Conserving aquatic ecosystems requires efficient tools to accurately assess the biodiversity of aquatic species. However, existing knowledge is insufficient in terms of the reliability and the comparability of methods measuring fish diversity. Environmental DNA (eDNA), as a promising method, was used to detect fish taxa in this study. We optimized the eDNA method in the laboratory, and applied the optimal eDNA method to survey fish diversity in a natural aquatic life reserve. We simulated necessary steps of the eDNA method in the lab to increase the confidence of the field survey. Specifically, we compared different eDNA sampling, extraction, and sequencing strategies for accurately capturing fish species of the target area. We found that 1L water samples were sufficient for sampling eDNA information of the majority taxa. The filtration was more effective than the centrifugal precipitation for the eDNA extraction. The cloning sequencing was better than the high-throughput sequencing. The field survey showed that the Shannon–Wiener diversity index of fish taxa was the highest in Huairou Reservoir. The diversity index also showed seasonal changes. The accuracy rate of detecting fish taxa was positively correlated with the eDNA concentration. This study provides a scientific reference for an application of the eDNA method in terms of surveying and estimating the biodiversity of aquatic species.

Hulun Lake, a UNESCO Biosphere Reserve, faces mounting threats from extreme climate events and anthropogenic pressures, highlighting the need for robust biodiversity monitoring. Environmental DNA (eDNA) has emerged as a promising tool for aquatic biomonitoring, yet different bioinformatic pipelines—such as Amplicon Sequence Variant (ASV) and Operational Taxonomic Unit (OTU) clustering—may yield divergent results. This study compares ASV and OTU clustering approaches in eDNA metabarcoding alongside traditional capture-based surveys to assess fish diversity in Hulun Lake. Across all methods, we identified 43 taxa (40 species), including the critically endangered Acheilognathus hypselonotus and vulnerable Choi’s spiny loach (Cobitis choii). While eDNA methods detected 2~3 times more species than in nets (13 species), strong methodological correlations (p < 0.001) were observed between net frequencies and eDNA-derived relative abundances (based on both ASV and OTU datasets using 4th-root and log transformations). Clustering analysis of capture-based data revealed four distinct ecological zones: the areas near tourist facilities, Wuerxun River inflow region, Wulan Nuoer Lake (connected via the Wuerxun River), and the Lake Centre. Significant spatial variation (p < 0.05) between these four zones was found in eDNA datasets, whereas nets captured more heterogeneous patterns, consistent with previous studies. Community structures were shaped by both generalists (e.g., Cyprinus carpio, Hemiculter bleekeri) and habitat specialists such as Amur catfish (Silurus asotus). The Lake Centre hosted a unique assemblage, likely due to reduced human disturbance. Overall, both eDNA clustering methods outperformed capture-based survey in detecting species richness and offered semi-quantitative insights. However, discrepancies between ASV and OTU approaches were evident in resolving fine-scale community differences. We recommend an integrated monitoring strategy that combines the sensitivity of eDNA with the abundance resolution of net captured to inform spatially targeted conservation and habitat protection in this vulnerable ecosystem.