NSF Award
2413627
Predicting how species will be impacted by ongoing and future changes to their environment is critical. Species responses to these changes will determine how well ecosystems function and the ability of the Earth to continue providing food and other resources. Most such predictions focus on changes where a species can occur, but not changes in the numbers of a species, which can be more important for ecology. One major difficulty is that the environment can differ a lot from year to year, which makes it harder to predict how species will be impacted by gradual changes over a long period of time. Also, individuals of widespread species are often adapted to do best in their local environments, which means that the same species in different areas can have different environmental requirements. This project uses transplant experiments and long-term monitoring of wild populations to overcome these challenges, and tests how two common plant species are impacted by environmental change from New Mexico to arctic Alaska. The researchers also team up with educators to create middle and high school curriculum to teach students how to think critically and use real data to investigate ecological and environmental questions. <br/><br/>This research relies on a comprehensive dataset spanning 15-28 years documenting demographic trends in two widespread, long-lived tundra plant species (Silene acaulis and Polygonum viviparum) in 29 populations across western North America. By continuing to monitor these wild populations, the researchers will develop a functional definition of rare climate events and assess their demographic impacts. The project also uses common garden transplants and controlled thermal performance experiments to assess local adaptation to climate and the demographic mechanisms driving it. This project will follow the performance of transplants for a total of 9 years, allowing researchers to test the importance of environmental extremes and cumulative abiotic effects on the magnitude and spatial scale of local adaptation. The researchers will integrate demographic and experimental datasets to develop environmentally-explicit and density-dependent demographic models to make range-wide predictions of distribution and local abundance, considering environmental variability and local adaptation. Notably, predictive models will be validated by testing their ability to “present-cast” current patterns of abundance and occurrence in new locales across the species’ latitudinal ranges before forecasting responses to projected climate change. The project’s goals are to both better predict how these particular species will respond to changes in their environment and to develop and test methods for making predictions that can be used for many other species.<br/><br/>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.
