Untangling the role of temporal and spatial variations in persistance of populations

TL;DR

This paper investigates how temporal and spatial variations in growth rates affect population persistence, revealing that small dispersal can induce exponential growth (inflation) in populations across habitats with switching environments.

Contribution

It demonstrates that low dispersal rates can cause inflation in populations under periodic growth rate switching, extending understanding of population dynamics in variable environments.

Findings

Small dispersal induces inflation at large periods.

Inflation threshold is exponentially small with period.

Inflation persists under random switching and in extended models.

Abstract

We consider a population distributed between two habitats, in each of which it experiences a growth rate that switches periodically between two values, $1- \varepsilon > 0$ or $ - (1 + \varepsilon) < 0$. We study the specific case where the growth rate is positive in one habitat and negative in the other one for the first half of the period, and conversely for the second half of the period, that we refer as the $(\pm 1)$ model. In the absence of migration, the population goes to $0$ exponentially fast in each environment. In this paper, we show that, when the period is sufficiently large, a small dispersal between the two patches is able to produce a very high positive exponential growth rate for the whole population, a phenomena called inflation. We prove in particular that the threshold of the dispersal rate at which the inflation appears is exponentially small with the period. We show that inflation is robust to random perturbation, by considering a model where the values of the growth rate in each patch are switched at random times: we prove, using theory of Piecewise Deterministic Markov Processes (PDMP) that inflation occurs for low switching rate and small dispersal. Finally, we provide some extensions to more complicated models, especially epidemiological and density dependent models.