2026-10-14T12:05:40Z https://www.scidb.cn/oai

10.57760/sciencedb.iga.001gt 2026-09-18T15:16:15Z

2026-09-18 Article“Threats to the soil microbiome from nanomaterials: A global meta and machine-learning analysis”(new) doi:10.57760/sciencedb.iga.001gt en This thesis focuses on the soil microbial community as the research object. Through a global-scale Meta-analysis, it was found that exposure to nanomaterials significantly reduced soil microbial diversity (-0.96%), biomass (-14.01%), activity (-3.39%), and functionality (-14.44%). The negative effects of metal nanomaterials are stronger than those of carbon nanomaterials, with Ag nanomaterials being the most toxic. The particle size and content of nanomaterials are the main factors affecting their toxicity. Additionally, the random forest (RF) and XGBoost machine learning models constructed in this study can effectively predict the impact of nanomaterials on the soil microbial community. These findings provide scientific basis for the ecological risk assessment of nanomaterials and offer references for the rational application of nanomaterials in the soil environment. Nanomaterials; Soil microbial community; Meta-analysis; Random forest; XGBoost 陈森森 任文杰 PUBLIC https://creativecommons.org/licenses/by-nc/4.0/ dataset Science Data Bank