The contribution of statistical physics to evolutionary biology

TL;DR

This paper explores how concepts and methods from statistical physics, such as non-equilibrium mechanics and Monte Carlo simulations, have been applied to understand complex evolutionary processes in biology.

Contribution

It highlights the integration of statistical physics techniques into population genetics, emphasizing new approaches to studying evolution.

Findings

Statistical physics methods have been successfully applied to polygenic evolution.

Monte Carlo methods aid in modeling range expansions.

Non-equilibrium dynamics provide insights into adaptation rates.

Abstract

Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. We discuss aspects of population genetics that have embraced methods from physics: amongst others, non-equilibrium statistical mechanics, travelling waves, and Monte-Carlo methods have been used to study polygenic evolution, rates of adaptation, and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics, for example, by following the distribution of paths taken by a population through time.