Earlier this fall I read Mark Vellend’s The Theory of Ecological Communities. I read it on my own, and also read it in a reading group with several ecology grad students. Here’s my review.*
tl;dr: It’s a very good book that fills a real pedagogical need. Whether it will also shape the direction of future research in community ecology is an open question, I think. Below the fold you’ll find me engaging with the book, which I think and hope Mark will welcome.
Platt (1964 Science) is a classic practical statement of philosophy of science by a scientist. Briefly, Platt argues that some fields of science progress faster than others, and that this is neither an accident nor attributable to variation in intrinsic skill or brilliance among scientists in different fields. Rather, he says that workers in some fields routinely use a method that more or less guarantees progress: strong inference. They line up a bunch of competing alternative hypotheses, and then conduct the decisive observations and experiments to distinguish among those hypotheses. So that in the end, they either identify the correct hypothesis, or know they have to go back to the drawing board and come up with some new hypotheses.
At least according to one small sample, ecologists mostly don’t do strong inference.* Why not?
tl;dr: I think Brian’s wrong and that the usual excuse for not doing strong inference in ecology is mostly bogus. I think ecologists could, and should, do a lot more strong inference than they do.
Note from Jeremy: this is a guest post, written by Karen Abbott after soliciting thoughts and discussion from Lauren Sullivan, Chris Stieha, Robin Snyder, Lauren Shoemaker, Sean Satterlee, Ben Nolting, Brent Mortensen, Chris Moore, Brett Melbourne, Brian Lerch, Geoff Legault, Aubrie James, Katie Dixon, and Sam Catella.
Karen adds: This was very much a group effort and these contributors (listed in reverse alphabetical order because regular alphabetical order feels a bit tyrannical when imposed by an Abbott) each made this post significantly more interesting than anything I would have come up with on my own – thanks to all.
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Over the past five years or so, I have spent more time than I should probably admit feeling hung up about what stochasticity really means. When my thoughts start to fall down a rabbit hole of semantics or to philosophical questions of determinism versus free will, I pull myself back. I’m not interested in those things, important as they may be. I’m interested in gaining a deep understanding of the role that “stochasticity” — the conceptual construct — plays in ecological thinking, as well as the role that actual stochasticity plays in real ecological systems.
Lots of other people think about these things too (particularly the latter question on the role of actual stochasticity), so I asked a non-random group of colleagues, collaborators, and lab members to share their thoughts on what stochasticity means and where or how stochasticity is important. I’m not sure if this exercise has made me feel more or less hung up, but it was really fun and a number of interesting themes emerged:
1) Collectively, we have lots of ideas about what stochasticity is, and what it’s not. These ideas can be roughly organized by whether stochasticity contributes as a mechanistic driver of observable patterns or whether it exists outside of (deterministic) drivers to add variance to observations.
2) Questions of scale are ubiquitous.
3) Semantics aside, there are some meaningful differences in how ecologists apply the concept of stochasticity. “Stochasticity” is a rather precise-sounding, technical word that may hide a lack of conceptual precision.
Taking these one at a time —
Scientists still enjoy a fairly high reputation in society as a whole (notwithstanding creationists and climate deniers). It is worth pausing to ask why scientists are still given credibility in this increasingly doubting age. Continue reading
A meme that seemed to run through much of the comments on Jeremy’s recent post on salesmanship in science seemed to be that you could be a wonderful scientist but a terrible communicator of your science and that you would suffer for this career-wise and that would be unfair. This came as a surprise to me. I have a hard time thinking of people who I would call a great scientist but a terrible communicator. Now they may have stage fright and give a bad talk, but write great papers (or vice versa). And they may be bad networkers or bad self-promoters. But the sterotypical genius with ground breaking ideas but who drools and can’t put two words together let alone coherently communicate what they’ve done and why it is important, no. Which leads to the deeper, more philosophical question, if there is “good science” inside somebody’s head and it can’t get out, is it science? Hence the allusion in the title to the zen koan about a tree falling in the forest. Or if somebody is shipwrecked on a desert island does research for 10 years and then dies and their notes decay before they are found, have they done science?
Dynamic Ecology 