Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics.
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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.
SUBMITTER: Jian S
PROVIDER: S-EPMC7672078 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
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