A stochastic game model of searching predators and hiding prey

Counterintuitive prey strategies against predators with finite budgets: protection heterogeneity among sites matters more than their number

Combining the search and pursuit aspects of predator-prey interactions into a single game, where the payoff to the Searcher (predator) is the probability of finding and capturing the Hider (prey) within a fixed number of searches was proposed by Gal and Casas (J. R. Soc. Interface 11, 20140062 (doi:10.1098/rsif.2014.0062)). Subsequent models allowed the predator to continue its search (in another 'round') if the prey was found but escaped the chase. However, it is unrealistic to allow this pattern of prey relocation to go on forever, so here we introduce a limit of the total number of searches, in all 'rounds', that the predator can carry out. We show how habitat structural complexity affects the mean time until capture: the quality of the location with the lowest capture probability matters more than the number of hiding locations. Moreover, we observed that the parameter space defined by the capture probabilities in each location and the budget of the predator can be divided into distinct domains, defining whether the prey ought to play with pure or mixed hiding strategies.

Pursuit and evasion strategies in the predator-prey interactions of fishes

Predator-prey interactions are critical to the biology of a diversity of animals. Although prey capture is determined by the direction, velocity, and timing of motion by both animals, it is generally unclear what strategies are employed by predators and prey to guide locomotion. Here we review our research on fishes that tests the pursuit strategy of predators and the evasion strategy of prey through kinematic measurements and agent-based models. This work demonstrates that fish predators track prey with variations on a deviated-pursuit strategy that is guided by visual cues. Fish prey employ a mixed strategy that varies with factors such as the direction of a predator's approach. Our models consider the stochastic nature of interactions by incorporating measured probability distributions to accurately predict measurements of survivorship. A sensitivity analysis of these models shows the importance of the response distance of prey to their survival. Collectively, this work demonstrates how strategy affects the outcome of predator-prey interactions and articulates the roles of sensing, control, and propulsion. The research program that we have developed has the potential to offer a framework for the study of strategy in the predator-prey interactions of a variety of animals.