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.

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Solitary Scleractinian fields 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.

The data set aims to contribute to a better biological characterization of European marine ecosystems. As such it represents probabilities of EUNIS (EUropean Nature Information System) habitat presence at Level 3 for marine habitats including information on sea ice coverage (this corresponds to EUNIS level 2 for terrestrial habitats). The map combines spatially explicit data on marine bathymetry and sea-bed with non-spatially referenced habitat information of the EUNIS classification. The objective of the data set produced by EEA and its Topic Centre ETC/ULS is to improve the biological description of marine based ecosystem types and their spatial distribution. The work supports Target 2 Action 5 of the implementation of the EU Biodiversity Strategy to 2020, established to achieve the Aichi targets of the Convention of Biological Diversity (CBD). It further addresses the MAES process (Mapping and Assessing of Ecosystems and their Services). The data set represents 2 classes of the MAES classification level 3, namely “Marine inlets and transitional waters” and “Marine”. The dataset comprises the following information: • Sea region (1 – Arctic, 2 – Atlantic, 3 – Baltic, 4 – Mediterranean, 5 – Black Sea) • Sea zone (1 – Littoral, 2 – Infralittoral, 3 – Circalittoral, 4 – Offshore circalittoral, 5 – Upper bathyal, 6 – Lower bathyal, 7 – Abyssal,8 - Coastal Lagoons, 9 - Coastal Lagoons) • Substrate (0 – undetermined substrate, 1 – rock and biogenic, 3 – coarse sediment, 4 – mixed sediment, 5 – sand, 6 – mud) • Sea ice coverage (0 – no sea ice presence, 1 – seasonal sea ice presence, 2 – perennial sea ice presence)

DTM of continental margin of Cantabric Sea, resolution 100 meters. This DTM includes the whole area from coast line to deepest level (5544,23 m).

This raster dataset represents physical disturbance to the seabed in the European seas. Several human activities disturb the seabed either directly or indirectly. Alteration of benthic living conditions as a result of increased sedimentation or attenuation of light penetration, abrasion of the seabed and exploitation of benthic biota, temporarily disturb the benthic habitat quality. The dataset is an aggregation of several different human activities that cause physical disturbance to the seabed: aquaculture, demersal fishing, dredging and dumping of dredged material, oil and gas rigs, offshore installations, ports, sand and gravel extraction, shellfish mariculture, shipping in shallow waters and windfarms. The resulting dataset is a raster (10km grid cell) derived from EMODnet, MED-IAMER, JRC-STECF, OSPAR, HELCOM and 4C Offshore datasets, and with reference temporal coverage from 2012 to 2017. 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.

JRA55-do is a surface dataset for driving ocean-sea ice models and used in phase 2 of OMIP (OMIP-2). JRA55-do corrects the atmospheric reanalysis product JRA-55 (Kobayashi et al., 2015) using satellite and other atmospheric reanalysis products. The merits of JRA55-do are the high horizontal resolution (~55 km) and temporal interval (3 h). An assessment by Tsujino et al. (2020) implies that JRA55-do can suitably replace the current CORE/OMIP-1 dataset. This reanalysis of atmospheric variables is provided by the Japanese Meteorological Agency starting in the year 1958 and will be used to drive the coupled NEMO-ERSEM model in the hindcast configuration.

Modelled density of the seapen Kophobelemnon stelliferum in the North East Atlantic. The Random Forest density model trained on data collected by an ROV was constrained by an ensemble of Maxent and Random Forest presence-absence model trained on a larger dataset also collected by an ROV. This species provides structural complexity in an environment where it is lacking and, thus, promotes higher biodiversity where they settle. They are vulnerable to mechanical disturbance of the sediment by fishing gear and a better understanding of their distribution will lead to better management of their population. This work was performed at the University of Plymouth in 2021.

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.