The dataset represents the introduction of non-indigenous species in European seas. Non-indigenous species are species that have been spread as a result of human activities to areas where they do not belong naturally. The main concern are the invasive species, which are defined as causing a significant negative impact on biodiversity as well as serious economic and social consequences. The dataset has been prepared first by individually mapping each aquatic invasive species that had a distinctive distribution area, which had been provided by several non-indigenous species online databases. The distribution of the species were then resampled into the EEA 10 km grid and summed together, showing the number of non-indigenous species per grid cell. The temporal reference of the dataset covers the last 30 years (1989 - 2018). 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 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.

Species distribution models (Maxent) predicting the distribution of two Vulnerable Marine Ecosystems (VME): the reef-forming Scleractinian coral Desmophyllum pertusum and the aggregations forming Hexactinellid sponge Pheronema carpenteri. Both of these species are VME indicator taxa and form habitat that enhance deep-sea diversity (Ross and Howell, 2013). Maps of the likely distribution of the habitat formed by these two species will enable efficient Marine Spatial planning to facilitate their conservation. This work was performed at the University of Plymouth in 2021. A GIS layer is provided for each species.

Classification of the Atlantic Ocean seabed into broad-scale benthic habitats employing a 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. For ease of use, a layer is provided for each level. Level 1 has 4 classes. Level 2 has 15 classes nested within level 1. Layers indices are 2 digits (1[level1 class index]1[level 2 class index]). Level 3 has 157 classes nested within level 2 and class names have 4 digits (1digit[level1 class index]1[level 2 class index]2[level 3 class index]). Note that the classification was performed for the whole world and thus it has more classes than in the presented layer.

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.

Coastal zones are presented as a series of 10 consecutive buffers of 1km width each (towards inland). For this dataset, were treated as sea data all areas with a class value of 523 (sea and ocean) in Corine Land Cover (details in lineage).

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.

This dataset is the coastal zone land surface region from Europe, derived from the coastline towards inland, as a series of 10 consecutive buffers of 1km width each. The coastline is defined by the extent of the Corine Land Cover 2018 (raster 100m) version 20 accounting layer. In this version all Corine Land Cover pixels with a value of 523, corresponding to sea and oceans, were considered as non-land surface and thus were excluded from the buffer zone.

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.