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. 2012 Jun;184(6):3761-74.
doi: 10.1007/s10661-011-2222-4. Epub 2011 Jul 15.

Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast, India

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Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast, India

P Satheeshkumar et al. Environ Monit Assess. 2012 Jun.

Abstract

Different multivariate statistical analysis such as, cluster analysis, principal component analysis, and multidimensional scale plot were employed to evaluate the trophic status of water quality for four monitoring stations. The present study was carried out to determine the physicochemical parameters of water and sediment characteristics of Pondicherry mangroves-southeast coast of India, during September 2008-December 2010. Seasonal variations of different parameters investigated were as follows: salinity (10.26-35.20 psu), dissolved oxygen (3.71-5.33 mg/L), pH (7.05-8.36), electrical conductivity (26.41-41.33 ms(-1)), sulfide (1.98-40.43 mg/L), sediment texture sand (39.54-87.31%), silt (9.89-32.97%), clay (3.06-31.20%), and organic matter (0.94-4.64%). pH, temperature, salinity, sand, silt, clay, and organic matter indicated a correlation at P < 0.01. CA grouped the four seasons in to four groups (pre-monsoon, monsoon, post-monsoon, summer) and the sampling sites in to three groups. PCA identified the spatial and temporal characteristics of trophic stations and showed that the water quality was worse in stations 3 and 4 in the Pondicherry mangroves.

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