Optimizing eDNA Detection in Fish Communities in Impounded Lakes: An Integrated Identification Approach

To evaluate the ecological impact of fish migrations resulting from interbasin water transfer projects, it is essential to optimize the environmental DNA (eDNA) detection protocols for freshwater systems and increase the accuracy of species identification. In this study, the impounded lakes along the Eastern Route of China’s South-to-North Water Diversion Project (SNWDP-ER) were investigated. The efficacy of fish species detection in these lakes was explored using an integrated identification approach and three common freshwater fish primers. Furthermore, the identification efficiency of different primers and the variations in fish community composition among the regulating lakes were analyzed. Following screening via the integrated annotation method, increases in species-level identifications were observed for all the primers. Notably, the MetaFish1 primer demonstrated superior performance, detecting the greatest number of taxa and yielding a greater proportion of species-level identifications. Significant disparities in fish trophic composition were observed between the southern and northern lakes. Additionally, a relatively high prevalence of non-native species was detected in lakes with relatively high connectivity to the main water transfer channels. The methodologies employed in this study provide a valuable reference for future eDNA-based monitoring in freshwater ecosystems, as well as for the baseline distribution assessment and management of biological invasions.

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Publication Details

Journal
ACS ES&T Water
Published
2026-06-26
DOI
https://doi.org/10.1021/acsestwater.6c00425
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing eDNA Detection in Fish Communities in Impounded Lakes: An Integrated Identification Approach

Zhe Xiao, Jingtian Zhang, Shouliang Huo, Nanyan Weng et al.
ACS ES&T Water
Environmental DNA in Biodiversity Studies
article

Optimizing eDNA Detection in Fish Communities in Impounded Lakes: An Integrated Identification Approach

Zhe Xiao, Jingtian Zhang, Shouliang Huo, Nanyan Weng, Hanxiao Zhang, Zhanyao Shi
article en

Abstract

To evaluate the ecological impact of fish migrations resulting from interbasin water transfer projects, it is essential to optimize the environmental DNA (eDNA) detection protocols for freshwater systems and increase the accuracy of species identification. In this study, the impounded lakes along the Eastern Route of China’s South-to-North Water Diversion Project (SNWDP-ER) were investigated. The efficacy of fish species detection in these lakes was explored using an integrated identification approach and three common freshwater fish primers. Furthermore, the identification efficiency of different primers and the variations in fish community composition among the regulating lakes were analyzed. Following screening via the integrated annotation method, increases in species-level identifications were observed for all the primers. Notably, the MetaFish1 primer demonstrated superior performance, detecting the greatest number of taxa and yielding a greater proportion of species-level identifications. Significant disparities in fish trophic composition were observed between the southern and northern lakes. Additionally, a relatively high prevalence of non-native species was detected in lakes with relatively high connectivity to the main water transfer channels. The methodologies employed in this study provide a valuable reference for future eDNA-based monitoring in freshwater ecosystems, as well as for the baseline distribution assessment and management of biological invasions.

ACS ES&T Water
Beijing Normal University (CN), Chinese Research Academy of Environmental Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 7%
Environmental DNA in Biodiversity Studies
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Optimizing eDNA Detection in Fish Communities in Impounded Lakes: An Integrated Identification Approach — Zhe Xiao, Jingtian Zhang, et al. · ACS ES&T Water (2026) | TGRS Research Map | TGRS