SMILE

Quoting T. Dobzhansky, “nothing in biology makes sense except in the light of evolution”. This idea could shed new light on how soil microbes access, transform, store, and release their most important resources – carbon and nutrients. We know that these microbial processes have global-scale impacts, including climate regulation and provision of nutrients to plants, but how microbes respond to changes in resources remains challenging to understand and quantify with models. In fact, current models cannot reliably reproduce carbon and nutrient storage and fluxes when soils are disturbed by land use changes or environmental fluctuations (especially of soil moisture). 

To address these urgent challenges and improve predictability of carbon and nutrient cycling, I propose a novel theory based on the premise that microbial use of soil resources is optimized by natural selection. This approach will provide a holistic explanation of microbial processes and yield models that are more reliable than traditional ones because they account for microbial adaptation. After testing this optimality hypothesis, I will answer the broader and globally relevant question – are land use and climatic changes increasing retention or loss of soil carbon and nutrients?

The project will achieve four objectives:
1) Determine the optimal strategies of resource use by soil microbes
2) Fill knowledge gaps on microbial processes by constructing new databases
3) Test the optimality theory using the new databases
4) Integrate the optimality theory into a land surface model to scale up results and assess impacts of land use and climatic (specifically hydrologic) changes on carbon and nutrient storage and fluxes

These theoretical advances will spur a new generation of soil models that translate the outcomes of natural selection into reliable predictions of land use and climate change effects on global ecosystems.