Conservation genetics of Pacific salmon – Project #2

I’ve just uploaded Project #2. As usual, you can find it either from the Lecture Schedule page or from the direct link below. This project is different from any of the lab exercises you’ve done so far. There isn’t data to analyze, and there aren’t simulations to do. Instead, there’s a paper by Robin Waples and David Teel to read: Conservation Genetics of Pacific Salmon I. Temporal Changes in Allele Frequency. [1]This link takes you to the website of Conservation Biology. I can’t seem to get to the full-text of the paper from off-campus, even though the VPN, but there is a freely available version at: … Continue reading After reading the paper, I have five questions for you to answer. When I grade this project, I will be evaluating how well you use what you’ve learned about genetic drift and natural selection to answer the questions. None of the answers need to be more than a couple of paragraphs. Feel free to submit them in whatever form you find convenient, Word document, R notebook, PDF, or Pages are formats I know I can handle easily. If you send it in a form I don’t recognize, I’ll be in touch.

References

References
1 This link takes you to the website of Conservation Biology. I can’t seem to get to the full-text of the paper from off-campus, even though the VPN, but there is a freely available version at: https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1431&context=usdeptcommercepub.

Exploring the coalescent

I’ve just posted Lab 7. You’ll find it in the usual places, i.e., from the Lab Schedule page or from the direct link below. As you’ll see, this lab exercise will allow you to explore the coalescent by comparing the time to coalescence of all alleles in a sample as a function of the rate of migration, the number of populations exchanging genes, and the migration model, i.e., either the finite island model you explored in last week’s exercise or the one-dimensional stepping stone. As noted in the exercise itself, the run_simulation() function will run 1000 samples by default. I recommend picking a smaller number first, say 50 or 100, to get a sense of how long a full run will take before you start the simulation. It shouldn’t be surprising that simulations take longer the more populations that you specify. There’s no need to try simulating more than 100 populations. You’ll see any patterns associated with differing numbers of populations by the time you get to that many.

Lab exercise for Week 6 posted

I’ll have grades returned for Week 5’s lab by the end of the day tomorrow. This week’s lab is a bit more involved for a couple of reasons.

  1. Each set of simulation conditions will take you longer to run. Each set takes about half an hour on my MacBook. You’ll want to get an early start on the exercise so you have a chance to explore at least five different sets of conditions.
  2. The questions ask you to stretch a little and interpret the results of the simulations relative to theoretical expectations.

As usual, you can get directly to the exercise from the link below, or you can get to it through the Lab Schedule page.