Abstract:
The present study investigated the prevailing condition of water quality and the abundance of
phytoplankton and zooplankton assemblages across the Batticaloa lagoon. Physicochemical
parameters including Salinity, Dissolved Oxygen, Turbidity, Nitrate, Phosphate, Temperature
and pH were determined using the samples collected at fortnight intervals for six months
from July 2013 to December 2013 from seven selected sites: Katthankudy, Kallady, Mandur,
Eravur, Thiruperumthurai, Paalameenmadu and Kaluthavalai of the Batticaloa Lagoon, Sri
Lanka. A distinct variation of the physico-chemical characteristics of the different regions of
the Batticaloa lagoon was observed during the study. In total, 58 species of phytoplankton
and 18 species of zooplankton were recorded from all seven sites. Among the 58 species of
phytoplankton recorded, a diatom (Bacillariophycea) was the dominant group, which
included 25 species comprising 43% of the total taxa. In addition 13 species of Cyanophycea
(22%), 10 species (17%) of Chlorophycea, 8 species (14%) of Conjugatophycea, and 2
species (4%) Fragillariophycea were recorded during the study period. The zooplankton
communities of the Batticaloa lagoon consisted of the members of the taxonomic groups of
Rotifera, Cladocera, Copepoda, Decapoda, Podocopida, Ploima, Arcellinida and Sessilida.
Members of the phylum Rotifera was the dominant group which consist 33% of the total
zooplankton. The results of the multivariate statistical analysis show that pH, turbidity,
dissolved oxygen and salinity were the most important measured environmental variables that
explained the species variation of zooplankton, while pH, salinity and turbidity were the most
important variables that helped to discriminate phytoplankton species in all sites during the
study. Thus the variation of environmental conditions and the plankton communities in
different regions of the lagoon demonstrate that both zooplankton and phytoplankton species
respond to environmental conditions proving the use of plankton communities in
environmental predictions.
