My objective was to understand how individual variation, in conjunction with variation in habitat, can affect individual and population-level variation in animal space use. I used coyotes (Canis latrans) as a model species to investigate the roles of hybridization, an inherited intrinsic factor, and spatial memory, a learned intrinsic factor, on space use. I used a diversity of methods and approaches, including meta-regression, multiple imputation, simulations, resource selection functions, step selection functions, net-squared displacement analysis, and survival analysis. A major contribution was my investigation of the performance of multiple imputation in a meta-regression framework in Chapter 2. My simulations indicated that multiple imputation performs well in estimating missing data within a meta-regression framework in most situations. In Chapter 3, I used published studies of coyote home range size in a meta-regression analysis with multiple imputation to examine the relative roles of hybridization and environmental variables on coyote home range size across North America. I found that hybridization with Canis species was a leading factor driving variation in coyote space use at a continental scale. In Chapter 4, I used telemetry data for 62 coyotes in Newfoundland, Canada, to investigate the influence of cognitive maps on resource use. I found that resident coyotes used spatial memory of the landscape to select or avoid resources at spatial scales beyond their immediate sensory perception relative to transient coyotes, presumably increasing their fitness. Taken together, my dissertation demonstrates that intrinsic factors, such as genetic ancestry and spatial memory, can have substantial influences on how animals use space at both individual and population levels, and at both a local and a continental scales.
Author Keywords: canis latrans, hybridization, meta-regression, multiple imputation, Newfoundland, spatial memory