The diet and stable isotopic (i.e. δ15N and δ13C values) compositions of eels have been studied during each season of 2019 with a fyke net in six estuaries located along the French coast of the eastern English Channel (Slack, Wimereux, Liane, Canche, Authie and Somme estuaries) (10.1371/journal.pone.0270348).

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) significant wave height (SWH) data (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) SWH data) with a particular focus for use in climate studies. This dataset contains the Sentinel-1 SAR Remote Sensing Significant Wave Height product (version 1.0), which is part of the ESA Sea State CCI Version 3.0 release. This product provides along-track SWH measurements at 20km resolution every 100km, processed using the Quach et al statistical model , separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI dataset v3 come from Sentinel-1 satellite missions spanning from 2015 to 2021 (Sentinel-1 A, Sentinel-1 B).

Particularly suited to the purpose of measuring the sensitivity of benthic communities to trawling, a trawl disturbance indicator (de Juan and Demestre, 2012, de Juan et al. 2009) was proposed based on benthic species biological traits to evaluate the sensibility of mega- and epifaunal community to fishing pressure known to have a physical impact on the seafloor (such as dredging and bottom trawling). The selected biological traits were chosen as they determine vulnerability to trawling: mobility, fragility, position on substrata, average size and feeding mode that can easily be related to the fragility, recoverability and vulnerability ecological concepts. The five categories retained are functional traits that were selected based on the knowledge of the response of benthic taxa to trawling disturbance (de Juan et al., 2009). They reflect respectively the possibility to avoid direct gear impact, to benefit from trawling for feeding, to escape gear, to get caught by the net and to resist trawling/dredging action, each of these characteristics being either advantageous or sensitive to trawling. To expand this approach to that proposed by Certain et al. (2015), the protection status of certain species was also indicated. To enable quantitative analysis, a score was assigned to each category: from low sensitivity (0) to high sensitivity (3). Biological traits of species have been defined, from the BIOTIC database (MARLIN, 2014) and from information given by Garcia (2010), Le Pape et al. (2007) and Brind’Amour et al. (2009). For missing traits, additional information from literature has been considered. The protection status of each taxa was also scored: Atlantic species listed in OSPAR List of Threatened and/or Declining Species and Habitats (https://www.ospar.org/work-areas/bdc/species-habitats/list-of-threatened-declining-species-habitats) and Mediterranean species listed in Vulnerable Marine Ecosystems (FAO, 2018 and Oceana, 2017) were scored 3 and other species were scored 1. The scores of 1085 taxa commonly found in bottom trawl by-catch in the southern North Sea, English Channel and north-western Mediterranean were described.

The upper ocean pycnocline (UOP) monthly climatology is based on the ISAS20 ARGO dataset containing Argo and Deep-Argo temperature and salinity profiles on the period 2002-2020. Regardless of the season, the UOP is defined as the shallowest significant stratification peak captured by the method described in Sérazin et al. (2022), whose detection threshold is proportional to the standard deviation of the stratification profile. The three main characteristics of the UOP are provided -- intensity, depth and thickness -- along with hydrographic variables at the upper and lower edges of the pycnocline, the Turner angle and density ratio at the depth of the UOP. A stratification index (SI) that evaluates the amount of buoyancy required to destratify the upper ocean down to a certain depth, is also included. When evaluated at the bottom of the UOP, this gives the upper ocean stratification index (UOSI) as discussed in Sérazin et al. (2022). Three mixed layer depth variables are also included in this dataset, including the one using the classic density threshold of 0.03 kg.m-3, along with the minimum of these MLD variables. Several statistics of the UOP characteristics and the associated quantities are available in 2°×2° bins for each month of the year, whose results were smoothed using a diffusive gaussian filter with a 500 km scale. UOP characteristics are also available for each profile, with all the profiles sorted in one file per month.

In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (eg become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (eg a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into ‘regions of interest’, spatiotemporal cylinders consisting of circles on the Earth’s surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is done for each of the other datasets, producing a dataset of matchups. About 35 million in situ datapoints were then matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of 287,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. This dataset was funded by ESA Satellite Oceanographic Datasets for Acidification (OceanSODA) project which aims at developing the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry.

The SWISCA Level 2S (L2S) product provides along-track colocation of SWIM wave measuring instrument onto SCAT scatterometer grid, over the global ocean. SWIM and SCAT are both instruments onboard CFOSAT. CFOSAT (Chinese French Ocean SATellite) is a french-chinese mission launched in 2018, whose aim is to provide wind (SCAT instrument) and wave (SWIM instrument) measurements over the sea surface. The SWISCA L2S product is broken down into three different subproducts: - L2A containing the sigma0 of both SWIM and SCAT - L2B containing the wave parameters measured by SWIM and wind vectors measured by SCAT - AUX containing additional ancillary fields such as sea ice concentration (from CERSAT/SSMI), ocean currents (from CMEMS/GlobCurrent), SST and Wind (from ECMWF), rain rate (from IMERG), and WaveWatch3 wave spectra. All SWIM and ancillary observations are resampled onto SCAT scatterometer's geometry (wind vector cells, WVC). The SWISCA level 2S product is generated in delayed mode, a few days after acquisition. It is intended to foster cross analysis of SWIM and SCAT observations, and their combination to improve the retrieval of both wind and wave parameters. The SWISCA L2S product is generated and distributed by Ifremer / CERSAT in the frame of the Ifremer Wind and Wave Operation Center (IWWOC) co-funded by Ifremer and CNES and dedicated to the processing of the delayed mode data of CFOSAT mission.

We developed a panel of single nucleotide polymorphism (SNP) markers for thornback ray Raja clavata using a RADSeq protocole. Demultiplexed sequences were aligned to the genome of Leucoraja erinacea which was used as reference genome. From an initial set of 389 483 putative SNPs, 7741 SNPs with the largest minor allele frequency were selected for implementation on an Infinium® XT iSelect-96 SNP-array implemented by LABOGENA DNA. For the array, SNPs [T/C] and [T/G] were replaced by those from the complementary strand [A/G] and [A/C] respectively. For some SNPs, a second SNP was found in the 50 nucleotide bases flanking sequence. In these cases, two SNP probes were developed with each of the two alleles of the second SNP. A SNP probe naming convention was adopted to identify these pairs of probes corresponding to the same SNP locus: “MAJ” or “MIN” followed by the corresponding base was included in the probe name. For some of these pairs, only one of the two markers could be developed, resulting in a total set of 9120 SNP probes, including 6360 single SNP probes, 10 MAJ or MIN probes for which a single probe was successfully developed, and 1375 pairs of probes with MAJ and MIN versions. The 9120 SNP genotypes were then scored using the clustering algorithm implemented in the Illumina® GenomeStudio Genotyping Analysis Module v2.0.3 for 7726 individual samples, including duplicates, mostly from the Bay of Biscay but also from the Mediterranean Sea and West Iberia. Overall, 1643 SNPs failed to be genotyped in all individuals, for 319 markers the minor allele was not found and 7158 markers (including 1974 for 987 MIN-MAJ pairs) produced bi-allelic genotypes. The majority of these SNPs had a minor allele frequency between 0.1 and 0.5. The MIN-MAJ probes can be used for quality checking the genotyping results

The ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution. It has been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. It covers the date range from 2002-2021. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

This dataset provides the meridional and zonal components of both the stress-equivalent wind (U10S) and wind stress (Tau) vectors. The ERA* product is a correction of the ECMWF Fifth Reanalysis (ERA5) output by means of geo-located scatterometer-ERA5 differences over a 15-day temporal window. The product also contains ERA5 U10S and Tau. The data are available through HTTP and FTP; access to the data is free and open. In order to be informed about changes and to help us keep track of data usage, we encourage users to register at: https://forms.ifremer.fr/lops-siam/access-to-esa-world-ocean-circulation-project-data/ This dataset was generated by ICM (Institute of Marine Sciences) / CSIC (Consejo Superior de Investigaciones Científicas) and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

This dataset contains the pictures used for morphometric measurements, as well as the elemental compositon and production rates data, of planktonic Rhizaria. Specimens were collected in the bay of Villefranche-sur-Mer in May 2019 and during the P2107 cruise in the California Current in July-August 2021. Analyses of the data can be found at https://github.com/MnnLgt/Elemental_composition_Rhizaria.