On Random Population Growth Punctuated by Geometric Catastrophic  Events

Huillet, Thierry

doi:10.37256/cm.152020600

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…This may be appropriate for some forms of catastrophic epidemics or when the catastrophe has a sequential propagation effect like in the predator-prey models-the predator kills prey until it becomes satisfied. More examples can be found in Artalejo et al [1], Cairns and Pollett [4], Economou and Gomez-Corral [5], Huillet [6] and Kumar et al [9].…”

Section: Geometric Catastrophementioning

confidence: 99%

Extinction time in growth models subject to geometric catastrophes

Vargas¹,

Machado²,

Roldán-Correa³

2023

J. Stat. Mech.

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Recently, different dispersion strategies in population models subject to geometric catastrophes have been considered as strategies to improve the chance of population’s survival. Such dispersion strategies have been contrasted with the strategy where there is no dispersion, comparing the probabilities of survival. In this article, we contrast survival strategies when extinction occurs almost surely, evaluating which strategy prolongs population’s life span. Our results allow one to analyze what is the best strategy based on parameters as the probability that each individual exposed to catastrophe survives, the growth rate of the colony, the type of dispersion and the spatial restrictions.

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Section: Geometric Catastrophementioning

confidence: 99%

Extinction time in growth models subject to geometric catastrophes

Vargas¹,

Machado²,

Roldán-Correa³

2023

J. Stat. Mech.

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“…They are part of the q-series theory (see [4]). Further instances and applications of geometric catastrophes are detailed in [1,9,10,15,17], while examples and applications of binomial catastrophes can be found in [1,5,6,14,16,18].…”

Section: Introductionmentioning

confidence: 99%

Extinction time in growth models subject to binomial catastrophes ^*

Duque,

Junior,

Machado

et al. 2023

J. Stat. Mech.

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Populations are often subject to catastrophes that lead to significant reductions in the number of individuals. Many stochastic growth models have been considered to explain such dynamics. Among the reported results, it has been considered whether dispersion strategies, at times of catastrophes, increase the survival probability of the population. In this paper, we contrast dispersion strategies by comparing the mean extinction times of a population under conditions of near-certain extinction. Specifically, we consider populations subject to binomial catastrophes, where the population size is reduced according to a binomial law when a catastrophe occurs. Our findings delineate the optimal strategy (dispersion or non-dispersion) based on variations in model parameter values.

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