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UC Santa Cruz Electronic Theses and Dissertations UC Santa Cruz UC Santa Cruz Electronic Theses and Dissertations Title The Demography and Comparative Ethology of Top Predators in a Multi-Carnivore System Permalink https://escholarship.org/uc/item/3xd9379b Author Anton, Colby Publication Date 2020 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA SANTA CRUZ THE DEMOGRAPHY AND COMPARATIVE ETHOLOGY OF TOP PREDATORS IN A MULTI-CARNIVORE SYSTEM A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in ENVIRONMENTAL STUDIES by Colby B. Anton June 2020 The Dissertation of Colby B. Anton is approved: _______________________________________ Professor Christopher Wilmers, chair _______________________________________ Professor Timothy Duane _______________________________________ Daniel Stahler, Ph.D. _____________________________________ Quentin Williams Acting Vice Provost and Dean of Graduate Studies Copyright © by Colby B. Anton 2020 TABLE OF CONTENTS Table of Contents iii List of Tables iv List of Figures vii Abstract x Acknowledgements xii Chapter 1 – Introduction 1 Chapter 2 – Applying Open-Population Noninvasive Genetic Spatial Capture-Recapture to Estimate Density of a Large Carnivore 6 Chapter 3 – Gray wolf habitat use in response to visitor activity along roadways in Yellowstone National Park 43 Chapter 4 – Linking energetic costs to hunting behavior, life history, and sociality in large carnivores 107 Literature Cited 159 iii LIST OF TABLES 2.1 Genotype analysis results from cougar noninvasive genetic samples 29 2.2 Yearly cougar abundance, apparent survival, recruitment, and population growth rate estimates 30 2.3 Sex-specific sigma estimates and beta coefficients for baseline detection probability 32 S2.1 Yearly snow-tracking effort 37 S2.2 Individual recapture frequencies 39 3.1 Model selection results for mixed-effects conditional logistic regression (MCLR) models demonstrating the relationship between wolf resource selection and seven spatial and/or temporal landscape metrics 68 S3.1 GPS collared gray wolves from 2001-2017 used to calculate step selection functions (SSF) 74 S3.2 MCLR model list displaying covariate combinations used for wolf SSF 76 S3.3 Spring wolf MCLR model selection table 78 S3.4 Summer wolf MCLR model selection table 79 S3.5 Fall wolf MCLR model selection table 80 S3.6 Covariate Parameter estimates for top Spring MCLR wolf SSF models or averaged estimates among models within D4 AIC of top model 81 iv S3.7 Covariate Parameter estimates for top Summer MCLR wolf SSF models or averaged estimates among models within D4 AIC of top model 83 S3.8 Covariate Parameter estimates for top Fall MCLR wolf SSF models or averaged estimates among models within D4 AIC of top model 85 S3.9 GEE model list and covariate combinations used for Elk SSFs. GEE models included cluster identification unique to individuals 93 S3.10 Spring elk model selection table using QIC 94 S3.11 Summer elk model selection table using QIC 95 S3.12 Fall elk model selection table using QIC 96 4.1 AIC model selection from linear regression models determining the influence of covariates on the ODBA displayed during the killing surge by cougars 141 4.2 AIC model selection from linear regression models determining the influence of covariates on the ODBA displayed during the killing surge by wolves 142 4.3 Estimates of female cougar consumption rates for different seasons and reproductive status phases 143 S4.1 Cougar GPS cluster search results including carcasses detected per individual by each season 150 S4.2 Wolf GPS cluster search results including carcasses detected v per individual by each season 150 S4.3 Prey Composition for cougars and wolves calculated from GPS cluster searches in Yellowstone National Park 151 S4.4 Averaged coefficients from models within 4DAIC based on all models within of the top model testing for influence on kill surge ODBA 153 S4.5 AIC model selection table for models determining influence of variables on cougar ODBA displayed during prey handling period 154 S4.6 AIC model selection table for models determining influence of variables on wolf ODBA displayed during prey handling period 155 S4.7 Averaged coefficients from models within 4DAIC of top models for covariates influencing cougar and wolf ODBA while handling prey carcasses 155 S4.8 Model selection table using AIC for models testing the influence of individual, group, prey, and spatial characteristics on cougar handling time 156 S4.9 Model selection table using AIC for models testing the influence of individual, group, prey, and spatial characteristics on wolf handling time 157 S4.10 Averaged coefficients from models within 4DAIC of top models for covariates influencing cougar and wolf handling time for prey carcasses 157 vi LIST OF FIGURES 2.1 Study area overview map 33 2.2 Directed acyclic graph and joint distribution for open-population spatial capture recapture model 34 2.3 Sex-specific and combined cougar density estimates 35 S2.1 Spatial and temporal organization of individual cougar genotypes 36 S2.2 Noninvasive genetic sampling included cougar hair, scat, and blood 37 S2.3 Yearly genotype success by sample type 38 S2.4 Yearly genotype success for hair samples from different sources 38 S2.5 Survey effort for each grid cell trap 40 S2.6 Calculated baseline detection probabilities for female and male cougars 41 3.1 Study area map in the Greater Yellowstone Ecosystem 71 3.2 Relative odds of habitat selection based on the wolf’s distance to road and the road view value 72 3.3 Results from mixed-effects conditional logistic regression modelling with random intercepts and slopes for each pack’s distance to road relationship 73 S3.1 Yellowstone National Park monthly visitation from 1979 and 2017 89 S3.2 Beta Parameter plot for elk SSF generalized estimating equations 92 S3.3 Spring day elk resource selection predictive surface 98 vii S3.4 Spring crepuscular elk resource selection predictive surface 99 S3.5 Spring night elk resource selection predictive surface 100 S3.6 Summer day elk resource selection predictive surface 101 S3.7 Summer crepuscular elk resource selection predictive surface 102 S3.8 Summer night elk resource selection predictive surface 103 S3.9 Fall day elk resource selection predictive surface 104 S3.10 Fall crepuscular elk resource selection predictive surface 105 S3.11 Fall night elk resource selection predictive surface 106 4.1 Example tri-axial accelerometer readings for a cougar and a solitary wolf 144 4.2 Predicted relationships between prey weight (kg) and the overall dynamic body acceleration (ODBA) displayed before and during a kill surge for cougars and wolves 145 4.3 Behavior phase time allocation for cougars and wolves 146 4.4 Daily energetic expenditure (DEE; kj/day) for maternal and solitary females at different stages of reproductive status 147 4.5 Correlation between dominant scavenger presence at cougar kills and time spent handling and total seasonal consumption rate 148 4.6 Energy expenditure during cougar kill surges 149 S4.1 Seasonal diet composition for wolves and cougars in Yellowstone National Park 152 S4.2 Age and sex-specific composition for cougar-killed elk and viii mule deer 152 S4.3 Age and sex-specific composition for wolf-killed elk and mule deer 153 S4.4 Calculated daily energy deficits (kj/day) using daily energetic expenditure (DEE; kj/day) and daily energetic consumption (DEC; kj/day) from consumption rates gained from GPS cluster searches for cougars in Yellowstone National Park 158 ix ABSTRACT THE DEMOGRAPHY AND COMPARATIVE ETHOLOGY OF TOP PREDATORS IN A MULTI-CARNIVORE SYSTEM Colby B. Anton Widespread habitat loss and overharvest have been identified as major drivers of population declines and range contractions for terrestrial mammalian species. Protected areas, like national parks, are increasingly important as refuges for rare and exploited species, as well as critical natural laboratories that serve as baseline examples of ecological processes largely free from human intervention. Yellowstone National Park (YNP) sits at the center of a 22-million-acre mosaic of federal, state, and privately managed land in northwest Wyoming known as the Greater Yellowstone Ecosystem. The region boasts one of the last nearly intact temperate- zone ecosystems on Earth, providing vital habitat for seven species of native ungulate and seven large predators. We sought to answer fundamental wildlife conservation and management questions pertaining to large predator distributions and behavior. We snow-tracked cougars (Puma concolor) for four consecutive winters to gather noninvasive genetic samples. We applied Bayesian spatial capture-recapture models to estimate abundance, density, apparent survival and recruitment for this cryptic, low-density species. In addition to these noninvasive studies, we captured and GPS- collared cougars and wolves (Canis lupus), a subset of which contained tri-axial accelerometers to monitor instantaneous movement signatures. Using GPS locations from these animals we searched and identified predation events, allowing us to x directly link known predatory behavior to accelerometer readings. We compared patterns in seasonal predatory behavior for these sympatric species that utilize divergent social strategies. Finally, we examined nearly twenty years of wolf GPS locations to understand the impact of growing visitation (>4 million human visitors/year) on habitat selection patterns. We identified
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