Gryphon Cast Episode 12 Transcript
Speakers: Amanda Reside, Mackenzie Charter and John Fryxell
Amanda Reside
What makes a relationship work? Trust. Communication. Not in the case of the lion and the warthog. No matter what the Lion King might tell you. It may not be a story of friendship, but the relationship between predators and prey is still very important to ecosystems. It provides an ebb and flow of population size that keeps both sides in a healthy balance. So, what does make this kind of relationship work? Open your ears and your mind and let's chat about that. Welcome to GryphonCast a podcast where we casually chat about science coming out of the College of Biological Science at the University of Guelph and how that work can affect lives around the world. I'm your host, Amanda Reside, and with me today is co-host Mackenzie Charter and special guest Dr. John Fryxell. Welcome to the podcast.
John Fryxell
It's great to be here.
Amanda Reside
We'll be chatting about the recently published study from the Fryxell Lab, which examines the relationships between predators and their prey and how the tendency of prey to live in groups or herds can affect those relationships. So, to begin, how would you describe your research or the general work that you do in your lab?
John Fryxell
Well, it's always tough to, you know, encapsulate a research program that covers decades in just one sentence. But by and large, what we're interested in is, is how the behaviour by organisms influences the outcome of the population dynamics that they're involved in, whether that be herbivores that are feeding on plants or the same set of herbivores that are at risk of being fed upon by predators. In each case, we're interested in how the choices that individuals make have ramifications in terms of the demography that they exhibit.
Mackenzie Charter
What made you decide to research this topic?
John Fryxell
Well, that's a good question. I grew up and went to graduate school at the University of British Columbia. And at that time, you know, it was kind of a burgeoning time for population ecology. Lots of exciting new ideas were being born. And one of those ideas that was just coming on the scene was the notion of optimal foraging. And this was a principle by which using that kind of decision-making analysis and really computer models to anticipate what organisms might be judging and what the benefits and costs might be. Behavioural ecologists began to first make some predictions about what kinds of behaviours we ought to see under what kinds of ecological circumstances. So,it was a pretty exciting time and I saw a really nice match with trying to understand how populations and communities of organisms fit together using this as a tool.
Mackenzie Charter
Sure. So, you recently published a study titled “Stabilizing Effects of Group Formation by Serengeti Herbivores on Predator-prey Dynamics”. What brought you all the way from Ontario to Africa to look at Serengeti wildlife?
John Fryxell
Well, I've been involved with African wildlife ever since my Ph.D. thesis, which was in the Sudan on Antelope, called the White-Eared Kob. In 1990, I was invited to a meeting in Serengeti that was meant to bring together people that worked on a wide variety of organisms. It was really the first time there had been any attempt to kind of model that system. And because the people that worked on carnivores hadn't had a great deal of experience, they asked if I would help with that group just to coordinate with some of the other groups that had a little bit more computing experience. And so, I got to know a number of people that had worked for several years in Serengeti at that time. One of those people was Craig Packer, and his study team contributes data on the population and the spacing of lions that are in the same area. So,it's a collaborative enterprise we’re both vested for contributing for both ends.
Amanda Reside
The paper that we're talking about today used mathematical models to assess the stability of predator-prey dynamics in this portion of the Serengeti. And so, just for the audience, can you briefly describe the concept of a predator-prey dynamic and what is meant by the stability of that relationship?
John Fryxell
Well, the way that ecologists, by and large, should have thought about interactions between predators and prey or herbivores and plants is by thinking of them as just particles that are mixed together. And mathematically, the origins of this kind of approach actually comes from the way that physicists think about gas particles interacting. So just as you can imagine, a couple of gas molecules meeting by chance and forming a new molecule. In the case of the interaction between predator and prey, you have, you know, two different actors here, one that's trying to avoid being captured, and the other that would love to find lunch. And so, when those two particles interact, when they're getting close in a proximity, if there's a successful attack, then we think of that as a predation event. Well, the mathematics of that is pretty well established and has been around for, you know, 60 or 70 years in various forms in one way or another. But it ignores one fundamental truth, and that is that a lot of organisms don't exist as independent particles that are floating around independently of each other. But rather many organisms start to form social groups of one sort or another where they're in close proximity with their conspecifics. And those essentially become the interactive groups that might determine success as a predator moves around the landscape. So, if you imagine a group of four lionesses that are wandering across the Serengeti plains, that group of four lionesses are behaving a little bit like one particle, not four. And similarly, if you have a group of 50 gazelles that are walking across the Serengeti landscape that group of 50 gazelles behaves much more like a single particle than 50 independent particles that are floating around. Well, what that does is it means that the rates of interaction, the rates that the frequency with which those groups run into each other by chance is changed quite a bit by the group sizes that they find themselves in. And so, what we've done is to try and understand and predict what the outcome of that would be based on the size of groups that we see and the rates that they move around the landscape, both of which we know pretty well.
Mackenzie Charter
What would you say the importance of mathematical modeling is within the context of ecology and conservation?
John Fryxell
Well, it's you know, math has always played a really important role in ecology because ecology is a quantitative discipline. We're interested in the, you know, the ebb and fall of population abundance. And that's a kind of a probabilistic process where some individuals are added to a population by births and some individuals disappear by death. There's movement around the landscape. These are all really fundamentally mathematical processes. And if we want to understand what happens to the entire population and we need to, we can gain some insight anyways in what happens to the whole population by trying to better understand and predict the rates of birth and death that we see in a population. So, mathematics is really fundamental to the whole notion of ecology, and that's a surprise for many students, of course. I mean, when they take our classes, they're expecting to see endless pictures of lions and gazelles, too. And of course, that's what takes us into the field. I mean, it's, you know, the love of nature that brings us all in the first place. But it's trying to explain the patterns of nature that keeps us there. And as a scientist, really our notion is that we would like to better explain the patterns that we see out there. And so, bridging the two, helping to understand the observations that we see, the exciting things that bring us there in the first place, requires some insight that often comes from mathematics.
Amanda Reside
Yeah, that sort of encapsulates a thought that I had when I was reading the paper was, you know, going through your methods. It starts with, you know, the models that you use and the equations. And then describing the surveys of, you know, driving, like you said, several kilometers to count individuals in a herd. You know, it has it all. You got the beauty of mathematics and the beauty of nature all wrapped into one. So that's kind of cool.
John Fryxell
Well, you know, I mean, it's mathematics, but you know, the parameters that go into the equations are the sort of things that you see every day. So, you know, we keep track of the probability that when a lion sees a prey, it's able to successfully capture it. How far an animal goes, how far it can see. All of these are mathematical parameters that go into the model. There’s in some sense, you know, abstractions, but in another sense very real encapsulation of the observations that we see. So it's the marriage between behaviour and the mechanics that produce population dynamics that we're after.
Amanda Reside
In your study, you chose to look at Serengeti lions and their eight main prey species. So, I'm just curious why you chose lions in particular. Is there any particular characteristic of them, like the fact that they hunt in groups that was particularly interesting to you? And were there any other predator species that you were considering looking at?
John Fryxell
Well, lions and hyenas are for sure the most predominant predators in the Serengeti plains. So, if you want to understand what's happening in a population, well, why do you need to start with those two species? But they are interesting in both cases because they are communal hunters, as you say. And we are certainly very interested in following up, thinking a little bit more about hyenas and lions interact. It's certainly not uncommon for a group of hyenas to drive a lion off of a kill, but that would be about the only interaction that, you know, might change some of the mathematics that we've looked at here. But it's certainly a relevant question, and it's not one that we've looked at much. Certainly, that would be a nice next generation study.
Mackenzie Charter
Your study used data that was collected over seven years and they were collected in a monthly census where researchers would drive out into the Serengeti, into a variety of different habitats and count herbivores that they could sort of see within a range. Do you think the accessibility of those tracks affected your results? Like do you think if there's other areas that are less accessible that weren't surveyed, that are kind of showing different dynamics or what have you?
John Fryxell
It's a good question to pursue. I mean, there are certainly cases where you might easily imagine that if you were going down the Trans-Canada through Banff National Park, probably that doesn't represent typical habitat for animals along the highway. Tracks in a lot of African parks like Serengeti or dirt tracks and creek. Not so much of an obstacle for organisms to cross, but nonetheless, there is probably a bit of a bias that's in our data in that some of the tracks are traveled more heavily by humans than others. About two thirds of the tracks, though, are tracks that are very rarely used by anybody in really are just a couple of wheel marks in the grass. We need to have tracks, though, because we really want to repeat this exercise in a dependable and predictable way. And it's hard to do that driving across a featureless landscape. To some degree, we need to use the tracks and we do choose them in such a way so that they're not generally too heavily travelled. And we do most of our observation very early in the morning when there isn't a good deal of traffic anyways. But these are always legitimate concerns. And, you know, the kind of thing that you do need to think about when you're setting up a field study.
Mackenzie Charter
Is this the type of thing like satellite imaging could help with?
John Fryxell
Certainly it could. But the satellite imagery is starting to come into vogue. And, you know, there are several labs around the world that are trying to work with photographs that are taken from satellites. Currently, the quality of the imagery that we can get is a little bit limited, and particularly for smaller organisms. But it's not hard to imagine the day will come when it's no longer necessary to trundle around in a four-wheel drive vehicle across the plains.
John Fryxell
But one thing that we do from the cars that is not really obvious, perhaps, is that what we're interested in is not just how many animals there are in the landscape, but we're interested in modeling the distribution of their group sizes and getting some idea of the frequency with which a predator would encounter herbivores groups of different sizes. And those groups fall into a pattern that we sometimes referred to as a power law, where you have an enormous number of observations of just one or two individuals and very few observations of very large groups of animals. With that kind of distribution, where you have a decay curve is often well described by a power formula. And so this power law gives us a way of anticipating how the number of groups changes as the population size changes, because there's a regular relationship between the frequency and the size of groups and the overall number of individuals that are forming those groups. So that becomes an important element in being able to turn this into a mathematical formula that we can rely on.
Amanda Reside
Right. So, when you say that the group number of groups and group sizes change as the population as a whole changes what I picture and you can tell me if this is an accurate idea of what's going on is, for example, you know, a group of gazelles has a really good birth year and the population of this herd goes up to the point where they might split off into two. Is that something that might happen?
John Fryxell
Well, it's not so much that you have new births that cause that process, but rather that there's a continual vision and fusion events that are occurring. And these models are literally modeled with the same way that we model coalescence of complex molec, where you have a large group of individuals that spontaneously split up into subgroups and the distribution of those subgroups takes on a very predictable fashion. And that's what forms the power relationship that I've just been alluding to. Okay. We would like to see how general that process is. And so currently we're trying to find similar data that are that are recorded across other parts of East Africa and North America as well, to see if that power law representation holds up. We think that it's a very general tendency. And so we're hopeful that it becomes something that that could be a reliable yardstick in many different organisms.
Amanda Reside
On the note of the generalizability of the power law. Your eight species of prey animals that you included in the study have a wide variation in grouping tendency. I believe warthogs tend to form smaller groups like family groups, whereas things like wildebeest form larger herds. And so the power law that you describe this is generalizable to these types of prey that have a wide variation in how they form groups.
John Fryxell
Well, it generalizes, you know, very well down, for all the individual, all the different species that don't have fixed social groups. But even for warthogs, as you say, that basically occur in family groups, it still makes a reasonable representation that the distribution that we see. So that's why we think that this is a fairly generic way of capturing the social process that's out there.
Mackenzie Charter
So, kind of building on that, your paper describes the influence of interspecific variation. So can you describe what that means and any of the remaining factors that affect the predator-prey relationship?
John Fryxell
Well, the number of groups, as I said earlier, dictates the frequency with which encounters that a predator encounters a potential prey item. And so, anything that tends to lead to a more accentuated grouping tends to reduce the frequency with which predators can encounter prey. And so that leads to important differences across some species because some, you know, are more social than others. And as a consequence, the risk of predation is affected accordingly. That suggests that socialization and the attraction that individuals have for other individuals might have a very solid fitness benefit in that the species is reducing the risk of all the individuals that are members. So, natural selection could play a strong role in encouraging that tendency that many species have to group together. This eight species that are worked on are the eight most common species in Serengeti, and perhaps that's no accident that they're all social.
Amanda Reside
So, based on the conclusions of this study, how is your perspective on the stability of the relationship between lions and their prey changed, if at all? Are the observed dynamics concerning or hopeful for, you know, the health and sustainability of the part of the Serengeti that you studied? And are there any prey species that are most at risk of instability in their population?
John Fryxell
Our model suggests that species that are loners and there are some species that like that Roan antelopes are an example. Some of the kudu species. Those kind of species might be at a little bit higher risk of intense predation. So, you know, you might be able to think of a spectrum of risk that applies across species. But there are many other things that come into play there too. So, it wouldn't be the only criteria by which I would, you know, predict that risk would occur. But nonetheless, it does give us a little bit of additional insight into the differences in pressures that different species might face. And it's certainly because these processes are unfolding over a very large landscape. One of the implications of our work is that maintaining a large landscape where this natural grouping pattern can occur spontaneously may be an important management priority.
Mackenzie Charter
So, I think that leads right into our next question. As humans, our population keeps growing and we keep changing in urbanizing the environment. Are we seeing the effect of that on herding behavior of wildlife, and is that something we can account for in sort of the mathematical modeling?
John Fryxell
Well, we don't know because there hasn't been much expansion of the ideas that we've explored in this paper to other species and other systems. But what we do know from work that was done a couple of years ago across the globe, is that in places where the human footprint is highly developed, that patterns of movement are often curtailed. And what that suggests it's not so much the animals, you know, can't move, it's just that they move less. And as a result of moving less, it means that there's probably some level of restriction on the kind of social aggregation that they can have. That's a hypothesis we would need to test it. But certainly, this notion of the human footprint having a negative impact on movement rates is well-established.
Amanda Reside
Moving on from, you know, the cold, hard facts, I'm curious as to what your favorite part of working on this study or this type of study is?
John Fryxell
Well, without a doubt. It's just the beauty of the system. You know, when I arrive in Serengeti, invariably there's a big smile on my face and it's just such a gorgeous place. It's a reminder of what, you know, primeval with primeval world was like. And we're lucky that there are places like that that still exist and remind us of who we are in our kind of small place in the firmament. But, you know, it's I think just the place itself is magic.
Amanda Reside
That's lovely.
Mackenzie Charter
And so, was there anything that surprised you about taking on this research project?
John Fryxell
Well, everything you do as a researcher is a surprise. And certainly, when we first, you know, stumbled on the relationships that form this underlying really this underlying model, you know, that was a thrill. And that kind of thrill of discovery in that we see when we look at mathematical models, it's no different from the thrill of discovery when you see a behaviour that you hadn't ever seen before or when you look under a microscope and to have a view of a cell that is you've never seen before. And these are all aha moments, really. And, you know, without a doubt, you know, that we had a quite a thrill when we realized that there is some predictability here that we could take advantage of. And it helps you think that you have explained just a little bit of the giant puzzle that nature presents to us. And, you know, that that giant jigsaw is kind of what keeps us all going. You know, you're fitting in just one piece at a time. And those little pieces sometimes take years, but every little bit gives you some satisfaction that you're getting closer to getting a clearer picture of how the world works.
Amanda Reside
Absolutely. If you could go back in time and change one thing about the study, what would it be and why?
John Fryxell
Well, I guess one thing I would like to do would have ideally would be to have a little bit more information on the interaction between hyenas and lions. I think that is actually a key element. It's hard to do without having a close collaboration with all of the study teams. And in this case, it just didn't work out. But that is the one thing I think I regret. And we would like to see that piece developed more.
Mackenzie Charter
Would you say that would be sort of the next step for this work?
John Fryxell
Well, we are certainly trying to collaborate with researchers in other areas, such as the Masai Mara area in Kenya. And there's a number of other reserves in South Africa and elsewhere in East Africa that have done work of a similar nature. And so, we would like to coordinate a lot of that work across systems, and we would love to extend some of these ideas to North American systems. I mean, the kind of patterns that we describe in Serengeti are probably very similar to the kind of patterns you would expect to unfold in Yellowstone or other areas where you have a large expanse and where you have group forming predators. So, in Yellowstone, it would be wolves instead of lions, but and instead of wildebeest, we'd be talking about elk or bison. But the same sort of mechanics probably, you know, would apply. And certainly, that would be a reasonable conjecture. So, I'd love to see that happen. Whether that happens in my lifetime, I don't know. But, you know, it'd be great to see that happen. So, if anyone out there with, you know that wants to spot to support our work in that we did in Serengeti in Yellowstone. Just give me a shout. We're ready and raring to go.
Amanda Reside
So, we're just going to take a couple of questions from social media and I'll get Mackenzie to read off the first one.
Mackenzie Charter
Okay. So, for someone who's interested in wildlife conservation, biology, and mathematical modeling, maybe who's new to it still in school, where would be a good place to begin learning about it?
John Fryxell
I would say the University of Guelph is a great place to start with it because I think that we, you know, bring that perspective. You know, right across a number of different labs. But I certainly think that anyone that's interested and fascinated by these kind of processes, key thing is not to be frightened by the notion of mathematics because I think there's often a tendency for biologists to be a little bit scared and a little bit timid about mathematics. Maybe it wasn't the subject that captured the heart, but if you love the processes and if you love the systems, the math will come to you. And there's no reason to be fearful about that. It just takes a little bit of openness and a willingness to explore new ways of thinking.
Mackenzie Charter
That's a great answer.
Amanda Reside
You said biologists are afraid of - just like me.
John Fryxell
Well, I see it in my classes. I mean, you know, people are a little bit fearful of the notion of using algebra. And I don't know why that fear is there. But, you know, I think that for most people, it should be a manageable thing.
Amanda Reside
Yeah. And just from talking to you, I can see that none of the magic of the system as you describe it and none of that, you know, sense of wonder or satisfaction of putting together the puzzle gets lost with mathematics. It really does sound like, you know, if you're willing to venture into that area, it just enhances it.
John Fryxell
Yeah, it's just another way of seeing things and more ways you get to see things. The richer your vision.
Amanda Reside
So, do you have any final comments that you'd like to make about your work or this paper? And if our listeners take only one thing away from our chat today, what do you hope that it is?
John Fryxell
Well, one thing I do want to mention, and it sometimes gets lost because, you know, these things often sound like they're, you know, solo enterprises. And that's not the case. I mean, this work happened in part because lots of people were involved. But there's a couple of people that really key. And, you know, certainly my colleague Craig Packer has been, you know, a great partner to work with on this, but even more importantly, has been Joseph Masoy, who has been working with me for all of those eighteen years. And, you know, as we speak is probably trundling someplace across Serengeti, doing something on my behalf. And, you know, without Joseph, we'd be no nowhere. He's kind of the glue that holds it, holds it all together for us. And so, you know, if anybody deserves credit for this, it's Joseph.
Amanda Reside
Wonderful.
Mackenzie Charter
Yeah, that's. It's super important to always acknowledge that science is, like, such a team effort. That brings us to the end of today's podcast. A big thank you to our guest, Dr. Fryxell for joining us today. GryphonCast is brought to you by your hosts Amanda Reside and myself, Mackenzie Charter with editing assistance from Ian Smith. If you're hungry to learn more about science topics, check out Scribe Research highlights that’s S-C-R-I-B-E Research Highlights on the University of Guelph website @uoguelph.ca you can follow us on social media @UofGCBS. Find us on Instagram, Twitter and Facebook. The music for this podcast comes from uppbeat.io, which will detail in our show notes. And until next time, stay curious.