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Self-Organizing Spatio-temporal Pattern Formation in Two-Dimensional Daisyworld

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Part of the Lecture Notes in Computer Science book series (LNCCN,volume 7166)

Abstract

Watson and Lovelock’s daisyworld model [1] was devised to demonstrate how the biota of a world could stabilise it, driving it to a temperature regime that favoured survival of the biota. The subsequent studies have focused on the behaviour of daisyworld in various fields. This study looks at the emergent patterns that arise in 2D daisyworlds at different parameter settings, demonstrating that a wide range of patterns can be observed. Selecting from an immense range of tested parameter settings, we present the emergence of complex patterns, Turing-like structures, cyclic patterns, random patterns and uniform dispersed patterns, corresponding to different kinds of possible worlds. The emergence of such complex behaviours from a simple, abstract model serve to illuminate the complex mosaic of patterns that we observe in real-world biosystems.

Keywords

  • Pattern Formation
  • Random Pattern
  • Global Dynamic
  • Species Dispersion
  • Periodic Spiral

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Punithan, D., McKay, R.I.(. (2012). Self-Organizing Spatio-temporal Pattern Formation in Two-Dimensional Daisyworld. In: Kuipers, F.A., Heegaard, P.E. (eds) Self-Organizing Systems. IWSOS 2012. Lecture Notes in Computer Science, vol 7166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28583-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-28583-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28582-0

  • Online ISBN: 978-3-642-28583-7

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