The maps of herring and sprat relative abundance are based on the Baltic International acoustic surveys (BIAS), years 2016-2020 (ICES WGBIFS reports), reported as millions of fish / ICES rectangle.

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.

The occurrence of suitable nursery habitats is crucial for maintaining fish populations (Sundblad et al. 2013). For perch, species distribution modelling studies (Snickars et al. 2010, Bergström et al. 2013, Sundblad et al. 2013) have shown the importance of suitable environmental conditions for reproduction. Due to lack of coherent data on perch spawning and nursery areas across the Baltic Sea countries, environmental variables were used in delineating potential recruitment areas for perch. The distribution area or perch recruitment is delineated by selecting areas where depth < 4 m (For Danish waters < 3 m), logged exposure < 5 (exposure model described in Isæus 2004), and salinity < 10 PSU. The threshold values have been obtained from literature (Snickars et al. 2010, Bergström et al. 2013, Skovrind et al. 2013, Sundblad et al. 2013). Relatively “loose” thresholds have been used, to rather overestimate than underestimate the recruitment area (precautionary approach). Along the Finnish coastline a national model has been used (Kallasvuo et al. 2016), with suitable environments for perch recruitment generalized to 1 km x 1 km grid.

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.

The map of sprat relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016, (ICES WGBIFS reports), reported as millions of sprat per ICES rectangle. The BIAS surveys cover almost the whole area where sprat is commonly encountered. Outside BIAS area, sprat landings data was used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, 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 2011-2015). MAX-value = millions of sprat according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported sprat landings were given the value 0. The abundance values / ICES rectangle were divided by the area of the rectangle to obtain values per 1km2, and then converted to 1 km x 1km grid cells. Values were first log transformed and then normalised.

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.

The map of herring relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016 (ICES WGBIFS reports), reported as millions of herring / ICES rectangle. Also herring landings data were used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, 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 = millions of herring according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported herring landings were given the value 0. The relative abundance values in each ICES rectangle were divided by the area of the rectangle to obtain values per 1km2. If the values in small coastal ICES rectangles (outside BIAS area) became unrealistically large due to high herring landings, the value of the neighboring rectangle was given. The final layer was converted to 1 km x 1km grid cells. Values were first log transformed and normalized.

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).

This map shows the distribution and abundance of harbour porpoise across the Baltic Sea. The ecosystem component maps on mammals distribution were drafted by EG MAMA harbour porpoise and seals distribution teams. The dataset was created to be used in the HELCOM Third Holistic Assessment of the Ecosystem health of the Baltic Sea. The methodology report can be found in https://dce2.au.dk/pub/TR240.pdf

The seals' distribution maps show the distribution and abundance of grey, harbour and ringed seals across the Baltic Sea. The ecosystem component maps on mammals' distribution were drafted by EG MAMA harbour porpoise and seal distribution teams. The maps were prepared as expert-derived distribution categories to be used in the HELCOM Third Holistic Assessment of the Ecosystem health of the Baltic Sea.