(Note: I wrote most of this post before seeing Brian’s recent post on how there is no one true way to do science. There is definitely overlap between the posts!)
Recently, I attended a symposium at the Kellogg Biological Station (KBS) that celebrated 50 years of research in aquatic ecology based at KBS. The event featured talks by former faculty and students, spanning the entire timespan of research at KBS. While everyone did research (at least at one point) in aquatic ecology at KBS, otherwise it was a fairly mixed group: evolutionary ecologists through ecosystem ecologists; research on small local streams vs. on Lake Baikal; junior folks vs. retired folks. But there were a few themes that kept emerging throughout the talks, one of which I want to focus on in this post. That theme? Tackling complex ecological questions requires a diversity of approaches. This theme came up over and over again.
For my own research program, I feel that the questions I’m interested in require a combination of observational studies on natural populations, experiments (in the field and lab), and mathematical modeling to tackle. First, I’ll go through why I use these approaches in my personal research. Then, I’ll come back to the general topic of the importance of diverse approaches.
In my research, I use observational studies to ground my research in natural systems. My goal with these studies is to identify phenomena in natural populations that are interesting and seem to warrant further study. For example: why do we see positive associations between some predators and levels of parasitism? Or, this parasite has shifted hosts and now infects an invasive species. What evolutionary changes allowed that? Sometimes these patterns are ones we find when we set out to look at that particular question. But, as I’ve written about in the past, sometimes these patterns emerge when we are studying something else.
Next, we often carry out experiments aimed at testing a hypothesized mechanism underlying a particular pattern. Of course, it isn’t always possible to manipulate the hypothesized driving factor, but, when it is, this allows one to directly test causality. In my case, these experiments are often done in the lab, at scales ranging from beakers to buckets. Other times, the experiments are done out in the field, using whole-water column enclosures. In all cases, the goal of these experiments is to test the effects of particular factors.
Finally, my research often uses mathematical models that help me link results from different scales, generalize results, and/or try to understand how a factor that can’t be experimentally manipulated might be influencing results. Can the shift in body size and infection risk that we observe in the lab when we manipulate a predator explain the observed links between that predator and epidemics in the field? If the parasite didn’t castrate its host, would we still expect the same effects on population dynamics? Those sorts of questions require mathematical modeling to tackle.
So, in the end, many of my papers end up having a combination of field patterns, experimental tests, and mathematical results. I feel like I can’t tackle the questions I’m interested in without using these different approaches. And, based on the symposium at KBS, it was clear that many other people also feel that they need to use a variety of approaches to study ecological questions. The particular approaches that would be used will differ between people, sub-disciplines, etc., but the need for diverse approaches seemed very consistent. In my opinion, if studies employing a variety of different approaches all point to the same answer, that gives me much more confidence in that answer. And, if there are discrepancies between the results found when using different approaches, uncovering the sources of those differences can be very important.
Now, back to the general topic of the importance of diverse approaches. There is no way that one person can do everything. In my case, I am finding, more and more often, that the questions I’m interested in require genetic skills that I do not possess. And I am very, very good at getting myself in over my head with a planned theoretical analysis. This is part of why collaborations are so valuable. (Another advantage to collaborations, in my opinion, is the diversity of perspectives that result.)
So, my advice to grad students is to try to develop a variety of skills, techniques, and approaches with which you are comfortable. In addition, develop skills that will make you a good collaborator, because the days of a scientist doing innovative, exciting, important work on his/her own are long over. (Brian made this point, too, in his rather lengthy footnote.) The important questions in ecology will not be tackled with a single approach.