Speaker: Licheng Liu, assistant professor, Department of Biological Systems Engineering, UW–Madison
Quantifying ecosystem greenhouse gas (GHG) fluxes and carbon sequestration is challenging due to strong nonlinear processes and complex land–atmosphere interactions. This talk introduces a knowledge-integrated artificial intelligence framework that embeds ecosystem process understanding into machine learning models to advance ecosystem GHG and carbon sequestration estimation. Case studies from agroecosystem carbon budgeting and ecosystem methane modeling demonstrate how this approach enhances predictive performance and interpretability, with potential to assist climate change mitigation and ecosystem management