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 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.

Esker islands (according to Habitats Directive Annex I) are glaciofluvial islands consisting mainly of relatively well sorted sand, gravel or less commonly of till. Also their underwater parts are included in the habitat. The distribution map is based on data submission by HELCOM contracting parties. Only Sweden and Finland reported occurrences of esker islands. Only underwater parts are included in the datasets. The data is based on modelling and GIS analysis. Data coverage, accuracy and the methods in obtaining the data vary between countries.

The pressure oil slicks and spills is combination of following datasets: • Illegal oil discharges • Polluting ship accidents Illegal oil discharge data is based on airborne surveillance with remote sensing equipment in the Baltic Sea Area. The area of the detected spills in 2011–2016 was used to represent the pressure. The value of spills under 1km2 were directly given to grid cell, spills over 1km2 were buffered based on estimate spill area. For polluting ship accidents the reported oil spill volumes (m3) in years 2011-2015 were used for the pressure. Some polluting ship accidents spills were missing spilled oil volume, thus a mean of reported volumes was given to accidents with missing oil volume. Datasets were handled separately. Both layers were normalized, summed and normalized again to produce the “oil slicks and spills” pressure layer. Please see below for further details.

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.

This map shows the distribution and abundance of grey 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 Baltic Sea Pressure index (BSPI) assesses the potential cumulative pressures in the Baltic Sea. The BSPI is based on georeferenced datasets of human activities (28 datasets), pressures (17 datasets) and uses the average sensitivity of each pressure layer to all ecosystems to weigth the pressure. Cumulative pressures 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 BSPI presents the full cumulative pressure assessment where all pressures are included. The framework also includes results for the Baltic Sea Impact Index (full cumulative impact 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.

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).

Pressure layer combines all human activities that cause physical disturbance or damage to seabed. For several human activity datasets, spatial extents were given (table below). Buffers with decreasing value rates were applied to represent the impact distance of physical disturbance. The following human activities were combined into the physical disturbance layer; - Cables (under construction, 1 km buffer) - Coastal defence and flood protection (under construction, 500 m buffer) - Deposit of dredged material (500 m buffer for points and areas) - Dredging (maintenance) (500 m buffer for points and areas) - Extraction of sand and gravel (500 m buffer) - Finfish mariculture (1 km buffer) - Fishing intensity 2011-2016 average (subsurface swept area ratio) - Furcellaria harvesting - Pipelines (0,3 km buffer) - Recreational boating and sports - Shellfish mariculture - Shipping density - Wind farms (under construction) (1 km buffer) - Wind farms (operational) (0,1 km buffer) The human activity data sets were first processed separately covering the whole Baltic Sea and then summed together. In this integration, some data layers were down-weighted to arrive at a balanced pressure layer, as described below. High pressure intensity and/or slow recovery (weighting factor 1): Coastal defence and flood protection, Deposit of dredged material, Dredging, Extraction of sand and gravel and Fishing intensity Moderate to high (Weighting factor 0,8): Pipelines and Shipping density Moderate (Weighting factor 0,6): Finfish mariculture, Shellfish mariculture and Wind farms (under construction) Low to moderate (Weighting factor 0,4): Cables Low (Weighting factor 0,2): Maerl and Furcellaria harvesting, Recreational boating and sports and Wind farms (operational) Harbours and marinas were left out from the physical disturbance pressure to avoid double counting due to their representation in the shipping density and recreational boating and sports data sets.

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.