Kongsfjorden is a glacial fjord in the Arctic (Svalbard) that is influenced by both Atlantic and Arctic water masses and harbours a mixture of boreal and Arctic flora and fauna. Inputs from large tidal glaciers create steep environmental gradients in sedimentation and salinity along the length of this fjord. The glacial inputs cause reduced biomass and diversity in the benthic community in the inner fjord. Zooplankton suffers direct mortality from the glacial outflow and primary production is reduced because of limited light levels in the turbid, mixed inner waters. The magnitude of the glacial effects diminishes towards the outer fjord. Kongsfjorden is an important feeding ground for marine mammals and seabirds. Even though the fjord contains some boreal fauna, the prey consumed by upper trophic levels is mainly Arctic organisms. Marine mammals constitute the largest top‐predator biomass, but seabirds have the largest energy intake and also export nutrients and energy out of the marine environment. Kongsfjorden has received a lot of research attention in the recent past. The current interest in the fjord is primarily based on the fact that Kongsfjorden is particularly suitable as a site for exploring the impacts of possible climate changes, with Atlantic water influx and melting of tidal glaciers both being linked to climate variability. The pelagic ecosystem is likely to be most sensitive to the Atlantic versus Arctic influence, whereas the benthic ecosystem is more affected by long‐term changes in hydrography as well as changes in glacial runoff and sedimentation. Kongsfjorden will be an important Arctic monitoring site over the coming decades and a review of the current knowledge, and a gap analysis, are therefore warranted. Important knowledge gaps include a lack of quantitative data on production, abundance of key prey species, and the role of advection on the biological communities in the fjord.

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.

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