Pitfalls and windfalls of detecting demographic declines using population genetics in long-lived species

Detecting recent demographic changes is a crucial component of species conservation and management, as many natural populations face declines due to anthropogenic habitat alteration and climate change. Genetic methods allow researchers to detect changes in effective population size (Ne) from sampling at a single timepoint. However, in species with long lifespans, there is a lag between the start of a decline in a population and the resulting decrease in genetic diversity. This lag slows the rate at which diversity is lost, and therefore makes it difficult to detect recent declines using genetic data. However, the genomes of old individuals can provide a window into the past, and can be compared to those of younger individuals, a contrast that may help reveal recent demographic declines. To test whether comparing the genomes of young and old individuals can help infer recent demographic bottlenecks, we use forward-time, individual-based simulations with varying mean individual lifespans ..., All data for this publication were generated via evolutionary simulations in SLiM. Here, we archive all scripts necesarily to generate, analyze, and visualize the results presented in Clark et al. 2024. 
First, we performed simulations in SLiM using a perennial and annual model for a variety of average lifespans (for the perennial model), and bottleneck severities. The output of these simulations is  (1) a .tree file contain the geneological history of the population, from which we will extract information about genetic diversity, (2) individual-based metadata for all individuls alive during the simulation sampling time: the generation number, individual pedigree id and the individual's age, (3) Census population size information about the population at each generation in the sampling period. 
Second, we used tskit, msprime, and pyslim to load and process .tree files as tree sequences. We then loop through focal sampling points in the tree sequence, and sampling individuals to perform a..., , # Pitfalls and windfalls of detecting demographic declines using population genetics in long-lived species

[https://doi.org/10.5061/dryad.w0vt4b91p](https://doi.org/10.5061/dryad.w0vt4b91p)

This repository details the generation and analysis of simulated data for exploring the application of age-aware sampling to detecting demographic declines. There is no empirical data associated with this study, but simulated datafiles are uploaded and detailed below. All code required to reproduce analyses in the paper are below. Please reach out to [Meaghan](https://orcid.org/0000-0003-3297-8372) with questions at meaghaniclark (at) gmail.com.

## Data

```
pWF_slim_output.tar.gz
nWF_slim_output_2.tar.gz
nWF_slim_output_5.tar.gz
nWF_slim_output_10.tar.gz
nWF_slim_output_20.tar.gz
```

These directories contain simulated data output from slim. Perennial model outputs (\"nWF\") are split by average age. File names denote the average age, bottleneck severity, and replicate number in that order for the...