The complexity of microbial systems necessitates the use of integrated theoretical and experimental approaches to extend our understanding of how individuals function and interact within natural systems. Trait-based models are emerging as powerful tools to explain and predict complex patterns in microbial distribution and function across environmental gradients in space and time. These models are mostly deterministic and require detailed understanding of microbial physiology and response to environmental factors. However as most microorganisms have yet to be cultivated, our understanding of the majority is limited to insights from environmental ‘omic information. However, if this information can be interpreted correctly, and resulting hypotheses tested appropriately, the possibility exists to construct more accurate and representative models of complex microbial communities.
Results/Conclusions
Here we describe a combined approach for the discovery and validation of key microbial traits and their integration into functional trait-based models of different forms (dynamic energy budget, reactive transport). Using multiple ‘omics, chemical and isotopic imaging, and phenotypic assays we derive both qualitative and quantitative traits including those related to substrate use, growth rate, product formation, temperature and light optima and show across three case studies in soil, subsurface and aquatic systems the ability to predict microbial interactions and community succession.