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Bottom fauna of dredging and dredge spoil disposal sites of a tropical estuary

International Scientific Publications
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  • Cochin Harbour
  • Sediment Dwelling Organisms


Sediment characteristics and bottom fauna were investigated extensively in and around Cochin harbour at 38 sampling stations grouped into seven areas, covering an area of 130 km sup(2), during premonsoon and monsoon periods. The seven areas were: (1) Ernakulam channel (4-10 m deep). (2) Mattanchery channel (2.5-5.5 m deep). (3) Vallarpadam (2.1-4.5 m deep). (4) Dredging channel (8.5-17.0 m deep). (5) North of dredging channel (6.6-14.0 m deep). (6) South of dredging channel (6.6-14.00 m deep) and (7) Disposal site (12.8-17.5 m deep). The silty clay and sandy clay substratum predominated the study area. In the dredging and disposal areas the values for organic matter were 3.40 and 4.51% during pre-monsoon and 3.51 and 4.00% during monsoon respectively. The standing stock in terms of total biomass (wet weight) in the study area varied from 37.47 to 297.30 g m sup(-2) during premonsoon and 12.63 to 215.97 g m during monsoon. The distribution of different faunal groups/species indicated a significant reduction in the dredging and disposal area. Polychaetes dominated the fauna. Bray-Curtis' Coefficient of Similarity between areas was higher during monsoon than during premonsoon in areas 4-6 with sediment characteristics controlling the occurrence of common species. Species which are abundant and more homogeneously distributed have low niche breadth preferably in sand dominated areas, particularly in areas 1-4. In area 5, a similar trends was observed with high niche breadth associated with organic matter content, whereas in areas 6 and 7 a reserve in the trend was observed with finer sediment dwelling organisms showing high niche breadth. In general a decreasing trend in the species niche breadth was observed from area 1 to 7 with higher values during monsoon than during premonsoon for species niche breadth. Grouping of species obtained by group average linkage clustering and using E-mode analysis are compared.

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