基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警

外来生物入侵是继生境破坏后造成生物多样性丧失的第二大威胁因素, 已对入侵地的生态安全、经济和社会发展及人类健康等造成严重负面影响, 成为21世纪五大全球性环境问题之一。作为水产养殖、航运和水生宠物交易大国, 我国水生生态系统的生物入侵问题尤为严重。研究表明, 系统地构建并应用早期监测预警技术是防控水生生态系统生物入侵最有效的途径。和陆生生物相比, 水生生物群落的物种繁多、群落结构复杂、生物形体微小且在入侵初期群体规模极小、隐匿于水下、可用于物种鉴定的外部形态缺乏, 使得在水生生态系统中构建并应用早期监测和预警体系在技术层面更具挑战。随着高通量测序技术的快速发展, 环境DNA-宏条形码技术成为构建水生生态系统入侵生物早期监测与预警技术的首选。本文主要综述了基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警技术方法; 解析了环境DNA-宏条形码监测系统的应用现状、技术优势; 着重探讨了影响监测结果准确性的I型和II型错误及其产生原因, 并为避免两类错误提供了可行的优化/改进方案; 最后对该方法在水生入侵生物监测中的应用前景进行了展望。

Environmental DNA (eDNA)-metabarcoding-based early monitoring and warning for invasive species in aquatic ecosystems

Biological invasion is a major threat to multiple ecosystems across the globe, causing severe damages to ecological integrity, loss of biodiversity, economic and social development and even human health. With the rapid development in aquaculture, shipping and aquarium and ornamental trades in the past several decades, China has become one of the countries most influenced by invasive species. Studies have clearly shown that the development and application of robust early monitoring and warning is one of the most effective ways to prevent and possibly control invasive species in aquatic ecosystems. Compared to terrestrial ecosystems, there remain several technical difficulties for developing early monitoring and warning in aquatic habitats. The technical challenges are mainly due to several features of aquatic biological communities such as high biodiversity and complex structure, a large number of microscopic species, extremely low population density and lack of available taxonomic keys for species identification. With the rapid development of high-throughput sequencing techniques, environmental DNA (eDNA)-metabarcoding has become the top priority method for developing the early monitoring and warning programs in aquatic ecosystems. In this review, we aim to synthesize the research progress on eDNA-metabarcoding and its application to early monitoring and warning of invasive species in aquatic ecosystems. In addition, we briefly discuss the technological advantages of eDNA-metabarcoding for the early monitoring and warning programs. Finally, we propose research perspectives for solutions to technical issues for false positive and false negative errors in the eDNA-metabarcoding process.