This visualization product displays the location of all the surveys present in the EMODnet marine litter database (MLDB). The different fishing gears used are represented by different colors. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. Unlike other EMODnet seafloor litter products, all trawls surveyed since 2006 are included in this map even if the wingspread and/or the distance are unknown. Only surveys with an unknown number of items were excluded from this product. More information on data processing and calculation are detailed in the attached document. 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 Marine Litter Database for this area.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification, contaminants and litter. The chosen parameters are relevant for the Marine Strategy Framework Directive (MSFD), in particular for descriptors 5, 8, 9 and 10. The dataset contains standardized, harmonized and validated data collections from beach litter (monitoring and other sources). Datasets concerning beach and seafloor litter data are loaded in a central database after a semi-automated validation phase. Once loaded, a data assessment is performed in order to check data consistency and potential errors are corrected thanks to a feedback loop with data originators. For beach litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on beach litter, including monitoring data, data from cleaning surveys and data from research. A relevant part of the monitoring data has been considered for assessment purposes by the European institutions and therefore is tagged as MSFD_monitoring. EMODnet beach litter data and databases are hosted and maintained by 'Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)' from Italy. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://nodc.ogs.it/marinelitter/vocab The harmonized datasets can be downloaded as EMODnet Beach litter data format Version 7.0, which is a spreadsheet file composed of 4 sheets: beach metadata, survey metadata, animals and litter. Local_CDI field in the survey metadata sheet allows to retrieve the original data.

This dataset contains the dynamical 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 cigarette related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations without UNEP-MARLIN data. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of cigarette related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata); - Exclusion of surveys without associated length; - Exclusion of surveys referring to the UNEP-MARLIN list: the UNEP-MARLIN protocol differs from the other types of monitoring in that cigarette butts are surveyed in a 10m square. To avoid comparing abundances from very different protocols, the choice has been made to distinguish in two maps the cigarette related items results associated with the UNEP-MARLIN list from the others; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of cigarette related items of the survey (normalized by 100 m) = Number of cigarette related items of the survey x (100 / survey length) Then, this normalized number of cigarette related items is summed to obtain the total normalized number of cigarette related items for each survey. Finally, the median abundance of cigarette related items for each beach and year is calculated from these normalized abundances of cigarette related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account cigarette related items from other sources data (excluding UNEP-MARLIN protocol) for all years. More information is available in the attached documents. 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 Marine Litter Database for this area.

The SOMLIT-Antioche observation station, located at 5 nautical miles from Chef de Baie harbor (La Rochelle) is part of the French monitoring network SOMLIT (https://www.somlit.fr/), accredited by the INSU-CNRS as a national Earth Science Observatory (Service National d’Observation : SNO), which comprises 12 observation stations distributed throughout France in coastal locations. It aims to detect long-term changes  of these ecosystems under both natural and anthropogenic forcings. SOMLIT is part of the national research infrastructure for coastal ocean observation ILICO (https://www.ir-ilico.fr/?PagePrincipale&lang=en). The SOMLIT-Antioche station (46.0842 °N, 1.30833 °W) is located in the north-eastern part of the Bay of Biscay, halfway between the islands of Ré and Oléron, at the centre of what is commonly known as the Pertuis Charentais area, which correspond to a semi-enclosed shallow basin and includes four islands (Ré, Oléron, Aix and Madame) and three Pertuis (i.e., detroit) (Breton, Antioche and Maumusson). This 40m-deep site, with muddy to sandy marine bottoms, is submitted to a macro-tidal regime and is largely open to the prevailing westerly swells. It remains under a dominant oceanic/neritic influence, even though its winter/spring hydrological context is influenced by the diluted plumes of the Charente, Gironde and Loire rivers, but not by those of too small estuaries (Lay, Seudre and Sèvre Niortaise). SOMLIT-Antioche hydrological monitoring has been carried out by the LIENSs/OASU laboratory on a fortnightly basis since June 2011. Surface water samples are collected  at high-tide during intermediate tides (70 ± 10 in SHOM units) on board the research  vessel ‘L’Estran’ owned by La Rochelle University. Samples are analyzed for more than 16 core parameters: temperature, salinity, dissolved oxygen, pH, ammonia, nitrates, nitrites, phosphates, silicates, suspended matter, particulate organic carbone, particulate organic nitrogen, chlorophyll, delta15N, delta13C; pico- and nano- plankton. Measurements are carried out in accordance with the ISO/IEC 17025:2017 standard. Simultaneous monitoring of the micro-phytoplankton community (since 2013, SNO PHYTOBS: https://www.phytobs.fr/en) and monitoring of prokaryotic communities (Bacteria and Archaea) are also carried out on a monthly basis. Since 2019, seasonal observations of benthic invertebrate communities (SNO BenthObs : https://www.benthobs.fr/) have also been carried out. This monitoring is complementary to that carried out at hydrological stations in the pre-existing REPHY and DCE networks, some of which are located near marine farming areas (oyster and mussel farms).

Moving 6-year analysis of Water body silicate in the NorthEast Atlantic for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1950/1955 until 2019/2024. Observation data span from 1950 to 2024. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 300km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.loglin) was applied to the data prior to the analysis. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

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.

'''Short description:''' Near-Real-Time multi-mission global satellite-based spectral integral parameters. Only valid data are used, based on the L3 corresponding products. Included wave parameters are partition significant wave height, partition peak period and partition peak or principal direction. Those parameters are propagated in space and time at a 3-hour timestep and on a regular space grid, providing information of the swell propagation characteristics, from source to land. The output products corresponds to one file per month gathering all the swell systems at a global scale. This product is processed by the WAVE-TAC multi-mission Sentinel-1- SAR and CFOSAT/SWIM data processing system to serve in near-real time the main operational oceanography and climate forecasting centers in Europe and worldwide. It processes data from the following missions: SAR (Sentinel-1C) and CFOSAT/SWIM. All the spectral parameter measurements are optimally interpolated using swell observations belonging to the same swell field. The spectral data processing system produces wave integral parameters by partition (partition significant wave height, partition peak period and partition peak or principal direction) and the associated standard deviation and density of propagated observations. '''DOI (product) :''' https://doi.org/10.48670/moi-00175

This visualization product displays fishing related items density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. In cases where the wingspread and/or the number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities were calculated on each trawl using the following computation: Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. 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 Marine Litter Database for this area.