eDNA complements scientific trawling in surveys of marine fish biodiversity components.

Environmental DNA (eDNA) metabarcoding is a method to detect taxa from environmental samples. It is increasingly used for marine biodiversity surveys. As it only requires water collection, eDNA metabarcoding is less invasive than scientific trawling and might be more cost-effective. Here, we analysed data from both sampling methods applied in the same scientific survey targeting Northeast Atlantic fishes in the Bay of Biscay. We compared the methods in terms of spatial patterns of taxonomic, phylogenetic and functional diversity. We found that eDNA captured more taxonomic and phylogenetic richness than bottom trawling and more functional richness at the local scale. eDNA was less selective than trawling and detected species in local communities spanning larger phylogenetic and functional breadths, especially as it detected large pelagic species that escaped the trawl, even though trawling detected more flat fish. eDNA indicated differences in fish community composition that were comparable to those based on trawling. However, consistency between abundance estimates provided by eDNA metabarcoding and trawl catches was low, even after accounting for allometric scaling in eDNA production. We conclude that eDNA metabarcoding is an efficient method that can complement scientific trawling for multi-component biodiversity monitoring based on presence/absence. Here with provide the eDNA data set that support these findings.

环境DNA（environmental DNA，简称eDNA）代谢条形码技术是一种从环境样本中检测生物类群的方法，目前正日益广泛应用于海洋生物多样性调查。由于仅需采集水样，该技术相较于科学拖网采样具有更低的侵入性，且可能具备更高的成本效益。本研究针对比斯开湾东北大西洋海域的鱼类开展了同一项科学调查，对两种采样方法获取的数据进行了分析，并从分类多样性、系统发育多样性与功能多样性的空间分布模式维度对两种方法展开对比。研究结果显示，相较于底拖网采样，eDNA技术可检测到更多的分类多样性与系统发育多样性，且在局域尺度上可检测到更高的功能多样性；eDNA技术的选择性弱于拖网，其可检测到的局域群落类群覆盖了更广的系统发育与功能范围，尤其能够捕获到逃离拖网的大型远洋鱼类，尽管拖网可检测到更多的比目鱼类。eDNA技术所揭示的鱼类群落组成差异与拖网采样结果具有可比性，但即便考虑了eDNA产出的异速缩放效应，eDNA代谢条形码技术与拖网捕捞的丰度估算结果之间的一致性仍然较低。综上，我们认为eDNA代谢条形码技术是一种高效的方法，可作为科学拖网采样的补充手段，用于基于有无数据的多维度生物多样性监测。本研究随文提供支撑上述研究结果的eDNA数据集。