What do you most think you should know but don’t?

I recently attended an event related to graduate student mental health. One point of emphasis was imposter syndrome (something I’ve blogged about before), and one thing the presenter stated was that it’s important to remind ourselves that it’s okay not to know what we’re doing. As a strategy for doing that, he suggested listing what you most think you should know but don’t. I thought this was an interesting idea, and thought it would be interesting to think about this question in three different areas:

  1. a specific area of ecology
  2. something that relates to my professional life but isn’t a content-related thing, and
  3. something outside my professional life.

I then wrote Brian & Jeremy who were on board with thinking about those questions, too, leading to this post. Read on to see what we think we should know but don’t, and please tell us what your responses are in the comments!1. What we most think we should know but don’t about a specific area of ecology

Meghan: various specific statistical approaches (but maybe this isn’t an area of ecology?). I feel like I should know so much more than I do. To give one recent embarrassing example, I had to look up last week to understand whether it really made sense to have treatments with overlapping 95% CIs but statistically significant differences.

That’s more stats than ecology, though. I guess maybe, within ecology, I would say that I feel like I should be able to better evaluate some of the back-and-forths in the literature related to biodiversity loss and its consequences.

Jeremy: I’m going to have to improve my knowledge of some topics when I teach graduate biostats for the first time. Hierarchical mixed effects models, planned contrasts, nonparametric smoothing…I do know something about these topics, but I don’t have the deep, in-your-bones familiarity needed to teach them really well. For a more ecology-specific topic, I need to get to grips with modern coexistence theory. I feel like I have a good grasp of the fundamentals, but I want to know more about the nuances and technical details so that I feel confident doing coexistence research. I also need to better understand the mathematical theory of synchronization, both within and outside ecology.

Brian: population ecology (I was up on it during my graduate career but have drifted away and have come back just enough to know lots of cool new things have happened) or disease ecology (never really engaged in the topic beyond Anderson-May SIR models but know it has gotten to be a huge and interesting and important field)

2. What we most think we should know but don’t about something that relates to our professional lives but that isn’t a content-related thing

Meghan: I have a couple of ideas for this one: a) how to have difficult conversations. This is one reason I’ve been reading Crucial Conversations! And, b) how to not take criticism personally. I am so variable in this — sometimes really tough criticisms don’t bother me, but other times even very gently worded things that suggest maybe I didn’t do something optimally send me into a tailspin.

Jeremy: How to write a book. I’d also like to improve on writing up papers quickly. How to budget my time more effectively and be more efficient, so work doesn’t expand into times I don’t want to be working.

Brian: Looking for a next career step beyond publishing more papers to have a different/bigger impact on science and society – pretty sure department chair is not it

3. What we most think we should know but don’t about something outside our professional lives

Meghan: Something that’s intermediate between 2&3 is how to make my brain turn off from work. More solidly into 3 territory, I am having a tough call deciding between a) how to identify birds & plants (I’ve improved very slowly over the years, but am nowhere near where I’d like to be), and b) how to speak another language.

Jeremy: “Learn to garden better” would probably be one of my picks for #3. Right now my procedure is basically “buy plants, plant them, if they die that means they were weak and deserved to die. Repeat.”

Brian: How to thrive in an emptying nest (first kid off to college in the fall, 2nd in 4 years) – presumably time to pick up old hobbies etc but it feels a little overwhelming to start reinventing life after 18 very busy but very fun years spent primarily as a parent (and yes I know parenting is never over, but it sure changes)

 

What about you? What would be your answers for:

  1. What you most think you should know but don’t about a specific area of ecology
  2. What you most think you should know but don’t about something that relates to your professional life but isn’t a content-related thing, and
  3. What you most think you should know but don’t about something outside your professional life?

Tell us in the comments!

13 thoughts on “What do you most think you should know but don’t?

  1. Very interesting post!
    1: Mathematical details of and mathematical reasoning behind classical statistical tests. I know what these tests are used to, how to use them, their assumptions, and the general logic behind them, but teaching stats to biology undergrads and not knowing the math is weird. Even though most biology students don’t care about the math. Also calculus and how to do GIS stuff. More into ecology, a better understanding of current population and community ecology theories.

    2. How my university works! I still don’t understand the organizational structure and the many regulations, and I probably should.

    3. How not to check my email doing rest hours! Also, how to do laundry by hand 🙂

    • Re your #2: I recently went to an event that was for people who had recently been promoted to full professor. They included a session on how money flows through the university. When I saw it on the schedule, I wasn’t sure what I’d think of it, but it was really interesting and I found myself applying some of the info I’d learned in a meeting the next day!

  2. 1. ecological statistics more and more of it…..it seems that it is never enough
    2. quantitative decision making and risk analysis
    3. how not to yell when anger is exceeding my limits……

  3. I love this post because I was embarking on a similar exercise of self-reflection this past weekend. I realized I often lament being ignorant in certain areas but rarely do anything to correct it, which is kind of a fixed mindset mode. I’m not an ecologist, but I definitely identify with needing to be more knowledgeable with statistics…and I’ve started seeking out some resources to improve. Professionally, as much as I’ve presented, I’ve never felt good at off-the-cuff speaking, so I’d like to improve on that front. And personally, my knowledge of history is abysmal, so again, I’m working on identifying some resources to fill in the gaps in my education. Thanks for this, Meg!

    • A great way to catch up on history is to listen to books while driving. 86 the stressful radio news! I’m listening to one right now on the Mongolian Empire.

      Ooo! Charle’s Mann’s book “1491…Americas before Columbus”. Must “read”. 🙂 Much deeper dive into pre-Columbian American cultures than Jared Diamond.

      Tons of great books very well read on history.

  4. 1. How “experimental biology” (i.e. bench science/cell biology/microbiology) is actually done. It’s very hard to evaluate the reproducibility of the results because results are generally presented as a clean series of logical experiments although I get the sense that this presentation is highly cleansed and there were a lot of dead-ends. (Not ecology, but related – that is, how is science done in ecology/evolution, which is my training, vs. “experimental biology”).
    2. how to mentor
    3. What Meghan said: how to make my brain turn off from work. Everything else that I’d like to learn how to do (furniture making, natural historying, backcountry skiing) would then follow

    Also, Meghan – a problem with trying to infer anything from a plot of means and SEs/CIs, is that one has to mentally compute effects and uncertainty. Many of us were trained mentally double the SE and see if it overlaps another group’s mean. This only works as a rule of thumb in the cleanest and simplest of experiments. What we really want to communicate is the effects and their uncertainty – show the model! — see here: https://www.biorxiv.org/content/10.1101/458182v2

  5. Re writing a book: “There is nothing to writing. All you do is sit down at a typewriter and bleed” —
    Ernest Hemingway.
    What I wish I knew?
    Matrix algebra; then I’d be able to explain statistical tests to my undergrads a lot more clearly. I also wish I could just look at the results of a mixed effects model and instantly see what the coefficients all mean without having to go back to Pinheiro and Bates.

    I also wish I knew more porgramming languages. I use R, but R is pretty limited if you want to write, say, a mechanistic model.

    • “sit down at a typewriter and bleed”

      I think for many academics the ‘sit down at a typewriter” part is harder than the bleed part.

  6. Interesting post and discussion. The next question is: what do you do once you’ve identified something you should know but don’t? Is it obvious that one should go ahead and learn more about that thing? Or might one more fruitfully accept their strengths and weaknesses, play to their strengths and seek out help when facing areas of weakness? I think about this in terms of the various statistical and quantitative things that seem likely to be high on many people’s list for category 1 (including mine). If one has collaborators with complementary skills, I can imagine reducing stress (constantly wishing one can “do it all”) by scratching some things from the “should know” list and accept a certain degree of specialization. Or maybe not. Just thinking out loud…

    • Good question.

      I definitely don’t just want to “know more stats”. The specific stats I want to know better, I have to know better because I have to teach them (and I have to teach them because the students in the course will be using them). But when my collaborators have the relevant expertise (as with Dave Vasseur, who knows wavelets), I lean on them.

      I tend to think of myself as someone who mostly plays to his strengths and has been slower than the typical ecologist to pick up new things, whether that’s new technical skills, or learning a second study system, or learning new pedagogical approaches. If you asked me to name my biggest limitations as a scientist, “inability and/or hesitancy to branch out and really learn something really new to me” would be high on the list. But on reflection, I don’t actually know much about how often/well/easily other ecologists learn new things (say, post-postdoc).

      • One thing that becomes really clear when I do my back-to-back-to-back meetings with lab folks on Mondays is the breadth the questions and techniques that people in my lab are working on & using. Physiology, population genetics, population & community ecology, evolutionary ecology, behavioral ecology, ecosystem ecology, evolutionary biology, mathematical modeling, chemical ecology. I frequently find myself at the limits of my knowledge of a subdiscipline, but that’s why I do a lot of collaborating!

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