Microorganisms govern the belowground economy of terrestrial ecosystems. In close association with plant roots, soil organic matter, and minerals, fungi and bacteria determine how efficiently plants acquire nutrients, whether soil organic matter is decomposed or stabilized, and how quickly minerals dissolve. These processes shape how ecosystems store carbon, recycle nutrients, and support plant growth, and how they respond to a changing climate. Yet these microbes are coarsely represented, or absent, in the models used to forecast those responses. That gap limits our mechanistic understanding of ecosystem function and our ability to evaluate strategies for climate mitigation, restoration, and sustainable land management.

The Shao Lab develops process-based ecosystem models in which microbes are active players rather than hidden inside the equations, and combines them with experimental and observational data to address questions experiments alone cannot resolve: what carbon cost do plants pay for their microbial partners, and when does that investment stop paying off? Which microbial traits propagate upward to shape ecosystem-scale carbon and nutrient fluxes? How much of the carbon removal predicted for a soil-based climate solution is actually realized in a living soil? We also couple these models with machine learning to build digital twins that forecast ecosystem change under future climate and management. We work across a range of ecosystems, including peatlands, forests, and agricultural systems, in collaboration with field and laboratory research groups.