As part of the European Horizon Europe FOCCUS project (https://foccus-project.eu/), the metadata inventory of European coastal platforms has been extracted. The inventory was based on the following History and Latest products, downloaded from the CMEMS website (https://marine.copernicus.eu/fr/acces-donnees) at: 1) Global Ocean-In-Situ Near-Real-Time Observation, 2) Atlantic Iberian Biscay Irish Ocean-In-Situ Near Real Time Observations, 3) Mediterranean Sea-In-Situ Near Real Time Observations, 4) Atlantic-European North West Shelf-Ocean In-Situ Near Real Time Observations. To carry out this inventory, it was decided to target only coastal platforms, located less than 200km from the coast and at a depth of less than 400m. For mobile platforms, it was also decided to focus only on the first position in the file. This data must be located within 200 km of the coast and at a depth of less than 400 m. In this inventory, FerryBox platforms have all been considered as coastal platforms. The following platforms were extracted from the products: BO (Bottles), CT (CTD), DB (Drifting Buoys), FB (Ferry Box), GL (Gliders), HF (High Frequency Radar), MO (Mooring), PF (Profiling Float), TG (Tide Gauge) and XB (XBT). Once the metadata had been extracted from the files, duplicates were removed (files with the same names). Duplicate platforms of type _TS_ and _WS_ were merged (date and parameters). Latest‘ files have been merged with ’History" files. Missing metadata have been replaced in the Excel file by ‘Missing Data’. Some old dates were also revised by hand because they had been badly extracted, as well as some institution names that included special characters. Platforms located on estuaries/rivers/lakes/ponds have also been removed by hand. This inventory identified a total of 10,479 coastal platforms.

Long-term time series of coliform bacteria concentration (fecal coliform or Escherichia coli) in shellfish in four submarine areas (North Sea/Channel, Britany, Atlantic, Mediterranean).

This dataset contains the biological outputs of a global ocean simulation coupling dynamics and biogeochemistry at ¼° over the year 2019. The simulation has been performed using the coupled circulation/ecosystem model NEMO/PISCES (https://www.nemo-ocean.eu/), which is here enhanced to perform an ensemble simulation with explicit simulation of modeling uncertainties in the physics and in the biogeochemistry. This dataset is one of the 40 members of the ensemble simulation. This study was part of the Horizon Europe project SEAMLESS (https://seamlessproject.org/Home.html), with the general objective of improving the analysis and forecast of ecosystem indicators.   See Popov et al. (https://os.copernicus.org/articles/20/155/2024/) for more details on the study.

'''DEFINITION''' Estimates of Ocean Heat Content (OHC) are obtained from integrated differences of the measured temperature and a climatology along a vertical profile in the ocean (von Schuckmann et al., 2018). The products used include three global reanalyses: GLORYS, C-GLORS, ORAS5 (GLOBAL_MULTIYEAR_PHY_ENS_001_031) and two in situ based reprocessed products: CORA5.2 (INSITU_GLO_PHY_TS_OA_MY_013_052) , ARMOR-3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). Additionally, the time series based on the method of von Schuckmann and Le Traon (2011) has been added. The regional OHC values are then averaged from 60°S-60°N aiming i) to obtain the mean OHC as expressed in Joules per meter square (J/m2) to monitor the large-scale variability and change. ii) to monitor the amount of energy in the form of heat stored in the ocean (i.e. the change of OHC in time), expressed in Watt per square meter (W/m2). Ocean heat content is one of the six Global Climate Indicators recommended by the World Meterological Organisation for Sustainable Development Goal 13 implementation (WMO, 2017). '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the ocean shapes our perspectives for the future (von Schuckmann et al., 2020). Variations in OHC can induce changes in ocean stratification, currents, sea ice and ice shelfs (IPCC, 2019; 2021); they set time scales and dominate Earth system adjustments to climate variability and change (Hansen et al., 2011); they are a key player in ocean-atmosphere interactions and sea level change (WCRP, 2018) and they can impact marine ecosystems and human livelihoods (IPCC, 2019). '''CMEMS KEY FINDINGS''' Since the year 2005, the upper (0-700m) near-global (60°S-60°N) ocean warms at a rate of 0.6 ± 0.1 W/m2. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00234

This visualization product displays the density of floating micro-litter per net normalized per m³ per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. Densities were calculated for each net using the following calculation: Density (number of particles per m³) = Micro-litter count / Sampling effort (m³) When the number of micro-litters was not filled, it was not possible to calculate the density. Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.

The present repository makes available the model, material and outputs of the ISIS-Fish modeling work showcased in the peer-reviewed scientific article by Bastardie et al. 2025. As part of the SEAwise research project (seawiseproject.org), we used an ISIS-Fish database (Mahevas et al 2003, Pelletier et al. 2009, isis-fish.org) previously developed within the MACCO project which describes the mixed demersal fishery in the Bay of Biscay. For this application, the spatial extent of the fishery is the Bay of Biscay, defined here by ICES divisions 8a, 8b and 8d and the resolution chosen is 1/16 ICES statistical rectangle. The biological module (Vajas et al. 2024) includes 7 species of economic interest in the mixed demersal fishery: European hake (Merluccius merluccius), common sole (Solea solea), Norway lobster (Nephrops norvegicus), megrim (Lepidorhombus whiffiagonis), anglerfish (Lophius piscatorius) and two ray species (Raja clavata, Leucoraja naevus). The fishing activities module (Mahevas et al. 2024) is made up of 41 demersal fleets (including all French vessels < 12 meters and > 12 meters fishing in this area, Spanich, UK and Belgium fleets) and 431 métiers (combination of a gear, location and mix of target species) catching these 7 species, as target or bycatch. Monthly effort of a fleet distributes among the possible métiers (those historically practiced). The biological and fishing activity modules are identical to the published version. The original model used here has been calibrated on historical catch data 2015-2018 by tuning accessibility and catchability parameters. In the present application the Bay of Biscay model is used to investigate the spatial- and effort- based fisheries management strategies. Consistently with for a task of the SEAwise project (Bastardie et al. 2024) simulations were conducted from 2021 onwards, projecting the effect of an implementation of 3 different closures from 2022 to 2050, under current fishing effort conditions or in a context of fishing effort reduction. Outcomes of these simulations are averaged over short/medium (10 year horizon) and long-term period (20 year horizon). The data project includes: 1) the database including the biological module and fishing activity module; 2) 8 .properties files, each corresponding to one combination of management measure and closure, to restore the simulations parameters in the ISIS-Fish interface and reproduce the simulation runs; 3) the .java scripts to force effort dynamics and simulate spatio-temporal closures, as well as generate the main output files - they will be called by the ISIS-Fish software once the simulations restored 4) the .rds containing the main outputs of the simulations and the associated .html document displaying the R code to compute the indices of interest at different levels of aggregation and reproduce the figures in Bastardie et al. 2025. All files are provided in the Zip. Associated with this material, a study summary and a readme .docx are provided. The first one provides context on the present work and describes the model and simulations' design. The second provides guidelines to reproduce the simulations and their derived outcomes from the data project material made available in this repository. They are both directly downloadable from this repository and are also copied to the zipped folder containing the data project. All the data are reproducible using isis-fish-4.4.8.1 (isis-fish.org; available at forge.codelutin.com) and R 4.2.0.

210Pb, 226Ra and 137Cs were measured by non-destructive gamma spectrometry on marine sediment cores, collected during RIKEAU 2002 cruise on board r/v Thalia, on the shelf of the Bay of Biscay

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Northeast Atlantic Ocean (40W). Data were harmonised and validated by '‘IFREMER / IDM / SISMER - Scientific Information Systems for the SEA’ in France. The dataset contains water (profiles), sediment (profiles and timeseries) and biota (timeseries). The temporal coverage is 1974–2018 for water measurements, 1966–2022 for sediment measurements and 1979–2023 for biota measurements. Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4 ). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/ . The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV ). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).

This visualization product displays the type of litter in percent per net per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. To calculate percentages for each type, formula applied is: Type (%) = (∑number of particles of each type)*100 / (∑number of particles of all type) When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter types are taken from Seadatanet's H01 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H01). Some morphological types of micro-litters may have been sampled but were not defined by the protocole applied during the survey. They are represented as « undefined micro-litter items ». Warnings: - the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area. - since 03/07/2023, the preferred label « Undefined micro-litter items » has been integrated into the H01 library whereas the labels « microplastic items », « non-plastic man-made micro-particles (e.g. glass, metal, tar) » and «non-plastic filaments (natural fibres, rubber) » have been deprecated. When defined, the material or polymer type can be checked directly in the source data.

Rocch, the french "mussel watch", provides chemical data for marine quality management. Once a year, trace metals, organic compounds (chlorinated, PAH, brominated flame retardants, perfluorinated compounds, organotins ...) are analysed in molluscs tissues to check chemical quality according to European Framework Directives and to Regional Seas Convention (OSPAR).