1998
DOI: 10.1016/s0304-3800(97)00202-0
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Cellular automata models for vegetation dynamics

Abstract: A short review of cellular automata models in ecology is given. Introduction of a spatial dimension into a discrete-time Markov chain leads to a class of cellular automata called spatio-temporal Markov chains (STMC). The behaviour of the model is determined by its temporal and spatial orders. It is proved that STMC models have ergodic distributions in certain cases for spatial order 0. Simulations suggest that STMC models of higher spatial order also have ergodic distributions. The model of Dytham (1995) is de… Show more

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Cited by 256 publications
(118 citation statements)
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“…These models have been increasingly unable to explain plant community dynamics (e.g., in Neotropic forests, fields and grasslands: see chapters in Myster 2007, Myster 2012a, Myster 2017a and so many researchers have turned to plant-plant replacement (Horn 1976, Grubb 1977, Busing 1996, Poulson and Platt 1996, Balzter et al 1998, Kneeshaw and Bergerson, 1998, Pacala et al 1998) as a new and better paradigm (Myster 2012b). Plant-plant replacements are not large-scale events like disturbances, nor do they occur over entire patches, but instead happen at the scale of individual plants of potentially different sizes throughout plant communities (Myster 2012b).…”
Section: A New Paradigmmentioning
confidence: 99%
“…These models have been increasingly unable to explain plant community dynamics (e.g., in Neotropic forests, fields and grasslands: see chapters in Myster 2007, Myster 2012a, Myster 2017a and so many researchers have turned to plant-plant replacement (Horn 1976, Grubb 1977, Busing 1996, Poulson and Platt 1996, Balzter et al 1998, Kneeshaw and Bergerson, 1998, Pacala et al 1998) as a new and better paradigm (Myster 2012b). Plant-plant replacements are not large-scale events like disturbances, nor do they occur over entire patches, but instead happen at the scale of individual plants of potentially different sizes throughout plant communities (Myster 2012b).…”
Section: A New Paradigmmentioning
confidence: 99%
“…The rich variety of CCA-and CA-based models that has been developed during the last decade for describing various spatial biological phenomena such as epidemics [6,14,28], population dynamics [3,5], tumor growth [13,23,24], biofilm development [21,22] and many other phenomena [10,25] is illustrative for the suitability of such models to mimic complex bioprocesses. In a forthcoming work, Baetens and De Baets [2] propose a generalized CCA for modelling various biological processes that are traditionally described by means of PDEs.…”
Section: The Modelmentioning
confidence: 99%
“…1997; Balzter et al, 1998) but they describe clonal expansion on a grid basis using simple empirical rules, or random processes. They can be used to predict patterns on a larger scale, but being empirical, they do not provide mechanistic insight.…”
Section: Comparison With Other Modelsmentioning
confidence: 99%