Foraging behavior in stochastic environments

How do temporally stochastic environments affect risk sensitivity in foraging behavior? We build a simple model of foraging under predation risks in stochastic environments, where the environments change over generations. We analyze the effects of stochastic environments on risk sensitivity of foraging animals by means of the difference between the geometric mean fitness and the arithmetic mean fitness. We assume that foraging is associated with predation risks whereas resting in the nest is safe because it is free of predators. In each generation, two different environments with given food amounts and predation risks occur with a certain probability. The geometric mean optimum is independent of food amounts. In most cases of stochastic environments, risk-averse tendency is increased, but in some limited conditions, more risk-prone behavior is favored. Specifically, risk-prone tendency is increased when the variation in food amount increases. Our results imply that the optimal behavior depends on the probability distribution of environmental effects under all selection regimes.