Coupling ecological concepts with an ocean-colour model: inversion modelling

Monitoring phytoplankton from space can help detect shifts in marine ecosystems, particularly under accelerating climate change. However, most existing ocean-colour chlorophyll-a (Chl-a) algorithms are empirical in nature, and do not explicitly consider any potential optical effects of shifts in phytoplankton community composition independent of a change in Chl-a. Similar ocean-colour signals may arise from different combinations of Chl-a and phytoplankton community composition. Revealing how phytoplankton are responding to environmental change using satellite data requires tackling this ambiguity. In previous work, we developed an Ocean Colour Modelling Framework (OCMF) to simulate ocean colour for varying Chl-a and phytoplankton size classes (PSCs). Here, we invert the OCMF to directly retrieve Chl-a, key inherent optical properties (IOPs), and PSCs, from satellite remote sensing reflectance and sea surface temperature (SST), accounting for deviations in non-algal particles (NAP) and coloured dissolved organic matter (CDOM) from assumed open ocean relationships with Chl-a. The model is validated using a global in situ dataset and shows stable performance across diverse oceanic conditions. Integrating ecological concepts into a bio-optical model may advance our ability to interpret long-term changes in phytoplankton community structure from space.