Ask us anything, and we’ll answer!

Here it is again: ask us anything, and we’ll answer!

Got a question about ecology, academia, bird poop, or anything else we blog about? Ask us! Past questions have ranged from the statistical techniques every ecologist needs to know, to how to transition from postdoc to PI, to how much time we spend reading the literature, to how we’d fix the entire scientific funding system.

Submit your questions in the comments on this post, or tweet them to @DynamicEcology. You have a week to submit questions. Ask as many questions as you like. We’ll compile them and answer them in future posts just as soon as we get the chance.* Meg even promises to try to answer this time!**

*Patience is a virtue. 🙂

**Though to be sure of that, I recommend baiting her with questions about hippo-sized Daphnia. Or Daphnia-sized hippos, whichever.

29 thoughts on “Ask us anything, and we’ll answer!

  1. What is and what is not a scientific hypothesis beyond a educated guess and which the preferable way to ask the question ? how, what, if … else .

  2. How do you help undergraduate researchers in your lab learn how to analyze data from independent research projects? This is particularly challenging when students have not taken a single statistics course, and these challenges involve both the conceptual aspect of understanding the statistics and the software aspect of learning how to use a particular stats package.

  3. How can ecologists build up their theoretical chops? Or, more specifically, what would you recommend for early-career ecologists (grad students, post-docs) with applied orientations and somewhat limited mathematical background, but interest in making use of ecological theory in their work? Courses, books, papers, exercises, etc. To what degree do you think building up one’s theoretical background should be subdiscipline-specific v. more generalized across ecology/biology/environmental science?

    • I can give you a short answer to that right now: Ted Case’s Illustrated Guide to Theoretical Ecology. It won’t teach you anything with a specifically applied bent. But if your goal is to learn the very basics of theoretical ecology, and your math background doesn’t go beyond mostly-forgotten first year undergrad calculus, Case’s book is for you. Totally unique graphical approach to the subject.

    • The short answer for me is that there’s nothing I feel like writing about but don’t because it wouldn’t be a good fit for this blog. I don’t have any urge to write about, say, European politics, or fantasy novels, or stuff from my personal life, or my own research, or etc.

      There are topics that would fit in on this blog, but that we avoid writing about. We tend not to rush out posts on whatever controversy is currently consuming the attention of the entire science blogosphere/Twittersphere. Tim Hunt or whatever. That’s because we usually don’t have anything to say that others aren’t saying already. Instead, we usually just wait until the next linkfest and post a few links to any pieces others have written that we thought were particularly good. Hopefully we add a little bit of value to the conversation that way (likely only a little bit). Or sometimes we’ll just ignore the controversy entirely; we don’t feel like we *have* to chime in on whatever the rest of the science blogosphere is talking about.

      Personally, I also avoid posting on whatever controversy is currently firing up the Twitterverse because I find really heated, largely Twitter-based arguments to be mostly unproductive. Even if I had something to say that I didn’t think anyone else was saying, I probably wouldn’t bother to say it, at least not until after the furor had died down.

      Similarly, I personally avoid posting on topics on which I think it’s hard to have a productive conversation because a critical mass of people have strongly held views. For instance (and this is just one example of several), I don’t post much on open access publishing for that reason. I just don’t feel like getting into an argument with the open access evangelists, there’d be no point. It’s not that I’d be worried that they could hurt my career or anything like that. It just wouldn’t be an enjoyable and productive use of my time.

      • It’s a shame about the evangelizing re open access or open science in general (on both or all sides of that debate). Especially when most people can see that it could be a good thing in general even if the downsides right now worry them. There are lots of ways to be more open, as a recent paper in Ecosphere shows. Being able to have those sorts of discussions/advice posts would certainly be of benefit to many people, especially grad students and post-docs caught between the Open Access / Open Science drive and the realities of the job market. But you’re right; such a post would need careful moderation to avoid dogma from all corners of the debate.

      • In fairness, when I have blogged about related topics in the past, our comment threads and the wider reaction on social media mostly have pleasantly surprised me by being thoughtful (e.g., this piece on how I decide where to submit my mss: But all it takes is a few bad reactions to ruin a comment thread (and one’s morning). So I sometimes find myself torn between relying on the demonstrated awesomeness of our commenters, and not wanting to overrely on that awesomeness for fear of destroying it. To some unknown extent, the awesomeness of our commenters presumably reflects our choices as to what topics to post on, and what topics to avoid. Our comment threads might deteriorate (or at least become much more work to moderate) if we regularly started posting on topics that too many people find it hard to discuss civilly and intelligently.

        My partial solution is to tread lightly around certain hot button topics. For instance, by linking to pieces that deal with the topic or a tangentially-related topic. Our linkfest posts get relatively few pageviews and few comments, and only a few dozen people at most will click any given link. So it’s a way for me to make my views on hot button topics known (or at least hint at my views), without taking much risk that someone will decide to flame me.

        The other thing we do is just try to anticipate when a post might upset some people, and write it carefully. As opposed to deliberately provocatively. Usually, when we do this we’re pleasantly surprised by the reaction of whoever we were worried about upsetting. But even that’s work. So if I don’t care enough about the topic to put in the effort required to write a carefully worded, thoroughly-researched post, I just don’t bother.

        And of course, once in a very great while we just get shocked that somebody finds something we’ve written seriously upsetting. Something we hadn’t thought twice about because it seemed totally innocuous. There’s some very low but non-zero probability that *anything* you write could seriously upset *somebody*. That risk just goes with the blogging territory and there’s nothing you can do about it.

  4. I think you’ve written about some of these questions, at least tangentially, in the past, but I’ll ask anyway.

    1) When do you think it’s appropriate to abandon an avenue of research? Is it never appropriate? Sometimes appropriate? By avenue of research, it could be something as small as abandoning a particular experimental design (i.e., data collection scheme, statistical test), or possibly giving up on trying to test a hypothesis entirely. Is there a point of no-return in the academic process where you should commit to finishing a project regardless of whether the preliminary results seem lackluster?

    2) As a follow-up. If it is sometimes appropriate to stop a project, and you decide to do so, what’s the best way to break it to co-authors or colleagues? How should you handle pressure from colleagues to continue a project you no longer believe is viable/interesting? (I’m thinking more from a non-student perspective here, but I think students might be interested in this issue as well).

    3) In a thematically related, but different question. Is there a time when you should consider abandoning the hunt for a T-T position? What career indicators (pub rates, years of unemployment, etc.) would be a warning sign that obtaining a T-T is improbable. I ask because the article below had an interesting statistic that the probability of obtaining a T-T decreases steadily every year to less than <1% after ten years.

  5. Hi Jeremy, Brian and Meg, here’s one that’s a little more frivolous – it’s a variation on the question fiction writers get

    Would you rather,

    1. Be very successful in your own time (i.e.lots of funding, lots of grad students, lots of publications) and all the things that go with that (e.g. jobs at big prestigious universities, more money, invites to plenary lectures in exotic places) but have little or no lasting impact on your field.


    2. Get relatively little recognition in your life (scrape for funding, few grad students, publications that get little notice or acclaim) but have a lasting impact on your discipline that is only recognised after your passing.

    Best, Jeff.

  6. When seeking specific ecosystem services or assessing functional diversity, is it worthwhile to consider traits that might slip under the radar of genomics? I.e., how important is it from the standpoint of theory that mammals can have blue skin despite not having the genetic machinery to produce blue pigments, that diatoms and nudibranchs can turn toxic or green via kleptoplasty, and that lichens can synthesize antioxidants and UV-resistant compounds that are orders of magnitude more effective than those of either of their constituent species?

  7. You hypothesize that factors A and B affect response variable C. However, you have no solid reason – but maybe a suspicion – that A and B interact to affect C. It is conceivable that the two interact and if they did interact it would be an amazing discovery. Do you test for an interaction even if it wasn’t part of your a priori hypothesis? If yes, how would you frame the test for the interaction in the introduction section of your paper?

    • I can give you a short answer now: the key thing is that whatever choice you make not compromise your error probabilities.

      For instance, if you eyeball the data, see what appears to be an interaction between factors A and B, and so then decide to test the null hypothesis that there’s no interaction between factors A and B, that’s not legit. It’s circular reasoning–you’re letting the data tell you what hypothesis to test, and then testing that hypothesis on the same data. It jacks your type I error rate up above the desired level.

      As an aside (or maybe it’s actually directly relevant rather than an aside…), I’m not a fan of speaking of statistical interactions between factors as if they were scientific hypotheses. “Factors A and B will have a significant interaction term in my statistical model” isn’t a scientific hypothesis in my book, and a statistical interaction term on its own never constitutes an amazing discovery. For instance, whether or not two variables have a statistical interaction totally depends on the measurement scale of the results (e.g., did you log-transform your data). That’s very much in contrast to some sort of mechanistic, process-based hypothesis about how two factors will or won’t “interact”, which is a proper scientific hypothesis. I have an old post on this (scroll to the end):

  8. When you have multiple manuscripts to write — that have come from collaborations with different sets of people — how do you allocate your writing time? (Possibilities that occur to me include: prioritizing the naggingest co-authors, prioritizing the MS with the biggest potential science impact, prioritizing the MS that will be fastest to finish and get off the desk. Others?)

  9. Here’s another one — more “just for fun”: What are your favorite ways to celebrate good news — papers published, grants funded, tenure received, etc.? What is the most interesting celebration you’ve heard of for such professional accomplishments?

    • Ooh, fun one!

      A quick answer: when I got my first paper accepted, I jumped in the air, punched my fist, and shouted “YES!”

      My lab celebrates successful defenses with a tradition I borrowed from my supervisor. I buy two bottles of champagne, which get drunk at the celebration. Then the student signs and dates them, keeps one bottle, and leaves the other for me. I line them up on a shelf in my office. 🙂

  10. Now there is race to publsh more paper but at faster pace. we have seen peple have attitude to publish anything anyhow. And, there are journals which will publish whatever comes (we have some evidences already). What do you think, does it leads to progress in science or creates more chaos?

  11. Maybe I’m 6 months too late for Ask us Anything, but if you are still accepting questions …??….

    How much detail do journal editors prefer in Response to Reviewers documents? Is it ok to frequently refer to line numbers and allow the editor to go to the paper to check that you have done as suggested? Or do editors prefer to be able to read the response document without necessarily needing to cross reference to the text?

    For example: Reviewer: Rewrite L10-19 incorporating ecological theory.
    OR: Reviewer: I disagree with your argument ….. and suggest that ….. is more plausable.

    Is the following sort of response preferred? “This section has been rewritten as suggested (L12-28).”

    Or is it better to quote the entire text of the recrafted section in the Response document? Or something in between?

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