Using eDNA Metabarcoding for the Analysis of Fish Communities in Rivers

Abstract

The present study aims to assess the effectiveness of eDNA metabarcoding for the analysis of fish communities in rivers. The findings suggest that the methodology attained an accuracy rate of 80% for species identification and was able to detect between 79.2% and 87.5% of the fish species recorded in the fish monitoring database for three rivers of Anseong, Bokha and Gyeongan during the period 2019 to 2021. Significantly, the eDNA metabarcoding technique enabled the successful detection of comparatively larger fish species, such as Channa argus and Silurus asotus. Furthermore, depending on the river, this method identified 12 to 14 additional species that could not be observed through traditional methodologies. However, it is worth noting that the Mifish primer used amplifies short gene segments, which can pose challenges in identifying species with identical gene sequences. Notwithstanding this limitation, the advantages of eDNA analysis over conventional methods are significant, enabling the identification of a broader range of species within a shorter timeframe, using smaller sample volumes and minimizing risks to both endangered fish and to researchers. As a result, eDNA analysis represents a valuable alternative for assessing biodiversity and for collecting data on fish species that are challenging to analyze.