Moderate Grazing Drives Contrasting Microbial Network Reorganization and Functional Shifts in Desert and Meadow Steppes of Inner Mongolia

In this study, we employed second-generation amplicon sequencing to analyze the microbial diversity in soils from meadow steppe and desert steppe under grazing and control conditions. Soil samples were collected from a depth of 0-30 cm in September 2021 and were subjected to microbial diversity analysis using 16S rRNA gene sequencing. The microbial diversity, including α-diversity and β-diversity, was calculated to understand the complexity and variation within and between the microbial communities. Differences in microbial communities between treatments were assessed using ANOVA and PERMANOVA methods. Functional predictions of the microbial communities were performed using the PICRUSt2 tool, which allowed us to infer potential microbial functions based on 16S rRNA gene sequences. Functional indices, including carbon cycling functions, were computed to evaluate the ecological roles of the microbial communities. Network analysis was conducted to investigate the interactions within the microbial communities. This analysis revealed the topological properties of bacterial and fungal networks, such as connectivity and centrality. Grazing treatments were found to increase the complexity and centrality of fungal networks while decreasing the connectivity and centralization of bacterial networks. Module network analysis further explored the modular structures within the microbial networks, identifying key functional modules and their responses to grazing. The findings highlight the distinct microbial community responses to grazing in meadow steppe and desert steppe ecosystems, emphasizing the need for tailored grazing management strategies to promote sustainable ecosystem functioning.本研究采用第二代扩增子测序技术，分析了放牧与对照条件下草甸草原与荒漠草原土壤中的微生物多样性。研究于2021年9月采集0~30 cm土层的土壤样品，采用16S核糖体RNA基因（16S rRNA gene）测序技术开展微生物多样性分析。研究计算了包括α多样性（α-diversity）与β多样性（β-diversity）在内的微生物多样性指标，以解析微生物群落内部及群落间的复杂性与变异特征。采用方差分析（ANOVA）与置换多元方差分析（PERMANOVA）方法评估不同处理组间的微生物群落差异。本研究借助PICRUSt2工具开展微生物群落功能预测，基于16S rRNA基因序列推断微生物潜在功能。计算包括碳循环功能在内的功能指标，以评估微生物群落的生态功能角色。 本研究开展了微生物群落网络分析，以解析群落内部的相互作用关系。该分析揭示了细菌与真菌群落网络的拓扑特征，包括连通性（connectivity）与中心性（centrality）等指标。研究发现，放牧处理可提升真菌群落网络的复杂性与中心性，同时降低细菌群落网络的连通性与中心化程度。模块网络分析进一步解析了微生物群落网络的模块化结构，明确了关键功能模块及其对放牧处理的响应模式。本研究结果凸显了草甸草原与荒漠草原生态系统中微生物群落对放牧的差异化响应，强调需制定针对性的放牧管理策略，以推动生态系统功能的可持续性。