English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

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