Description: © The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 7 (2010): 2851-2899, doi:10.5194/bg-7-2851-2010.

Description: The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna. Investigations of deep-sea habitats and their fauna began in the late 19th century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 28 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st century. However, for most of these habitats the global area covered is unknown or has been only very roughly estimated; an even smaller – indeed, minimal – proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation thus shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps. Here, chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold-water corals have an increased productivity through specific physical processes, such as topographic modification of currents and enhanced transport of particles and detrital matter. Because of its unique abiotic attributes, the deep sea hosts a specialized fauna. Although there are no phyla unique to deep waters, at lower taxonomic levels the composition of the fauna is distinct from that found in the upper ocean. Amongst other characteristic patterns, deep-sea species may exhibit either gigantism or dwarfism, related to the decrease in food availability with depth. Food limitation on the seafloor and water column is also reflected in the trophic structure of heterotrophic deep-sea communities, which are adapted to low energy availability. In most of these heterotrophic habitats, the dominant megafauna is composed of detritivores, while filter feeders are abundant in habitats with hard substrata (e.g. mid-ocean ridges, seamounts, canyon walls and coral reefs). Chemoautotrophy through symbiotic relationships is dominant in reducing habitats. Deep-sea biodiversity is among of the highest on the planet, mainly composed of macro and meiofauna, with high evenness. This is true for most of the continental margins and abyssal plains with hot spots of diversity such as seamounts or cold-water corals. However, in some ecosystems with particularly "extreme" physicochemical processes (e.g. hydrothermal vents), biodiversity is low but abundance and biomass are high and the communities are dominated by a few species. Two large-scale diversity patterns have been discussed for deep-sea benthic communities. First, a unimodal relationship between diversity and depth is observed, with a peak at intermediate depths (2000–3000 m), although this is not universal and particular abiotic processes can modify the trend. Secondly, a poleward trend of decreasing diversity has been discussed, but this remains controversial and studies with larger and more robust data sets are needed. Because of the paucity in our knowledge of habitat coverage and species composition, biogeographic studies are mostly based on regional data or on specific taxonomic groups. Recently, global biogeographic provinces for the pelagic and benthic deep ocean have been described, using environmental and, where data were available, taxonomic information. This classification described 30 pelagic provinces and 38 benthic provinces divided into 4 depth ranges, as well as 10 hydrothermal vent provinces. One of the major issues faced by deep-sea biodiversity and biogeographical studies is related to the high number of species new to science that are collected regularly, together with the slow description rates for these new species. Taxonomic coordination at the global scale is particularly difficult, but is essential if we are to analyse large diversity and biogeographic trends. Because of their remoteness, anthropogenic impacts on deep-sea ecosystems have not been addressed very thoroughly until recently. The depletion of biological and mineral resources on land and in shallow waters, coupled with technological developments, are promoting the increased interest in services provided by deep-water resources. Although often largely unknown, evidence for the effects of human activities in deep-water ecosystems – such as deep-sea mining, hydrocarbon exploration and exploitation, fishing, dumping and littering – is already accumulating. Because of our limited knowledge of deep-sea biodiversity and ecosystem functioning and because of the specific life-history adaptations of many deep-sea species (e.g. slow growth and delayed maturity), it is essential that the scientific community works closely with industry, conservation organisations and policy makers to develop robust and efficient conservation and management options.

Description: This paper has been written under the umbrella of the Census of Marine Life synthesis initiative SYNDEEP, supported by the Alfred P. Sloan Foundation, Fondation Total and EuroCoML, which are gratefully acknowledged. ERLL is funded by the CoML-ChEss programme (A. P. Sloan Foundation) and Fondation Total. CRG acknowledges support from the CoMLChEss programme. LAL acknowledges support from the National Science Foundation and the CoML-COMARGE and ChEss programmes. DPT acknowledges funding from the CoML-FMAP programme. MV acknowledges the CoML-MAR-ECO programme (Sloan Foundation and NOAA).

Description: The dataset contains polychaete abundance data collected from boxcores samples (BC; 0.25 m2) collected in the eastern Clarion Clipperton fracture Zone (northeast Pacific), an area currently being explored for polymetallic nodules. Macrobenthic samples were collected onboard RV Sonne during expedition SO239 in 2015. Four exploration contract areas (BGR, IOM, GSR and Ifremer) and one “Area of Particular Environmental Interest” (APEI#3) were sampled. Between 3 and 8 quantitative box cores were collected in each area. Boxcore samples were sliced in three layers (0-3, 3-5 and 5-10 cm depth) and sieved on a 300 µm mesh. Polychaetes have been counted, sequenced and identified. Identifications were realised based on morphology and DNA (COI, 16S and 18S genes) leading to morphotype in most cases (species-level). DNA sequences are available in Genbank or BOLD databases with their respective codes in this dataset.

Description: The dataset contains polychaete abundance data belonging to the family Polynoidae sampled using epibenthic sledge, ROV and box corer (BC; 0.25 m2) within the eastern Clarion Clipperton fracture Zone (northeast Pacific), an area currently being explored for polymetallic nodules. Macrobenthic samples were collected onboard RV Sonne during expedition SO239 in 2015. Four exploration contract areas (BGR, IOM, GSR and Ifremer) and one "Area of Particular Environmental Interest" (APEI#3) were sampled. Eight out of twelve epibenthic sledges samples were fully processed. All polynoids heads have been counted, sequenced and identified. Identifications were realized using morphology and DNA (COI, 16S and 18S genes) leading to morphospecies in most cases (species-level). DNA sequences are available in GenBank or BOLD databases with their respective codes in this dataset.

Description: Standardized video transects, 17 in total, were performed one meter above the seafloor using the Remote Operated Vehicle (ROV) Kiel 6000 to identify composition and densities of both sessile and mobile megabenthic epifauna (excluding fish, crustaceans and large protozoans) in areas with dense nodule concentrations (〉15% cover) and areas with very few or no obvious surface nodules (〈1%).

Description: We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach.  2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.

Description: This data is showing the outcomes of the analysis done by ATLAS researchers on the environmental status of nine deep-sea areas in the northeast Atlantic. These results are part of the ATLAS work facilitating the implementation of the European Commission's Marine Strategy Framework Directive in the deep waters of the North Atlantic. The nine study areas that were examined are: 1) LoVe Ocean Observatory, 2) Faroe-Shetland Channel, 3) Reykjanes Ridge, 4) Rockall Bank, 5) Mingulay Reef Complex, 6) Porcupine Seabight, 7) Bay of Biscay, 8) Azores, 9) Gulf of Cádiz. The analyses were carried out using the Nested Environmental status Assessment Tool (NEAT). The environmental status outcomes are shown for the total study area, the designated spatial assessment units (SAUs), the ecosystem components ("Benthic invertebrates", "Fish", "Benthos") and the habitats ("Aggregations of L. pertusa & M. oculata on soft sediments", "Aggregations of sea pens & alcyonaceans on soft sediments", "Aggregations of L. pertusa & M. oculata on hard substrates", "Aggregations of Antipatharians and alcyonaceans on hard substrates", "Benthic", "Rocky", "Sedimentary").

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. 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.