Temporal partitioning and aggression among foragers: modeling the effects of stochasticity and individual state

In many natural systems, individuals compete with conspecifics and heterospecifics for food and in some cases, individuals have been observed to partition their foraging times or fight over food. In this study, I investigated when it is optimal for a consumer to partition time and be aggressive. I formulated an individual-based model of foraging and used game theory to find evolutionarily stable strategies (ESSs) that maximize the probability that consumers survive each day and acquire their daily food requirements. Consumers choose when to forage and when to behave aggressively during confrontations over food. Consumers are each associated with a state variable, representing the amount of food eaten, and a dominance ranking, which describes how likely they are to forage and fight for food. The ESS is sensitive to food abundance, consumer state, and the dominance ranking. When food is abundant, temporal partitioning is often an ESS where the dominant consumer forages first; however, partitioning is unlikely to be an ESS when food abundance is low. Fights over food are typically avoided but may be part of an ESS when food abundance is low, both consumers are hungry, or the time available for foraging each day is drawing to a close. Because the ESS is sensitive to consumer state, the stochastic nature of finding food often results in considerable variation in observed foraging dynamics from one day to the next, even when consumers adopt the same state-dependent strategy each day. Results are compared with empirical observations, and I discuss implications for consumer coexistence.