Summary Estimated observations of the biotope 1610 were collected from the Baltic Sea area by expert judgements for HELCOM Red List of biotopes, habitats and biotope complexes. Description Baltic esker islands with sandy, rocky and shingle beach vegetation and sublittoral vegetationThe 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 1610 according to HELCOM RED LIST assessment experts:Esker islands occur mainly in the northern parts of the Baltic Sea but are most abundant on archipelago coasts. Typical esker islands in Finland and Sweden are Hailuoto and Gotska Sandön. The islands may include dune areas, sandy plains, sandy banks or pine forests also common in other areas with sand or gravel. The distribution map indicates the area in the 100 x 100 km grid where biotope is known or inferred to occur (Naturvårdverket 2011, HELCOM 1998). The geologically defined occurrences are considered to be permanent.(Data (expert judgements) collected in HELCOM RED LIST project, released in May 2013)

Observations of Abra prismatica 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. Abra prismatica has been placed to the Red List category of Vulnerable 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.

The dataset contains information on commercial fishery with coastal and stationary gears in Baltic Sea in 2007 (Lithuanian data from 2008). Total catches/landings are given per ICES rectangle in tons. The dataset contains information on commercial fishery with coastal and stationary gears in Baltic Sea in 2007 (Lithuanian data from 2008). Total catches/landings are given per ICES rectangle in tons. Coastal and stationary gears (gear category 3) include traps, barriers, fences, weirs, pound nets and pot gears. The totalcatches/landings with this type of gears are 63,000 tons. The catches/landings per ICES rectangle are also given per species. Data was requested from HELCOM contracting parties through HELCOM HOLAS project. Landings/ catches data from Finland, Sweden, Denmark, Germany, Poland, Lithuania, Latvia and Estonia is based on national data, while Russian data is based on the ICES report "Report of the Baltic Fisheries Assessment Working Group (WGBFAS)" (2008). Commercial fishery data was reported by the following persons/authorities to HELCOM Secretariat: Germany:Dr. Christopher Zimmermann (Institut für Ostseefischerei (OSF), Johann Heinrich von Thünen-Institut (vTI), Bundesforschungsinstitut für Ländliche Räume, Wald und Fischerei) Lithuania: Open sea: Irina Jakovleva (Fisheries Reguliation Division, Baltic Sea Fisheries Department, Fisheries Department under the Ministry of Agriculture); coastal: Rimantas Repecka (Head of Laboratory of Marine Ecology, Institute of Ecology of Vilnius University) Sweden: Jarl Engquist (Avdelningen för fiskerikontroll, Swedish Board of Fisheries) Latvia: Marina Fettere (Fishery and Information section, Latvian Fish Resources Agency) Finland: Pirkko Söderkultalahti (Finnish Game and Fisheries Research Institute) Estonia: Ministry of Agriculture Denmark: Troels Pade (The Danish Directorate of Fisheries, Ministry for Food, Agriculture and Fisheries) Russia: no contact person, data from ICES reports Poland: Malgorzata Marciniewicz-Mykieta (Departament Monitoringu i Informacji o Srodowisku, Glówny Inspektorat Ochrony Srodowiska) Abbreviation of species ABK=White Bream; ACC=Ruffe; ACH=Charr; ALR=Bleak; ANE=European anchovy; ANF=Anglerfishes; BLL=Brill; CAT=Rockfishes; CGO=Goldfish; COD=Cod; CRA=Marine crabs; CRE=Edible Crab; CSH=Common shrimp; DAB=Dab; DGS=Sourdog/Spint Dogfish; ELE=Eel; ELP=Eelpout; FAS=Asp; FBM=Bream; FBR=Freshwater breams; FBU=Burbot; FCC=Crucian carp; FCP=Common carp; FGR=Grayling; FID=Orfe (=Ide); FIE=Common dace; FLE=Flounder; FLX=Flatfishes; FPE=Perch; FPI=Pike; FPP=Zander (Pikeperch); FRD=Rudd; FRF=Freshwater fishes; FRO=Roach; FRU=Ruffe; FSB=Silver bream; FTE=Tench; FVE=Vendace (Cisco); FVI=Freshwater Vimba; GAR=Garfish; GPA=Gobies; GTA=Three-Spined Stickleback; GUG=Grey Gurnard; HAD=Haddock; HAL=Halibut; HER=Herring; HKE=Hake; HOM=Horse Mackarel; JAX=Jack and horse mackerels; LAR=River lamprey; LAU=Sea lamprey; LBE=European Lobster; LEM=Lemon Sole; LIN=Ling; LUM=Lumpfish; MAC=Mackerel; MLR=Thicklip Grey Mullet; MON=Monkfish; MQS=Four Spined Sculpin; MTL=Thick-lipped Mullet; MUL=Grey mullets; MUS=Blue mussel; MUX=Surmullets (= Red mullets); MZZ=Marine fishes; NBU=Round Goby NEP=Norway lobster; NOP=Norway pout; OTH=Other sp; PLA=Long-rough dab; PLE=Plaice; PLN=European Whitefish; POK=Saithe; POL=Pollack; PPZ=Common Prawn; PRA=Northern Pink Shrimp; SAL=Salmon; SAN=Sandeels; SKA=Skates, rays; SKB=Sticklebacks; SME=Smelt; SOL=Sole; SPR=Sprat; SQU=Squids; SRA=Atlantic searobins; SRE=Rudd; TAS=Twaite Shad; TGQ=Fourhorn Sculpin; TRB=Rainbow Trout; TRO=Trouts; TRR=Rainbow Trout; TRS=SeaTrout; TSD=Twaite Shad; TUR=Turbot; UNK=Unknown Catches; USK=Tusk; WEG=Greater Weever; WHB=Blue Whiting; WHF=Whitefish, Houting, Powan; WHG=Whiting; WIT=Witch; VIV=Vimba bream

A vector grid in 2 x 2 km resolution showing the environmental sensitivity and the underlying themes that have caused the final vulnerability in spring for the Baltic Sea area. 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/). Sensitivity map is based on datasets provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report. Field explanations: RS_SR: Rocky shores and stony reefs, Estuaries; Estuaries, Lagoons: Coastal lagoons, Bays: Shallow inlets and bays, Sandbanks: Underwater Sand banks, Beach: Sandy beaches, Seagrass: Sea grass, meadows, Spawning: Spawning area for fish with demersal eggs, Nursery: Nursery areas for fish on shallow water, Off_spawn: Offshore spawning areas for fish with pelagic eggs, Win_Birds: Wintering areas for sea and shore birds, Staging: Staging areas for migrating sea and shore birds, Breeding: Breeding areas for sea and shore birds, Moulting: Moulting areas for sea birds, Mammals: Marine Mammals, Protected: Protected areas, Aquacult:: Fish farms and aqua cultures, Sum: Weighted vulnerability index, Index: Not used Weighted vulnerability index is used to depict vulnerability for the Baltic Sea. Certain parameters have been used to map the environmental sensitivity to oil and each has been weighted for four seasons based on expert judgment. Two alternative sensitivity weighting matrices were also prepared in order to evaluate and validate the results. The sensitivity maps has been combined with the data on oil impact to model environmental damage, and to quantitatively compare the relative efect of the proposed new measures to reduce the risk, impact and damage of oil. Underlaying paramenters used in the vulnerability calculation can be obtained from HELCOM map service under Shipping\Risk Assessment (BRISK)\Environmental parameters -folder.

The dataset contains information on commercial fishery with unspecified gears in Baltic Sea in 2007 (Lithuanian data from 2008). Total catches/landings are given per ICES rectangle in tons. The dataset contains information on commercial fishery with unspecified gears in Baltic Sea in 2007 (Lithuanian data from 2008). Total catches/landings are given per ICES rectangle in tons. Unspecified gears (gear category 0) are gears that the countries have not defined more specifically. The total catches/landings with this type of gears is 150 tons. The catches/landings per ICES rectangle are also given per species. Data was requested from HELCOM contracting parties through HELCOM HOLAS project. Landings/ catches data from Finland, Sweden, Denmark, Germany, Poland, Lithuania, Latvia and Estonia is based on national data, while Russian data is based on the ICES report "Report of the Baltic Fisheries Assessment Working Group (WGBFAS)" (2008). Commercial fishery data was reported by the following persons/authorities to HELCOM Secretariat: Germany:Dr. Christopher Zimmermann (Institut für Ostseefischerei (OSF), Johann Heinrich von Thünen-Institut (vTI), Bundesforschungsinstitut für Ländliche Räume, Wald und Fischerei) Lithuania: Open sea: Irina Jakovleva (Fisheries Reguliation Division, Baltic Sea Fisheries Department, Fisheries Department under the Ministry of Agriculture); coastal: Rimantas Repecka (Head of Laboratory of Marine Ecology, Institute of Ecology of Vilnius University) Sweden: Jarl Engquist (Avdelningen för fiskerikontroll, Swedish Board of Fisheries) Latvia: Marina Fettere (Fishery and Information section, Latvian Fish Resources Agency) Finland: Pirkko Söderkultalahti (Finnish Game and Fisheries Research Institute) Estonia: Ministry of Agriculture Denmark: Troels Pade (The Danish Directorate of Fisheries, Ministry for Food, Agriculture and Fisheries) Russia: no contact person, data from ICES reports Poland: Malgorzata Marciniewicz-Mykieta (Departament Monitoringu i Informacji o Srodowisku, Glówny Inspektorat Ochrony Srodowiska) Abbreviation of species ABK=White Bream; ACC=Ruffe; ACH=Charr; ALR=Bleak; ANE=European anchovy; ANF=Anglerfishes; BLL=Brill; CAT=Rockfishes; CGO=Goldfish; COD=Cod; CRA=Marine crabs; CRE=Edible Crab; CSH=Common shrimp; DAB=Dab; DGS=Sourdog/Spint Dogfish; ELE=Eel; ELP=Eelpout; FAS=Asp; FBM=Bream; FBR=Freshwater breams; FBU=Burbot; FCC=Crucian carp; FCP=Common carp; FGR=Grayling; FID=Orfe (=Ide); FIE=Common dace; FLE=Flounder; FLX=Flatfishes; FPE=Perch; FPI=Pike; FPP=Zander (Pikeperch); FRD=Rudd; FRF=Freshwater fishes; FRO=Roach; FRU=Ruffe; FSB=Silver bream; FTE=Tench; FVE=Vendace (Cisco); FVI=Freshwater Vimba; GAR=Garfish; GPA=Gobies; GTA=Three-Spined Stickleback; GUG=Grey Gurnard; HAD=Haddock; HAL=Halibut; HER=Herring; HKE=Hake; HOM=Horse Mackarel; JAX=Jack and horse mackerels; LAR=River lamprey; LAU=Sea lamprey; LBE=European Lobster; LEM=Lemon Sole; LIN=Ling; LUM=Lumpfish; MAC=Mackerel; MLR=Thicklip Grey Mullet; MON=Monkfish; MQS=Four Spined Sculpin; MTL=Thick-lipped Mullet; MUL=Grey mullets; MUS=Blue mussel; MUX=Surmullets (= Red mullets); MZZ=Marine fishes; NBU=Round Goby NEP=Norway lobster; NOP=Norway pout; OTH=Other sp; PLA=Long-rough dab; PLE=Plaice; PLN=European Whitefish; POK=Saithe; POL=Pollack; PPZ=Common Prawn; PRA=Northern Pink Shrimp; SAL=Salmon; SAN=Sandeels; SKA=Skates, rays; SKB=Sticklebacks; SME=Smelt; SOL=Sole; SPR=Sprat; SQU=Squids; SRA=Atlantic searobins; SRE=Rudd; TAS=Twaite Shad; TGQ=Fourhorn Sculpin; TRB=Rainbow Trout; TRO=Trouts; TRR=Rainbow Trout; TRS=SeaTrout; TSD=Twaite Shad; TUR=Turbot; UNK=Unknown Catches; USK=Tusk; WEG=Greater Weever; WHB=Blue Whiting; WHF=Whitefish, Houting, Powan; WHG=Whiting; WIT=Witch; VIV=Vimba bream.

This map shows the distribution and abundance of harbour seals across the Baltic Sea. The map was originally created for HELCOM Red list assessment of the Baltic Sea, using seal expert consultation. For the Baltic Sea Impact Index, the map was modified to represent four abundance classes, based on expert consultation. The map has been updated from the 1st version of HOLASII, based on expert consultation (HELCOM Seal EG).

The data set is showing seagrass meadows in the Baltic Sea area as polygon areas used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data from Poland and Russia. The dataset includes data provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report.

This dataset depicts risk of oil spill from overtaking and head-on collisions. 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.

A vector grid in 2 x 2 km resolution showing model results of environmental impact caused by spill of soluble chemicals from ships with size less than 5000 t 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).

A vector grid in 2 x 2 km resolution showing model results of environmental impact caused by spill of soluble chemicals from ships with size greater than 5000 t 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).