Code and data for:

Stoffel, M. A., Humble, E., Paijmans, A. J., Acevedo-Whitehouse, K., Chilvers, B. L., Dickerson, B., … & Hoffman, J. I. (2018). Demographic histories and genetic diversity across pinnipeds are shaped by human exploitation, ecology and life-history. Nature Communications, 9(1), 1-12.

Project

We analysed genetic data from 11,000 individuals spanning 30 pinniped species around the globe to shed light on the consequences of large scale seal-hunting in the 18th and 19th century. Around a third of these species showed distinct genetic signatures of past population bottlenecks. Pinniped species with harem-based mating systems and land-breeding species (as opposed to ice-breeding species) were particularly affected by population declines and loss of genetic diversity due to overhunting.

Estimated bottleneck effective population sizes for eleven severely hunted pinniped species using Approximate Bayesian Computation. Pinniped illustrations by Rebecca Carter.

Reproducing the analysis

To run the analyses, please download the complete folder. The folder named R contains the complete analysis divided into 14 scripts, which are named 01_ to 14_ . As some of the analyses are computationally intensive, many datasets which are produced along the way are already saved in data/ , so that the analysis can be started at any point. The coalescent simulations and ABC analyses are outsourced into a second repository (but the results are available in data/).

To sum up, the complete analysis workflow is split into two repositories:

1. Coalescent simulations and ABC analysis

• repository: https://github.com/mastoffel/Pinniped_bottleneck_CoalSimABC
• the scripts in this repository should run on a server with sufficient computing power and memory

2. All further analyses are in the current repo.

• repository: https://github.com/mastoffel/pinniped_bottlenecks
• these scripts can be run a standard desktop machine (except for script 1, the STRUCTURE analysis)
• the scripts to reproduce the main results including the figures have been placed in the R folder and are sequentially named from 01 to 14.

In addition, we packaged some specific functions into two packages:
(a) sealABC: devtools::install_github(“mastoffel/sealABC”)
(b) mcmcR2: devtools::install_github(“mastoffel/mcmcR2”)

Both packages are highly specific to the current analysis and probably have to be modified to be of use in other projects.