Kotrys, B., Tomczak, M., Witkowski, A., Harff, J., Seidler, J.
Diatom-based estimation of sea surface salinity in the south
Baltic Sea and Kattegat
The new diatom-based sea-surface salinity (SSS) estimation
has been applied to a collection of 27 taxa in 48 present-day sediment and
surface water samples recovered in the Baltic Sea and Kattegat. The sediment
core 303610-12 (2005) from the Eastern Gotland was chosen for the study of the
Holocene sequence spanning the past 8160 yrs BP. The Artificial Neuronal
Network (ANN) method provided an estimation of spring (March-April) SSS values
ranging between 7.04-8.25 ‰. The low amplitude of salinity change might be
caused by mixing of fresh water with upper surface layer of the Baltic Sea due
to high precipitation and riverine input. These findings were compared with
independent geochemical proxies for salinity (K, Ti and S) derived from XRF
Core Scanner record. Significant correlation between salinity and sulphur
records and an inverse correlation between K and Ti demonstrate that the ANN
method, when combined with quantitative and qualitative analyses of diatoms,
provides a useful tool for palaeo-salinity reconstructions from the Holocene
sediments of the Baltic Sea.