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.

When wind speeds are 2–10 m s⁻¹, reflective contrasts in the ocean surface make oil slicks visible to synthetic aperture radar (SAR) under all sky conditions. Neural network analysis of satellite SAR images quantified the magnitude and distribution of surface oil in the Gulf of Mexico from persistent, natural seeps and from the Deepwater Horizon (DWH) discharge. This analysis identified 914 natural oil seep zones across the entire Gulf of Mexico in pre‐2010 data. Their ∼0.1 µm slicks covered an aggregated average of 775 km². Assuming an average volume of 77.5 m³ over an 8–24 h lifespan per oil slick, the floating oil indicates a surface flux of 2.5–9.4 × 10⁴ m³ yr⁻¹. Oil from natural slicks was regionally concentrated: 68%, 25%, 7%, and <1% of the total was observed in the NW, SW, NE, and SE Gulf, respectively. This reflects differences in basin history and hydrocarbon generation. SAR images from 2010 showed that the 87 day DWH discharge produced a surface‐oil footprint fundamentally different from background seepage, with an average ocean area of 11,200 km² (SD 5028) and a volume of 22,600 m³ (SD 5411). Peak magnitudes of oil were detected during equivalent, ∼14 day intervals around 23 May and 18 June, when wind speeds remained <5 m s⁻¹. Over this interval, aggregated volume of floating oil decreased by 21%; area covered increased by 49% (p < 0.1), potentially altering its ecological impact. The most likely causes were increased applications of dispersant and surface burning operations.

Ocean oil slicks can be attributed to natural seepages or to anthropogenic discharges. To date, the global picture of their distribution and relative natural and anthropogenic contributions remains unclear. Here, by analyzing 563,705 Sentinel-1 images from 2014–2019, we provide the first global map of oil slicks and a detailed inventory of static-and-persistent sources (natural seeps, platforms, and pipelines). About 90% of oil slicks were within 160 kilometers of shorelines, with 21 high-density slick belts coinciding well with shipping routes. Quantified by slick area, the proportion of anthropogenic discharges was an order of magnitude greater than natural seepages (94 versus 6%), in contrast to the previous estimate quantified by volume during 1990–1999 (54 versus 46%). Our findings reveal that the present-day anthropogenic contribution to marine oil pollution may have been substantially underestimated.