Data available in the French Coast

Analysis of tuna stomach contents

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.

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.

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 predicted suitable habitat for six cold-water-coral, six deep-water fish and one sponge species, on the North Atlantic (18°N to 76°N and 36°E to 98°W). For each species, predicted habitat distribution was obtained for present-day conditions (1951-2000) and for the future climate refugias, i.e. the areas that were predicted as suitable both for present-day and forecasted future (2081-2010) conditions. The dataset gathers 26 raster layers created on the same grid of 25km * 25km resolution, downgraded from source layers (3km *3km resolution) that were created within the work package 3 of EU ATLAS project. The presence (value=1) of climate refugia and the relative cover (value ranging from 0 to 1) of present-day suitable habitat was extracted in 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.

Planning units layers used for ATLAS EU prioritization scenarios on the North Atlantic (18°N to 76°N and 36°E to 98°W). This raster layer is designed on a grid of 25km * 25km resolution, that served to extract all the spatial data used prioritization. The 31 518 planning units (cells with value) corresponded to areas containing depths shallower or equal to 3500m, even if they could also contain deeper areas locally. For connectivity scenarios, only the planning units matching with the extent of available connectivity data were selected. One layer allocates planning units to the 13 geographical provinces (values ranging from 1 to 13) created for the purpose of prioritization. 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.

This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic, in the framework of the ATLAS H2020 project. This approach aimed to inform Marine Spatial Planning and conservation initiatives for the deep sea of the North Atlantic, by identifying conservation priority areas for the Vulnerable Marine Ecosystems (VMEs) and deep fish species and discussing the efficiency of the current spatial management context relatively to conservation stakes. This publication provides (1) the links to spatial datasets used as an input, (2) the R scripts used to run the final conservation scenarios together with associated table of targets and connectivity matrix, that can be run on the input data, and (3) the outputs of the final scenarios constructed and computed for ATLAS. Produced by IFREMER. This output reflects the authors’ views and the European Union is not responsible for any use that may be made of the information it contains. Please note that you use these data at your own risk. No warranty is expressed or implied and no liability is accepted for any inconveniences or damages that may ensue from their use.

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.