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Identifying the critical domain size necessary for a population to persist is an important question in ecology. Both demographic and environmental stochasticity impact a population's ability to persist. Here we explore ways of including this variability. We study populations with distinct dispersal and sedentary stages, which have traditionally been modelled using a deterministic integrodifference equation (IDE) framework. Individual-based models (IBMs) are the most intuitive stochastic analogues to IDEs but yield few analytic insights. We explore two alternate approaches; one is a scaling up to the population level using the Central Limit Theorem, and the other a variation on both Galton-Watson branching processes and branching processes in random environments. These branching process models closely approximate the IBM and yield insight into the factors determining the critical domain size for a given population subject to stochasticity.

Original publication

DOI

10.1007/s00285-016-1021-5

Type

Journal article

Journal

J Math Biol

Publication Date

02/2017

Volume

74

Pages

755 - 782

Keywords

Branching processes, Critical domain size, Individual-based model, Integrodifference equation, Stochasticity, Ecology, Environment, Models, Biological, Population Dynamics, Stochastic Processes