Ecotoxicity and chemical sediment data classification by the use of self-organising maps.

The present paper deals with the presentation in a new interpretation of sediment quality assessment. This original approach studies the relationship between ecotoxicity parameters (acute and chronic toxicity) and chemical components (polluting species like polychlorinated biphenyls (PCBs), pesticides, polycyclic aromatic hydrocarbons (PAH), heavy metals) of lake sediments samples from Turawa Lake, Poland by an application of self-organising maps (SOMs) to the monitoring dataset (59 samplesx44 parameters) in order to obtain visual images of the components distributed at each sampling site when all components are included in the classification and data projection procedure. From the SOMs obtained, it is possible to select groups of similar ecotoxicity (either acute or chronic) and to analyse within each one of them the relationship of the other chemicals to the toxicity determining parameters (EC(50) and mortality). Studies have shown, convincingly, that different regions from the Turawa Lake bottom indicate different patterns of ecotoxicity related to various chemical pollutants, such as the "heptachlor-B" pattern, "pesticide and PAH" pattern, "structural" pattern or "PCB congeners" pattern. Thus, an easy way of multivariate analysis of small datasets with ecotoxicity parameters involved becomes possible. Additionally, a distinction between the effects of pollution on acute and chronic toxicity seems reasonable.