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Water trophicity of Utricularia microhabitats identlfied by means of SOFM as a tool in ecological modeling

DOI: 10.5586/asbp.2007.029

Keywords: artificial neural networks , cluster analysis , ecological modeling , trophicity , Utricularia , water-quality data

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Abstract:

The study objects were 48 microhabitats of five Utricularia species in Lower and Upper Silesia (POLAND). The aim of the paper was to focus on application of the Self-Organizing Feature Map in assessment of water trophicity in Utricularia microhabitats, and to describe how SOFM can be used for the study of ecological subjects. This method was compared with the hierarchical tree plot of cluster analysis to check whether this techniques give similar results. In effect, both topological map of SOFM and dendrogram of cluster analysis show differences between Utricularia species microhabitats in respect of water quality, from eutrophic for U. vulgaris to dystrophic for U. minor and U. intermedia. The used methods give similar results and constitute a validation of the SOFM method in this type of studies.

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