Abstract

How long does it take for an initially advantageous mutant to establish itself in a resident population, and what does the population composition look like then? We approach these questions in the framework of the so called Bare Bones evolution model (Klebaner et al. in J Biol Dyn 5(2):147–162, 2011. https://doi.org/10.1080/17513758.2010.506041) that provides a simplified approach to the adaptive population dynamics of binary splitting cells. As the mutant population grows, cell division becomes less probable, and it may in fact turn less likely than that of residents. Our analysis rests on the assumption of the process starting from resident populations, with sizes proportional to a large carrying capacity K. Actually, we assume carrying capacities to be a_1K and a_2K for the resident and the mutant populations, respectively, and study the dynamics for Krightarrow infty . We find conditions for the mutant to be successful in establishing itself alongside the resident. The time it takes turns out to be proportional to log K. We introduce the time of establishment through the asymptotic behaviour of the stochastic nonlinear dynamics describing the evolution, and show that it is indeed frac{1}{rho }log K, where rho is twice the probability of successful division of the mutant at its appearance. Looking at the composition of the population, at times frac{1}{rho }log K +n, n in mathbb {Z}_+, we find that the densities (i.e. sizes relative to carrying capacities) of both populations follow closely the corresponding two dimensional nonlinear deterministic dynamics that starts at a random point. We characterise this random initial condition in terms of the scaling limit of the corresponding dynamics, and the limit of the properly scaled initial binary splitting process of the mutant. The deterministic approximation with random initial condition is in fact valid asymptotically at all times frac{1}{rho }log K +n with nin mathbb {Z}.

Highlights

  • There has been much work in stochastic adaptive dynamics and evolutionary branching, see Dieckmann and Law (1996), Metz et al (1996), Champagnat et al (2002), Champagnat and Méléard (2011) and Sagitov et al (2013), to mention just a few.Here we confine ourselves to a simple mathematical model for evolution, where an established resident population is invaded by a mutant

  • We confine ourselves to a simple mathematical model for evolution, where an established resident population is invaded by a mutant

  • At the moment of invasion the resident, wild-type, population is assumed to have the size near its carrying capacity a1 K

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Summary

Introduction

There has been much work in stochastic adaptive dynamics and evolutionary branching, see Dieckmann and Law (1996), Metz et al (1996), Champagnat et al (2002), Champagnat and Méléard (2011) and Sagitov et al (2013), to mention just a few. We confine ourselves to a simple mathematical model for evolution, where an established resident population is invaded by a mutant. The size of the mutant population is initially negligible as compared to K , since it starts from one individual. It has a reproductive advantage over the resident, but as its progeny grows this advantage diminishes. We want to answer the question of how long it takes for a mutant to become established, i.e. to grow to a size comparable to the host population. Unlike in the classical case on deterministic approximation (Kurtz 1970; Barbour 1980), some stochasticity remains and enters as a random initial condition

The Bare Bones evolutionary model
Stochastic nonlinear dynamics for the evolution of the density
Deterministic dynamics
The large capacity limit of the stochastic dynamics
Main results
A preview
An auxiliary recursion in dimension one
Proof of Theorem 2
The main approximation

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