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  • 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 recruitment areas for perch was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Perch (Perca fluviatilis) is a key species in many Baltic coastal areas. It is of freshwater origin and spawns predominantly in freshwater tributaries, close to the coastline, or in enclosed bays. Species distribution modelling have shown the importance of suitable environmental conditions for perch reproduction. Young perch has limited dispersal from its spawning area, and tagging studies have shown that most (50-95 % of the recaptures of perch are made up to 20 km from tagging site (Johnsson 1978, Böhling and Lehtonen 1985, Veneranta et al. 2011, Saks et al. 2020). Due to lack of coherent data on perch spawning and nursery areas across the Baltic Sea countries, environmental variables were used in delineating potential recruitment areas for perch. The map was originally developed within the HOLAS II project (HELCOM 2018) when it was approved by all HELCOM Contracting Parties in a dedicated review process. Potential perch recruitment areas were delineated as areas with suitable condition of depth, wave exposure and salinity. Thresholds were obtained from literature, and selected to rather overestimate than underestimate the recruitment area. For the Finnish coastline, a national model was used. The map was subsequently considered by the Pan Baltic Scope project, who proposed adjustments to thresholds for some areas in Russian waters, and corrections to Estonian and German waters. Stock: Several, undefined EFH type: Recruitment areas Approach: Environmental window, national modelling approach in Finnish waters, supplemented with corrections to Estonian, German and Russian waters based on national validation with monitoring data. Variables and thresholds: Depth < 4 m (for Danish waters < 3 m), Logged exposure < 5 (For Koporo Bay and Narva Bay in Russian waters < 5.23), Salinity < 10. Based on the model for the Finnish coastline, perch recruitment areas were defined as: Unsuitable for reproduction: P(catch larvae) < 0.5, Suitable for reproduction: P(catch larvae) > 0.5, Important for reproduction: the smallest area where the expected cumulative larval abundance is 80% of the total expected abundance over study area. Quality: Recruitment area here refers to essential habitats for young-of-the-year perch (based on inventory data from spawning until the end of the first summer). The map is based on literature and environmental variables, derived from inventory data. The species distribution modelling studies, where the thresholds values for environmental variables have been obtained, are from the northern Baltic Sea. Here, the same thresholds have been applied in the southern Baltic. Also, the data layers on environmental variables are based on modelling. Due to these constraints, the data layer should be considered as a rough estimation. Attribute information: Raster value representing the potential occurrence of perch recruitment area (either 0 or 1). References - Bergström, U, G Sundblad, A-L Downie, M Snickars, C Boström, and M Lindegarth (2013) Evaluating eutrophication management scenarios in the Baltic Sea using species distribution modelling. Journal of Applied Ecology 50:680-690 - Böhling, P, and H Lehtonen (1985) Effect of environmental factors on migrations of perch (Perca fluviatilis) tagged in the coastal waters of Finland. Finnish Fisheries Research 5: 31-40 - HELCOM (2018) State of the Baltic Sea - Second HELCOM holistic assessment 2011-2016. Baltic Sea Environment Proceedings 155 - HELCOM (2020) Essential fish habitats in the Baltic Sea – identification of potential spawning, recruitment and nursery areas - Isæus, M (2004) Factors structuring Fucus communities at open and complex coastlines in the Baltic Sea. PhD thesis, Stockholm University - Johnsson, T (1978) Dispersal area of perch, Perca fluviatilis, tagged in a stream flowing into the Bothnian Sea. Aquilo, Series Zoologica 18: 62-64 - Kallasvuo, M, J Vanhatalo, and L Veneranta (2017) Modeling the spatial distribution of larval fish abundance provides essential information for management. Canadian Journal of Fisheries and Aquatic Sciences 74:636-649 - Saks, L, R Eschbaum, K Jürgens, and I Taal (2020) Ahvena ränded Liivi lahel ja Väinameres. Eesti Mereinstituut, Tartu. https://www.kalateave.ee/images/pdf¬/Uuringud/¬Ahvena_r%¬C3%A4nded_Liivi_lahel_-ja_V%C3%A4inameres.pdf - Seifert, T, F Tauber, and B Kayser (2001) A high resolution spherical grid topography of the Baltic Sea -2nd edition. Baltic sea Science Congress, Stockholm 25-29 November 2001, Poster #147 - Skovrind, M, EAF Christensen, L Jacobs, and PR Moller (2013) Marine spawning sites of Perca fluviatilis revealed by oviduct-inserted acoustic transmitters. Aquatic Biology 19:201-206 - Snickars, M, G Sundblad, A Sandström, L Ljunggren, U Bergström, G Johansson, and J Mattila (2010) Habitat selectivity of substrate spawning fish - modelling requirements of the Eurasian perch, Perca fluviatilis. Marine Ecology Progress Series 398:235-243 - Sundblad, G, Bergström, U, Sandström, A, and P Eklöv (2014) Nursery habitat availability limits adult stock sizes of predatory coastal fish. ICES Journal of Marine Science 71:672-680 - Veneranta, L, L Urho, A Lappalainen, and M Kallasvuo (2011) Turbidity characterizes reproduction areas of pikeperch (Sander lucioperca (L.)) in the northern Baltic Sea. Estuarine, Coastal and Shelf Science 95:199-206

  • 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 Diatom/Dinoflagellate ration 2018. 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. Attribute information: "Station" = Name of station "Date" = Sampling date and time "Assessment" = Name of HELCOM level 2 assessment unit "Biomass_of" = Biomass of all diatoms "Biomass_1" = Biomass of all dinoflagellates (autotrophic and mixotrophic) "Data_origi" = Data originating organization "Use_restri" = Data use restrictions (YES/NO). Restricted data is not included.

  • 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 Seasonal succession of dominating phytoplankton groups 2018. 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. Attribute information: "Code"= ID of HELCOM level 2 assessment unit "Assessment" = Name of HELCOM level 2 assessment unit "Station" = Name of station "Lat" = Latitude of station in WGS 84 decimal degrees "Lon" = Longitude of station in WGS 84 decimal degrees "Data_avail" = Data availability period (years) "Reference" = Reference period (years) "Data_provi" = Data provider organisation "Country" = Data provider country "Station_na" = Station name "Date" = Sampling date and time "Year" = Year of sampling "Month" = Month of sampling "Cyano" = Cyanobacteria "Dino" = Dinoflagellates "Diatoms" = Diatoms "Meso_rub" = Mesodinium rubrum "CyanoIn" = "DinoIn" = "DiatomsIn" = "MesoRubIn" =

  • 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

  • Essential fish habitat (EFH) map on Potential recruitment areas for pikeperch was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Pikeperch (Sander lucioperca) is a species of freshwater origin, which spawns predominantly in freshwater tributaries and has a relatively limited dispersal away from its recruitment area. Species distribution modelling studies have shown the importance of suitable environmental conditions for pikeperch recruitment. Due to lack of coherent data on pikeperch spawning and nursery areas across the Baltic Sea countries, the distribution of pikeperch recruitment areas was delineated based on areas with suitable conditions of depth, wave exposure, salinity, water transparency (Secchi depth) and distance to deeper (10 m) waters. The threshold values were obtained from literature. Temperature, although important for pikeperch, was left out due to high variation in timing of suitable spawning temperatures across the Baltic Sea. The map on pikeperch recruitment areas was originally developed within the HOLAS II project (HELCOM 2018) when it was approved by all HELCOM Contracting Parties in a dedicated review process after correction to Swedish waters. The map was subsequently considered by the Pan Baltic Scope project, who proposed adjustments to Estonian, German, Lithuanian and Polish waters. Stock: Several, undefined EFH type: Recruitment areas Approach: Environmental window with national approach for Finnish waters, selected data points corrected for Estonian, German, Lithuanian, Polish, and Swedish waters. Variables and thresholds: Depth < 5 m, Logged exposure < 5, Salinity < 7, Secchi depth < 2, Distance to deep (10m) water < 4km. Based on the model for the Finnish coastline, pikeperch recruitment areas were defined as: Unsuitable for reproduction: P(catch larvae) < 0.5, Suitable for reproduction: P(catch larvae) > 0.5, Important for reproduction: the smallest area where the expected cumulative larval abundance is 80% of the total expected abundance over study area. Quality: Recruitment area here refers to essential habitats for young-of-the-year pikeperch (based on inventory data from spawning until the end of the first summer). The map is based on literature and environmental variables, derived from inventory data. The species distribution modelling studies, where the thresholds values for environmental variables have been obtained, are from the northern Baltic Sea. Also, the data layers on environmental variables are based on modelling. Here, same thresholds have been applied in the southern Baltic. Due to these constraints, the data layer should be considered as a rough estimation. In addition, temperature is important for pikeperch recruitment but was not included as a delineating variable due to high variation in timing. The data layer may underestimate pikeperch in Finnish waters with respect to habitats for young-of-the-year pikeperch, as it focused on newly-hatched larvae when the dispersal is more limited compared to later in the season. Attribute information: Raster value representing the potential occurrence of pikeperch reproduction area (either 0 or 1). References: - Alikas, K, and Kratzer, S (2017) Improved retrieval of Secchi depth for optically-complex waters using remote sensing data. Ecological Indicators 77: 218-227 - Bergström, U, G Sundblad, A-L Downie, M Snickars, C Boström, and M Lindegarth (2013) Evaluating eutrophication management scenarios in the Baltic Sea using species distribution modelling. Journal of Applied Ecology 50:680-690 - HELCOM (2018) State of the Baltic Sea - Second HELCOM holistic assessment 2011-2016. Baltic Sea Environment Proceedings 155 - HELCOM (2020) Essential fish habitats in the Baltic Sea – identification of potential spawning, recruitment and nursery areas - Gunnartz, U, M Lif, P Lindberg, L Ljunggren, A Sandström, and G Sundblad (2011) Kartläggning av lekområden för kommersiella fiskarter längs den svenska ostkusten - en intervjustudie (In Swedish with summary in English). Finfo 2011:3:1-42 https://www.havochvatten.se/download/18.64f5b3211343cffddb2800018015/1348912838028/finfo2011_3.pdf - Isæus, M (2004) Factors structuring Fucus communities at open and complex coastlines in the Baltic Sea. PhD thesis, Stockholm University - Kallasvuo, M, J Vanhatalo, and L Veneranta (2017) Modeling the spatial distribution of larval fish abundance provides essential information for management. Canadian Journal of Fisheries and Aquatic Sciences 74:636-649 - Seifert, T, F Tauber, and B Kayser (2001) A high resolution spherical grid topography of the Baltic Sea -2nd edition. Baltic sea Science Congress, Stockholm 25-29 November 2001, Poster #147 - Sundblad, G, Bergström, U, Sandström, A, and P Eklöv (2013) Nursery habitat availability limits adult stock sizes of predatory coastal fish. ICES Journal of Marine Science 71:672-680 - Veneranta, L, L Urho, A Lappalainen, and M Kallasvuo (2011) Turbidity characterizes reproduction areas of pikeperch (Sander lucioperca (L.)) in the northern Baltic Sea. Estuarine, Coastal and Shelf Science 95:199-206

  • Essential fish habitat (EFH) map on Potential spawning areas for Baltic flounder was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Baltic flounder (Platichthys solemdali) is a key species in many coastal areas of the Baltic Sea. It is the only endemic fish species of the Baltic Sea. Baltic flounder spawns in shallow coastal areas and on offshore banks, with eggs developing on the sea floor. Successful spawning may be expected at salinities down to around 5-7 (Nissling et al. 2002). ‘‘Potential spawning areas’ were initially delineated by a species distribution model (Orio et al. 2017) developed based on years 1993-1997 to consider a period with relatively better oxygen conditions, but applied with more recent data (2011-2014). The area was further delineated to encompass only areas shallower than 30 m in order to represent the demersal spawning habitat. ‘High probability spawning areas’ were identified as the sub-section encompassing salinity > 6. It should be noted that flounders in the Baltic Sea were recently separated into two species, and that spawning areas of the European flounder (Platichthys flesus) are described separately. The two data layers do not overlap and can be combined to obtain a map on spawning areas for both flounder species taken together. Stocks: ICES identifies two stocks of 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). EFH Type: Spawning areas Approach: Species distribution modelling combined with identification of environmental salinity window and depth conditions for spawning, supplemented with additional information from monitoring in Estonian waters. Variables and thresholds: Depth < 30 m, Salinity > 6 Quality: The data layer is based on species distribution modelling focusing on mature flounder at the spawning stage and should be considered a rough estimation. The data layers on environmental variables are based on modelling. Other variables than those tested in the model may also be influential. The studies from which the thresholds values for environmental variables have been obtained are based on publications conducted before the separation of Baltic flounder from European flounder but have taken the specific characteristics of the separate spawning ecotypes into account. Attribute information: Raster value representing no spawning (0), potential spawning area (0.5) and high probability spawning area (1). References: - Momigliano, P, GP Denys, H Jokinen, and J Merilä (2018) Platichthys solemdali sp. nov. (Actinopterygii, Pleuronectiformes): a new flounder species from the Baltic Sea. Frontiers in Marine Science 5:225 - Nissling, A, L Westin, and O Hjerne (2002) Reproductive success in relation to salinity for three flatfish species, dab (Limanda limanda), plaice (Pleuronectes platessa), and flounder (Pleuronectes flesus), in the brackish water Baltic Sea. ICES Journal of Marine Science 59:93-108 - Orio, A, U Bergström, M Casini, M Erlandsson, R Eschbaum, K Hüssy, A Lehmann, L Ložys, D Ustups, and A-B Florin (2017a) Characterizing and predicting the distribution of Baltic Sea flounder (Platichthys flesus) during the spawning season. Journal of Sea Research 126:46-55 - Seifert, T, F Tauber, and B Kayser (2001) A high resolution spherical grid topography of the Baltic Sea -2nd edition. Baltic sea Science Congress, Stockholm 25-29 November 2001, Poster #147