A hydration-based biophysical index for the onset of soil microbial coexistence

Abstract

Mechanistic exploration of the origins of the unparalleled soil microbial biodiversity represents a vast and uncharted scientific frontier. Quantification of candidate mechanisms that promote and sustain such diversity must be linked with microbial functions and measurable biophysical interactions at appropriate scales. We report a novel microbial coexistence index (CI) that links macroscopic soil hydration conditions with microscale aquatic habitat fragmentation that impose restrictions on cell dispersion and growth rates of competing microbial populations cohabiting soil surfaces. The index predicts a surprisingly narrow range of soil hydration conditions that suppress microbial coexistence; and for most natural conditions found in soil hydration supports coexistence. The critical hydration conditions and relative abundances of competing species are consistent with limited experimental observations and with individual-based model simulations. The proposed metric offers a means for systematic evaluation of factors that regulate microbial coexistence in an ecologically consistent fashion.

Figure 1. Aqueous phase configuration on a schematic rough surface delineating connected clusters of sizes R_C(ψ) and associated microbial mean generation length, R_G(ψ) under (a) wet, and (b) dry conditions.

Gray dash lines illustrate the additional distance required for a full generation length (additional time is required for cell division after reaching the aqueous cluster boundary). Red rods represented superior microbial species and blue ones inferior species, both are flagellated (dashed lines mark hypothetical cell trajectories).

Figure 2. (a) Predicted and simulated radii (mean±s.d., n = 5) of aqueous clusters (normalized by maximum cluster size under saturation condition) as a function of matric potential, (b) predicted and simulated (mean±s.d., n = 5) effective nutrient diffusion coefficients (normalized by diffusion coefficient of glucose in bulk water), UD and LR represent simulated diffusion coefficients with flux from top to bottom and from left to right boundaries of a domain, respectively, (c) analytical prediction for mean cell velocity and comparisons with numerical simulations and experimental measurements (mean±s.e.m., n = 34600 for simulation and n>248 for experiments), and aqueous cluster distributions on (d) wet and (e) dry surfaces, colors mark different clusters.

Figure 3. (a) Analytical microbial CI predictions (mean±s.d., n = 6, gray area marks 1 s.d.) and corresponding common Simpson species evenness (initial inoculation size of 64 cells of each species), and comparisons with simulated CI values (mean±s.d., n = 384) and Simpson evenness (mean±s.d., n = 16 mixed population inoculated colonies), and (b) analytical and simulated (mean±s.d., n = 16 mixed population inoculated colonies) relative abundance as a function of CI.

Note the trend towards higher evenness under drier conditions. The simulated abundance distributions were extracted from the same set of numerical simulations used for evenness indices presented in (a).

Figure 4. Analytical CI predictions and calculated relative fitness (RF) (initial inoculation size of 100 cells of each species) for 3D porous media, and comparisons of RF with experimental data (“triangle” and “square” symbols mark experimental data extracted from Fig. 3 and Fig. 4 in Reference 20, respectively).