Data available in the French Coast

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.

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).

Analysis of tuna stomach contents

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.

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.

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.

Presence of deep-sea mining exploration zones on the North Atlantic (18°N to 76°N and 36°E to 98°W). These areas correspond to the three polymetallic sulphides exploration contracts on the Mid-Atlantic Ridge, attributed to Poland, France and Russia. Each of the three contract areas is divided into 100 squares of 10km by 10km. Source polygons originated from the International Seabed Authority. The presence (value=1) of deep-sea mining 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.

Distribution of three categories of protected or significant areas on the North Atlantic (18°N to 76°N and 36°E to 98°W). Categories were delineated according to relative levels of protection, from the highest to the lowest: fishing closures implemented by Regional Fisheries Management Organisations (RFMOs) and marine reserves; other MPAs likely to benefit from a lower protection; and Ecologically or Biologically Significant Marine Areas (EBSAs). Source vector data originated from the RFMOs (NAFO, NEAFC and GFCM), the World Database on Protected Areas (WDPA), national MPAs databases (US: NOAA and SAFMC; Canada: Fisheries and Oceans Canada; Norway: Institute of Marine Research) and the CBD website. The relative cover or each protection category on 25km *25km gridsquares was computed. 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.