Computational Science Technical Note CSTN-040

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A Minimal Spatial Cellular Automata for Hierarchical Predator-Prey Simulation of Food Chains

K. A. Hawick and C. J. Scogings

Archived July 2007, Revised March 2010.

Abstract

Models of complex spatial environmental and ecological systems are usually constructed using partial differential equations (PDEs), but cellular automata (CA's) can provide microscopically simple yet macroscopically rich alternatives. We develop a cellular automata model of a hierarchical predator-prey system and show that even a minimal automaton is able to capture the essential boom-bust and dynamical behaviour of real physical systems. A single probability rate of predator death is used to control predator behaviour. We describe the model in detail and explore the CA model for one- and two-predator food chains. We find a well delineated phase transition in the 2-predator system when the predator lifetime parameter is varied and present some system analysis and quantitative metrics. We discuss the CA model in comparison with PDE and more detailed event-driven agent-based models.

Keywords: cellular automata; spatial models; predator-prey; Lotka-Volterra; food chains; phase transition; stochastic rate equation.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-040,
  author = {K. A. Hawick and C. J. Scogings},
  title = {A Minimal Spatial Cellular Automata for Hierarchical Predator-Prey
	Simulation of Food Chains},
  booktitle = {Proc. International Conference on Scientific Computing (CSC'10)},
  year = {2010},
  pages = {75-80},
  address = {Las Vegas, USA},
  month = {12-15 July},
  publisher = {WorldComp},
  institution = {Computer Science, Massey University},
  timestamp = {2008.03.07}
}


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