Abstract

Soil microbial spatial variation across forest types would obscure the huge impact of tree species on microbial community structure and function, and the underlying mechanisms of spatial pattern in the same tree forests was poorly described. We investigated the spatial variation and drivers of microbial communities in the topsoil (0–20 cm) of Robinia pseudoacacia forests at the regional scale on the Loess Plateau. Soil bacterial and fungal communities showed a significant distance decay pattern, and fungi exhibited a more apparent spatial pattern than bacteria. Microbial diversity (Shannon-Wiener and Chao1 indexes) and the relative abundance of Actinobacteria, Gemmatimonadetes, Nitrospirae, Latescibacteria, Verrucomicrobia, Rozellomycota significantly differed among regions. Community dissimilarities of bacterial and fungal indicator species were sensitive to changes in mean annual temperature (MAT) and mean annual precipitation (MAP), respectively. However, the first axis of nonmetric multidimensional scaling (nMDS1) of soil bacterial and fungal communities were respectively associated with soil pH and MAP. The proportion of positive links of co-occurrence networks between microorganisms increased with the decrease in MAP, suggesting that the decrease in precipitation increases species coexistence. Soil bacterial and fungal community assemblies were both dominated by stochastic processes and were well predicted by the neutral community model. The effects of soil properties were larger on bacteria than fungi, and soil properties respectively explained 54.54% and 37.29% of the total variation in the bacterial and fungal community compositions. The major drivers of community dissimilarity varied between bacteria and fungi, indicating that bacterial community was mainly drove by soil pH, NH4+ and geographic distance and fungal community was mainly drove by MAP, pH and geographic distance. Our observations suggested that soil bacterial and fungal communities exhibited distance decay pattern in the Robinia pseudoacacia forests at the regional scale, and this pattern was primarily driven by soil pH and MAP.

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