HELCOM Metadata catalogue
HELCOM Metadata catalogue (Helcom)
Continents, countries, sea regions of the world.
This dataset contains the most up-to-date reported data about hydrographical monitoring stations in the Baltic Sea. Dataset for download contains Baltic Sea hydrographical monitoring stations. Frequency can be found in corresponding name column.
Use constraints: Data can be used freely given that the source (HELCOM) is cited.
Access constraints: No limitations on public access.
The dataset was collected during the HELCOM MORE project.The dataset was updated in 18 February 2015 with Finnish and Swedish monitoring stations reported by the end of 2014 as requested in HELCOM STATE 1-2014 meeting. Following update was done in 11 September 2015 regarding Polish stations following update request in HELCOM STATE & CONSERVATION 2-2015 meeting.
AA.A1H2, AB.A1H2, AA.M1H2 and AB.M1H2 (NT)
Summary Estimated observations of the biotope AA.A1H2, AB.A1H2, AA.M1H2 and AB.M1H2 were collected from the Baltic Sea area by expert judgements for HELCOM Red List of biotopes, habitats and biotope complexes. Description Baltic photic or aphotic rock and boulders or mixed substrate dominated by erect moss animals (Flustra foliacea) The HELCOM Red List of Baltic Sea underwater biotopes, habitats and biotope complexes (2013) is an updated and improved version of the Red List assessment of marine and coastal biotopes and biotope complexes published in 1998. The classification of the report follows the proposed International Union for Conservation of Nature (IUCN) criteria and assessment principals but with some modifications for the Baltic Sea. Altogether, the HELCOM Underwater Biotope and habitat classification (HELCOM HUB) includes 209 biotopes of which 59 were red-listed. Many of the red-listed biotopes are located in deep areas of the Baltic Sea due to oxygen-free nature as well as in the southwestern Baltic Sea due to the salinity restricted distribution of species in certain biotope. The HELCOM assessment relies heavily on expert judgment and inference, and the questionnaire data represents the estimated presence-absence data not in-situ measured data. This must be taken in account when observing the map presentation. The biotopes are shown on the map using the EEA 100 km grid. This dataset displays estimated presence of AA.A1H2, AB.A1H2, AA.M1H2 andAB.M1H2according to HELCOM RED LIST assessment experts: The Flustra foliacea dominated biotope commonly occurs from Kattegat to the Mecklenburg Bight andArkona Basin (Kadetrinne). The spatial restriction to the Western Baltic Sea is due to the salinityrequirements of the dominant species Flustra foliacea. The more to the west or north-west this biotopeoccurs the higher the salinities, and in consequence the higher the diversity of inhabiting invertebrateand fish communities. The distribution map indicates the area in the 100 x 100 km grid where biotope isknown to occur, the occurrence of the biotope in the photic zone is restricted to the negative surfaces offor example boulders. AA.A1H2, AB.A1H2, AA.M1H2 and AB.M1H2 have been placed in the Red List classification to the category of Near Threatened (NT) biotopes. (Data (expert judgements) collected in HELCOM RED LIST project, released in May 2013)
Use constraints: Data can be used freely given that the source (HELCOM, 2013) is cited.
ETRS-LAEA5210 is the recommended projection for reference grids by the European Environment Agency. Based on proposal at the "1st European Workshop on Reference Grids", this grid is the recommened grid for EEA grids. This reference grid is based on ETRS89 Lambert Azimuthal Equal Area projection with parameters: latitude of origin 52° N, longitude of origin 10° E, false northing 3 210 000.0 m, false easting 4 321 000.0 m. Origin of grid is calculated from 0 m N 0 m E of projection. Parameters for grid calculation: start X-axis from origin: 0 m, start Y-Axis from origin: 700000 m, number of rows: 67 and number of columns: 84.
Summary Estimated observations of the biotope 1140 were collected from the Baltic Sea area by expert judgements for HELCOM Red List of biotopes, habitats and biotope complexes. Description Mudflats and sandflats not covered by seawater at low tideThe HELCOM Red List of Baltic Sea underwater biotopes, habitats and biotope complexes (2013) is an updated and improved version of the Red List assessment of marine and coastal biotopes and biotope complexes published in 1998. The classification of the report follows the proposed International Union for Conservation of Nature (IUCN) criteria and assessment principals but with some modifications for the Baltic Sea.Altogether, the HELCOM Underwater Biotope and habitat classification (HELCOM HUB) includes 209 biotopes of which 59 were red-listed. Many of the red-listed biotopes are located in deep areas of the Baltic Sea due to oxygen-free nature as well as in the southwestern Baltic Sea due to the salinity restricted distribution of species in certain biotope. The HELCOM assessment relies heavily on expert judgment and inference, and the questionnaire data represents the estimated presence-absence data not in-situ measured data. This must be taken in account when observing the map presentation. The biotopes are shown on the map using the EEA 100 km grid. This dataset displays estimated presence of the biotope 1140 according to HELCOM RED LIST assessment experts:Mudflats and sandflats not covered by sea water at low tide occur in all parts of the Baltic Sea area, but patterns and descriptions of their distribution are mostly missing. In the Lahemaa area (Southern Gulf of Finland) for example, they are representing 3% of all habitats and also in the German Baltic Sea region they form a very narrow strip along some the coastlines. No information is available on their historical distribution. The distribution map indicates the area in the 100 x 100 km grid where biotope is known to occur (Naturvårdverket 2011, EUNIS Database).(Data (expert judgements) collected in HELCOM RED LIST project, released in May 2013)
This dataset describes fishing intensity for Otter mobile bottom contacting gear in 2009 based on VMS/Log book data processed by ICES Working Group on Spatial Fisheries Data (WGSFD). ICES secretariat collected during 2017 relevant VMS and logbook data for 2009-2016 to produce, as a technical service to HELCOM, updated spatial data layers on fishing intensity/pressure. Improved data quality control checks were implemented. Submitted data across the HELCOM area have improved in quality compared to previous data 2009-2013 published in 2015. Standardized methods were used to produce the requested data layers. The code used to create the data products is available here: https://github.com/ices-eg/wg_WGSFD For further technical information on the advice request, see http://www.ices.dk/sites/pub/Publication%20Reports/Advice/2017/Special_requests/helcom.2017.18.pdf HELCOM secretariat did the following processing to the shapefile provided by ICES: - Conversion to ETRS89LAEA coordinate system - Added feature and attribute "Reported" to display unreported areas. Dataset attribute information: c-square: Unique reference of the c-square polygon Year: Year of fishing activity mid_lat: latitude coordinate of the centroid of c-square inWGS84 decimal degrees mid_lon: longitude coordinate of the centroid of c-square inWGS84 decimal degrees SurfaceSAR: Surface area ratio (Swept area, < 2 cm penetration depth of the gear components) Subsurface: Subsurface area ratio (Swept area, subsurface =>2 cm penetration depth of the gear components) totweight: Total Weight (kg) totvalue: Total value (Euros) Kw Fishing Hours: (Kw*h) Fishing hours: (h) Reported: Yes=Reported data. No= No reported data (area that does not contain effort/intensity value due to lack of reported data). Please note that this dataset was updated (v2) in January 2019, see further details below in the lineage section.
Use constraints: The data products derived from the advice are downloadable from HELCOM Map and Data service and can be used freely given that the source is cited. The correct data product citation is following: ICES. 2017. Spatial data layers of fishing intensity/pressure per gear type for surface and subsurface abrasion, for the years 2009 and 2016 in the HELCOM area. Available as shapefile datasets at: https://doi.org/10.17895/ices.pub.2860.
ICES secretariat collected during 2017 relevant VMS and logbook data for 2009-2016 to produce, as a technical service to HELCOM, updated spatial data layers on fishing intensity/pressure. Improved data quality control checks were implemented. Submitted data across the HELCOM area have improved in quality compared to previous data 2009-2013 published in 2015. Standardized methods were used to produce the requested data layers. The code used to create the data products is available here: https://github.com/ices-eg/wg_WGSFD HELCOM secretariat downloaded the data and did the following processing to the shapefile provided by ICES: - Conversion to ETRS89LAEA coordinate system - Added feature and attribute "Reported" to display unreported areas. After processing, the datasets were published via HELCOM Map and Data service as individual map layers. Dataset corrected in January 2019: Upon request of the data provider outputs have been updated by ICES to better ensure vessel anonymity. Three ICES advice products (associated with sr.2018.14, sr.2017.17, and sr.2017.18) that use VMS and logbook data to describe detailed bottom trawling fishing activity have been updated to better ensure individual vessel anonymity. For these products, the level of gear grouping dis-aggregation at a c-square resolution of (0.05 degrees x 0.05 degrees) over one year were deemed too detailed by the original data provider subsequent to the release of the original advice. For these c-squares (containing 3 vessels or less) the value "-9" has been inserted to indicate that the data value for effort is missing from the c-square, but that the c-square does have a footprint from bottom trawling.
This core indicator evaluates the average chlorophyll-a concentration in surface water (0 – 10 m) during summer (June – September) during the assessment period 2016-2021. The measured average chlorophyll-a is a combined estimate of three types of data: 1) in-situ measurements from oceanographic monitoring data (surface water 0-10 m) and 2) earth observation data. 3) Ferrybox data. More detailed description on methodology can be found at HELCOM Core indicator report at https://indicators.helcom.fi/indicator/chlorophyll/ This dataset displays the result of the indicator in HELCOM Assessment Scale 4b (Division of the Baltic Sea into 19 open sea sub-basins and division of coastal areas to WFD water types or water bodies). The open sea areas have been assessed based on HELCOM Monitoring data, earth observation data and ferrybox data. Results for coastal areas are based on national WFD results reported by HELCOM EG EUTRO. Attribute information: "HELCOM_ID" = Code of the HELCOM scale 4b assessment unit "Country" = Country/ Opensea "level_2" = name of the subbasin "level_4" = Name of the HELCOM scale 4 assessment unit "Area (km2)" = Area of the HELCOM scale 4 assessment unit "Indicator" = Name of indicator “Season” = Season of the indicator (Summer = June-September) “Period” = Assessment period (20162021 = 2016 – 2021) Indicator value (ES) = Indicator value calculated for the assessment unit "Standard deviation (STD)" = Standard deviation of data used for calculating ES "Number of samples " = Number of samples by assessment unit "Theshold value (ET)" = Commonly agreed thershold value "Ratio between ES and ET (ER)" = Eutrophication ratio: Ratio between ES and ET (in case of indicator with positive response to eutrophication) "ES_SCORE” = Confidence based on the data used for calculating ES "ET_SCORE” = Confidence of target-setting procedure "I_SCORE” = Confidence (%) = average of ES-Score and ET-Score "Indicator Weight" = Indicator Weight in integrated eutrophication assessment “Status” = Status of the indicator (“Good”, “Not good”, “Not assessed” or "Not applicable") “Confidence” = Confidence of result based on I-SCORE (“High”, “Moderate” or “Low”) "AULEVEL" = Assessment unit level used for the indicator
Use constraints: Data can be used freely given that the source is cited (following creative commons license CC-BY). The source should be cited as: “HELCOM HOLAS 3 Dataset (2023)"
Data source: The average chlorophyll-a was combined estimate of two types of data: 1) In-situ monitoring data provided by the HELCOM Contracting Parties, and kept in the HELCOM COMBINE database, hosted by ICES (www.ices.dk), added with data from the Gulf of Finland year database, hosted by the Finnish Environment Institute. 2) FerryBox flow-through data is reported to ICES by Contracting Parties, to be included into the eutrophication assessment database. It is reported according to the QA/QC guidance for FerryBox Flowthrough information, providing adequate metadata and quality information, including the following: • (arithmetic and) geometric mean • mode (most frequently occurring value in dataset) • standard deviation • percentiles (5,25, 50, 75, 95) • N of observations that were used to derive statistics Additional information: http://www.helcom.fi/baltic-sea-trends/indicators/chlorophyll-a
The dataset contains the extent of the land claim (permanent or temporary establishments of the sea) and the type of construction reported by the Contracting Parties for the period 2016-2021. The data was made available by HELCOM Contracting Parties in response to a data call. The data was reported by Denmark, Estonia, Finland, Poland, Russia, and Sweden. The activity was declared as not relevant in Germany and Latvia. Attribute specification and units (for points and polygons): Name: Name of the site Descrip: Brief description of the type of land claim Year: Year of construction, especially if built between 2016-2021 Area: Area in km2 Notes: Notes regarding the data Attribute specification and units (for lines): Country: Contracting Party that reported the information Type: Brief description of the type of land claim Estimated: Estimated year Area: Area in km2 Name: Name of the site descripto: Description of the site in national language Notes: Notes regarding the data
The dataset was created in order to update the information for the Baltic Sea Region for the HELCOM Assessments. Data was collected by the HELCOM Secretariat in 2022 and early 2023. The data was made available by HELCOM Contracting Parties in response to a data call. The data was reported by Denmark, Estonia, Finland, Poland, Russia, and Sweden. The activity was declared as not relevant in Germany and Latvia. National remarks: Estonia: According to orthophotos by Maa-Amet (Estonian Land Board). During the HOLAS 3 reference period (2016-2021) only one land claim event took place - in Tallinn (construction of Reidi Street). Finland: Data extracted from Vesistötyöt VESTY database. Construction and other activities conducted in water areas are reported to VESTY, mainly by ELY Centres. Includes land claim sites from before 2016. Poland: The data comes from the location decisions for the construction or use of artificial islands 2016-2021, structures and devices, issued on the basis of the Act by the Director of the Maritime Office in Gdynia. Sweden: This dataset is based on information from court decisions, the Swedish maritime administration and three different map providers: Lantmäteriet [1] and Google Earth [2]. Court decisions are used to identify places where land claims have occurred. There is a bias towards places where dredging has occurred since this type of information has been characterized in another dataset. This identification process has been complemented with notification from the Swedish maritime administration [1] and searching in the Swedish Agency for Marine and Water Management archives for cases related to land claims. However, these archives do not generally contain decisions on small land claims, such as small pier constructions, since these types of decisions are ruled by county administrative boards or municipalities. There are likely many more places where land claims have occurred in Sweden during this time period. Please also note that some land claims also function as breakwaters. If the breakwater implies permanent change it has been included in this data set, if not, the breakwater has instead been included in the coastal defense dataset. [1] https://kso.etjanster.lantmateriet.se/ [2] https://www.google.com/earth/desktop/ Denmark: The shapefiles (point/”punkt”, line/”linje” or area/”polygon”) contain data of approved projects from 2016-2021 regarding landfilling and seabed modification (deepening) regarding the Coastal Protection Act § 16 a. There are no distinct categories named land claim and watercourse modification, so the ones could involve land claim and/or watercourse modification were added to the shapefile. All records provided are included in the data. National data provider: Estonia: Estonian Land Board (Maa-Amet) Finland: Finnish Environment Institute Poland: Maritime Office in Gdynia Sweden: Swedish Agency for Marine and Water Management Denmark: The Danish Environmental Protection Agency
Summary This dataset was collected by HELCOM Secretariat during the HELCOM MORE project and represents monitoring stations in the Baltic Sea Description This dataset contains all shared hydrographical stations in the Baltic Sea as reported to the HELCOM MORE project. It was collected and published at the beginning of 2013.The data came originally from the CORESET project. Contracting Parties were then asked to complete and check the info.
Use constraints: HELCOM data can be used freely for non-commercial purposes. Users are requested to cite HELCOM as the data source when using downloaded datasets in publications.
This dataset contains all shared hydrographical stations in the Baltic Sea as reported to the HELCOM MORE project. It was collected and published at the beginning of 2013.The data came originally from the CORESET project. Contracting Parties were then asked to complete and check the info.
This core indicator evaluates the status of the marine environment based on concentrations of heavy metal Mercury (Hg) in fish muscle. Quantitative threshold value is used to evaluate if core indicators status is "Achieve", "Fail" or "Not assessed". Threshold values are based on Environmental quality standards (EQS), defined at EU level for substances included in the priority list under the Water Framework Directive. This dataset displays the result of the indicator in HELCOM Assessment Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "OBJECTID" = Object identification "HELCOM_ID" = Code of the HELCOM scale 4 assessment unit "Descriptio" = Description of the HELCOM scale 4 assessment unit "Contamination ratio" = Contamination ratio in biota for this substance "STATUS" = Status of the indicator in biota, which in this case is also the overall Status, one-out-all-out (“Achieve”, “Fail” or “Not assessed”) "AULEVEL" = Assessment unit level used for the indicator
Use constraints: Data and resulting data products (tables, figures and maps) available on the indicator web pages can be can be used freely given that the source is cited (following creative commons license CC-BY). The source should be cited as: “HELCOM (2018) Metals (Mercury). HELCOM core indicator report. Online. [Date Viewed], [Web link].”
The indicator is based on data held in the HELCOM COMBINE database, hosted at the International Council for the Exploration of the Seas (ICES). All available data on Mercury in fish muscle up to 2016 were used. Evaluation is carried out using an agreed R-script that runs a statistical analysis. The overall confidence of the indicator evaluation is high. Additional information: http://www.helcom.fi/baltic-sea-trends/indicators/metals/ Link to metadata of dataset used for indicator calculation: http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/2d7c004d-29bc-415d-a7a1-03511e0e3365
Furcellaria areas of production remained the same since the HELCOM Second Holistic Assessment of the Ecosystem health of the Baltic Sea (HOLAS 2). The production figures were extracted from EUROSTAT. Data contain data for the period 2016-2020 for Estonia. Attribute specification and units: Dredged_ar: Furcellaria dredging area (km2, ND = no data available) Total: Amount (Sum) of dredged Furcellaria during the period (tonnes) Average: Calculated annual average of the amount of dredged Furcellaria (tonnes/year) Area_km2: Area (fishing area) within dredging occurs (km2), area do not represent actual dredging area. F2016 - F2020: Amount of dredged Furcellaria (tonnes / year)
Use constraints: Data can be used freely given that the source is cited (following creative commons license CC-BY). The source should be cited as: “HELCOM HOLAS 3 Dataset (2023)”.
The area of production of Furcellaria harvesting remained the same since the HELCOM Second Holistic Assessment of the Ecosystem health of the Baltic Sea - HOLAS 2 (https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/e72b634a-e4ca-4c1d-a3af-99a24aa10be8). The production figures were extracted from EUROSTAT (https://ec.europa.eu/eurostat/databrowser/view/FISH_LD_EE__custom_2462181/default/table?lang=en). in April 2022. Data contain the ‘Red seaweed’ production sites in Estonia for the period 2016-2020.
The dataset contains point data describing the location of oil platforms in the Baltic Sea as reported by the Contracting Parties for the period 2016-2021. The data was made available by HELCOM Contracting Parties in response to a data call. The data was reported by Poland (HOLAS 2 data) and Russia. The activity was declared as not relevant by Estonia, Denmark and Latvia. Attribute specification and units: COUNTRY: The country where the structure is located LATITUDE: Latitude of the point location LONGITUDE: Longitude of the point location Name: Name of the structure Notes: Notes regarding the data
The dataset was created in order to update the information for the Baltic Sea Region for the HELCOM Assessments. Data was collected by the HELCOM Secretariat during 2022 and early 2023. The data was made available by HELCOM Contracting Parties in response to a data call. The data was reported by Poland (HOLAS 2 data: https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/fddc27ec-b6ae-407b-9dd8-f31a42d75412) and Russia. The activity was declared as not relevant by Estonia, Denmark and Latvia.
Summary This marine benthic landscape map of the Baltic Sea includes 60 broad scale habitat types which are defined according to different combinations of bottom substrate, photic zone and salinty level. Description This dataset was produced by the EU funded Balance project and maps the ecologically relevant benthic landscapes (broad-scale benthic habitats) of the Baltic Sea, identified on salinity, sediments and photic depth (as light touching the seabed). This marine benthic landscape map of the Baltic Sea includes 60 broad scale habitat types which are defined according to different combinations of bottom substrate, photic zone and salinty level. Each habitat is described with a three digit grid code, where the first digit refers to bottom substrate, the second digit refers to photic zone and the third refers to salinity. Description of grid code digits: Bottom substrate: 1= bedrock, 2 = hard bottom, 3 = sand, 4 = hard clay, 5 = mud Photic zone: 1 = photic, 2 = aphotic Salinity: 1 = 0-5 psu, 2 = 5 - 7.5 psu, 3 = 7.5 -11 psu, 4 = 11 - 18 psu, 5 = 18-30 psu, 6 = <30 psu The approach to marine landscape mapping within the Baltic Sea is based on the use of available physical, chemical and hydrographic data to prepare ecologically meaningful maps for areas with little or no biological information. It is basically a broad-scale map-ping/modelling approach based on presenting geophysical and hydrographical data in thematic GIS layers from which “marine landscapes” can be derived. In order to limit the number of possible landscapes the thematic layers are typically presented in a lim-ited number of categories reflecting shifts in major ecological entities (e.g. distinguish between habitats assumed to be within or below the photic zone). The approach aims to recognise the ecological linkage between major assemblages of species and the physical environment in which they reside. It can be applied to charac-terising broad-scale benthic complexity using parameters such as surface sediment, temperature, water motion, photic depth and slope and for semi-enclosed areas, like the Baltic Sea, salinity and oxygen content.Due to the limited resolution of the dataset, it should be only used for broadscale purposes. The dataset also requires verifications. (The quality of data collated differs from high to low-resolution data. Some of the modelled datasets has 7km resolution while others have ~600m resolution. All datasets were re-gridded to a 200 × 200m grid. This process ensures data continuity but it does not increase the out-put map resolution.)
Use constraints: The data can be used freely for non-commercial purposes but EU-funded Balance project should always be cited as the data source.
As the first step the necessary environmental parameters and data sets were selected for the identification of marine landscapes in the Baltic Sea. The next step was to harmonise and standardise the selected individual data sets and present them in unified formats. To produce the broad-scale benthic marine landscape map from a number of different sources efficiently raster map algebra in a GIS was used. The primary environmental parameters included for the developing the benthic marine landscapes were sediment, the photic – non-photic zone (where 1% of available light reaches the seabed) and salinity as they are important for determining broad-scale dis-tribution of species in a regional Baltic Sea context. National seabed sediment classification categories were harmonized in order to produce one classification scheme, which had to be as simple as possible, but still take into account biological importance. The resulting classification scheme consisting of five sediment classes are applied in the mapping and modelling of the Baltic Sea marine landscapes. These are: I. Bedrock. II. Hard bottom complex, includes patchy hard surfaces and coarse sand (some-times also clay) to boulders. III. Sand including fine to coarse sand (with gravel exposures). IV. Hard clay sometimes/often/possibly exposed or covered with a thin layer of sand/gravel. V. Mud including gyttja-clay to gyttja-silt. Available light at the seabed was included and divided into two categories, the photic and non-photic zones. The Baltic Sea is characterised by some fairly stable salinity gradients ranging from > 30psu in the northern Kattegat to almost fresh water in the Bothnian Bay. As the salt concentration influences marine life in a number of different ways, salinity was split into 6 categories reflecting the distribution of structuring species. The approach used by the BALANCE project is fully applicable for an ecologically relevant characterisation of the Baltic Sea, however, end users might find it necessary to validate and further refine and improve the maps. Such validations and refinements are necessary in order to fully exploit the potential application of the maps and for linking them to the implementation of national and international legislation. For more information, see the Balance technical summary report no. 2 Baltic Sea marine landscapes and habitats: Mapping and modelling (http://balance-eu.org/xpdf/balance-technical-summary-report-no-2-4.pdf).
Summary Estimated observations of the biotope AB.H3L5 were collected from the Baltic Sea area by expert judgements for HELCOM Red List of biotopes, habitats and biotope complexes. Description Baltic aphotic muddy sediment dominated by Astarte spp.The HELCOM Red List of Baltic Sea underwater biotopes, habitats and biotope complexes (2013) is an updated and improved version of the Red List assessment of marine and coastal biotopes and biotope complexes published in 1998. The classification of the report follows the proposed International Union for Conservation of Nature (IUCN) criteria and assessment principals but with some modifications for the Baltic Sea.Altogether, the HELCOM Underwater Biotope and habitat classification (HELCOM HUB) includes 209 biotopes of which 59 were red-listed. Many of the red-listed biotopes are located in deep areas of the Baltic Sea due to oxygen-free nature as well as in the southwestern Baltic Sea due to the salinity restricted distribution of species in certain biotope. The HELCOM assessment relies heavily on expert judgment and inference, and the questionnaire data represents the estimated presence-absence data not in-situ measured data. This must be taken in account when observing the map presentation. The biotopes are shown on the map using the EEA 100 km grid. This dataset displays estimated presence of AB.H3L5 according to HELCOM RED LIST assessment experts:The Astarte borealis is found in the Western parts of the Baltic Sea, it’s most eastern populations appearing in the Bornholm Basin. Dense populations of the Astarte elliptica were common on the muddy sediments of the Kiel Bay at depths greater than 15 meters (Trutschler & Samtleben 1988). The distribution map indicates the area in the 100 x 100 km grid where environmental conditions required by the biotope are known to occur and the biotope is estimated to occur in the grid cells.(Data (expert judgements) collected in HELCOM RED LIST project, released in May 2013)
This core indicator evaluates the status of the marine environment based on concentrations of heavy metal cadmium (Cd) in seawater, biota and sediments. Quantitative thresholds are used to evaluate if core indicators status is "Achieve", "Fail" or "Not assessed". Threshold values are based on Environmental quality standards (EQS), defined at EU level for substances included in the priority list under the Water Framework Directive. This dataset displays the result of the indicator in HELCOM Assessment Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "OBJECTID" = Object identification "HELCOM_ID" = Code of the HELCOM scale 4 assessment unit "Descriptio" = Description of the HELCOM scale 4 assessment unit "AULEVEL" = Assessment unit level used for the indicator "Contamination ratio in biota" = Contamination ratio in biota for this substance "Status in biota" = Status of the indicator in biota (“Achieve”, “Fail” or “Not assessed”) "Contamination ratio in sediment" = Contamination ratio in sediment for this substance "Status in sediment" = Status of the indicator in sediment (“Achieve”, “Fail” or “Not assessed”) "Contamination ratio in water" = Contamination ratio in water for this substance "Status in water" = Status of the indicator in water(“Achieve”, “Fail” or “Not assessed”) "Overall Status" = Overall Status of the indicator according to one-out-all-out (“Achieve”, “Fail” or “Not assessed”)
Use constraints: Data and resulting data products (tables, figures and maps) available on the indicator web pages can be can be used freely given that the source is cited (following creative commons license CC-BY). The source should be cited as: “HELCOM (2018) Metals (Cadmium). HELCOM core indicator report. Online. [Date Viewed], [Web link].”
The indicator is based on data held in the HELCOM COMBINE database, hosted at the International Council for the Exploration of the Seas (ICES). All available data on cadmium concentrations in seawater, mussel and sediments up to 2016 were used. Evaluation is carried out using an agreed R-script that runs a statistical analysis. The overall confidence of the indicator evaluation is high. Additional information: http://www.helcom.fi/baltic-sea-trends/indicators/metals/ Link to metadata of datasets used for indicator calculation: http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/af827af9-ba0a-4e69-966d-52a44d6ecf25 http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/8cf593e1-d699-4253-83da-9cbcbbe96392 http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/69335f70-b990-4ee9-904f-2f2865b63e0c
Pressure layer combines all human activities that cause physical disturbance or damage to seabed. For several human activity datasets, spatial extents were given (table below). Buffers with decreasing value rates were applied to represent the impact distance of physical disturbance. The following human activities were combined into the physical disturbance layer; - Cables (under construction, 1 km buffer) - Coastal defence and flood protection (under construction, 500 m buffer) - Deposit of dredged material (500 m buffer for points and areas) - Dredging (maintenance) (500 m buffer for points and areas) - Extraction of sand and gravel (500 m buffer) - Finfish mariculture (1 km buffer) - Fishing intensity 2011-2016 average (subsurface swept area ratio) - Furcellaria harvesting - Pipelines (0,3 km buffer) - Recreational boating and sports - Shellfish mariculture - Shipping density - Wind farms (under construction) (1 km buffer) - Wind farms (operational) (0,1 km buffer) The human activity data sets were first processed separately covering the whole Baltic Sea and then summed together. In this integration, some data layers were down-weighted to arrive at a balanced pressure layer, as described below. High pressure intensity and/or slow recovery (weighting factor 1): Coastal defence and flood protection, Deposit of dredged material, Dredging, Extraction of sand and gravel and Fishing intensity Moderate to high (Weighting factor 0,8): Pipelines and Shipping density Moderate (Weighting factor 0,6): Finfish mariculture, Shellfish mariculture and Wind farms (under construction) Low to moderate (Weighting factor 0,4): Cables Low (Weighting factor 0,2): Maerl and Furcellaria harvesting, Recreational boating and sports and Wind farms (operational) Harbours and marinas were left out from the physical disturbance pressure to avoid double counting due to their representation in the shipping density and recreational boating and sports data sets. Detailed information about this pressure layer can be found in the indicator report.
Data source: See separate fact sheet on human activities listed below Data quality: Gaps may occur due to lack of data from all the countries. Also, missing data values were given with 25% percentile of remaining values in a dataset which reduces the accuracy of the data. Attribute information: Index value, representing combined pressure from several human activities. Spatial coverage: Entire Baltic Sea. Fishing intensity data missing from RU. Spatial resolution: Original data as vectors, shipping density and recreational boating and sports as 1 x 1 km grid, fishing intensity as 0,05 x 0,05 c-square degree grid. Finally converted to 1 km x 1 km grid. Human activity; Spatial extent; Attenuation gradient; Data calculations Cables (construction); 1 km; with sharp decline after 0.5 km; Location of constructed cables, Normalised Coastal defence and flood protection (construction); 0.5 km; sharp decline; Normalised Deposit of dredged material; 0,5 km; sharp decline; Sum amount of deposited material (tonnes), log-transformed, normalised Dredging (maintenance); 0,5 km; sharp decline; Sum amount of dredged material (tonnes, m³), For missing values 25% percentile of existing information was given, all sites where no information about dredging type given, was considered as maintenance dredging, log-transformed, normalised Extraction of sand and gravel; 0,5 km; sharp decline; Average amount of extracted material (m³), For missing values 25% percentile of existing information was given, log-transformed, normalised Finfish mariculture; 1 km; linear decline; Average P load, For missing values 25% percentile of existing information was given, weighted with bed exposure, log-transformed, normalised, weighting factor 0,6 Fishing intensity; ; ;Average of seabed surface contacting gear fishing intensity 2011-2016 (subsurface swept area ratio), log-transformed, normalised Furcellaria harvesting; ; ;Amount/area of harvested material normalised Pipelines (operational); 0.3 km; linear decline; Normalized, multiplied (with 0.8) to represent 80% of maximum possible intensity Recreational boating and sports; ; ; Fuel usage range in a 1km x 1 km cell, log-transformed, normalised Shellfish mariculture;1 km; linear decline; Average production (kg), For missing values 25% percentile of existing information was given, log-transformed, normalised Shipping density; ; linear decline; Average of total shipping density in a 1km x 1 km cell, rescaled in relation to water depth, log-transformed, normalised Wind turbines (construction); 1 km; sharp decline after 0.5 km; Normalised Wind turbines (operational); 0.3 km; linear decline; Normalised
Detected spills of mineral oil and other substances
This dataset contains points of information describing the location and size of spills of mineral oil observed during aerial surveillance flights by HELCOM Contracting Parties during 1998-2023. The data covers detections from fixed-wing aircraft only. Since 2014 Contracting Parties have also reported spills of other substances and unknown substances. The purpose of the regional aerial surveillance is to detect spills of oil and other harmful substances and thus prevent violations of the existing regulations on prevention of pollution from ships. Such illegal spills are a form of pollution which threatens the marine environment of the Baltic Sea area. Further information on detected spills in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ and https://helcom.fi/action-areas/response-to-spills/aerial-surveillance/ The dataset contains the following information: Country Year Spill_ID = A unique code which will enable each individual spill to be individually identified FlightType = The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "SC", Tour d’Horizon = “TDH” Date = The date of the detection (dd.mm.yyyy) Time_UTC = The time of the detection in UTC (hh:mm) Wind_speed = The wind speed at the time of the detection (m/s) Wind_direc = The wind direction in degrees at the time of the detection (degrees) Latitude = The latitude of the detection (decimal degrees, WGS84) Longitude = The longitude of the detection (decimal degrees, WGS84) Length__km = The length of the detection (km) Width__km = The width of the detection (km) Area__km2_ = The area of the detection (km2) Spill_cat = Spill/pollution category: Mineral Oil = “Oil", Other Substance = "Other substance" , "Unknown substance" = “Unknown” EstimVol_m = If Spill_cat="Oil", then estimated min. volume of oil spill. Volume of the detection confirmed/observed as mineral oil as calculated using the Bonn Agreement Oil Appearance Code using the lower figure (BAOAC minimum) in m3. Vol_Category = Category of the detection: <0,1m3 = “1”, <0,1-1m3 = “2”, 1-10 m3 = “3”, 10-100 m3 = “4”, >100 m3 = “5” Type_substance = If Spill_cat="Other substance" or "Unknown. Product name or type of OS or GAR substances that could be identified (in case of known polluter, or via visual identification - cf. BAOAC Atlas). - Examples for OS: vegetable oils (palm oil sun flower oil, soya oil etc.), fish oil, molasses, various chemicals (methanol, biodiesels/FAME, toluene, paraffines etc.); Examples of GAR: solid cargo residues (e.g. coal residues), plastics, fish nets, … OR "Unknown" (in case the type of substance could not be identified) Polluter = Type of polluter source: Offshore Installation = “Rig”, Vessel = “Ship”, Other Polluter or source (e.g. land based source) = “Other”, Unknown = “Unknwon” (in case of an “orphan” spill that cannot be linked to a polluter) Remarks = Any additional information to inform on particular situations Description of marine litter sightings
Use constraints: HELCOM data is free for public use, however, HELCOM should always be cited as the data source.
Data on illegal oil discharges observed by aerial surveillance by HELCOM Contracting Parties was originally submitted and processed by Germany. In 2004 it was decided that HELCOM Secretariat will take over the responsibility of processsing the data and producing maps. Data is annually reported to HELCOM Secretariat and quality assured and verified by HELCOM IWGAS working group. Dataset updated in August 2024.