Growth Models Under Uniform Catastrophes

Abstract We consider stochastic growth models for populations organized in colonies and subject to uniform catastrophes. To assess population viability, we analyze scenarios in which individuals adopt dispersion strategies after catastrophic events. For these models, we derive explicit expressions for the survival probability and the mean time to extinction, both with and without spatial constraints. In addition, we complement this analysis by comparing uniform catastrophes with binomial and geometric catastrophes in models with dispersion and no spatial restrictions. Here, the terms uniform, binomial and geometric refer to the probability distributions governing the number of individuals that survive immediately after a catastrophe. This comparison allows us to quantify the impact of different types of catastrophic events on population persistence.

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Journal
Journal of Statistical Physics
Published
2026-10-28
DOI
https://doi.org/10.1007/s10955-026-03718-8
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
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article
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article

Growth Models Under Uniform Catastrophes

Alejandro Roldán-Correa, V. Valdivino, Fábio P. Machado, Joan Amaya
1 links
Journal of Statistical Physics
Mathematical and Theoretical Epidemiology and Ecology Models
article

Growth Models Under Uniform Catastrophes

Alejandro Roldán-Correa, V. Valdivino, Fábio P. Machado, Joan Amaya
article en

Abstract

Abstract We consider stochastic growth models for populations organized in colonies and subject to uniform catastrophes. To assess population viability, we analyze scenarios in which individuals adopt dispersion strategies after catastrophic events. For these models, we derive explicit expressions for the survival probability and the mean time to extinction, both with and without spatial constraints. In addition, we complement this analysis by comparing uniform catastrophes with binomial and geometric catastrophes in models with dispersion and no spatial restrictions. Here, the terms uniform, binomial and geometric refer to the probability distributions governing the number of individuals that survive immediately after a catastrophe. This comparison allows us to quantify the impact of different types of catastrophic events on population persistence.

Journal of Statistical PhysicsVol. 193(11)
Universidade de São Paulo (BR), Universidad de Antioquia (CO)
Openalex Percentile: Top 93%
Mathematical and Theoretical Epidemiology and Ecology Models
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