Life history strategies and niches of soil bacteria emerge from interacting thermodynamic, biophysical, and metabolic traits

Abstract

To comprehensively represent the diverse traits found in soil microbiomes in biogeochemical models, it is crucial to leverage information from microbial genomes. This can be achieved by incorporating microbial traits into a theory-based hierarchical framework, allowing for emergent behavior to occur through trait interactions. Here, we combined theory-based predictions of substrate uptake kinetics with a new genome-informed trait-based dynamic energy budget model to predict life history traits and trade-offs of soil bacteria. These bacteria play a critical role in determining the long-term fate of soil carbon through the biochemical transformation of plant root-derived carbon. Without calibration, and using only genome-derived microbial parameters, the model successfully predicted substrate preferences during plant growth and captured resource-dependent trade-offs between growth rate (power) and growth efficiency (yield) that are fundamental to microbial fitness and carbon retention in soil. This approach provides a generalizable data-driven foundation for the trait-based representation of microorganisms in biogeochemical models.