On my last evening at the Evolution meeting this year, I was once again wandering around alone when I bumped into a group of people who were chatting outside the poster tent. Earlier in the day, I had attended a talk given by one of them, and was once again really impressed by his work. The questions are really cool and the work is really well done. While sitting in the audience listening to his talk, I started to think “Man, I wish I worked on that system.” So, when I saw him at the poster session, I jokingly told him that I wanted to be his postdoc. And he said “Really? But I want to be yours!” which totally surprised me. It turns out we both had system envy.
As we talked about things more, it became clear that part of the reason for this is that, when you just see the polished talk showing the most exciting results, it’s easy to overlook all the effort that went into collecting those data, including all the failed experiments. There will always be times when you do an experiment and, for whatever reason, all the animals die right away, or no one gets infected, or everyone gets infected, or something similarly frustrating. For example, for the study that I presented at Evolution, I didn’t mention that we had to do it three times to get useful data. We were trying to characterize logistic growth of two parasites, but we missed the inflection point the first two times we did the experiment. Those “failed” experiments helped us figure out a better design for our final experiment (especially when we needed to kill animals to count spores), but it was an awful lot of work to yield no publishable data! (I should emphasize that when I say “worked”, I do not mean “got significant results”. I mean “got reliable data” – meaning, we didn’t have lots of animals die inexplicably or something like that.) And these are just the fluke things. There are the additional frustrations of establishing a new study system (figuring out how to culture things is incredibly time consuming) and a new lab (we lost an entire semester worth of work in my lab at Georgia Tech because someone had used a copper coupler on the deionized water line feeding the dishwasher – we couldn’t see it and it took a long time for us to figure out the source of the massive Daphnia death in the lab).
So, I suppose it makes sense – given that we do not include those failed attempts in our talks – that it’s easy to have a certain degree of system envy at these meetings. Perhaps if we had #overlyhonestmethods in our talks, it would help avoid this!
It does raise the question of whether I might ever switch to another system. While at Georgia Tech, I spent several years trying to set up a rotifer-parasite system. It had a lot of promise, in my opinion, but I just couldn’t get infections to work reliably enough in the lab to be willing to start working on it in a big way. And my motivation for trying to get that system set up was because there were infections in a local population, which I could use for dynamical studies. Now that I’m back in the Midwest, near good populations of my Daphnia system, I see no reason to try to work on another system. We already have more than a career’s worth of questions to address with this system, so why switch? (Besides, then I’d have to come up with a new avatar.)
Have you made a big switch in study system? If not, is it something you consider? And do you sometimes have system envy?
Dynamic Ecology 
As an artist who has worked as a lab tech in multiple science labs for a decade, I have had the advantage of getting to switch systems, not entirely upon a whim, but every few years I can sort of indulge my wandering curiosity. In that way, being a tech is more liberating than being a PI. But even more than that, I’ve gotten to observe science as a kind of outsider, since I was not formally trained in it (I was formally trained in the arts).
One of the things I’ve noticed is that the way scientists are required to present their results is very linear and tidy: We knew this background A, so we were curious about this hypothesis B, so we employed the following methods C, then we got these results D, and here is our discussion about its relevance and suggestions for further work. Tidy. But what scientist in the world, in a candid discussion at a cocktail party with their own lab members, would tell the story that way?
Here’s how it really happened: Well, we set out to find out X but the grad student overslept and missed their time points, so the stuff didn’t get frozen but we noticed, Y, and said … huh… THAT’s ODD… what if we do Z instead… so then we collected a bunch of data and realized there wasn’t really a story there, but the story was really LMNOP which isn’t as pretty but it’s more complex and really kind of cool so now we’re on this whole LMNOP track.
I have been to a lot of talks in the sciences, mostly life sciences, because I’m a biology groupie, an EEB groupie to be precise. I have also been to a lot of talks by serious artists working in many media. What’s interesting is that people in the arts RELISH those stories, those meandering, serendipitous, if-we-knew-what-we-were-doing-they-wouldn’t-call-it-art stories. Artists are allowed to have random, intuitive, not necessarily planned, non-linear paths. Why are scientists expected to package their work as if it was planned-that-way, even though every other scientist knows that’s not the way the story goes?
I find this immensely irritating. Why does this matter? Because if scientists continue to posture as if they are in total control of the process, and continue to paint this very linear and orderly picture, it sacres away young people who might aspire to work in the sciences. Young people who look at science from the outside, who know anything about reality, might notice, “Wow, my life never works like that, I’d better stay away.” I sure did. If I had known as a young woman that the doing of science is messy, uncertain, and full of interesting accidents, I might have ended up running a lab instead of a studio.
System envy, indeed. I have DISCIPLINE envy. But in the end, it’s all the same. We are trying to find out about the world, chewing little meandering trails that get bigger as we grow, just like leaf miners. My trail doesn’t look like yours, but they’re all cool. Chomp, chomp…..
What a fantastic comment! Thanks, Nancy!
I agree that the way we talk about our work is misleading, and that this might scare off some students. My fabulous technician at Georgia Tech first started working in my lab as an undergrad. She was the first or second person in the lab to try to work on the new rotifer system. Things didn’t work at first, as is inevitably the case. One day, she said something to my postdoc about how it didn’t seem like real science, because nothing was working. My postdoc pointed out that, if things always work, it’s not science. But this student had received the message that things are always neat and tidy in science.
Actually, this also reminds me that I had in mind another “story behind the paper” post, about an Oecologia paper of mine. This paper was downloaded a huge number of times from my website, and I couldn’t figure out why. But then I had people start telling me that they assign it in their classes because it’s an example of a failed experiment that got published. And, to be honest, the only reason I wrote it up as a failed experiment that then also showed something interesting is because it was so completely obvious that the experiment was designed for the original question. I should get to writing that post, I guess!
Your comments remind me of a recent Malcolm Gladwell piece in the New Yorker about an economic planner who “saw virtue in the fact that nothing went as planned” (http://www.newyorker.com/arts/critics/books/2013/06/24/130624crbo_books_gladwell)
I’d like to think that scientists give linear talks because these are easier for an audience to follow and absorb, and not just out of convention. But I don’t know if that is true…
Yes, I agree that ease of following is at least part of the reason for how scientists give talks. It’s hard to follow a talk that has lots of unexpected plot twists. But it does seem like a downside of that effect is that it makes science seem so much neater and tidier than it is — which is presumably part of why people (including myself) enjoyed the #overlyhonestmethods hashtag so much.
Great comment Nancy. In response, I’d say more or less the same thing Meg and Peter said: I think we present our results as stories that have a nice logical flow because it’s easier for the audience to follow.
I agree that that can give the audience a distorted view of the actual scientific process. But at least when scientists are giving presentations to their fellow scientists (say, at scientific conferences), I think the attitude is that everybody knows the scientific process isn’t a neat, tidy linear narrative. So it does no harm to gloss over that fact and just present a cleaned-up version of one’s work that omits all the false starts, failures, and blind alleys.
One nice thing about the rise of blogging is that many scientists use it as a forum to talk about the false starts, failures, and blind alleys that they don’t feel they can talk about in their papers or their formal presentations.
One other thing: I think sometimes the desire to present our results as neat, tidy stories can actually distort not just our presentation of the scientific process, but the actual process itself. That is, it can cause us to make real scientific mistakes. For instance, scientists do often write papers in which data that were originally collected for one purpose are used for some other purpose, without the original purpose of the study ever being mentioned. Such studies often arise because the experiment failed for its original purpose, but seemed to throw up some other interesting-looking pattern. That opportunistic approach–changing your question post hoc, based on how the data happened to come out–runs a high risk of leading you to make serious mistakes. If you’re not very careful, it’s very easy to mistake noise for signal in this context. Letting the data tell you what questions to ask, and then trying to answer those questions by running formal statistical tests *on the same data*, seriously inflates your risk of drawing mistaken conclusions.
Now that I think of it, for my talk last year at the ESA meeting I told a story that included a significant detour in the middle. I suppose I could’ve glossed over it and told a linear story. But it seemed both more interesting, and more honest, to tell the story with a detour. And I was confident I could do so without confusing the audience. But yeah, when it comes time to write the paper I’ll probably frame it in such a way that there’s no unexpected detour in the middle.
Now that y’all have the ‘comments elevated to be part of a post’ feature, this has got to be one of them.
Way ahead of you; it’s already plugged in the forthcoming Friday linkfest. 🙂
I had extreme aquatic envy when I was a grad student. Being able to go from phytoplankton to piscivorous fish is really powerful for asking community/ecosystem questions. Doing cool manipulations on wolves (for example) and monitoring ecosystem responses is logistically (and probably legally) problematic. I was going to apply to some aquatic labs for a postdoc, but my adviser pointed out that my water phobia would probably interfere with my field work. He was right (as usual). I would have been miserable.
Ha! Yeah, that would be a problem. I spent a semester working in Antarctica between college and grad school. One of the women I was working with had been planning on being an oceanographer, but discovered on the cruise that she gets extremely sea sick (as in, almost needing to be medevaced out because she was so ill). I felt so bad for her, since it seemed clear that oceanography was not in the cards for her.
I don’t know that anyone who doesn’t work in microcosms envies them, exactly, in the sense of wishing they worked in the system. But I do think there’s a perception that microcosm experiments always come out the way you expect, or the way simple theory would predict, and that they never fail. And I can appreciate where that perception comes from. You’re in a lab, working with really simple organisms under highly controlled conditions, there’s no weather or anything–what could go wrong? But the perhaps surprising answer is “lots of things”! As you say, failures in any system are mostly invisible to people who don’t work in that system, and microcosms are no exception. I’ve talked about this a bit in an old post:
https://dynamicecology.wordpress.com/2011/06/10/objections-to-microcosms-in-ecology-and-their-answers/
Like you, one source of the many failures I’ve had over the years was problems with the water supply to the lab. Protists are finicky about their water too. That’s why I now get all my water from a ground-fed spring in a provincial park. And it’s why some other protist microcosm folks buy pallets of commercial spring water.
Yes, I do have system envy. I envy your Daphnia disease work, it seems like it’s right in the sweet spot of “complicated enough story to be really rich and interesting, but simple enough story to be tractable and general”. Like everyone, I envy Rich Lenski’s long term E. coli evolution work. I envy the Pseudomonas adaptive radiation folks (and I’ve dipped my toe in that system, though not yet enough to have anything publishable). I envy various things Andy Hector has done or led. I envy the Ellner-Hairston eco-evolutionary dynamics work. I envy Desharnais and Constantino’s flour beetle dynamics work. And lots of others.
I don’t know if I’ll ever switch systems myself. My approach so far has been to work in my own system but let my students mostly work in other systems, which means I get to dip a toe in other systems without having to fully commit to them. But I suppose there might come a time when some of my students’ work pans out so well that I decide to switch to their system.
Ugh, I tried commercial spring water. My Daphnia really hated that. Water problems are a pain, aren’t they?
It’s funny, because the species of Daphnia that I work on the most, Daphnia dentifera, hasn’t been worked on a lot because it’s relatively difficult to culture. But culturing it became much more feasible when someone discovered that adding a surfactant (cetyl alcohol) to the beakers helps them avoid beaching themselves in the surface film. But, still, they’re very finicky, and we had a hard time getting them happy in Georgia.
I do somewhat envy microcosm work for the elegance of experiments that can be done with them. But I do really like being able to pair my lab experiments with field observational studies, and you’re right that Daphnia might be in a sweet spot there.
And, yeah, I’m pretty sure everyone is blown away by Rich’s long term evolution experiment!
Wait, your Daphnia *get stuck in the surface film*? So basically, *their own habitat is fatal to them*?! 🙂
Perhaps you should switch to working on an aquatic organism that doesn’t suck at living in water. 🙂
Ha! I like to view them as tiny little whales who get confused and beach themselves. 🙂
I’ve switched primary systems a few times: deer during my PhD to spiders as a postdoc and now to skunks as a professor. Each time requires large quantities of activation energy. Also, when you switch systems, you learn the pros and cons of each and also where your scientific “heart” truly rests. While spiders were easy to get and easy to work with and manipulate in the lab, I couldn’t answer the questions I really wanted to ask and I just didn’t find the experience as satisfying or “cool” as working on mammals. Now I’m moving into a system I’ve been drooling over for years and it’s got me excited about all of the cool things I can do. So as a person who has learned that the grass isn’t always greener, I would advise people to stick with what they ENJOY working on and provides enough brain candy to keep your research going. My PhD advisor always encouraged me to take the approach that research should feel like you are playing – do the work that makes you happy and satisfies the curiosity that led you into this career in the first place.
Yeah, certainly if research stops being enjoyable in general, then it would be time for a new system! I feel very lucky that I love being on lakes, and that lake systems are very well-suited to the sorts of questions that interest me.
You’re in good company. Peter Medawar (Nobel Prize for discovery of acquired immune tolerance) once published a paper called “Is the scientific paper a fraud?” [http://www.albany.edu/~scifraud/data/sci_fraud_2927.html]. Answer:
“The scientific paper in its orthodox form does embody a
totally mistaken conception, even a travesty, of the nature of scientific thought.” Medawar 1964
Along the same lines, just read somewhere that someone once asked Medawar (EiC of Nature at the time) what fraction of the work published in Nature was wrong. He instantly answered “All of it”. Which didn’t bother him at all, as he felt that was how science was supposed to work–you learn new things that overturn previous conclusions.
My PhD adviser switched systems, from anurans in mesocosms and small ponds to protists in microcosms. He wanted to ask questions about long-term population dynamics, and to do that you need organisms with short generation times.
Dave Tilman famously switched from working on algae in chemostats to grassland plants in the field, but kept working on the same questions, or at least closely-related ones. I’ve heard that was in part because some people didn’t think algae were “real” organisms or that chemostats were a “real” system, so he switched systems to prove that his ideas about competition and R* values were relevant in a “real” system. But I don’t know if that’s actually why he switched.
I’ve done a switch between my MSc and my PhD and then again to a post doc. There’s been some overlap but it does seem like I have a lot of learning to do each time (which makes it hard to feel like an expert).
Generally, I think biologists/ecologists can be grouped into question-people who work with the best system for their question(s); and taxa-people who ask a range of questions about the same/similar things. Studying birds and especially herps, you run into a lot of the latter. I know with my career goals (applied biology), I’ve tended to be more of a taxa-person because I want to have a range of tools (methods, approaches) to address questions. If I was more academically inclined, I probably would have tried to work on a more limited number of questions but in more detail.
Ah, yes, the question-driven vs taxa/system-driven split. Since I’ve worked on Daphnia since I was an undergrad, I imagine that I fall in the taxa/system camp — except that, in my head, at least, it is certainly the questions that are the primary motivator. In theory, I think it seems like the question-driven approach is one most people would consider preferable; in practice, I think knowing a system well tells you what the interesting questions are, and that hopping between systems risks overlooking important, potentially confounding aspects of the system being used to address the question. This is probably a topic for a whole post — thanks for raising it!
A related aspect is that, even when people are system-driven, in the current funding climate it’s essential that they know how to frame their research in terms of big, fundamental questions. Though, I guess if the system is a charismatic one, there might be system-specific funding. Sadly, I am one of a relatively small number of people who consider Daphnia charismatic. 😉
I haven’t really switched: ants are awesome! Beyond that, one of the reasons I’m not interested in switching is that I am able to get cool, rather unique, kinds of data in this particular system (a whole community that has entire colonies within leaf litter) that other people can’t get from other systems. I’m able to more easily test ideas the field that otherwise couldn’t be readily done with other organisms.
Ants are, indeed, pretty awesome.But so are Daphnia. 😉
I’ve never had too much system envy per se (though I am actually envious of mesocosm experiments like what Brad Cardinale uses to look at theories of biodiversity and productivity; and perhaps I am envious of the work you can do with microcosms Jeremy, so there’s one person!), but that may be because, as ATM pointed out, I am a “question person.” I definitely have location envy though. I primarily work in Africa, and so have often been jealous of people that can just drive to their experimental site on Tuesday afternoon to make sure everything is going ok. Though I’ve loved the upsides of working in Africa (both scientific and cultural), I do sometimes wish I had more “control” over my experiment that is hopefully intact 6,000 miles away.
It’s interesting to read this! Yet another post that I have in mind is in defense of boring field sites. When I say I work on Midwestern lakes, it’s generally met with a collective yawn; if I worked in, say, Fiji, people would get super excited about it. But I love my little lakes — I can monitor the populations regularly; if I break something, I can just swing by the hardware store; and I can go home at night and see my family. Boring field sites have their advantages!
Something that several of the comments have made me think about is the timing of a switch to a new field system. It does seem most likely during a transition (such as grad school to postdoc). At this point, if I decided I wanted to work on, say, ants, I could probably learn a lot about working on them during a sabbatical, but would lack the gear necessary. At least, I’m pretty sure the lab kayak wouldn’t be super useful for collecting ants.
During my BSc or MSc I was actually advised to move between systems as it provides a breadth of understanding and shows adaptability. I do know other people however that stayed in the same university, working in the same systems from BSc right through to PhD. I wonder what the best strategy actually is… Stick with what interests you I suppose…
Yes, I agree that showing that you’re not a one-trick pony can be valuable. But that can come in other ways (e.g., combining different techniques/approaches), too.
And if you bounce around too much you risk being perceived as unfocused. See this old post: https://dynamicecology.wordpress.com/2013/05/22/guest-post-on-having-the-courage-to-build-your-own-non-academic-career-path/
I switch systems three times a day in my own lab. I’m much more interested in an overall question that spans across several groups of organisms than in any one particular taxon. I think there’s more power in finding parallels between systems than sticking to a single model, but I’ve moved between systems my whole career so I’m less invested in any one. Perhaps that makes me a jack of all trades and master of none, but it makes for good collaborations.
I agree, that’s always been my philosophy too. In fact I tend to have multiple questions being addressed by multiple taxa at any one time. I think it’s partly due to a short attention span 🙂
I would love to hear more about how you pitch yourself. I’m finding that having worked in multiple systems makes it a lot harder to do a brief pitch about the sort of questions I’m interested in. Ecologists really seem to want to box others into a specific system: “are you a limnologist or a marine ecologist or a forest ecologist or a grassland ecologist or a desert ecologist or what?”
I sometimes say I’m an aquatic ecologist, but more often I describe myself as a disease ecologist or evolutionary ecologist. So, even though I’ve worked in one particular system, I don’t usually use that system when describing myself.
I sometimes experience CPU system envy. When animals don’t breed, equipment breaks, and mosquito bites get unbearable, I dream of sitting in my office, press enter, let the model run and go for a coffee :). Yes, I know, that is not how it works, but sometimes, somtimes…
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