Assessing different components of diversity across a river network using eDNA

Autor: Samuel Hürlemann, Emanuel A. Fronhofer, Chelsea J. Little, Jean-Claude Walser, Roman Alther, Isabelle Gounand, Remo Wüthrich, Elvira Mächler, Florian Altermatt, Eric Harvey
Přispěvatelé: Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Universität Zürich [Zürich] = University of Zurich (UZH), Department of Aquatic Ecology - (Dübendorf, Suisse), Swiss Federal Insitute of Aquatic Science and Technology [Dübendorf] (EAWAG), University of Zurich, Mächler, Elvira, Altermatt, Florian, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Environmental DNA
Environmental DNA, John Wiley & Sons Inc., 2019, 1 (3), pp.290-301. ⟨10.1002/edn3.33⟩
Environmental DNA, 2019, 1 (3), pp.290-301. ⟨10.1002/edn3.33⟩
ISSN: 2637-4943
DOI: 10.1002/edn3.33⟩
Popis: International audience; Assessing individual components of biodiversity, such as local or regional taxon richness, and differences in community composition is a long-standing challenge in ecology. It is especially relevant in spatially structured and diverse ecosystems. Environmental DNA (eDNA) has been suggested as a novel technique to detect taxa and therefore may allow to accurately measure biodiversity. However, we do not yet fully understand the comparability of eDNA-based assessments to classical morphological approaches. We assessed may-, stone-, and caddisfly genera with two contemporary methods, namely eDNA sampling followed by molecular identification and kicknet sampling followed by morphological identification. We sampled 61 sites distributed over a large river network, allowing a comparison of various diversity measures from the catchment to site levels and providing insights into how these measures relate to network properties. We extended our data with historical morphological records of total diversity at the catchment level. At the catchment scale, identification based on eDNA and kicknet samples detected similar proportions of the overall and cumulative historically documented richness (gamma diversity), 42% and 46%, respectively. We detected a good overlap (62%) between genera identified from eDNA and kicknet samples at the regional scale. At the local scale, we found highly congruent values of local taxon richness (alpha diversity) between eDNA and kicknet samples. Richness of eDNA was positively related to discharge, a descriptor of network position, while kicknet was not. Beta diversity, a measure of dissimilarity between sites, was comparable for the two contemporary methods and is driven by species replacement and not by nestedness. Although eDNA approaches are still in their infancy and optimization regarding sampling design and laboratory work is still needed, our results indicate that it can capture different components of diversity, proving its potential utility as a new tool for large sampling campaigns across hitherto understudied complete river catchments.
Databáze: OpenAIRE
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