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GeoTIFF

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  • The raster dataset represents the intensity of species disturbance due to human presence along European coastlines. The dataset was created by combining the coastal urbanisation layer derived from Corine Land Cover 2012 (with the percentage of urbanised coastline per EEA 10 km grid cell) and the population density layer based on EUROSTAT NUTS 2016 data (with the population density in the NUTS 3 region corresponding to the coastal EEA 10 km grid cell). The dataset does not cover southern and western Mediterranean Sea, northern Black Sea and northernmost Atlantic Ocean. The dataset was prepared for the combined effect index produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

  • Maps of seasonal p90 (percentile 90) of Chla on the North Atlantic basin for the past ten years (2005-2014) using the Global Copernicus chla level 4 (L4) products (resolution of 4 km). Method as Gohin Francis, Saulquin Bertrand, Bryere Philippe (2010) Atlas de la Température, de la concentration en Chlorophylle et de la Turbidité de surface du plateau continental français et de ses abords de l’Ouest européen. Ifremer. http://archimer.ifremer.fr/doc/00057/16840/

  • This product is a map of the uncertainty of available digital bathymetry measurements for the North Atlantic Ocean. This is done for a spatial resolution feasible for this large area (25km x 25km). It is designed to assess the quality of the bathymetry readings with a view to supporting assessments of future need. The product is formulated through a number of characteristics of the data including age of measurement and slope.

  • This data product selects sample areas of digital bathymetry, chosen for their relevance to marine activities and data sources alternative to GEBCO. The approach for building the digital map of water depth is to use GEBCO as a baseline and look at a set of sample areas where GEBCO could be improved upon. Sample areas have also been selected to be representative of each continent bordering the Atlantic and expected future requirements. Data sources include GEBCO, EMODNET, USGS and CHS.

  • This raster dataset represents the input of continuous anthropogenic sound in the European Seas. Continuous anthropogenic underwater noise is found in the entire European marine area and is mainly produced by maritime traffic. As no thresholds for pressure have been agreed yet, even areas of low or infrequent maritime traffic are included as pressures. This dataset uses shipping density as a representation of distribution of continuous underwater noise. This dataset is based on a truncated version of the EMODnet (Automatic Identification System) AIS based vessel density dataset for 2017 (all ships, year average). The vessel density was rescaled from a 1 km to 10 km resolution (mean values) using the EEA 10 km grid. The dataset has been transformed to a logarithmic scale (ln1). This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

  • The raster dataset represents bycatch fishing intensity (kilowatt per fishing hour) from bottom touching mobile gears in the European seas. The dataset has been derived from Automatic Identification System (AIS) based demersal fishing intensity data received from the European Commission’s Joint Research Centre - Independent experts of the Scientific, Technical and Economic Committee for Fisheries (JRC STECF) as well as Vessel Monitoring System (VMS) and logbook based demersal fishing intensity data downloaded from from OSPAR and HELCOM Commissions. The temporal extent varies between the data sources (between 2014 and 2017). OSPAR and HELCOM data superseded the JRC STECF data where they overlapped spatially. The cell values have been transformed into a logarithmic scale (ln1). This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

  • 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.

  • This product is a map of the uncertainty of available digital bathymetry measurements for the North Atlantic Ocean. This is done for a spatial resolution feasible for this large area (25km x 25km). It is designed to assess the quality of the bathymetry readings with a view to supporting assessments of future need. The product is formulated through a number of characteristics of the data including age of measurement and slope.

  • Maps of potential biomass catches (tons/year) per surface unit (0.25º latitude x 0.25º longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling 490:110632 ( https://doi.org/10.1016/j.ecolmodel.2024.110632 ), for more details.