| Summary: | 2017 Spring. Includes bibliographical references. Much is known about the general biology and natural history of harbor seals (Phoca vitulina), but questions remain about the aquatic and terrestrial space use of these marine mammals. This is in large part because methods for examining the spatial ecology of harbor seals are poorly developed. The objective of this dissertation is to pair existing telemetry data with contemporary spatio-temporal modeling to quantify the space use and resource selection of harbor seals in the coastal waters of southern Alaska. Recent extensions to models for analyzing animal telemetry data address complications such as autocorrelation and telemetry measurement error; however, additional challenges remain, especially in the context of analyzing Argos satellite telemetry data collected on marine mammals like harbor seals. For example, existing methods assume elliptical (or circular) patterns of measurement error, even though Argos satellite telemetry devices impose more complicated error structures on the data. Constraints, or barriers, to animal movement present another complication. Harbor seals and other marine mammals are constrained to move within the marine environment, and mechanistic models that do not adhere to movement barriers yield unreliable inference. Therefore, a primary goal of this research is to develop statistical tools that account for these nuances and provide rigorous, ecologically relevant inference. Even though the models presented in this dissertation were specifically developed with Argos satellite telemetry data and harbor seals in mind, the methods are general and can be applied to other species and types of telemetry data. This dissertation consists of five chapters. In Chapter 1, I briefly discuss the general biology of harbor seals, focusing on what is known about their spatial habits in Alaska. I then summarize trends in Alaskan harbor seal abundance, a topic that motivated my research as well as the work of many others. I describe the existing ...
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