The vertical distribution and control factor of microbial biomass and bacterial community at macroecological scales

Abstract

Microorganisms exist throughout the soil profile and those microorganisms living in deeper soil horizons likely play key roles in regulating biogeochemical processes. However, the vertical differentiations of microbes along soil depth and their global biogeographical patterns remain poorly understood. Herein, we conducted a global meta-analysis to clarify the vertical changes of microbial biomass, diversity, and microbial relative abundance across the soil profiles. Data was collected from 43 peer-reviewed articles of 110 soil profiles (467 observations in total) from around the world. We found soil microbial biomass and bacterial diversity decreased with depth in soils. Among examined edaphic factors, the depth variation in soil pH exhibited significant negative associations with the depth change in microbial biomass and bacterial Shannon index, while soil total organic carbon (TOC) and total nitrogen (TN) exhibited significant positive associations. For the major bacteria phyla, the relative abundances of Proteobacteria and Bacteroidetes decreased with soil depth, while Chloroflexi, Gemmatimonadetes, and Nitrospirae increased. We found both parallels and differences in the biogeographical patterns of microbial attribute of topsoil vs. subsoil. Microbial biomass was significantly controlled by the soil nutrient concentrations in both topsoil and subsoil compared with climatic factors, while bacterial Shannon index was significantly controlled by the edaphic factors and across latitudes or climatic factors. Moreover, mean annual precipitation can also be used as a predictor of microbial biomass in subsoil which is different from topsoil. Collectively, our results provide a novel integrative view of how microbial biomass and bacterial community response to soil depth change and clarify the controlling factors of the global distribution patterns of microbial biomass and diversity, which are critical to enhance ecosystem simulation models and for formulating sustainable ecosystem management and conservation policies.