By Lynley Hargreaves 27/08/2015

If you believe the next mass extinction event (caused by humans) has begun, how do humans begin to choose which species to save? Rutherford Discovery Fellow Dr Daniel Stouffer may be able to help, although he isn’t looking at kiwi, lichens, or in fact any particular species. Instead, he’s working on ways to study all of them at the same time, and he and his University of Canterbury team can tell us something about how food webs fit together across the world, and perhaps the future of ecology.

Are we saving the wrong species?

This is the exact question that managers of conservation policy are asking and answering every day. Unfortunately, the first big step forward might be realising that it may be the wrong question. What I mean is there’s lots of evidence that species at the top of the food chain are critically important, and we also accept that nothing can survive without the species at the very bottom, even microbes. However, the truth of the matter is that maintaining a well-functioning ecological community depends on all the species fitting together and we’re only just starting to figure out what that really entails.

So the answer is we don’t know?

Dr Daniel Stouffer and the Stouffer Lab
Dr Daniel Stouffer and the Stouffer Lab: “In 10-20 years we might routinely be predicting ecological events as well as early meteorologists predicted the weather.”

Not yet. Ecology is one of the youngest disciplines in biology and we’re still learning about very fundamental things like what determines whether one species eats another or what allows two species to coexist or even thrive together. To further complicate things, much of the past 100 years in ecology is based on studies of single species, or, at most, a paired predator-prey interaction like the lynx and hare. We’re now realising that we need to move well beyond this to understand the whole network, while still being able to see past that complexity and work out what’s going on at the single species level. The Marsden Fast-Start grant I got a few years back was about doing exactly this by studying ecological networks like food webs, the complex network of predator-prey interactions that forms the backbone of every ecological community.

What have you found?

One of the most surprising and exciting things we’ve found is how predictable the roles of species in food webs can be, over time, over space, and across the globe. For example, we showed that the roles of species in food webs here in New Zealand are very similar to the roles of related species elsewhere. So despite a completely changed geographic location, climate, and history, if we have an idea of the interactions of a species in one place, we can predict its relative’s interactions in a new environment.

This result is really neat since a specie’s interactions influence whether or not it’s what’s called a “keystone” species:  these are species that are particularly important for the dynamics of their community, just like a keystone is critical to holding together an archway. That means if a species in a food web have been studied elsewhere, for example, we can predict their dynamic importance with reasonable certainty here. Along similar lines, we’re trying to work out what it is that makes a community more resilient or vulnerable to change, and why exactly disturbances of some species have far greater impacts on the rest of community. Ultimately, we hope to shed some light on the tough questions and tough dilemmas such as which types of species we might we be able to afford to lose and which species we have to protect absolutely.

This doesn’t sound like it will help policy makers any time soon.

Realistically? Probably not. When I talk about prediction, I’m talking about it in the loosest sense of the word. But ecologists are collecting way more data than ever before and we’re actually going to be able to start making pretty specific predictions soon. In a perfect world, I would say that in 10-20 years we might routinely be predicting ecological events as well as early meteorologists predicted the weather. Who knows, maybe someday soon we might also be able to argue that there’s a really good chance that the first bumblebee will land on a flower in your garden at precisely 8.25am next 23 February.

You didn’t start as an ecologist. How did you get to where you are?

To be honest, it was close to pure random chance that I ended up in this field. All my degrees are in chemical engineering, and I initially planned to work on tissue engineering during my PhD. As luck would have it, my eventual PhD supervisor gave a talk about complex systems on the first day of doing my PhD in a new department and a mention of ecological networks just grabbed me. I dove right in from there and the more I learned about ecology the more I savoured the opportunity to ask those basic, fundamental questions I mentioned before – it was like a drug. We know a lot, but we know so little.

As another wrinkle, I did my PhD under the supervision of a statistical physicist. I actually suffered a bit of an identity crisis for it during the early stages of my PhD since I often felt I was a chemical engineer masquerading as a physicist masquerading as an ecologist. By the end, I realised that my atypical background instead meant I was already equipped with mathematical and computational tools whereas many biologists weren’t. It also gave me a unique perspective to ask novel questions and challenge long-held assumptions in a way that a typical ecologist might never consider. To this day, I’ve tried to replicate this experience by building a diverse research group of my own that includes biologists, mathematicians, engineers, and physicists, and funding from my Marsden Fast-Start and Rutherford Discovery Fellowship has been integral in making this happen.

These interviews are supported by the Royal Society of New Zealand, which promotes, invests in and celebrates excellence in people and ideas, for the benefit of all New Zealanders.