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- Title
The critical domain size of stochastic population models.
- Authors
Reimer, Jody; Bonsall, Michael; Maini, Philip
- Abstract
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.
- Subjects
POPULATION density; MATHEMATICAL domains; DISPERSAL (Ecology); CENTRAL limit theorem; BRANCHING processes; DETERMINISTIC processes
- Publication
Journal of Mathematical Biology, 2017, Vol 74, Issue 3, p755
- ISSN
0303-6812
- Publication type
Article
- DOI
10.1007/s00285-016-1021-5