This dataset contains the outputs of nutrients concentrations 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.

The BioSWOT-Med campaign (Doglioli et al., 2023) was conducted aboard R/V L’Atalante from April 20 to May 15, 2023 in the Northwestern Mediterranean Sea, in the region of the North Balearic Front (NBF) to study interactions between fine-scale oceanic circulation and biogeochemical processes.  Three water masses were sampled across the NBF, northern ('A'), southern ('B'), and frontal ('F'). Each Lagrangian station consisted of a 24-hour sampling period following the displacement of a water parcel (Doglioli et al., 2024). Vertical profiles down to 500 m were collected every 6 hours at 06:00 ('T1'), 12:00 ('T2'), 18:00 ('T3'), and 00:00 ('T4') UTC, for a total of 28 Lagrangian stations: first between April~24-28 (A1, F1, B1), and again between May~4-7 (B2, F2, A2), with a final station in southern waters (B3) on May~12-13. B2 and B3 stations were located inside an anticyclonic eddy. Hydrological profiles were obtained using a Sea-Bird CTD, with data averaged to a 1~m vertical resolution, they include potential temperature (°C), practical salinity, fluorescence-derived chlorophyll-a (µg/L) and oxygen (µmol/kg).  Samples for nitrate + nitrite and phosphate (µM) were collected from Niskin bottles and analyzed onboard within 2-12~hours using a segmented flow analyzer (AAIII HR Seal Analytical) following (Aminot et al., 2007). Quantification limits (QL) were 0.05 µM for nitrate and 0.02 µM for phosphate. Phosphate concentrations at a nanomolar level analyses were performed in the laboratory using a high-sensitivity method combining a 1 m Liquid Waveguide Capillary Cell (LWCC) and an auto-analyzer (Zhang et al. 2002), achieving a detection limit of 0.002µM.  A BGC-Argo float (WMO: 1902605 - Provor CTS4 SUNA) equipped with a CTD and SUNA nitrate sensor was deployed near station B2 and sampled the anticyclonic eddy. To better resolve the photic and nutricline layers, the standard sampling cycle was modified to a 6-hour frequency, reaching depths of 300-400~m. The BGC-Argo float nitrate dataset spans May~2-16 and includes 55~profiles, with a 0.5 µM limit of quantification. It passed through a nitrate calibration procedure against 8 ship-made  profiles at B2 and B3. Data export in NetCDF format - Dataset at the 7 Lagrangian stations (28 vertical profiles for each variable, 4 at each station):  ‘BioSWOT-Med_LS_Date_Time.nc’ (with day, time, longitude and latitude);  ‘BioSWOT-Med_LS_Nutrients.nc’ (with nitrate, phosphate and phosphate at nanomolar level concentrations and depths);  'BioSWOT-Med_LS_CTD.nc' (with temperature in situ, practical salinity, chlorophyll-a and oxygen concentrations, photosynthetically active radiations and depth). - Dataset of the BGC-Argo float including 55 vertical profiles recorded between May 2 and 16:  'BioSWOT-Med_BGC-Argo' (with day and time, longitude, latitude; nitrate concentrations with associated depth; temperature in situ and practical salinity associated depth; chlorophyll-a concentrations with associated predepthssure; and oxygen concentrations with associated depth). Contact list  Aude Joël (aude.joel@mio.osupytheas.fr), Sandra Nunige (sandra.nunige@mio.osupytheas.fr, for ship-made nutrient dataset), Riccardo Martellucci (rmartellucci@ogs.it, for the BGC-Argo float dataset) and Andrea Doglioli (andrea.doglioli@mio.osupytheas.fr, for the BioSWOT-Med cruise). References Aminot, A., & Kérouel, R. 2007. Dosage automatique des nutriments dans les eaux marines: méthodes en flux continu. Méthodes d’analyse en milieu marin. Ifremer. Doglioli, A.M., & Gregori, G. 2023. BioSWOT-Med cruise, RV L’Atalante. doi:10.17600/18002392. Doglioli, A., Grégori, G., D’Ovidio, F., Bosse, P. E., A., Carlotti, F., Lescot, M.,. . . Waggonet, E. (2024). Bioswot med. biological applicati.ons of the satellite surface water and ocean topography in the mediterranean. ref. rapport de campagne. université aix-marseille. (doi:10.13155/100060) Zhang, J.Z., & Chi, J. 2002. Automated analysis of nanomolar concentrations of phosphate in natural waters with liquid waveguide. Environ Sci Technol., 1;36(5), 1048–53. doi: 10.1021/es011094v.  

In the context of contamination of shellfish species by domoic acid produced by microalgal species of the genus Pseudo-nitzschia, we studied the particular case of depuration kinetics of king scallops, Pecten maximus. The study was based on the REPHYTOX dataset (https://doi.org/10.17882/47251) which includes, among others, long-term time series of domoic acid in shellfish species. We selected only the locations along the English Channel and the Atlantic coastline. Contamination events were defined for each locations, depuration rates were estimated fitting an exponential decay model using a non-linear least squares regression. Spatio-temporal variability was assessed as well as correlations to environmental conditions, using REPHY dataset (https://doi.org/10.17882/47248). Finally, scenarios for predictions of either the dynamics of depuration or the domoic acid contamination at a precise date were performed. Four files are available as data used for the study and results : (i) subset of REPHYTOX dataset, (ii) subset of REPHY dataset, used in this study and (iii) contamination event information (i.e., initial and end date of the event, initial domoic acid concentration) and depuration rate estimations, and (iv) predictions of depuration dynamics with different scenarios. Information on each file is detailed in the end user manual and methodology and results are linked to an article in preparation.

This visualization product displays plastic bags 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 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 and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags 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.

This visualization product displays the spatial distribution of 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 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 and year using the following computation: Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Then a grid with 30km x 30km cells was used to calculate the weighted mean of densities in each cell from the formula : Weighted mean (number of items per km²) = ∑ (Distance (km) * Density (number of items per km²)) / ∑ Distance (km) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. More information on data processing and calculation are 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. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

'''DEFINITION''' Important note to users: These data are not to be used for navigation. The data is 100 m resolution and as high quality as possible. It has been produced with state-of-the-art technology and validated to the best of the producer’s ability and where sufficient high-quality data were available. These data could be useful for planning and modelling purposes. The user should independently assess the adequacy of any material, data and/or information of the product before relying upon it. Neither Mercator Ocean International/Copernicus Marine Service nor the data originators are liable for any negative consequences following direct or indirect use of the product information, services, data products and/or data. Product overview: This is a satellite derived bathymetry product covering the global coastal area (where data retrieval is possible), with 100 m resolution, based on Sentinel-2. This global coastal product has been developed based on 3 methodologies: Intertidal Satellite-Derived Bathymetry; Physics-based optical Satellite-Derived Bathymetry from RTE inversion; and Wave Kinematics Satellite-Derived Bathymetry from wave dispersion. There is one dataset for each of the methods (including a quality index based on uncertainty) and an additional one where the three datasets were merged (also includes a quality index). Using their expertise and special techniques the consortium tried to achieve an optimal balance between coverage and data quality. '''DOI (product):''' https://doi.org/10.48670/mds-00364

This visualization product displays the spatial distribution of the sampling effort (based on the start position of the sampling tow) over the six-years' period 2017-2022 from other specific 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 samplings carried out according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. The spatial distribution was then determined by calculating the number of times each cell was sampled during the period 2017-2022, only taking into account the start position of the tows. The corresponding total distance (kms) sampled in each cell is also provided in the attribute table. Information on data processing and calculation are 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 National Oceanographic Data Centre (NODC) for this area. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

Worldwide, shellfish aquaculture and fisheries in coastal ecosystems represent crucial activities for human feeding. But these biological productions are under the pressure of climate variability and global change. Anticipating the biological processes affected by climate hazards remains a vital objective for species conservation strategies and human activities that rely on. Within marine species, filter feeders like oysters are real key species in coastal ecosystems due to their economic and societal value (fishing and aquaculture) but also due to their ecological importance. Indeed oysters populations in good health play the role of ecosystem engineers that can give many ecosystem services at several scales: building reef habitats that contribute to biodiversity, benthic-pelagic coupling and phytoplankton bloom control through water filtration, living shorelines against coastal erosion… The Pacific oyster, Crassostrea gigas (Thunberg, 1793), which is currently widespread worldwide, was introduced into the Atlantic European coasts at the end of the 19th century for shellfish culture purposes and becomes the main marine species farmed in France (around 100 000 tons) despite severe mortalities crisis. But in the same time and because of warming, natural oysters beds has spread significantly along the French coast and are supposed to have reach approximately 500 000 tons. In that context, Pacific oyster populations (natural and cultivated) in France are the subjects of many scientific projects. Among them, a specific long-term biological monitoring focuses on the reproduction of these populations at a national scale: the VELYGER national program. With more than 8 years of weekly data at many stations in France, this field-monitoring program offers a valuable dataset for studying processes underpinning reproduction cycle of this key-species in relation to environmental parameters, water quality and climate change.   Database content: Larval concentration (number of individuals per 1.5 m3) monitored, since 2008, at several stations in six bays of the French coast (from south to north): Thau Lagoon and bays of Arcachon, Marennes Oléron, Bourgneuf, Vilaine and Brest (see map below).   Methods used to monitor larval concentration: An important volume of seawater (1.5 m3) is pumped twice a week throughout the spawning season (june-september), at one meter below the surface at high tide (+/- 2h) in several sites within each VELYGER ecosystem. Water is filtered trough plankton net fitted with 40 µm mesh. After a proper rinsing of the net, the retained material is transferred into a polyethylene bottle (1 liter) and fixed with alcohol. At laboratory, sample is then gently filtered and rinse again and transferred into eprouvette. Two sub-samples of 1 mL are then taken using a pipette and examined on a graticule slide for microscope. The microscopic examination is made with a conventional binocular optical microscope with micrometer stage at a magnification of 10 X (or above). During the counting, a special care is necessary as larvae of other bivalves are also collected and confusion is possible. Larvae of C. gigas are also classified into four stage of development: - Stage I = D-shaped straight hinge larvae (shell length <105 µm) - Stage II = Early umbo evolved larvae (shell length between 105 and 150 µm) - Stage III = Medium umbo larvae (shell length between 150 and 235 µm) - Stage IV*= Large umbo eyed pediveliger larvae (shell length > 235 µm) * Larvae that are very closed to settle are sometimes identified into a separated 5th stage, but generally this stage is included in stage IV.   Illustrations: Location of the different Velyger sites along the French coast. From south to north: Thau Lagoon and bays of Arcachon, Marennes Oléron, Bourgneuf, Vilaine and Brest.   Legend: Pacific Oyster Larvae (left side) and Natural oyster bed (right side). Photos : © S. Pouvreau/Ifremer

This visualization product displays the spatial distribution of the sampling effort over the six-years' period 2017-2022. 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. The spatial distribution was determined by calculating the number of times each cell was sampled during the period 2017-2022. The corresponding total distance (kms) sampled in each cell is also provided in the attribute table. Information on data processing and calculation are 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. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.