Biotic and abiotic factors predict the biogeography of soil microbes in the Serengeti

Field-based observational research is the first step in understanding the factors that predict the biogeography and community structure of soil microbes. The Serengeti National Park in Tanzania is an ideal location for this type of research because active volcanoes generate strong environmental gradients due to ash deposition and a rain shadow. Also, as one of the last remaining naturally grazed ecosystems on Earth, the Serengeti provides insights about the influence of herbivory on microbial communities. We used 16S rRNA amplicons to characterize bacterial and archaeal communities in soils from a 13-year herbivore removal experiment to study the influence of environmental factors and grazing on the natural distribution of soil microbes. We collected soil samples from seven sites, each with three naturally grazed plots and three plots that were fenced to prevent grazing by large mammalian herbivores. Soil fertility (phosphorus, nitrogen, iron, calcium, organic matter), texture, and pH were measured at each plot. Beta diversity of bacterial and archaeal communities was most strongly correlated with soil texture (R2 = 32.4%). The abundance of many operational taxonomic units (OTUs) were correlated with soil texture, and the evenness of taxa within samples increased with fine-textured soil. Removal of grazing shifted community structure, with 31 OTUs that were significant indicator taxa of the ungrazed treatment and three OTUs that were significant indicators of the grazed treatment. ImportanceOur results show that in this regional scale study, soil texture was the best environmental predictor, and grazing by large mammals also structures bacterial and archaeal communities. When large mammals are removed, as humans have been doing for millenia, there are cascading effects into the microbial world that can influence ecosystem functions like carbon and nitrogen cycles. These empirical findings from a natural tropical savannah can help inform models of the global distribution and function of soil microbes.