This dataset contains all PCB in biota monitoring station locations, observed matrix, biota matrix and monitored species as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This dataset contains all dioxins in sediments monitoring station locations as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This dataset contains all PBDE in sediment monitoring station locations as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This dataset contains all TBT in sediments monitoring station locationsas reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

Springtime Chl-a concentration is here used as a proxy for productive surface waters. In the Baltic Sea Impact Index (BSII), areas with high springtime phytoplankton production will be given higher importance, as they are considered important areas for the Baltic Sea food web. In the current map, mean of springtime maximum weekly values (weeks 12-22, years 2003-2011) Chl-a concentration of the surface waters has been used, derived from satellite data (MERIS). Years 2003-2011 have been used, as there is no MERIS data available for years 2012-2016. The data for eastern Baltic Sea is provided by the Finnish Environment Institute (~300m resolution). Outside this high resolution data, MERIS-data downloaded from JRC-database has been used (~4 km resolution, to calculate average of maximum monthly values for April or May for 2003-2011). Both datasets were converted to 1 km x 1 km grid cells.

Distribution of Fucus sp. based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of Fucus were submitted, originally gathered in national mapping and monitoring campaigns, or for scientific research purposes. From Estonian waters, a predictive model was used (200m resolution), that was converted to presence/absence using minimized difference threshold (MDT) criteria. All data (Fucus points and the raster presenting predicted presence of Fucus) were generalized to 5km x 5km grid cells.

The occurrence of suitable nursery habitats is crucial for maintaining fish populations (Sundblad et al. 2013). 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, environmental variables were used in delineating potential recruitment areas for pikeperch. The pikeperch recruitment area presented on the map is mainly delineated by selecting areas where depth < 5 m, logged exposure < 5, salinity < 7 PSU, Secchi depth < 2 m and distance to deep (10m) water < 4km. The threshold values have been obtained from literature (Veneranta et al. 2011, Bergström et al. 2013, Sundblad et al. 2013, Kallasvuo et al. 2016). Temperature, although important for pikeperch, was left out due to high variation in timing of suitable spawning temperatures across the Baltic Sea. In Finnish coastal waters, a national pikeperch model (Kallasvuo et al. 2016) has been used, with very suitable areas for pikeperch generalized to 1 km grid. In Sweden, the areas delineated by environmental variables have been complemented with information from national interview survey (Gunnartz et al. 2011) as well as expert opinion.

The occurrence of suitable nursery habitats is crucial for maintaining fish populations (Sundblad et al. 2013). For perch, species distribution modelling studies (Snickars et al. 2010, Bergström et al. 2013, Sundblad et al. 2013) have shown the importance of suitable environmental conditions for reproduction. 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 distribution area or perch recruitment is delineated by selecting areas where depth < 4 m (For Danish waters < 3 m), logged exposure < 5 (exposure model described in Isæus 2004), and salinity < 10 PSU. The threshold values have been obtained from literature (Snickars et al. 2010, Bergström et al. 2013, Skovrind et al. 2013, Sundblad et al. 2013). Relatively “loose” thresholds have been used, to rather overestimate than underestimate the recruitment area (precautionary approach). Along the Finnish coastline a national model has been used (Kallasvuo et al. 2016), with suitable environments for perch recruitment generalized to 1 km x 1 km grid.

This dataset contains all PBDE in seawater monitoring station locationsas reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This map presents the Special Protection Areas (SPAs) with reported wintering areas for birds. The spatial data on SPAs were gathered from the HELCOM contracting parties by Lund University, Sweden. In the data, the countries also indicated whether the sites were designated mainly due to wintering or breeding birds in the area. For Denmark, the information was obtained from standard forms for Natura 2000 sites. For Denmark, the data was updated after review process 20 February 2017. For Germany, the areas that were reported as “NA”(=information not available) were included in both breeding and wintering area maps. Many of the SPAs are both wintering and breeding areas. For the Baltic Sea Impact Index, the data was converted to 1 km x 1km grid cells.