College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, China.
CSIC, Global Ecology Unit CREAF- CSIC-UAB, Bellaterra, Barcelona 08193, Catalonia, Spain; CREAF, Campus Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona 08193, Catalonia, Spain.
Sci Total Environ. 2023 May 1;871:162070. doi: 10.1016/j.scitotenv.2023.162070. Epub 2023 Feb 9.
River microbiotas contribute to critical geochemical processes and ecological functions of rivers but are sensitive to variations of environmental drivers. Understanding the geographic pattern of river microbial traits in biogeochemical processes can provide important insights into river health. Many studies have characterized river microbial traits in specific situations, but the geographic patterns of these traits and environmental drivers at a large scale are unknown. We reanalyzed 4505 raw 16S rRNA sequences samples for microbiota from river basins in China. The results indicated differences in the diversity, composition, and structure of microbiotas across diverse river basins. Microbial diversity and functional potential in the river basins decreased over time in northern China and increased in southern China due to niche differentiation, e.g., the Yangtze River basin was the healthiest ecosystem. River microbiotas were mainly involved in the cycling of carbon and nitrogen in the river ecosystems and participated in potential organic metabolic functions. Anthropogenic pollutants discharge was the most critical environmental driver for the microbial traits, e.g., antibiotic discharge, followed by climate change. The prediction by machine-learning models indicated that the continuous discharge of antibiotics and climate change led to high ecological risks for the rivers. Our study provides guidelines for improving the health of river ecosystems and for the formulation of strategies to restore the rivers.
河流微生物组对河流的关键地球化学过程和生态功能有贡献，但对环境驱动因素的变化很敏感。了解生物地球化学过程中河流微生物特征的地理格局，可以为河流健康提供重要的见解。许多研究都在特定情况下对河流微生物特征进行了描述，但这些特征的地理格局以及大尺度上的环境驱动因素尚不清楚。我们重新分析了来自中国河流流域的 4505 个 16S rRNA 序列样本的微生物组数据。结果表明，不同河流流域的微生物多样性、组成和结构存在差异。由于生态位分化，中国北方的河流流域的微生物多样性和功能潜力随时间推移而下降，而中国南方则有所增加，例如长江流域是最健康的生态系统。河流微生物组主要参与了河流生态系统中碳和氮的循环，并参与了潜在的有机代谢功能。人为污染物的排放是影响微生物特征的最关键的环境驱动因素，例如抗生素的排放，其次是气候变化。机器学习模型的预测表明，抗生素的持续排放和气候变化给河流带来了很高的生态风险。我们的研究为改善河流生态系统的健康以及制定河流恢复策略提供了指导。
