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.

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.

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Syringammina fragilissima fields assemblage in the North East Atlantic. 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.

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.

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 raster dataset represents the Sea Surface Temperature (SST) anomalies, i.e. changes of sea temperatures, in the European Seas. The dataset is based on the map "Mean annual sea surface temperature trend in European seas" by Istituto Nazionale di Geofisica e Vulcanologia (INGV), which depicts the linear trend in sea surface temperature (in °C/yr) for the European seas over the past 25 years (1989-2013). Since all changes of sea temperatures can be considered to have an impact on the marine environment, the pressure layer includes absolute values of SST anomalies, i.e. negative/decreasing temperature trends were changed to positive values so that they represent a pressure. The original data was in a 1° grid format but was converted to a 100 km resolution, adapted to the EEA 10 km grid and clipped with the area of interest. 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.