These maps represent the monthly probability of being a seabass spawning area for each month of the spawning season (January to March), and the mean probability of being a seabass spawning area over all spawning months in the Bay of Biscay. These probability maps were calculated by performing a geostatistical analysis of fishing data from geolocated vessels, and have a spatial resolution of 3 by 3 nautical miles.

Analysis of tuna stomach contents

Raw multibeam from acoustic echosounding of the water column and archived at SISMER. These data have been acquired: - by oceanographic vessels and national equipment managed by the French Oceanographic Fleet (FOF) - by foreign or national oceanographic vessels in collaboration with Ifremer

A ten-year numerical hindcast of hydrodynamics, hydrology and sediment dynamics in the Loire Estuary (France), produced by coupling the hydrodynamics model MARS3D with the sediment dynamics module MUSTANG and the wave spectral model WAVEWATCH III®. Numerical simulations are based on the same model chain used in the Seine Estuary (curviseine) and the Gironde Estuary (curvigironde).

Daily and monthly surface wind analyses are determined as gridded wind products over global oceans, with regular spatial resolution of 0.25° in latitude and longitude. They are estimated from scatterometer wind retrievals (L2b data). According to the scatterometer sampling scheme, the objective method allowing the determination of regular in space surface wind fields uses remotely sensed observations as well as ECMWF analyses. The calculation of daily estimates uses ascending as well as descending available and valid retrievals. The objective method aims to provide daily-averaged gridded wind speed, zonal component, meridional component, wind stress and the corresponding components at global scale. The error associated to each parameter, related to the sampling impact and wind space and time variability, is provided too. Monthly wind analyses are calculated from daily estimates.

Data available in the French Coast

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 unequivocal Vulnerable Marine Ecosystems (VMEs) and VME likelihood based on indicator taxa records, on the North Atlantic (18°N to 76°N and 36°E to 98°W). Several datasets, originating from public databases, literature review and data call to ATLAS partners, were gathered to compute the presence of unequivocal VME habitats in 25km * 25 km cells for the ATLAS work package 3. One layer displays the unequivocal VMEs (value=4) and the assigned high (value=3), medium (value=2) or low (value=1) likelihood of gridsquares to host VMEs, indexed on indicator taxa records from public databases with the method detailed in Morato et al (2018). The second displays the confidence associated to the VME likelihood score, indexed on data quality as detailed in Morato et al (2018) (values for unequivocal VMEs thus 100% confidence=4; high confidence=3; medium confidence=2; low confidence=1). 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.

Global wave hindcast (1961-2020) at 1° resolution using CMIP6 wind and sea-ice forcings for ALL (historical), GHG (historical greenhouse-gas-only), AER (historical Anthropogenic-aerosol-only), NAT (historical natural only) scenario.

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.