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..., The dataset was collected by running R scripts that describe a stochastic model of evolutionary rescue in resistance to pesticides. The R scripts are also included alongside the dataset., , # Datasets for 'Evolutionary rescue in resistance to pesticides'

[https://doi.org/10.1098/rspb.2024.0805](https://doi.org/10.1098/rspb.2024.0805) ; [https://doi.org/10.5061/dryad.n02v6wx41](https://doi.org/10.5061/dryad.n02v6wx41)

There are four datasets that are used to plot the figures in the paper and the supplementary figures, which are tagged with a file name that starts with:

1. ScenarioMS = multiple selection coefficients; having run the simulation under standard conditions with 6 representative selection coefficient values;
2. ScenarioAS = across selection coefficients; having run the simulation under standard conditions for a large number of selection coefficient values;
3. ScenarioPV = parameter variation; having run the simulation under a large number of parameter combinations;
4. SpreadingProbability = simulations across selection coefficients to generate the spreading (or fixation) probability

## Description of the data and file structure

For the ScenarioMS/AS/PV d...