Variations of soil microbial communities accompanied by different vegetation restoration in an open-cut iron mining area.

Overexploitation of iron mining in China has caused serious environmental pollution. Therefore, establishing a stable ecological restoration with vegetation in mining areas has gradually aroused people's awareness and obtained extensive concerns. This study aimed to evaluate vegetation restoration with Robinia pseudoacacia (RP), Acer mono (AM) and Pinus koraiensis (PK) in iron mining compared with unrestored area, to investigate the soil environment factors and microbial communities, and to better understand the correlations between soil environment factors and soil microbial communities. Vegetation restoration could reduce soil pH and alleviate soil alkaline, and remarkably increase soil nutrients, especially in RP site. Analysis of 16S rRNA and ITS rRNA gene sequences provided a total of 645,004 and 906, 276 valid sequences clustered into 7091 OTUs and 1689 OTUs at a 0.03 genetic distance for bacteria and fungi, respectively. The predominant bacterial and fungal phyla were Actinobacteria and Ascomycota in studied sites, respectively. Additionally, revegetation significantly increased the relative abundances of Proteobacteria, Gemmatimonadetes, Bacteroidetes and Patescibacteria, and decreased the relative abundance of Actinobacteria. Robinia pseudoacacia harbored the highest soil fungal community diversity, and bacterial Simpson index and Shannon index. Vegetation restoration with RP could clearly shifted soil communities compared to AM and PK. Along with the restoration of vegetation, the remarkable abiotic changes were the accumulation of total C, total N, total P, available P, available N and available K and the decreasing of soil pH, which were the most important factors affecting soil microbial communities. Our results addressed that Robinia pseudoacacia was the best preferable species than AM and PK in improving soil nutrients, soil community diversity and structure in Fe mining, providing a helpful guideline for selection of tree species.