Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics

Siyang Jian, Jianwei Li (), Gangsheng Wang (), Laurel A. Kluber, Christopher W. Schadt, Junyi Liang and Melanie A. Mayes
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Siyang Jian: Tennessee State University
Jianwei Li: Tennessee State University
Gangsheng Wang: State Key Laboratory of Water Resources and Hydropower Engineering Sciences, Wuhan University
Laurel A. Kluber: Biosciences Division & Climate Change Science Institute, Oak Ridge National Laboratory
Christopher W. Schadt: Biosciences Division & Climate Change Science Institute, Oak Ridge National Laboratory
Junyi Liang: Environmental Division & Climate Change Science Institute, Oak Ridge National Laboratory
Melanie A. Mayes: Environmental Division & Climate Change Science Institute, Oak Ridge National Laboratory

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (–8.2 ± 5.1% or –3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., > 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections.

Date: 2020
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DOI: 10.1038/s41467-020-19428-y

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