River Connectivity in Dammed Areas Studied Through Environmental DNA Metabarcoding at Community and Species Levels

ABSTRACT The field of environmental DNA (eDNA) is rapidly expanding with established applications in biodiversity monitoring, rare species detection and ecological assessment. However, its potential to evaluate species connectivity in fragmented aquatic systems remains underexplored. This study addresses this gap by applying eDNA metabarcoding to assess community connectivity in a dam‐fragmented river network, combining a multispecies framework with haplotype‐level analyses to investigate both community composition and within‐species variability. Community changes associated with reservoirs included biodiversity losses in the dammed area and have been found, as well as dams acting as barriers to the upstream advance of the invasive acute bladder snail Physella acuta . Haplotype analysis of the fish Phoxinus bigerri and Salmo trutta , the red alga Sheathia arcuata and the amoeba Koretnevella stella showed different levels of connectivity according to species biology, with genetic barriers associated with dams for the three species and diversity losses in the dammed area for the native S. trutta . Despite methodological limitations such as the non‐met premise of one haplotype one individual, the results suggest that metabarcoding on eDNA extracted from water samples can provide valuable insights into genetic diversity and connectivity across multiple taxa, offering new opportunities in conservation biology.

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Publication Details

Journal
Aquatic Conservation Marine and Freshwater Ecosystems
Published
2026-02-01
DOI
https://doi.org/10.1002/aqc.70324
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
0.00

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River Connectivity in Dammed Areas Studied Through Environmental DNA Metabarcoding at Community and Species Levels

Eva García‐Vázquez, Sara Fernández, Alba Ardura
Aquatic Conservation Marine and Freshwater Ecosystems
Environmental DNA in Biodiversity Studies
article

River Connectivity in Dammed Areas Studied Through Environmental DNA Metabarcoding at Community and Species Levels

Eva García‐Vázquez, Sara Fernández, Alba Ardura
article en

Abstract

ABSTRACT The field of environmental DNA (eDNA) is rapidly expanding with established applications in biodiversity monitoring, rare species detection and ecological assessment. However, its potential to evaluate species connectivity in fragmented aquatic systems remains underexplored. This study addresses this gap by applying eDNA metabarcoding to assess community connectivity in a dam‐fragmented river network, combining a multispecies framework with haplotype‐level analyses to investigate both community composition and within‐species variability. Community changes associated with reservoirs included biodiversity losses in the dammed area and have been found, as well as dams acting as barriers to the upstream advance of the invasive acute bladder snail Physella acuta . Haplotype analysis of the fish Phoxinus bigerri and Salmo trutta , the red alga Sheathia arcuata and the amoeba Koretnevella stella showed different levels of connectivity according to species biology, with genetic barriers associated with dams for the three species and diversity losses in the dammed area for the native S. trutta . Despite methodological limitations such as the non‐met premise of one haplotype one individual, the results suggest that metabarcoding on eDNA extracted from water samples can provide valuable insights into genetic diversity and connectivity across multiple taxa, offering new opportunities in conservation biology.

Aquatic Conservation Marine and Freshwater EcosystemsVol. 36(2)
Universidad de Oviedo (ES)
Ministerio de Ciencia e Innovación
Life in Land
Openalex Percentile: Top 71%
Environmental DNA in Biodiversity Studies
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River Connectivity in Dammed Areas Studied Through Environmental DNA Metabarcoding at Community and Species Levels — Eva García‐Vázquez, Sara Fernández, et al. · Aquatic Conservation Marine and Freshwater Ecosystems (2026) | TGRS Research Map | TGRS