Advanced omics technologies enable the identification of microbial functional diversity, which has encouraged the scientific community to explore ways to improve microbial process representation in soil biogeochemical models and earth system models. However, it is still unclear how the power of omics data could be harnessed to model microbial functional diversity and how the resulted increase in model sophistication may improve our current understanding about climate-carbon feedbacks. In this study, we applied a new, omics-informed soil biogeochemical model to examine the impact of microbial functional diversity on the resilience of soil carbon storage under climate change. We designed a flexible model structure that allows the representation and comparison of microbial functional diversity at three levels (low, medium, and high). To enable model simulations, we used microbial metagenomics to identify microbial enzyme functional classes (EFCs) involved in soil carbon, nitrogen, and phosphorus cycling and biochemical datasets (e.g., BRENDA) to quantify the temperature responses of different EFC activities. We then conducted simulations with Panamanian tropical soils to investigate how microbial functional diversity affects the loss of soil carbon storage under CMIP5 climate change scenarios.
Results/Conclusions
We found that enhanced representation of microbial functional diversity mitigates the projected soil carbon loss in response to climate warming. This is because that the presence of functional complementation inherent in a community of diverse microbes responds collectively to climate change. This finding indicates that incorporating omics-informed microbial functional diversity into earth system models can mitigate uncertainty in soil carbon projection under climate change.