Predicting patterns of long-term adaptation and extinction with population genetics

TL;DR

This paper develops a stochastic model to predict long-term population adaptation and extinction, revealing how evolutionary dynamics and environmental challenges influence species persistence over millions of years.

Contribution

It introduces a Markov chain model capturing long-term evolutionary processes and extinction risk, extending beyond short-term or catastrophe-focused models.

Findings

Long-term persistence depends on adaptation rate exceeding environmental deterioration.

Extinction risk peaks during establishment phase and stabilizes later.

Model aligns with fossil species persistence times of several million years.

Abstract

Population genetics struggles to model extinction; standard models track the relative rather than absolute fitness of genotypes, while the exceptions describe only the short-term transition from imminent doom to evolutionary rescue. But extinction can result from failure to adapt not only to catastrophes, but also to a backlog of environmental challenges. We model long-term evolution to long series of small challenges, where fitter populations reach higher population sizes. The population's long-term fitness dynamic is well approximated by a simple stochastic Markov chain model. Long-term persistence occurs when the rate of adaptation exceeds the rate of environmental deterioration for some genotypes. Long-term persistence times are consistent with typical fossil species persistence times of several million years. Immediately preceding extinction, fitness declines rapidly, appearing as though a catastrophe disrupted a stably established population, even though gradual evolutionary processes are responsible. New populations go through an establishment phase where, despite being demographically viable, their extinction risk is elevated. Should the population survive long enough, extinction risk later becomes constant over time.