Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

He, Liyuan; Lipson, David A.; Mazza Rodrigues, Jorge L.; Mayes, Melanie; Björk, Robert G.; Glaser, Bruno; Thornton, Peter; Xu, Xiaofeng

doi:10.1029/2020ms002283

Title: Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Journal Article · Mon Dec 07 00:00:00 EST 2020 · Journal of Advances in Modeling Earth Systems

DOI:https://doi.org/10.1029/2020ms002283· OSTI ID:1763456

^[1]; Lipson, David A. ^[1];

^[2];

^[3];

^[4]; Glaser, Bruno ^[5];

^[3];

^[1]

San Diego State Univ., CA (United States)
Univ. of California, Davis, CA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.
Univ. of Gothenburg (Sweden); Gothenburg Global Biodiversity Center, Gothenburg (Sweden)
Martin Luther Univ. Halle-Wittenberg, Halle (Saale) (Germany). Inst. of Agricultural and Nutritional Sciences

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R²=0.70, P<0.001) and BBC (R²=0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1763456

Journal Information:: Journal of Advances in Modeling Earth Systems, Vol. 13, Issue 2; ISSN 1942-2466

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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