Broad-scale habitat maps for the Baltic Sea have been produced in the EUSeaMap project in 2016. For German and Estonian marine areas, national (more accurate) datasets were used. German data included both substrate and light information (division into infralittoral/circalittoral). Estonian data included only substrate and the division into light regimes was obtained from the EuSeaMap data. Here, the habitat class “circalittoral mud” includes classes “Fine mud”, “Sandy mud” and “Mud to sandy mud” of the original data, in the circalittoral zone. The original polygon maps have been converted to 1 km x 1 km grid. The scale of the substrate data used in broad-scale habitat maps varies from 1:250 000 to 1:1M (data from EMODnet Geology). Coarser resolution data has been used in areas, where 1: 250 000 substrate data has not been available. Due to different scales used, the habitat classes may show different sized patterns in different areas.

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 PAH in seawater station locationsas reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

Locations of the coastal protection structures. The dataset contains information about the coastal defence structure type and for some the structure length (m) and the year of construction. The data was made available by HELCOM Contracting Parties in response to data request. The data was received from Denmark, Estonia, Germany, Finland, Poland and Sweden. The activity was declared as not relevant in Lithuanian area. From Latvia and Russia no data was reported. Attribute specification and units Country: Country Type: Modification structure type Const_year: Year of construction Estimated: Estimated date of completion if under construction (Estonia) or the year of environmental permit if year of construction is lacking (Finland) Out_of_use: Year when costal defence structure has been taken out of use Measure: Additional information about the modification structure Length: Length of the modified coastline (m) width: Width of the modification structure (m) Area: Area of the modification structure (km2) X_Lon: Original X (Longitude) coordinate point (Finland)

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

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

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.

This dataset contains all heavy metal monitoring station locations where sediment is samples are analyzed as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.