Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Abstract

Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at µm-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These µm-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs, and copiotrophic cheaters). Our modeling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modeling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (µm) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.

Competition within low-density bacterial populations as an unexpected factor regulating carbon decomposition in bulk soil

“…4 blue line, Fig. 6), in agreement with the results of Pagel et al (2020), suggesting that copiotrophs have more aggregated distributions than oligotrophs. The negligible mineralization even without dispersion (Fig.…”

Competition within low-density bacterial populations as an unexpected factor regulating carbon decomposition in bulk soil

“…4A , Fig. 6 ), in agreement with the results of Pagel et al (2020) suggesting that copiotrophs have more aggregated distributions than oligotrophs. The negligible mineralization even without dispersion ( Fig.…”

Accounting for soil architecture and microbial dynamics in microscale models: Current practices in soil science and the path ahead

“…Other studies on the emergence of a spatial structure of bacterial colonies repeat this same approach (Kaiser, Franklin, Dieckmann, & Richter, 2014;Kaiser, Franklin, Richter, & Dieckmann, 2015;König et al, 2017König et al, , 2018König et al, , 2019Wang & Allison, 2019). In two other similar studies (Chakrawal et al, 2020;Pagel et al, 2020), the effective diffusion coefficients are calculated via the macroscopic relationship proposed by Millington and Quirk (1961), which considers hydration. However, spatial information about the water content at each grid node is not provided.…”

“…In the majority of implicit microscale models, physicochemical processes are not considered at all. In the few articles that are exceptions (Babey et al, 2017;Banitz, Gras, & Ginovart, 2015;Gras, Ginovart, Portell, & Baveye, 2010;Gras, Ginovart, Valls, & Baveye, 2011;Pagel et al, 2020), the sorptions of dissolved OM components, organic pollutant (pesticide) and/or NH4 + are described as mass transfer processes.…”