With the intensification of industrial activities, soil ecosystems are increasingly threatened by co-contamination with heavy metals and polycyclic aromatic hydrocarbons (PAHs). Previous studies have predominantly focused on individual pollutants, with limited research into the interactions under combined pollution. Therefore, this study employed high-throughput sequencing and multifunctionality assessments to investigate soils from a coking plant in North China and surrounding areas with diverse land-use types. The results demonstrate that bacterial communities are predominantly comprised of Actinobacteria and Proteobacteria, whereas fungal communities are primarily composed of Ascomycota and Basidiomycota. Microbial diversity was highest in forest and farmland and lowest in abandoned land. Microbial community assembly revealed that fungal communities were predominantly influenced by random processes, whereas bacterial communities in coking plants, farmlands, and abandoned lands were primarily assembled through deterministic processes. Fungal richness positively correlated with CNP multifunctionality (R² = 0.249, P < 0.01), whereas fungal diversity negatively correlated with PAHs multifunctionality (R² = 0.141, P < 0.05). Structural equation modelling indicated that microbial carbon content exerted a significant positive effect on microbial diversity (P < 0.05). Fungal community diversity ultimately enhanced ecosystem multifunctionality (EMF) by promoting fungal network interactions. These findings provide theoretical support for the ecological remediation of complex contaminated soils.
山东省济南市章丘区文博路2号
齐鲁师范学院 genelibs生信实验室
山东省济南市高新区舜华路750号
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