Kai Zhu is interested in global change biology, ecological modeling, and environmental data science, where he enjoys integrating ecological theory with advanced tools in statistics and computer science. His current research focuses on plant and soil responses to environmental change in the coupled natural and human systems, spanning from meter-scale experiments to global-scale analyses. Recent projects include quantifying climate change impacts on forest geographic distribution and growth in North America; synthesizing a multi-factor global change experiment in California grassland; understanding soil fungi and tree mutualisms across geographical gradients in the United States; detecting land surface phenology change in Northern Hemisphere.
Accomplishments and Awards
- 2023 Propelling Original Data Science (PODS) Grant Award: Bayesian modeling of multi-source phenology to forecast airborne allergen concentration