What I do
My work addresses fundamental questions in population, community, and evolutionary ecology. I’m curiosity-driven. I like solving puzzles, and I love the “a-ha!” moment when I finally understand something I didn’t understand before (or had misunderstood before).
I am most interested in questions to do with system dynamics (changes over time) and the processes that drive them. Accordingly, much of my work uses a combination of mathematical modeling and experiments in tractable model systems such as laboratory microcosms. I use mathematical models because ecological and evolutionary systems are complex and nonlinear. It’s hard to develop and test rigorous hypotheses without mathematical help. I use microcosms because their high control and replicability allows powerful, rigorous experiments that would otherwise be impossible.
My lab is currently funded by an NSERC Discovery Grant.
Below are the main lines of research I’m currently looking for graduate students to work on.
Spatially-separated populations of the same species often fluctuate synchronously, even though they’re hundreds or even thousands of km apart. The result is that, across vast areas, all populations increase (or decrease) simultaneously. Coexisting populations of different species also often fluctuate synchronously. Synchrony is pretty amazing when you think about it, and so cries out for an explanation. We have theories of why synchrony happens, but those theories are hard to test in nature because it’s impossible to do experiments at the right spatial and temporal scales. You can’t, say, manipulate the weather across all of Canada and then wait a century to see what happens to the spatial synchrony of lynx-hare cycles (and even if you could you wouldn’t have a control or any replication…). The solution is to scale nature down and do experiments in protist microcosms. I’m currently seeking grad students interested in pursuing synchrony-related experimental and modeling projects.
Much of my work on synchrony is in collaboration with my former postdoc David Vasseur of Yale University.
Higher order interactions and species coexistence
Are ecological communities more than just the sum of their parts? If you knew enough about the population dynamics of each species on its own, and about all the pairwise interspecific interactions, could you predict the population dynamics of every species in the entire community? If not, the community dynamics are driven in part by “higher order” interactions: “emergent” effects that can’t be predicted just from knowledge of single-species and pairwise dynamics. Higher order interactions potentially present a major challenge to our ability to explain and predict community dynamics, but we don’t know much about their prevalence or importance. Ecologists have some good short-term case studies of some of the the biological mechanisms that can give rise to higher order interactions, but few predictions about the circumstances in which higher order interactions will matter, and few long-term studies of their consequences for community dynamics. Protist microcosms are a great system in which to study the consequences of higher order interactions for community dynamics. Indeed, pioneering experiments tried to do this decades ago, but back then we didn’t have the statistical tools needed to properly analyze such experiments. We have those tools now. Here’s a recording of a recent online seminar I gave on the theoretical side of this ongoing research.
My stuck-at-home-during-the-pandemic side project has developed into a new line of research for me: studying ecologists. Aided by my outstanding research assistant Laura Costello, we assembled a database of all the effect sizes reported in most of the meta-analyses ecologists have ever published. That database is a fairly comprehensive record of what ecologists have learned about a large sample of all the empirical topics ecologists have ever studied. We can use that database, and supplement it with additional information, to ask all sorts of questions. How rapidly does our knowledge of a typical ecological topic increase as more and more studies are published? How many studies of an ecological topic do we typically need to have before we can be confident that our conclusions aren’t likely to change in future? Is there systemic publication bias against studies reporting small effects, or against studies that oppose the conclusions of previous ones? Many of the questions one could ask with this database would make for great side projects for any graduate student. Others could comprise an entire MSc.
Other lines of research
I have various other lines of research that are mostly on the backburner right now. And I’m always on the lookout for new ideas. So if you’re a prospective graduate student, and there’s a line of research you’d like to pursue in my lab that’s not listed here, I’m all ears.