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Deep sea bacterial communities demonstrate remarkable adaptability to high-pressure environments coupled with low temperatures which has sparked curiosity about their diversity and exceptional metabolic pathways. Additionally, bacteria in the deep sea exert a substantial influence over various biogeochemical processes. To date, we have relatively very little information about the deep-sea bacterial communities and, they remain largely unexplored. We investigated the variability in the physicochemical conditions, heavy metals and their influence on deep-sea bacterial community structure across three different depths in the Bay of Bengal. The structural and metabolic diversity of deep-sea sediment microbial communities were examined through culture-based sequencing of 16S rRNA genes, ecto-enzymatic studies, and community-level physiological profiling. Bacillota was the most dominant phylum representing 61% of the cultured bacterial isolates, while the remaining belonged to Actinomycetota and Pseudomonodata. Five potential novel species belonging to the genera Fictibacillus, Lysinibacillus, Salinicola, Robertmurraya and Blastococcus were identified. The extracellular enzymatic activity was positive for >50% of the bacterial isolates, wherein the genera Bacillus and Micromonospora exhibited versatile profiles. High metabolic diversity was recorded through the carbon substrate utilization profiles indicating that microbial communities are active participants in biogeochemical cycles in the deep sea. The most prominently utilized carbon substrates were α-cyclodextrin, glucose-1-phosphate, D-xylose, glycogen, and 2-hydroxy benzoic acid which serve as organic substrates for microbial metabolism, facilitating the decomposition of organic matter and, recycling carbon in deep-sea ecosystems. Multivariate statistical analyses confirmed that the environmental variables had a profound influence on the bacterial community. The findings shed light on spatial variability in the bacterial community structure, enzyme activity and metabolic profiles, and enhance our understanding of Bay of Bengal deep-sea sedimentary microbial ecology.

Coastal waters are dynamic because of anthropogenic activities that contribute nutrients and contaminants. These changes have the potential to alter patterns of primary production and thus pelagic food webs. Here, we investigated the spatial variation of the phytoplankton community and its response to changing environmental variables at 84 stations along the five coastal districts of Tamil Nadu (TN). During the present study, 85 phytoplankton species were recorded, such as diatoms (64), dinoflagellates (18), silicoflagellates (1), and Cyanophyceae (2). The maximum phytoplankton abundance was recorded on the Thanjavur coast and gradually decreased towards the south coast of Tamil Nadu. Among the phytoplankton community, 50% was dominated by pennate diatoms, attributed to higher NO3− concentrations in the coastal waters due to agricultural discharge. Cluster analysis revealed that Ramanathapuram and Tirunelveli formed a closed cluster, whereas Thanjavur and Pudukottai formed a separate closed cluster associated with higher nutrient and metal concentrations, highlighting the difference in physicochemical parameters between the northern and southern districts of the TN coast. Relatively high nutrient concentrations in the coastal waters of northern districts are of greater concern, which could impact the coastal ecosystem. Coastal eutrophication is becoming a widespread phenomenon, causing disruption in the food chain and ecosystem balances and hence requiring regular monitoring and management.

A planned artificial reef (AR) deployment program as part of a fisheries enhancement might be a useful tool for managers to supplement traditional ways to utilize available space and augment local productivity. Several AR deployment initiatives have been carried out globally, but they are rarely subjected to a rigorous site selection process. We created a site selection procedure in this study that includes systematic stages including exclusion mapping, underwater visual transect, benthic composition, seawater quality, and comparative visual mapping. This research focused on restoring the fishing grounds for artisanal fishermen by deploying AR along the southeast coast of India. The results of each stage in the procedure enabled us to choose suitable locations at a target depth with low wave action, no slope, and a good substrate capable of supporting an AR. Analysis of variance (ANOVA-one way) showed significant (p < 0.05) spatial variation for depth, slope, seawater current, salinity, chlorophyll-a, benthic density, and diversity. The geographical information system (GIS) based model output showed space allocation for AR deployment. The GIS methodology for site selection was developed to be easily adaptable to the demands of diverse artificial reef programs. The integrated strategy has proven to be a successful regulatory intervention for AR deployment practices in order to facilitate coastal restoration and management.