title: Numerical analyses of soft bottom invertebrates to diagnose the pollution in tropical coastal waters.
abstract: Soft 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 coast of India, a hot-spot area. Univariate techniques such as Pearson Rosenberg 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.
authors.affiliation: Biological Oceanography Division, National Institute of Oceanography, Dona Paula, Goa, India. sadanand@darya.nio.org
authors.forename: Sadanand N
authors.initials: SN
authors.lastname: Harkantra
authors.forename: Nimi R
authors.initials: NR
authors.lastname: Rodrigues
mesh_terms: D000818:Animals; D018533:Biomass; D004784:Environmental Monitoring / Q000379:methods*; D020387:Food Chain; D007220:Industrial Waste; D007448:Invertebrates; D015999:Multivariate Analysis; D011157:Population Dynamics; D014329:Tropical Climate; D014873:Water Pollutants / Q000506:poisoning*
chemical_list: D007220:Industrial Waste; D014873:Water Pollutants