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 Charophytes (Chara spp., Nitella spp., Nitellopsis spp., Tolypella spp.) mainly based on data submission by HELCOM contracting parties. Submitted point data was originally gathered in national mapping and monitoring campaigns, or for scientific research. Also scientific publications were used to complement the data (in Curonian, Vistula and Szczechin lagoons, see reference list). Polygon data from Poland was digitized based on Polish Marine Atlas. 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 Charophytes) were generalized to 5km x 5km grid cells.

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.

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.

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.

Boreal Baltic islets and small islands (according to Habitats Directive Annex I) are groups of skerries, islets or single small islands, mainly in the outer archipelago or offshore areas. They are important nesting sites for birds and resting sites for seals. The surrounding sublittoral vegetation is also included. The distribution map is based on data submission by HELCOM contracting parties. Only Sweden and Finland reported occurrences of boreal Baltic islets and small islands.

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 “infralittoral mud” includes classes “Fine mud”, “Mud to sandy mud” and “Sandy mud” of the original data, in the infralittoral zone. The original polygon maps have been converted to 1 km x 1km 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.

The Baltic Sea Impact index (BSII) assesses the potential cumulative impact of pressures over ecosystem components. The BSII is based on georeferenced datasets of human activities (28 datasets), pressures (17 datasets) and ecosystem components (57 datasets), and sensitivity estimates of ecosystem components to pressures (sensitivity scores). Cumulative impacts are 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, where the BSII presents the full cumulative impact assessment where all pressures and ecosystem components are included. The framework also includes results for the 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.

Estuaries (according to Habitats Directive Annex I) are coastal inlets that are strongly influenced by freshwater. The distribution map is based on data submission by HELCOM contracting parties. Most of the submitted data is based on modelling, GIS analysis and/or aerial photos. Data coverage, accuracy and the methods in obtaining the data vary between countries.

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).