Conditioning the logistic branching process on non-extinction

TL;DR

This paper analyzes the logistic branching process conditioned on non-extinction, deriving transition rates and distributions using connections to population genetics, and explores implications for understanding long-term survival and genealogical structures.

Contribution

It provides explicit formulas for transition rates and distributions of the logistic branching process conditioned on survival, linking it to diffusion processes and genealogical structures.

Findings

Derived transition rates conditioned on survival until time T.

Obtained the probability generating function of the Yaglom distribution.

Explicit expressions for the Q-process transition rates and genealogical joint generator.

Abstract

We consider a birth and death process in which death is due to both `natural death' and to competition between individuals, modelled as a quadratic function of population size. The resulting `logistic branching process' has been proposed as a model for numbers of individuals in populations competing for some resource, or for numbers of species. However, because of the quadratic death rate, even if the intrinsic growth rate is positive, the population will, with probability one, die out in finite time. There is considerable interest in understanding the process conditioned on non-extinction. In this paper, we exploit a connection with the ancestral selection graph of population genetics to find expressions for the transition rates in the logistic branching process conditioned on survival until some fixed time $T$, in terms of the distribution of a certain one-dimensional diffusion process at time $T$. We also find the probability generating function of the Yaglom distribution of the process and rather explicit expressions for the transition rates for the so-called Q-process, that is the logistic branching process conditioned to stay alive into the indefinite future. For this process, one can write down the joint generator of the (time-reversed) total population size and what in population genetics would be called the `genealogy' and in phylogenetics would be called the `reconstructed tree' of a sample from the population. We explore some ramifications of these calculations numerically.