Don’t know that I’ll have the energy to do daily wrap-up posts from the ESA as I have in the past. But I’m doing one today mostly because Tony Ives rocks. His MacArthur Award lecture this morning was one of the very best talks I’ve ever seen in my life. If you weren’t there, here are a bunch of things that were awesome about it (and I’m probably forgetting some):
- Great, interactive opening. Tony first posed a question to the audience: Should ecology be about general laws? Yes or no? And by “posed a question to the audience”, I mean that literally. He put the question up, told people to take two minutes to discuss the answer with their neighbors, and just to make sure people knew he was serious, walked off the stage. And so people did as he’d asked–the room was buzzing. And then he came back two minutes later and took a show of hands (for the record, “no” won about 2/3 to 1/3). Not only was this a great way to engage the audience and grab their attention, it was a great setup for the rest of the talk. As Tony noted, if you think ecology is about the study of general laws, then it’s obvious that there’s an important role for mathematical theory (think general relativity or quantum mechanics in physics). But if you don’t think ecology is about the study of general laws, it’s much less obvious why ecology needs theory. The rest of the talk was about elucidating the role of narrowly-tailored, system-specific theory, using as an example a long, ongoing collaborative project aimed at explaining the very unusual population dynamics of midges in an Icelandic lake (Ives et al. 2008).
- A personal introduction. Tony talked about his family history in Iceland and how it ultimately led to the development of this collaboration. It’s always a lot of fun and very interesting to hear about the (often non-scientific) stories behind scientific papers.
- The science itself was really interesting, and very well-explained. This part was familiar to me from reading the paper, but it was still good to hear about it again. Briefly, these midges go through very high amplitude fluctuations (5 orders of magnitude), but with an irregular period. Building and estimating the parameters of a mathematical model of the known midge biology reveals an explanation. Midge dynamics are characterized by alternative attractors, a high-amplitude limit cycle and a locally-stable equilibrium, and environmental stochasticity kicks the system from one attractor to the other at irregular intervals. A nice illustration of how stochasticity and determinism are not alternatives, or even ends of a continuum. Rather, the combination of stochastic and deterministic processes leads to a rich array of “emergent” outcomes.
- Throughout the talk, and at the end, Tony made all kinds of great points about how to do mathematical modeling (especially system-specific modeling), and what we learn from the exercise:
- That math can give you biological insight. Here, theory revealed highly non-obvious dynamical implications of the known biology. It suggested which bits of biology need further study if we really want to nail down the explanation for the midge dynamics. And it revealed otherwise-unsuspected possibilities. To understand any actual system, it often helps to understand where that system falls within the range of possibilities–including hypothetical possibilities that don’t exist.
- That the way to test mathematical models is mostly not to test their predictions, unless perhaps the predictions are quite precise and quantitative. Because if all a model predicts is that, say, some variable will increase, or that two variables will be positively correlated, it’s not really very impressive or informative if that prediction is borne out (much as correctly calling a single coin flip isn’t impressive or informative about whether or not you have psychic powers). Testing model assumptions often is a much better way to go (I have an old post that touches on this). Because if the model’s assumptions are right, or right enough, the predictions are guaranteed to be right too.
- That system-specific theory, theoretical “case studies” if you like, aren’t just a stamp collection of special cases having nothing to do with one another. They’re more like a reference library, a source of potentially-relevant information, analogies, and ideas. In trying to solve a quite specific problem–explaining the very unusual dynamics of midges in one particular lake–Tony drew on past experience with other cases that differ from the midge case in many ways but which share some key features (e.g., other systems in which he’s encountered alternative attractors).
- That there’s no such thing as a “typical” system, and that even “unusual” systems like the midges can yield broadly-relevant insights.
- That you should never be impressed just because some model can be fitted to some data with a very high R^2. The inference that the model correctly explains the midge dynamics is a quite sophisticated one, based on far more than just the fact that the model can fit the time series data very well. In particular, other models that lack alternative attractors fail to fit the data, despite being more flexible (in the sense of having more free parameters). That’s a key line of evidence that, if you’re going to explain the midge dynamics, you need a model capable of generating alternative attractors, and capable of flipping from one attractor to the other. That’s a great example of using models that are known to be false in order to infer what’s actually true in the real world.
- That models are no more abstract, and no more (or less) difficult to extrapolate, than experiments. Tony used a great example here. Ecologists all agree that Bob Paine’s experiments on Tatoosh Island revealed very generally-relevant principles (e.g., keystone predation). But from a strict statistical perspective, there are no grounds to extrapolate any of those results beyond the rocky intertidal zone of Tatoosh Island.
At the end of the talk, some folks near the front (members of Tony’s lab, I assume?) held up some huge signs, one of which just said something like “Tony rocks!” Yes he does!
If you missed the talk, you’ll get a chance to read it. The MacArthur award lecture, suitably revised, is always published as a paper in Ecology. I’m really looking forward to seeing that paper, I think it will be a must-read, especially for students.
UPDATE: For another summary of the Monday highlights, see The EEB and Flow. Caroline Tucker actually went to a lot of the same talks I did and picked her favorites, so her summary isn’t too different from the one I might’ve written had I not been too tired to write about anything besides Tony’s talk.
No chance of seeing a video of the talk(s)?
Not as far as I know, sorry. And the ESA has a policy that filming presentations yourself is not allowed.
The talk sounds amazing. I’m bummed I missed it. Thanks for the great recap.
You’re welcome Don.
I wasn’t there, but I’m pretty sure those were current or former Ives Lab members holding the signs. There was email coordination of this ahead of time. 🙂 Sadly, it seems that the plans to use body paint to spell out TONY IVES on 8 current/former lab members fell through.
Hi Jeremy, I have to say I’m disappointed to hear that 2/3’sf the audience suggested we shouldn’t be looking for general laws. In my opinion, the only reason to take that position is because you don’t believe there are general laws or you believe we have as good a handle on the general laws as we are ever going to have. The most ambitious scientists in any discipline that believes there are general laws are trying to discover those laws – but 2/3’s of ecologists (admittedly an imprecise estimate) have given up on even trying. I’m a little saddened by thaT. Jeff
Well, Tony himself said he’s not motivated by trying to discover general laws, though he emphasized that that was merely a personal preference.
One other thought, Jeff: the sort of system-specific problem-solving approach Tony takes often lends itself to building predictive models. General laws don’t always lend themselves to making very precise predictions for any particular system. So if you want a predictive science (and I know you do!), I think there’s something to be said for the sort of modeling Tony often does.
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Thanks so much for the review – especially since I wasn’t able to take the time for ESA this year. Also, it’s exciting to see interactive techniques used in a venue like this.
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