Description: Abundance data of the epibenthic fauna annotated on each photograph taken with the ROV Isis (NOC, UK) at a deep-sea wall located offshore the West coast of Greenland (Labrador Sea, [63°51.9'N, 53°16.9'W, depth: 703 to 803 m]). Abundances were standardized to 1 m² using the images' total area. Screenshots of the morphospecies are presented in the morphospecies guide pdf. These data were used to assess for differences in community composition analysis pooled in 20 m² samples defined according to high-resolution terrain abiotic clusters computed in an unsupervised way.

Description: We used carbon and nitrogen stable isotope (δ13C and δ15N) analyses to investigate the trophic network of the CWC reef habitat off Angola (SE Atlantic Ocean). Samples were collected in January 2016 during the M122 (“ANNA”) expedition on board R/V Meteor. In total, 18 reef sites, including seven CWC mound settings over a bathymetric range of 250 to 530 m water depth, were sampled for stable isotope analyses. Samples of organisms belonging to the taxa Porifera, Cnidaria, Arthropoda, Annelida, Echinodermata and Chordata were collected by means of a box corer, a Van-Veen grab sampler and the Remotely Operated Vehicle (ROV) SQUID (MARUM, Bremen, Germany). To investigate potential food sources of the benthic megafauna, three types of Particulate Organic Matter (POM) were collected: Suspended Particulate Organic Matter (SPOM) was collected with a McLane phytoplankton pump; settling SPOM was collected with a sediment trap (SPOM trap) and sediment samples were collected with a box corer and a grab sampler. Analyses of benthic megafauna were performed using a Elementar IsoPrime 100 isotope ratio–mass spectrometry (IR–MS) (IsoPrime Ltd.) coupled to a CNS elemental analyzer (Elementar Vario Pyro Cube EA CNS; Elementar Analysensysteme GmbH), while POM samples were analyzed by a Delta V Advantage IR–MS coupled online to an elemental analyzer (Flash 2000 EA-IRMS) by a ConFlo IV (Thermo Fisher Scientific Inc.). Vienna Pee Dee belemnite (V.P.D.B.) for carbon, and atmospheric N2 (Air) for nitrogen, were used as reference materials, and stable isotope values are reported in respect to that.

Description: Terrain data retrieved with a forward-looking sonar (Reson7125) the ROV Isis (NOC, UK) used to map a deep-sea wall located offshore the West coast of Greenland (Labrador Sea, [63°51.9'N, 53°16.9'W, depth: 703 to 803 m]) with a high resolution. The file contains a 3D point cloud storing terrain variables derived from the bathymetry [m] and backscatter [nominal unit] extracted at a resolution of 0.3 m. Different terrain descriptors were computed: Slope, Bathymetric Position Index (BPI), Terrain Ruggedness Index, Roughness, Mean and Gaussian curvatures and orientations (Northness and Eastness), at scales of 0.9, 3 and 9 m. Using a Principal Component Analysis (PCA), the terrain descriptors enabled to retrieve 4 terrain clusters and their associated confusion index, to investigate the spatial heterogeneity of the terrain.

Description: This data set presents the results of an automated cluster analysis using Gaussian mixture models of the entire Atlantic seafloor environment. The analysis was based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities (see Source data set). We obtained nine seabed areas (SBAs) that portray the Atlantic seafloor that are shown as polygons in the data set. The attribute table holds short descriptions of each SBA as well as about the colours used in the accompanying paper publication. Data sets like this can be used for further analysis like e.g. for landscape ecology metrics to identify regions of interest. The compressed file further contains a style file that can be used to directly load the correct style in the QGIS software package.

Description: Multibeam data collected around Cabo Verde on the iMirabilis2 Cruise, 04/08/2021-26/08/2021, as part of the iAtlantic Project. The data were collected using an Atlas Hydrosweep DS-3 Multibeam Echosounder, using Atlas Naviscan and PDS2000 from Teledyne. The data has been manually cleaned using swath and subset editors in CARIS HIPS and SIPS versions 10.4 and 11.1. CTD derived sound velocity profiles were applied during data acquisition and a Polpred generated tide file was applied during processing to correct the vertical datum to mean sea level (MSL). The dataset spans ~200m - 4500m depth. A raster was created in CARIS HIPS AND SIPS using the swath angle gridding method at 100m resolution, the 'Fill raster holiday' function was used with a matrix size 5 x 5 and 6 neighbours. This was then exported as a GeoTIFF, imported to ArcMap and reprojected to a GeoTIFF in WGS84, EPSG code: 4326.

Description: We used a multibeam echosounder (Reson7125) front-mounted onto the ROV Isis (Dive D333, DY081 expedition) to map the terrain of a vertical feature marking the edge of a deep-sea glacial trough (Labrador Sea, [63°51.9'N, 53°16.9'W, depth: 650 to 800 m]). After correction of the ROV navigation (i.e. merging of USBL and DVL), bathymetry [m] and backscatter [nominal unit] were extracted at a resolution of 0.3 m and different terrain descriptors were computed: Slope, Bathymetric Position Index (BPI), Terrain Ruggedness Index, Roughness, Mean and Gaussian curvatures and orientations (Northness and Eastness), at scales of 0.9, 3 and 9 m. Using a Principal Component Analysis (PCA), the terrain descriptors enabled to retrieve 4 terrain clusters and their associated confusion index, to investigate the spatial heterogeneity of the terrain. This approach also underlined the presence of geomorphic features in the wall terrain. The extraction of the backscatter intensity for the first time considering vertical terrains, opens space for further acquisition and processing development. Using photographs collected by the ROV Isis (Dive D334, DY081 expedition), epibenthic fauna was annotated. Each image was linked to a terrain cluster in the 3D space and pooled into 20-m² bins of images. A Bray-Curtis dissimilarity matrix was constructed from morphospecies abundances. This enabled to test for differences of assemblage composition among clusters. Few species appeared more abundant in particular clusters such as L. pertusa in high-roughness cluster. However, nMDS suggested differences in assemblage composition but these dissimilarities were not strongly delineated. Whereas the design of this study may have limited distinctive differences among assemblages, this shows the potential of this cost-effective method of top-down habitat mapping to be applied in undersampled benthic habitat in order to provide a priori knwoledge for defining appropriate sampling design.

Description: This dataset includes 11 regional EUNIS-classified habitat maps (100-1000 km) and associated confidence maps that were created as a project milestone (Nr. 12) of the EU H2020 project 'iAtlantic'. The 12 iAtlantic regions encompass 1. Subpolar Mid-Atlantic Ridge, off Iceland MFRI, 2. Rockall Trough to PAP, 3. Central mid-Atlantic Ridge, 4. NW Atlantic, Gully Canyon, 5. Sargasso Sea, 6. Eastern Tropical North Atlantic, Cape Verde, 7. Equatorial Atlantic, Romanche Fracture Zone, 8. Slope & margin off Angola & Congo Lobe, 9. Benguela Current, Walvis Ridge to South Africa, 10. Brazil margin & Santos and Campos Basin, 11. Vitória-Trindade Seamount Chain and 12. Malvinas Current. For each of the regions 2-12, a shapefile of polygons classified according to the 2022 EUNIS classification level 3 and a second shapefile of the same polygons attributed with their confidence level according to the MESH Accuracy & Confidence Working approach was created. EUNIS classifications combined biozone and substrate data. Biozones were assigned from bathymetry. Where MBES was not available, GEBCO bathymetry was used. Substrate data were extracted from pre-existing geological/substrate mapping efforts and converted to EUNIS classifications via cross walks or, where substrate data were limited, substrate layers were modelled using Random Forest. The EUNIS habitat map for Region 4 was based on the pre-existing surficial geology compilation of the Scotian Shelf bioregion compiled by the Geological Survey of Canada. The EUNIS habitat map for Region 9 was based on the pre-existing South African habitat map that uses a modified IUCN hierarchical classification system. No additional information to that used in the EUSeaMap was available for Region 1. Therefore, shapefiles were not created for Region 1.

Description: Raw multibeam and sound velocity data collected around Cabo Verde on the iMirabilis2 Cruise, 04/08/2021-26/08/2021, as part of the iAtlantic Project. The data were collected using an Atlas Hydrosweep DS-3 Multibeam Echosounder, using Atlas Naviscan and PDS2000 from Teledyne. The sound velocity profiles (SVP) were collected using CTD casts and XBTs. The dataset spans ~200m - 4500m water depth.

Description: This dataset includes 11 regional EUNIS-classified habitat maps (100-1000 km) and associated confidence maps that were created as a project milestone (Nr. 12) of the EU H2020 project 'iAtlantic'. The 12 iAtlantic regions encompass 1. Subpolar Mid-Atlantic Ridge, off Iceland MFRI, 2. Rockall Trough to PAP, 3. Central mid-Atlantic Ridge, 4. NW Atlantic, Gully Canyon, 5. Sargasso Sea, 6. Eastern Tropical North Atlantic, Cape Verde, 7. Equatorial Atlantic, Romanche Fracture Zone, 8. Slope & margin off Angola & Congo Lobe, 9. Benguela Current, Walvis Ridge to South Africa, 10. Brazil margin & Santos and Campos Basin, 11. Vitória-Trindade Seamount Chain and 12. Malvinas Current. For each of the regions 2-12, a shapefile of polygons classified according to the 2022 EUNIS classification level 3 and a second shapefile of the same polygons attributed with their confidence level according to the MESH Accuracy & Confidence Working approach was created. EUNIS classifications combined biozone and substrate data. Biozones were assigned from bathymetry. Where MBES was not available, GEBCO bathymetry was used. Substrate data were extracted from pre-existing geological/substrate mapping efforts and converted to EUNIS classifications via cross walks or, where substrate data were limited, substrate layers were modelled using Random Forest. The EUNIS habitat map for Region 4 was based on the pre-existing surficial geology compilation of the Scotian Shelf bioregion compiled by the Geological Survey of Canada. The EUNIS habitat map for Region 9 was based on the pre-existing South African habitat map that uses a modified IUCN hierarchical classification system. No additional information to that used in the EUSeaMap was available for Region 1. Therefore, shapefiles were not created for Region 1.

Description: This dataset includes 11 regional EUNIS-classified habitat maps (100-1000 km) and associated confidence maps that were created as a project milestone (Nr. 12) of the EU H2020 project 'iAtlantic'. The 12 iAtlantic regions encompass 1. Subpolar Mid-Atlantic Ridge, off Iceland MFRI, 2. Rockall Trough to PAP, 3. Central mid-Atlantic Ridge, 4. NW Atlantic, Gully Canyon, 5. Sargasso Sea, 6. Eastern Tropical North Atlantic, Cape Verde, 7. Equatorial Atlantic, Romanche Fracture Zone, 8. Slope & margin off Angola & Congo Lobe, 9. Benguela Current, Walvis Ridge to South Africa, 10. Brazil margin & Santos and Campos Basin, 11. Vitória-Trindade Seamount Chain and 12. Malvinas Current. For each of the regions 2-12, a shapefile of polygons classified according to the 2022 EUNIS classification level 3 and a second shapefile of the same polygons attributed with their confidence level according to the MESH Accuracy & Confidence Working approach was created. EUNIS classifications combined biozone and substrate data. Biozones were assigned from bathymetry. Where MBES was not available, GEBCO bathymetry was used. Substrate data were extracted from pre-existing geological/substrate mapping efforts and converted to EUNIS classifications via cross walks or, where substrate data were limited, substrate layers were modelled using Random Forest. No additional information to that used in the EUSeaMap was available for region 1. Therefore, shapefiles were not created for region 1.