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      The distribution and diversity of benthic macroinvertebrate fauna in Pondicherry mangroves, India

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          Abstract

          Background

          Species distribution, abundance and diversity of mangrove benthic macroinvertebrate fauna and the relationships to environmental conditions are important parts of understanding the structure and function of mangrove ecosystems. In this study seasonal variation in the distribution of macrobenthos and related environmental parameters were explored at four mangrove stations along the Pondicherry coast of India, from September 2008 to July 2010. Multivariate statistical analyses, including cluster analysis, principal component analysis and non-multidimensional scales plot were employed to help define trophic status, water quality and benthic characteristic at the four monitoring stations.

          Results

          Among the 528 samples collected over 168 ha of mangrove forest 76 species of benthic macroinvertebrate fauna were identified. Macrofauna were mainly composed of deposit feeders, dominated numerically by molluscs and crustaceans. Statistical analyses yielded the following descriptors of benthic macroinvertebrate fauna species distribution: densities between 140–1113 ind. m -2, dominance 0.17-0.50, diversity 1.80-2.83 bits ind -1, richness 0.47-0.74 and evenness 0.45-0.72, equitability 0.38-0.77, berger parker 0.31-0.77 and fisher alpha 2.46-5.70. Increases of species diversity and abundance were recorded during the post monsoon season at station 1 and the lowest diversity was recorded at station 2 during the monsoon season. The pollution indicator organisms Cassidula nucleus, Melampus ceylonicus, Sphaerassiminea minuta were found only at the two most polluted regions, i.e. stations 3 and 4. Benthic macroinvertebrate fauna abundances were inversely related to salinity at the four stations, Based on Bray-Curtis similarity through hierarchical clustering implemented in PAST, it was possible to define three distinct benthic assemblages at the stations.

          Conclusions

          From a different multivariate statistical analysis of the different environmental parameters regarding species diversity and abundance of benthic macroinvertebrate fauna, it was found that benthic communities are highly affected by all the environmental parameters governing the distribution and diversity variation of the macrofaunal community in Pondicherry mangroves. Salinity, dissolved oxygen levels, organic matter content, sulphide concentration were the most significant parameters.

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          Most cited references19

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          Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)--a case study.

          This case study reports different multivariate statistical techniques applied for evaluation of temporal/spatial variations and interpretation of a large complex water-quality data set obtained during monitoring of Gomti River in Northern part of India. Water quality of the Gomti River, a major tributary of the Ganga River was monitored at eight different sites selected in relatively low, moderate and high pollution regions, regularly over a period of 5 years (1994-1998) for 24 parameters. The complex data matrix (17,790 observations) was treated with different multivariate techniques such as cluster analysis, factor analysis/principal component analysis (FA/PCA) and discriminant analysis (DA). Cluster analysis (CA) showed good results rendering three different groups of similarity between the sampling sites reflecting the different water-quality parameters of the river system. FA/PCA identified six factors, which are responsible for the data structure explaining 71% of the total variance of the data set and allowed to group the selected parameters according to common features as well as to evaluate the incidence of each group on the overall variation in water quality. However, significant data reduction was not achieved, as it needed 14 parameters to explain 71% of both the temporal and spatial changes in water quality. Discriminant analysis showed the best results for data reduction and pattern recognition during both temporal and spatial analysis. Discriminant analysis showed five parameters (pH, temperature, conductivity, total alkalinity and magnesium) affording more than 88% right assignations in temporal analysis, while nine parameters (pH, temperature, alkalinity, Ca-hardness, DO, BOD, chloride, sulfate and TKN) to afford 91% right assignations in spatial analysis of three different regions in the basin. Thus, DA allowed reduction in dimensionality of the large data set, delineating a few indicator parameters responsible for large variations in water quality. This study presents necessity and usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets with a view to get better information about the water quality and design of monitoring network for effective management of water resources.
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            Application of multivariate statistical techniques in the assessment of surface water quality in Uluabat Lake, Turkey.

            The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, PO(-3)(4), NH(4)-N, NO(2)-N, NO(3)-N, SO(3-)(4), BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.
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              Macrofaunal community structure in the western Indian continental margin including the oxygen minimum zone

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                Author and article information

                Contributors
                Journal
                Aquat Biosyst
                Aquat Biosyst
                Aquatic Biosystems
                BioMed Central
                2046-9063
                2013
                11 August 2013
                : 9
                : 15
                Affiliations
                [1 ]Department of Ecology and Environmental Sciences, Pondicherry University, Puducherry 605014, India
                [2 ]Department of Biological and Environmental Sciences, University of Messina, Messina 98166, Italy
                Article
                2046-9063-9-15
                10.1186/2046-9063-9-15
                3751066
                23937801
                b20c7d89-c9f6-43c3-ac19-cab41671bc09
                Copyright © 2013 Kumar and Khan; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 May 2012
                : 7 August 2013
                Categories
                Research

                Ecology
                density,diversity,mangroves,benthic macroinvertebrate fauna,seasonal variation
                Ecology
                density, diversity, mangroves, benthic macroinvertebrate fauna, seasonal variation

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