Building reference libraries of DNA barcodes is relatively straightforward when specifically designed primers are available to amplify the COI-5P region from a relatively narrow taxonomic group (e.g. single class or single order). DNA barcoding marine communities have been comparatively harder to accomplish due to the broad taxonomic diversity and lack of consistently efficient primers. Although some of the so-called “universal” primers have been relatively successful, they still fail to amplify COI-5P of many marine animal groups, while displaying random success even among species within each group. Here we propose a new pair of primers designed to enhance amplification of the COI-5P region in a wide range of marine organisms.

Morphology-based profiling 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 identifications for estuarine macrobenthos is still lacking. Here we report a combination of experimental and field studies to assess the aptitude of COI metabarcoding to provide robust species-level identifications 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 different 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 identified through morphology versus 61 detected by metabarcoding. Although further refinement is required to improve efficiency and output of this approach, here we show the great aptitude of COI metabarcoding to provide high quality and auditable species identifications in estuarine macrobenthos monitoring.