A generalized optimization model of microbially driven aquatic biogeochemistry based on thermodynamic, kinetic, and stoichiometric ecological theory

We have developed a mechanistic model of aquatic microbial metabolism and growth, where we apply fundamental ecological theory to simulate the simultaneous influence of multiple potential metabolic reactions on system biogeochemistry. Software design was based on an anticipated cycle of adaptive hypothesis testing, requiring that the model implementation be highly modular, quickly extensible, and easily coupled with hydrologic models in a shared state space. Model testing scenarios were designed to assess the potential for competition over dissolved organic carbon, oxygen, and inorganic nitrogen in simulated batch reactors. Test results demonstrated that the model appropriately weights metabolic processes according to the amount of chemical energy available in the associated biochemical reactions, and results also demonstrated how simulated carbon, nitrogen, and sulfur dynamics were influenced by simultaneous microbial competition for multiple resources. This effort contributes an approach to generalized modeling of microbial metabolism that will be useful for a theoretically and mechanistically principled approach to biogeochemical analysis.

Duke Scholars

Author Emily S. Bernhardt Biology