EAGER: Using eco-evolutionary interactions to understand forest responses to environmental change

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Trees take a long time to grow and begin producing seeds, which means they have long generation times. Therefore, it has been thought that the main way they could survive rapidly changing climates is by spreading into areas that are more suitable before they die out in areas that are becoming less suitable. However, tree species may also harbor a substantial amount of genetic diversity among individual trees within a populations, which may allow them to adapt to changing conditions on short time frames (50-100 years). This research will test this idea using computer models developed using information from real forest sites. If trees species can adapt quickly, this could influence how forests are managed and how we predict forests will change in the future. This project will also support the research of an early career scientist, provide research training to students, including those from under-served populations, in the use of computer simulations for biology, and provide outreach to the public. This project uses a multi-species individual-based modeling approach to examine how heritable variation in demographic responses to climate may influence how forests respond when climates shift. These responses include changes in tree species ranges and local forest composition. The researchers will modify the forest simulator SORTIE-ND to allow parameters determining how temperature and precipitation affect tree demography to differ between individuals and be passed to offspring with various degrees of heritability. Traditional simulations that assume all individuals of a species are the same will be compared to simulations that allow adaptation to changing temperature and rainfall over 90 years. If heritable environmental responses can substantially affect forest responses to rapid environmental change, this would greatly affect our understanding of the role eco-evolutionary processes will play in future forest dynamics. It would suggests that models need to take these responses into account, and that measuring the magnitude of potential responses to selection is a key empirical need.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.