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The scaly-foot snail (Chrysomallon squamiferum) inhabiting deep-sea hydrothermal vents in the Indian Ocean relies on its sulphur-oxidising gammaproteobacterial endosymbionts for nutrition and energy. In this study, we investigate the specificity, transmission mode, and stability of multiple scaly-foot snail populations dwelling in five vent fields with considerably disparate geological, physical and chemical environmental conditions. Results of population genomics analyses reveal an incongruent phylogeny between the endosymbiont and mitochondrial genomes of the scaly-foot snails in the five vent fields sampled, indicating that the hosts obtain endosymbionts via horizontal transmission in each generation. However, the genetic homogeneity of many symbiont populations implies that vertical transmission cannot be ruled out either. Fluorescence in situ hybridisation of ovarian tissue yields symbiont signals around the oocytes, suggesting that vertical transmission co-occurs with horizontal transmission. Results of in situ environmental measurements and gene expression analyses from in situ fixed samples show that the snail host buffers the differences in environmental conditions to provide the endosymbionts with a stable intracellular micro-environment, where the symbionts serve key metabolic functions and benefit from the host's cushion. The mixed transmission mode, symbiont specificity at the species level, and stable intracellular environment provided by the host support the evolutionary, ecological, and physiological success of scaly-foot snail holobionts in different vents with unique environmental parameters.

Coastal waters are inherently dynamic due to river discharge, industrial effluents, shipping, dredging, waste dumping, and sewage disposal. Population growth in urban cities, climate change and variability, and changes in land-use practices all contribute to pressure on coastal water quality (SKOVSKI et al., 2012; MILLER and HUTCHINS, 2017; KUMAR et al., 2020; Vijay PRAKASH et al., 2021). Anthropogenic activity is evident around these estuaries and coastal and open ocean environments. Hence, it is important to assess the water quality on a regular basis and provide mitigation measures for coastal pollution (YUVARAJ et al., 2018). Improving water quality and variability in coastal waters is necessary and should be prioritized. Observational programs, which are more expensive and time-consuming, aid in understanding the status of water quality and its trends. Many countries have coastal programs that use predictive systems to inform the public and stakeholders about coastal health. Hydrodynamic processes are an integral part of complex surface water systems. The main factor that determines the concentration of pollutants is hydrodynamic transport, which includes advection, dispersion, vertical mixing, and convection (James, 2002). The flow and circulation patterns have a great influence not only on the distribution of temperature, nutrients, and dissolved oxygen (DO) but also on the aggregation and distribution of sediments and pollutants. When a load of pollutants is discharged into coastal waters, it is affected by the fate and transportation processes that change its concentration. Several studies have been conducted to evaluate the coastal water quality spatiotemporally along the east coast of Indian coastal waters using site-specific data and model configuration (PANDA et al., 2006; BHARAHTI et al., 2017; NAIK et al., 2020; MOHANTY et al., 2021). Through numerical modeling and remote sensing, estimation is user-friendly and low-cost in evaluating any water quali

Phytoplankton biomass, quantified as the concentration of chlorophyll-a (CHL), is the base of the marine food web that supports fisheries production in the Bay of Bengal (BoB). Nutrients from river discharge, the ocean subsurface layer, and the atmosphere have been reported to determine CHL in the BoB. Which source of nutrients mainly determines CHL in different parts of the bay has not been determined. Furthermore, how climate variations influence nutrient inputs from different sources and their impacts on CHL have not been detailed. To address these questions, we used relationships between satellite-derived CHL and in situ river discharge data (a proxy for river-borne nutrients) from 1997 to 2016, physical variables, and modeled dust deposition (DD), a proxy for atmosphere-borne nutrients. Nutrients supplied from the ocean subsurface layer were assessed based on variations in physical parameters (i.e., wind stress curl, sea surface height anomaly, and sea surface temperature). We found that nutrients from the Ganges and Brahmaputra Rivers were important for CHL along the northern coast of the bay. By increasing rainfall and river discharge, La Niña extended high-CHL waters further southward. Nutrients from the ocean subsurface layer determine CHL variations mainly in the southwestern bay. We suggest that the variations in the supply of nutrients from the subsurface layer are related to the generation of mesoscale cyclonic eddies during La Niña, a negative Indian Ocean Dipole, or both. Climate-driven cyclonic eddies together with cyclones can intensify Ekman divergence and synergistically lead to a pronounced increase in CHL in the southwestern bay. Nutrients from the atmosphere mainly determine CHL in the central/eastern BoB. We further suggest that DD in the central/eastern BoB is influenced by ENSO with a 6-7-month time lag. CHL in the central/eastern bay responds to the ENSO 6-7 months after the ENSO peak because of the 6-7-month lag between ENSO and DD

The existing oligotrophic conditions in the southwest tropical Indian Ocean (SWTIO) is believed to be one of the causes for low phytoplankton productivity (PP) observed in this area. Though many remote sensing based studies on PP have been carried out in SWTIO, studies on in situ estimation of PP and its cause(s) of variability are scarce. Thus, to understand the controlling environmental forcings on the variability in phytoplankton biomass (chlorophyll-a; Chl-a), community structure and productivity, time series (TS; @6 h intervals for 10 days; 1 station), plus point measurements (RT; 3 stations) were carried out in the SWTIO during the southwest monsoon (June) of 2014. Strong thermohaline stratification resulted in shallow (35-40 m) mixed layer (ML). Subsurface Chl-a maximum (SCM) was observed to oscillate within 40-60 m with majority of peaks at ∼50 m, and existed just beneath the ML depth. Light availability during sampling period was highly conducive for algal growth; nutrient ratios indicated N- and Si-limitation (N:P < 10; N:Si < 1 and SiO4 < 5 μM) suggesting unfavorable conditions for diatoms and/or silicoflagellates growth within the ML. Furthermore, HPLC-based pigments analysis confirmed dominance of nano-sized plankton (53%) followed by pico-plankton (25%) and micro-plankton (22%). Column integrated production (IPP) varied from 176 to 268 (241 ± 43 mgC m-2 d-1) and was relatively stable during the observation period, except a low value (19.4 E m-2 d-1) on 11 June, which was ascribed to the drastic dropdown in the daily incident PAR due to overcast sky. Vertical profiles of PP and Chl-a resembled each other and maximum PP usually corresponded with SCM depths. The Chl-a-specific PP (PB) was mostly higher within the ML and showed no surface photoinhibition, due to the dominance of smaller phytoplankton (less prone to pigment packaging effect) in the surface layer. Comparatively, higher PB within the ML is indicative of phytoplankton healthine

To clarify the changes in phytoplankton community and influencing factors in short-term nutrient-addition experiments in the Equatorial Eastern Indian Ocean, we conducted three experiments (one in situ-like experiment, one on-deck experiment with deep seawater, and one on-deck experiment with surface seawater). Our findings indicate that when nutrients were added, there was a more significant increase in the chlorophyll a (chl a) concentrations of microphytoplankton (>20 μm) compared to those of nanophytoplankton (2-20 μm) and picophytoplankton (<20 μm phytoplankton. Furthermore, bottle effects should be considered when conducting incubation experiments.

The Java Trench is the only subduction trench in the Indian Ocean that extends to the hadal zone (> 6,000 m water depth), and except for sevenbenthic trawls acquired around the 1950s, there has been little to no sampling at hadal depths undertaken since. In 2019, we undertook a 5-day expedition comprising a scientific dive using a full ocean depth-rated submersible, the DSV Limiting Factor, seven hadal-lander deployments, and high-resolution bathymetric survey. The submersible performed a video transect from the deepest point of the trench, up a 150 m high near-vertical escarpment located on the forearc, and then across a plateau at a depth of ∼7,050 m to make in situ observations of the habitat heterogeneity and biodiversity inhabiting these hadal depths. We found the Java Trench hadal community to be diverse and represented by 10 phyla, 21 classes, 34 orders and 55 families, with many new records and extensions in either depth or geographic range, including a rare encounter of a hadal ascidian. The submersible transect revealed six habitats spanning the terrain. The deepest trench axis comprised fine-grained sediments dominated by holothurians, whereas evidence of active rock slope failure and associated talus deposits were prevalent in near-vertical and vertical sections of the escarpment. Sediment pockets and sediment pouring down the steep wall in "chutes" were commonly observed. The slope terrain was dominated by two species in the order Actiniaria and an asteroid, as well as 36 instances of orange, yellow, and white bacterial mats, likely exploiting discontinuities in the exposed bedrock, that may indicate a prevalence of chemosynthetic input into this hadal ecosystem. Near the top of the escarpment was an overhang populated by > 100 hexactinellid (glass) sponges. The substrate of the plateau returned to fine-grained sediment, but with a decreased density and diversity of epifauna relative to the trench floor. By providing the first visual insights of the h

The microbial communities of the hydrothermal Scaly-foot Snails (SFSs) from independent hydrothermal vent fields have not been investigated in depth. In this study, we collected SFSs from two different hydrothermal environments located on the Central Indian Ridge (CIR) and the Southwest Indian Ridge (SWIR), the Kairei and Longqi vent fields, respectively. Additionally, one SFS collected from the Kairei vent field was reared for 16 days with in situ deep-sea seawater. The epibiotic and internal samples of SFSs, including ctenidium, esophageal gland, visceral mass, shells, and scales, were examined for microbial community compositions based on the 16S rRNA gene. Our results revealed significant differences in microbial community composition between SFSs samples collected from Kairei and Longqi vent fields. Moreover, the microbial communities of epibiotic and internal SFS samples also exhibited significant differences. Epibiotic SFS samples were dominated by the bacterial lineages of Sulfurovaceae, Desulfobulbaceae, Flavobacteriaceae, and Campylobacteraceae. While in the internal SFS samples, the genus Candidatus Thiobios, affiliated with the Chromatiaceae, was the most dominant bacterial lineage. Furthermore, the core microbial communities of all samples, which accounted for 78 ∼ 92% of sequences, were dominated by Chromatiaceae (27 ∼ 49%), Sulfurovaceae (10 ∼ 35%), Desulfobulbaceae (2 ∼ 7%), and Flavobacteriaceae (3 ∼ 7%) at the family level. Based on the results of random forest analysis, we also found the genera Desulfobulbus and Sulfurovum were the primary bacterial lineages responsible for the dissimilarity of microbial communities between the SFS samples collected from the Kairei and Longqi vent fields. Our results indicated that the microbial lineages involved in the sulfur cycle were the key microorganisms, playing a crucial role in the hydrothermal vent ecosystems. Our findings expand current knowledge on microbial diversity and composition in the e

Chlorophyll-a can be used as a proxy for phytoplankton and thus is an essential water quality parameter. The presence of phytoplankton in the ocean causes selective absorption of light by chlorophyll-a pigment resulting in change of the ocean color that can be identified by ocean color remote sensing. The accuracy of chlorophyll-a concentration (Chl-a) estimated from remote sensing sensors depends on the bio-optical algorithm used for the retrieval in specific regional waters. In this work, it is attempted to estimate Chl-a from two currently active satellite sensors with relatively good spatial resolutions considering ocean applications. Suitability of two standard bio-optical Ocean Color (OC) Chlorophyll algorithms, OC-2 (2-band) and OC-3 (3-band) in estimating Chl-a for turbid waters of the northern coastal Bay of Bengal is assessed. Validation with in-situ data showed that OC-2 algorithm gives an estimate of Chl-a with a better correlation of 0.795 and least bias of 0.35 mg/m3. Further, inter-comparison of Chl-a retrieved from the two sensors, Landsat-8 OLI and Sentinel-2 MSI was also carried out. The variability of Chl-a during winter, pre-monsoon, and post-monsoon seasons over the study region were inter-compared. It is observed that during pre-monsoon and post-monsoon seasons, Chl-a from MSI is over estimated compared to OLI. This work is a preliminary step toward estimation of Chl-a in the coastal oceans utilizing available better spatially resolved sensors.

Recent studies suggest that pelagic sediments can enrich rare-earth elements (REE) acting as a significant reservoir for the global REE budget as well as a potential resource for future exploitation. Although Ca-phosphate (e.g., bioapatite fossils) and Fe-Mn (oxyhydr)oxides (e.g., micronodule) have been considered important REE carriers in deep-sea sediments, the proportion of REE held by each mineral phase remains enigmatic. Here, we have investigated the sediments from two promising REE-rich prospective areas: the Tiki Basin in the Southeast Pacific (TKB) and the Central Indian Ocean Basin (CIOB). The mineral grains including bioapatite fossils and Fe-Mn micronodules have been inspected individually by in-situ microscale analytical methods. Correspondently, the REE bound to Ca-phosphate and Fe-Mn (oxyhydr)oxides have been sequentially extracted and quantified. The crucial role of Ca-phosphate is substantiated by sequential leaching which reveals its dominance in hosting ~69.3-89.4% of total REE. The Fe-Mn (oxyhydr)oxides carry ~8.2% to 22.0% of REE in bulk sediments, but they account for ~70.0-80.5% of Ce owing to their preferential adsorption of Ce over the other REE. Surface sediment on modern seafloor can accumulate high REE contents resulting from the REE scavenging by the host phases within the range of sediment-seawater interface. Differences between TKB and CIOB samples indicate that the REE enrichment in the deep-sea environment may be controlled by multiple factors including the productivity of overlying seawater (e.g., phosphorus flux), water depth relative to carbonate compensation depth (CCD), sedimentation rate, redox condition, and hydrothermal vent input (e.g., Fe-Mn precipitations).

Pocket beaches bound by headlands or other geologic features are common worldwide and experience constrained alongshore transport that influences their morphological changes. Pocket beaches fringed by shallow reefs have not been well-studied, yet can be commonly found throughout temperate and tropical regions. The presence of a reef is expected to drive distinct hydrodynamic processes and shoreline responses to offshore waves and water levels, which is investigated in this study. To examine the drivers of shoreline variability, a 20-month field study was conducted on a reef-fringed pocket beach in southwestern Australia (Gnarabup Beach), using a series of in situ wave and water level observations, topographic surveys, as well as video shoreline monitoring. The results indicate that the beach as a whole (alongshore averaged) was in a mostly stable state. However, we observed substantial spatial variability of the local shorelines in response to offshore wave and water levels across a range of time-scales (from individual storms to the seasonal cycle). We observed local regions of beach rotation within cells that were partitioned by the headlands and offshore reefs. The shoreline response was also dictated by the combination of offshore waves and water level which varied seasonally, with the shoreline generally eroding with lower water levels for the same wave height. Despite the contrasting responses in different alongshore locations of the beach, the overall beach volume of the pocket beach was largely conserved.

Surface and sub-surface ocean temperature observations collected by sea turtles (ST) during the first phase (Jan 2019-April 2020) of the Sea Turtle for Ocean Research and Monitoring (STORM) project are compared against in-situ and satellite temperature measurements, and later relied upon to assess the performance of the Glo12 operational ocean model over the west tropical Indian Ocean. The evaluation of temperature profiles collected by STs against collocated ARGO drifter measurements show good agreement at all sample depths (0-250 m). Comparisons against various operational satellite sea surface temperature (SST) products indicate a slight overestimation of ST-borne temperature observations of ∼0.1°±°0.6° that is nevertheless consistent with expected uncertainties on satellite-derived SST data. Comparisons of ST-borne surface and subsurface temperature observations against Glo12 temperature forecasts demonstrate the good performance of the model surface and subsurface (50 m), the model is, however, shown to significantly underestimate ocean temperatures as already noticed from global evaluation scores performed operationally at the basin scale. The distribution of model errors also shows significant spatial and temporal variability in the first 50 m of the ocean, which will be further investigated in the next phases of the STORM project.

Imagery has become a key tool for assessing deep-sea megafaunal biodiversity, historically based on physical sampling using fishing gears. Image datasets provide quantitative and repeatable estimates, small-scale spatial patterns and habitat descriptions. However, taxon identification from images is challenging and often relies on morphotypes without considering a taxonomic framework. Taxon identification is particularly challenging in regions where the fauna is poorly known and/or highly diverse. Furthermore, the efficiency of imagery and physical sampling may vary among habitat types. Here, we compared biodiversity metrics (alpha and gamma diversity, composition) based on physical sampling (dredging and trawling) and towed-camera still images (1) along the upper continental slope of Papua New Guinea (sedimented slope with wood-falls, a canyon and cold seeps), and (2) on the outer slopes of the volcanic islands of Mayotte, dominated by hard bottoms. The comparison was done on selected taxa (Pisces, Crustacea, Echinoidea, and Asteroidea), which are good candidates for identification from images. Taxonomic identification ranks obtained for the images varied among these taxa (e.g., family/order for fishes, genus for echinoderms). At these ranks, imagery provided a higher taxonomic richness for hard-bottom and complex habitats, partially explained by the poor performance of trawling on these rough substrates. For the same reason, the gamma diversity of Pisces and Crustacea was also higher from images, but no difference was observed for echinoderms. On soft bottoms, physical sampling provided higher alpha and gamma diversity for fishes and crustaceans, but these differences tended to decrease for crustaceans identified to the species/morphospecies level from images. Physical sampling and imagery were selective against some taxa (e.g., according to size or behavior), therefore providing different facets of biodiversity. In addition, specimens collected at a larger scale

The aim of this study was to document the composition and distribution of deep-water fishes associated with a submarine canyon-valley feature. A work-class Remotely Operated Vehicle (ROV) fitted with stereo-video cameras was used to record fish abundance and assemblage composition along transects at water depths between 300 and 900 metres. Three areas (A, B, C) were sampled along a submarine canyon-valley feature on the continental slope of tropical north-western Australia. Water conductivity/salinity, temperature, and depth were also collected using an ROV mounted Conductivity Temperature and Depth (CTD) instrument. Multivariate analyses were used to investigate fish assemblage composition, and species distribution models were fitted using boosted regression trees. These models were used to generate predictive maps of the occurrence of four abundant taxa over the survey areas. CTD data identified three water masses, tropical surface water, South Indian Central Water (centred ∼200 m depth), and a lower salinity Antarctic Intermediate Water (AAIW) ∼550 m depth. Distinct fish assemblages were found among areas and between canyon-valley and non-canyon habitats. The canyon-valley habitats supported more fish and taxa than non-canyon habitats. The fish assemblages of the deeper location (∼700-900 m, Area A) were different to that of the shallower locations (∼400-700 m, Areas B and C). Deep-water habitats were characterised by a Paraliparis (snail fish) species, while shallower habitats were characterised by the family Macrouridae (rat tails). Species distribution models highlighted the fine-scale environmental niche associations of the four most abundant taxa. The survey area had a high diversity of fish taxa and was dominated by the family Macrouridae. The deepest habitat had a different fish fauna to the shallower areas. This faunal break can be attributed to the influence of AAIW. ROVs provide a platform on which multiple instruments can be mounted and com