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The phenology of phytoplankton blooms: Ecosystem indicators from remote sensing

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  • Platt, Trevor
  • White, George N.
  • Zhai, Li
  • Sathyendranath, Shubha
  • Roy, Shovonlal

Abstract

Remote sensing offers many advantages in the development of ecosystem indicators for the pelagic zone of the ocean. Particularly suitable in this context are the indicators arising from time series that can be constructed from remotely sensed data. For example, using ocean-colour radiometry, the phenology of phytoplankton blooms can be assessed. Metrics defined in this way show promise as informative indicators for the entire pelagic ecosystem. A simple phytoplankton–substrate model, with forcing dependent on latitude and day number is used to explore the qualitative features of bloom phenology for comparison with the results observed in a suite of 10-year time series of chlorophyll concentration, as assessed by remote sensing, from the Northwest Atlantic Ocean. The model reveals features of the dynamics that might otherwise have been overlooked in evaluation of the observational data.

Suggested Citation

  • Platt, Trevor & White, George N. & Zhai, Li & Sathyendranath, Shubha & Roy, Shovonlal, 2009. "The phenology of phytoplankton blooms: Ecosystem indicators from remote sensing," Ecological Modelling, Elsevier, vol. 220(21), pages 3057-3069.
    • Handle: RePEc:eee:ecomod:v:220:y:2009:i:21:p:3057-3069
    DOI: 10.1016/j.ecolmodel.2008.11.022
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    References listed on IDEAS

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    1. Vanhoutte-Brunier, Alice & Fernand, Liam & Ménesguen, Alain & Lyons, Sandra & Gohin, Francis & Cugier, Philippe, 2008. "Modelling the Karenia mikimotoi bloom that occurred in the western English Channel during summer 2003," Ecological Modelling, Elsevier, vol. 210(4), pages 351-376.
    2. Trevor Platt & Csar Fuentes-Yaco & Kenneth T. Frank, 2003. "Spring algal bloom and larval fish survival," Nature, Nature, vol. 423(6938), pages 398-399, May.
    3. Chu, Peter C. & Ivanov, Leonid M. & Margolina, Tetyana M., 2007. "On non-linear sensitivity of marine biological models to parameter variations," Ecological Modelling, Elsevier, vol. 206(3), pages 369-382.
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    Cited by:

    1. Brewin, Robert J.W. & Sathyendranath, Shubha & Hirata, Takafumi & Lavender, Samantha J. & Barciela, Rosa M. & Hardman-Mountford, Nick J., 2010. "A three-component model of phytoplankton size class for the Atlantic Ocean," Ecological Modelling, Elsevier, vol. 221(11), pages 1472-1483.
    2. Mayersohn, Benjamin & Smith, K. Shafer & Mangolte, Inès & Lévy, Marina, 2021. "Intrinsic timescales of variability in a marine plankton model," Ecological Modelling, Elsevier, vol. 443(C).

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