Abstract
Behavioral changes that result from rapid environmental shifts such as those brought about by human activity are some of the most immediate and consequential responses in the biotic world. However, deriving community models that take into account non-trivial behavior and therefore the ecological significance of those changes is an ongoing challenge in ecology. Here, we propose methods for deriving community models from populations of evolved agents who both forage and avoid predation. We exemplify those methods with a case study of sensory pollution by manipulating the sensor of the agents and deriving functions that characterize resulting interaction rates with both food and predators. We believe these methods can apply to any question regarding how a specific behavior or behavioral change will affect community structure and population dynamics. Spatial limitations of the method are discussed as an area for future work.