Evidence map›Paper›PMID 40750987›Full record

ArticleScientific reports2025

Harnessing eDNA technology to identify fish diversity and distribution in the Kashi River, a tributary of the Ili River, Xinjiang, China.

Jiangong Niu, Hui Jia, Tao Zhang, Jiangwei Hu, Liuyi Huang, Hui Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jiangong Niu *College of Fisheries, Ocean University of China, Qingdao, 266003, China.
Hui Jia *CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China.
Tao ZhangXinjiang Fisheries Research Institute, Urumqi, 830000, China.
Jiangwei HuXinjiang Fisheries Research Institute, Urumqi, 830000, China.
Liuyi HuangCollege of Fisheries, Ocean University of China, Qingdao, 266003, China. huangly@ouc.edu.cn.
Hui ZhangCAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China. zhanghui@qdio.ac.cn.

Funding

Key Research and Development Project of Xinjiang 2022B02006-2
6 · The paper itself

Abstract

Monitoring species diversity and distribution patterns in remote ecosystems presents significant challenges due to vast geographic coverage, harsh environmental conditions, and the limited availability of traditional survey resources. Environmental DNA (eDNA) technology has been proven to be an effective method for biodiversity assessment, offering a non-invasive, cost-effective, and efficient solution. The study used eDNA metabarcoding technology to investigate fish communities in the Kashi River, a vital waterway in Xinjiang. Two-season of 37 eDNA water samples were taken from multiple sites, and 77 species were detected in April and 137 in September. Additionally, the results of spatial analysis showed that there were significant differences in fish composition among the different areas. These findings provided valuable insights into the ecological dynamics of the Kashi River of the Ili River, contributing to fish biodiversity conservation in freshwater ecosystem regions like the Xinjiang Uygur Autonomous Region. Furthermore, the study underscored the potential of eDNA for long-term monitoring of freshwater ecosystems, informing conservation efforts, and managing fish resources in the Kashi River of the Ili River and similar freshwater ecosystems.

Indexed as

BiodiversityDNA, EnvironmentalFishesRiversAnimalsChinaDNA Barcoding, TaxonomicEcosystemEnvironmental MonitoringDNA, EnvironmentaleDNAFish diversityFreshwater ecosystemMonitoringThe Kashi River

Identifiers

PMID40750987
PMCPMC12317054

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.