The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Cellular automata models for vegetation dynamics
Open accessAbstract
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 has been proven 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 demonstrated to be an STMC. Modelling population dynamics of three plant species on a lawn, two STMC models of different order are compared. The model validation shows a good agreement for Glechoma hederacea, but large deviations for Lolium perenne and Trifolium repens. The species-dependent performance of the models can be explained by selective grazing. Modifications of the transition matrices are used to examine possible causes of the deviations.
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Cites
An introduction to probability theory and its applications
(1958) · Journal of the Franklin Institute · doi:10.1016/0016-0032(58)90688-4 · Cited by 29,269
Statistical mechanics of cellular automata
Wolfram, S. (1983) · Reviews of Modern Physics · doi:10.1103/revmodphys.55.601 · Cited by 3,114
An Introduction to Probability Theory and Its Applications
Feller, W., & Morse, P. M. (1958) · Physics Today · doi:10.1063/1.3062516 · Cited by 2,040
Universality and complexity in cellular automata
Wolfram, S. (1984) · Physica D: Nonlinear Phenomena · doi:10.1016/0167-2789(84)90245-8 · Cited by 1,914
Introduction to the Numerical Solution of Markov Chains
Stewart, W. J. (1995) · Princeton University Press eBooks · doi:10.1515/9780691223384 · Cited by 1,750
An Introduction to Probability Theory and Its Applications, Vol. 1
Feller, W. (1968) · Cited by 1,446
Markov Random Field Modeling in Computer Vision
Li, S. Z. (1995) · Computer Science Workbench · doi:10.1007/978-4-431-66933-3 · Cited by 1,276
Spatial structure and chaos in insect population dynamics
Hassell, M. P., Comins, H. N., & Mayt, R. M. (1991) · Nature · doi:10.1038/353255a0 · Cited by 854
Connecting landscape patterns to ecosystem and population processes
Kareiva, P., & Wennergren, U. (1995) · Nature · doi:10.1038/373299a0 · Cited by 581
Spatially Explicit Population Models: Current Forms and Future Uses
Dunning, J. B., Stewart, D. J., Danielson, B. J., Noon, B. R., Root, T. L., Lamberson, R. H., & Stevens, E. E. (1995) · Ecological Applications · doi:10.2307/1942045 · Cited by 534
Cited by
Verburg, P. H., de Koning, G. H. J., Kok, K., Veldkamp, A., & Bouma, J. (1999) · Ecological Modelling · doi:10.1016/s0304-3800(98)00156-2 · Cited by 408
ANALYSIS OF ELECTRICAL EQUIPMENT OPERATING MODES OF THE EXCAVATION SITE OF A MODERN COAL MINE
Kuzbass State Technical University after T. F. Gorbachev, VORONIN, V., NEPSHA, F., Kuzbass State Technical University after T. F. Gorbachev, ERMAKOV, A., Kuzbass State Technical University after T. F. Gorbachev, KANTOVICH, L., & MISIS, N. (2021) · Sustainable Development of Mountain Territories · doi:10.21177/1998-4502-2021-13-4-599-607 · Cited by 3
Metadata
- Authors
- Balzter, H., Braun, P. W., & Köhler, W.
- Venue
- Ecological Modelling
- Publisher
- Elsevier BV
- Published
- 1998-04
- Volume
- 107
- Issue
- 2-3
- Pages
- 113-125
- ISSN
- 0304-3800 (ISSN-L)
- OpenAlex
- W2037202670
- Cited by
- 511
- References
- 35
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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