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.

This pressure dataset is derived from three human activities datasets - Urban land use (on land) - Recreational boating and sports (updated layer for 2018 version, please see separate http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/8c30e828-1340-4162-b7f9-254586ae32b6) - Bathing sites These data are described in more detail in separate fact sheets. 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. Bathing sites (points) were converted to 1km grid and given value 1, rest of the sea areas were given value 0. Normalized recreational boating data was converted to 1 km grid cells. These three layers were summed to produce the layer (values from 0 to 3), after that the layer was normalized. 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.

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).

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.

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.

Distribution of Fucus sp. based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of Fucus 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. All data (Fucus points and the raster presenting predicted presence of Fucus) were generalized to 5km x 5km grid cells.

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.

Summary Model results for the distribution of where at least 1% available light touches the seabed (the photic zone) and non-photic zone in the Baltic Sea based on 1% mean annual irradiance Description This dataset shows model results forthe distribution of where at least 1% available light touches the seabed (the photic zone) and non-photic zone in the Baltic Sea based on 1% mean annual irradiance. From an ecological point of view, available light is one of the primary physical parameters influencing and structuring the biological communities in the marine environment, as it is the driving force behind the primary production by providing the energy for the photosynthesis - energy that ultimately is transferred to other organisms not capable of photosynthesis. The depth of the photic zone is traditionally defined, for benthic plants, as the depth where 1% of the surface irradiance (as measured just below the water surface) is available for photosynthesis. Only two intervals based on light regime were used in the dataset, because they reflect the significant ecological difference between the shallow water depth with the presence of submerged aquatic vegetation, and the deeper waters where fauna (and bacteria) dominate diversity of species, abundance, and biomass. The intervals are: I. The photic zone (where at least 1% of the available light touches the seabed). II. The non-photic zone.The measurements of Secchi Depth used for producing this dataset are not evenly distributed and some areas in the Baltic Proper, Gulf of Riga and southern Baltic are not well covered.

The data represents the seabed slope of the Baltic Sea and has been derived from a bathymetry dataset. Both datasets have been produced by the BSR INTERREG IIIB project BALANCE. For more information see also the metadata file on bathymetry. Seabed slope (BALANCE) layer is expressed as percent slope (%).

This dataset is the first dedicated SMOS Sea Surface Salinity (SSS) product for the Baltic basin to enhance the science capabilities in the Baltic region and help to fill the gaps and grand challenges identified by the scientific community. These new product has been created under the funded ESA project ITT Baltic+ Salinity dynamics (4000126102/18/I-BG). This basin is one of the most challenging regions for the satellite SSS retrieval. The available EO-based SSS products are quite limited in terms of spatio-temporal coverage and quality. This is mainly due to technical limitations that strongly affect the brightness temperatures (TB), such as the high contamination by interferences and the contamination close to land and ice edges. Moreover, the sensitivity of TB to SSS changes is very low and dielectric models present limitations in this low salinity regime. Baltic+ L4 SSS product comprises 9 years (2011-2019) of daily maps at 0.05 degrees. A detailed explanation of the product algorithms and validation can be found at http://bec.icm.csic.es/doc/BEC_PD_SSS_Baltic_L3_L4.pdf and in the publication: Gonzalez-Gambau et al., “First SMOS Sea Surface Salinity dedicated products over the Baltic Sea“, Earth System Science Data, 2021 We present here the seasonal averaged Baltic+ L4 SSS products for the period 2011-2019. The daily Baltic+ L4 SSS products can be downloaded from the BEC FTP service (sftp://becftp.icm.csic.es) in the directory OCEAN/SSS/SMOS/Baltic/v1.0/L4/daily/