Geodiversity as a Driver of Soil Microbial Community Diversity and Adaptation in a Mediterranean Landscape

Extreme meteorological events and anthropogenic influences determine important variations in microbial community composition. To know the extent of these variations, it is necessary to delve deeper into the geogenic factors to be considered as a baseline. The purpose of this study was to assess the effect of topographic characteristics and soil geochemistry on the spatial distribution of three Actinobacteria genera considered as molecular biomarkers of landforms belonging to Mediterranean environments. Given the important role that Actinobacteria play in the ecosystem, we performed a spatial distribution model of the genera Rubrobacter, Gaiella, and Microlunatus and investigated the fungi/bacteria ratio in a machine learning (ML)-based framework. Variable importance provided insight into the controlling factor of geomicrobial spatial distribution. The spatial distribution of the predicted Actinobacteria genera generally follows topographic constraints, mostly altitude. Rubrobacter was related to the slope aspect and lithium; Microlunatus was related to the topographic wetness index (TWI) and normalized difference water index (NDWI), as well as the fungi/bacteria ratio; and Gaiella was related to flow path and metals. Our results provide new information on the adaptation of Actinobacteria in Mediterranean areas and show the potential of using ML frameworks for the spatial prediction of OTUs distribution.