Simulation scripts and data for the stochastic modelling of evolutionary rescue in resistance to pesticides

Evolutionary rescue occurs when the genetic evolution of adaptation saves
a population from extinction after environmental change. The evolution of
resistance to pesticides is a special scenario of abrupt environmental
change, where rescue occurs under strong selection for one or a few de
novo resistance mutations of large effect. Here, we develop
continuous-time approximations that accurately predict classic
discrete-time dynamics in population genetics and population ecology in an
integrated eco-evolutionary model of adaptive rescue through pesticide
resistance. We derive analytical approximations for the key distributions
and statistics that characterise the results, including the probability
density function for the time to resistance and the probability of
population extinction. The time to resistance shows a lag period, a narrow
peak and a long tail, which implies that it can be difficult to predict
when resistance will arise. The probability of population extinction shows
a sharp transition, in that when extinction is possible, it is also highly
likely, which can make eradication a theoretically achievable goal.
Alongside these results contributing to the theory of evolutionary rescue,
the methods have produced powerful approximations that lay the foundations
of a flexible modelling framework for the applied study of
eco-evolutionary dynamics to improve scientific resistance management.