Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding

Research output: Contribution to journalJournal articleResearchpeer-review

  • Alice Valentini
  • Pierre Taberlet
  • Claude Miaud
  • Raphaël Civade
  • Jelger Herder
  • Philip Francis Thomsen
  • Eva Bellemain
  • Aurélien Besnard
  • Eric Coissac
  • Frédéric Boyer
  • Coline Gaboriaud
  • Pauline Jean
  • Nicolas Poulet
  • Nicolas Roset
  • Gordon H Copp
  • Philippe Geniez
  • Didier Pont
  • Christine Argillier
  • Jean-Marc Baudoin
  • Tiphaine Peroux
  • Alain Jean Crivelli
  • Anthony Olivier
  • Manon Acqueberge
  • Matthieu Le Brun
  • Tony Dejean
Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present into the environment. In this study, we tested if an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro, and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90-0.99) versus 0.58 (CI = 0.50-0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA-based approach has the potential to become the next-generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems. This article is protected by copyright. All rights reserved.
Original languageEnglish
JournalMolecular Ecology
Issue number4
Pages (from-to)929-942
Number of pages14
Publication statusPublished - 2016

ID: 161819868