PS 40-119 - A microbial data system to support microbial modeling: case studies with CLM-Microbe

Abstract: Soil microbes play a key role in climate feedback through processes such as the production and consumption of greenhouse gas (primarily CO₂ and CH₄) flux. Over the past ten years, numerous microbial models have been developed to explicitly simulate microbial mechanisms in soil carbon cycling. Model applications have been promising; however, large uncertainties remain due to the implicit representation of microbial processes and untuned parameters, which a comprehensive microbial dataset can address. The objective of this project is to develop a community dataset of microbial variables to support Earth system model development and application, as demonstrated by case studies of the CLM-Microbe.



Using a data synthesis approach, our team has compiled data points for a set of microbial variables including microbial abundance, community structure, functional activities, and substrate and products of microbial processes. The sources for data compilation include raw data, unpublished data obtained from colleagues, dissertations, reports, published literature, and online databases. The microbial data system has been hosted at the Environmental Data Initiative (EDI). Three levels of data have been archived, following the data preparation procedure adopted by the EDI. Level 0 is raw data to maintain transparency; level 1 is the processed data with consistent units, data structures, and projections for spatial data; level 2 is published data products. All three levels of data are publicly accessible.



Meanwhile, the CLM-Microbe model has been developed with four major features. (1) Bacterial and fungal biomass are directly comparable with observational data. (2) A microbial-functional-group-based CH₄ module can assimilate metagenomic data. (3) All carbon processes are coupled with nitrogen processes. (4) These mechanisms are coupled in the Community Land Model (CLM). Thus, the carbon-nitrogen feedback and above- and below-ground interactions are fully considered. Integrating the CLM-Microbe model with the microbial data system has demonstrated the importance of microbial mechanisms in CO₂ and CH₄ flux. Specifically, the CLM-Microbe with methanogen and methanotroph dynamics reached a better agreement with observational data for both ecosystem respiration and CH₄ flux in Arctic tundra and temperate wetlands. After parametrization and validation in major biomes, CLM-Microbe simulated the promoting effects of microbial fluctuations on soil carbon emissions can be as high as 32%, indicating the importance of representing microbial dynamics in projecting soil carbon cycling. In conclusion, the developed microbial data system and the CLM-Microbe model serve as meaningful support and tools for the community to understand microbial mechanisms.