PARENT SESSION
Oral Session 11: Predator - Prey Ecology I: Modeling.
Presiding: L Prugh
Monday, August 2, 8:00 AM to 11:30 AM, Meeting Room C 124.
Prey management by predators in the predator-prey shell game: An individual based model of predator prey interactions on a large spatial scale.
Mitchell, William*,1, Lima, Steven1, 1 Indiana State University, Terre Haute, IN, USA
ABSTRACT- In some predator-prey interactions, individuals (predator and/or prey) regularly make large-scale movements within the landscape. In a previous model (Mitchell and Lima 2002) we showed that such movement among widely distributed landscape patches could be part of a predator-prey shell game, in which predators attempt to learn prey locations, and prey attempt to be unpredictable in space. Here, we expand upon the shell game model to consider how responsive predators and prey interact on a landscape. For example, responsive prey can vary costly anti-predator behavior such as vigilance or large-scale movement as a function of time since encountering a predator. Responsive predators can vary movements and attack rates as a function of prey anti-predator behavior. To determine simultaneously the adaptive behaviors of responsive prey and predator, we developed an object-oriented, individual-based model characterizing the predator-prey interaction on a landscape, and then we incorporated this individual-based model into a genetic algorithm to find the evolutionarily stable predator and prey strategies. Our results show that when prey evolve responsive anti-predator behaviors such as vigilance or randomized movement associated with the shell game, responsive predators may evolve a strategy of prey management. Prey management, in this sense, includes frequent landscape-scale movements by the predators that mitigate the effect of anti-predator responses by prey. For both predators and prey, the landscape-scale model predicts patch departure behavior different from that predicted by a model that does not explicitly account for landscape scale.
Key words: individual-based model, genetic algorithm, predator-prey, prey management