Friday links: science on stage and screen, petri dish art, and more

Also this week: Plos One may be struggling, NEON is definitely struggling, musings on the MacArthur “genius awards”, and more

From Jeremy:

Last week’s Science had a series of news articles on how NEON is struggling. Here’s one. Indeed, judging from the articles, “struggling” is too mild a word.

An interview with the creators of The Martian, on the role of science in the film. Related: my recent post on how science ends up on screen in Hollywood movies.

From science on film to science on stage: writing in Nature, Philip Ball reviews Nicole Kidman as Rosalind Franklin in Photograph 51. Sigh; I remember when I could’ve gone to see this sort of thing rather than settling for reading about it. :-( Other reviews from the NY Times, the Guardian and Variety. The Variety review includes particularly thoughtful comments on the larger issues raised by the play. (Irrelevant aside: if I ever do something so great as to cause someone to make a play or a movie about me, I want to be played by Jeff Goldblum.)

How do MacArthur “genius grant” winners spend the money? It varies; Sally Otto is giving it away.

Speaking of the MacArthur genius grants, computational population geneticist John Novembre just got one.

Related: here are two pieces discussing whether the MacArthur awards go too often to people who are already established. And see the comments on the first piece, where a couple of people recommend former population ecologist and now “cliodynamicist” Peter Turchin for a MacArthur. What do you think? If you were writing $625,000 checks to a small number of people whom you hope will go on to do great scientific, artistic, or other world-improving work, to spend on anything they wanted, would you write any checks to ecologists? If so, who? And why?

Also related: here are your options for how to react when you don’t win a MacArthur. :-) (ht Crooked Timber). A sample:

“Well, it’s hard to get a MacArthur when so much of my work has been classified by Executive Order, anonymous by personal choice, or published under the pseudonym ‘Samuel Beckett.’ ” Taking this line has the advantage of not requiring you to be able to point to any unrecognized achievement in particular.

Is Plos One struggling? Their output has been plummeting. Their impact factor is declining (though that decline may be stabilizing). And now they’re raising their author charge to $1495. Which you’d think would further discourage submissions, though I have no idea by how much. I don’t actually know anything about the economics here. I’m just surprised that, with so many open access advocates trying to get publishing costs down, that Plos One would move in the other direction. Even if the stated reason is to invest in their infrastructure. Anybody know more about this? Is it possible that the real reason they’re raising the fee is to try to make up for the decline in submissions? (ht Retraction Watch)

Speaking of author pays open access publishing, its origin (at least when it comes to BioMed Central) is a hardheaded business calculation, not an idealistic passion for access. (ht Scholarly Kitchen)

A new study of the effects of open peer review (i.e. everybody involved knows the identities of the authors and reviewers), and of the use of reviewers suggested by authors. Uses various lines of comparative evidence. The evidence on open vs. single-blind review is mixed, which leads to the conclusion that open peer review isn’t clearly better or worse than single-blind review. Also finds that reviews by author-suggested reviewers are equal in quality to those of other reviewers on average, but that author-suggested reviewers are more likely to recommend acceptance (though those recommendations don’t affect editorial decision making). I can believe that last conclusion. When I suggest reviewers, I don’t recommend them based on whether I think they’ll recommend acceptance of my ms. But I do suggest people whom I’m confident will “get” my ms, which I’m sure is correlated with their likelihood of recommending acceptance. Note that the study focuses on review quality and doesn’t address other issues, such as that many scientists won’t do open review.

Shane Hanlon on why he stopped seeking a tenure track job in ecology, even though he was getting interviews.

Yet another person who thinks that the primary obstacles to post-publication review (or to online “peer feedback” more broadly) are to do with the technical design of commenting and reviewing systems. Don’t misunderstand, I think it’s great that people are trying out new ways of communicating, and I’m sure this one will hit the spot for some people. But I doubt it’ll ever take off in a big way. Semi-related recent post here. (ht Retraction Watch)

Ok, this is just a silly, trivial political gaffe, and linking to it probably slightly contributes to the decline of our political discourse. But I’m linking to it anyway because I can’t wait to vote against the current Canadian government. The government that promoted its salmon-protecting credentials in British Columbia with a picture of an Atlantic salmon. From the UK. With this government, we’re lucky it wasn’t a picture of a rainbow trout or a shark or something.

Entrants in the American Society of Microbiologists’ petri dish art contest.

What “probability” means in different professions. Professions covered include “weather forecaster”, “political journalist” and “Mission: Impossible agent”. Funny and true. :-)

Sticking with Math with Bad Drawings: a (somewhat strained) positive spin on the dumbest mathematical mistake you’ll ever see on an official sign. Actually, it’s possible the mistake is an intentional joke. I sure hope it is, because as a commenter over there points out, there are other examples! :-)

Finally found a self storage place that slowly crushes my stuff over time.” :-)

Strategies (and reasons) for being more productive with fewer hours

A really common theme in discussions of work-life balance is the need to be efficient in getting work done. As I’ve written about before, I don’t come close to working the legendarily long hours some report; instead, I try to focus on making good use of the hours that I am at work. Recently, my colleague Trisha Wittkopp and I led a session on time management and work-life balance at our department’s annual retreat. I figured that it might be useful to write up some of what came up during that discussion.

But first, before going into the strategies themselves, I find it personally useful to reflect on why I want to be efficient. A downside to focusing a lot on being efficient is that I sometimes get really stressed out if something seems inefficient or like a waste of time. I was recently at a meeting that ended up being a complete waste of time, and was getting kind of panicky because there was no good way to leave and OMG I WAS WASTING AN HOUR. That level of focus on efficiency is not so helpful. Similarly, I sometimes get really focused on getting a lot of work done, and then have a hard time turning off the work part of my brain in the evening to focus on my kids. In those cases, I need to remind myself that a large part of why I try so hard to be efficient during the day is so that I can focus on them when I am at home! And, finally, I feel like I need to avoid falling into what I think is a common trap of getting obsessed with efficiency just for the sake of efficiency. When people say one of their time management tips is to always type in 1:11 (or something to that effect) on the microwave to save time, I wonder: how much time is really saved that way? Or, as this piece put it, “This is not so much a ruthless use of time as a fetishization of time—the cult of the billable hour run amok.” So, yes, I think efficiency is important, but I also think that it’s possible to get carried away and get obsessed with efficiency.

Now, on to the strategies. I don’t use all of these strategies, but, if they aren’t ones I use but that seem useful to lots of people, I wanted to include them. This is certainly not an exhaustive list, and I’d love to hear from others what works (or doesn’t work) for them.

  1. Recognize what is “good enough”. As the saying goes, perfect is the enemy of good. And recognize that “good enough” will vary between different tasks. It’s okay if the email you are sending to your lab about lab meeting isn’t perfectly composed.
  2. Say no. Or, put more precisely, choose the tasks you work on carefully. Saying “yes” to one thing means (often implicitly) saying “no” to something else. It’s hard to say no, but I try to remind myself that I’m saying no to something either way, because my time is a limited resource. I try to make myself think of what I will not do because I agree to task X. Sometimes that seems like a worthwhile (or important) trade. Other times it doesn’t, and that can make it easier to say no. That said, this is definitely still something I struggle with.
  3. Block off time in your schedule for tasks that are important but that can be easily postponed otherwise (e.g., writing, analyzing data). I find it much easier to say no to a meeting if I have to physically move the little box in my calendar that says I was planning on working on a proposal or manuscript or whatever at that time. It took me a while to realize that being free at the time of a particular meeting didn’t mean that I necessarily had time for that meeting.
  4. Figure out when you write best and block off time for it then. One thing that has come up in discussions I’ve been involved with on this topic is to make sure that you don’t let email creep into quality writing time.
  5. For me, blocking off time for exercise is just as important as blocking off time for writing. If I stop exercising, I stop sleeping well, and then it all goes south.
  6. If possible, delegate (or collaborate). In recently evaluating what I need to do this academic year, it became clear it just wasn’t logistically feasible. But there were a couple of tasks that could be shared with others and where working on them would help the other person. As another example: when working on a grant proposal this summer, the control freak in me wanted to personally enter all the budget stuff into Fastlane. But we have someone in the department whose job is to help with that, and I really needed that time for other things. In that case, it made sense for her to handle the budget in Fastlane.
  7. Have a way of keeping track of tasks that need to be accomplished. This makes it so that you can get it out of your mind and focus on the task at hand. I mostly use Remember The Milk for this, but there are lots of options. Find a system that works for you.
  8. Have bite-sized tasks on your “to do” list. Don’t put “write paper” on the list – that’s much too big of a task, and it will be hard to motivate yourself to get started on it. Instead, put “make figures for paper X” on that list (or even “Make figure 1”).
  9. Set deadlines for getting tasks done, even if they don’t have a hard deadline. This is something that works really well for me due to some handy personality quirk, but I know it doesn’t work as well for others. I seem to be easily able to convince myself that a task needs to be done by a certain date, even if that date is really just one I made up. This helps me avoid procrastination.
  10. Deal with things that can be done in just a couple of minutes right away. The idea is to do things right away if it would take just as long (or longer) to add them to a “to do” list and to get back up to speed later in order to do the task. Often, this is replying to an email. However, a problem for me with checking email on my phone when I’m walking places is that these tasks end up getting buried in my email. I don’t reply while walking (though others have success with using dictation for this), and it means that things that I could have dealt with quickly right away end up getting forgotten sometimes. So, I liked this suggestion in the article on multitasking that Jeremy linked to on Friday: “Set up a filing system within your email so that when a message arrives that requires a proper keyboard to answer — ie 50 words or more — you can move that email out of your inbox and place it in a folder where it will be waiting for you when you fire up your computer.” I need to try that!
  11. Speaking of dictation software, some people find it really helpful. I’ve tried a little bit, but it didn’t really seem to be helping me, so I don’t use it at present.
  12. If you are sending an email to just one person and it’s going to be more than a couple of sentences, a phone call might be more efficient. Sometimes the email is good for keeping a record of what was discussed, but sometimes a phone call can save a lot of time spent writing the email.
  13. Have a ritual that signals that you are starting work and stopping work. If you work lots of different places (e.g., your office, the library, a coffee shop), this needs to be portable. I haven’t tried this, but really liked this idea. For some people, it’s something like turning on a particular lamp on their desk. I suppose I used to find that putting my headphones on at my computer really helped me focus, so maybe that was a sort of ritual for starting to work.
  14. Try to find a way to keep email from occupying a ton of time. Some people set aside certain time for email and, once that’s up, go back to other things. I should probably try that. I feel like I should treat email the way primary care offices treat sick patients: you know there will be some that need attention right away, and so you should set aside some time in the day to take care of it/them. But I haven’t formalized that yet. A more minor thing I do (but that adds up) is use lots of filters. Each lab member, for example, has a folder, and messages from them automatically gets the correct label attached. That way I can reply and then hit “Send and archive” and the email goes to the correct place without me having to do that manually. I also have some emails that go straight to a folder skipping the inbox (and, for cases where I’ve been unable to successfully unsubscribe myself from some list, even a few filters that set things up to go straight to the trash).
  15. Related to the above: have an email folder for things that still need to be done, but that you don’t need to do immediately. Mine is labeled “1 still needs attention” (the 1 is so that it is right up at the top of the list of folders in my gmail). My colleague Trisha said that, in addition to the folder for things that still need attention, she has a “waiting for” folder for things where she’s waiting on someone else to do something before she replies. That sounds like a great idea. I tend to just archive those (or leave them in my mailbox), but that can mean losing them (or adding to inbox clutter).
  16. Log time spent on work (and perhaps even break it down into different categories). When I first did this, I was surprised to realize how much time those little breaks were adding up to. I just use an excel spreadsheet, but there are fancier programs. I mostly don’t log my time anymore, but if I feel like I’ve gotten in the habit of wasting time, I start it up again. Just knowing that I am logging my time makes me focus better.
  17. That said, remember that taking breaks is important for staying sharp. Breaks are not necessarily a waste of time! Some people use the Pomodoro technique for this. Here are some ideas for what to do in a five minute break. And here are some more.
  18. Write daily. I don’t specifically try to do this, but I often end up doing it unintentionally. One benefit for me of blogging is that it means I am generally in the habit of writing, which makes working on a manuscript or grant proposal less daunting. I’ve had a few writing tasks in the past year that felt completely overwhelming at first, until I started viewing them as blog posts.
  19. Keep track of projects at all stages of development – make sure there are projects at all stages of development. sciwo has a great post on running the research conveyor belt. I have a file that is my “Project Level To Do List”. It includes the manuscripts in review, the ones we are currently writing up (these are also listed on my white board, just to keep them totally front and center), the ones where we need to finish processing or analyzing data, the ones where we are still collecting the data but it looks like it will turn into a paper, the experiments we still need to run but that are relatively well planned out, and the ones that are still nascent ideas that need to be fleshed out. The key is to make sure there are projects at all stages of the pipeline. I recall reading at some point that, when women have babies, if there is a “baby gap” on the CV, it often is 1-2 years after the baby is born. With a newborn, you still manage to make time for revisions, but might not make time for getting a new project started. This visual split of the projects into the different bins helps me try to ensure there are things at all stages of development.
  20. Have a general organizational system. For example, come up with a way of keeping track of the different projects on your conveyor belt, for keeping track of papers you want to read, and making notes about changes you want to make to your lectures for next year. I’ve been using Evernote for this more and more.
  21. Streamline tasks that will need to be done repeatedly. I teach a very large course, where certain issues will predictably come up (e.g., illness, injury, or a death in the family). Rather than write a new email laying out options for the student in each case, we have a standardized version that then gets tailored to the specific case. My colleague Trisha makes great use of keyboard shortcuts and text expanders for these tasks.
  22. Limit the time you leave for lecture prep. Some people, when they are first teaching a course, to try to prep things well in advance. There are at least two reasons why this is not a good idea: a) you may vastly misjudge the pace at which you can reasonably cover things, and so may need to redo almost all of your work later; b) there are diminishing returns with lecture prep. Spending an extra hour trying to find the perfect figure showing an effect of X on Y is not necessarily a great way to spend time. Remember the concept of “good enough” from above! You are less likely to spend a whole ton of time on lecture prep if you haven’t left yourself a whole ton of time. I say all this even though I care a lot about teaching and put a lot of effort into it. But teaching prep can be an immediate reward task that can crowd out other tasks that are also really important (especially work on manuscripts and grant proposals). As a new faculty member, I was given the advice to prep lectures one week before lecture. That leaves a little flex time in case you get sick or have something major come up, but I tried to be religious about giving a lecture in the morning, and then finishing the lecture for the next week (along with various other essential tasks) by the time I left work that day. I now break this rule, and have updated all of my lectures for the semester, but that is because I was just updating the lectures, rather than writing them all from scratch.
  23. Schedule meetings back-to-back when possible. This helps keep the meetings from dragging on, and reduces the number of times you need to get back into work mode after.
  24. Be productive in those interstitial spaces. That can be a good time to tackle emails, for example.
  25. Remember that, sometimes, investing more time upfront is worth it in the long run. I spent a lot of time last semester figuring out how to do things in R that I could have done much more quickly elsewhere because I think that up front investment will have big payoffs over the longer term. Being able to take that view was definitely aided by being on leave for the semester!

Finally, this isn’t so much a strategy as an observation: An interesting thing that came up during the recent discussion I led with Trisha is that some people do better when compartmentalizing tasks, whereas others are integrators. I tend to shift my brain to work mode and then can have a hard time shifting back to “life” mode if something comes up during the day. I also tend to compartmentalize within work tasks, which is why my collaborators will suddenly receive 12 emails in a row from me, or why I will reply to all the comments on a post at once. Others do better if they just deal with the “life” tasks when they pop up, even if it is in the middle of the day. Which comes to a bigger point: just keeping in mind that different things work for different people is important. This is part of why I like hearing about what other people do: I’m sure some of what they do will be useful to me, too, but also that some of what they do won’t work for me. That’s fine.

So, what are some of your strategies for time management and efficiency?

Postscript: After writing this, I finally got a chance to read this recent piece by Tim Harford on multi-tasking and how to survive in the 21st century. I added one relevant bit above, but mostly didn’t update the post related to it. Some of the strategies at the end of his piece overlap with ones above. The piece as a whole is interesting and worth a read.

Limits to continental-scale species richness: thoughts on the debate

A while back, the ASN held a formal debate on whether species richness at continental scales is governed by ecological limits. The opposing papers–Dan Rabosky and Allen Hurlbert arguing in favor, Luke Harmon and Susan Harrison in opposition–came out in Am Nat a few months ago. I finally got around to reading them. Great stuff–there’s a lot to chew on here! Well worth reading even if you’re not all that interested in macroecology or macroevolution, because they comprise a terrific case study of science in action. For any question big and interesting enough to be worth asking, it’s often not obvious exactly what the question is, or how to answer it. It’s fascinating to see how different experts define a question and evaluate the evidence.

Below are thoughts inspired by the papers. I’m going to assume that you’ve read the papers, so go do that if you haven’t already (or if you’re lazy you can try to get by with Carolyn Tucker’s brief summary).

Don’t think of this as “post-publication review”. I’m very glad both papers were published and wouldn’t change a thing about them. And nothing I say is a personal criticism of any of the authors, all of whom I hugely respect. That I sometimes disagree with them just shows that disagreement is a normal part of science.

  • A big part of the disagreement here is about what “limit” means.
    I’m totally with Rabosky & Hurlbert on this one. Species richness is gonna vary over time. We don’t know of any reason why that wouldn’t happen, but we do know of lots of things that might impart some negative feedback or return tendency to that variation. So the sensible first-order question to ask is the one Rabosky & Hurlbert ask: is there any return tendency? That is, does continental scale species richness tend on average to increase from low values, and decline from high values? As opposed to, say, just tending to grow exponentially, except when mass extinctions knock it back. Or as opposed to doing an unbiased random walk (i.e. per-species speciation and extinction rates are equal on average, but are either constant over time or else vary independently of species richness). In contrast, I’m not sure exactly what Harmon and Harrison mean by “limit”. But they seem to mean either “species richness remains constant or nearly so, with only biologically-trivial amounts of variation”, or “species richness has a hard, extrinsically-imposed upper limit that can never be exceeded”. Assuming I’m not badly misreading them (and apologies if I am), I don’t like either of those ways of defining “limits”, for several reasons. First, it’s pretty easy to reject both, but doing so doesn’t teach you much because it still leaves you with a whole world of very different possibilities–including the one that Rabosky & Hurlbert consider. A world in which continental-scale species richness has a strong return tendency is a very different world, ecologically and evolutionarily, from one in which it has no return tendency at all–but neither is a world in which species richness doesn’t vary, or always stays below some hard upper limit. Defining “limits” as Rabosky & Hurlbert do doesn’t set the burden of proof for “limits” too low, it just frames the question so that it has an informative answer. Second, it’s a mistake to think that, because some variable of interest exhibits high temporal variance, or has ups and downs that are correlated with the ups and downs of some extrinsic driving variable, that it must have little or no return tendency, or that whatever return tendency it has is somehow unimportant. See Ziebarth et al. 2010 for an exceptionally clear discussion of this mistake in the context of population ecology. The strength of a variable’s return tendency, its temporal variance, and the fraction of its variation explained by variation in some extrinsic driver variable, are three very different things. They’re related, but often in the opposite way to how you might intuitively think. So I disagree with Harmon & Harrison when they claim the temporal variability of species richness in fossil time series data as evidence against Rabosky & Hurlbert. Any amount of temporal variability in a time series is consistent with any strength of return tendency. Third, I can’t think of any variable in biology that has a hard, extrinsically-imposed upper limit on its value, the way nothing in the physical world can move faster than the speed of light. In particular, it’s tempting but very misleading to think of “niches” as like houses that exist independently of species, so that once all the houses are filled no more species can live in that neighborhood. Species are not like Dr. Seuss’ nutches. The only constraints I can think of that impose hard upper limits on the values of biological variables are mathematical constraints. For instance, the species richness in some part of North America can’t be negative, and can’t exceed species richness in all of North America.
  • This debate is just like the density dependence debate in population ecology–so can we resolve it the same way? Following on from the previous bullet, Harmon and Harrison note, correctly, that the debate here is just like the debate over density dependence in population ecology. Which is why it puzzles me that they define “limits” as they do. It’s actually Rabosky and Hurlbert who define “limits” analogous to how most population ecologists these days define density dependence. One thing Rabosky & Hurlbert’s way of defining “limits” has going for it is that it lets you bring modern statistical techniques of time series analysis to bear. So despite my puzzlement over Harmon & Harrison’s way of defining “limits”, I agree 100% with them that we ought to be as statistically rigorous as we can in testing for limits. Rather than just eyeballing time series of continental-scale species richness to see if they have any return tendency, we ought to be trying to estimate that return tendency statistically, for instance using the approach of Ziebarth et al. 2010 or Knape & de Valpine 2012. Not that this will be a panacea. Rabosky and Hurlbert quite rightly point out that the stationary distribution to which species richness tends to return can change over time (and also vary from place to place). And in response, Harmon & Harrison quite rightly point out that it’s very hard to distinguish a system without any return tendency from a system which has a return tendency but which tends to return to different stationary distributions at different times in its history. My suggestion is to start simple, as population ecologists have done. Start by looking at whether time series data on continental-scale species richness are best described by a model with a return tendency, that includes exponential growth and a density-independent random walk as limiting cases. Based on the results of that analysis, decide whether it’s useful to estimate something complicated, like a model with some sort of temporally-varying stationary distribution, or a model that switches back and forth between having a return tendency and lacking one. There’s precedent for this sort of approach in other contexts in paleontology, like Gene Hunt’s work asking which of several different time series models best describes trait evolution time series (Hunt 2007, Hunt 2008, Hunt et al. 2015). So now I’m very curious to dig into the paleontological literature to see what the state of the art is with regard to analyzing time series data on species richness or clade richness.
  • The importance of checking assumptions as well as testing predictions. I love that both pairs of authors want to check both the predictions and the assumptions of the ecological limits hypothesis. Testing predictions is great, but ecologists often focus too narrowly on testing predictions, to the exclusion of checking assumptions (see here and here). Checking assumptions as well as testing predictions is how you distinguish between a model that’s actually right, and a model that’s just getting lucky.
  • The importance, and challenge, of using microscale evidence to test macroscale hypotheses. love that both pairs of authors consider various “microscale” lines of evidence, even though they’re ultimately interested in explaining macroscale data. They all agree that the macroscale is–has to be–the aggregate outcome of lots of microscale events. Just because you ultimately care about the macroscale doesn’t mean the microscale is somehow irrelevant or unimportant or ignorable. Rather, if your macroscale hypothesis makes microscale assumptions (and how could it not, at least implicitly), or makes predictions about microscale data, then you have to check those assumptions and test those predictions. But of course, as we’ve discussed in lots of old posts, scaling up from the microscale to the macroscale is really challenging (e.g., here and here). A lot of the disagreement between the two sides seems to come down to disagreement about what, if anything, various lines of microscale evidence imply about the macroscale hypothesis Rabosky & Hurlbert defend. I won’t comment too much on that, except to say that…
  • I disagree with Harmon & Harrison on local-regional richness relationships. One line of microscale evidence both sides discuss are data on how the species richness of local communities relates to the richness of the “regional species pools” from which those local communities were presumably assembled. I’m totally with Rabosky & Hurlbert on this one–you cannot infer anything about whether or not local communities are “saturated” with species, or even whether species interactions have any appreciable affect on local species richness, by looking at plots of local vs. regional richness. I think that’s a zombie idea–see this old post. (Aside: that post is based on two recent meta-analyses of local-regional richness data, neither of which is cited by these two papers.)
  • I think I disagree with Rabosky & Hurlbert on how island biogeography models work. This is a small and possibly-pedantic point. Rabosky & Hurlbert describe their hypothesis as analogous to simple models of island biogeography. They say that, in simple island biogeography models, the fact that there is some stable equilibrium value of island species richness towards which the system tends is a reflection of finite resource availability. I don’t think that’s right. The fact that simple island biogeography models have a stable equilibrium value of species richness reflects the assumption that there’s a fixed, finite number of species on the mainland. Consider a system in which there are P species on the mainland. They colonize the island at some constant per-species rate c that’s the same for all species. The island has S species. The probability that a newly-arrived species is not already present on the island, thereby increasing island species richness, is 1-S/P. Species on the island go extinct at a constant per-species rate e that’s the same for all species. These assumptions imply that the rate of change of species richness on the island is dS/dt=cP(1-S/P)-eS. That equation has a single equilibrium, S*=cP/(c+e), and that equilibrium is globally stable. It’s not globally stable because of any resource-based limit to how many species can colonize the island, or because per-species extinction rates increase with island species richness due to resource competition. It’s globally stable because, the more species there are on the island, the lower the odds that any colonist is a new species. That’s not to say that resource limitation sensu Rabosky and Hurlbert doesn’t occur or isn’t important. My point is a conceptual one–you don’t need that sort of resource limitation to have a stable equilibrium value of species richness in an island biogeography model. Of course, maybe you do need resource limitation or something that does the same job in the context of the macroecological/macroevolutionary speciation-extinction model Rabosky & Hurlbert propose. Since in those models, speciation, not a fixed mainland species pool, is the ultimate source of diversity.* Anyway, I wanted to raise this because I’m always puzzled and surprised when I discover that even experienced ecologists sometimes don’t mean the same thing when they refer to some very basic textbook model or concept.

*In fact, the total rate at which new species colonize doesn’t even need to decline with increasing island species richness for the island to have a stable equilibrium species richness. For instance, consider the model dS/dt=x-eS, where x is some constant rate at which new species arrive on the island. Doesn’t matter from where; it doesn’t have to be from a mainland with some fixed number of species on it. Could be that, once per unit time, the Flying Spaghetti Monster (or an experimenter!) adds one or more new species to the island. That model has a globally stable equilibrium island species richness, S*=x/e. It’s globally stable because the per-species rate at which new species colonize is x/S, which of course declines with increasing S. This model is “density dependent” in the same way that population ecology models with a constant rate of immigration are density dependent. There are ecologists who would regard this sort of “apparent” density dependence as some kind of trivial or misleading artifact, but I don’t think it is. It’s just a different mechanism giving rise to density dependence. Now, fair enough if you don’t think this is a realistic island biogeography model; I don’t think it’s realistic either. But don’t let that blind you to the conceptual point. You don’t have to have resource limits to have a stable equilibrium species richness on an island (well, unless you want to argue–debatably–that without resource limits no species would ever go extinct, so e=0).

Ask us anything: when to give up (on a research project, and an academic career)

Today, three related questions from Andrew:

When is it appropriate to abandon a line of research? Is there a point of no return when you finish a project regardless of how lackluster the results have been or seem likely to be?

If it is appropriate to stop a project, how do you break the news to collaborators? And how do you deal with pressure from them to continue a project you no longer believe in?

When should you abandon the hunt for a tenure track job? What indicators warn you that obtaining a TT job is improbable? The data in this article indicate that the probability of obtaining a TT job declines to <1% 10 years post-PhD.

Jeremy: When to give up on research project is a very context-dependent judgment call, so it’s hard to give advice. I have an old post that posed a similar question to the commentariat, but didn’t get much feedback, unfortunately.

When to give up on the search for a TT job is a very personal decision. I decided to give up after four years–and then got lucky when Calgary offered me the job I currently hold. But had my personal circumstances been different, I might well have kept trying. I’d been getting multiple interviews/year for four years, a strong indicator that I was very competitive. Conversely, had my personal circumstances been different in some other way, or had I not been getting any interviews, I might’ve given up a bit sooner.

If you no longer enjoy what you’re doing, then you should look for something else to do. Don’t worry about wasting your PhD (you’re not, not even if your new career doesn’t require a PhD), don’t worry about letting anyone else down (it’s your life, not theirs), don’t feel like you’ve failed (you haven’t), and don’t feel that you’re settling for second best (you’re not).

Try to be clear-eyed about what sort of TT job you really want. For instance, if I recall correctly, Terry McGlynn has an old post at Small Pond Science arguing that many people who only apply for (and fail to get) TT jobs at research universities would be just as happy (and more likely to get hired) if they applied for jobs at teaching universities. Giving up on a TT job at Princeton or Stanford doesn’t mean giving up on a TT job.

Think about what else you want out of life besides a TT job. For instance, do you want to live in a particular place or type of place? A big part of why I gave up was that I really liked life in the city where I was a postdoc, and so did my wife, and she had a good job there. So I decided that, rather than moving again to continue chasing a TT job, I’d rather do something else so as to be able to stay in the same place (then Calgary called, changing the calculation). And of course, if you’re determined to live in a specific city or state, that’s going to make it difficult-to-impossible to get a TT job.

Learn about other options. You don’t want to keep chasing a TT job just because you have no idea what else to do, or because doing something else would seem like a scary leap into the unknown. We have a series of guest posts on non-academic careers for ecologists that might help. Starts here. But you don’t necessarily have to limit yourself to non-academic careers that will make use of your degree and skills in some obvious way. I know of a guy who left academic ecology to open a brewpub, and a commenter on an old post said that her backup plan was farming llamas. I suggest doing what I did: think about what you like about academia, and try to identify other careers that have those attributes.

Finally, regarding your odds of getting a TT job: ideally you want to estimate your odds. Not the odds of the average person. Different individuals can have very different odds, for all sorts of reasons. If you’re getting interviews, you’re competitive and your odds are reasonable. If you’re not getting interviews, ideally you want some information as to why not, so that you know how to improve your odds. Informal feedback from someone on the search committee is helpful (your supervisor may be able to get this for you, if he or she knows someone on the search committee). Comparing your cv to those of people who’ve recently been hired at the sort of place you would like to work can give you a rough sense of how you stack up, as long as you aren’t naive about it. (Thinking “Hey, I have X papers and didn’t even get interviewed for the job that John/Jane Doe got even though he/she only has X-3 papers! The search committee must’ve been full of biased morons!” is naive. See here and here if you want to know how faculty search committees actually work.) Asking your supervisor or some other experienced close colleague who knows you well and is familiar with the current job market to give you honest feedback is useful. But yes, if you’re an ecologist who is 5-6 years or more post-PhD, and you’re not getting interviews (phone interviews and/or on campus), your odds are probably pretty low and there’s a good chance they’re going to keep dropping.

Brian:  The first two questions are rather separate from the 3rd. When to give up on a project? It’s context dependent. If you’re early career and its not panning out, you may need to just optimal forage and move on to something you’re more certain will lead quickly to a paper. If its mid-late career and you’re convinced that you’re onto something even when its hard slogging and other’s don’t agree, well stick with it. That’s how a lot of Nobel prizes have been won. In short, if you can afford it, go with your scientific intuition about whether it is good/important work or not. If you’re early career you may need to be more pragmatic. But regardless of career stage, if you’re scientific intuition tells you it’s a loser, listen to that. Pursuing something further just because you already spent a lot of time on it is never a good idea – time is the main limiting resource for most scientists (of course that doesn’t mean you can’t ask yourself if you can’t get a quick paper but not killer paper out of what you’ve already done).

As for abandoning the pursuit of a tenure track job, that’s a tough one. Of course the ideal is you get good mentorship and guidance so that you don’t make this decision far down the road but are steered in alternative directions earlier. When that doesn’t happen, I think its a very tough decision. Jeremy is right that somewhere around the end of your 3rd postdoc, there starts being a stigma that will only compound the troubles. That said, I think being realistic about how far you’ve been making it into search processes is important. Actually being the one person to get a signed contract in a specific job on a specific campus has a lot of stochasticity. But making short lists, getting phone interviews, getting on-campus interviews are good signs. If those are happening with some regularity, then being persistent waiting for the right fit/stars aligning is rational (it becomes a bit of a lottery where you just have to play enough times). But if those things are not happening by your second postdoc (plus or minus one postdoc – i.e. that’s very approximate), then that is probably a strong signal. I think Jeremy’s reference to Terry McGlynn’s post is very relevant. And more generally, I think it is a question of how open you are. I hear people say they really want a tenure track job but then say they’ll only take a job in state X and at a research intensive university (or never at a research intensive university). That’s just not realistic in academia (unless you’re a superstar, and even then I don’t think its realistic, but might have a non-zero chance of happening). There are a lot of scoping questions to ask. Will you take a job anywhere in the US? Anywhere in the world? At any type of institution? or if not all types of institutions, then what types? This obviously has a big impact on how long you will have to wait/likelihood of getting a job. (Of course preferring a non-academic job if you can’t get an academic job in state X is a perfectly reasonable life choice – its just important to be realistic about how much you’ve upped the odds of “non-academic”).

So in summary, I think realistic assessments of whether you’re coming close or not (short lists, phone interviews, on campus interviews) and whether you’ve scoped yourself out of the job by where you don’t apply are two important questions to ask before deciding whether to look elsewhere.

Friday links: Bill Nye vs. Wayne Brady, Greek gods vs. salmon, and more

Also this week: make yourself happy in just five minutes per day, Japan vs. everything that’s not STEM, you suck at multitasking, Wildlife Photographer of the Year, and more.

From Meg:

On twitter this week, Auriel Fournier asked:

It was interesting for me to think about (I couldn’t think of anything automatically, though I suppose eating chocolate during that time would make me feel happy!) I liked reading through the replies. (Here’s the storified version.)

From Jeremy:

Ever wonder why organisms that ordinarily reproduce once and then die are called “semelparous”? Stephen Heard has the answer–and as he notes, once you hear the answer, you never forget it.

This week in Reports of Death That Were Greatly Exaggerated: in an old linkfest I lamented that the Oikos blog apparently was no more, while admitting that I don’t really read it these days. Actually, it just moved to a new URL a while back, and I failed to notice. Sorry for any confusion; my bad.

The Wildlife Photographer of the Year finalists are out. Jaw dropping stuff as always, many of the images are like nothing you’ve ever seen before. It’s my impression that many of the world’s very best nature photographers submit their very best stuff to this competition. I have fond memories of attending the exhibition of the winning images every year back when I was a postdoc in London. If I could somehow instantly acquire one skill I don’t currently have, it’d probably be the ability to take pictures like these.

The Japanese government just ordered every public university in the country to stop teaching humanities, social sciences, and law. Yes, really. Details and some critical commentary from the perspective of an economist who used to live in Japan here.

Is it ethical to sell complimentary copies of textbooks?

A leading social science journal will no longer consider submissions from authors who won’t review for them. Interesting policy. I wonder if the effect will be to incentivize reviews or disincentivize submissions. My own view is that authors should review in appropriate proportion to how much they submit, but that they owe this obligation to the field as a whole rather than to any particular journal. At least so long as they’re submitting to various journals rather than just to one journal. Related: here’s the data on how often thousands of individuals submit to, review for, and get asked to review for, the British Ecological Society’s journals.

Noah Smith on the modeling tradeoff between microscale and macroscale validity. The claim is that realistic modeling assumptions about microscale phenomena (e.g., about the behavior of individual organisms) lead to inability to fit macroscale data (e.g., macroecological patterns in species richness, composition, and abundance). Conversely, models that fit the macroscale data do so by making obviously-false microscale assumptions, justified (if at all) by saying that the macroscale world works “as if” those microscale assumptions were true. Smith suggests that this tradeoff isn’t universal, and only exists because of deep problems with a field’s entire approach to modeling. Actually it’s about economics, but it’s interesting to think about in an ecological context, which is why I suggested ecological examples.

If you want to try–probably futilely–to convince students to quit “multitasking” and pay attention to your lecture, you may want to point them to experiments showing that (i) nobody’s “good” at multitasking, and (ii) the people who think they’re best at it actually are worst at it. Note that I haven’t looked at the experiments themselves, so can’t vouch for them myself.

And finally: holy crap, Bill Nye can really move! :-)

Guest post: many American universities use score sheets to rank faculty job applicants

Note from Jeremy: this is a guest post from evolutionary ecologist Ruth Hufbauer. Thanks Ruth!


In helping a friend with some academic job applications, I recounted my experience on search committees. As it was eye opening to my friend, I thought it might be useful to others who are applying to academic jobs. The approach taken at my university is not taken everywhere, but my impression is that it is fairly common.

The excellent and thorough post written by Jeremy Fox a couple of years ago covers how search committees for tenure track positions work from start to finish in North America, particularly (given our fields) for Ecology/Biology positions. I will not reiterate what he wrote. It is a useful post even if you are not a biologist

My experience differs from him in how members of the search committee come up with a short list. At my R1 state school (Colorado State University, ~32,000 students, has a vet school, no med school), part of the process of conducting a search is creating a score sheet to rank applicants.

The job ad is critical because it provides the framework that the search committee uses to create the score sheet. Each of the minimum and preferred qualifications listed in the advertisement can be incorporated into the score sheet. If something is not in the ad at all, it cannot, per Office of Equal Opportunity regulations, be listed in the score sheet. That leads often to words being individually debated in writing the ad, as Fox noted in his post.

The upshot is that we do not have individualized rankings of candidates. The score sheet, like the example from an actual search linked to above, structures how the members of the search committee rate each candidate. The rating is done on a set scale that can be fairly coarse (e.g. out of 20 maximum) or it can attempt finder gradation (e.g. out of 100). Members of the committee score each candidate in each of the different areas: research, teaching, grant writing, postdoc experience, collegiality etc. These areas are often awarded different point values, according to what the position entails (e.g. a position with more teaching would allot more points toward evidence of teaching experience and ability). There can be heated debate on the search committee about what should be emphasized on the score sheet.

Using a set score sheet is not unique to my university. A colleague who is a chair at a major west coast research university system confirms that they use something similar there, and that they use it system wide across all disciplines.

For something like publications, the search committee typically takes time since PhD into account, and indeed, I have even seen committees create graphs of the productivity of the top 20 candidates by time since PhD (separated by first authored vs. total publications).

If a job attracts many applicants (e.g. >150) then often there will be a first cull of candidates who do not meet the minimum qualifications stated in the advertisement. This is typically done by just two members of the search committee. Not meeting the minimum qualifications can be things like not quite yet having a PhD, or having a PhD in an area different from that stipulated in the ad.

I haven’t personally served on a search that I would consider very large (with more than 200 minimally qualified applicants). In the last big search I was on (~90 applicants who met the minimum qualifications) every member of the search committee scored every single file.

The goal with this type of ranking system is to look at each applicant’s qualifications more objectively and holistically – not focusing solely on publications, and considering more completely what applicants bring to the table rather than, for example, their academic pedigree. It is by no means entirely successful in that effort, but it is a start. I find that it forces me, even when tired, to really evaluate each candidate in all the different areas, and not skip over aspects of an application.

A scoring system like this means, however, that applicants are reduced to a number on a spreadsheet. Major differences in individual scores given by members of the search committee are discussed in detail, but really only for the upper echelon of candidates. The majority of the applicant pool is not discussed. Only applications in the top ~10-20 are individually discussed. That group often is divided into a ranked list of potential interviewees, and a cut-off of people not acceptable to the department. The short list called for interviews is taken from the top 3 or top 5 (after discussions, during which some scores might have been adjusted if another member of the search committee points out something others hadn’t noticed). The upshot is that whether or not you make the top 20 is not at all a judgment of you personally. It is done by the numbers.

I’m curious –For those searching for an academic post – have you heard of this type of rating system before?

Among those who serve on search committees – Do you use this approach, or a more individualized/personalized ranking like at Jeremy Fox’s university?

Thanks to out to Josh Drew and Jeremy Fox whose suggestions and questions improved this post.

Ask us anything: absentee collaborators and prioritizing writing tasks

How do you deal with absentee collaborators/coauthors? (from Adam Stuckert, @PoisonEcology)

Brian: well every paper I write these days seems to have a physically remote co-author. I’m not sure if you’re asking about how to make this work? but I think I recall from the original comment/tweet that you’re asking more about people who are not being timely? The short answer is if matters enough to me I do the work and move on without them. If it doesn’t I stop investing time. This is of course much harder when you’re still a graduate student and the non-responsive person is e.g. a committee member. I ultimately though think you have to (and I do so advise my students stuck in this position) do the move-on without them. People lose their right to complain after a certain time window.

Jeremy: I’ve only once run into this issue in the context of a collaboration that was sufficiently formal and far along where it was a problem. So I’m not a great source of advice here.

In the context of working groups, I recommend doing everything on Brian’s checklist for successful working groups.

I’ve had several “exploratory” collaborations, as I call them. Where you toss around ideas with someone, and maybe even get so far as doing an easy, first-pass data analysis or something. But then you stop hearing from the other person. At which point I’ve always just moved on.

How do you allocate time to grant-writing vs. ms writing as a pre-tenure faculty member? (from Randa Jabbour, @randajab) Relatedly: When you have multiple mss to write, involving different sets of collaborators, how do you prioritize them? (from Margaret Kosmala)

Brian: this is of course the million dollar question. I tell students that the most important skill they need to learn to succeed as an academic is time management which is partly about efficiency but a lot about prioritizing correctly. For Randa’s question, I am sure I am being naive, but ultimately I think grants exist to make research resulting in papers possible. In short, papers are the legitimate end, grants are just a means. Now university administrators may have a different view. Of course in the real world, you have to have some success on both fronts. But in the end I put a higher priority on papers myself and I think most tenure committees do too. For Margaret’s question, I tend to prioritize mss that a) are the best science, and b) have collaborators who are prompt themselves. One of course has to be a little sensitive to political reality and not ignoring mss with collaborators much more senior than you. But in truth, collaborators much more senior than you are likely to have so many papers in the fire they’re not going to be particularly concerned or worried if you take longer.

Jeremy: Meg has a good post on this.

Day to day, I used to prioritize whatever I happened to feel like working on that day. That’s less viable now that I have more grad students and collaborators counting on me. I tend to prioritize what I think is the best stuff, and the stuff that’s already close to submission-ready. But really, I don’t usually have that many difficult choices to make. I don’t have so many students or collaborators that I have some huge list of projects all demanding some attention from me. I think if you find yourself in that situation, you need to ask if you’re overextending yourself.

I’m in Canada, where I can write one grant every 5 years to keep my lab going, so prioritizing papers vs. grants isn’t a choice I’m faced with.

Using our posts as course material? Please tell us just so we know.

A request: if you’re using our posts as course material, please let us know in the comments (what post, what college or university, what course). Not because you need our permission (you don’t), but just for our information. It helps us make the case to our employers and funding agencies that our blogging is worthwhile. Thanks!

If you’ve let us know about this in the past, you don’t need to tell us again.

Ask us anything: how do you celebrate good professional news?

What are your favorite ways to celebrate good news–papers published, grants funded, tenure received, etc.? What’s the most interesting such celebration you’ve ever heard of? (from Margaret Kosmala)

Jeremy: When I got my first paper accepted, I jumped as high as I could, punched the air, and shouted “YES!” This may have disturbed people in nearby offices. :-)

After Calgary hired me, I took out all the rejection letters I’d gotten for all the faculty positions I’d applied for, and ceremonially tore them up. (No, I don’t know what I’d have done with them had I never gotten a faculty position…)

I celebrate my graduate students’ successful thesis defenses with a tradition I stole from my own supervisor, Peter Morin. I buy two bottles of champagne, which get drunk at the post-defense celebration. The student then signs and dates both bottles, keeping one as a memento for themselves and leaving the other for me. I line them up on a shelf in my office. So far I only have a couple. Peter has a big shelf full, which looks super-cool.

A colleague of mine has students sign a deer skull after their successful thesis defenses.

Brian: In general, I think academics don’t celebrate often enough. Just for example, I encourage all my PhD students to actually go to graduation because its about the only time you ever slow down and appreciate what the major accomplishment you’ve made instead of focusing on the next to do.

Champagne bottles after defenses seems to be a very common theme.

For more minor things (e.g. paper acceptance), a little celebratory music is apropos (I lean classically so the Hallelujah Chorus or Beethoven’s Ode to Joy or such). Actually just taking time to take a break and go for a walk or treat yourself to a nice and slow lunch is not a bad idea.

Friday links: against quit lit, ecologist fired, syllabus easter egg, and more (UPDATED)

Also this week: a radically traditional publishing model, secrets of community college jobs, BAHfest, and more. Oh, and this week in Links of Interest Only to Jeremy: why the British are the way they are.

From Jeremy:

UPDATE: Just found this, didn’t want to wait until next week with it: Terry McGlynn of Small Pond Science fame is starting a podcast! He’ll be chatting with a colleague of his about scientific and non-scientific topics. I’m impressed with the ambition. Good luck with it, Terry!

Kansas State ecologist Joe Craine has been fired after alleging that colleagues misrepresented data in an Ecology paper. The university decided his accusations were “malicious, or at the very least frivolous”, and NSF denied his request for whistleblower status. Craine stands by his accusations, and says his dismissal was illegal. Newspaper articles here and here. I don’t know anyone involved, haven’t read the paper in question, don’t work on the topic, and have no other information besides what’s in the links. It sounds like a complicated and unusual situation, with some history behind it. So while I’m passing on the news, I don’t have any opinion on it, am not drawing any larger lessons from it, and do not consider it an illustration of any broader problem, trend, or phenomenon. (ht Retraction Watch)

A rant against academic quit lit. I agree that these pieces ultimately are just reporting people’s purely personal career decisions. But I disagree that that’s useless; it’s useful to the extent that others happen to find it useful, just as with sharing any anecdotal personal experience that others might find useful. I agree that the authors of some (not all) quit lit pieces overgeneralize from their own preferences and experiences, and seem to want credit for recognizing some deep flaw in academia that everyone else can’t or won’t recognize. Meg and I both nearly quit academic science. I hope we both made clear that we were merely sharing our own personal experiences. And I don’t think the prevalence of academic quit lit says anything special about academia–that it’s uniquely good at sucking in idealists and then crushing their ideals or whatever. Academics aren’t uniquely prone to writing quit lit. Every profession or even hobby that people want to join has its share of quit lit. There’s quit lit about baseball, finance, elementary school teaching, football, football fandom, acting, organic farming, the military, basketball, the Congressional Research Service, baristas, foreign language teaching (that person quit to become a barista), management consulting, medicine, dentistry, painting, dancing, private accounting, public accounting, programming, the Mafia, the US Senate, orchestra (that person quit to become an academic), tv show hosting…Basically, some people who quit any profession or hobby they once wanted to join will feel the urge to publicly explain their choice. The only activities that don’t have quit lit are the ones nobody wants to do in the first place (“I used to love filing my taxes. Here’s why I quit doing it…”)

Three things you might not have realized about a career teaching at a community college. Items #1 and #3 are “the pay and benefits might well be better than at an R1 university” and “the teaching load often isn’t insanely high”. Written by an English prof, so I’m not sure if #2 on her list (“you can still do research”) applies in the sciences. And I think #1 only applies to people with some sort of permanent or long-term full-time contract, not people hired to teach a single course on a one-time basis. Hopefully some of you can comment on this.

Via a commenter, news of an arXiv overlay journal. Basically, it’s a totally traditional selective peer reviewed journal, except it takes advantage of arXiv hosting of the articles to bring the costs of publishing and reading down to near-zero. This is the kind of publishing experiment I tend to like: narrowly targeted to solve one specific problem. It’ll only work for fields that already make heavy use of arXiv or a similar service, of course, and in which many people still like to filter the literature in a traditional way. Curious what others think of this. In particular, I’m curious to hear what strong advocates of wide-ranging, revolutionary publishing reform think. Because this journal does something revolutionaries want (free publishing for authors and readers), but also uses and thus helps entrench some practices they want to get rid of.

Philosopher Deborah Mayo defends Karl Popper’s views on how to distinguish science from pseudoscience (or stronger science from weaker science, I’d add). Worth reading both as a corrective to oversimplified, n-th hand cartoon versions of Popper, and because the issues raised are still live in ecology. For instance, see this recent exchange of comments between Brian, Mark Vellend, and I on “pattern hunting” research approaches in ecology (starts about here), or this old comment from Jim Grace on searching for evidence for one’s ideas with a broad vs. narrow-beam “searchlight”. And for readers of a more philosophical bent interested in the “demarcation problem” of separating science and pseudoscience, see this old post.

I’m kind of glad I’m not at a big US university, so that I don’t have to worry about this kind of thing.

A novel way to check if your students read the syllabus: hide an easter egg in it. :-) I’m totally doing this next term. And I’m giving bonus marks for finding it.

BAHFest is coming! A hilarious and biting example of what to expect. Watch that video if you’ve never seen it–it’s one of the funniest and sharpest things I’ve ever seen.

And finally, the British, explained. :-)