This dataset contains Amphipod distribution records and is based on literature from the years 1931 to 2018. The data were collected during a variety of cruises and sampling events while the majority was obtained during the Danish Ingolf expedition. Sampling events took place in the North Atlantic and Arctic waters which included the Artic Ocean, Barents Sea, Kara Sea, Labrador Sea, Buffin Bay and Greenland Sea. Amphipods were predominantly collected using dredges, epibenthic sledges and remotely operated vehicles but scuba divers and vehicle-free baited traps were also used. This way, over 1566 Amphipod samples were collected in total which include 45 families, 117 genera and 164 species.

<p>Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.-nbsp;</p>

This visualization product displays the spatial distribution of seafloor litter density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys. In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl and year using the following computation: Density (number of items per km²) = ∑Number of items / Swept area (km²) Then a grid with 30km x 30km cells is used to calculate the weighted mean of densities in each cell from the formula : Weighted mean (number of items per km²) = ∑ (Distance (km) * Density (number of items per km²)) / ∑ Distance (km) Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. More information on data processing and calculation are detailed in the document attached. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

<p>Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.-nbsp;</p>

This layer was created for the EUSeaMap 2019. It was computed from the CMEMS product "ARCTIC OCEAN - SEA ICE CONCENTRATION CHARTS - SVALBARD" (product identifier: SEAICE_ARC_SEAICE_L4_NRT_OBSERVATIONS_011_002). Daily values were averaged over the year 2018

The MALINA oceanographic campaign was conducted during summer 2009 to investigate the carbon stocks and the processes controlling the carbon fluxes in the Mackenzie River estuary and the Beaufort Sea. During the campaign, an extensive suite of physical, chemical and biological variables was measured across seven shelf–basin transects (south-north) to capture the meridional gradient between the estuary and the open ocean. Key variables such as temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll-a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured onboard the Canadian research icebreaker CCGS Amundsen and from a barge in shallow coastal areas or for sampling within broken ice fields. This dataset is the results of a joint effort to tidy and standardize the collected data sets that will facilitate their reuse in further studies of the changing Arctic Ocean. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Mapping and classifying the seabed of the West Greenland continental shelf. Marine benthic habitats support a diversity of marine organisms that are both economically and intrinsically valuable. Our knowledge of the distribution of these habitats is largely incomplete, particularly in deeper water and at higher latitudes. The western continental shelf of Greenland is one example of a deep (more than 500 m) Arctic region with limited information available. This study uses an adaptation of the EUNIS seabed classification scheme to document benthic habitats in the region of the West Greenland shrimp trawl fishery from 60┬░N to 72┬░N in depths of 61ÔÇô725 m. More than 2000 images collected at 224 stations between 2011 and 2015 were grouped into 7 habitat classes. A classification model was developed using environmental proxies to make habitat predictions for the entire western shelf (200ÔÇô700 m below 72┬░N). The spatial distribution of habitats correlates with temperature and latitude. Muddy sediments appear in northern and colder areas whereas sandy and rocky areas dominate in the south. Southern regions are also warmer and have stronger currents. The Mud habitat is the most widespread, covering around a third of the study area. There is a general pattern that deep channels and basins are dominated by muddy sediments, many of which are fed by glacial sedimentation and outlets from fjords, while shallow banks and shelf have a mix of more complex habitats. This first habitat classification map of the West Greenland shelf will be a useful tool for researchers, management and conservationists.

The "EMODnet Digital Bathymetry (DTM)- 2022" is a multilayer bathymetric product for Europe’s sea basins covering: • the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties,Dover, Wight, and Portland • the English Channel and Celtic Seas • Western Mediterranean, the Ionian Sea and the Central Mediterranean Sea • Iberian Coast and Bay of Biscay (Atlantic Ocean) • Adriatic Sea (Mediterranean) • Aegean - Levantine Sea (Mediterranean). • Madeira and Azores (Macaronesia) • Baltic Sea • Black Sea • Norwegian and Icelandic Seas • Canary Islands (Macaronesia) • Arctic region and Barentz Sea The DTM is based upon 21937 bathymetric survey data sets and Composite DTMs that have been gathered from 64 data providers from 28 countries riparian to European seas and beyond. Also Satellite Derived Bathymetry data products have been included fro Landsat 8 and Sentinel satellite images. Areas not covered by observations are completed by integrating GEBCO 2022 and IBCAO V4. The source reference layer in the portal viewing service gives metadata of the data sets used with their data providers; the metadata also acknowledges the data originators. The incorporated survey data sets itself can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that in December 2022 contained > 41.000survey data sets from European data providers for global waters. The Composite DTMs can be discovered through the Sextant Catalogue service. Both discovery services make use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). In addition, the EMODnet Map Viewer (https://emodnet.ec.europa.eu/geoviewer/ ) gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as: • water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form on a DTM grid of 1/16 * 1/16 arc minute of longitude and latitude (ca 115 * 115 meters). • option to view depth parameters of individual DTM cells and references to source data • option to download DTM in 58 tiles in different formats: ESRI ASCII, XYZ, EMODnet CSV, NetCDF (CF), GeoTiff and SD • option to visualize the DTM in 3D in the browser without plug-in • layer with a number of high resolution DTMs for coastal regions • layer with wrecks from the UKHO Wrecks database. The EMODnet DTM is also available by means of OGC web services (WMS, WFS, WCS, WMTS), which are specified at the EMODnet Bathymetry portal. The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.

This metadata refers to the CORINE Land Cover Plus Land Use, Land-Use Change and Forestry Instance (CLCplus LULUCF Instance), an annually updated, pan-European, spatially consistent and seamless geospatial proxy for land use reporting under the LULUCF regulation. The product is delivered as a single raster layer with a spatial resolution of 100 m, derived from multiple pan-European Copernicus Land Monitoring Service (CLMS) high resolution input datasets. The LULUCF Instance is available for the reference years 2018, 2021, 2022 and 2023, with production moving to an annual update cycle starting from the 2021 product. Each raster cell represents a dominant LULUCF land-use class, assigned according to thematic and spatial rulesets implemented during the extraction process. While each pixel corresponds primarily to one of the six main LULUCF land use categories - forest land, grassland, cropland, settlements, wetlands, and other lands - the dataset further differentiates these categories into sub classes, resulting in a total of 27 classes. This classification structure supports greenhouse gas reporting and other applications within the LULUCF sector by providing a harmonised and policy relevant representation of land use across Europe. It is crucial to understand that this product is fundamentally different from other CLMS products, as it is not based directly on satellite image classification or visual interpretation. Instead, it is produced through the combination and integration of existing CLMS data layers. Consequently, the dataset does not introduce fundamentally new information; rather, its novelty lies in the expert driven integration of multiple sources to produce a LULUCF oriented land use representation.

This product displays for DDT, DDE, and DDD, positions with values counts that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for all available years.