Performing Department
College of Forestry and Conservation
Non Technical Summary
An extinction vortex is the single greatest threat to endangered species; when demographic, environmental, and genetic stochasticity interact with each other and with deterministic factors, such as habitat quality, to reinforce the demise of a small population. To successfully escape an extinction vortex and enable species recovery, all processes that affect endangered populations must be comprehensively assessed and incorporated into conservation plans. For this project, we were given the rare opportunity by CDFG to develop a comprehensive research program to guide conservation efforts for Sierra Nevada bighorn sheep, the rarest subspecies of bighorn sheep in North America. We initiated a combination of demographic, habitat and genetic analyses to identify the stochastic and deterministic factors limiting the recovery of this subspecies, examine the relative and synergistic impacts of these factors on the population performance, and the benefits of different management activities for stimulating subspecies recovery. While meeting these objectives, another major focus of the study has been on improving quantitative methods for data on small and endangered populations. We have developed a novel non-asymptotic life-stage simulation analysis method for examining transient dynamics in critically small populations. We have also extended the use of hierarchical Bayesian state-space models to combine multiple data types (minimum count, mark-resight, and telemetry) to better estimate key population parameters and their ecological drivers. Additionally, we compared inferences from neutral and adaptive genetic markers for their application in prioritizing populations for conservation. Results from this study will elucidate critical aspects of Sierra Nevada bighorn ecology, develop a framework for quantifying and alleviating extinction processes in endangered populations, and provide a recovery strategy for Sierra Nevada bighorn that will be implemented by Yosemite National Park, Sequoia-Kings Canyon National Park, and other state and federal wildlife agencies.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
An extinction vortex is the single greatest threat to endangered species; when demographic, environmental, and genetic stochasticity interact with each other and with deterministic factors, such as habitat quality, to reinforce the demise of a small population. To successfully escape an extinction vortex and enable species recovery, all processes that affect endangered populations must be comprehensively assessed and incorporated into conservation plans. For this project, we were given the rare opportunity by CDFG to develop a comprehensive research program to guide conservation efforts for Sierra Nevada bighorn sheep, the rarest subspecies of bighorn sheep in North America. We initiated a combination of demographic, habitat and genetic analyses to identify the stochastic and deterministic factors limiting the recovery of this subspecies, examine the relative and synergistic impacts of these factors on the population performance, and the benefits of different management activities for stimulating subspecies recovery. While meeting these objectives, another major focus of the study has been on improving quantitative methods for data on small and endangered populations. We have developed a novel non-asymptotic life-stage simulation analysis method for examining transient dynamics in critically small populations. We have also extended the use of hierarchical Bayesian state-space models to combine multiple data types (minimum count, mark-resight, and telemetry) to better estimate key population parameters and their ecological drivers. Additionally, we compared inferences from neutral and adaptive genetic markers for their application in prioritizing populations for conservation. Results from this study will elucidate critical aspects of Sierra Nevada bighorn ecology, develop a framework for quantifying and alleviating extinction processes in endangered populations, and provide a recovery strategy for Sierra Nevada bighorn that will be implemented by Yosemite National Park, Sequoia-Kings Canyon National Park, and other state and federal wildlife agencies.
Project Methods
The data collection methods for this project included both field work and lab work. We depolyed and re-collected 30 global-positioning-sytem collars on bighorn sheep using net-gun helicopter captures. We also collected annual demographic data (information on population size, growth rate, survival, and fecundity) on 4 bighorn sheep populations using minimum count and mark-resight surveys. Field crews tracked the individual survival and reproduction of 40 adult female bighorn sheep using ground and aerial radio-telemetry. We also conducting genetics lab work on 152 individual bighorn sheep, genotyping blood DNA at 27 neutral and adaptive microsatellite genetic markers. Finally, we coordinated the fecal nitrogen analysis of bighorn sheep pellets at Washington State Wildlife Habitat Laboratory, single-nuceotide-polymorphism marker development at the University of Montana Conservation Genetics Laboratory, and remote sensing snow analysis of the Sierra Nevada at the University of California. Data was analyzed with the variety of bayesian state-space population models, vital rate sensitivity analyses, cause-specific mortality analyses, genetic analyses, cox proportional hazards modeling, and resource-selection function modeling. Results from this study have elucidated critical aspects of Sierra Nevada bighorn ecology, developed a framework for quantifying and alleviating extinction processes in endangered populations, supplied new quantitative tools for examining the dynamics of small populations, and provided a recovery strategy for Sierra Nevada bighorn that is being implemented by California Dept. of Fish and Game, the U.S. Fish and Wildlife Service, the National Park Service and the U.S. Forest Service.