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The fishing intensity map displays data provided in C-square (0.05 x 0.05 degrees) converted to 1x1 km raster 2011-2016. The value of raster cell is subsurface swept area ratio. The data does not cover Russian waters.
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.
Data set represents dredging activities around the Baltic Sea. The dataset contains information about the dredging activity and for some the type (capital, maintenance) and the year of activity as reported by HELCOM Contracting Parties in response to data request. The dredging data is missing from Denmark.
This dataset shows the sub-basins of the Baltic Sea which are used for Baltic Sea Pollution Load Compilation 6.
Distribution of eelgrass based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of eelgrass were submitted, originally gathered in national mapping and monitoring campaigns, or for scientific research. Polygon data from Puck Bay (Poland) was digitized based on Polish Marine Atlas and Orlowo cliff area was added based on expert knowledge. From Estonian waters, a predictive model was used (200m resolution), that was converted to presence/absence using minimized difference threshold (MDT) criteria. All data (points, polygon and the raster presenting predicted presence of eelgrass in the Estonian waters) were generalized to 5km x 5km grid cells.
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.
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 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.
This data set on deposition sites of dredged material (areas) reported by HELCOM Contracting parties according to http://www.helcom.fi/Recommendations/Rec%2036-2.pdf for the reporting period 2011-2016. The dataset contains data reported by nationally by nominated experts by HELCOM PRESSURE group for Denmark, Germany, Estonia, Finland, Latvia, Lithuania, Poland, Russia and Sweden.
Eutrophication, caused by excess inputs of nutrients, is one of the main threats affecting the Baltic Sea marine environment. Nutrients enter the Baltic Sea as waterborne (riverine inputs from the catchment area and direct discharges from point and diffuse sources in coastal areas) and airborne (atmospheric deposition) inputs. In 2007 HELCOM adopted a nutrient reduction scheme which is based on maximum allowable nutrient inputs (MAI) to reach "good environmental status" and country-wise nutrient reduction targets (CART) to share the burden of reducing nutrient pollution to the sea (HELCOM Baltic Sea Action Plan). Monitoring of nutrient inputs to the sea is important for assessing progress of countries towards their CART and to evaluate the effectiveness of measures to reduce pollution. This dataset displays total normalized annual average phosphorus loading as produced for href="http://www.helcom.fi/baltic-sea-trends/indicators/inputs-of-nutrients-to-the-subbasins" target="_blank"> HELCOM Core indicator: Inputs of nutrients to the subbasins based on HELCOM PLC data. Green colour of PLC subbasin indicates that inputs during 2016 were lower than MAI, red colour when they were higher, while yellow indicates that when taking into account the statistical uncertainty of input data it is not possible to determine whether MAI was fulfilled. The dataset contains following attributes: Basin: Name of PLC Subbasin Maximum allowable nutrient input: Maximum allowable phosphorus input for the subbasin (tons/year) P input including statistical uncertainty 2016: the average normalized phosphorus input during 2016 (tonnes/year) including statistical uncertainty for the subbasin Input 2016 including stat. uncertainty in % of MAI: proportion of average normalized phosphorus input during 2016 compared to MAI Classification of achieving MAI: Classification of achieving MAI is given in colours: green=MAI fulfilled, yellow= fulfilment is not determined due to statistical uncertainty, and red=MAI not fulfilled.