Behavioral tradeoffs when dispersing across a patchy landscape

A better understanding of the behavior of dispersing animals will assist in determining the factors that limit their success and ultimately help improve the way dispersal is incorporated into population models. To that end, we used a simulation model to investigate three questions about behavioral tradeoffs that dispersing animals might face: (i) speed of movement against risk of predation, (ii) speed of movement against foraging, and (iii) perceptual range against risk of predation. The first investigation demonstrated that dispersing animals can generally benefit by slowing from maximal speed to perform anti-predatory behavior. The optimal speed was most strongly influenced by the disperser's energetic reserves, the risk of predation it faced, the interaction between these two parameters, and the effectiveness of its anti-predatory behavior. Patch arrangement and the search strategy employed by the dispersers had marginal effects on this tradeoff relative to the above parameters. The second investigation demonstrated that slowing movement to forage during dispersal may increase success and that optimum speed of dispersal was primarily a function of the dispersing animal's energetic reserves, predation risk, and their interaction. The richness (density of food resources) of the interpatch matrix and the patch arrangement had relatively minor impacts on how much time a dispersing animal should spend foraging. The final investigation demonstrated animals may face tradeoffs between dispersing under conditions that involve a low risk of predation but limit their ability to perceive distant habitat (necessitating more time spent searching for habitat) and conditions that are inherently more risky but allow animals to perceive distant habitat more readily. The precise nature of this tradeoff was sensitive to the form of the relationship between predation risk and perceptual range. Our overall results suggest that simple depictions of these behavioral tradeoffs might suffice in spatially explicit population models.