拖网捕鱼
生物多样性
河口
湿地
渔业
生态系统
环境DNA
航程(航空)
生态学
地理
垂钓
生物
复合材料
材料科学
作者
Keshu Zou,Jianwei Chen,Huiting Ruan,Zhenhai Li,Wenjie Guo,Min Li,Li Liu
标识
DOI:10.1016/j.scitotenv.2019.134704
摘要
The difficulty of censusing fish diversity hampers effective management and conservation in estuarine and coastal ecosystems, especially wetland ecosystems. Improved noninvasive fish diversity monitoring programs are becoming increasingly crucial for coastal ecosystems. In this study, we investigated fish diversity and its seasonal variation in the Nansha wetland ecosystem using environmental DNA (eDNA) metabarcoding and bottom trawling, and the two approaches were compared. With the combination of the two methods, the identified fish taxa included 78 species within 60 genera and 33 families, and five nontarget taxa were only identified by eDNA metabarcoding. Compared to the two surveys, eDNA metabarcoding identified a significantly greater number of fish species per site and per season than bottom trawling (p < 0.05), with eDNA metabarcoding identifying 32.05% more fish species than bottom trawling. The overwhelming majority of the fish orders captured in the Nansha coastal wetland by bottom trawling were recovered from eDNA analysis, although certain taxa were not sampled due to limitations. Furthermore, the Whittaker index and relative abundance analysis of the two methods showed distinct differences between the sampling seasons, suggesting seasonal variations and reflecting the current or recent existence of fish species in the coastal ecosystem. Thus, our work provides more detailed seasonal data on biodiversity in the Nansha wetland of the Pearl River Estuary, which is essential for the long-term management and conservation of coastal biodiversity. Our study also adds to the evidence that the eDNA metabarcoding approach can be used in coastal environments to monitor a broad range of taxa and reflect seasonal fluctuations in fish diversity. As an emerging and transformative method, eDNA metabarcoding shows great potential for fish diversity monitoring in coastal wetland ecosystems.
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