| Summary: | Given current rates of anthropogenic environmental change, combined with the increasing lethal and non-lethal mortality threat that human activities pose, there is a vital need to understand wildlife movement and behaviour in human-dominated landscapes to help inform conservation efforts and wildlife management. As long-term monitoring of wildlife populations using Global Positioning System (GPS) telemetry increases, there are new opportunities to quantify change in wildlife movement and behaviour. The objective of this PhD research is to develop novel methodological approaches for quantifying change in spatial-temporal patterns of wildlife movement and habitat by leveraging long time series of GPS telemetry and remotely sensed data. Analyses were focused on the habitat and movement of individuals in the threatened grizzly bear (Ursus arctos) population of Alberta, Canada, which occupies a human-dominated and heterogeneous landscape. Using methods in functional data analysis, a multivariate regionalization approach was developed that effectively summarizes complex spatial-temporal patterns associated with landscape disturbance, as well as recovery, which is often left unaccounted in studies quantifying patterns associated with disturbance. Next, the quasi-experimental framework afforded by a hunting moratorium was used to compare the influence of lethal (i.e., hunting) and non-lethal (i.e., anthropogenic disturbance) human-induced risk on antipredator behaviour of an apex predator, the grizzly bear. In support of the predation risk allocation hypothesis, male bears significantly decrease risky daytime behaviours by 122% during periods of high lethal human-induced risk. Rapid behavioural restoration occurred following the end of the hunt, characterized by diel bimodal movement patterns which may promote coexistence of large predators in human-dominated landscapes. A multi-scale approach using hierarchical Bayesian models, combined with post hoc trend tests and change point detection, was developed to test the ...
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