Distribution of blue mussel based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of Mytilus spp. were submitted, originally gathered in national mapping and monitoring campaigns, or for scientific research. Point data from Poland was digitized based on Polish Marine Atlas. From Lithuania, a polygon delineating reefs was used to present Mytilus occurrence. For Germany, point data was complemented with a model describing Mytilus biomass in the German marine area (Darr et al. 2014), where predicted biomasses > 1g dw/ m2 were included as presence. From Estonian waters, a predictive model was used (200m resolution), that was converted to presence/absence using minimized difference threshold (MDT) criteria. All data (points, polygon and the raster presenting predicted presence of Mytilus) were generalized to 5km x 5km grid cells.

'Availability of deep water habitat, based on occurrence of H2S' layer describes the suitability of the bottom areas for the Baltic Sea biota, with regard to oxygen conditions of the near bottom waters. The data used to produce the layer was received from Leibniz-Institut für Ostseeforschung Warnemünde (IOW): - areas (polygons) with hydrogen sulfide (H2S) based on point measurements and modelling. Five time periods / year, for years 2011-2016 (altogether 30 layers). The polygons were converted to raster layers in a way, that for each time period (6 years, 5 time periods each year), areas with H2S got a value 0, other areas got the value 1. All layers were summed, (representing 6 years, 5 time periods each year, maximum value 30) and data was normalised. For more detailed information on the data used, please see Feistel et al. 2016.

This pressure dataset is derived from three human activities datasets - Urban land use (on land) - Recreational boating and sports (updated layer for 2018 version, please see separate http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/8c30e828-1340-4162-b7f9-254586ae32b6) - Bathing sites These data are described in more detail in separate fact sheets. Urban land use data was first converted to 1 km grid cells and expanded with 1 km. Thus, coastal urban areas extended also to the sea. These areas were given value 1 and other sea areas, value 0. Bathing sites (points) were converted to 1km grid and given value 1, rest of the sea areas were given value 0. Normalized recreational boating data was converted to 1 km grid cells. These three layers were summed to produce the layer (values from 0 to 3), after that the layer was normalized. Hunting and recreational fishing data were excluded from human disturbance layer, as they are mostly reported per country and would have resulted in overestimation of the actual pressure.

Distribution of Furcellaria lumbricalis based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of Furcellaria 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. For Poland, only confirmed occurrence of Furcellaria were included (Slupsk bansk, Rowy reef and reef at Orlowo cliff). All data (Furcellaria points and the raster presenting predicted presence of Furcellaria) were generalized to 5km x 5km grid cells.

Physical loss pressure layer combines all human activities that cause physical loss of seabed. The pressure is given as area lost in each cell (km2). For the polygon datasets the area was assumed to be the lost area. For line and point datasets spatial extents were calculated with buffers (below in brackets). If no buffer extent is indicated, the data was reported as polygon. The human activities used for the physical loss pressure: - Bridges (2 m) - Cables (operational; 1,5 m) - Coastal defence and flood protection (area of polygon, 50 m for lines) - Dredging (capital dredging, Area of polygon or a 25/50 m buffer for <5000 m3 / >5000m3 points) - Extraction of sand and gravel - Finfish mariculture (150 m) - Harbours (polygon with 200 m buffer) - Land claim (area of polygon, 30m buffer for lines) - Marinas and leisure harbours (200 m) - Oil platforms (25 m) - Oil terminals and refineries (200 m) - Pipelines (operational; 15 m) - Shellfish mariculture (area of polygon, 150 m points) - Watercourse modification (50 m) - Wind turbines (operational; 30m point location of turbine) The datasets were first processed separately covering the whole Baltic Sea and then merged into one uniform data layer and minimizing the effect of overlapping areas. Polygon areas were clipped with coastline to remove buffered areas that reached to land.

The extraction of herring data set is based on: 1. http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/a3b67a55-7c1e-469e-b692-58c4e7b79279 for years 2011-2016 reported per ICES statistical rectangles (tonnes / ICES rectangle). Landing values were redistributed within each ICES rectangle by the c-square fishing effort data provided by ICES (all gears, 2011-2013). Tonnes / km² was calculated and the results were converted to 1 km x 1 km grid cells. The layer was log-transformed and normalised to produce the final pressure layer on extraction of herring. Please see "lineage" section below for further details on attributes, data source, data processing, etc.

Concentration of nitrogen pressure layer is interpolated from annual seasonal average of total nitrogen concentrations from surface waters (0-10 m) extracted from ICES’s oceanographic database, database of Swedish Meteorological and Hydrological Institute, EEA’s Eionet database and Data from Gulf of Finland year 2014. The points were interpolated to cover the entire Baltic Sea with Spline with barriers interpolation method. Values were log-transformed and normalised (more detailed description below).

The map of herring relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016 (ICES WGBIFS reports), reported as millions of herring / ICES rectangle. Also herring landings data were used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, values are calculated as: MAX-value x Weighting factor. The weighting factor is specific to each ICES rectangle, calculated as the ratio between the commercial landings in that rectangle and the commercial landings in the ICES rectangle with highest landings (based on averages for 2011-2016). MAX-value = millions of herring according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported herring landings were given the value 0. The relative abundance values in each ICES rectangle were divided by the area of the rectangle to obtain values per 1km2. If the values in small coastal ICES rectangles (outside BIAS area) became unrealistically large due to high herring landings, the value of the neighboring rectangle was given. The final layer was converted to 1 km x 1km grid cells. Values were first log transformed and normalized.

This data set on deposition sites of dredged material (areas) reported by HELCOM Contracting parties according to http://www.helcom.fi/Recommendations/Rec%2036-2.pdf for the reporting period 2011-2016. The dataset contains data reported by nationally by nominated experts by HELCOM PRESSURE group for Denmark, Germany, Estonia, Finland, Latvia, Lithuania, Poland, Russia and Sweden.

This dataset is built from following Human activities datasets: • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/81c917ea-492d-48e2-9f00-e1bb7fe3e4fc • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/4fcd51dd-b8be-4e83-8cad-37c566782e8f The game hunting of seabirds data (see separate metadata): The total number of hunted seabirds were averaged over 2011-2015 (number of hunted seabirds / year). The area of the reporting unit was used to calculate the number of hunted seabirds / km2 and the data was converted to 1km x 1km grid. The predator control of seabirds data (see separate metadata): The total number of hunted cormorants were averaged over 2011-2015 (number of hunted cormorants / year). The area of the reporting unit was used to calculate the number of hunted cormorants / km2 and the data was converted to 1km x 1km grid. The two datasets were first separately log transformed and then summed, to get the total value for each grid cell. Zero values were given to all grid cells with no reported seabird hunting activity. The layer was normalized.