Measuring phytoplankton abundance and composition




Crucial to synoptically monitoring phytoplankton biomass – the first link of the foodweb – over the Southern Ocean (SO) and understanding their temporal changes is our ability to obtain unbiased measurements from satellite ocean color radiometry (OCR).This is generally achieved though the estimate of a biomass proxy: the chlorophyll concentration [Chl].

Over much of the global ocean, these estimates are reliable and decadal studies can be carried out to examine, for instance, shifts in phytoplankton abundance and how they relate to environmental changes. However, large errors in the estimate of [Chl] from remote sensing occur in the SO because of a lack of observations and the consequent gap in our knowledge of the light-matter interaction.

To remedy this situation, the project aims at

1) Building a consistent data set of radiometric, optical and biogeochemical variables for the Southern Ocean

2) Using this unique data set in combination with historical and other contemporaneous data sets to describe regionally-specific bio-optical relationships, and to identify the origin of the biases in current satellite OCR observations

3) Applying this understanding to develop new algorithms that will allow robust studies of seasonal to decadal changes of phytoplankton abundance and species composition in the SO using satellite observations. Achieving these aims will allow us to address key questions about the bio-optics and the phytoplankton changes in the Southern Ocean.


Principal Investigator (PI)

David Antoine
Remote Sensing & Satellite Research Group (RSSRG)


Curtin University, Perth, Australia


A bio-optical approach to understanding long term changes in phytoplankton abundance and composition in the Southern Ocean and their impact on the biological productivity

Principal institution / country

  • CSIR / UCT, Cape Town (South Africa)
  • NASA GSFC, Greenbelt (USA)
  • University of Tasmania, Hobart (Australia)
  • CSIRO O&A, Perth (Australia)
  • University of Maine, Orono (USA)
  • CNRS-LOG, Wimereux (France)
  • CNRS-LOV, Villefranche sur mer (France)
  • University of Sherbrooke (Canada)
  • CNRS-LOCEAN, UPMC, Paris (France)
  • Bigelow lab for ocean sciences (USA)