ABSTRACT
Animal movement in heterogeneous environments involves the interplay of landscape features, such as resource patches, barriers, and different land cover types, with behavioral responses of animals to those features and their interactions with other animals. To account for this complexity, ecologists typically describe movements using rule-based simulation models such as variants of correlated random walks. Random walk models are a natural way to describe animal movement in that they can easily be modified to incorporate increasingly complex behaviors and landscapes (e.g., Revilla et al., 2004; Vuilleumier and Perrin, 2006; Matanoski and Hood, 2006; Peer et al.,
2006), and they provide rules that can be used to simulate long-term consequences of these behaviors under current conditions, or to examine the potential responses of animals to novel environments (e.g., Tischendorf et al., 2003). However, at the same time, the ability of these models to incorporate system-specific behavior makes them potentially idiosyncratic and data-intensive descriptors of particular populations, that can be difficult to generalize, or even compare, using a common currency (Grimm et al., 1999).
