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  • Here, we provide plankton image data that was sorted with the web applications EcoTaxa and MorphoCluster. The data set was used for image classification tasks as described in Schröder et. al (in preparation) and does not include any geospatial or temporal meta-data. Plankton was imaged using the Underwater Vision Profiler 5 (Picheral et al. 2010) in various regions of the world's oceans between 2012-10-24 and 2017-08-08. This data publication consists of an archive containing  "training.csv" (list of 392k training images for classification, validated using EcoTaxa), "validation.csv" (list of 196k validation images for classification, validated using EcoTaxa), "unlabeld.csv" (list of 1M unlabeled images), "morphocluster.csv" (1.2M objects validated using MorphoCluster, a subset of "unlabeled.csv" and "validation.csv") and the image files themselves. The CSV files each contain the columns "object_id" (a unique ID), "image_fn" (the relative filename), and "label" (the assigned name). The training and validation sets were sorted into 65 classes using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). This data shows a severe class imbalance; the 10% most populated classes contain more than 80% of the objects and the class sizes span four orders of magnitude. The validation set and a set of additional 1M unlabeled images were sorted during the first trial of MorphoCluster (https://github.com/morphocluster). The images in this data set were sampled during RV Meteor cruises M92, M93, M96, M97, M98, M105, M106, M107, M108, M116, M119, M121, M130, M131, M135, M136, M137 and M138, during RV Maria S Merian cruises MSM22, MSM23, MSM40 and MSM49, during the RV Polarstern cruise PS88b and during the FLUXES1 experiment with RV Sarmiento de Gamboa. The following people have contributed to the sorting of the image data on EcoTaxa: Rainer Kiko, Tristan Biard, Benjamin Blanc, Svenja Christiansen, Justine Courboules, Charlotte Eich, Jannik Faustmann, Christine Gawinski, Augustin Lafond, Aakash Panchal, Marc Picheral, Akanksha Singh and Helena Hauss In Schröder et al. (in preparation), the training set serves as a source for knowledge transfer in the training of the feature extractor. The classification using MorphoCluster was conducted by Rainer Kiko. Used labels are operational and not yet matched to respective EcoTaxa classes.

  • The network was initiated by IFREMER from 1993 to 2009 (under the acronym REMORA) to study the rearing performance of the Pacific oyster Crassostrea gigas at a national scale. To do so, the network monitored annually the mortality and growth of standardized batches of 18-month-old oysters. Starting in 1995, the monitoring of the rearing performance of 6-month-old oyster spat was integrated into this network. These sentinel batches were distributed simultaneously each year on 43 sites and were monitored quarterly. These sites were distributed over the main French oyster farming areas and allowed a national coverage of the multiannual evolution of oyster farming performances. Most of the sites were located on the foreshore at comparable levels of immersion. Field studies were carried out by the "Laboratoires Environnement Ressources" (LER) for the sites included in their geographical area of investigation. Following the increase in spat mortality in 2008, the network evolved in 2009 (under the acronym RESCO). From this date, the network selected 13 sites among the 43 sites previously monitored in order to increase the frequency of visits (twice a month) and the number of sentinel batches. More precisely, sentinel batches of oysters corresponding to different origins (wild or hatchery, diploid or triploid) and to two rearing age classes (spat or 18-month-old adults) were selected. The monitoring of environmental variables (temperature, salinity) associated with the 13 sites was also implemented. The actions of the network have thus contributed to disentangle the biotic and abiotic parameters involved in mortality phenomena, taking into account the different compartments (environment / host / infectious agents) likely to interact with the evolution of oyster rearing performance. Finally, since 2015, the network has merged the RESCO and VELYGER networks to adopt the acronym ECOSCOPA. The general objective of this current network is to analyze the causes of spatio-temporal variability of the main life traits (Larval stage - Recruitment - Reproduction - Growth - Survival - Cytogenetic abnormalities) of the cupped oyster in France and to follow their evolution on the long term in the context of climate change. To do this, the network proposes a regular spatio-temporal monitoring of the major proxies of the life cycle of the oyster, organized in three major thematic groups: (1) proxies related to growth, physiological tolerance and survival of experimental sentinel populations over 3 age classes: (2) proxies related to reproduction, larval phase and recruitment of the species throughout its natural range in France, and: (3) proxies related to environmental parameters essential to the species (weather conditions, temperature, salinity, pH, turbidity, chlorophyll a and phytoplankton) at daily or sub-hourly frequencies. Working in a geographical network associating several laboratories, ECOSCOPA provide these monitoring within 8 sites selected among the previous ones to ensure the continuity of the data acquisition. Today, these 8 sites are considered as ecosystems of common interest, contrasted, namely : - The Thau lagoon - The Arcachon basin - The Marennes Oléron basin - The Bourgneuf Bay - The bay of Vilaine - The bay of Brest - The bay of Mont Saint Michel - The bay of Veys The ECOSCOPA network is therefore one of the relevant monitoring tools on a national scale, allowing to objectively measure through different proxies the general state of health of cultivated and wild oyster populations, and this for the different sensitive phases of their life cycle. This network aims at allowing a better evaluation, on the long term, of the biological risks incurred by the sector but also by the ecosystems, in particular under the increasing constraint of climatic and anthropic changes. Figure : Sites monitored by the ECOSCOPA network  

  • The dataset on offshore active licences for Oil and Gas exploitation and exploration in the EU was created in 2014 by Cogea for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by several EU and non-EU sources. It is updated every year, and is available for viewing and download on EMODnet - Human Activities web portal (www.emodnet-humanactivities.eu). It contains polygons representing active offshore licenced areas in the following countries: Croatia, Cyprus, Denmark, France, Germany, Ireland, Italy, Malta, Netherlands, Norway, Poland, Spain and United Kingdom. Where available each polygon has the following attributes: country, code, name, type (exploitation, exploration, exploitation and exploration, other, N/A), licensing round (it includes also pending applications in France and Spain), area (square km), area info (it indicates if the area value is original from the source or has been calculated), starting year, ending year, operator or administrator. Compared with the previous release, 'Exploitation, exploration' new type of licence has been added. Italy's exploration licences are all temporarily suspended.

  • Map of seasonal averages of dissolved oxygen indicator (mg/l) for eutrophication for the past 10 years (2005-2014) in the Atlantic basin. It will be generated using in situ measurements of the different parameteres required to assess the dissolved oxygen indicator and the OSPAR Convention Common procedure methodology (OSPAR 2013, Common Procedure for the Identification of the Eutrophication Status of the OSPAR Maritime Area. Agreement 2013-08. 67 pp)

  • to deliver maps showing the extent of the trawling fishing grounds for identifying the changes in level of disturbance over the past ten years and identifying the gaps of fishing vessels’ tracking systems in the Mediterranean Sea

  • The European Union’s Copernicus-funded TRUSTED project (Towards Fiducial Reference Measurements of Sea-Surface Temperature by European Drifters) has deployed over 100 state of the art drifting buoys for improved validation of Sea Surface Temperature (SST) from the Sentinel-3 Sea and Land Surface Temperature Radiometers (SLSTR). These buoys are manufactured by NKE. The TRUSTED drifting buoys data and metadata are distributed in qualtity control NetCDF files, as a subset of DBCP drifting buoys GDAC (Global Data Assembly Centre). Coriolis DAC  (Data Assembly Centre) routinely collects, decodes, quality controls, preserves and distributes data and metadata as NetCDF-CF files. The TRUSTED buoys have specific features managed by Coriolis DAC python data processing chain: a high resolution temperature sensor in addition to the classic drifting buoy temperature sensor. The high sampling and high resolution observations are distributed in specific variables TEMP_HR, TEMP_HR_SPOT, TEMP_HR_XX (XX is the percentile sample).  

  • Annual time series of Total Nitrogen/Nitrates [mg/l] from in situ and model data

  • The PHYTOBS-Network dataset includes long-term time series on marine microphytoplankton, since 1987, along the whole French metropolitan coast. Microphytoplankton data cover microscopic taxonomic identifications and counts. The whole dataset is available, it includes 25 sampling locations. PHYTOBS-Network studies microphytoplankton diversity in the hydrological context along French coasts under gradients of anthropogenic pressures. PHYTOBS-Network allows to analyse the responses of phytoplankton communities to environmental changes, to assess the quality of the coastal environment through indicators, to define ecological niches, to detect variations in bloom phenology, and to support any scientific question by providing data. The PHYTOBS-Network provides the scientific community and stakeholders with validated and qualified data, in order to improve knowledge regarding biomass, abundance and composition of marine microphytoplankton in coastal and lagoon waters in their hydrological context. PHYTOBS-Network originates of two networks. The historical REPHY (French Observation and Monitoring program for Phytoplankton and Hydrology in coastal waters) supported by Ifremer since 1984 and the SOMLIT (Service d'observation en milieu littoral) supported by INSU-CNRS since 1995. The monitoring has started in 1987 on some sites and later in others. Hydrological data are provided by REPHY or SOMLIT network as a function of site locations.

  • This dataset provides a global Look-Up Table (LUT) of physiological ratios for the real-time adjustment of chlorophyll-a fluorescence measured by biogeochemical Argo (BGC-Argo) profiling floats. The physiological ratios aim to account for the global variability in the relationship between fluorescence and chlorophyll-a concentration, as influenced by phytoplankton physiology. The LUT was developed using two different gap-filled observational Argo-based products (SOCA machine learning-based methodology ; Sauzède et al., 2016; Sauzède et al., 2024). The first product provides gap-filled chlorophyll-a data derived from fluorescence corrected for dark signal and non-photochemical quenching (NPQ) following Schmechtig et al. (2023), while the second product provides chlorophyll-a concentrations derived from light attenuation. The latter is based on the downward irradiance at 490 nm (ED490) derived from the SOCA-light method (Renosh et al., 2023). From this, the diffuse attenuation coefficient (KD490) is computed, which is subsequently used to estimate the chlorophyll-a concentration through the bio-optical relationships described by Morel et al. (2007). These two products, based on fluorescence and radiometry, enable the derivation of spatially varying correction factors, or physiological ratios. These ratios provide a validated grounded framework for adjusting real-time fluorescence observations from OneArgo floats into chlorophyll-a concentrations. The LUT is distributed in NetCDF format and is provided on a regular 1°×1° latitude–longitude grid covering the global ocean. Each grid cell contains the temporal mean, averaged over the water column (from the surface to 1.5 times the euphotic depth), of the physiological ratio. The file also includes metadata describing variable definitions, units, and other relevant information. Variables included: - physiological_ratio — fluorescence-to-radiometry-based chlorophyll correction factor (dimensionless) - physiological_ratio_sd — temporal standard deviation (over the twelve months) of the fluorescence-to-radiometry-based chlorophyll correction factor (dimensionless) - lat, lon — spatial coordinates (degrees north/east) - Global attributes — dataset description, reference citation, and contact information

  • The DTM is a compilation of multibeam echosounder surveys acquired in 2013. The resolution is 1/64 arc-minutes (~30m). Surveys are located on the Capbreton Submarine Canyon (France) with depths from -4.7m to -344.9m. Depths are referenced to the Lowest Astronomical Tide and the coordinates are expressed into the WGS84 reference frame. The surveys which compose the DTM are S201306500-09 and S201306500-11. Data and metadata associated to these surveys are available on the website http://diffusion.shom.fr/pro/lots-bathy.html. The DTM is not to be used for navigation.