Magnetic data of the ridge axis of Mohn's ridge (NE Atlantic) in order to study the mecanisms of the oceanic accretion.

Gravimetry data of the ridge axis of Mohn's ridge (NE Atlantic) in order to study the mecanisms of the oceanic accretion.

Magnetic data of the ridge axis of Mohn's ridge (NE Atlantic) in order to study the mecanisms of the oceanic accretion.

Agencies education in marine trades geolocalized to municipality. This information was produced as part of the initial assessment of the MSFD. Referent expert Sophie Devergie. WARNING: the spatial structure of the data must be improved because it contains superpositions of points (several training agencies per commune). Here the tool "Representation" of ArcGIS was used to facilitate the mapping of the data that does not meet basic standards of the topology. Ultimately, the quality of the data can be improved by refining the address geolocation.

Shellfish farming areas can have different meanings. Sometimes their identification is prescribed and used for health classification of production areas. In Euroshell project, the choice was made to map the production areas whose identification makes sense for both scientists and professionals. A limited number of areas is then showed, often corresponding to a hydrographic reality. Indeed, the shellfish industry is mainly installed in estuaries, river mouths, bays, fjords, estuaries or lagoons. This map shows the shellfish production sites, which include several areas. Some information is given on species produced, the number of companies and / or concessions and / or producers, the approximate amount of production.

Distribution of three geomorphologic features (fracture zones, canyons, and seamounts) on the North Atlantic (18°N to 76°N and 36°E to 98°W). Source vector data originated from the GEBCO Gazetteer of Undersea Features Names for fractures, Harris & Whiteway (2011) for canyons, and Yesson et al. (2011) for seamounts. The presence (value=1) of fracture zones or seamounts and the total length of canyons (in km, independently for shelf-incising or blind canyons) was extracted in 25km * 25km gridsquares. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.

Localization of professional organizations linked to shellfish farming within Euroshell project

Distribution of three bathymetric terrain variables (depth, slope and Bathymetric Position Index) on the North Atlantic (18°N to 76°N and 36°E to 98°W). This dataset originated from three source layers (3km * 3km resolution) computed within the work package 3 of EU ATLAS project, and based on the EMODnet Digital Bathymetry portal and the General Bathymetric Chart of the Oceans (GEBCO). From these source layers, the mean depth (m), slope (degree) and BPI (no unit) were calculated for each 25km * 25km gridsquare. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.

Distribution of catch from deep-sea impacting fishing on the North Atlantic (18°N to 76°N and 36°E to 98°W), for the period 2010-2015. The average of yearly fishing catch for the period 2010-2015 is displayed as an index on the ATLAS grid of 25km * 25km resolution. Source data originated from the Global Fisheries Landings V4.0 database. The dataset was filtered to select only the fishing gears that have an impact on large areas of the seafloor (dredges, bottom trawls, and Danish seines). Within each cell, all remaining catch records were summed to get the total catch rate of the considered year. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.