Social Learning of Innovations in Dynamic Predator-Prey Systems.

Abstract

We investigate the social transmission of innovations between predators. We focus on two classic predator-prey models. We assume that innovations increase predator attack rates or conversion efficiencies or that innovations reduce predator mortality or handling time. We find that a common outcome is the destabilization of the system. Destabilizing effects include increasing oscillations or limit cycles. Particularly, in more realistic systems (where prey are self-limiting and predators have a type II functional response), destabilization occurs because of overexploitation of the prey. Whenever instability increases the risk of extinction, innovations that benefit individual predators may not have positive long-term effects on predator populations. Additionally, instability could maintain behavioral variability among predators. Interestingly, when predator populations are low despite coexisting with prey populations near their carrying capacity, innovations that could help predators better exploit their prey are least likely to spread. Precisely how unlikely this is depends on whether naive individuals need to observe an informed individual interact with prey to learn the innovation. Our findings help illuminate how innovations could affect biological invasions, urban colonization, and the maintenance of behavioral polymorphisms.