Quasi-stationary distributions for structured birth and death processes with mutations

TL;DR

This paper investigates the existence and uniqueness of quasi-stationary distributions in a complex, measure-valued birth-death process with mutations, providing theoretical insights into long-term behavior conditioned on non-extinction.

Contribution

It establishes the existence of quasi-stationary distributions in an infinite-dimensional setting and proves their uniqueness for populations with constant birth and death rates.

Findings

Existence of quasi-stationary distributions in the general setting.

Uniqueness of the quasi-stationary distribution under certain conditions.

Identification of the maximal exponential decay rate for the distribution.

Abstract

We study the probabilistic evolution of a birth and death continuous time measure-valued process with mutations and ecological interactions. The individuals are characterized by (phenotypic) traits that take values in a compact metric space. Each individual can die or generate a new individual. The birth and death rates may depend on the environment through the action of the whole population. The offspring can have the same trait or can mutate to a randomly distributed trait. We assume that the population will be extinct almost surely. Our goal is the study, in this infinite dimensional framework, of quasi-stationary distributions when the process is conditioned on non-extinction. We firstly show in this general setting, the existence of quasi-stationary distributions. This result is based on an abstract theorem proving the existence of finite eigenmeasures for some positive operators. We then consider a population with constant birth and death rates per individual and prove that there exists a unique quasi-stationary distribution with maximal exponential decay rate. The proof of uniqueness is based on an absolute continuity property with respect to a reference measure.