Modeling Microbial Biogeochemistry from Terrestrial to Aquatic Ecosystems Using Trait-Based Approaches

Currently, there is uncertainty in how climate or land-use-induced changes in hydrology and vegetation will affect subsurface carbon flux, the spatial and temporal distribution of flow and transport, biogeochemical cycling, and microbial metabolic activity. Here we focus on the initial development of a Genome-Enabled Watershed Simulation Capability (GEWaSC), which provides a predictive framework for understanding how genomic information stored in a subsurface microbiome affects biogeochemical watershed functioning, how watershed-scale processes affect microbial function, and how these interactions co-evolve. This multiscale framework builds on a hierarchical approach to multiscale modeling, which considers coupling between defined microscale and macroscale components of a system (e.g., a catchment being defined as macroscale and biogeofacies as microscale). Here, we report our progress in the development of a trait-based modeling approach within a reactive transport framework that simulates coupled guilds of microbes. Guild selection is driven by traits extracted from, and physiological properties inferred from, large-scale assembly of metagenome data. Meta-genomic, -transcriptomic and -proteomic information are also used to complement our existing biogeochemical reaction networks and contributes key reactions where biogeochemical analyses are unequivocal. Our approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolitho(auto)trophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for each based upon dynamic intracellular and environmental conditions. In addition to biomass development, anabolism includes the production of key enzymes, such as nitrogenase for nitrogen fixation or exo-enzymes for the hydrolysis of extracellular polymers. This internal resource partitioning represents a trade-off against biomass formation and results in microbial population emergence across a fitness landscape. We use this model in simulations to explore the controls on community emergence and impact on rates of reactions that contribute to the cycling of carbon across distinct redox zones of an aquifer.