We offer a new framework for cellular automata modeling to describe and predict vegetation dynamics. The model can simulate community composition and spatial patterns by following a set of probabilistic rules generated from empirical data on plant neighborhood dynamics. Based on published data (Lippe et al. 1985), we apply the model to simulate Atlantic Heathland vegetation dynamics and compare the outcome with previous models described for the same site. Our results indicate reasonable agreement between simulated and real data and with previous models based on Markov chains or on mechanistic spatial simulation, and that spatial models may detect similar species dynamics given by non-spatial models. We found evidence that a directional vegetation dynamics may not correspond to a monotonic increase in community spatial organization. The model framework may as well be applied to other systems.
Wolfram, S. 1983. Statistical mechanics of cellular automata. Reviews of Modern Physics 55: 601-644.
'Statistical mechanics of cellular automata' () 55Reviews of Modern Physics: 601-644.
Statistical mechanics of cellular automataReviews of Modern Physics55601644)| false
Madhur Anand, CAN (forest ecology, computational ecology, and ecological complexity)
S. Bagella, ITA (temporal dynamics, including succession, community level patterns of species richness and diversity, experimental studies of plant, animal and microbial communities, plant communities of the Mediterranean)
P. Batáry, HUN (landscape ecology, agroecology, ecosystem services)
P. A. V. Borges, PRT (community level patterns of species richness and diversity, sampling in theory and practice)
A. Davis, GER (supervised learning, multitrophic interactions, food webs, multivariate analysis, ecological statistics, experimental design, fractals, parasitoids, species diversity, community assembly, ticks, biodiversity, climate change, biological networks, cranes, olfactometry, evolution)
Z. Elek, HUN (insect ecology, invertebrate conservation, population dynamics, especially of long-term field studies, insect sampling)
T. Kalapos, HUN (community level plant ecophysiology, grassland ecology, vegetation-soil relationship)
G. M. Kovács, HUN (microbial ecology, plant-fungus interactions, mycorrhizas)
W. C. Liu,TWN (community-based ecological theory and modelling issues, temporal dynamics, including succession, trophic interactions, competition, species response to the environment)
L. Mucina, AUS (vegetation survey, syntaxonomy, evolutionary community ecology, assembly rules, global vegetation patterns, mediterranean ecology)
P. Ódor, HUN (plant communities, bryophyte ecology, numerical methods)
F. Rigal, FRA (island biogeography, macroecology, functional diversity, arthropod ecology)
D. Rocchini, ITA (biodiversity, multiple scales, spatial scales, species distribution, spatial ecology, remote sensing, ecological informatics, computational ecology)
F. Samu, HUN (landscape ecology, biological control, generalist predators, spiders, arthropods, conservation biology, sampling methods)