Natasha Gownaris, Ph.D.

Behavioral plasticity as a mechanism for adaptation in rapidly changing environments

Abstract

We are living in a time of environmental shifts and extremes. For many species, evolution is unlikely to keep pace with these changes. Behavioral plasticity, the ability of an organism to alter their behavior in response to the environment, may buy time for evolution to occur. However, we still have a poor understanding of what drives plasticity and of how plasticity influences population persistence. Using seabirds as a study system, this research addresses key knowledge gaps regarding the causes and consequences of behavioral plasticity in long-lived species, providing insight into their capacity for adaptation and resilience to climate change. This work leverages long-term and field-collected datasets on tern (Arctic tern and common tern) and alcid (Atlantic puffin and black guillemot) breeding colonies located in the Gulf of Maine and large, open datasets on the foraging behavior of over 100 seabird species. The Gulf of Maine is warming three times faster than the global average, with long-term trends punctuated by extreme “marine heatwaves”. It provides a natural experiment for testing the potential for long-lived species to adapt to rapid environmental change through individual-level plasticity. The dataset developed will include information on seabird diet, foraging movements, and life history and on the environmental context in which these species forage. It will provide a powerful tool for examining which ecological (e.g., foraging mode) and environmental (e.g., habitat productivity) variables are associated with plasticity, informing how and why the magnitude of plasticity varies across individuals, species, sites, and behaviors. These data will be used to test how individual-level plasticity covaries with fitness, an individual’s ability to survive and raise offspring, and to understand how these relationships scale up to influence population-level dynamics. The approaches developed will therefore provide more accurate predictions of population responses to rapidly changing environments.

Award amount: $149,814

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