Developing Theory to Understand Variation in Behavioral Responses to Human-induced Rapid Environmental Change

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Almost all living organisms (including humans) are now living in a world altered by environmental change including climate change, habitat change, and exposure to exotic species (e.g., novel predators or diseases). Some species are coping poorly with environmental change and declining in numbers, while others are thriving (e.g., invasive or urbanized pests). The relative ability of organisms to respond well behaviorally to novel conditions associated with environmental change often has critical effects on their success in the modern world. A better understanding of variation in behavioral responses to environmental change will be useful for enhancing the recovery of declining species, for more efficiently controlling pest species, and for anticipating ecological problems before new changes unfold. This project develops new theory to explain observed patterns and generate new predictions on the variation in behavioral response to human-induced rapid environmental change (HIREC). It thus has potential to substantially advance our scientific understanding of one the most important ecological issues of our time. The project brings together a team of behavioral/evolutionary ecology modelers to develop theory to better understand variation in behavioral responses to environmental change. To explain both adaptive and maladaptive responses to novel situations, the modeling team will employ novel extensions of signal detection theory, bet hedging (generalist-specialist) theory, adaptive plasticity theory, and theory on adaptive learning. The team will also integrate these modeling approaches in fresh ways to generate novel insights for both basic behavioral ecology and for understanding responses to environmental change. Finally, the modelers will collaborate with empiricists to review relevant empirical literature and to write conceptual overview papers on behavioral responses to environmental change. The project offers abundant opportunities for training a new generation of young scientists on the interface between math and biology. The project will also include workshops that will involve not just the team and mentees, but also dozens of other empiricists and applied scientists. The project will create a new website that will feature: 1) summaries of the models, predictions, and implications, with 2) advice to empiricists on which models to apply to specific scenarios, and 3) computer code including user-friendly models suitable for use in undergraduate courses. Finally, the project will seek to collaboratively develop classroom modules for potential implementation as part of Next Generation Science Standards that have been adopted in much of the United States.