Agent‐based Modeling of Animal Movement: A Review

Abstract

Animal movement is a complex spatiotemporal phenomenon that has intrigued researchers from many disciplines. Interactions among animals, and between animals and the environments that they traverse, play an important role in the development of the complex ecological and social systems in which they are embedded. Agent‐based models have been increasingly applied as a computational approach to the study of animal movement across landscapes. In this article, we present a review of agent‐based models in which the simulation of animal movement processes and patterns is the central theme. Our discussion of these processes is focused on four key components: internal states, external factors, motion capacities, and navigation capacities. These four components have been identified in the emerging movement ecology research paradigm and are important for modeling animal movement behavior. Because agent‐based models allow for an individual‐based approach that encapsulates these four components, the underlying processes that drive animal behavior can be deeply explored using this technique. A set of challenges and issues remain, however, for agent‐based models of animal movement. In this article, we review the existing literature and identify potential research directions that could help address these challenges.