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 dataset is built from following Human activities datasets: • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/81c917ea-492d-48e2-9f00-e1bb7fe3e4fc • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/4fcd51dd-b8be-4e83-8cad-37c566782e8f The game hunting of seabirds data (see separate metadata): The total number of hunted seabirds were averaged over 2011-2015 (number of hunted seabirds / year). The area of the reporting unit was used to calculate the number of hunted seabirds / km2 and the data was converted to 1km x 1km grid. The predator control of seabirds data (see separate metadata): The total number of hunted cormorants were averaged over 2011-2015 (number of hunted cormorants / year). The area of the reporting unit was used to calculate the number of hunted cormorants / km2 and the data was converted to 1km x 1km grid. The two datasets were first separately log transformed and then summed, to get the total value for each grid cell. Zero values were given to all grid cells with no reported seabird hunting activity. The layer was normalized.

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 hard substrate” includes classes “Rock and other hard substrate” and “Coarse substrate” of the original data, in the infralittoral zone. The original polygon maps have been converted to 1 km x 1 km 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.

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.

Input of impulsive anthropogenic sound includes impulsive events from 2011-2016 • Seismic surveys (HELCOM-OSPAR Registry; national data call submissions as lines in the folder of data) • Explosions (HELCOM-OSPAR Registry) • Pile driving (HELCOM-OSPAR Registry) • Airguns (HELCOM-OSPAR Registry) For the different event types, numeric intensity value was used to represent the pressure as categorized in HELCOM-OSPAR Impulsive noise registry. All nationally reported seismic surveys were given intensity values “Very low” (0.25) - Very low (0.25) - Low (0.5) - Medium (0.75) - High (1) The impact distance has not been taken into account due to the different nature of separate datasets used for the pressure layer. We acknowledge that e.g. pile driving and airguns may impact up to 20 km from the source event. The spread of the sound wave depends on the sound frequency, water salinity, temperature and density.

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 “circalittoral hard substrate” includes classes “Rock and other hard substrate” and “Coarse substrate” of the original data, in the circalittoral zone. The original polygon maps have been converted to 1 km x 1 km 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 is an assessment component that describes the potential cumulative burden on the environment in different parts of the Baltic Sea. The BSII is based on georeferenced datasets of human activities (36 datasets), pressures (18 datasets) and ecosystem components (36 datasets), and on sensitivity estimates of ecosystem components (so-called sensitivity scores) that combine the pressure and ecosystem component layers, created in http://www.helcom.fi/helcom-at-work/projects/holas-ii project. Cumulative impacts are calculated for each assessment unit (1 km2 grid cells) by summing all pressures occurring in the unit for each ecosystem component. Highest impacts are found from the cells where both are abundant, but high impacts can be caused also by a single pressure if there are diverse and sensitive habitats in the grid cell. All data sets and methodologies used in the index calculations are approved by all HELCOM Contracting Parties in review and acceptance processes. This data set covers the time period 2011-2016. Please scroll down to "Lineage" and visit http://stateofthebalticsea.helcom.fi/cumulative-impacts/ for more info.

Springtime Chl-a concentration is here used as a proxy for productive surface waters. In the Baltic Sea Impact Index (BSII), areas with high springtime phytoplankton production will be given higher importance, as they are considered important areas for the Baltic Sea food web. In the current map, mean of springtime maximum weekly values (weeks 12-22, years 2003-2011) Chl-a concentration of the surface waters has been used, derived from satellite data (MERIS). Years 2003-2011 have been used, as there is no MERIS data available for years 2012-2016. The data for eastern Baltic Sea is provided by the Finnish Environment Institute (~300m resolution). Outside this high resolution data, MERIS-data downloaded from JRC-database has been used (~4 km resolution, to calculate average of maximum monthly values for April or May for 2003-2011). Both datasets were converted to 1 km x 1 km grid cells.

Essential fish habitat (EFH) map on Potential spawning areas for sprat was prepared in PanBalticScope project (co-founded by the European Maritime and Fisheries Fund of the European Union) http://www.panbalticscope.eu/ Sprat (Sprattus sprattus) occurs in the entire Baltic Sea, and mainly in open sea areas. It is assessed as a single stock in the Baltic Sea within fisheries management. Sprat eggs are pelagic, and sprat spawning is well known from the deep basins in the central Baltic, where it typically occurs from February to August. Further north, spawning starts later in the year, and is less certain. Recent fisheries surveys indicate that sprat spawning does no longer occur in the Gulf of Finland. Sprat spawning areas were delineated using environmental variables due to lack of coherent field data across the Baltic Sea countries. “Potential sprat spawning areas” were delineated as areas with salinity > 6 and water depth > 30 m, but for the Arcona basin depth > 20 m was used (Grauman, 1980, Bauman et al. 2006, Voss et al. 2012). “High probability spawning areas” were delineated for areas deeper than 70 m. Stock: Sprat in subdivisions 22-32 (ICES) EFH type: Potential spawning areas Approach: Environmental envelope, corrected for areas 20-40 m south of Bornholm. Variables and thresholds: Potential spawning area: Depth > 30 m, Salinity > 6 (annual average) High probability spawning area: Depth >70 m, Salinity > 6 (annual average) Quality: The map is based on literature and environmental variables, not actual data on sprat spawning. The map might overestimate the spawning area west and north of Gotland. The data layers on environmental variables are based on modelling. Attribute information: Raster value representing no spawning (0), potential spawning area (0.5) and high probability spawning area (1). References: - Baumann, H, H Hinrichsen, C Mollmann, F Koster, A Malzahn, and A Temming (2006) Recruitment variability in Baltic Sea sprat (Sprattus sprattus) in tightly coupled to temperature and transport patterns affecting the larval and early juvenile stages. Canadian Journal of Fisheries and Aquatic Science 63:2191-2201 - Grauman GB (1980) Long term changes in the abundance data of eggs and larvae of sprat in the Baltic Sea. Fisheries research in the Baltic Sea, Riga. 15:138-150 (in Russian) - HELCOM (2018) Outcome of the regional expert workshop on essential fish habitats, organized by Pan Baltic Scope project and HELCOM (HELCOM Pan Baltic Scope EFH WS 1-2018) - Voss R, MA Peck, HH Hinrichsen, C Clemmesen, H Baumann, D Stepputis, M Bernreuther, JO Schmidt, A Temming, and FW Köster (2012) Recruitment processes in Baltic sprat - A re-evaluation of GLOBEC Germany hypotheses. Progress in Oceanography 107:61-79

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.