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.

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Publication Details

Journal
Frontiers in Remote Sensing
Published
2026-01-29
DOI
https://doi.org/10.3389/frsen.2025.1692306
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Gavin H. Tilstone, Malika Kheireddine, Vincenzo Vellucci, Fang Shen et al.
Frontiers in Remote Sensing
Marine and coastal ecosystems
article

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

Gavin H. Tilstone, Malika Kheireddine, Vincenzo Vellucci, Fang Shen, Xuerong Sun, Ray Barlow, David Antoine, Mengyu Li, Shubha Sathyendranath, Jaime Pitarch, Yuan Zhang, Astrid Bracher, Robert J. W. Brewin, Dionysios E. Raitsos
article en

Abstract

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.

Frontiers in Remote SensingVol. 6
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Centre National de la Recherche Scientifique (FR), Planetary Science Institute (US), University of Bremen (DE), National Academies of Sciences, Engineering, and Medicine (US), National and Kapodistrian University of Athens (GR), Plymouth Marine Laboratory (GB), Sorbonne Université (FR), Center For Remote Sensing (United States) (US), The Polytechnic University of Japan (JP), National Centre for Earth Observation (GB), Department of Chemistry and Earth Sciences (BY), Laboratoire de Biologie du Développement de Villefranche-sur-Mer (FR), Laboratoire d’Océanographie de Villefranche (FR), Bayworld Centre for Research and Education (ZA), National Institute of Oceanography and Applied Geophysics (IT), Institut de la Mer de Villefranche (FR), Université Paris 1 Panthéon-Sorbonne (FR), East China Normal University (CN)
National Aeronautics and Space Administration, Government of Canada, University of Exeter, National Oceanic and Atmospheric Administration, Natural Environment Research Council
Life below water
Openalex Percentile: Top 77%
Marine and coastal ecosystems
DOIOpen Access PDFOpenAlex
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