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From 1 - 10 / 967
  • 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 core indicator evaluates the status of the marine environment based on concentrations of perfluorooctane sulphonate (PFOS) in Baltic Sea fish and in a few assessment units using the secondary matrix seawater. Quantitative thresholds are used to evaluate if core indicators status is "Achieve", "Fail" or "Not assessed". Good status is achieved when the concentrations of PFOS are below the threshold value. 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 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”)

  • This dataset describes fishing intensity for Dredge mobile bottom contacting gear in 2015 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 pre-core indicator results developed under the HELCOM Third Holistic Assessment of the Ecosystem Health of the Baltic Sea (HOLAS 3).

  • This dataset contains the commercial Ports of Baltic Sea. The dataset was created in 2016 to be used in HELCOM Assessments. Attribute specification and units port: Name of the port Country: Name of the country LOCodes: the United Nations Code for Trade and Transport Locations

  • 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 dataset represents the underlying data on core indicator Population trends and abundance of seals 2018. This dataset contains reported observations for harbour seals. The core indicator evaluates seal distribution to determine whether it reflects good status. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. Attribute information: "Species" = Species (HS = Harbour seal) "Country" = Country (2 digit acronym) "Site" = Name of site "Area" = Area "HELCOM_SUB" = Name of HELCOM Level 2 assessment unit "Latitude" = Latitude (WGS84 decimal degrees) of site "Longitude" = Longitude (WGS84 decimal degrees) of site "N2000_ID" = Natura2000 ID, if the site is located within Natura 2000 site (if available) "Year" = Year of observation "Month" = Month of observation "Day" = Day of observation (if available) "Count" = Number of individuals observed on site "Count_type" = County type "Age" = Age of individuals (if available) "No_surveys" = Number of surveys "Method" = Method of survey "CV_Estimate" "Estimate_T" = Estimate type: Modelled / minimum (observed) "Source" = Data source

  • The indicator evaluates the coincidence of seasonal succession of dominating phytoplankton groups over an assessment period (commonly 5-6 years) using regionally established reference seasonal growth curves and wet weight biomass data. The indicator result value is based on the number of data points falling within the acceptable deviation range set for each monthly point of the reference growth curve and expressed as the percentage to the total number of data points. This result value is then compared to regionally relevant threshold values established to represent acceptable levels of variation. Strong deviations from the reference growth curves will result in failure to meet the thresholds set for acceptable variation, indicating impairment of the environmental status and a failure to meet good status. Seasonal succession of dominating phytoplankton groups displays the result of the indicator in HELCOM Assessment Scale 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and offshore areas). Attribute information: "HELCOM_ID" = HELCOM ID of the HELCOM scale 3 assessment unit "country" = Country "level_2" = Name of HELCOM scale 2 assessment unit "level_3" = Name of HELCOM scale 3 assessment unit "Area (km2)" = Area of HELCOM assessment unit "Overall Score" = Indicator value or result "Info" = additional info "AULEVEL" = Assessment unit level used for the indicator "Status" = Status of the indicator (“Achieve”, “Fail” or “Not assessed”) "Assessment" = Assessment unit name "Reference period" = Reference period(s) "Threshold value" = Threshold value (overall) "Indicator cyanobacteria" = Indicator value for cyanobacteria "Indicator dinoflagellates" = Indicator value for dinoflagellates "Indicator diatoms" = Indicator value for diatoms "Indicator Mesodinium rubrum" = Indicator value for Mesodinium rubrum "Indicator green algae" = Indicator value for green algae

  • Observations of Hippasteria phrygiana 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. Hippasteria phrygiana 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.

  • This dataset represents the underlying data on the pre-core indicator Diatom/Dinoflagellate index for HOLAS 3. The core indicator evaluates phytoplankton community structure to determine whether it reflects good environmental status. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed.