The layer presents the cumulative negative impacts on marine biodiversity caused by alien species in the Baltic Sea. The layer is based on the Cumulative IMPact of ALien species (CIMPAL) index, developed by Katsanevakis et al. (2016). The original methodology was applied for the Baltic Sea similarly as Korpinen et al. (2019) applied it for the EU waters in their report Multiple pressures and their combined effects in Europe’s seas. The list of species and habitats together with the sensitivity scores are originating from this study and listed in the linage section of this metadata. The index follows a conservative additive model for calculating the cumulative negative impacts of invasive alien species (IAS), based on magnitude of impact and the related strength of evidence following an uncertainty averse strategy. Cumulative impacts of IAS were estimated on the basis of the distributions of invasive species and ecosystems, and both the reported magnitude of ecological impacts and the strength of such evidence. 29 invasive species and 12 habitats were used for the layer, detailed information on the species, habitats and sensitivity scores used in the assessment are given in the lineage section. The information on species and habitats were aggregated to 10x10 km grid, based on their occurrence within each grid cell. Calculation of the index was done with the HELCOM SPIA tool, and the result were converted to the 1x1km SPIA grid. The layer was normalized to be used in the assessment.

Physical loss pressure layer combines all human activities that cause physical loss of seabed. The pressure is given as area lost in each cell (km2). For the polygon datasets the area was assumed to be the lost area. For line and point datasets spatial extents were calculated with buffers (below in brackets). If no buffer extent is indicated, the data was reported as polygon. The human activities used for the physical loss pressure: Land claim - Area of polygon or 50 m buffer for points, 30m buffer for lines. Area of polygon - buffered line or point data, equals lost area. Watercourse modification - 50 m buffer. Area of polygon, buffered line or point data, equals lost area. Coastal defence and flood protection - 50 m buffer for lines, area of polygon. Area of polygon, buffered line or point data, equals lost area. Extraction of sand and gravel - Area of polygon. Area of polygon equals lost area. Dredging (capital) - Area of polygon or a 25/50 m buffer for <5000 m3 / >5000m3 sites. Area of polygon, buffered line or point data, equals lost area. Oil platforms - 25 m buffer. Buffered point data, equals lost area. Pipelines - 15 m buffer around cables with operational status. Area of polygon, buffered line or point data, equals lost area. Wind farms - 30 m buffer around each turbine with operational status. Buffered point data, equals lost area. Cables - 1.5 m buffer around cables with operational status. Buffered line data, equals lost area. Harbours - Polygon with 200 m buffer. Area of polygon, buffered line or point data, equals lost area. Marinas and leisure harbour - Point with 200 m buffer. Buffered point data, equals lost area. Bridges - 2 m buffer. Buffered line data, equals lost area. Finfish mariculture - 150 m buffer. Buffered point data, equals lost area. Shellfish mariculture - Area of polygon, 150 m buffer for points. Buffered point data, equals lost area. Activities are combined and potentially overlapping areas are removed. Dataset is clipped with coastline. Combined layer is intersected with 1 km grid to calculate % of area lost within a cell.

Input of impulsive anthropogenic sound includes impulsive events from 2016-2021 • 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.

Introduction of radionuclides is based on HELCOM MORS discharge data (2016-2020) . Annual averages of CO60, CS137 and SR90 from the period 2016-2020 per nuclear power plant. Gradual buffer around outlet to 10km distance (Type B decline). 10 km buffer with linear decline composed of 5 rings from discharges of radioactive substances (Type B decline)12.

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. Detailed information about this pressure layer can be found in the indicator report.

This pressure dataset is derived from three human activities datasets Recreational boating and sports: Total fuel consumption of recreational boats modelled directly to 1 km grid cells[1]. Total fuel consumption of recreational boats presented as presence / absence. Rescaled with depth, log-transformed and normalized. Bathing sites, beaches: Point data converted directly to 1 km grid cells. Location of beaches presented as presence (1) / absence (0). Urban land use: Urban land use data was first converted to 1 km grid cells and expanded with 1 km[2]. 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. 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.S pecific pressure layers first modified by spatial extents and depth influence. Each of them is considered as of equal importance (same weight). Calculate the sum of the pressure in a cell. Normalized. [1] SHEBA project [2] Estimate of the human disturbance (underwater sound, visual disturbance).

Pressure layer combines all human activities that cause changes to hydrological conditions. The human activities were presented as point data which were given spatial extents (given below). The pressure value was given as the proportion of the grid cell under the pressure. Water course modification: 1 km buffer[10]. Location of water course modifications used for buffer. Overlaps removed and areas of buffer calculated per each grid cell. The final value was the area of the buffer in each individual cell. Wind farms: 300 m buffer around each turbine classified as operational, with linear decline (Type B decline), composed of 3 rings. Location of operational turbines as points were buffered and values given over linear decline. Oil platforms: 500 m buffer around each turbine with linear decline (Type B decline) composed of 5 rings. Location of oil platforms as points were buffered and values given over linear decline. Hydropower dams: A grid cell in the estuary. Locations of hydropower dams were crossed with rivers and the grid cell located in the end of the river was selected as presence (1) – those that are operational and produces energy. Other values in the grid were considered absence. [10] Extent based on wind farms and cables but expanded to 1 km because hydrological parameters are widely spreading. The human activity datasets were first processed separately covering the whole Baltic Sea and then summed together and overlapping areas were dissolved to remove double counting. Attenuation gradients are assigned to each layer as described above. Area effected decreases when distance from avtivity increases. Layer was normalized.

The dataset contains the extraction of one of the target species, sprat, for the period 2016-2020. The extraction of sprat data set is based on "Fish extraction - commercial fisheries HOLAS 3". Further information about how this dataset was collected and extracted can be found at: https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/a0104cfd-d237-459b-84f8-8e9e21d2df9b Reported per ICES Rectangles, Russian data extracted from ICES annual reports, reported per ICES sub-divisions. Values are redistributed with fishing effort data c-squares (all gears) 2016-2021. Effort values missing from Russia and sub-basin average values given. Extraction of fish species (landings) per ICES c-squares, average of 2016-2020. Landings calculated per km2. Tons/km2 calculated for each species. Log-transformed and normalized.

The dataset contains the extraction of one of the target species, cod, for the period 2016-2021. The extraction of cod data set is based on "Fish extraction - commercial fisheries HOLAS 3". Further information about how this dataset was collected and extracted can be found at: https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/a0104cfd-d237-459b-84f8-8e9e21d2df9b Reported per ICES Rectangles, Russian data extracted from ICES annual reports, reported per ICES sub-divisions. Values are redistributed with fishing effort data c-squares (all gears) 2016-2021. Effort values missing from Russia and sub-basin average values given. Extraction of fish species (landings) per ICES c-squares, average of 2016-2020. Landings calculated per km2. Tons/km2 calculated for each species. For cod, recreational fisheries catches were added. Log-transformed and normalized.

The dataset contains the extraction of one of the target species, herring, for the period 2016-2020. The extraction of herring data set is based on "Fish extraction - commercial fisheries HOLAS 3". Further information about how this dataset was collected and extracted can be found at: https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/a0104cfd-d237-459b-84f8-8e9e21d2df9b Reported per ICES Rectangles, Russian data extracted from ICES annual reports, reported per ICES sub-divisions. Values are redistributed with fishing effort data c-squares (all gears) 2016-2021. Effort values missing from Russia and sub-basin average values given. Extraction of fish species (landings) per ICES c-squares, average of 2016-2020. Landings calculated per km2. Tons/km2 calculated for each species. Log-transformed and normalized.