I’m on sabbatical this semester and in early January sat down to think of my sabbatical goals. The top one: getting lots of work done on manuscripts – we’ve collected a lot of interesting data and it’s time to get it written up and submitted! I was also looking forward to going for mid-morning runs – my favorite time to run, but hard to pull off with all the normal semester responsibilities. Instead, I ended up getting injured shortly thereafter, in a way that definitely cut out running and also made it hard to work (and especially to type). So much for those sabbatical plans.

Recently, I had just gotten home from PT when I got a call that one of my kids was sick and needed to be picked up. By the time I got to the school, it was clear it was a stomach virus, and I immediately worried about how many of us were going to catch it. The combination of frustration at a lingering (and highly impactful) injury & the prospect of a stomach virus moving through the family led me to draw this:

Drawing silly cartoons has always been a way for me to process things (here’s one example), and this one also prompted me to sit down and re-evaluate my sabbatical goals. Clearly the ‘crank out lots of papers and go for mid-morning runs’ goals have gone out the window. As I thought about it more, I realized a key goal for the remainder of my sabbatical: emerge from it less harried. 

This week: making Stephen Heard’s head explode, ecology dream job, academia vs. baseball, Peak Analogy, and more. Led with the fun links as an experiment this week, curious to see if it changes which links readers click on.

Welcome to our latest interview with the author of a recent(ish) interesting paper. Today’s interview is with theoretical ecologist Chuliang Song. I asked Chuliang about Song & Levine 2025 Nat Ecol Evol, which proposes a powerful new technique (well, new to ecologists) for testing ecological models such as predator-prey models using time series data. I also asked Chuliang some questions about how the conversation around theory in ecology has changed over the years, as the field has become both more quantitative and more applied. Chuliang is a super interview subject, he’s got a really interesting point of view and he’s great at coining phrases. Seriously, you don’t want to miss this one! Reading this is going to be way more entertaining and thought-provoking than whatever you were planning to spend the next 15 minutes doing. 🙂

The interview was conducted by email.

The question in the post title is one I’ve long been meaning to post on, but never got around to it because I never got around to doing the background research to answer my own question. So instead, I’m just going to throw the question out there and suggest an answer off the top of my head, in the confidence that commenters will improve on my answer. 🙂

This week: c’mon, find something else to talk about besides US politics Beowulf, the canary province in the coal mine, Humphreys opacity, Stewart Brand, Stephen Heard vs. Scrooge McDuck, and more.

My post drafts folder contains a bunch of ideas for unwritten posts. Many of them are years old, so there’s basically no chance I’ll ever actually write them. Others are quite new, so there’s a good chance I’ll write them. My post ideas tend to get written up either fairly quickly, or not at all.

So here are a bunch of posts I haven’t written yet, some of which I’ll never write. But they’re all mixed up, so you’ll have to guess which is which. 🙂

Writing in Plos Biology, Carl Bergstrom and Kevin Gross model meltdown of the peer review system.

I find these sorts of sociological models interesting to think about, but I’m often unsure how seriously to take them. I feel like there are lots of different plausible-ish models of the peer review system, and the behavior of the (many!) people involved in it, that lead to quite different predictions. I say this as someone who was arguing more than 15 years ago for urgent, fundamental changes to the incentives to do peer review, on the grounds that the peer review system was in imminent danger of meltdown. Those changes did not come to pass, and yet the peer review system seems to be chugging along more or less as it was 15 years ago. I was wrong in thinking that the peer review system was in imminent danger of meltdown unless something radical changed. So if you say that the incentives associated with the peer review system will make it melt down eventually, my question is: when?

Related: my old review of The Bet, a book about a famous prediction of imminent ecological and societal meltdown.

This week: bird papers still have the best figures, metascience observatory, against metascience observatories, AI vs. particle physics, AI vs. everybody’s jobs, and more.

Previously, I’ve compiled and analyzed data on the number of applicants for tenure-track EEB faculty positions in North America. I’ve looked at two kinds of data. One is data on the true, exact number of applicants, compiled from a combination of anonymous surveys of our readers and reports of true exact applicant numbers on ecoevojobs.net. The other is data on the number of ecoevojobs.net users who reported applying to a given job (the “number applied” counter on ecoevojobs.net). This second data source provides a much larger sample of jobs, at the cost of substantial measurement error. If you compare the two datasets for jobs for which they overlap, you find that the number of ecoevojobs.net users who report applying to a given job is an unbiased but extremely noisy index of the true number of applicants to that job. I’ve analyzed both datasets to identify predictors of which jobs attract the most applicants.

Recently, I collected some new data on the true, exact number of applicants to tenure-track EEB jobs advertised in North America in the last five years. I mostly just wanted to make the total sample size bigger, but I also figured it couldn’t hurt to check whether there have been any other changes to the geography of EEB faculty job applications in the last few years. Unfortunately, that new survey didn’t yield all that much additional data: just 29 new tenure-track jobs advertised in the last five years, to add to the 86 jobs for which I already had data on the true exact number of applicants.

So here’s an analysis of the geography of EEB faculty job applications in North American, using the combined dataset of 115 tenure-track EEB jobs. What factors determine which tenure-track EEB faculty positions get more applicants?

tl;dr: the answers haven’t changed all that much from my previous analysis of the smaller 86 job dataset.

This week: everything old is new again (image manipulation edition), mapping the garden of forking paths (and wondering why we bothered), life after p-hacking, teaching vs. crockpots, and more.