This dataset is built from the following Human activities dataset: • Hunting of seals The number of hunted seals (see separate metadata on hunting of seals) were averaged over 2011-2014 separately for grey seals, ringed seals and harbour seals (e.g. number of hunted grey seals / year). In Sweden the numbers of hunted grey seals in 2011 (74) were reported for the whole Swedish territorial waters), but here the numbers were set only to Swedish Gulf of Bothnia, as corresponding numbers were reported there in 2013 (75) and 2014 (65). The area of the reporting unit was used to calculate the number of hunted seals / km2 and the data was converted to 1km x 1km grid. For the Baltic Sea Impact Index, the values were normalized. Normalized value 0.5 was set to the level of quota for hunting of seal species in the Baltic Sea. The following quotas for hunting were used: Grey seal: 2000, Ringed seal: 350, Harbour seal 230.

This dataset represents the underlying biota data on core indicator Heavy metals – Mercury.The 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. The Core indicator 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: "region" = name of subbasin "country" = country "station" = Unique code for the station "stationNam" = name for the station "determinan" = determinant parameter (HG = Mercury) "detGroup" = the grouping of determinands used to display the results "species" = species of measurement "_shape" = shape used to map assessment results "colour" = colour used to map assessment results "l3area" = HELCOM assessment unit on scale 3 "l4area" = HELCOM assessment unit on scale 4 "nyall" = total number of years of data "nyfit" = number of years of data used in the assessment "nypos" = number of years with at least one measurement above the limit of detection "lastyear" = most recent year of data "prtrend" = the significance of the change over the most recent 20 years; for the assessment conducted in November 2017 and published in June 2018, this is the period 1996-2016 "rtrend" = annual ‘linear’ change over the most recent 20 years "meanLY" = fitted value in last monitoring year "clLY" = upper one-sided 95% confidence limit on fitted value in last monitoring year "HQS" = Threshold value "HQSdiff" = difference between clLY and HQS "HQSbelow" = whether the mean value in the last monitoring year is significantly below HQS

This map shows probability of detection of harbour porpoise (Phocoena phocoena) in the Baltic Sea, for May – Oct. This dataset was produced by the EU LIFE+ funded SAMBAH project and maps the probability of detection of harbour porpoises in the study area, which extends from the Åland Islands in the north to the Darss and Limhamn underwater ridges in the southwest. The study area excludes areas of depths greater than 80 m. Probability of detection was modelled using General Additive Modelling and static covariates such as depth, topographic complexity, month, spatial coordinates and with time surveyed as a weight. Monthly predictions were done on a 1x1 km grid and averaged to result in seasonal distribution maps for May – Oct and Nov – Apr. This division of the year is a result of visual inspection of data and results, showing a clear separation of spatial clusters of harbour porpoises in the summer season May – Oct and a more dispersed pattern with no clear separation in Nov – Apr.

This dataset depicts risk of oil spill from illegal spills. The modeled risk is calculated for the years 2008/2009. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, 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/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.

This web mapping service contains datasets on land-based pollutions sources, human activities and aggregated pressure layers used for Baltic Sea Pressures and Impact Index. The service is created with ArcGIS Server 10.6.1 and can be accessed via ArcGIS REST interface or OGC WMS. The service is used by HELCOM Map and Data service.

This dataset represents the underlying biota data on core indicator Polyaromatic hydrocarbons (PAH) and their metabolites. The core indicator evaluates the status of the marine environment based on concentrations of Polyaromatic hydrocarbons (PAH) in sediment and biota. Quantitative threshold value is used to evaluate if core indicators status is Achieve, Fail or Not assessed. As There is no commonly agreed threshold value for measuring metabolites available, this report only considers concentrations of contaminants. 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: "region" = name of subbasin "country" = country "station" = Unique code for the station "stationNam" = name for the station "determinan" = determinant parameter (FLU = fluoranthene, BAP = benzo(a)pyrene) "detGroup" = the grouping of determinands used to display the results "species" = species of measurement "_shape" = shape used to map assessment results "colour" = colour used to map assessment results "l3area" = HELCOM assessment unit on scale 3 "l4area" = HELCOM assessment unit on scale 4 "nyall" = total number of years of data "nyfit" = number of years of data used in the assessment "nypos" = number of years with at least one measurement above the limit of detection "lastyear" = most recent year of data "prtrend" = the significance of the change over the most recent 20 years; for the assessment conducted in November 2017 and published in June 2018, this is the period 1996-2016 "rtrend" = annual ‘linear’ change over the most recent 20 years "meanLY" = fitted value in last monitoring year "clLY" = upper one-sided 95% confidence limit on fitted value in last monitoring year "HQS" = Threshold value "HQSdiff" = difference between clLY and HQS "HQSbelow" = whether the mean value in the last monitoring year is significantly below HQS

This map presents the Special Protection Areas (SPAs) with reported wintering areas for birds. The spatial data on SPAs were gathered from the HELCOM contracting parties by Lund University, Sweden. In the data, the countries also indicated whether the sites were designated mainly due to wintering or breeding birds in the area. For Denmark, the information was obtained from standard forms for Natura 2000 sites. For Denmark, the data was updated after review process 20 February 2017. For Germany, the areas that were reported as “NA”(=information not available) were included in both breeding and wintering area maps. Many of the SPAs are both wintering and breeding areas. For the Baltic Sea Impact Index, the data was converted to 1 km x 1km grid cells.

Summary Estimated observations of the biotope AB.A1G4 and AB.M1G4 were collected from the Baltic Sea area by expert judgements for HELCOM Red List of biotopes, habitats and biotope complexes. Description Baltic aphotic rock and boulders or mixed hard and soft substrates dominated by soft corals (Alcyonacea)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.A1G4 and AB.M1G4 according to HELCOM RED LIST assessment experts:The biotopes occur in the Kattegat and Belt Sea on rocky substrates in exposed areas of high salinity. The distribution map indicates the area in the 100 x 100 km grid where biotopes are estimated to occur based on environmental gradients and the availability of the specific substrate.(Data (expert judgements) collected in HELCOM RED LIST project, released in May 2013)

This dataset represents the underlying data on the core indicator Abundance of waterbirds in the breeding season during HOLAS 3. The data results from a data call carried out by HELCOM for the State of the Baltic Sea report. Spatial data was provided as points, lines, and polygons. Further data in excel format was also provided.

Distribution of Furcellaria lumbricalis based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of Furcellaria were submitted, originally gathered in national mapping and monitoring campaigns, or for scientific research purposes. From Estonian waters, a predictive model was used (200m resolution), that was converted to presence/absence using minimized difference threshold (MDT) criteria. For Poland, only confirmed occurrence of Furcellaria were included (Slupsk bansk, Rowy reef and reef at Orlowo cliff). All data (Furcellaria points and the raster presenting predicted presence of Furcellaria) were generalized to 5km x 5km grid cells.