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Comparative Analyses of Community and Biological Indices based on Benthic Macroinvertebrates in Streams using a Self-Organizing Map  

Tang, Hong Qu (Department of Biology and The Korea Institute of Ornithology, Kyung Hee University)
Bae, Mi-Jung (Department of Biology and The Korea Institute of Ornithology, Kyung Hee University)
Chon, Tae-Soo (Department of Biological Sciences, Pusan National University)
Song, Mi-Young (West Sea Fisheries Research Institute)
Park, Young-Seuk (Department of Biology and The Korea Institute of Ornithology, Kyung Hee University)
Publication Information
Korean Journal of Ecology and Environment / v.42, no.3, 2009 , pp. 303-316 More about this Journal
Abstract
Benthic macroinvertebrate communities collected from eight different streams in South Korea were analyzed to compare community and biological indices across different levels of water pollution. The Self-Organizing Map (SOM) was utilized to provide overview on association of the proposed indices. The sample sites were accordingly clustered according to the gradient of pollution on the SOM. While the general trends of the indices were commonly observable according to different levels of pollution, the detailed differences among the indices were also illustrated on the SOM. The conventional diversity and evenness indices tended to be high even though the water quality state was poor representing relatively weak gradient at polluted sites, while the index presenting the saprobic degree such as family biotic index showed the stronger gradient at the polluted area and was robust to present the gradient. Our results also confirmed the general characterization of two indices: The Shannon index is more strengthened by the number of species occurring at the sample sites, while the Simpson index is more influenced by the degree of evenness among the species. The patterning based on the SOM was efficient in comparatively characterizing the proposed indices to present ecological states and water quality.
Keywords
community indices; biological indicators; diversity; water quality; Self-organized Map; pollution;
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