This Cambridge-based project asks how well can remotely sensed ocean colour be used to predict carbon cycling, from capture to seabed storage? How does this vary with season, sea ice levels and geographic factors (eg on vs offshore). EO ocean colour (derived from stacks of Sentinel-3 OLCI and other suitable datasets) & albedo data would be collated from Atlantic sector Arctic and Southern Ocean continental shelves to examine trends in marine ice losses and greening duration. Patterns and trends in colour would be ground-truthed for accuracy /error levels using in situ direct measurements of size-fractionated phytoplankton standing stock where and when they are present. Primary production would be linked to regional oceanography (eg flow/water residence time) and water column biogeochemistry. This key stage of the project would construct a model to link ice loss and primary production – through colour change – to predict levels of phytoplankton biomass reaching the seabed. This would be mapped onto existing data on local and regional standing stocks of zoobenthic blue carbon, by splitting zoobenthos into functional groups to separate suspension, deposit and grazing primary consumers and various categories of higher trophic levels. The last major component would be adding georeferenced organic and inorganic carbon profiles in sediments from sediment cores. This can be done from existing core data and unprocessed cores. The last work phase involves analysis of ocean surface to seabed connectivity in carbon sink, lag phases in time and space, and locations of/reasons for strong connectivity. This last stage will include use of data analytics and statistical/machine learning approaches to establish linkages between available datasets.