A birth-death model of ageing: from individual-based dynamics to evolutive differential inclusions

TL;DR

This paper introduces a birth-death model of aging based on a two-phase Smurf phenotype, deriving an adaptive dynamics framework that predicts convergence of fertility and survival traits, highlighting the role of the Lansing effect in evolution.

Contribution

It develops a new stochastic and adaptive dynamics model incorporating age structure and the Lansing effect, extending the canonical equation to differential inclusions.

Findings

Traits converge to $x_b=x_d$ during evolution.

The model predicts finite-time convergence to the diagonal in trait space.

The differential inclusion captures the lack of regularity in invasion fitness.

Abstract

Ageing's sensitivity to natural selection has long been discussed because of its apparent negative effect on individual's fitness. Thanks to the recently described (Smurf) 2-phase model of ageing we were allowed to propose a fresh angle for modeling the evolution of ageing. Indeed, by coupling a dramatic loss of fertility with a high-risk of impending death - amongst other multiple so-called hallmarks of ageing - the Smurf phenotype allowed us to consider ageing as a couple of sharp transitions. The birth-death model (later called bd-model) we describe here is a simple life-history trait model where each asexual and haploid individual is described by its fertility period $x_b$ and survival period $x_d$. We show that, thanks to the Lansing effect, $x_b$ and $x_d$ converge during evolution to configurations $x_b-x_d\approx 0$. This guarantees that a certain proportion of the population maintains the Lansing effect which in turn, confers higher evolvability to individuals. \\To do so, we built an individual-based stochastic model which describes the age and trait distribution dynamics of such a finite population. Then we rigorously derive the adaptive dynamics models, which describe the trait dynamics at the evolutionary time-scale. We extend the Trait Substitution Sequence with age structure to take into account the Lansing effect. Finally, we study the limiting behaviour of this jump process when mutations are small. We show that the limiting behaviour is described by a differential inclusion whose solutions $x(t)=(x_b(t),x_d(t))$ reach the diagonal $\lbrace x_b=x_d\rbrace$ in finite time and then remain on it. This differential inclusion is a natural way to extend the canonical equation of adaptive dynamics in order to take into account the lack of regularity of the invasion fitness function on the diagonal $\lbrace x_b=x_d\rbrace$.