Collaborative Research: BoCP-Implementation: Functional Biodiversity on a Changing Planet Through the Lens of Seasonal Camouflage

About This Grant

Camouflage is one of the most widespread and most important adaptations in the animal kingdom. In seasonal environments, many bird and mammal species (e.g., snowshoe hares, short-tailed weasels, willow ptarmigans) change from brown in summer to white in winter to stay camouflaged against snow. But due to environmental variability, these seasonally color molting species can become more visible to predators or prey during years with unusual snow cover. For example, if snow comes late in the fall or melts very early in the spring the animals’ coat color might be mismatched with the environment. This raises the question of how these species cope with variation in their environments, including whether they forgo the seasonal color molt or change their behaviors to remain undetected from their prey or predators. This project will develop comprehensive artificial intelligence (AI) tools to work with camera trap images of animals from around the world to understand animal coloration and mismatch in seasonal camouflage on our rapidly changing planet. These tools will also create opportunities for the scientific community to explore an even broader set of questions surrounding the function of animal coloration and camouflage across any habitat. The research will further support public understanding of animal color adaptations via hands-on training for students and educational materials produced in collaboration with the North Carolina Museum of Natural Sciences. This project uses camouflage as a model functional trait to understand the connections between functional biodiversity and the shifting dynamics of adaptive responses to changing environmental conditions. During this four-year project, the researchers will first develop publicly available AI tools to analyze coat color, background color, and camouflage from camera trap images collected across the globe. Next, the newly generated data will be used to test ecological and evolutionary hypotheses aiming to understand the spatial, temporal, and taxonomic distribution in coloration and camouflage mismatch and to quantify the potential of seasonally color molting species to adapt to environmental changes via phenotypic plasticity in color molts and behavior. This second objective will be achieved using advanced statistical modeling approaches that will enhance our understanding of how organisms adapt to their local environments, how interspecific ecological interactions shape these adaptations, and how species may respond to future environmental change. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.