Self Organizing Maps (SOMs) are increasingly popular methods in processing highdimensional ecological data, however, their potentials are not yet fully utilized. It was our objective to prove evidence on an unknown advantage of the SOMs which we aimed to test using data on the spatial distributional patterns of gammarids. Quantitative samples and a wide spectrum of environmental data were obtained from the catchment area of two of the largest side tributaries of the Tisza River. Distributional patterns and habitat preference of three Gammarus species were described by Self Organizing Map methods and regression tree analysis (CART) on spatial and temporal scale. Using SOMs helped us to bring out distinctions in our data and enhance the differences, thus making them easier to recognize and
A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPTalso, with their help, we were able to model the relations of the species to habitat types nonexistent among our samples. According to the analysis Gammarus roeselii preferred low altitudes, high conductivity, fine substrate, deep actual mean depth and dense plant coverage;G. fossarum preferred rocky stream beds, high altitude, lower temperatures and little actual mean depth; while G. balcanicus preferred coarse substrate, little or no plant coverage and low temperature. SOMs improved the correlations that proved to be highly useful: besides their use to display complex data in a perspicuous way they have other advantages in bringing out existing relationships in data otherwise difficult to detect.