A Comparison of Linear Conventional and Nonlinear Microbial Models for Simulating Pulse Dynamics of Soil Heterotrophic Respiration in a Semi‐Arid Grassland. Issue 5 (19th May 2021)

• Record Type: Journal Article
• Authors: Zhou, Jian; Chen, Shiping; Yan, Liming; Wang, Jing; Jiang, Ming; Liang, Junyi; Zhang, Xuanze; Xia, Jianyang
• Is Part Of: Journal of geophysical research. Volume 126:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-19
• Subjects: heterotrophic respiration -- nonlinear process -- rain pulse effect -- soil carbon cycle model -- soil microbial model -- soil moisture; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2020JG006120
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: As a critical process in regulating terrestrial feedback to climate change, soil heterotrophic respiration is commonly simulated with the first‐order kinetics in current Earth system models. Compared with the first‐order kinetic models, explicit microbial models are expected to better simulate nonlinear carbon (C)‐cycle phenomena, such as the pulse dynamics of soil heterotrophic respiration driven by dry‐rewetting cycles in grasslands. However, these two types of models (i.e., linear conventional and nonlinear microbial models) have never been compared based on in situ observations of soil heterotrophic respiration in the semi‐arid grassland, which is significantly affected by the dry‐rewetting events. Here, based on the field data of soil heterotrophic respiration in a semi‐arid grassland in northern China, we first showed that the shift from a conventional linear model to a nonlinear microbial model did not substantially improve the simulation of soil heterotrophic respiration. Then, we quantified the contributions of different moisture‐response functions to the uncertainty in simulating the soil C dynamics. The results showed that the selection of moisture‐response functions combined with parameterization in the soil C models dominated the modeled uncertainties in soil heterotrophic respiration. These findings suggest that both the conventional linear model and nonlinear microbial model can simulate well the pulse dynamic of soil heterotrophic respiration in grasslands with an improved parameterization of water regulation on soil carbon decomposition. This study also calls for more observations of nonlinear C phenomena for reducing the simulation uncertainty on soil C cycling in Earth system models. Plain Language Summary: Soil heterotrophic respiration refers to the process of decomposing soil organic carbon and releasing CO2 into the atmosphere. Current soil carbon models use the first‐order kinetics to represent the decomposition process, but large uncertainties have emerged in simulating soil heterotrophic respiration among these models. Therefore, models incorporating microbial mechanisms are expected to better simulate soil carbon processes than the conventional models, especially in simulating the nonlinear phenomena of soil heterotrophic respiration. To test the ability of these two types of models (i.e., linear conventional and nonlinear microbial models) in simulating the nonlinear soil processes, we evaluate them based on in situ observations of the pulsed dynamics of soil heterotrophic respiration in a semi‐arid grassland. We found the microbial‐explicit model did not substantially improve the simulation of soil heterotrophic respiration. The moisture‐response function combined with parameterization played an important role in reducing the uncertainties in simulating the pulsed dynamics of soil heterotrophic respiration in both types of models. Key Points: Both conventional linear and microbial nonlinear models can capture the pulsed dynamics of heterotrophic respiration The moisture‐response function combined with model parameterization dominates the modeled uncertainties in heterotrophic respiration More observations of nonlinear C phenomena are needed to reduce the simulation uncertainty on soil C cycling in Earth system models