Exploring phyto- and zooplankton community structure, spatial variation, and driving forces shaping the community from a large-scale freshwater dominated estuary

Abstract Plankton is essential to estuarine food webs, providing key food for species like fish larvae, and understanding their dynamics helps us comprehend ecological interactions and energy transfer in aquatic ecosystems. This study examined the plankton community structure, diversity, variability and the environmental variables of water that influenced these communities in a freshwater-dominated estuary along the Northern Bay of Bengal during the dry season. A variety of tools were employed, including a dissecting microscope, a Sedgwick-Rafter cell, and a Hanna multi-parameter meter, to obtain detailed and comprehensive data. From the analyses, in total 37 genera of phytoplankton belonging to 11 classes such as Bacillariophyceae (66%), Coscinodiscophyceae (28%), Fragilariophyceae (1%), Euglenophyceae (1%), Cyanophyceae (1%), others (3%) were recorded. Zooplankton, consisting of multicellular organisms, was represented by 11 genera across five classes, with Monogononta (53%) and Insecta (29%) being the most prevalent. Phytoplankton exhibited a mean abundance of 180,000 ± 20,200 cells l −1 whereas zooplankton showed a mean abundance of 3,000 ± 200 cells l −1 . The diversity indices (H′), evenness (J′) and dominance (D) ranged from 1.188 ± 0.015 to 0.19 ± 0.006, 0.9377 ± 0.002 to 0.5118 ± 0.006, 0.365 ± 0.001 to 0.143 ± 0.002 respectively, suggested low to moderate plankton diversity with a suppressed community and moderate to high dominance in the river water. Based on the similarity percentage (SIMPER) and analysis of similarity (ANOSIM), Phytoplankton and zooplankton varied significantly between stations while non-metric multi-dimensional scaling (nMDS) indicated greater consistency in phytoplankton communities across stations compared to zooplankton. Furthermore, Pearson’s correlation coefficient (rs) and canonical correspondence analysis (CCA) identified transparency, sulfates, dissolved oxygen, conductivity, TDS, pH, and salinity as major influencers of plankton abundance; nitrate had a moderate effect. Spearman’s rank correlations showed significant positive (p < 0.05) correlations between diversity indices and environmental variables. Future research should focus on long-term monitoring and the potential impacts of environmental changes on plankton communities.