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    Datapaketet Skogsområden med högt biodiversitetsvärde i Finland består av 12 landsomfattande rasterkartor. Dessa 12 kartor är olika versioner av biodiversitetsvärden i Finlands skogar. Rasterkartornas upplösning är 96 x 96 meter. Enkla anvisningar för att läsa rasterkartorna: Ju större numeriskt värde, desto högre biodiversitetsvärde. National = Nationella analyser över biodiversitetsvärden i finska skogar (sex analyser) Regional = Regionala analyser över biodiversitetsvärden i finska skogar (ser ut som en karta men är i själva verket en samling av 13 separata analyser, region = Närings-, trafik- och miljöcentralen i Finland) (sex analyser) Sex olika prioriteringar av naturskydd gjordes med Zonation-programvaran (a) så att varje ny version innefattade allt som fanns med i tidigare, enklare analysversioner. National / Regional 1 Potentiell mängd död ved: Version 1 (V1) innefattade potentiell mängd död ved* på lokal nivå. Områden med många stora träd, många trädslag och ovanliga skogsmiljöer får högt lokalt värde. National / Regional 2 Potentiell mängd död ved och straff: Version 2 = V1 + straff för åtgärder som har negativ inverkan på biodiversiteten. De lokala värdena stämde bättre överens med verkligheten när man tog hänsyn till verkliga förändringar i skogar. National / Regional 3 Potentiell mängd död ved – straff + skogskonnektivitet: Version 3 = V2 + konnektivitet utifrån ekologisk likhet, avstånd och kvalitet mellan skogsområden (genomsnittlig försvagning 400 m). Ofragmenterade skogsområden av hög kvalitet framkommer. National / Regional 4 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter: Version 4 = V3 + observationer av rödlistade skogsarter. Habitat med rödlistade skogsarter framkommer. National / Regional 5 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter + skogslagen 10 §: Version 5 = V4 + konnektivitet till särskilt viktiga livsmiljöer enligt skogslagens 10 § (genomsnittlig försvagning 200 m). Värdefulla skogsområden och landskap i närheten av skyddade skogsområden med högt biodiversitetvärde framkommer. National / Regional 6 Potentiell mängd död ved – straff + skogskonnektivitet + RL-arter + skogslagen 10 § + PN-konnektivitet: Version 6 = V5 + konnektivitet till permanenta naturskyddsområden (genomsnittlig försvagning 2 km). Värdefulla skogsområden och landskap i närheten av skyddade områden med högt biodiversitetvärde framkommer. *Uträkning av potentiell mängd död ved (PMDV) PMDV beräknades i två skeden för varje skikt träslag i varje trädskikt: 1) Index för potentiell mängd död ved (PMDVi) togs fram med MOTTI-programmet (b, c, d). • 168 trädslag, fertilitetsklass och latitudkombinationer 2) PMDVi användes för att omvandla diameter och volym till potentiell mängd död ved • Genererades för hela Finland enligt bestånd med en upplösning på 16 x 16 m • Kombinerades sedan i 20 trädslag och fertilitetsklasser och förenades till 96 x 96 m upplösning. Inmatade data Den potentiella mängden död ved beräknades från beståndsdata (trädslag, medeldiameter, volym, vegetationsklass) vilket omfattade hela landet. Bästa möjliga data användes för varje område. - 24 % av Finland täcks av statligt ägda skogs- och naturskyddsområden och privata naturskyddsområden. o Forststyrelsens Naturtjänster: data om fält- och bestånd (5/2015) o Forststyrelsens Skogsbruk: data om fält- och bestånd (5/2015) o Privatägda naturskyddsområden: data om fält- och bestånd (5/2015) - 37 % av Finland täcks av privatägd skog som inte är naturskyddsområden: Skogscentralen, skogsdata (6.5.2005–6.5.2015) - 39 % av Finland täcks av o Naturresursinstitutet: Nationella skogsinventariedata som är tillverkat med skogsinventeringsmetod som utnyttjar information om riksskogstaxeringens provytor och satellitbilder 2013 (volym, trädslag, vegetationsklass och medeldiameter) Spatiella data om skogsbruk med negativ effekt på biodiversitet (till exempel fällning, gallring och dikning) (uppdaterades 10/2017) - Lantmäterivärket och Finlands miljöcentral SYKE: dikning i finsk torvmark (SOJT_09b1) - Forststyrelsens Skogsbruk: utförda anmälningar om användning av skog och dikningsfigurer - Skogscentralen: anmälningar om användning av skog och dikningsfigurer - University of Maryland/Dept. of Geographica Sciences: Global Forest Change/Forest Cover Loss 2000-2014 Observationer av skogsarter som har rödlistats av IUCN (sedan 1990): Finländska miljödatabasen HERTTA Spatiella data om särskilt viktiga livsmiljöer enligt skogslagens 10 § (uppdaterades 10/2017) - Forststyrelsens Skogsbruk och Skogscentralen Spatiella data om permanenta naturskyddsområden (uppdaterades 2/2018) - Forststyrelsens Naturtjänster: databas över naturskyddsområden SATJ Bakgrund Områden som är viktiga för skogens biodiversitet identifierades runt om i Finland för att främja hållbar markanvändning genom planering och naturskydd på lokal, regional och nationell nivå genom att informera markägare, ministerier och skogtjästemän. Vikten av sådana analyser beror på ökad användning av naturresurser och skadliga effekter på biodiversiteten tillsammans med begränsade naturskyddsresurser. Dessa betonar vikten av att utveckla kostnadseffektiv, ekologiskt hållbar markanvändning som dessa spatiella prioriteringar av naturskydd för skogar som görs för första gången för hela Finland. Prioriteringsmetoden Zonation användes för att hitta nya skogsområden med potentiellt högt skyddsvärde. Det övergripande målet var att tillämpa rikstäckande prioriteringsanalyser utifrån skogsdata relaterade till biodiversitet och markanvändningsdata som hade samlats in på beståndsnivå. De data som primärt tillämpades på skogsstruktur och -kvalitet (vegetationsklass, trädslag, volym och diameter) gav ekologiskt användbara ersättningar för skyddsvärde i barrskog. Resultaten visar att en betydande andel skog med högt biodiversitetsvärde finns utanför det aktuella nätverket för finska naturskyddsområden. Eftersom största delen av det finska skogsområdet är kommersiellt kan nätverket för naturskyddsområden inte stoppa den pågående nedgången av biodiversitet i skogarna. Nyckelord: biodiversitet, död ved, GIS, Handlingsplanen för den biologiska mångfalden i skogarna i södra Finland METSO, markanvändning, värdering, prioritering, skogar, skogarnas biodiversitet, skogsbruk, skogsskydd, spatiell prioritering av naturskydd,Zonation-programvara Datapaketet innefattar 12 rasterkartor och en .lyr-fil. .lyr-filen innehåller färgade symboler och beskrivningar av olika analysversioner. .lyr-filen är troligen endast genomförbar med GIS-programmet som tillhandahålls av ESRI Inc. Datapaketet kan hämtas från: http://www.syke.fi/en-US/Open_information/Spatial_datasets High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailjerad poster på engelska: http://www.syke.fi/en-US/Research__Development/Ecosystem_services/Specialist_work/Zonation_in_Finland/Zonation_materials/Posters eller http://www.syke.fi/download/noname/%7B771FF5A4-DAB6-45EE-8246-F38FC0090CAD%7D/138289 Detailjerad rapport på finska: http://hdl.handle.net/10138/234359 Mikkonen et al. 2018. Suomen ympäristökeskuksen raportteja 9/2018. Monimuotoisuudelle tärkeät metsäalueet Suomessa - Puustoisten elinympäristöjen monimuotoisuusarvojen Zonation-analyysien loppuraportti. Andra källor: a) Moilanen et al. 2014. Zonation–Spatial Conservation Planning Methods and Software. Version 4. User Manual. See also www.syke.fi/Zonation/en b) Hynynen et al. 2015. Eur. J. For. Res. 134/3. Long-term impacts of forest management on biomass supply and forest resource development: a scenario analysis for Finland. c) Hynynen et al. 2014. Metlan työraportteja 302. Scenario analysis for the biomass supply potential and the future development of Finnish forest resources. d) Salminen et al. 2005. Comput. electron. agr. 49/1. Reusing legacy FORTRAN in the MOTTI growth and yield simulator. Användar lisens: Creative Commons 4.0. © SYKE Datasources: Finnish Forest Centre, Metsähallitus, Natural Resources Institute Finland, National Land Survey of Finland, Hansen/UMD/Google/USGS/NASA

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    Forests of high biodiversity value 2018 (Zonation) datapackage consists of 12 nationwide raster maps from Finland. These 12 maps are all different versions of biodiversity values of Finnish forests. Resolution of these raster maps is 96 meters x 96 meters. Simple instructions for reading the raster maps: The bigger the numeric value the higher the biodiversity value. NAT = National scale analyses of biodiversity values of Finnish forests (6 analysis) REG = Regional scale analyses of biodiversity values of Finnish forests (map looks like one but is in reality a collection of 13 separately done analysis, region = Centre for Economic Development, Transport and the Environment in Finland) (6 analysis) Six different spatial conservation prioritizations were made with Zonation Software (a) so that each new version included everything that had been included in previous, simpler, analysis versions. NAT / REG 1 Decaying wood potential: Version 1 (V1) included the local decaying wood potentials*. Areas with lot of large trees, many tree species and rare forest environments get high local value. NAT / REG 2 Decaying wood potential – penalties: Version 2 = V1 + penalties for forestry operations with negative impact on biodiversity. More realistic local values when taking into account real life changes in forests. NAT / REG 3 Decaying wood potential – penalties + forest connectivity: Version 3 = V2 + connectivity based on ecological similarity, distance and quality between forest patches (attenuation avg. 400m). Unfragmented high value forests areas emerge. NAT / REG 4 Decaying wood potential – penalties + forest connectivity + RL species: Version 4 = V3 + observations of Red List forest species. Red List forest species habitats emerge. NAT / REG 5 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§: Version 5 = V4 + connectivity to woodland key habitats protected by Finnish Forest Act 10 § (attenuation avg. 200m). Valuable forest areas and landscapes close to protected high biodiversity forest patches emerge. NAT / REG 6 Decaying wood potential – penalties + forest connectivity + RL species + FFA 10§ + PA connectivity: Version 6 = V5 + connectivity to permanent conservation areas (attenuation avg. 2km). Valuable forest areas and landscapes close to protected high biodiversity areas emerge. *Calculation of Decaying wood potential (DWP) DWP was calculated for every strata of tree species in every crown storey class in 2 stages: 1) Decaying wood potential indexes (DWPi) were modelled with MOTTI-program (b, c, d). • 168 tree species, fertility class and latitude combinations 2) DWPis were used for converting diameter and volume into decaying wood potential • Generated for the whole Finland at tree stand level at the resolution of 16 m x 16 m • Eventually combined into 20 tree species & fertility classes and aggregated to 96 m x 96 m resolution. Input data Decaying wood potential was calculated from forest stand level datasets (tree species, diameter, volume, fertility) covering whole Finland. Best possible data was used for every area. - 24 % of Finland covered by state-owned forestry and conservation areas and private conservation areas o Metsähallitus Parks & Wildlife: field and forest stand data (5/2015) o Metsähallitus Forestry Inc.: field and forest stand data (5/2015) o Private owned conservation areas: field and forest stand data (5/2015) - 37 % of Finland covered by privately owned other than protected forest areas: Finnish Forest Centre, forest information (6.5.2005 – 6.5.2015) - 39 % of Finland covered by o Natural Resources Institute Finland: Multi-source national forest inventory data of Finland 2013(volume, tree species, fertility class, diameter) Spatial data on forestry operations with negative impact on biodiversity (e. g. fellings, thinning and ditching) (updated 10/2017) - National Land Survey of Finland & Finnish Environment Institute SYKE: Ditching state of Finnish peatlands (SOJT_09b1) - Metsähallitus Forestry Inc.: Executed forest operations of forest operations from field and forest stand data and ditching status - Finnish Forest Centre: Forest declariations and ditching status - University of Maryland / Dept. of Geographica Sciences: Global Forest Change / Forest Cover Loss 2000-2014 Observations of IUCN Red List forest species (since 1990): Finnish Environmental database HERTTA Spatial data on woodland key habitats protected by The Finnish Forest Act 10§ (updated 10/2017) - Finnish Forest Centre: woodland key habitats protected by Finnish Forest act 10§ Spatial data on permanent conservation areas (updated 2/2018) - Metsähallitus Parks & Wildlife: Conservation area database SATJ Background Areas important to forest biodiversity were identified throughout Finland to support sustainable land using planning and nature conservation at local, regional and national level by informing land owners, ministries and forestry stakeholders. Importance of analyzes like this rise from increased usage of natural resources and consequent harmful impacts on biodiversity together with limited resources for conservation. These highlight the importance of developing cost-effective, ecologically sustainable land use planning approaches such as these spatial conservation prioritizations of forests made for a first time for the whole Finland. Prioritization approach, Zonation, was used to find new forest areas of potential high conservation value. The overall aim was to implement nationwide prioritization analyses based on biodiversity-related forest data and land use data recorded at the level of forest stand. Primarily employed data on forest structure and quality (vegetation class, tree species, volume and diameter) provided ecologically useful surrogates for conservation value in boreal forest. Results show that a significant portion of high biodiversity value forests lay outside the current Finnish protected area (PA) network. As most of the Finnish forest area is under commercial management, PA network cannot halt the on-going decline of forest biodiversity. Keywords: biodiversity value, decaying wood, forest biodiversity, Forest Biodiversity Programme for Southern Finland (METSO), forest conservation, forestry, geographical information system (GIS), land use, spatial conservation prioritization, Zonation software Datapackage includes all 12 raster maps and a .lyr -file. .lyr -file contains coloured symbology and descriptions of different analysis versions. .lyr -file is probably operable only with GIS-software prvided by ESRI Inc. Datapackage can be loaded from: http://www.syke.fi/en-US/Open_information/Spatial_datasets High Biodiversity Value Forests 2018 (Zonation) nationwide High Biodiversity Value Forests 2018 (Zonation) regional Detailed poster available: http://www.syke.fi/en-US/Research__Development/Ecosystem_services/Specialist_work/Zonation_in_Finland/Zonation_materials/Posters OR http://www.syke.fi/download/noname/%7B771FF5A4-DAB6-45EE-8246-F38FC0090CAD%7D/138289 Detailed report (only in Finnish): http://hdl.handle.net/10138/234359 Mikkonen et al. 2018. Suomen ympäristökeskuksen raportteja 9/2018. Monimuotoisuudelle tärkeät metsäalueet Suomessa - Puustoisten elinympäristöjen monimuotoisuusarvojen Zonation-analyysien loppuraportti. Other references: a) Moilanen et al. 2014. Zonation–Spatial Conservation Planning Methods and Software. Version 4. User Manual. See also www.syke.fi/Zonation/en b) Hynynen et al. 2015. Eur. J. For. Res. 134/3. Long-term impacts of forest management on biomass supply and forest resource development: a scenario analysis for Finland. c) Hynynen et al. 2014. Metlan työraportteja 302. Scenario analysis for the biomass supply potential and the future development of Finnish forest resources. d) Salminen et al. 2005. Comput. electron. agr. 49/1. Reusing legacy FORTRAN in the MOTTI growth and yield simulator. Availability: Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0) Creative Commons 4.0. © SYKE Datasources: Finnish Forest Centre, Metsähallitus, Natural Resources Institute Finland 2015, National Land Survey of Finland, Hansen/UMD/Google/USGS/NASA

  • This dataset contains points of information describing the location and size of illegal oil discharges observed during aerial surveillance flights by HELCOM Contracting Parties during 1998-2017. Further information about illegal discharges of oil in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ The dataset contains the following information: Country Year Spill_ID = Spill ID FlightType = The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "S" Date = The date of the detection (dd.mm.yyyy) Time_UTC = The time of the detection (hh:mm) Wind_speed = The wind speed at the time of the detection (m/s) Wind_direc = The wind direction 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 = The category of the detection: OIL EstimVol_m = Estimated volume of the detection (m3) Polluter = Polluter (rig, ship, other, unknown) Category = Category of the detection: 100m3 = "5" Casefile = The name of the casefile the detection refers to Remarks = Any additional information

  • This dataset contains points of information describing the location and size of other discharges than illegal oil discharges observed during aerial surveillance flights by HELCOM Contracting Parties 2014-2017. Further information about illegal discharges of oil in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ The dataset contains the following information: Country Year Spill_ID= Spill ID FlightType= The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "S" Date= The date of the detection (dd.mm.yyyy) Time_UTC= The time of the detection (hh:mm) Wind_speed= The wind speed at the time of the detection (m/s) Wind_direc= The wind direction at the time of the detection (degrees) Latitude= The latitude of the detection (decimal degrees) Longitude= The longitude of the detection (decimal degrees) 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= The category of the detection: other substance = "OS", unknown substance = "UNKNOWN" EstimVol_m= Estimated volume of the detection (m3) Polluter= Polluter (rig, ship, other, unknown) Category= Category of the detection: 100m3 = "5" Casefile= The name of the casefile the detection refers to Remarks= Any additional information

  • This dataset contains the ship accidents in the Baltic Sea during the period 1989 to 2017. It is constructed from the annual data collected by HELCOM Contracting Parties on ship accidents in the Baltic Sea. The accident data has been compiled by the HELCOM Secretariat. According to the decision of the HELCOM SEA 2/2001 shipping accident data compilation will include only so called conventional ships according to the Regulation 5, Annex I of MARPOL 73/78 - any oil tanker of 150 GT and above and any other ships of 400 GT and above which are engaged in voyages to ports or offshore terminals under the jurisdiction of other Parties to the Convention. According to the agreed procedure all accidents (including but not limited to grounding, collision with other vessel or contact with fixed structures (offshore installations, wrecks, etc.), disabled vessel (e.g. machinery and/or structure failure), fire, explosions, etc.), which took place in territorial seas or EEZ of the Contracting Party irrespectively if there was pollution or not, are reported. The dataset contains the following information: Country Year Latitude = Latitude (decimal degrees) Longitude = Longitude (decimal degrees) Cause_details = Details on the accident cause Offence = Offence against Rule Damage = Damage Assistance = assistance after the accident Pollution = Pollution (Yes/No) Date = Date (dd.mm.yyyy) Time = Time (hh:mm) Location = Location of the accidents (open sea / port approach / at port) Sh1_Categ = Ship 1 type (according to AIS category) Sh1_Type = Ship 1 more detail ship type category Sh1_Hull = Ship 1 hull construction Sh1Size_gt = Ship 1 GT Sh1Sizedwt = Ship 1 DWT Ship1Draug_m = Ship 1 draught in meters Sh2_Categ = Ship 2 type (according to AIS category) Sh2_Type = Ship 2 more detail ship type category Sh2_Hull = Ship 1 hull construction Sh2Size_gt = Ship 2 GT Sh2Sizedwt = Ship 2 DWT Ship2Draug_m = Ship 2 draught in meters Acc_type = Type of accidents Colli_type = Type of collisions Acc_Detail = More information on the accident Cause_Sh1 = Cause of accidents from ship 1 Cause_Sh2 = Cause of accidents from ship 2 HumanEleme = Reason of human error IceCondit = Ice conditions CrewIceTra = Crew trained for ice conditions Pilot_Sh1 = Presence of pilot on ship 1 Pilot_Sh2 = Presence of pilot on ship 2 Pollu_m3 = Pollution in m3 Pollu_t = Pollution in t Pollu_type = Type of pollution RespAction = Response actions after the accidents Add_info = Additionnal information Ship1_name = Ship 1 identification Ship2_name = Ship 2 identification Cargo_type = cargo type ship 1 For more information about shipping accidents in the Baltic Sea, see the HELCOM annual reports: http://www.helcom.fi/action-areas/shipping/publications/

  • This dataset represents the Integrated biodiversity status assessment for fish used in State of the Baltic Sea – Second HELCOM holistic assessment 2011-2016. Status is shown in five categories based on the integrated assessment scores obtained in the BEAT tool. Biological Quality ratios (BQR) above 0.6 correspond to good status. The assessment is based on core indicators of coastal fish in coastal areas, and on internationally assessed commercial fish in the open sea. The open sea assessment includes fishing mortality and spawning stock biomass as an average over 2011–2016. Open sea results are given by ICES subdivisions, and are not shown where they overlap with coastal areas. Coastal areas results are given in HELCOM Assessment unit Scale 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas) Attribute information: "COUNTRY" = name of the country / opensea "Name" = Name of the coastal assessment unit, scale 3 (empty for ICES open sea units) "HELCOM_ID" = ID of the HELCOM scale 3 assessment unit (empty for ICES open sea units) "EcoystemC" = Ecosystem component analyzed "BQR" = Biological Quality Ratio "Conf" = Confidence (0-1, higher values mean higher confidence) "Total_indi" = Number of HELCOM core indicators included (coastal assessment units) "F__of_area = % of area assessed "D1C2" = MSFD descriptor 1 criteria 2 "Number_of" = Number of open sea species included "Confidence" = Confidence of the assessment "BQR_Demer" = Demersal Biological Quality Ratio "F_spec_Deme" = Number of demersal species included "Conf_Demer" = Confidence for demersal species "BQR_Pelagi" = Pelagic Biological Quality Ratio "F_specPela" = Number of pelagic species included "Conf_Pelag" = Confidence for pelagic species "ICES_SD" = ICES Subdivision number "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

  • This dataset contains borders of the HELCOM MPAs (former Baltic Sea Protected Areas (BSPAs). The dataset has been compiled from data submitted by HELCOM Contracting Parties. It includes the borders of designated HELCOM MPAs stored in the <a href="http://mpas.helcom.fi" target="_blank">HELCOM Marine Protected Areas database</a>. The designation is based on the HELCOM Recommendation 15/5 (1994). The dataset displays all designated or managed MPAs as officially reported to HELCOM by the respective Contracting State until in November 2018 (latest data update). The latest related HELCOM publication based on MPA related data is <a href="http://www.helcom.fi/Lists/Publications/BSEP148.pdf" target="_blank"> Ecological coherence assessment of the Marine Protected Area network in the Baltic. Balt. Sea Environ. Proc. No. 148 (HELCOM 2016)</a> The dataset contains the following information: MPA_ID: Unique ID of the MPA as used in HELCOM Marine Protected Areas database Name: Name of the MPA Country: Country where MPA is located Site_link: Direct link to site's fact sheet in the <a href="http://mpas.helcom.fi" target="_blank">HELCOM Marine Protected Areas database</a> where additional information is available MPA_status: Management status of the MPA Date_est: Establishment date of the MPA Year_est: Establishment year of the MPA

  • This dataset represents the Integrated biodiversity status assessment for pelagic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. Open sea areas were assessed based on the core indicators ‘Zooplankton mean size and total stock’ and ‘Chlorophyll-a’, as well as the pre-core indicator ‘Cyanobacterial bloom index’ . Coastal areas were assessed by national indicators. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit 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: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = Code of the HELCOM assessment unit "Country" = Country of coastal assessment unit/ open sea "Level2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the HELCOM scale 4 assessment unit "Area_km2" = Area of assessment unit "AULEVEL" = scale of the assessment unit "HID" = assessment unit ID by country "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

  • This dataset represents the Integrated biodiversity status assessment for seals (grey seal, harbour seal and ringed seal). Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological quality ratios (BQR) above 0.6 correspond to good status. The status of the seals was assessed using four core indicators: population trends and abundance of seals, distribution of Baltic seals, nutritional status of seals, and reproductive status of seals. In the latter two only grey seals are considered for the 2018 State of the Baltic Sea report. The assessment is based on the one-out-all-out approach, i.e. the species reflecting the worst status in each assessment unit. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit Scale 2 (Division of the Baltic Sea into 17 sub-basins). Attribute information: "HELCOM_ID" = ID of the HELCOM scale 2 assessment unit "level_2" = Name of the HELCOM scale 2 assessment unit "EcosystemC" = Ecosystem component analyzed "BQR" = Biological Quality Ratio "Conf" = Confidence of the assessment "Total_indi" = Number of indicators used "% of area assessed" = Share of the total assessed area "D1CX" = MSFD descriptor 1 criteria X "conf_D1CX" = Confidence for MSFD descriptor criteria X "Confidence" = Conifdence of the assessment ("high"/ "moderate"/ "low") "STATUS" = Status of the assessment (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

  • This dataset represents the Integrated biodiversity status assessment for benthic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. The assessment in open sea areas was based on the core indicators ‘State of the soft-bottom macrofauna community’ and ‘Oxygen debt’. Coastal areas were assessed by national indicators, and may hence not be directly comparable with each other. This dataset displays the result of the integrated biodiverity status in HELCOM Assessment unit 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: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = id of the HELCOM assessment unit "country" = name of the country / opensea "level_2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the coastal assessment unit on scale 4 "AULEVEL" = scale of the assessment units "type_descr" = Name of the HELCOM scale 4 assessment unit "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "Area_km2" = Area of assessment unit (km2) "Confiden_1" = Confidence level of the assessment (scores < 0.5 = low, 0.5 - 0.75 = intermediate, > 0.75 = high) "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score), 0.8-1.0 = good (highest score))