AI Article Synopsis
- Understanding population persistence is key in population biology, with historical roots in the 1950s KiSS model that highlights the importance of patch size for survival.
- The KiSS model portrays a population living in a finite-sized area surrounded by high mortality, revealing that only adequately sized patches sustain populations.
- The study introduces an individual-based version of the KiSS model to explore how human population dynamics, including randomness and patch size, affect extinction times and distributions.
Article Abstract
Understanding the conditions ensuring the persistence of a population is an issue of primary importance in population biology. The first theoretical approach to the problem dates back to the 1950s with the Kierstead, Slobodkin, and Skellam (KiSS) model, namely a continuous reaction-diffusion equation for a population growing on a patch of finite size L surrounded by a deadly environment with infinite mortality, i.e., an oasis in a desert. The main outcome of the model is that only patches above a critical size allow for population persistence. Here we introduce an individual-based analog of the KiSS model to investigate the effects of discreteness and demographic stochasticity. In particular, we study the average time to extinction both above and below the critical patch size of the continuous model and investigate the quasistationary distribution of the number of individuals for patch sizes above the critical threshold.
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| http://dx.doi.org/10.1103/PhysRevE.92.012722 | DOI Listing |
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