The processes governing soil bacteria biogeography are still not fully understood. It remains unknown how the importance of environmental filtering and dispersal differs between bacterial taxonomic and functional biogeography, and whether their importance is scale-dependent. We sampled soils at 195 plots across the Tibet plateau, with distances among plots ranging from 20 m to 1,550 km. Taxonomic composition of bacterial community was characterized by 16S amplicon sequencing, and functional community composition by qPCR targeting 9 functional groups involved in N dynamics. Twelve climatic and soil characteristics were also measured. Both taxonomic and functional dissimilarities were more related to environmental dissimilarity than geographic distance. Taxonomic dissimilarity was mostly explained by soil pH and organic matter, while functional dissimilarity was mostly linked to moisture, temperature and N, P and C availabilities. The roles of environmental filtering and dispersal were, however, scale-dependent and varied between taxonomic and functional dissimilarities, with distance affecting taxonomic dissimilarity over short distances (<~300 km) and functional dissimilarity over long distances (>~600 km). The importance of different environmental predictors varied across scales more for functional than taxonomic dissimilarity. Our results demonstrate how biodiversity dimension (taxonomic versus functional) and spatial scale strongly influence the conclusions derived of bacterial biogeography.

Soil microbes play a key role in shaping terrestrial ecosystems. It is therefore essential to understand what drives their distributions. While multivariate analyses have been used to characterise microbial communities and drivers of their spatial patterns, few studies focused on modelling the distribution of Operational Taxonomic Units (OTUs). Here, we evaluate the potential of species distribution models (SDMs), to predict the presence-absence and relative abundance distribution of bacteria, archaea, fungi and protist OTUs from the Swiss Alps. Advanced automated selection of abiotic covariates was used to circumvent the lack of knowledge on the ecology of each OTU. ‘Presence-absence’ SDMs were successfully applied to most OTUs, yielding better predictions than null models. ‘Relative-abundance’ SDMs were less successful, yet, they were able to correctly rank sites according to their relative abundance values. Archaea and bacteria SDMs displayed better predictive power than fungi and protist ones, indicating a closer link of the latter with the abiotic covariates used. Microorganism distributions were mostly related to edaphic covariates. In particular, pH was the most selected covariate across models. The study shows the potential of using SDM frameworks to predict the distribution of OTUs obtained from environmental DNA (eDNA) data. It underscores the importance of edaphic covariates and the need for further development of precise edaphic mapping and scenario modelling to enhance prediction of microorganism distributions in the future.

The processes governing soil bacteria biogeography are still not fully understood. It remains unknown how the importance of environmental filtering and dispersal differs between bacterial taxonomic and functional biogeography, and whether their importance is scale-dependent. We sampled soils at 195 plots across the Tibet plateau, with distances among plots ranging from 20 m to 1 550 km. Taxonomic composition of bacterial community was characterized by 16S amplicon sequencing, and functional community composition by qPCR targeting 9 functional groups involved in N dynamics. Twelve climatic and soil characteristics were also measured. Both taxonomic and functional dissimilarities were more related to environmental dissimilarity than geographic distance. Taxonomic dissimilarity was mostly explained by soil pH and organic matter, while functional dissimilarity was mostly linked to moisture, temperature and N, P and C availabilities. The roles of environmental filtering and dispersal were, however, scale-dependent and varied between taxonomic and functional dissimilarities, with distance affecting taxonomic dissimilarity over short distances (<~300 km) and functional dissimilarity over long distances (>~600 km). The importance of different environmental predictors varied across scales more for functional than taxonomic dissimilarity. Our results demonstrate how biodiversity dimension (taxonomic versus functional) and spatial scale strongly influence the conclusions derived from bacterial biogeography studies.