Unraveling Fish Community Diversity and Structure in the Yellow Sea: Evidence from Environmental DNA Metabarcoding and Bottom Trawling.

Abstract

The use of environmental DNA (eDNA) metabarcoding to analyze fish species diversity across different aquatic ecosystems is well documented. Nonetheless, there is a gap in validating eDNA metabarcoding studies on the diversity and structure of fish communities in coastal ecosystems, particularly in comparing these findings with bottom trawl catch data. In this study, we employed eDNA metabarcoding to explore species composition and relative abundance in fish communities, taxonomic-level diversity variations, and the interplay between community structures and environmental factors in the Yellow Sea and compared these results with those obtained from bottom trawl catches. In addition, we compared the various methods used to estimate the distributions of taxonomic, phylogenetic, and functional diversity factors. We found that eDNA metabarcoding detected a greater number of species (86 vs. 41), genera (73 vs. 37), and families (42 vs. 25) than bottom trawl results at each sampling station. eDNA metabarcoding provided higher Shannon, Simpson, and Chao1 alpha diversity indices than the bottom trawl results. The PCoA results showed that eDNA metabarcoding samples could be more clearly separated at the sampling sites in the Zhuanghe (ZH) and Lianyungang (LYG) areas than bottom trawling samples. The RDA analysis indicated that temperature, along with NO3- and NH₄⁺ concentrations, were pivotal in shaping the geographical patterns of fish communities, as identified through eDNA metabarcoding, echoing findings from bottom trawling studies. Furthermore, our findings suggest that eDNA barcoding surpasses bottom trawling in detecting taxonomic and phylogenetic diversity, as well as in uncovering greater functional diversity at the local level. Conclusively, eDNA metabarcoding emerges as a valuable complement to bottom trawling, offering a multifaceted approach to biodiversity monitoring that not only boosts efficiency but also reduces environmental impact on coastal ecosystems.