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Conditions for growth and extinction in matrix models with environmental stochasticity

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  • Sanz, Luis

Abstract

In this kind of model, the main characteristic that determines population viability in the long term is the stochastic growth rate (SGR) denoted λS. When λS is larger than one, the population grows exponentially with probability one and when it is smaller than one, the population goes extinct with probability one. However, even in very simple situations it is not possible to calculate the SGR analytically. The literature offers some approximations for the case in which environmental variability is low, and there are also some lower and upper bounds, but there is no study of the practical situations in which they would be tight. Some new bounds for the SGR are built and the conditions under which each bound works best are analyzed. These bounds are used to give some necessary and some sufficient conditions for population explosion and extinction that are easy to check in practice. The general results are applied to several cases, amongst them a population structured as juveniles and adults living in an environment switching randomly between “rich” and “poor”.

Suggested Citation

  • Sanz, Luis, 2019. "Conditions for growth and extinction in matrix models with environmental stochasticity," Ecological Modelling, Elsevier, vol. 411(C).
    • Handle: RePEc:eee:ecomod:v:411:y:2019:i:c:s0304380019303059
    DOI: 10.1016/j.ecolmodel.2019.108797
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    Cited by:

    1. Dmitrii O. Logofet & Leonid L. Golubyatnikov & Nina G. Ulanova, 2020. "Realistic Choice of Annual Matrices Contracts the Range of λ S Estimates," Mathematics, MDPI, vol. 8(12), pages 1-15, December.
    2. Logofet, Dmitrii O., 2019. "Does averaging overestimate or underestimate population growth? It depends," Ecological Modelling, Elsevier, vol. 411(C).
    3. Dmitrii O. Logofet & Leonid L. Golubyatnikov & Elena S. Kazantseva & Nina G. Ulanova, 2021. "“Realistic Choice of Annual Matrices Contracts the Range of λ S Estimates” under Reproductive Uncertainty Too," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    4. Logofet, Dmitrii O. & Golubyatnikov, Leonid L. & Kazantseva, Elena S. & Belova, Iya N. & Ulanova, Nina G., 2023. "Thirteen years of monitoring an alpine short-lived perennial: Novel methods disprove the former assessment of population viability," Ecological Modelling, Elsevier, vol. 477(C).

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