Optimal locomotor strategy for predator avoidance in fish prey.

The control and mechanics of locomotion determine the outcome of a variety of predator-prey interactions. The strategies that optimize prey survival have primarily been considered for cases where the prey initiates an escape in response to a predator's approach. However, a diversity of prey survive by avoiding encounters with predators without the aid of evasive maneuvers. To understand locomotor strategies for these conditions, we developed an agent-based numerical model for individual prey damselfish (Chromis viridis) when targeted by a lionfish predator (Pterois volitans). Based on previous experiments, we modeled the predator to track prey with a pure-pursuit strategy and the prey avoided the predator with intermittent bouts of swimming that were biased away from the threat. We found that simulations were statistically similar to experimental measurements in the duration of the interactions. In contrast to distance-optimal evasion models, a sensitivity analysis revealed that prey survived encounters with faster predators most successfully by swimming towards the predator and capitalizing on the relatively slow capacity of the predator to change direction. These findings demonstrate the power of agent-based mathematical modeling to determine the salient features that determine the outcome of coupled predator-prey interactions.