| Summary: | Evaluating how animals behave and how populations perform across broad bioclimatic gradients is critical to a complete understanding of a species’ ecology. Given a landscape of varying habitat types and quality, individuals should select habitats that provide the greatest benefits to individual fitness, ultimately distributing themselves such that localized densities at equilibrium should positively covary with increasing habitat quality. Variation in habitat selection should give rise to demographic patterns across space, and knowledge of how one influences the other should provide new insight into how and why behaviour and demography may change over space. In my PhD thesis, I develop individually-based models of habitat selection, and population-based models of demography as driven by landscape configuration, pursuant to exploring the interrelatedness of individual preference and population distribution. In the first chapter, I estimate a model of habitat selection of moose (Alces alces) as a function of temperature variation across seasons based on fine-scale global positioning data in northwestern Ontario. In the second chapter, I estimate moose habitat selection models using recently updated landscape layers and aerial census data (i.e., presence/absence) across two spatially distinct study sites. In the third chapter, I estimate carrying capacities and intrinsic growth rates of moose populations using time series of abundance and hunting mortality across the managed forests of Ontario. In the third chapter, I estimate carrying capacities and intrinsic growth rates of moose populations using time series of abundance and hunting mortality across the managed forests of Ontario. In the fourth chapter, I use the models of habitat selection and carrying capacity to predict moose density in a third, novel site, as well as compare density predictions from the habitat model to carrying capacities derived in the third chapter. Ultimately, my thesis provides an explicit evaluation of population prediction based on ...
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