How environmental conditions vary locally in mountainous regions of the western United States and how rapid climate change determine the survival and migration rates of trees will be studied by an interdisciplinary team of climate scientists, ecologists, hydrologists and plant geographers. Current climate data and models are too coarse to accurately predict the finer scale spatial variation that enables plant communities to exist and persist. Moreover, there is scant knowledge of how colonization by tree seedlings and tree growth differ among local climates and how that might influence tree population dynamics at the regional scale. This project couples field studies of local climate, tree establishment and tree growth with regional climate modeling and models that depict spatial processes of plant population and fire dynamics. This project will bridge environmental and plant processes from the local scale of individual trees to whole tree populations at the regional level. Models based on field data and theory will predict future changes in the distribution and abundance of important oak and pine trees in California, a topographically complex and ecologically diverse region.
Understanding and forecasting climate change effects on tree species is important, given the role of forests in carbon cycling, timber production, water resources and biodiversity. This project aims to revise extinction risk due to climate change, refine understanding of the ability of trees to migrate and track rapid changes, and improve predictions of how economically important trees will respond to climate change and associated changes in wildfire risk. At least three Doctoral students and three Post-Doctoral scholars will be trained to help prepare the next generation of scientists to tackle future challenges. The project also involves governmental and other non-university researchers to strengthen linkages to public and private land managers, policy makers and non-Government organizations. This will ensure that results will be translated to better adaptive management of public and private forest resources.
