ESIIL Postdoctoral Associate

Project Summary

Woody encroachment, driven by climate warming, disturbance, and altered nutrient cycling, is occurring across ecosystems globally with significant implications for surface energy balance and ecosystem functions and services. These vegetation shifts modify biogeochemical and biophysical processes locally, altering ecosystem energy, water, and carbon (C) fluxes. While there is widespread agreement that woody encroachment has regional and global consequences that can create non-linear climate feedbacks, the underlying biological processes are poorly incorporated into land models that are used for climate change projections.

Two related challenges must be addressed to incorporate shrub encroachment into land models. First, studies using modeling approaches to explore shrub encroachment have largely assumed arbitrary increases in cover, demonstrating a need for predictive tools to understand the mechanisms driving these transitions. Second, land models have largely overlooked trait-environmental relationships even though plant traits vary with environmental conditions and trait differences between encroaching shrubs and resident species are likely critical in shaping ecosystem responses and climate feedbacks. By leveraging big datasets in combination with remote sensing techniques, machine learning approaches, and process-based ecosystem modeling, my project will tackle these challenges and increase our ability to incorporate vegetation dynamics into regional and global land model predictions. I will integrate diverse, open datasets at local and regional scales to quantify woody encroachment rates while helping to develop a pipeline for using these datasets in ecological studies with land models in other ecosystems.

Visit Dr. Katya Jay's tundra shrub expansion repository to learn more: Link to GitHub