Megafaunal Community Structure of Andaman Seamounts Including the Back-Arc Basin – A Quantitative Exploration from the Indian Ocean

Species rich benthic communities have been reported from some seamounts, predominantly from the Atlantic and Pacific Oceans, but the fauna and habitats on Indian Ocean seamounts are still poorly known. This study focuses on two seamounts, a submarine volcano (cratered seamount – CSM) and a non-volcano (SM2) in the Andaman Back–arc Basin (ABB), and the basin itself. The main purpose was to explore and generate regional biodiversity data from summit and flank (upper slope) of the Andaman seamounts for comparison with other seamounts worldwide. We also investigated how substratum types affect the megafaunal community structure along the ABB. Underwater video recordings from TeleVision guided Gripper (TVG) lowerings were used to describe the benthic community structure along the ABB and both seamounts. We found 13 varieties of substratum in the study area. The CSM has hard substratum, such as boulders and cobbles, whereas the SM2 was dominated by cobbles and fine sediment. The highest abundance of megabenthic communities was recorded on the flank of the CSM. Species richness and diversity were higher at the flank of the CSM than other are of ABB. Non-metric multi-dimensional scaling (nMDS) analysis of substratum types showed 50% similarity between the flanks of both seamounts, because both sites have a component of cobbles mixed with fine sediments in their substratum. Further, nMDS of faunal abundance revealed two groups, each restricted to one of the seamounts, suggesting faunal distinctness between them. The sessile fauna corals and poriferans showed a significant positive relation with cobbles and fine sediments substratum, while the mobile categories echinoderms and arthropods showed a significant positive relation with fine sediments only

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Not AvailableThe lockdowns imposed to contain the COVID-19 spread had an indisputably cascading effect on the aquaculture industry across the globe. It has adversely impacted the Indian fisheries sector through changing purchaser demand, supply chain disruptions, trade restrictions, and also the livelihood of millions dependent on it. However, the consequential reduced fishing will also likely help in replenishment of the aquatic biodiversity and provide the balance needed in the long-term sustenance of the fisheries sector. The technological and policy interventions in pre- and post-harvest fisheries operations are anticipated to reduce some of these negative impacts in similar lockdown scenarios.Not Availabl

Soft bottom species richness and diversity as a function of depth and iceberg scour in Arctic glacial Kongsfjorden (Svalbard)

Macrozoobenthic soft-sediment communities inhabiting six depth zones of central Arctic Kongsfjorden were analysed comparatively using SCUBA-diving. 63 taxa were found, 30 of which had not been reported for Kongsfjorden and seven for Svalbard. Suspensivorous or surface and sub-surface detritivorous polychaetes and deposit-feeding amphipods were dominant. Only eleven taxa of 45 species and additional 18 families identified inhabited the complete depth range. Biomass ranged from 3.5 to 25.0 g ash free dry mass m-2 and mean Shannon diversity (Log e) was 2.06. Similarity clustering from abun-dance and biomass data showed a significant difference between the shal-low station (5m) and the rest. The latter formed two subgroups (10-20m, 25-30m). These differences together with information on ice-scouring support the intermediate disturbance hypothesis indicating that habitats impacted by moderate iceberg scouring enable higher diversity. In contrast, biotopes frequently affected only host pioneer communities, while mature, less diverse assemblages dominate depths of low impact

Global patterns and predictions of seafloor biomass using random forests

A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management