Morphology-based profling of benthic communities has been extensively applied to aquatic
ecosystems’ health assessment. However, it remains a low-throughput, and sometimes ambiguous,
procedure. Despite DNA metabarcoding has been applied to marine benthos, a comprehensive
approach providing species-level identifcations for estuarine macrobenthos is still lacking. Here we
report a combination of experimental and feld studies to assess the aptitude of COI metabarcoding
to provide robust species-level identifcations for high-throughput monitoring of estuarine
macrobenthos. To investigate the ability of metabarcoding to detect all species present in bulk DNA
extracts, we contrived three phylogenetically diverse communities, and applied four diferent primer
pairs to generate PCR products within the COI barcode region. Between 78–83% of the species in
the contrived communities were recovered through HTS. Subsequently, we compared morphology
and metabarcoding-based approaches to determine the species composition from four distinct
estuarine sites. Our results indicate that species richness would be considerably underestimated if
only morphological methods were used: globally 27 species identifed through morphology versus 61
detected by metabarcoding. Although further refnement is required to improve efciency and output
of this approach, here we show the great aptitude of COI metabarcoding to provide high quality and
auditable species identifcations in estuarine macrobenthos monitoring.This study has been funded by the project “Te NextSea: Next generation monitoring of coastal ecosystems in a
scenario of global change” (operação NORTE-01-0145-FEDER-000032), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). JL was supported by a PhD fellowship (SFRH/BD/69750/2010) from FCT. Tis study had the fnancial support of Fundação para a Ciência e Tecnologia (FCT), through the strategic project UID/MAR/04292/2013 granted to MARE. Te authors would like to thank Stephanie Boilard (Biodiversity Institute of Ontario) for her support in the lab work.info:eu-repo/semantics/publishedVersio
