and 95% confidence intervals. Survival parameters for subadults were derived estimates calculated in MARK from monthly survival rates that produced average stage (i.e., 12-month) survival rates, standard errors, and 95% confidence intervals. For cub survival, we estimated the overdispersion parameter c-hat in MARK to test for violation of the independence assumption. Likewise, we considered 1.0 <c-hat ≤1.2 as weak evidence of overdispersion as suggested by Bishop et al. (2008) and Ruth et al. (2011). We followed the method of Cooch and White (2015) and used the Tests option in program MARK to run 1000 bootstrap simulations on our cub data set in the most parameterized model we could use. We then estimated c-hat by dividing the observed c-hat in the original model estimates by the mean simulated c-hat. If the results indicated non-independence in the cub fates, then we used the Adjustments option for c-hat in MARK and entered in the estimated c-hat to adjust for the quasi-likelihood estimate (QAICc) in program MARK. We considered the models with the lowest QAICc and <2 as having the most support. Survival parameters for cubs were derived estimates calculated in MARK from monthly survival rates that produced average stage (i.e., 12-month) survival rates, standard errors, and 95% confidence intervals. Examining survival rates of adults, subadults, and cubs in the reference and treatment periods with contrasting models with and without the hunting treatment allowed us to assess changes in survival that might be associated with the treatment effect. The reference period would include all detectable natural and human causes of mortality in the population, sans hunting mortality. The treatment period would include all detectable causes of mortality, with the addition of hunting mortality. A treatment effect supported an inference that sport-hunting mortality was an important factor explaining the variation in puma survival and a factor that was to some extent additive if survival declined in association with the treatment. However, if models lacking the treatment effect received the most support, this would indicate that hunting mortality was primarily compensatory and that survival was influenced mainly by some other factors, or that statistical power was insufficient to detect a treatment effect. Reproduction Female pumas with GPS/VHF collars were monitored year round. Data from those pumas provided information on parturition, litter size, sex ratio of cubs observed in nurseries, birth intervals, and age at first breeding. Reproduction was verified by direct observations of cubs in nurseries and in direct association of adult females during capture efforts. Parturition rate, defined as the proportion of adult female pumas giving birth each year, was estimated annually from reference year 2 (RY2) through treatment year 5 (TY5) when we had ≥12 adult females in annual samples (there were only 4 adult females in RY1). Data on each adult female each year was coded with the individual identification number and as producing a litter of cubs (1) or not producing a litter (0) and whether the individual female produced a litter each year in the reference period (1) or the treatment period (2). Because adult females comprising the samples within each year were not independent of other years (i.e., some of the same females were monitored in a series of years within and among periods) mean period parturition rates were modeled by using the generalized linear mixed model procedure (PROC GLIMMIX) in SAS (Version 9.3, 2010, SAS Institute) where the period was the fixed effect and individual puma identification was the random effect. We used the binomial distribution and logit link. We also investigated all adult females that exhibited extremely constrained GPS and VHF location clusters or movements that might indicate the birth of a litter. When the cubs were 25 to 45 days 15 �old we entered the nurseries when the mothers were absent to examine the cubs and to mark them. We coded the data with each adult female identification number, the period in which the litter was produced (reference = 1, treatment = 2) and the number of cubs observed in each litter (1, 2, 3, 4). Similarly, because adult females comprising the samples within each year were not independent of other years and some occurred in both periods, we modeled period mean litter size using the mixed linear model procedure (PROC MIXED) in SAS, where period was the fixed effect and individual puma identification was the random effect. The sex ratio of cubs produced in the reference and treatment periods was compared to an expected 1:1 sex ratio by using the Goodness of fit Chi-square procedure (Zar 1984). This procedure was also used to test for a difference in the ratio of litters subject to infanticide in the reference and treatment periods and determined significance at alpha = 0.05. Sex and age structure We looked for changes in the sex and age structure of the population of independent pumas by graphically analyzing the population at the beginning of treatment years TY1 and TY5. The age structure at the beginning of TY1 represented ages of the independent pumas in this population after 5 years of protection from hunting and just before any pumas were removed in the first treatment year. The age structure at the beginning of TY5 represented the ages of independent pumas in the population after 4 years of hunting (TY1−TY4) and other causes of mortality operated on the population up to the start of TY5. PRELIMINARY FINDINGS Puma capture From December 2, 2004 to October 30, 2014 we captured about 256 individual pumas a total of 440 times on the UPSA. None of the adult or subadult pumas died from capture procedures. However, 3 cubs died as a result of premature expansions of the radiocollars (indicated previously in Field Methods) and 1 cub was killed by our tracking dogs. We individually marked 226 pumas: 109 in the reference period and 115 in the treatment period. The number of radio-collared pumas monitored each year ranged from 16 to 56 and averaged 40. Marked pumas provided known-fate data on 75 adults, 75 subadults, and 118 cubs. About 30 individuals were captured with dogs, but were not handled due to dangerous positions in trees. Of those pumas not handled, 11 were captured in the reference period and 19 were captured in the treatment period. Six of 11 pumas not handled in the reference period were associated with marked family members (i.e., mothers or siblings). Similarly, 8 of 19 pumas not handled in the treatment period were associated with marked family members. By the end of the study, we could account for the fates of all of the radio-collared adults (i.e., we determined they either survived or died), including those with failed radiocollars, except for one adult male. In addition to the pumas captured by our research team during the treatment period, puma hunters captured and killed a total of 35 pumas, including 8 adult females, 16 adult males, 3 subadult females, and 8 subadult males. Puma hunters also reported having captured and released 30 independent pumas, with their reported gender identification of 19 females and 11 males. The sex ratio of independent pumas captured and released by hunters (1.7 females:1 male) fell into the range of our winter counts of independent pumas (1.2 females: 1 male to 2.8 females: 1 male; Table 2) in the treatment period. The sex ratio of pumas killed by hunters (1 female: 2.2 males) reflected a hunter selection bias toward males reported in hunter surveys during the treatment period (K. Logan, unpublished data). Reliability of population count methods The camera grid survey by K. Yeager (2016) in TY4 spanned 102 days from December 2012 to March 2013. The survey partially overlapped with 3 months of our winter capture efforts which spanned from January 1 to April 18, 2013. Eleven GPS and VHF collared pumas were known to use the survey grid for varying amounts of time, including 7 adult females, 1 subadult female, 2 adult males, and 1 16 �subadult male. During the survey cameras acquired 18 photographs of pumas visiting the sampling sites, and all 18 of the photographs depicted GPS or VHF collared pumas. The photographed pumas included 1 subadult female and 1 subadult male that we captured and marked for the first time in January 2013, before cameras subsequently detected them 5 and 3 times each, respectively. An adult male that we captured and marked for the first time February 14, 2013 was not detected by the cameras. Of the 11 collared pumas known to use the grid, 7 were photographed 1 to 5 times each, including 5 adult females, 1 subadult female, and 1 subadult male. The results of the camera grid survey indicated that our field methods could produce reliable counts of independent pumas for our index to abundance because: 1) no non-collared pumas were detected during the survey; and 2) we detected, captured and marked 3 new pumas before the cameras detected any of them. Furthermore, the ratio of marked-to-non-marked independent pumas killed by hunters during the treatment period before our research teams inserted to search for non-marked pumas was 19:16. The hunters’ survey responses indicated that marks on pumas did not influence their decisions to harvest a puma (K. Logan, unpublished data). A preponderance of this evidence indicated that our field operations thoroughly accounted for the abundance of independent pumas on the UPSA and enabled us to sample a majority of the independent pumas for estimates of survival, agent-specific mortality, reproduction and age structure. Puma population counts The number of days we spent each winter and early spring searching for pumas with dogs was similar in each period (reference mean = 77.2, SD = 4.0, range 71−82; treatment mean = 79, SD = 4.8, range 74−86). We believe we had a thorough knowledge of the study area and search routes for reliable counts of the winter population of independent pumas on the study area by reference year 4 (RY4) and throughout the treatment period. However, in RY5 a Colorado state government-mandated hiring freeze (in response to economic recession) resulted in insufficient personnel for thorough searches of the study area for a reliable winter count of independent pumas. Therefore, the count in RY5 (n = 37) was probably biased low, but was still larger than RY4 (n = 33). Recognizing this probable bias, we modeled the population by using the count data in winter 2007−08 (RY4) and previous reference period parameter estimates (see Appendix II, Table AI.3), which projected an expected 45 independent pumas in RY5 (Table 2, Fig. 3). The hunting treatment The hunting treatment on the puma population during TY1−TY3 consisted of a designed 15% harvest rate of the independent pumas in UPSA. The quota to represent a 15% harvest was 8 pumas based on a model projected 53 independent pumas expected in TY1 (Appendix II). The model projected 53 independent pumas turned out to be very close to the 56 pumas we actually counted in TY1. The graphed results of the treatment period counts indicated a non-ambiguous monotonic decline in the number of independent pumas from TY1−TY4 (Fig. 3). Clearly, the population declined when subjected to a 15% design harvest for the UPSA GMU (actual average 16.1% harvest of independent pumas, range = 15.4−16.7%) from TY1−TY3 and when other human and natural causes of mortality operated on the population. Of the 25 independent pumas killed by hunters in TY1−TY3, 32% of them were females with 20% adult females. Therefore, a 15% design harvest of independent pumas comprised of 35−45% females was not supported for managing toward a stable or increasing puma population in GMU-based management when other human and natural causes of mortality were operating. The actual average harvest rate of 16.1% (Table 3A) of independent pumas from TY1−TY3 exceeded the 15% design harvest because the quota was exceeded by one puma in TY1, and as the population declined the quota exceeded the 15% harvest in TY2 and TY3. Because the population declined with an average 16.1% actual harvest rate, we wanted to find a harvest rate of independent pumas that might be sustainable with other human and natural causes of mortality operating on the 17 �population. Therefore, in TY4 and TY5 the quota was reduced to 5 pumas constituting 11−12% design harvest of independent pumas. However, additional independent pumas died of other causes during the treatment period hunting seasons (i.e., Nov.−Mar., Table 3B). Additional pumas deaths each hunting season ranged from 0−2 each season. All of the deaths were adult females. Adding these puma deaths to the harvest the total mortality as a percentage of the winter counts of independent pumas ranged from 16.1−20.8% and averaged 18.7% during TY1−TY3 when the puma population declined. In TY4 and TY5 the total mortality of independent pumas was 14.3% and 13.6%, respectively (Table 3B). In addition, hunting in surrounding GMUs contributed to the decline in the abundance of independent pumas on UPSA. Ten radio-collared independent pumas (2 adult females, 7 adult males, 1 subadult female) included in treatment year winter counts were killed by hunters in adjoining GMUs 61 North, 62 North, 65, and 70 because those pumas had home ranges that extended beyond the boundaries of UPSA. Two of the adult radio-collared males were actually trailed by hunter’s dogs off of UPSA and were caught and killed in adjacent GMUs 65 and 70. In addition, as reported by the hunters, 2 noncollared adult males were trailed with dogs off of the study area and killed in adjacent GMUs 62 North and 70. The number of study animals killed by hunters outside of UPSA ranged from 0 to 4 and averaged 2 each year from TY1−TY5, and those pumas were counted in the hunting quota in the adjoining GMUs, not UPSA. Including these deaths off the study area, the percent of hunting kill from TY1−TY5 ranged from 11.4%−25% (average = 18.2%) of independent pumas in winter counts on the UPSA. The actual hunter-kill of the number of independent pumas during TY1−TY3 ranged from 17.3−25% (average = 21.8%), and was associated with the population decline phase. During TY4−TY5 the actual hunter-kill was 11.4−19.0% (average = 15.2%), and was associated with the low population phase. Therefore, hunting mortality in the adjacent GMUs added to the overall mortality impacting the UPSA puma population. This indicated that GMU-based puma management must consider that GMUs do not represent closed puma population segments and that harvest in adjacent GMUs can confound the expected management results for any particular GMU. Changes in puma abundance The population of independent pumas increased by about 70% (i.e., 33 in RY4 to 56 in TY1) during the reference period without hunting as a mortality factor (Fig. 3). We counted the highest number of independent pumas during winter of TY1 which was preceded by 5 years without hunting. The increasing puma population during the reference period was an indication that previous hunting mortality was probably a major factor that reduced the population. In the treatment period, the population of independent pumas declined from a total count of 56 in TY1 to a low of 42 in TY4, a 25% decline after three hunting seasons (Fig. 3). The abundance of adult females declined 23.3% by TY5. Adult males declined 55% by TY3 and TY4, and were 50% lower by TY5 (Table 2, Fig. 4). The percentage of independent females in the harvest TY1−TY5 was 31.6%; comprised of 23% adult females and 8.6% subadult females. The remainder of the harvest was comprised of adult males (45.7%) and subadult males (22.9%). After we reduced the quota to 5 for TY4 and TY5, the decline in abundance of independent pumas stopped, stayed in a low phase, and may have slightly increased. An increase in subadult males also contributed to a slight increase in independent pumas by TY5 (Table 2, Fig. 4). Considering the total independent puma mortality that occurred in treatment period hunting seasons (Table 3B), the percentage of independent females in the mortality TY1−TY5 was 41.5%; comprised of 34.1% adult females and 7.3% subadult females. In TY3 and TY4 the percent independent and adult females in the total mortality was 50% and 33.3%, respectively (Tables 3A, 3B) and were associated with the population low phase. 18 �These results were evidence that a designed hunting off-take of 15% of independent pumas plus other human- and natural-caused mortality could result in a decline in abundance of adult and independent pumas at the GMU level. Furthermore, data on the puma population in the UPSA GMU indicated that the puma population responded to our hunting closure and treatment, and thus GMU-based hunting management could be an effective way of managing localized puma population segments. Mortality in marked pumas The regulations implemented to eliminate sport-hunting as a mortality factor on pumas on the UPSA in the reference period were effective. The puma population responded to this regulation change on the UPSA GMU by increasing by about 70% (previously). Of the 32 (21 females, 11 males) adult radio-collared pumas we monitored, 7 adult pumas died but none from hunting (Table 4A). Causes of death were attributed to: 5 natural causes (4 intra-specific strife, 1 unknown), 1 vehicle strike, and 1 depredation control. Of the 22 subadults (8 females, 14 males) providing known-fate data in the reference period, 3 died. One male that had moved off the study area was killed by a hunter that did not see the tags. The other causes of death in subadults were 1 natural cause (trampled by elk) and 1 vehicle strike. Of 55 radio-collared cubs (28 females, 27 males) monitored in the reference period, 16 died. Causes included: 13 infanticide, 1 predation, 1 unknown natural, and 1 vehicle strike. In the reference period natural causes dominated deaths of adults and cubs (71.3% and 93.8%, respectively), but 2 of 3 subadult deaths were from human causes. Sport-hunting was the most important cause of death for independent pumas during the treatment period (Table 4B). Of the 61 adults (39 females, 22 males) we radio-monitored during the period, 37 died. Hunting caused 56.8% of adult deaths (n = 21: 14 males, 7 females), followed by natural causes (27%; n = 10: 7 unknown with 6 probably disease-related and 1 due to starvation with senescence, 3 intra-specific strife), and other human causes (16.2%; n = 6: 3 vehicle strike, 2 depredation control, and 1 illegal kill). Of the 53 subadults (19 females, 34 males) providing known-fate data in the treatment period, 20 died. Hunting caused 55% of the subadult deaths (n = 11: 9 males, 2 females). Natural mortality followed in importance with 25% (n = 5: 3 intra-specific strife, 2 other natural), then closely by 20% other human causes of death (n = 4: 3 depredation control, 1 vehicle strike). Combining adult and subadult puma deaths in the treatment period, human causes were 73.7 % (i.e., 42/57*100), of which hunting caused 76.2% (i.e., 32/42*100) and other human causes comprised 23.8% (10/42*100). Of the 63 radio-collared cubs (27 females, 36 males) monitored in the treatment period, 27 died (Table 4B). Mortality causes in the cubs included: 9 infanticide, 4 other natural, 2 vehicle strike, 3 depredation control, and 9 starvation. The 9 cubs starved after the deaths of 5 mothers due to: hunting (2 mothers involving 3 cubs), depredation control (1 mother with 3 cubs), and natural causes (2 mothers involving 3 cubs). Natural mortality comprised the majority of cubs deaths (15/27*100 = 55.6%). But, human-caused cub deaths in the treatment period increased to 44.4% (12/27*100 = 44.4%) from 6.2% in the reference period. There was no apparent compensation to hunting mortality by a reduction of other causes of death for most independent puma categories in the treatment period. Hunting-caused deaths were additive mortality to adult male pumas, because percentages of other causes of death in the treatment period were similar to the reference period (Figs. 5A, 5B). Hunting and other human-caused deaths added to natural mortality in adult females in the treatment period, which was higher than in the reference period (Figs. 5A, 5B). Similarly, hunting and other human-caused deaths to subadult male pumas appeared to be additive mortality (Figs. 6A, 6B). But, the few hunting deaths to subadult females appeared to be partially compensatory, as there was a decline in the percentage of non-hunting deaths during the treatment period (Figs. 6A, 6B). The additive quality of hunting and other human-caused deaths was further reflected in significantly lower adult and subadult male survival rates and a decline in abundance of independent and adult pumas on UPSA during the treatment period. As we previously indicated, the abundance of 19 �independent pumas declined 25% by TY4, adult females declined 23% by TY5, and adult males declined 55% by TY3 and TY4 (Fig. 4). Infanticide is thought to be sexually selected and a means by which adult male pumas compete for reproductive success (Hrdy 1979, Logan and Sweanor 2010). It has been theorized that periods of male territory instability contribute to reduced cub survival via increased infanticide as immigrant males and shifting neighbor territorial males move into vacated territories (Logan and Sweanor 2001, Ruth et al. 2011). Conditions on UPSA were not sufficient for testing this hypothesis, because there was not an adequate duration of time for adult male abundance and their territories to stabilize. The population of independent pumas increased at least by 70% during the reference period. During this growth period, the abundance of adult males increased as a result of high survival. Theoretically, we would expect competition among the males to increase as well. The population of independent pumas declined by 21.4% during the hunting treatment period and included a 50−55% reduction in adult males. Although territory stability was put into flux again due to high mortality in adult males during the treatment period, there also were 55% less adult males in the population to compete for mates by TY3 and TY4 and 50% less by TY5. These conditions might explain why during the reference period that 8 of 32 litters involving 13 cubs of the radio-collared litters we monitored were impacted by infanticide, and during the treatment period 5 of 45 litters involving 9 cubs of the radio-collared litters we monitored were impacted by infanticide. The ratio of litters subject to infanticide in the reference period was significantly different than the ratio of litters subject to infanticide in the treatment period (χ2 = 4.571, 1 d.f., 0.025 < P < 0.05). In addition to deaths revealed by the radio-collared cubs, we observed deaths of 4 entire litters on the day we entered nurseries to examine cubs for the first time. These cubs were not part of the radiocollared cub population used to model or estimate cub survival (see below in Puma Survival, Cubs). One litter of 3 nursling cubs starved to death in the reference period after the mother was killed for depredation control. In the treatment period, we observed that three entire litters died; 2 litters (1 with 2 cubs and 1 litter with ≥1 cubs) died of infanticide, and the third litter (with ≥1 cub) died due to black bear predation. Mortality in independent marked and non-marked pumas We calculated the percentage of detected marked and non-marked independent puma deaths on UPSA each 12-month study year RY4−TY5 attributed to natural-, other human-, total human-, and hunting-causes, and the portion of total human-caused deaths attributed to hunting on UPSA (Table 5). In this way, the percentages for each type of death could relate to the trends in the population for each period (Figs. 3, 4). Total detected deaths of independent pumas on UPSA for reference years RY4 and RY5 ranged from 3−5 independent pumas each year. Natural causes of death ranged from 33.3−60% and averaged 46.7% per year. Other human-caused deaths ranged from 40−66.7% and averaged 53.4% per year. There were no hunting deaths in RY4−RY5 by design. During the treatment years TY1−TY5, total detected deaths ranged from 9−17 per year. Natural causes of death ranged from 11.1−25% and averaged 18.6% per year. Other human-caused deaths (excluding hunting) ranged from 8.3−36.4% and averaged 24.6% per year. Hunting-caused deaths ranged from 45.5−69.2% and averaged 56.8% per year. Total human-caused deaths (with hunting) ranged from 75−88.9% and averaged 81.4% per year. Of the total human-caused deaths, hunting ranged from 55.6−88.9% and averaged 70.6%. Puma density The density of independent pumas based on our defined winter search area (1,701 km2, 657 mi.2) ranged from 1.9/100 km2 in RY4 to a high of 3.3/100 km2 in TY1 (Table 6). During the treatment period, density declined from 3.3/100 km2 to a low of 2.5/100 km2 in TY4 and increased only slightly in RY5 to 2.6/100 km2. For broader management considerations in Colorado (see Analytical Methods, Puma density, previously), the density of independent pumas based on puma habitat as defined by the Colorado puma RSF model was based on two strata groupings (Table 6). In the first, we calculated density for strata 20 �3 and 4 combined (1,636 km2). Strata 3 and 4 represented 0.50 to 0.749 and 0.75 to 0.99 probability of puma presence, respectively. These density estimates were very similar to our estimates based on winter search area because of the similarity in the areas (i.e., total km2) where pumas were concentrated with their ungulate prey in winter. In the second grouping of RSF strata, we included the area of stratum 2, which represented 0.25 to 0.49 probability of puma presence. The combined area of strata 2, 3, and 4 was 2,426 km2, and therefore produced lower density estimates (Table 6). We did not include stratum 1 because it was comprised primarily of non-puma habitat, including towns, reservoirs, farmlands, and high elevation areas with deep snow that probably could not sustain pumas in winter. Expected presence of pumas in stratum 1 was 0.001 to 0.249. Puma harvest density We assumed that Colorado RSF strata 3 and 4 combined represented mule deer, elk, and puma winter range, which was consistent with our direct observations on the UPSA. Puma harvest densities on the UPSA during the puma population decline (TY1−TY3) ranged from 4.9−5.5 and averaged 5.1 independent pumas/1,000 km2 of RSF strata 3 and 4 combined (Table 7A). During the entire treatment period TY1−TY5, which included the population decline and low phases, harvest density ranged from 3.1−5.5 and averaged 4.3 pumas/1,000 km2. Considering that the UPSA puma population was partially affected by hunting in surrounding GMUs, we calculated harvest densities for those same RSF strata in GMUs adjacent to the UPSA, including 61 North, 62 North, 65, and 70 during the treatment period (CPW puma harvest data, Denver, CO). Generally, harvest densities all five years in each of the GMUs, except for 62 North, was within or greater than the range of harvest densities on the UPSA during the population decline phase during TY1−TY3 (Table 7A). In all four of the adjacent GMUs combined, harvest densities ranged from 3.2−5.4 and averaged 4.8 pumas/1,000 km2, and three of the five years exhibited harvest densities within the range of UPSA harvest densities during the decline phase TY1−TY3 (Table 7A). The percentage of adult females in the combined harvest for all 4 of the GMUs during TY1−TY5 ranged from 10.3−35.3% and averaged 18%. Assuming that the puma harvest densities and the percent of adult females in the harvest (i.e., 20%) with other natural and human causes of death on the UPSA during TY1−TY3 following a 5-year hiatus from hunting mortality relate to population decline, then one interpretation is that it is probable that puma abundance in the area of these adjacent GMUs declined or was in a low phase if they also experienced similar rates of natural and other human causes of mortality (Fig. 7A). We also presented puma harvest densities on the UPSA and the same adjacent GMUs based on RSF strata 2, 3, and 4 areas for consideration by managers (Table 7B, Fig. 7B). Our interpretation of these results was similar to results of the previous analysis using RSF strata 3 and 4, except that four of the five years exhibited harvest densities within the range of UPSA harvest densities during the decline phase TY1−TY3. Puma age structure The age structure of independent male pumas we examined in the UPSA declined from TY1 to TY5 (Fig. 8). After 5 years of no hunting, the younger and up to middle aged (i.e., 1−5 years old) pumas comprised a majority (55.3%) of the population and with both adult females and males being represented up to the oldest ages (i.e., >5−10+ years old). After 5 years of hunting, adult males >5 years old were eliminated from the age structure. Previously at TY1 adult males >5−10+ years old had comprised 57% of the adult male (>2 yr. old) population. There was an increase in the abundance of subadult males by TY5, but recruitment of males into the adult stage during the treatment period was not sufficient to numerically replace the adult males that died. There was no noticeable change in the female age structure in the treatment period although there was a 23.3% decline in the abundance of adult females from TY1−TY5 (previously). The changing age structure and abundance of independent pumas at each age could be explained by patterns of puma survival associated with the hunting treatment of the population. Puma survival Adults 21 �Our adult survival sample included 75 radio-collared individuals, with 32 monitored in the reference period and 61 monitored in the treatment period. The most parsimonious survival model indicated a treatment effect on gender with gender interacting with period (i.e.,{S(gender*period)}; Table 8). The evidence ratio for this model using AICc weights (wi) indicated it had only 1.3 times the support of the second-ranked model with gender interacting with combined mule deer and elk abundance. These two top models explained over 86% of the variation in adult puma survival. However, when we graphed the estimates of deer and elk abundance with model generated estimates of annual adult female and male puma survival rates (converted from monthly rates), a serendipitous relationship was revealed (Fig. 9). That relationship was clearly and directly influenced by our manipulation of the puma population which resulted in the high adult puma survival in the reference period and the decline in adult male puma survival during the treatment period, mainly caused by our hunting treatment. Mule deer and elk abundance generally declined during the reference period and the first 3 years of the treatment period. But then ungulate abundance seemed to stabilize or increase slightly in TY4 and TY5 at the same time we purposely reduced the harvest rate of pumas which also was reflected in the adult survival rate estimates. Therefore, we believe the model of gender interacting with deer and elk abundance was primarily coincidental with our study design and attendant manipulation rather than a biological explanation for variation in adult puma survival. We did not observe malnutrition or starvation as a common malady in adult pumas we examined. Only one adult female puma died apparently due to starvation associated with senescence; she was about 11 years old when she died in TY3 of the treatment period. Considering this, we reduced the model set by excluding the models with deer and elk abundance as a covariate (Table 9). The reduced set of adult puma survival models indicated gender interacting with period as the most parsiminious model (Table 9). The evidence ratio using AICc weights (wi) indicated very strong support for the top model with 10.10 times the support of the second model with gender in an additive effect with period. Moreover, >4 ∆AICc separated the top model from the second-ranked model. Thus, the remainder of the models in the 6 model candidate set had weak to no support. Adult male survival declined significantly (i.e., 95% confidence intervals did not overlap) from 0.96 (95% CI = 0.746−0.994) in the reference period to 0.40 (95% CI = 0.223−0.569) in the treatment period. The decline in adult male survival was also indicated by the 50% decline in the abundance of adult males in the treatment period (Fig. 4). The adult female survival estimate was higher for the reference period (i.e., 0.86; 95% CI = 0.715−0.935) than the treatment period (i.e., 0.74; 95% CI = 0.632−0.823), but the difference was not statistically significant (i.e., 95% confidence intervals overlapped; Table 10). However, the 23.3% decline in the abundance of adult females in the population during the treatment period indicated that lower survival was biologically significant, as we did not observe radio-collared adult females emigrating from the population and female recruitment was not sufficient to replace the adult females that died (Fig. 4). Subadults Our subadult survival sample included 75 individuals with known-fates: 22 in the reference period and 53 in the treatment period. For subadult pumas the modeling results indicated period as an important factor influencing survival as indicated by the two top-ranked models <2 ∆AICc points (Table 11), which together accounted for 77% of the model weights (wi). Evidence ratios using AICc weights (wi) indicated the top-ranked model of gender interacting with period had weak support for the best model with 1.7 times the support of the second-ranked model with period as the main explanatory factor. Subadult males were negatively affected by hunting-caused mortality, similar to adult males. Subadult male survival declined significantly from 0.92 (95% CI = 0.611−0.989) in the reference period to 0.43 (95% CI = 0.265−0.607) in the treatment period. However, subadult female survival estimates increased in those respective periods from 0.63 (95% CI = 0.232−0.906) to 0.70 (95% CI = 0.425−0.883), but the difference was not statistically significant (Table 10). The second-ranked model Speriod (with genders combined) had reasonable support as the best model (i.e., 1.0567 ∆AICc, wi=0.28631) for explaining variation in subadult survival which declined from 22 �0.84 (95% CI = 0.599−0.946) in the reference period to 0.52 (95% CI = 0.37−0.659) in the treatment period, but the difference was not statistically significant (Table 12). Recruitment of subadults was not sufficient to offset the mortalities of adult males and females, as the abundance of both declined during the treatment period (previously). Three models not in Table 11 included: [{S(month*period)}, {S(month*gender)}, {S(month*period*gender)}] in which MARK could not estimate all the parameters because of the sparseness of the monthly data. Cubs Our cub survival sample included 118 radio-collared cubs: 55 cubs from 32 litters in the reference period, and 63 cubs from 45 litters in the treatment period. We could not use the most parameterized model {S(month*period*gender)} or model {S(month*period)} to estimate c-hat because MARK could not estimate all of the parameters due to the sparseness of the monthly data. Therefore, we used the next most parameterized model {S(period*gender)}. The estimated c-hat for kitten survival was 1.545, indicating that the fates of siblings were not independent. We documented numerous occasions of this phenomenon. In the reference period 9 radio-collared siblings in 4 litters died at the same time due to infanticide. In addition 3 non-collared cubs in 1 litter starved after the dam was killed for depredation control. In the treatment period 19 radio-collared siblings in 8 litters died at the same time due to a variety of causes, including: depredation control (3 cubs in 1 litter), vehicle strike (2 cubs in 1 litter), infanticide (7 cubs in 3 litters), and starvation (7 cubs in 3 litters). Of the 3 litters that starved, the dams died due to a natural cause, hunting, and depredation control. In addition, 2 non-collared cubs in 1 litter died from infanticide. Modeling results indicated three models with <2 QAICc with the covariate for dam’s status (i.e., damld) that accounted for 66% of the model weights (wi) (Table 13). These models indicated that whether the dam lived or died [{S(damld)}] was the single most important factor affecting cub survival. Evidence ratios using QAICc weights (wi) indicated the top model with the covariate damld alone had 2.5 times the support of the second-ranked model [{S(gender+damld)}] and 2.7 times the support of the third-ranked model {{S(period+damld)}]. However, the second- and third-ranked models provided additional information about how cub survival varied with gender and period (Table 14). Cub survival considering dam status alone was 0.45 (95% CI = 0.34−0.57) for the entire study duration. Considering gender additive to dam status, female cub survival was 0.42 (95% CI = 0.27−0.58) and similar to male cub survival of 0.48 (95% CI = 0.33−0.63). Considering period additive to dam status, there was no statistically significant change in cub survival in the reference period (S = 0.47; 95% CI = 0.31−0.64) and the treatment period (S = 0.43; 95% CI = 0.28−0.59). These top models and data on fates of dams indicated that any factors that contributed to a dam’s death while cubs were dependent resulted in lower cub survival. There was no support for period alone explaining variation in cub survival (∆QAICc = 5.8). Likewise, there was no support for mule deer and elk abundance influencing cub survival (∆QAICc >4.5 for all models with the covariate). Starvation in cubs that we observed occurred because their mothers were no longer alive to provision them, not because of a lack of deer and elk in the environment. We estimated the probability of cub survival to the adult stage (i.e., 2 yr. old) by using survival estimates from the set of top-ranked survival models (<2 QAICc) from this study (see Tables 11−14). For cubs we used model S(period+damld) (third-ranked model) and for subadults we used model S(period) (second-ranked model) for both genders. The estimated probability of cub survival to the adult stage in the reference period was 0.39 (1*0.471cubS*0.837subadultS = 0.394). The estimated probability of cub survival to the adult stage in the treatment period was 0.22 (1*0.431cubS*0.515subadultS = 0.222). Puma reproduction Adult female pumas on the Uncompahgre Plateau produced litters of cubs between the months of March to September, spanning the early spring to early fall seasons. Data on 66 birth dates revealed that births increased rapidly in May and June, peaked in July, followed by a slight decline in August and a 23 �rapid decline in September. No live births were detected in the months of October, November, December, January, or February (Fig. 10). Considering a 92-day gestation period (Anderson 1983, Logan and Sweanor 2001, this study), the distribution of birth months indicated that puma breeding activity would have spanned the months of December to June, with a rapid increase in February and peaking March through May. We estimated gestation for 17 litters by 13 females based on GPS- or VHF- location data of females with prospective sires that produced minimum and maximum estimates. Gestation lengths averaged 90.4min−91.8max days (SDmin = 2.6, 95% CImin = 89.1−91.6; SDmax = 1.0, 95% CImax = 90.7−92.8). Birth intervals for 18 adult females that produced 33 litters averaged 18.5 months (SD = 5.9, 95% CI = 16.4−24.4). We estimated the age of 13 adult females when they produced their first litters that we were able to observe based on estimated ages (n = 11) or known-ages (n = 2) of pumas at previous captures and nipple characteristics (i.e., tiny, pink or white color) and associated reproduction histories. As a practical matter, we probably would not have observed births of litters if the cubs died before the 2−4 weeks it took us to confirm the production of litters by observation. Therefore, some of the ages we recorded may be biased high. The median age at first litter was 30 months (range = 21−48); the average was 32.2 months (SD = 8.4, 95% CI = 27.6−36.8). This meant those females conceived at the median age of 27 months (range = 18−45); the average age was 29.2 months (SD = 8.4, 95% CI = 24.6−33.8) assuming an average 92 day gestation period. Litter sizes were determined for 26 litters produced by 14 females in the reference period where we were reasonably certain we counted all the cubs in nurseries when the cubs were 26 to 42 days old. Likewise, we determined litter sizes for 21 litters of 16 females in the treatment period for nursling cubs 25 to 45 days old. Average litter sizes for each period estimated using linear mixed models were 2.76 (SE = 0.1806, 95% CI = 2.41−3.12) for the reference period and 2.38 (SE = 0.1972, 95% CI = 1.99−2.76) for the treatment period. Change in the average litter sizes in the two periods was small and not statistically significant because the 95% confidence intervals on the slope for period included zero. The male:female sex ratio for 72 nursling cubs in the reference period was 41:31 and was not significantly different from an expected 1:1 ratio (χ2 = 1.388, 1 d.f., 0.10 < P < 0.25). Similarly, the 27:22 sex ratio for 49 nurslings in the treatment period was not significantly different from an expected 1:1 ratio (χ2 = 0.51, 1 d.f., 0.25 < P < 0.50). With all the cubs pooled from both periods, the sex ratio 68:53 was not significantly different from parity (χc2 = 1.860, 1 d.f., 0.10 < P < 0.25). Parturition rate, defined here as the proportion of adult female pumas giving birth each year, was determined for reference period years RY2−RY5 when we radio-monitored 12 to 13 individual females per year and treatment period years TY1−TY5 when we radio-monitored 15 to 17 individual females per year. Average parturition rate per year for each period estimated using generalized linear mixed models was 0.63 (SE = 0.068, 95% CI = 0.49−0.75) for the reference period and 0.48 (SE = 0.057, 95% CI 0.37−0.59) for the treatment period. Although the average parturition rate in the reference period was higher than in the treatment period, the change was not statistically significant because the 95% confidence interval for the slope included zero. Conclusions The general purpose of this research was to investigate potential effects of sport-hunting on a puma population in Colorado, because the puma population in the state is managed and conserved primarily by regulating puma sport-hunting with kill quotas. More specifically, the purpose was to test puma management assumptions used by CPW to manage puma population segments with sport-hunting. The preponderance of evidence from the data indicated that the addition of hunting as a mortality factor limited the puma population. In the context of the GMU-based puma management structure in Colorado, 24 �elimination of puma hunting in a reference period resulted in at least a 70% increase in the abundance of independent pumas and high adult and subadult male survival rates. However, in a treatment period a 15% design harvest including 32% females in the harvest in addition to other human-caused and natural mortality during TY1−TY3 resulted in a 25% decline in independent puma abundance by TY4 in the UPSA GMU. Declines in the abundance of independent pumas overall and adult female and male pumas in annual winter counts, survival of adult and subadult male pumas, and male age structure all were biologically significant changes associated with sport-hunting mortality with other human and natural causes of mortality operating on the puma population. There was no evidence of biologically significant compensatory reproduction or immigration with recruitment to offset the mortalities in adult pumas during the treatment period. Hunting-caused mortality to independent pumas on UPSA in the treatment period was the single-most important cause of death ranging from 11.4−16.7% of independent pumas per winter. Additional hunting mortality of independent pumas that ranged onto adjacent GMUs contributed to a decline and low phase in abundance of UPSA pumas from TY1−TY5, with total hunting mortality (i.e., occurring on and around UPSA) ranging from 11.4−25% (average = 18.2%) of independent pumas on the UPSA each winter. Responses of the UPSA puma population to our designed manipulations in both the reference and treatment periods indicated that puma population segments at the GMU-size represented by UPSA can be managed for specific population segment objectives as long as managers understand the potential effects of sport-hunting, other human caused-, and natural mortality on puma abundance on the GMU of interest and the surrounding GMUs. Management Implications 1) In the GMU-based puma management structure in Colorado, a design hunting-caused mortality of ≥15% of independent pumas with an average of ≥20% adult (i.e., 2 years old and older) females in the harvest, and with other human and natural causes of mortality ranging from 16.1−20.8% each hunting season operating on a relatively high density puma population can cause 25% reduction in the independent puma population after 3 hunting seasons. Hunting harvest is the only component of puma mortality that can be managed by regulation to determine population trend, as the other causes of mortality (natural and other human causes) occur randomly and vary in amount annually. Moreover, natural causes of death are rarely observed by managers, but other human causes (e.g., depredation control kills, some vehicle strikes) are observed and recorded and occur throughout any year. In our study, other human causes of death comprised about 24−29% of the total human-caused mortality in independent pumas (i.e., 74−81% of all deaths) with 71−76% of deaths (depending on accounting method) due to hunting in the treatment period on the UPSA GMU when the puma population declined to a low phase. 2) It can take up to 5 years for a puma population previously reduced to a low density to recover to a relatively high density after hunting has been eliminated. 3) Design hunting harvests of up to 11−12% of independent pumas with an average of <20% adult (i.e., 2 years old and older) females in the harvest and with total mortality to independent pumas ranging from 13.6−14.3% is expected to result in a stable, possibly increasing population, considering that other human- and natural-causes of mortality will operate on the population. 4) Total mortality metrics in each hunting season treatment year associated with the decline in the independent puma population on UPSA during TY1−TY3 averaged 18.7% (range = 16.1−20.8%). During TY4 and TY5 when the population decline stopped and possibly increased slightly total mortality to independent pumas were 14.3% and 13.6%, respectively. If total mortality metrics are used by managers to set kill quotas, all detected mortalities of independent pumas occurring during hunting seasons should be discounted from quotas. 5) Other metrics that might be useful to managers for gauging potential effects of hunting mortality include harvest density and percentage of adult females in the harvest. On the UPSA, we observed a declining abundance of independent pumas when harvest density was 4.9−5.5 independent pumas/1000 km2 of RSF strata 3 and 4 combined and the percentage of adult females 25 �6) 7) 8) 9) in the harvest was 20%. For RSF strata 2, 3, & 4 combined, the abundance of independent pumas declined when the harvest density was 3.3−3.7 independent pumas/1000 km2. Puma population segment management objectives can be achieved at the GMU level as exhibited by the puma population responses to our research manipulations on UPSA GMU-size study area (2,996 km2, 1,157 mi.2). Puma hunting harvest can affect puma abundance in the particular GMUs of interest and adjacent GMUs where puma home ranges overlap GMU boundaries because GMUs in connected puma habitat are not closed puma populations. Puma harvest management structure which includes provisions for reducing puma population segments to achieve specified management objectives (e.g., reduce predation on livestock or mule deer populations) should also provide for puma population segments managed with conservative harvest rates to allow for stable or increasing puma population segments (i.e., source-sink management) to ensure overall puma population resiliency because of all the unknowns and uncertainties associated with puma population management, including puma abundance, and effects of harvest and other human and natural causes of mortality in GMUs. Management experiments and research involving puma population segments should consider potential population effects of historical puma hunting on and around the study areas. When experimental designs require reference conditions, human-caused mortality to pumas should be limited or eliminated if possible. 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Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K. M. 1983. Relationships between a mountain lion population and hunting pressure in western Montana. Master’s Thesis, University of Montana. Pierce, B. M., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: Does a landtenure system regulate population size? Ecology 81:1533-1543. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Ruth, T. K., M. A. Haroldson, K. M. Murphy, P. C. Buotte, M. G. Hornocker, H. B. Quigley. 2011. Cougar survival and source-sink structure on Greater Yellowstone’s Northern Range. Journal of Wildlife Management 75:1381-1398. 27 �Spreadbury, B. R., K. Musil, J. Musil, C. Kaisner, and J. Kovak. 1996. Cougar population characteristics in southeastern British Columbia. Journal of Wildlife Management 60:962-969. Stoner, D. C., M. L. Wolfe, and D. M. Choate. 2006. Cougar exploitation levels in Utah: Implications for demographic structure, population recovery, and metapopulation dynamics. Journal of Wildlife Management 70:1588-1600. Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Watkins, B. 2004. Mountain lion Data Analysis Unit L-22 Management Plan. Colorado Division of Wildlife, Denver, Colorado. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Wielgus, R. B., D. E. Morrison, H. S. Cooley, and B. Maletzke. 2013. Effects of male trophy hunting on female carnivore population growth and persistence. Biological Conservation 167:69-75. Yeager, K. 2016. A noninvasive method using auditory predator calls and hair snares to detect and genetically sample cougars (Puma concolor). Master’s Thesis. Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Ft. Collins. Zar, J. H. 1984. Biostatistical analysis. Second edition. Prentice Hall, Englewood Cliffs, New Jersey. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 28 �Table 1. Puma search areas on the Uncompahgre Plateau Study area. West-side East-side 25 Mesa Road to Cottonwood Creek and San 25 Mile Mesa Road to east rim of Roubideau Miguel Canyon (west reach) Canyon and Ben Lowe Mesa ---------------------------------------------------------------------------------------------------+-------------------------------Cottonwood Creek to Horsefly Canyon Roubideau Canyon to Transfer Road ---------------------------------------------------------------------------------------------------!-------------------------------San Miguel Canyon (mid reach) to Maverick Draw Transfer Road to east rim of Dry Creek Basin ---------------------------------------------------------------------------------------------------!-------------------------------Horsefly Canyon and San Miguel Canyon (mid East rim of Dry Creek Basin to east rim of Spring reach) to Clay Creek Canyon ---------------------------------------------------------------------------------------------------!-------------------------------Clay Creek and San Miguel Canyon (upper reach) Spring Canyon to Happy Canyon to McKenzie Creek ---------------------------------------------------------------------------------------------------!-------------------------------McKenzie Creek and San Miguel Canyon (upper Happy Canyon to Horsefly Canyon reach) to Leopard Creek ---------------------------------------------------------------------------------------------------+-------------------------------Horsefly Canyon to McKenzie Butte McKenzie Butte to Loghill Mesa Table 2. Winter count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during reference years 4 and 5 (RY4, RY5) and treatment years 1-5 (TY1─TY5). Also indicated * is the population projection for RY5 due to lack of a reliable count (see text), Uncompahgre Plateau study area, Colorado. Period & Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Study Area region Adults Female Male Subadults Female Male Female East slope 10 4 3 4 4 West slope 6 4 2 0 1 subtotals 16 8 5 4 5 Total Independent Pumas = 33: 21 females, 12 males. Cubs = 20-21 East slope 11-13 5-6 2-4 0-1 2 West slope 9-10 4 1-2 1 3 subtotals 20-23 9-10 3-6 1-2 5 Total Independent Pumas = 37 counted, *45 modeled estimated East slope 16 10 1 2 1 West slope 14 10 0 3 3 subtotals 30 20 1 5 4 Total Independent Pumas = 56: 31 females, 25 males. Cubs = 18-23 East slope 15 5 3 2 7 West slope 15 7 2 3 2 subtotals 30 12 5 5 9 Total Independent Pumas = 52: 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 West slope 14 5 3 5 1 subtotals 27 9 4 8 5 Total Independent Pumas = 48: 31 females, 17 males. Cubs = 19 East slope 15 4 3 2 4 West slope 10 5 3 0 2 subtotals 25 9 6 2 6 Total Independent Pumas = 42: 31 females, 11 males. Cubs = 24 East slope 10 6 3 6 6-7 West slope 13 4 1 1 1 subtotals 23 10 4 7 7-8 Total Independent Pumas = 44: 27 females, 17 males. Cubs = 25-28 29 Cubs Male 4 2 6 Unknown sex 7 2-3 9-10 5 2 7 5 4 9 3 3 6 4-8* 5-6 9-14 9 5 14 7 9 16 2 2 4 4 6 10 4 5 9 3 6 9 2 3 5 2 11-13 13-15 �Table 3A. Independent pumas killed by hunters on the study area during each of the treatment period hunting seasons, Uncompahgre Plateau, Colorado. Adult Treatment Period Year Female Male TY1 2 5 TY2 0 5 TY3 3 1 TY4 2 2 TY5 1 3 subtotals 8 16 Subadult Female 1 2 0 0 0 3 Male 1 1 4 1 1 8 Quota 8 8 8 5 5 Actual No. pumas killed 9 8 8 5 5 No. of Independent pumas in count 56 52 48 42 44 Percent harvest of Independent pumas 16.1 15.4 16.7 11.9 11.4 Table 3B. Independent pumas that died of all causes (i.e., total mortality) on the study area during each of the treatment period hunting seasons, Uncompahgre Plateau, Colorado. Treatment Hunting Vehicle Depredation Natural Total Winter % yr. season strike control mortalities count mortality TY1 9 0 0 9 56 16.1 TY2 8 0 2 10 52 19.2 TY3 8 0 0 2 10 48 20.8 TY4 5 0 0 1 6 42 14.3 TY5 5 0 0 1 6 44 13.6 30 �Table 4A. Causes of death in adult, subadult, and cub pumas in the reference and treatment periods, Uncompahgre Plateau, Colorado. Reference Period Adults (21F,11M at Females Females Males Males Total Total risk Number Percent Number Percent Number Percent Strife 3 50 1 100 4 57 Other natural 1 16.7 0 0 1 14.3 Vehicle strike 1 16.7 0 0 1 14.3 Depredation control 1 16.7 0 0 1 14.3 Illegal kill 0 0 0 0 0 0 Hunting 0 0 0 0 0 0 Subadults (8F,14M at risk) Strife 0 0 0 0 0 0 Other natural 1 50 0 0 1 33.3 Vehicle strike 1 50 0 0 1 33.3 Depredation control 0 0 0 0 0 0 Illegal kill 0 0 0 0 0 0 Hunting 0 0 1 100 1 33.3 Cubs (28F,27M at risk) Infanticide 9 75 4 100 13 81.3 Predation 1 8.3 0 0 1 6.2 Other unknown natural 1 8.3 0 0 1 6.2 Starvation 0 0 0 0 0 0 Vehicle strike 1 8.3 0 0 1 6.2 Depredation control 0 0 0 0 0 0 Illegal kill 0 0 0 0 0 0 Hunting 0 0 0 0 0 0 31 �Table 4B. Continued Adults (39F,22M at risk) Strife Other natural Vehicle strike Depredation control Illegal kill Hunting Subadults (19F,34M at risk) Strife Other natural Vehicle strike Depredation control Illegal kill Hunting Cubs (27F,36M at risk) Infanticide Predation Other unknown natural Starvation Vehicle strike Depredation control Illegal kill Hunting Mauled by dogs Treatment Period Females Females Males Number Percent Number 3 14.3 0 7 33 0 2 9.5 1 2 9.5 0 0 0 1 7 33 14 Males Percent 0 0 0 0 6.7 93.3 Total Number 3 7 3 2 1 21 Total Percent 8.1 18.9 8.1 5.4 2.7 56.8 1 0 0 1 0 2 25 0 0 25 0 50 2 2 1 2 0 9 12.5 12.5 6.2 12.5 0 56.2 3 2 1 3 0 11 15 10 5 15 0 55 3 0 0 5 0 2 0 0 0 30 0 0 50 0 20 0 0 0 5 0 4 4 2 1 0 0 1 29.4 0 23.5 23.5 11.8 5.9 0 0 5.9 8 0 4 9 2 3 0 0 1 29.6 0 14.8 33.3 7.4 11.1 0 0 3.7 32 �Table 5. Percent of deaths by cause of marked and non-marked independent pumas by study year RY4−TY5, Uncompahgre Plateau study area, Colorado. Study RY4 RY5 Average % of TY1 TY2 TY3 TY4 TY5 Average % of Year deaths in deaths in reference years 13 treatment years 5 3 17 12 9 11 Total no. RY4−RY5 TY1−TY5 deaths 60 33.3 46.7 15.4 23.5 25.0 11.1 18.2 18.6 % Natural deaths 40 66.7 53.4 15.4 29.4 8.3 33.3 36.4 24.6 % Other humancaused deaths 0 0 0 69.2 47.1 66.7 55.6 45.5 56.8 % Hunting deaths 40 66.7 53.4 84.6 76.5 75.0 88.9 81.8 81.4 % Total humancaused deaths 0 0 0 81.8 61.5 88.9 62.5 55.6 70.6 Hunting as % of humancaused deaths 33 �Table 6. Density* of independent pumas per 100 km2 on the Uncompahgre Plateau, Colorado. Study Year Estimated Estimated density of Estimated density of Estimated density of No. independent independent pumas/100 independent pumas/100 independent pumas/100 km2 of km2 of RSF strata 3 and km2 of RSF strata 2, 3 pumas winter search area 4 (1,636 km2) and 4 (2,426 km2) 2 (1,701 km ) RY4 33 1.9 2.0 1.4 RY5 45 2.6 2.8 1.9 TY1 56 3.3 3.4 2.3 TY2 52 3.1 3.2 2.1 TY3 48 2.8 2.9 2.0 TY4 42 2.5 2.6 1.7 TY5 44 2.6 2.7 1.8 *Density/100 km2=winter count/area*100. Table 7A. Harvest density of independent pumas per 1,000 km2a in combined Colorado puma RSF strata 3 & 4 combined during the treatment period on the UPSA and surrounding GMUs 61 North, 62 North, 65, and 70. GMU puma harvest density/1000 km2 RSF strata 3 & 4 combined Study UPSA 61 North 62 North 65 70 GMUs 61 North, 62 North, Year (1,635)b (1,204) (1,043) (912) (2,211) 65 & 70 combined (5,369) TY1 5.5 5.8 1.0 4.4 6.3 4.8 TY2 4.9 2.5 2.9 5.5 2.7 3.2 TY3 4.9 5.8 6.7 6.6 3.6 5.2 TY4 3.1 5.0 3.8 7.7 5.4 5.4 TY5 3.1 3.3 5.8 6.6 5.4 5.2 a Harvest density=No. independent pumas reported killed by hunters/GMU strata area km2*1000. b Numbers in parenthesis=area in GMU comprised of Colorado puma RSF strata 3 & 4. Table 7B. Harvest density of independent pumas per 1,000 km2a in combined Colorado puma RSF strata 2, 3, & 4 combined during the treatment period on the UPSA and surrounding GMUs 61 North, 62 North, 65, and 70. GMU puma harvest density/1000 km2 RSF strata 2, 3 & 4 combined Study UPSA 61 North 62 North 65 70 GMUs 61 North, 62 North, Year (2,426)b (1,419) (1,477) (1,443) (3,362) 65 & 70 combined (7,701) TY1 3.7 4.9 0.7 2.8 4.2 3.4 TY2 3.3 2.1 2.0 3.5 1.8 2.2 TY3 3.3 4.9 4.7 4.2 2.4 3.6 TY4 2.1 4.2 2.7 4.9 3.6 3.8 TY5 2.1 2.8 4.1 4.2 3.6 3.6 a Harvest density=No. independent pumas reported killed by hunters/GMU strata km2*1000. b Numbers in parenthesis=area in GMU comprised of Colorado puma RSF strata 2, 3, & 4. 34 �Table 8. Adult puma survival modeling results, Uncompahgre Plateau, Colorado. AICc Model Number Model AICc ∆AICc Weights Likelihood Parameters Deviance {S(gender*period)} 396.9874 0 0.49405 1 4 162.0375 {S(gender*deerelk)} 397.5432 0.5558 0.37418 0.7574 4 162.5933 {S(gender+period)} 401.613 4.6256 0.0489 0.099 3 168.6719 {S(gender*year)} 402.1608 5.1734 0.03719 0.0753 14 147.0023 {S(gender+deerelk)} 402.4021 5.4147 0.03296 0.0667 3 169.461 {S(period)} 405.339 8.3516 0.00759 0.0154 2 174.4044 {S(deerelk)} 406.1359 9.1485 0.0051 0.0103 2 175.2013 {S(gender)} 416.7478 19.7604 0.00003 0.0001 2 185.8131 {S(.)} 417.3778 20.3904 0.00002 0 1 188.4475 {S(month)} 509.8345 112.8471 0 0 108 53.2893 {S(gender*month)} 716.7591 319.7717 0 0 216 0 Table 9. Reduced model set for adult puma survival, Uncompahgre Plateau, Colorado. Model Number ∆ AICc AICc wi Likelihood Parameters Deviance Model AICc {S(gender*period)} 396.9874 0 0.84055 1 4 162.0375 {S(gender+period)} 401.613 4.6256 0.0832 0.099 3 168.6719 {S(gender*year)} 402.1608 5.1734 0.06327 0.0753 14 147.0023 {S(period)} 405.339 8.3516 0.01291 0.0154 2 174.4044 {S(gender)} 416.7478 19.7604 0.00004 0 2 185.8131 {S(.)} 417.3778 20.3904 0.00003 0 1 188.4475 Table 10. Puma adult and subadult annual survival rates, estimated from top model Sgender*period for each stage, Uncompahgre Plateau, Colorado. Adults (≥24 months old) Period Gender Average annual Lower 95% CI Upper 95% CI Survival estimate Reference Female 0.8599 0.7153 0.9345 Male 0.9593 0.7459 0.9942 Treatment Female 0.7415 0.6324 0.8230 Male 0.3971 0.2232 0.5692 Subadults (13-24 months old) Period Gender Survival estimate Lower 95% CI Upper 95% CI Reference Female 0.6303 0.2320 0.9058 Male 0.9233 0.6106 0.9893 Treatment Female 0.7026 0.4247 0.8832 Male 0.4272 0.2651 0.6071 35 �Table 11. Subadult puma modeling results, Uncompahgre Plateau, Colorado. Model Number Model AICc ∆ AICc AICc wi Likelihood Parameters Deviance {S(gender*period)} 190.0683 0 0.48562 1 4 39.4874 {S(period)} 191.125 1.0567 0.28631 0.5896 2 44.5933 {S(gender+period)} 192.1299 2.0616 0.17323 0.3567 3 43.5771 {S(.)} 195.2243 5.156 0.03687 0.0759 1 50.7065 {S(gender)} 196.6757 6.6074 0.01784 0.0367 2 50.1439 Table 12. Subadult puma survival rates estimated with second-ranked model Speriod, females and males combined, Uncompahgre Plateau, Colorado. Subadults (13─24 months old) Period Survival estimate Lower 95% CI Upper 95% CI Reference 0.8371 0.5991 0.9464 Treatment 0.5152 0.3685 0.6594 Table 13. Cub puma modeling results, Uncompaghre Plateau, Colorado. Delta AICc Model Number Model QAICc QAICc Weights Likelihood Parameters QDeviance {S(damld)} 201.4726 0 0.37516 1 2 197.4528 {S(gender+damld)} 203.3312 1.8586 0.14813 0.3948 3 197.2916 {S(period+damld)} 203.426 1.9534 0.14127 0.3766 3 197.3864 {S(gender*damld)} 204.6335 3.1609 0.07724 0.2059 4 196.5674 {S(period*damld)} 205.0772 3.6046 0.06187 0.1649 4 197.0111 {S(gender*deerelk)} 205.9641 4.4915 0.03971 0.1058 4 197.898 {S(.)} 206.6167 5.1441 0.02865 0.0764 1 204.6102 {S(deerelk)} 206.7965 5.3239 0.02619 0.0698 2 202.7767 {S(period)} 207.2866 5.814 0.0205 0.0546 2 203.2669 {S(birthmonth)} 208.0169 6.5443 0.01423 0.0379 2 203.9971 {S(period*gender)} 208.1739 6.7013 0.01315 0.0351 4 200.1078 {S(gender)} 208.3153 6.8427 0.01226 0.0327 2 204.2955 {S(gender+deerelk)} 208.3844 6.9118 0.01184 0.0316 3 202.3448 {S(gender+period)} 208.9231 7.4505 0.00904 0.0241 3 202.8835 {S(birthmonth^2)} 209.6091 8.1365 0.00642 0.0171 3 203.5694 {S(gender*period)+birthmonth} 209.6737 8.2011 0.00621 0.0166 5 199.5744 {S(gender+birthmonth)} 209.8226 8.35 0.00577 0.0154 3 203.783 {S(gender*period)+birthmonth^2} 211.6137 10.1411 0.00236 0.0063 6 199.4744 36 �Table 14. Cub puma survival rates estimated with top-ranked models, Uncompaghre Plateau, Colorado. Cubs (1─12 months old) Model Survival estimate Lower 95% CI Upper 95% CI {S(damld)} 0.450 0.338 0.567 {S(gender+damld)} 0.421 0.274 0.584 {S(period+damld)} I Reference period 0.471 0.306 0.641 0.282 0.594 I Treatment period 0.431 37 �43 ' 40 Figure 1. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70, with surrounding GMUs referred to in the text. 38 �Figure 2. The Uncompahgre Plateau Study Area Game Management Unit (UPSA) indicating all the puma search routes and the more intensively used search routes on the east and west winter search areas. 39 �)Q 50 - - - - - - - - z-----:.111 f '-,:____ _ _____,,= ----=-....aa =------=-=-------§ c.. 40 - - -~ _;., 45 -.............. ..... _. . .- • - 44 -~ - - - - - - - - - - - - - - • - ,,< ~ 4 _2 _ _ __ ~ 30 - - - - - - - - - - - - - - - - - - - - - - - - 4t Q. 4t "0 20 - - - - - - - - - - - - - - - - - - - - - - - - - .E 0 :z: 10 - - - - - - - - - - - - - - - - - - - - - - - - - 0 RYS RY4 TY1 TY2 TY3 TY4 Study Ye ar Figure 3. Annual winter counts of independent pumas, Uncompahgre Plateau, Colorado. Counts in RY4 and TY1 to TY5 are from ground surveys and capture efforts. RY5 is a modeled data point (see text). The count for RY5 is biased low because capture efforts were insufficient due to lack of personnel to thoroughly search the study area (see text). 60 50 )8 ~.., 40 C Cl.I ~ 30 11,1 Q. • • TY1 TY2 ] 20 0 :z; • • TY3 TY4 4 10 --, 0 Treatment Period Year l1idependent PL1111as ..,_No. Adu lt F ...... No. Adult M Figure 4. Change in numbers of independent and adult pumas, Uncompahgre Plateau, Colorado. Abundance of independent pumas declined 25% by TY4, adult females declined 23% by TY5, and adult males declined 55% by TY4 and 50% by TY5. See text for puma harvest rates. 40 �100.0 90.Q 80.0 70.0 60 .0 C: (II ...u(II 50.0 CL 40.0 ... ■ Ad ult F 30.0 2.0.0 10.0 ■ Ad ult M 0.0 Hunting Other human Natural Unknown Survived fate period Cause.s of Adt.dl Puma Mortality in Reference Period Figure 5A. Categories of causes of death in radio-collared adult pumas monitored during the reference period, Uncompahgre Plateau, Colorado. 70.0 60.0 50.0 ...; 40.0 ~ £ 30. 0 ■ Adult F 20.0 ■ Adult M 10.0 0.0 Hunting • Other human tlatural Unl-.nown Survived fat e penod Causes of Adult Puma Mortality In Treatment Period Figure 5B. Categories of causes of death in radio-collared adult pumas monitored during the treatment period, Uncompahgre Plateau, Colorado. 41 �100.0 90.0 80.0 70. 0 ....C: 60 .0 Cl.I u 50.0 Cl.I Q. 40.0 30.0 20 .0 ... ■ Subadlllt F ■ Subadlllt M 10.0 0. 0 Hunting Other Natural Unknown Survived human fate period Causes of Subadult Puma Mortality in Reference Period Figure 6A. Categories of causes of death in known-fate subadult pumas during the reference period, Uncompahgre Plateau, Colorado. 80~0 ~ - - - - - - - - - - - - - - - - 70.0 60.0 - + - - - - - - - - - - - - - - .., 50.0 - + - - - - - - - - - - - - - - - c: Cl.I l: 40.0 Cl.I c. 30.0 - + - - - - - - - - - - - - - - - - - ■ Subadult F ■ Subadlllt M 20.0 10.0 0.0 Hunting Other human l~atural Unknown Sllrvived fate period Causes of Subadult Pum'?I Mortality in Treatment Period Figure 6B. Categories of causes of death in known-fate subadult pumas during the treatment period, Uncompahgre Plateau, Colorado. 42 �<( 60 0 ~ 1 .! lQ 45 2 "' ... 3 "+l ~ 35 C: 4 la i "' s 5 ~ 55 § so i::i- 5 o. 40 §.... ~ C :c ! 30 25 Q. ~ 20 6 TYl TY2 1Y4 rY3 TVS Treatment Period Year No. Independent pumas on UPSA ...- Purn a h arvest / 1000 sq . km RSF Strata. 39:4 111 GMU s 61 N ,62M,65 1 70 combined .....,UPSA Puma harvest/ 1000 sq . lm1 RSF Strata 3&4 Figure 7A. Relationships of the abundance of independent pumas on the UPSA, puma harvest density on the UPSA, and harvest density on adjacent GMUs 61 North, 62 North, 65, and 70 in RSF strata 3 and 4 combined within each GMU during the treatment period, Uncompahgre Plateau Puma Project, Colorado. 0 60 0. 5 E ,:,&, 1 .,,er 3 "'E :::, 3. 5 Go 20 4 TY1 TY2 TY4 TY3 Treatment Period Vear TY5 llo. Independen t pumas on UPSA - Puma harvest / 1000 sq. km RSF St rata 2, l , 4 1n GMU$ 6111,6211 ,651 70 combined UPSA Puma h arvest / 1000 sq . km RSF Strata 2 ,3.4 Figure 7B. Relationships of the abundance of independent pumas on the UPSA, puma harvest density on the UPSA, and harvest density on adjacent GMUs 61 North, 62 North, 65, and 70 in RSF strata 2, 3 and 4 combined within each GMU during the treatment period, Uncompahgre Plateau Puma Project, Colorado. 43 �Agestn1 ctu1 e o r i udep endtni pum::1si11 Non•mbc1· 21109 at lt~ lnnhtg of lht> puma hnnUug :W:J'lOU Ill Tl t'a lmt'IIC Yea r J l lncom1n1hgre Plakan. C'olo1ad o. G 5 "' ~ 4 if ._ :3 ., i 0 1 0 I I- Female I r 1 to 2 >2 to >3 to -.4 lCl ,5 lo >6 lo ,7 ft) >8 lO >9 tCI 3 4 ~ fi 7 R ll LO ■ M.ile 101 A u•(yl":m ;I Agestrncture of independen t p umas in November 1013 at beginning of puma hunting season in Treatment Year 5. Uncompahgre Plateau. Colol'aclo. 6 ---------------------- "' 5 84 E3 0 Female o2 z. 1 t-----------=--~ r ------l r - ■ Ma l e 0 1 lo 2 >l' to >3 lo >4 to >5 to >.6 lo >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age (years) Figure 8. Age structures of independent pumas at the start of TY1 (top) and TY5 (bottom), Uncompahgre Plateau, Colorado. The top graph represents the age structure after 5 years of no sport-hunting and ages of independent pumas just before the first treatment hunting season on the study area. Therefore, it represents the oldest age structure after 5 years with no hunting. The bottom graph represents the change in age structure at the start of TY5 after 4 years of sport-hunting pumas (TY1─TY4) and other causes of mortality operated on the population. 44 �45000 "" 40000 ~ 35000 :, 1.200 +l~ii:::~::=;,;;;ii======================J ....recu 1.000 a:: iii > ·;;: ... c. ... 30000 0.800 Cl ~ 20000 0 .600 E :, {l 15000 OAOO .::: :, ~ 25000 re c.. C "Cl ] 10000 <t: :, Vl <( 0.200 iii 5000 ::, C C 0 .000 <( 0 RY2 RY3 RY4 RYS TYl TY2 TY3 TY4 TVS Study Year - DeerElk - AMS - AFS Figure 9. Mule deer and elk abundance combined estimates graphed with the modeled adult puma monthly survival rates converted to annual point estimates to illustrate this relationship. The relationship of deer and elk abundance to adult puma survival rates was influenced directly by our manipulation of the puma population that caused it to increase in the reference period and to decline in the treatment period. Therefore we excluded this model from the model set for adult puma survival (see text). 20 18 16 1.4 ~ ...$ 12 .2 10 0 0 z 8 6 I- f-- 4 2 0 ■ -,Jan. Feb. Mar. Apr. May June July Aug, Sep. Oct. lfov. Dec. Figure 10. Puma births (black bars) detected by month from May 19, 2005 to September 30, 2014 (n = 66 litters of 33 females; 60 litters were examined at nurseries when cubs were 25-45 days old, 4 litters were confirmed by tracks of ≥1 cubs following GPS- and VHF-collared mothers and 2 litters by remains of cubs of 2 GPS-collared mothers when cubs were ≤45 days old, Uncompahgre Plateau, Colorado. 45 �APPENDICES Appendix I. ACUC Capture and Handling Forms and Protocols File # _________________ Revised Date ______________ (ACUC Secretary will supply) COLORADO PARKS AND WILDLIFE ANIMAL CARE AND USE COMMITTEE (CPW ACUC) FORM FOR REVIEW OF NEW RESEARCH PROJECTS 1. Principal Investigator (s): Dr. Kenneth A. Logan, Mammals Researcher, CPW. Phone: 970-252-6013(o) or 970-275-3227(c) E-mail: ken.logan@state.co.us 2. 3. All investigators (including all individuals involved in implementing research: Principal investigator Ken Logan (CPW), all CPW technicians and other houndsmen. Location of facility or study area: The study area is on the Uncompahgre Plateau in western 4. Beginning date: December 1, 2008. 5. Ending date: April 1, 2014. 6. Title of project: Assessing Effects of Hunting on a Puma Population on the Uncompahgre Plateau, Colorado. 7. Species of animal (s): Puma concolor 8. A study Plan or Prospectus describing each research or pilot project is required with this form. Is the Study Plan attached? Yes _X_ No ___ 9. Rationale for use of this animal model: a. Explain why other models (e.g. nonanimal models, in vitro techniques) are inappropriate. This study pertains specifically to puma population dynamics and attendant effects of hunting off-take. It is intended to provide wildlife managers with useful information for the management of pumas in Colorado. b. If not a species specific study, why is this the most appropriate species for this research? Colorado in areas west and southwest of Montrose. The study area is the South Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties). The study area includes about 2,200 km2 of the southern halves of GMUs 61 and 62, and about 155 km2 of the northern edge of GMU 70. The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. c. If capturing wild animals for pen research, why is this source most appropriate? 46 �10. 11. If the study will use wild animals, describe capture and transport methods: Please refer to the attached study plan Puma capture and marking (pages 13-15, 18, 24) and the Mountain Lion Capture and Handling Guidelines. Location of capture: Pumas will be captured on the study area described in question 3 above. 12. Indicate number of animals to be used _20-30 pumas/year_. Provide a brief justification (or page reference in Study Plan) for sample size selected: Please see study plan sections Puma capture and marking, Population monitoring, and Population Size (pages 13-19). 13. By signing this form, you are verifying that all persons involved in this project are adequately trained. Briefly describe the training process(es) and list personnel responsible for animal care and handling: K. Logan, S. Young, have all been trained in and have directly captured, immobilized, and sampled pumas. All new technicians and houndsmen will receive training on pumas by principal investigator Ken Logan. 14. Provide a detailed description of the procedures and manipulations of animals, including an end point (if necessary) at which animals will be removed from experiment or be euthanized. (If described in Study Plan or Prospectus, provide reference page numbers.) If administration of anesthesia and /or surgery is part of the procedure, identify who will perform these tasks: Please see study plan section Puma capture and marking (pages 13-19). 15. Are the levels of pain and suffering, stress, discomfort, deprivation, etc., to be experienced by experimental animals greater than normally associated with handling, administration of therapeutics by commonly used methods, or routine venipuncture? Yes __ No _X_ If answered yes, attach a detailed justification and indicate here the date of search, some of literature search, date range searched, and key words and combination of key words searched to document the lack of alternative methods: 16. 17. Will pain and suffering be controlled? Yes ____ No ____ N/A _X__ If answered no, attach a detailed justification. Describe how pain and suffering not associated with routine handling will be controlled. a. Methods and dosage of anesthesia to be used: N/A b. Methods and dosage of analgesia to be used: N/A c. Methods and dosage of tranquilization to be used: N/A The attending veterinarian must be consulted when planning projects where handling of any animal will occur. Do this prior to submitting this application. Date consulted_________ Does the proposed project include planned euthanasia of animals? Yes _____ No _X__ 47 �Signing below assures that all investigators have reviewed the CPW ACUC Euthanasia Guidelines and that investigators will use appropriate methods for humanely destroying animals involved in their study. Please indicate the criteria for and methods of euthanasia to be used in this study: Date: ________ 18. Signed: ___________________________________ Principal Investigator Signing below assures that the planned research does not unnecessarily duplicate previous research on the subject and species proposed for study. Date: ________ Signed: ___________________________________ Principal Investigator 48 �Appendix II. Puma Population Model and Simulations Research on the Uncompahgre Plateau Puma Project from December 2004 to July 2007 provided estimates of puma population structure and parameters for a model-based approach developed by CPW biometrician Dr. P. Lukacs and Mammals Researcher Dr. K. Logan to examine options for the design of the remainder of this research, and as a preliminary assessment of the CPW puma management assumptions. Puma Population Modeling Our puma population projections for the study area involved an age-structured, deterministic, discrete time model. The additive puma population model structure is: Nt+1 = Adult Females = (SAF * NAFt + SSF * NSFt) * (1 – HAFt+1) + Adult Males = (SAM * NAMt + SSM * NSMt) * (1 – HAMt+1) + Subadult Females = ((r * SC * NCt) * (1 – HSFt+1)) * PISF/ESF + Subadult Males = (((1 − r) * SC * NCt) * (1 – HSMt+1)) * PISM/ESM + Cubs = Lỹ * AFR * NAFt+1 Terms: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). PI/E = Ratio of progeny + immigrants/emigrants. Lỹ = Average litter size. AFR = Proportion of adult females giving birth to new litters each year. Basic assumptions of the model include: 1) expected puma population projections and annual rates of increase (i.e., lambda) are conditional on the assigned puma population structure and demographic estimates, and 2) no density dependent responses are built into the model. In reality, density dependence probably operates in puma population dynamics, with competition for food regulating adult female density and competition for mates regulating adult male density (Logan and Sweanor 2001). We parameterized the model with data gathered on the pumas on the study area during the previous 3.7 years. The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table AI.1). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radio-collared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table I.2). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature (Table 2), because our current sample sizes (i.e., number of individuals and years) were not adequate for realistic estimates (i.e., estimates from our data were 1.0 for adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to 49 �emigrants as a model input was from the literature, because such data were scarce and does not exist for Colorado (all references in Table AI.2). We preferred using the population characteristics and parameter estimates gathered in the current research effort, because this is the puma population we intend to manipulate to assess current CPW puma management strategies. Table AI.1. Minimum puma population count on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008 (RY4). The minimum count involves counting all radio- and GPS-collared pumas, all other marked pumas, and all presumably unmarked pumas detected on the study area during the period. Presumed unmarked pumas could be marked with ear-tags and tattoos. Their tracks and movements could be separated from movements of radio- and GPS-collared pumas. Or they exhibited evidence that could separate them from other local marked pumas from their tracks (i.e., distinguishable by sex, number of cubs and/or relative size of cubs varied). Region East slope West slope Totals a Adults Subadults Female Male Female Male 10 4 3 4 6 4 2 0 16 8 5 4 Total Independent Pumas = 33a,b Female 4 1 5 Cubs Male 4 2 6 Unknown sex 7 2-3 20-21 Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. Table AI.2. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Parameter Adult age Estimate 2+ years Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas of both sexes 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radiocollared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). 50 �Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). This result supported Logan and Sweanor 2001:69, n = 148). Proportion of adult females giving birth each year (n = 3 years for n = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits/Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). Results of Puma Population Simulations Expected minimum population sizes for independent pumas for RY5 and TY1 conditional upon the number of independent pumas counted in Reference Year 4 (RY4) and the model input parameters and assumptions (given in Tables AI.1 and AI.2). Table AI.3. Year RY4 RY5 TY1 Adult Female 16 18 23 Puma Population Size Subadult Male Female 8 5 10 9 14 8 Male 4 8 8 Cub 20 33 42 51 Independent Pumas Total 33 count 45 projected 53 projected �Appendix III. MOUNTAIN LION HUNTER SURVEY MOUNTAIN LION HUNTER SURVEY EXPERIMENTAL LION HARVEST UNCOMPAHGRE PLATEAU STUDY AREA- GMUs 61, 62, and 70 Hunter Name: ___ License No.: CID No.: 1. Please circle the days on which you hunted (please count partial days hunting as full days) November: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 December: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 January: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 2. Name the drainages and mesas where you hunted __________________________________________________ ____________________________________________________________________________________________ ____________________________________________________________________________________________ 3. Did you hunt with hounds? YES or NO (circle one) 4. Did you hunt with an outfitter? YES or NO (circle one) 5. Do you consider yourself to be a SELECTIVE hunter or a NON-SELECTIVE hunter? (read explanation below, then circle one) A SELECTIVE hunter is one that purposely is hunting for a specific type of legal lion, such as a male, large male, or large female, and therefore attempts to distinguish between male and female tracks, large and small males or females before taking the animal, and is willing to pass up lions that are detected from tracks or when treed. A NON-SELECTIVE hunter is one that intends to take whatever legal lion is first encountered or caught, with no desire for sex or size. 6. What was the sex of the lion that made the first set of tracks you encountered that were less than one day old? FEMALE  MALE  Did you pursue the lion to harvest it? YES  NO  NOTE: Adult & subadult male lions usually have hindfoot heel pad widths greater than or equal to 2 1/16 in. (52mm) wide. Adult & subadult female lions usually have hindfoot heel pad widths less than or equal to 1 15/16 in. (50 mm) wide. 7. Of the total tracks you encountered that were less than one day old, how many were male (_____) and female (_____) lions? (write number on the blank) 8. How many tracks were of females followed by cubs? _________ 9. How many times did you pursue lions with dogs? _________ 10. How many times did you tree or bay lions with dogs? _________ 11. How many of the lions treed and bayed were males (________), females (________), and cubs (________)? 12. Were any of the lions marked with a visible collar or ear-tags? YES or NO (circle one) If YES, describe the collar color, ear-tag color and number on each lion and its sex & age (i.e., male or female; adults ≥2 yrs. or subadults ~1-2 yrs.; indicate male or female and adult or subadult for each) ___________________________________________________________________________________________ 13. Describe the non-marked lions you caught (e.g., adult male, adult female, subadult male, subadult female) and list here: ___________________________________________________________________________________ 14. Did you harvest a lion? YES or NO (circle one) If YES, what was it? MALE or FEMALE (circle one). ADULT (≥2 yrs.) or SUBADULT (~1-2 yrs.) (circle one) 15. What was the seal number? ____________________ 16. Did marks (e.g., collar, ear-tag) on the lion influence your decision to harvest or not harvest the animal? (check one)  TO HARVEST  NOT TO HARVEST  NO INFLUENCE AT ALL 17. Did snow facilitate your harvest? YES if the puma was tracked on snow. NO if the puma was tracked on ground without snow. (circle one) 52 �Compliance Endangered Species Act This research will involve trapping mountain lions using hounds, cage traps and snares. It is extremely unlikely that any listed species under the Endangered Species Act will be inadvertently captured. However, in the unlikely event that a lynx or wolverine was captured, we will immediately release the animal unharmed. We will utilize existing roadways on public and private lands to access areas for running hounds and setting traps. Other field work on this project will comprise telemetry monitoring primarily from roads and fixed wing aircraft, minimizing potential for disturbing any listed species. No activities associated with this project pose a threat to the well-being of any listed species in Colorado. Animal Welfare Act The project is approved through Colorado Division of Wildlife’s Animal Care and Use Committee (Project #08-2004 and #03-2007). NEPA This research falls under a Categorical Exclusion as set forth in Title 40, Section 1508.4 of the Code of Federal Regulations (i.e., 40 CFR 1508.4) because the actions in this research do not involve significant environmental impacts. Other Landscape-Oriented Federal Acts This research will have no impact on the landscape, and therefore, will not violate provisions of other Federal Legislation governing floodplains and wetlands, historical sites, and prime and unique farmlands. Americans With Disabilities Act When hiring personnel as part of this project, qualified individuals will not be discriminated against based on disability. 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Colorado Division of Parks and Wildlife Ju ly2010 - June20 1 l WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Federal Aid Proj ect No. Colorado 3430 3003 Division of Parks and Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July I, 20 lO - June 30, 2011 Author: H.E. Johnson; project cooperators, C. Bishop, J. Brodrick, J. Apker, M. Alldredge, S. Breck, J. Beckmarm, K. Wilson, M. Reynolds-Hogland, T. Speeze, and P. Dorsey. - All information in this report is preliminary and subject to further evaluation. Infor·mation IVIA Y NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT -..., - -- -- Across the country conflicts among people and black bears are increasing in number, frequency and severity, and have become a high priority wildl ife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unk nown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resu lted in a unique collaboration that builds on the resources and abil ities of personnel from 5 entities: the Colorado Di vision of Wildlife (now Colorado Parks and Wi ldl ife [CPW]), the National Wildlife Research Center, Colorado State University, Wildlife Conservation Soc iety, and Bear Trust fnternational. Collectively, we are implementing a 5-year study on black bears that I) tests management strategies for reducing bear-human conflicts, including a large-scale treatment/control urban-food- removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. We initiated this project in FYI 0- 11 by developing a research proposal, selecting a field site for detailed data collection (Durango, CO), coordinating with numerous entities (non-profit organizations, private citizens, and personnel from city, county, state, and federal government agenc ies) on fie ld logistics, and commencing several aspects of data collection (trapping and collaring bears, monitoring human-related bear mortalities, implementing DNA hair-snare protocols, monitoring garbage-related bear-human conflicts, and conducting mast surveys). Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal (i.e., conduct an urban-food- removal experiment, increase the sample size of OPS collared bears, and acquire telemetry collars to test a translocation model). lnformation from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildl ife managers in Colorado and across the country. 139 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS - - HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on black bears in Colorado that 1) tests management strategies for reducing bearhuman conflicts, including a large-scale treatment/control urban-food-removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in the state. SEGMENT OBJECTIVES 1. Develop a research proposal for internal CP W peer review and funding solicitation. 2. Consult with CPW personnel on potential study sites and compile key information about those sites including num bers ofreporied bear-human conflicts, publ ic land access, urban sanitation practices, harvest data, and urban development statistics. 3. Work with personnel from the City of Durango, La Plata County, the San Juan Public Lands Office (USFS/BLM), the Columbine and Pagosa USFS/BLM Ranger Districts, Bear Smart Durango, CPW South west Region, CPW Area 15, and private landowners on logistical fi eld considerations. 4. Initiate black bear capture and GPS coll aring efforts to collect data on bear movements, habitatuse patterns, and vital rates. 5. Track human-related bear mortalities and removals around Durango from tra nslocations, vehicle collisions, conflict mortalities and harvest. 6. Deploy bear hair-snares in an "urban" Durango sampling grid and a "wildland" Piedra sampling grid to obtain DNA for genetic mark-recapture analyses. Genotyped hair samples will be used to estimate population densities. 7. Collect data on natural food ava ilability for bears based on the mast abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 8. M onitor the frequency of garbage-related bear-human conflicts within proposed treatment and control areas for an urban-food-removal experiment. - -- - V ~ -- 140 �'Cl INTRODUCTION 'cl Conflicts among people and black bears (Ursus americanus) are increasing nationwide (Hristienko and McDonald 2007), as the human population grows and urban development expands in and around bear habitat. State and federal wildlife agencies are responsible for both minimizing bear-human conflicts and maintaining and monitoring viable bear populations; two mandates that are proving to be incredibly challenging. Conflicts between bears and people can result in human injuries, property damage, and bear mortality (i.e. euthanasia), but despite increasing efforts from wildlife agencies to reduce conflicts, rates have been on the rise (Baruch-Mordo et al. 2008). Meanwhile, bear population parameters have been exceedingly difficult to estimate across large spatial scales (Garshelis and Hristienko 2006), and current population sizes and trends are largely unknown. As a result, management agencies are uncertain whether recent increases in bear-human conflicts reflect increases in the bear population or just bear behavioral shifts to anthropogenic food resources. Without a thorough understanding of the factors that drive nuisance bear behavior, and the relationship between conflict rates and bear dynamics, it has been difficult for wildlife agencies to initiate effective management practices. This issue has generated a pressing need for comprehensive bear research in Colorado, and resulted in the development of a detailed study proposal by Johnson et al. (2011 ; Appendix I). The proposal outlines a 5-year project on black bears that 1) tests management strategies for reducing bearhuman conflicts, including a large-scale treatment/control urban-food-removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. Overall, this study should explicitly link bear movement and resource-use to population parameters, while rigorously testing an array of management techniques to reduce conflicts. This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY 10-11 we developed a research proposal, identified a study site, determined the logistics of collecting field data at that site, and initiated data collection. Field efforts focused largely on meeting research objectives 1 and 2, which will yield data that will eventually be used to address objective 3. Specifically, we captured and collared adult female bears, collected data on human-related bear mortalities, deployed and monitored hair-snares to collect DNA for estimating population size, tracked garbage-related bear-human conflicts, and collected data on natural food availability for bears. We report general summary information from recent fieldwork (1 May- 15 Sept 2011) in this progress report; detailed analyses of field data will occur during FY 11-12. While we have initiated data collection for several aspects of this project, collaborators will need to generate additional funding to conduct all research activities outlined in the proposal (i.e., conduct the urban-food-removal experiment, increase the sample size of GPS collared bears, and obtain telemetry collars to test a translocation model). STUDY AREA \id 'el To meet study objectives, a combination of detailed, site-specific field data, and statewide data will be required. For the information presented in this progress report, we focus specifically on the selection of a site for detailed data collection on bear resource-use, demography, and the effectiveness of urban bear-proofing. To make this determination we evaluated a suite of factors. We first identified urban areas in Colorado that reported the highest numbers of conflict-related bear mortalities, translocations, and public calls. From those cities, we then considered the quality and history of bear-human conflict reporting, current bear-proofing infrastructure, the feasibility of conducting a large-scale human-foodremoval experiment (based on current city waste management practices), the size of the urban-wildland interface, harvest management, and public land accessibility. Based on those factors, project collaborators 141 �decided that field efforts should be initiated around the urban center of Durango, Colorado (La Plata County). Durango consistently exhibits some of the highest numbers of bear-human conflicts in the state, conflict reports are regularly monitored by CPW Area 15 and Bear Smart Durango (a local non-profit organization), and unlike other areas experiencing high conflict rates, bear harvest was expected to be maintained at similar levels for the foreseeable future. Durango also had limited bear-proofing infrastructure, was the only city with a coordinated residential waste management system (all residential waste is removed by the city), and is largely surrounded by public land (USFS, BLM, CPW, City of Durango and La Plata County; Fig. 1). The city of Durango contains~ 17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from~ 1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon-juniper, aspen, mountain shrub, and agricultural communities. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Ame/anchier alnifolia), hawthorne (Crataegus spp), squaw apple (Peraphyllum ramosissimum ), angelica (Angelica spp), sweet cicily (Osmorhiza spp ), cow parsnip (Herac/eum sphondylium) and waterleaf (Hydrophy//um spp ). Public land in the region is primarily managed by the San Juan National Forest, the Bureau of Land Management, Colorado Parks and Wildlife, La Plata County and the City of Durango. 'wl METHODS Logistical Considerations During fall and early winter FY l 0-11, we developed a research proposal for internal CPW review and identified a field site for collecting detailed bear habitat-use and demography data. In late winter and spring we worked with various entities around Durango to prepare to conduct fieldwork. We presented our research proposal to personnel from the U.S. Forest Service and BLM (San Juan Public Lands Office, Columbine Ranger District, and Pagosa Ranger District) and worked to develop an operating plan for capturing bears and deploying hair-snares on federal land. We also presented our proposal to staff from the City of Durango and La Plata County, and discussed access to their respective lands for meeting research objectives. Within CPW, we worked with personnel from Area 15 and the Southwest Region to identify initial capture and hair-snare sites, create a bear-human conflict mailbox for recording public calls, and clarify the research objectives relative to local management actions. Additionally, we solicited various entities for financial contributions to the project. Bear trapping and collaring, tracking of humanrelated bear mortalities, DNA hair-snare surveys, garbage-related conflict monitoring, and mast surveys were all initiated during summer 2011; the study proposal (Appendix I) provides detailed descriptions of these methods so we only briefly describe them below. Bear Trapping and Collaring To relate the habitat-use patterns of bears to their demographic trends, we captured and collared adult female bears. We specifically targeted adult females as they represent the reproductive segment of the population and should provide reliable inference to general demographic trends. Additionally, we can obtain information on multiple key vital rates from collaring a single sex-stage class, because, in addition to adult female survival (the vital rate with the greatest elasticity), collared females allow us to track fecundity and cub survival from winter den checks. While our long-term goal is to collar ~50 adult females (Appendix I), in the first year of the study we had the resources available to deploy 25 GPS collars (20 new Vectronics collars, 5 used Lotek collars). We targeted our trapping efforts within~ 12 km of the center of Durango to capture a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of habitat-use patterns relative to the urban-wildland interface. 142 'wl �From May through 15 September we used a combination of box traps and leg-hold snares to capture black bears (Jonkel 1993). We built smaller box traps than those previously used for bear research in Colorado (previously built traps are 0.91 x 0.91 x 1.83 m and weigh ~205 kg; newly constructed traps are 0. 71 x 0.66 x 1.83 m and weigh ~ 125 kg), allowing for increased mobility and flexibility in placement (Fig. 2). A detailed description of the capture and handling procedures is available in Appendix II. Traps and snares were baited with fish, fruit, human foods (at urban locations) and manufactured scents; they were set in the evening and checked the following morning. Adult female bears were fitted with a GPS collar, marked with a PIT tag, and had a tooth pulled for age verification. All other bears (except cubs) were uniquely marked with a PIT and ear-tag (a single small black tag). Bears were weighed, measured, and sampled for blood and hair. GPS locations from Vectronics collars were programmed to upload 4 locations/day through a satellite system, while locations from Lotek collars were manually downloaded in the field using a hand-held device from the ground or air (fixed-wing aircraft). Monitoring Human-Related Bear Mortalities Between I May and I 5 September 2011 we recorded all human-related black bear mortalities and removals in the vicinity of Durango. Mortalities and removals occurred from translocations, vehicle collisions, conflict-related euthanasia and harvest. For all bears removed from the study area we collected a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. Tooth samples will be used to age and genotype these bears so they can be incorporated into population density analyses. Hair-Snare Surveys To estimate the density of black bears around Durango we used a DNA hair-snare sampling scheme (Woods et al. 1999, Mowat and Strobeck 2000). We centered a 36 cell grid (576 kni) over Durango where each cell was 4 x 4 km in size and contained one snare. We sampled a total of3 l grid cells, dropping 5 cells along the outer edge of the grid where public or motorized access was prohibited (Fig. 3 ). Snares consisted of a scented bait hanging high in a tree, surrounded by barbed wire around a cluster of trees encircling the bait; when the bears climbed over or under the wire to investigate the bait, they left a hair sample on the barbed wire. On half of the snares we hung a single strand of barbed wire (50 cm high), and on the other half of the snares we hung two strands (50 and 20 cm high). Our goal with this design was to determine whether the additional strand of wire increased capture probability. Snares were deployed from June I to 14, and we conducted 6 weekly sampling occasions thereafter. On each occasion, we re-baited the snare (randomly baited with anise, strawberry, fish, or maple), and collected hair samples off all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. Samples will be sent to the laboratory at Wildlife Genetics International for genotyping during fall 2011 and we will use the pattern of genotypes to estimate density using mark-recapture statistics. In addition to implementing the Durango hair-snare grid, we also conducted a pilot grid in the Piedra watershed (located between Durango and Pagosa Springs; see Appendix I Figure 7). This site was chosen as high quality ''wildland" bear habitat, reflecting representative densities of bears in the region in the absence of urban development and human food resources. Initially, we intended to deploy and monitor ~32 snares in both the Durango and Piedra grids, however, lack of motorized access in the Piedra watershed inhibited field crews from constructing and checking all snares in a timely fashion. As a result, we opted to run a subset of 9 snare sites in the Piedra to determine whether twice/month sampling (as opposed to weekly) would have significant impacts on DNA quality, DNA contamination (hair samples from > I bear/barb), and recapture rate. These samples will be genotyped this fall. Depending on the results, we will design an appropriate sampling scheme to estimate the wildland bear density in FYI 1-12. 143 �Mast Surveys Bear-human conflicts and bear-use of urban environments may increase when natural foods are in short supply (Zack et al. 2003, Baruch-Morda 2007, Baruch-Morda et al. 2010). To quantify the role of natural food availability on bear habitat selection, we initiated weekly surveys of the local soft and hard mast. In the Durango region, the key mast species for bears are gambel oak, chokecherry, serviceberry, hawthome, squaw apple, and pinyon pine (Beck 1991, Tom Beck, personal communication). Although the phenology of these species is variable throughout the late summer/early fall, they generally reach peak fruit or nut maturation between mid-August and mid-September. We randomly selected 12 transects throughout the 576 km 2 hair-snare study area to evaluate bear natural food availability (Fig. 3). Each transect was 1 km in length and ran along an existing public trail or public-accessible stream drainage. Field technicians walked vegetation transects each week between 15 August and 15 September and for each species, recorded the phenological stage and the percentage of plants that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, etc). Conffict Monitoring One management strategy proposed for reducing bear-human conflicts is removing access to human foods for bears (Peine 200 I, Spencer et al. 2007). Given the high price to operationally "bearproof' a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this study we plan on implementing the first rigorous scientific evaluation of the efficiency of widescale urban bear-proofing for minimizing bear-human conflicts. Although this portion of the project has not yet been funded, we conducted pre-treatment monitoring in proposed treatment and control areas (Fig. 4). During July and August, the months that experience the highest numbers of bear-human conflicts (CPW unpublished data) we patrolled each street within proposed treatment/control areas on the day that waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Patrols were conducted from 06:00- 07:00 AM; for all locations where there was evidence that bears had obtained garbage we recorded UTM coordinates and the trash container type. RESULTS AND DISCUSSION During the summer 2011 field season we conducted 92 total bear captures; 71 captures were unique individuals and 21 were recaptures (see map of capture locations in Fig. 3). Of the unique individuals captured, there were 30 females, 38 males, and three cubs of unidentified sex (cubs were released without being immobilized and thus, gender was not determined; Table I). The mean age of captured bears ~l year old was 4.9, and the mean weight was 80.9 kg (60.0 kg for females and 97.4 kg for males). In total, we placed traps/snares at 105 different locations and we had 1,253 trap nights. Across all bear captures (new captures and re-captures), 86 bears were captured using box traps (I, 119 box trap nights) and 6 with leg-hold snares (134 snare nights). Generally capture success peaked during the first couple weeks of June and again in mid-August; capture success was low during July. We modified our newly constructed, smaller box traps to have a locking mechanism on the door that, once triggered, only allowed the door to close shut and not re-open. This was a critical design element, and allowed us to use the smaller box traps to catch bears::; 214 kg. Generally, we found these traps to be convenient to place in the field and successful in safely capturing and holding bears until they were immobilized. We collared a total of 26 female bears, however two bears slipped out of their collars and were not recaptured leaving us with 24 collared bears at the end of the field season. During the trapping season, Vectronics collars successfully uploaded >5,000 GPS locations through the satellite system, and we downloaded an additional 1,500 locations from Lotek co11ars (Fig. 5). One Vectronics collar prematurely switched to low-battery mode in August; we are currently attempting to recapture the bear to replace the collar. Although we have not yet conducted any formal movement analyses, one collared female moved 144 �~50 km southwest from Perins Peak State Wildlife Area (adjacent to Durango), eventually moving back after several weeks. The second longest movement by a collared bear was ~ 16 km. Between I May and 15 September, 23 bears were removed from the greater Durango area due to human-related causes. Of those bears that were removed, three were translocated due to conflicts with people, seven were killed i•n vehicle collisions, one was killed during research trapping, and 12 were euthanized due to conflicts with people (breaking into house, killing livestock, etc). There were three cubs, two yearling females, five yearling males, six adult females and nine adult males that were removed. Until bears begin hibernating, additional mortalities and removals are expected to occur. Field crews collected a total of 998 individual bear hair samples, 743 samples from the Durango grid and 255 samples from the pilot Piedra grid. Over the 6 sampling occasions from 31 snares around Durango we collected 224, 167, 138, 77, 68, and 69 hair samples, respectively. Over the three sampling occasions from nine snares in the Piedra we collected 127 samples; 46, 50, and 31 samples/occasion, respectively. We also collected 128 additional samples from snares in the Piedra watershed that were only checked on a single occasion. Samples will be sent to Wildlife Genetics International for genotyping in the fall, and results will allow us to estimate bear density. ....,, 'Cl Within the proposed treatment and control areas for the urban bear-proofing experiment, we observed 129 incidences of bears accessing human garbage during July and August; incidences peaked during the first week of August. Of those events, I 0% were wildlife-resistant garbage containers and 90% were regular containers. Bears accessed human food from wildlife-resistant containers when they were not closed properly or could break the locking mechanism on the lid. In assessing the availability of garbage to bears, we recorded the location and container type of 1,167 garbage cans in the proposed treatment and control areas (Fig. 4 ). Of those containers, 14% were wildlife resistant and 86% were regular (non-wildlife resistant). This demonstrates the limited residential bear-proofing that currently exists in Durango, and the relevance of conducting an experimental test of wide-scale urban bear-proofing in this community. Mast surveys are currently ongoing; results will be in the annual report for FY 11-12. SUMMARY AND FUTURE PLANS -.;I -.I During FY 10- l l we successfully developed a research proposal addressing bear-human conflict issues in Colorado, selected a field site, coordinated with numerous entities (non-profit organizations, private citizens, and personnel from city, county, state, and federal government agencies) on field logistics, and initiated several aspects of data collection (trapping and collaring bears, tracking humanrelated bear mortalities, implementing DNA hair-snare protocols, monitoring garbage-related bear-human conflicts, and conducting mast surveys). We will continue these field activities during summers 20122015. Additionally, we will begin winter den checks in January 2012 to track fecundity and cub survival, and ensure that collars are fitting appropriately. Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal. These activities include the implementation of an urban bear-proofing experiment, increasing the number of GPS collared female bears, and purchasing telemetry collars for a translocation study. In addressing the objectives of this project we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear population trends, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. 145 �LITERATURE CITED Baruch-Mordo, S. 2007. B1ack-bear human conflicts in Colorado: spatiotemporal patterns and predictors. Thesis, Colorado State University, Fort Collins, Colorado. Baruch-Mordo, S., S. W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72: 1853-1862. Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. Roaring Fork Valiey urban black bear ecology study: progress report to the Colorado Division of Wildlife. Contact Sharon Baruch-Mordo for copy. Email: sharonb m@yahoo.com Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication No. 39, Colorado Division of Wildlife, Colorado. Garshelis, D.L., and H. Hristienko. 2006. State and provincial estimates of American black bear numbers versus agency assessments of population trend. Ursus 17: 1-7. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21 st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Jonkel, J.J. 1993. A manual for handling bears for managers and researchers. Office of Grizzly Bear Recovery, United States Fish and Wildlife Service, Missoula, Montana. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64: 183-193. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Spencer, R.D., R.A. Beausoleil, and D.A. Martore11o. 2007. How agencies respond to human-bear conflicts: a survey of wildlife species in North America. Ursus 18: 217-229. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27 :616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31 :517-520. Prepared by _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Heather E. Johnson, Wildlife Researcher 146 �..._ -al I.a/ ..., ... .... '-.I 'el '-.I 'cl '-.I .I .I ...,; '...,/ -.._; \SI "'111 -.I '-.I 'SI -..,) ...; '-' -..I -..I 'cl ,..,; 1..,1 '-' I._/ '-' le/ ...., 'cl '-' 'c;/ -al ~ -el \_,I ~ .._ Table 1. Capture information for 65 bears ~ l year old in the vicinity of Durango, CO . Unigue ID Ca~ture Date Bl 82 B3 84 B5 86 B7 88 89 810 Bl 1 B12 813 814 B15 B16 B17 B18 B19 820 B21 B22 823 B24 B25 826 827 B28 B29 830 B31 B32 833 834 835 836 837 838 B39 840 B41 B42 843 844 B45 846 847 5/10/201 I 5/12/2011 5/13/2011 5/16/2011 5/16/2011 5/17/2011 5/17/2011 5/18/2011 5/26/2011 5/26/2011 6/3/2011 6/2/2011 6/3/2011 6/6/2011 6/6/2011 6/7/2011 6/7/2011 6/8/2011 6/9/2011 6/9/2011 6/10/2011 6/10/2011 6/13/2011 6/14/2011 6/15/2011 6/15/2011 6/16/2011 6/16/2011 6/21/2011 6/22/2011 6/24/2011 6/24/2011 6/28/2011 6/28/2011 7/5/2011 7/6/201 I 7/7/2011 7/13/2011 7/13/2011 7/21/2011 7/22/2011 7/26/2011 8/3/2011 8/3/2011 9/3/2011 9/5/2011 8/8/2011 Sex M M M M M F F F M F. M M M F M M F F M M F M M F F M F M M F M F M M F M M M M F M F F M M F F Estimated Age Weight {k2) I 35 144 130 84 135 63 64 52 35 81 130 103 59 58 58 117 52 62 147 132 69 5 5 3 6 3 6 3 4 8 5 3 6 3 7 6 6 9 10 7 8 3 8 4 10 88 65 65 64 109 75 101 49 60 85 19 35 85 44 67 39 145 150 81 67 70 85 35 176 58 54 IO 6 4 4 1 3 3 4 1 8 6 5 3 6 8 2 6 3 8 147 Capture Location UTM Easting UTM Northing 246233 271495 271495 270950 270227 243210 243225 271478 238803 269869 252163 253216 253216 252157 253216 253216 256936 256918 235193 243258 252298 252163 246350 243252 239003 252164 243252 253233 239840 235911 239840 243252 239294 239001 246350 239840 243252 243236 251222 248550 237368 245945 246183 756124 245965 243435 251783 4142768 4130889 4130894 4127914 4139984 4128716 4133053 4130892 4126790 4139040 4137968 4137387 4138868 4137967 4138868 4138868 4134633 4134625 4128894 4133040 4136435 4137968 4135617 4133030 4134158 4137966 4133030 4138873 4126949 4128916 4126949 4133030 4133260 4134154 4135617 4126949 4133030 4128710 4133120 4131645 4132272 4141391 4142791 4132494 4139587 4128720 4131581 �Table I-Continued Unigue ID Ca2ture Date B48 B49 B50 B51 B52 B53 B54 B55 B56 B57 B58 B59 B60 B61 B62 B63 B64 B65 B66 B67 B68 8/10/2011 8/11/2011 8/11/2011 8/12/2011 8/12/2011 8/15/2011 8/16/2011 8/18/2011 8/29/2011 8/30/2011 8/31/2011 9/1/2011 9/2/2011 9/3/2011 9/6/2011 9/7/2011 8/6/2011 9/15/2011 9/20/2011 9/21/2011 9/21/2011 Sex F F F F F M M F M F M M F M Estimated Age We~ht{ke} 1 3 7 12 4 7 2 3 26 55 101 62 65 163 53 49 167 46 48 153 35 214 23 37 30 91 41 54 209 10 3 3 15 2 7 M M 2 M F F F M l 5 1 3 8 148 Capture Location UTMEasting UTM Northing 245914 243435 245965 249049 245965 243435 251898 251464 246321 243374 243374 243952 242187 244602 245790 248612 245850 243948 240731 256930 249067 4139620 4128720 4139587 4130370 4139587 4128720 4130516 4134423 4132993 4135903 4135903 4132935 4133020 4130321 4128530 4131251 4141969 4134848 4130163 4134626 4133006 �Figure. I. Land ownership in the vicinity of Durango, CO. - - LANDOWNER ) c=J USFS --- - C=1 BLM c=J corw c=J La Plata County 11111 City of Durango c=J State Land Board c=J Private Ute Tribe N 0 1.5 3 6 Kilometers A 149 �Figure 2. Photos of a newly designed box trap to capture black bears. 1w - - 150 �Figure 3. Location of bear hair-snare sites, mast survey transects, and capture sites around Durango, CO. - "1111 -Masting Plant Surveys -- N A 0 2 4 Hair Snare Locations 0 Capture Locations 8 Kilometers -- - 0 15 l �Fig ure 4. Proposed treatment and control areas for an urban bear-proofing experiment and observations of garbage-related confl icts from pre-treatment monitoring. Red stars indicate evidence of bears foraging on human garbage, circ les indicate the availability of human food for bears (green circles represent regular garbage containers and yellow circles represent wildlife-resistant containers). Garbage Conflict 0 Regular Container 0 Wildlife Resistant Container i ol..,__ ___ o.,_ .5_ _ _ _.1,___ _ __ ....___ _ ___,2 Kilometers 152 - �Fig ure 5. Ad ul t female black bear GPS locations collected between May and September 20 11 in the vicinity of Durango, CO (different colored circles represent different individual bears). N A 0 5 10 153 20 Kilo meters �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2011-12 - FY 2015-16 State of: Cost Center: Work Package: Task No. Federal Aid Project No. Colorado --------3430 --------3003 --------- Division of Parks and Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Principal Investigators Heather Johnson, Mammals Researcher, Colorado Parks and Wildlife Chad Bishop, Mammals Researcher Leader, Colorado Parks and Wildlife Mathew Alldredge, Mammals Researcher, Colorado Parks and Wildlife John Broderick, Terrestrial Programs Leader, Colorado Parks and Wildlife Jerry Apker, Carnivore Coordinator, Colorado Parks and Wildlife Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center Kenneth Wilson, Professor, Colorado State University Jon Beckmann, Associate Conservation Scientist, Wildlife Conservation Society w '_.I 'w Cooperators Melissa Reynolds-Hogland, Executive Director, Bear Trust International Tom Spezze, Southwest Regional Manager, Colorado Parks and Wildlife Patt Dorsey, Area Wildlife Manager, Colorado Parks and Wildlife STUDY PLAN APPROVAL Prepared by: Heather Johnson Date: 2/15/2011 Submitted by: Heather Johnson Date: 3/12/2011 Reviewed by: Jon Runge Date: 3/25/2011 Chuck Anderson Date: 3/14/2011 Danny Martin 4/4/2011 Biometrician: Paul Lukacs Date: 3/10/2011 Approved by: Chad Bishop Mammals Research Leader Date: 3/10/2011 'wl 154 �-- 1w - PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH .... Black Bear Exploitation of Urba n Environments: Finding Management Solutions and Assessing Regional Population Effects A Research Proposal Submitted bv: Heather Johnson. Mammals Researcher. Colorado Parks and Wildlife Chad Bishop, Ma111111als Researcher Leader, Colorado Parks and Wildl{fe Mathe w Alldredge, Mammals Researcher, Colorado Parks and Wildlife John Broderick. Terrestrial Programs Leader, Colorado Parks and Wilr/lffe Jerry Apker, Carnivore Coordinator, Colorado Parks and Wildlife Stewart Breck. Research Wildlife Biologist, National Wildlife Research Center Kenneth Wilson, Professor, Colorado State Universily Jon Beckmann, Associate Conservation Scientist, Wildl{le Conservation Society J. Need Conflicts among people and black bears (Ursus americanus) are increasing nationwide, as the human population grows and urban development expands in and around black bear habitat. In a survey of 4 1 state wild Ii Fe agencies that manage black bears, 30 repo1ied increasing numbers of bear-human confli cts in recent decades (Hristienko and McDonald 2007). Wh ile state and federal wildlife agencies are responsible for minimizing bear-human conflicts, they are also responsible fo r maintai ning viable bear populations. Achieving this balance is proving to be difficult, as agencies struggle to find effective management solutions while conflict rates continue to rise, particularly around urban areas (Tavss 2005, Baruch-Mordo et al. 2008). Whethe r increases in conflicts reflect recent changes in bear population trends or j ust behavioral sh ifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceedingly difficult to estimate (Garshelis and Hristienko 2006). The primary cause of bl ack bear-human confli cts along the urban-wildland inte rface has been attributed to the availability of anthropogenic food resources to bears (Fig. I; Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009). Urban areas contain a wealth of reliable, high-calorie foods, in the form of garbage, fru it trees, vegetable gardens, pet food, and bird feeders. As opportunistic foragers, bears readi ly ex ploit these resources, resulti ng in negative interactions with people. These interacti ons, however, have been highly temporally and spatially variable (Baruch- Morda et al. 20 I 0), generating uncertainty about the relative infl uence of natural food availabil ity, confl ict management, harvest, and bear population trends on driving annual variation in rates of bear-human con fl icts. Without a thorough understand ing of the factors that exacerbate nuisance bear behavior, and uncertainty about the relationship between conflict rates and bear dynam ics, it has been difficul t for w ildlife agencies to initiate effective management practices. -~---. -- -- - Bear use of the urban environment has serious consequences for people, bears, and wildlife managers. For people, bear-human conflicts lead to increased public safety concerns, property damage, and high management costs, while fo r bears they lead to increased mortal ity (Beckmann and Berger 2003, Beckmann et a l. 2008, Hostetler et al. 2009). For 155 Figure I. Black bearforaging on urban food resources. �example, in 2007 Colorado data analysis unit (DAU) 8-11 reported >500 public safety and property damage conflicts with bears, resulting in >$500,000 expended by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) in bear management. This is one of 19 bear DAUs in Colorado, and encompasses the towns of Aspen and Vail, which have been hotspots of bear-human conflicts. That year, in 8-11 alone, 44 bears were euthanized for conflict control, 25 were translocated for nuisance behavior, 27 died of road kill, and 30 were legally harvested. Overall, this resulted in >75% of bear mortality attributed to conflicts with people, with unknown consequences for local bear populations. In addition to high management costs, these extreme conflict solutions have critical repercussions for wildlife management agencies. Because managers are obligated to respond to conflict calls, conflict management usurps limited resources and radically reduces those available for other programs. High conflict rates and unpopular management activities (i.e. lethal bear removals) also degrade the credibility of wildlife agencies to the general public, and ultimately reduce the inherent value of black bears in the public eye (Will 1980). Given expected changes in both human development and climate patterns, bear-human conflicts should rise in the future. As the human population grows, development will continue to permeate bear habitat, creating additional opportunities for conflicts with bears (Kretser et al. 2008). This situation will likely be exacerbated by anticipated changes in annual weather patterns. Drought conditions reduce the availability of natural foods for bears and are associated with an increase in bear-human conflicts (Zack et al. 2003, Baruch-Mordo 2007). Drier, wanner weather, as predicted with climate change, is expected to escalate conflicts with bears in the coming years. ► Identify management strategies to reduce bear-1,uman conflicts Ultimately, the public will not tolerate ever-increasing conflicts with bears and wildlife agencies must find effective solutions to resolve this pressing problem. Yet, despite the trajectory of increasing black bear-human conflicts, and the severe consequences of those conflicts for both people and bears, best management practices for reducing conflicts remain unclear. Managers commonly employ education (Gore et al. 2008, Baruch-Mordo et al. 2011), aversive conditioning (Beckmann et al. 2004, Mazur 2010), and increased harvest (Treves et al. 20 I0) to curb conflict rates, yet when the effectiveness of these strategies has been scientifically tested, they have been found to be largely ineffective as implemented. Investigators have suggested alternative approaches for reducing conflicts, such as reducing the availability of anthropogenic food for bears, using models to increase translocation success of nuisance bears, and altering public hunting programs to be spatially or temporally aligned to remove nuisance bears. These techniques may be useful for reducing conflicts, but their efficacy has not been rigorously tested. Removing anthropogenic food - Given that bears are attracted to anthropogenic food it is believed that eliminating the availability of this resource will dramatically reduce nuisance bear behavior (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Lyons 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the costs and benefits of"cleaning up" a town. Given the high price to operationally "bear-proof' a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. A thorough, rigorous evaluation of this approach would provide guidance to wildlife agencies and municipalities on the benefit of investing in bear-proofing infrastructure. Trans location Suitability Modeling - Translocation of nuisance black bears is another common management technique that has been applied with varied results (Rogers 1986, Linnell et al. 1997, Landriault et al. 2009). Often bear translocation decisions are handled by field managers without formal guidance. These professionals are knowledgeable on bear capture and transport techniques, but often lack the flexibility to release bears in other management areas without obtaining approvals from different managers, who are often also experiencing nuisance bear problems. Limitations in selecting a 156 �translocation site and the profound movement ability of bears can result in an unsuccessful translocation where the bear continues to cause conflicts either in its new location or after returning to the capture site. To improve bear management, a strategic translocation approach is needed that applies the best available science on bear habitat quality, conflict potential, and harvest in the selection of bear release sites, while incorporating statewide collaboration among managers. Targeted Bear Hunting - Wildlife managers frequently increase harvest quotas to reduce bearhuman conflicts, but the scientific literature has been equivocal on the effectiveness of this approach (Obbard et al. 1997, Hristienko and McDonald 2007, Treves et al. 2010). Hristienko and McDonald (2007) found that states with higher harvest rates reported fewer conflicts, while other studies evaluating elevated harvest on region-specific spatial scales have concluded either no effect or increases in numbers of conflicts (Obbard et al. 1997, Tavss 2005, Treves et al. 2010). Lack of harvest success has been largely attributed to a mismatch between the timing and location of bear-human conflicts and the timing and location of the hunt, as bear-human conflicts peak during summer months along the urban interface while public hunting occurs during the fall in areas away from development (Treves et al. 20 I 0). As a result, a general increase in harvest likely translates into a reduction in the population at large, not necessarily the removal of nuisance bears. This strategy also inherently assumes that conflict rates reflect bear population sizes, an untested assumption that could potentially lead to overexploitation. To determine whether public harvest can successfully curb conflict rates, hunts need to be spatially and/or temporally coordinated with conflicts as they occur. While this is a strategy that has the potential to reduce management-related conflict mortality, it has yet to be thoroughly evaluated. ► 'Cl IC,/ >cl 'ell -..I Elucidate tl,e dynamics of bear populations along tl,e wild/and-urban interface To sustainably manage bear populations in the face of a growing human population and changing landscape conditions, it is critical to elucidate the dynamics and drivers of bear populations. Of those factors that influence bear dynamics, the contribution of urban environments is the least understood, most contentious, and has the greatest potential to elicit major population change. While urban environments offer bears the benefit of anthropogenic food, they also inflict the cost of increased mortality from lethal removals, translocations, and other urban factors (i.e. road kills), yielding uncertainty about whether urban environments contribute to the growth or decline of local bear populations. In the two studies that have evaluated bear populations along the wildland-urban interface, bears experienced reduced survival with population-level consequences (Beckmann and Berger 2003, Hostetler et al. 2009). In Florida, Hostetler et al. (2009) found that reduced adult survival caused the "urban" bear population to decrease in size, while the adjacent "wild" population increased, demonstrating the possibility of source-sink dynamics. Meanwhile, in Nevada, Beckmann and Berger (2003) found that bears around urban development were present at higher densities and had greater reproductive rates, but cubs had exceedingly low survival. The researchers suggested that urban areas did not just operate as a sink but as an ecological "trap" as human food attracted bears into town only to lead to their demise and depopulate the adjacent wildlands. While these studies suggest that urban environments may reduce bear populations, many management agencies have assumed that increasing conflicts reflect increasing populations, and that the availability of anthropogenic foods has bolstered demographic rates. So, do urban areas serve as population sources or sinks for bears, and are these impacts static or do they vary under different conditions? Do urban environments operate as ecological traps, attracting bears into habitat that is maladaptive when suitable conditions exist elsewhere? This question is complicated by the influence of annual variation in natural foods, or environmental stochasticity, on bear behavior and demography. While Beckmann et al. (2004) and McCarthy and Seavoy (1994) report that bears habituated to anthropogenic foods regularly return to them, preliminary data from Aspen, Colorado also suggests that bears increase time spent in urban environments in years of natural food failure and decrease that use when natural foods are readily abundant (Fig. 2; Baruch-Morda et al. 20 I 0). This pattern implies that bears may avoid urban environments when conditions allow, despite the common assumption that a bear savvy to anthropogenic 157 �Figure 2. Annual distances between the home range and the center of town.for a collared adult female bear in a good natural f ood year when she had no cubs (2005), a had natural.food year when she had no cubs (2007), and a good natural food year when she had cubs (2008; from Baruch-Morda et al. 2010). foods w ill consistently be a "conflict bear." In a state like Colorado, where human development has effectively permeated almost all tracks of prime bear habitat, the consistency of bear foraging behaviors has key implications for managers. For example, ifa small subset of bears consistently causes a majority of the conflicts with people, then the removal ofa few key indi viduals should alleviate the problem. If, however, high rates of conflict coincide with years of natural food fa ilure because a large proportion of the population is seeking alternative food resources, such a removal strategy may be ineffective. O r perhaps a combination of these hypotheses are true, that a subset of bears cause a majori ty of confli cts unti l a food-failure " teaches" a new group of bears to use human foods, a pattern that is then repeated in subsequent years, despite natural food conditions. Currently, managers have no information about the proportion of bears that cause conflicts, how the use of urban resources varies among individuals, and how variation in the availability of natural foods drives temporal variation in urban resource-use. As agencies struggle to de fine conflict management practices with minimal information on population trajectories, unde rstanding the effects of urban e nvironments on bear demography is critica l. Currently, conflict bear management practices (lethal removal and trans locations) are based on several inherent assumptions such that I) there is a correlation between bear-human conflicts and bear population size, 2) conflicts are caused by a few individual bears and their removal will alleviate local problems, and 3) management removals do not signi licantly influence regional bear dynamics or local harvest opportun ities. The validity o f these assumptions have yet to be dete1111ined, despite their importance for bear management. To develop sustainable management practices for black bears, we must tease apart the relati ve influences of annual variation in natural bear foods, the availability of an thropogenic foods, conflict-management (lethal remo vals and translocations) and harvest on bear dynamics and bear-h uman conflicts. ► Develop better tools to m onitor the dynamics and drivers of bear pop11/atio11s Despite the need to understand the drivers and trends of bear populations to direct management, Garshelis and Hristien ko (2006) fo und that most states have limited data from which to make sound decisions. As a result, state agencies rely on coarse harvest indices that yield little power for detecting population change, and no ability to di still the underlying causes of change. New tools that increase the scientific rigor in monitoring bear populations are desperately needed, so that harvest quotas are biologically-based and designed to meet population objectives. Recent advances in wildli fe statistics have foc used on max imizing the use of traditional age/sexat-harvest data, that which is routinely collected during mandatory harvest reporting. New techniques are available to more effectively extract information about population trend from harvest data (Skalski et al. 158 - �2007) and can be augmented with mark-recapture or radio-telemetry data to increase precision in parameter estimation (Fieberg et al. 20 I0, Johnson et al. 2010). While these approaches hold tremendous promise for supporting biologically-based bear monitoring and management, they are still in their infancy and have yet to be widely implemented. These techniques could be used to identify the value of different data types for tracking populations and to allocate field efforts that most efficiently determine bear population trends across a region of interest. Such information could also be used to inform annual harvest recommendations, elucidate statewide bear dynamics, and reconcile the relationship between bear population trends and conflict rates. -...I K. Objectives 1) Test management strategies to red11ce bear-1,uman conflicts. Bear-human conflicts in urban areas of Colorado echo nationwide trends, as they are increasing in number, frequency, and severity, and have become a high priority management issue in all regions of the state (Baruch-Mordo et al. 2008, Colorado Division of Wildlife unpublished data). In evaluating strategies to reduce conflicts we will: 1A) Experimentally reduce the availability of anthropogenic food to bears in an urban environment to assess the effect on bear-human conflicts and bear behavior. 18) Develop and evaluate a strategic statewide plan for the translocation of nuisance black bears. 1C) Assess a spatially-targeted bear harvest program designed to reduce the nwnber of nuisance animals. '..al "el 2) Determine the influence of urban environments on regional bear population dynamics. According to the 2010 U.S. Census, Colorado is the ninth fastest growing state in the country, with associated increases in housing and development (Mackun and Wilson 2011 ). Despite these trends, there is substantial uncertainty about the effects of urban habitats on bear habitat selection and population dynamics. To elucidate the effects of urban environments on bears we will: 2A) Evaluate the role of annual variation in natural foods on bear movement and resource-use. 2B) Estimate vital rates of urban and wildland bears relative to their resource-use patterns. 2C) Quantify the effects of resource-use, conflict bear management (lethal removals and translocations) and harvest on bear demography. 3) Develop pop11lation and habitat models to support the sustainable management of black bears in Colorado. Bear populations have been notoriously difficult to monitor for state wildlife agencies (Garshelis and Hristienko 2006). While meeting other project objectives we will obtain key biological data on bears from which we can: 3A) Use multiple data sources (harvest, DNA mark-recapture, and telemetry data) to develop improved bear population models to guide harvest regulations and inform estimates of population size and trend. 3B) Build regional habitat models to better predict bear density, direct the location of future monitoring efforts, and identify key seasonal resource areas. L. Expected Results or Benefits 'Cl This will be one of the most comprehensive studies to date on bear-human conflicts and the ecology of urban and wildland bears, resulting in crucial information that will be used to manage black bears in Colorado and across the country. Results from this study will: • Quantify the relative effectiveness of different management strategies (anthropogenic food removal, translocations, and spatially-targeted harvest) for reducing bear-human conflicts, information which will be broadly used by wildlife managers. A reduction in bear-human conflicts will ultimately increase public safety, reduce property damage, decrease wildlife management costs, and gain management credibility for collaborating agencies. 159 �• Identify key differences in the de mographic and behavioral patterns of urban and wildland bears to better in form managers about the efficacy of conflict-bear management (lethal removals and translocations) on bear behavior and population dynamics. For example, tl1is study will e lucidale the proportion o f bears using urban food resources, how that proportion varies due to natural food conditions, the relati onship between population perfomiance and conflict rates, and whether "town" serves as a source, sink, or ecological trap. • Provide robust, data-driven population and habitat model s to guide the monitoring and management of bears in Colorado. These models will be used to inform annual harvest regulations, revise statewide estimates of population size and trend, and direct the location of future data collecti on efforts. S uch information will increase the scientific rigor that is applied to the management of bears in Colorado and ensure that management actions to minimize conflicts are consistent with population o bjecti ves. • Advance theory and statistical methodology for linking resource-use patterns of animals to their demographic rates, and ultimately, population growth. To date, ha bitat and de mographic analyses have been largely conducted independently of one another, with a re lationship that is often inferred rather than directly measured. Using intensive field populati on data and GPS collar locations, this study will expli citly link space-use, resource acq uis ition, and demographic patterns, exploring new concephral and statistical avenues to elucidate their relationshi ps. M. Approach :.-; ( 'J , '..::/', i.. I r- :/ ' IA) Reducing the availability ofanthropogenic joods to bears in an urban environment to assess the effect 011 bear-human conflicts and bear behavior. . ,:;:. To test the effectiveness of reducing the availability o f human food on reducing bear-human conflic ts, we will conduct a large-scale experiment. We will drastically reduce the accessibili ty o f anthropogenic foods known to attract bears (garbage, bird-feeders, pet food, etc) within a designated ' treatment' area, while simultaneously monitoring comparable 'control' areas where no action w ill occur. We w ill perfom1 this experi ment in Durango, Colorado, a town with one of the highest bearhuma n conflict rates Ln the state as 200-900 conflicts were annually reported between 2007 and 20 IO (see Fig. 3). This town has abundant human food resources available to bears and a definitive urbanwi ldland interface, where urban developme nt is juxtaposed Lo high quality bear habitat. - Within Durango we will specify a treatment area and 2 control areas focused on the core zones of bear-human conflicts (Fig. 3). Each area wi ll contain Figure 3. locations ofbear-human conflicts in Durango, Colorado from 2007-2010 are shown with yellow circles and proposed treatment and control areas are represented by black boxes. approx imately 500 structures (residences and businesses) and be roughly the equivalent in size 2 (0.6 km ). T he treatment will occur in north west section of town, where the highest numbers of conflicts have been reported. In the treatment zone we wi ll provide bear-proof garbage containers, 160 -- �canvass citizens to discourage food availability outside of secure structures (bird-feeders, pet food, etc), conduct daily patrols to remove human food and provide strict enforcement. Our primary control area will occur on the south side of the Animas River (a moderate barrier to bear movement), to facilitate independence among experimental units. Additionally, we wiH monitor a second "spil1over" control area, adjacent to the treatment (north of the river) to measure the influence of the treatment on human behavior in adjacent neighborhoods. We wiH monitor treatment and control areas for 1 pre-treatment year and 4 post-treatment years, measuring changes in two key response variables: bear-human conflicts and bear behavior. We will define a "conflict" as any bear-human interaction that results in property damage or a threat to public safety, and compare the number of conflicts and their severity (i.e., a bear in a garbage can versus a bear breaking into a house) between treatment and control areas. Currently, citizens report conflicts to the Colorado Division of Wildlife, the non-profit organization BearSmart Durango, and the city newspaper; we wiH compile data from all sources for analysis. During the months bears are active, we will also conduct weekly patrols of treatment and control areas. Patrols will occur the morning that residential trash is collected, with an observer recording visible human food resources available to bears and evidence that bears have obtained human foods (i.e. trash cans knocked over and strewn garbage). We will use conflicts from treatment and control areas, and from pre- and post-experiment implementation to measure the effect of bear-proofing on the number and severity of urban bear-human conflicts. Additionally, we will monitor the influence of the food removal treatment on bear behavior. Bears Jiving on the urban-wildland interface wi11 be collared with global positioning system (GPS) satellite technology (see Objective 2 for capture and collaring details). GPS collars will automatically record the location of each bear every 4 hours, and we will use locations to conduct detailed resource selection analyses (Manly et al. 2002). Using selection indices from "in town" bear locations, we will test for differences in bear use among treatment and control areas (Blomquist and Hunter 2010, Boyce et al. 2010), and whether such use varies over the course of the active bear season. By tracking bear locations relative to our treatment and control sites, we should be able to quantify the benefits of 'cleaning-up' a community for reducing conflicts and modifying bear behavior in urban environments. JB) Developing and evaluating a strategic plan for the translocation ofnuisance black bears. To develop a strategic, statewide translocation plan, we will use existing information on black bears to map relative habitat quality, resource selection, nuisance potential, and hunter harvest potential across Colorado. These factors will be combined to generate a single layer depicting overall translocation suitability. Nuisance bears will then be allocated to release sites based on this suitability rating and their respective age, sex, reproductive status, management history (i.e. whether the bear was hazed), and distance to capture site. We will compare the success rates of bears translocated using the strategic approach with those of bears translocated following existing procedures, with success defined as a bear that does not engage in new conflict behavior. In all cases, bears will be marked using very high frequency (VHF) or GPS collars to quantify movements and fates following translocation. Additiona1ly, we will augment information from newly captured bears with data from >80 bear translocations that have already occurred in Colorado. Translocation success will be analyzed in a known-fate, time-to-failure framework (Hosmer et al. 2008), where the translocation outcome is modeled as a function of the relevant covariates. If our strategic approach increases translocation success our model will be incorporated into a user-friendly, internet-based tool for wildlife managers to assist with translocation decisions in the field. Specifically, a wildlife manager would enter the bear characteristics and capture site into the internet program and be given a set of optimal release sites. When a bear is released, the wildlife manager would enter the date and location of release into the program, which would be used to update subsequent releasesite decisions. 161 �1C) Assessing a spatially-targeted bear harvest strategy designed to reduce nuisance animals. Managers in southeast Colorado are responding to high numbe rs of conflicts by increasing harvest rates, however, they are using a novel approach. Rather than implement unit-wide increases in ha rvest quotas, managers will be spatially targeting hunting pressure in zones adj acent to conflict hotspots. These new harvest management zones are ex pected to be implemented in fa ll 2 011 with the goal of reducing bear densities in a reas bordering the urban interface (see example in Fig. 4). We w ill measure the success of this strategy for reducing conflicts in the communities of Colorado Springs, Pueblo, and Colorado City; cities which re po11 hundreds of conflicts/year. Using nuisance reports from pre- and postimplementation of this stra tegy, we wil l compare the number of conflicts, conflict severity, and numbers o f trans located and euthanized bears. Colorado Division of Wildlife has recorded these metrics for the past 16 years, a nd w ill continue to collect this data in the future. In addition, we will compare harvested numbers of bears in the DA Us in which these cities are located (82 and 8 7) pre- and post-implementation of the new strategy, to determine its effect on meeting annual bear harvest obj ectives. With 2:3 replications of this approach (around different urban centers) we will examine whether a spatiall ytargeted harvest approach, executed by the public, significantly decreases urban bear conflic ts w hil e increasing hunting opportuni ties. 2A) Evaluating rhe role ofannual variation in natural.foods on bear movement and resource-use. While anthropogen ic food is consistently avai lable to bears in urban e nvironments, the availability of natural foods can dramatically fluctuate based on annual patterns in temperahire and precipitat ion. For example, late frosts and summer droughts can cause fai lures in the local berry and acorn resources, fo rcing bears to expand their search for calories and potentially increase their use of urban environments (Zach et a l. 2003, 8 aruch-Mordo 2007, 8aruch-Mordo et al. 2010). To determine the influence o f annual variation in natural foods, or e nvironmental stochastic ity, on bear habitat-use we will evaluate location data from GP S collared adult females. From June through September, we will capture bears using c ulvert traps, box traps and A ldrich snares following the techniques described in Jonke! ( 1993, Appendix 2). Captured adult famles will be fitted with a Vectronics collar with a degradable spacer, ear-tagged, weighed, and measured fo r morphometric characteristi cs. Additionally, we will pull a tooth for age determination and obtain a blood sample for DNA. See Detailed capture and handling protocols are provided in Appendix 2. Each year we will attempt to maintain a sample of 50 collared females, with approximately ha!f collared in and arotmd the town of Durango ( La Plata county), and the other half in the surrounding w ildlands (La Plata, Hinsdale, and Archueta counties). This ~ Bear Manogemenl Ama Figure 4. The hatched-blue area represents the proposed bear conflict harvest zone on the wildland-urban inte,:face near Pueblo, CO. 162 - �collaring strategy will allow us to track a range of resource-selection patterns of bears, from those that are heavily dependent on human foods to those that rely exclusively on natural foods, quantifying the proportion of bears using urban resources and their frequency of urban habitat-use. -.,I We will also use GPS location data to examine resource selection and movement patterns in response to temporal variation in natural food availability (see Figs. 2 and 6). To do this we will partition location data into weekly intervals and use a repeated-measures resource selection function (RSF) approach (Manly et al. 2002, Borger et al. 2006, Kie et al. 2010, Mcloughlin et al. 2010). We will determine· those factors that drive temporal resource selection, evaluating the availability of natural foods, changes in weather patterns, distance to town, reproductive status, and conflict management history (i.e. whether the animal was hazed, trapped, etc). We will also evaluate the influence of these covariates on the size ofbear home-ranges and their rates of seasonal movements (Jonsen et al. 2005, Morales et al. 2010). Additionally, we will employ a time-to-failure analysis to examine those covariates (listed above) that predict when a bear will "fail" and use urban resources (Cook and Lawless 2007, Hosmer et al. 2008). We will work with colleagues in the Remote Sensing/Ecology program at Colorado State University to develop satellite image signatures to track annual vegetation productivity for natural bear foods. To quantify weather patterns, we will use PRISM spatial data (http://www.prism.oregonstate.edu/) which interpolates monthly temperature and precipitation patterns across landscapes, accounting for elevation and topography. All covariates related to human development will be extracted from existing CPW digital data layers. Ultimately, these analyses will not only allow us to summarize patterns of movement and resource-use, but elucidate the underlying drivers of bear behavior, providing insight for the design of better management strategies to minimize conflicts. 2B) Estimating the vital rates of urban and wild/and bears relative to their resource-use patterns. To assess differences in the population dynamics of those bears that use urban food resources versus those that do not, we will track the demographic trends of female bears collared in adjacent urban and wildland habitats. We are concerned with the vital rates (survival and reproductive rates) of female bears, as they represent the reproductive segment of the population and should provide reliable inference to the population at large. We will monitor ~50 GPS collared bears each year for their annual survival, fecundity, and the survival of their cubs; collecting this data for a total of 5 years. Survival of adult females will be tracked with real-time GPS locations, and all mortalities will be immediately investigated. To estimate annual fecundity and cub survival, we will inspect the winter natal dens of collared females for the presence of newborn and yearling cubs. If a newborn cub is observed with an adult female in year t, but is not observed in the den with that female in year t+ I, we will assume the cub is dead (Obbard and Howe 2008). Based on power analyses, our target sample size and study timeframe should allow us to detect biologically significant differences among the demographic rates of bears that use urban and wildland habitats, while still being logistically feasible (Fig. 5). In conducting power analyses to detennine samples Adult Female Survival Fecundity l 09 • 1 ~ 0.9 · 0.8 0.7 a: 0.6 11,1 ~ 0.5 0 g_ 0.4 0.3 0.2 0.1 o:s j 0.7 ffi o.6 1 ~ 0.5 1 -a-20% Decrease -.-1S%Decrease -10¾0K-rP;m• 0 15 25 35 45 ~ 0.4 1 -,!,-40%1ncrease 0.3 7 -11-30% Increase 0.2 1 0.1 ~ ~200/21ncrease 0 .,_!----,-----.----......----, 40 30 Sample Size/Group so 60 Sample Size/Group 163 70 Figure 5. Power to detect significant differences (alpha = 0.05) in vital rates between bears using urban habitats and those that do not, based on the sample sizes ofeach group. �sizes for adult female survival, we assumed a baseline survival rate of 0.90 with a standard deviation of 0.20 (Beck 1991, Koehler and Pierce 2005, Obbard and Howe 2008, Hostetler et al. 2009). The only study that has measured differences in adult female survival between urban and wildland bears found a 20% reduction in the survival of"urban bears" (Hostetler et al. 2009). With a sample of ~50 collared bears/year (~25 in urban habitat and ~25 in wildland habitat) for 5 years, we should have power~ 0.8 to detect at least a 15% difference in the survival of those bears that use urban habitats and those that do not. Similarly, assuming that adult female fecundity is 0.44 (Beck 1991) with a standard deviation of0.25 (Hebblewhite et al. 2003), we expect to observe >150 cubs in dens over the course of the study. This number will yield power~ 0.9 to detect a significant difference of~30% in the fecundity rates of urban and wildland bears; Beckmann and Berger (2003) reported >60% difference in fecundity rates of bears in these different habitats. Using GPS location data, we will model the demographic rates of individual bears as a continuous function of how they use urban and wildland habitat, explicitly linking habitat-use to population performance (Mcloughlin et al. 2007, Gaillard et al. 2010). To estimate annual adult female survival we will use Cox proportional hazard models (Therneau and Grambsch 2000, Murray 2006), which allow for staggered entry, continuous-time data collection, and the evaluation of different covariates. We will use multinomial and binomial logistic regression to model fecundity and cub survival rates, respectively (Obbard and Howe 2008), which will rely on annual counts of juvenile bears in winter dens. In these models, we will insert random effects to account for fecundity rates of individual females measured over multiple years, and for the survival of cubs born in the same litter. With all vital rate models we will use GPS data to specifically test whether time in urban habitats, annual availability of natural foods, or density of urban development influences bear population parameters (McLoughlin et al. 2007, Gaillard et al. 20 I0). Annual variation in natural foods will be tracked with satellite imagery (Pettorelli et al. 2005) and information on urban development will be obtained from existing digital data layers. We will also test for the covariate effects of year (to account for variation in natural foods), age (for adult survival and fecundity models), season (for adult survival models) and reproductive status (for adult survival models). We will build a set of apriori candidate models for each vital rate from our covariate set, and identify the best models using model selection (Burnham and Anderson 2002). Additionally, for adult female bears, we will evaluate cause-specific mortality. We will use competing risks analyses (Heisey and Patterson 2006) to examine the differential sources of mortality and their relative importance in urban and wildland habitats. 2C) Quantifying the relative influence ofresource-use, conflict bear management practices (lethal removals and translocations) and harvest on bear demography. Vital rate means and variances measured from Objective 2B will then be inserted into stagestructured matrix projection models (Caswell 2001, Morris and Doak 2002) to assess differences in the population growth rate among those bears that use urban food resources ("urban") and those that do not ("wildland"; Hostetler et al. 2009). The wildland model will serve as a baseline, representing bear demography in the absence of urban food or conflict management, and in the presence of natural food variability. Of those bears that use urban environments, we will then simulate a suite of scenarios to tease apart the inherent effects of anthropogenic food, management-related conflict mortality (i.e. lethal removals and translocations), other urban-related mortality (i.e. road kill, electrocution, etc), and harvest on vital rates, and ultimately, population growth (Fig. 6). First, we will project a matrix with vital rates from bears that used town to estimate the actual ( or realized) growth rate. This model will allow us to compare harvest rates among bears that use urban versus wildland habitats. Second, we will quantify the inherent benefit of anthropogenic food for bears in the absence ofall harvest and urban conflict mortality. To do this we will re-calculate adult female survival censoring all harvest and conflict-related deaths/removals (management and non-management related). We will use the updated values, along with cub survival rates from wildland bears (conservatively assuming that in the absence of human-related mortality "town" cubs would have survival~ than those in the wild) to re-project population growth rates (Hostetler et al. 2009). This will allow us to assess the inherent, but hypothetical, benefit of human food 164 �.... - -- .._J - -- - on local bear demography without urba n- related motiality. Third, we will isolate the impacts of conflict management removals ( lethal removals and translocations) on bear populations. For this scena rio, we will re-calculate adult and c ub survival by censo1ing all management- related removals (but maintaining harvest and non-management mortal ity), and insert these new values into a projection matri x. T his will a llow us to estimate the cha nge in population growth associated with current conflict management practices and estimate their c umulati ve impacts on local populations. Additionall y, for all scenario matrices, we will identi fy those vital rates with the highest elasticity and those dri ving overall growth rates (Wisdom et al. 2000, Caswell 2001). T his wi ll allow us to better understand how patterns of population g rowth respond to vital rate-specific changes in natural and human food availabil ity, confli ct management, and harvest. (' -Individual Attributes - -~ eprloducdv e ~ __ Natural Food Human Food Availabil~...--_) ~ __..,/ I ~. - Resource-Use ••., __c--::o-nf-lic_t__, Removals Stage-Specific Vital Rates In addition to tracking the dri vers of indi vidual Population bear vital rates, we will also assess changes in population Growth Rate density. Density w ill be estimated from hair-snare grids using mark-recapture techniq ues (Woods et al. 1999, Mowat Figure 6. Conceptual model depicting /) the and Strobeck 2000). Bear DNA will be extracted and d(fj'erentfactors that c![fect bear resourcegenotyped from hair to effectively " mark" ind iv id ual bears use, 2) that resource-use influences bear and the pattern of"recaptured" anirua ls will be used to susceptibility to harvest and conflict estimate population s ize. We will set up one hair-snare grid removals, and. 3) how the combined impacts aro und the town of Durango and another grid in adjacent ofresource-use, harvest, and cor1/lict wildland habitat, moni toring each grid for 4 yea rs (Fig. 7). removals determine stage-specific vital Each grid wi ll be composed of 36 cells that are 4km x 4km rates, and ultimately. population growt/1. in size. We will collect bear hair fro m two different sampling sources within each cell , a baited scent trap and a natural rub tree. Baited scent stations will be sunounded by barbed w ire to collect hair fro m bears as they climb around the wire to investigate the bait. We will use multiple bait scents, randomly assigned to different traps each sampling occasion to maintain a hig h hair recapture rate. Additionally, we will attempt to identify l nah1ral rub tree/cell. Rub trees wi ll not be baited, but affixed with a piece of barbed wi re to faci litate hair collection. B y collecting hair fro m both these sources (baited traps and rub trees) we should increase recapture rates and reduce indi vidual heterogeneity in capture response (Boulanger et al. 2008). We will conduct 6 sampling occasions/summer (mid-June through July), checking baited traps and rub trees for hair once/week, and re-baiting scent traps. At the encl of the sampling season hair samples will be sent to the Wildlife Genetics International Laboratory for microsatellite genoty ping. We will use genotype data to estimate density using a spatiallyexplicit Bayesian model for open populations (Gardner e t al. 2009, Gardner et al. 20 I 0). Addi tionally, we use the genotype data to interpolate a spatia l density surface that will allow us to identify habitat covariates associated with high and low bear dens ities in both urban and wild land sampling g rids. We w ill compare densities among sites to detennine whether the availability of human food increases bear density adjacent to town (Beckmann and Berger 2003). Over the course of the study we will also estimate the annual variability in density among urban and wildland habitats. This will e lucidate whether dens ities in each habitat type vary in association with natural food producti on, and the reliability of the hair-snare technique for "snapshot" density measures for statewide mon itoring purposes. Additionally, hair-snare grids will allow us to in fer m ovement of bears from wildland to urban habitats. For example, if high bear densities are maintained along the urban interface despite negative population growth rates (as projected from individual vital rates), it wi ll be suggestive that bears are moving into 165 �Figure 7. Location of urban and wildand DNA hair snare grids. Red circles represent sampling baited traps sites within each cell. Yellow circles represent conflicts reported around Durango, 2007-2010. town from adjace nt wildl ands ( Robinson et al. 2008). Ultimately, using data on both the vital rates from collared animals and density from hair-snares, we w ill be able to discri minate whether town serves as source or sink for local bear populati ons, whether this influence varies under different env ironmental conditions. 3A) Using multiple data sources to build bear population models to inform annual harvest management and elucidate population trajectories. We will use ind ividual vital rate and mark-recapture data fro m O bjective 2, in conjunction w ith annual harvest data, to develop more precise population models for the management of black bears in Colorado. ClUTentl y, it is mandatory fo r hunters to report all harvested bears to Colorado Division of Wildlife and submit a tooth for age estimation (Willey 1974, Stoneberg and Jonke! 1996). Combin ing the three different data types we w ill have available on bears around Durango (sex/age-at-harvest, indi vidual demography from collared bears, and mark-recapture data) we will first estimate baseline population parameters, dramaticall y increasing precis ion in those estimates ( Fiebe rg 20 l 0, Johnson et al. 20 I 0). Then, we will identify the value of each data ty pe (based on sample s ize and years of data collection) for mode ling bear dynamics according to the precision required for making management decisions. Thi s info rmation will be used to generate a parsimonious model that adequate ly describes changes in bear population trends while minimizing unnecessary field data. In do ing this, we hope to provide guidance to the Colorado Division of Wildlife on the allocation of field efforts for effectively monitoring populations, and allow managers to set biologically-based harvest quotas. We will test the accuracy and effecti veness of population mode ls using data collected around Durango, Trinidad, and Aspen (all areas where multipl e bear data types are available), and simulated data, all owing us to furt her validate model structure and precision (Fiebe rg et al. 20 I0). These models w ill be used to inform annual harvest regulations, update population traj ectories, and revise statewide estimates of population s ize. 38) Developing regional habitat models .from GPS collar location data. We will use the wealth o f GPS collar data that we will collect around Durango and which is available from --40 bears around Aspe n (CPW, unpublished data) to build detailed regional habitat models. Currently, bear habitat models for Colorado are deri ved from the perceived value of different vegetation types, as determined by Colorado Division of Wildl ife managers. We hope to enhance regional models through analyses of thousands of bear GPS locations, using additional information on elevation, topography, satellite m easures of annual primary producti vity, and human development variables (i.e. road density, distance to town, etc). We will use a mixed-effects RSF approach lo identify habitat characteristics associated with bear occupancy, appl ying a use-availability design (Manly et al. 2002, Gillies et al. 2 006). We w ill specifically identify second-order habitat selection (Johnson 1980), the 166 - �-..I conditions under which bears establish their home-ranges, using established model selection procedures (Burnham and Anderson 2002). To test the predictive power of the habitat model, we will use crossvalidation (Boyce et al. 2002) and then map expected relative probabilities of selection across the landscape. Additionally, we will use harvest locations and bear sightings from other geographic regions to test the validity of our models for application in other parts of the state. These data-driven habitat models can then be used to provide better estimates of statewide bear density, design more efficient monitoring strategies (Allen et al. 2008), and to identify critical seasonal resources and movement corridors for bears. -....I ._, 'cl N. Location Data used to meet different objectives of this study will be obtained from various parts of Colorado. The anthropogenic food removal experiment (Objective IA) and the demography/resource-use portion of the study (Objective 2A-C) will be conducted in the vicinity of Durango, Colorado (La Plata, Hinsdale, and Archuleta counties). Durango was selected as the focal urban environment based on several factors including a history of high bear-human conflicts (Fig. 3), a good record of recent conflict reporting, the feasibility of conducting the food-removal experiment (based on city waste management practices), and minimal city-wide bear-proofing infrastructure. Tracking bear population parameters in this region will require that trapping and hair-snaring will occur on a combination of USFS, BLM, state, city, and private lands. We will test the effectiveness of a spatially-targeted harvest program along the southern Front Range (Objective lC), and opportunistically throughout the state as changes occur in harvest management. The strategic translocation model will be developed on a statewide basis (Objective 1B), along with population and habitat models (Objectives 3A-B). 0. Schedule of Work Activity Trap and collar bears Monitor bear survival Conduct DNA hair-snare grids Genotype hair samples Distribute bear-resistant containers Monitor human-food-removal experiment Translocation modeling and evaluation Implement spatially-targeted harvest program Evaluate spatially-targeted harvest program Conduct winter den checks (reproduction) Estimate population parameters (individual vital rates, and population density) Develop and test population and habitat models 167 Timeline Summer 2011-2015 Summer 2011-2016 Summer 2011-2014 Fall 2011-2014 Spring 2012 Spring-Fall 2012-2015 Summer-Fall 2012-2015 Fall 2012 2012-2015 Winter 2012-2016 Winter 2012-2016 Winter 2013-2017 �P. Estimated Costs NEED INDIVIDUAL DEMOGRAPHY (5 Yrs) 50 OPS Collars ( 10 Purchased) GPS Battery Replacements (2/ea) Telemetry Receivers/Ant (3) Traps (20) Snares (10) Jab Stick ( 1) Misc Equipment Snowmobiles Field Technicians Spring Trapping Yr I (3.5mo) Spring Trapping Yrs 2-5 (3 .5 mo) Winter Dens Yrs 1-5 (3 mo) COST/UNIT FY201 l-12 $4,800 $300 $695 $1,000 $100 $800 $192,000 3 & Maintenance Tech! (3)/TechII (I) Tech I (I )/Techll (I) Techl(3)/TechII(l) 2 DNA HAIR-SNARE GRIDS (4 Yrs) Field Equipment Field Technicians (2.5 mo) Tech! (2) Genetic Analysis $20,000/Grid GARBAGE EXPERIMENT (4 Yrs) Bear-resistant containers Residental/Commerical Field Technicians (5 mo) Tech! (1) TRANSLOCATIONPLAN (4 Yrs) Store-on-Board OPS Collars (50) $1,500 Web Prot:[ammer {1 mo} Programmer {1} PROJECT TOTAL FY2012-13 FY2013-14 FY2014-15 FY2015-16 TOTAL $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $192,000 $30,000 $2,085 $20,000 $1,000 $800 $30,000 $40,000 $31,984 $19,301 $31,984 $19,301 $31,984 $19,301 $31,984 $19,301 $31,984 $37,209 $77,204 $159,920 $1,200 $12,792 $40,000 $250 $12,792 $40,000 $250 $12,792 $40,000 $250 $12,792 $40,000 $250,000 $12,792 $12,792 $12,792 $30,000 $2,085 $20,000 $1,000 $800 $10,000 $20,000 $37,209 $1,950 $51,168 $160,000 $12,792 $75,000 $75,000 $3,200 $3,200 $369,070 $452,119 $157,119 $130,319 $250,000 $51,168 $74,077 $1,182,704 168 ( ( { ( ( { { ( { { ( { ( { ( ( C{ C( CC( ( C{ ( ( CC( ( C( ( CC( C{ C( { �-..I Q. Related Federal Projects There are no related federal projects. R. Literature Cited Allen, J.R., L.E. Mclnenly, E.H. Merrill, and M.S. Boyce. 2008. 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Wildlife Society Bulletin 31 :517-520. 172 �\&I APPENDIX II CAPTURE AND HANDLING PROCEDURES FOR FREE-RANGING BLACK BEARS Black bears will be initially captured and collared during the summer months and annually recaptured in their dens during winter months to obtain reproductive information. Summer We will capture and collar adult female black bears during summer months (May-Sept) using cage traps and foot snares. We will use cage traps in areas close to Durango or with high human activity, and where there is good road access. Snares will be used for more remote trapping locations, away from human activity and where vehicle access is limited. Once a bear has been captured using either method, field crews will use an identical protocol to process animals. ..., wl Cage Traps We will capture bears with two different trap designs, a cage trap designed and used extensively by Beck ( 1993), and a newly designed trap to specifically target female bears. The trap developed by Beck is 1.8 m long and l .O m in height and width. The frame is constructed of angle iron, all side and top panels are wire mesh of 1.9 x 1.9 in size, and the trap has a floor that is 16-gauge steel. A spring-powered, solid aluminum door is mounted on a full-length hinge at one end and a latching mechanism holds the door closed. The door is triggered via a treadle pedal on the floor, and a standard garage door coil spring provides closing power. A hinged panel along the back of the trap allows access for administering immobilizing drugs via jabpole. In total, the trap weighs approximately 236 kg. In the first study in which these traps were used, only 1 bear in 134 captures was injured, as the individual broke a canine on the wire mesh. Because we are specifically interested in capturing and collaring female black bears, we worked with Mat Alldredge, Tom Davies, Lye) Willmarth and others to design a smaller, lighter trap that would discourage the capture of large males and increase portability in the field. These traps were built to be slightly larger than those that have been successfully used for cougars (Alldredge et al. personal communication) and are 34in high, 60in long, and 25in wide. The frame is built with lxl in heavy gauge steel, covered with 1x 1in heavy gauge, high tinsel, steel mesh. The smaller dimensions of the mesh will reduce the possibility that animals will break their teeth on the cage. The sides of the trap have additional braces to increase overall strength and support. The door of the trap comprises one end of the structure and is designed drop and latch to the bottom of the frame. Bait is hung from a cable attached to an archery trigger, and the door falls shut when the trigger is released. Due to the smaller size of the trap, it only weighs approximately 60 kg. Cage traps will be positioned so they are in the shade, and exposure to sun and precipitation is minimized. All cage traps will be clearly marked with warning signs. Cages will be baited with rotting fish, fruit, or road kill. They will be set in the late afternoon or evening and checked by field crews the following morning to minimize the time an animal spends in a trap. If the bear can be clearly identified as a male in the trap, or the bear is a cub or yearling (too small for a GPS collar), it will be released without being immobilized. If the bear is an adult female, or there is uncertainty in the sex of the adult bear, it will be immobilized following procedures described below. Bears will be immobilized with ajabpole, syringe pole, or syringe (hand injection), with the injection targeted into muscle tissue along the shoulder or thigh. Aldrich Foot Snares Aldrich foot snares were specifically developed to capture bears and have proven to be safe and effective (Jonke) 1993 ). The spring activated snare secures a ¼ inch steel cable around the foot of the bear, closing tight with the action of a small piece of angle iron fashioned into a sliding lock mechanism. 173 �The inside of the snare loop is wrapped with duct tape to minimize surface abrasion on the skin of the foot. We will modify snares with additional duct tape and/or surgical tubing over the cable to serve as a "cub stopper" such that small bears (cubs and yearlings) have a low probability of being captured (Jonkel 1993). An in-line swivel is placed in the cable to avoid torsion of the foot and a potential bone fracture. A short lead is attached to the snare to further minimize stress to the leg. The lead is then secured to an anchor tree at least IO inches in diameter with a ¼ in steel cable clamped and stapled to the base of the tree so the bear cannot climb it. Branches of the tree are lopped off with a saw or axe about 8 ft up, so the bear cannot hang itself from a branch by the snare cable. An area of 2::5 meters is cleared around the snare site to eliminate potential that the bear is able to twist the snare loop around any obstacles (saplings, brush, etc). Large branches will be angled over the snare to force ungulates to step over or go around it, minimizing the possibility of catching non-target animals. Additional details of setting snares can be found in Jonkel ( 1993). A disadvantage of using foot snares is that all bears that are caught (even if they are a male bear or too small to collar) must be immobilized to be released. Other non-target animals that are caught (i.e. mountain lions, coyotes, etc) will be immobilized with Telazol and released. Snares will be set in the evening and checked in the morning, operated when ambient temperatures are between 32 and 90°F. Snared bears will be immobilized using a jabpole or CO2 dart gun with the injection targeted into muscle tissue along the shoulder or thigh. "W' Animal Processing During summer months bears will be anesthetized with butorphanol, azaperone, and medetomidine (BAM), a drug combination that has been successful immobilizing black bears and is reversible with atipamezole (a medetomidine antagonist), allowing a faster and safer release of animals around urban environments (Wolfe et al. 2008). BAM will be administered at a volume of 0.4ml/23kg (50 lbs) with a dosage of 0.26mg/kg for butorphaneol, 0.22mg/kg for azaperone and 0.09mg/kg for medetomidine. We will initially give the recommended dose based on estimated animal weight and boost as necessary by½ and¼ of the original dose for the first and second boosters, respectively. To reverse immobilization we will intravenously administer atipamezole. We will dispense a volume of 1ml/1ml at a dosage of 5mg/I mg of medetomidine or 0.45mg/kg. One dose should be sufficient to reverse BAM. Bears immobilized with BAM should not be consumed for 45 days afterward, information which will be printed on collars and ear-tags (see below). Following the injection of BAM, field personnel will approach and gently prod the bear to ensure that the animal is fully anesthetized, administering additional doses as needed. Once anesthetized, the bear will be removed from the trap or snare and placed in a stemally recumbent position with front and rear legs extended. If the bear will not be collared (either because it is a male or too young) it will be subcutaneously injected with a passive integrated transponder (PIT) tag and marked with a single black or brown ear-tag that is labeled with the appropriate consumption date information. Afterwards, the bear will be administered atipamezole and released. Adult female bears will be discriminated from subadults based on weight, and nipple size and coloration (Beck 1991 ). Adult female bears will be fully processed. They will immediately be treated with eye ointment and blindfolded to reduce visual stimuli and protect the eyes from debris and bright light. Throughout the time a bear is anesthetized, its vital signs (heart rate, respiration and temperature) will be monitored. Normal ranges for vital rates of adult bears: heart rate = 60-90 beats/minute, respiration = 15-20 breaths/minute, and temperature= 99.6 - 101.0°F (Jonkel 1993). If a bear's body temperature exceeds the normal range, field staff will cool the underside of the bear with water, particularly the arm pits, groin and stomach. If heart rate and respiration values fall outside normal expectations we will reverse the anesthesia and release the bear. 174 ~ �...,; cl 'Cl In processing female bears, we will check each animal for any lacerations that occurred in the capture process and treat them with topical antibiotics. Additionally, bears will be given an injection of Oxytetracycline (9mg/1b) or Baytril (7 .5 mg/kg) to reduce chances of infection from darting and tooth extraction (described below). Adult female bears will be subcutaneously injected with a PIT tag. If the individual has been identified by CPW Area staff as a hconflict" bear it will be marked in accordance with CPW Administrative Directive W-2. Individuals will be weighed using a portable spring scale and pulley system and their breeding status will be recorded (lactating, cubs present, evidence of suckling, etc). We will take multiple body size measurements including total length, chest girth and neck girth. During winter months we will also use bioelectrical impedance analysis to measure bear body fat (Farley and Robbins 1994, Hilderbrand et al. 1998). Additionally we will draw blood and collect a hair sample. These samples will be used for gepetic, stable isotope, and telomere analysis. To age captured bears using tooth cementum annuli counts (Stoneberg and Jonkel 1966, Willey 1974), we will remove the first vestigial premolar ( or if unavailable the lower first premolar) using a dental elevator. For tooth extraction, we will topically apply Lidocaine and subcutaneously administer Ketofen for analgesia ( 1cc/ I 00lb ). A piece of foam gel will then be placed on the removal site and left for adhesion and filling of the wound. We will attach a GPS collar (~700 g) with a ~2 year life expectancy. Collars will be programmed to collect ?:3 locations/day, and will be labeled with the appropriate conswnption date based on immobilization. The GPS collar will include a VHF transmitter that allows tracking via standard telemetry equipment and the retrieval of collars. We will recapture each collared female each winter to assess fecundity and cub survival. If we are unable to recapture a bear, however, each collar will have a degradable canvas spacer that should break-down within 1-2 years and allow the collar to fall off. GPS collars will upload the location of each individual every day via a satellite system and the location will be available to researchers in real-time. When animal processing procedures are completed, the blindfold will be removed and the immobilization reversal will be administered. Field staff will observe the bear from a safe distance to ensure that the animal recovers to a standing position (Wolfe et al. 2008). ._ Winter Den Checks To assess fecundity and cub survival we will recapture collared female bears each winter. Bears will be tracked to their dens using GPS collar locations, and researchers will dig through the snow as needed to access the den~ Adult female bears and accompanying yearlings will be anesthetized with Telazol using ajabpole or CO2 dart gun. Telazol will be administered intramuscularly with a dose of 1.5 2.5mg/1b at a lower concentration (5cc at 100mg/ml). Bears will be immobilized at a higher concentration (3cc at 166 mg/ml) if they are particularly agitated or large. We will initially give the recommended dose based on estimated animal weight and boost as necessary by ½ and ¼ of the original dose for the first and second boosters, respectively. Unlike BAM, there is no reversal drug for Telazol. That said, an immobilized bear can be returned to its den for recovery, reducing animal stress and increasing researcher safety. 'el Once immobilized, bears will be removed from the den, placed on blanket, and processed in a similar manner to that described above. Field staff will check the fit of the GPS collar and make any necessary modifications, and clean up any neck wounds with saline solution. Newborn cubs in the den will be tucked inside the jacket of a field crew member, next to their body, so that the cub says warm and quiet. After processing, bears will be returned to the den; adults and yearlings will be positioned on their side and newborn cubs will be placed on their mother's back. The den entrance will be covered with sticks and boughs and a layer of snow to discourage the bear from leaving the den. We will retain a small opening in the snow to ensure that the bear has a fresh supply of air (Jonkel 1993). 175 �Injuries and Euthanasia If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that severely compromises its ability to survive and/or causes severe pain or distress) during capture, it will be quickly and humanely euthanized. Bears will be deeply anesthetized with BAM or Telazol and euthanized via a intravenous potassium chloride (KCI; 400-800 mEq) injection or gunshot to the head or neck. Carcasses that are euthanized will be disposed of in a landfill or left in an area appropriate for scavengers. LITERATURE CITED Beck, T.D.l. 1991. Black bears of west-central Colorado. Technical Publication 39, Colorado Division of Wildlife, Fort Collins, Colorado. Beck, T.D.l. 1993. Development of black bear inventory techniques;job progress report. Colorado Division of Wildlife, Project Number W-153-R-6. Farley, S.D., and C.T. Robbins. 1994. Development of two methods to estimate body composition of bears. Canadian Journal of Zoology 72:220-226. Hilderbrand, G.V., S.D. Farley, and C.T. Robbins. 1998. Predicting body condition of bears via two field methods. Journal of Wildlife Management 62:406-409. Jonkel, J.J. 1993. A manual for handling bears for managers and researchers. Office of Grizzly Bear Recovery, US Fish and Wildlife Service, University of Montana, Missoula, Montana. Stoneberg, R.P ., and C.J. Jonke I. 1966. Age determination of black bears by cementum layers. Journal of Wildlife Management 30:411-414. Willey, C.H. 1974. Aging black bears from first premolar tooth sections. Journal of Wildlife Management 38:97-100. Wolfe, L.L., C.T. Goshorn, and S. Baruch-Mordo. 2008. Immobilization ofblack bears (Ursus americanus) with a combination ofbutorphanol, azaperone, and medetomidine. Journal of Wildlife Diseases 44:748-752. 176 ..,, �-..,, Colorado Division of Parks and Wildlife July 2011 - June 201 2 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban envirnrunents: finding management solutions and assessing regional population effects Federal Aid Project No. Period Covered: July 1, 2011 - June 30, 201 2 .,.,, Author: H.E. Johnson; proj ect cooperators, C. Bishop, J. Broderick, J. Apker, S. Lischke, M. Alldredge, S. Breck, J. Beckmann, K. Wilson, M. Reynolds-Hogland, T. Spezze, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT ..,,JI .,,,,,, ...,,,, ..,.; Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 5 entities: the Colorado Parks and Wildlife (CPW), the USDA National Wildlife Research Center, Colorado State University, Wildlife Conservation Society, and Bear Trust Internationa l. Collectively, we completed year 1 of a 5-year study on black bears that I) tests management strategies for reducing bear-human conflicts, 2) determines the influence of urban environments on bear habitat-use patterns and demography, 3) identifies public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY 10-11; during this past fiscal year we have primarily focused on coordinating research logistics and collecting field data in the vicinity of Durango, Colorado. Specifica lly, we obtained data on garbage-related bear-human conflicts, trapped and marked black bears, monitored the vital rates of collared bears (surviva l, fecundity and cub survival) through telemetry and winter den visits, collected data on the availabi lity of late summer/fall mast, tracked human-related bear mortalities and removals, performed non-invasive genetic mark-recapture surveys, and conducted a survey of public attitudes and perceptions about bear-human encounters. Project collaborators will continue to seek additional fundi ng to implement the remaining activities outlined in the research proposal (i.e., purchase additional containers for an urban-food-removal experiment, increase the sample size of collared bears, and acquire telemetry collars to test a translocation model). Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critica l for wildlife managers in Colorado and across the country. 114 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on black bears in Colorado that l ) tests management strategies for reducing bearhuman conflicts, 2) determines the influence of urban environments on bear habitat-use patterns and demography, 3) identifies public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears. SEGMENT OBJECTIVES 1. Work with personnel from CPW Area 15, CPW Southwest Region, the City of Durango, La Plata County, US Forest Service (Columbine and Pagosa Ranger Districts), Bureau of Land Management (BLM; Tres Rio Field Office), and private landowners on field research logistics. 2. Collect pre-treatment data on the frequency of bears accessing human garbage in preparation for an urban bear-proofing experiment. 3. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear habitatuse patterns and demography. 4. Monitor bear survival via global position system (GPS) collar locations. 5. Obtain data on summer/fall natural food availabi lity for bears based on the phenology and abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 6. Investigate the winter dens of collared female bears to collect data on fecundity and cub survival, inspect collar fit, and replace collar spacers and batteries. 7. Track human-related bear mortalities and removals around Durango from lethal conflict mortalities, vehicle collisions, harvest, and translocations. 8. Perform non-invasive genetic mark-recapture surveys to estimate bear density and population size around Durango (urban site) and in the Piedra watershed (wildland site). 9. Conduct a survey of public attitudes and perceptions about bears, the local bear population, bear management and bear-human encounters. INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human confl icts can result in public safety concerns, property damage, bear mortaUty (i.e. euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman confl icts (i.e., education, aversive conditioning of bears, and modifications to harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceeding difficult to estimate (Garshelis and Hristienko 2006). Without a thorough understanding of the relationship between conflict rates and bear behavior and population dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. 11 5 - ...., --...,, -- �While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, agricultural resources, fruit trees, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of this resource. Bear-use of human food not only increases interactions between bears and people but has been found to alter bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly alter both bear behavior and demography. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Morda et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for ·modifying bear-habitat relationships, they also have critical implications for increasing rates of bear-human conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society, Colorado State University, and Bear Trust International. Collectively, we initiated a project in FYl0-11 to 1) test management strategies for reducing bear-human conflicts, 2) determine the influence of urban environments on bear habitat-use patterns and demography, 3) identify public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develop population and habitat models to support the sustainable monitoring and management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. \cl During FY 11-12 _we worked with internal and external stakeholders on field research logistics, obtained data on garbage-related bear-human conflicts, trapped and marked black bears, monitored the vital rates of collared bears (survival, fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals, performed non-invasive genetic mark-recapture surveys, and conducted a survey of public attitudes and perceptions about bear-human encounters. Our efforts focused largely on collecting field data to meet research objectives 1-3, information which will eventually be used to address objective 4. We report general summary information from field activities over the past year; detailed analyses of field data will occur in future years. STUDY AREA To meet study objectives, a combination of site-specific field data and statewide data will be required. Site-specific field data is being collected in the vicinity of Durango, and is the focus of this progress report. Regional and statewide analyses will be conducted in future years. The town of Durango contains ~ 17,000 people ( within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from~ 1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon-juniper, aspen, mountain shrub, and agricultural 116 �communities. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Amelanchier alnifolia), hawthome (Crataegus spp), squaw apple (Peraphyllum ramosissimum), angelica (Angelica spp), sweet cicily (Osmorhiza spp), cow parsnip (Herac/eum sphondylium) and waterleaf (Hydrophyllum spp ). Durango is predominately surrounded by public land managed by the San Juan National Forest, BLM, CPW, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts. METHODS Objective 1: Testing management strategies to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that food source (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of "cleaning up" a town. Given the high price to operationally "bearproof' a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project we will be implementing the first experimental test of wide-scale urban bear-proofing for reducing bear-human conflicts. To do this, we will drastically reduce the accessibility of anthropogenic foods known to attract bears (garbage, bird-feeders, pet food, etc) within 2 designated 'treatment' areas, while simultaneously monitoring 2 comparable 'co~trol' areas where no action will occur. In the treatment areas we will provide bear-proof garbage containers, canvass citizens to discourage food outside of secure structures (bird-feeders, pet food, etc), conduct daily patrols to remove human foods, and provide strict enforcement. Each area will contain approximately 500 homes in residential neighborhoods. Treatment and control areas will be monitored for 3 years after the experiment has commenced, and we will track the number of conflicts and their severity among our experimental units. Conflicts will be recorded from weekly monitoring and from calls received by CPW, the City of Durango, and Bear Smart Durango (local non-profit organization). During summer 201 l project personnel collected pre-treatment data (data collection for 2012 is ongoing) on bears accessing garbage in Durango. In July and August, months that experience the highest numbers of bear-human conflicts (CPW unpublished data), technicians patrolled each street within proposed treatment/control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from ~05:30 - 06:30 AM and recorded the locations where there was evidence that bears had obtained garbage or other human food sources. Additionally, during late July, we quantified the "availability" of garbage to bears, by • documenting the location and container type (wildlife-resistant or regular) of every garbage receptacle in the survey area. These data will allow us to track changes in the number of wildlife-resistant containers over the course of the study, and provide an estimate of the amount of human food available to bears in town. In addition to collecting pre-treatment data, we worked with the City of Durango to coordinate the logistics of implementing the bear-proofing experiment in spring 2013. Objective 2: Determining the influence of urban environments on bear behavior and demography To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear habitat-use patterns and demography, we are collecting a suite of data types 117 �'-' including locations from collared bears on the urban-wildland interface, survival and reproductive rates of those bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitat types. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011 ). Collaring and Marking Bears - To assess bear movement and habitat-use patterns with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, vital rates that are often associated with variation in bear population growth rates (Mitchell et al. 2009, Beston 2011). We have targeted summer trapping efforts within ~ l 0 km of the center of Durango to collar a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urbanwildland interface. Bears are trapped with box traps, which are baited with fish, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar manufactured by Vectronics, and a tooth is pulled for age verification. A collar records a bear's location every hour, and uploads a location to a central database via satellite system every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair.. Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wild/and Interface-To examine movement and habitat-use patterns of bears along the urban-wildland interface we will use GPS collar location data from adult female bears. We will assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear behavior. During winter 2012, we downloaded hourly GPS location data from the collars during winter den checks, and will continue to download and process this data on an annual basis. We will use locations in conjunction with various types of spatial data to conduct a suite of movement and resource selection analyses (Manly et al. 2002, Mcloughlin et al. 20 l 0, Morales et al. 2010). In terms of spatial data, we will use satellite imagery to track annual spring/early summer forage availability, and ground surveys to track late summer/fall mast availability (see details below). Weather information will be modeled using PRISM spatial data (www.prism.oregonstate.edu/) which interpolates monthly temperature and precipitation patterns across landscapes, accounting for elevation and topography. Covariates related to human development will be derived from existing CPW digital data layers such as parcel density, road density, and census population size. 'Cl ,...; While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of acorn and berry resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural forage for bears around Durango we conducted weekly mast surveys. Surveys were performed between mid-August and mid-September in 2011, when fruits and nuts should reach peak maturation. In the Durango region, the key mast species for bears are gambel oak, chokecherry, serviceberry, hawthome, squaw apple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 12 transects on public lands to evaluate bear natural food availability. Each transect was l km in length and was situated along an existing trail or stream drainage. For each transect, field technicians recorded the phenological stage and the percentage of plants of each 118 'c,/ �species that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, 25 - 50% of plants with mast, etc). Estimating Demographic Rates-To assess the influence of human development on bear demographic rates and population trends we are using the following data types: 1) survival and reproduction of collared adult female bears, 2) mortalities and removals from marked and unmarked bears in the vicinity of Durango, and 2) samples from non-invasive genetic surveys of bears around Durango and in the Piedra watershed. Collared female bears allow us to track annual survival, fecundity and cub survival, parameters we monitored in FYl 1-12 and which we will continue to monitor for the next 4 years. We used real-time GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations were stationary for multiple sampling points. Fecundity and cub survival were monitored from den checks of collared females. Numbers of newborn cubs provide information to estimate fecundity rates, while repeated annual den checks of collared females allow us to estimate cub survival. Yearlings hibernate with their mothers, so we can observe the number of cubs alive in the den in year t that have survived their first year of life to t+ 1. Adult female survival, fecundity and cub survival will be collectively used in projection models to assess population performance in future analyses (Caswell 2001). In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on humanrelated bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and harvest. For all bears removed from the study area we collected a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery analyses to estimate adult male survival and subadult survival, while also gaining valuable information on cause-specific bear mortality around human development. To better understand the influence of urban environments on bear density and population sizes, we are employing non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between a bear population around the urban center of Durango and in a nearby "wildland" area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size; we constructed 1 snare in each cell. Snares consisted of a scented bait hanging high in a tree, surrounded barbed wire around a cluster of trees encircling the bait. When the bears climbed over or under the wire to investigate the bait, they left a hair sample on the barbed wire. In summer 2011 we hung a single strand of barbed wire (50 cm high), and on the other half of the snares we hung two strands (50 and 20 cm high). Our goal with this design was to determine whether the additional strand of wire increased capture probability. In summer 2012 all sites were strung with a single strand of wire. Snares were deployed during the first 2 weeks of June, and we conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with anise, strawberry, fish, maple or bacon scent, and collected hair samples off all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. In 2011, we sampled a total of 31 grid cells in Durango (dropping 5 cells where public or motorized access was prohibited) and 9 cells in the Piedra watershed. We did not have the logistical capability to sample both grids in their entirety, so we ran a pilot study on the Piedra to determine whether twice/month sampling (as opposed to weekly) would have significant impacts on DNA quality, DNA contamination (hair samples from> 1 bear/barb), and recapture rate. In 2012, we constructed 35 snares in the Durango grid and 34 snares in the Piedra grid. The layout of the Piedra grid had to be modified in 119 �th 2012 to account for closures associated with the Little Sand fire, which began burning on May 13 2012 (Figure 1). This modification can be easily accounted for in future analyses with spatially-explicit mark recapture statistics (Efford et al. 2009, Gardner et al. 2010). In fall 2011, all hair samples were sent to the laboratory at Wildlife Genetics International for genotyping; genetic results were returned at the end of June 2012. Summary data from the Durango grid is provided, and the remainder of the analyses will occur during FY12-13. Samples collected in 2012 will be sent to the laboratory this fall. 'Cl 'Cl Objective 3: Identifying public attitudes about bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have simulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011 ). Thus, in conjunction with Stacy Lischka, Human Dimensions Specialist for CPW, we have initiated a public survey to 1) better understand public perceptions about bears, bear management, and bear-human encounters and 2) explore motivations for compliance and non-compliance with wildlife ordinances designed to reduce bear-human conflicts. To meet those objectives, we developed a three part public mail survey to be conducted in conjunction with our urban bear-proofing experiment. Residents will be surveyed pre-, during, and postimplementation of the experiment, in treatment and control areas, as well as across a larger portion of the community. Surveys will be mailed to all residents within Durango city limits, and a subset of La Plata county residents within the study area. Survey responses will allow us to quantify current public attitudes and perceptions about bears, and how those perceptions change over time in association with a management effort such as wide-scale urban bear-proofing. The survey will also determine the number of residents that have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. The pre-treatment survey was mailed to 5,852 residents; 4,352 residents in Durango city limits and 1,500 in surrounding areas of La Plata county (Appendix 1). The total valid sample, once surveys mailed to incorrect addresses were returned, was 5,329. Surveys were mailed on January 17th 2012, a reminder postcard was mailed on February 2 nd 2012, and a second survey was mailed to non-respondents on February 29 th 2012. For those people that did not send back a completed survey, we mailed a nonresponse postcard on May l 8th 2012. The postcard had a few background questions so that any systematic biases in respondents could be assessed and incorporated into analyses (Appendix 2). RESULTS AND DISCUSSION 'Cl Objective 1: Testing management strategies to reduce bear-human conflicts During summer 2011 we collected pre-treatment data for the proposed bear-proofing experiment. We observed 129 instances of bears accessing garbage during our weekly surveys in July and August; observations peaked the first week of August. Of those garbage containers accessed by bears, 10% were wildlife-resistant and 90% were regular containers. Bears accessed human food from wildlife-resistant containers when they were not closed properly or the locking mechanism on the lid was broken. In quantifying the availability of garbage to bears, we recorded the location and container type of 1,167 garbage cans in the proposed treatment and control areas. Of those containers, 14% were wildlife resistant and 86% were regular (non-wildlife resistant). This demonstrates the limited residential bear-proofing that currently exists in Durango, and the relevance of conducting an experimental test of wide-scale urban bear-proofing in this community. 120 �This past year, we have worked on the logistics of conducting a wide-scale urban bear-proofing experiment that should commence in spring 2013. A majority of the necessary funds were secured through CPW and the Summerlee Foundation; we are still seeking funds to complete project needs. With funds currently dedicated to the project, we purchased 760 wildlife-resistant containers from Solid Waste Systems (Parker, CO), a company that manufactures products certified by the Living with Wildlife Foundation. This fall, those containers will be fitted with electronic chips and entered into the Durango's Solid Waste Program database. Because all residential waste is removed by the City of Durango, city staff will replace regular garbage containers with the newly purchased wildlife-resistant containers according to CPW's study design. The wildlife-resistant containers will be distributed in late fall and winter after the bears have hibernated so that they are in place for the experiment in spring 2013. Objective 2: Determining the influence of urban environments on bear behavior and demography Between May 15t1t 2011 and August 15 th 2012, a total of 162 different bears were marked as part of this study, during 287 bear captures. Information about these captures is described below for each discrete capture season: summer 2011, winter 2012, and summer 2012 (ongoing; Table 1). During summer 2011 we conducted 92 total bear captures; 71 captures were unique individuals and 21 were recaptures. Of the unique individuals captured, there were 30 females, 38 males, and 3 cubs of unidentified sex (cubs were released without being immobilized and thus, gender was not determined; Table 1). We collared a total of 26 adult females, however two bears slipped out of their collars and were not recaptured, leaving 24 collared bears at the end of the field season. The mean estimated age of bears ~1 year-old on their initial capture date was 5.3 (5.7 for females and 5.1 for males), and the mean weight was 80.8 kg (59.9 kg for females and 97.4 kg for males). The mean age of collared females, based on tooth cementum, was 6 years, and estimated ages ranged from 2.5 to 23. In total, we placed traps/snares at 102 different locations (26 on public land and 76 on private land) and we had 1,253 trap nights. Capture success generally peaked during the first couple weeks of June and was highly variable throughout the remainder of the summer (Figure 2). We visited the winter dens of22 collared females between January and March 2012. Although we had 24 adult female bears collared in fall 2011, 1 female was harvested (B49), and we could not locate the den of 1 bear wearing a Lotek collar (B51 ). Nine females did not have any cubs or yearlings, 3 bears had yearlings (6 yearlings in total) and 10 had newborn cubs (21 cubs in total; 11 females and 10 males). Of those females with yearlings, 1 bear had 1 yearling, 1 bear had 2 yearlings, and 1 bear had 3 yearlings. Of those females with newborn cubs, 1 had only 1 cub, 7 bears had twins, and 2 bears had triplets. We PIT and ear-tagged yearlings in the den, recorded information on weight and body size, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. One collared bear (B43) died during the immobilization process in the den. Between May 15 th and August 15 th 2012, we conducted summer captures to obtain a sample of 40 GPS collared adult females (captures are currently ongoing). During that time there were 153 total captures; 74 were unique individuals and 79 were recaptures (Table 1). Of the unique individuals captures, 33 bears were females, 3 7 were males, and 4 cubs were of unidentified sex (cubs were not immobilized). The mean estimated age of bears ~1 year-old on their initial capture date was 4.7 (5.3 for females and 4.3 for males) and the mean weight was 72.3 kg (58.3 kg for females and 83.5 kg for males). This summer, to date, 22 new adult females have been collared. Given mortalities and slipped collars (3 collars were slipped in spring/summer 2012), 37 females were collared as of August 15t\ and trapping will continue through mid-September or until 40 GPS collars have been deployed. To date, traps have been placed in ~78 different trap locations (26 on public land and 52 on private land) for approximately 1,024 trap nights. Capture success generally climbed each week until the second week of July, and has remained high (Figure 2). The increase in capture success in 2012 is likely due to extra trapping effort, as 121 �we increased our weekly trap nights from 5 nights/week to 7 nights/week and had a higher number of traps that were baited and set on a consistent basis. Although we are still working to deploy collars for the study, the Vectronics GPS technology has been highly efficient at tracking collared bears for movement rates, habitat-use patterns, den site locations, and daily survival. To date, we have obtained >60,000 locations from 48 different female bears (Figure 3). Additionally, the GPS collar technology has allowed us to observed long-distance movements by females, particularly during the estrous period; data which has been rarely collected and reported. For example, this past June, 3 different collared bears traveled between ~60 and ~320 km in different directions from the study area (Figure 4). Two of the bears returned to their original home ranges, and I died in a vehicle collision as she appeared to be returning to Durango (B35). In 2011, mast surveys revealed that the peak timing for serviceberry maturation was in midAugust, for chokecherries it was during the last week of August and first week of September, for squaw apples it was around September I s1, and for acorns it was during in the first two weeks of September. Hawthorne berries and pinyon cones were only observed on 2 of 12 transects; neither had reached peak maturation by mid-September. Across the transects, on average, <25% of gambel oak, chokecherry, squaw apple, and hawthorn plants had mast production. Serviceberry and pinyon production was categorized as a complete failure for the year. Between I May 2011 and August 15 th 2012, 25 bears were removed from the vicinity of Durango due to non-harvest, human-related causes. Of those bears that were removed, 9 were lethally removed due to nuisance behavior (breaking into houses, killing livestock, etc), IO were killed in vehicle collisions (including 2 collared females), 4 were translocated due to conflicts with people (including I collared female), and 2 died from research activities (including I collared female). Of those mortalities and removals, 17 bears were unmarked and 8 were marked/collared for the research project ( I marked bear was a lethal conflict removal outside the study area); there were 8 adult females, 4 adult males, 2 subadult females, 7 subadult males, and 4 cubs. In addition, approximately 20 bears were harvested in the greater Durango area (GMUs 74, 75, and 751), three of which were marked by the research project (1 collared female and 2 adult males). ....,I 'Cl In summer 2011, we collected 998 hair samples from the Durango and Piedra hair-snare grids; 743 samples from Durango and 255 from Piedra. Over the 6 sampling occasions from 31 snares around Durango we collected 224, 167, 138, 77, 68, and 69 hair samples, respectively. Over the 3 sampling occasions from 9 snares in the Piedra we collected 127 samples; 46, 50, and 31 samples/occasion, respectively. We also collected 128 additional samples from 10 snares in the Piedra watershed that were only checked on a single occasion. We received the genetic results back from Wildlife Genetics International at the end of June 2012, and have summarized the Durango data. Of the 743 hair samples submitted to the laboratory, good genotypes were obtained for 438 samples. Of the remaining samples that did not produce a valid genotype, 193 did not contain enough genetic material, 104 failed during analyses for other reasons, 4 samples were not black bear, and 2 were contaminated (hair from > l bear in the sample). Across the 438 valid samples there were 107 different individuals (61 females and 47 males) detected during 192 "captures" (multiple hair samples from a single bear during I sampling occasion were considered l "capture"). Of the different individuals, 21 were only detected in I sampling occasion and 86 were detected in> I occasion (recaptures). The probability of detecting a bear within any single sampling occasion was ~0.21, and across all sampling occasions was ~O. 76. More detailed analyses of these data will be included in the FY12-13 report. In summer 2012, we collected 1,367 hair samples from the Durango and Piedra grids; 586 samples from Durango and 781 samples from Piedra. Over the 6 sampling occasions from 35 snares around Durango we collected 92, 136, 59, 55, 142, and I 02 samples, respectively. Over the 6 sampling 122 �occasions from 34 sites in the Piedra watershed we collected 73, 135, 142, 118, 144, and 169 samples respectively. Samples will be sent to Wildlife Genetics International this fall for genetic analysis. Objective 3: Identifying public attitudes about bear-human encounters Of the 5,334 valid surveys that were mailed to residents, we received 2,947 completed surveys; 2, 170 from Durango residents and 777 from La Plata county residents. The overall response rate was 55%. Non-response postcards were mailed to 2,375 residents and 354 postcards were returned (15%). Survey results are being electronically recorded so this data can be analyzed in FY12-13. SUMMARY AND FUTURE PLANS During FYl 1-12 we successfully coordinated field logistics and conducted several aspects of data collection (monitoring garbage-related bear-human conflicts, trapping and collaring bears, tracking human-related bear mortalities, assessing summer/fall forage availability, implementing DNA hair-snare surveys, and conducting a public survey). We will continue these field activities through 2015, and begin data analyses as field data are compiled. Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal. These activities include the implementation of an urban bear-proofing experiment, increasing the number of GPS collared female bears, and purchasing telemetry collars for a translocation study. In addressing the objectives of this project we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and population trends, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. Plos One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. Roaring Fork Valley urban black bear ecology study: progress report to the Colorado Division of Wildlife. Contact Sharon Baruch-Mordo for copy. Email: sharonb m@yahoo.com Beck, T.D.I. 1991-. Black bears of west-central Colorado. Technical Publication No. 39, Colorado Division of Wildlife, Colorado. Beckmann, J.P., and J. Berger. 2003a. Using black bears to test ideal-free distribution models experimentally. Journal of Mammalogy 84:594-606. Beckmann, J.P., and J. Berger. 2003b. Rapid ecological and behavioural changes in carnivores: the response of black bears (Ursus americanus) to altered food. Journal of Zoology 261:207-212. Beckmann, J.P., L. Karasin, C. Costello, S. Matthews, and Zoe Smith. 2008. Coexisting with black bears: perspectives from four case studies across North America. Wildlife Conservation Society Working Paper No 33. Beckmann, J.P., C.W. Lackey, and J. Berger. 2004. Evaluation of deterrent techniques and dogs to alter behavior of"nuisance" black bears. Wildlife Society Bulletin 32: 1141-1146. Beston, J.A. 2011. Variation in life history and demography of the American black bear. Journal of Wildlife Management 75:1588-1596. Caswell, H. 200 I. Matrix population models: construction, analysis, and interpretation. Second Edition, Sinauer Associates, Sunderland, Massachussetts. Efford, M.G., D.K. Dawson, and D.L. Borchers. 2009. Population density estimated from locations of individuals on a passive dector array. Ecology 90:2676-2682. 123 �'-' 'Cl ...,; 'Cl Garshelis, D.L., and H. Hristienko. 2006. State and provincial estimates of American black bear numbers versus agency assessments of population trend. Ursus 17: 1-7. Gardner, B., J.A. Royle, M.T. Wegan, R.E. Rainbolt, P.O. Curtis. 2010. Estimating black bear density using DNA data from hair snares. Journal of Wildlife Management 74:318-325. Gore, M.L., W.F. Siemer, J.E. Shanahan, D. Schuefele, and D.J. Decker. 2005. Effects on risk perception of media coverage of a black bear-related human fatality. Wildlife Society Bulletin 33 :507-516. Gore, M.L., B.A. Knuth, C.W. Scherer, and P.O. Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflicts. Conservation Letters 1: 136-145. Greenleaf, S.S., S.M. Matthews, R.G. Wright, J.J. Beecham, and H.M. Leithead. 2009. Food habitat of American black bears as a metric for direct management of human-bear conflict in Yosemite Valley, Yosemite National Park, California. Ursus 20:94-101. Hostetler, J.A., J.W. McCown, E.P. Garrison, A.M Neils, M.A. Barrett, M.E. Sunquist, S.L. Simek, and M.K. Oli. 2009. Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation 142:2456-2463. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21 st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. McLoughlin, P.O., D.W. Morris, D. Fortin, E. Vander Wal, and A.L. Contasti. 2010. Considering ecological dynamics in resource selection functions. Journal of Animal Ecology 79:4-12. Mitchell, M.S., L.B. Pacifici, J.B. Grand, and R.A. Powell. 2009. Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64: 183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8: 169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human-bear conflicts: a survey of wildlife species in North America. Ursus 18: 217-229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83 :340-354. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31 :517-520. Prepared by _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ Heather E. Johnson, Wildlife Researcher 124 �wt _,I _,i Table 1. Capture information for black bears that have been marked in the vicinity of Durango, CO (collared adult females are identified with an"*"). Only information from the initial capture of each individual is shown {no recaEtures}. Bear ID Bl B2 B3 B4 B5 B6* B7* B8* B9 BIO* Bl I B12 B13 B14* B15 B16 B17* B18* B19 B20 B21* B22 B23 B24* B25* B26 B27* B28 B29 B30* B31 B32 B33 B34 B35* B36 B37 B38 B39 B40* Capture Date 5/10/2011 5/12/2011 5/13/2011 5/16/2011 5/16/2011 5/17/2011 5/17/2011 5/18/2011 5/26/2011 5/26/2011 6/3/2011 6/2/2011 6/3/2011 6/6/2011 6/6/2011 6/7/2011 6/7/2011 6/8/2011 6/9/2011 6/9/2011 6/10/2011 6/10/2011 6/13/2011 6/14/2011 6/15/2011 6/15/2011 6/16/2011 6/16/2011 6/21/2011 6/22/2011 6/24/2011 6/24/2011 6/28/2011 6/28/2011 7/5/2011 7/6/2011 7/7/2011 7/13/2011 7/13/2011 7/21/2011 UTM Easting 246233 271495 271495 270950 270227 243210 243225 271478 238803 269869 252163 253216 253216 252157 253216 253216 256936 256918 235193 243258 252298 252163 246350 243252 239003 252164 243252 253233 239840 235911 239840 243252 239294 239001 246350 239840 243252 243236 251222 248550 UTM Northing 4142768 4130889 4130894 4127914 4139984 4128716 4133053 4130892 4126790 4139040 4137968 4137387 4138868 4137967 4138868 4138868 4134633 4134625 4128894 4133040 4136435 4137968 4135617 4133030 4134158 4137966 4133030 4138873 4126949 4128916 4126949 4133030 4133260 4134154 4135617 4126949 4133030 4128710 4133120 4131645 Sex M M M M M F F F M F M M M F M M F F M M F M M F F M F M M F M F M M F M M M M F Age 1 9 6 3 6 4 4 4 1 7 8 5 3 7 3 7 4 8 9 10 8 8 3 7 4 10 23 6 1 6 4 1 1 3 3 4 1 8 6 4 Kg 35.4 144.2 130.2 84.4 135.2 62.6 63.5 51.7 34.9 80.7 130.2 103.4 59.0 58.1 58.1 117.0 51.7 61.7 146.5 131.5 69.4 87.5 64.9 64.9 63.5 108.9 75.3 101.2 49.0 60.3 85.3 19.1 34.9 85.3 44.5 67.1 39.0 145.1 149.7 80.7 \_.I _,, 1w 1w' w ~ .._, ~ 1w ~ 'w .._, 1w ~ _,i '-' 1w 1w 1w' ~ '-" \wl 1w '-' 'w I-, ~ ~ w' 1w ~ ._, ~ '-" 125 _, ~ '-' �'<al ,_, ..., '.-i '-.I "-' .._ '..,I .,,.; 'Cl ~ '-' .I I,.) 'cl 'el '«;I ....._-__, .I ... ~ \al ...., 'el ~ ..._ 'cl -..I 'Cl ..., ...,, "1111 1.'661 .,I ._ 'SI ._ ,.,,, B41 B42* B43* B44 B45 B46* B47* B48 B49* B50* B51* B52* B53 B54 B55* B56 B57* B58 B59 B60 B61 B62 B63 B64 B65* B66 B67* B68 B95 B96 B97 B98 B99 BIOO BIOi Bl02 Bl03 Bl04 Bl05 Bl06 Bl07 Bl08 Bl09 BllO Bl 11 7/22/2011 7/26/2011 8/3/2011 8/3/2011 9/3/2011 8/5/2011 8/8/2011 8/10/2011 8/11/2011 8/11/2011 8/12/201 I 8/12/2011 8/15/2011 8/16/2011 8/18/2011 8/29/2011 8/30/201 I 8/31/2011 9/1/2011 9/2/2011 9/3/2011 9/6/2011 9/7/2011 8/6/2011 9/15/2011 9/20/2011 9/21/2011 9/21/2011 1/19/2012 1/19/2012 1/19/2012 1/26/2012 2/27/2012 2/27/2012 2/29/2012 2/29/2012 3/1/2012 3/1/2012 3/6/2012 3/8/2012 3/8/2012 3/14/2012 3/14/2012 3/15/2012 3/15/2012 4132272 4141391 4142791 4132487 4139587 4128720 4131581 4139620 4128720 4139587 4130370 4139587 4128720 4130516 4134423 4132993 4135903 4135903 4132935 4133020 4130321 4128530 4131251 4141969 4134848 4130163 4134626 4133006 4142276 4142276 4142276 4134879 4137615 4137615 4126214 4126214 4120831 4120831 4132714 4139774 4139774 4138519 4138519 4140021 4140021 237368 245945 246183 765141 245965 243435 251783 245914 243435 245965 249049 245965 243435 251898 251464 246321 243374 243374 243952 242187 244602 245790 248612 245850 243948 240731 256930 249067 247647 247647 247647 257183 249929 249929 248090 248090 243713 243713 240146 268055 268055 245785 245785 244547 244547 126 M F F M M F F F F F F F M M F M F M M F M M M M F F F M M M M M M F M F M M F F F F M M F 3 8 11 I 6 4 6 I 4 11 12 4 7 2 3 IO 3 3 15 2 7 I 2 I 4 I 3 8 I I I I cub cub cub cub cub cub cub cub cub cub cub cub cub 67.1 69.9 85.3 35.4 176.0 58.1 53.5 26.3 55.3 101.2 61.7 65.3 163.3 52.6 49.0 166.9 46.3 48.1 153.3 35.4 213.6 22.7 37.2 28.6 89.8 39.9 52.6 207.7 44.0 44.0 49.0 20.9 I.I 1.2 1.8 1.7 1.9 1.7 2.0 2.7 2.7 1.4 1.4 2.5 2.5 �~ w B112 B113 B114 B115 B116 B117 B118 B119 B120 B121 * B122* B123 B124* B125* B126 B127* B128* B129* B130 B131 B132 B133* B134* B135 B136 B137 B138 B139 B140 B141* B142 B143* B144* B145* B146 B147 B148 B149 B150 B151 B152* B153 B154 B155 B156 3/15/2012 3/17/2012 3/17/2012 3/17/2012 3/20/2012 3/20/2012 3/22/2012 3/22/2012 5/27/2012 5/29/2012 5/30/2012 6/5/2012 6/6/2012 6/8/2012 6/8/2012 6/10/2012 6/11/2012 6/14/2012 6/22/2012 6/23/2012 6/28/2012 6/29/2012 6/30/2012 6/30/2012 7/1/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/6/2012 7/6/2012 7/7/2012 7/7/2012 7/7/2012 7/10/2012 7/11/2012 7/15/2012 7/16/2012 7/26/2012 7/17/2012 7/17/2012 7/17/2012 7/19/2012 7/19/2012 244547 245228 245228 245228 240909 240909 243524 243524 254732 251670 249059 240102 249158 244618 251670 239005 239005 254576 250152 765047 765047 765932 765932 252014 765047 249059 254997 238245 763921 765132 254997 241210 238245 763921 254739 241334 255983 244618 241334 243888 241210 249059 253439 241334 252621 4140021 4143164 4143164 4143164 4134002 4134002 4146585 4146585 4133249 4132767 4132998 4128939 4127065 4132132 4132767 4134459 4134159 4135043 4127691 4131635 4131635 4127651 4127651 4133509 4131635 4132998 4135825 4131204 4132873 4132506 4135825 4137115 4131204 4132873 4133234 4138018 4135921 4132132 4138018 4129546 4137114 4132998 4134693 4138018 4130532 127 F F M M M F M F F F F M F F F F F F M M M F F M F M F M M F M F F F M M M M M M F M M F F cub cub cub cub cub cub cub cub 1 4 5 2 7 8 1 10 8 6 1 6 1 3 8 1 2 2 2 1 3 3 3 3 9 6 5 1 3 1 2 3 8 2 3 2 1 2.6 2.5 2.0 2.0 2.0 2.0 2.5 2.9 20.9 76.2 66.2 48.1 80.7 98.9 15.9 58.1 56.2 54.4 12.7 111.6 20.4 49.0 90.7 20.9 46.3 26.8 30.8 30.4 67.1 55.3 37.2 45.4 72.6 70.3 110.2 43.5 73.9 45.4 53.5 60.3 99.8 49.9 63.5 30.8 26.3 'w ~ 'w ~ 1-, ~ 1w ~ 'w ~ 1w' l_.i ~ 1w' w '- 1w, '-' 'wl w 'w 'w' wl ._ W' iw 1w' ~ l.,J '-' -' ~ 1w ., 'WI Iv �..., \ell 'Cl ...., ...., "Cl "el ,.-I .._ 1,./ _, "161 'Cl ...,, ~ '411 'Cl ._ ,._ '-.I 'Cl ..., le/ 'cl 'Cl \(SJ/ -el ...., val >,cl B157 B158 B159 B160 B161 * B162 B163 B164 B165* B166 B167* B168 B169 B170 B171 B172 B173* B174* B175* B176 B177 B178 B179 B180* B181 * B182 B190 B191 B192 B193 B194 B195 B196 7/19/2012 7/20/2012 7/21/2012 7/24/2012 7/25/2012 7/25/2012 7/26/2012 7/28/2012 7/29/2012 7/29/2012 7/31/2012 7/31/2012 7/31/2012 8/1/2012 8/2/2012 8/2/2012 8/3/2012 8/3/2012 8/3/2012 8/3/2012 8/4/2012 8/4/2012 8/5/2012 8/5/2012 8/5/2012 8/8/2012 8/9/2012 8/11/2012 8/11/2012 8/12/2012 8/12/2012 8/13/2012 8/14/2012 4144294 4134789 4127920 4132998 4134789 4132998 4134875 4133863 4133706 4130532 4139143 4134693 4132998 4132998 4137051 4139143 4139143 4128740 4128609 4130532 4139143 4132988 4139143 4141533 4138557 4132998 4128959 4132998 4128959 4129360 4128712 4132998 4132998 248417 252546 242236 249059 242546 249059 243954 242611 251815 252621 248578 253439 249059 249059 248192 248578 248578 253341 254916 252621 248578 249059 248578 248939 247127 259049 245293 249059 245293 243652 243218 259049 249059 'SI 'cl 'ct/ - ..I ..., 'cl 'CJ/ le/ ._ 'ct/ .I ..,., . 128 M M F M F M F M F M F M F M M F F F F M M M M F F M M M M M M M F 6 3 2 2 5 10 1 6 12 8 18 4 2 4 2 2 5 3 10 2 7 2 1 3 3 2 12 4 9 5 5 6 2 136.1 50.8 39.9 64.0 76.2 108.0 37.6 117.0 85.3 121.6 58.1 87.5 44.5 119.3 26.8 28.1 73.9 43.5 76.2 54.4 93.9 35.4 35.4 71.7 58.1 70.8 153.3 60.3 148.8 87.5 137.0 151.0 42.2 �Figure I. Map of the locations of the 2012 hair snare sites for the Durango and Piedra non-invasive genetic sampling grids. ,·~~·~:- :.w .- ' .· -.r~!:~:~>-~. -~ \"' ,'·, ,. •• ,,. '( .. ,r. )~~ ,_,-~ -~ :~ ' ~ . ,±.,~ · :; • . ~ ~ \·---=· ' : 7 < ' t ['-'t ~ ·, .,·1t .L.' __, ·:'·• ~ -~ .... ! '. -• • :·;-!! • 2012 Hair s nare Locations Major Roads Perimeter of Little Sand Fire 3.75 7.5 '.:'-:-, , .1 -~ • . ',\ I J~~•••·, . ·~· ,::;,-;:- f"'!""'":"""~~...rt ... :.~ 'L;.,. .~ 129 �Figure 2. Number of black bear captures by week from May 15 th through September 3rd for the 2011 and 2012 summer trapping seasons (2012 is currently ongoing). 20 --t--2011 18 -4--2012 u, 16 cu ...a.~ 14 '-' ,, " a... 12 I \ I \ "' -... ~ 10 0 cu .a E :::, z ,..-,) 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Week (from May 15th through August) 'Cl ...._ 130 16 17 18 �Figure 3. Locations from 48 adult female black bears collected with GPS collars from May 20 11 to present in the vicin ity of Durango, CO (different colored clusters of points represent di fferent individual bears). t ·, ~ 131 t ,- ..., ~1,} • ·P ( : -~ -!; �Figure 4. Long distance movements of three collared adult female bears during the breeding season in June 20 12. -~~,,. ·-"·"' A~ ~o .,, e .... 0 <¢ ~ ~ ' ~ (.)(t) (D ..,,,o oeo 0 "'""'(t) 0 "' ., ~~ • 1-..I i~----, Bear ID B67 • B57 ,..___ 0 !.1'11tg.1,11,r.- -. ,.,er,.,, 0 ~-- 0 B35 0 l:,{t',lUVff ".£, 5 . 10 '.'I 20 Kilometers ; " f 1HOIJ 1.14•.;. If) ;H .lOC.., K•rtt~J -- • Bloomfield , ...~lt.1. £ lllf,;_•:t.l t 4 Al I r •1t, l Ah.4 IJJ.C.rl{l'IJ.,.\. :r4'.l. ~r,t')fJ H ;1,~ .;.t fll,.J ..c~u, Ii• ,.., .. 21:: m ...IJ'J. · ~4w.f 132 I �Colorado Division of Parks and Wildlife July 2012 – June 2013 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 3 Federal Aid Project No. W-204-R1 : : : : : Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2012 – June 30, 2013 Author: H.E. Johnson; project cooperators, C. Bishop, J. Broderick, J. Apker, S. Lischke, S. Breck, J. Beckmann, K. Wilson, M. Reynolds-Hogland, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 4 entities: Colorado Parks and Wildlife (CPW), the USDA National Wildlife Research Center, Colorado State University, and Wildlife Conservation Society. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear habitat-use patterns and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY10-11; during this past fiscal year we have primarily focused on collecting field data in the vicinity of Durango, Colorado. Specifically, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, collected GPS collar data on bear locations, monitored demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys, deployed 900 bear-resistant containers for an experiment on the effectiveness of urban-bear-proofing, obtained data on garbage-related bear-human conflicts, and specified a sampling design to assess human compliance with city ordinances. Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 119 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS HEATHER E. JOHNSON PROJECT NARRATIVE OBJECTIVES To conduct a study on black bears in Colorado that 1) determines the influence of urban environments on bear habitat-use patterns and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears. SEGMENT OBJECTIVES 1. Work with personnel from CPW Area 15, CPW Southwest Region, the City of Durango, La Plata County, US Forest Service (Columbine and Pagosa Ranger Districts), Bureau of Land Management (BLM; Tres Rio Field Office), Southern Ute Tribe, and private landowners on field research logistics. 2. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear habitatuse patterns and demography. 3. Monitor bear locations and survival via global position system (GPS) collar locations. 4. Monitor bear fecundity and cub survival through winter den investigations of collared adult female bears. 5. Obtain data on summer/fall natural food availability for bears based on the phenology and abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 6. Track human-related bear mortalities and removals around Durango from lethal conflict managment, vehicle collisions, harvest, and translocations. 7. Perform non-invasive genetic mark-recapture surveys to estimate bear density and population size around Durango (urban site) and in the Piedra watershed (wildland site). 8. Deploy 900 bear-resistant garbage containers for an experiment on the effectiveness of wide-scale urban bear-proofing for reducing bear-human conflicts. 9. Collect data on the frequency of bears accessing human garbage in treatment and control areas for an urban bear-proofing experiment. 10. Specify a sampling design to quantify compliance of human behavior with wildlife ordinances. INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human conflicts can result in public safety concerns, property damage, bear mortality (i.e. euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman conflicts (i.e., education, aversive conditioning of bears, and modifications to harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceeding difficult to estimate (Garshelis and Hristienko 2006). Without a thorough understanding of the relationship between conflict rates and bear behavior and population 120 �dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, agricultural resources, fruit trees, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of this resource. Bear-use of human food not only increases interactions between bears and people but has been found to alter bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly influence both bear behavior and demography. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures for bears in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for modifying bearhabitat relationships, they also have critical implications for increasing rates of bear-human conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we initiated a project in FY10-11 to 1) determine the influence of urban environments on bear habitat-use patterns and demography, 2) test a management strategy for reducing bear-human conflicts, 3) examine public attitudes and behaviors related to bear-human encounters, and 4) develop population and habitat models to support the sustainable monitoring and management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY12-13, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, collected GPS collar data on bear locations, monitored demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys, deployed 900 bear-resistant containers for an experiment on the effectiveness of urban-bear-proofing, obtained data on garbage-related bear-human conflicts, and specified a sampling design to assess human compliance with city ordinances. Our efforts focused largely on collecting field data to meet research objectives 1-3, information which will eventually be used to address objective 4. We report general summary information from field activities over the past year; detailed analyses of field data will occur in future years. STUDY AREA To meet study objectives, a combination of site-specific field data and statewide data will be required. Site-specific field data is being collected in the vicinity of Durango, and is the focus of this progress report. Regional and statewide analyses will be conducted in future years. The town of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town 121 �is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon-juniper, aspen, mountain shrub, and agricultural communities. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), squaw apple (Peraphyllum ramosissimum) and pinyon pine (Pinus edulis). Durango is predominately surrounded by public land managed by the San Juan National Forest, BLM, CPW, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts (Baruch-Mordo et al. 2008, CPW unpublished data). METHODS Objective 1: Determining the influence of urban environments on bear behavior and demography To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear habitat-use patterns and demography, we are collecting a suite of data types including locations from collared bears on the urban-wildland interface, survival and reproductive rates of those bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitat types using markrecapture methods. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011). Collaring and Marking Bears – To assess bear habitat-use patterns and demographic rates with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates that drive population growth. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, vital rates that are often associated with variation in bear population trends (Mitchell et al. 2009, Beston 2011). We have targeted summer trapping efforts within ~10 km of the center of Durango to collar a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urbanwildland interface. Bears are trapped with box traps, which are baited with fish, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar (manufactured by Vectronics), and a tooth (first pre-molar) is pulled for age verification. GPS collars record bear locations every hour, and upload realtime locations to a central database via satellite system every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair. Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wildland Interface – To examine movement and habitat-use patterns of bears along the urban-wildland interface, we are using GPS collar location data from adult females. Hourly GPS data are downloaded from the collars in the field on a biannual basis (during early fall and winter den checks). We will use those locations to assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear movement and resource selection patterns (Manly et al. 2002, McLoughlin et al. 2010, Morales et al. 2010). For spatial data, we will use satellite imagery to track annual spring/early summer forage availability, and ground surveys to 122 �track late summer/fall mast availability (see details below). We will obtain information on elevation, aspect, slope and terrain ruggedness information from digital elevation models. Weather information will be acquired from PRISM spatial data (www.prism.oregonstate.edu/) which interpolates monthly temperature and precipitation patterns across landscapes, accounting for elevation and topography. We will derive spatial models on distances to perennial water sources and watershed drainages from the National Hydrology Dataset. Vegetation type and cover layers will be generated from the USFS LandFire datasets (http://www.landfire.gov/vegetation.php). Covariates related to human development (e.g., density of human structures and paved roads) will be derived from existing CPW and La Plata County digital data layers on locations of human structures, roads, and census information. While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of acorn and berry resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural fall forage for bears around Durango, we conducted bimonthly mast surveys. Surveys were performed from early August through mid-September in 2011 and 2012, when fruits and nuts should reach peak maturation and bears are in their hyperphagia stage prior to hibernation. In the Durango region, key mast species for bears are gambel oak, chokecherry, serviceberry, hawthorne, squaw apple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 16 transects on public lands to evaluate bear mast availability. Each transect was 1 km in length and was situated along an existing trail or stream drainage. For each transect, field technicians recorded the phenological stage and the percentage of plants of each species that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, 25 – 50% of plants with mast, etc). Estimating Demographic Rates – To assess the influence of human development on bear demographic rates and population trends we are using the following data types: 1) survival and reproduction of collared adult female bears, and cub survival, 2) mortalities and removals of marked and unmarked bears in the vicinity of Durango, and 3) non-invasive genetic surveys to estimate density and abundance of bears around urban and wildland sites. Collared female bears allow us to track annual survival, fecundity and cub survival (of their offspring); parameters we have monitored since summer 2011 and which we will continue to monitor for the next 3 years. We used real-time GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations were stationary for multiple sampling points. Fecundity and cub survival were monitored from den checks of collared females. Numbers of newborn cubs provide information on fucundity, while repeated annual den checks of collared females allow us to estimate cub survival. Yearlings hibernate with their mothers, so we can observe the number of cubs alive in the den in year t that survived their first year of life to t+1. Adult female survival, fecundity and cub survival will be used in projection models to assess population performance (Caswell 2001), particularly in relation to habitat selection. In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked (i.e., males, subadults) and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on human-related bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and hunter harvest. For all bears removed from the study area we collect a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery analyses to estimate adult male and subadult survival, while also gaining valuable information on cause-specific bear mortality within the study system. 123 �To better understand the influence of urban environments on bear density and abundance, we are employing non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between a bear population around the urban center of Durango and in a nearby “wildland” area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size, and within each cell we constructed 1 snare site. Snares consisted of a scented bait hanging high in a tree, surrounded barbed wire around a cluster of trees encircling the bait (wire was strung 50 cm above ground). When bears climb over or under the wire to investigate the bait, they leave a hair sample on the barbed wire. During summers 2011 through 2013, snares were deployed during the first 2 weeks of June, and we conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with anise, berry, fish, maple or bacon scent, and collected hair samples from all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. In summer 2012, we constructed 35 snares in the Durango grid and 34 snares in the wildland grid. The layout of the wildland grid had to be modified to account for closures associated with the Little Sand fire, which began burning on the San Juan National Forest on May 13th 2012. This modification can be easily accounted for in future analyses with spatially-explicit mark recapture statistics (Efford et al. 2009, Gardner et al. 2010) which increase flexibility with sampling designs. In fall 2012, all hair samples were sent to the laboratory at Wildlife Genetics International (Nelson, British Columbia, Canada) for genotyping; genetic results were returned at the end of July 2012. In summer 2013, we constructed 34 snare sites in the Durango grid and 35 sites in the wildland grid (Figure 1). Samples collected in 2013 will be sent to the laboratory this fall and results are expected in summer 2014. Objective 2: Testing a management strategy to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that food source (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of “cleaning up” a town. Given the high price to operationally “bearproof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project, we are implementing the first experimental test of wide-scale urban bearproofing for reducing bear-human conflicts. As part of the experiment we have designated 2 residential ‘treatment’ areas and 2 paired ‘control’ areas, consisting of a total of ~2,000 homes (Figure 2). In spring and early summer 2013 we deployed ~900 bear-resistant garbage containers within the treatment areas (approximately 100 homes already had these containers), such that all residents had a bear-resistant container. We also canvassed homes within the treatment areas, talking with residents about methods to bear-proof their properties, reminding them to lock their garbage containers, and asking that they remove bird feeders, outdoor pet food, and other bear attractants (no action occurred in control areas). Additionally, we increased enforcement of wildlife ordinances within treatment areas, providing official warnings and notifying City Code Enforcement when wildlife ordinances were violated. To track the effectiveness of these efforts in reducing bear-human conflicts we have planned to collect pre- and post-treatment data. For 2 years pre-treatment (summers 2011 and 2012), field technicians patrolled each street within proposed treatment/control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from ~05:30 - 06:30 AM and recorded locations where there was evidence that bears had obtained garbage or other human food sources. Monitoring occurred from early July through midSept, months that experience the highest numbers of bear-human conflicts in Durango (CPW unpublished 124 �data). During summer 2013 project personnel have been collecting the first year of post-treatment data (currently ongoing); post-treatment data will be collected for a minimum of 3 years. Each summer, in addition to collecting information on bears accessing human foods, we have quantified the “availability” of garbage to bears, by documenting the location and container type (wildlife-resistant or regular) of every garbage receptacle in the survey area accessible to bears the night prior to garbage pick-up. These data will allow us to track changes in the number of wildlife-resistant containers in the study area over the course of the experiment, and provide an estimate of the amount of human food available to bears in town. Once the experiment is complete, we will use pre- and posttreatment data collected during morning patrols and from calls received by CPW and the City of Durango to quantify the effectiveness of residential bear-proofing. Objective 3: Identifying public attitudes and behaviors related to bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have stimulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011). Thus, in conjunction with Stacy Lischka, Human Dimensions Specialist for CPW, we have initiated efforts to better understand human attitudes and behaviors in the context of our ecological data on bears. To assess data on human attitudes we are using public surveys to 1) quantify perceptions about bears, bear management, and bear-human encounters, and 2) explore motivations for compliance and noncompliance with wildlife ordinances designed to reduce bear-human conflicts. To meet those objectives, we developed a three part public mail survey to be conducted in conjunction with our urban bear-proofing experiment. Residents will be surveyed pre-, during, and post-implementation of the experiment, in treatment and control areas, as well as across a larger portion of the community. Surveys will be mailed to all residents within Durango city limits, and a subset of La Plata county residents within the study area. Survey responses will allow us to quantify current attitudes and perceptions about bear-human interactions, and how those perceptions change over time in association with a management effort such as wide-scale urban bear-proofing. The survey will also determine the number of residents that have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. The first (pre-treatment) public survey was implemented during winter 2012 (see Johnson et al. 2012 for details). The second survey will be conducted during fall 2013 or winter 2014. In addition to collecting data on human attitudes, we will also collect data on human behavior as part of an effort that was initiated this past year. Data collection will occur in conjunction with the treatment and control areas of the bear-proofing experiment starting summer 2013 (mid-July through midSept). Using a random stratified sampling design we will monitor human compliance with wildlife ordinances at residences throughout the conflict season. Houses will be surveyed on the morning of garbage pick-up (5:30 – 7:00 AM) to record whether those residences have secured their garbage the night prior (locked wildlife-resistant container or in a garage or shed that is not visible from the street) or have garbage available to bears. Compliance data will be analyzed in conjunction with survey information, spatial covariates, and bear activity to better understand how factors such as management actions and rates of wildlife-human interactions influence human behavior. The first year of data collected on human compliance will be summarized in the annual report for FY2013-14. 125 �RESULTS AND DISCUSSION Objective 1: Determining the influence of urban environments on bear behavior and demography Between May 20th 2012 and August 26th 2013, an additional 140 unique bears were marked during 327 bear captures; on the project to date there have been 232 different individuals marked during 435 captures. Information about these captures is described below for each discrete capture season: summer 2012, winter 2013, and summer 2013 (ongoing; Table 1). During summer 2012 we conducted 179 total bear captures; 86 captures were unique individuals and 93 were recaptures. Of the unique individuals captured, there were 37 females and 49 males (Table 1). We placed collars on 25 new adult females, and with those that had been previously collared in 2011, had 40 collars deployed by the end of August. The mean estimated age of bears ≥1 year-old on their initial capture date was 4.8 (5.7 for females and 4.2 for males), and mean weight was 73.2 kg (61.4 kg for females and 82.4 kg for males). The mean age of females that were newly collared in 2012, based on tooth cementum, was 8.6 years, with ages ranging from 3 to 24 years. In total, we placed traps at 90 different locations and conducted 1,114 trap nights. Capture success generally climbed each week until the second week of July, and remained high except for the second week of August (Figure 3). High trapping rates in 2012 were likely due to a combination of extra effort (we increased weekly trap nights from 5 nights/week to 7 nights/week and had a higher number of traps that were baited and set on a consistent basis) and a poor natural food year that brought additional bears into the urban-wildland interface around Durango. We visited the winter dens of 27 collared females between January and March 2013. Although we had 40 adult female bears collared at the end of summer 2012 there were 4 mortalities in fall: 1 female was legally harvested (B173), 1 was killed in a vehicle collision (B35), one was illegally shot (B134) and 1 died of unknown causes (B174). Additionally, in fall 2012, 9 GPS collars on collared females prematurely failed (B14, B18, B21, B24, B42, B55, B121, B122, and B144) and we could not locate their dens via VHF or GPS signals. Of the 27 adult females that we processed last winter, 13 did not have any cubs or yearlings, 6 had yearlings (6 yearlings in total, all bears had only one surviving yearling), and 8 had newborn cubs (14 cubs in total; 5 females and 9 males). Of those females with newborn cubs, 2 bears had only 1 cub and 6 bears had twins. We PIT and ear-tagged yearlings in the den, recorded information on weight, body size, body condition, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. We found that reproductive success, measured as the number of cubs/adult female/year was 0.52 (SE = 0.16) for winter 2013, almost half of the reproductive rate observed in 2012 (0.95, SE = 0.24). Cub survival for 2013 (survival from newborn to 1 year) was ~40% (we do not have these data for 2012 as 2 sequential years are required for estimation). Between June 1st and August 26th 2012, we conducted summer captures with the goal of obtaining a sample of 40 GPS collared adult females (captures are currently ongoing). During that time there were 114 total captures; 37 were unique individuals and 77 were recaptures (Table 1). Of the unique individuals captures, 17 bears were females and 20 were males (there were also 9 cubs caught of unidentified sex; cubs were not immobilized or processed). The mean estimated age of bears ≥1 year-old on their initial capture date was 5.0 (4.9 for females and 5.0 for males) and the mean weight was 77.5 kg (56.9 kg for females and 92.1 kg for males). This summer, to date, 7 new adult females have been collared, and 5 females were recaptured that had previously slipped collars or had a malfunctioning collar. Given malfunctioning collars and 1 mortality (B65, vehicle collision), 35 females were collared as of August 26th, and trapping will continue through mid-September or until working GPS collars have been deployed. To date, traps have been placed in 93 different trap locations (30 on public land and 63 on private land) for 1,124 trap nights. Thus far, capture success has been fairly steady throughout the summer (Figure 3). 126 �To date, we have obtained >183,000 locations from GPS collars on 56 different female bears; 44 different bears collected location data in 2012 (Figure 4). We will start analyzing habitat-use data in the coming year and have generated spatial covariate data for elevation, slope, aspect, terrain ruggedness, distance to perennial water, distance to drainage, vegetation type, vegetation cover, distance to human structure, density of human structures, distance to paved road, and density of paved roads. The availability of natural mast foods was extremely limited in 2012, likely due to late freezes in June that destroyed berry and acorn flowers, and due to extreme summer drought. Of the few berries and acorns observed that summer, most were shriveled and dried up during the peak period of hyperphagia for bears (late summer/early fall). For example, gambel oak can be observed along all vegetation transects, but acorns were only observed on 5 of 15 transects, with limited production. Those acorns that did reach maturation were at their peak in mid-Sept. Chokecherry and serviceberry plants were observed on 13 of 15 transects, but no chokecherry fruits were seen (complete mast failure), and only a few shriveled serviceberries were seen. Pinyon pine nuts were fairly abundant on 2 transects, with mast production peaking in mid-Sept. Squaw apple fruits were only seen on 2 transects, and there were limited fruits that were mostly dried up. Hawthorne fruits were not found on any transect (complete mast failure). Between May 1st 2011 and November 1st 2012, a total of 59 bears were removed from the vicinity of Durango. Of those bears, 21 were killed in vehicle collisions, 18 were legally harvested, 10 were lethally removed due to nuisance behavior (breaking into houses, killing livestock, etc.), 3 died from nonharvest related gunshots, 2 were translocated due to conflicts with people, 1 was electrocuted, and 4 died from unknown causes. Of those mortalities and removals there were 17 adult females, 14 adult males, 11 subadult females, 9 subadult males, 6 cubs, and 2 bears of unknown sex/age class. Forty-one bears were unmarked and 17 were marked or collared for the research project. Additionally, 5 marked bears were reported killed outside the study area; 3 died from lethal conflict management and 2 died from vehicle collisions. In summer 2012, we collected 1,367 hair samples from the Durango and wildland grids; 586 samples from Durango and 781 samples from the wildland site. Over the 6 sampling occasions from 35 snares around Durango, we collected 92, 136, 59, 55, 142, and 102 samples, respectively. Over the 6 sampling occasions from 34 sites in the wildland grid, we collected 73, 135, 142, 118, 144, and 169 samples, respectively. We received the genetic results back from Wildlife Genetics International at the end of July 2013. Of the 1,367 hair samples submitted to the laboratory, good genotypes were obtained for 707 samples (52%). Of the remaining samples that did not produce a valid genotype, 363 (27%) did not contain enough genetic material, 274 (20%) failed during analyses for other reasons, and 23 (2%) samples were not black bear. Across the 707 valid samples there were 303 genotypes generated from the Durango grid and 404 generated from the wildland grid. In the Durango grid, 97 different individuals were detected during 138 “captures” (multiple hair samples from a single bear during 1 sampling occasion were considered 1 “capture”). Of those individuals, 71 were only detected in 1 sampling occasion and 26 were detected in >1 occasion (recaptures). The probability of detecting a bear within any single sampling occasion was 0.14, and across all sampling occasions was 0.58. In the wildland grid, 55 different individuals were detected during 71 “captures.” Of those individuals, 44 were only detected in 1 sampling occasion and 11 were detected in >1 occasion (recaptures). The probability of detecting a bear within any single sampling occasion was 0.09, and across all sampling occasions was 0.42. Detailed mark-recapture analyses of these data will be conducted in the future to estimate annual density and abundance at each site. In summer 2013, we collected 1,365 hair samples from the Durango and wildland grids; 680 samples from Durango and 685 samples from the wildland site. Over the 6 sampling occasions from 34 snares around Durango we collected 106, 151, 131, 62, 106, and 124 samples, respectively. Over the 6 127 �sampling occasions from 35 sites in the wildland grid we collected 112, 83, 141, 100, 126, and 123 samples, respectively. The number of samples/snare ranged from 0 to 121 in the Durango grid and from 1 to 78 in the wildland grid. Samples will be sent to Wildlife Genetics International this fall for genetic analysis. Objective 2: Testing management strategies to reduce bear-human conflicts During summer 2012 (July through mid-August) we collected a second year of pre-treatment data for the bear-proofing experiment. Within proposed treatment and control areas we observed 177 instances of bears accessing residential garbage during our morning patrols (Figure 2); observations peaked in early September. Of those garbage containers accessed by bears, 94% were regular containers or unsecured trash bags and 6% were wildlife-resistant containers. Bears accessed human food from wildlife-resistant containers when they were not properly latched. In quantifying the availability of garbage to bears, we recorded the location and container type of 1,530 garbage cans in proposed treatment and control areas. Of those containers, 86% were regular (non-wildlife resistant) and 14% were wildlife-resistant. This demonstrates the limited residential bear-proofing that currently exists in Durango, and the relevance of conducting an experimental test of wide-scale urban bear-proofing in this community. This past year, we worked on the logistics of implementing the urban bear-proofing experiment. Final funds were secured through CPW, the Summerlee Foundation, and the International Bear Association to purchase the remaining containers needed for the study. Wildlife-resistant containers were acquired through Solid Waste Systems (Parker, CO), a company that manufactures containers certified by the Living with Wildlife Foundation. Containers were delivered to Durango, entered into the City of Durango’s Solid Waste Program database, and distributed by the City in spring and early summer 2013 to residences within treatment areas. Starting in mid-July 2013, we initiated the first year of post-treatment conflict monitoring. Data collection is currently ongoing, but as of August 26th we had recorded 153 incidences of bears accessing residential garbage; 75 conflicts in the treatment areas and 78 conflicts in control areas. Of those conflicts, 71% occurred with regular garbage containers or unsecured trash, and 29% occurred with wildliferesistant containers. In quantifying the availability of garbage to bears, we recorded the location and container type of 1,678 garbage cans in treatment and control areas. Within the northern control area 72% of containers were regular and 28% were wildlife-resistant, in the southern control area 91% were regular and 9% were wildlife-resistant, in the northern treatment area 11% of containers were regular (residents that refused a bear-resistant container or have kept additional regular containers on their property) and 89% were wildlife-resistant, and in the southern treatment area 27% were regular and 73% were wildliferesistant. SUMMARY AND FUTURE PLANS During FY12-13 we successfully coordinated field logistics and conducted several aspects of data collection (trapping and collaring bears, tracking human-related bear mortalities, assessing summer/fall forage availability, implementing DNA hair-snare surveys, and monitoring garbage-related bear-human conflicts). We will continue these field activities through 2015, and begin data analyses as field data are completed. In addressing the objectives of this project we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and population trends, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. 128 �LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. Plos One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. 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Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8:169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83:340-354. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 130 �Table 1. Capture information for black bears that have been marked in the vicinity of Durango, CO since May 2012 (collared adult females are identified with an “*”). Only information from the initial capture of each individual is shown (no recaptures). Bear ID B120 B121* B122* B123 B124* B125* B126 B127* B128* B129* B130 B131 B132 B133* B134* B135 B136 B137 B138 B139 B140 B141* B142 B143* B144* B145* B146 B147 B148 B149 B150 B151 B152* B153 B154 B155 B156 B157 B158 Capture Date 5/27/2012 5/29/2012 5/30/2012 6/5/2012 6/6/2012 6/8/2012 6/8/2012 6/10/2012 6/11/2012 6/14/2012 6/22/2012 6/23/2012 6/28/2012 6/29/2012 6/30/2012 6/30/2012 7/1/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/6/2012 7/6/2012 7/7/2012 7/7/2012 7/7/2012 7/10/2012 7/11/2012 7/15/2012 7/16/2012 7/26/2012 7/17/2012 7/17/2012 7/17/2012 7/19/2012 7/19/2012 7/19/2012 7/20/2012 UTM Easting 254732 251670 249059 240102 249158 244618 251670 239005 239005 254576 250152 765047 765047 765932 765932 252014 765047 249059 254997 238245 763921 765132 254997 241210 238245 763921 254739 241334 255983 244618 241334 243888 241210 249059 253439 241334 252621 248417 252546 UTM Northing 4133249 4132767 4132998 4128939 4127065 4132132 4132767 4134459 4134159 4135043 4127691 4131635 4131635 4127651 4127651 4133509 4131635 4132998 4135825 4131204 4132873 4132506 4135825 4137115 4131204 4132873 4133234 4138018 4135921 4132132 4138018 4129546 4137114 4132998 4134693 4138018 4130532 4144294 4134789 131 Sex F F F M F F F F F F M M M F F M F M F M M F M F F F M M M M M M F M M F F M M Age 1 4 5 2 7 8 1 10 8 6 1 6 1 3 8 1 2 2 2 1 3 3 3 3 9 6 5 1 3 1 2 3 8 2 3 2 1 6 3 Kg 20.9 76.2 66.2 48.1 80.7 98.9 15.9 58.1 56.2 54.4 12.7 111.6 20.4 49.0 90.7 20.9 46.3 26.8 30.8 30.4 67.1 55.3 37.2 45.4 72.6 70.3 110.2 43.5 73.9 45.4 53.5 60.3 99.8 49.9 63.5 30.8 26.3 136.1 50.8 �B159 B160 B161* B162 B163 B164 B165* B166 B167* B168 B169 B170 B171 B172 B173* B174* B175* B176 B177 B178 B179 B180* B181* B182 B190 B191 B192 B193 B194 B195 B196 B197 B198* B199 B200 B201 B202 B203 B204 B205* B206 B207 B212 B213* B214 7/21/2012 7/24/2012 7/25/2012 7/25/2012 7/26/2012 7/28/2012 7/29/2012 7/29/2012 7/31/2012 7/31/2012 7/31/2012 8/1/2012 8/2/2012 8/2/2012 8/3/2012 8/3/2012 8/3/2012 8/3/2012 8/4/2012 8/4/2012 8/5/2012 8/5/2012 8/5/2012 8/8/2012 8/9/2012 8/11/2012 8/11/2012 8/12/2012 8/12/2012 8/13/2012 8/14/2012 8/16/2012 8/16/2012 8/17/2012 8/17/2012 8/18/2012 8/19/2012 8/21/2012 8/21/2012 8/22/2012 8/22/2012 8/23/2012 8/24/2012 8/24/2012 8/24/2012 242236 249059 242546 249059 243954 242611 251815 252621 248578 253439 249059 249059 248192 248578 248578 253341 254916 252621 248578 249059 248578 248939 247127 259049 245293 249059 245293 243652 243218 259049 249059 242772 247295 244208 245293 244600 249059 244174 243652 243652 247295 249059 243274 244174 249059 4127920 4132998 4134789 4132998 4134875 4133863 4133706 4130532 4139143 4134693 4132998 4132998 4137051 4139143 4139143 4128740 4128609 4130532 4139143 4132988 4139143 4141533 4138557 4132998 4128959 4132998 4128959 4129360 4128712 4132998 4132998 4129388 4132138 4129996 4128959 4132218 4132998 4130027 4129360 4129360 4132138 4132998 4129124 4130027 4132998 132 F M F M F M F M F M F M M F F F F M M M M F F M M M M M M M F M F M M M M M M F M M M F M 2 2 5 10 1 6 12 8 18 4 2 4 2 2 5 3 10 2 7 2 1 3 3 2 12 4 9 5 5 6 2 1 10 5 5 5 3 1 3 4 2 3 2 6 2 39.9 64.0 76.2 108.0 37.6 117.0 85.3 121.6 58.1 87.5 44.5 119.3 26.8 28.1 73.9 43.5 76.2 54.4 93.9 35.4 35.4 71.7 58.1 70.8 153.3 60.3 148.8 87.5 137.0 151.0 42.2 34.0 75.3 140.6 91.6 99.8 47.6 24.5 71.7 49.9 46.3 59.0 45.4 61.2 63.5 �B215 B216 B244 B245* B246 B259 B247 B248 B249 B250 B251 B252 B253 B254 B255 B256 B257 B258 B294 B295 B260 B261* B262 B263 B265 B266 B267 B268 B269 B274 B275 B276 B277 B278 B280 B281* B282 B283 B284 B285* B287 B289 B290 B291* B292 8/24/2012 8/28/2012 1/25/2013 2/14/2013 2/14/2013 6/3/2013 3/10/2013 3/11/2013 3/11/2013 3/14/2013 3/15/2013 3/15/2013 3/16/2013 3/16/2013 3/19/2013 3/19/2013 3/27/2013 3/27/2013 4/19/2013 4/19/2013 6/4/2013 6/7/2013 6/10/2013 6/11/2013 6/14/2013 6/17/2013 6/19/2013 6/21/2013 6/21/2013 6/26/2013 6/27/2013 6/29/2013 6/30/2013 7/1/2013 7/8/2013 7/11/2013 7/16/2013 7/16/2013 7/19/2013 7/19/2013 7/23/2013 7/25/2013 8/1/2013 8/2/2013 8/4/2013 247295 249059 240578 243288 243288 251514 243920 247275 247275 245069 255660 255660 240747 240747 255951 255951 240819 240819 268453 268453 253231 253231 251343 254584 251343 251933 249872 251817 249153 256824 256937 237708 238206 256763 240340 255385 244631 242022 247443 254750 248532 764348 246591 237566 246591 4132138 4132998 4137131 4123754 4123754 4137313 4135766 4126961 4126961 4137542 4131489 4131489 4132514 4132514 4141487 4141487 4154867 4154867 4207298 4207298 4138879 4138879 4134446 4134994 4134446 4137246 4130099 4131555 4132855 4134340 4134617 4130726 4130573 4134317 4131577 4133334 4132166 4127361 4137388 4133273 4139266 4132592 4135689 4124276 4135689 133 M M F F F M M M M F M M F F M M M F F M M F M M F M F F M M F F M M F F M M F F M M M F M 5 3 1 15 1 1 Cub Cub Cub Cub Cub Cub Cub Cub Cub Cub Cub Cub Cub Cub 6 8 1 6 1 8 2 2 4 6 2 2 10 3 1 13 3 2 0 8 3 3 4 4 3 127.0 59.9 15.0 83.0 26.3 32.7 2.4 2.6 4.3 2.4 1.9 2.2 2.0 2.0 1.5 1.4 2.7 2.7 2.4 2.4 102.1 78.0 30.8 83.9 38.6 125.6 30.8 31.3 54.4 116.6 34.9 57.2 181.4 79.8 25.9 63.5 73.0 33.6 10.4 66.2 75.3 88.5 93.4 64.4 56.7 �B293* B296 B297 B298* B299* B300 B301 B302 B303* B304 8/6/2013 8/10/2013 8/10/2013 8/14/2013 8/16/2013 8/17/2013 8/20/2013 8/23/2013 8/23/2013 8/23/2013 245913 245913 246383 245848 245848 243934 243934 248263 240787 243934 4139623 4139623 4142011 4141980 4141980 4134857 4134793 4136448 4130376 4134857 134 F M M F F M F M F M 3 2 4 5 3 10 1 8 7 1 49.4 45.8 99.3 51.7 61.7 122.0 33.1 133.8 93.0 42.2 �Figure 1. Locations of the 2013 hair snare sites (red dots) for the Durango and Wildland genetic sampling grids. -- 0 1.5 3 N 6 9 + .• ~ ! 135 �Figure 2. Location of garbage-related conflicts observed during morning patrols and garbage containers (by type) available to bears during summer 2012. Treatment and control areas for the bear-proofing experiment (implemented in summer 2013) are also shown. Garbage Conflicts and Availability 2012 Summary * 2012 Conflicts ., 2012 Garbage Availabiity o Regular can • Wildlrte-Resistant Can Experimental Zone 8 0 Treatment Cootrol 0. 125 0.25 0.5 Mi5es s OOpens:reetMap(.nl) comJ10UICG. cc-ev.-s,,.. 136 �Figure 3. Number of black bear captures by week from May 15th through September 15th for bear captures during the 2011 through 2013 summer trapping seasons (2013 is currently ongoing). Number of Bear Captures 25 2011 2012 2013 20 15 10 5 0 1 3 5 7 9 11 13 Week (May 15th through Sept 15th) 137 15 17 �Figure 4. GPS collar locations from 44 adult female black bears from April 2012 through December 2012 in the vicinity of Durango, CO (different colored clusters of points represent different individual bears): A) an overview of all locations and B) locations around the town of Durango. B A ·•• : ~ ~-. i ;,, ·. ·...... ·--~~1,:.· :,,a u1 1M rn + -- 0 10 • \ ui. ln~ 1;2 n N 20 R•-rvahon ,. 2588m 2:,o5m ,. 2.Je'- .A'. - ~ .... ,,J" Du lce ~· 2 ~~ ~ ·· A >l ec 5 40 -, 60 g1 80 Ki lometers ... ' ·-,. . ·-· 14.lO .••"':•,... -- 0 J a:;; aolla Ap.,h• lrn::l ,;2 r, Hl111Gt1Lakt. 2.5 138 5 Sot.1 th •r n Lit• lnd111-n ~;.,, rv iu>o n �Colorado Division of Parks and Wildlife July 2013 – June 2014 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 3 Federal Aid Project No. W-204-R1 : : : : : Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2013 – June 30, 2014 H.E. Johnson, S.A. Lischka, J. Broderick, J. Apker, S. Breck, J. Beckmann, K. Wilson, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 4 entities: Colorado Parks and Wildlife (CPW), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we have primarily focused on collecting field data in the vicinity of Durango, Colorado. Specifically, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, collected GPS collar location data on bears along the urban-wildland interface, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys, deployed ~150 bear-resistant containers for an experiment on the effectiveness of urban-bear-proofing, obtained data on garbagerelated bear-human conflicts, monitored resident use of project-supplied bear-resistant garbage containers, and conducted a survey assessing resident attributes about bears and bear-human interactions. Additionally, we conducted an initial analysis of bear selection of human development. Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 1 �PROJECT OBJECTIVES FY13-14 1. Work with personnel from CPW Area 15, CPW Southwest Region, City of Durango, La Plata County, US Forest Service (Columbine and Pagosa Ranger Districts), Bureau of Land Management (BLM; Tres Rio Field Office), Southern Ute Tribe, and private landowners on field research logistics. 2. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear behavior and demography. 3. Track bear locations and survival via global position system (GPS) collar locations. 4. Monitor bear fecundity and cub survival through winter den investigations of collared adult female bears. 5. Obtain data on summer/fall natural food availability for bears based on the abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 6. Track human-related bear mortalities and removals around Durango from lethal conflict managment, vehicle collisions, harvest, and translocations. 7. Perform non-invasive genetic mark-recapture surveys to estimate bear density and population size around Durango (urban site) and in the Piedra watershed (wildland site). 8. Deploy ~150 bear-resistant garbage containers to “clean up” treatment areas for an experiment on the effectiveness of wide-scale urban bear-proofing for reducing bear-human conflicts. 9. Collect data on the frequency of bears accessing garbage in treatment and control areas of the bear-proofing experiment. 10. Estimate appropriate use of project-supplied bear-resistant garbage containers by residents in treatment areas. 11. Assess attitudes about bears and bear-human interactions among residents of Durango and La Plata county. INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human conflicts can result in public safety concerns, property damage, bear mortality (i.e., euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman conflicts (i.e., education, aversive conditioning of bears, and increased harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceedingly difficult to estimate (Garshelis and Hristienko 2006). Without a thorough understanding of the relationship between conflict rates and bear behavior and population dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. 2 �While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, fruit trees, livestock, birdfeeders, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of additional resources. Bear-use of human food not only increases interactions between bears and people but has been found to alter bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly influence both bear behavior and demography. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures for bears in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for modifying bear-habitat relationships, they also have critical implications for increasing rates of bearhuman conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we initiated a project in FY10-11 to 1) determine the influence of urban environments on bear behavior and demography, 2) test a management strategy for reducing bear-human conflicts, 3) examine public attitudes and behaviors related to bear-human interactions, and 4) develop population and habitat models to support the sustainable monitoring and management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY13-14, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, collected GPS collar data on bear locations, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys, deployed ~150 bear-resistant containers for an experiment on the effectiveness of urban-bear-proofing, obtained data on garbage-related bear-human conflicts, monitored resident use of project-supplied bear-resistant garbage containers, and conducted a survey assessing resident attributes about bears and bear-human interactions. Additionally, we performed an initial analysis of bear selection of human development using GPS collar data. Our efforts focused largely on collecting field data to meet research objectives 1-3, information which will eventually be used to address objective 4. We report general summary information from field activities over the past year; detailed analyses of field data will occur in future years. STUDY AREA To meet study objectives, a combination of site-specific field data and statewide data will be required. Site-specific field data is being collected in the vicinity of Durango, and is the focus of this progress report. The town of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience 3 �monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon pine, juniper, aspen, mountain shrubs, and agriculture. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), wild crabapple (Peraphyllum ramosissimum) and pinyon pine (Pinus edulis). Durango is predominately surrounded by public land managed by the San Juan National Forest, BLM, CPW, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts (Baruch-Mordo et al. 2008, CPW unpublished data). METHODS Objective 1: Determining the influence of urban environments on bear behavior and demography To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear behavior and demography, we are collecting a suite of data types including locations from collared bears on the urban-wildland interface, survival and reproductive rates of those bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitats using mark-recapture methods. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011). Collaring and Marking Bears – To assess bear behavior and demographic rates with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates that drive population growth. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, vital rates that are often associated with variation in bear population trends (Mitchell et al. 2009, Beston 2011). We have targeted summer trapping efforts within ~10 km of Durango to collar a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urban-wildland interface. Bears are trapped with box traps, which are baited with fish, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar (manufactured by Vectronics), and a tooth (first pre-molar) is pulled for age verification. GPS collars record bear locations every hour, and upload a real-time location to a central database via a satellite system every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair. Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wildland Interface – To examine movement and habitat-use patterns of bears along the urban-wildland interface, we are using GPS location data from collared females. Hourly GPS data are downloaded from the collars in the field on a biannual basis (fall and winter). Locations are being used to assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear movement and resource selection patterns (Manly et al. 2002, McLoughlin et al. 2010, Morales et al. 2010). For spatial covariate data, we have generated rasters representing elevation, aspect, slope and terrain ruggedness using digital elevation models. We also created rasters depicting distances to drainages and perennial water using the National Hydrology Dataset, 4 �and have estimated the proportion of different vegetation types using the USFS LandFire dataset (http://www.landfire.gov/vegetation.php). We derived rasters depicting human structure and road densities using data from La Plata county and CPW. Weather information will be acquired from local weather stations and PRISM datasets (www.prism.oregonstate.edu/). While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of berry and nut resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural forage for bears around Durango, we conducted bimonthly mast surveys. Surveys were performed from late July through mid-September, when berries and nuts should reach peak maturation and bears are experiencing hyperphagia prior to hibernation. Key mast species for bears around Durango are gambel oak, chokecherry, serviceberry, hawthorne, wild crabapple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 16 transects on public lands to evaluate bear mast availability. Each transect was 1 km in length and was situated along an existing trail or stream drainage. For each transect, field technicians recorded the phenological stage and the percentage of plants of each species that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, 25 – 50% of plants with mast, etc). During FY13-14 we conducted an initial analysis of bear selection for human development around Durango, examining temporal patterns of selection both within and across years. We used GPS collar data collected in 2011, a good natural food year for bears, and in 2012, a poor natural food year. We used mixed-effects resource selection models (RSFs) following a use-availability design (Manly et al. 2002), using random intercepts account for differences in sample sizes among individuals and autocorrelation within animal datasets (Gillies et al. 2006). “Used” locations were evaluated on an animal-year-specific basis, collected from May – Oct and “available” locations were randomly generated from animal-specific 95% minimum convex polygons. We used 80% of the animal-year datasets for developing models and withheld 20% for model validation. We first ran a “base” model that accounted for topography, vegetation, and distance-to-drainage, which are covariates consistently associated with black bear habitat (Clevenger et al. 2002; Carter et al. 2010; Sadeghpour and Ginnett 2011). We then compared the base model to a series of models that included density of human development (HD), based on point data of human structures in La Plata county. We evaluated the following models: base + HD, base + HD * Food Year (temporal variation in selection for HD between years), base + HD * Week (temporal variation in selection for HD within the active bear year) and base + HD * Food Year * Week (both across and within year variation in selection for development; models included all relevant main effects and interactions). We fit models using maximum likelihood estimation and used minimum AIC scores to assess the relative support for models with different fixed effects (Burnham and Anderson 2002). We assessed the predictive power of our top model with cross-validation using hold-out data (Boyce et al. 2002). Estimating Demographic Rates – To assess the influence of human development on bear demographic rates we have been collecting the following data types: 1) survival and reproduction of collared adult female bears, 2) cub survival monitored during annual winter den checks of collared females, 3) mortalities and removals of marked and unmarked bears in the vicinity of Durango, and 4) non-invasive genetic surveys that estimate density and abundance of bears around urban and wildland sites. Collared female bears allow us to estimate annual adult female survival, fecundity (number of cubs born/adult female) and cub survival (survival from newborn cub to yearling); parameters we have monitored since summer 2011 and which we will continue to monitor through winter 2017. We use realtime GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations are stationary during multiple fixes. Fecundity and cub survival are monitored from 5 �winter den checks of collared females. Numbers of newborn cubs provide information on fecundity, while consecutive annual den checks of collared females allow us to estimate cub survival. Because yearlings hibernate with their mothers, we can observe the number of cubs alive in the den in year t that survived their first year of life to t+1. Adult female survival, fecundity and cub survival will be used in matrix projection models to assess population performance (Caswell 2001), particularly in relation to use of human development. In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked (i.e., males, subadults) and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on human-related bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and hunter harvest. For all bears removed from the study area we collect a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery data to estimate adult male and subadult survival, while also gaining valuable information on cause-specific bear mortality within the study system. To better understand the influence of urban environments on bear density and abundance, we are employing non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between the bear population around Durango and for a nearby “wildland” area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size. We constructed and monitored 1 snare site within each cell. Snares consisted of a scented bait hanging high in a tree, surrounded by barbed wire around a cluster of trees encircling the bait (wire was strung 50 cm above ground). When bears climb over or under the wire to investigate the bait, they leave a hair sample on the barbed wire. During summers 2011 through 2014, we deployed snares during the first 2 weeks of June, and conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with a scent (anise, berry, fish, maple or bacon), and collected hair samples from all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. In summer 2013, we constructed and monitored 34 snares in the Durango grid and 35 snares in the wildland grid. All hair samples were sent to the laboratory at Wildlife Genetics International (Nelson, British Columbia, Canada) for genotyping; genetic results were returned in July 2014. In summer 2014, we conducted the final year of hair-snare data collection. We constructed and monitored 35 snare sites in the Durango grid and 34 sites in the wildland grid (Figure 1). Samples collected in 2014 will be sent to the laboratory this fall and results are expected in summer 2015. Once genotypes are returned, we will use spatially-explicit mark recapture statistics (Efford et al. 2009, Gardner et al. 2010) to estimate abundance and density for the urban and wildland grids in each year of the study. Objective 2: Testing a management strategy to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that resource (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of “cleaning up” a town. Given the high price to operationally “bearproof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project, we are implementing the first experimental test of wide-scale urban bearproofing for reducing bear-human conflicts. As part of the experiment we have designated 2 residential ‘treatment’ areas and 2 paired ‘control’ areas, consisting of a total of ~2,000 homes (Figure 2). In spring and early summer 2013 we deployed ~900 bear-resistant garbage containers within the treatment areas 6 �(approximately 100 homes already had these containers) with the goal that regular receptacles were exchanged with bear-resistant containers for all residents. In spring and early summer 2014 we deployed an additional ~150 containers to “clean-up” treatment areas, ensuring that all residences had a bearresistant container. This second deployment was necessary due to errors in the City of Durango database and logistical challenges with the initial container deployment. In July 2013 and 2014 we also canvassed homes within treatment areas, reminding residents to lock their bear-resistant garbage containers and asking that they bear-proof their properties (remove bird feeders, outdoor pet food, and other bear attractants); no canvassing occurred in control areas. Additionally, we increased enforcement of wildlife ordinances within treatment areas, providing official warnings at residences with bear-strewn trash and notifying City Code Enforcement. To track the effectiveness of these efforts in reducing bear-human conflicts we are collecting preand post-treatment data. For 2 years pre-treatment, summers 2011 and 2012, field technicians patrolled streets within proposed treatment and control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from 5:30 – 7:30 am and recorded locations of bear-strewn trash. Monitoring occurred from July through September, months that experience the highest numbers of bear-human conflicts in Durango (CPW unpublished data). During summers 2013 and 2014 project personnel have been collecting post-treatment data (currently ongoing); post-treatment data will be collected for a minimum of 3 years. Each summer, in addition to collecting information on bears accessing human foods, we have quantified the “availability” of garbage to bears, by documenting the location and container type (bearresistant or regular) of every garbage receptacle in the survey area accessible to bears the night prior to garbage pick-up. These data provide an index of the garbage available to bears in town and allow us to track changes in the number of bear-resistant containers in the study area over the course of the experiment. Once the experiment is complete, we will use data from pre- and post-treatment years, and from treatment and control areas, to quantify the effectiveness of residential bear-proofing. Additionally, we will use information from conflict reports to the CPW Area 15 Office to examine differences in conflict rates between treatment and control areas during post-treatment years. Objective 3: Identifying public attitudes and behaviors related to bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have stimulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011). Thus, we have initiated efforts to better understand human attitudes related to bears and bear-human interactions, and human behaviors related to the appropriate use of bear-resistant garbage containers. To assess data on human attitudes we are using public mail surveys to 1) quantify perceptions about bears, bear management, and bear-human interactions, and 2) explore motivations for compliance and non-compliance with wildlife ordinances designed to reduce bear-human conflicts. To meet these objectives, we developed a three-part mail survey, conducted in conjunction with our urban bear-proofing experiment. Residents are being surveyed pre- (2012), during (2014), and post-implementation (2016) of the experiment, in treatment and control areas, as well as across a larger portion of the community. Surveys are mailed to all residents within Durango city limits, and a subset of La Plata county residents within the study area. Survey responses will allow us to quantify current attitudes and perceptions about bear-human interactions, and how those perceptions change over time in association with a management effort such as wide-scale urban bear-proofing. Survey data will also identify the number of residents that 7 �have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. The first (pre-treatment) public survey was conducted during winter 2012 (see Johnson et al. 2012 for details) and the second survey was conducted during winter 2014, following the first year of the bear-proofing experiment. In addition to collecting data on human attitudes and perceptions, we are also collecting data on human behavior through direct observations. Using a random, stratified sampling design we monitored human compliance with wildlife ordinances at residences in treatment and control areas. Durango city ordinances specify that garbage can only be accessible after 6:00 am on the morning of pick-up; therefore, we define compliance as having garbage adequately secured so that bears cannot access it, either through appropriate use of a bear-resistant garbage container (e.g. latching both latches and having all garbage completely inside the can) or by keeping garbage enclosed in a garage or shed until the morning of trash pick-up. Non-compliance is defined as allowing garbage to be accessible to bears by not using a bearresistant can appropriately (leaving it unlatched) or putting a regular garbage container at the curb the night before garbage pickup. To assess compliance, houses were surveyed on the morning of pick-up (between 5:00 and 6:00 am) between July and September 2013. In each treatment and control area, a sample of 40 randomly selected blocks were monitored (total of 160 blocks) such that the number and type of cans (regular or bear-resistant) and compliance status were recorded. Each block was surveyed twice, once during midsummer and again during late summer. In the north experimental area, compliance was recorded for each parcel, but in the south experimental area, compliance was recorded per block because garbage containers are stored along alleys and cannot be easily tracked to parcel. This protocol was developed, field tested and modified during summer 2013 and data collected this year should be considered pilot. Data collections methods were further modified in summer 2014. Compliance data will be analyzed in conjunction with mail survey data, spatial covariates, and conflict activity to better understand how factors such as management actions and rates of bear-human interactions influence human behavior. A predictive model of compliance behavior will be developed to determine how CPW may tailor education and communication efforts to be most effective at achieving public compliance with wildlife ordinances. RESULTS AND DISCUSSION Objective 1: Determining the influence of urban environments on bear behavior and demography Between 6 June 2013 and 25 March 2014 (the 2013-2014 capture year), an additional 75 unique bears were marked during 206 bear captures. To date on the project there have been 280 different individuals marked during 601 captures. Information about these captures is described below for summer 2013 and winter 2014. During summer 2013 we conducted 129 total bear captures; 42 captures were newly marked unique individuals and 87 were recaptures. Of the unique individuals captured, there were 18 females and 24 males (Table 1). We placed collars on 9 new adult females. With those bears that had been previously collared in 2011 and 2012, this resulted in 39 collars deployed by mid-September, the end of the summer capture season. The mean estimated age of bears ≥1 year-old on their initial capture date was 5.5 (5.7 for females and 5.4 for males), and mean weight was 81.7 kg (57.6 kg for females and 96.6 kg for males). In total, we placed traps at 94 different locations and conducted 1,403 trap nights. Capture success was fairly consistent throughout the summer with peaks in late June and late August (Figure 3). Trapping success was less than in 2012, when limited natural foods likely brought additional bears into the urban-wildland interface around Durango. Between January and March 2014, we visited the winter dens of 35 collared females. Although we had 39 adult female bears collared at the end of summer 2013 there were 4 mortalities in fall: 2 females were legally harvested (B25 and B143), 1 was lethally removed by a landowner (B21), and 1 died 8 �of unknown causes (B167). Of the 35 adult females that we processed, 13 did not have any cubs or yearlings, 9 had yearlings (13 yearlings in total), and 13 had newborn cubs (27 cubs in total, but one was dead in the den; 14 females and 13 males). Of those females with newborn cubs, 1 bear had only 1 cub, 10 bears had twins, and 2 bears had triplets. We PIT and ear-tagged yearlings in the den, recorded information on weight, body size, body condition, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. We found that reproductive success, measured as the number of live cubs/adult female was 0.74 (SE = 0.18) for winter 2014, compared to 0.95 (SE = 0.24) in 2012 and 0.52 (SE = 0.16) in 2013. Cub survival for 2014 (survival from newborn to 1 year) was 50% (based on 12 cubs), compared to 40% in 2013. To date, we have obtained >318,000 locations from GPS collars on 67 different adult female bears; 42 different bears provided location data during the summer of 2013 (Figure 4). While most locations were in close proximity to Durango, a few animals ventured outside the primary study area, including a sow that moved to New Mexico (Figure 4). In our initial analyses of bear habitat-use patterns we found that female bears around Durango generally selected for lower elevations, steeper slopes, northern aspects (avoiding southern and western aspects), and alpine, aspen, oak, and riparian vegetation. Bears avoided mixed conifer, meadow/grassland, pinyon-juniper, and shrub vegetation. In testing a series of models describing bear selection for HD, we found that bears selected positively for development, and that the best model included both between- and within-year temporal variation in selection for development (second best model had ∆AIC score = 1911). Bears exhibited greater selection for HD during the poor natural food year (Figure 5, Figure 6). When limited natural food was available, bear selection for HD increased throughout the active season (May-Oct), while in good years, selection for HD decreased throughout the active season (Figure 5). Individual bears also displayed a bimodal pattern, either selecting for very high or very low HD (Figure 5), although selection was predominately for high HD. Our top model had high predictive power when tested against hold-out data. With 10 equal-area bins of predicted resource use, Spearman rank correlations of selection probabilities between training and testing data were 0.99 (p < 0.001). The availability of natural mast foods was generally good in late summer and fall 2013. Mast surveys revealed that the peak time for serviceberry and wild crabapple maturation was early August, for chokecherry and hawthorne was mid-August, for gambel oak was the end of August, and for pinyon pine was early September. On transects that had those species, mast was present for about 10-15% of serviceberry plants, about 25% of pinyon pines and wild crabapples, and for about 50% of hawthorns and chokecherries. Presence of acorns on gambel oaks was highly variable on different transects, ranging from complete failure on some transects to 75% of the plants with acorns on other transects. This was the first year that all mast foods were observed in the study area during the survey period. Between 1 April and 1 December 2013 (the active bear season of 2013), a total of 37 bears were removed from the vicinity of Durango. Of those bears, 15 were killed in vehicle collisions, 14 were legally harvested, 5 were lethally removed due to nuisance behavior (breaking into houses, killing livestock, etc), 2 died from unknown causes, and 1 died when trapped for research purposes. Of those mortalities and removals there were 8 adult females, 3 adult males, 2 subadult females, 5 subadult males, 7 female cubs, and 12 male cubs. Twenty-four bears were unmarked and 13 were marked for the research project. Additionally, 7 marked bears died outside the study area; 4 were legally harvested, 2 died from lethal conflict management (including a bear that died in New Mexico) and 1 was killed in a vehicle collision. In summer 2013, we collected 1,365 hair samples from the Durango and wildland grids; 680 samples from Durango and 685 samples from the wildland site. Over the 6 sampling occasions from 34 snares around Durango we collected 106, 151, 131, 62, 106, and 124 samples, respectively. Over the 6 sampling occasions from 35 sites in the wildland grid we collected 112, 83, 141, 100, 126, and 123 samples, respectively. The number of samples/snare ranged from 0 to 121 in the Durango grid and from 1 9 �to 78 in the wildland grid. We received the genetic results back from Wildlife Genetics International in July 2014. Of the 1,365 hair samples submitted to the laboratory, good genotypes were obtained for 693 samples (51%). Of those samples that did not produce a valid genotype, 389 (28%) did not contain enough genetic material, 273 (20%) failed during analyses for other reasons, and 12 (0.9%) samples were not black bear. Across the 693 valid samples there were 334 genotypes generated from the Durango grid and 359 generated from the wildland grid. In the Durango grid, 86 different individuals were detected during 160 “captures” (multiple hair samples from a single bear during 1 sampling occasion were considered 1 “capture”). Of those individuals, 50 were only detected in 1 sampling occasion and 36 were detected in >1 occasion (recaptures). The probability of detecting a bear within any single sampling occasion was 0.24, and across all sampling occasions was 0.80. In the wildland grid, 110 different individuals were detected during 183 “captures.” Of those individuals, 67 were only detected in 1 sampling occasion and 43 were detected in >1 occasion (recaptures). The probability of detecting a bear within any single sampling occasion was 0.18, and across all sampling occasions was 0.69. Detailed mark-recapture analyses of these data will be conducted in the future to estimate annual density and abundance at each site. Objective 2: Testing management strategies to reduce bear-human conflicts During summer 2013 (July through mid-August) we collected our first year of post-treatment data on the bear-proofing experiment. Within proposed treatment and control areas we observed 330 instances of bears accessing residential garbage during our morning patrols; observations peaked in early September. Of those garbage containers accessed by bears, 84% were regular containers and 16% were bear-resistant containers. Bears accessed human food from bear-resistant containers when they were not properly latched. In quantifying the number of garbage containers out the night before garbage pick-up, we recorded information on 1,678 garbage cans in experimental areas. Within the northern treatment area 89% of the containers were bear-resistant and 11% were regular, and in the southern treatment area 73% of containers were bear-resistant and 27% were regular. In the northern control area 28% of containers were bear-resistant and 72% were regular, and in the southern control area 9% of containers were bearresistant and 91% were regular. Given that we wanted >95% of residents to have a bear-resistant container in the treatment areas, we worked on “cleaning up” the bear-proofing experiment treatment areas this past year. Our intention was to outfit every resident with a bear-resistant container in 2013, but about 150 regular containers were not exchanged due primarily to errors in the city waste management database and oversights by city personnel during deployment. During fall 2013 funds were secured to purchase additional containers through the USDA National Wildlife Research Center and the City of Durango. Containers were purchased from Solid Waste Systems (Parker, CO), a company that manufactures bear-resistant containers certified by the Living with Wildlife Foundation. Containers were distributed to the reminder of residences by City of Durango and CPW staff in spring and early summer 2014. The second year of post-treatment monitoring began in July 2014. Data collection is currently ongoing, but as of August 22nd we had recorded 146 incidences of bears accessing residential garbage; 38 conflicts in treatment areas and 108 conflicts in control areas. In quantifying the number and type of containers in experimental areas (n = 1,483) early the morning of pick-up, we found that our clean-up efforts were a success. Within the northern treatment area 98% of containers were bear-resistant and 2% were regular, and in the southern treatment area 95% were bear-resistant and 5% were regular. Within the northern control area 37% of containers were bear-resistant and 63% were regular, and in the southern control area 11% were bear-resistant and 89% were regular. We will continue working with the City of Durango to replace regular containers with bear-resistant ones in treatment areas. 10 �Objective 3: Identifying public attitudes and behaviors related to bear-human encounters Between January and April 2014, we administered the second mail survey of resident attitudes about bears. Surveys were sent to all residents within Durango city limits and a random sample of 1,500 residents outside city limits but within our study area in La Plata County. A total of 5,853 residents were sent mailings, including a pre-notification letter asking them to complete the survey online, 3 printed copies of the survey, 2 reminder postcards and 1 non-respondent survey. As individuals responded to the survey, they were removed from the mailing list and received no subsequent mailings. We removed a total of 698 bad addresses from the original mailing list, for an adjusted sample of 5,155 residences. We received 2,310 responses (782 online, 1,528 paper) to the survey, for an adjusted response rate of 45%. Non-response bias is currently being assessed. Detailed analysis of tolerance for black bears, compliance behaviors and perceived risk of bear-human conflicts will be conducted in future years. During the 2013 mid-summer compliance survey we found that compliance in the north treatment area was 51%, in the south treatment area was 27%, in the north control area was 12%, and in the south control area was 2%. During the late summer survey, we found that compliance was 39% in the north treatment area, 31% in the south treatment area, 14% in the north control area, and 4% in the south control area. We expected that compliance would increase over the course of the summer as conflicts increased. This pattern appeared evident in all areas except the north treatment area, which demonstrated a notable decrease in compliance (51% to 39%). Because observations sometimes occurred after 6:00 am, residents may have unlatched cans to allow for garbage collection, causing our compliance estimates to be biased low. To account for this, compliance surveys were modified in 2014 to be completed before 6:00 am. Additionally, in 2013, we did not determine if unlatched cans actually contained garbage, therefore making them truly non-compliant, as defined by the city ordinance. As a result, we have updated field data collections methods for 2014 to inspect a sub-sample of compliance sampling blocks to determine the proportion of empty, unlatched cans in our sample. This information will be used to correct bias for data on non-compliance in the future. SUMMARY AND FUTURE PLANS During FY13-14 we successfully coordinated field logistics and conducted several aspects of data collection (trapping and collaring bears, tracking human-related bear mortalities, assessing summer/fall mast availability, implementing DNA hair-snare surveys, monitoring garbage-related bear-human conflicts, assessing resident use of project-supplied bear-resistant containers, etc). Data collection will continue on most aspects of the study through winter 2017, with the collection of some data types concluding earlier (i.e., DNA hair-snare surveys and compliance data will be completed after summer 2014). We have initiated data analysis on bear resource selection of human development, and will continue to analyze data on various aspects of the project in the coming years. In addressing our research objectives we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and demography, understand the effect of bear-human interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. Plos One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. 11 �Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. Roaring Fork Valley urban black bear ecology study: progress report to the Colorado Division of Wildlife. Contact Sharon Baruch-Mordo for copy. Email: sharonb_m@yahoo.com Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication No. 39, Colorado Division of Wildlife, Colorado. Beckmann, J.P., and J. Berger. 2003a. Using black bears to test ideal-free distribution models experimentally. Journal of Mammalogy 84:594-606. Beckmann, J.P., and J. Berger. 2003b. Rapid ecological and behavioural changes in carnivores: the response of black bears (Ursus americanus) to altered food. Journal of Zoology 261:207-212. Beckmann, J.P., L. Karasin, C. Costello, S. Matthews, and Zoë Smith. 2008. Coexisting with black bears: perspectives from four case studies across North America. Wildlife Conservation Society Working Paper No 33. Beckmann, J.P., C.W. Lackey, and J. Berger. 2004. Evaluation of deterrent techniques and dogs to alter behavior of “nuisance” black bears. Wildlife Society Bulletin 32: 1141-1146. Beston, J.A. 2011. Variation in life history and demography of the American black bear. Journal of Wildlife Management 75:1588-1596. Boyce, M.S., P.R. Vernier, S.E. Nielsen, and F.K.A. Schmiegelow. 2002. Evaluating resource selection functions. Ecological Modelling 157:281-300. Burnham, K.P., and D.R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition, Springer, New York, New York. Carter, N.H., D.G. Brown, D.R. Etter, and L.G. Visser. 2010. American black bear habitat selection in northern Lower Peninsula, Michigan, USA, using discrete-choice modeling. Ursus 21:57-71. Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation. Second Edition, Sinauer Associates, Sunderland, Massachussetts. Clevenger, A.P., J. Wierzchowski, B. Chruszcz, and K. Gunson. 2002. GIS-generated, expert-based models for identifying wildlife habitat linkages and planning mitigation passages. Conservation Biology 16:503-514. Efford, M.G., D.K. Dawson, and D.L. Borchers. 2009. Population density estimated from locations of individuals on a passive dector array. Ecology 90:2676-2682. Garshelis, D.L., and H. Hristienko. 2006. State and provincial estimates of American black bear numbers versus agency assessments of population trend. Ursus 17:1-7. Gardner, B., J.A. Royle, M.T. Wegan, R.E. Rainbolt, P.D. Curtis. 2010. Estimating black bear density using DNA data from hair snares. Journal of Wildlife Management 74:318-325. Gillies, C.S., M. Hebblewhite, S.E. Nielsen, M.A. Krawchuk, C.L. Aldridge, J.L. Frair, D.J. Saher, C.E. Stevens, and C.L. Jerde. 2006. Application of random effects to the study of resource selection by animals. Journal of Animal Ecology 75:887-898. Gore, M.L., W.F. Siemer, J.E. Shanahan, D. Schuefele, and D.J. Decker. 2005. Effects on risk perception of media coverage of a black bear-related human fatality. Wildlife Society Bulletin 33:507-516. Gore, M.L., B.A. Knuth, C.W. Scherer, and P.D. Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflicts. Conservation Letters 1:136–145. Greenleaf, S.S., S.M. Matthews, R.G. Wright, J.J. Beecham, and H.M. Leithead. 2009. Food habitat of American black bears as a metric for direct management of human-bear conflict in Yosemite Valley, Yosemite National Park, California. Ursus 20:94-101. Hostetler, J.A., J.W. McCown, E.P. Garrison, A.M Neils, M.A. Barrett, M.E. Sunquist, S.L. Simek, and M.K. Oli. 2009. Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation 142:2456-2463. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. 12 �Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Johnson, H.E. 2012. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Federal Aid Annual Report, Colorado Division of Parks and Wildlife, Fort Collins, USA. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. McLoughlin, P.D., D.W. Morris, D. Fortin, E. Vander Wal, and A.L. Contasti. 2010. Considering ecological dynamics in resource selection functions. Journal of Animal Ecology 79:4-12. Mitchell, M.S., L.B. Pacifici, J.B. Grand, and R.A. Powell. 2009. Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8:169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Sadeghpour, M.H., and T.F. Ginnett. 2011. Habitat selection by female American black bears in northern Wisconsin. Ursus 22:159-166. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83:340-354. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. 13 �Table 1. Capture information for black bears that were marked in the vicinity of Durango, CO between 1 June 2013 and 1 April 2014 (collared adult females are identified with an “*”). Only information from the initial capture of each individual is shown (no recaptures). Bear ID B259 B260 B261* B262 B263 B265 B266 B267 B268 B269 B274 B275 B276 B277 B278 B280 B281* B282 B283 B284 B285* B287 B289 B290 B291* B292 B293* B296 B297 B298* B299* B300 B301 B302 B303* B304 B306 B307 B308 Capture Date 6/3/2013 6/4/2013 6/7/2013 6/10/2013 6/11/2013 6/14/2013 6/17/2013 6/19/2013 6/21/2013 6/21/2013 6/26/2013 6/27/2013 6/29/2013 6/30/2013 7/1/2013 7/8/2013 7/11/2013 7/16/2013 7/16/2013 7/19/2013 7/19/2013 7/23/2013 7/25/2013 8/1/2013 8/2/2013 8/4/2013 8/6/2013 8/10/2013 8/10/2013 8/14/2013 8/16/2013 8/17/2013 8/20/2013 8/23/2013 8/23/2013 8/23/2013 8/29/2013 8/29/2013 8/31/2013 UTM Easting 251514 253231 253231 251343 254584 251343 251933 249872 251817 249153 256824 256937 237708 238206 256763 240340 255385 244631 242022 247443 254750 248532 764348 246591 237566 246591 245913 245913 246383 245848 245848 243934 243934 248263 240787 243934 248263 250971 244631 UTM Northing 4137313 4138879 4138879 4134446 4134994 4134446 4137246 4130099 4131555 4132855 4134340 4134617 4130726 4130573 4134317 4131577 4133334 4132166 4127361 4137388 4133273 4139266 4132592 4135689 4124276 4135689 4139623 4139623 4142011 4141980 4141980 4134857 4134793 4136448 4130376 4134857 4136448 4132450 4132166 14 Sex M M F M M F M F F M M F F M M F F M M F F M M M F M F M M F F M F M F M F M M Age 1 6 8 1 6 1 8 2 2 4 6 2 2 10 3 1 13 3 2 0 8 3 3 4 4 3 3 2 4 5 3 10 1 8 7 1 1 6 4 Kg 32.7 102.1 78.0 30.8 83.9 38.6 125.6 30.8 31.3 54.4 116.6 34.9 57.2 181.4 79.8 25.9 63.5 73.0 33.6 10.4 66.2 75.3 88.5 93.4 64.4 56.7 49.4 45.8 99.3 51.7 61.7 122.0 33.1 133.8 93.0 42.2 33.1 87.1 70.8 �B311 B312 B313* B315 B316 B317 B318 B319 B320 B321 B322 B324 B325 B326 B327 B328 B329 B330 B331 B332 B333 B334 B335 B336 B337 B338 B339 B340 B341 B342 B343 B344 B345 B346 B347 9/3/2013 9/6/2013 9/12/2013 1/24/2014 1/24/2014 2/11/2014 2/11/2014 2/25/2014 2/25/2014 2/25/2014 2/25/2014 2/26/2014 2/26/2014 2/27/2014 2/27/2014 2/28/2014 2/28/2014 2/28/2014 2/28/2014 3/4/2014 3/4/2014 3/5/2014 3/5/2014 3/7/2014 3/7/2014 3/7/2014 3/11/2014 3/11/2014 3/11/2014 3/13/2014 3/13/2014 3/15/2014 3/15/2014 3/17/2014 3/17/2014 243225 248460 248263 257532 257532 253426 253426 248885 248885 248878 248878 242007 242007 249876 249876 245874 245874 250426 250426 244707 244707 236152 236152 237280 237280 237280 241748 241748 241748 250685 250685 256122 256122 763528 763528 4129043 4135188 4136448 4132989 4132989 4131665 4131665 4136736 4136736 4137006 4137006 4135878 4135878 4131660 4131660 4138878 4138878 4130202 4130202 4140518 4140518 4148573 4148573 4133531 4133531 4133531 4133069 4133069 4133069 4138783 4138783 4132990 4132990 4133211 4133211 15 M M F M M M F M F M F M F M M F F M F F F F M M M F F F M F M F F M M 8 10 15 1 1 1 1 1 1 cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub 142.4 179.2 77.1 16.3 16.3 17.2 16.8 15.0 15.9 1.4 1.3 1.9 2.0 1.9 1.8 1.6 1.6 1.6 1.1 1.7 1.8 1.5 1.9 1.9 1.9 1.8 2.9 3.4 2.7 1.5 1.3 2.6 2.6 2.4 2.6 �Figure 1. Locations of the 2014 hair snare sites (red dots) for the Durango and wildland genetic sampling grids. 16 �Figure 2. Change in garbage containers (regular to bear-resistant) at residences in experimental areas pretreatment (2012) and post-treatment (2014), Durango, Colorado. Locations of garbage-related conflicts for each year are also displayed. Garbage Conflicts & Availabitty • Conllicls • R-1...-Gart>age Can • WildMfe-Resistant Gabage Can C Trutment Area C Contn,IA,ea -- 0 0.1 0.2 ' ~+ f ' 0.4 0.6 mer,enl PCCjp, USGS. lnla'lllilp, E5'I Japan, IETI, e.. 0.8 (Hang l<a,g). - ~Rm'lllnl. Miles Cllna l&apny1nlla, OOpenSIIM!Map ~ aid llo 0 0 .1 02 0 .4 O.tl =~ S<luf1lKC DeLam10. USGS.lrltMnal>, n:n,n,nt1>cap. ~CAN. METl El'1 M~s CN"' (ttorg Ka,g~ art (1)l&nlJ. llln'lllnl. """"""'..00pensneu.iap-., an<11ne 0.8 GIS lMr C0nmlnlly GIS UW COMrru1ly 17 �Figure 3. Number of weekly black bear captures from May 15th through September 15th during the 2011 through 2013 summer trapping seasons. 25 2011 Number of Bear Captures 2012 20 2013 15 10 5 0 0 2 4 6 8 10 12 14 Week (May 15th through Sept 15th) 18 16 �Figure 4. GPS collar locations from 42 adult female black bears collected during 1 January – 31 December 2013 in the vicinity of Durango, Colorado (different colored clusters of points represent different individual bears): A) an overview of all locations and B) locations around the town of Durango. B A 21 IM7m F.uu11ng1ou 172m z/plm Ao~--~=-= N on,1"o"a 20 40 60 ...... '00Kilometers 19 �Figure 5. Probabilities of selection by black bears for density of human development from June through October in Durango, Colorado (selection is depicted on a monthly basis). Warm colors depict selection during a poor natural food year (2012) and cooler colors depict selection in a good natural food year (2011). 1 Jun1/Poor Jul1/Poor Aug1/Poor Sep1/Poor Oct1/Poor Jun1/Good Jul1/Good Aug1/Good Sep1/Good Oct1/Good Probability of Selection 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 100 200 300 Density of Human Development/km2 20 �Figure 6. Spatial predictions of resource selection from female black bears in Durango, Colorado, for a good (A) and poor (B) natural food year during fall (Oct 1st). B A 21 �Colorado Division of Parks and Wildlife July 2014 – June 2015 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 3 Federal Aid Project No. W-204-R4 : : : : : Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2014 – June 30, 2015 Author: H. E. Johnson Personnel: H.E. Johnson, S.A. Lischka, J. Broderick, J. Apker, S. Breck, J. Beckmann, K. Wilson, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear demography and behavior, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we focused on collecting field data in the vicinity of Durango, and publishing papers on bear selection for human development and on new immobilization drugs for black bears (Johnson et al. 2015, Wolfe et al. 2014). With respect to data collection, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys to estimate bear density, collected GPS collar location data on bears along the urban-wildland interface, monitored the availability of late summer/fall mast, obtained data on garbage-related bear-human conflicts, and assessed resident use of project-supplied bear-resistant garbage containers. Information from this study will provide solutions for sustainably managing black 1 �bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 2 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPUATION EFFECTS HEATHER E. JOHNSON PROJECT NARRATIVE OBJECTIVES 1. Determine the influence of urban environments on black bear demography and behavior. 2. Test a management strategy for reducing bear-human conflicts. 3. Examine public attitudes and behaviors related to bear-human interactions. 4. Develop population and habitat models to support the sustainable monitoring and management of bears in Colorado. SEGMENT OBJECTIVES 1. Work with personnel from CPW Area 15, CPW Southwest Region, City of Durango, La Plata County, US Forest Service (Columbine and Pagosa Ranger Districts), Bureau of Land Management (BLM; Tres Rio Field Office), Southern Ute Tribe, and private landowners on field research logistics. 2. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear demography and behavior. 3. Track bear movements and survival via global position system (GPS) collar locations. 4. Monitor bear fecundity and cub survival through winter den investigations of collared adult female bears. 5. Obtain data on natural food conditions for bears based on the abundance of mast from gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and wild crabapple. 6. Track human-related bear mortalities and removals around Durango from lethal conflict management, vehicle collisions, harvest, and translocations. 7. Perform non-invasive genetic mark-recapture surveys to estimate bear density and population size around Durango (urban site) and in the Piedra watershed (wildland site). 8. Assess the efficacy of wide-scale urban bear-proofing for reducing bear-human conflicts by quantifying conflicts in areas with and without bear-resistant containers. 9. Examine human behavior by monitoring resident compliance with wildlife ordinances in neighborhoods that were provided with bear-resistant garbage containers. 10. Complete an analysis and publication on bear selection for human development. Collaborate with colleagues to test new immobilization drugs for black bears, and disseminate results (Wolfe et al. 2014). 3 �INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human conflicts can result in public safety concerns, property damage, bear mortality (i.e., euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman conflicts (i.e., education, aversive conditioning of bears, and increased harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceedingly difficult to estimate (Garshelis and Hristienko 2006). Without a thorough understanding of the relationship between conflict rates and bear behavior and population dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, fruit trees, livestock, birdfeeders, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of novel resources. Bear-use of human food not only increases interactions between bears and people but has been found to alter bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly influence both bear demography and behavior. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures for bears in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for modifying bear-habitat relationships, they also have critical implications for increasing rates of bearhuman conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we initiated a project in FY10-11 to 1) determine the influence of urban environments on bear behavior and demography, 2) test a management strategy for reducing bear-human conflicts, 3) examine public attitudes and behaviors related to bear-human interactions, and 4) develop population and habitat models to support the sustainable monitoring and management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY14-15, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys to estimate bear density, collected GPS collar location data on bears along the urban-wildland interface, monitored the 4 �availability of late summer/fall mast, obtained data on garbage-related bear-human conflicts, and assessed resident use of project-supplied bear-resistant garbage containers. Our efforts focused largely on collecting field data to meet research objectives 1-3, information which will be used to address objective 4. Additionally, we used GPS collar data to perform an analysis of bear selection of human development (Johnson et al. 2015, Appendix 1) and collaborated on a study to develop and test new immobilization drugs for black bears and other species (Wolfe et al. 2014, Appendix 2). We report general summary information from field activities over the past year; detailed analyses of field data are ongoing. STUDY AREA To meet study objectives, we are using a combination of site-specific field data and statewide data. Site-specific field data are being collected in the vicinity of Durango, and are the focus of this progress report. The town of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon pine, juniper, aspen, mountain shrubs, and agriculture. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Prunus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), wild crabapple (Peraphyllum ramosissimum) and pinyon pine (Pinus edulis). Durango is predominately surrounded by public land managed by the San Juan National Forest, BLM, CPW, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts (Baruch-Mordo et al. 2008, CPW unpublished data). METHODS Objective 1: Determining the influence of urban environments on bear demography and behavior To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear demography and behavior, we are collecting a suite of data types including survival and reproductive rates of bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitats using mark-recapture methods. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011). Collaring and Marking Bears – To assess bear demographic rates and behavior with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates that drive population growth. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, the vital rates that are typically associated with variation in bear population trends (Mitchell et al. 2009, Beston 2011). We have focused summer trapping efforts within ~10 km of Durango to collar a cohort of bears that experience similar natural food conditions, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urban-wildland interface. Bears are trapped with box traps, which are baited with fish, road kill, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar (manufactured by Vectronics), and a tooth (first pre-molar) is pulled for 5 �age verification. GPS collars record bear locations every hour, and upload a real-time location to a central database via satellite every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair. Estimating Demographic Rates – To assess the influence of human development on bear demographic rates we have been collecting the following data types: 1) survival and reproduction of collared adult female bears, 2) cub survival monitored during annual winter den checks of collared females, 3) mortalities and removals of marked and unmarked bears in the vicinity of Durango, and 4) non-invasive genetic surveys that estimate density and abundance of bears around urban and wildland sites. Collared female bears allow us to estimate annual adult female survival, fecundity (number of cubs born/adult female) and cub survival (survival from newborn cub to yearling); parameters we have monitored since summer 2011 and which we will continue to monitor through winter 2017. We use realtime GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations are stationary during multiple fixes. Fecundity and cub survival are monitored from winter den checks of collared females. Numbers of newborn cubs provide information on fecundity, while consecutive annual den checks of collared females allow us to estimate cub survival. Because yearlings hibernate with their mothers, we can observe the number of cubs alive in the den in year t that survived their first year of life to t+1. Adult female survival, fecundity and cub survival will be used in matrix projection models to assess population performance (Caswell 2001), particularly in relation to use of human development. In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked (i.e., males, subadults) and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on human-related bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and hunter harvest. For all bears that are removed from the study area we collect a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery data to estimate adult male and subadult survival, while also gaining valuable information on cause-specific bear mortality. To better understand the influence of urban environments on bear density and abundance, we are employing non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between the bear population around Durango and for a nearby “wildland” area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size. We constructed and monitored 1 snare site within each cell. Snares consisted of a scented bait hanging high in a tree, surrounded by barbed wire around a cluster of trees encircling the bait (wire was strung 50 cm above ground). When bears climb over or under the wire to investigate the bait, they leave a hair sample on the barbed wire. During summers 2011 through 2014, we deployed snares during the first 2 weeks of June, and conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with a scent (anise, berry, fish, maple or bacon), and collected hair samples from all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. In summer 2014 we conducted the final year of hair-snare data collection. We constructed and monitored 35 snare sites in the Durango grid and 34 sites in the wildland grid (Figure 1). All hair samples collected in the field were sent to Wildlife Genetics International (Nelson, British Columbia, Canada) for genotyping; genetic results will be returned during summer 2015. Once genotypes are returned, we will use spatially-explicit mark recapture statistics (Efford et al. 2009, Gardner et al. 2010) to estimate abundance and density for the urban and wildland grids in each year of the study. 6 �Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wildland Interface – To examine movement and habitat-use patterns of bears along the urban-wildland interface, we are using GPS location data from collared females. Hourly GPS data are downloaded from the collars in the field on a biannual basis (fall and winter). Locations are being used to assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear movement and resource selection patterns (Manly et al. 2002, McLoughlin et al. 2010, Morales et al. 2010). For spatial covariate data, we have generated rasters representing elevation, aspect, slope and terrain ruggedness using digital elevation models. We also created rasters depicting distances to drainages and perennial water using the National Hydrology Dataset, and have estimated the proportion of different vegetation types using the USFS LandFire dataset (http://www.landfire.gov/vegetation.php). We derived rasters depicting human structure and road densities using data from La Plata county and CPW. Weather information will be acquired from local weather stations and PRISM datasets (www.prism.oregonstate.edu/). While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of berry and nut resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural forage for bears around Durango, we conduct bimonthly mast surveys. Surveys are performed from late July through mid-September, when berries and nuts should reach peak maturation. Key mast species for bears around Durango are gambel oak, chokecherry, serviceberry, hawthorne, wild crabapple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 15 transects on public lands to evaluate bear mast availability. Each transect is 1 km in length and situated along an existing trail or stream drainage. For each species, along each transect, field technicians qualitatively assess the phenological stage (immature fruits/nuts, peak maturation, etc) and abundance of mast (proportion of plants with no mast, scarce fruits/nuts, moderate fruits/nuts, etc). During FY14-15 we used GPS collar data to conduct an analysis examining bear selection for human development (Johnson et al. 2015, Appendix 1). In addition to using data from bears around Durango, we collaborated with researchers that have collected similar data around Aspen, Colorado and Lake Tahoe, Nevada, to assess bear selection for development across these 3 sites. I have provided a brief summary of the methods and results in this report, and have included the paper as Appendix 1. Our objectives were to 1) identify temporal patterns of selection for human development within a year and across years based on natural food conditions, 2) compare spatial patterns of selection for development across systems, and 3) examine individual characteristics associated with increased selection for development. We used generalized linear mixed-effects models (GLMMs) following a use-availability design (Manly et al. 2002), using random intercepts account for differences in sample sizes among individuals and autocorrelation within animal datasets (Gillies et al. 2006). “Used” locations were evaluated on an animal-year-specific basis, collected from May – Oct and “available” locations were randomly generated from animal-specific 95% minimum convex polygons. We used 80% of the animal-year datasets for developing models and withheld 20% for model validation. We first ran a “base” model that accounted for topography, vegetation, and distance-to-drainage, which are covariates consistently associated with black bear habitat (Clevenger et al. 2002; Carter et al. 2010; Sadeghpour and Ginnett 2011). We then compared the base model to a series of models that included density of human development (HD), based on point data of human structures in La Plata county. We evaluated the following models: base + HD, base + HD * Food Year (temporal variation in selection for HD between years), base + HD * Week (temporal variation in selection for HD within the active bear year) and base + HD * Food Year * Week (both across and within year variation in selection for development; models included all relevant main 7 �effects and interactions). We fit models using maximum likelihood estimation and used minimum AIC scores to assess the relative support for models with different fixed effects (Burnham and Anderson 2002). We assessed the predictive power of our top model with cross-validation using hold-out data (Boyce et al. 2002). Model results were used to make inferences about bear selection for human development across and within years, and among study sites. To determine whether individual covariates were correlated with bear selection for development we estimated individual selection coefficients (random slope) from GLMMs (Hebblewhite and Merrill, 2008 and Wagner et al., 2011). We restricted this analysis to locations collected during Aug-Sep, allowing us to assess bear selection for human development during the time period of peak conflict activity across sites. Individual selection coefficients were then used as the response variable in a linear regression to test whether bear selection for HD was associated with several covariates. Covariates included the bear’s age, maternal status (cubs or no cubs based on den visits the previous winter), mean HD within the total known 95% MCP for an individual (HDall), and mean HD within the year-specific Aug-Sep 95% MCP (HDhyperphagia). Objective 2: Testing a management strategy to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that resource (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of “cleaning up” a town. Given the high price to operationally “bearproof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project, we are implementing the first experimental test of wide-scale urban bearproofing for reducing bear-human conflicts. As part of the experiment we have designated 2 residential ‘treatment’ areas and 2 paired ‘control’ areas, consisting of a total of ~2,000 homes. In spring and early summer 2013 we deployed ~900 bear-resistant garbage containers within the treatment areas (approximately 100 homes already had these containers) with the goal that regular receptacles were exchanged with bear-resistant containers for all residents. In spring and early summer 2014 we deployed an additional ~150 containers to “clean-up” treatment areas, ensuring that all residences had a bearresistant container. In July 2013 and 2014 we also canvassed homes within treatment areas, reminding residents to lock their bear-resistant garbage containers and asking that they bear-proof their properties (remove bird feeders, outdoor pet food, and other bear attractants); no canvassing occurred in control areas. Additionally, we increased enforcement of wildlife ordinances within treatment areas, providing official warnings at residences with bear-strewn trash and notifying city code enforcement for subsequent ticketing. To track the effectiveness of these efforts in reducing bear-human conflicts we are collecting preand post-treatment data. For 2 years pre-treatment, summers 2011 and 2012, field technicians patrolled streets within proposed treatment and control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from 5:00 – 7:00 am and recorded locations of bear-strewn trash. Monitoring occurred from July through September, months that experience the highest numbers of bear-human conflicts in Durango (CPW unpublished data). During summers 2013 and 2014 project personnel collected post-treatment data; posttreatment data will be collected through 2016. Each summer, in addition to collecting information on bears accessing human foods, we have quantified the “availability” of garbage to bears, by documenting the location and container type (bearresistant or regular) of every garbage receptacle in the survey area accessible to bears the night prior to 8 �garbage pick-up. These data provide an index of the garbage available to bears in town and allow us to track changes in the number of bear-resistant containers in the study area over the course of the experiment. Once the experiment is complete, we will use data from pre- and post-treatment years, and from treatment and control areas, to quantify the effectiveness of residential bear-proofing. In addition to our observations of bear-strewn trash, we will use conflict calls to the CPW Area 15 Office to examine differences in conflict rates pre- and post-treatment, and across treatment and control areas. Objective 3: Identifying public attitudes and behaviors related to bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have stimulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011). Thus, we have initiated efforts to better understand human attitudes related to bears and bear-human interactions, and human behaviors related to the appropriate use of bear-resistant garbage containers. To assess data on human attitudes we are using public mail surveys to 1) quantify perceptions about bears, bear management, and bear-human interactions, and 2) explore motivations for compliance and non-compliance with wildlife ordinances designed to reduce bear-human conflicts. To meet these objectives, we developed a three-part mail survey, conducted in conjunction with our urban bear-proofing experiment. Residents are being surveyed pre- (2012), during (2014), and post-implementation (2016) of the experiment, in treatment and control areas, as well as across a larger portion of the community. Surveys are mailed to all residents within Durango city limits, and a subset of La Plata county residents within the study area. Survey responses will allow us to quantify current attitudes and perceptions about bear-human interactions, and how those perceptions change over time in association with a management effort such as wide-scale urban bear-proofing. Survey data will also identify the number of residents that have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. The first (pre-treatment) public survey was conducted during winter 2012 (see Johnson et al. 2012 for details) and the second survey was conducted during winter 2014 (see Johnson et al. 2014 for details), following the first year of the bearproofing experiment. In addition to collecting data on human attitudes and perceptions, we are also collecting data on human behavior through direct observations. Using a random, stratified sampling design we are monitoring human compliance with wildlife ordinances at residences in treatment and control areas. Durango city ordinances specify that garbage can only be accessible after 6:00 am on the morning of pick-up; therefore, we define compliance as having garbage adequately secured so that bears cannot access it, either through appropriate use of a bear-resistant garbage container (e.g. latched lid) or by keeping garbage enclosed in a garage or shed until the morning of trash pick-up. Non-compliance is defined as allowing garbage to be accessible to bears by not latching a bear-resistant container or putting a regular garbage container at the curb the night before garbage pickup. To assess compliance, we survey residences on the morning of garbage pick-up (5:00-6:00 am) between July and September. Compliance monitoring began in 2013 and will continue through 2016. In each treatment and control area, a sample of 40 randomly selected blocks are monitored (a total of 160 blocks) such that the number and type of cans (regular or bear-resistant) and compliance status are recorded. Each block is surveyed three times/summer. In the north experimental area, compliance is recorded for each parcel, but in the south experimental area, compliance is recorded per block because garbage containers are stored along alleys and cannot be easily tracked to parcel. Compliance data will be 9 �analyzed in conjunction with mail survey data, spatial covariates, and conflict activity to better understand how factors such as management actions and rates of bear-human interactions influence human behavior. This should help CPW tailor education and communication efforts to be more effective at achieving public compliance with wildlife ordinances. In monitoring compliance, we expected that some residents likely had unsecured containers that did not contain any food for bears, potentially biasing our estimate. We examined this source of bias in summer 2014 by looking in garbage cans to develop a correction factor for “non-compliant” but empty containers. We divided the study area into three smaller areas: the north experimental area with parcels without alleys, the north experimental area with parcels with alleys, and the south experimental area (all parcels had alleys). We aimed to examine ~50 garbage cans/area to determine the proportion that were unsecured but empty. In the north experimental area without alleys, we visually identified all containers that were inaccessible to the technician (those visible but not placed on the street). Those homes were revisited by the technician later in the day, and homeowners were asked if there was garbage in the container the night before their garbage pick-up day. RESULTS AND DISCUSSION Objective 1: Determining the influence of urban environments on bear behavior and demography Between 8 July 2014 and 31 March 2015 (the 2014-2015 capture year), an additional 63 unique bears were marked during 147 bear captures. To date on the project there have been 327 different individuals marked during 717 captures. Information about these captures is described below for summer 2014 and winter 2015. During summer 2014 we conducted 56 total bear captures; 20 captures were newly marked unique individuals and 36 were recaptures. Of the unique individuals captured, there were 7 females and 13 males (Table 1). We placed collars on 5 new adult females. Including bears that were already collared at the start of the summer, this resulted in 42 collars deployed by mid-September, the end of the summer capture season. The mean estimated age of bears ≥1 year-old on their initial capture date was 4.0 (5.9 for females and 3.0 for males), and the mean weight was 65.9 kg (64.2 kg for females and 66.8 kg for males). In total, we placed traps at 63 different locations and conducted 1,021 trap nights. Capture success was fairly consistent throughout the summer, dropping off at the end of the season (Figure 2). Capture effort was slightly reduced from previous years, as we only needed to collar a few additional female bears. Between January and March 2015, we visited the winter dens of 37 collared females. Although we had 42 female bears collared at the end of summer 2014 there were 2 mortalities in fall (B417 was harvested and B161 was shot but not recovered by a hunter), and 3 dens that could not be located. Of the 37 adult females that we processed, 11 did not have any cubs or yearlings, 8 had yearlings (12 yearlings in total; 6 females and 6 males), and 19 had newborn cubs (41 cubs in total; 25 females and 16 males). Additionally, we were able to confirm that B67, a sow that we could not locate during den work, had 2 yearlings in spring of 2015. Of those females with newborn cubs, 1 bear had only 1 cub, 14 bears had twins, and 4 bears had triplets. We PIT and ear-tagged yearlings in the den, recorded information on weight, body size, body condition, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. We found that reproductive success, measured as the number of cubs/adult female ≥4 years old was 1.15 (SE=0.20) for winter 2015. This was the highest fecundity rate observed since the study commenced, as previous fecundity rates were between 0.52 (SE=0.16) and 0.95 (SE=0.24). Cub survival for 2015 (survival from newborn to 1 year) was 58% (SE=0.10; based on 24 cubs), compared to 50% in 2014 and 40% in 2013. Between 1 April and 1 December 2014 (the active bear season of 2014), a total of 32 bears were removed from the study area. Of those bears, 22 were legally harvested, 3 were killed in vehicle collisions, 2 were lethally removed for nuisance behavior, 2 were electrocuted (from bears climbing 10 �power poles), 2 died of unknown causes, and 1 was killed by gunshot but not recovered by a hunter. Of those mortalities there were 12 adult males, 7 adult females, 3 subadult males, 5 subadult females, 2 male cubs, 2 female cubs, and 1 male of unknown age. Twenty-two of those bears were unmarked and 10 had been marked by research personnel. Additionally, 6 marked bears died outside the study area; 4 were legally harvested and 2 died in vehicle collisions. Survival of collared adult female bears was high in 2014. The known fate Kaplan Meier estimate of survival was 0.95 (SE=0.04), compared to 0.85 (SE=0.07) in 2013 and 0.82 (SE=0.08) in 2012. Survival in 2011 was similar to 2014 at 0.96 (SE=0.04). In summer 2014, we collected 1,209 hair samples from the Durango and wildland grids; 551 samples from Durango and 658 samples from the wildland site. Over the 6 sampling occasions from 35 snares around Durango we collected 82, 122, 87, 91, 88, and 81 hair samples, respectively. Over the 6 sampling occasions from 34 sites in the wildland grid we collected 159, 134, 127, 81, 61, and 96 hair samples, respectively. The number of samples/snare ranged from 0 to 66 in the Durango grid and from 2 to 50 in the wildland grid. Genotype results should be returned from Wildlife Genetics International during summer 2015. Detailed mark-recapture analyses of these data will be conducted in FY15-16 to estimate annual density and abundance at each site. The availability of natural mast foods was generally very good in late summer and fall 2014. Mast surveys demonstrated that the peak time for maturation of wild crabapple was late July, serviceberry was the first half of August, chokecherry was mid-August, hawthorne was late August, gambel oak was early September, and pinyon pines had cones developing in mid-September. On transects that had those species, mast was present on about 40% of wild crabapple shrubs, 70% of hawthorne shrubs and trees, and 50% of chokecherry, serviceberry oak and pinyon pine shrubs and trees. This was the second year that all mast foods were observed in the study area during the survey period. To date, we have obtained >496,000 locations from GPS collars on 70 different adult female bears; 42 different bears provided location data during the summer of 2014 (Figure 3). While most locations were in close proximity to Durango, a few animals ventured outside the primary study area. For example, B67 had moved to New Mexico in 2013, but moved back to Durango in fall of 2014 (with 2 cubs in tow). Another sow, B57, left her home range in lower Junction Creek (just north of Durango) to travel north to Hamilton Mesa (just south of Norwood; Figure 3), before returning to her original range. Using mixed effects resource selection models we found that bear selection for human development was highly dynamic, varying as a function of changing environmental and physiological conditions (See Appendix 1 for details). Bears increased use of development in years when natural foods were scarce, throughout the summer-fall, as they aged, and as a function of gender, with males exhibiting greater use of development. While patterns were similar across systems, bears at sites with poorer quality habitat selected development more consistently than bears at sites with higher quality habitat. Black bears appear to use development largely for food subsidy, suggesting that conflicts with bears will increase when the physiological demand for resources outweighs risks associated with human activity. These results have key implications for bear management. For example, many bears may be considered “conflict” individuals in a poor natural food year that otherwise exhibit natural foraging behavior. Wildlife agencies often assume that increases in human-bear conflicts reflect increases in bear populations, but our work suggests that bear selection for development may be increasing as animals age and gain more experience with anthropogenic foods. This behavior may then be the source of additional conflicts without an associated increase in population size. Objective 2: Testing management strategies to reduce bear-human conflicts During summer 2014 we collected our second year of post-treatment data on the bear-proofing experiment. To ensure that >95% of residences in treatment areas had bear-resistant containers, we surveyed each treatment and control area during mid-August to quantify the number and type of containers that were visible from the street (n = 1,678). We found that our efforts to “clean up” treatment 11 �areas were a success. Within the northern treatment area 98% of containers were bear-resistant and 2% were regular, and in the southern treatment area 95% were bear-resistant and 5% were regular. Within the northern control area 37% of containers were bear-resistant and 63% were regular, and in the southern control area 11% were bear-resistant and 89% were regular. We will continue working with the City of Durango to replace regular containers with bear-resistant containers in treatment areas. Within proposed treatment and control areas we observed 202 instances of bears accessing residential garbage during morning patrols, 40 conflicts in treatment areas and 162 in control areas (Figure 4). Of those conflicts, 25 were in the north treatment area, 45 were in the north control area, 15 were in the south treatment area and 117 were in the south control area. The number of trash-related conflicts in 2014 was lower than during the previous 2 years and generally peaked in mid-August. Of those garbage containers accessed by bears, 79% were regular containers and 21% were bear-resistant containers. Bears accessed human food from bear-resistant containers when they were not properly latched. While monitoring garbage-related conflicts, we issued 16 notices of violation in treatment areas. One resident was issued a second notice and a ticket from city code enforcement. Objective 3: Identifying human behaviors related to bear-human encounters During summer 2014 we found that the average compliance of residents to wildlife ordinances was 52% in the north treatment area and 34% in the south treatment area. “Compliance” was defined as having a container that was properly locked (both latches clipped) or secured in a garage or shed before 6:00 am. Across all sampling periods, compliance was generally higher in the northern experimental area than in the southern area. In the northern area, compliance increased from ~45% in 2013 to ~55% in 2014. In the southern area compliance remained ~45% in both years. When we surveyed residences to assess the proportion of containers that we labeled “non-compliant” but were devoid of any trash, we found that 7% met that description in the northern experimental area without alleys, 2% in the northern experimental area with alleys, and 14% in the southern experimental area. Future estimates of compliance will be corrected based on these numbers. SUMMARY AND FUTURE PLANS During FY14-15 we successfully coordinated field logistics and conducted several aspects of data collection (trapping and collaring bears, tracking human-related bear mortalities, collecting bear locations on the urban-wildland interface, assessing summer/fall mast availability, implementing DNA hair-snare surveys, monitoring garbage-related bear-human conflicts, etc.). Data collection will continue on most aspects of the study through winter 2017, with the collection of some data types concluding earlier (i.e., DNA hair-snare surveys are now complete). We have initiated data analysis on bear demographic rates and population dynamics, and will continue to analyze data on various aspects of the project in the coming years. In addressing our research objectives we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and demography, understand the effect of bear-human interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. PLoS One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. 12 �Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. 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Effects on risk perception of media coverage of a black bear-related human fatality. Wildlife Society Bulletin 33:507-516. Gore, M.L., B.A. Knuth, C.W. Scherer, and P.D. Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflicts. Conservation Letters 1:136–145. Greenleaf, S.S., S.M. Matthews, R.G. Wright, J.J. Beecham, and H.M. Leithead. 2009. Food habitat of American black bears as a metric for direct management of human-bear conflict in Yosemite Valley, Yosemite National Park, California. Ursus 20:94-101. Hebblewhite, M., and E. Merrill. 2008. Modelling wildlife – human relationships for social species with mixed-effects resource selection models. Journal of Applied Ecology 45:834-844. Hostetler, J.A., J.W. McCown, E.P. Garrison, A.M Neils, M.A. Barrett, M.E. Sunquist, S.L. Simek, and M.K. Oli. 2009. Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation 142:2456-2463. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. 13 �Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Johnson, H.E. 2012. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Federal Aid Annual Report, Colorado Division of Parks and Wildlife, Fort Collins, USA. Johnson, H.E., S.A. Lischka, J. Broderick, J. Apker, S. Breck, J. Beckmann, K. Wilson, and P. Dorsey. 2014. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Federal Aid Annual Report, Colorado Parks and Wildlife, Fort Collins, USA. Johnson, H.E., S.W. Breck, S. Baruch-Mordo, D.L. Lewis, C.W. Lackey, K.R. Wilson, J. Broderick, J.S. Mao, and J.P. Beckmann. 2015. Shifting perceptions of risk and reward: dynamic selection for human development by black bears in the western United States. Biological Conservation 187:164-172. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. McLoughlin, P.D., D.W. Morris, D. Fortin, E. Vander Wal, and A.L. Contasti. 2010. Considering ecological dynamics in resource selection functions. Journal of Animal Ecology 79:4-12. Mitchell, M.S., L.B. Pacifici, J.B. Grand, and R.A. Powell. 2009. Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8:169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Sadeghpour, M.H., and T.F. Ginnett. 2011. Habitat selection by female American black bears in northern Wisconsin. Ursus 22:159-166. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83:340-354. Wagner, T., D.R. Diefenbach, S.A. Christensen, and A.S. Norton. 2011. Using multilevel models to quantify heterogeneity in resource selection. Journal of Wildlife Management 75:1788-1796. Wolfe, L.L., H.E. Johnson, M.C. Fisher, M.A. Sirochman, B. Kraft, and M.W. Miller. 2014. Use of Acepromazine and Medetomidine in combination for sedation and handling of Rocky Mountain elk (Cervus elaphus nelsoni) and black bears (Ursus americanus). Journal of Wildlife Diseases 50:979-981. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. 14 �Prepared by Heather E. Johnson, Mammals Researcher 15 �Table 1. Capture information for black bears that were newly marked in the vicinity of Durango, CO between 1 June 2014 and 1 March 2015 (collared adult females are identified with an “*”). Only information from the initial capture of each individual is shown (no recaptures). Bear ID B393* B394 B401 B402 B403 B404 B405 B406 B407* B408* B409 B410* B411 B412 B413 B414 B415 B416 B417* B422 B425 B424 B429 B428 B431 B430 B436 B435 B432 B434 B433 B438 B437 B442 B441 B444 B443 B446 B445 B451 B450 B449 B448 B447 B454 Capture Date 7/8/2014 7/11/2014 7/14/2014 7/17/2014 7/24/2014 7/26/2014 7/28/2014 7/30/2014 7/30/2014 8/1/2014 8/8/2014 8/9/2014 8/18/2014 8/18/2014 8/20/2014 8/23/2014 8/26/2014 8/28/2014 8/30/2014 9/14/2014 2/18/2015 2/18/2015 3/4/2015 3/4/2015 3/4/2015 3/4/2015 3/5/2015 3/5/2015 3/5/2015 3/6/2015 3/6/2015 3/9/2015 3/9/2015 3/9/2015 3/9/2015 3/10/2015 3/10/2015 3/11/2015 3/11/2015 3/12/2015 3/12/2015 3/12/2015 3/12/2015 3/12/2015 3/13/2015 UTM Easting 237643 239018 242541 243210 238209 237184 237184 237184 245924 245967 243625 249071 251815 249071 243210 251902 249071 240554 250671 243443 260637 260637 245250 245250 245342 245342 247265 247265 241748 249168 249168 238077 238077 231755 231755 248984 248984 252802 252802 244240 244240 244240 239542 239542 249644 UTM Northing 4124202 4134402 4128373 4128717 4130574 4131686 4131686 4131656 4139622 4141967 4129374 4133006 4131559 4133006 4128717 4130512 4133006 4131370 4132079 4131784 4145413 4145413 4137726 4137726 4137855 4137855 4140832 4140832 4135821 4127890 4127890 4110252 4110252 4115088 4115088 4137372 4137372 4134347 4134347 4133716 4133716 4133716 4134694 4134694 4136076 16 Sex F M M M F M M M F F M F M F M M M M F M F M M F F F F F M F F F F F M F F M M M F F M F F Estimated Age 14 2 2 2 2 2 3 2 8 3 5 5 4 1 4 3 3 4 8 0 cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub Weight (kg) 16.2 44.1 28.4 84.6 44.6 52.2 72.9 41.4 80.1 66.2 95.4 73.4 64.8 30.2 107.1 81.0 43.2 80.1 75.6 30.6 1.0 1.0 2.5 2.2 1.4 1.2 1.5 1.4 1.4 3.4 3.5 2.8 2.5 1.7 1.8 1.6 1.7 2.4 2.5 2.6 2.9 3.4 2.4 2.2 2.8 �B453 B452 B457 B456 B455 B459 B458 B462 B461 B460 B464 B463 B466 B465 B468 B467 3/13/2015 3/13/2015 3/16/2015 3/16/2015 3/16/2015 3/17/2015 3/17/2015 3/18/2015 3/18/2015 3/18/2015 3/19/2015 3/19/2015 3/23/2015 3/23/2015 3/30/2015 3/30/2015 249644 249644 257293 257293 257293 252458 252458 255500 255500 255500 242198 242198 243371 243371 243306 243306 4136076 4136076 4133607 4133607 4133607 4139329 4139329 4133416 4133416 4133416 4131891 4131891 4153025 4153025 4124104 4124104 17 F M F M M M F M M F M F M F F F cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub cub 2.5 2.8 1.8 1.6 1.6 2.7 2.8 2.0 2.0 2.3 2.2 2.2 3.3 3.2 3.5 3.9 �Figure 1. Locations of the 2014 hair snare sites (red dots) for the Durango and wildland genetic sampling grids. 8 12 16 -==-□•••===-••■ Kilometers F ORIDA Mic 18 �Figure 2. Number of weekly black bear captures from May 15th through September 15th during the 2011 through 2014 summer trapping seasons. Note: trapping did not commence until July in 2014. 25 2011 Number of Bear Captures 2012 20 2013 2014 15 10 5 0 0 2 4 6 8 10 12 Week (May 15th through Sept 15th) 19 14 16 �Figure 3. GPS collar locations from 42 adult female black bears collected during 1 January – 31 December 2014 in the vicinity of Durango, Colorado (different colored clusters of points represent different individual bears): A) an overview of all locations and B) locations around the town of Durango. A B .... 20 �Figure 4. Garbage-related black bear-human conflicts observed during July through September 2014. Red lines indicate treatment areas and black lines indicate control areas. Green circles represent conflicts with regular residential garbage containers and yellow circles represent conflicts with wildlife-resistant containers. 231 A o-__;. 02 ic:::::: 50:::i5_ _ _1Kilometers 21 �Colorado Division of Parks and Wildlife July 2015 – June 2016 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 3 Federal Aid Project No. W-204-R5 : : : : : Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2015 – June 30, 2016 Author: H. E. Johnson Personnel: H.E. Johnson, S.A. Lischka, J. Broderick, J. Apker, S. Breck, J. Beckmann, K. Wilson, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing and have become a high priority for wildlife management agencies. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have implemented a study on black bears that 1) determines the influence of human development on bear demography and behavior, 2) tests a management strategy for reducing bearhuman conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we focused on collecting field data in the vicinity of Durango and modeling demographic parameters from known-fate and mark-recapture data. With respect to data collection, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, collected GPS collar location data from bears along the urban-wildland interface, monitored the availability of summer/fall mast, obtained data on garbage-related bear-human conflicts, assessed resident use of project-supplied bear-resistant containers, and surveyed residents about their attitudes and behaviors with respect to bears. Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 1 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPUATION EFFECTS HEATHER E. JOHNSON PROJECT NARRATIVE OBJECTIVES The objectives of this project are to 1) determine the influence of urban environments on bear demography and behavior, 2) test a management strategy for reducing bear-human conflicts, 3) examine public attitudes and behaviors related to bear-human interactions, and 4) develop population and habitat models to support the sustainable management of bears in Colorado. SEGMENT OBJECTIVES 1. Work with personnel from CPW Area 15, CPW Southwest Region, City of Durango, La Plata County, US Forest Service, Bureau of Land Management, Southern Ute Tribe, and private landowners on field research logistics. 2. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear demography and behavior. 3. Track bear movements and survival via global position system (GPS) collar locations. 4. Monitor bear fecundity and cub survival through winter den investigations of collared adult female bears. 5. Obtain data on natural food conditions for bears based on the abundance of mast from gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and native crabapple. 6. Track human-related bear mortalities and removals around Durango from lethal conflict management, vehicle collisions, harvest, and translocations. 7. Assess the efficacy of wide-scale urban bear-proofing for reducing bear-human conflicts by quantifying conflicts in areas with and without bear-resistant containers. 8. Examine human behavior by monitoring resident compliance with wildlife ordinances in neighborhoods that were provided with bear-resistant garbage containers. 9. Survey residents in the study area about their attitudes and behaviors with respect to black bears. INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human conflicts can result in public safety concerns, property damage, bear mortality (i.e., euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman conflicts (i.e., education, aversive conditioning of bears, and increased harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceedingly difficult to estimate (Garshelis and Hristienko 2006). Without a �thorough understanding of the relationship between conflict rates and bear behavior and population dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, fruit trees, livestock, birdfeeders, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of novel resources. Bear-use of human food not only increases interactions between bears and people but has been associated with changes in bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly influence both bear demography and behavior. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures for bears in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for modifying bear-habitat relationships, they also have critical implications for increasing rates of bearhuman conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we initiated a project in FY10-11 to 1) determine the influence of urban environments on bear behavior and demography, 2) test a management strategy for reducing bear-human conflicts, 3) examine public attitudes and behaviors related to bear-human interactions, and 4) develop population and habitat models to support the sustainable management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY14-15, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, collected GPS collar location data on bears along the urban-wildland interface, monitored the availability of summer/fall mast, obtained data on garbage-related bear-human conflicts, assessed resident use of project-supplied bear-resistant garbage containers, and surveyed residents about their attitudes and behaviors with respect to bears. Our efforts focused largely on collecting field data to meet research objectives 1-3, and initiating the development of bear population models to meet objective 4. We report general summary information from field activities over the past year; detailed analyses of field data are ongoing. STUDY AREA To meet study objectives, we are using a combination of site-specific field data and statewide data. Site-specific field data are being collected in the vicinity of Durango, Colorado and are the focus of �this progress report. The town of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon pine, juniper, aspen, mountain shrubs, and agriculture. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Prunus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), native crabapple (Peraphyllum ramosissimum) and pinyon pine (Pinus edulis). Durango is predominately surrounded by public land managed by the San Juan National Forest, Bureau of Land Management, Colorado Parks and Wildlife, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts (Baruch-Mordo et al. 2008, CPW unpublished data). METHODS Objective 1: Determining the influence of urban environments on bear demography and behavior To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear demography and behavior, we are collecting a suite of data types including survival and reproductive rates of bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitats using mark-recapture methods. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011). Collaring and Marking Bears – To assess bear demographic rates and behavior with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates that drive population growth. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, the vital rates that are typically associated with variation in bear population trends (Mitchell et al. 2009, Beston 2011). We have focused summer trapping efforts within ~10 km of Durango to collar a cohort of bears that experience similar natural food conditions, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urban-wildland interface. Bears are trapped with box traps, which are baited with fish, road kill, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar (manufactured by Vectronics), and a tooth (first pre-molar) is pulled for age verification. GPS collars record bear locations every hour, and upload a real-time location to a central database via satellite every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair. Estimating Demographic Rates – To assess the influence of human development on bear demographic rates we have been collecting the following data types: 1) survival and reproduction of collared adult female bears, 2) cub survival monitored during annual winter den checks of collared females, 3) mortalities and removals of marked and unmarked bears in the vicinity of Durango, and 4) non-invasive genetic surveys that estimate density and abundance of bears around urban and wildland sites. Collared female bears allow us to estimate annual adult female survival, fecundity (number of cubs born/adult female) and cub survival (survival from newborn cub to yearling); parameters we have �monitored since summer 2011 and which we will continue to monitor through winter 2017. We use realtime GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations are stationary during multiple fixes. Fecundity and cub survival are monitored from winter den checks of collared females. Numbers of newborn cubs provide information on fecundity, while consecutive annual den checks of collared females allow us to estimate cub survival. Because yearlings hibernate with their mothers, we can observe the number of cubs alive in the den in year t that survived their first year of life to t+1. Adult female survival, fecundity and cub survival will be used in matrix projection models to assess population performance (Caswell 2001), particularly in relation to bear use of human development. In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked (i.e., males, subadults) and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on human-related bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and hunter harvest. For all bears that are removed from the study area we collect a hair and tooth sample and record the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery data to estimate adult male and subadult survival, while also gaining valuable information on cause-specific bear mortality. To better understand the influence of urban environments on bear density and abundance, we have employed non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between the bear population around Durango and for a nearby “wildland” area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size. We constructed and monitored 1 snare site within each cell. Snares consisted of a scented bait hanging high in a tree, surrounded by barbed wire around a cluster of trees encircling the bait (wire was strung 50 cm above ground). When bears climb over or under the wire to investigate the bait, they leave a hair sample on the barbed wire. During summers 2011 through 2014, we deployed snares during the first 2 weeks of June, and conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with a scent (anise, berry, fish, maple or bacon), and collected hair samples from all barbs. All hair samples were sent to Wildlife Genetics International (Nelson, British Columbia, Canada) for genotyping. This past year, we used genotype data to estimate female bear abundance and density around Durango. We used an integrated modeling approach that combined spatially-explicit capture-markrecapture data (SCR) from non-invasive hair snags and location data from GPS-collared females into a single unified analysis (Royle et al. 2013). This approach provided annual estimates of female population abundance, density, and population growth rate and annual estimates of resource selection parameters at the 2nd and 3rd order (Johnson 1980). Between 2011 and 2014, during June and July, non-invasive genetic sampling resulted in the annual detection of 41–61 females and the annual monitoring of 12–34 GPScollared females. We modeled 3rd-order resource selection as a function of 15 spatial covariates previously identified as important predictors of black bear space use (Johnson et al. 2015) and as a function of distance from a bear’s summer home range center. We modeled spatial variation in black bear density (i.e., 2nd-order resource selection) as a function of 4 spatial covariates including elevation, human development, stream density, and a forest classification that included a mixture of aspen, mesic montane, and mixed-conifer forest types. We fit 15 models that included all combinations of the 4 density covariates and a null model that assumed constant density across space. We also fitted 4 additional models that added an interaction term between forest and development to models in the previous model set that contained both covariates. We added a second-order polynomial term for elevation to all models that contained that covariate. We used AIC-based model selection and multi-model inference to rank candidate models and derive model-averaged parameter estimates. To evaluate the potential benefits of integrating GPS data in to our analysis, we also fit the same set of candidate models for abundance and density within a standard SCR framework (no GPS data) that assumes a bivariate-normal space-use model for comparison. �Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wildland Interface – To examine movement and habitat-use patterns of bears along the urban-wildland interface, we are using GPS location data from collared females. Hourly GPS data are downloaded from the collars in the field on a biannual basis (fall and winter). Locations are being used to assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear movement and resource selection patterns (Manly et al. 2002, McLoughlin et al. 2010, Morales et al. 2010, Johnson et al. 2015). For spatial covariate data, we have generated rasters representing elevation, aspect, slope and terrain ruggedness using digital elevation models. We also created rasters depicting distances to drainages and perennial water using the National Hydrology Dataset, and have estimated the proportion of different vegetation types using the USFS LandFire dataset (http://www.landfire.gov/vegetation.php). We derived rasters depicting human structure and road densities using data from La Plata county and CPW. Weather information has been acquired from local weather stations and from PRISM nationwide datasets (www.prism.oregonstate.edu/). While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of berry and nut resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural forage for bears around Durango, we conduct bimonthly mast surveys. Surveys are performed from late July through mid-September, when berries and nuts should reach peak maturation. Key mast species for bears around Durango are gambel oak, chokecherry, serviceberry, hawthorne, native crabapple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 15 transects on public lands to evaluate bear mast availability. Each transect is 1 km in length and situated along an existing trail or stream drainage. For each species, along each transect, field technicians qualitatively assess the phenological stage (immature fruits/nuts, peak maturation, etc) and abundance of mast (proportion of plants with no mast, scarce fruits/nuts, moderate fruits/nuts, etc). Objective 2: Testing a management strategy to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that resource (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of “cleaning up” a town. Given the high price to operationally “bearproof” a community, many municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project, we are implementing the first experimental test of wide-scale urban bearproofing for reducing bear-human conflicts. As part of the experiment we have designated 2 residential ‘treatment’ areas and 2 paired ‘control’ areas, consisting of a total of ~2,000 homes. In spring and early summer 2013 we deployed ~900 bear-resistant garbage containers within the treatment areas (approximately 100 homes already had these containers) with the goal that regular receptacles were exchanged with bear-resistant containers for all residents. In spring and early summer 2014 we deployed an additional ~150 containers to “clean-up” treatment areas, ensuring that all residences had a bearresistant container. In July 2013, 2014 and 2015 we also canvassed homes within treatment areas, reminding residents to lock their bear-resistant garbage containers and asking that they bear-proof their properties (remove bird feeders, outdoor pet food, and other bear attractants); no canvassing occurred in control areas. Additionally, we increased enforcement of wildlife ordinances within treatment areas, providing official warnings at residences with bear-strewn trash and notifying city code enforcement for subsequent ticketing. �To track the effectiveness of these efforts in reducing bear-human conflicts we are collecting preand post-treatment data. For 2 years pre-treatment, summers 2011 and 2012, field technicians patrolled streets within proposed treatment and control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from 5:00 – 7:00 am and recorded locations of bear-strewn trash. Monitoring occurred from July through September, months that experience the highest numbers of bear-human conflicts in Durango (CPW unpublished data). During summers 2013-2015 project personnel collected post-treatment data, conducting surveys twice/week; post-treatment data will be collected through 2016. Once the experiment is complete, we will use data from pre- and post-treatment years, and from treatment and control areas, to quantify the effectiveness of residential bear-proofing. In addition to our observations of bear-strewn trash, we will use conflict calls to the CPW Area 15 Office to examine differences in conflict rates preand post-treatment, and across treatment and control areas. Objective 3: Identifying public attitudes and behaviors related to bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have stimulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011). Thus, we have initiated efforts to better understand human attitudes related to bears and bear-human interactions, and human behaviors related to the appropriate use of bear-resistant garbage containers. To assess data on human attitudes, we are using public mail surveys to 1) quantify perceptions about bears, bear management, and bear-human interactions, and 2) explore motivations for compliance and non-compliance with wildlife ordinances designed to reduce bear-human conflicts. To meet these objectives, we developed a three-part mail survey, conducted in conjunction with our urban bear-proofing experiment. Residents were surveyed pre- (2012), during (2014), and post-implementation (2016) of the experiment, in treatment and control areas, as well as across a larger portion of the community. Johnson et al. (2012) and (2014) provide detailed information about the 2012 and 2014 surveys, respectively. The 2016 survey occurred between January and June 2016 (Appendix 1), where all residents within the city limits of Durango and a sample of residents within the county were asked about their interactions with bears, perceptions of management actions to reduce conflicts, and household actions to reduce conflict. The survey was mailed to a total of 6,566 individuals and we had a valid sample of 5,449 (1,117 surveys were invalid because they could not be delivered to the intended recipients). Responses are currently being electronically recorded. Survey responses will allow us to quantify current attitudes and perceptions about bear-human interactions, and how those perceptions have changed over time in association with a management effort such as wide-scale urban bear-proofing. Survey data will also identify the number of residents that have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. In addition to collecting data on human attitudes and perceptions, we are also collecting data on human behavior through direct observations. Using a random, stratified sampling design we are monitoring human compliance with wildlife ordinances at residences in treatment and control areas. Durango city ordinances specify that garbage can only be accessible after 6:00am on the morning of pickup; therefore, we define compliance as having garbage adequately secured so that bears cannot access it, either through appropriate use of a bear-resistant garbage container (e.g. latched lid) or by keeping garbage enclosed in a garage or shed until the morning of trash pick-up. Non-compliance is defined as allowing garbage to be accessible to bears by not latching a bear-resistant container or putting a regular garbage container at the curb the night before garbage pickup. �To assess compliance, we observe residences on the morning of garbage pick-up (5:00-6:00 am) between July and September. Compliance monitoring began in 2013 and will continue through 2016. In each treatment and control area, a sample of 40 randomly selected blocks are monitored (a total of 160 blocks) such that the number and type of cans (regular or bear-resistant) and compliance status are recorded. Each block is surveyed three times/summer. In the north experimental area, compliance is recorded for each parcel, but in the south experimental area, compliance is recorded per block because garbage containers are stored along alleys and cannot be easily tracked to parcel. Compliance data will be analyzed in conjunction with mail survey data, spatial covariates, and conflict activity to better understand how factors such as management actions and rates of bear-human interactions influence human behavior. This should help CPW tailor education and communication efforts to be more effective at achieving public compliance with wildlife ordinances. RESULTS AND DISCUSSION Objective 1: Determining the influence of urban environments on bear behavior and demography Between 5 July 2015 and 23 March 2016 (the 2015-2016 capture year), an additional 54 unique bears were marked during 136 bear captures (Table 1). To date on the project there have been 380 different individuals marked during 891 captures. Information about these captures is described below for summer 2015 and winter 2016. During summer 2015 we conducted 56 total bear captures; 29 captures were newly marked unique individuals and 27 were recaptures. Of the unique individuals captured, there were 7 females and 20 males (Table 1). We placed collars on 5 new adult females. Including bears that were already collared at the start of the summer, this resulted in 38 collars deployed by mid-September, the end of the summer capture season. The mean estimated age of bears ≥1 year-old on their initial capture date was 5.0 (7.0 for females and 4.6 for males), and the mean weight was 78.4 kg (73.5 kg for females and 79.6 kg for males). In total, we placed traps at 43 different locations and conducted 767 trap nights. Capture success peaked in late August and early September (Figure 1). Capture effort was slightly reduced from previous years, as we only needed to collar a few additional female bears to maintain our target sample size. Between January and March 2016, we visited the winter dens of 34 collared females. Although we had 38 female bears collared at the end of the trapping season in mid-September 2015, 4 bears lost their collars in September and October due to faulty ‘spacers’. In case we cannot recapture a bear, we always attach collars using a biodegradable spacer (designed to rot off >12 months post-deployment). Fabricon, our manufacuture, had given us a new spacer design this past year that was prematurely rotting off; the problem was subsequently rectified. Of those 34 dens that we visited, we processed bears in 30 dens; 2 dens were too dangerous to enter and 2 bears left the dens when we approached and never redenned during the field season (both were barren). We obtained reproductive information from all 34 collared bears (trail cameras were used on the dens that were too dangerous to enter): 7 were barren, 15 had yearlings (24 yearlings in total; 13 females, 10 males, and 1 unknown [confirmed on trail camera]), and 12 had newborn cubs (25 cubs in total; 10 females and 15 males). Of those females with newborn cubs, 3 bears had only 1 cub, 5 bears had twins, and 4 bears had triplets. We PIT and ear-tagged yearlings in the den, recorded information on weight, body size, body condition, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. We found that reproductive success, measured as the number of cubs/adult female ≥4 years old was 0.74 (SE=0.15) for winter 2016; previous fecundity rates have varied between 0.58 and 1.28. Annual cub survival (survival from newborn to 1 year) was 0.66 (SE=0.08; based on 33 cubs) which was the highest rate observed during the study. Previous annual values have varied from 0.42 to 0.54. Between 1 April and 30 March 2016 (based on when bears emerge from their dens each spring), annual survival of collared adult female bears was 0.88 (SE=0.05), which is close to the 5 year study average (range: 0.82 – 0.94). Four collared bears died during the year: 2 died in vehicle collisions, 1 was harvested and 1 died of unknown causes (the bear was estimated to be 16+ years old). Throughout the �study area, a total of 41 bears (marked and unmarked) died or were translocated. Sixteen bears were killed in vehicle collisions, 14 were legally harvested, 6 were lethally removed for nuisance behavior, 2 died of unknown causes, 2 were translocated, and 1 was electrocuted (cub climbing a power pole). Of those mortalities there were 9 adult males, 8 adult females, 6 subadult males, 2 subadult females, 2 male cubs, 2 female cubs, and 1 cub of unknown gender. Seventeen of those bears were unmarked and 13 had been marked by research personnel. Additionally, 2 marked bears died outside the study area; both were males that were legally harvested. To date, we have obtained >705,000 locations from GPS collars on 83 different adult female bears; 46 different bears provided 113,973 GPS locations during the summer of 2015 (Figure 2). Collared bears generally stayed within the vicinity of Durango; there were no extraordinary movements recorded this past year. The furthest a bear traveled to the north was up Hermosa Creek, to the east was Vallecito Reservoir, to the south was the Colorado-New Mexico border, and to the west was the La Plata River. The availability of natural mast foods was generally moderate in late summer and fall 2015 (Figure 3). Surveys demonstrated that the peak time for mast maturation of native crabapple was early August, serviceberry was between mid-August and mid-September (depending on transect location), chokecherry was early September, hawthorne was mid-September, gambel oak was mid-September, and pinyon pines was in mid- to late-September. Generally, the maturation of soft and hard mast occurred later in 2015 than in previous years. On transects that had key mast species, mast was present on about 25% of chokecherry, 15% of native crabapple, and 10% of oak and serviceberry shrubs, while approximately 30% of pinyon pines produced moderate to abundant cones. Hawthorne berries were only observed on 1 transect, but production was abundant on 80% of those plants. While mast from important species like oak and chokecherry were relatively low in 2015, mast from native crabapple and pinyon pines were quite high; pinyon pines had >3 times the mast that had been observed during any previous year of the study (Figure 3). Based on a study area size of 840km2, integrated spatially-explicit capture-mark-recapture models (IntSCR) estimated that female bear abundance in the vicinity of Durango was 156.6 (SE = 22.2) in 2011, 182.7 (SE = 35.7) in 2012, 83.7 (SE = 9.8) in 2013, and 76.2 (SE = 11) in 2014. Density estimates ranged from 0.09 (SE = 0.01) to 0.22 (SE = 0.04; Figure 4). Model averaged estimates of abundance and density based on standard SCR models (using only hair-snare data, no GPS data) were typically greater than the integrated-SCR estimates and were generally less precise (Figure 4). We identified the following models as the top-ranked model for each year, respectively; 2011: forest-only model, 2012: development-only model, 2013: development and elevation model, and 2014: elevation-only model. Predicted density surfaces derived from model-averaged estimates are provided in Figure 5. Abundance and density estimates were dramatically lower in 2013 and 2014, which followed a severe natural food failure in late summer/fall of 2012. Objective 2: Testing management strategies to reduce bear-human conflicts During summer 2015 we collected our third year of post-treatment data on the bear-proofing experiment. To ensure that >95% of residences in treatment areas had bear-resistant containers, we surveyed each treatment and control area during early-August to quantify the number and type of containers that were visible from the street (n = 1,341). We found that our efforts to “clean up” treatment areas were a success. Within the northern treatment area 98% of containers were bear-resistant and 2% were regular, and in the southern treatment area 95% were bear-resistant and 5% were regular. We will continue working with the City of Durango to replace regular containers with bear-resistant containers in treatment areas. Within the northern control area 40% of containers were bear-resistant and 60% were regular, and in the southern control area 24% were bear-resistant and 76% were regular. The proportions of bear-resistant containers within control areas have increased over the course of the study as residents have purchased them from the City. For example, when the study was initiated in 2011, only 28% of �residences in the northern control area had bear-resistant containers and only 9% had bear-resistant containers in the southern control area. Within treatment and control areas we observed 473 instances of bears accessing residential garbage during morning patrols, 115 conflicts in treatment areas and 358 in control areas (Figure 6). Of those conflicts, 47 were in the north treatment area, 103 were in the north control area, 33 were in the south treatment area and 290 were in the south control area. The number of trash-related conflicts in 2015 was higher than during the previous 3 years and peaked in late-August. Of those garbage containers accessed by bears, 76% were regular containers and 24% were bear-resistant containers. Bears accessed human food from bear-resistant containers when they were not properly latched or when trash was stored outside of the cans. We used kernel density functions (Worton 1987) with an href value (Gitzen et al. 2006) to spatially estimate the probability of trash-related bear conflicts before and after the distribution of bear resistant containers. We found that since the implementation of the bear-proofing experiment in 2013, trash conflicts have been significantly reduced in the northern experimental unit, and have shifted to the control area in the south experimental unit (Figure 7). While monitoring garbage-related conflicts, we issued 31 notices of violation in treatment areas. Objective 3: Identifying human behaviors and attitudes related to bear-human encounters We received a total of 2,432 valid mail survey responses from residents in Durango and La Plata county, which resulted in a 45% survey response rate. Of those surveys, 1,681 residents completed paper surveys and 751 submitted online responses. Survey data is currently being electronically recorded for future analysis. During summer 2015 we found that the average compliance of residents to wildlife ordinances was 59% in the north treatment area and 35% in the south treatment area. “Compliance” was defined as having a container that was properly locked (both latches clipped) or secured in a garage or shed before 6:00am. Across all sampling periods, compliance was higher in the northern experimental area than in the southern area. In the northern area, compliance increased from 45% in 2013 to 52% in 2014, to 59% in 2015. In the southern area compliance increased from 29% in 2013, to 34% in 2014, to 35% in 2015. When we surveyed residences to assess the proportion of containers that we labeled “non-compliant” (clips unlatched) but were devoid of any trash, we found that 4% met that description in the northern experimental area, and 26% in the southern experimental area (which has alleys). Future estimates of compliance will be corrected based on these numbers. SUMMARY AND FUTURE PLANS During FY15-16 we successfully coordinated field logistics and conducted several aspects of data collection (trapping and collaring bears, tracking human-related bear mortalities, collecting bear locations on the urban-wildland interface, assessing summer/fall mast availability, monitoring garbage-related bearhuman conflicts, conducting mail surveys, etc.) and initiated demographic analyses. Data collection will continue through winter 2017, and we will continue to analyze data and prepare research publications. In the coming year, we will be finalizing demographic estimates from the non-invasive genetic markrecapture data, and developing integrated population models which can be used to better track trends in bear population dynamics. In addition, we will be identifying factors affecting driving tolerance for black bears, compliance behaviors related to bear-proofing, and the effects of bear-proofing efforts on risk of conflict with bears. Once data collection is complete, we will then be able to conduct the remainder of the analyses needed to meet project goals. By addressing our research objectives we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and demography, understand the effect of bear-human interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. �LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. PLoS One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. 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Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflicts. Conservation Letters 1:136–145. Greenleaf, S.S., S.M. Matthews, R.G. Wright, J.J. Beecham, and H.M. Leithead. 2009. Food habitat of American black bears as a metric for direct management of human-bear conflict in Yosemite Valley, Yosemite National Park, California. Ursus 20:94-101. Hebblewhite, M., and E. Merrill. 2008. Modelling wildlife – human relationships for social species with mixed-effects resource selection models. Journal of Applied Ecology 45:834-844. Hostetler, J.A., J.W. McCown, E.P. Garrison, A.M Neils, M.A. Barrett, M.E. Sunquist, S.L. Simek, and �M.K. Oli. 2009. Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation 142:2456-2463. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. Johnson, D.H. 1980. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61:65-71. Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Johnson, H.E. 2012. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Federal Aid Annual Report, Colorado Division of Parks and Wildlife, Fort Collins, USA. Johnson, H.E., S.A. Lischka, J. Broderick, J. Apker, S. Breck, J. Beckmann, K. Wilson, and P. Dorsey. 2014. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Federal Aid Annual Report, Colorado Parks and Wildlife, Fort Collins, USA. Johnson, H.E., S.W. Breck, S. Baruch-Mordo, D.L. Lewis, C.W. Lackey, K.R. Wilson, J. Broderick, J.S. Mao, and J.P. Beckmann. 2015. Shifting perceptions of risk and reward: dynamic selection for human development by black bears in the western United States. Biological Conservation 187:164-172. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. McLoughlin, P.D., D.W. Morris, D. Fortin, E. Vander Wal, and A.L. Contasti. 2010. Considering ecological dynamics in resource selection functions. Journal of Animal Ecology 79:4-12. Mitchell, M.S., L.B. Pacifici, J.B. Grand, and R.A. Powell. 2009. Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8:169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Royle, J.A., R.B. Chandler, C.C. Sun, and A.K. Fuller. 2013. Integrating resource selection information with spatial capture-recapture. Methods in Ecology and Evolution 4:520-530. Sadeghpour, M.H., and T.F. Ginnett. 2011. Habitat selection by female American black bears in northern Wisconsin. Ursus 22:159-166. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83:340-354. Wagner, T., D.R. Diefenbach, S.A. Christensen, and A.S. Norton. 2011. Using multilevel models to quantify heterogeneity in resource selection. Journal of Wildlife Management 75:1788-1796. Wolfe, L.L., H.E. Johnson, M.C. Fisher, M.A. Sirochman, B. Kraft, and M.W. Miller. 2014. Use of �Acepromazine and Medetomidine in combination for sedation and handling of Rocky Mountain elk (Cervus elaphus nelsoni) and black bears (Ursus americanus). Journal of Wildlife Diseases 50:979-981. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Worton, B.J. 1987. A review of models of home range for animal movement. Ecological Modelling 38:277-298. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. Prepared by Heather E. Johnson, Wildlife Researcher �Table 1. Capture information for black bears that were newly marked in the vicinity of Durango, CO during summer 2015 and winter 2016 (collared adult females are identified with an “*”). Only information from the initial capture of each individual is shown (no recaptures). Bear ID B470 B469 B471 B472 B473 B474 B475 B476 B477 B478 B479 B480* B481* B482 B483* B484 B485 B486 B487 B488 B489 B490 B491* B492* B493 B514 B515 B531 B547 B532 B533 B534 B535 B536 B537 B538 B539 B540 B541 B542 B543 B544 B545 B546 Capture Date 7/15/2015 7/21/2015 7/28/2015 8/4/2015 8/10/2015 8/19/2015 8/21/2015 8/22/2015 8/25/2015 8/27/2015 8/27/2015 8/28/2015 8/29/2015 8/31/2015 8/31/2015 9/2/2015 9/3/2015 9/3/2015 9/9/2015 9/10/2015 9/11/2015 9/11/2015 9/12/2015 9/14/2015 9/16/2015 1/28/2016 1/28/2016 2/18/2016 3/15/2016 3/1/2016 3/1/2016 3/1/2016 3/3/2016 3/3/2016 3/4/2016 3/7/2016 3/8/2016 3/10/2016 3/10/2016 3/10/2016 3/11/2016 3/11/2016 3/14/206 3/14/2016 UMT Easting 243847 243861 243861 244219 242544 246530 239245 239992 246530 246530 243944 238871 246530 244608 242766 238209 239245 244608 249044 243215 249035 249065 248536 248536 248536 240613 240613 239003 236722 236340 236340 236340 252235 252235 256994 248987 249773 240429 240429 240429 247170 247170 257188 257188 UTM Northing 4122598 4122743 4122743 4122743 4128370 4135648 4128553 4128359 4135648 4135648 4134850 4126931 4135648 4125554 4133049 4130562 4128553 4125554 4131886 4128740 4131895 4133012 4139267 4139267 4139267 4125119 4125119 4137869 4133888 4132122 4132122 4132122 4138922 4138922 4140745 4140248 4129514 4104602 4104602 4104602 4134166 4134166 4134879 4134879 14 Sex Estimated Age M 3 M 12 M 2 M 3 M 2 M 5 M 8 M 10 M 10 M 1 M 2 F 5 F 8 M 4 F 4 M 10 M 1 M 1 M 1 M 2 M 3 M 1 F 6 F 12 M 10 M 1 F 1 M 1 F 1 M cub F cub F cub F cub M cub F cub M cub M cub M cub M cub M cub M cub M cub F cub F cub Weight (kg) 74.8 199.6 40.4 64.0 52.6 97.1 119.7 122.5 152.4 35.8 56.7 60.8 78.9 74.8 61.2 131.1 46.7 42.6 34.0 43.1 62.1 41.3 80.7 73.5 137.9 40.8 36.3 30.8 11.8 1.1 1.2 1.2 2.3 2.4 0.8 1.6 3.2 2.3 1.9 2.4 2.2 2.5 2.9 2.8 �B548 B549 B550 B551 B552 B553 B554 B555 B556 B557 3/16/2016 3/16/2016 3/17/2016 3/17/2016 3/17/2016 3/18/2016 3/18/2016 3/19/2016 3/19/2016 3/19/2016 245703 245703 252210 252210 252210 235030 235030 763412 763412 763412 4141023 4141023 4132171 4132171 4132171 4150681 4150681 4133906 4133906 4133906 M M F F M F M M M F cub cub cub cub cub cub cub cub cub cub 1.8 1.8 2.9 2.3 2.3 1.6 1.8 2.9 2.9 2.6 �Figure 1. Number of weekly black bear captures from May 15th through September 15th during the 2011 through 2015 summer trapping seasons. Note: trapping did not commence until July in 2014 and 2015. Number of Bear Captures 25 ..-·•·. 20 2011 2012 2013 2014 2015 j\ I \ I \. I 15 10 5 0 0 2 4 6 8 10 12 Week (May 15th through Sept 15th) 14 16 �Figure 2. GPS collar locations from 46 adult female black bears collected during 1 January – 31 December 2015 in the vicinity of Durango, Colorado (different colored clusters of points represent different individual bears). ~~ 0 ol - 00 0 00 0 0 0 ¢ () Q --~ ..o .....i • 0 0 ,.. • -.· ...... ..-1 . .•.••• ;'.- ~,-.. ,j'10 • • •• • • 6:·~ ' 0 0, r~,,, , . •e,:,,ffib!d ,U1tte ♦ O 0 0 0. (;,.J. i j ,., 0 N Q L JP1 8:.t*'O 1 A :D'l 1 Ill 0 3 6 12 Kilometers I sou t h111 n L!J " r,..-.h ,." n .. .. .., , t• •n• lrfbaX 17 �Figure 3. Mean abundance of soft and hard mast observed on vegetation transects from 2011-2015. Mast species included gamble oak, chokecherry, serviceberry, native crabapple and pinyon pine. Abundance reflects the proportion of plants observed with mast. Gamble Oak Choke Cherry g Service Berry g g -, I I I I I I I I lil lil lil lil -, I I .,. I I 8 -r BT .□ -'- 0 2011 2013 -'- 2013 2015 year Pinyon Native Crab Apple lil - -, -, I I .., o· i ~□~□~ I 2011 I lil - I 2013 year I I 2015 1s: o - I I I I I I -, I ~-□□B I 2011 I I 2013 year 18 I I 2015 I I I I I ~□ 2011 2013 year lil - I I I I I -, BT 0 year -, 0 • -'- 2011 .,. -'I g _ lil - - I I I I I 0 2015 g - 1s: - 1s: I I I I I I lil iI gi LJ I 0 1s: -, -, I I I I I I .,. 0 0 -, 2015 �Figure 4. Model averaged density estimates based on integrated spatially-explicit capture-mark-recapture models (solid lines; using both hair-snare and GPS collar data) and standard spatially-explicit capturemark-recapture models (dashed lines; using hair-snare data only) for female black bears near Durango, Colorado, USA from 2011 to 2014. Density 0.5 0.4 cu 0.3 , iii E z; 1/) , w 0.2 , , , ,, , ~ . . .. ,, ', ' • I I I ~ \ \ ~ \ '\ 'I 1 r· -, I 0 .1 l 0.0 2011 2012 2013 Year 19 201 �Figure 5. Predicted density surfaces for female black bears/km2 near Durango, Colorado, USA from 2011 to 2014. Surfaces were derived from year-specific model-averaged estimates. 2011 0 g ... ;"' .,.+ + + + ..."':::! i-T 230000 + Oura.,,go + 0 0 + + + + + + -+ • g + + + + 0 0 0 + ++ 8 "' "':;; 2012 + -1- + + + + + t J0,O.9.8 0 .7 ,6 80.4.5 0 ,3 8? 0,0 ... 0 8 "' "';; 250000 260000 230000 240000 2013 0 + ++ "';!;... ++ + + + + + + + + + 0 8 'il ;; + + + 80 + !!... + .. Durango + g t + + + + + l LO .9 80.7.8 - g:i.4 0 ,3 800,2, 1 ++ + + + "'...;!; - + - -+ 240000 260000 0 8 ..."'p 0 250000 - - 0 !!... 0 260000 + ++ ..+ '-8 0. 0.8 0.7 ++ + + + + + + + + + + + + + Ourangi + +I• ++ + + + + ++ + I 230000 250000 2014 0 8 1.0 80.7:t 80.4.5,6 0.3 80,0.? • g 0 :i1 ... + 240000 + + + + + ++ + + + + + + + + + + + + + + + +Dutaogo t + + + + + ..+ + + + + "' ;!; 230000 I I 240000 I I 250000 I 80.4:i 0,3 800,2, 1 I 260000 Figure 6. Garbage-related black bear-human conflicts observed during July through September 2015. Red lines indicate treatment areas and black lines indicate control areas. Green circles represent conflicts with �regular residential garbage containers and purple circles represent conflicts with wildlife-resistant containers. e;,.f ..~.JQ,'>- 1 .,.-f .~ ~ oj t:,.. ~, '?~-- 3 M ~.,e1\\~r,tJ~, ~'JJra-s, . ~ 'll x; ,...,, , I I Garbage Container Type o Residential Container 0 Wildlife Resistant Container f- StudyArea D Treatment □ control N ----- 0 0.25 0.5 Kilometers ,,,, A Sot.rce-;; Esri. H ERE,. Q8'L,✓ me. USGS, ln-iermap, increment P Corp., NRCAN. E.sri-Japan, METI, Esri China {Hong Kcr.g) , Esr i (Thailand). Mapmylndis. ® O~nSlle<!tMap conllil>llto,;; ano th~ GIS Use, Community Figure 7. ‘Hot spots’ of black-bear human trash conflicts pre- and post-distribution of bear-resistant trash containers in Durango, Colorado. All residents in treatment areas (outlined in red) were given bearresistant trash containers in 2013; residents in the control areas (outlined in black) did not receive bear- �resistant containers. Pre-treatment data were collected 2011-2012, and post-treatment data were collected 2013-2015. Hot spots were identified as those areas with the highest probabilites of conflict from kernal density functions of all observed trash conflicts. Pre-Treatment Post-Treatment Treatment Control Treatment Control �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2016 - June 30, 2017 Principal Investigator: Heather E. Johnson, heatherjohnson@usgs.gov Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Apker, K. Wilson, and P. Dorsey All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. Field data collection for this project was initiated spring 2011 and completed spring 2016. Several publications from this work are in various stages of analyses, peer-review and publication. Publications in progress and published abstracts are listed below: Publications in Progress: Laufenberg, J., H.E. Johnson, S. Breck, and P. Doherty. Using integrated population models to understand spatio-temporal dynamics in Colorado black bear populations. In Preparation for Ecological Applications. Kirby, R., H.E. Johnson, M.W. Alldredge, and J.N. Pauli. The tension between foraging and hibernation shapes biological aging in bears. In Preparation for Journal ofAnimal Ecology. Lischka, S., T. Teel, H. E. Johnson, S. Breck, and K. Crooks. Factors associated with public compliance of wildlife ordinances. In Preparation for Journal of Wildlife Management. Johnson, H.E., S.W. Breck, and D.L. Lewis. The effects of human development on black bear survival and fecundity. In Preparation for Journal ofAnimal Ecology. Lischka, S. T. Teel, H.E. Johnson, S. Breck, and K. Crooks. What drives real and perceived risk of human-wildlife conflict? In Preparation for Human Dimensions of Wildlife. 28 �Johnson, H.E., D.L. Lewis, S. Lischka, and S. W. Breck. Bear-resistant containers reduce human-black bear conflicts and improve public perceptions. Journal of Wildlife Management, In Press. Wibur, R.C., S.A. Lischka, J.R. Young and H.E. Johnson. 2017. Experience, attitudes and demographic factors influence the probability ofreporting human-black bear interactions. Wildlife Society Bulletin, In Press. Published Abstracts: Shifting perceptions of risk and reward: Dynamic selection for human development by black bears in the western United States H.E. Johnson1, S.W. Breck2, S. Baruch-Mordo3, D.L. Lewis4, C.W. Lackey5, K.R. Wilson4, J. Broderick6, J.S. Mao', J.P. Beckmann 8 1 Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA USDA-Wildlife Services, National Wildlife Research Center, 4101 La Porte Ave, Fort Collins, CO 80521, USA 3 The Nature Conservancy, 117 E Mountain Ave, Suite 20 I, Fort Collins, CO 80524, USA 4 Colorado State University, 1474 Campus Delivery, Fort Collins, CO 80523, USA 5Nevada Department of Wildlife, 2788 Esaw Street, Minden, NV 89423, USA 6 Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA 7 Colorado Parks and Wildlife, 0088 Wildlife Way, Glenwood Springs, CO 81601, USA 8 Wildlife Conservation Society, 301 North Willson Ave, Bozeman, MT 59715, USA 2 Citation: Johnson, H. E., Breck, S. W., Baruch-Mordo, S., Lewis, D. L., Lackey, C. W., Wilson, K. R., Broderick, J., Mao, J. S., & Beckmann, J. P. 2015. Shifting perceptions of risk and reward: Dynamic selection for human development by black bears in the western United States. Biological Conservation 178: 164-172. Abstract As landscapes across the globe experience increasing human development, it is critical to identify the behavioral responses of wildlife to this change given associated shifts in resource availability and risk from human activity. This is particularly important for large carnivores as their interactions with people are often a source of conflict, which can impede conservation efforts and require extensive management. To examine the adaptations of a large carnivore to benefits and risks associated with human development we investigated black bear behavior in three systems in the western United States. Our objectives were to (I) identify temporal patterns of selection for development within a year and across years based on natural food conditions, (2) compare spatial patterns of selection for development across systems, and (3) examine individual characteristics associated with increased selection for development. Using mixed effects resource selection models we found that bear selection for development was highly dynamic, varying as a function of changing environmental and physiological conditions. Bears increased their use of development in years when natural foods were scarce, throughout the summer-fall, as they aged, and as a function of gender, with males exhibiting greater use of development. While patterns were similar across systems, bears at sites with poorer quality habitat selected development more consistently than bears at sites with higher quality habitat. Black bears appear to use development largely for food subsidy, suggesting that conflicts with bears, and potentially other large carnivores, will increase when the physiological demand for resources outweighs risks associated with human activity. 29 �Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts Heather E. Johnson1, David L. Lewis1, Tana L. Verzuh1, Cody F. Wallace1, Rebecca M. Much1, Lyle K. Willmarth 1, Stewart W. Breck2 1 Colorado Parks and Wildlife, Durango CO, USA USDA National Wildlife Research Center, Fort Collins, CO, USA 2 Citation: Johnson, H. E., D. L. Lewis, T. L. Verzuh, C. F. Wallace, R. M. Much, L. K. Willmarth and S. W. Breck. 2017. Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts. Journal of Applied Ecology, DOI:10.l l l l/1365-2664.13021 Abstract 1. Expanding human development and climate change are dramatically altering habitat conditions for wildlife. While the initial response of wildlife to changing environmental conditions is typically a shift in behaviour, little is known about the effects of these stressors on hibernation behaviour, an important lifehistory trait that can subsequently affect animal physiology, demography, interspecific interactions and human-wildlife interactions. Given future trajectories of land use and climate change, it is important that wildlife professionals understand how animals that hibernate are adapting to altered landscape conditions so that management activities can be appropriately tailored. 2. We investigated the influence ofhuman development and weather on hibernation in black bears (Ursus americanus), a species of high management concern, whose behaviour is strongly tied to natural food availability, anthropogenic foods around development and variation in annual weather conditions. Using GPS collar data from 131 den events of adult female bears (n = 51 ), we employed fine-scale, animalspecific habitat information to evaluate the relative and cumulative influence of natural food availability, anthropogenic food and weather on the start, duration and end of hibernation. 3. We found that weather and food availability (both natural and human) additively shaped black bear hibernation behaviour. Of the habitat variables we examined, warmer temperatures were most strongly associated with denning chronology, reducing the duration of hibernation and expediting emergence in the spring. Bears appeared to respond to natural and anthropogenic foods similarly, as more natural foods, and greater use of human foods around development, both postponed hibernation in the fall and decreased its duration. 4. Synthesis and applications. Warmer temperatures and use of anthropogenic food subsides additively reduced black bear hibernation, suggesting that future changes in climate and land use may further alter bear behaviour and increase the length of their active season. We speculate that longer active periods for bears will result in subsequent increases in human-bear conflicts and human-caused bear mortalities. These metrics are commonly used by wildlife agencies to index trends in bear populations, but have the potential to be misleading when bear behaviour dynamically adapts to changing environmental conditions, and should be substituted with reliable demographic methods. 30 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July I, 2017-June 30, 2018 Principal Investigator: Heather E. Johnson, heatherjohnson@usgs.gov Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Apker, K. Wilson, and P. Dorsey Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the U.S. Department of Agriculture (USDA) National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that I) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. Field data collection for this project was initiated spring 2011 and completed spring 2016. Several publications from this work are in various stages of analyses, peer-review and publication. Publications in progress and abstracts from published manuscripts during the reporting period are listed below: Publications in Progress: Kirby, R., H.E. Johnson, M.W. Alldredge, and J.N. Pauli. The tension between foraging and hibernation shapes biological aging in bears. In Review with Scientific Reports. Lischka, S., T. Teel, H.E. Johnson, S. Breck, and K. Crooks. Factors associated with public compliance of wildlife ordinances. In Preparation for Journal of Wildlife Management. Johnson, H.E., S.W. Breck, and D.L. Lewis. The effects of human development on black bear survival and fecundity. In Preparation for Journal ofAnimal Ecology. Published Abstracts: Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts Heather E. Johnson', David L. Lewis', Tana L. Verzuh 1, Cody F. Wallace', Rebecca M. Much 1, Lyle K. Willmarth', Stewart W. Breck2 1 Colorado Parks and Wildlife, Durango CO, USA USDA National Wildlife Research Center, Fon Collins, CO, USA 2 29 �Citation: Johnson. H. E., D. L. Lewis, T. L. Vcrzuh, C. F. Wallace, R. M. Much, L. K. Willmarth and S. W. Breck. 2017. Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts. Journal of Applied Ecology, DOl:10.I I I l/1365-2664.13021 Abstract 1. Expanding human development and climate change are dramatically altering habitat conditions for wildlife. While the initial response of wildlife to changing environmental conditions is typically a shift in behaviour, little is known about the effects of these stressors on hibernation behaviour, an important lifehistory trait that can subsequently affect animal physiology, demography, interspecific interactions and human-wildlife interactions. Given future trajectories of land use and climate change, it is important that wildlife professionals understand how animals that hibernate are adapting to altered landscape conditions so that management activities can be appropriately tailored. 2. We investigated the influence of human development and weather on hibernation in black bears ( Ursus americanus), a species of high management concern, whose behaviour is strongly tied to natural food availability, anthropogenic foods around development and variation in annual weather conditions. Using GPS collar data from 131 den events of adult female bears (n = 51 ), we employed fine-scale, animalspecific habitat information to evaluate the relative and cumulative influence of natural food availability, anthropogenic food and weather on the start, duration and end of hibernation. 3. We found that weather and food availability (both natural and human) additively shaped black bear hibernation behaviour. Of the habitat variables we examined, warmer temperatures were most strongly associated with denning chronology, reducing the duration of hibernation and expediting emergence in the spring. Bears appeared to respond to natural and anthropogenic foods similarly, as more natural foods, and greater use of human foods around development, both postponed hibernation in the fall and decreased its duration. 4. Synthesis and applications. Warmer temperatures and use of anthropogenic food subsides additively reduced black bear hibernation, suggesting that future changes in climate and land use may further alter bear behaviour and increase the length of their active season. We speculate that longer active periods for bears will result in subsequent increases in human-bear conflicts and human-caused bear mortalities. These metrics are commonly used by wildlife agencies to index trends in bear populations, but have the potential to be misleading when bear behaviour dynamically adapts to changing environmental conditions, and should be substituted with reliable demographic methods. Experience, attitudes, and demographic factors influencing the probability of reporting human-black bear interactions Ryan C. Wilbert, Stacy A. Lischka 2, Jessica R. Young 1, Heather E. Johnson 3 'Western State Colorado University, 600 N. Adams St., Gunnison, CO 81231, USA 2Colorado Parks and Wildlife, 317 W. Prospect Ave., Fort Collins, CO 80526, USA 3Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA Citation: Wilber, R. C., S. A. Lischka, J. R. Young and H. E. Johnson. 2018. Experience, attitudes, and demographic factors influencing the probability of reporting human-black bear interactions. Wildlife Society Bulletin; DOI: 10.1002/wsb.854 ABSTRACT Interactions between people and American black bears (Ursus americanus) have been increasing throughout the United States, with negative interactions becoming a major management challenge for wildlife agencies. To monitor the number, location, and severity of these conflicts, wildlife agencies typically rely on voluntary public reports. Although trends in voluntary reports are commonly assumed to reflect actual trends in human-bear interactions, recent research suggests an individual's likelihood ofreporting interactions may be biased, influenced by attitudes toward the species and its management, previous experiences with wildlife, or demographic factors. During 2012, we used a mail survey of residents in the vicinity of Durango, Colorado, USA, (n = 1,667) to explore the relative importance of tolerance for black bears, satisfaction with bear management, personal experience with 30 �bears, and demographic traits as predictors of a resident's decision to report interactions to the authorities. We found that residents' experiences with bears were most important in predicting reporting behavior, followed closely by attitudes related to tolerance for bears, and satisfaction with management; demographic factors had relatively little influence. Respondents were more likely to report when they had seen black bears near their homes, had been threatened by bears, were intolerant of bears, dissatisfied with management, and were female. Although several variables in our analyses were influential in explaining reporting behavior, the overall predictive power of our models was low (R 2 = 0.17), suggesting future investigations of reporting behavior should include a broader set of covariates. Our results indicate that public reports represent a biased measure of human-bear interactions, and management agencies should either account for bias, or collect different types of interaction data, when assessing patterns of bear activity. Compounding effects of human development and a natural food shortage on a black bear population along a human development-wildland interface Jared S. Laufenberg0 , Heather E. Johnsonh, Paul F. Doherty Jr.a, Stewart W. Breckc 3 Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA bColorado Parks and Wildlife, 415 Turner Drive, Durango, CO 82303, USA cusDA-Wildlife Services, National Wildlife Research Center, 4101 La Porte Ave., Fort Collins, CO 80521, USA Citation: Laufenberg, J. S., H. E. Johnson, P. F. Doherty Jr., and S. W. Breck.2018. Compounding cfTects of human development and a natural food shortage on a black bear population along a human-wildland interfact. Biological Conservation 224:188-198; doi.org/l0.1016/j.biocon.2018.05.004 Abstract Human development and climate change are two stressors that threaten numerous wildlife populations, and their combined effects are likely to be most pronounced along the human development-wildland interface where changes in both natural and anthropogenic conditions interact to affect wildlife. To better understand the compounding influence of these stressors, we investigated the effects of a climate-induced natural food shortage on the dynamics of a black bear population in the vicinity of Durango, Colorado. We integrated 4 years of DNA based capture-mark-recapture data with OPS-based telemetry data to evaluate the combined effects of human development and the food shortage on the abundance, population growth rate, and spatial distribution offemale black bears. We documented a 57% decline in female bear abundance immediately following the natural food shortage coinciding with an increase in human-caused bear mortality (e.g., vehicle collisions, harvest and lethal removals) primarily in developed areas. We also detected a change in the spatial distribution of female bears with fewer bears occurring near human development in years immediately following the food shortage, likely as a consequence of high mortality near human infrastructure during the food shortage. Given expected future increases in human development and climate-induced food shortages, we expect that bear dynamics may be increasingly influenced by human-caused mortality, which will be difficult to detect with current management practices. To ensure long-term sustainability of bear populations, we recommend that wildlife agencies invest in monitoring programs that can accurately track bear populations, incorporate non-harvest humancaused mortality into management models, and work to reduce human-caused mortality, particularly in years with natural food shortages. Assessing ecological and social outcomes of a bear-proofing experiment Heather E. Johnson', David L. Lewis', Stacy A. Lischka2, Stewart W. Breck3 1 Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA 2Colorado Parks and Wildlife, 317 W. Prospect Ave., Fort Collins, CO 80526, USA 3 U. S. Department of Agriculture National Wildlife Research Center, 4101 LaPorte, Ave., Fort Collins, CO 80521, USA 31 �Citation: Johnson, M. E., D. L. Lewis, S. A. Lischka, and S. W. Breck. 2018. Assessing ecological and social outcomes ofa bearproofing experiment. Journal of Wildlife Management 82: 1102-1114; DOI: I 0.1002/jwmg.21472 ABSTRACT Human-black bear conflicts within urban environments have been increasing throughout North America, becoming a high priority management issue. The main factor influencing these conflicts is black bears foraging on anthropogenic foods within areas of human development, primarily on residential garbage. Wildlife professionals have advocated for increased bear-proofing measures to decrease the accessibility of garbage to bears, but little research has been conducted to empirically test the effectiveness of this approach for reducing conflicts. Between 2011 and 2016, we conducted a beforeafter-control-impact experiment in Durango, Colorado where we distributed 1,110 bear-resistant trash containers, enhanced education, and increased enforcement to residents in 2 treatment areas, and monitored 2 paired control areas. We examined the ecological and social outcomes of this experiment, assessing whether bear-resistant containers were effective at reducing conflicts; the level of public compliance (i.e., properly locking away garbage) needed to reduce conflicts; whether the effectiveness of bear-resistant containers increased over time; and if the distribution of bear-resistant containers changed residents' attitudes about bear management, support for ordinances that require bear-proofing, or perceptions of their future risk of garbage-related conflicts. After the bear-resistant containers were deployed, trash-related conflicts (i.e., observations of strewn trash) were 60% lower in treatment areas than control areas, resident compliance with local wildlife ordinances (properly locking away trash) was 39% higher in treatment areas than control areas, and the effectiveness of the new containers was immediate. Conflicts declined as resident compliance with wildlife ordinances increased to approximately 60% (by using a bear-resistant container or locking trash in a secure location), with minor additional declines in conflicts at higher levels of compliance. In addition to these ecological benefits, public mail surveys demonstrated that the deployment of bear-resistant containers was associated with increases in the perceived quality of bear management and support for ordinances that require bear-proofing, and declines in the perceived risk of future trash-related conflicts. Our results validate efforts by wildlife professionals and municipalities to reduce black bear access to human foods, and should encourage other entities of the merits of bear-proofing efforts for reducing human-bear conflicts and improving public attitudes about bears and their management. A conceptual model for the integration of social and ecological information to understand human-wildlife interactions Stacy A. Lischka"· h, Tara L. Teele, Heather E. Johnsond, Sarah E. Reedb,e, Stewart Breck', Andrew Don CarlosC, Kevin R. Crooks., Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA hDcpartment ofFish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA cDepartmcnt of Murnan Dimentions of Natural Resources, Colorado State University, Fort Collins, CO 80523, USA dResearch, Policy, and Planning Branch, Colorado Parks and Wildlife, 415 Turner Dr., Durango, CO 81303, USA eAmericas Program, Wildlife Conservation Society, 2300 Southern Blvd., Bronx, NY I 0460, USA i'National Wildlife Research Center, USDA Wildlife Services, 4101 Laporte Ave., Fort Collins, CO 80521, USA 3 Citation: Lischka, S. A., T. L. Teel, II. E. Johnson, S. E. Reed, S. Breck, A. D. Carlos, and K. R. Crooks. 2018. A conceptual model for the integration of social and ecological information to understand human-wildlife interactions. Biological Conservation 225:80-87: doi.org/l0.1016/j.biocon.2018.06.020 Abstract There is growing recognition that interdisciplinary approaches that account for both ecological and social processes are necessary to successfully address human-wildlife interactions. However, such approaches are hindered by challenges in aligning data types, communicating across disciplines, and applying social science information to conservation actions. To meet these challenges, we propose a conceptual model that adopts a social-ecological systems approach and integrates social and ecological theory to identify the 32 �multiple, nested levels of influence on both human and animal behavior. By accounting for a diverse array of influences and feedback mechanisms between social and ecological systems, this model fulfills a need for approaches that treat social and ecological processes with equal depth and facilitates a comprehensive understanding of the drivers of human and animal behaviors that perpetuate human-wildlife interactions. We apply this conceptual model to our work on human-black bear conflicts in Colorado, USA to demonstrate its utility. Using this example, we identify key lessons and offer guidance to researchers and conservation practitioners for applying integrated approaches to other human-wildlife systems. 33 � https://cpw.cvlcollections.org/files/original/79dd3c63e5f783d321c9deca307a6ef3.pdf e6a8b673ffb6692fa88b8b75b5230b7c PDF Text Text Colorado Division of Parks and Wildlife July 2010–June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0638 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Wolverine Conservation Assessing the efficacy of monitoring wolverine on a regional scale using occupancy and abundance estimation Period Covered: July 1, 2010 – June 30, 2011 Author: J. S. Ivan Personnel: M. Schwartz, USFS Rocky Mountain Research Station; M. Ellis, University of Montana All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The wolverine (Gulo gulo) has a circumpolar distribution comprised mostly of tundra and boreal forest. However, its current range extends southward in peninsular fashion to the Cascades and Rocky Mountains of the conterminous United States. Recently the U.S. Fish and Wildlife Service ruled that the North American wolverine in the contiguous U. S. is a candidate species for protection under the Endangered Species Act. Thus, there is considerable interest in identifying monitoring schemes capable of detecting declines in wolverine populations over a large scale. We used spatially explicit simulations in which wolverine were sampled on a virtual landscape to quantify our ability to detect declines using robust-design occupancy estimation. We systematically varied 1) the number of sample units surveyed, 2) the number of visits made to each unit in the sample, and 3) the rate of population decline and computed the power to detect declines under various scenarios. Initial results indicate that occupancy estimation may work well for detecting large declines (50% decline over 10 years), but power to detect less catastrophic declines was low. Approximately 100 sample units would need to be surveyed to have adequate power to detect a 50% decline over 10 years. A census (350 sample unit) would be needed to ensure decent power for detecting smaller declines. Power increases as number of visits to each sample unit increases from 2 to 3 per survey season, but making more than 3 visits does not increase power substantially. If confronted with design tradeoffs that lead to having a better detection probability vs. those that allow for more units to be sampled, it is better to increase detection probability and survey fewer units. Future simulations will address the power to detect increases in population size in addition to declines, and we will attempt to compare power to detect declines using abundance estimation with that obtained using occupancy estimation. 1 �WILDLIFE RESEARCH REPORT ASSESSING THE EFFICACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION. JACOB S. IVAN P. N. OBJECTIVE Assess power for detecting trends in wolverine population growth using occupancy and abundance estimation. SEGMENT OBJECTIVES 1. Build code to simulate realistic distribution and space use of wolverine on the landscape. 2. Build code to realistically simulate sampling the wolverine population using an occupancy framework. 3. Build code to analyze data “collected” via occupancy surveys. 4. Summarize results of 100s of iterations of randomly generated wolverine distributions and subsequent occupancy surveys; plot power to detect trends against various scenarios intended to reflect the range of conditions expected for both the sampling and process portions of the simulation. INTRODUCTION The wolverine (Gulo gulo) has a circumpolar distribution comprised mostly of tundra and boreal forest. However, its current range also extends southward in peninsular fashion to the Cascades and Rocky Mountains of the conterminous United States. Recently the U.S. Fish and Wildlife Service ruled that the North American wolverine in the contiguous U. S. was a candidate for protection under the Endangered Species Act (U.S. Fish and Wildlife Service 2010). Therefore, considerable interest exists in identifying monitoring schemes capable of detecting declines in wolverine populations over a large scale. Colorado Parks and Wildlife (CPW) has expressed interest in potentially pursuing a wolverine reintroduction, and monitoring program would be an integral part of such an effort. Additionally, with minor modifications, the simulation approach outlined here could be used to inform current Canada lynx (Lynx canadensis) monitoring efforts in Colorado. Thus, the work described here holds benefits for wolverine conservation in general as well as current and future CPW projects. Estimating abundance or occupancy are 2 means around which a monitoring scheme for wolverines could be constructed. Within these general approaches, there are numerous sampling methods that could be employed in the field. For instance, individual identification necessary for abundance estimation can be obtained from pelage patterns (Royle et al. 2011), scat samples (Flagstad et al. 2004, Ulizio et al. 2006), hair snags (Mulders et al. 2007), or a combination of methods (Magoun et al. 2011). Similarly, occupancy information can be obtained via aerial track surveys (Magoun et al. 2007, Gardner et al. 2010), remote cameras (R. Inman, Wildlife Conservation Society, unpublished data) or any genetic sampling technique. In all cases, the models used to estimate abundance and/or occupancy are the same; field methods only change the probability of detecting (and potentially identifying an individual(s) and the cost of obtaining those detections. Our aim was to use simulation to generically estimate power for detecting population declines of interest in the Northern Rockies. Simulations are spatially explicit, sampling occurs randomly and we are currently using robust design occupancy models to look at power. Here we report only on our initial simulations using occupancy estimation. 2 �METHODS Simulated landscape and wolverine distribution All simulations were programmed in R (R Core Development Team 2011), with calls to C++ (Stroustrup 1997), RMARK (Laake and Rexstad 2011), and MARK (White and Burnham 1999) as necessary. The simulation landscape included Idaho, western Montana, and northwest Wyoming (Figure 1). We overlaid this landscape with a raster dataset depicting “persistent spring snow” as this layer adequately captures the bioclimatic niche of wolverines (Copeland et al. 2010). Each 500-m pixel in the raster could take values 1 to 7 depending on the number of years from 2000-2006 that snow was present between April 24 and May 15 in that pixel. At the beginning of each iteration of the simulation, we randomly dispersed home range centers across the landscape subject to the following constraints based on wolverine ecology (Figure 2): 1) 2) 3) 4) Home range centers (points) were required to fall within the spring snow layer. Male home range centers were required to be >12.5 km apart. Female home range centers were required to be >8.5 km apart. Female home range centers could fall within male buffers, and transient males could fall within resident male or female buffers. Once home range centers were distributed, we temporarily assigned each animal a bivariate normal utilization distribution scaled to match UD estimates from the literature. To impart more realism in these UDs, we multiplied the bivariate normal kernel for each animal by the underlying spring snow layer, then divided each pixel value in the resulting product by the total of all values for that animal to recreate a probability distribution. Functionally this process produces a center-weighted UD in which mass is piled up over pixels with higher values of persistent spring snow. Each animal’s UD was different depending on the underlying configuration of spring snow. We began each simulation with 200 males, 200 females, and 100 transients for a total of 500 wolverines in the Northern Rockies landscape. Our simulated population size was based on available wolverine abundance information and expert opinion. We then simulated a 10%, 20%, or 50% decline in this population over 10 years by randomly removing individuals from the landscape at each time step. Simulated Sampling To simulate collection of occupancy data, we overlaid a sampling grid of 225km2-cells (n = 385 total cells) across the landscape. This cell size corresponds roughly to the home range size of female wolverine. At the beginning of each year, we computed the probability of at least 1 wolverine being available to sample in each cell on any given occasion for each cell in sampling grid: p(2: 1 wolverine present in cell J) = 1 - [(}c1 - p (individual; is present ))] where w = total number of wolverines in the simulation. For each visit within a given year, we drew a random uniform number (i.e., U(0,1)) and compared this number to the product: p(≥1 wolverine available)p(wolverine detected | available). If the random number was less than this product, wolverine were detected in that cell on that visit (occasion) and we entered a “1” in the encounter history for that cell-occasion. Otherwise, we entered a “0.” We proceeded to sample in this manner for each visit to each cell for each year of the simulation. This results in a vector of 0s and 1s (i.e., an encounter history) for each cell that is 10x in length where “x” is the number of visits made during each of 10 years. For each unique landscape and declining wolverine population, we created several different datasets using this general sampling process. We specified detection probability, p(wolverine detected | available), to be 3 �either 0.2 or 0.8 and specified the number of visit to each cell in a year to be 2, 3, 4, 5, 6, or 7. This results in 2 × 6 = 12 datasets for each simulated population decline. We also considered the situation in which surveys could only be accomplished every other year, which resulted in another 12 datasets in which no data were collected during even years. Analysis of simulated data For each simulated dataset we used the R (R Development Core Team 2011) package RMARK (Laake and Rexstad 2011) to construct a robust design occupancy model (MacKenzie et al. 2006, p. 183224) for fitting in program MARK(White and Burnham 1999). We allowed the occupancy (use) parameter (ψt) as well as colonization (γt) and extinction (εt) to vary through time in an unconstrained manner, but constrained detection probability (p) to be constant to reflect how it was simulated. This resulted in 10 estimates of probability of occupancy, or use, from each dataset. We then fit a random effects trend model to these 10 data points (also using the RMARK interface for MARK to account for covariance between estimates; Figure 4), and retained the slope of the trend line along with 95% confidence interval for that slope. When the 95% confidence interval for the slope of the trend line did not include zero, we considered a trend detected, otherwise a trend was not detected. The number of times a trend was detected out of the total simulations is an estimate of the power of the approach to identify the specified declines given the number of visits and detection probability specified. RESULTS As expected, initial results indicate that occupancy estimation should work well for detecting large declines (50% decline over 10 years, λ = 0.933) when detection probability is high (p = 0.8). Under these conditions, power was 80% when sampling 50 units, regardless of the number of visits, and approached 100% when sampling 100 units (Figure 5, “continuous sampling” panels). Power declined some, but was still respectable, even when detection probability was low (p = 0.2). In that case a power of 0.8 could be achieved with 4-6 visits to 100 sample units. Power to detect a 20% decline over 10 years (λ = 0.977) was diminished, however, especially when detection probability was low. For instance, in order to achieve 80% power, even with high detection probability, would require surveys in an estimated 300 sample units. There is no realistic chance of detecting minor declines (e.g., 10% over 10 years, λ = 0.989) using occupancy estimation (Figure 5). Not surprisingly, power declines when sampling occurs every other year rather than annually (Figure 5, “gap sampling” panels). However, if detection probability is high, adequate power (0.8) can be achieved to detect a 50% decline over 10 years if such a scheme is implemented in a reasonable number of sample units (100), even with as few as 2-3 visits. Ability to detect smaller declines (20% or 10% over 10 years) is poor regardless of detection probability, number of sample units or number of visits (Figure 5, “gap sampling” panels). Generally, we found that when detection probability is high, power increases as number of visits to each sample unit increases from 2 to 3 per survey season, but making more than 3 visits does not increase power substantially. However, when detection probability is low, gains can be realized by making more visits. This result re-confirms a well-documented phenomenon unique to occupancy estimation (MacKenzie et al. 2006, p. 168). Also, if confronted with design tradeoffs that lead to having a better detection probability vs. those that allow for more units to be sampled, it is always better to increase detection probability and survey fewer units. DISCUSSION Our initial simulations suggest that occupancy estimation may work well in a monitoring context if the survey techniques employed have relatively high detection probability and interest lies only in 4 �detecting sharp declines in the population. Future work on this project will focus on determining the effects of varying the size of sample units, using alternate starting population sizes, detecting increasing trends rather than decreasing, and making sure that detection and occupancy estimates match well with recently collected pilot data (R. Inman, unpublished data). 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Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 6 �Figure 1. Study area for simulation including montane regions of Idaho, western Montana, and northwest Wyoming. Black polygons indicate primary wolverine habitat defined as areas with snowcover between April 24 and May 15 during at least 1 year from 2000-2006. 7 �Females Resident Males Transient Males Figure 2. Example distribution of home range centers for male, female, and transient wolverines on the virtual landscape. Home range centers were required to fall within the spring snow layer, and intrasexual territorialty was enforced, except for transient individuals. The buffer around male home range centers was 12.5 km; female buffers were 8.5 km. 8 �Bivariate Normal UD x Persistent Snow Layer = Modified UD Figure 3. Simulated utilization distributions (UDs) for each individual were created by positioning a bivariate normal UD directly over each home range center (see Figure 2) then multiplying by the underlying persistent snow layer to form a modified, more realistic UD unique to each individual. 1 ] 0.8 V, ::I C 0 ·.g 0 .6 Q. ...0 Q. ] ....ro 0.4 E ·.;::; ~ 0 .2 0 1 2 3 4 5 6 7 8 9 10 Year Figure 4. Example output from a single simulation: estimates of occupancy over a 10-year period fitted with a linear random effects model. If the 95% confidence interval on the slope of the linear trend did not include zero, then we concluded that a trend had been detected. The percentage of iterations in which trends were detected out of the total iterations provided a measure of power. 9 �1 = 0.933 1 = 0.977 1 = 0.989 080 § 0.6C: ~ o 4(1) • II visits £ (J) - 2 - 3 C: 2 02- 0 © D E :::, ~ - 4 - 5 - G 7 (I) C: detP ~ o.su -0.2 (I) - - 0.8 2u m 0.60 0.4- 0.2- I I I I I I I 50 100 150 200 250 300 350 50 100 150 200 250 I I I I I 300 350 50 100 150 I I 200 250 I I 300 350 Number of grid eels sampled Figure 5. Power to detect population declines of 50% (λ=0.933), 20% (λ=0.977), and 10% (λ=0.989) using occupancy estimation. Curves represent 2 levels of detection probability (0.2 and 0.8) and varying number of visits annually to a sampled unit (2, 3, 4, 5, 6, 7). Top 3 panels depict estimates of power when occupancy surveys occur annually; bottom 3 panels depict power when surveys are conducted biannually. Note that the lowest power to detect a 50% decline with annual sampling is apparently realized with 7 visits to each sampling unit. This result is counterintuitive, and likely due to a coding error. It will be addressed in future simulations. 10 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0638 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Wolverine Conservation Assessing the efficacy of monitoring wolverine on a regional scale using occupancy and abundance estimation Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan* Personnel: M. Schwartz, USFS Rocky Mountain Research Station; M. Ellis, University of Montana *(J. S. Ivan was the sole Colorado Parks and Wildlife contributor for this work and is thus listed as “author.” However, the draft manuscript included here was a collaborative effort and all personnel listed are co-authors on the manuscript. M. Ellis is the first author.) All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Conservation biologists and resource managers are often faced with the task of designing monitoring programs for species that are rare, diffuse, or patchily distributed across large landscapes. These efforts are frequently very expensive and seldom can be conducted by one entity. It is essential that a power analysis is undertaken to ensure stated goals are feasible. We developed a spatial-based simulation, which accounts for natural history, habitat use, and sampling scheme, to investigate power for monitoring wolverines in two areas of the U.S. Rocky Mountains. The first area is a well-established metapopulation of wolverine in the northern Rocky Mountain states of Montana, Idaho, and Wyoming, where the current population is approximately 350 individuals and there are concerns of population decline. Based on current population size estimates and detection probabilities in the northern U.S. Rockies, most sampling schemes are likely to only detect large declines in population sizes (i.e. 50% decline over 10 years). In general, increasing the number of grids sampled or the per visit detection probability had a much greater effect on power than increasing the number of visits per year. For small populations, we found very low power to detect declines. The second analysis was a forecast of the effort required to monitor an increasing population in the southern U.S. Rockies, given recolonization or reintroduction. Occupancy-based methods can only produce enough power to detect population trends if populations are increasing dramatically (i.e. doubling or tripling in 10 years), regardless of the sampling effort. In sum, our approach provides a spatially based framework to evaluate monitoring protocols and objectives by explicitly incorporating the link between changes in population size and estimated occupancy, all while accounting for natural history of the species in question. These analyses were specific to wolverines, but our approach could easily be adapted to other species. 6 �WILDLIFE RESEARCH REPORT ASSESSING THE EFFICACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION. JACOB S. IVAN P. N. OBJECTIVE Assess power for detecting trends in wolverine population growth using occupancy. SEGMENT OBJECTIVES 1. Build code to simulate realistic distribution and space use of wolverine on the landscape. 2. Build code to realistically simulate sampling the wolverine population using an occupancy framework. 3. Build code to analyze data “collected” via occupancy surveys. 4. Summarize results of 1000s of iterations of randomly generated wolverine distributions and subsequent occupancy surveys; plot power to detect trends against various scenarios intended to reflect the range of conditions expected for both the sampling and process portions of the simulation. 5. Prepare manuscript for publication INTRODUCTION Wildlife populations worldwide have faced major population reductions in abundance and geographic range due to both natural and anthropogenic causes (Butchart et al. 2010, Hoffmann et al. 2010, Rands et al. 2010, Inman et al. 2011). Currently, many populations are facing multiple threats including habitat fragmentation and loss, climate change, direct and indirect exploitation, disease, invasive species, and the interaction among these threats (Primack 2006, Laurance et al. 2008, Povilitis and Suckling 2010). Responding to these major threats to wildlife and fish populations worldwide, many countries have adopted legislations aimed at affording protection to species of conservation concern (Hutchins et al. In Press, Waples et al. In Review). Two of the more powerful pieces of legislation are Canada’s Species at Risk Act (SARA) and the United States’ Endangered Species Act (ESA). These acts not only identify species at risk and aim to protect them from additional harm, but also stipulate and provide mechanisms for recovery. For example, in the United States approximately half of the annual budget spent on threatened and endangered species is designated for recovery (GAO 2005, Male and Bean 2005). However, determining when a species of concern is declining or subsequently recovering requires information about trend. The majority of studies that have examined trends in fish and wildlife were historically based in assessments of population abundance (Dennis et al. 1991, Bart et al. 2007, Foster et al. 2009, Broms et al. 2010). While estimates of abundance are important, other measures such as changes in genetic or demographic parameters or changes in geographic range size have been used to infer trend (Gaston 1991, Schwartz et al. 2007, Marucco et al. 2009, Broms et al. 2010). Recently, more attention has been placed on estimating changes in occupancy of a species geographic range (Joseph et al. 2006, MacKenzie et al. 2006). Occupancy estimation generally requires multiple surveys to a set of sample units, noting on each survey whether the species of interest was detected or not. Subsequently, these repeat-visit data are used to estimate the probability of detecting the species of interest if it was present, and then adjusting the raw presence-absence data in light of this probability to estimate the proportion of area occupied (MacKenzie 7 �et al. 2006). If occupancy estimation is conducted over multiple time intervals, trend in occupancy is obtained (Field et al. 2005, MacKenzie 2005, Marsh and Trenham 2008). Before launching an occupancy study, power analysis should be conducted to allocate monitoring effort efficiently (Field et al. 2005, MacKenzie 2005, Rhodes et al. 2006). Most studies base power analyses for occupancy estimation on detecting declines in occupancy over time; however, these simulations rarely consider spatial dynamics. Also, monitoring trends in occupancy is often used as a surrogate for trends in abundance, but this link is rarely evaluated (e.g. Field et al. 2005, Finley et al. 2005, Otto and Roloff 2011). Rhodes et al. (2006) and Rhodes and Jonzén (2011) modeled spatial and temporal correlations in population dynamics to account for spatial structure in populations and provide allocation recommendations in occupancy studies. They find, when spatial correlation is low and temporal correlation is high, it is most efficient to sample many sites infrequently. In the opposite situation, when spatial correlation among population dynamics is high and temporal correlation is low, they recommend sampling few sites often. Finally, when there is a decoupling of abundance and space, they suggest maximizing spatial replication (Rhodes and Jonzén 2011). Furthermore, if interest is in detecting declines in occupancy, they suggest sampling high quality habitats, whereas if the objective is to detect an increase, sampling intermediate-quality habitats is the best strategy. We extended their work by building a species-specific model of a population changing over time. We then sampled from this population using a multi-season occupancy framework to determine power to detect population trends under various scenarios. This approach allows us to optimally allocate scarce monitoring resources for designing an occupancy-based monitoring effort. Our model was designed to optimize sampling allocation for a large-scale wolverine monitoring effort. Wolverines are a Holarctic carnivore species known for their large home ranges, low densities, and occasional long distance movements (Lofroth and Krebs 2007, Squires et al. 2007, Inman et al. 2012). The species is currently under consideration for listing under the ESA (USFWS 2010) largely due to the fact that their numbers were greatly reduced (possibly eliminated) in the contiguous United States in the early 20th century. Wolverine populations have recolonized Idaho, Montana, Washington, and Wyoming and single male wolverines have recently dispersed to California and Colorado (Aubry et al. 2007, Moriarty et al. 2009). Yet, they are still absent from significant portions of their historical range and their current abundance in the contiguous United States is still likely to be at most 500 individuals. Recent research by Aubry et al. (2007) and Copeland et al. (2011) has shown that the historical distribution of wolverine was consistent with the distribution of persistent spring snow. Copeland et al. (2011) characterized persistent spring snow cover in the entire northern hemisphere based on a 21-day composite (24 April–15 May) of images from 2000-2006 at a 0.5km2 resolution using moderate resolution imaging spectroradiometer (MODIS) satellite images (Hall et al. 2006). They found that >99% of wolverine den sites and >89% year-round telemetry locations were located within areas that were classified as having persistent spring snow in at least one of the seven years for which data were available. Schwartz et al. (2009) demonstrated that wolverine gene flow was facilitated by areas with persistent spring snow compared to areas that were snow free. In this paper we use habitat (i.e., persistent spring snow), movement, and home range data to build a spatially based model for assessing the power for monitoring wolverine in their current range and in areas where they may eventually recolonize either naturally or through reintroduction. METHODS Study area There are two study areas for this project. The primary study area consists of the U.S. Rocky Mountains in northern and central Idaho, western Montana, and northwest Wyoming (“Northern 8 �Rockies”, Figure 1). The area is composed of individual mountain ranges each characterized by high alpine areas (maximum elevation 3900 m) and surrounded by wide areas of semiarid grasslands and irrigated agriculture (elevation ~1400 m). This area is known to be occupied by wolverines, with current population estimates ranging from 200-500 individuals (USFWS 2010). We removed from our analyses mountain ranges on the edge of this range, including the Wallowa Mountains of Eastern Oregon, the Bighorn Mountains of Eastern Montana and Wyoming, and the Bear River Range on the Idaho/Utah border; all three of which have no historical records of wolverines (Aubry et al. 2007) and do not contain continuous patches of persistent spring snow cover (Schwartz et al. 2009, Copeland et al. 2011). We allowed areas ‘used’ by simulated wolverines to extend up to 50 km into Alberta and British Columbia, Canada to account for continuous wolverine populations in the Northern Rockies, but excluded these areas from occupancy analyses. The second study area is the mountainous region of the Southern U.S. Rockies (“Southern Rockies”). This area is characterized by high, steep mountains (max elevation 4,400 m). As a result, there are strong gradients in physical attributes of the landscape, which lead to heavily dissected vegetation types. In the Southern Rockies, alpine and subalpine zones can be relatively narrow and give way to montane forests, montane shrublands, and semiarid grassland or sagebrush communities over relatively short distances. This area does not currently have a population of wolverines, although wolverines are thought to have occurred there historically (Aubry et al. 2007), and there seems to be adequate habitat, including persistent spring snow (Aubry et al. 2007, McKelvey et al. 2011). Areas of persistent spring snow are more patchily distributed in the Southern Rockies landscape, and separated from areas of persistent spring snow in the Northern U.S. Rockies by >200km. Most mountain ranges in this study area occur in Colorado, but we included the Medicine Bow and Sierra Madre ranges in southern Wyoming, as well as the southern San Juan Mountains in northern New Mexico. Individual Utilization Distributions We randomly selected points within areas of persistent spring snow (using Copeland et al. 2010) for the center of individual home ranges for adult female, adult male, and transient male wolverines. Among these three groups, locations were chosen independently to allow for overlapping home ranges (Copeland 1996, Inman et al. 2011); however, within each group, selection of home range centers was constrained to reflect territoriality. The buffer distances required between home ranges centers were at least 16 km for adult females, reflecting a 225 km2 home range, and at least 25.2 km for adult and transient males, reflecting 500 km2 home ranges (Banci 1994, Krebs et al. 2007, Schwartz et al. 2009). We also required that all home range centers were located in snow patches large enough to support at least one resident female wolverine (Krebs et al. 2007). Within each group (adult females, adult/resident males, adult/transient males), locations for home range centers were randomly selected in an iterative fashion until no additional individuals could be placed in the landscape or until the desired number of individuals was met. Once home range centers were established for a given simulated landscape, we assigned a bivariate normal utilization distribution for each individual. For resident females, we assumed that an individual spends 90% of her time within their 225 km2 home range (radius = 8.5 km). For resident males, we assumed individuals spend 90% of their time within their 12.6 km home range radius, but we allowed for larger sizes and greater overlap among transient male home ranges by assuming individuals only spend 70% of their time in the original 500 km2 home range. Each of these distributions produced a surface with decreasing probability of use with increasing distance from the home range center. To make these bivariate normal utilization distributions more realistic, we overlaid them on the persistent spring snow layer and multiplied the layers together. In the persistent spring snow layer, areas of non-snow were weighted as having 1/20 the probability of use compared to snow areas, based on resistance values found for models of genetic least cost paths (Schwartz et al. 2009). We standardized the product of the 9 �two layers to transform it back into a probability density. Thus, each individual utilization distribution takes a unique shape based on availability of snow. In this approach, it is possible for individuals to make short term, long distance movements during a given study period. The tails of the bivariate normal utilization distribution allow for a very small, but non-zero, probability of reaching any point on the landscape. In preliminary analyses, we tested for the effect of excluding these long distance movement events by cutting off the tails of the bivariate normal, such that the probability of an individual being more than 1-2 standard deviations away from its home range center was set to 0, compared to a situation with no limit on movement. Although allowing short-term, long-distance movements did affect the estimated occupancy of the landscape, the effect on power was minor. Occasional long-distance movements are possible in wolverine ecology, especially by males and transients (Moriarty et al. 2009). For territorial males and females, we would expect these movements to be less likely over the course of the relatively short survey period. Thus we based our power analyses on a ‘mixed’ scenario in which long distance movements were possible for transient males (i.e. no limit), resident males were allowed some larger movement events (limited to within 2 s.d. of home range center), and movements of females, which may have dens, were limited 1 sd from their home range center. Following the rules state above, our program, SPACE (Spatially-based Power Analyses for Conservation and Ecology), created 1000 surfaces for N=500 or N=200 individuals on the Northern Rockies landscape, reflecting high and low estimates of wolverine population size in the study area. We then simulated 10%, 20%, or 50% declines in our simulated populations over a decade (λ = 0.989, 0.977, 0.933) by randomly removing an appropriate number of individuals at each time step. We also simulated scenarios (nsim = 1000) for a hypothetical reintroduced or recolonizing population in the Southern Rockies. These populations were started with N=30 individuals then allowed to increase by 50%, 100%, or 200% over a decade (λ = 1.041, 1.072, 1.0116). We initiated all populations with a 2:1:2 ratio of females:resident males:transient males. Sampling To estimate occupancy, we sampled from our simulated landscapes during each time step or “year” of the simulation. We divided the study area into 225km2 sample units (cells), matching home range sizes for resident females, a strategy widely used for monitoring carnivores (e.g., Zielinski and Stauffer 1996). We excluded cells that did not overlap the persistent snow layer by ≥50%. This resulted in 388 cells for the main Northern Rockies study region, and 128 cells for the Southern Rockies. For each cell, the probability of at least one wolverine being present (hereafter, ‘probability of presence’ was Eqn 3): N   Ρ(# wolverines ≥ 1) j = 1 − Ρ( wolverines absent ) j = 1 − ∏ 1 − ∫∫ f i ( x, y ) dx dy    ( x , y )∈Ω i =1 j   where N is the number of wolverines in the simulated study area, fi(x,y) is the probability density function (i.e., utilization distribution) describing the use surface for the ith wolverine, and Ωj represents the area included in the jth grid. We approximated integral values by summing pixel values in the raster, assuming equal pixel areas. To construct a simulated encounter history (i.e., the data necessary for occupancy estimation) for cell j in year k, we assigned a 1 (present) or 0 (absent) for each visit by comparing a random draw from Uniform (0,1) with the probability of presence for that cell (draws less than the probability of presence resulted in a detection, and a 1 in the encounter history for that visit). Thus, a cell with simulated encounter history “010” indicates that 3 visits were made to the cell in a given year, and wolverines were 10 �detected on the second visit only. After initial construction, we used progressively reduced versions of the encounter histories to explore the effect of changes in parameters associated with sampling on power to detect population changes. For example, we omitted data from even numbered years (i.e., inserted “.” for each “0” or “1” of the omitted years) to examine the effect of sampling every other year; we tested the effects of smaller sample sizes by reducing the number of cells or visits included in the encounter histories; and we reduced the number of detections to simulate imperfect detection (See Table 1). To create encounter histories with lower detection probability, we randomly removed an appropriate proportion of 1s from each encounter history. Thus, to go from a detection probability of 1.0 to 0.8, we retained 0.8/1.0 = 80% of the 1s; for each 1 (wolverine detected) in a given encounter history, we conducted a random draw from uniform (0,1) and compared this draw against 0.8. We retained the 1 if the draw was ≤0.8, and changed it to a 0 (wolverine not detected) otherwise. Similarly, to go from encounter histories reflecting detection probability = 0.8 to detection probability = 0.2, we evaluated each 1 in a given history, retaining it if the random draw was ≤0.25 (0.2/0.8), changing it to 0 otherwise. We used these encounter histories to obtain annual estimates of occupancy and detection probability for each simulated landscape and parameter set. Note that the subject of our simulations is a mobile carnivore capable of moving freely between sample cells, and our simulation setup reflected this reality. Therefore, interpretation of estimated occupancy parameters was different than the usual context in which the status (occupied or not) of a given cell is assumed static over the course of a survey. Specifically, the estimate of occupancy (Ψ) generated under this context is the probability that any given cell is used rather than occupied, and any reference to Ψ or “occupancy” from here forward refers to probability of use. Furthermore, the estimate of detection probability generated in this context is actually the product of true detection probability (i.e., probability of detection given that the species of interest is present; this quantity is specified directly for any given simulation) and a landscape-wide probability that an individual is present and available for detection (i.e., probability of presence; see above). We refer to the detection probability estimated by the model as pest, and the actual detection probability specified for the simulations as psim, such that pest = psim × probability of presence. We used the R (R Development Core Team 2011) package RMark to input the encounter histories and construct models to fit in Program MARK (White and Burnham 1999). Specifically, we employed the ‘Robust Design Occupancy‘ data type (MacKenzie et al. 2006) in which colonization (γ) could vary through time but was constrained to be the complement of extinction (ε; i.e., changes in occupancy were considered random rather than Markovian or static) and detection probability (p) varied with time. This model structure is appropriate because: 1) we were interested primarily in the occupancy estimates themselves; we had no interest in modeling occupancy dynamics (colonization, extinction) explicitly, 2) the simulation specifications allowed “movement” in and out of adjacent cells, thus mimicking random changes in occupancy, and 3) “movement” between adjacent cells forced pest to be a function of probability of presence, which changed through time depending on the simulated landscape and birth/death of individuals. Thus, pest should have varied through time as well. We extracted the 10 occupancy estimates and the variance-covariance matrix for these estimates from each simulation, then used the variance components procedure in RMark to fit a linear random effects trend model to the estimates. A trend was ‘detected’ if the 95% confidence interval of the trend parameter (on the logit scale) from the random effects model excluded zero and was in the correct direction (e.g., <0 for declining trends; Tallmon et al. 2010). Thus, we computed the statistical power produced by a sampling scenario, i.e. the probability that we detect a significant trend given that there is a trend in the underlying data, as the percentage of simulations in which a trend was detected. For datasets in which we simulated sampling every other year, we fit models in which we fixed γ =γ , γ =γ4, etc. such that the product of these parameters were estimated, and we bridged years in which no data were collected to produce valid estimates of occupancy for those years where data were collected. 1 2 3 11 �In these scenarios, only 5 occupancy estimates were generated, and we fit random effects models to those 5 estimates. We repeated these analyses for each combination of population growth or decline, simulated detection probability (psim), number of visits, cell size, number of cells sampled, and annual or alternating year sampling schemes that were applied to the 1000 simulated landscapes of N = 30, 200, or 500 (Table 1). Where applicable, all sampling was cumulative to facilitate the most meaningful contrasts between levels of a parameter; for example, a sample of n = 50 cells would include the same cells as an n = 25 sample with 25 additional cells included. Similarly, an encounter history with 4 visits would include the same string of 0s and 1s as a 3-visit history, with one additional visit included. Our simulations were designed to be generalizations in that we do not attempt to define when a sampling season might begin, what the sampling mechanism was, or what constitutes a visit. Thus, these simulations could represent flying over selected cells in the study area to search for tracks in the snow, in which case a ‘visit’ is a single flight (Gardner et al. 2010), or they could reflect the use of hair snag devices in which a ‘visit’ is 1 month of continuous sampling (Magoun et al. 2011). We bracketed the sampling parameters (cell size, detection probability, visits) based on previous efforts described in the literature (Magoun et al. 2007, Gardner et al. 2010, Magoun et al. 2011). RESULTS Effects of home range parameters Due to the spacing rules among individuals that we used to reflect wolverine territoriality, the Northern Rockies landscape becomes saturated with approximately 850 individuals (420 ± 6 females, 219 ± 4 resident males, 219 ± 4 transient males; mean ± s.d. across 100 simulated landscapes). For N=800, the median probability of at least one wolverine per cell across the landscape was 0.47. This value reflects the availability of individuals on the landscape, yielding on average 280.4 cells in which wolverine were available for detection per sampling occasion across the 388 cells in the grid. As the population size decreased, the average probability of at least one wolverine per cell fell to 0.74 (212.4 detections per occasion) for N=500 and 0.05 (18.9 detections per occasion) for N=30 across simulations. With perfect detection associated with sampling (psim = 1), these cell-based probabilities for use translate to an estimated occupancy (Ψ) of 0.99±0.01 for the entire landscape for populations with N = 500 individuals and 0.06±0.01 for N = 30. Effects of population size and trend We investigated the upper limits of power with occupancy estimation by examining the ability to detect trends when the simulated detection probability was perfect (psim = 1) and with a large number of visits (5) to each unit. We focused these analyses on the U.S. Northern Rockies landscape and a quickly declining population (λ = 0.933). Even with perfect detection and intense sampling, detecting a large decline (50% over 10 years) in a large starting population (N = 500) with adequate power (>80% chance of detecting the trend) required a sample of 50 out of 388 cells (Figure 2). As the population size decreased, the amount of sampling needed to detect a 50% decline even under this ‘best case’ scenario with perfect detection increased dramatically. For example, when N=200, achieving 80% power required sampling approximately 75 to 150 cells. Detecting trends in small populations (N=30) was difficult; even if we included the entire grid (388 cells) in the sample and assumed perfect detection, we had less than 70% power to detect a trend. Regardless of the starting sample size, power to detect trends was lower for increasing populations compared to the decreasing scenarios described above. For example, to detect a 50% increase (λ = 1.041) with >80% confidence, the amount of the total sampling grid that would need to be included in the sample increased to ~25% of the grid (ncells≈60) for N=500 or ~ 50% (ncells≈125) for 12 �N=200. For N=30, sampling the entire grid, assuming perfect detection probability, and with an intense sampling effort (5 visits), we were able to detect a 50% increase in <40% of the simulations. With current population sizes (N=500) in the Northern Rockies, the ability to detect declines fell dramatically as the strength of the decline decreased (Figure 3). We found a reasonable chance ( ≥80%) of detecting a 50% decline in population size over a 10-year period, depending on the combination of sample size and detection probability. However, for a 10% decline in population size over the 10 year period, no amount of sampling could yield enough power to detect the trend. Similarly, even with a large sample size and high detection probability, a 20% decline was detected in <60% of the simulations (Figure 3). With either population increases or declines, sampling every other year substantially increased the number of cells and visits that would need to be sampled. Trade-offs in sampling methodology After the strength of the population decline or increase, the parameter that most influences power to detect change was the simulation detection probability (psim). In nearly all scenarios relatively large gains in power were realized when psim increased from 0.2 to 0.8. For instance, a monitoring scheme that called for 2 visits to each of 100 sample units would have ~25% chance of detecting a 50% decline over 10 years when psim = 0.2. Power for detecting that same decline under the same sampling regime increased to 80% when psim = 0.8 (Figure 3, upper left panel). By comparison, an increase in sample size from ncells = 50 to ncells = 300 resulted in only a doubling in power (25% to ~50%). In fact, when psim = 0.2, 80% power cannot be achieved even if the entire grid is sampled. Similar gains in power relative to simulation detection probability and sample were realized in other scenarios we simulated. The exceptions to this result were when the goal was to detect a 10% decline over 10 years or to detect a 20% decline when sampling was only conducted every other year. Both scenarios yield very low power and negligible improvement with increased psim or sample size (Figure 3, middle panels). The number of visits to each sample unit influenced power as well, although generally to a lesser degree than magnitude of population change, simulation detection probability, and sample size. Even with perfect simulation detection probability (psim = 1), the power to detect a trend increased with the number of visits at each grid cell due to the number of opportunities for an individual to be present. When simulation detection probability is high but imperfect (i.e., psim = 0.8), some gain in power could be realized by visiting each sampled cell 3 times vs. visiting them only twice (Figure 3, separation between the two lightest dotted lines). However, the gain realized for making 4 visits rather than 3 is small, and there is no appreciable difference in power for 4, 5, 6, or 7 visits under the scenarios we simulated. When simulated detection probability was low (i.e., psim = 0.2), potentially greater gains in power could be realized by making more visits, but it depends on the scenario (Figure 3, in some cases there is a moderate amount of separation in the solid lines, in other cases there is not). Note that at low detection probabilities (psim = 0.2), it is often inadvisable to make more visits to each sampled cell because such an approach actually decreases power (See discussion). Effect of Cell Size In order to achieve the threshold of 80% power to detect a 50% population decline, changing cell sizes in the grid had implications for both the number of cells and the total area that would need to be sampled. (Figure 5). Grids of 100km2 and 225km2 cells yielded similar power in terms of the percent of the grid that would need to be included in the sample, although the smaller cell size requires sampling more cells (i.e., the total grids were comprised of 887 100km2 cells versus 388 225km2 cells). Assuming 3 visits and high detection, getting 80% power for detecting a 50% decline required 120 cells (12,000km2) from the small grid versus 70 cells (15,750km2) for the medium sized grid. As the size of the grid increased, the power to detect trends in occupancy decreased. The 1000km2 grid produced very low power to detect population trends. In this case, the grid in the Northern Rockies comprised only 76 cells. Including every cell in the sample, with seven visits and high detection probability, we detected a 50% 13 �population decline in <20% of the runs. The phenomenon in which power is actually reduced with a high number of visits occurs for the 225km2 cell size at low psim, and for the 500km2 and 1000km2 size at high psim. Power to detect increases in small populations For small populations (N=30), power for detecting population trends was limited except for situations with large population increases and high detection probability (Figure 4). For the purposes of comparison, there was greater power for detecting trends in the Southern Rockies landscape than in the Northern Rockies, although the total sampling area in the Southern Rockies landscape is approximately only a third of the Northern Rockies. For both landscapes, a doubling of the population over ten years (λ = 1.072) could be detected with >80% power in scenarios where a large proportion of the landscape was included with relatively high capture probability. If simulation detection probability is low, then adequate power can only be achieved via sampling a large portion of the available landscape, and making a large number (≥5) of visits to each sampled cell. DISCUSSION Monitoring population trends over time is one of the most common goals for management of endangered species. Using a spatially explicit simulation for wolverine in the U.S. Rocky Mountains, we were able to test the ability of occupancy-based approaches to detect trends in population size under a range of monitoring scenarios. Even for large changes in population size (e.g. 50% declines over 10 years), we found that detecting population trends required large-scale, intensive sampling. In many scenarios, no amount of sampling could produce sufficient power to achieve monitoring goals. Our results highlight the importance of analyzing the statistical power of monitoring schemes and using approaches that incorporate the effect of sampling and power over the course of multiple steps in a monitoring protocol. In the case of the wolverine, work has commenced to evaluate the effectiveness of various approaches for detecting presence. These range from using fix-winged aircraft to find tracks in 100-km2 (Magoun et al. 2007) or 1000-km2 (Gardner et al. 2010) sampling cells, to using cameras at bait stations (Mulders et al. 2007, Magoun et al. 2011), to the use of non-invasive genetic sampling (Ulizio et al. 2006, Schwartz and Monfort 2008, Magoun et al. 2011). These efforts produce varying detection probabilities from 0.2 to 0.8 as bracketed in our simulations. However, matching estimates from field studies to our results, is not straightforward. It is important to note that detection probability estimated from pilot analysesis not the same as the psim input in our analyses. Due to the ‘mobile animal’ phenomenon, animals are capable of moving freely between sample cells and therefore can be detected in multiple cells during one sampling occasion. As a result, occupancy models cannot separate the effects of true detection probability (psim) and probability of presence (See Methods). Consequently, pest returned from pilot studies will be smaller than the detection probabilities used in our simulations (psim). For example, if pilot work indicates that pest = 0.2, power can be assumed to be slightly better than the curves shown for psim = 0.2 in our figures. The exact correspondence between pest and psim is dependent on cell size, population size, and home range size of the species in question. Thus, no rule of thumb holds for converting between the two. However, matching pest derived from pilot work to curves for psim can still be useful as it will result in conservative estimates of power, which would be a prudent way to design monitoring schemes. In the case of wolverines, pilot work specific to occupancy monitoring in the Northern Rockies has been carried out using camera stations (B. Inman, Wildlife Conservation Society, unpublished data) and hair snags (J. Waller, Glacier National Park, unpublished data) in 100-km2 sample units. Initial results from this work suggest pest is approximately 0.25 – 0.3, which in our simulations corresponded to 14 �psim ≈0.8 (i.e., pest = psim × probability of presence, where our mean probability of presence was 0.33; thus 0.25/0.33 ≈ 0.8). It’s important to note that the mean probability of presence depends on assumptions about the number of animals, the landscape, and home range configurations. Based on this estimate, and assuming 3-4 visits to each sample unit (sampling occurred during 3-4 months over winter for each pilot study), our research suggests that roughly 100-150 100-km2 cells would need to be sampled per year to attain an 80% probability of detecting a 50% decline in the Northern Rockies population (Figure 5). Thus, intensive sampling over a small area is unlikely to be a viable solution for detecting population trends. To accomplish anything meaningful, monitoring will require well-coordinated surveys across multiple entities and jurisdictions. Anything less than a large-scale, coordinated effort will likely be of limited or no value. The spatially explicit nature of our approach is especially important in linking changes in occupancy to population trends. Our results demonstrate that the underlying landscape can influence power to detect population changes. Specifically, in the comparison of power for populations with N=30 in the Northern versus Southern Rockies, power to detect trends in occupancy was similar in terms of percent of the total study area included in the sample, but very different in terms of the absolute area that needs to be sampled. For example, to detect a 3x increase of the N=30 populations with a 225km2 grid and >80% power required sampling ~20% of either landscape, which translates to sampling 16000km2 in the northern landscape versus 6000km2 in the south. Note, however, that the scenarios in this comparison, populations of N=30 in the Northern versus Southern U.S. Rockies, are intended to illustrate the effect of underlying landscape for a fixed population size. In reality, changing the size of a study area would generally also change the size of the population included, which we found to substantially affect power to detect trends. Previous recommendations for selecting cell sizes have been ad hoc. In some cases, our results indicate a relatively straightforward relationship between cell size and the number of cells needed or the total area sampled to achieve a given power threshold. Between a 100km2 grid and a 225km2 grid, with high detection probability, 80% power can be obtained either by sampling many small cells or fewer of the larger cells. However, by the time cell sizes reach 1000km2 for wolverine, the home ranges for multiple individuals are included in the cell, such that occupancy-based methods alone will only pick up changes once a much larger population decline has occurred. The point at which this switch occurs will likely depend on an interaction of the population size, landscape, home range sizes, and cell size. We also discovered a counterintuitive anomaly when computing power under scenarios in which cell size is equal to home range size, as is often advised for occupancy surveys of mobile carnivores. Specifically, we noted that when detection probability is low, power generally increases with increasing visits to each sample unit, but there is a point at which conducting more visits actually decreases power. We offer the following explanation for this phenomenon: When the cell size is equal to the home range size, the interplay between psim (i.e., 0.2) and availability is such that the pest is fairly low and makes a substantial upward adjustment on the count of cells (c) in which wolverines were actually detected. As we make more visits we detect wolverine use in cells that are seldom used, so c increases, but pest from the model does not (only the precision on pest improves). After about 6 or 7 visits c increases enough that the occupancy estimates resulting from upward adjustments on c approach 1.0. If estimates for all years are at or near 1.0, then there is no trend and we have no power to detect declines. This does not occur when cell sizes are small, because c will also be small, and any upward adjustments will not approach 1.0. A similar phenomenon occurs if cells are large and psim is high. In that case, most cells are used, and c will be large, especially with a large number of visits. Thus, even a small upward adjustment on c pushes the estimates to close to 1.0, which again makes detecting trends difficult. Thus, if maximizing power is a goal, increasing visits beyond a certain threshold may not be helpful depending on cell size, availability of animals, and the probability of detecting them given their presence. 15 �Our simulations currently do not include cost functions, so trade-offs between cell size, number of cells to sample, number of visits at each cell, and detection probability have been conducted absent an important real-world consideration. For instance, in a given situation, it may be easy to complete more visits to a site (e.g., leave camera sets out 1 more month), but extremely costly to improve capture probability (e.g, purchase an entire set of new cameras with improved functionality). Therefore, managers may opt to make more visits to improve power even though intensifying effort (visits) by a given percent may be inferior to improving detection probability by a similar percentage. Future simulation work should include cost as a factor in weighing the importance of the design factors we considered here. Most studies base power analyses for occupancy estimation solely on detecting various simulated declines in occupancy. Here, we employed a more mechanistic, spatially-based approach in which we simulated animals on a landscape, accounted for their natural history (territoriality, difference between sexes), tied their space use to key habitat features (persistent spring snow), and forced declines or increases in the real parameter of interest (abundance) to determine whether occupancy estimation could detect those changes. Thus, our approach is a direct test of the link between occupancy and abundance, providing a more meaningful examination of whether real-world changes of interest in population size can actually be detected using occupancy estimation. It also sets the stage for direct comparisons between occupancy and estimation of other metrics (e.g., abundance) that could potentially be used to monitor populations. That is, we have established the machinery necessary to simulate ‘truth’ (the configuration of animals on the landscape and changes in that configuration and/or number) and can then sample from that true population in various ways to simulate data gathering under different monitoring approaches. While results from this analysis can be used directly to guide the monitoring of wolverine or similar species, the largest contribution is the framework which can be used for making decisions about the design of a large scale monitoring effort provided information on movement and habitat use is available. Our goals were to establish this framework to encourage cost-effective decisions in designing monitoring programs and to inspire well-coordinated surveys across multiple entities and jurisdictions. Without such coordination our analyses convincingly show that most efforts for species like wolverine will be wasted. ACKNOWLEDGMENTS We thank Paul Lukacs, Gary White, and Larissa Bailey for providing invaluable technical advice, and Jeff Laake for implementing the “random occupancy dynamics” model into RMark so it could be used in this analysis. We thank the RMRS and a PECASE award to MKS for providing the initial funding for this effort. LITERATURE CITED Aubry, K. B., K. S. McKelvey, and J. P. Copeland. 2007. Distribution and broadscale habitat relations of the wolverine in the contiguous United States. Journal of Wildlife Management 71:2147–2158. Banci, V. 1994. Wolverine. Pages 99–122 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, L. J. Lyone, andW. J. Zielinski, editors. The scientific basis for conserving forest carnivores in the western United States. U.S. Forest Service, General Technical Report, RM-254. Bart, J., S. Brown, B. Harrington, and R. I. G. Morrison. 2007. Survey trends of North American shorebirds: Population declines or shifting distributions? . Journal of Avian Biology 38:73–82. 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Wildlife Society Bulletin 34:1326–1332. USFWS. 2010. Endangered and threatened wildlife and plants; 12-month finding on a petition to list the North American wolverine as endangered or threatened. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation for populations of marked animals. Bird Study 46:120–138. Zielinski, W. J., and H. B. Stauffer. 1996. Monitoring Martes Populations in California: Survey Design and Power Analysis. Ecological Applications 6:1254–1267. Prepared by ___________________________ Jacob S. Ivan 19 �Table 1. A summary of variables and ranges of those variables tested in our simulations using program SPACE. Variable Population size Population growth rates Limit on movement Simulated detection probability Number of cells sampled Number of visits Cell size Sampling Values tested N = 30, 200, 500 0.933, 1.041, 1.072, 1.116 N = 30 λ = 0.933, 1.041 N=200 0.933, 0.977, 0.989, 1.041 N=500 none; 1, 2 s.d. from home range center 0.2, 0.8 10 - 90% of grid 2-7 100, 225, 500, 1000 km2 Annual or alternating years (every other year) 20 �■ ■ •Northern U.S. Rockies ■ ■ ■ 1 ■ ·~·~·~·~•_j • tJt • ••• •:Southern Rocki s --..i=~·~··; ; ·~ ·~·~·~·~· :··············· ■ •• ■ ■ ■ .. ■ • • • • ■ ■ ■ ■ ■ ■ ■ ■ •• ( ■ 0 90 180 350 1<11ometers Figure 1. Map of study area. Distribution of persistent spring snow in the U.S. Rocky Mountains. Two separate landscapes were included in this study: one corresponding to fairly continuous habitat in the U.S. Northern Rockies, which is currently occupied by wolverines, and a second area in the Southern Rockies, where wolverines may recolonize or be reintroduced. 21 �No = 30 No = 200 No= 500 1.0 1 0.8 0.6 ~ II 0 "'C "' <,) <,) 2 0.4 0 'Q) .D 0.2 ~ E :, z # visits - 2 - 3 - 4 -5 vi Q) .£ 0 Q) - 6 - 7 ~0.8 -i Q) P s1m ts Q) - m0.6 1 0 0.4 ., 0.2 50 100 150 200 250 300 350 50 100 150 200 250 300 350 50 100 150 200 250 300 350 Number of cells sampled Figure 2. Effect of population size. Effect of population size on power to detect trends in the Northern U.S. Rockies. Assumes perfect detection associated with sampling for a 50% decline (λ = 0.933) or a 50% increase (λ = 1.041) from initial population sizes of 30, 200, and 500 individuals in the Northern Rockies. Simulated populations were sampled using a grid of 225km2 cells overlaid on the landscape. 22 �1.0 1 •0.977 t• 0.989 t• 1.0,11 --=~~~::::::::::::::=-11---....c..._='-'----r ----"---'"-=---i '-------'C......C.'-"----h r , 0.8 0.6 1 -= 0.933 r -I ,I "' Porn C: 2 0.4 - 0.2 -- • 0.8 # visits 2 - 3 0.4 0.2 0.0 ■ :a ,-, 7! fft Ai '--,---,--,c---,---.--,--,-' •-..--,--.---,--,--,--,-,--,--,---,--,c---,---,--r'--,--..--,--.---,--,--,-'-' 50 100 150 200 250 300 350 50 100 150 200 250 300 350 50 100 150 200 250 300 350 50 100 150 200 250 300 350 Number of cells sampled Figure 3. Power for detecting trends in the U.S. Northern Rockies. Results from a power analysis for assessing the feasibility of using occupancy to monitor trend in the population of wolverines in the U.S. Northern Rockies, assuming N=500 individuals and a cells size of 225km2. Results are parsed by population growth rate (λ = 0.933, 0.977, 0.989, 1.041 corresponding to 50%, 20%, and 10% declines over 10 years or a 50% increase), sampling effort (whether sampling occurred annually or every other year), detection probability for sampling, number of visits per year, and number of grid cells sampled from a total of 388. Power is based on number of detected trends in 1,000 simulated populations. 23 �"iij J!l "- = 0.933 '". '"..,,' '' rf> ~u ' ' Q) :i2 Q a:: 0 C: .c Q) Cl) :i 0 '"'"' ' .,, ' ,,, ,,, ., '" 0 C> 00 C> <.O ' 1\\\ \ I \\\ \ I \\\ \ I "<I" C> C> N C> O ~ ~ ~ 0 0 ""': 0 0 C"! N ! o....: O M 1,. =1.041 \\ I \ I . I\ I . ,u au • a 111 an , a 111 O V LO Ill <.0 ~ ~ 0 0 I I I "' = 1.072 ...,''' ' '' ., ' ' ' •'..,'\ ' •' ""': 0 sunJ JO JaqwnN/Sau1pap papaiaa 1,. =1.116 \ 0 0 \ ,,, ,,, ' ' •'' ' ,',, ' ,,, •"•".., C> N 0 00 \ \ \ ' ... .. ,, , .,...' , ........., . C> 0 0 C> 00 (!) 0 .. O"O Q) v a. 0 N 0 0 ."'.,,.,,'',' 0 0 N LO 0 ,,...,,'............. '... .,. ... .... (!) 0 v C> 0 0 ~ LO 0 C> N C> 0 cu Cl) E Q) (/) LO'+- oO MQ .0 ME .... Q) o::J ~z 24 Figure 4. Comparison of N=30 populations in Northern and Southern Rockies. Power to detect population trends for populations of 30 wolverines in U.S. Northern Rockies compared to the same population size in the Southern Rockies landscape. Ability to detect a population decline depends on population growth rate (λ = 0.933, 1.041, 1.072, 1.116 corresponding to a 50% decline over 10 years or 50%, 2-fold, or 3-fold increases in population size over 10 years) and sampling effort (detection probability for sampling, number of visits per year, number of grid cells sampled from a total of 388 for the Northern Rockies or 128 for Colorado). Power is based on number of detected trends from 1,000 simulated populations. r-.. �500km2 1000km2 ,,j 1.0 0.6 "'20.4 Psm C - 0 0.2 - • 0.8 -Fz Wii? 7 C # visits - 2 - 3 - 4 ~ .,3 -s -< - ,; "'~ -6 7 {/) "'3 '2. 5· co 0.2 0.0 200 400 600 800 50 100 150 200 250 300 350 40 60 80 100 120 140 10 20 30 40 50 60 70 Number of cells sampled Figure 5. Effect of cell size on power. Effect of grid size on power to detect population trends in the wolverine population (N=500) in the Northern Rockies using occupancy. As grid size changes, the total number of grid cells on the landscape also changes from 887 for a 100km2 grid, 388 for a 225 km2 grid, to 76 for a 1000km2 grid. 25 � https://cpw.cvlcollections.org/files/original/9167cc61f07a79259299692f05e84e2d.pdf c23b922d1d1b7b9689588c8b9d5dd8d4 PDF Text Text Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3002 : : : : : Division of Parks andWildlife Mammals Research Elk Conservation Evaluating solutions to reduce elk and mule deer damage on agricultural resources Federal Aid Project No. Period Covered: July 1, 2010 – June 30, 2011 Author: H.E. Johnson; project cooperators, P. Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Elk and mule deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments. This situation has generated significant challenges for wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage. One of the most severe areas of ungulate damage in Colorado has been the sunflower fields around Dove Creek. In this region, roughly a quarter of million dollars were annually paid to farmers between 2007 and 2009, and kill permits, distribution hunts and private-land-only doe hunts have been routinely distributed to farmers. Pressure from local growers over damage, and frustration from the general public over kill permits, have generated the need for the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) to evaluate other management options for reducing elk and deer crop depredation. As a result, CPW partnered with wildlife damage researchers from the National Wildlife Research Center to find science-based solutions for reducing crop damage. Collaboratively, our goals are to 1) examine elk and mule deer distribution patterns to design public hunting opportunities to reduce depredation, 2) experimentally test a suite of non-lethal fencing techniques to minimize crop damage, and 3) map and model landscape characteristics associated with damage to specify more effective site-specific management practices. During FY10-11 we developed a research proposal for internal review, generated project funding, and initiated the construction of experimental fence plots. Other project activities (i.e., monitoring the effectiveness of the different fence types for minimizing elk and deer damage, deploying telemetry collars, and mapping and modeling ungulate damage) will be initiated between FY11-12 and FY13-14. 123 �WILDLIFE RESEARCH REPORT EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on elk and mule deer around the agricultural fields of Dove Creek that 1) examines wild ungulate distribution patterns to design public hunting opportunities to reduce crop damage, 2) experimentally tests a suite of non-lethal fencing techniques to minimize crop depredation, and 3) maps and models landscape characteristics associated with damage to specify more effective site-specific management practices. SEGMENT OBJECTIVES 1. Work with staff from CPW and the National Wildlife Research Center to develop a research proposal for internal CPW peer review and funding solicitation. 2. Implement the construction of experimental fence plots on sunflower fields south of Dove Creek, Colorado, including electric fences, temporary winged fences, and chemical repellent fences. INTRODUCTION Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural areas (Austin et al. 1998, Wisdom and Cook 2000). In Colorado, elk and deer damage of crops accounts for a majority of the wildlife damage claims in the state. CPW is obligated to pay eligible wildlife damage claims on agricultural resources, and in recent years, the agency has spent approximately $500,000 on an annual basis to compensate growers. One of the most significant hotspots of elk and mule deer damage has been in the vicinity of Dove Creek, in conjunction with a recent switch in the agricultural crops that are locally grown. Farmers traditionally grew crops such as dry beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels, and highly desirable by wild ungulates. The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits, distribution hunts, and private land only doe hunts, however tolerance for these permits has been low among local sportsman and the general public. Given pressure by farmers over elk and deer crop damage, and frustration by sportsmen and the public over kill permits, CPW wildlife managers were interested in finding alternative management solutions for reducing sunflower depredation. As a result, CPW managers partnered with the CPW research branch and wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find non-lethal science-based solutions for reducing sunflower damage. Collaboratively, our goals are to 1) identify public hunting strategies that reduce crop damage, 2) test a suite of non-lethal fencing techniques to minimize crop depredation, and 3) map and model landscape characteristics associated with damage behavior to specify more effective management practices. Results from this study should enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments, a decrease in kill permits/distribution hunts, and an increase in public hunting opportunities. A detailed research proposal (Johnson et al. 2011) is provided in Appendix I. 124 �STUDY AREA The study will be conducted in the vicinity of Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties), which is comprised of a mixture of agricultural and public lands. The project will focus on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed with irrigated and dryland agricultural fields, ranging from 1,981 to 2,590 m in elevation. The mountain shrub habitat type is primarily composed of serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum) and black sagebrush (Seriphidium novum). Sunflower fields around Dove Creek are spatially juxtaposed to deep canyons that provide refugia for elk, exacerbating ungulate damage on agricultural crops (Fig. 1). METHODS During winter and spring of FY10-11 project collaborators developed a research proposal for internal CPW review and for funding solicitation (Appendix I). We successfully obtained project funds from the Rocky Mountain Elk Foundation, Colorado Statewide Habitat Partnership Program (HPP), Montelores HPP, National Wildlife Research Center and CPW Auction/Raffle Grants. Project grants and in-kind contributions totaled ~$279,000 which was sufficient to fully finance the project. Once project funding was solidified we initiated field logistics: the acquisition of field materials (fencing materials, elk and deer GPS collars, etc), contracting a fence installation company to construct experimental fence plots, hiring a temporary employee to monitor elk and deer damage on experimental fence plots, and scheduling a helicopter capture to deploy elk and deer collars. During FY10-11 we constructed the experimental fence plots based on a randomized block design. We identified 5 replicate fields that have repeatedly suffered high ungulate crop damage. Within each field we specified 4 10-acre plots, one for each experimental fence treatment type (polyrope fence, temporary winged fence, chemical repellent fence) and a control (see Appendix I for detailed descriptions of the fence types and study design). The 4 plots were randomly assigned within each field, such that each field (block) contained one replicate of all treatments (Gotelli and Ellison 2004). Other scheduled project activities will be initiated during FY11-12 such as monitoring the effectiveness of the different fence types for minimizing elk and deer damage, deploying telemetry collars, and mapping and modeling ungulate damage. SUMMARY AND FUTURE PLANS During FY10-11 we successfully developed a research proposal, generated project funding, and constructed the experimental fence plots for the first year of fieldwork. Starting in FY11-12 we will monitor the efficiency of the experimental fence plots in reducing elk and deer damage (July – Oct 2011) and deploy 40 GPS collars; 20 collars on adult female elk and 20 on adult female deer (Oct 2011). Experimental fence plots will also be monitored for elk and deer damage during FY12-13 (July-Oct). Elk and deer collars will collect data for 2 years and then detach in Sept 2013. Once collars are retrieved we will analyze and model elk and deer location data relative to agricultural and wildland habitat (FY13-14) 125 �LITERATURE CITED Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Johnson, H.E., P.Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. 2011. Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Study Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Wisdom, M.J., and J.G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P.R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 126 �Figure 1. Placement of experimental fence plots within the 5 replicate sunflower fields. Fields are located adjacent to wildland canyons. 127 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 Evaluating solutions to reduce elk and mule deer damage on agricultural resources A Research Proposal Submitted By Heather Johnson, Mammals Researcher, CPW Patt Dorsey, Area Wildlife Manager, CPW Matt Hammond, District Wildlife Manager, CPW Chad Bishop, Mammals Research Leader, CPW Kurt VerCauteren, Ungulate Damage and Disease Project Leader, National Wildlife Research Center David Walter, Post-Doctoral Researcher, National Wildlife Research Center Charles Anderson, Post-Doctoral Researcher, National Wildlife Research Center A. Need Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments (Austin et al. 1998, Wisdom and Cook 2000). Because crops are typically more digestible and contain higher levels of crude protein than native grasses and browse species, they are often preferentially selected and consumed by wild ungulates (Mould and Robbins 1981). Agricultural producers have reported more damage by elk and deer than any other wildlife species, and damage by deer alone has been projected to exceed 100 million dollars annually in the U.S. (Conover 2002). This situation has generated significant challenges for management agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage (Van Tassell et al. 1999, Wagner et al. 1997, Wilson et al. 2009, Hegel et al. 2009, Walter et al. 2010). Elk and deer crop depredation results from a combination of factors including the seasonal distribution and abundance of local forage resources, landscape configuration, and herd density patterns (Vecellio et al. 1994; Yoder 2002; Hegel et al. 2009). Damage can be highly variable within and among growing seasons, as local precipitation and temperatures will alter the availability of native forage and the motivation of ungulates to feed on agricultural fields (Walter et al. 2010). The juxtaposition of cropland and wildland has also been found to be particularly important in driving damage rates, as those cultivated fields closer to cover experience more damage (Nixon et al. 1989, Hegel et al. 2009). Additionally, studies have found that ungulate damage is often caused by only a subset of individuals in the population, depending on the spatial and social structuring of the herd. These observations have critical implications for wildlife managers, as 1) management practices may be differentially effective based on the variability of native forage and the spatial juxtaposition of other habitat features, and 2) management techniques targeted at specific animals may be more effective than implementing those techniques on the population at large (Blejwas et al. 2002, Hegel et al. 2009). As a result, an understanding of both the spatial configuration of seasonal resources and the resource selection patterns of different segments of local ungulate populations is important to successfully identify strategies to reduce elk and deer crop damage (Hegel et al. 2009). In Colorado, elk and deer damage of crops accounts for a majority of the wildlife damage claims in the state. The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) is obligated to pay eligible wildlife damage claims on agricultural resources, and in recent years, the agency has spent 128 �approximately $500,000 on an annual basis to compensate growers. One of the most significant hotspots of elk and mule deer damage has been in the vicinity of Dove Creek (Montezuma, San Miguel and Dolores Counties; Fig. 1), where roughly a quarter of million dollars was annually paid to farmers between 2007 and 2009. These extraordinary reimbursements have resulted from a recent switch in the agricultural crops that are locally grown. Farmers around Dove Creek traditionally grew crops such as dry beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels. In 2009 growers were paid approximately $.43/lb for organically grown sunflowers and $.28/lb for conventionally grown sunflowers. In that same year, dry land yields averaged 800 lbs/acre in the region. Elk and deer have demonstrated a strong affinity for sunflowers, causing up to 100% crop loss on certain fields, and resulting in high damage claims. Ungulate damage around Dove Creek is exacerbated by the spatial distribution of sunflower fields in relation to the surrounding wildlands (e.g., sagebrush-mixed shrublands and piñon-juniper woodlands). The region is fractured with deep canyons that provide refugia for elk, and fields adjacent to the canyon rims experience the greatest amount of depredation. With the substantial increase in biofuel production in the U.S. (World Resources Institute 2008), the agricultural conversion observed around Dove Creek will likely become common, as highpriced, crops replace more traditionally-grown, lower-cost crops (Walter et al. 2009). The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits (for males and females), distribution hunts, and private land only (PLO) doe hunts. In response to damage reports, CPW has been allocating these permits to local growers between June and October, with the intent of harvesting resident animals rather than migratory elk and deer. This management strategy has resulted in exceptionally high private land harvests. For example, in 2008, kill permits or distribution hunts were allocated on as many as 25 different fields, with approximately 300 deer and 30 elk harvested. On a single 140-acre sunflower field, 57 female mule deer were harvested, and still the annual damage claim for the field was approximately $40,000 in that year. The CPW, the Bureau of Land Management, Montelores Habitat Partnership Program (HPP) Committee, U.S. Forest Service and Rocky Mountain Elk Foundation have initiated several habitat enhancement projects in the region to draw elk and deer off of agricultural fields, but the benefits of these projects are expected to take several years to fully materialize. Although tolerance for elk and mule deer damage on sunflower crops is low among farmers, tolerance for kill permits and distribution hunts is also low among sportsmen, the general public and some farmers. A majority of the damage occurs during July and August when calves and fawns are still dependent on their mothers, reducing the acceptability of female hunts. Additionally, both elk and deer population numbers in the study area (DAUs D24 and E24) are below or near management objectives creating a paradox where CPW ultimately wants to increase ungulate herds, but reduce crop depredation. Finally, this region is popular with hunters, as large bulls and bucks have been harvested in recent years. Hunting is economically important to Dolores, Montezuma and San Miguel Counties, providing approximately 230 jobs and there is a strong desire to have increased public hunting opportunities. Pressure from local growers over damage, and frustration from the general public over kill permits, have generated the need for CPW to evaluate other management options for reducing elk and mule deer crop depredation. As a result, managers from CPW have partnered with wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find science-based solutions for reducing sunflower damage. Collaboratively, the goals of our study are to design public hunting opportunities to reduce crop damage, test a suite of non-lethal techniques to minimize crop depredation, and map and model landscape characteristics associated with damage behavior to specify more effective management practices. Results from this study should ultimately enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments and kill permits/distribution hunts, and an increase in public hunting opportunities and support from farmers and sportsmen. 129 �B. Objectives Objective 1: Examine the spatial structure, distribution, and migration patterns of local elk and mule deer around agricultural areas. This will enable CPW to design public hunting opportunities that better address crop damage while decreasing the need for kill permits/distribution hunts on private lands. Objective 2: Use treatment and control fields to experimentally test novel methods for reducing elk and mule deer damage to crops including a) the repellent “fence” Plantskydd, b) an electric polyrope fence, and c) a temporary “winged” fence. Objective 3: Map and model the spatial juxtaposition of crop fields, ungulate habitats, human infrastructure and topographic features to assess the predictors of elk and mule deer resource-use and damage. This will allow CPW to explicitly account for landscape configuration when working with landowners to identify best management strategies for reducing damage. C. Expected Results or Benefits Long-Term Benefits  Sustain healthy elk and mule deer populations on public and private lands where they do not cause agricultural damage and can provide quality hunting opportunities.  Reduce elk and deer game damage payments on sunflowers and other crops.  Allow sportsmen to harvest a greater proportion of elk and deer by strategically allocating the number of licenses, the location of those licenses, and the timing of hunts to target conflict animals, reducing the need for kill permits and distribution hunts.  The identification of alternative, non-lethal methods to prevent damage and reduce elk and deer use of crop fields.  The development of a modeling tool that can be used by CPW and growers to select the most appropriate management techniques to minimize damage based on field characteristics, ungulate distribution and landscape configuration.  The application of sound science to on-the-ground wildlife damage management. Short-Term Benefits  Gain knowledge about local elk and deer movements and distribution relative to the location of crop damage.  Help farmers with on-going damage by providing management tools and assistance.  Strengthen CPW’s relationship with the local community (farmers, sportsmen, and the general public) by reducing elk and deer crop damage and increasing public hunting opportunities. D. Approach Examining the spatial distribution of elk and mule deer: To understand ungulate movement patterns and more effectively address damage problems we will capture and collar 20 adult female elk and 20 adult female mule deer. Females cause a majority of the crop depredation and will provide the greatest insight into herd distributions. We will capture animals using a net-gun fired from a helicopter (Krausman et al. 1985), targeting elk and mule deer in the vicinity of high-damage crops. Captured animals will be fitted with global positioning system (GPS) collars, and locations of elk and mule deer will be remotely downloaded, collected once collars are retrieved, and 130 �recorded via ground or aerial telemetry. For both species, GPS collars will be programmed to collect ≥3 locations a day on a revolving schedule for 2 years. Elk and mule deer locations will be tracked yearround so that seasonal resource-use, migration patterns, and distributions can be clearly identified. Due to the elk herd’s close proximity to the Utah border, information on elk locations will be shared with Utah Division of Wildlife, as it is suspected that some animals travel across the Utah border during winter and forage on Colorado sunflower crops during summer. We will use elk and mule deer locations to map seasonal distributions and migration patterns, using kernel density analyses in ArcGIS mapping software (Worton 1989, Worton 1995). This will allow CPW to determine the best timing of special season hunts, kill permits and distribution hunts to avoid the private land harvest of migratory elk at the sportsman’s expense. CPW will also be able use distribution data to design public hunts that will target conflict elk and mule deer. For example, the Utah Division of Wildlife Resources is willing to consider special elk hunts south of Hwy 491 if we find that any or all of the resident elk herds (causing damage) spend portions of the year in Utah. Locations will also allow us to determine the amount of use of crop fields by elk and deer, and the proportion of animals using crop fields (whether it is only certain segments of the population, or the population at large). Testing 3 novel methods to reduce crop damage: In addition to implementing effective harvest practices to reduce crop damage, there is strong public interest in the application of nonlethal techniques for reducing ungulate depredation, generating a need for rigorous evaluation of such techniques by wildlife agencies. Most nonlethal techniques are designed to physically exclude offending animals or reduce the motivation of animals to access protected resources (Nolte 1999). We will test three exclusionary management tools for reducing elk and mule deer crop damage that can be easily implemented by farmers during the growing season: a repellent “fence”, a polyrope electric fence, and a temporary “winged” fence. To test the effectiveness of these methods we will initially select 5 replicate fields that have repeatedly suffered high ungulate crop damage (~160-200 acres), situated along the canyon rims. Within each of those fields we will identify 4 plots, one for each treatment type (repellent, polyrope fence, winged fence) and a control. The 4 plot types will be randomly assigned within each field, utilizing a randomized block study design where each field (block) contains one replicate of all treatments (Gotelli and Ellison 2004). This will allow us to statistically account for environmental heterogeneity, as we expect that damage will be variable among fields. Within the fields, study plots will be spaced as far apart as possible, to account for plot independence, and each plot will be 10 acres2 in size. All study plots will be placed along the agriculture/wildland boundary, where depredation is expected to be concentrated. Plots will be monitored from June through October during the growing seasons of 2011 and 2012. We will quantify the relative success of each nonlethal method by comparing crop depredation and ungulate incursion among treatment and control plots. Plantskydd - Repellents are nonlethal substances used to deter ungulates by decreasing a plant’s palatability, and have had mixed success in deterring ungulate foraging activity (Andelt et al. 1992; Baker et al. 1999). We will test the effectiveness of a relatively new product, Plantskydd, for reducing sunflower damage around Dove Creek. This product was developed in Sweden to reduce mammalian wildlife damage on commercial forests and works by emitting an odor that animals associate with predator activity, repelling the animal before it forages on crop plants. There is great interest in the success of such a technique as it can be easily applied to vegetation by ground and aerial spraying, used on both organic and conventionally grown sunflower crops, and is cost-effective for growers. That said, the effectiveness of Plantskydd has not been experimentally tested, only anecdotally reported. To test this method, the 5 Plantskydd treatment plots will be ground or aerial sprayed around field borders once germination has been begun. We will then re-apply Plantskydd to the treatment plots once/month throughout the 131 �sunflower growing season as the repellent may wash off or decompose over time and will need to be reapplied to new plant material. Polyrope electric fence – Fences provide an effective long-term, nonlethal tool for minimizing ungulate crop damage, providing both a physical and psychological barrier (Walter et al. 2010). While a permanent 2.4 meter woven-wire fence provides a true physical barrier to elk and deer, such a structure is can cost >$20/meter, prohibiting wide-spread use. We will test a novel design of a less expensive polyrope electric fence (approximately $8/meter), which acts primarily as psychological barrier based on learned behavioral, avoidance conditioning (Fig. 2; McKillop and Sibly 1988). These fences consist of conductive wires which are woven into synthetic electric “ropes” that are more durable, visible, and easy to install than traditional electric fences (Hygnstrom and Craven 1988, VerCauteren et al. 2006). Permanent fence posts are placed, and then the polyrope is strung between the posts to provide seasonal crop protection. Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives a powerful electric shock. Training can be expedited by baiting the fence wire with peanut butter or molasses to create a negative stimuli when making contact with the electric charge (Porter 1983, Hygnstrom and Craven 1988, Jordan and Richmond 1992, USDA National Wildlife Research Center, unpublished data). Polyrope fences have had success in reducing deer damage (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing elk damage. For the 5 randomly selected polyrope treatment plots, we will construct a fence that is approximately 1.8 meter tall with 5 strands to discourage passage under, through, or over the fence. We will treat the polyrope with a sweet attractant, designed to facilitate avoidance learning, using a minimum charge of 3,000 volts (Curtis et al. 1994). The polyrope will be powered by a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) which has a maximum pulse output of 3.0 joules and will be powered by a 12-volt deep-cycle battery with a solar-panel recharger. Temporary winged fence - For seasonal agricultural resources, such as sunflowers, temporary fences may provide reliable ungulate protection. Temporary fences are inexpensive, lightweight, and easy to erect and remove (Rosenberry et al. 2001, VerCauteren et al. 2006). Recently, investigators have been experimenting with a temporary “winged” fence made of polypropylene mesh. The fence is installed completely on one side of the target field, and partially installed on two other sides having 50-100 meter “wings” that extend perpendicular from the full fence line (see Fig. 3). This design was found to reduce deer damage in corn fields (Hildreth et al. In Review) while requiring limited costs for fence materials and installation. The effectiveness of such a fence has not yet been tested on elk or on deer with other crops than corn, but has potential to be an easily implemented management tool that could reduce crop depredation. On those plots randomly selected to be winged-fence treatments, we will install a fence with a similar design to Hildreth et al. (In Review), where the crop/wildland interface receives complete protection. For increased height and visual deterrence, the fence will be made of 2.4 meter tall orange barrier material (e.g., Guardian Orange Warning Barrier, Tenax Corporation, USA, Baltimore, Maryland). Monitoring the effectiveness of non-lethal treatments: All treatment and control plots will be monitored for 2 response variables: crop damage and elk/deer incursion. To measure damage to sunflower crops, we will monitor fields every 2 weeks between the time of germination and harvest. We will utilize the variable-area-transect (VAT) method for estimation of crop damage, which consists of both low and high intensity area monitoring (Engeman and Sterner 2002, Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). We will randomly place 4 low-intensity sampling areas within each study plot. In each low-intensity sampling area, we will inspect a row of sunflowers, counting the total number of sunflowers including those that are damaged and undamaged. If 5 cervid-damaged sunflowers are tallied in 100 meters, we will record the distance traveled and the total number of sunflowers. If 5 cervid-damaged sunflowers were not tallied in 100 meters, the observer will record the total number of sunflowers and any cervid-damaged sunflowers observed in that distance. We will calculate the percentage of sunflowers damaged per sampling area using the equation ~ damage per area = [number of damaged sunflowers/(number of 132 �damaged sunflowers+number of undamaged sunflowers)] x 100 (Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). We will also randomly locate 2 high-intensity sampling areas along every treatment and control plot edge to measure damage in proximity to places of high cervid pressure. Within the high-intensity sampling areas, we will use 5 VATs within each area. This will result in 12 total sampling areas (4 low intensity, 8 high intensity) per plot. Additionally, at the end of the season, we will evaluate game damage and year-end yields between treatment and control plots, the ultimate measure of success for each management technique. We will also quantify the level of incursion that occurs into treatment and control fields by elk and mule deer. To do this, we will use animal-activated cameras to record the number and frequency of elk and mule deer that pass through repellents or fence designs into sunflower fields. Cameras will be mounted on posts on the corners of treatment and control fields, capturing images of elk and mule deer inside and outside the field boundaries. Cameras will be positioned along field border that is closest to the agriculture/wildland boundary which is most likely to experience depredation. The Camera type is Moultrie® Game Spy Digital I-65 Infrared, 6.0 mega pixel (Moultry Products, LLC, Alabaster, AL, USA). Cameras can capture images up to 50 feet away, are weather-resistant with a built in solar panel and security box, and can wirelessly transmit images to a private web site for download by project personnel. Cameras will be activated for the duration of the growing season, and at the end of the season we will tally the number of elk and mule deer that penetrated each treatment and control plot boundary. Differences in elk and mule deer use of treatment/control fields will then be tested using repeated measures parametric statistics. This will allow us to evaluate the effectiveness of the repellent, polyrope fence, and winged fence in reducing crop depredation, relative to control plots. Mapping and modeling the spatial juxtaposition of ungulate damage within the landscape: To more effectively address ungulate damage problems we will use ArcGIS software to map crop fields, surrounding habitat types, human development, and topography. These variables have been important in explaining rates of ungulate depredation as damage tends to increase closer to cover, further from roads, and depending on crop palatability (Grover and Thompson 1986, Nixon et al. 1989, Hegel et al. 2009). Information about the location of a crop field in the context of the overall landscape will allow CPW to work with local growers to identify the most appropriate tools, and the timing of their implementation, to reduce damage. To meet this objective we will use satellite imagery to digitize agricultural fields and attribute those fields by crop type. We will use existing landcover, infrastructure, and digital elevation model (DEM) coverages to identify non-agricultural vegetation types, distance to human development, and topographic features (i.e. elevation, slope, aspect), respectively. We can then use landscape variables in conjunction with elk and mule deer location data (see Objective 1) to model the probability that a field is depredated by ungulates (Manly et al. 2002). This model can provide a powerful tool for CPW managers, as they will be able to predict the likelihood of depredation, depending on field location, the surrounding environment, and the crop type, and therefore help landowners specify crop choice or management actions that will reduce elk and deer damage. Timeline The study will take 3 years to complete. Non-lethal management techniques to reduce elk and deer damage will be implemented and monitored during the growing seasons of 2011 and 2012 (June – October), and the results of treatment/control plots will be analyzed thereafter. We will collar elk and deer during August or September 2011, and monitor animals for 2 years (the length of battery life of GPS collars). Once the GPS collars have been retrieved, we will analyze elk and deer location data. We will use that data to conduct damage mapping and modeling over the following ~6 months. 133 �Budget We obtained grants from the Colorado Statewide Habitat Partnership Program, the Montelores Committee Habitat Partnership Program, the Rocky Mountain Elk Foundation, the National Wildlife Research Center and from Colorado Division of Parks and Wildlife Auction/Raffle funds to conduct this work. Below is an itemized project budget. Item EQUIPMENT 20 Elk GPS Collars ($1,300 ea) Capture of Elk ($454 ea + per diem) 20 Deer GPS Collars ($2,500 ea) Capture of Mule Deer ($429 ea + per diem) Plantskydd Materials & Application Polyrope Materials & Installation Winged Fence Materials & Installation Animal-Activated Cameras (20 @ $750 ea) Camera Activation/Maintenance GIS Mapping Leased Truck (Jun-Oct/2 yrs) Gas for Leased Truck (Jun-Oct 2 yrs) PERSONNEL Technician for Monitoring (Jun-Oct/2 yrs) CPW Permanent Employee Salary (2 yrs) NWRC Post-doctoral Salary TOTAL Cost $26,000 $9,330 $50,000 $8,830 $16,710 $32,643 $19,042 $15,000 $4,180 $3,000 $12,000 $5,000 $25,583 $40,000 $12,000 $279,318 E. Location The study will be conducted in the vicinity of Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties), which is comprised of a mixture of agricultural and public lands. The project will focus on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed in irrigated and dryland agricultural areas. The mountain shrub habitat type, which occurs on both private and public lands, is composed primarily of serviceberry, antelope bitterbrush, mountain mahogany, squaw apple and black sagebrush. This habitat type is limited to elevations between 6,500 and 8,500 feet. F. Literature Cited Andelt, W.F., K.P. Burnham, and J.A. Manning. 1991. Relative effectiveness of repellents for reducing mule deer damage. Journal of Wildlife Management 55:341-347. Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Baker, D.L., W.F. Andelt, K.P. Burnham, and W.D. Sheppard. 1999. Effectiveness of hot sauce and Deer Away repellents for deterring elk browsing of aspen sprouts. Journal of Wildlife Management 63:1327-1336. Blejwas, K.M., B.J. Sacks, M.M. Jaeger, and D.R. McCullough. 2002. The effectiveness of selective removal of breeding coyotes in reducing sheep predation. Journal of Wildlife Management 66:451-462. Conover, M.R. 2002. Resolving human-wildlife conflicts: the science of wildlife damage management. CRC Press LLC, Boca Raton, Florida, USA. 134 �Curtis, P.D., M.J. Farigone, and M.E. Richmond. 1994. Preventing deer damage with barrier, electrical, and behavioral fencing systems. Proceedings of the Vertebrate Pest Control Conference 16:223227. Engeman, R.M., R.T. Sterner. 2002. A comparison of potential labor-saving sampling methods for assessing large mammal damage in corn. Crop Protection 21:101-105. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004a. Evaluation of a deer-activated bio-acoustic frightening device for reducing deer damage in cornfields. Wildlife Society Bulletin 32:515-523. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004b. Propane exploders and Electronic Guards were ineffective at reducing deer damage in cornfields. Wildlife Society Bulletin 32:524-531. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Grover, K.E., and M.J. Thompson. 1986. Factors influencing spring feeding site selection by elk in the Elkhorn Mountains, Montana. Journal of Wildlife Management 50:466-470. Hegel, T.M., C.C. Gates, and D. Eslinger. 2009. The geography of conflict between elk and agricultural values in the Cypress Hills, Canada. Journal of Environmental Management 90:222-235. Hildreth, A.M., S.E. Hygnstrom, E.E. Blankenship, and K.C. VerCauteren. In Review. Efficacy of a partial poly-mesh fence with wings to reduce deer damage to corn. Hygnstrom, S.E. and S.R. Craven. 1988. Electric fences and commercial repellents for reducing deer damage in cornfields. Wildlife Society Bulletin 16:291-296. Jordon, D.M., and M.E. Richmond. 1992. Effectiveness of a vertical 3-wire electric fence modified with attractants or repellents as a deer exclosure. Proceedings of the Eastern Wildlife Damage Control Conference 5:44-47. Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71–73. McKillop, I.G., and R.M. Sibly. 1988. Animal behaviour at electric fences and implications for management. Mammal Review 18:91-103. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. Mould, E.D., and C.T. Robbins. 1982. Digestive capabilities in elk compared to white-tailed deer. Journal of Wildlife Management 46:22-29. Nixon, C.M., L.P. Hansen, P.A. Brewer, J.E. Chelsvig. 1989. Ecology of white-tailed deer in an intensively farmed region of Illinois. Wildlife Monographs 118:1-77. Nolte, D. 1999. Behavioral approaches for limiting depredation by wild ungulates. Pages 60-69 in K.L. Launchbaugh, K.D. Sanders, and J.C. Mosley, editors. Grazing behavior of livestock and wildlife. Idahor Forest, Wildlife & Range Experimental Station Bulletin #70, University of Idaho, Moscow, USA. Porter, W.F. 1983. A baited electric fence for controlling deer damage to orchard seedlings. Wildlife Society Bulletin 11:325-329. Rosenberry, C.S., L.I. Muller, and M.C. Conner. 2001. Movable, deer-proof fencing. Wildlife Society Bulletin 29:754-757. Seamans, T.W., and K.C. VerCauteren. 2006. Evaluation of ElectroBraid™ fencing as a white-tailed deer barrier. Wildlife Society Bulletin 34:8-15. Van Tassell, L.W., C. Phillips, B. Yang. 1999. Depredation claim settlements in Wyoming. Wildlife Society Bulletin 25:886-894. Vecellio, G.M., R.H. Yahner, and G.L. Storm. 1994. Crop damage by deer at Gettysburg Park. Wildlife Society Bulletin 22:89-93. VerCauteren, K.C., M.J. Lavelle, and S. Hygnstrom. 2006. Fences and deer-damage management: a review of designs and efficacy. Wildlife Society Bulletin 34:191-200. 135 �Wagner, K.K., R.H. Schmidt, and M.R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W.D., M.J. Lavelle, J.W. Fischer, T.L. Johnson, S.E. Hygnstrom, and K.C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Walter, W.D., K.C. VerCauteren, J.M. Gilsdorf, and S.E. Hygnstrom. 2009. Crop, native vegetation, and biofuels: response of white-tailed deer to changing management priorities. Journal of Wildlife Management 73:339-344. World Resources Institute. 2008. WRI EarthTrends monthly update page. http://earthtrends.org/updates/node/180. Worton, B.J. 1989. Kernal methods for estimating the utilization distribution in home-range studies. Ecology 70:164-168. Worton, B.J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. 136 �Figure 1. Pink areas delineate zones of high ungulate-crop depredation around Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties; figure from a Montelores HPP report). DOVE CORT 137 �Figure 2. Photo of a polyrope electric fence constructed in a sunflower field south of Dove Creek, CO. Figure 3. Photo along a wing of a temporary fence constructed in a sunflower field south of Dove Creek, CO. 138 �Colorado Division of Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3002 : : : : Division of Parks andWildlife Mammals Research Elk Conservation Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Federal Aid Project No. Period Covered: July 1, 2011 – June 30, 2012 Author: H.E. Johnson; project cooperators, P. Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, C. Anderson, and J. Fischer. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Elk and mule deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments. This situation has generated significant challenges for wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage. One of the most severe areas of ungulate damage in Colorado has been the sunflower fields around Dove Creek. In this region, roughly a quarter of million dollars were annually paid to farmers between 2007 and 2009 for depredation caused by elk and deer. The main management tool used by Colorado Parks and Wildlife (CPW) to reduce ungulate damage has been the allocation of kill permits, distribution hunts, and private land only doe/cow hunts; however, tolerance for these permits has been low among local sportsman and the general public. Pressure from local sunflower growers over crop damage, and frustration from the general public over kill permits, generated the need for CPW to evaluate other management options for reducing elk and deer crop depredation. As a result, CPW partnered with wildlife damage researchers from the National Wildlife Research Center to find science-based solutions for reducing crop damage. Collaboratively, our goals are to 1) examine elk and deer distribution and migration patterns around agricultural areas to design public hunting opportunities to reduce depredation, 2) experimentally test a suite of non-lethal fencing techniques to minimize crop damage, and 3) map and model landscape characteristics associated with ungulate damage to specify more effective site-specific management techniques to minimize depredation. During FY11-12 we focused on collecting field data to meet project objectives. Specifically, we constructed experimental fence plots and monitored their effectiveness in reducing elk and deer damage (objective 2) and collared elk and deer to collect information about local movement and distribution patterns (data required to meet objectives 1 and 3). 100 �WILDLIFE RESEARCH REPORT EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on elk and mule deer around the agricultural fields of Dove Creek that 1) examines wild ungulate distribution patterns to design public hunting opportunities to reduce crop damage, 2) experimentally tests a suite of non-lethal fencing techniques to minimize crop depredation, and 3) maps and models landscape characteristics associated with damage to specify more effective site-specific management practices. SEGMENT OBJECTIVES 1. Implement the construction of experimental fence plots on sunflower fields in the vicinity of Dove Creek, including electric fences, temporary winged fences, and chemical repellent fences. 2. Collect field data on elk and deer damage to sunflowers in experimental fence plots throughout the growing season. 3. Capture and collar adult female elk and mule deer around agricultural fields in the vicinity of Dove Creek. INTRODUCTION Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural areas (Austin et al. 1998, Wisdom and Cook 2000). In Colorado, elk and deer crop depredation accounts for a majority of the wildlife damage claims in the state, and CPW is obligated to pay for those lost resources. In recent years, the agency has spent approximately $500,000 on an annual statewide basis to compensate farmers for ungulate depredation. This situation has generated significant challenges for CPW and other wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage (Van Tassell et al. 1999, Wagner et al. 1997, Hegel et al. 2009, Walter et al. 2010). Elk and deer crop depredation results from a combination of factors including the seasonal distribution and abundance of local forage resources, landscape configuration, and herd density patterns (Vecellio et al. 1994; Yoder 2002; Hegel et al. 2009). Damage can be highly variable within and among growing seasons, as local patterns in precipitation and temperature will alter the availability of native forage and the motivation of ungulates to feed on agricultural fields (Walter et al. 2010). The juxtaposition of cropland and wildland has also been found to be particularly important in driving damage rates, as those cultivated fields closer to cover experience more damage (Nixon et al. 1989, Hegel et al. 2009). Additionally, studies have found that ungulate damage is often caused by only a subset of individuals in the population, depending on the spatial and social structuring of the herd. These observations have critical implications for wildlife managers, as 1) management practices may be differentially effective based on the variability of native forage conditions and the spatial juxtaposition of other habitat features, and 2) management techniques targeted at specific animals may be more effective than implementing those techniques on the population at large (Blejwas et al. 2002, Hegel et al. 2009). As a result, it is important to understand both the spatial configuration of seasonal resources and the resource selection patterns of different segments of local ungulate populations to successfully identify strategies to reduce elk and deer crop damage (Hegel et al. 2009). 101 �One of the most significant hotspots of elk and mule deer depredation in Colorado has been in the vicinity of Dove Creek, where CPW paid roughly a quarter of million dollars annually to farmers between 2007 and 2009. High damage in this region has been primarily attributed to a recent switch in the crops that are locally grown. Farmers traditionally grew beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels, and a crop that is highly desirable to wild ungulates. In addition to this recent switch in crops, ungulate damage around Dove Creek is exacerbated by the spatial distribution of sunflower fields in relation to the surrounding wildlands (e.g., sagebrushmixed shrublands and piñon-juniper woodlands). The region is fractured with deep canyons that provide refugia for elk and deer, and fields adjacent to the canyon rims experience the greatest amount of depredation. With the substantial increase in biofuel production in the U.S. (World Resources Institute 2008), the agricultural conversion observed around Dove Creek will likely become common, as highpriced, crops replace more traditionally-grown, lower-cost crops (Walter et al. 2009). The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits, distribution hunts, and private land only (PLO) doe/cow hunts, however tolerance for these permits has been low among local sportsman and the general public. Permits are typically allocated to farmers between June and August, when calves and fawns are still dependent on their mothers, reducing the acceptability of female hunts. Additionally, local elk and deer populations are near or below management objectives, creating a paradox where CPW ultimately wants to increase ungulate herds, but reduce crop depredation. Hunting is also economically important around Dove Creek, so there is a strong desire in the local community to have increased public hunting opportunities and reduced PLO damage hunts. Given pressure by farmers over elk and deer sunflower damage, and frustration by sportsmen and the public over kill permits, CPW wildlife managers were interested in finding alternative solutions for reducing sunflower depredation. As a result, personnel from CPW partnered with wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find non-lethal science-based solutions for reducing sunflower depredation. Collaboratively, we developed a proposal to 1) identify public hunting strategies that reduce crop damage, 2) test a suite of non-lethal fencing techniques to minimize crop depredation, and 3) map and model landscape characteristics associated with damage behavior to specify more effective management practices (Johnson et al. 2011). Results from this study should enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments, a decrease in kill permits/distribution hunts, and an increase in public hunting opportunities. In FY11-12 we focused on collecting field data to meet project objectives. Specifically, we constructed experimental fence plots and monitored their effectiveness in reducing elk and deer damage (objective 2) and collared elk and deer to collect information about local movement and distribution patterns (data required to meet objectives 1 and 3). STUDY AREA The area around Dove Creek, Colorado (Montezuma, San Miguel and Dolores counties) is comprised of a mixture of agricultural and public lands. This project focuses on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed with irrigated and dryland agricultural fields, ranging from 1,981 to 2,590 m in elevation. The mountain shrub habitat type is primarily composed of serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum) and black sagebrush (Seriphidium novum). 102 �Sunflower fields around Dove Creek are spatially juxtaposed to deep canyons that provide refugia for elk, exacerbating ungulate damage on agricultural crops (Figure 1). METHODS Testing the effectiveness of different fence types for reducing ungulate damage During FY11-12 we constructed experimental fence plots to test the effectiveness of three nonlethal exclusionary fences for reducing elk and deer damage: a polyrope electric fence, a temporary “winged” fence, and an organic repellent “fence.” These differ from traditional exclusionary fencing for elk and deer, in that they are cheaper to construct and can be easily moved among fields over time, as farmers grow sunflowers on a rotational basis. Each fence type is described below: • Polyrope electric fence – The polyrope electric fence acts primarily as psychological barrier for elk and deer based on learned behavioral, avoidance conditioning (McKillop and Sibly 1988). The fences consists of conductive wires which are woven into synthetic electric “ropes” that are more durable, visible, and easy to install than traditional electric fences (Figure 2; Hygnstrom and Craven 1988, VerCauteren et al. 2006). Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives a powerful electric shock. Polyrope fences have had success in reducing deer damage (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing elk damage. For the 5 randomly selected polyrope treatment plots, we constructed a fence approximately 1.8 meter tall with 5 strands to discourage passage under, through, or over the fence. The polyrope was powered by a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) using a 12-volt deep-cycle battery with a solar-panel recharger. • Temporary winged fence - For seasonal agricultural resources, such as sunflowers, temporary fences may be sufficient to provide protection from wild ungulates and are inexpensive, lightweight, and easy to erect and remove (Rosenberry et al. 2001, VerCauteren et al. 2006). We tested the effectiveness of a temporary “winged” fence made of polypropylene mesh (Figure 3). The fence is installed completely on one side of the target field, and partially installed on two other sides having 50-100 meter “wings” that extend perpendicular from the full fence line. This design was found to reduce deer damage in corn fields (Hildreth et al. In Review) but has not yet been tested on elk or on deer with crops other than corn. On those plots receiving winged-fence treatments, we installed the fence such that the side receiving complete protection was along the crop/wildland interface. The fence was made of 2.4 meter tall black barrier material (e.g., Guardian Warning Barrier, Tenax Corporation, USA, Baltimore, Maryland) for increased height and visual deterrence. • Plantskydd - Repellents are nonlethal substances that can be used to deter ungulates by decreasing a plant’s palatability (Walter et al. 2010). We will test the effectiveness of a relatively new product, Plantskydd, for reducing sunflower damage around Dove Creek. This product was developed in Sweden to decrease mammalian wildlife damage on commercial forests. It works by emitting an odor that animals associate with predator activity, repelling the animal before it forages on crop plants. There is great interest in the success of this product as it can be easily applied to vegetation by ground and aerial spraying, used on both organic and conventionally grown sunflowers, and is cost-effective for growers. That said, the effectiveness of Plantskydd has not been experimentally tested, only anecdotally reported. To test this method, 5 Plantskydd treatment plots were ground sprayed in a ~20 ft swath around the plot perimeters after germination had begun (as directed by the manufacturer). Plantskydd was reapplied to treatment plots once/month throughout the growing season as the repellent may wash off or decompose over time and needs to be reapplied to new plant material. We constructed the fence plots based on a randomized block design. We identified 5 different sunflower fields to serve as replicates (~160-200 acres in size); all fields had previously suffered high 103 �ungulate crop damage. Within each field we specified 4 10-acre plots, one for each experimental fence treatment type (polyrope fence, temporary winged fence, chemical repellent fence) and a control (Figure 1). The 4 plots were randomly assigned within each field, such that each field (block) contained one replicate of all treatments (Gotelli and Ellison 2004). This design allows us to statistically account for environmental heterogeneity, as we expect that damage will be variable among fields. Within the fields, study plots were spaced as far apart as possible, to account for plot independence. Plots were also placed along the agriculture/wildland boundary, where depredation is expected to be concentrated. Fences were installed by Dillon Fencing (Naturita, CO) during the end of June and early July 2011, after sunflowers had germinated. The 20 plots (experimental and control plots) were delineated were monitored from mid-July through mid-October (time of harvest). Treatment and control plots were examined for 2 key response variables: elk/deer incursion and sunflower damage. We quantified incursion by elk and deer into our plots on a biweekly basis, assessing the permeability of the different fence types. To do this, an observer walked the perimeter of each plot, counting the number of elk and deer tracks entering and exiting the field. Tracks were raked out between observations so they were not double-counted. Differences in the number of elk and mule deer tracks into treatment/control fields were tested using repeated measures ANOVA. In addition to quantifying incursion into experimental plots, we also quantified direct damage to sunflower plants. We assessed damage every 2 weeks using the variable-area-transect (VAT) method for estimation of crop depredation (Engeman and Sterner 2002, Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). In each plot, we conducted 15 VAT transects at random starting points, inspecting a row of sunflowers, and counting the total number of sunflowers that were damaged and undamaged. If 5 cervid-damaged sunflowers were tallied in 100 meters, we recorded the distance traveled and the total number of sunflowers on the transect. If 5 cervid-damaged sunflowers were not tallied in 100 meters, the observer recorded the total number of sunflowers and any cervid-damaged sunflowers observed in that distance. We calculated the percentage of sunflowers damaged per transect using the equation ~ damage = (number of damaged sunflowers) / (number of damaged sunflowers+number of undamaged sunflowers) (Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). Additionally, at the end of the season, we had an agricultural assessor evaluate game damage and year-end yields between treatment and control plots, the ultimate measure of success for each management technique. Just prior to the sunflower harvest in mid-October 2011, we removed all fencing materials from our study fields. The materials were stored over the winter by CPW and re-deployed to 4 different sunflower fields in June 2012 for the second year of testing. Collaring elk and deer to collect information on movement and distribution To obtain data on ungulate movement and distribution patterns we contracted Quicksilver Air to capture and collar 20 adult female elk and 20 adult female deer using a net gun from a helicopter (Krausman et al. 1985). Females were the target of collaring efforts because they cause a majority of the crop depredation and should provide valuable insight into herd distributions. Helicopter captures were scheduled from 11-13 October 2011, just prior to the start of first rifle season. There was a narrow window in which to capture animals, as helicopter operations could only occur after the heat of the summer had passed, but before rifle season had begun (to minimize impacts to hunters). Captured elk and deer were hobbled and blindfolded, fitted with a global positioning system (GPS) collar, aged, measured and released. GPS collars were programmed to collect a location every 4 hours for 2 years, and then drop off the animals in fall 2013. The collars are “store-on-board,” meaning that the data can only be downloaded once the collar is retrieved from the field. Until collars drop-off, we are conducting monthly aerial telemetry flights to monitor survival and obtain some general location information. 104 �Once GPS collar data has been retrieved, elk and mule deer locations will be used to map seasonal distribution and migration patterns in ArcGIS. This should allow CPW to design public hunts that will target conflict elk and mule deer, while minimizing the need for PLO hunts and kill permits. For example, the Utah Division of Wildlife Resources is willing to consider special elk hunts south of Hwy 491 if we find that any or all of the resident elk herds (causing damage) spend portions of the year in Utah. Locations will also allow us to determine the amount of use of crop fields by elk and deer, and the proportion of animals using crop fields (whether it is only certain segments of the population, or the population at large). Animal location data will also be used to model ungulate damage potential in relation to field locations, surrounding habitat types, human development, and topography. These variables have been important in explaining rates of ungulate depredation, as damage tends to increase closer to cover, further from roads, and depending on crop palatability (Grover and Thompson 1986, Nixon et al. 1989, Hegel et al. 2009). Information about the location of a crop field in the context of the overall landscape will allow CPW to work with local growers to identify appropriate management tools, and the timing of their implementation, to reduce game damage. Such a model will serve as a powerful tool for CPW managers, as they will be able to predict the likelihood of depredation for different fields, depending on location, the surrounding environment, and the crop type, and therefore help landowners specify crop choice or management actions to reduce damage. RESULTS AND DISCUSSION Between 20 July 2011 and 20 October 2011 we conducted 137 incursion surveys of the 20 fence plots and 2,100 sunflower ungulate damage assessments. We used repeated measures ANOVA to determine whether there were statistically significant differences in elk and deer incursion into each fence treatment type. We found that incursion varied by treatment for both elk and deer (Elk: F20, 116 = 6.84, P < 0.001; Deer: F20, 116 = 6.24, P < 0.001) such that the electric fence plots had the fewest elk and deer tracks entering the plot, followed by the winged fences, the Plantskydd repellant fences, and the control plots (Figure 4). Biweekly damage assessments of the sunflower fields showed that crop damage followed the same general trends as the frequency of elk and deer entering the treatment plots. Generally, the electric fence plots received the least elk and deer damage, followed by the winged fence, and then by the Plantskydd treatment; the control fields had the highest levels of ungulate damage (Table 1, Figure 5). As expected, the percentage of damaged plants/plot generally increased throughout the growing season, except during the last two assessments. This pattern may have resulted from differences in an observer’s ability to detect damage at different stages of sunflower growth. At the end of the growing season, when the plants are dry and sunflower heads are bent over, damage may be harder to detect than at earlier stages of growth (i.e., when the heads are upright and the leaves are erect). Damage, however, was generally minimal in 2011 across all fields and plots (<1% in plots with electric fences and ~4% in control plots). We suspect that minimal damage was the result of abundant natural forage for elk and deer, as late spring rains in 2011 generated more forage than is typically observed in the vicinity of Dove Creek during summer. Indeed, CPW did not pay out any damage claims to farmers for elk and deer crop depredation in 2011, as wild ungulates were not readily observed on fields. We plan on constructing and monitoring experimental fence plots for a second year in 2012, to test the effectiveness of these treatments when sunflower fields experience more typical rates of damage. Quicksilver Air captured and collared 20 adult female deer and 9 adult female elk. Although deer were readily available for capture throughout the study area, the helicopter crew had a difficult time finding elk in the study area. Wildlife managers suspect that the elk had already left the agriculture areas 105 �around Dove Creek, and had potentially crossed the Utah border by that point in the fall. We plan on trying to ground dart elk during summer 2012 to deploy the remaining elk collars. We conducted monthly aerial telemetry flights for collared animals to track survival and general movement patterns. Four deer died during winter 2011. One deer died in late October, likely due to capture related causes (D12). The other 3 mortalities occurred in February and March 2011, one from a vehicle collision (D4) and the other two from unknown causes (D8 and D19). GPS collars were retrieved from all mortalities so that the data could be downloaded and processed (Figure 6). This information will be used during FY13-14 to map and model seasonal ungulate distributions, game damage potential, and management options for farmers. SUMMARY AND FUTURE PLANS During FY11-12 we constructed the experimental fence plots for the first year of fieldwork, quantified elk and deer damage across our different fencing treatment types, and collared elk and deer in the study area. In FY12-13 we will conduct the fencing experiments for a second field season, and attempt to deploy our remaining elk collars via ground darting. We will continue to monitor the survival and movements of collared animals on a monthly basis using aerial telemetry, until collars detach from the animals in fall 2013. The benefits of this project include gaining knowledge about local elk and deer movements and distribution relative to agricultural fields, identifying non-lethal techniques for reducing ungulate damage to sunflowers and other crops, the development of models to identify areas highly susceptible to damage based on landscape characteristics, and the potential to redesign public hunting opportunities to increase opportunity while reducing those resident animals causing a majority of the damage. LITERATURE CITED Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Blejwas, K.M., B.J. Sacks, M.M. Jaeger, and D.R. McCullough. 2002. The effectiveness of selective removal of breeding coyotes in reducing sheep predation. Journal of Wildlife Management 66:451-462. Engeman, R.M., R.T. Sterner. 2002. A comparison of potential labor-saving sampling methods for assessing large mammal damage in corn. Crop Protection 21:101-105. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004a. Evaluation of a deer-activated bio-acoustic frightening device for reducing deer damage in cornfields. Wildlife Society Bulletin 32:515-523. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004b. Propane exploders and Electronic Guards were ineffective at reducing deer damage in cornfields. Wildlife Society Bulletin 32:524-531. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Hegel, T.M., C.C. Gates, and D. Eslinger. 2009. The geography of conflict between elk and agricultural values in the Cypress Hills, Canada. Journal of Environmental Management 90:222-235. Hildreth, A.M., S.E. Hygnstrom, E.E. Blankenship, and K.C. VerCauteren. In Review. Efficacy of a partial poly-mesh fence with wings to reduce deer damage to corn. Hygnstrom, S.E. and S.R. Craven. 1988. Electric fences and commercial repellents for reducing deer damage in cornfields. Wildlife Society Bulletin 16:291-296. Johnson, H.E., P.Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. 2011. Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Study Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. 106 �Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71–73. McKillop, I.G., and R.M. Sibly. 1988. Animal behaviour at electric fences and implications for management. Mammal Review 18:91-103. Nixon, C.M., L.P. Hansen, P.A. Brewer, J.E. Chelsvig. 1989. Ecology of white-tailed deer in an intensively farmed region of Illinois. Wildlife Monographs 118:1-77. Rosenberry, C.S., L.I. Muller, and M.C. Conner. 2001. Movable, deer-proof fencing. Wildlife Society Bulletin 29:754-757. Seamans, T.W., and K.C. VerCauteren. 2006. Evaluation of ElectroBraid™ fencing as a white-tailed deer barrier. Wildlife Society Bulletin 34:8-15. Van Tassell, L.W., C. Phillips, B. Yang. 1999. Depredation claim settlements in Wyoming. Wildlife Society Bulletin 25:886-894. Vecellio, G.M., R.H. Yahner, and G.L. Storm. 1994. Crop damage by deer at Gettysburg Park. Wildlife Society Bulletin 22:89-93. VerCauteren, K.C., M.J. Lavelle, and S. Hygnstrom. 2006. Fences and deer-damage management: a review of designs and efficacy. Wildlife Society Bulletin 34:191-200. Wagner, K.K., R.H. Schmidt, and M.R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W.D., M.J. Lavelle, J.W. Fischer, T.L. Johnson, S.E. Hygnstrom, and K.C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Walter, W.D., K.C. VerCauteren, J.M. Gilsdorf, and S.E. Hygnstrom. 2009. Crop, native vegetation, and biofuels: response of white-tailed deer to changing management priorities. Journal of Wildlife Management 73:339-344. World Resources Institute. 2008. WRI EarthTrends monthly update page. http://earthtrends.org/updates/node/180. Wisdom, M.J., and J.G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P.R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 107 �Table 1. Average percentage of damaged plants/transect during successive damage assessments across the 2011 sunflower growing season. Averages are displayed by field and treatment plot. FIELD/PLOT Guynes Control Electric Plantskydd Winged Schear-Brewer Control Electric Plantskydd Winged Schear-Homestead Control Electric Plantskydd Winged Schear-Hudgeons Control Electric Plantskydd Winged Warren Control Electric Plantskydd Winged 1 2 3 ASSESSMENT 4 5 6 7 1.7 0.0 0.8 0.0 5.2 0.1 4.5 0.3 5.6 0.1 6.6 0.9 6.9 0.2 2.5 0.6 9.2 0.4 3.9 1.0 8.9 0.2 7.4 1.0 1.5 0.2 1.5 0.7 0.3 0.0 0.0 0.0 1.1 0.1 6.5 0.3 0.7 0.7 2.3 1.8 1.0 0.4 1.9 0.7 2.6 0.6 4.5 1.1 1.2 0.6 1.0 1.5 1.4 0.4 2.2 1.1 0.0 0.0 0.0 0.1 7.1 0.1 0.4 0.3 3.0 0.2 3.2 5.6 7.7 0.1 2.4 3.1 3.1 0.2 9.4 8.1 7.5 0.1 5.3 5.6 2.5 0.2 1.6 2.1 0.1 0.0 0.0 0.1 0.6 0.5 0.3 0.5 0.7 0.9 0.4 1.1 1.3 0.8 0.6 0.5 0.5 0.8 0.4 2.5 0.7 0.5 0.3 1.1 0.6 0.7 0.4 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.0 0.1 0.2 0.1 0.1 0.2 0.3 0.2 0.0 0.1 108 �Figure 1. Placement of experimental fence plots within the 5 replicate sunflower fields during the 2011 growing season (July – October). Fields are located adjacent to wildland canyons. 109 �Figure 2. Photo of a polyrope electric fence constructed in a sunflower field south of Dove Creek. Figure 3. Photo along a winged temporary fence constructed in a sunflower field south of Dove Creek. 110 �Figure 4. Mean number of deer and elk that crossed into experimental fence plots on a biweekly basis, by treatment type, during damage surveys throughout the growing season (results generated from a repeated measures ANOVA). Mean Number of Ungulates 7 Deer Elk 6 5 4 3 2 1 0 control electric plantskydd winged Treatment Figure 5. Average percentage of damaged plants/transect for biweekly assessments across all fields for different treatment types. 111 �Figure 6. GPS collar locations from deer mortalities during FY11-12 in the vicinity of Dove Creek, CO. 112 �Colorado Parks and Wildlife July 2012 – June 2013 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3002 Federal Aid Project No. : : : : : Parks and Wildlife Mammals Research Elk Conservation Evaluating solutions to reduce elk and mule deer damage on agricultural resources Period Covered: July 1, 2012 – June 30, 2013 Author: H.E. Johnson; project cooperators, P. Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, C. Anderson, and J. Fischer. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Elk and mule deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments. This situation has generated significant challenges for wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage. One of the most severe areas of ungulate damage in Colorado has been the sunflower fields around Dove Creek. In this region, roughly a quarter of million dollars were annually paid to farmers between 2007 and 2009 for depredation caused by elk and deer. The main management tool used by Colorado Parks and Wildlife (CPW) to reduce ungulate damage has been the allocation of kill permits, distribution hunts, and private land only doe/cow hunts; however, tolerance for these permits has been low among hunters and the general public. Pressure from local sunflower growers over crop damage, and frustration from the public over kill permits, generated the need for CPW to evaluate other management options for reducing elk and deer crop depredation. As a result, CPW partnered with wildlife damage researchers from the National Wildlife Research Center to find sciencebased solutions for reducing crop damage. Collaboratively, our goals are to 1) experimentally test a suite of non-lethal exclusion and repellent techniques to minimize crop damage, 2) examine elk and deer distribution and migration patterns around agricultural areas to design public hunting opportunities to reduce depredation, and 3) map and model landscape characteristics associated with ungulate damage to specify more effective site-specific management techniques. During FY12-13 we conducted the second and final year of an experiment to test exclusionary techniques for reducing elk and deer damage (objective 1), and submitted a scientific manuscript for publication on the results (Appendix 1). We also monitored collared elk and deer on a monthly basis to collect location information and to retrieve GPS collars from mortalities (data required to meet objectives 2 and 3). 67 �WILDLIFE RESEARCH REPORT EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES HEATHER E. JOHNSON PROJECT NARRITIVE OBJECTIVES To conduct a study on elk and mule deer around the agricultural fields of Dove Creek that 1) experimentally tests a suite of non-lethal exclusion and repellent techniques to minimize crop depredation, 2) examines wild ungulate distribution patterns to design public hunting opportunities to reduce crop damage, and 3) maps and models landscape characteristics associated with damage to specify more effective site-specific management practices. SEGMENT OBJECTIVES 1. Implement the second (and final) year of an experiment to assess non-lethal techniques to exclude or repel deer and elk from sunflower fields in the vicinity of Dove Creek. 2. Conduct data analysis on the exclusionary treatment experiment and submit a scientific manuscript with research results (Appendix 1). 3. Monitor collared deer and elk on a monthly basis for movements, survival and collar retrieval. INTRODUCTION Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural areas (Austin et al. 1998, Wisdom and Cook 2000). In Colorado, elk and deer crop depredation accounts for a majority of the wildlife damage claims in the state, and CPW is obligated to pay for those lost resources. In recent years, the agency has spent approximately $500,000 on an annual statewide basis to compensate farmers for ungulate depredation. This situation has generated significant challenges for CPW and other wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage (Wagner et al. 1997, Van Tassell et al. 1999, Hegel et al. 2009, Walter et al. 2010). Elk and deer crop depredation results from a combination of factors including the seasonal distribution and abundance of local forage resources, landscape configuration, and herd density patterns (Vecellio et al. 1994; Yoder 2002; Hegel et al. 2009). Damage can be highly variable within and among growing seasons, as local patterns in precipitation and temperature will alter the availability of native forage and the motivation of ungulates to feed on agricultural fields (Walter et al. 2010). The juxtaposition of cropland and wildland has also been found to be particularly important in driving damage rates, as those cultivated fields closer to cover experience more damage (Nixon et al. 1989, Hegel et al. 2009). Additionally, studies have found that ungulate damage is often caused by only a subset of individuals in the population, depending on the spatial and social structuring of the herd. These observations have critical implications for wildlife managers, as 1) management practices may be differentially effective based on the variability of native forage conditions and the spatial juxtaposition of other habitat features, and 2) management techniques targeted at specific animals may be more effective than implementing those techniques on the population at large (Blejwas et al. 2002, Hegel et al. 2009). As a result, it is important to understand both the spatial configuration of seasonal resources and the resource selection patterns of different segments of local ungulate populations to successfully identify strategies to reduce elk and deer crop damage (Hegel et al. 2009). 68 �One of the most significant hotspots of elk and mule deer depredation in Colorado has been in the vicinity of Dove Creek, where CPW paid roughly a quarter of million dollars annually to farmers between 2007 and 2009. High damage in this region has been primarily attributed to a recent switch in the crops that are locally grown. Farmers traditionally grew beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels, and a crop that is highly desirable to wild ungulates. In addition to this recent switch in crops, ungulate damage around Dove Creek is exacerbated by the spatial distribution of sunflower fields in relation to the surrounding wildlands (e.g., sagebrushmixed shrublands and piñon-juniper woodlands). The region is fractured with deep canyons that provide refugia for elk and deer, and fields adjacent to the canyon rims experience the greatest amount of depredation. With the substantial increase in biofuel production in the U.S. (World Resources Institute 2008), the agricultural conversion observed around Dove Creek will likely become common, as highpriced crops replace more traditionally-grown, lower-cost crops (Walter et al. 2009). The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits, distribution hunts, and private land only (PLO) doe/cow hunts, however tolerance for these permits has been low among hunters and the general public. Permits are typically allocated to farmers between June and August, when calves and fawns are still dependent on their mothers, reducing the acceptability of female hunts. Additionally, local elk and deer populations are near or below management objectives, creating a paradox where CPW ultimately wants to increase ungulate herds, but reduce crop depredation. Hunting is also economically important around Dove Creek, so there is a strong desire in the local community to have increased public hunting opportunities and reduced PLO damage hunts. Given pressure by farmers over elk and deer sunflower damage, and frustration by hunters and the public over kill permits, CPW wildlife managers were interested in finding alternative solutions for reducing sunflower depredation. As a result, personnel from CPW partnered with wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find non-lethal, science-based solutions for reducing sunflower depredation. Collaboratively, we developed a proposal to 1) test a suite of non-lethal exclusionary techniques to minimize crop depredation, 2) identify public hunting strategies that reduce crop damage, and 3) map and model landscape characteristics associated with damage behavior to specify more effective site-specific management practices (Johnson et al. 2011). Results from this study should enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments, a decrease in kill permits/distribution hunts, and an increase in public hunting opportunities. In FY 2012-13 we completed objective 1, and continued to monitor collared elk and deer for objectives 2 and 3. Specifically, we conducted the second (and final) year of the experiment to assess non-lethal exclusion and repellent techniques for reducing elk and deer damage. We analyzed data from the experiment (collected during the growing seasons of 2011 and 2012) and submitted a scientific manuscript with research results for publication (currently in revision, Appendix 1). We also monitored collared elk and deer on a monthly basis to collect information about local movement and distribution patterns, and to retrieve collars from mortalities (GPS collar data will be used to meet objectives 2 and 3). STUDY AREA The area around Dove Creek, Colorado (Montezuma, San Miguel and Dolores counties) is comprised of a mixture of agricultural and public lands. This project focuses on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed with irrigated and dryland agricultural fields, ranging from 1,981 to 2,590 m in elevation. The mountain shrub habitat type is primarily composed of 69 �serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum) and black sagebrush (Seriphidium novum). Sunflower fields around Dove Creek are spatially juxtaposed to deep canyons that provide refugia for elk, exacerbating ungulate damage on agricultural crops (see Appendix 1, Figure 1). METHODS Testing the effectiveness of different exclusionary treatment types for reducing ungulate damage During the sunflower growing seasons (Jul-Oct) of 2011 and 2012, we constructed experimental plots to test the effectiveness of three non-lethal exclusion and repellent techniques for reducing elk and deer damage: a polyrope electric fence, a temporary “winged” fence, and an organic repellent. These methods differ from traditional exclusionary fencing for elk and deer, in that they are cheaper to construct and can be easily moved among fields over time, as farmers grow sunflowers on a rotational basis. Each exclusionary treatment is described below: • • • Polyrope electric fence – The polyrope electric fence acts primarily as psychological barrier for elk and deer based on learned behavioral, avoidance conditioning (McKillop and Sibly 1988). The fences consists of conductive wires which are woven into synthetic electric “ropes” that are more durable, visible, and easy to install than traditional electric fences (Appendix 1, Figure 2; Hygnstrom and Craven 1988, VerCauteren et al. 2006). Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives a powerful electric shock. Polyrope fences have had success in reducing deer damage (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing elk damage. We constructed polyrope fences approximately 1.8 meters tall with 5 strands to discourage passage under, through, or over the fence. The polyrope was powered by a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) using a 12-volt deepcycle battery with a solar-panel recharger. Temporary winged fence - For seasonal agricultural resources, such as sunflowers, temporary fences may be sufficient to provide protection from wild ungulates and are inexpensive, lightweight, and easy to erect and remove (Rosenberry et al. 2001, VerCauteren et al. 2006). We tested the effectiveness of a temporary “winged” fence made of polypropylene mesh (Appendix 1, Figure 2). The fence is installed completely on one side of the target field, and partially installed on two other sides having 50-100 meter “wings” that extend perpendicular from the full fence line. This design was found to reduce deer damage in corn fields (Hildreth et al. 2012) but has not yet been tested on elk or on deer with crops other than corn. On those plots receiving winged-fence treatments, we installed the fence such that the side receiving complete protection was along the crop/wildland interface. The fence was made of 2.4 meter tall black barrier material (e.g., Guardian Warning Barrier, Tenax Corporation, USA, Baltimore, Maryland) for increased height and visual deterrence. Plantskydd - Repellents are nonlethal substances that can be used to deter ungulates by decreasing a plant’s palatability (Walter et al. 2010). We tested the effectiveness of a relatively new product, Plantskydd, for reducing sunflower damage around Dove Creek. This product was developed in Sweden to decrease mammalian wildlife damage on commercial forests. It works by emitting an odor that animals associate with predator presence, repelling the animal before it forages on crop plants. There is great interest in the success of this product as it can be easily applied to vegetation by ground and aerial spraying, used on both organic and conventionally grown sunflowers, and is cost-effective for growers. That said, the effectiveness of Plantskydd has not been experimentally tested, only anecdotally reported. To test this method, Plantskydd treatment plots were ground sprayed in a swath around the plot perimeters after germination had begun (as directed by the manufacturer). Plantskydd was reapplied to treatment plots once/month 70 �throughout the growing season as the repellent may wash off or decompose over time and needs to be reapplied to new plant material. We constructed treatment plots based on a randomized block design. We identified 5 sunflower fields to serve as replicates in 2011 and 4 fields in 2012 (~160-200 acres in size); all fields had previously suffered high ungulate crop damage. Within each field we specified 4 10-acre plots, one for each experimental treatment type (polyrope fence, temporary winged fence, chemical repellent fence) and a control. The 4 plots were randomly assigned within each field, such that each field (block) contained one replicate of all treatments (Gotelli and Ellison 2004). This design allowed us to statistically account for environmental heterogeneity, as we expected that damage would be variable among fields. Within the fields, study plots were spaced as far apart as possible, to account for plot independence. Plots were also placed along the agriculture/wildland boundary, where depredation was expected to be concentrated. Fences were installed during the end of June and early July after sunflowers had germinated. Experimental plots were monitored from mid-July through mid-October (just prior to harvest). Treatment and control plots were examined for 2 key response variables: sunflower damage and the number of elk and deer tracks that crossed plot perimeters. We used the variable-area-transect method for estimation of crop damage (Engeman and Sugihara 1998; Engeman and Sterner 2002; Gilsdorf et al. 2004a, b), conducting final damage assessments immediately before harvest (mid-Oct). In 2011 we assessed damage on 15 transects/plot, and in 2012 we increased the number to 30 transects/plot. For each transect, we randomly (with replacement) identified a starting location within the plot and inspected a row of sunflowers, counting the total number of sunflower plants, and the number of plants that were damaged by deer or elk. Typical damage was characterized by the removal of the terminal bud, consumption of the seed head and trampling of the plants, verified by accompanying cervid tracks. If 5 cervid-damaged sunflowers were tallied within 100 m, we recorded the distance traveled to the fifth damaged plant (<100 m) and the total number of sunflower plants observed within that distance. If 5 cervid-damaged sunflowers were not tallied within 100 m, the observer recorded the total number of sunflowers and the number of cervid-damaged plants counted within that distance. If the end of the sunflower row was reached before completing a transect, the observer would randomly select an adjacent row (i.e., right or left row) to complete the transect. We calculated mean proportion of end-of-season damage for each treatment and control plot, and mean number of elk and deer tracks traversing plot perimeters for each plot across the growing season. We used a generalized linear mixed model to identify whether exclusion or repellent treatment types were effective in reducing cervid damage to sunflower plots (Pinheiro and Bates 2000). Because damage data were recorded for each transect as the number of damaged plants/total plants, we used a binomial distribution with a logit link function. To evaluate the influence of exclusion techniques on deer and elk tracks traversing plot perimeters, we used generalized linear mixed models with Poisson distributions and log link functions. We generated separate models for predicting the number of tracks by deer and elk, as we hypothesized that treatments may vary in their effectiveness among cervid species. We used model coefficients to assess the direction and magnitude of different treatment types on cervid damage and plot use (95% confidence intervals non-overlapping zero). Collaring elk and deer to collect information on movement and distribution To obtain data on ungulate movement and distribution patterns, we captured and collared adult female elk and mule deer using a net gun from a helicopter in fall 2011 (Krausman et al. 1985). Females were the target of collaring efforts because they cause a majority of the crop depredation and should provide valuable insight into herd distributions. Captured elk and deer were hobbled and blindfolded, fitted with a global positioning system (GPS) collar, aged, measured and released. GPS collars were programmed to collect a location every 4 hours for 2 years, and then drop off the animals in fall 2013. The collars are “store-on-board,” meaning that the data can only be downloaded once the collar is 71 �retrieved from the field. Until collars drop-off, we are conducting monthly aerial telemetry flights to obtain some general location information and to monitor mortalities so collars can be retrieved from the field. Once GPS collar data has been retrieved, elk and mule deer locations will be used to map seasonal distribution and migration patterns in ArcGIS. This should allow CPW to design public hunts that will target conflict elk and mule deer, while minimizing the need for PLO hunts and kill permits. Animal location data will also be used to model ungulate damage potential in relation to field locations, surrounding habitat types, human development, and topography. These variables have been important in explaining rates of ungulate depredation, as damage tends to increase closer to cover, further from roads, and depending on crop palatability (Grover and Thompson 1986, Nixon et al. 1989, Hegel et al. 2009). Information about the location of a crop field in the context of the overall landscape will allow CPW to work with local growers to identify appropriate management tools, and the timing of their implementation, to reduce game damage. Data analysis for this portion of the project will be primarily conducted by collaborators at the USDA National Wildlife Research Center. RESULTS AND DISCUSSION Exclusion and Repellent Treatments - During summers 2011 and 2012, we conducted 3,288 damage transects and 233 track surveys across all treatment plots. The percentage of sunflowers damaged by cervids across plots and years ranged from 0.0% to 72.6% ( x = 8.3%, SE = 0.8). The mean bimonthly number of deer tracks crossing plot perimeters ranged from 0 to 149.8 ( x = 23.0, SE = 5.3) and the mean number of elk tracks ranged from 0 to 21.6 ( x = 5.3, SE = 1.1). Mean percentage sunflower damage and number of deer tracks were greater in 2012 than in 2011 (damage: t = -3.300, df = 29, P = 0.003 [Fig. 3a]; deer tracks: t = -4.512, df = 34, P < 0.001; Fig. 3b), but mean values for elk tracks were similar between years (t = 0.371, df = 34, P = 0.713). In 2011, treatment and control plots averaged 0.9% sunflower plant damage at the end of the growing season, and a bimonthly average of 6.0 deer and 5.7 elk tracks crossed plot boundaries. Conversely, 2012 plots had an average of 17.1% of plants damaged at harvest and an average of 44.4 deer tracks and 4.9 elk tracks crossed plot boundaries on a bimonthly basis. We found that electric fencing was the only treatment that significantly reduced damage and plot use by deer and elk (see Appendix 1 for details). Across years, the mean proportion of damaged plants on electric fence plots was 0.01 (95% CI: 0.00 – 0.03), on control plots was 0.05 (95% CI: 0.00 – 0.33), on repellent fences was 0.04 (95% CI: 0.01 – 0.15) and on winged fences was 0.04 (95% CI: 0.01 – 0.15). The average bimonthly number of deer tracks that crossed plot perimeters on plots with electric fencing was 0.6 (95% CI: 0.3 – 1.1), on control plots was 18.5 (95% CI: 3.8 – 91.5), on repellent fence plots was 18.4 (95% CI: 11.4 – 29.7), and on winged plots was 16.8 (95% CI: 10.4 – 27.0). Electric fences also reduced the number of elk that crossed plot perimeters on a bimonthly basis, but the effect was lesser than for deer. An average of only 0.1 elk tracks crossed electric fence plot boundaries (95% CI: 0.0 – 0.2), while 4.3 crossed control plots (95% CI: 1.8 – 10.3), 3.4 crossed repellent plots (95% CI: 2.2-5.2) and 3.7 crossed winged plots (95% CI: 2.4 – 5.7). For wildlife agencies seeking non-lethal management options for reducing elk and deer damage to high-value agricultural crops, we found that 5-strand polyrope electric fencing was effective. Polyrope is easy to assemble/disassemble, cost-effective relative to permanent fencing, and can be used on a temporary basis to minimize damage for certain crops grown on rotation or during years when natural forage for cervids is scarce. In areas where management agencies are working to maintain or increase deer and elk populations, but reduce cervid damage, the application of an effective exclusion technique like polyrope electric fencing could protect high-value crops, decrease the need for compensation payments and lethal cervid depredation permits, and increase satisfaction of producers and the public. Wildlife agencies will need to continue to work with producers to test and apply management techniques 72 �for crop protection based on the wildlife species present, population densities, crop types, landscape configuration, and abundance of local forage. Monitoring Collared Deer and Elk - We conducted monthly aerial telemetry flights for collared animals to track survival and general movement patterns. Three deer and one elk died during FY12-13 from unknown causes. GPS collars were retrieved from all mortalities so that the data could be downloaded and processed. This information will be used during FY13-14 to map and model seasonal ungulate distributions, game damage potential, and management options for sunflower producers. SUMMARY AND FUTURE PLANS During FY12-13 we completed the non-lethal, exclusionary treatment experiment, analyzed ungulate damage and use on plots by treatment type, submitted a scientific manuscript for publication with experiment results (Appendix 1), and monitored collared elk and deer in the study area. In FY13-14 we will continue to monitor the survival and movements of collared animals on a monthly basis using aerial telemetry, collect collars in the field once they drop off animals in fall 2013, and map and model GPS location data. The benefits of this project include the identification of non-lethal techniques for successfully reducing ungulate damage to sunflowers and other crops, gaining knowledge about local elk and deer movements and distribution relative to agricultural fields, and the development of models to identify areas highly susceptible to damage based on landscape characteristics. LITERATURE CITED Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Blejwas, K.M., B.J. Sacks, M.M. Jaeger, and D.R. McCullough. 2002. The effectiveness of selective removal of breeding coyotes in reducing sheep predation. Journal of Wildlife Management 66:451-462. Engeman, R.M., R.T. Sterner. 2002. A comparison of potential labor-saving sampling methods for assessing large mammal damage in corn. Crop Protection 21:101-105. Engeman, R. M., and R. T. Sugihara. 1998. Optimization of variable area transect sampling using Monte Carlo simulation. Ecology 79:1425-1434. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004a. Evaluation of a deer-activated bio-acoustic frightening device for reducing deer damage in cornfields. Wildlife Society Bulletin 32:515-523. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004b. Propane exploders and Electronic Guards were ineffective at reducing deer damage in cornfields. Wildlife Society Bulletin 32:524-531. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Grover, K.E., and M.J. Thompson. 1986. Factors influencing spring feeding site selection by elk in the Elkhorn Mountains, Montana. Journal of Wildlife Management 50:466-470. Hegel, T.M., C.C. Gates, and D. Eslinger. 2009. The geography of conflict between elk and agricultural values in the Cypress Hills, Canada. Journal of Environmental Management 90:222-235. Hildreth, A.M., S.E. Hygnstrom, E.E. Blankenship, and K.C. VerCauteren. 2012. Efficacy of a partial poly-mesh fence with wings to reduce deer damage to corn. Wildlife Society Bulletin 36:199203. Hygnstrom, S.E. and S.R. Craven. 1988. Electric fences and commercial repellents for reducing deer damage in cornfields. Wildlife Society Bulletin 16:291-296. 73 �Johnson, H.E., P.Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. 2011. Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Study Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71–73. McKillop, I.G., and R.M. Sibly. 1988. Animal behaviour at electric fences and implications for management. Mammal Review 18:91-103. Nixon, C.M., L.P. Hansen, P.A. Brewer, J.E. Chelsvig. 1989. Ecology of white-tailed deer in an intensively farmed region of Illinois. Wildlife Monographs 118:1-77. Pinheiro, J., and D. M. Bates. 2000. Mixed effects models in S and S-Plus. Springer-Verlag, New York, New York, USA. Rosenberry, C.S., L.I. Muller, and M.C. Conner. 2001. Movable, deer-proof fencing. Wildlife Society Bulletin 29:754-757. Seamans, T.W., and K.C. VerCauteren. 2006. Evaluation of ElectroBraid™ fencing as a white-tailed deer barrier. Wildlife Society Bulletin 34:8-15. Van Tassell, L.W., C. Phillips, B. Yang. 1999. Depredation claim settlements in Wyoming. Wildlife Society Bulletin 25:886-894. Vecellio, G.M., R.H. Yahner, and G.L. Storm. 1994. Crop damage by deer at Gettysburg Park. Wildlife Society Bulletin 22:89-93. VerCauteren, K.C., M.J. Lavelle, and S. Hygnstrom. 2006. Fences and deer-damage management: a review of designs and efficacy. Wildlife Society Bulletin 34:191-200. Wagner, K.K., R.H. Schmidt, and M.R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W.D., M.J. Lavelle, J.W. Fischer, T.L. Johnson, S.E. Hygnstrom, and K.C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Walter, W.D., K.C. VerCauteren, J.M. Gilsdorf, and S.E. Hygnstrom. 2009. Crop, native vegetation, and biofuels: response of white-tailed deer to changing management priorities. Journal of Wildlife Management 73:339-344. World Resources Institute. 2008. WRI EarthTrends monthly update page. http://earthtrends.org/updates/node/180. Wisdom, M.J., and J.G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P.R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 74 �Appendix 1 Evaluating techniques to reduce cervid damage Evaluation of techniques to reduce deer and elk damage to agricultural crops Colorado Parks and Wildlife and US Dept. of Agriculture, Heather Johnson Justin Fischer Mathew Hammond Patricia Dorsey W. David Walter Charles Anderson Kurt VerCauteren Research Report 75 �8/22/2013 Corresponding Author: Heather Johnson Colorado Parks and Wildlife 415 Turner Drive Durango, CO 81303 Phone: (970) 375-6715 FAX: (970) 375-6705 Email: Heather.Johnson@state.co.us Evaluation of techniques to reduce deer and elk damage to agricultural crops RH: Johnson et al. • Evaluating techniques to reduce cervid damage HEATHER E. JOHNSON,1 Colorado Parks and Wildlife, 415 Turner Drive, Durango CO 81303, USA JUSTIN W. FISCHER, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA MATTHEW HAMMOND, Colorado Parks and Wildlife, 151 East 16th Street, Durango CO 81301, USA PATRICIA D. DORSEY, Colorado Parks and Wildlife, 415 Turner Drive, Durango CO 81303, USA W. DAVID WALTER2, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA CHARLES ANDERSON3, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA KURT C. VerCAUTEREN, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA 1 E-mail: Heather.Johnson@state.co.us 2 Present addresses:United States Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, 403 Forest Resources Building, University Park, PA 16802, USA (WDW), 3Missouri Department of Conservation, 2901 W. Truman Blvd., Jefferson City, MO 65109, USA (CA) KEY WORDS Cervus elaphus nelsoni, crop damage, electric fence, elk, mule deer, Odocoileus hemionus, repellent, sunflowers, wildlife damage management, winged fence. 76 �ABSTRACT Mule deer (Odocoileus hemionus) and Rocky Mountain elk (Cervus elaphus nelsoni) provide important recreational, ecological, and economic benefits, but can also cause substantial damage to agricultural crops. Cervid damage to agriculture creates challenges for wildlife agencies responsible for minimizing crop depredation while maintaining healthy deer and elk populations. Sunflower producers in southwestern Colorado have experienced high deer and elk damage and were interested in temporary methods to reduce damage that were cost-effective for rotational crops. To address this challenge we investigated three temporary, non-lethal exclusion and repellent techniques for reducing deer and elk damage to sunflowers: 1) a polyrope electric fence, 2) the chemical repellent Plantskydd™, and 3) a winged fence. During July through October 2011 and 2012, we used a randomized block design to test the efficacy of these techniques by quantifying cervid damage to sunflowers and the number of deer and elk tracks traversing treatment and control plot boundaries. Using generalized linear mixed models we found that polyrope electric fences reduced deer and elk damage and presence within plots, while the repellent and winged fences did not reduce ungulate activity. Polyrope electric fences may be a suitable tool in areas where wildlife management agencies want to maintain deer and elk populations but reduce seasonal damage by cervids to high value crops. In Colorado, use of an effective exclusion technique like polyrope electric fence could also decrease the need for lethal depredation permits and damage compensation payments, and increase satisfaction among producers and the public. Wildlife Society Bulletin: 00(0): 000-000, 201X Mule deer (Odocoileus hemionus) and Rocky Mountain elk (Cervus elaphus nelsoni) provide important recreational, ecological, and economic benefits, but also can cause substantial damage to agricultural crops (Austin et al. 1998, Wisdom and Cook 2000). Because crops are typically more digestible and contain higher levels of crude protein than native grasses and browse species, they are often selected and consumed by wild cervids (Mould and Robbins 1982). Agricultural producers have reported more damage by elk and deer (Odocoileus sp.) than any other wildlife species, and damage by deer alone has been projected to exceed 100 million dollars annually in the U.S. (Conover 2002). Cervid damage to crops has created significant challenges for wildlife management agencies, as agencies are often responsible for both maintaining cervid population sizes for recreation while minimizing damage to agriculture (Wagner et al. 1997, Hegel et al. 2009, Van Tassell et al. 1999, Walter et al. 2010). Agricultural producers often experience varying amounts of crop depredation caused by cervids depending on the seasonal distribution, abundance and landscape configuration of local food resources (Vecellio et al. 1994, Yoder 2002, Hegel et al. 2009). Damage also can be variable both within and among growing seasons, as local precipitation and temperatures will alter the availability of native forage and the motivation of deer and elk to feed on agricultural products (Walter et al. 2010). The proximity of cropland and wildland is also important in predicting patterns of damage, as cultivated fields closer to wildlife cover experience greater depredation (Nixon et al. 1989, Hegel et al. 2009). As a result, the effectiveness of management practices to reduce cervid damage may vary based on native forage availability, proximity of cover, and other habitat features (Hegel et al. 2009). Common management tools used to reduce cervid damage to crops include permanent fencing and lethal removal of animals through depredation permits (Walter et al. 2010); however, there are drawbacks to each approach. Permanent cervid-proof fencing is effective but often cost-prohibitive for producers that have large tracts of land (VerCauteren et al. 2006) or grow crops on a rotational basis where only one crop type experiences high rates of damage. Permanent fencing is also a concern as it can interfere with wildlife movements and reduce access to nearby habitat. Wildlife agencies use depredation permits to lethally remove animals causing damage, but tolerance for these permits is often low among hunters, some producers, and the general public (Colorado Parks and Wildlife [CPW], unpublished data). Hunters often perceive depredation permits as reducing hunting opportunity (Fritzell et al. 1995, Horton and Craven 1997), particularly when local deer and elk population sizes are below agency management 77 �objectives. Depredation permits are also often unpopular with the public, particularly when lethal removal includes female cervids with dependent young. Identifying cost-effective, non-lethal methods that reduce cervid damage to agricultural crops is of particular interest in Colorado. Deer and elk account for about 50% of wildlife damage claims on agriculture, and CPW is mandated to pay all eligible claims. These compensation payments are costly (i.e., $458,760 was paid in compensation for deer and elk damage in 2012; CPW 2012), thus, CPW is interested in methods to reduce cervid depredation and associated payments. While damage to agriculture is a management concern, many of Colorado’s deer and elk populations are at or below their management objectives, making depredation permits highly unpalatable to local hunters and the general public. Because deer and elk often depend upon private lands for habitat, finding cost-effective, non-lethal solutions to prevent cervid depredation is also essential to encourage private landowner tolerance of wildlife and to build effective agency-landowner partnerships. To identify cost-effective, non-lethal strategies for reducing deer and elk damage to crops, our objective was to experimentally test three temporary techniques: 1) a 5-strand polyrope electric fence (hereafter electric), 2) an organic chemical repellent (Plantskydd™; hereafter repellent), and 3) a winged or partial fence (hereafter winged). These methods are less expensive than permanent fencing and can be implemented on a temporary basis to account for crop rotation (VerCauteren et al. 2006, Walter et al. 2010). While these methods have received some testing on white- and black-tailed deer (Odocoileus virginianus, O. h. columbianus; Nolte 1998, Seamans and VerCauteren 2006, Hildreth et al. 2012), little is known about their effectiveness in reducing mule deer or elk damage to agriculture. STUDY AREA We tested temporary exclusion and repellent techniques for deer and elk near Dove Creek, Colorado, USA (Dolores County; 37⁰45’58.05” N, 108⁰54’21.10”W; Fig. 1). Experimental plots were placed in agricultural fields growing sunflowers that were spatially juxtaposed to native vegetation and wildland canyons, and which had previously experienced cervid damage (CPW, unpublished data). All sunflower fields were located on private property, but the region is generally comprised of a mix of private and public lands. Elevation in the study area ranges from 1,981 to 2,590 m, and vegetation is characterized as mountain shrub and pinyon-juniper woodlands, interspersed with irrigated and dryland agriculture. The native vegetation is primarily composed of serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum), black sagebrush (Seriphidium novum), pinyon pine (Pinus edulis) and juniper (Juniperus osteoperma). Between 1996 and 2012 mean annual precipitation was 26.7 cm, which is typically received during late summer rains and as snow during winter (Weather Station DVCO1, Colorado Agricultural Meteorological Network 2012). Mean annual minimum and maximum temperatures were -0.4⁰C and 16.6⁰C, respectively (Colorado Agricultural Meteorological Network 2012). Since 1998 estimated deer population sizes have been consistently below CPW’s management objectives, while estimated elk population size has been above or within management objectives (CPW, unpublished data). The study area has experienced high rates of mule deer and elk agricultural damage in association with a recent switch in the types of crops that are grown. Farmers traditionally grew dry beans, spring and winter wheat, and grass hay which experienced minimal damage by cervids. Since 2007, however, many farmers started growing sunflowers on a rotational basis, a high-value seed oil crop used for biofuel, and have experienced up to 100% depredation on fields in some years. Sunflowers in the region are generally grown on a 3 to 4-year rotation with other crops (e.g., winter wheat, pinto beans) that experience minimal damage and thus, producers were interested in exclusion or repellent techniques that could be moved between fields in different years. Cervid damage in this area was also exacerbated by the spatial 78 �juxtaposition of agricultural fields alongside wildland canyons that provided refugia for deer and elk (Fig. 1). METHODS Exclusion and Repellent Methods Evaluated Electric – We tested a polyrope electric fence (ElectroBraid™ Fence Limited, Yarmouth, Nova Scotia, Canada; approximately $5-10/m for materials), which acts primarily as a psychological barrier based on learned behavioral and avoidance conditioning (Fig. 2a; McKillop and Sibly 1988, VerCauteren et al. 2012). The fence consisted of conductive copper wires woven into synthetic “ropes” that are more durable, visible and easier to install than traditional electric fence designs (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006, VerCauteren et al. 2006, Fischer et al. 2011). We constructed fences 1.8 m high, with wooden h-brace assemblies placed approximately every 100 m and metal t-posts spaced every 15 m. Five polyrope lines were attached to the fence posts at 20, 56, 89, 135, and 183 cm above ground to discourage deer and elk incursions. Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives an electric shock. Polyrope fences have reduced whitetailed deer damage to crops (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing mule deer or elk damage. The polyrope fence used a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) which had a maximum pulse output of 3.0 joules and was operated from a 12-volt deep-cycle battery with a solar-panel recharger. Repellent - We tested the effectiveness of Plantskydd™ (Tree World Plant Care Products Inc, St. Joseph, Missouri, USA) for reducing deer and elk damage. This repellent can be used on conventional and organic crops and can be applied by ground or aerial spraying. Plantskydd™ was developed in Sweden for reducing mammalian wildlife damage on commercial forests. The active ingredient is dried bloodmeal, which the manufacturer asserts works by emitting an odor that wildlife associate with predator presence. We mixed Plantskydd™ powder with water following the manufacturer’s directions for severe damage (14.8 kg of Plantskydd™/plot perimeter). The manufacturer recommends spraying a swath ≥10 m around plot perimeters, and we sprayed an 18 m swath around treatment plot perimeters, the maximum distance that could be covered with an industrial ground sprayer (Model 4720, John Deere, Deere and Company, Moline, Illinois, USA). Given materials and application, this treatment cost ≤ $1/m of field perimeter spraying. Plantskydd™ was applied monthly throughout the growing season (Jul – Sept) to account for the repellent washing off or degrading, and to spray new plant growth. Plantskydd™ has reduced damage to tree seedlings caused by black-tailed deer (Nolte 1998, Wagner and Nolte 2001), but has been not been tested on mule deer or elk. Winged fence –Hildreth et al. (2012) recently experimented with “winged” or “partial” fences designed to reduce white-tailed deer access along field edges adjacent to cover. The fence is completely installed on the field side that borders native vegetation, and partially installed on the perpendicular sides, creating “wings” that extend around a portion of the field (Fig. 2b; approximately $6/m for materials). This fence is highly economical as only a portion of the field needs to be enclosed and materials can be easily erected and removed depending on crop rotation. We installed winged fences following Hildreth et al. (2012), where the side of the treatment plot closest to the crop/wildland interface received complete protection. We erected fences 2.1 m in height which consisted of UV-stable polypropylene high-strength mesh (Benner’s Gardens, Phoenixville, PA) secured to 3 m metal t-posts spaced every 7 m using cable ties. Two strands of 12.5 gauge high-tensile wire were placed 0.8 m and 2.1 m above ground, so the mesh could be suspended and anchored to the wire with circular staples along the length of the fence for support. The fence also had a 0.2 m apron extending outward from the field, secured with 0.3 m steel stakes, to further reduce elk and deer access. Corners and ends of the winged fence were supported with metal t-post angled h-brace assemblies. The fence wings extended 50 m along the two sides of the treatment plots that were adjacent to the fully installed side of the fence. 79 �Experimental Design We used a randomized block design (Gotelli and Ellison 2004) where each “block” was a sunflower field (~65-80 ha in size) that had previously experienced cervid crop damage, and which was directly adjacent to the wildland boundary where damage was expected to be greatest (Fig. 1). Within each field we delineated 4 4-ha treatment plots. Treatment plots were randomly assigned to receive one of the following treatments: no exclusion or repellent method (control), electric fence, repellent, or winged fence. We used this design to account for environmental heterogeneity, as we expected damage to vary among fields. We monitored 5 replicate fields during 2011 (Fields A-E) and 4 replicate fields in 2012 (Fields F-I); because sunflowers were grown on rotation the same fields were not tested in both years. Fences were constructed in late June and early July after sunflowers had germinated to ensure planting was successful, as pests or low soil moisture can cause failure in germination. The corners of all plots were marked with easily visible metal stakes to facilitate data collection. Monitoring Fence Effectiveness Plots in each field were monitored for two response variables: damage to sunflower plants and number of deer and elk tracks traversing plot boundaries (entry/exit into plots). We used the variablearea-transect method for estimation of crop damage (Engeman and Sugihara 1998; Engeman and Sterner 2002; Gilsdorf et al. 2004a, b), conducting final damage assessments immediately before harvest (midOct). In 2011 we assessed damage on 15 transects/plot, and in 2012 we increased the number to 30 transects/plot. For each transect, we randomly (and with replacement) identified a starting location within the plot and inspected a row of sunflowers, counting the total number of sunflower plants, and the number of plants that were damaged by deer or elk. Typical damage was characterized by the removal of the terminal bud, consumption of the seed head and trampling of the plants, verified by accompanying cervid tracks. If 5 cervid-damaged sunflowers were tallied within 100 m, we recorded the distance traveled to the fifth damaged plant (<100 m) and the total number of sunflower plants observed within that distance. If 5 cervid-damaged sunflowers were not tallied within 100 m, the observer recorded the total number of sunflowers and the number of cervid-damaged plants counted within that distance. If the end of the sunflower row was reached before completing a transect, the observer would randomly select an adjacent row (i.e., right or left row) for completing the transect. Each treatment and control plot was also monitored for deer and elk tracks that traversed plot boundaries on a bimonthly basis throughout the growing season (mid-Jul through mid-Oct). An observer would walk the perimeter of each plot, counting the total number of deer and elk tracks that crossed the plot perimeter. Cervid tracks were raked or stamped out after each observation to avoid double-counting in subsequent sampling periods. Statistical Approach We calculated mean proportion of end-of-season damage for each treatment and control plot, and mean number of elk and deer tracks traversing plot perimeters for each plot across the growing season. We also calculated mean values separately for fields monitored in 2011 and 2012, as cervid damage was uncharacteristically low in 2011. We did not include end-of-season damage values from the repellent plot of one field (Field F in 2012) because cervid damage occurred in that plot before the first application of the repellent. Similarly, end-of-season damage information from all treatment plots of a field in 2012 (Field I) were removed from data summaries and analyses because substantial depredation occurred after germination but before fence construction. We used a generalized linear mixed model to identify whether exclusion or repellent treatment types were effective in reducing cervid damage to sunflower plots (Pinheiro and Bates 2000). Because damage data were recorded for each transect as the number of damaged plants/total plants, we used a binomial distribution with a logit link function (Bolker et al. 2009). Treatment was included in the model as a categorical fixed effect (control plots were considered the reference class) and we nested plot within field within year for the random effects model structure. We used model coefficients to assess the 80 �direction and magnitude of different treatment types on cervid damage (95% confidence intervals nonoverlapping zero). To evaluate the influence of exclusion or repellent types on deer and elk tracks traversing plot perimeters, we used generalized linear mixed models with Poisson distributions and log link functions. As with the damage models, we included treatment type as a categorical fixed effect and nested plot within field within year for the random effects portion of the model. We generated separate models for predicting the number of tracks by deer and elk, as we hypothesized that treatments may vary in their effectiveness among cervid species (e.g., VerCauteren et al. 2006, Walter et al. 2010). As with the damage model, we used model coefficients, and their 95% confidence intervals, to assess the direction and magnitude of treatment effects on the number of tracks traversing plot boundaries. We used the package “lme4” in program R for all statistical modeling (R Core Team 2012). RESULTS Cervid damage and tracks varied across treatment and control plots. Just prior to harvest, the percentage of sunflowers damaged by cervids across plots and years ranged from 0.0% to 72.6% ( x = 8.3%, SE = 0.8). The mean bimonthly number of deer tracks crossing plot perimeters ranged from 0 to 149.8 ( x = 23.0, SE = 5.3) and the mean number of elk tracks ranged from 0 to 21.6 ( x = 5.3, SE = 1.1). Mean percentage sunflower damage and number of deer tracks were greater in 2012 than in 2011 (damage: t = -3.300, df = 29, P = 0.003 [Fig. 3a]; deer tracks: t = -4.512, df = 34, P < 0.001; Fig. 3b), but mean values for elk tracks were similar between years (t = 0.371, df = 34, P = 0.713). In 2011, treatment and control plots averaged 0.9% sunflower plant damage at the end of the growing season, and a bimonthly average of 6.0 deer and 5.7 elk tracks crossed plot boundaries. Conversely, 2012 plots had an average of 17.1% of plants damaged at harvest and an average of 44.4 deer tracks and 4.9 elk tracks crossed plot boundaries on a bimonthly basis. Despite differences in damage between years, plots protected with electric fencing consistently received the least amount of cervid damage and tracks (Fig. 3). The only treatment type that reduced damage to sunflowers was the electric fence (Table 1). Treatment effects on damage and plot use across both years, however, showed limited biological effect given that more data were collected in 2011 when minimal damage occurred. Across years, the mean proportion of damaged plants on electric fence plots was 0.01 (95% CI: 0.00 – 0.03), on control plots was 0.05 (95% CI: 0.00 – 0.33), on repellent fences was 0.04 (95% CI: 0.01 – 0.15) and on winged fences was 0.04 (95% CI: 0.01 – 0.15). Electric fencing was also the only treatment type that reduced cervid activity within sunflower plots (Table 1). The average bimonthly number of deer tracks that crossed plot perimeters on plots with electric fencing was 0.6 (95% CI: 0.3 – 1.1), on control plots was 18.5 (95% CI: 3.8 – 91.5), on repellent fence plots was 18.4 (95% CI: 11.4 – 29.7), and on winged plots was 16.8 (95% CI: 10.4 – 27.0). Electric fences also reduced the number of elk that crossed plot perimeters on a bimonthly basis, but the effect was lesser than for deer. An average of only 0.1 elk tracks crossed electric fence plot boundaries (95% CI: 0.0 – 0.2), while 4.3 crossed control plots (95% CI: 1.8 – 10.3), 3.4 crossed repellent plots (95% CI: 2.25.2) and 3.7 crossed winged plots (95% CI: 2.4 – 5.7). DISCUSSION As wildlife management agencies look for methods to reduce cervid damage to agricultural crops while maintaining deer and elk population sizes, non-lethal methods of crop protection will become increasingly important. We tested three methods for reducing deer and elk damage to sunflowers, a highvalue crop, but found that only polyrope electric fencing significantly reduced damage and use by deer and elk. Investigators have found different polyrope electric fence designs to be successful at reducing white-tailed deer damage to crops (Hygnstrom and Craven 1998, Seamans and VerCauteren 2006), but to 81 �our knowledge, this is the first study to test the 5-strand polyrope fence design on mule deer or elk. Polyrope appears to be effective at reducing deer and elk damage to sunflowers, providing a temporary and cost-effective option for producers to reduce depredation through non-lethal means. While the chemical repellent Plantskydd™ is advertised to imitate predator presence and induce fear in cervids, it was not consistently effective in our evaluation. Fear inducing repellents are generally more successful than repellents with other strategies (i.e., aversive taste or pain inducing; Wagner and Nolte 2001), and studies have found this repellent to reduce black-tailed deer damage to tree seedlings (Nolte 1998, Wagner and Nolte 2001). In our sunflower plots, however, the repellent did not reduce mule deer or elk damage or tracks, a result which may be influenced by numerous factors including: animal habituation, availability of native forage, local weather conditions, animal nutritional state, repellent concentration, or the frequency of repellant application (Kimball et al. 2009, Walter et al. 2010, Elmeros et al. 2011). Indeed, drought conditions in 2012 may have increased motivation by deer and elk to forage on sunflowers, despite the repellent odor. We applied repellent once/month to treatment plots. While >1 application/month may have increased effectiveness of the treatment, such a high frequency of applications would not be feasible for most sunflower producers, and therefore, not particularly useful as a routine damage management tool. The winged fence we used also did not decrease deer and elk damage and use of the plots. In contrast, Hildreth et al. (2012) found winged fencing reduced white-tailed deer depredation to corn by 13.5%. Based on profits from the yield of corn and the cost of fence construction, Hildreth et al. (2012) concluded that corn producers could save approximately $205/ha/annually by using a winged fence along the agriculture-wildland interface. In our experiment, damage in winged plots was lesser than control plots in 7 of 8 fields, but did not have a strong treatment effect. We often observed elk and deer tracks along the partial portion of the fence to cross into the plot at the termination of the wing. DeVault et al. (2008) reported similar results in which white-tailed deer (Odocoileus virginianus) traveled around partial fences at an airport runway to gain access to crop fields. Animal habituation and motivation, crop palatability, and wing length may all influence the success of this approach. We placed the fully fenced treatment side against the dominant wildland boundary, but the complex juxtaposition of agricultural fields and canyons in southwestern Colorado may reduce the utility of this approach in this region. This exclusionary method may perform better in a more homogenous landscape. Given that the number of elk tracks remained fairly consistent between years, while the number of deer tracks was greater in 2012, it appears that the greater damage rates in 2012 were primarily attributable to deer crop depredation. Elk in the vicinity of Dove Creek migrate seasonally, often arriving at agricultural areas during summer, and spending the remainder of the year in secluded, wildland canyons (CPW, unpublished data). In contrast, mule deer often inhabit agricultural areas year-round (CPW, unpublished data), potentially increasing their habituation to novel structures and odors. In the case of electric fencing, smaller bodied deer are more likely able to breach the strands of polyrope, an obstacle which may be more effective at inhibiting larger-bodied elk. Despite differences in habitat-use patterns, behavior and morphology of deer and elk, polyrope electric fences were effective at reducing crop damage for both species. We tested three techniques for reducing damage to sunflowers during 2011 and 2012, years when crop depredation was dramatically variable. In 2011, deer and elk damage to sunflowers averaged 1%, well within tolerance levels for farmers as evidenced by no damage claims filed by farmers that year (CPW, unpublished data). Spring and summer (Mar-Aug) precipitation was exceedingly high during 2011 (Weather Station DVCO1, Colorado Agricultural Meteorological Network 2012), ~153% of normal, and it appears that the availability of abundant natural forage likely reduced damage by deer and elk. In 2012, however, the Dove Creek region experienced a drought, receiving about 60% of spring and summer precipitation, and only 30% of average spring (Mar-Jun) rainfall, a critical time for dryland farming in 82 �southwest Colorado. Soil moisture was so low in 2012 that few producers planted sunflowers, and the majority of seeds planted in some fields never germinated. We suspect that observed differences in plot damage and use between 2011 and 2012 were largely driven by differences in weather, and the resulting effects on the native vegetation for deer and elk. High temporal and spatial variability in cervid damage, as observed in this study, is particularly challenging for producers and wildlife management agencies seeking solutions to reduce depredation. Such variability may reduce the motivation of producers to protect crops and alter priorities of wildlife managers, depending on whether cervid damage is severe or minimal in a particular year or area. This variability in damage also highlights the utility of a temporary method, like polyrope electric fence, for protecting crops when damage is expected to be high (e.g., in drought years). Ultimately, however, the decision to invest in a tool like polyrope electric fencing will depend on field size, expected amount of damage, crop prices, and the frequency and duration a producer will need to use the fencing, particularly for rotational crops. MANAGEMENT IMPLICATIONS For wildlife agencies seeking non-lethal management options for reducing deer and elk damage to high-value agricultural crops, we found that 5-strand polyrope electric fencing was effective. Polyrope is easy to assemble/disassemble, cost-effective relative to permanent fencing, and can be used on a temporary basis to minimize damage for certain crops grown on rotation or during years when natural forage for cervids is scarce. In areas where management agencies are working to maintain or increase deer and elk populations, but reduce cervid damage, the application of an effective exclusion technique like polyrope electric fencing could protect high-value crops, decrease the need for compensation payments and lethal cervid depredation permits, and increase satisfaction of producers and the public. Wildlife agencies will need to continue to work with producers to test and apply management techniques for crop protection based on the wildlife species present, population densities, crop types, landscape configuration, and abundance of local forage. ACKNOWLEDGEMENTS We thank M. Glow, C. Priest, M. Preisler, A. Brown, A. Hildreth, M. Lavelle, G. Martin, D. Sanders, and B. Beltran-Beck for collecting field data and helping with fence construction. We also thank T. Brown and G. Phillips for help in purchasing fencing supplies, and A. Berrada, P. White and D. Fernandez for project support. This project would not have been possible without the cooperation of landowners around Dove Creek. Funding was provided by the USDA National Wildlife Research Center, Colorado Habitat Partnership Program, Montelores Habitat Partnership Program, Rocky Mountain Elk Foundation, and Colorado Auction/Raffle Grant program. 83 �LITERATURE CITED Austin, D. D., P. J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Bolker, B. M., M. E. Brooks, C. J. Clark, S. W. Geange, J. R. Poulsen, M. H. H. Stevens, and J.S. S. White. 2009. Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology and Evolution 24:127-135. Burnham, K. P., and D. R. Anderson. Model selection and multimodel inference: a practical informationtheoretic approach. Second Edition. Springer-Verlag, New York, New York USA. Colorado Agricultural Meteorological Network. 2012. 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Wildlife Society Bulletin 34:191-200. VerCauteren, K. C., R. Dolbeer, and E. Gese. 2012. Identification and management of wildlife damage. Pages 232-269 in N. Silvy, editor. The Wildlife Techniques Manual. Seventh edition. The John Hopkins University Press, Baltimore, Maryland, USA. Wagner, K. K., and D. L. Nolte. 2001. Comparison of active ingredients and delivery systems in deer repellents. Wildlife Society Bulletin 29:322-330. Wagner, K. K., R. H. Schmidt, and M. R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W. D., M. J. Lavelle, J. W. Fischer, T. L. Johnson, S. E. Hygnstrom, and K. C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Wisdom, M. J., and J. G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P. R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. 85 �Table 1. Coefficients for fixed effects from generalized linear mixed models evaluating the effectiveness of different treatment types for reducing cervid sunflower damage and the number of deer and elk tracks traversing experimental plot boundaries. Model Damage β SE P L 95% CI U 95% CI -3.020 1.169 <0.010 -5.311 -0.729 Electric* -2.227 0.943 0.018 -4.075 -0.379 Repellent -0.296 0.806 0.713 -1.876 1.284 Winged -0.108 0.709 0.879 -1.498 1.282 2.919 0.815 <0.001 1.322 4.516 Electric* -3.451 0.302 <0.001 -4.043 -2.859 Repellent -0.005 0.244 0.982 -0.483 0.473 Winged -0.100 0.244 0.684 -0.578 0.378 1.468 0.441 <0.001 0.604 2.332 Electric* -4.052 0.416 <0.001 -4.867 -3.237 Repellent -0.249 0.222 0.262 -0.684 0.186 Winged -0.163 0.221 0.460 -0.596 0.270 Variable Intercept* Treatment Deer Tracks Intercept* Treatment Elk Tracks Intercept* Treatment *Statistically significant at α = 0.05 level. 86 �Figure 1. Location of experimental treatment fields near Dove Creek, Colorado where exclusion and repellent methods for cervids were evaluated. 87 �Figure 2. A polyrope electric fence (A) and a partial winged fence (B) for excluding deer and elk from agricultural fields. A B 88 �Figure 3. Proportion of sunflower plants damaged at time of harvest (A) and number of deer and elk tracks that crossed plot boundaries (B), summarized across plots ( x and SE) for each treatment type, Dove Creek, Colorado, 2011 and 2012 A Proportion of Plants Damaged 50 2011 2012 40 30 20 10 0 Control No. of Tracks Crossing Plot Boundaries 100 90 80 70 Electric Repellent Winged Electric Repellent Winged B 2011 Deer 2012 Deer 2011 Elk 2012 Elk 60 50 40 30 20 10 0 Control Treatment Type 89 � https://cpw.cvlcollections.org/files/original/acfed9c505d6f6c4b56632119157f26f.pdf c927932ce857bdce9ae2eb5708c184c8 PDF Text Text Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 3.7 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. The widespread mortality of forested systems in Colorado is likely to have a dramatic, but poorly understood effect on wildlife species that depend on these habitats. The project described here uses occupancy estimation to determine which wildlife species (both species of conservation concern and game species) decrease their use of an area as bark beetles pass through, which increase their use, and which exhibit use similar to levels prior to infestation. Statewide sampling was conducted during the summers of 2013 and 2014 (Figure 2). We sampled 150 Engelmann spruce (Picea engelmanni)/subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that have yet to be impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Fieldwork for this phase of the project is now complete. However, data entry for 2014 is ongoing. For the purposes of this interim document, we report preliminary results for 3 mammalian species of conservation concern based on 2013 data only: snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus), which together comprise nearly 100% of the diet of the federally listed Canada lynx (Lynx canadensis), and American marten (Martes americana), which is a USFS Region 2 sensitive species. We collected 197,092 photos of 25 species during summer 2013. Occupancy analyses of these data indicate that snowshoe hares are more likely to use spruce/fir stands than lodgepole stands, but in both cases, use of these stands declines as bark beetle infestations pass by. We expected use to increase dramatically at some point as the understory responds to increased light, but that response will apparently take longer than the decade or so that has passed since the earliest infestations. Unlike hares, red squirrel use is similar for spruce/fir and lodgepole stands, but similar to hares, use of these stands declined after bark beetle infestations. This may be related to significant mortality of cone-bearing trees that occurs with beetle infestations. Use of the 2 stand types by marten was similar, but in contrast to the previous 2 species, use is expected to increase following bark beetle infestations. We expect to complete a full analysis and report for this project by Fall 2015. 1 �Figure 1. Current (2013) extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (blue-green) and lodgepole pine (bright green) forests in Colorado. Bark beetle data were collected via USFS aerial surveys. Figure 2. Sites sampled via point counts and remote cameras to assess impacts of bark beetle infestations on breeding bird and mammal species in spruce/fir (blue-green, N = 150) and lodgepole pine (bright green, N = 150) stands in Colorado, 2013−2014. 2 �1.0 0.9 0.8 - Lodgepole - Spruce/Fir 10 12 0.7 [,' o,6 C C'O §- 0.5 (.) (.) O 0.4 0.3 0.2 0.1 0.0 2 0 4 6 8 Years Since Initial Infestation Figure 3. Snowshoe hare occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir stands is generally higher than use of lodgepole stands, but in both strata, use is expected to decline through time as bark beetles pass over an area. 1.0 0.9 0.8 >, 0.7 g 0.6 co g-o.5 (.) (.) 0.4 0 0.3 0.2 0.1 0.0 0 2 4 6 8 10 12 Years Since Initial Infestation Figure 4. Red squirrel occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir and lodgepole stands is generally similar (only a single line here compared to 2 lines for snowshoe hares above) and is predicted to decline through time as bark beetles pass over an area. 3 �1.0 0.9 0.8 0.7 i:,'o,6 C: Cll g-o.s (.) (.) 0 0.4 0.3 0.2 0.1 0.0 0 2 4 6 8 10 12 Years Since Initial Infestation Figure 3. American marten occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir and lodgepole stands is generally similar (only a single line here compared to 2 lines for snowshoe hares above) and is predicted to increase through time as bark beetles pass over an area. 4 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 4 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. The widespread mortality of forested systems in Colorado may have a dramatic, but poorly understood effect on wildlife species that depend on these habitats. The project described here uses occupancy estimation to determine which wildlife species (both species of conservation concern and game species) decrease their use of an area as bark beetles pass through, which increase their use, and which exhibit use similar to levels prior to infestation. Statewide sampling was conducted during the summers of 2013 and 2014 (Figure 2). We sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that have yet to be impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (26 mammalian species). For the purposes of this interim document, we report preliminary results for 3 mammalian species of conservation concern: snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus), which together comprise nearly 100% of the diet of the federally listed Canada lynx, and American marten (Martes americana), which is a USFS Region 2 sensitive species. Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we fit a base model with parameters for the spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover, amount of down wood, amount of bare ground, and three physiographic variables that collectively account for elevation, moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linearly, quadratic, spline, change-point, etc.) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum and/or response to beetles and the severity of the impact (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set to provide a best estimate of response of each species to beetles. 1 �Results indicate that snowshoe hares are more likely to use spruce-fir stands than lodgepole stands (Figure 3). There may be a slight increase in use around the time needles drop, followed by a steady fall back to ‘green’ forest levels, but in general hare use remained relatively constant for the initial decade after bark beetle infestation. Red squirrel use was similar between the two stand types (Figure 4). However, best fitting models included an interaction between severity of the beetle outbreak and response of red squirrels. In areas of low severity, response was minimal (Figure 4a). However, in areas of high severity, red squirrel use was 25−35% lower (Figure 4b). Use of the two stand types by marten was similar and relatively invariant to beetle impact (Figure 5). Literature Cited Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Figure 1. Current (2014) extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (blue-green) and lodgepole pine (bright green) forests in Colorado. Bark beetle data were collected via USFS aerial surveys. 2 �Figure 2. Sites sampled via point counts and remotes cameras to assess impacts of bark beetle infestations on breeding bird and mammal species in spruce/fir (blue-green, N = 150) and lodgepole pine (bright green, N = 150) stands in Colorado, 2013−2014. 1.0 0.9 - Lodgepole Pine 0.8 - Spruce-Fir 0.7 {$' c: 0.6 co §- 0.5 8 0.4 0 :: ..~ - - -- -::===· -- - - ---------- - ~- - - - - -- 0.3 0.2 ------ -- - -- - - - - - ---- - - - - -- - - - ---- -- -- - - - - 0.1 0.0 - + - - . . - - . - - - - . - - - - r - - - , - - - r - - - , - - , - - - , - - - , - - - . - - - , Figure 3. Snowshoe hare occupancy (i.e., use) of stands in relation to stage of infestation by bark beetles. ‘Green’ forests are those that have not yet been impacted. ‘Red’ forests are recently impacted; dead needles remain on trees. ‘Silver’ forests were impacted more distantly in the past and needles have fallen. Numbers in parentheses approximately correspond to the number of years that have passed since trees initially turned red. 3 �a) 1.0 0.9 0.8 0.7 ~ 0.6 --- - - - ---- - - - -- ------ -- -------- ---------- -- -- - --- ----- --------- ---- ---- - ---- ---- ------------------ ------ ---- ffi 0.5 a. i3 0.4 --------------------- -------- --------- ,... - ---- - - - (.) O 0.3 - Lodgepole Pine, 25% dead 0.2 - spur ce-fir, 25%dead 0.1 0.0 + - - ~ , - - - , - - , - , - - , - ~ , - - , - - , - ~ , - - - , -, -- , b) 1.0 Lodgepole Pine, 75% dead 0.9 Spruce-fi r, 75%dead 0.8 ----------- -------- --- ------ 0.7 ~ 0.6 ffi 0.5 a. i3 0.4 ----------------- - - - - ...... _______ _ (.) O 0.3 0.2 -- -- - -- ----------- 0.1 0.0 + - - ~ , - - - , - - , ~ , ~ ~ , - - , - - , - ~ , - - - , - - , - - , ~ , Figure 4. Red squirrel occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Use of spruce-fir and lodgepole stands is generally similar and remains stable for stands that are lightly impacted by beetles (a; 25% dead). However, red squirrel occupancy is reduced by 25-35% in stands that are heavily impacted (b; 75% dead). 4 �1.0 0.9 - Lodgepole Pine - spruce-Fir 0.8 --_-_-..---..-_............ - -_-_-_- 0.7 ~ 0.6 ffi 0.5 B o.4 a. Cl O 0.3 0.2 -- --- - - - - - ------ --- - - --- - --- - - - --- - - -- -- -- ----- ---- --- --- 0.1 0.0 +---.------,-----r----r-----,-----.----r---r---..-----,r-----.----, Figure 5. American marten occupancy (i.e., use) of stands in relation to stage of infestation by bark beetles. Use does not vary appreciably by stand type, and remains stable through time as bark beetles pass over an area. 5 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2015  June 30, 2016 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 4 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future, which in turn may have dramatic, but poorly understood effects on wildlife species that depend on these habitats. This project used occupancy estimation to determine statewide wildlife response to bark beetle outbreaks, as mediated by changes in forest structure. Surveys were conducted during the summers of 2013 and 2014. We randomly sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that were not impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (26 mammalian species). Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we fit a base model with parameters for the spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover, amount of down wood, amount of bare ground, and three physiographic variables that collectively account for elevation, moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linear, quadratic, 3rd order polynomial, or change points when needles drop following an outbreak) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum or the severity of the outbreak (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set (i.e., ‘year since beetle outbreak’ was treated as a group such that parameters for each group could be averaged across all models in the set) to provide a best estimate of response of each species to beetles. Note that because we sampled mobile animals in a continuous landscape, ‘occupancy’ in this case refers to the probability that a species uses the forest stand which the camera was placed. 1 �Mean responses indicate that use of subalpine forest by elk (Figure 2) and mule deer (Figure 3) increased after stands were impacted by bark beetles (either through time or with increasing severity). Use by red squirrels (Figure 4) and coyotes (Figure 5) declined. Use by red fox (Figure 6) and black bears (Figure 7) was mixed as it increased through time after an outbreak, but may have declined with increasing severity. Snowshoe hares (Figure 9), and American martens (Figure 10) were largely unaffected by bark beetles in terms of their use of a stand as a function of beetle outbreaks. Both red squirrels and snowshoe hares used spruce-fir stands more heavily than lodgepole stands. Data from other species was too sparse to support fitting of the suite of models presented here. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Figure 1. Extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (bluegreen) and lodgepole pine (bright green) forests in Colorado, 2014. Data were summarized from USFS Aerial Surveys. 2 �10% Dead , .o 0.9 o.a o.a 0.7 0.7 o.• g o.• il o.s ~ o.s g s •O O • • •-••••••••••• •• • •• ••• ••••• •••• ~ 0.◄ 0.l 90% Dead 1.0 0.9 i I O.◄ _j 0. l · --. 0.2 ~ 0 .2 0.1 0,1 0.0 0.0 10 11 10 11 Years Since Outbreak Years Since Outbreak Figure 2. Elk occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas Dotted lines indicate 95% confidence intervals. Color bar indicates approximately when forest canopy changes from green to red (dead needles) to gray (no needles) following a bark beetle outbreak. 10% Dead 1.0 0.9 0.9 ---·· 0.8 0.8 0.7 g 90% Dead 1.0 0.7 g 0.b il , o.s 0.b il o.s s ~ o., 0.l ...-· • ••••·•··················- .. O. ◄ 0.l 0.2 • 0.2 0.1 o., 0.0 0.0 10 10 11 Years Since Outbreak 11 Years Since Outbreak Figure 3. Mule Deer occupancy occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 10% Dead ,.o - ....= .. J.9 J.9 , .a ).8 J.7 ).7 r; ,,.s.• r; ~ ,.• 90% Dead 1.0 SpnJoo-Fir Lodgepol8 " - Spruce-Fir - Lodge~t-~ . ·- •• ·····--·--·-· ).6 ).5 ~ ,.• ,., ,., J.3 ,., , .1 ).1 ,.o ,.o 10 10 11 Years Since Outbreak 11 Years Since 0Ltbteak Figure 4. Red squirrel occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 3 �HJ% Dead 1_0 0-1 g o_. I 90% Dead 1_0 o_, o_, 0.9 0,8 -.. ..... 0-7 g o.~ - a 0.5 o_, o_, o_, so., o_, 0_2 0.2 ••••·•··· 0_1 0_1 00 ••••••• ····· 0.0 11 10 11 10 ■■■■■■■.:::==v.=.=,,:s;:1nc =•=0u =,br:e:a:k=====--- Years Since Outbreak Figure 5. Coyote occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 10% Dead 1_0 0,9 o_s 0,1 o_, o_, .. •·· .- g 0.6 ; g a 0. 5 05 so., 0,) 0.) 0,1 / 0.6 ~ o., 0_2 90% Dead 1_0 0_9 ·--~----·-···· ········ ..• - ... ·········-- 0.2 - - - - - :··········· : - -:~ -··· ••• ------------------ 0, 1 o_o o_o 11 10 10 Years Since Outbreak 11 Years Since Outbreak Figure 6. Red Fox occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 10%Dead 1.0 90% Dead ,_o 09 09 0.8 0.8 0-1 ~ 0 .6 ~ 0 .6 g. 0.5 g. 0.5 ~ 0 .4 ~ 0.4 O.J o_, 0.2 0-2 0,1 ._, o.o 0 -0 10 11 10 YeArs Sioce Outbreak 11 Years Since Outbreak Figure 7. Black bear occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 4 �HJ% Dead 1.0 0.9 0.8 o.a 0.7 0.7 g 0.6 g 0.6 ~ 0.5 ~ 0.4 90% Dead 1.0 0.9 0.5 ~ o., ··············,······························"···•············ ~ 0.3 0.l 0.2 0.2 0.1 0.1 $pruc:e-Fw - L- ..-•·· ····••••• ...•···· ••••••••• - ·-..................................................... ··-... 0.0 0.0 10 10 11 11 Years Since Outbreak Years Since Outbreak Figure 8. Snowshoe Hare occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. HJ% Dead 1.0 g 0.9 0.8 0.8 0.7 0,7 O.b g 0.6 a. a 0.5 0., ,a. 0.5 ~ o., 90% Dead 1.0 0.9 ···············-·········· ......... ·---···· •••••••••••• ~ 0.l 0.) 0.2 0.2 0,1 0,1 0.0 0.0 10 11 10 Years Since Outbreak 11 Years Since Outbreak Figure 9. American marten occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 5 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2016  June 30, 2017 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT: Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting over 4 million acres since the initial outbreak in 1996. Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. Here we used occupancy estimation to determine statewide wildlife response to bark beetle outbreaks, as mediated by changes in forest structure. Surveys were conducted during the summers of 2013 and 2014. We randomly sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that were not impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 (0.4 mi2) site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (25 mammalian species). Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we identified the best-fitting ‘base’ model from among all combinations of 0-4 of the following variables: spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover due to deciduous species, shrub cover due to conifer species, shrub height, amount of down wood, amount of bare ground, and four physiographic variables that collectively account for elevation, topographic position (e.g., valley bottom, ridge top), moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linear, quadratic, 3rd order polynomial, or change points when needles drop following an outbreak) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum or the severity of the outbreak (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set (i.e., ‘year since beetle outbreak’ was treated as a group such that parameters for each group could be averaged across all models in the set) to provide a best estimate of response of each species to beetles. As per our hypotheses, results suggest that ungulate species are positively associated with bark beetle outbreaks, although the shape and nature of their responses was variable (Fig. 1). Also not 2 �surprisingly, granivore species comprised the majority of species that were negatively associated with bark beetle outbreaks, although again the magnitude and shape of responses was variable (Fig. 2). We did not detect any response to bark beetles by American marten or black bears (Fig. 3). Snowshoe hares did not follow expectation either, as their use did not markedly increase through time with increasing development of a dense understory (Fig. 3). Both red squirrels and snowshoe hares used spruce-fir stands more heavily than lodgepole stands. 10% Dead ... ... ... ... •• Q) V, L< •• 1.1 1.1 ~ :.0 ro .0 0 ~ a... .r ---- . ... ~ .. .~ · ., ...~ .. • . •• • ::> .._ ,. 0 50% Dead • .. •• . ••... ..... •• ... • " ; " u ... • i u u ...., . ~ , , ~·.. • " ... .. u , r- ..." ~ •• , u ... ...•• 90% Dead • • , u u ...... , . , . ~ ... . . , •• I u • • " Years Since Outbreak Figure 1. Species that exhibited a positive association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for elk, mule deer, and moose. Probably of use was estimated to vary little between the spruce-fir and lodgepole pine stands, so responses are pooled among strata for these species. Shaded areas represent model-averaged 95% confidence intervals. 3 �,.. 10% Dea<! •• •• ., ., u u • • • ,. .... => . - .. 0 ~ (1) .0 • • • , .. ... " u u •• ·- - - - - ,. • • u ... •• .. . u • ' .. • • ' " .. • • ' " .... . •• ... •• u " .. •'-----,. • •• u • ~ u ... ,, ---- .. " ..••. u • • OU .... • .... • u •• ...•• •• ,. u .. ., e ... a.. ... ,. . .. -----.. .. :a •• .... ~ .,.,,, ... •• rJ) 90% Dead •• ... •• Q) SO% Dead ..•• .. u L?• ,, " I Years Since Outbreak Figure 2. Species that exhibited a negative association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for red squirrel, golden-mantled ground squirrel, chipmunk spp., and coyote. For red squirrels, use was estimated to vary between the spruce-fir (blue) and lodgepole pine stands (gray); for other species, habitat strata was less important and responses are pooled across habitat types. Shaded areas represent model-averaged 95% confidence intervals. 4 �,.. 10% Dea<! .. •• •• , . u .. • .,, ... e a.. • • • ,. ..., • • " ..... .. .. ---u . • u H u u .. • ,. ., .. • , .. •• ... ... ,. , .... ~ ., :0 ,. Ill .0 u tJ 0 ~ ... . . ,.-----..__ ... ... - .. rJ) ::) ..•• ... ... ., 90% Dead u .. • • , •• Q) 50% Dead .... ... .. u ,. .... , • " ,,; . , •• ... ,, .. .. . u • • " ...•• .. " • .. • • • " .. , u •• u .. U• .. ,, I Years Since Outbreak • • ,, Figure 3. Species that exhibited a little association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for American marten, black bear, snowshoe hare, and porcupine. For snowshoe hares, and porcupine, use was estimated to vary between the sprucefir (blue) and lodgepole pine stands (gray); for other species, habitat strata was less important and responses are pooled across habitat types. Shaded areas represent model-averaged 95% confidence intervals. 5 �10% Dead .... .. Q) 0 ., .., u z- •• • ,. ... . .... .. •• :.0 (I) •• ------------- ...u •• ,, ' • ' I ' • ' ' •' ' ' ' ' I ..•• u 0 Cl.. ., Ll • .. • . , ....... 1-... ...., ~ .. . • • •• .0 •• •• ... ::::, •• 90% Dead .... ••• •• (JJ 50% Dead u ; ' I Years Since Outbreak Figure 4. Species that exhibited mixed associations between use of forested stands and beetle activity (positive association with YSO but negative with severity, or vice-versa). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show responses for red fox and yellow-bellied marmot. Use was estimated to vary little between the spruce-fir and lodgepole pine stands, so responses are pooled among strata for these species. Shaded areas represent model-averaged 95% confidence intervals. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populationsof marked animals. 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S. Ivan Personnel: M. Rice, P. Lukacs, T. Shenk (National Park Service), D. Theobald (Colorado State University), E. Odell All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). The purpose of this project was to develop a statewide predictive map of relative lynx use based upon location data collected during the reintroduction period. To build the map, we divided the state into 1.5 km × 1.5 km cells and tallied the number of locations in each cell. We then fit models to these count data using vegetation, elevation, slope, wetness, and degree of human development in each cell as predictor variables. We produced models for both summer and winter habitat use. We found that regardless of season, lynx were positively associated with spruce/fir (Picea engelmannii/Abies lasiocarpa), mixed spruce/fir, aspen (Populus tremuloides), elevation and slope; they were negatively associated with distance to large forest patches. During summer, lynx use of lodgepole pine (Pinus contorta) stands was predicted to increase. Lynx were predicted to avoid montane forest (Douglas-fir [Pseudotsuga menziesii], Ponderosa pine [Pinus ponderosa]), and areas near high traffic volume road segments, especially during summer. These maps of predicted lynx use should aid land managers in prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx and lynx habitat. 21 �WILDLIFE RESEARCH REPORT PREDICTED LYNX HABITAT IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Use location data collected during Canada lynx (Lynx canadensis) reintroduction to build a model of relative use, then apply this model statewide to produce a predictive map of relative lynx use for Colorado. SEGMENT OBJECTIVES 1. Compile and filter raw location data to isolate highest quality lynx locations. 2. Compile spatial data for use as covariates for the model (e.g. vegetation type, elevation, etc). 3. Build a series of candidate models to explain variation on locations across the landscape using covariate data layers. 4. Model-average predictions from all candidate models to produce a maps of predicted relative use for Colorado. INTRODUCTION In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW], Devineau et al. 2010). In 2010, CPW determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). Attainment of this goal is a conservation success, but it has also created a series of issues for land management agencies to consider as they plan changes to the landscape. These issues require knowledge of the types of landscapes and forest stands important for reproduction, movement, dispersal, and general home range use by lynx. As a first step toward providing this information, Theobald and Shenk (2011) conducted an analysis to describe the types of areas that were known to be used by re-introduced lynx. Specifically, they used LoCoH (Getz and Wilmers 2004, Getz et al. 2007) methods to create a population-level utilization distribution (UD, a probability surface of lynx occurrence) for lynx in Colorado. They then summarized landscape attributes within the 90% isopleth (i.e., polygon(s) containing 90% of the probability surface) of this UD. This work provides valuable information regarding the types of areas that were known to be used by lynx from 1999 to 2010. By nature of the data collection and research focus, most of this “use” information was derived from core areas in the San Juan Mountains of southwest Colorado and Sawatch Range in the central part of the state. The purpose of the current project is to extend the work of Theobald and Shenk (2011) by producing a map of predicted lynx use on a statewide scale. Such an exercise will identify areas within Colorado that should contain high quality lynx habitat, regardless of whether or not it was used by the sample of radio-telemetered individuals tracked during reintroduction research. Both works have strengths and weaknesses, but together they provide tools for prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx. 22 �METHODS Location Data Location data were collected from reintroduced lynx using 2 types of telemetry devices. All lynx released into Colorado, and those subsequently captured or re-captured, were fitted with a traditional VHF transmitter. VHF data were collected via telemetry from fixed-wing aircraft at approximately weekly intervals when research was ongoing during winter (approximately December – March) and reproductive seasons (May – June), but less often otherwise. Beginning in April 2000, released and captured lynx were outfitted with dual VHF-Argos satellite collars. In addition to sampling via fixed-wing aircraft, the satellite portion of these collars transmitted repeatedly for 12 hours, 1 day per week, year-round. Nearly 40,000 combined locations were collected between VHF and satellite sampling. These data were originally intended for assessing the success of the reintroduction and served CDOW well in estimating survival, productivity, and dispersal. They were not intended for use in constructing a predictive map of habitat use. We used only the best subset of these data following the filters applied by Theobald and Shenk (2011). Specifically, locations obtained during the first 6 months post-release were removed in order to exclude atypical movements made by animals that had not yet settled into home ranges. Next, poor precision satellite data (e.g., Argos location codes A, B, Z, 0 which do not have associated error estimates) were filtered out because they were too unreliable to be informative of lynx habitat use. We minimized dependence among locations (satellite collars transmitted several times per day, and a VHF location could have been obtained during the same day as well) by retaining only the most precise location for each lynx on a given day. When ties occurred, a single location was randomly selected from among the most precise locations. Finally, we discarded all data from lynx that were located fewer than 30 times over the course of the study. Predictor variables After filtering the location data, we assembled raw covariate data. We obtained housing density (HDENS, units per 1000 ha), road density (RDENS, km/km2 − all roads), slope (SLOPE), elevation (ELEV), topographic wetness (TW), distance to high-volume road segments (D10K, annual average daily traffic volume > 10,000 vehicles), and distance to mesic forest patches >50 ha (D50HA) from Theobald and Shenk (2011). We also downloaded vegetation data from the Colorado Vegetation Classification Project (CVCP, Colorado Division of Wildlife, U.S. Department of Interior Bureau of Land Management, U.S. Forest Service. http://ndis.nrel.colostate.edu/coveg/). CVCP is geographically limited to Colorado, but it accurately depicts many vegetation types that may be important to lynx including riparian zones and willow. Other vegetation data sources (i.e., LANDFIRE) have the advantage of a larger spatial extent, but classification of these non-forest vegetation types is not as detailed. We reclassified the 114 vegetation types in CVCP into 17 classes to simplify the number of covariates available for analysis (Appendix 1). Next, we divided the western portion of Colorado into 1.5 km × 1.5 km cells, which corresponds to 1 SD of the error distribution for the most imprecise (satellite) locations retained for analysis, as well as the smallest 90% UD observed for an individual lynx (Theobald and Shenk 2011). We computed the proportion of different vegetation types in each cell as well as mean SLOPE, ELEV, TW, HDENS, RDENS, D10K, and D50HA. We excluded cells with mean elevations <2,438m (8000 ft), assuming such cells do not provide habitat for lynx. This cutoff is consistent with previous literature (McKelvey et al. 2000, Ruediger et al. 2000), and over 99% of locations from our dataset were above 2,438m. We then standardized each covariate using all cells we intended to make predictions for. To maximize precision of parameter estimates and guard against erroneous predictions later on, we computed a correlation matrix between the potential explanatory variables but none were highly correlated (correlation coefficients were all <0.52 for covariates listed here). 23 �Analysis The response variable of interest for our models was the number of locations per individual in each cell, which we sought to predict using landscape attributes of the cells. We only used cells with ≥1 location for the purpose of constructing models. Excluding cells with no locations (zero counts) results in models that reflect relative use by lynx rather than resource selection. Thus in the generation of the model, we avoided delineation of what was available and suitable to lynx but never used (i.e., we avoided decisions regarding how many zero-count cells to include in the dataset and where they should come from on the landscape), which is a criticism of resource selection approaches. Furthermore, given ~10 years of work including weekly locations on hundreds of animals, we argue that nearly all cells in the Core Study Area that were suitable and available included ≥1 lynx location. This approach does, however, warrant the use of zero-truncated probability models to avoid possibly introducing bias in parameter estimates (Zuur et al. 2009, p. 269). In addition, we expected the data to be over-dispersed (variance of the counts was expected to be larger than the mean), we knew the number of locations collected per animal varied considerably, and we anticipated spatial autocorrelation in the residuals. To evaluate these assertions and determine the best model structure for our data, we successively compared the fits of a basic Poisson generalized linear model (GLM), negative binomial GLM, zero-truncated negative binomial (ZTNB), and ZTNB with an offset. We compared the fit of these alternate structures using Akaike’s Information Criterion (AIC, Burnham and Anderson 2002) and found that fitting a basic negative binomial GLM was an improvement over a Poisson (ΔAIC = 700.4), ZTNB was an improvement over the negative binomial (ΔAIC = 6463.0), and ZTNB with an offset provided the best fit (ΔAIC = 53.7). Thus, we used a ZTNB with an offset as the base model structure. We fit all models using the VGAM package (Yee 2010, 2011) in R (R Core Development Team 2011). To assess spatial autocorrelation we computed a variogram using the gstat package (Pebesma 2004) and standardized residuals from a highly parameterized model (including all covariates below; Figure 1). We found minimal autocorrelation, so we proceeded to build ZTNB models absent spatial structure in the error term. Within the general ZTNB model structure, we specified the candidate model set by including combinations of covariates for modeling the mean count for each cell as follows: 1) Lynx are associated with conifer forests and deep snow, and they rely heavily on snowshoe hares. In the Southern Rockies, lynx occur largely in conifer stands within the sub-alpine zone (Aubry et al. 2000). Therefore, we included proportion spruce/fir (SF, Picea engelmannii/Abies lasiocarpa,), mixed spruce/fir (MIXSF, spruce/fir mixed with Douglas-fir [Pseudotsuga menziesii], aspen [Populus tremuloides], and/or lodgepole pine [Pinus contorta], distance to forest patch >50ha (D50HA), ELEV, and SLOPE in every model. We expected positive associations with each of these covariates except D50HA, which we expected to be negative. 2) Research conducted during the reintroduction of lynx into Colorado focused primarily in the southern portion of the state. Lodgepole pine (LODGE) occurs only in the northern portion of the state, so we know relatively little regarding the importance of this vegetation type with respect to habitat use by lynx. Therefore, we included a LODGE effect in some models, but when LODGE entered as a covariate, we also included a LODGE × latitude (NORTH) interaction to attempt to account for the distribution of this forest type in Colorado. Thus, lodgepole pine was allowed to be an important predictor of lynx use (or not) depending on latitude. 3) Vegetation types other than spruce/fir occur in or adjacent to the subalpine zone. We know relatively little about how lynx use these types but they may be important intermittently and/or as travel corridors. Therefore, we also built models that included combinations of montane forest (MONFOR: Douglas-fir, Ponderosa pine [Pinus ponderosa], and mixed Doug-fir/ponderosa pine), aspen (ASPEN), willow (WILLOW), and montane shrub (MONSHB: Gambel oak 24 �[Quercus gambelii], serviceberry [Amelanchier utahensis], and snowberry [Symphoricarpos sp.]). 4) Though lynx are considered a high elevation species, we opted to exclude “alpine” in any model because lynx are forest-dwelling, and there are few opportunities to manage structure of alpine areas, which included both alpine tundra and rock/snow/ice. 5) Lynx are often considered reclusive. Thus, covariates representing human development might be important predictors of habitats used (or not used) by lynx, and we initially considered HDENS, RDENS, and D10K as potential covariates to include in the model set. However, initial modelfitting resulted in HDENS and RDENS having slightly positive effects on lynx locations (but confidence intervals on these slopes were largely centered on zero indicating the effect was negligible), which is probably an artifact of the trapping/collaring effort that often occurred near roads due to logistical considerations. Many cells outside of those used to construct the models had HDENS and RDENS scores that were orders of magnitude above those used to construct the models. Thus, when projected to the entire set of cells covering western Colorado, these models predicted the best lynx habitat in highly developed, urban areas with high road density. Given this implausible result, we excluded HDENS and RDENS from the analysis. We retained D10K because high volume road segments occurred throughout broad areas used by lynx (nearly every state highway has high volume segments) and it did not result in completely implausible results. We expected counts of lynx locations to be positively associated with distance to high traffic volume road segments. 6) TW was excluded from all models after initial model-fitting produced a result similar to HDENS and RDENS. TW was positively associated with lynx locations, which seems reasonable, but when projected to the expanse of western Colorado, the best lynx habitat was predicted in heavily irrigated agricultural areas, residential lawns, and lakes. These features had TW values that were orders of magnitude larger than any forest-dominated cell. Note that this phenomenon, predicting beyond the range of data used to build the model, can be risky, and it may have operated similarly on other variables but went undetected. 7) Lynx often make long-distance movements outside of the winter season, and these movements may include use of many types of vegetation. Therefore, we fit the model set to summer locations (April through October) and then to winter locations (November through March). Seasonal definitions were based on mean daily movement patterns of telemetered lynx (Theobald and Shenk unpublished data). We expected that the association between lynx locations and vegetation types other than SF and MIXSF would vary with season, with more use of these perceived secondary types during summer. In summary, our model set included all combinations of 5 vegetation types (LODGE, MONFOR, ASPEN, WILLOW, MONSHB) and D10K. Each combination was always paired with the base covariates (SF, MIXSF, ELEV, SLOPE, D50HA) listed in 1) above. This resulted in 26 = 64 models. We used Akaike’s Information Criterion (AIC, Burnham and Anderson 2002) to determine which model structures best explained variation in lynx locations, to assess the importance of each covariate, and to model-average predictions of lynx use for each cell across all models. Predictions were defined as the probability of observing at least 10 locations in a cell over a hypothetical 10-year sampling period, which corresponds to an average of 1 location per year over the time frame of the actual data generating process. We color-coded predictions into 10 quantiles for display such that each color represents 10% of the total (i.e., the darkest red represents the predicted best 10% of cells, dark red plus deep orange represent the predicted best 20% of cells, etc.) 25 �RESULTS The final winter dataset consisted of 3,915 locations from 68 individuals (min = 30 locations/lynx, max = 113, mean = 57.6). Winter cell counts ranged from 1 to 29 (mean = 2.3). Summer data consisted of 5,464 locations from 74 individuals (min = 30, max = 178, mean = 73.8). Summer cell counts ranged from 1 to 36 total lynx locations (mean = 2.8). Predicted Winter Use As expected, relative predicted use by lynx during winter months was negatively associated with D50HA and positively associated with SF, MIXSF, ELEV, and SLOPE (Table 1). Of these associations, SF was strongest (largest magnitude and 95% confidence interval [±2×SE] was well away from zero), followed by ELEV, MIXSF, and D50HA, respectively. The parameter estimate for SLOPE was small and its 95% CI substantially overlapped zero in all models. Thus it was not important in explaining variation in predicted habitat use. Of the covariates that were not included in every model, ASPEN was strongly, positively associated with use and was the only effect in this group that was clearly different from zero. MONSHB was negatively associated with predicted lynx use, but evidence for this effect was weak. WILLOW, MONFOR, and D10K were somewhat positively associated with lynx use, but evidence for these effects was relatively weak as well. LODGE and NORTH did not appear in any of the top models (cumulative AIC weights = 0.12). The winter predictive map reflects the strong effect of SF. Arbitrarily defining the top 20% of predictions as high quality lynx habitat, there are 1,869,975 ha of such habitat in Colorado. Most of this is predicted to occur in the southern part of the state in the San Juan, Culebra, and Wet Mountain Ranges (Figure 2). In the central portion of the state, high predicted use is expected in the northern Sawatch and West Elk Ranges, along with Grand Mesa. The Park Range and Flat Tops comprise the best predicted winter lynx habitat farther north (Figure 2). Predicted Summer Use Associations between relative predicted summer use and SF, MIXSF, ELEV, SLOPE, and D50HA were similar to those observed during winter (Table 2). However, the association with SLOPE was much stronger (larger effect and 95% CI indicated clear separation from zero) during summer, possibly due to den site selection and attendance during this time of year. The association with D50HA was slighter stronger as well. Of the covariates not included in every model, MONFOR and MONSHB were negatively associated with lynx locations; LODGE, NORTH, ASPEN, WILLOW, and D10K were positively associated. The effects of MONFOR, ASPEN, and D10K were substantially different from zero based on 95% CIs. Effects of other covariates were not clearly different from zero. The summer predictive map reflects more dispersed predicted use by lynx with LODGE, NORTH, and the LODGE × NORTH interaction playing a larger role (Figure 3). The central and southern Sawatch Range in central Colorado is predicted to have more use than during winter, whereas use on Grand Mesa is predicted to decline. In the northern part of the state, lynx use is predicted to shift more toward the Medicine Bow and Front Ranges. Using the same definition as before, we predict 1,791,675 ha of high quality summer habitat in Colorado. The overlap between high quality summer and winter cells (as arbitrarily defined above) is ~95%. DISCUSSION The data analyzed here were not collected for the purpose of constructing a predictive map and suffer from at least two shortcomings. First, the locations were not precise. We attempted to account for 26 �this imprecision by modeling at a 1.5 km scale, but matching covariates, response variables, and predictions at this scale reduces the clarity of relationships and weakens the modeling process. Second, the bulk of the reintroduction research effort, from which these data originated, was conducted in the southern and central portions of Colorado. Lodgepole pine only occurs in the northern 2/3 of the state, and is dominant there. Thus, predicting lynx habitat use in northern Colorado is difficult because the landscape is very different, yet we have little data available to help model lynx response to that landscape. That is, we are extrapolating beyond the range of covariates used to fit the models, which is tenuous. Caution should be exercised in interpreting results north of I-70. In addition to issues regarding the location data, we also lack important vegetation data that could be crucial in making accurate predictions. Snowshoe hares (Lepus americanus) are tied to forests with dense understory cover throughout their range (Hodges 2000a;b), including Colorado (Dolbeer and Clark 1975, Zahratka and Shenk 2008, Ivan 2011). Given the close tie between hares and lynx, habitat use of the latter should be strongly tied to understory cover as well. However, we have no covariate data for understory. Our models treat all spruce/fir, mixed spruce/fir, and lodgepole forests equally, but the quality of these forests likely varies considerably. Additionally, pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) epidemics throughout the state are drastically changing the structure and composition of current and future forests. Our predictions are based on forest composition prior to these outbreaks. Despite these weaknesses, the predictive maps constructed here also have a distinct strength in that they were constructed objectively from rigorous mathematical models based on empirical data collected from wild lynx. They are the first such maps for Colorado. Results from this effort confirm relationships that were already known (e.g., lynx are strongly associated with high elevation spruce/fir and mixed spruce/fir forests but avoid lower elevation montane forests and montane shrublands), and highlight others that may be of interest. For instance, we found clear evidence that lynx use was positively associated with ASPEN during both summer and winter. It is unclear what the ecological relationship between the two might be and we have no causal evidence for ASPEN driving lynx use. However, this pattern is not a simple artifact of ASPEN occurring near SF or MIXSF − our preliminary vetting of potential covariates indicated that the correlation between ASPEN and SF or MIXSF was small and negative (-0.15 and -0.14, respectively). We also found evidence that lynx use of lodgepole forests may increase during summer, and that they tend to avoid areas near high traffic volume road segments, especially in summer. The strengths of this analysis and resulting maps merit their inclusion as a tool for making land management decisions. However, inherent weaknesses of the data require the reader to exercise caution when interpreting results. These maps should be viewed as a compliment to expert opinion and existing maps produced by other means. When assessing habitat quality for lynx at a given project site, it is imperative that managers consider current stand characteristics (especially understory) in formulating land use plans or specific management recommendations relative to lynx. LITERATURE CITED Aubry, K. B., G. M. Koehler, and J. R. Squires. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. 27 �Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty, P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Dolbeer, R. A., and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Getz, W. M., S. Fortmann-Roe, P. C. Cross, A. J. Lyons, S. J. Ryan, and C. C. Wilmers. 2007. LoCoH: Nonparameteric Kernel Methods for Constructing Home Ranges and Utilization Distributions. Plos One 2. Getz, W. M., and C. C. Wilmers. 2004. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27:489-505. Hodges, K. E. 2000a. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. _____. 2000b. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Ivan, J. S. 2011. Density, demography, and seasonal Movement of snowshoe hares in central Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. McKelvey, K. S., K. B. Aubry, and Y. K. Ortega. 2000. History and distribution of lynx in the contiguous United States. Pages 207-264 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Pebesma, E. J. 2004. Multivariable geostatistics in S: the gstat package. Computers & Geosciences 30:683-691. R Core Development Team. 2011. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3900051-07-0, URL http://www.R-project.org/. Ruediger, B., J. Claar, S. Gniadek, B. Holt, L. Lyle, S. Mighton, B. Naney, G. Patton, T. Rinaldi, J. Trick, A. Vendehey, F. Wahl, N. Warren, D. Wenger, and A. Williamson. 2000. Canada lynx conservation assessment and strategy. 2nd edition. R1-00-53, U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service, Missoula, Montana, USA. Shenk, T. M., and R. H. Kahn. 2010. The Colorado lynx reintroduction program. Colorado Division of Wildlife. Theobald, D. M., and T. M. Shenk. 2011. Areas of high habitat use from 1999-2010 for radio-collared Canada lynx reintroduced to Colorado. Colorado State University. Yee, T. W. 2010. The VGAM package for categorical data analysis. Journal of Statistical Software 32:134. _____. 2011. VGAM: Vector Generalized Linear and Additive Models. R package version 0.8-3. URL http://CRAN.R-project.org/package=VGAM. Zahratka, J. L., and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72:906-912. Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed Effects Models and Extensions in Ecology with R. Springer, New York, New York, USA. Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 28 �D10K MONSHB WILLOW ASPEN MONFOR LODGE: NORTH NORTH LODGE SLOPE ELEV D50HA MIXSF SF Table 1. Model selection results (top 10 of 64) and parameter estimates (SE) for zero-truncated negative binomial models fit to cell counts of Canada lynx locations collected during winter (November – March) 1999-2010, southwest and central Colorado, USA. AIC ΔAIC AIC Wt. K 0.53 0.15 -1.1 0.24 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.06 (0.08) (0.04) 4672.1 0.0 0.15 9 0.48 0.13 -1.09 0.29 0.04 (0.06) (0.07) (0.69) (0.11) (0.05) 0.26 (0.08) 4672.9 0.8 0.10 8 0.52 0.14 -1.09 0.21 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.07 -0.33 (0.08) (0.04) (0.38) 4673.2 1.1 0.09 10 0.53 0.17 -1.12 0.25 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.27 0.06 (0.08) (0.04) 0.08 4673.2 (0.09) 1.1 0.09 10 0.48 0.15 -1.12 0.3 0.04 (0.06) (0.08) (0.69) (0.11) (0.05) 0.25 (0.08) 0.09 4673.8 (0.09) 1.7 0.06 9 0.54 0.16 -1.1 0.27 0.07 (0.07) (0.08) (0.69) (0.13) (0.06) 0.08 0.29 0.06 (0.22) (0.08) (0.04) 4673.9 1.9 0.06 10 0.47 0.12 -1.09 0.27 0.04 (0.07) (0.07) (0.69) (0.11) (0.05) 0.26 (0.08) 4674.1 2.1 0.05 9 0.52 0.16 -1.12 0.22 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.06 -0.32 0.08 4674.3 (0.08) (0.04) (0.38) (0.09) 2.2 0.05 11 4674.8 2.8 0.04 9 0.08 4675.0 (0.09) 3.0 0.03 11 0.49 0.14 -1.1 0.31 0.04 (0.07) (0.08) (0.69) (0.13) (0.05) 0.05 0.26 (0.22) (0.08) 0.54 0.18 -1.13 0.27 0.07 (0.08) (0.08) (0.69) (0.13) (0.06) 0.08 0.28 0.06 (0.22) (0.08) (0.04) 29 -0.29 (0.37) �-2.75 (0.7) 0.34 0.26 0.11 (0.13) (0.05) (0.11) 0.08 (0.1) 0.24 (0.12) AIC ΔAIC AIC Wt. K 0.2 (0.08) 6684.3 0.0 0.13 13 0.2 (0.08) -0.66 (0.5) 0.2 (0.08) 6684.4 0.1 0.13 14 0.39 0.11 -2.76 0.19 0.24 (0.06) (0.06) (0.67) (0.11) (0.05) -1.81 0.14 (0.39) (0.08) -0.87 (0.51) 0.15 (0.07) 6684.6 0.3 0.11 11 0.41 0.13 -2.77 0.23 0.25 (0.06) (0.06) (0.67) (0.11) (0.05) -1.82 0.13 (0.39) (0.08) 0.15 (0.07) 6685.9 1.6 0.06 10 0.34 0.07 -2.95 (0.05) (0.06) (0.67) -1.84 (0.39) -0.76 (0.49) 0.16 (0.07) 6686.0 1.7 0.06 10 -1.78 0.15 (0.39) (0.08) -0.85 (0.5) 6686.2 1.9 0.05 10 0.2 (0.08) 6686.3 2.0 0.05 14 -0.67 (0.5) 0.19 (0.08) 6686.3 2.0 0.05 15 0.39 0.11 -2.77 0.2 0.24 (0.06) (0.06) (0.67) (0.11) (0.05) -1.81 0.14 0 -0.86 (0.39) (0.08) (0.04) (0.51) 0.15 (0.07) 6686.6 2.3 0.04 12 0.36 0.09 -2.94 0.13 0.25 (0.05) (0.06) (0.67) (0.09) (0.05) -1.86 (0.38) 0.16 (0.07) 6686.8 2.4 0.04 9 0.09 (0.1) 0.25 (0.05) 0.4 0.08 -2.75 0.21 0.25 (0.06) (0.06) (0.67) (0.11) (0.05) -1.65 (0.4) D10K 0.45 0.11 (0.07) (0.07) MONSHB LODGE: NORTH 0.25 -1.65 0.2 (0.12) (0.39) (0.08) WILLOW NORTH 0.08 (0.1) ASPEN LODGE 0.38 0.27 0.13 (0.12) (0.05) (0.11) SLOPE -2.74 (0.7) ELEV D50HA 0.47 0.11 (0.07) (0.07) SF MIXSF MONFOR Table 2. Model selection results (top 10 of 64) and parameter estimates (SE) for zero-truncated negative binomial models fit to cell counts of Canada lynx locations collected during summer (April – October) 1999-2010, southwest and central Colorado, USA. 0.47 0.12 (0.07) (0.07) -2.74 (0.7) 0.37 0.27 0.13 (0.12) (0.05) (0.11) 0.08 (0.1) 0.25 -1.65 0.2 0.01 (0.12) (0.39) (0.08) (0.04) 0.46 0.11 (0.07) (0.07) -2.74 (0.7) 0.33 0.27 0.11 (0.13) (0.05) (0.11) 0.07 (0.1) 0.24 (0.12) -1.65 (0.4) 30 0.2 0.01 (0.08) (0.04) �i I 0.8 - I I • • • • • • • • • • • • • • • 0.6 - Q) 0 C: ro ·;:: ro ..:: E Q) 0.4 - (/) 0.2 - I I I I 10 20 30 40 Distance (km) Figure 1. Variogram contructured using standardizied residuals from a highly parameterized model fit to count data of lynx locations within 1.5km × 1.5km cells, 1999-2011, southwestern and central Colorado. Variance among pairs of points is similar regardless of the distance separating them, indicative of a lack of residual spatial autocorrelation after fitting important covariate effects. Strong evidence of spatial autocorrelation in residuals would result in a graph with small variance between pairs points that are near to each other, and larger variance at greater distances (i.e., a monotonically increasing pattern). 31 �Predicted Lynx Habitat Use (Winter) Probability of observing >10 locations) - 0.000000 - 0.000001 - 0.445108 - 0.445109 - 0 .523365 D D o.523366 - o.557893 o.557894 - o.582060 D o.582061 - 0 .601338 - 0.601339 - 0 .618958 - 0.618959 - 0 .635619 - 0.635620 - 0 .650491 - 0.650492 - 0 .674444 Figure 2. Predicted winter habitat use by Canada lynx in western Colorado. Predictions are probabilities of observing at least 10 locations within a 1.5 × 1.5km cell over a hypothetical 10-year sampling period. Predictions were averaged across 64 models constructed using all combinations of covariates of interest. 32 �Predicted Lynx Habitat Use (Summer) Probability of observing >10 locations) - 0.000000 - 0.000001 - 0.097487 - 0 .097488 - 0.362282 D D D o.362283 - o.518213 o.518214 - o.596715 o.596716- o.632416 - 0.632417 - 0.651318 - 0.651319 - 0.664720 - 0 .664721 - 0.677897 - 0.677898 - 0.712318 Figure 3. Predicted summer habitat use by Canada lynx in western Colorado. Predictions are probabilities of observing at least 10 locations within a 1.5 × 1.5km cell over a hypothetical 10-year sampling period. Predictions were averaged across 64 models constructed using all combinations of covariates of interest. 33 �Appendix I. Raster reclassification of CVCP dataset for use in lynx predictive map analysis. Lynx Reclass Null 2 2 2 1 1 1 1 4 4 8.2 4 4 4 4 4 14 4 4 4 8.2 8.2 8.2 8.2 8.2 8.2 8.1 8.1 8.2 8.2 8.2 8.2 8.2 4 8.2 4 4 4 4 8.2 10 10 8.1 8.2 8.1 8.1 3.1 8.2 10 10 10 CVCP Value 0 1 2 3 4 5 6 7 8 9 10 11 12 13 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 43 44 46 47 48 49 50 51 53 54 55 Description Unclassified Urban/Built Up Residential Commercial Agriculture Land Dryland Ag Irrigated Ag Orchard Rangeland Grass/Forb Rangeland Snakeweed/Shrub Mix Grass Dominated Forb Dominated Grass/Forb Mix Mid-grass Prairie Short-grass Prairie Sand Dune Complex Foothill and Mountain Grasses Disturbed Rangeland Sparse Grass (Blowouts) Shrub/Brush Rangeland Sagebrush Community Saltbush Community Greasewood Sagebrush/Gambel Oak Mix Snakeweed Snowberry Snowberry/Shrub Mix Bitterbrush Community Salt Desert Shrub Community Sagebrush/Greasewood Shrub/Grass/Forb Mix Sagebrush/Grass Mix Rabbitbrush/Grass Mix Sagebrush/Mesic Mtn Shrub Mix Grass/Misc. Cactus Mix Winterfat/Grass Mix Bitterbrush/Grass Mix Grass/Yucca Mix Sagebrush/Rabbitbrush Mix Pinon-Juniper Juniper Gambel Oak Xeric Mountain Shrub Mix Mesic Mountain Shrub Mix Serviceberry/Shrub Mix Upland Willow/Shrub Mix Manzanita PJ-Oak Mix PJ-Sagebrush Mix PJ-Mtn Shrub Mix 34 �Lynx Reclass 10 10 10 10 11 8.1 13 9.1 13 12 9.1 9.1 9.2 13 13 13 9.2 9.2 9.2 13 9.1 13 13 13 13 12 9.2 13 13 14 6 6 1 2 7 7 7 7 7 6 7 7 3.2 3.2 3.2 3.1 3.2 3.1 3.2 3.2 3.2 5 CVCP Value 56 57 58 59 62 63 65 66 67 68 69 70 71 72 73 75 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 96 97 98 99 100 101 102 103 104 105 106 108 109 110 111 112 113 114 Description Sparse PJ/Shrub/Rock Mix Sparse Juniper/Shrub/Rock Mix Juniper/Sagebrush Mix Juniper/Mtn Shrub Mix Aspen Aspen/Mesic Mountain Shrub Mix Ponderosa Pine Englemann Spruce/Fir Mix Douglas Fir Lodgepole Pine Sub-Alpine Fir Spruce/Fir Regeneration Spruce/Lodgepole Pine Mix Bristlecone Pine Ponderosa Pine/Douglas Fir Mix Limber Pine Lodgepole/Spruce/Fir Mix Fir/Lodgepole Pine Mix Douglas Fir/Englemann Spruce Mix Mixed Forest Land Spruce/Fir/Aspen Mix P. Pine/Gambel Oak Mix Ponderosa Pine/Aspen Mix Douglas Fir/Aspen Mix P. Pine/Aspen/Gamble Oak Mix Lodgepole Pine/Aspen Mix Spruce/Fir/Lodgepole/Aspen Mix Ponderosa Pine/Mesic Mtn. Shrub Ponderosa Pine/Aspen/Mesic Mtn. Barren Land Rock Talus Slopes & Rock Outcrops Soil Disturbed Soil Alpine Meadow Alpine Forb Dominated Alpine Grass Dominated Alpine Grass/Forb Mix SubAlpine Shrub Community Snow Subalpine Meadow Subalpine Grass/Forb Mix Riparian Forested Riparian Cottonwood Conifer Riparian Shrub Riparian Willow Exotic Riparian Shrubs Herbaceous Riparian Sedge Water 35 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 0670 N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Predicted lynx habitat in Colorado N/A Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: M. Rice, P. Lukacs, T. Shenk (National Park Service), D. Theobald (Colorado State University), E. Odell All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). The purpose of this project was to develop a statewide predictive map of relative lynx use based upon location data collected during the reintroduction period. To build the map, we divided the state into 1.5 km × 1.5 km cells and tallied the number of locations in each cell. We then fit models to these count data using vegetation, elevation, slope, wetness, and degree of human development in each cell as predictor variables. We produced models for both summer and winter habitat use. We found that regardless of season, lynx were positively associated with spruce/fir (Picea engelmannii/Abies lasiocarpa), mixed spruce/fir, aspen (Populus tremuloides), elevation and slope; they were negatively associated with distance to large forest patches. During summer, lynx use of lodgepole pine (Pinus contorta) stands was predicted to increase. Lynx were predicted to avoid montane forest (Douglas-fir [Pseudotsuga menziesii], Ponderosa pine [Pinus ponderosa]), and areas near high traffic volume road segments, especially during summer. These maps of predicted lynx use should aid land managers in prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx and lynx habitat. 36 �WILDLIFE RESEARCH REPORT PREDICTED LYNX HABITAT IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Use location data collected during Canada lynx (Lynx canadensis) reintroduction to build a model of relative use, then apply this model statewide to produce a predictive map of relative lynx use for Colorado. SEGMENT OBJECTIVES 1. Prepare manuscript for submission to Journal of Wildlife Management. INTRODUCTION In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW], Devineau et al. 2010). In 2010, CPW determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). Attainment of this goal is a conservation success, but it has also created a series of issues for land management agencies to consider as they plan changes to the landscape. These issues require knowledge of the types of landscapes and forest stands important for reproduction, movement, dispersal, and general home range use by lynx. As a first step toward providing this information, Theobald and Shenk (2011) conducted an analysis to describe the types of areas that were known to be used by re-introduced lynx. Specifically, they used LoCoH (Getz and Wilmers 2004, Getz et al. 2007) methods to create a population-level utilization distribution (UD, a probability surface of lynx occurrence) for lynx in Colorado. They then summarized landscape attributes within the 90% isopleth (i.e., polygon(s) containing 90% of the probability surface) of this UD. This work provides valuable information regarding the types of areas that were known to be used by lynx from 1999 to 2010. By nature of the data collection and research focus, most of this “use” information was derived from core areas in the San Juan Mountains of southwest Colorado and Sawatch Range in the central part of the state. The purpose of the current project is to extend the work of Theobald and Shenk (2011) by producing a map of predicted lynx use on a statewide scale. Such an exercise will identify areas within Colorado that should contain high quality lynx habitat, regardless of whether or not it was used by the sample of radio-telemetered individuals tracked during reintroduction research. Both works have strengths and weaknesses, but together they provide tools for prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx. METHODS While this worked was completed in January 2012, the final report was included in revisions to the previous annual report and is not repeated here. We refer the reader to Ivan (2011) for details regarding methods and results from this work. Our intent is to work this report into a manuscript submission to Journal of Wildlife Management by Fall 2012. 37 �SUMMARY As expected, relative predicted use by lynx during winter months was negatively associated with distance to large patches of conifer (D50HA) and positively associated with spruce/fir (SF), mixed spruce/fir (MIXSF), elevation (ELEV) and slope . Of these associations, the relationship with spruce/fir was strongest. Predicted use was also positively associated with topographic wetness and aspen cover. We projected these associations (and other more minor associations included in competing models) onto a map of the state and arbitrarily defined the top 20% of predictions as high quality lynx habitat. There are 1,869,975 ha of such habitat in Colorado. Most of this high quality habitat was predicted to occur in the southern part of the state in the San Juan, Culebra, and Wet Mountain Ranges. In the central portion of the state, high predicted use is expected in the northern Sawatch and West Elk Ranges, along with Grand Mesa. The Park Range and Flat Tops comprised the best predicted winter lynx habitat farther north Associations between relative predicted summer use and SF, MIXSF, ELEV, slope, and D50HA were similar to those observed during winter. However, the associations with D50HA and slope were stronger during summer. We also found positive associations between lodgepole pine, aspen, and distance to high volume road segments. The summer predictive map reflects more dispersed predicted use by lynx with the lodgepole playing a larger role, especially farther north. The central and southern Sawatch Range in central Colorado is predicted to have more use than during winter, whereas use on Grand Mesa is predicted to decline. In the northern part of the state, lynx use was predicted to shift more toward the Medicine Bow and Front Ranges. LITERATURE CITED Ivan, J. S. 2011. Predicted lynx habitat in Colorado. Wildlife Research Report. Colorado Division of Parks and Wildlife, Fort Collins, CO, USA. Pages 21–35. Prepared by ___________________________ Jacob S. Ivan 38 � https://cpw.cvlcollections.org/files/original/12f296ca22f8138b094b66063aad8a4c.pdf 61237c58b17fe6f5592a656309257fac PDF Text Text Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Quantifying loss and degradation of mule deer habitat across western Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Sarah E. Reed, Jessica R. Sushinsky, Andy Holland, Trevor Balzer, Jim Garner All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. In recent decades, mule deer populations have declined across the western U.S., causing wildlife management agencies to seek factors limiting deer performance and strategies to increase their population sizes. The trend of declining mule deer populations has been primarily attributed to loss and degradation of deer habitat, through mechanisms such as urban/exurban development, resource extraction, agriculture, roads and vehicular traffic, fire suppression, and changing patterns in weather and plant productivity. While wildlife managers are well aware that these different factors can negatively affect deer populations, there is no information on their relative or cumulative impacts. In a report to the Colorado state legislature in 2001 titled, “Declining mule deer populations in Colorado: reasons and responses” Gill (2001) concluded that habitat factors had likely taken the greatest toll on deer populations but that there was no information quantifying the extent of habitat loss or deterioration across the state; critical information that is still lacking today. To address this issue, our objective is to conduct the first spatial and temporal analysis of landscape changes that have occurred to mule deer habitat across western Colorado (west of Interstate 25; Fig. 1). Specifically we are 1) mapping and quantifying changes to deer habitat that have occurred over the last ~40 years (in 5-10 year increments) related to residential development, energy development, fire, climate, and plant productivity, 2) calculating the amount of habitat that has been degraded and lost (directly and indirectly) due to these factors on an individual and cumulative basis for each deer data analysis unit (DAU) and within winter and summer ranges of each DAU, and 3) examining whether spatial and temporal changes to habitat conditions may be associated with observed trends in deer recruitment rates. During fiscal year 2013-2014 we completed the first two objectives of this project, and quantified the total area and proportion of deer habitat that was impacted by each land use land cover (LULC) factor, summarized by DAU. While we wanted to conduct these calculations across all LULC types for the past ~40 years, we were limited by the available data. We calculated metrics for climate and wildfire on an annual basis and in 5-year increments. Habitat loss due to residential development was summarized by decade because that is the finest temporal resolution available for the selected data source. Changes to deer habitat were determined on 5-year increments for energy development and annually for vegetation productivity, because collaborators agreed these were the most useful temporal resolutions for these LULC types. A brief summary of the data used to quantify each type of LULC change is described below: • Climate data were acquired from Parameter-elevation Regressions on Independent Slopes Models (PRISM) to quantify changes to precipitation and temperature. This dataset is considered to be one of the highest-quality historical climate datasets currently available, and was summarized at a 800 m spatial scale. From this dataset we calculated annual precipitation, June precipitation, summer precipitation, winter precipitation, and June minimum temperatures. 9 �• • • • Data on energy development were acquired from the Colorado Oil and Gas Conservation Commission. We obtained a spatial dataset representing the point locations of all oil and gas wells statewide and a tabular dataset representing years of well activity. We merged these datasets to produce a database which attributes all wells with the year the wells were drilled or first became active. At 5-year increments, we calculated the cumulative area affected by energy development at three distances: 200 m, 700 m, and 2,700 m. Changes to residential development were mapped and quantified using the Spatially Explicit Regional Growth Model (SERGoM) dataset. This nationwide dataset models housing density by decade at a spatial resolution of 100 m. Changes to deer habitat by DAU were calculated for urban, suburban, exurban, rural and undeveloped housing categories. We quantified plant productivity or “greenness” from the Normalized-Difference Vegetation Index (NDVI), which has been widely used to assess forage quality for deer and other large herbivores. We used NDVI metrics derived from 1 km Advanced Very High Resolution Radiometer (AVHRR) satellite imagery. For each DAU, on an annual basis, we determined the length of the growing season, time peak plant productivity, the rate of “green-up” across the season, and the cumulative area under the curve for the growing season. Data on fire history were obtained from the Monitoring Trends in Burn Severity (MTBS) project of the US Geological Survey and USDA Forest Service. This nationwide dataset maps the boundaries of wildfires as polygons on an annual basis between 1985 and 2010, on a 100 m spatial resolution. Information on changes to deer habitat due to climate, energy development, residential development, plant productivity and wildlife will be 1) distributed to biologists and relevant CPW staff in western Colorado to aid in future DAU planning, and 2) used to assess whether spatial and temporal changes to mule deer habitat are related to deer recruitment, a key measure of deer population performance. Results of this work will benefit wildlife professionals at statewide, regional, and local scales that will be able to use project results to help prioritize habitat enhancement efforts, connect deer population objectives to landscape conditions, identify key areas for habitat protection, provide comments on land-use proposals, develop policies related to land-use in critical deer ranges, and quantify general habitat impacts that are relevant to deer across western Colorado. Figure 1. The area of interest including all deer analysis units west of Interstate 25 in Colorado. ' Colorado state boundary - - 10unit (DAU) Deer analysis Interstate highway 25 - �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Quantifying loss and degradation of mule deer habitat across western Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Sarah E. Reed, Jessica R. Sushinsky, Andy Holland, Trevor Balzer, Jim Garner, Eric Bergman All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Background In recent decades, mule deer populations have declined across the western U.S., causing wildlife management agencies to seek factors limiting deer performance and strategies to increase their population sizes. The trend of declining mule deer populations has been primarily attributed to loss and degradation of deer habitat, through mechanisms such as urban/exurban development, resource extraction, roads and vehicular traffic, and changing patterns in weather and plant productivity. Other factors have also been implicated in contributing to deer declines, such as predation, interspecific competition with elk, and disease, but these factors have not been associated with much empirical support. While wildlife managers are well aware that different habitat factors can negatively affect deer populations, there is no information on their relative or cumulative impacts. In a report to the Colorado state legislature in 2001 titled, “Declining mule deer populations in Colorado: reasons and responses” Gill (2001) concluded that habitat factors had likely taken the greatest toll on deer populations but that there was no information quantifying the extent of habitat loss or deterioration across the state; critical information that is still lacking today. To address this issue, we conducted the first spatial and temporal analysis of landscape changes that have occurred to mule deer habitat across western Colorado (west of Interstate 25). Specifically, our objectives were to 1) quantify the annual changes that had occurred across the DAU and within winter and summer ranges relative to residential development, energy development, wildfire, plant productivity and weather conditions, and 2) test for associations between those changes in habitat conditions and deer recruitment. During FY2013-2014 we quantified changes that had occurred within mule deer ranges for each habitat factor (see Johnson et al. 2014), and in FY2014-15 we tested for associations between those factors and patterns in deer recruitment. In this summary we report findings with respect to residential development, energy development and climate conditions using data collected between 1980 and 2010. These habitat factors had consistent data available across this time period, years when major changes in both landscape conditions and deer populations occurred. Methods To quantify changes in residential development, energy development and climate conditions across western Colorado we were limited to coarse data types with high temporal and spatial extents. We tracked changes in residential development using the Spatially Explicit Regional Growth Model dataset (Bierwagen et al. 2010), which estimates changes in areas of rural, exurban, suburban and urban housing units over time (100m resolution). We obtained information on energy development from the Colorado Oil and Gas Conservation Commission, and used the date of first activity to monitor increases in the number of wells over the course of the study. Because the exact impact area for each well was unknown, we calculated areas within deer ranges that were within 2700m of oil and gas wells (100m resolution), 16 �based on Sawyer et al. (2006) that demonstrated mule deer avoidance within that distance. To assess climatic patterns that may influence deer recruitment, we used historic data from the Parameter-elevation Regressions on Independent Slopes Model (www.prism.oregonstate.edu). The model depicts precipitation and temperature on a monthly basis (800m resolution), which we used to calculate several metrics hypothesized to affect recruitment: average June minimum temperature, June precipitation, summer precipitation (May-Sep), average summer maximum temperature (Jun-Aug), winter precipitation (DecMar) and average winter minimum temperature (Dec-Mar). For more detailed information about the data types used in the analysis refer to Sushinsky et al. (2014). To examine the influence of development and climate factors on mule deer, we used recruitment as our response variable. We chose this demographic parameter because it exhibits high temporal and spatial variation, is sensitive to environmental conditions, is minimally influenced by harvest regulations, and is typically the most influential vital rate driving population growth. Our measure of fawn recruitment was fawn ratios collected annually by CPW personnel. Fawn ratios were observed with post-hunt helicopter surveys in each deer DAU in most years. Surveys occurred between 1 December and 15 January; survey data collected in January were considered data from the previous calendar year (the biological birth year of the fawns). During surveys, non-random paths were flown across the winter ranges with the purpose of encountering as many deer as possible. All observed deer were counted and classified as adult females, fawns or males based on body size and antler morphology. Annual ratios of the number of fawns/100 adult females (n = 904 ratios) and the number of males/100 adult females (n = 901 ratios) for each DAU were calculated from classification data. In conducting the analyses, we first estimated changes in habitat conditions across each DAU, winter and summer ranges by fitting linear mixed models with “year” as the explanatory variable and treating DAU as a random intercept to account for repeated measurements over time. We then tested univariate relationships between each habitat variable and recruitment rates (while also testing for lag effects), retaining those variables that had 80% confidence intervals non-overlapping zero. From the remaining variables, we then checked for multicollinearity. If two variables were highly correlated (r >|0.6|) we retained the variable with the higher univariate relationship with recruitment rates (based on tvalues). Our final variable set included total development across the DAU, exurban development on winter range, energy development on winter range, winter precipitation, June minimum temperature, June precipitation, summer precipitation, the male/female ratio, an interaction between June temperature and precipitation, and an interaction between energy development and precipitation on winter range. We used linear mixed models (DAU was the random intercept) to test all subsets of these habitat variables in predicting fawn recruitment. We used model selection to identify the top models and model averaging to estimate standardized and unstandardized coefficients. Results Increases in residential housing were significant for all development classes (rural, exurban, suburban and urban), particularly on mule deer winter ranges (Fig. 1). Between 1980 and 2010, across all DAUs, the proportion of winter range that was associated with residential development (all types) increased by an average 0.25%/year (SE=0.01, range = 0 – 0.85%/year), while on summer range it increased by an average of 0.18% (SE=0.01, range = 0.02 – 0.65%/year). Both winter and summer ranges experienced major increases in rural development, and winter ranges also experienced major increases in exurban development. On average, 23.8% of deer winter ranges overlapped with some form of residential development in 1980 and 31.2% overlapped with development in 2010; on average, 14.0% of deer summer ranges overlapped with development in 1980 and 19.5% in 2010. Changes in development were greatest in the Southwest and Southeast regions, driven by increases in the number of rural housing units. By 2010 between 0.7% (DAU 1) and 66.0% (DAU 29) of DAU winter ranges overlapped with residential development, while between 0.8% (DAU 41) and 46.0% (DAU 34) of summer ranges overlapped with development. On both winter and summer ranges, energy development significantly increased over time, although winter ranges experienced the greatest increase. Between 1980 and 2010, on average, the 17 �proportion of winter range associated with a well within 2700 m increased by an average of 0.24%/year (SE=0.01; range = 0.0 – 1.4%/year), while on summer range it increased by 0.18%/year (SE=0.01, range = 0.0 – 1.9%/year). Across all DAUs the average proportion of winter range within 2700 m of a well was 16.7% in 1980 and 23.8% in 2010. The average proportion of summer range within 2700 m of a well was 9.6% in 1980 and 15.6% in 2010. Rates of energy development differed among regions with the Northwest and Southeast experiencing the highest rates of increase. By 2010, the proportion of deer winter ranges within 2700 m of a well varied among DAUs between 0% (DAUs 14, 18, 25, and 53) and 79% (DAUs 11 and 12), while summer range varied between 0% (DAUs 18 and 25) and 68% (DAU 11). Seasonal temperature metrics significantly increased over time, while seasonal precipitation metrics significantly decreased, with the exception of winter precipitation which displayed no temporal trend. Between 1980 and 2010, models estimated that on average, June mean minimum temperatures increased from 3.91°C to 5.23°C, summer mean maximum temperatures increased from 21.98°C to 22.58°C, winter mean minimum temperatures increased from -10.72°C to -9.84°C, June precipitation decreased from 3.42 cm to 3.00 cm, and summer precipitation decreased from 26.29 cm to 21.42 cm. The only metric that showed a significant difference by region was the change in minimum temperatures in June, which were much higher in Southwest Colorado than any other region of the state (Table 1). The mean fawn ratio across all DAUs over the course of the study was 56.0 fawns/100 adult females (SE=13.6), with mean ratios in different DAUs ranging between 42.9 (SE=7.6; DAU 23) and 76.6 (SE=12.7, DAU 27). Across years, the mean ratio in the Southwest was 50.2 (SE=11.3), in the Southeast was 58.5 (SE=16.9), in the Northwest was 60.3 (SE=12.4) and in the Northeast was 64.6 (SE=14.6; Fig. 2A). Across all DAUs, in 1980 the modeled mean ratio was 65.4 (SE = 1.4) and in 2010 it was 50.4 (SE = 1.3). Over the course of the study, recruitment decreased by an average of 0.5 fawns/100 adult females/year, with the greatest rates of decline in Southwest (-0.66) and Northwest (-0.46) Colorado. Rates of change were highly variable among DAUs. Forty DAUs exhibited declining trends over time while 4 DAUs exhibited slightly increasing trends, with the rates of change varying between 8.50 to 0.15 fawns/100 adult females/year (Fig. 2B). In contrast to fawn ratios, the ratio of adult male/adult female mule deer significantly increased over the course of the study. In 1980 the mean was 13.5 adult males/100 adult females (SE = 1.1) and by 2010 the mean was 34.0 adult males/100 adult females (SE = 1.0). This increase was influenced by conservative buck harvest strategies implemented during the late 1990s. On average the number of adult males/100 adult females increased by 0.68 males/100 adult females/year (SE=0.03). There was no significant difference in the rate of change in male ratios among regions. Fawn ratios generally decreased in association with increasing residential development, energy development, June temperatures, winter precipitation, and male ratios. Fawn ratios increased in association with higher June precipitation, summer precipitation and winter precipitation in the previous year (lag effect). The interaction of June temperature and precipitation indicated that cold, dry weather had the greatest positive correlation with fawn recruitment, while warm, dry weather had the greatest negative correlation with recruitment. The interaction of energy development and precipitation on winter range suggested that winter severity had the strongest association with fawn recruitment when development was minimal. When a greater proportion of the winter range was impacted by energy development, the negative association with winter precipitation dampened. Fawn recruitment was predicted to be highest when both winter precipitation and energy development were low. Standardized coefficients of the main effects suggested that residential development had the strongest association with fawn recruitment (>2 times the magnitude of any other main effect), and fawn ratios were predicted to vary by 16 fawns/100 adult females across the observed range of development values. Energy development had the second strongest association with recruitment, followed closely by the climate variables. Conclusions Our results indicate that declining trends in mule deer recruitment are correlated with increasing residential and energy development on deer ranges, particularly within winter ranges. Recruitment is the 18 �primary demographic parameter responsible for ungulate population growth, and thus, factors that reduce deer productivity have long-term consequences for overall population performance. Comparing the relative magnitude of correlations of human development factors with climate factors, which are wellknown to be important drivers of juvenile survival, we found that residential housing had >2 times the magnitude of association of any other factor, and that the association with energy development was similar to key climate variables. We detected significant relationships between deer recruitment and habitat conditions, but it is important to acknowledge drawbacks of our analysis that limit our inference. For example, the correlations we detected between recruitment and habitat conditions do not demonstrate causation, as we could not experimentally manipulate levels of human development or climate metrics. Additionally, the data sources used in this analysis were coarse, limited to those that were available over extensive spatial and temporal scales. While development factors were associated with declining recruitment, the specific mechanisms responsible for these correlations are largely unknown and will require additional investigation. Finally, it is important to remember that this analysis only examined a few factors affecting deer habitat, but numerous factors have been associated with demographic trends in deer (i.e., predation, disease, competition with native and domestic ungulates, etc). Our findings have key implications for the conservation of mule deer across Colorado. Adequate, high quality winter range has been speculated to be the primary factor limiting mule deer in the state, and our findings generally corroborate this hypothesis. Indeed, development impacts on winter ranges were more strongly correlated with declining recruitment than impacts on summer ranges, and increases in both development types were greater on winter ranges. Our results suggest that expanding residential and energy development on mule deer ranges may not be compatible with the goal of maintaining highly productive deer populations, and that additional development may further reduce recruitment rates, and potentially, population sizes. Additionally, historic mule deer population objectives may be unrealistic given the increased development activity associated with declining fawn recruitment. While additional research is needed on the mechanisms driving the correlation between anthropogenic developments and declining deer recruitment, wildlife professionals should carefully consider changes to the human footprint when specifying long-term population objectives. If healthy mule deer populations are going to be maintained across the state, conservation practitioners, policy-makers, and land-use planners will need to collectively work to ensure that seasonal habitats, particularly winter ranges, are well preserved. Literature Cited Bierwagen, B.G., D.M. Theobald, C.R. Pykec, A. Choated, P. Crothd, J.V. Thomase, and P. Morefield. 2010. National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences of the United States of America 107:20887-20892. Johnson, H.E., S.E. Reed, J.R. Sushinsky, A. Holland, T. Balzer, J. Garner, and E. Bergman. 2014. Quantifying loss and degradation of mule deer habitat across western Colorado. Wildlife Research Project Summary. Colorado Parks and Wildlife, Fort Collins, Colorado. Sawyer, H., R.M. Nielson, F. Lindzey, and L.L. McDonald. 2006. Winter habitat selection of mule deer before and during development of a natural gas field. Journal of Wildlife Management 70:396- 403. Sushinsky, J.R., H.E. Johnson, A. Holland, T. Balzer, J. Garner, and S.E. Reed. 2014. Quantifying landuse and land-cover change in mule deer habitat across Western Colorado. Technical report to Colorado Parks and Wildlife. Wildlife Conservation Society, North America Program, Bozeman, Montana. 19 �D-1 .,_, N D-6 • ,, -- ' D-7 % Residential Develop 0.01 - 0.04 N 0.04 -0.12 A 0.12 - 0.14 0.14- 0.17 0.17 - 0 .26 0.26 - 0.29 0.29 - 0.39 0.39 - 0.56 '" D-29 Figure 1. Map of Colorado deer data analysis units (DAUs) and regions (heavy black lines) designated by Colorado Parks and Wildlife. DAU colors represent the average annual rate of increase in residential development between 1980 and 2010. 80.00 75.00 Northeast --------------------- - ........... 70.00 65.00 60.00 7S ............ ____ . . ----- 4S ro 40.00 40 C 35.00 1980 er: ~ 1990 2000 2010 ro u. 70 ss 50 4S 40 35 1980 75.00 Southwest 70,00 6S 60 B so 50.00 45.00 ·,;::; Northwest :: ::---------------------:: --------------------~:. 55.00 0 l 6S.00 ::----------................. --.... ... ......... ............ ...... 60.00 -- 90 80 70 60 1990 2000 2010 50 40 South east ........................................ --------- 30 20 5S,00 ... ... ... ...... ...... ... ...... .................. 100 Fawn Ratio A S0,00 10 45.00 40,00 3S + - - - - ~ - - - ~ - - - ~ 35.00 + - - - - ~ - - ~ ~ - - ~ 1980 1990 1990 2000 2010 1980 2000 2010 Yea r 0 1980 1990 2000 2010 Year Figure 2. Mean temporal trends between 1980 and 2010 in mule deer recruitment in Colorado by a) region and b) deer data analysis unit. 20 � https://cpw.cvlcollections.org/files/original/f1426445e0c41e397bce7e001c1825e4.pdf 9edb463492f30355f1fe80fb579ba6e9 PDF Text Text Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Shifting perceptions of risk and reward: temporal and spatial variation in selection for human development by black bears around three urban systems Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Stewart W. Breck, Sharon Baruch-Mordo, David L. Lewis, Carl W. Lackey, Kenneth R. Wilson, John Broderick, Julie S. Mao, and Jon P. Beckmann All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. As landscapes across the globe rapidly change due to increased human development, there is uncertainty about the behavioral responses of wildlife to these changes given associated shifts in resource availability and risk. Human development typically reduces native foods for animals, but introduces novel anthropogenic foods (crops, livestock, garbage, watered landscaping, etc) along with risks associated with foraging in human-dominated landscapes. The initial response of animals to human development is typically a change in behavior, as animals have been observed to alter patterns of habitat selection, vigilance, daily activities and foraging, often in highly diverse ways. These behavioral responses reflect perceived trade-offs between the benefits of acquiring key resources and the risks associated with human activity. While these trade-offs should be dynamic in space and time as a function of habitat quality, natural food conditions and the physiological states of individuals, little is known about how animals in human-altered landscapes behaviorally adapt to such variation, particularly under varying ecological conditions. Elucidating the behavioral responses of wildlife to human development is particularly important for large carnivores as their home ranges frequently overlap with human infrastructure and activities, and their interactions with people are often a major source of conflict. In many cases, large carnivores avoid people indicating they associate humans with risk. Some carnivores, however, forage within human development on their natural foods or on anthropogenic foods, exploiting resources associated with human infrastructure. Such behavior has been associated with increased human-carnivore conflicts, generating concern over human safety and property, and stymieing conservation efforts for some carnivore species. If wildlife managers are going to be successful at reducing human-carnivore conflicts and promoting public tolerance for these species, they need to understand how these animals are behaviorally responding to increased development, and the conditions that modify their behavior. These concerns are particularly relevant for black bears (Ursus americanus). Bears can readily exploit the wealth of reliable, high-calorie food resources available around residential development (i.e., garbage, fruit trees, livestock), but are also susceptible to increased mortality from vehicle collisions, conflict-related euthanasia, and other human-related factors. Although studies have found that bears perceive risk associated with human activity, human-bear conflicts have generally increased over time, albeit highly variable. As a long-lived species with relatively stable population dynamics, variation in conflict activity is likely a consequence of shifting foraging behavior, not shifting population sizes, as bears reassess trade-offs of using human foods. Factors such as natural food conditions, a bear’s gender, age, physiological state (e.g., reproductive status), or degree of exposure to human activity, may influence 19 �the benefits and risks of foraging in human-dominated landscapes, driving observed variation in conflict activity. To understand how a large carnivore weighs the benefits and risks of using human development, we examined patterns of black bear resource selection in three developed areas in the western US (Aspen [CO], Durango [CO], and Lake Tahoe [NV]). Using data from 109 bears, our objectives were to 1) examine temporal patterns of selection for development within and across years, 2) compare spatial patterns of selection for development across study systems, and 3) identify individual attributes (e.g., age, maternal status) associated with increased selection for development. Using mixed effects resource selection models we found that use of development by bears was similar across study sites, modifying their selection within and across seasons based on changing environmental and physiological conditions (Fig. 1). Results were based on 331851 locations collected May - October; 87,530 locations for Aspen females (14 different bears), 82,272 for Aspen males (29 bears), 152,365 for Durango females (50 bears), and 9,684 for Tahoe females (16 bears). Selection for human development was tied to nutritional demands, as bears increased their use of anthropogenic foods throughout the summer-fall and in years with poor natural food availability (Figs. 1 and 2). Selection also appeared to be related to bear experience, increasing with animal age. While there were general trends in how bears selected for human development across sites, there were also idiosyncratic differences between them. For example, Aspen males, Aspen females, and Tahoe females tended to select for intermediate development densities, while Durango females displayed a bimodal pattern of either selecting for very high or very low development densities (Fig. 1). In Aspen, males selected for intermediate densities of development in both good and poor natural food years (amplifying their selection for development in poor food years), while females avoided areas with high development densities in good natural food years and strongly selected for high development in poor years, particularly during hyperphagia (Fig. 1). Our findings illustrate that for three areas in the western US black bears selected positively for human development, increasing their use of development in years with poor natural food conditions, throughout the summer-fall, and as bears increased in age. These patterns were generally consistent across study systems and over numerous years of data collection, despite variation in individual bear behavior. Such patterns suggest that bears are similarly interpreting the shifting benefits and risks associated with foraging in human-dominated landscapes, as factors such as natural food conditions, physiological state (i.e., hyperphagia), and experience with anthropogenic foods, simultaneously shape their habitat selection decisions. Variation in bear use of development appeared to be primarily tied to nutritional demands, as the benefits of obtaining anthropogenic foods likely outweighed the risks of foraging around human activity when bears needed additional food resources. Results from this study have key implications for bear management. Wildlife agencies often assume that bears exposed to human food will consistently exhibit nuisance behavior, but our results suggest that bear behavior can be highly variable within and across years, and that bears may often use anthropogenic resources as a source of subsidy rather than relying on those resources outright. Because bear populations are notoriously difficult to monitor, wildlife agencies also often assume that increases in human-bear conflicts reflect increases in bear populations. Our work, however, suggests that bear selection for development may be increasing over time, particularly as individuals get older and gain experience with anthropogenic foods. This behavior may then be the source of additional conflicts without an associated increase in population size, a pattern that has been observed for polar bears. As human development continues to permeate bear habitat, and as changes in climate reduce natural foods for bears in some areas, we expect that bear exposure to development and anthropogenic foods will increase as will their selection for these resources. 20 �Figure 1. Black bear probabilities of selection for density of human development from May through October in Aspen (CO), Durango (CO), and Tahoe (NV), USA. Warm colors depict selection during poor natural food years and cooler colors depict selection in good natural food years. Data for bears in Tahoe were not available for years with different natural food conditions. Note: Durango experienced a maximum of 375 human structures/km2, while Aspen and Tahoe had maximum densities of 540 and 660 structures/km2, respectively. Aspen Males Aspen Females Durango Females Tahoe Females ~ 0.9 0.9 0.8 0.8 0.9 0.8 0 0.7 .:; u 0.7 0.7 0.1 0.6 0.6 C 0.9 0.8 41 0.6 0.6 Vl o.s 0.5 o.s i 0.4 0.4 0.4 :0 0.3 0.3 0.3 0.3 !? 0.2 0.2 0.2 0.1 0.1 0.1 0,1 0 0 0 di 0 "' .n 0.. 100 200 300 400 Density of Human Structures/km1 500 0 100 200 300 400 500 0 100 200 300 Density of Hu man Structures/km2 Density of Human Structures/km 2 - Sep! - Oct ! 100 400 100 300 soo Density of Human Structures/km2 Figure 2. Spatial predictions of resource selection from female black bears in Durango, Colorado, for a good (A) and poor (B) natural food year during fall (Oct 1st). 21 600 � 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. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mammals Research Projects pdfs (2011-2020) Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/NoC-NC/1.0/">No Copyright - Non-Commercial Use Only</a>