From Diffusion to Cognition: Analytical, Statistical and Mechanistic Approaches to the Study of Animal Movement




Avgar, Tal

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University of Guelph


Ecology is the scientific study of processes that determine the distribution and abundance of organisms in space and time. Animal movement plays a crucial role in determining the fates of individuals, populations, communities, and ecosystems. Hence, understanding how and why animals change their spatial location through time is fundamental to ecological research. Animal movement patterns reflect behavioral, physiological and physical interactions between individuals and their environment. Coupling movement and environmental data may thus provide a rich source of information regarding many aspects of animal ecology. In my PhD thesis, I develop and demonstrate different approaches to understanding and predicting animal movement patterns in relation to their environment. In the first chapter, I merge two fundamental ecological models, the functional response and random walk, to formally derive diffusion rates of consumers as function of their handling time and the abundance, distribution and mobility of their resources. This mechanistic null model provides a simple behavior-free explanation to commonly observed negative associations between movement rates and resource abundance, often attributed to area-restricted search behavior. In the second chapter, I use positional data of woodland caribou in Ontario to calculate random walk-based movement expectations for each individual during each month. I then statistically link these expectations to ecologically significant environmental conditions. I show that landscape correlates of forage abundance and habitat permeability explain much of the observed variation in caribou movement characteristics and that residual variability may be attributed to spatial population structure. In the third chapter, I develop a novel state-space approach, enabling simultaneous consideration of resource preference, cognitive capacities and movement limitations, within a simulation model of animal movement across heterogeneous landscapes. The model is designed to enable direct parameterization based on empirical movement and landscape data. This approach allows one to both theoretically explore the consequences of different cognitive abilities and to predict animal space-use patterns across novel or altered landscapes. Overall, my thesis contributes to the rapidly developing field of movement ecology by formulating mechanistically defendable linkages between animal movement and landscape characteristics.



movement ecology