Simulating the Evolution of Whale Migration

Whale species are some of the most famous and enigmatic of marine animals. We know much about where and when they migrate, but we know relatively little about why they go where they do, and the role that myopic interactions between individual whales may have on these patterns. To address this knowledge gap, we have developed adaptive agent-based models of whale movement. These simulate the movement of individual whales by combining resource fields generated from a global oceanographic model with individual behavioral rules and bioenergetics. Whale agents are characterized by three movement behaviors: social behavior, resource-following behavior and memory-following behavior. We show that with these three possible behaviors, evolutionary stable strategies and long distance migration patterns emerge from myopic scale interactions, and that these patterns reflect real migration pathways. We use this modeling framework to explore how migration pathways change under different climate change scenarios and from anthropogenic perturbations such as the loss of individuals from collision with vessels.