Modeling Microbial Dynamics and Heterotrophic Soil Respiration

Abs, Elsa; Ferrière, Régis

doi:10.1002/9781119413332.ch5

Cited by 5 publications

(4 citation statements)

References 136 publications

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“…Soil moisture is a critical factor controlling SOC decomposition because, at high water content, O 2 becomes a limiting factor, whereas, at low water content, diffusion is constrained by thin and discontinuous water films (Abramoff et al, 2017;Abs & Ferrière, 2020;Sihi et al, 2018).…”

Section: Environmental Control On Microbial Processesmentioning

confidence: 99%

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kinetics, to represent SOC decomposition, (4) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo-mineral interaction (~39% of microbial models) that protects SOC from decomposition, and (5) various temperature and moisture modifiers and pH effects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: Environmental Control On Microbial Processesmentioning

confidence: 99%

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Chandel

Luo

Jiang

2023

Preprint

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“…Modeling the response of microbial communities to pulse moisture dynamics is challenging because moisture controls complex physical and biological interactions in soil and has significant direct and indirect impacts on the decomposition rates (Lawrence et al, 2009). Soil moisture is a critical factor controlling SOC decomposition because, at high water content, O 2 becomes a limiting factor, whereas, at low water content, Table 3 Continued diffusion is constrained by thin and discontinuous water films (Abramoff et al, 2017;Abs & Ferrière, 2020;Sihi et al, 2018). Diverse mathematical functions were used to represent the responses of microbial processes to soil moisture; for example, the moisture response variables vary widely by including the function of soil water potential, water holding capacity, or soil water content (Table 3).…”

Section: Environmental Control On 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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“…The optimal ω * can be calculated for that temperature and given all other environmental parameters (see Supplementary note S2 for details). A similar approach was developed in Abs and Ferrière [41] to model the eco-evolutionary dynamics of soil microbial populations exposed to changes in the physical or chemical properties of their environment.…”

Section: Bacterial Adaptation and The Growth Efficiencyresource Acqui...mentioning

confidence: 99%

Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production

Cherabier

Ferrière

2021

The ISME Journal

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Predicting the response of ocean primary production to climate warming is a major challenge. One key control of primary production is the microbial loop driven by heterotrophic bacteria, yet how warming alters the microbial loop and its function is poorly understood. Here we develop an eco-evolutionary model to predict the physiological response and adaptation through selection of bacterial populations in the microbial loop and how this will impact ecosystem function such as primary production. We find that the ecophysiological response of primary production to warming is driven by a decrease in regenerated production which depends on nutrient availability. In nutrient-poor environments, the loss of regenerated production to warming is due to decreasing microbial loop activity. However, this ecophysiological response can be opposed or even reversed by bacterial adaptation through selection, especially in cold environments: heterotrophic bacteria with lower bacterial growth efficiency are selected, which strengthens the “link” behavior of the microbial loop, increasing both new and regenerated production. In cold and rich environments such as the Arctic Ocean, the effect of bacterial adaptation on primary production exceeds the ecophysiological response. Accounting for bacterial adaptation through selection is thus critically needed to improve models and projections of the ocean primary production in a warming world.

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Modeling Microbial Dynamics and Heterotrophic Soil Respiration

Cited by 5 publications

References 136 publications

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production

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