January 20, 2021

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Simulating Microbial Community Structure (Fungi and Bacteria) in an Earth System Model: The CLM‐Microbe Model

The CLM-Microbe model can simulate fungi and bacteria and their roles in the carbon cycle.

Comparison of the averaged observed and simulated a) fungal and b) bacterial biomass. The blue star indicates the a) fungal or b) bacterial biomass in calibration phase, and the black filled circle represents a) fungal or b) bacterial biomass in validation phase; vertical and horizontal error bars indicate standard error of simulated and observed values, respectively, for both a) fungal and b) bacterial biomass.
[Image Credit: Reprinted under a Creative Commons Attribution 4.0 International License (CC BY 4.0) from He, L., D. A. Lipson, J. L. Mazza Rodrigues, et al. “Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site‐level Applications of the CLM‐Microbe Model.” Journal of Advances in Modeling Earth Systems. 13(2), e2020MS002283 (2021). DOI:10.1029/2020MS002283]

The Science

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for 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 and bacterial biomass C from nine biomes, the researchers parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling.

The Impact

Simulating microbial community improves the mechanistic understanding of carbon cycle and reduces uncertainties in global carbon projection.

Summary

The CLM-Microbe model is able to reasonably capture the seasonal dynamics of fungal and bacterial biomass across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland. The researchers found good consistencies between simulated and observed fungal and bacterial biomass on average across biomes, although the model is not able to fully capture the large variation in observed biomass. 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 carbon density. The further application of the CLM-Microbe model would deepen the understanding of microbial contributions to the global carbon cycle.

Principal Investigator

Xiaofeng Xu
San Diego State University
xxu@sdsu.edu

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

This work is financially supported by the U.S. Department of Energy (DOE) Office of Biological and Environmental Research through the Terrestrial Ecosystem Science Scientific Focus Area at Oak Ridge National Laboratory (ORNL), the U.S. National Science Foundation (NSF) HBCU-EiR, the DOE Early Career Program, and the DOE Genomic Science Program. Financial support from ORNL to Tennessee State University (TSU) was provided through a subcontract. ORNL is managed by the University of Tennessee-Battelle, LLC with the U.S. DOE.

Related Links

References

He, L., D. A. Lipson, J. L. Mazza Rodrigues, et al. "Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site‐level Applications of the CLM‐Microbe Model". Journal of Advances in Modeling Earth Systems 13 (2), e2020MS002283  (2020). https://doi.org/10.1029/2020MS002283.