Soil heterotrophic respiration (HR) is an important source of soil-to-atmosphere CO2 flux, but its response to changes in soil water content (θ) is poorly understood. Earth system models commonly use empirical moisture functions to describe the HR–θ relationship, introducing significant uncertainty in predicting CO2 flux from soils. Generalized, mechanistic models that address this uncertainty are thus urgently needed. Here we derive, test, and calibrate a novel moisture function, fm, that encapsulates primary physicochemical and biological processes controlling soil HR. We validated fm using simulation results and published experimental data, and established the quantitative relationships between parameters of fm and measurable soil properties, which enables fm to predict the HR–θ relationships for different soils across spatial scales. The fm function predicted comparable HR–θ relationships with laboratory and field measurements, and may reduce the uncertainty in predicting the response of soil organic carbon stocks to climate change compared with the empirical moisture functions currently used in Earth system models.
The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO 2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The porescale results were then averaged to calculate the effective respiration rates as a function of water content in soils. The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75, which is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geophysical, and biochemical factors.
Biofilms are critical locations for biogeochemical reactions in the subsurface environment. The occurrence and distribution of biofilms at microscale as well as their impacts on macroscopic biogeochemical reaction rates are still poorly understood. This paper investigated the formation and distributions of biofilms in heterogeneous sediments using multiscale models and evaluated the effects of biofilm heterogeneity on local and macroscopic biogeochemical reaction rates. Sediment pore structures derived from X‐ray computed tomography were used to simulate the microscale flow dynamics and biofilm distribution in the sediment column. The response of biofilm formation and distribution to the variations in hydraulic and chemical properties was first examined. One representative biofilm distribution was then utilized to evaluate its effects on macroscopic reaction rates using nitrate reduction as an example. The results revealed that microorganisms primarily grew on the surfaces of grains and aggregates near preferential flow paths where both electron donor and acceptor were readily accessible, leading to the heterogeneous distribution of biofilms in the sediments. The heterogeneous biofilm distribution decreased the macroscopic rate of biogeochemical reactions as compared with those in homogeneous cases. Operationally considering the heterogeneous biofilm distribution in macroscopic reactive transport models such as using dual porosity domain concept can significantly improve the prediction of biogeochemical reaction rates. Overall, this study provided important insights into the biofilm formation and distribution in soils and sediments as well as their impacts on the macroscopic manifestation of reaction rates.
Bacterial chemotaxis can enhance the bioremediation of contaminants in aqueous and subsurface environments if the contaminant is a chemoattractant that the bacteria degrade. The process can be promoted by traveling bands of chemotactic bacteria that form due to metabolism-generated gradients in chemoattractant concentration. We developed a multiple-relaxation-time (MRT) lattice-Boltzmann method (LBM) to model chemotaxis, because LBMs are well suited to model reactive transport in the complex geometries that are typical for subsurface porous media. This MRT-LBM can attain a better numerical stability than its corresponding single-relaxation-time LBM. We performed simulations to investigate the effects of substrate diffusion, initial bacterial concentration, and hydrodynamic dispersion on the formation, shape, and propagation of bacterial bands. Band formation requires a sufficiently high initial number of bacteria and a small substrate diffusion coefficient. Uniform flow does not affect the bands while shear flow does. Bacterial bands can move both upstream and downstream when the flow velocity is small. However, the bands disappear once the velocity becomes too large due to hydrodynamic dispersion. Generally bands can only be observed if the dimensionless ratio between the chemotactic sensitivity coefficient and the effective diffusion coefficient of the bacteria exceeds a critical value, that is, when the biased movement due to chemotaxis overcomes the diffusion-like movement due to the random motility and hydrodynamic dispersion.
Soil nitrous oxide (N2O) is an important source of greenhouse gas contributing to climate change. Many processes produce N2O in soils and the production rate of each process is affected variably by climatic-edaphic factors, making the soil-to-atmosphere N2O flux extremely dynamic. Experimental approaches, including natural and enriched isotopic methods, have been developed to separate and quantify the N2O production from different processes. However, these methods are often costly or difficult to conduct, hampering their widely applications. This study aimed to develop a mechanistic model quantifying the soil N2O production from nitrifier nitrification (NN), nitrifier denitrification (ND), and heterotrophic denitrification (HD), which are considered as the most important biological contributors, and to investigate how climatic-edaphic factors affect individual processes as well as total N2O production rates. The developed model demonstrated its robustness and capability by reliably reproducing N2O productions from the three individual processes of NN, ND, and HD under different moisture contents and oxygen concentrations. The model simulations unraveled how environmental conditions and soil properties controlled the total N2O production rate by regulating individual rates variably. Therefore, the mechanistic model is able to potentially elucidate the large spatiotemporal variances of in-situ soil N2O flux and improve the assessment of soil N2O emission at regional and global scales.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.