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Understanding the interactions of soil microbial species and how they responded to disturbances are essential to ecological restoration and resilience in the semihumid and semiarid damaged mining areas. Information on this, however, remains unobvious and deficiently comprehended. In this study, based on the high throughput sequence and molecular ecology network analysis, we have investigated the bacterial distribution in disturbed mining areas across three provinces in China, and constructed molecular ecological networks to reveal the interactions of soil bacterial communities in diverse locations. Bacterial community diversity and composition were classified measurably between semihumid and semiarid damaged mining sites. Additionally, we distinguished key microbial populations across these mining areas, which belonged to Proteobacteria, Acidobacteria, Actinobacteria , and Chloroflexi . Moreover, the network modules were significantly associated with some environmental factors (e.g., annual average temperature, electrical conductivity value, and available phosphorus value). The study showed that network interactions were completely different across the different mining areas. The keystone species in different mining areas suggested that selected microbial communities, through natural successional processes, were able to resist the corresponding environment. Moreover, the results of trait-based module significances showed that several environmental factors were significantly correlated with some keystone species, such as OTU_8126 ( Acidobacteria ), OTU_8175 ( Burkholderiales ), and OTU_129 ( Chloroflexi ). Our study also implied that the complex network of microbial interaction might drive the stand resilience of soil bacteria in the semihumid and semiarid disturbed mining areas.

Molecular Ecological Network Complexity Drives Stand Resilience of Soil Bacteria to Mining Disturbances among Typical Damaged Ecosystems in China