The dataset on dredging activities in the EU was created in 2014 by AZTI for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by several sources from all across the EU. It is available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities). The database contains points representing dredging sites in the following countries: Belgium, Bulgaria, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Latvia, Lithuania, Malta, Norway, Poland, Portugal, Spain, Sweden, The Netherlands and United Kingdom. Where available, each point has the following attributes: Id (Identifier), Position Information (e.g.: Estimated, Original, Polygon centroid of dredging area, Polygon centroid of dredging polygon), Country, Sea basin, Sea, Extraction Area, Year (when data is for a time period, the first year of the period is indicated), Permitted Amount (m3), Permitted Amount (t), Extracted Amount (m3), Extracted Amount (t), Extraction Type (e.g.: Harbour dredging, Estuary dredging, Sea lane), Purpose (e.g.: Maintenance dredging, Capital dredging, Others), End Use (e.g.: Beach nourishment, Commercialization, Confined deposit, Construction material, Embankment, Filling material, Land deposit, Reuse, Sea disposal, Wetland restoration), Material type (e.g.: silt, sand, gravel), Notes, Link to Web Sources. In the 2022 update, extraction data until 2020 has been included.

The dataset on aggregate extraction in the EU was created in 2014 by AZTI for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by several sources from all across the EU. It is available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities). The database contains points representing aggregate extraction sites, by year (although some data are indicated by a period of years), in the following countries: Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Lithuania, Poland, Portugal, Spain, Sweden, The Netherlands and United Kingdom. Where available, each point has the following attributes: Id (Identifier), Position Info (e.g.: Estimated, Original, Polygon centroid of dredging area, Estimated polygon centroid of dredging area), Country, Sea basin, Sea, Name of the extraction area, Area of activity (km2), Year (the year when the extraction took place), Permitted Amount (m3) (permitted amount of material to be extracted, in m3), Permitted Amount (t) (permitted amount of material to be extracted, in tonnes), Requested Amount (m3) (requested amount of material to be extracted, in m3), Requested Amount (t) (requested amount of material to be extracted, in tonnes), Extracted Amount (m3) (extracted amount of material, in m3), Extracted Amount (t) (extracted amount of material, in tonnes), Extraction Type (Marine sediment extraction), Purpose (e.g.: Commercial, Others, N/A), End Use (e.g.: Beach nourishment, Construction, Reclamation fill, N/A), Material type (e.g.: sand, gravel, maerl), Notes, Link to Web Sources. In the 2022 update, extraction data until 2021 has been included.

The database on shellfish aquaculture in the EU was created in 2014 by AND-International for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by national sources across the EU (plus Norway and the UK) and by the project Euroshell. Data are available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities). The database contains points representing shellfish farms or shellfish production areas (depending on available data) in the following countries: Bulgaria, Denmark, France, Greece, Ireland, Italy, Netherlands, Norway, Slovenia, Spain and United Kingdom. Data from Bulgaria, Denmark, Greece, Ireland, Norway, Spain and Scotland come from the official lists of registered aquaculture sites. Data from France relies on cadastral data. Data from the Netherlands, Italy and England and Wales come from the Euroshell project. Data is missing for Germany, Portugal, Sweden and Croatia. Except for Germany, the shellfish production remains limited in those MS. There is no production in other MS. Each point has the following attributes (where available): status (active, inactive, licensed), country, owner name, farm type (Mussels, Oysters, Mussels-Oysters, Clams, Specialised (other), Mixed (other)), production method (Beds, Long lines, Rafts, Saltwater closed (recirculation), Saltwater ponds, Saltwater tanks/raceways, Trestles or trays, Other), production stage (Grow out for human consumption, Hatchery, Nursery, Broodstock, Reproduction, Harvest, Other), purpose (Commercial, Research, Education, Display, Other), products detailed (English translation of the information provided on species grown or authorised in the source), point information (Polygon centroid, Original) depending on how the information is provided in the source (polygons or points), site_id, distance to coast (metres), position from coastline (At sea, within the coastline). The farm type relies on a typology established by AND-International, based on available information on species grown or authorised. A relational table provides harmonised information about species grown or authorised using Eurostat nomenclature for the Species Group (Mussels; Oysters; Clams, cockles, arkshells; Scallops, pectens; Abalones, winkles, conchs; Sea-urchins and other echinoderms) and when available the species name (e.g. Blue mussels - Mytilus edulis). The distance to coast (EEA coastline shapefile) has been calculated using the original data map projections, where available. In the other cases it was used the UTM WGS84 Zone projected coordinate system where data fall in. Compared with the previous version this new version includes updated data for Denmark, Greece, Ireland, Norway and Scotland and new data from Slovenia and Spain.

The dataset on Ocean Energy projects in the EU was created in 2014 by AZTI for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of data provided by several sources from all across the EU. It is updated every year, and is available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities). The database contains points representing Ocean Energy project sites in the following countries: Belgium, Cyprus, Denmark, Finland, France, Greece, Ireland, Israel, Italy, Monaco, Norway, Portugal, Russia, Spain, Sweden, The Netherlands and United Kingdom. Where available, each point has the following attributes: site code (ID_1), project code (ID), name, location, country, sea basin, distance to coast (metres), resource type (wave, tidal, salinity gradient, wave/wind), starting year, ending year, lease status, technology (Based on www.aquaret.com/), device, device scale (Full scale, prototype, etc.), project scale (Commercial, Demonstrator Array, etc.), project status (operational, completed, etc.), project capacity (KW), promoter, position info (it indicates if the attribute value is original from the source or has been estimated or calculated the polygon centroid) and the studies conducted for the environmental assessment (EIA). In 2022, new data has been included and existing data has been updated.

Stanton Banks was designated as a Special Area of Conservation (SAC) through the Offshore Marine Conservation (Natural Habitats) Regulations 2007 and has now been accepted as a Site of Community Importance (SCI). The Joint Nature Conservation Committee (JNCC) in partnership with Cefas and supported by British Geological Survey (BGS) staff conducted a field survey to investigate the presence and extent of Annex I habitat features within the Stanton Banks SCI in order to facilitate discussions on possible fisheries management options. The survey was designed to acquire sufficient data to provide a robust characterisation of the Annex I rocky reef habitats, targeting areas of particular interest to fishers, and to contribute to the development of a robust baseline for future monitoring within the proposed SAC. In addition, the survey involved the characterisation and mapping of the sedimentary habitats surrounding the reef feature within the site boundary, in order to provide information on the wider environmental context.

Updated habitat map resulting from an integrated analysis of the 2013 dedicated survey data (collected on cruise CEND0613) for South-West Deeps (West) recommended Marine Conservation Zone (rMCZ). A new habitat map for the site was produced by analysing and interpreting the available acoustic data and the ground-truth data collected by the dedicated surveys of South West Deeps West rMCZ. The process is a combination of two approaches, auto-classification (image analysis) and expert interpretation. The routine for auto-classification is flexible and dependent on site-specific data, allowing for application of a bespoke routine to maximise the acoustic data available. ArcGIS was used to perform an initial unsupervised classification on the supplied backscatter image. The single band backscatter mosaic was filtered and smoothed prior to the application of an Iso cluster/maximum likelihood classification routine. For further information, refer to the South-West Deeps (West) rMCZ Post-survey Site Report.

This it the updated broadscale habitat (BSH) map for the Whitsand and Looe Bay MCZ. Several BSH were identified as part of this map creation including: Infralittoral rock, moderate energy circalittoral rock, subtidal sand, subtidal mixed sediments, subtidal coarse sediment

JNCC requested that BGS carry out geostatistical analysis of sediment sample data from the CEND 8/12 survey of Swallow Sand MCZ and CEND 6/13 survey of South-west Deeps (West) MCZ in order to produce maps of sediment distribution in the sites. For each of the MCZ a geostatistical analysis of the data is reported leading to the selection of a robust linear model of corregionalization for the composition of the sediment, based on the additive log-ratio transformation of data on mud, sand and gravel content. This model is then used for spatial prediction on a 250-m grid. At each grid node a prediction distribution is obtained, conditional on neighbouring data and the selected model. By sampling from this distribution, and back-transforming onto the original compositional simplex of the data, we obtain a conditional expectation for the proportions of sand, gravel and mud at each location, a 95% confidence interval for the value at each node, and the probability that each of the four sediment texture classes that underly the EUNIS habitat classification is found at the node.

JNCC requested that BGS carry out geostatistical analysis of sediment sample data from the CEND 8/12 survey of Swallow Sand MCZ and CEND 6/13 survey of South-west Deeps (West) MCZ in order to produce maps of sediment distribution in the sites. For each of the MCZ a geostatistical analysis of the data is reported leading to the selection of a robust linear model of corregionalization for the composition of the sediment, based on the additive log-ratio transformation of data on mud, sand and gravel content. This model is then used for spatial prediction on a 250-m grid. At each grid node a prediction distribution is obtained, conditional on neighbouring data and the selected model. By sampling from this distribution, and back-transforming onto the original compositional simplex of the data, we obtain a conditional expectation for the proportions of sand, gravel and mud at each location, a 95% confidence interval for the value at each node, and the probability that each of the four sediment texture classes that underly the EUNIS habitat classification is found at the node.

Broadscale habitat (EUNIS level 3) for the Dover to Deal recommended Marine Conservation Zone (rMCZ).Seabed texture polygons mapped using expert interpretation of acoustic data (MBES bathymetry and backscatter) and groundtruthing data from PSA analysis and image (stills and video).