This layer is based on data from the BIAS project representing ambient underwater noise, modelled into a 0.5 km x 0.5 km grid, and representing sound pressure levels at 1/3 octave bands of 125 Hz exceeded at least 5% of the time. Measured and modelled acoustic data is provided as Sound Pressure Level (SPL). The time period for the data is annual values for year 2014. The selected depth interval is 0 m – bottom to represent the ambient underwater noise in the whole water column. The data were normalized setting level 0 at 92 db re 1µPa and level 1 at 127 db re 1µPa.

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).

Potential effect of continuous noise to mobile species assesses the cumulative potential effect of continuous noise on mobile species and their presence in the HELCOM area. The evaluation is based on the pressure layer on input of continuous noise, combined with information on the distribution of 15 mobile species and their habitats. The thematic analyses on the potential effect of continuous noise to mobile species is calculated for each assessment unit (1 km2 grid cells) and the data set covers the time period 2016-2021. Spatial Pressure and Impact Assessment (SPIA) is the framework for assessing spatial and cumulative pressures and impacts in HOLAS 3, and this analyses present a thematic assessment including only a certain subset of layers. The framework also includes results for the Baltic Sea Impact Index (full cumulative impact assessment), Baltic Sea Pressure Index (full cumulative pressure assessment), and other thematic assessments where a subset of pressure and ecosystem layers are used. For more info please - visit the HOLAS 3 website (http://stateofthebalticsea.helcom.fi/) - download the report thematic assessment of spatial distribution of pressures and impacts 2016-2021 (https://helcom.fi/post_type_publ/holas3_spa) - or check out the HELCOM SPIA online tool to make calculations for any desired combination of pressures and ecosystem layers (https://maps.helcom.fi/website/bsii/). Please scroll down to "Lineage" for a more detailed description of the methodology.

Input of heat pressure dataset contains delta heat values from warm water discharge of - Discharge of warm water from nuclear power plants - Fossil fuel energy production. The Discharge of warm water from nuclear power plants was requested from HELCOM Contracting Parties. Average temperature change of the cooling water (°C) and amount of cooling water (m3) was used to calculate the heat load in TWh. No data on heat load was available for the Leningrad nuclear power plant; therefore the average heat load (TWh) of discharge of warm water from nuclear power plants was given. No heat load information was available for fossil fuel energy production sites. Heat load of 1 (TWh) was given to all production sites, based on average heat load of individual production site in Helsinki from recent years. 1 km buffer was used for both datasets with steep decline around the outlet. Overlapping areas were summed. Heat load from both layers were summed and the layer was normalized.

Input of hazardous substances pressure layer is interpolated from CHASE Assessment tool concentration component. The contamination ratio values were calculated with CHASE Assessment tool for hazardous substances monitored in water, sediment and biota. Classified mean contamination ratio was used in the interpolation. Classification is based on the http://stateofthebalticsea.helcom.fi/about-helcom-and-the-assessment/downloads-and-data/. The points were interpolated to cover the entire Baltic Sea with Spline with barriers interpolation method. Please see "lineage" section below for further details on attributes, data source, data processing, etc.

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.

Summary Model results for the distribution of where at least 1% available light touches the seabed (the photic zone) and non-photic zone in the Baltic Sea based on 1% mean annual irradiance Description This dataset shows model results forthe distribution of where at least 1% available light touches the seabed (the photic zone) and non-photic zone in the Baltic Sea based on 1% mean annual irradiance. From an ecological point of view, available light is one of the primary physical parameters influencing and structuring the biological communities in the marine environment, as it is the driving force behind the primary production by providing the energy for the photosynthesis - energy that ultimately is transferred to other organisms not capable of photosynthesis. The depth of the photic zone is traditionally defined, for benthic plants, as the depth where 1% of the surface irradiance (as measured just below the water surface) is available for photosynthesis. Only two intervals based on light regime were used in the dataset, because they reflect the significant ecological difference between the shallow water depth with the presence of submerged aquatic vegetation, and the deeper waters where fauna (and bacteria) dominate diversity of species, abundance, and biomass. The intervals are: I. The photic zone (where at least 1% of the available light touches the seabed). II. The non-photic zone.The measurements of Secchi Depth used for producing this dataset are not evenly distributed and some areas in the Baltic Proper, Gulf of Riga and southern Baltic are not well covered.

This map shows the distribution and abundance of harbour seals across the Baltic Sea. The map was originally created for HELCOM Red list assessment of the Baltic Sea, using seal expert consultation. For the Baltic Sea Impact Index, the map was modified to represent four abundance classes, based on expert consultation. The map has been updated from the 1st version of HOLASII, based on expert consultation (HELCOM Seal EG).

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 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.