Hydrology and small pelagic fish drive the spatio–temporal dynamics of springtime zooplankton assemblages over the Bay of Biscay continental shelf. (January 2023)

• Record Type: Journal Article
• Authors: Grandremy, Nina; Romagnan, Jean-Baptiste; Dupuy, Christine; Doray, Mathieu; Huret, Martin; Petitgas, Pierre
• Is Part Of: Progress in oceanography. Volume 210(2023)
• Publication Date: 2023-01
• Subjects: Mesozooplankton -- Imaging analysis -- Time–consistent spatial patterns -- Ecosystem structure -- Spring habitat -- Multi Factor Analysis -- Bay of Biscay; Oceanography -- Periodicals; 551.4605
• DOI: 10.1016/j.pocean.2022.102949
• Languages: English
• ISSNs: 0079-6611

Abstract

Highlights: Taxonomically and spatially–resolved zooplankton dataset over 16 years in spring. Time–consistent zooplankton composition spatial structure with multi–table analysis. Explanation of zooplankton spatial patterns with gradients in the pelagic ecosystem. Zooplankton spatial pattern underpinned by taxonomic composition and size structure. River plumes, temperature gradients and pelagic fish correlated zooplankton pattern. Abstract: As mesozooplankton is the preferential prey of small pelagic fish (SPF), environmentally–driven mesozooplankton dynamics can have critical effects on SPF population dynamics. Despite previous studies on SPF habitats' dynamics, hydrological landscapes and mesozooplankton dynamics in the Bay of Biscay (BoB), knowledge gaps persist at the BoB regional–scale pelagic ecology and in particular about the mesozooplankton assemblages and their long–term space–time patterns. Here, we present 16 years of spring mesozooplankton assemblage interannual spatial dynamics over the BoB continental shelf and we describe the correlations between the mesozooplankton space–time patterns and those in hydrology, primary producers and SPF. We gathered data originating from the PELGAS surveys (2004–2019) and remote sensing products. Mesozooplankton samples were collected with a 200–µm mesh size WP2 net vertically towed from 100 m depth (or 5 m above the sea floor) to the surface. They were analysed with imaging and deep-learning tools and the biomass in 24 coarse taxonomic groups was calculated. Automated procedures for spatial gridding and missing data imputation enable the generation of yearly maps time series with the same spatial resolution across the pelagic ecosystem components and years. These comprehensive multivariate datasets were analysed with a multi–table method known as Multiple Factor Analyses to depict time–consistent spatial patterns in each ecosystem component and the temporal variability around them. Finally, the main time–consistent spatial patterns in the hydrology, primary producers and SPF ecosystem components were used as predictors in generalized linear models, to explain those in the mesozooplankton. Mesoscale coastal-offshore and north–south gradients were the main patterns observed in each of the pelagic ecosystem components studied. The spatial patterns in the mesozooplankton assemblage were stable, without any significant changes detected in the taxonomic composition nor its spatial structure over the studied period. Small copepods, gelatinous and meroplanktonic organisms characterised coastal areas. Euchaetidae and meroplanktonic crustaceans' larvae displayed higher biomass in the northern part of the BoB while Metridinidae, Cladocera, Appendicularia and Echinodermata had higher biomass in the southern part. Surface and bottom water temperature, salinity–related parameters, water column stratification and SPF biomasses were the variables that best explained the observed space–time patterns in the mesozooplankton communities.