EN
Nine sites studied in the years 1997-1998 along the Upper Vistula course (from 10.9 to 336.7 km) were characterized based on the relative abundance of various net phytoseston (≥50 μm) predominant taxa. The prevalence of oligo-mesotraphentic diatoms (Fragilaria arcus (Ehr.) Cl.) and green alga Stichococcus sp. indicated generally pure waters at the montane sector of the river course. They were associated with betamesosaprobic taxa of chrysophytes (Kephyrion spp.) and rhodophytes (Audouinella sp.) characteristic for well oxygenated waters. Increased abundance of beta- and alpha-meso/polysaprobic indicators (Melosira varians Ag.) and those tolerant to organic pollution (Navicula lanceolata (Ag.) Ehr., Fragilaria ulna (Nitzsch) Lange-Bertalot) was noted on 36.6 km of the river indicating slight pollution. An increased trophic state, organic pollution and salinity level, expressed with the predominance of betamesosaprobic and eutraphentic diatoms (Aulacoseira granulata (Ehr.) Sim.) accompanied by desmids and euglenins (typical of beta-alpha-mesosaprobic zones) was observed on 45.7 km. The prevalence of Stichococcus sp. and Pediastrum spp. with increased share of alpha-meso/polysaprobic indicators (Stephanodiscus hantzschii Grun.) and polysaprobic (Nitzschia palea (Kütz.) W. Sm.) was found on 66.2 km. The sector between 117.6-185.2 km of the river course with strongly polluted waters of the worst quality, was characterized by augmented percentage share of cyanobacteria. Decreasing pollution level found on 248.2-336.7 km probably resulted from the dilution effect caused by montane Carpathian tributaries of the Vistula. The increase in beta-mesosaprobic and meso-eutraphentic indicators was related to Chlorococcales, which dominated over dense populations of cyanobacteria. Evaluation of water quality using net phytoseston groups with predominant indicator taxa, provides important information concerning the abundance of rapidly renewing Chlorococcales and potentially toxic cyanobacteria what is omitted in benthic diatom indices method.