| Summary: | Thesis (Ph.D.) University of Alaska Fairbanks, 2023 Landscape-level wildlife monitoring in the Arctic is technically and logistically challenging. The Arctic is experiencing rapid and unprecedented climate-related changes as well as increased industrial development. Understanding how environmental change and anthropogenic activity impact wildlife populations is essential to informing responsible management and policy decisions. Caribou (Rangifer tarandus) are a wide-ranging, highly mobile species in the Arctic with important socio-economic, cultural, and ecological value. Most caribou herds across the circumpolar north are in decline or at historic lows. These conditions create an urgent demand to assess conventional wildlife monitoring strategies and inform opportunities to advance them by integrating new techniques and technologies. In this dissertation, I advanced knowledge on the use of camera traps (i.e., remotely triggered cameras) for monitoring wildlife in the Arctic by informing new techniques specifically tailored to open landscapes and by evaluating their capacity to assess seasonal caribou distribution and habitat use on the Arctic coastal plain of Alaska, USA. Collectively, I established a new method for estimating animal size or distance from the camera, evaluated the efficacy of image collection and processing techniques, and demonstrated how camera traps can help reinforce conventional knowledge of caribou ecology while providing opportunities to gain new insights and perspectives. I built on a limited body of research exploring the application of camera traps for monitoring a migratory species in the vast open landscape of Alaska's Arctic tundra and contributed knowledge to advance long-term, landscape-level ecological monitoring in this region. National Science Foundation (Office of Polar Programs, Arctic System Science Program Award # 1839192), University of Alaska Fairbanks Graduate School, and Calvin J. Lensink Fund Chapter 1: General introduction -- Chapter 2: Estimating animal size ...
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