How density dependence, genetic erosion, and the extinction vortex impact evolutionary rescue

Following severe environmental change that reduces mean population fitness below replacement, populations must adapt to avoid eventual extinction, a process called evolutionary rescue. Models of evolutionary rescue demonstrate that initial size, genetic variation, and degree of maladaptation influence population fates. However, many models feature populations that grow without negative density dependence or with constant genetic diversity despite precipitous population decline, assumptions likely to be violated in conservation settings. We examined the simultaneous influences of density-dependent growth and erosion of genetic diversity on populations adapting to novel environmental change using stochastic, individual-based simulations. Density dependence decreased the probability of rescue and increased the probability of extinction, especially in large and initially well-adapted populations that previously have been predicted to be at low risk. Increased extinction occurred shortly fol..., Data enclosed is generated from individual-based stochastic simulation; code to generate and analyze this data is included with the repository., , # How density dependence, genetic erosion, and the extinction vortex impact evolutionary rescue

[https://doi.org/10.5061/dryad.zgmsbccjj](https://doi.org/10.5061/dryad.zgmsbccjj)

Simulation code and data from the simulated experiment in the manuscript \"How density dependence, genetic erosion, and the extinction vortex impact evolutionary rescue.\" Data is in `.csv` format and code is in `.R` format.

## Description of the data and file structure

There are two main types of `.csv`s with results for main text and a third type `.csv` for the robustness analysis. These files are described below:

#### `alldata_n{20/100}_a{000/035}_{hi/low}var.csv`

These files are the \"main\" batch of simulations with all relevant variables recorded. There are 4000 per parameter combination. All trials were run for up to 15 timesteps. The name implies the treatment: initial size (`n`) 20 or 100, alpha (`a`) 0 or 0.0035, and genetic variation (`var`) high or low.

Columns:

* `trial` trial number (replicate...