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Application of eDNA metabarcoding in a fragmented lowland river: Spatial and methodological comparison of fish species composition

  • Caterina M. Antognazza
  • , Robert J. Britton
  • , Daniel S. Read
  • , Tim Goodall
  • , Anna Mantzouratou
  • , Vanessa De Santis
  • , Peter Davies
  • , Miran Aprahamian
  • , Elizabeth Franklin
  • , Emilie A. Hardouin
  • , Demetra Andreou
  • Bournemouth University

Research output: Contribution to journalArticlepeer-review

Abstract

Assessments of fish communities tend to rely on capture‐based methods that, due to sampling biases, can underestimate actual species richness. Alternatively, environmental DNA (eDNA) based metabarcoding is a noncapture approach that infers species richness and distribution by collecting and sequencing DNA present in the ecosystem. Here, eDNA metabarcoding was applied to the lower River Severn, a highly modified and impounded river, to identify the species present in the fish assemblage. Using a universal primer for fish (12S mtDNA region), comparisons were made between the species identified as present by eDNA metabarcoding versus long‐term data available from fisheries monitoring data based on capture methods. Depending on the stringency of detection thresholds applied, the two methods detected between 15 and 25 fish species present in the river, with the eDNA metabarcoding detecting most species previously reported in the capture surveys, although with differences in the relative abundance of species between the methods. Notably, eDNA metabarcoding detected species of high conservation importance that were never sampled by capture techniques, including native European shads (<jats:italic>Alosa</jats:italic> spp.). Differences in the similarity indices of species detection were greater between the sampling methods than between sampling sites on each river. These results highlight the high potential of eDNA metabarcoding to provide an effective monitoring tool for biodiversity and conservation in rivers, but also indicate the need for complementary multi‐method sampling for robust estimates of fish species richness.
Original languageEnglish
Pages (from-to)458-471
JournalEnvironmental DNA
Volume3
Issue number2
Early online date14 Sept 2020
DOIs
Publication statusPublished - Mar 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

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