4.6 Article

Fine-tuning biodiversity assessments: A framework to pair eDNA metabarcoding and morphological approaches

Journal

METHODS IN ECOLOGY AND EVOLUTION
Volume 12, Issue 12, Pages 2397-2409

Publisher

WILEY
DOI: 10.1111/2041-210X.13718

Keywords

biodiversity; environmental DNA; metabarcoding; morphological approaches

Categories

Funding

  1. Fundacao para a Ciencia e a Tecnologia [PTDC/AAG-MAA/3764/2014, PTDC/BIA-BIC/0352/2014, PTDC/CTA-AMB/30793/2017, SFRH/BD/102020/2014]
  2. H2020 European Research Council [731065, 871081]
  3. FEDER [POCI-01-0145-FEDER-007688]
  4. Fundação para a Ciência e a Tecnologia [PTDC/AAG-MAA/3764/2014, PTDC/CTA-AMB/30793/2017, SFRH/BD/102020/2014, PTDC/BIA-BIC/0352/2014] Funding Source: FCT

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Accurate quantification of biodiversity can be challenging and costly, with environmental DNA (eDNA) metabarcoding offering a potential solution. However, combining eDNA metabarcoding with morphological data can enhance taxonomic resolution and accuracy in assigning species traits and abundance. This integrated approach demonstrates the potential for improving biodiversity assessments through the complementary use of traditional and modern methods.
Accurate quantification of biodiversity can be demanding and expensive. Although environmental DNA (eDNA) metabarcoding can facilitate biodiversity assessments through non-invasive, cost-efficient and rapid surveys, the approach struggles to outperform traditional morphological approaches in providing reliable quantitative estimates for surveyed species (e.g. abundance and biomass). We present an integrated methodology for improving biodiversity surveys that pairs eDNA metabarcoding with morphological data, following a series of taxonomic and geographical filters. We demonstrate its power by applying it to a new spatiotemporal dataset generated on an Iberian-wide distributed aquatic mesocosm infrastructure that spans a wide biogeographical gradient. By building upon the strengths that these two approaches offer, our framework improved taxonomic resolution for 30% of the taxa and enabled species' traits (e.g. body size) and abundance to be assigned to 85% of the taxa in hybrid datasets. These results indicate that eDNA-based assessments can complement, but not always replace, conventional approaches. Integrating conventional and modern eDNA metabarcoding approaches, already available in the ecologist's toolbox, will greatly enhance biodiversity assessments.

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