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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects

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Author(s):
Mendonca, J. Ricardo G. ; Gevorgyan, Yeva
Total Authors: 2
Document type: Journal article
Source: Physical Review E; v. 95, n. 5 MAY 18 2017.
Web of Science Citations: 1
Abstract

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found. (AU)

FAPESP's process: 15/21580-0 - Analysis and simulation of random walks and exclusion processes over graphs
Grantee:José Ricardo Gonçalves de Mendonça
Support type: Regular Research Grants