Metabarcoding as a quantitative tool for estimating biodiversity and relative biomass of marine zooplankton

Author:

Ershova E A123ORCID,Wangensteen O S4ORCID,Descoteaux R1,Barth-Jensen C1ORCID,Præbel K4

Affiliation:

1. Faculty for Biosciences, Fisheries and Economics, Department for Arctic and Marine Biology, UiT The Arctic University of Norway, P.O. Box 6050, Langnes, 9037 Tromsø, Norway

2. Institute of Marine Research, P.O. Box 1870, Nordnes, 5817 Bergen, Norway

3. Shirshov Institute of Oceanology, Russian Academy of Sciences, 36 Nahimovskiy Prospekt, 117997 Moscow, Russia

4. Faculty for Biosciences, Fisheries and Economics, Norwegian College of Fishery Science, UiT The Arctic University of Norway, P.O. Box 6050, Langnes, 9037 Tromsø, Norway

Abstract

Abstract Although metabarcoding is a well-established tool for describing diversity of pelagic communities, its quantitative value is still controversial, with poor correlations previously reported between organism abundance/biomass and sequence reads. In this study, we explored an enhanced quantitative approach by metabarcoding whole zooplankton communities using a highly degenerate primer set for the mitochondrial marker cytochrome oxidase I and compared the results to biomass estimates obtained using the traditional morphological approach of processing zooplankton samples. As expected, detected species richness using the metabarcoding approach was 3–4 times higher compared to morphological processing, with the highest differences found in the meroplankton fraction. About 75% of the species identified using microscopy were also recovered in the metabarcoding run. Within the taxa detected using both approaches, the relative numbers of sequence counts showed a strong quantitative relationship to their relative biomass, estimated from length-weight regressions, for a wide range of metazoan taxa. The highest correlations were found for crustaceans and the lowest for meroplanktonic larvae. Our results show that the reported approach of using a metabarcoding marker with improved taxonomic resolution, universal coverage for metazoans, reduced primer bias, and availability of a comprehensive reference database, allow for rapid and relatively inexpensive processing of hundreds of samples at a higher taxonomic resolution than traditional zooplankton sorting. The described approach can therefore be widely applied for monitoring or ecological studies.

Funder

UiT The Arctic University of Norway

Tromsø Research Foundation

RFBR

RAS

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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