Dominance of forest structural traits in shaping soil bacterial community assembly in Beijing's urban forests

Yi Zheng¹Conghai Han²Jixin Cao¹Yanchun Wang¹Huiwen Hu³Dongyan Yan¹Yushu Zhang¹Xixi Zhang¹Wei Dai⁴Zuzheng Li¹Xi Ding^1*

• ¹Beijing Academy of Forestry and Landscape Architecture, Beijing, China
• ²Beijing Municipal Bureau of Landscape and Forestry, Beijing, China
• ³Beijing Huiwen Middle School，Beijing, Beijing, China
• ⁴Miyun District Forestry and Parks Bureau, Beijing, China

Urban forests constitute vital ecological interfaces between built environments and natural systems, yet the mechanisms driving soil microbial community assembly in these ecosystems remain poorly understood. Through an integrated analysis of five dominant forest types (Populus tomentosa, Salix matsudana, Robinia pseudoacacia, Eucommia ulmoides, and Ailanthus altissima) in Beijing's plain ecological forests, we reveal hierarchical environmental controls over bacterial diversity and network structure. High-throughput sequencing and co-occurrence network analyses demonstrated that Salix matsudana forest harbored the highest microbial diversity (Shannon index = 5.82 ± 0.14), with Proteobacteria abundance significantly elevated compared to other forest types (P < 0.01). Structural equation modeling (SEM) identified soil total nitrogen (TN) as the principal direct suppressor of bacterial diversity (path coefficient = -0.33, P < 0.001), while forest structural traits—particularly diameter at breast height—emerged as critical mediators of community composition through nutrient modulation (R² = 0.502). Notably, microbial networks exhibited forest-type-specific topologies: Populus tomentosa forest stands showed exceptional connectivity (edge density = 0.29), whereas Robinia pseudoacacia forest developed modular architectures (modularity = 2.30) enhancing ecological resilience. These findings establish a mechanistic framework linking forest management practices to microbial-mediated ecosystem functions, with direct implications for urban green space optimization under accelerating anthropogenic pressures.