I study how trees make decisions under uncertainty, and what happens when the environment changes faster than their strategies can keep up. My research uses coastal forests threatened by sea level rise as a model system for this problem. These forests offer a natural gradient of stress where you can watch trees acclimate, struggle, and sometimes die, all within centimeters of elevation change. By combining hands-on field physiology (hydraulics, carbon) with computational modeling, I try to connect what we can measure about a tree's physiological state to its latent strategies that we can't easily observe.
During my exchange with the SalGo team and INET, I'm working to formalize this integration using tools from complex systems science, like agent-based frameworks that let us represent trees as unified decision-makers with physiological constraints rather than collections of independent processes. I think ecology has an exciting opportunity to borrow from fields that have learned to compress complex dynamics into tractable models, and I'm especially interested in how ideas from information theory can help us bridge the gap between organism-scale physiology and reliable prediction at larger scales. I also care a lot about building better tools for the field, open-source instruments, software, and methods that break the tradeoff between scale and precision.
