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        <gco:CharacterString>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 &gt; 6 and water depth &gt; 30 m, but for the Arcona basin depth &gt; 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 &gt; 30 m, Salinity &gt; 6 (annual average)
High probability spawning area: Depth &gt;70 m, Salinity &gt; 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</gco:CharacterString>
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            <gco:CharacterString>Sprat spawning areas were delineated using environmental data due to lack of coherent field data across the Baltic Sea countries. “Potential sprat spawning areas” were delineated as areas with salinity &gt; 6 and water depth &gt; 30 m, but for the Arcona basin depth &gt; 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. Following source data was used:

Depth: Baltic Sea Bathymetry database (http://data.bshc.pro/#2/51.8/20.1), complemented in some coastal areas with Seifert et al. (2001)
Salinity: Copernicus Marine Environment Monitoring Service, SMHI. The data represents monthly data for years 2011-2016 downloaded from Copernicus Marine Environment Monitoring Service (http://marine.copernicus.eu). Reanalysis products of SMHI for years 1989-2004, 5.5km grid cells. The layers represent conditions at the sea floor. Extrapolation to some coastal areas that were outside the original data due to low resolution of the grid was carried out

Layer edited in February 2021 to remove Nodata cells within the http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/7a0256db-f557-4f8f-a5a1-bfb25fee225f. Nodata cells were given the value based on the value of adjacent cells. The tool “focal statistics” was used by including 3 adjacent cells to each direction (rectangle) in the analysis and populating the Nodata cells with the most frequent value (Majority) found within that area. The tool was run several times with the same settings, if the Nodata area was larger and all cells could not be populated with on go.

This data was uploaded to EMODnet in September 2023.</gco:CharacterString>
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