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dc.contributor.authorHarkantra, S.N.
dc.contributor.authorRodrigues, N.R.
dc.date.accessioned2008-07-18T05:07:22Z
dc.date.available2008-07-18T05:07:22Z
dc.date.issued2003
dc.identifier.citationEnvironmental Monitoring and Assessment, Vol.93; 251-275p.
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/1218
dc.description.abstractSoft bottom benthic organisms especially polychaetes are known to adapt as r or k selected strategies to different gradients of pollution. This will result in changes of benthic community structure from that of normal structure. There are a number of techniques to assess the impact of pollution on benthic community structure. Hence, to test this hypotheses some of the univariate and multivariate techniques were applied to soft bottom macro-invertebrates data of coastal waters of Mangalore, central west coat of India, a hot-spot area. Univariable techniques such as Pearson Roesenberg Model (PRM), abundance biomass comparison curve (ABC), geometrical class distribution, dominance-diversity curve, benthic community structure indices and multivariate techniques such as cluster classification, multidimensional scaling (MDS) and principal component analysis (PCA) were used to discriminate and diagnose the disturbance among the sites. Effectiveness and applicability of some of the above techniques are highlighted and discussed with the present set of data for environmental impact assessment studies
dc.language.isoen
dc.publisherSpringer
dc.rightsCopyright [2003]. It is tried to respect the rights of the copyright holders to the best of the knowledge. If it is brought to our notice that the rights are violated then the item would be withdrawn.
dc.subjectbenthos
dc.subjectcoastal zone
dc.subjectpollution indicators
dc.subjectindicator species
dc.subjecttropical environment
dc.subjectindustrial wastes
dc.subjectpollution effects
dc.subjectnumerical analysis
dc.titleNumerical analyses of soft bottom macroinvertebrates to diagnose the pollution in tropical coastal waters
dc.typeJournal Article


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