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Observations and Models of Highly Intermittent Phytoplankton Distributions

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  • Sandip Mandal
  • Christopher Locke
  • Mamoru Tanaka
  • Hidekatsu Yamazaki

Abstract

The measurement of phytoplankton distributions in ocean ecosystems provides the basis for elucidating the influences of physical processes on plankton dynamics. Technological advances allow for measurement of phytoplankton data to greater resolution, displaying high spatial variability. In conventional mathematical models, the mean value of the measured variable is approximated to compare with the model output, which may misinterpret the reality of planktonic ecosystems, especially at the microscale level. To consider intermittency of variables, in this work, a new modelling approach to the planktonic ecosystem is applied, called the closure approach. Using this approach for a simple nutrient-phytoplankton model, we have shown how consideration of the fluctuating parts of model variables can affect system dynamics. Also, we have found a critical value of variance of overall fluctuating terms below which the conventional non-closure model and the mean value from the closure model exhibit the same result. This analysis gives an idea about the importance of the fluctuating parts of model variables and about when to use the closure approach. Comparisons of plot of mean versus standard deviation of phytoplankton at different depths, obtained using this new approach with real observations, give this approach good conformity.

Suggested Citation

  • Sandip Mandal & Christopher Locke & Mamoru Tanaka & Hidekatsu Yamazaki, 2014. "Observations and Models of Highly Intermittent Phytoplankton Distributions," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-10, May.
  • Handle: RePEc:plo:pone00:0094797
    DOI: 10.1371/journal.pone.0094797
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    Cited by:

    1. Priyadarshi, Anupam & Chandra, Ram & Kishi, Michio J. & Smith, S.Lan & Yamazaki, Hidekatsu, 2022. "Understanding plankton ecosystem dynamics under realistic micro-scale variability requires modeling at least three trophic levels," Ecological Modelling, Elsevier, vol. 467(C).

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