Soils act as a vast carbon storehouse that could also be a huge source of greenhouse gas emissions. Microbes within the soil control carbon emissions via cellular respiration, which feeds on surrounding carbon. Oddly, microbes’ metabolic activities are generally substrate (carbon) limited. This contradiction creates significant challenges in the development of models that predict carbon dioxide (CO2) emissions from soil. This project used a spatial modeling analysis to demonstrate how distance among the diverse components of soil impacts microbial access to substrate—its nourishment—and thus respiration rates at micrometer scales. Findings indicate that contrary to previous predictions, there are fewer CO2 emissions when the distribution of substrates is varied.
Soil contains twice as much carbon as all vegetation on Earth and far more than is currently in the atmosphere as CO2. Predicting how carbon is stored in soil and released as CO2 is a critical calculation in understanding future climate dynamics. This study used novel numerical experiments to examine how the respiration of microbes in soil should be modeled. Results show that simulations must acknowledge the proximity of microbes and substrates within the soil in order to accurately predict carbon emissions.
The distribution of carbon in soil is highly localized due to the arrangement of soil particles, organic carbon, water, and gas. This diverse makeup influences how microbes access substrates for nourishment, which fuels their respiration, and how that respiration also depends on soil moisture. Using a simple diffusion-reaction model and numerical experiments, this study demonstrates that moisture interacts with varying substrate distribution at the micrometer scale to control the dynamic transitions between regimes where either the rate of substrate diffusion or microbial metabolic activity limits respiration. Such regime shifts are driven by the nonlinearity that emerges from varying distances between microbes and substrates and the varying saturation behaviors of microbial utilization of substrates. As a result, the “real” spatially resolved rates of microbial respiration are always lower than rates calculated based on homogeneous substrate distribution. The novel formulation of diffusion-limited microbial respiration proposed in this study provides biophysical insights about how microscale nonlinearity between substrate distribution and microbial respiration drives prediction biases at a macroscopic level.
Vanessa Bailey, firstname.lastname@example.org
This research was supported by the Department of Energy, Office of Science, Biological and Environmental Research program as part of the Environmental System Science Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830.
Published: March 2, 2022
Zheng, Jianqiu, Bond-Lamberty, Benjamin, and Bailey, Vanessa L. 2022. Revisiting diffusion-based moisture functions: why do they fail?. United States: N. p. Web. doi:10.1016/j.soilbio.2021.108525.