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Related Experiment Videos

Spatially implicit plankton population models: Transient spatial variability.

Philip J Wallhead1, Adrian P Martin, Meric A Srokosz

  • 1National Oceanography Centre, Southampton SO14 3ZH, UK. pjw5@noc.soton.ac.uk

Journal of Theoretical Biology
|May 20, 2008
PubMed
Summary
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Ocean plankton models can be improved by accounting for small-scale variations. New methods like spatial moment closure better predict ecosystem dynamics by addressing the failure of the mean field approximation in models.

Area of Science:

  • Oceanography
  • Ecology
  • Mathematical Biology

Background:

  • Ocean plankton models are crucial for ecosystem prediction.
  • The mean field approximation in models fails when grid cells are not well-mixed, leading to inaccurate population dynamics due to biological Reynolds fluxes.

Purpose of the Study:

  • To investigate the domain-scale behavior of plankton models with spatial variability.
  • To explore methods for improving the accuracy of large-scale plankton model predictions.

Main Methods:

  • Analysis of two-component, 2D reaction-diffusion plankton models with transient dynamics.
  • Investigation of implicit spatial resolution methods, including spatial moment closure and a two-spike approximation.

Main Results:

Related Experiment Videos

  • Spatial moment closure models significantly improve upon the mean field approximation for weak to moderate nonlinearity, especially at low mixing rates.
  • The two-spike approximation is accurate for stronger nonlinearity and weaker transience at low mixing rates.

Conclusions:

  • The mean field approximation's failure in ocean plankton models can be substantial.
  • Spatial moment closure and two-spike approximations offer improved predictions for marine ecosystem dynamics.
  • These methods may enhance our understanding and prediction of large-scale marine ecosystem behavior.