Graduate Theses & Dissertations

Linking large scale monitoring and spatially explicit capture–recapture models to identify factors shaping large carnivore densities
Understanding the spatial ecology of large carnivores in increasingly complex, multi-use landscapes is critical for effective conservation and management. Complementary to this need are robust monitoring and statistical techniques to understand the effect of bottom-up and top-down processes on wildlife population densities. However, for wide-ranging species, such knowledge is often hindered by difficulties in conducting studies over large spatial extents to fully capture the range of processes influencing populations. This thesis addresses research gaps in the above themes in the context of the American black bear (Ursus americanus) in the multi-use landscape of Ontario, Canada. First, I assess the performance of a widely adopted statistical modelling technique – spatially explicit capture-recapture (SECR) – for estimating densities of large carnivores (Chapter 2). Using simulations, I demonstrate that while SECR models are generally robust to unmodeled spatial and sex-based variation in populations, ignoring high levels of this variation can lead to bias with consequences for management and conservation. In Chapter 3, I investigate fine-scale drivers of black bear population density within study areas and forest regions by applying SECR models to a large-scale, multi-year black bear spatial capture-recapture dataset. To identify more generalizable patterns, in Chapter 4 I then assess patterns of black bear density across the province and within forest regions as a function of coarse landscape-level factors using the same datasets and assess the trade-offs between three different modeling techniques. Environmental variables were important drivers of black bear density across the province, while anthropogenic variables were more important in structuring finer-scale space use within study areas. Within forest regions these variables acted as both bottom-up and top-down processes that were consistent with ecological influences on black bear foods and intensity of human influences on the species’ avoidance of developed habitats. Collectively, this thesis highlights the opportunities and challenges of working across multiple scales and over expansive landscapes within a SECR framework. Specifically, the multi-scale approach of this thesis allows for robust inference of the mechanisms structuring fine and broad scale patterns in black bear densities and offers insight to the relative influence of top-down and bottom-up forces in driving these patterns. Taken together, this thesis provides an approach for monitoring large carnivore population dynamics that can be leveraged for the species conservation and management in increasingly human-modified landscapes. Author Keywords: animal abundance, black bear, capture-recapture, density estimation, statistical ecology, wildlife management

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2014 - 2024
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