Unlocking biodiversity and conservation studies in high-diversity environments using environmental DNA (eDNA): A test with Guianese freshwater fishes.


Journal

Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604

Informations de publication

Date de publication:
Jan 2019
Historique:
received: 25 07 2017
accepted: 29 03 2018
pubmed: 17 5 2018
medline: 6 3 2019
entrez: 17 5 2018
Statut: ppublish

Résumé

Determining the species compositions of local assemblages is a prerequisite to understanding how anthropogenic disturbances affect biodiversity. However, biodiversity measurements often remain incomplete due to the limited efficiency of sampling methods. This is particularly true in freshwater tropical environments that host rich fish assemblages, for which assessments are uncertain and often rely on destructive methods. Developing an efficient and nondestructive method to assess biodiversity in tropical freshwaters is highly important. In this study, we tested the efficiency of environmental DNA (eDNA) metabarcoding to assess the fish diversity of 39 Guianese sites. We compared the diversity and composition of assemblages obtained using traditional and metabarcoding methods. More than 7,000 individual fish belonging to 203 Guianese fish species were collected by traditional sampling methods, and ~17 million reads were produced by metabarcoding, among which ~8 million reads were assigned to 148 fish taxonomic units, including 132 fish species. The two methods detected a similar number of species at each site, but the species identities partially matched. The assemblage compositions from the different drainage basins were better discriminated using metabarcoding, revealing that while traditional methods provide a more complete but spatially limited inventory of fish assemblages, metabarcoding provides a more partial but spatially extensive inventory. eDNA metabarcoding can therefore be used for rapid and large-scale biodiversity assessments, while at a local scale, the two approaches are complementary and enable an understanding of realistic fish biodiversity.

Identifiants

pubmed: 29768738
doi: 10.1111/1755-0998.12900
doi:

Substances chimiques

DNA 9007-49-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

27-46

Informations de copyright

© 2018 John Wiley & Sons Ltd.

Auteurs

Kévin Cilleros (K)

Laboratoire Évolution & Diversité Biologique (EDB UMR5174), Université de Toulouse, CNRS, IRD, UPS, Toulouse Cedex, France.

Alice Valentini (A)

SPYGEN, Savoie Technolac, Le Bourget-du-Lac, France.

Luc Allard (L)

Laboratoire Environnement de Petit Saut, HYDRECO, Kourou Cedex, French Guiana.

Tony Dejean (T)

SPYGEN, Savoie Technolac, Le Bourget-du-Lac, France.

Roselyne Etienne (R)

Laboratoire Évolution & Diversité Biologique (EDB UMR5174), Université de Toulouse, CNRS, IRD, UPS, Toulouse Cedex, France.

Gaël Grenouillet (G)

Laboratoire Évolution & Diversité Biologique (EDB UMR5174), Université de Toulouse, CNRS, IRD, UPS, Toulouse Cedex, France.

Amaia Iribar (A)

Laboratoire Évolution & Diversité Biologique (EDB UMR5174), Université de Toulouse, CNRS, IRD, UPS, Toulouse Cedex, France.

Pierre Taberlet (P)

Laboratoire d'Ecologie Alpine (LECA UMR5553), CNRS, Université Joseph Fourier, Grenoble, France.

Régis Vigouroux (R)

Laboratoire Environnement de Petit Saut, HYDRECO, Kourou Cedex, French Guiana.

Sébastien Brosse (S)

Laboratoire Évolution & Diversité Biologique (EDB UMR5174), Université de Toulouse, CNRS, IRD, UPS, Toulouse Cedex, France.

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Classifications MeSH