Life on the Edge

Storytime! When I was an undergraduate student at Dalhousie University, BACK IN THE DAY, I spent my summers making slides of rocks brought up by drills from offshore Nova Scotia and identifying and counting coccoliths (or, nannofossils). One of my supervisors for these projects was Dave Scott, a micropalaeontologist who also taught me invertebrate palaeontology at Dal. One day, unprompted, Dave offered up the fascinating personal tidbit that he hated seals, and when pressed for some kind of explanation for hating such a universally beloved animal, explained that it had to do with his time spent on Sable Island many years ago. Sable Island is a ridiculous, giant sand dune that is, hilariously, part of Halifax despite being located 300 km away in the Atlantic Ocean. It’s inhabited by feral horses, about 5 human beings, and seals, and that’s about it. Why did Dave hate the seals on Sable Island? “One hissed at me.”

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So You Want to Make a Time-Calibrated Phylogenetic Tree

Are you a palaeontologist interested in incorporating phylogenetic comparative methods into your research? Would you like to increase your toolkit of hypothesis-testing analyses for fossil-related questions? There’s a pretty good chance you’re going to need a time-calibrated phylogenetic tree. And to get one, you’re going to need to try your hand at R.

If you’re new to R programming or phylogenetic comparative methods, it can seem like a pretty steep uphill battle to learn some of these techniques, especially if you don’t feel like you got a great grounding in programming or statistics as an undergrad. Nevertheless, there are great resources out there for learning the basics of moving around in R (I like this one but I also just google things a lot), and good resources on phylogenetic comparative methods and statistical methods in biology. Today I’m going to do my best to make a bit of a tutorial for an important R package, paleotree (David Bapst), which will make magical time-calibrated trees for you that you can then use for all kinds of wonderful analyses. Continue reading