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Bulletin of Mathematical Biology

, Volume 64, Issue 4, pp 747–769 | Cite as

Pattern formation in reaction-diffusion models with nonuniform domain growth

  • E. J. CrampinEmail author
  • W. W. Hackborn
  • P. K. Maini
Article

Abstract

Recent examples of biological pattern formation where a pattern changes qualitatively as the underlying domain grows have given rise to renewed interest in the reaction-diffusion (Turing) model for pattern formation. Several authors have now reported studies showing that with the addition of domain growth the Turing model can generate sequences of patterns consistent with experimental observations. These studies demonstrate the tendency for the symmetrical splitting or insertion of concentration peaks in response to domain growth. This process has also been suggested as a mechanism for reliable pattern selection. However, thus far authors have only considered the restricted case where growth is uniform throughout the domain.

In this paper we generalize our recent results for reaction-diffusion pattern formation on growing domains to consider the effects of spatially nonuniform growth. The purpose is twofold: firstly to demonstrate that the addition of weak spatial heterogeneity does not significantly alter pattern selection from the uniform case, but secondly that sufficiently strong nonuniformity, for example where only a restricted part of the domain is growing, can give rise to sequences of patterns not seen for the uniform case, giving a further mechanism for controlling pattern selection. A framework for modelling is presented in which domain expansion and boundary (apical) growth are unified in a consistent manner. The results have implications for all reaction-diffusion type models subject to underlying domain growth.

Keywords

Pattern Formation Pattern Selection Peak Splitting Lady Beetle Domain Growth 
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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Copyright information

© Society for Mathematical Biology 2002

Authors and Affiliations

  1. 1.Centre for Mathematical Biology, Mathematical InstituteUniversity of OxfordOxfordUK
  2. 2.Mathematical Sciences DivisionAugustana University CollegeCamroseCanada

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