Publications by authors named "G P Shtereva"

Recent DNA-based phylogenetic studies have reported high eukaryotal diversities in a wide range of settings including samples obtained from anoxic environments. However, parallel RNA-based surveys are required in order to verify whether the species detected are in fact metabolically active in such extreme environments. The Black Sea is the World's largest anoxic basin but remains undersampled with respect to molecular eukaryotic diversity studies.

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Varna Bay is one of the hot spots along the Black Sea coastal zone. Its ecological state is strongly influenced by the connection with the Varna Lake. Along the lake coast are located many sources of pollution such as rivers, ports, chemical industry, WWTPs.

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Intrinsic fluorescence and SDS-PAGE analysis were employed to study the seasonal qualitative and quantitative changes of phytoplankton composition at Varna Bay (Black Sea). Variation in the maximum emission wavelength (lambda(max)) of the phytoplankton proteins (398 nm in the summer and 340 nm in the spring) was observed. In addition, a decrease in fluorescence intensity, and a shift in lambda(max) as a result of changes in phytoplankton protein stability, according to the season, was noted.

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The paper discusses the seasonal dynamics of nutrients and oxygen during the period 1995-1998 in comparison to the previous periods. This study is based on monthly and seasonally monitoring in the 3-20 n. m.

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The present paper is an attempt to test the applicability of the trophic state index (TRIX) for scaling the eutrophication along the Bulgarian Black Sea coastal zone in concert with a number of chemical and biological descriptors aimed at selection of relevant indicators of marine coastal area ecological quality. The following environmental parameters have been considered: t(o), salinity, nutrients--inorganic P, N and dissolved Si, dissolved oxygen and oxygen saturation, phytoplankton--taxonomic structure, abundance and biomass, chlorophyll a, zooplankton--taxonomic structure, abundance and biomass. Principal Component Analysis was applied in order to figure out and score the most relevant combination of parameters to discriminate between sites and select representative descriptors (pressure/state) of eutrophication.

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