A Microbial‐Explicit Soil Organic Carbon Decomposition Model (MESDM): Development and Testing at a Semiarid Grassland Site

Xia, Zhang; Xie, Zhenghui; Ma, Zhuguo; Barron‐Gafford, Greg A.; Scott, Russell L.; Niu, Guo Yue

doi:10.1029/2021ms002485

Cited by 9 publications

(9 citation statements)

References 114 publications

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“…Microbial decomposition is a critical process in the soil C cycle because it is the primary pathway through which CO 2 fixed by plants is returned to the atmosphere (Zhang et al, 2022). Therefore, microbial models have taken diverse approaches to represent the decomposition process (Fig.…”

Section: Microbial Decomposition Of Socmentioning

confidence: 99%

“…There is a consensus among microbial models that microbes produce ENZ to degrade complex SOC into dissolved organic carbon (DOC) through catalysis, take up DOC, convert the assimilated C into microbial biomass for growth, and release CO 2 through respiration (Sinsabaugh et al, 2008;Zhang et al, 2022). Two pathways are used for the representation of the decomposition of SOC: enzymatic-and microbial biomass-mediated decomposition (Fig 2a).…”

Section: Microbial Decomposition Of Socmentioning

confidence: 99%

“…In our review, only 10 out of 70 models explicitly simulated microbial transformation between active and dormant states (Brangarí et al, 2020;Gignoux et al, 2001;He et al, 2015;Huang et al, 2018;Huang et al, 2021;Liu et al, 2019;Wang et al, 2015;Wang et al, 2017;Zha & Zhuang, 2020;Zhang et al, 2022), (Table 1). SOMKO was one of the first microbial models that distinguish active and dormant microbial biomass (Gignoux et al, 2001).…”

Section: Therefore An Understanding Of Dormancy Could Improve the Pre...mentioning

confidence: 99%

“…Unlike the above-mentioned microbial models that consider the substrate dependence of dormancy, the microbial dormancy in the microbial models DORMANCY 2.0, EcoSMMARTS, and MESDM is also affected by soil moisture content (Table 2). Such microbial models were developed to simulate the soil respiration in soil moisture-limited conditions to capture the drying-rewetting effect (i.e., Birch effect) under the assumptions that the soil water content determines the overall microbial performance and changes in soil water content can alter the physiological state of a 502 portion of the microbes (Brangarí et al, 2020;Zhang et al, 2022).…”

Section: Therefore An Understanding Of Dormancy Could Improve the Pre...mentioning

confidence: 99%

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Microbial Models for Simulating Soil Carbon Dynamics: A Review

Chandel

Luo

Jiang

2023

Preprint

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Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical to the global C balance. Numerous microbial models have been developed over the last few decades to represent microbial processes that regulate the responses of soil organic carbon (SOC) to climate change. However, the representation of microbial processes varies, and how microbial processes are incorporated into SOC models has not been well explored. Here, we reviewed 70 microbial models to characterize the microbial processes incorporated into SOC models and analyzed variations in mechanistic complexity. We revealed that (1) four processes (microbial decomposition, mineral interaction, microbial mortality, and transition between active and dormant microbial states) are commonly incorporated in microbial models, (2) ~47% of models simulate only one (i.e., microbial decomposition) and 33% simulated two microbial processes: microbial decomposition and mineral interaction, (3) more than 80% microbial models use nonlinear mathematical equations, such as forward Michaelis-Menten kinetics, to represent SOC decomposition, (4) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo-mineral interaction (~39% of microbial models) that protects SOC from decomposition, and (5) various temperature and moisture modifiers and pH effects have been used to explain the environmental effect on microbial processes. Finally, we propose a roadmap for SOC model improvement. In the future, to realistically incorporate microbial processes into Earth System Models, it is imperative to identify experimental evidence on rate limitation processes and firmly ground model structure on the field and laboratory data.

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Section: Microbial Decomposition Of Socmentioning

confidence: 99%

Section: Microbial Decomposition Of Socmentioning

confidence: 99%

Section: Therefore An Understanding Of Dormancy Could Improve the Pre...mentioning

confidence: 99%

Section: Therefore An Understanding Of Dormancy Could Improve the Pre...mentioning

confidence: 99%

See 2 more Smart Citations

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Chandel

Luo

Jiang

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Unlike the above‐mentioned microbial models that consider the substrate dependence of dormancy, the microbial dormancy in the microbial models DORMANCY 2.0, EcoSMMARTS, and MESDM is also affected by soil moisture content (Table 2). Such microbial models were developed to simulate the soil respiration in soil moisture‐limited conditions to capture the drying‐rewetting effect (i.e., Birch effect) under the assumptions that the soil water content determines the overall microbial performance and changes in soil water content can alter the physiological state of a portion of the microbes (Brangarí et al., 2020; X. Zhang et al., 2022).…”

Section: Model Representation Of Microbial Processesmentioning

confidence: 99%

Microbial Models for Simulating Soil Carbon Dynamics: A Review

2023

View full text Add to dashboard Cite

Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical to the global C balance. Numerous microbial models have been developed over the last few decades to represent microbial processes that regulate the responses of soil organic carbon (SOC) to climate change. However, the representation of microbial processes varies, and how microbial processes are incorporated into SOC models has not been well explored. Here, we reviewed 71 microbial models to characterize the microbial processes incorporated into SOC models and analyzed variations in mechanistic complexity. We revealed that (a) four processes (microbial‐mediated decomposition, mineral interaction, microbial necromass recycling, and active and dormant microbial dynamics) are commonly incorporated in microbial models, (b) ∼48% of models simulate only one microbial process (i.e., microbial‐mediated decomposition) and 35% of models simulate two microbial processes: for example, microbial‐mediated decomposition and mineral interaction, (c) more than 80% microbial models use nonlinear equations, such as forward Michaelis‐Menten kinetics, to represent SOC decomposition, (d) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo‐mineral interaction (∼39% of microbial models) that protects SOC from decomposition, and (e) various temperature and moisture modifiers and pH effects have been used to explain the environmental effect on microbial processes. In the future, to realistically incorporate microbial processes into Earth System Models, it is imperative to identify experimental evidence on rate limitation processes and firmly ground model structure on the field and laboratory data.

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