Essential fish habitat (EFH) map on Potential spawning areas for cod was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Cod (Gadus morhua) is represented by three stocks in the Baltic Sea; Eastern Baltic, Western Baltic and Kattegat cod, which is reflected in the map. “Potential spawning areas” were initially delimitated based on Hüssy (2011). In addition, the Gdansk deep as delineated by Bagge et al. (1994) was included as it sometimes contributes to reproduction of Eastern Baltic cod (Hinrichsen et al. 2016). The Gotland basin has ceased to contribute to the reproduction of cod (Hinrichsen et al. 2016). These definitions were applied in the HOLAS II project (HELCOM 2018a) based on approval by all HELCOM Contracting Parties in a review process (there referred to as ‘occasional successful spawning’ and ‘successful spawning’). Following HELCOM (2018b) additional potential spawning areas were identified by environmental thresholds for egg development and survival based on salinity and oxygen conditions (Hinrichsen et al. 2016) during 2011-2016. Separate thresholds were used for Eastern Baltic, Western Baltic and Kattegat cod. Areas denoted “high probability spawning areas” correspond to where the initial delineations (Hüssy 2011, Bagge et al. 1994) achieve the environmental threshold values. Stocks: Kattegat cod: ICES subdivision 21, Western Baltic cod: ICES subdivisions 22-24 Eastern Baltic cod: ICES subdivisions 24 + 25-32 EFH type: Potential spawning areas Approach: Literature review combined with identification of environmental window for spawning based on: salinity and oxygen for Eastern Baltic cod, and on: salinity and depth for Western Baltic Cod and Kattegat cod Variables and thresholds: Eastern Baltic cod: Salinity > 11, Oxygen > 1.5 ml/L (annual average) Western Baltic cod and Kattegat cod: Salinity > 18, Depth >20 m Quality: The Arkona deep is functional for spawning of both the Eastern and the Western Baltic cod and in effect, the definition of the Arcona Basin as a high probability areas in the Arkona basin reflect the result for Eastern Baltic cod. The effective distribution of cod spawning areas is highly dependent on the prevailing hydrological regime, and the presence of spawning also depends on seasonally variable hydrographical conditions, such as temperature, salinity and oxygen. Seasonal differences lead to a progressive spawning season towards the east, typically starting in Kattegat and the Sound in January/February and ending in July/August in the Bornholm area. Fluctuations in temperature can delay the spawning season up to two months. It is difficult to collect egg samples to verify cod spawning, as cod eggs may drift in deep areas, and instead the level of ichthyoplankton is a main source for estimation of good environmental conditions for cod spawning. Modelling based on ichthyoplankton should be validated by comparison with distribution of running adults, to resolve the potential influence of prevailing current speed. The proposed delineations are also influenced by research on the maturity of adults and histology of gonads. The adult and juvenile cod are distributed far outside of the spawning areas depicted in the map. Attribute information: Raster value representing no spawning (0), potential spawning area (0.5) and high probability spawning area (1). References - Bagge, O, F Thurow, E Steffensen, and J Bay (1994) The Baltic cod. Dana 10:1-28 - HELCOM (2018a) State of the Baltic Sea - Second HELCOM holistic assessment 2011-2016. Baltic Sea Environment Proceedings 155 - HELCOM (2018b) Outcome of the regional expert workshop on essential fish habitats, organized by Pan Baltic Scope project and HELCOM (HELCOM Pan Baltic Scope EFH WS 1-2018) - Hüssy, K (2011) Review of western Baltic cod (Gadus morhua) recruitment dynamics. ICES Journal of Marine Science 68:1459-1471 - Hüssy, K, HH Hinrichsen, and B Huwer (2012) Hydrographic influence on the spawning habitat suitability of western Baltic cod (Gadus morhua). ICES Journal of Marine Science, doi:10.1093/icesjms/fss136 - Hinrichsen, HH, A Lehmann, C Petereit, A Nissling, D Ustups, U Bergström, and K. Hüssy (2016) Spawning areas of eastern Baltic cod revisited. Using hydrodynamic modelling to reveal spawning habitat suitability, egg survival probability, and connectivity patterns. Progress in Oceanography 143:13-25 SwAM (2019). Swedish Agency for Marine and Water Management. Symphony Metadata March 2019.whttps://www.havochvatten.se/download/18.67e0eb431695d86393371d86/1552566811384/bilaga-1-symphony-metadata.zip

Essential fish habitat (EFH) map on Potential spawning areas for sprat was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Sprat (Sprattus sprattus) occurs in the entire Baltic Sea, and mainly in open sea areas. It is assessed as a single stock in the Baltic Sea within fisheries management. Sprat eggs are pelagic, and sprat spawning is well known from the deep basins in the central Baltic, where it typically occurs from February to August. Further north, spawning starts later in the year, and is less certain. Recent fisheries surveys indicate that sprat spawning does no longer occur in the Gulf of Finland. Sprat spawning areas were delineated using environmental variables due to lack of coherent field data across the Baltic Sea countries. “Potential sprat spawning areas” were delineated as areas with salinity > 6 and water depth > 30 m, but for the Arcona basin depth > 20 m was used (Grauman, 1980, Bauman et al. 2006, Voss et al. 2012). “High probability spawning areas” were delineated for areas deeper than 70 m. Stock: Sprat in subdivisions 22-32 (ICES) EFH type: Potential spawning areas Approach: Environmental envelope, corrected for areas 20-40 m south of Bornholm. Variables and thresholds: Potential spawning area: Depth > 30 m, Salinity > 6 (annual average) High probability spawning area: Depth >70 m, Salinity > 6 (annual average) Quality: The map is based on literature and environmental variables, not actual data on sprat spawning. The map might overestimate the spawning area west and north of Gotland. The data layers on environmental variables are based on modelling. Attribute information: Raster value representing no spawning (0), potential spawning area (0.5) and high probability spawning area (1). References: - Baumann, H, H Hinrichsen, C Mollmann, F Koster, A Malzahn, and A Temming (2006) Recruitment variability in Baltic Sea sprat (Sprattus sprattus) in tightly coupled to temperature and transport patterns affecting the larval and early juvenile stages. Canadian Journal of Fisheries and Aquatic Science 63:2191-2201 - Grauman GB (1980) Long term changes in the abundance data of eggs and larvae of sprat in the Baltic Sea. Fisheries research in the Baltic Sea, Riga. 15:138-150 (in Russian) - HELCOM (2018) Outcome of the regional expert workshop on essential fish habitats, organized by Pan Baltic Scope project and HELCOM (HELCOM Pan Baltic Scope EFH WS 1-2018) - Voss R, MA Peck, HH Hinrichsen, C Clemmesen, H Baumann, D Stepputis, M Bernreuther, JO Schmidt, A Temming, and FW Köster (2012) Recruitment processes in Baltic sprat - A re-evaluation of GLOBEC Germany hypotheses. Progress in Oceanography 107:61-79

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

This dataset represents the underlying data on core indicator Abundance of salmon spawners and smolt. The indicator evaluates the status of the abundance of salmon spawners and smolt in the Baltic Sea based on salmon smolt production in rivers flowing into the sea, also making use of additional supporting data on numbers of adult spawners. Determination of whether the threshold value that determines good status is achieved is based on a comparison of estimated smolt production with an estimated potential smolt production capacity. River-specific information provided by ICES WGBAST has been joined with river geometry by HELCOM Secretariat. Attribute information: "River_name" = Name of the river "A_unit" = HELCOM scale 2 Assessment unit "ICES_A_uni" = ICES assessment unit number "Assessment" = HELCOM scale 2 Assessment unit "ICES_Asses" = Number of ICES assessment unit "Estimates_" = Estimates of wild smolt production (*1000) median value "F90_proba" = 90% probability interval "Method_of_" = Method of estimation (1. Bayesian linear regression model, i.e. river model, 2. Sampling of smolts and estimate of total smot run size, 3. Estimate of smolt run from parr production by relation developed in the sae iver, 4. Estimate of smolt run from parr production by relation developed in another river, 5. Inference of smolt production from data derived from similar rivers in the region, 6. Count of spawners, 7. Estimate inferred from stocking of reared fish in the river, 8. Salmon catch in river, exploitation and survival estimate) "Data_sourc" = Data source "Data_origi" = Data originator (natonal instiute) "National_m" = National monitoing (YES/NO) "Use_restri" = Use restrictions (YES/NO)

This dataset represents the underlying data on core indicator Abundance of sea trout spawners and parr 2018. The indicator evaluates the status of the Baltic Sea area based on sea trout spawning in rivers flowing into the sea. River-specific information provided by ICES WGBAST has been joined with relevant HELCOM Level 3 assessment unit by HELCOM Secretariat. Attribute information: "HELCOM_ID": ID of HELCOM Assessment unit "Country": Country in which the assessment unit resides "level_3" = Name of the HELCOM scale 3 assessment unit "AULEVEL" = Scale of assessment "AU" = Name of the HELCOM scale 3 assessment unit "ICES_AU" = ID of ICES Assessment unit "ICES_SD" = ICES Subdivision "Rivername" = Name of river(s) used in analysis for the assessment unit "Year" = Years covered by the assessment "Data_sourc" = Data source "Data_origi" = Data originator (natonal instiute) "National_m" = National monitoing (YES/NO) "Use_restri" = Use restrictions (YES/NO)

This dataset represents the underlying data on core indicator Abundance of coastal fish key functional groups. The core indicator evaluates the abundance of selected functional groups of coastal fish in the Baltic Sea. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. As a rule, good status is achieved when the abundance of piscivores (i.e. fish that feed on other fish) is above a site-specific threshold value, and the abundance of cyprinids or mesopredators (i.e. mid trophic-level fish) is within an acceptable range for the specific site. The status of functional groups of coastal fish in the Baltic Sea has been evaluated by assessing the status of piscivores and cyprinids/mesopredators during the period 2011-2016. This dataset 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: "COUNTRYID" = Country code "ORGANIZATI" = Data provider "AREANAME" = ICES area name "ASSESSMENT" = Name of scale 3 HELCOM assessment unit "IndicatorI" = Indicator name (abbreviation) "Functional" = Functional group "IndicatorV" = Result value for the indicator "MethodId" = Catch method "GearType_N" = Gear type of catch "Season_NAM" = Season

This dataset represents the underlying data on core indicator Abundance of coastal fish key functional groups. The core indicator evaluates the abundance of selected functional groups of coastal fish in the Baltic Sea. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. As a rule, good status is achieved when the abundance of piscivores (i.e. fish that feed on other fish) is above a site-specific threshold value, and the abundance of cyprinids or mesopredators (i.e. mid trophic-level fish) is within an acceptable range for the specific site. The status of functional groups of coastal fish in the Baltic Sea has been evaluated by assessing the status of piscivores and cyprinids/mesopredators during the period 2011-2016. This dataset 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: "COUNTRY" = Country code "DATAPROVID" = Data provider "AREANAME" = ICES area "ASSESSMENT" = Name of scale 3 HELCOM assessment unit "FUNC_GROUP" = Functional group "IND_VALUE" = Result value for the indicator "METHOD" = Catch method "GEARTYPE" = Gear type of catch "SEASONID" = Season

This dataset contains data used for the HELCOM Core indicator State of the soft-bottom macrofauna community 2018. Attribute information: "SampleID" = Sample ID "Station" = Station name "Year" = Year of sampling event "Latitude" = Latitude coordinate (WGS84 decimal degrees) "Longitude" = Longitude coordinate (WGS84 decimal degrees) "Depth" = Depth of station (m) "Sentivit" = Sensitivity subset "Sampling_a" = Sampling area (cm2) "Sieve_mesh" = Sive mesh size (microm) "BQI" = Benthic quality index value "Data sourc" = Source of data (national monitoring / other) "Data_origi" = Data providing organization "Country" = Data providing country "Assessment" = HELCOM Level 2 assessment unit where the station resides

Essential fish habitat (EFH) map on Potential nursery areas for flounders was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ The two flounder species in the Baltic Sea (Platichthys flesus and P. solemdali) have different reproductive strategies, spawning in the pelagic and in shallow waters, respectively. However, they utilize the same type nursery habitat. For both species, young of the year are found on shallow bottoms from June to September, primarily on sandy substrates. Flounder nursery areas were predicted by a generalized additive model with flounder abundance as response variable and seven map-based predictor variables. The model was based on data from available surveys of juvenile flounder in the Baltic Sea, compiled within the Pan Baltic Scope project (see HELCOM 2018a). To represent the nursery season and the current situation, only results from surveys performed in June-September during 2004-2018 were used, resulting in totally 2,114 samples. All abundance estimates were harmonized to numbers of juvenile flounder per square meter. Values for the predictor variables were extracted for each sampling point in GIS. The following environmental variables were used: salinity, wave exposure, water depth, slope of the bottom, surface temperature, bottom currents, and distance to high probability spawning area for European flounder. Stock: Baltic flounder: ICES subdivisions 26, 28 (East of Gotland and Gulf of Gdansk), and 27, 29-32 (Northern Central Baltic Sea and Northern Baltic Sea). European flounder: ICES subdivisions 22-23 (Belt Sea and the Sound), and 24-25 (West of Bornholm and Southern Central Baltic Sea).). EFH type: Nursery areas Approach: Species distribution modelling Variables and thresholds: High probability nursery areas represent areas with a predicted abundance > 0.03 juvenile flounder/m² based on the applied data sets and model. Potential nursery areas represent predicted abundance levels between 0,0001 and 0,03 juvenile flounder/m². Areas with a predicted abundance < 0.0001 juvenile flounders/m² are defined as not being flounder nursery areas. Quality: Data on juvenile flounder abundances to support the spatial model is missing from Denmark, Germany, Poland and Russia. Predictions are uncertain in these areas, and especially along the south coast of the Baltic Sea. The mix of data from different years, months and gear types may have contributed to increasing the variability in the dataset, even though a relatively high deviance explained by the model (41%) shows that it has predictive power. The spatial resolution of the predictor variables varies between 200 m and 2 km, which gives coarse predictions locally even though values are representative at an overall regional scale. The prediction is limited by a lack of accurate spatial information on surface sediments. Sandy substrates are well known as important flounder nursery habitats. Unfortunately, the only available sediment map on a Baltic Sea wide scale was too inaccurate for shallow waters where juvenile flounder occurs and was therefore excluded from the model. The map on flounder nursery areas does not make assumptions on species identity in any area. Attribute information: Raster value representing no nursery area (0), potential nursery area (0.5) and high probability nursery area (1). -999 indicates No data. References HELCOM (2018a) Outcome of the regional expert workshop on essential fish habitats, organized by Pan Baltic Scope project and HELCOM (HELCOM Pan Baltic Scope EFH WS 1-2018) HELCOM (2018b) HELCOM Map and Data service. Layers: mean slope and bottom currents. https://maps.helcom.fi/website/mapservice/. Accessed March 2019 HELCOM (2020) Essential fish habitats in the Baltic Sea – identification of potential spawning, recruitment and nursery areas. Lehmann, A, W Krauß, and HH Hinrichsen (2002) Effects of remote and local atmospheric forcing on circulation and upwelling in the Baltic Sea. Tellus A 54:299-316

This dataset represents the underlying data on core indicator Population trends and abundance of seals 2018. This dataset contains reported observations for grey seal species. 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 (GS = Grey 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" = Count 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