随着人类活动对全球氮循环的改变，氨氮污染已经对天然水生生态系统产生严重危害，氨氮的生态效应也备受关注。基于野外的群落调查表明氨氮对水生生态群落的影响明显被低估，这是因为以往对氨氮生态效应的研究主要基于实验室生物毒性测试，而忽略了物种间相互作用的影响，难以准确评估氨氮污染产生的实际生态效应。本项目拟通过野外微宇宙实验，利用新型环境DNA宏条形码技术，研究氨氮对微宇宙各生态类群的直接毒性和间接作用，解析氨氮污染的群落效应及其机制。首先，应用eDNA宏条形码技术全面系统地研究氨氮对微宇宙各生态类群的直接影响；其次，基于eDNA和机器学习构建微宇宙生态网络，研究氨氮对生态网络中各生态类群的间接作用；最后，综合氨氮的直接影响和间接作用，解析氨氮群落效应的干扰机制。本研究也为利用eDNA宏条形码技术研究其他污染物的生态效应提供有益的借鉴和方法学参照。

With the increasing impacts of human activities on the global nitrogen cycle, the adverse ecological effects of ammonia pollution on aquatic ecosystem has been attracted more attentions from public and scientists. However, previous studies paid more attention to the direct toxic of ammonia on individual and sub individual level, ignoring the bio-interactions. In this study, a new genetic tool (eDNA metabarcoding) was created to explore the ecological effect and interference mechanism of ammonia on field microcosm experiments. Both direct and indirect effects of ammonia on various ecological groups were analyzed by eDNA metabarcoding. The ecological networks of microcosm were constructed by eDNA and machine learning approach. Explore the interference mechanism of ammonia`s ecological effect via integrating ecological networks and direct effect of ammonia. This study also provides novelty insights and a useful methodology for the ecological effects of other pollutants via the eDNA metabarcoding technology.