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Abstract Mesozooplankton is a very diverse group of small animals ranging in size from 0.2 to 20 mm not able to swim against ocean currents. It is a key component of pelagic ecosystems through its roles in the trophic networks and the biological carbon pump. Traditionally studied through microscopes, recent methods have been however developed to rapidly acquire large amounts of data (morphological, molecular) at the individual scale, making it possible to study mesozooplankton using a trait‐based approach. Here, combining quantitative imaging with metabarcoding time‐series data obtained in the Sargasso Sea at the Bermuda Atlantic Time‐series Study (BATS) site, we showed that organisms' transparency might be an important trait to also consider regarding mesozooplankton impact on carbon export, contrary to the common assumption that just size is the master trait directing most mesozooplankton‐linked processes. Three distinct communities were defined based on taxonomic composition, and succeeded one another throughout the study period, with changing levels of transparency among the community. A co‐occurrences' network was built from metabarcoding data revealing six groups of taxa. These were related to changes in the functioning of the ecosystem and/or in the community's morphology. The importance of Diel Vertical Migration at BATS was confirmed by the existence of a group made of taxa known to be strong migrators. Finally, we assessed if metabarcoding can provide a quantitative approach to biomass and/or abundance of certain taxa. Knowing more about mesozooplankton diversity and its impact on ecosystem functioning would allow to better represent them in biogeochemical models. 

Abstract The increasing use of image-based observing systems in marine ecosystems allows for more quantitative analysis of the ecological zonation of zooplankton. Developing methods that take advantage of these systems can provide an increasingly nuanced understanding of how morphometric characteristics (especially size) are related to distribution, abundance and ecosystem function via a wider application of allometric calculations of biogeochemical fluxes. Using MOCNESS sampling of zooplankton near the Bermuda Atlantic Time Series and a ZooSCAN/EcoTaxa pipeline, we apply a new taxonomically resolved biomass to biovolume dataset and a suite of R scripts that provide information about the relationships between zooplankter size, taxonomy, distribution, depth of migration, magnitude of migration and biogeochemical contributions (e.g. respiratory O2 consumption). The analysis pipeline provides a framework for quantitatively comparing and testing hypotheses about the distribution, migration patterns and biogeochemical impacts of mesozooplankton. Specifically, our code helps to visualize a size-based structure in the extent of vertical migration and allow for a quantification of the relative importance of non-migratory versus migratory organisms of various size classes. It additionally allows us to quantify the error associated with various methods of calculating active flux, with size-based analysis being the most important methodological choice, and taxonomic identification being the least.