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Comparison between eDNA and Traditional Morphological Methods for Fish Diversity Monitoring in Rivers
Open accessPreprint — published as 10.1038/s41598-025-32964-1 · Paper page
Abstract
Environmental DNA (eDNA) technology has emerged as an emerging tool for monitoring organisms, including fish, in the natural environment. However, the effectiveness of eDNA in fish monitoring has not been fully validated compared to traditional direct monitoring methods by capturing fish and identifying them morphologically. Fish monitoring plays a crucial role in assessing the health of aquatic ecosystems, conserving biodiversity, and developing science-based fisheries management policies. However, eDNA technology faces many challenges in practical application due to the complexity of fish habitats, the dynamics of population distribution, and the degradation rate of eDNA in the aquatic environment. In this study, samples were collected from six major rivers typical of Liaoning Province at 14 sampling sites, and fish species composition and spatial diversity were analyzed using four primers (12S, COI, MiFish, and MiFish high variant) in conjunction with high-throughput sequencing technology. The results showed that eDNA technology detected a total of 211 fish species belonging to 17 orders, 71 families and 146 genera, which was much more than the traditional methods in terms of detection coverage; however, it was insufficient in the identification of some key species and could not provide ecological and biological information about individual body size and population structure. Traditional ecological methods are often cumbersome and time-consuming, however, given that the completeness of the eDNA database has not yet reached the desired level, nine fish species were identified by traditional ecological methods in the study that were not detected by eDNA technology. This fully demonstrates its still irreplaceable value in ecological assessment. In addition, the effectiveness of eDNA detection is affected by factors such as primer selection, environmental DNA stability and incomplete reference databases, especially in some specific taxa. At this stage, traditional ecological methods cannot be completely replaced by eDNA technology, which is complementary to traditional methods, and it is suggested that the two should be used together in ecological monitoring to enhance the accuracy and comprehensiveness of biodiversity monitoring.
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Metadata
- Authors
- Yu, Y., Shao, M., Zhou, H., Su, F., Guan, P., Ding, L., Ma, T., Zhou, B., Xu, S., Song, S., & Qu, B.
- Affiliations
- Shenyang Agricultural University (CN)
- Shenyang Agricultural University
- Liaoning water conservancy and hydropower research institute co.，ltd
- Corresponding author
- Song, Shuang
- Qu, Bo
- Venue
- Scientific Reports
- Published
- 2025-08-06
- Volume
- 16
- Issue
- 1
- Pages
- 3098-3098
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC12830926
- OpenAlex
- W7124741398
- Cited by
- 3
- References
- 49
- Citations by year
- 2026: 3
- FWCI
- 10.45
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Scientific Reports (publishedVersion, cc-by-nc-nd)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Key Research and Development Program of China
- Topics
- Physical Sciences › Environmental Science › Ecology › Environmental DNA in Biodiversity Studies
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Invertebrate Taxonomy and Ecology
- Keywords
- environmental DNA, fish diversity, primer comparison, 12S rRNA, COI, MiFish, species richness, species composition, taxonomic resolution
- MeSH terms
- DNA, Environmental, Extrachromosomal DNA, Animals, China, Environmental Monitoring, Fishes, Ecosystem, Biodiversity, Rivers, High-Throughput Nucleotide Sequencing
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