UKSeaMap 2016 has been generated by JNCC and is a by-product of the 2013-2016 activities of the EMODnet Seabed Habitats 2013-2016 consortium. It is a composite of two broad-scale habitat maps, arranged in the following priority order: 1. A roughly 100 m* resolution broad-scale habitat map, which covers the majority of the UK shelf area. 2. EUSeaMap 2016, a coarser resolution** broad-scale habitat map, which covers all European seas (view/download on the EMODnet Seabed Habitats interactive map). Both of these datasets have been created using identical methods; the only difference is in the resolution of the seabed substrate input data and the source and resolution of the depth data. Classification systems: EUNIS habitat classification system, with additional deep sea zones MSFD predominant habitats The Marine Habitat Classification for Britain and Ireland Input data layers: Seabed substrate type Depth to the seabed Amount of light reaching the seabed Wave disturbance at the seabed Kinetic energy at the seabed caused by tidal currents and waves Outputs: Predictive seabed habitat map Confidence layers The map follows the EUNIS 2007-11 classification system where it is appropriate.

Data holdings of individual modelled maps of specific habitats. These models have been collated by EMODnet Seabed Habitats partners from a variety of sources. Ownership of the individual models is retained by the original owners, for more information please see the individual metadata record tied to the model, which can be seen in the data layer. Models are available individually through EMODnet Seabed Habitats' "maplibrary" OGC service endpoints: For WMS (view) access to models, please use https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_view_maplibrary/wms? For WCS (download) access to open models, please use https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_open_maplibrary/wcs?

"Site Condition Monitoring has been (SCM) undertaken to determine whether the status of the special interest features which underpin the designation of habitats or areas are being maintained, and to guide site management action where appropriate. This study aimed to provide additional baseline data against which future changes can be measured to support Natural England’s overall programme of monitoring and surveillance of the sites into the future."

This map shows subtidal reef habitats in Kilkieran Bay. MBES bathymetry and its derivatives slope, rugosity and variability, were used in a Random Forest model trained using video sample data to predict high level EUNIS (version 2022) habitats. The MBES bathymetric data were collected as part of the Irish national seabed mapping programme - INFOMAR.

The dataset provides full-coverage maps of the habitats and biotopes in the German Baltic Sea at a resolution of 1 x 1 km for the entire region and at 50 x 50 m resolution in specific areas. We combined geological and biological surveys to map the seabed and collected extensive data to classify different habitats and their associated benthic communities. Using newly established national guidelines and predictive habitat modelling, we produced highly accurate maps. For upload to EMODnet four separate maps were made: - Broad Habitat Types according to the Marine Strategy Framework Directive (MSFD). - Annex I Habitat types - Habitat types classified according to the Baltic Sea-wide HELCOM underwater biotope and habitat classification (HUB) - other habitat types, OHTs for German marine waters include biotope types according to S30 of the German Federal Nature Conservation Act (BNatSchG), according to the European Habitats Directive (92/43/EEC), as well as the Baltic Sea-wide HELCOM Red List types

Confidence in the classification of the EUNIS 2007 habitat types in the EUSeaMap (2023) broad-scale predictive habitat map. Values are 1 (Low confidence), 2 (Moderate confidence) or 3 (High confidence). The final habitat type is classified by overlaying several layers of information; these layers of information are collectively known as 'habitat descriptors'. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed substrate Riverine input The confidence in the classification of the habitat type is taken as the minimum of the confidence in all of the relevant habitat descriptors at that location. Confidence values are also available for each habitat descriptor and input data layer. Detailed information on the modelling process is found in the EMODnet Seabed Habitats technical reports and its appendices (links in Resources). Created by the EMODnet Seabed Habitats project consortium. Credit: Licensed under CC-BY 4.0 from the European Marine Observation and Data Network (EMODnet) Seabed Habitats initiative (www.emodnet-seabedhabitats.eu), funded by the European Commission. It is important to note that a habitat type confidence score is only relevant to that particular level of the classification system. For example, a cell of A3.1 high energy infralittoral rock with ÔÇÿlowÔÇÖ energy class confidence, ÔÇÿmoderateÔÇÖ biozone confidence and ÔÇÿhighÔÇÖ substrate type confidence would have an overall ÔÇÿlowÔÇÖ confidence. However, moving up the hierarchy to EUNIS level two (A3 infralittoral rock) removes the energy class; therefore, the confidence of the EUNIS level two habitat type would only consider the ÔÇÿmoderateÔÇÖ biozone confidence and ÔÇÿhighÔÇÖ substrate type confidence, resulting in an overall ÔÇÿmoderateÔÇÖ confidence.

Output of the 2023 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to the Barents Sea in the north. The map was produced using a "top-down" modelling approach using classified habitat descriptors to determine a final output habitat. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed substrate Riverine input Habitat descriptors (excepting Substrate) are calculated using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced using R and Arc Model Builder (10.1). The model was created using raster input layers with a cell size of 0.00104dd (roughly 100 metres). The model includes the sublittoral zone only; due to the high variability of the littoral zone, a lack of detailed substrate data and the resolution of the model, it is difficult to predict littoral habitats at this scale. EUSeaMap is classified into EUNIS 2019 level 3 (or more detailed levels where appropriate), EUNIS 2019 level 2 , EUNIS 2007-2011, the MSFD benthic broad habitat types, the HELCOM HUB classification in the Baltic, and the recently revised habitat classification in the Mediterranean. In the Black Sea, EUSeaMap is not classified into EUNIS 2007-2011 (due to inapplicability), but is classified according to a classification that was developed by EMODnet Seabed Habitats (Populus et a, 2017, and for a revised version Vasquez et al, 2020, See Online resources). Reports that provide methods used for the classification of the predicted habitats into the new 2019 EUNIS classification, regional classifications, and MSFD BBHT (v.2017) are linked in Online Resources. A report on the methods used in the 2023 version of EUSeaMap and reports on previous versions (v2019 and V2021) are linked in Online Resources. Credit: Licensed under CC-BY 4.0 from the European Marine Observation and Data Network (EMODnet) Seabed Habitats initiative (www.emodnet-seabedhabitats.eu), funded by the European Commission.

Confidence in the classification of energy level in the EUSeaMap (2023) broad-scale predictive habitat map. Values are on a range from 1 (Low confidence), 2 (Moderate confidence), 3 (High confidence). Energy level is one of the layers of information used to categorise physical habitat types in EUSeaMap; these layers of information are collectively known as 'habitat descriptors'. Confidence in the classification of an energy level at any location is driven by both the confidence in the values of the input variables, and the confidence in the classification based on proximity to, and uncertainty in, the boundary between classes (i.e. areas closer to a boundary between two classes will have lower confidence). Layers are also available showing confidence in the values of the input variables used to model energy levels (kinetic energy at the seabed and wave exposure). A report on the methods used in the 2023 version of EUSeaMap and reports on previous versions (v2019 and V2021) are linked in Online Resources. Created by the EMODnet Seabed Habitats project consortium.

Predictive Biological Zone layer produced by EMODnet Seabed Habitats as an input layer for the 2023 EUSeaMap broad-scale habitat model. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to the Barents Sea in the North. The map of biological zone was produced using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced in R and Arc Model Builder (10.1). The model was created using raster input layers with a cell size of 0.00104dd (roughly 100 meters). The model includes the sublittoral zone only (Infralittoral to Abyssal zone). An accompanying confidence layer is available for viewing and download from EMODnet Seabed Habitats. Reports detailing the methods used in the previous versions of EUSeaMap (v2019 and V2021) are linked in online resources a new report is in progress. Vasquez M., Manca E., Inghilesi R., Martin, S., Agnesi S., Al Hamdani Z., Annunziatellis A., Bekkby T., Pesch R., Askew A., Bentes L., Castle L., Doncheva V., Drakopoulou V., Gon├ºalves J., Laamanen L., Lillis H., Loukaidi V., McGrath F., Mo G., Monteiro P., Muresan M., O'Keeffe E., Populus J., Pinder J., Ridgeway A., Sakellariou D., Simboura M., Teaca A., Tempera, F., Todorova V., Tunesi L. and Virtanen E. EUSeaMap 2019, A European broad-scale seabed habitat map, Technical Report, 2019. Available from: https://archimer.ifremer.fr/doc/00636/74782/ Vasquez Mickael, Allen Harriet, Manca Eleonora, Castle Lewis, Lillis Helen, Agnesi Sabrina, Al Hamdani Zyad, Annunziatellis Aldo, Askew Natalie, Bekkby Trine, Bentes Luis, Doncheva Valentina, Drakopoulou Vivi, Duncan Graeme, Gonçalves Jorge, Inghilesi Roberto, Laamanen Leena, Loukaidi Valia, Martin Simon, McGrath Fergal, Mo Giulia, Monteiro Pedro, Muresan Mihaela, Nikilova Christina, O'Keeffe Eimear, Pesch Roland, Pinder Jordan, Populus Jacques, Ridgeway Amy, Sakellariou Dimitris, Teaca Adrian, Tempera Fernando, Todorova Valentina, Tunesi Leonardo, Virtanen Elina (2021). EUSeaMap 2021. A European broad-scale seabed habitat map. D1.13 EASME/EMFF/2018/1.3.1.8/Lot2/SI2.810241– EMODnet Thematic Lot n° 2 – Seabed Habitats EUSeaMap 2021 - Technical Report. https://doi.org/10.13155/83528 Credit: Licensed under CC-BY 4.0 from the European Marine Observation and Data Network (EMODnet) Seabed Habitats initiative (www.emodnet-seabedhabitats.eu), funded by the European Commission.

Classified seabed substrate types for European seas. Produced by EMODnet Seabed Habitats as an input layer for the 2023 EUSeaMap broad-scale habitat model, based on a combination of EMODnet Geology seabed substrate products and biological substrates extracted form individual habitat maps from surveys around European seas. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to the Barents Sea in the north. The layer of seabed substrate was produced using data from EMODnet geology at the following scales: - 1:5k, 1:10k, 1:15k, 1:20k, 1:25k, 1:50k, 1:100k, 1:200k, 1:1M (these were all update in 2023) Biological substrates were included in the 2023 version of EUSeaMap to assist in the classification of biogenic habitats for the 2019 version of EUNIS. The Folk 5 classification of substrate is adopted because it is compatible with both the 2007-11 and 2019 versions of EUNIS, both of which have been applied in EUSeaMap 2023. A report on the methods used in the 2023 version of EUSeaMap and reports on previous versions (v2019 and V2021) are linked in Online Resources.