Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/47200
Title: Factors influencing shell size and shape in Donax incarnatus (Gmelin) inhabiting Panambur sandy beach, Mangalore, India
Authors: Thippeswamy, Seetharamaiah
Modiayil, Mohan Joseph
Shubharekha, Baikampady
Shettigar, Malathi
Keywords: Allometry;Morphometry;Length-weight;Biotic and abiotic variables;Multivariate statistical analysis;Karnataka
Issue Date: Apr-2019
Publisher: NISCAIR-CSIR, India
Abstract: The samples of wedge clam Donax incarnatus (Gmelin), sediment and seawater were collected for a period of 12 months from Panambur sandy beach, near Mangalore. A total of 2258 individuals of D. incarnatus were subjected to analysis. The air (27.5-31.2 oC), sand (28.5-36 oC) and seawater (25-32.2 oC) temperatures showed seasonal fluctuations. The dissolved oxygen (3.29-4.55 ml L-1) and salinity (30.24-34.84 x 10-3) of seawaters showed variations. Fine sand dominated (75.09 to 94.2%) throughout the period of study, followed by medium sand (1.51 to 20.65%). The density (89 to 39446 no. m-2) and biomass (124 to 1892 g. m-2) of wedge clams showed marked variations during breeding season. Principal component analysis of biological variables and environmental parameters showed six components which together accounted for 90.39% of total variance. The component 1 (dissolved oxygen, density, biomass, wet weight, dry) accounted for 24.02% of total variance followed by component 2 (air, water and sediment temperatures, salinity and b values of length-breadth and length-dry weight relationships) for 20.64% of total variance and component 3 (mean shell length, mean shell breadth, mean shell width) for 17.27% of total variance. The rest of the variance of 28.46% was accounted for component 4 (medium sand, fine sand, very fine sand), component 5 (coarse sand, b value of length-wet weight relationship, b value of length-width relationship) and component 6 (silt & clay). The hierarchical cluster analysis produced a dendrogram with six sub-groups of clusters. The temporal variability of six factor scores was delineated using factor analysis.
Page(s): 475-483
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.48(04) [April 2019]

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