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  • This dataset was prepared within the COMPLETE project (Completing management options in the Baltic Sea Region to reduce risk of invasive species introduction by shipping, 2017-2021), funded by the EU Interreg Baltic Sea Region Programme, includes partner institutions from Estonia, Finland, Germany, Latvia, Lithuania, Poland, and Sweden, as well as HELCOM (https://www.balticcomplete.com/). The dataset includes only cleaning companies, which offer capture and filtration of the cleaning waste according the COMPLETE project recommendations. The administrations of the ports have to be contacted to check if cleaning is permitted and what requirements for a cleaning have to be fulfilled. There is included data layer of effective, environmentally sustainable, and appropriate antifouling systems for ships and boats operating in the Baltic Sea and summary of aspects concerning IWC of commercial ships and leisure boats. All information is without guarantee. We endeavour to ensure that the information presented here is complete, but despite regular follow-up checks and research, we cannot guarantee it. If a company is not listed, you can contact us any time and we will check whether it is included in the database and in the map. Our contacts: biofouling@bsh.de; solvita.strake@lhei.lv

  • Observations of Hippolyte varians were collected from the Baltic Sea area for HELCOM Red List species list. The HELCOM Red List of Baltic Sea species in danger of becoming extinct (2013) is the first threat assessment for Baltic Sea species that covers all marine mammals, fish, birds, macrophytes (aquatic plants), and benthic invertebrates, and follows the Red List criteria of the International Union for Conservation of Nature (IUCN). Almost 2800 species were considered in the Red List assessment and about 1750 were evaluated according to the IUCN Red List criteria. Hippolyte varians has been placed to the Red List category of Vulnerable (VU) species. Dataset for download contains spatial grid of the Baltic Sea. Distribution of the species can be found in corresponding name column. Values are coded: 1 - Present before year 2000 or in 2000, 2 - Present after year 2000, 3 - Present both before and after year 2000.

  • Information on the number of ships equipped with Automatic Identification Systems (AIS) crossing specific passage lines in the Baltic Sea during one year period. Years included in the attribute table are 2006 to 2020 (included). For visualisation in the map service, total amount of passage line crossings during 2020 is used. Description of the attribute table field headings: Location= name of the AIS crossing line Cargo_XXXX = Year XXXX cargo ship crossings Passg_XXXX = Year XXXX passenger ship crossings Tankr_XXXX = Year XXXX tanker ship crossings Other_XXXX = Year XXXX other ship crossings Data is available for the following passage lines (rows in attribute table): Bothnian Sea, Drogden, East of Gotland, Gulf of Finland, Irbe Strait, Kadet Fairway, Langeland East, North of Bornholm, Skaw, South of Bornholm, The Great Belt East Bridge, West of Gotland, Åland East and Åland West. For more information about shipping traffic in the Baltic Sea, see http://www.helcom.fi/Lists/Publications/BSEP152.pdf

  • A vector grid in 2 x 2 km resolution showing model results of environmental impact caused by spill of soluble oil from ships of all sizes as g oil / km^2 weighted.This dataset has been produced by COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). Fields: COL_NO (Dbl): Column ROW_NO (Dbl): Row WLoad (Dbl): Environmental impact (g oil / km^2 weighted).

  • This dataset contains all PCB in sediment monitoring station locations as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

  • Input of heat pressure dataset contains delta heat values from warm water discharge of - Discharge of warm water from nuclear power plants - Fossil fuel energy production. Discharge of warm water from nuclear power plants (2016-2021): 1 km buffer with steep decrease around outlet (Type D decline), composed of 4 rings [1]. Average input of heat load (Twh) of discharge of warm water from the nuclear power plant outlets. No data on heat load was available for the Leningrad nuclear power plant; therefore, the average heat load of discharge of warm water from nuclear power plants was given. Fossil fuel energy production (only location available): 1 km buffer with steep decrease around outlet (Type D decline), composed of 6 rings[12]. Heat load 1 (TWh) was given to all production sites, based on the average heat load of an individual production site in Helsinki. Heat load from both layers were summed and the layer was normalized. [1] Extent based on Ilus et al. 1986.

  • This core indicator evaluates the status of the marine environment based on population trends and abundance of the three species of seals that occur in the Baltic Sea. This dataset is for Grey seal. Good status is achieved for each species when the abundance of seals in each management unit is at least 10,000 individuals and the species-specific growth rate is achieved. Harbour seals in the southwestern Baltic and the Kattegat form a metapopulation, where subpopulations are genetically connected. The combined sizes of the subpopulations are here used to evaluate the Limit Reference level (LRL). The status evaluation is presented separately for the three seal species. The grey seal in the Baltic proper is evaluated as a single unit, whereas the Kattegat grey seals are evaluated separately. The status of ringed seals is evaluated for two management units. The status of harbour seals is evaluated for three management units. Grey seal dataset displays the result of the indicator in HELCOM Assessment Scale 1 (whole Baltic Sea) so that Baltic proper is evaluated as a single unit, whereas the Kattegat grey seals are evaluated separately. Attribute information: "level_1" = Name of assessment unit for the evaluation "AULEVEL" = Assessment unit level used for the indicator "Status" = Status of the indicator (“Achieve”, “Fail” or “Not assessed”) "Unit of indicator" = Unit of indicator (Abundance - Grey seal / % decrease) "Threshold" = Threshold value "Area (km2)" = Area of HELCOM assessment unit "Indicator" = Indicator value "ConfA" = Confidence of classification "ConfT" = Temporal confidence of classification "ConfS" = Spatial confidence of classification "ConfM" = Methodological confidence of classification "Notes" = Additional information

  • This dataset describes fishing intensity for OT DMF mobile bottom contacting gear in 2014 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.

  • This dataset contains results on HELCOM Assessment unit level 4b for shallow water oxygen. The information provided represents the data and results from the HELCOM HOLAS 3 indicator evaluation for eutrophication, covering the data period from 2016-2021. Shallow Water Oxygen results are reported by Contracting Parties based on data collected on national level by the Contracting Parties applying the indicator. Coastal assessment units (WFD water types or water bodies) are assessed based on WFD result data reported by countries. Indicator analysis of both open sea and coastal areas is carried out using the HEAT assessment tool (https://github.com/ices-tools-prod/HEAT). This analysis provide the basis of the HELCOM indicator evaluations and are utilized in the HOLAS 3 thematic assessment of eutrophication. Attribute description: ES = Eutrophication Status ES_SD = Standard Deviation ES_N = Number of Observations ES_N_Min = Minimum Number of Observations any given year ES_SE = Standards Error ES_CI = Confidence Interval ET = Eutrophication Target / Threshold ER = Eutrophication Ratio ACDEV = Acceptable Deviation BEST = ET / (1 + ACDEV / 100) EQR = Ecological Quality Ratio EQR_HG = Ecological Quality Ratio High/Good Boundary EQR_GM = Ecological Quality Ratio Good/Moderate Boundary EQR_MP = Ecological Quality Ratio Moderate/Poor Boundary EQR_PB = Ecological Quality Ratio Poor/Bad Boundary EQRS = Ecological Quality Ratio Scaled GTC = General Temporal Confidence STC = Specific Temporal Confindence TTC = Total Temporal Confidence GSC = General Spatial Confidence SSC = Specific Spatial Confidence TSC = Total Spatial Confidence TC = Total Confidence

  • Broad-scale habitat maps for the Baltic Sea have been produced in the EUSeaMap project in 2016. For German and Estonian marine areas, national (more accurate) datasets were used. German data included both substrate and light information (division into infralittoral/circalittoral). Estonian data included only substrate and the division into light regimes was obtained from the EuSeaMap data. Here, the habitat class “infralittoral sand” includes classes “Sand” and “Muddy sand” of the original data, in the infralittoral zone. The original polygon maps have been converted to 1 km x 1km grid. The scale of the substrate data used in broad-scale habitat maps varies from 1:250 000 to 1:1M (data from EMODnet Geology). Coarser resolution data has been used in areas, where 1: 250 000 substrate data has not been available. Due to different scales used, the habitat classes may show different sized patterns in different areas.