Amount of hunted birds (number of birds/area) per year per area (county) is given separately for each target species: common scooter (Melanitta nigra), velvet scoter (Melanitta fusca), eider (Somateri molissima) and long tailed duck (Clangula hymalis). The data was made available by HELCOM Contracting Parties in response to data request. The data was received from Denmark, Estonia, Finland and Sweden. The activity was declared as not relevant in Germany, Latvia, Lithuania and Poland. For each species, a total number of hunted birds during the time period and a calculated average (hunted birds/year), is given. Data includes a total number (sum) of all hunted birds during the time period per county (total number of hunted birds/ county) and an average for hunted birds annually (hunted individuals/year). Velvet scoter is protected species in Sweden and Finland, and not listed as a game in Estonia. Common scoter is also protected species in Finland, thus hunting data is not available. Attribute specification and units: Country: Country AreaCode: County’s national code Area: County, unit area TOTAL: Total number of hunted birds in 2011-2015 Average: An average of hunted birds in a year (hunted birds/year) 2011_Sco – 2015_Sco: Number of hunted common scoters in 2011-2015 SUM_Sco: Total number of hunted common scoters in 2011-2015 Mean_Sco: An average number of hunted common scoters in a year (hunted individuals/year) 2011_VSco – 2015_VSco: Number of hunted velvet scoters in 2011 - 2015 SUM_Vsco: Total number of hunted velvet scoters in 2011-2015 Mean_Vsco: An average number of hunted velvet scoters in a year (hunted individuals/year) 2011_Eider – 2015_Eider: Number of hunted eiders in 2011 - 2015 SUM_Eider: Total number of hunted eiders in 2011-2015 Mean_Eider: An average number of hunted eiders in a year (hunted individuals/year) 2011_LTDuc – 2015_LTDuc: Number of hunted long tailed ducks in 2011 – 2015 SUM_LTDuck: Total number of hunted long tailed ducks in 2011-2015 Mean_LTDuc: An average number of hunted long tailed ducks in a year (hunted individuals/year) Notes: Notes regarding the data

The extraction of Sprat data set is based on: 1. http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/1fb1bd2d-8dff-493a-9ed3-a278aec8f371 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 Sprat. Please see "lineage" section below for further details on attributes, data source, data processing, etc.

The dataset contains total landings of herring for years 2011-2016 reported per ICES statistical rectangles (tonnes / ICES rectangle) under EU Joint Research Centre’s data collection framework for fisheries data. Russian data extracted from ICES annual reports.

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.

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.

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.

This data set on deposition sites of dredged material (points) 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.

The map of sprat relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016, (ICES WGBIFS reports), reported as millions of sprat per ICES rectangle. The BIAS surveys cover almost the whole area where sprat is commonly encountered. Outside BIAS area, sprat landings data was 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 2011-2015). MAX-value = millions of sprat according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported sprat landings were given the value 0. The abundance values / ICES rectangle were divided by the area of the rectangle to obtain values per 1km2, and then converted to 1 km x 1km grid cells. Values were first log transformed and then normalised.

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.

Data set represents dredging activities around the Baltic Sea. The data set contains information about the dredging activity and for some the type (capital, maintenance) and the year of activity as reported by HELCOM Contracting Parties in response to data request. The dredging data is missing from Denmark.