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Chironomid species in water bodies are useful indicators of the nutrient and environmental states. The relative abundance of chironomids and nutrients like organic carbon (C), potassium ions (K + ), nitrate (NO 3¯) , and phosphate (PO 4 2¯) of the water bodies were analyzed using numerical techniques such as Principal Component Analysis (PCA), Canonical Correspondence Analysis (CCA) and Cluster Analysis (CA) to justify the use of chironomids in environmental biomonitoring. The data analyses of 90 samples from eight different ponds Kolkata, India, revealed the presence of 12 chironomid species in different relative densities. The chironomid immature numbers per unit area was found to be positively correlated with C and PO 4 2¯, while no definite significant correlation was observed for K + or NO 3¯. The PCA yielded three components that could explain >63% of variation of the observed data. In terms of factor loadings, pH, K + , NO 3¯a nd PO 4 2¯ contributed to the first factor, while C, water temperature and dissolved O 2 contributed to the second factor. The CCA showed distribution of the chironomid species to differ against the variance of water quality parameters. The first canonical axis (λ 1 =0.156; F=5.126; P<0.05) explained 69% of species -environment relationship. The abundance of three species of chironomid midges, Chironomus striatipennis, C. circumdatus and Kiefferulus calligaster was prominent in all the water bodies. Cluster analysis showed that these species were highly correlated in their abundance contrast to remaining species. The results indicate that the water quality parameters influence the chironomid species assemblages to a considerable extent. This is supportive of the use of chironomid midges in biomonitoring for ecological management of urban water bodies of Kolkata, India and similar geographical areas.

Chironomid