April 15, 2024
Microbial Parameters Can Be Generalized in Soil Biogeochemical Model
Microbial parameters in a soil carbon cycling model can be generalized across different soil series, potentially simplifying the application for the future.
The Science
Incorporating soil microbial processes can improve soil model projections, and achieving a common set of microbial parameters across sites would enable more widespread application. Based on a 2‐year soil incubation data set, this study showed key microbial parameters could be generalized at the soil series level (four distinct soil series from three soil orders) but not land cover type (forest vs. grassland). The common set of parameters includes those processes controlling microbial growth and maintenance as well as extracellular enzyme production and turnover.
The Impact
Future microbial model applications can potentially use the same parameters across different soil series but not across plant functional types when implementing models at various sites. Besides heterotrophic respiration and microbial biomass data, soil extracellular enzyme data sets are particularly needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.
Summary
The study used the Microbial ENzyme Decomposition (MEND) model for simulations. MEND is one of the earlier soil process models (2013) that explicitly incorporates microbial biomass and enzyme function to simulate soil carbon and nitrogen cycling. MEND has been applied to incubation studies, long-term field studies, and ecosystem demographic and earth system models. Therefore, the findings that microbial parameters can be generalized across different soil series and orders could enable broader application of explicit microbial activities in earth system models. This approach should be tested with other datasets and microbial soil carbon cycling models.
Principal Investigator
Paul Hanson
Oak Ridge National Laboratory
[email protected]
Program Manager
Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]
Funding
Support was received from the U.S. National Science Foundation HBCU‐EiR (No. 1900885), the U.S. Department of Energy (DOE) Office of Science Research Development and Partnership Pilot program (DE‐SC0023206), and the U.S. Department of Agriculture’s National Institute of Food and Agriculture Grant (No. 2021‐67020‐34933). Funding was also received from the DOE Biological and Environmental Research program through the Oak Ridge National Laboratory (ORNL) Terrestrial Ecosystem Science Scientific Focus Area and subcontracted to Tennessee State University (No. 4000148926) and DOE’s Genomic Science Program (Award Number DESC0020163 and DE‐SC0023106). Contributions from Wuhan University are supported by National Natural Science Foundation of China (No. 42371032). ORNL is managed by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with DOE.
Related Links
References
Jian, S., et al. "Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi-Site Incubation Experiment." Journal of Geophysical Research: Biogeosciences 129 (4), e2023JG007825 (2024). https://doi.org/10.1029/2023JG007825.