Speaker
Description
Evolvability—the capacity of a population to generate heritable phenotypic variation—plays a central role in adaptation, yet its evolutionary dynamics are not fully understood. In this work, we investigate how evolvability, treated as a continuous phenotypic trait, shapes the adaptation of asexual populations. To this end, we develop ad hoc discrete and continuum mathematical models describing the evolutionary dynamics of phenotype structured cell populations, characterised by their fitness and evolvability. Through analysis and simulation of these models, we study how proliferative potential and evolvability are selected over short and long time scales, and under various conditions, including asymmetries in the distribution of fitness effects and increasingly steep phenotypic landscapes.
Our results reveal a robust two step adaptive trajectory: highly evolvable individuals initially accelerate exploration of the phenotypic landscape, enabling rapid access to fitter proliferative states; once high proliferative potential is reached, selection favours reduced evolvability, promoting stabilisation. We further show that strong selection gradients, high evolvability costs, and asymmetric distributions of fitness effects can slow adaptation or even drive extinction when populations start from highly evolvable, low fitness states. These findings highlight evolvability as a dynamic trait whose short term benefits may conflict with long term persistence \cite{ref1}.
Bibliography
@article{ref1,
title={First explore, then settle: a theoretical analysis of evolvability as a driver of adaptation},
author={Jim{\'e}nez-S{\'a}nchez, Juan and Ortega-Sabater, Carmen and Maini, Philip K and P{\'e}rez-Garc{\'\i}a, V{\'\i}ctor M and Lorenzi, Tommaso},
journal={Bulletin of Mathematical Biology},
volume={88},
number={2},
pages={21},
year={2026},
publisher={Springer}
}
