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GeoTIFF

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From 1 - 10 / 151
  • This raster dataset represents the input of microbial pathogens along the European coastlines. The pressure layer was created using three different datasets rasterized using the EEA 10 km grid: urban agglomerations reported under the Urban Waste Water Treatment Directive (2017), EMODnet dataset of ports lying on the sea coast together with passenger information (annual average 2006-2016) and Intestinal enterococci and Escherichia coli data at bathing sites as measured under the Bathing Water Directive reporting obligation (average 2008-2016). All three datasets were then classified into four classes, aggregated and classified again (quantile classes between 0 and 1, with the latter being the highest pathogen pressure). 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.

  • 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.

  • Classification of the seabed in the Atlantic Ocean into broad-scale benthic habitats employing a non-hierarchical top-down clustering approach aimed at informing Marine Spatial Planning. This work was performed at the University of Plymouth in 2021 with data provided by a wide group of partners representing the nations surrounding the Atlantic Ocean. It classifies continuous environmental data into discrete classes that can be compared to observed biogeographical patterns at various scales. It has 3 levels of classification. The numbers in the raster layer correspond to individual classes. Description of these classes is given in McQuaid, K.A. et al. (2023).

  • This raster dataset presents the number of different hydrographical pressures per grid cell along the European coastlines. Hydrographical pressures are human activities that cause changes in hydrological conditions, i.e. changes to freshwater input, salinity, seawater flows, waves, currents, and temperature. Examples of such activities include riverine or coastal dams, offshore infrastructure, and outflows from power plants. The layer has been created using the Water Framework Directive (WFD) reported data on hydrographical pressures joined with the water body polygon features for the reference year 2016. The dataset was then rasterized into the EEA 10 km grid, and the cell values assigned with the number of different hydrographical pressures in the area covered by the cell. 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.

  • This raster dataset represents the physical loss of the seabed in the European seas. Physical habitat loss is an extreme pressure on the marine ecosystem which was defined to include all impacts on the seabed which take more than 12 years to recover, a time span influencing even long living marine mammals and seabirds. Habitat is lost if its substrate, morphology or topography is permanently altered. The dataset is an aggregation of several different human activities that cause physical loss in the seabed: dredging and dumping of dredged material, oil and gas rigs, offshore installations, ports, sand and gravel extraction and windfarms. The resulting dataset is a raster (10km grid cell) derived from EMODnet, MED-IAMER and 4C Offshore datasets and with temporal reference from 2012 to 2017. Higher values mean more loss causing activity in the area. Due to its resolution, loss causing activity in a cell does not usually mean that all the seabed habitat in the area is lost. 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.

  • This raster dataset represents the probability of occurrence of whales in the Europe Seas, where the species included are: Blue whale, Sei whale, Humpback whale, Sperm whale, Fin whale and Northern right whale. The northern right whale model only describes the range of the western population of this species, since the eastern population is probably almost extinct. Thus, the northern right whale model only partly overlaps with the EEA area on interest. This dataset is based on AquaMaps distribution maps (version 10/2019). The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (EMSA-EEA report, 2021: https://www.eea.europa.eu/publications/maritime-transport).

  • The raster dataset (1ºx1º) shows the projected change in relative sea level (in metres) in 2081-2100 compared to 1986-2005 for the medium-low emission scenario RCP4.5, based on an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Projections consider land movement due to glacial isostatic adjustment but not land subsidence due to human activities. No projections are available for the Black Sea. The dataset has been used as a source for an earlier version of the EEA indicator “Global and European Sea Level”: https://www.eea.europa.eu/data-and-maps/indicators/sea-level-rise-5/assessment.

  • Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Acanella arbuscula assemblage in the Celtic Sea. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.