Advice: weak studies of short-term dynamics

In the comments on a previous post, I got into a discussion about the reasons why one might study short-term (i.e. transient) dynamics as opposed to long-term (i.e. asymptotic) dynamics. For instance, one might study a system's short-term response to a single disturbance event, as opposed to the system's long-term dynamics under repeated disturbances. I decided to expand my comments and put them up as a separate post.

There are many reasons why one might study short-term dynamics—and some of the most commonly-stated reasons are pretty weak. Further, even people who have good reason to study short-term dynamics often do so in weak ways. So if you're interested in short-term dynamics, you may wish to consider the following:

1. Some ecologists who study short-term dynamics mistakenly think they're studying long-term dynamics. Now, "long-term" does not have a universally-applicable and precise definition. But it does not mean "longer than one year" (at least not for most organisms ecologists study), "longer than the duration of a typical grant", "as long or longer than the typical study in my field", "long enough for me to see a statistically-significant treatment effect", or even "longer than a human lifetime". What's "long-term" is determined by the question you're asking and the ecology of your study system. In particular, if you're testing some theoretical prediction about the asymptotic behavior of a system, you had better either study your system long enough to be confident that you've observed asymptotic behavior (i.e., the means, variances, and other relevant system features are no longer changing), or else find some way to reliably infer your system's asymptotic behavior from shorter-term data. Unfortunately, this is a difficult standard to meet because transients can be very long-lasting, as Alan Hastings often points out. But hey, if ecology was easy it would be boring.

2. If you really are interested in short-term rather than long-term dynamics, please don't use models that are about long-term dynamics to guide your work. Obeying this dictum means you'll probably have to develop your own models, because pretty much every well-known and widely-studied model on every topic in ecology (including, for instance, both zombie and non-zombie ideas about disturbance) is about long-term outcomes, not transients. Theoreticians study asymptotic behavior almost exclusively, because it's much easier to study mathematically.

3. If you think (or hope!) that it's ok to study transients because they will look sort of like the long-term outcome, I’m sorry, but they typically won’t. Transients are infamously idiosyncratic and highly sensitive to initial conditions (i.e. the initial state the system happens to be in, independent of whatever drives system dynamics). That's the other reason theoreticians generally don't bother to study transients—they're totally wonky (the transients, not the theoreticians) (ok, maybe both). There's a vast array of theoretical and empirical studies, in all areas of ecology, which have made precisely this point. Just off the top of my head, besides Alan Hastings’ work, see Briggs and Borer (2005), Neubert and Caswell’s (1997) work on ‘reactivity’ (even stable systems can temporarily move further from equilibrium after being perturbed before eventually returning), my 2007 Oikos paper on the transient dynamics of trophic cascades, Jim Brown’s classic 1980's work on the contrasting transient and long-term effects of competing seed predators on one another, and many, many other papers. Unfortunately, I know of no rules of thumb on when transient dynamics will resemble long-term outcomes and when they won’t, and I doubt that any such rules exist (or that they're very generally applicable if they do exist).

4. Ecologists who conduct short-term studies often justify them by saying "Ideally, I'd like to conduct a long-term study, but it's only feasible to conduct a short-term study." Which is sometimes defensible, but often is not—not if what's "feasible" reflects your own previous choices. If you would really like to study long-term outcomes, but transient dynamics are all you can measure in your system, why don’t you change study systems? That's why my own doctoral supervisor did—Peter Morin switched from mesocosms of amphibians to microcosms of protists in order to do long-term community ecology.  Alternatively, why don’t you stick to asking questions you can actually answer with short-term data? Or, why don’t you find a rigorous way to infer something about long-term outcomes from short-term data? (Note that “Collect short-term data, compare to theoretically-predicted long-term outcome” is not a rigorous thing to do). For instance, if you’re interested in long-term coexistence, you can do short-term mutual invasibility experiments (i.e. experiments that just test whether rare competitors tend to “bounce back”, which is a short-term question), use them to parameterize dynamical models of your system, and then use the models to project the long-term outcome expected from your short-term data. Folks like Jon Levine have been doing exactly that. That approach isn’t foolproof (e.g., if you’re parameterizing a bad model, the long-term projections will be wrong). But no approach is foolproof, and the potential drawbacks of that particular approach are knowable and checkable in various ways (e.g., you can compare the projected long-term outcome of competition to observed species abundances, or long-term time series data). So if you say "I’d like to study long-term outcomes, but it's only feasible to measure transients", you'd better have a good argument why you're not doing the equivalent of tying your own shoelaces together and then complaining that it's only feasible to walk slowly. The handicap principle should only apply to our study organisms, not to our studies of them.

5. Ecologists who study short-term dynamics often admit that these dynamics are likely to be different than long-term dynamics, but argue that short timescales are still "ecologically-relevant". Sometimes this is a reasonable argument; it's one I've made myself on occasion (e.g., "These competitors have coexisted for over 100 generations, which is not forever but is long enough to demand an explanation, making 100 generations an ecologically-relevant timescale"). Short timescales also can be "relevant" for other reasons, such as legal ones (e.g., "The law obliges management decisions to be made on this timescale") But in my experience, talking about "ecologically-relevant" timescales often is shorthand for "I don’t have long-term data, but I want to publish the data I do have, so I’ll call them data about ecologically-relevant timescales." That is, "ecologically-relevant timescale" often is shorthand for "a timescale long enough for something or other to happen". Which is a pretty low bar, given that something happens on every timescale.