Abstract

Coastal ecosystems, one of the most productive ecosystems, are subjected to natural and anthropogenic stresses. Coastal bacterioplankton communities are highly dynamic due to spatiotemporal heterogeneity in the environmental parameters. We investigated the seasonal and spatial variation in bacterioplankton communities, their abundances and environmental drivers during one year period in Chilika, a brackish water coastal lagoon of India. High-throughput sequencing of 16S rRNA genes of bacterioplankton communities showed that they were dominated by heterotrophs namely α-Proteobacteria SAR11 and their sub-clades (SAR11_Ib, Chesapeake-Delaware_Bay, Candidatus_Pelagibacter, and SAR11_Surface_1), actinobacterial lineages (hgcI, CL500-29, and Candidatus_Aquiluna), β-Proteobacteria MWH-UniP1, β-Proteobacteria OM43, and verrucomicrobial clade Spartobacteria ‘LD29’. Synechococcus was the dominant member within autotrophic cyanobacterial community. Response ratio derived from comparisons of taxon-specific absolute abundances and indicator analyses showed that SAR11_Surface_1 sub-clade occupied high-salinity environment especially during summer and winter and emerged as a strong indicator for mesohaline-polyhaline salinity regime. In contrast, Spartobacteria ‘LD29’, Actinobacteria hgcI, and CL500-29 preferred low-salinity freshwater environment and were strong indicators for oligohaline-mesohaline regimes. Spatiotemporal patterns were governed by ‘distance-decay’ and ‘similarity-time’ relationships. Bacterioplankton communities were mostly determined by salinity, dissolved oxygen, phosphate, and pH which resulted 'species sorting' leading to biogeographical patterns in the bacterioplankton communities. Modeling analysis revealed the characteristic shift in the indicator bacterioplankton taxa along with estuarine salinity gradient. This study has provided baseline information on the bacterioplankton communities and their environmental drivers within an anthropogenically impacted cyclone prone coastal lagoon which would be useful in assessing the impact of multiple stressors on this vulnerable ecosystem.

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