NSF Award
2412076
The health of U.S. forests is of paramount importance for economic security, but rapid environmental change is placing unprecedented stresses on trees that may lead to catastrophic forest loss. Forecasting these changes is a priority for management, but scientists and managers alike require new tools for understanding how near-term stresses influence tree survival, a process often delayed by months or years. In this interdisciplinary project, ecologists, biochemists, and modelers are applying a new laboratory technology related to chemical fingerprinting to understand how immediate changes in leaf chemistry may determine whether a tree lives or dies in response to drought. This approach is novel because it ‘peeks inside’ a leaf to measure how it handles stress in real-time, but performed in natural forest settings to take advantage of long-term datasets of tree growth and survival in two iconic U.S. National Parks. In this way, this project is developing early-warning markers of tree mortality risk, with the ultimate goal of providing accurate forecasts of forest health under changing environmental conditions. The project will provide training to two postdoctoral fellows, three PhD students, two REU students, and additional undergraduate students at Clemson and Denver, and expose all personnel to cross-<br/>institutional and governmental (NPS) research collaborations.<br/><br/> Researchers are testing new hypotheses that provide a mechanistic framework for linking stress-related metabolomics to whole-plant physiology and forest demography. The main hypothesis is that energetic constraints induced by light competition significantly alter the leaf metabolome composition of drought-stressed saplings toward those compounds that maximize the efficacy of antioxidant and osmoregulant activity at a relatively low cost of biosynthesis. Such constraints potentially decouple growth-survival and growth-fecundity relationships in forest demography. Researchers will first couple measurements of leaf physiology and metabolome composition in controlled drought-response experiments of eight different tree species to that of the same species along moisture gradients in Great Smoky Mountain and Rocky Mountain National Parks. Forest simulation models will incorporate effects of drought and light on tree recruitment, growth, and survival, and integrate demographic outcomes conveyed by metabolomics profiling. A transformative aspect of this activity is the identification of ‘stasis’ populations that are demographically stable but experiencing significant drought stress. Such populations indicate disequilibrial dynamics in species distribution models, and provide critical information for forecasting future forest composition.<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.
