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.

Data shows the extent of land claim (permanent or temporary establishments of the sea) and the type of the construction. The data was made available by HELCOM Contracting Parties in response to data request. The data was received from Denmark, Finland, Sweden and Poland. The activity was declared as not relevant in Germany, Estonia, Latvia and Lithuanian. From Russia no data was reported. Attribute specification and units: Country: Country Type: Type of construction (land claim) Type_spec: More specified information about the type of land claim Year: Year of construction Estimated: Estimated year of construction from the identification information (environmental permit) given by the country in question Length: Length of the land reclamation (m) Area: Area (km2) of the land claim X_lon: Original Longitude coordinate point (for the data that has been transformed from points into lines) Y_Lat: Original latitude coordinate point (for the data that has been transformed from points into lines)

Concentration of phosphorus pressure layer is interpolated from annual seasonal average of total phosphorus measurements 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 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 (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.

Data set represents dredging activities around the Baltic Sea. The dataset 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.

This map shows the distribution and abundance of harbour porpoise across the Baltic Sea. The abundance of harbour porpoise is presented using 4 abundance classes. The classification is based on expert consultation and information from scientific literature (e.g. Sveegaard et al. 2011, Viquerat et al. 2014). The class borders are defined by expert opinion and generalizing the data gathered and modelled in SAMBAH project. For the Baltic Proper the SAMBAH results have been used to delineate the class borders: 20% probability of detection during May-October has been used to define the area of “common occurrence and reproduction”, and the 20% probability of detection during November-April has been used to define the “regular occurrence, no regular reproduction” area. Please note: The applied spatial scale includes lagoons and estuaries of the inner coastal waters (e.g. Szczecin Lagoon, Jasmund lagoon) where harbour porpoises do not or only exceptionally occur unlike the map suggests.

This dataset contains modelled small vessel fuel consumption. This describes the geographical distribution of the fuel used by small boats. The total fuel consumption was modelled in SHEBA project to study emissions from pleasure boats. The model is based on locations and berths in marinas and leisure harbours, AIS information, statistics on fuel sale and extensive survey. For 2018 version the layer is weighted with depth, log-transformed and normalised (please see below). This dataset was also used on HOLAS 3.

Baltic International Trawl Survey (BITS) data (2011-2016) from ICES DATRAS database was used as a base to create a map of cod relative abundance (quarter 1 data, CPUE values per ICES subdivision). Cod = 30cm was included. For ICES rectangles surveyed by BITS, values shown are the mean CPUE per ICES subdivision based on BITS data, average for 2011-2016. For ICES rectangles not surveyed by BITS, 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 = CPUE according to BITS in the ICES rectangle with highest landings. ICES rectangles outside the BITS survey area with no reported cod landings were given the value 0. Values were first log transformed and then normalized.

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.