Environmental DNA (eDNA) technology, as an alternative to traditional gillnet surveys, has attracted widespread attention. However, comparisons between eDNA and traditional methods regarding biodiversity and community structure have not yet been fully elucidated. This study compared the ability of eDNA and gillnets for fish monitoring in a large deep reservoir (Qiandao Lake) in East China. The results showed that eDNA exhibited higher taxonomic resolution and detection rates, and significantly larger species diversity and richness indices compared with traditional gillnetting methods. Using abundance and biomass datasets from gillnets revealed significant differences in fish community composition between gillnetting and eDNA survey methods. Gillnet abundance was dominated by small-sized fish species, while gillnet biomass was dominated by larger-sized ones, and the prevailing species detected in eDNA reads included the dominant species from gillnet abundance and biomass, as well as a medium-sized invasive alien fish (Lepomis macrochirus). Non-metric multidimensional scaling (NMDS) showed that the spatial distribution in abundance of fish species sampled by gillnetting was more dispersed than that using eDNA. The explanatory power with the gillnet abundance and biomass together as predictor variables of the eDNA reads increased moderately compared with taking them separately, and the fitting degree of quadratic functions was also improved somewhat compared to linear equations when using biomass to predict eDNA reads. Furthermore, the key environmental factors affecting fish communities differed between the two methods. Current research indicates that eDNA has advantages over gillnets in detecting fish species diversity, and it is recommended to combine it with traditional sampling methods. Under natural aquatic ecosystem conditions, the eDNA reads may comprehensively reflect the biomass and abundance information obtained through gillnetting, but their relationship is complex and requires further research. This study will provide guidance for biodiversity monitoring.
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