Microbial community response to hydration-desiccation cycles in desert soil

Abstract

Life in desert soil is marked by episodic pulses of water and nutrients followed by long periods of drought. While the desert flora and fauna flourish after rainfall the response of soil microorganisms remains unclear and understudied. We provide the first systematic study of the role of soil aqueous habitat dynamics in shaping microbial community composition and diversity. Detailed monitoring of natural microbial communities after a rainfall event revealed a remarkable decrease in diversity and a significant transition in community composition that were gradually restored to pre-rainfall values during soil desiccation. Modelling results suggest a critical role for the fragmented aqueous habitat in maintaining microbial diversity under dry soil conditions and diversity loss with wetting events that increase connectivity among habitats. This interdisciplinary study provides new insights into wetting and drying processes that promote and restore the unparalleled microbial diversity found in soil.

Hydration status and diurnal trophic interactions shape microbial community function in desert biocrusts

“…This approach allows us to extend the surface model to the vertical cross-sectional model and to include gas diffusion and mass transfer between the liquid and gas phases as a function of matric potential by using effective film thickness ( Fig. 2c) without the complexity of 3-D modelling of the pore space in the biocrust (Kim and Or, 2016;Št'ovíček et al, 2017). We represent a section through the biocrust by using a spatially distributed soil properties and assigning key parameters {φ, , D} to individual patches (representing soil grains or small aggregates).…”

“…Geometrically explicit features of the rough surface (pyramid-shaped depressions of different sizes) are averaged according to a probability distribution of the pore sizes (representing the roughness decorating soil grains). For the size distribution, we assign three parameters: local porosity φ, surface roughness porosity , and fractal dimension D (Št'ovíček et al, 2017;Kim and Or, 2016). This abstract representation of the physical domain permits a physically based calculation of the amount of water held within the rough surface for a given matric potential (our standard hydration metric).…”

“…The rough surface is simplified with abstract geometries to calculate the effective film thicknesses of the surface on a patch scale. To represent interference of the liquid phase with respect to gas diffusion, we consider two rough soil surfaces (cross sections) facing each other as described previously (Kim and Or, 2016;Št'ovíček et al, 2017). (b) Spatio-temporal variations in light intensity and temperature as boundary conditions (wet and dry) during a diurnal cycle.…”

“…The microbial feedback on biocrust pH can vary based on types of enzymes, the number of ionisable groups, and the organisms under consideration. In this work, a non-competitive inhibition model in the form of a Monod function is employed (Tan et al, 1998):…”

“…We use a modified rough surface patch model (Št'ovíček et al, 2017;Kim and Or, 2016) to represent the top millimetres to centimetres of soil where most biocrusts develop (see Fig. 2a).…”