Unveiling the Role of Wetland Strategies in Antibiotic Risk Reduction across China by Machine Learning.

ABSTRACT: Pervasive antibiotic pollution in water environments has emerged as a serious threat to global ecosystem functions and public health. While wetland expansion─including protection, restoration, and construction, is widely promoted for sustainable water quality improvement, its effectiveness in mitigating antibiotic pollution remains poorly understood. Here, we develop a machine learning model based on a compiled data set of 337 experimental observations to quantify antibiotic removal and map risk distribution in wetlands across 2,833 counties/districts in mainland China. Between 2010 and 2020, the wetland area across China expanded by 34.7%, yet antibiotic removal improved by only 0.1%, failing to meaningfully reduce the risk. We find that antibiotic removal in wetlands is primarily constra

SUBMITTER: Chen L 

PROVIDER: S-EPMC12329719 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature