Episode 029: Jeremy Kerr & Catherine Sirois-Delisle

Jeremy Kerr, Professor of Biology at the University of Ottawa, studies the causes of biodiversity decline and ecosystem degradation.

Catherine Sirois-Delisle, PhD student at the University of Ottawa, uses complex distribution models to study the effects of human activities on the ranges of dragonflies and bumblebees.

Transcript

Cameron Graham: "The world has entered a period of mass extinctions that must be halted." That's the first line of the website bio of Professor Jeremy Kerr. He and doctoral student Catherine Sirois-Delisle are my guests today, and they study macroecology, biodiversity and the impact of climate change. Jeremy and Catherine work at the University of Ottawa. They're looking at small creatures to understand large events. Their work on the changing ranges of bumblebees and other insects provides key insights into the decline of biodiversity due to global warming. Their work integrates remote sensing tools, field ecology, and computer based models. It has led to major discoveries around the conservation of endangered species, and the fundamental determinants of biodiversity. On previous episodes of this podcast, we've talked a lot about how we should live, today with Jeremy and Catherine's help, we're going to talk about, whether we live. Catherine, Jeremy, welcome to the podcast.

Catherine Sirois-Delisle: Thank you.

Jeremy Kerr: It's a pleasure to join you.

Cameron: I'm going to talk to Catherine about her paper on range losses among bumblebee species. But first, Jeremy, you're the research chair. So let me ask you for a definition, what is macroecology?

Jeremy: It isn't a particularly complicated thing, but it's just one of those things in science that we like to do where we need a special name for everything. Macroecology is just the broad scale study of the distribution and abundance of species on the planet. It has implications for how we understand things like global change, which obviously is becoming a pretty urgent issue. And to understand global scale patterns, sometimes you need to think about global scale processes. And that's something that macroecology was built from the ground up to do.

Cameron: Catherine, let's get right into your paper because it's directly on this topic. The title of the paper is, "Climate Change-Driven Range Losses Among Bumblebee Species are Poised to Accelerate," by yourself and Jeremy, published in 2018. It sounds alarming that things are getting worse, things are going to accelerate. So let me just start with the question of why you're looking at bees.

Catherine: I have many different reasons, but firstly, bees, we do have a lot of information about them just because they are so important in the agro-industry and also, they provide key ecological services to habitat. And so due to that importance, I think, it plays a large role in the fact that we do have a lot of data relating to bees. And even though they are very small insects, they really do give us information on really broad systems. And so we have this massive data set in our lab, and it allows us to use it in different ways to better understand how climate change is affecting insects. Why bees? I think regardless of the organism that you study, the more that we can vary these different organisms, the better. Whether it had been butterflies, bees, other insects, I think it's just another way of better understanding climate change and how it's affecting species. So, I don't have one definitive answer for why bees, but also I think bees are undeniably very cool and very cute. I think we should preserve what we have and so my interest started from there.

Cameron: Yeah. Well, I think we all have a Winnie the Pooh fascination with bumblebees.

Catherine: Absolutely.

Cameron: So I just want to understand. Obviously, bees play a huge role in pollinating plants, which has incredible consequences for biodiversity, but also for the food that we eat. They're referred to as "key pollinators." To me that implies that there's other pollinators. Are there, or are bees it?

Catherine: There are other pollinators. Bees, especially bumblebees, are extremely good pollinators. There are things that are specific to bumblebees like buzz pollination, which is very efficient type of pollination where they vibrate their flight muscles. And so they are probably - Jeremy, correct me if I'm wrong - the best pollinators that we have. But there are other great pollinators like honeybees or like many butterfly species. So there are other pollinators, it's just, I believe they are the most important and efficient on es.

Cameron: I've already betrayed my ignorance by referring to bumblebees and Winnie the Pooh, because clearly Winnie the Pooh was interested in honeybees, and you're drawing a distinction between honeybees and bumblebees. It's already over my head!

Bombus terrestris on catmint. Photo from macroecology.ca, © Jeremy Kerr

Catherine: So yes, they are sister groups. They're both types of bees, but honeybees produce the honey that we eat, and they were actually imported to North America. So they're not indigenous to our continent, whereas bumblebees are indigenous. The species we have here are indigenous to North America. So, I think there's a lot of confusion often with these two groups.

Cameron: You're looking at the distribution of these different species and how they're affected by climate change. A big question I've got is, how do you know where the bees are? How do you collect data?

Catherine: [knocking heard in background, dog barks] I'm so sorry.

Cameron: Who is that?

Catherine: There's someone at the door. I'm so sorry. My dog is barking. [loud barking]

Cameron: What's your dog's name?

Catherine: Callie, ça va bien la... I'm so sorry.

Cameron: No, not a problem.

Catherine: It should stop in the next few minutes, I think.

Cameron: I'm keeping this in though. This is great.

Catherine: [barking continues] Oh, my God. Callie! She just needs to see that there's no danger here.

Cameron: Yeah, exactly.

Catherine: Okay. I think they're done. I'm so sorry.

Cameron: No, I love pets especially dogs. I'm a dog person.

Jeremy: Ahh! What about parrots? I feel so left out.

Cameron: [laughs] Yeah. Oh well.

Catherine: Oh, my God, I knew this would happen.

Cameron: [barking stops] There we go! Let me ask the question again. So I'm interested in how you conduct this research. You're studying the movement of populations of bees, how do you know where they are? Where do you get the data?

Catherine: So there's a massive data set that is in our lab that was not assembled by me, I think it was assembled by previous students. Is that correct, Jeremy?

Jeremy: We worked with data providers and systematists across North America, and they have funneled data into a large data set. But most of this data set is publicly available through the Global Biodiversity Information Facility at this point. That is just a portal into massive museum-based specimen observations of things like bumblebees or butterflies. And that's really ultimately the source.

Cameron: Okay, so you said museum based. So a lot of research done at museums. They're the ones who would go out into the field to observe the populations?

Jeremy: Largely speaking. Historically, curators and insect researchers or biodiversity researchers at museums would just go collect information about the biological characteristics of different places, collect specimens from the field, bring those specimens back to museums, curate the specimens rather carefully so that they're pinned and identified, and their location information is recorded. And then they're stored under very controlled circumstances, and places like the Royal Ontario Museum would be a great place to see examples of how those specimens are managed and maintained. And they represent a kind of a time machine for us to go back and look at past distributions of species and how they've changed over time.

Cameron: So this is not data that you're just collecting in the last few weeks, this goes back, say decades?

Catherine: Even a century.

Cameron: Oh, my goodness. Yeah.

Catherine: Yeah. Since 1901, is the first record in the database. I did not use all of these older records, but they are available for use.

Cameron: Okay. So given that it's collected by experts, this data would be very precise as to classifying the particular species. Is there a role for citizen participation in this data collection as well?

Catherine: Yes. So there are, especially in the GBIF dataset that Jeremy has mentioned, there are observations in there that are reported by citizens, for instance, through websites like iNaturalist, and these observations can be expert-vetted. So you can't misidentify as a non-expert and then report that species, it goes through a series of steps to validate that you did your identification correctly.

Cameron: That's amazing. Because one of the key things for any research project is the quality of the data, not just the volume, but the quality of it. So that's quite fantastic. North America is very large place, you've got only so many museum researchers going to so many different places in North America. So by definition, you're going to end up with a partial sample of where the populations of bees are distributed.

Catherine: I would say so. Yes. So there are a few areas that are a bit more sparsely sampled, but it's mostly pretty dense. And one way that I've dealt with that is simply to include many, many years. So I'm using 1960 to 1990 to have an idea of a baseline distribution for these 31 species. And so there are various ways to deal with that, including many years, including observations from as many sources as possible, just to represent the species ranges as best as we can. But there's always going to be places that are much more difficult to sample. But absolutely, you describe that perfectly. The methods that I'm using, the Maxent distribution models, are really useful to get around that, to identify the series of environmental tolerances for each species. Due to the sheer volume of observations that we have, we can still draw those conclusions and better understand species’ environmental niches.

Cameron: So you're looking at 31 different species of bee?

Catherine: Yes.

Cameron: How specific are the habitats of these species? The difference from where one species will hang out to another species, is there a lot of overlap or are they quite distinctive in terms of the actual ecological niche that they like to sit in?

Catherine: For bumblebees, there's generally a lot of overlap. But just by mapping the observations, you can see that there are very large differences in terms of where certain species are found compared to others. There are some that are completely on the east of the continent, and then others that are in the completely opposite direction. There are species that are more found in the northern regions of the continent, others are more warm-adapted. And so I would say, even though there's a lot of overlap, there are still differences that are important enough that make it important to study species by species when we're asking these questions.

Cameron: Right. I think the general phenomenon that we're looking at here with global warming, at least in the Northern Hemisphere is that, if a species of bees is ideally suited to a certain a habitat, as global warming progresses, that ideal habitat is going to move because the area where it was gets warmer and it's no longer ideal for the bumblebees. And then an area that might have been too cool is now warm enough for them. And so what you're tracking is whether the bees are moving in synchronization with the changes in the range of their habitat? Help me out, is that what you're doing?

Catherine: Very close. So what you're describing actually reminds me very much of discoveries by Jeremy Kerr and colleagues in 2015. They really looked at species range limits and how they were shifting in space.

Cameron: Okay.

Catherine: What we've done in that paper really builds on those discoveries. So now we're trying to better understand the conditions where species are found now and then seeing how could species habitats be translated to future climate scenarios.

Cameron: Catherine, I want to ask you about this software package that you're using called Maxent. The “Maxent” stands for the phrase “maximum entropy.” And that phrase, as far as I understand, originates with Jaynes in 1957, who was talking about making inferences based on partial information. So when you've only got a sample of all the things that happened, and you want to make inferences from that small sample of the data, it's best to assume a random distribution of things. And then if you notice anything that doesn't just spread out naturally, then you can infer from that some kind of an obstacle or a blockage in the system. So that is helpful in what way, in understanding how these species are affected by climate change?

Catherine: Maxent is extremely helpful, it's probably the most commonly used species distribution model. So there are many different things that make it, I guess, more practical than other types of models. So for instance, they only use presence-only data. And there are other model settings that just make it practical to use. So in our context, we really used the software to use the environmental conditions where species are found in their current geographical range. We could then generate maps that showed where species habitats in terms of their climatic suitability could be found in the future. So it was really just a way of better understanding species climatic niches currently, and then using that information to have a better idea of where they might be found in future years. So, 2050 and then 2070.

Maxent map showing changes in bee habitats by 2070, from Catherine & Jeremy’s article

Cameron: Right. So the data that you're working with within Maxent then, is largely related to the habitats that are suitable for the bees, is that correct?

Catherine: To represent species habitats, we're using four climatic variables. And so we used the ones that were more likely to be biologically meaningful, but also the least correlated just for statistical reasons. And so we used precipitation variables and then temperature.

Cameron: Okay. So this would take into account things like the altitude that might affect the suitability of the habitat?

Catherine: We actually did not take altitude into account. We could have, but I think the surface temperature is definitely going to be reflected by the altitude. And so-

Cameron: So this is what you meant about using variables that aren't correlated, because if you use altitude that also affects temperature, so you don't really need both in the model.

Catherine: Exactly. It's important to not include variables that could be driving each other. So it was really a matter of digging into the literature and seeing how others have dealt with these challenges in the past, and we chose these four variables.

Cameron: Right. So this Maxent software then, is taking these variables and producing a geographical map, a visual map of where these species could be located?

Catherine: Yes, exactly.

Cameron: Right. So that is a map that then is changing dynamically as the climate changes?

Catherine: Yes. We are going to see these changes, since climate is changing in every single future climate scenario. Even in the most optimistic climate scenario, there are still very important changes that will be reflected by the climatic suitability maps that Maxent will generate. So yes.

Cameron: I want to talk about this data set that you describe in the paper as a massive data set of geo-referenced observations. The database contains 324,000 observations across North America. And that sounds like an awful lot, until you realize that North America is 24 million square miles in area. So that's one observation for every 75 square kilometers. It seems like a very, very thin sample. Is there other factors that make the sample more useful to you or is it as sparse as I imagine it to be?

Catherine: I think there are definitely other factors that you might not be taking into account. Because every species has a unique range. And so for each species range, we could imagine that we're trying to represent, as best as we can, that species range.

Cameron: Right.

Catherine: And we also did different things where we even had to pare down the dataset. For instance, where the climate is very homogenous, we don't need as many data points, and we want to try to avoid autocorrelation between data points. And so we pared down in different ways to take into account climate heterogeneity, as well. And so even though it seems sparse, we actually did not need all of those data points.

Cameron: So you actually, in your paper, were using 10,000 observations out of this 324,000. Is that what you mean, you're trimming it down to the ones that are actually useful for your model?

Catherine: Yes, exactly. So we really did our best to really include the most informative data points. So for instance, where the climate is very heterogeneous, we want to include more data points, because it gives us more information based on the species climatic tolerances, whereas in a very climatically homogenous area, we don't need as many points to understand those tolerances.

Cameron: Okay, I see. I want to clarify what the word observation means here. Is this like they found a hive of bumblebees or is this an individual insect or what?

Catherine: So each observation is an individual insect that was collected at some point, or in more recent years could have been simply photographed. So each observation consists of a species [identification] and then other information that could have been reported by the collector, and it includes the latitude, the longitude, the date, the year. So we have all of that information for each of our observations.

Cameron: You have some wonderful photographs of bumblebees on your website Jeremy? And how close does a photographer have to get to be able to identify what the actual individual is?

Jeremy: It really depends a lot on your camera. So if you have yourself a fairly powerful camera frame, but especially a really strong lens. You can be a good distance away from these things, and it isn't difficult to identify what you're looking at. So it really varies a lot. But bumblebees in North America, in my experience, tend to be fairly calm, little critters, and you can get pretty close to them. I think some of my very best photographs, actually, not all of them, but some of my best pictures are with my iPhone. So I will get within a foot of them or 10 inches or something. And as long as I'm not doing anything too weird or abrupt, they will allow me to approach

Cameron: I am interested Of course in how often you've been stung.

Jeremy: I've never been stung by a bumblebee. Not even once.

Cameron: Wow, that's very impressive record. You must be a very calm researcher.

Jeremy: They're not angry animals I have to say. The only hymenoptera, the only bees and wasps and ants that have ever stung me, -- and there are no fire ants here in Ottawa yet, so we'll leave them aside -- are yellow jacket wasps, which are the only critters I've ever encountered that sting purely randomly. Just standing around, one lands on you, stings and flies away and you're like, "What did I do? Nothing." Bumblebees don't behave like this and neither do honeybees or other kinds of bees in my experience. But there are of course some bees that can be aggressive and different people should, depending on their personal situation, be a little bit cautious about approaching bees.

Cameron: I want to go back to this map data just to make sure I understand just how finely tuned your model is. The climate data that you're using, according to your paper, is at the five arc-minute resolution. So I did some calculations, I don't know whether I've done them correctly, but it seems to me that each pixel on your map then, is going to be somewhere around nine or 10 kilometers across. Does that sound about right?

Catherine: Yes, that's correct.

Cameron: So that's like taking Greater Toronto and dividing it up into about 100 different pieces. So it's fairly precise from the perspective of all of North America, but not very precise from the point of view of Toronto. Those are still fairly big chunks of geography to map to.

Catherine: They are, but in terms of climatic data, you can imagine that across the city of Toronto the climate is going to be fairly similar if you take the most southern point of the city compared to the most northern point. There might be differences yes, but at that point they're so small at the macroecological scale. If you're using five arc minutes, I think it's fine enough that we can still gather information on the species climatic needs.

Cameron: Right. Well, of course there's the effect of the lake in Toronto. So if you're within a kilometer or two of the lake the temperatures can be different than further inland. So your data is not quite fine tuned enough to pick up that difference. But from a point of the whole GTA ...

Catherine: No exactly. Due to the scale of the study, I really can't capture fine data like that. And in terms also of the climatic models that are provided on WorldClim, if you try to extract data that is too fine, it's simply extrapolated by the model itself. So it's not like if we had a weather station at every square kilometer. That data just doesn't exist. So it's really a matter of using the finest data out there that I can.

Cameron: You've got climate models generated by NASA, by the Meteorological Office at Hadley Center in the UK, I think you've got some from Tokyo, and some from the National Center for Atmospheric Research. These are the climate databases?

Catherine: Yes, they are. So each future climate model is going to be a little bit different. It just depends on how it was built. I decided to use as many as I could. Well, I selected these four. And after I obtained my results with Maxent, then I could average my maps. So it was really just a matter of trying to eliminate that bias that could be occurring due to simply the data that I could have chosen.

Cameron: Right. So by using all four, you're developing a more general model?

Catherine: Exactly, yeah.

Cameron: Right. Before we get into the mathematics and the actual tweaking that you did to the data with different dispersal rates, and so forth, there's two phrases or two terms that you use in the paper I'm not clear on. One is "niche limit," and the other is "range limit." Could you or Jeremy explain that to me?

Catherine: Yes, so the range limit is very intuitive. It's simply the limit of the distribution of a species. So if you imagine all of the points on a map where a species was collected, we can imagine that there are a lot of barriers, or I guess, limits all around the area that represents a species range. So we often refer to the northern range limit and the southern range limit. And so it's, I guess, the most intuitive type of limit. The niche limit is often very similar to the range limit. So the niche limit encompasses the set of environmental conditions that a species can tolerate. And so these limits translate geographically as well. We can imagine that for a species that experiences a maximum of a certain temperature, we could draw a line on a map where ... or I guess, data points that fall into that temperature. And so the niche limit is really based on the environmental conditions, and it's more theoretical in the sense that what Maxent is doing is, it's finding species climatic niches.

Cameron: Okay, so it's trying to predict probabilistically where these other niches might be that you could anticipate the bees moving to as they become more and more viable?

Catherine: Yes, exactly. Yeah.

Cameron: Okay great. And so in terms of the dispersal rates for the species, f irst of all, what's the base rate for dispersal? How fast, at the theoretical maximum, could bumblebees disperse as they move from year to year into new habitats? What's the fastest they would go?

Catherine: Dispersal for bumblebees, we measured it as the distance that a queen can travel in the spring as she's finding a place for her nest. And according to the literature, I found, actually that it was largely unknown, but the numbers that are reported tended to vary between three and five kilometers per year. There is one invasive species, one invasive bumblebee that is not included in the study, but it was found to invade parts of Tasmania at 10 kilometers per year. And in order to obtain the absolute largest dispersibility that could be in a bumblebee, we used 10 kilometers per year as the maximum dispersibility, and we used zero kilometers per year as the minimum. So species cannot disperse anywhere further than their current ranges, which is probably the closest to what we're actually observing right now, because we know that bumblebees are not dispersing at their northern range limits. And so this scenario was also interesting, even though it assumed that species couldn't disperse anywhere, which they probably can a little bit but in my opinion, that scenario was the closest to reality and the unlimited dispersal scenario was to represent something that was purely theoretical in the sense that we know that species cannot disperse in an unlimited way. But it allowed us to map the areas that could be suitable, even though they cannot be reached.

Cameron: Right. Okay. So these potential areas, these suitable areas, just to give me a point of reference, how fast are these new suitable habitats being created as the climate warms up? How fast is the climate moving across North America, compared to the bees?

Catherine: I'm not sure if that is something that is known. You're talking here about climate debt. So the distance or the lag that is created when the climate is changing and the species are staying at one place, we can really map what that lag is through time. But I'm actually not sure for bees that I could quantify that, since we know that the climate is advancing, but bees are not, that their ranges are not tracking climate change, we know that that lag is present.

Cameron: Given the fact that there is climate change, and the habitats that were ideal are now perhaps too warm, and the habitats that used to be too cool are now becoming more viable for the species, the next level of an ideal scenario would be that the bees move naturally in sync with this climate change. You're finding that they don't move as fast as they need to.

Catherine: Yes. We are definitely expecting that bees will not disperse in a way that will be sufficient to counteract the losses that we're going to see in other places.

Cameron: Your paper suggests that if there's no dispersal, if the bees don't move, that they may lose up to 50% of their range by 2050 and up to 75% by 2070, correct?

Catherine: Yes.

Cameron: You are also pointing out, that even assuming a 10 kilometer per year dispersion, which is the fastest bees have ever moved, they still lose range.

Catherine: Yes.

Cameron: No matter what happens, there's going to be this huge impact on the bee populations.

Catherine: Yes, there is. Especially looking at the different climate scenarios, even in the most optimistic scenario, we could still find a pretty drastic range loss. And so, it is alarming. And I think it's pointing out that we need to focus on conservation actions that take the effect of climate change on bumblebees into account. It's something that we don't often hear about in terms of the decline of bees in the media, we don't hear about climate change. In fact, it's very, very limited. We hear about a lot of the other threats, like pesticides or land use change. But I think, in terms of conservation actions, we really have to take the effect of climate change into account. And it has to be done, like yesterday.

Cameron: So, do we yet understand what these obstacles might be that are preventing the bees from moving as fast as perhaps they ideally could?

Catherine: I don't think it is known in terms of why they aren't dispersing as fast as they could. I know it was hypothesized in the past that it could be due to land use change: if they're disappearing due to land use change, perhaps they're not able to keep up with the changing climate. But in Jeremy's 2015 paper, they found that the effect of land use change and pesticide use was actually very limited. And so honestly, I don't know and I would love to know.

Cameron: Jeremy, I see you nodding your head.

Jeremy: This is one of those areas in biological research that we are going to have to grapple with if we are going to get a handle on the sixth mass extinction. This problem applies to bees, it applies to a very large number of other organisms as well. So it's pretty fundamental. And the question [is], what do we have to do to try to figure out what the answers to the mystery actually are? And one of those things that we're going to have to do is, I think we're going to have to grapple with the difference between shifting mean conditions and changes in climatic variability. When we think about global warming, which is this term which implies that, slowly over time, the average temperatures are rising, precipitation is changing in some average way, you got to ask yourself how you actually measure those averages. We measure those averages typically as the 30 year average of weather. No bumblebee on earth has ever experienced the 30 year average of anything. Adults over the summer, typically live for a few weeks, queens might live for about one year, and what they experience is weather. So the thing that is going to cause problems for them in a proximate sense, relative to climate change, is the frequency and intensity of events that push them beyond their niche limits. And those things can operate in direct and indirect ways. That's the challenge that we have, measuring those things on scales that are extensive, but still detecting variation at local levels. This is a ferociously difficult problem for us. And the fact of the matter is, that the environment is changing faster than we can keep up with. And this is causing problems for bees as well as other groups of organisms.

Bombus ternarius experiencing lovely weather on Manitoulin Island. Photo from macroecology.ca, © Peter Soroye.

Cameron: This I think provides a nice segue to the second paper that we discussed prior to the show. And this is the paper that you wrote with Peter Soroye and Tim Newbold. Peter is one of your doctoral students at the University of Ottawa. Tim, I believe, is at University College London in the UK. And this paper is two years more recent than the previous paper we were talking about with Catherine, and you're taking into account, I think, some of the factors that might have caused previous studies to underestimate the impact of climate change on bees. Could you describe what that's about?

Jeremy: Yeah, so the point that I was making a moment ago regarding the trajectory of average conditions, versus how the frequency and severity of extreme events can change, was the focus of what this paper was seeking to do. And a few years ago, we had this insight inspired, I have to say, in part by some of the work that Catherine has done, inspired to think about more proximate reasons why climate change causes problems. So if you think about a bumblebee species, these are not migratory animals, they're present in more or less the same environment all the year round. Weather at any time of year can influence them in ways that are potentially harmful. If you have a strange heatwave in the middle of the winter, for example, you can basically kickstart their physiological machinery, they start burning energy. This is a cost for bees. We don't usually think about those kinds of things when we think about climate change. Heat waves in the wintertime seems like an unintuitive concept. But we can actually measure the degree to which monthly temperatures deviate from historical norms, and we can ask the question, given the array of temperatures that this species is known to be able to handle, are we starting to see temperatures exceed those limits more frequently, and by how much? So you can actually measure that using some of the climate data that Catherine has described, and then you can actually create a prediction from one place to another across Europe and across North America, that essentially assesses the degree to which environments are now imposing these growing extreme conditions. And then you can ask the question, is that associated with differences in the likelihood that these bees are still there? And that was the main focus of that study, trying to get a little closer to the reasons why climate change causes problems.

Cameron: So you're studying the volatility of the temperatures, not just the general trend?

Jeremy: That's correct. And so we're thinking about the ways that ... There's a bridge we have to cross in a biological sense, between how we do things at global scales in climate science, for example, where we produce these gigantic maps at quite coarse resolutions. There's a huge bridge to cross from that kind of measurement to the experience that an organism has in a particular environment on a short timescale. So we were trying to create a bridge that let us get closer to the experience that an organism has, and then ask the question, does it make it more likely that this organism will successfully colonize a new area, or if it was present in that area already, whether it was more or less likely to disappear from an existing place? So that's the gist of it, we're trying to get toward the experience of climate change at an organismal level, rather than the measurement of climate change in a climate science way.

Cameron: Right. Because the individual, as you point out, only experiences the weather, they don't experience the overall climate change.

Jeremy: Exactly. And that's what people experience as well. And the same kinds of negative experiences that people report with respect to extreme weather also exert effects in biological terms. And so super hot and unpleasant heat waves in the summer, also cause problems for organisms. But if you measure the average temperature over the course of a year, it might only be a degree or two above the long term normal. But that degree or two above the long term normal is not really problematic in terms of survival, what really matters is whether you had two weeks in July that were 12 or 13 degrees above seasonal norms. Those extremes are the things that really exert effects.

Cameron: Catherine, in your paper, you talked about what could be done to mitigate the effects of climate change. So one of them has to do with, if you can identify where bees might be likely to thrive, you might do what's called assisted colonization. But how does an individual human being assist a colony of bees to move? These are not honeybees that are kept domestically.

Catherine: So that is a very big question. It's also a very debated question. In no way are we suggesting that tomorrow morning, we should go move bees all around North America. But we definitely suggested it as a type of conservation action that should be further explored. There should be further tests, we should better understand how we can use different techniques to help species move where they need to go, where the climate is newly suitable, but that a specific organism cannot reach. So here we're really talking about, it could entail the movement of a fertile queen in the spring, to an area adjacent to the species range limit. And while making sure not to cross any biogeographical barriers, really taking into account the places where an organism needs to go, and where it should naturally go, but it cannot due to the various anthropogenic threats.

Cameron: So at this point, that's a hypothetical thing we might do?

Catherine: It should be further explored, definitely.

Jeremy: It's controversial.

Cameron: Is there anything that can be done for the habitats that are slowly losing their viability for the species? Can anything be done to mitigate the effects there?

Catherine: There are a few things that can be done, especially in terms of just landscape management. We should definitely consider managing habitats for bumblebees, especially where the climate is becoming unsuitable. We could consider for instance, micro habitats where the effects of climate change could be decreased. So a refuge for bumblebees. We could also consider identifying the corridors that could lead species to perhaps disperse a little bit more easily if we manage the landscape with a more broad approach. Also, I think, considering the places that are likely to become suitable. Well, I'm passionate about conservation, so I'm always going to say that we need more areas that are protected. And I think protecting the areas that will become suitable in the future is one big step as well.

Cameron: Jeremy, I'm interested in the way that research gets into the popular imagination, into the popular press. Catherine mentioned that a lot of coverage of the bees has to do with the pesticides. But now you're talking about the effects of climate change. In general, Jeremy, do you think that the media conveys scientific understanding well or not in this area?

Jeremy: I actually think the media has changed a very great deal in about the last 10 years regarding its communication of climate change. Historically, it had taken an approach which is intended to convey the concept of balance. Since the Copenhagen meetings, which I believe were in 2011, this whole issue has ... gosh, sorry, 2009 ... this issue has kind of gone away. And what has happened is that mainstream media is no longer giving equal time in non-ideological venues to contrarian viewpoints. My sense is that the media is beginning to do a pretty good job of this. But there are also some other issues in the background that are really important for us as scientists, when we think about how we communicate with the press, because the press likes sensation, and scientists like evidence. And we need to be careful not to try to create sensation that goes beyond the boundaries of what the evidence actually supports. And then the flip side of this, is that we need to be also careful that when we convey bad news, we also try to think about the evidence that may support mechanisms to enable us to do better. Despair makes for inaction, not action. And what we're looking for here, as researchers is a way forward. And so if what we convey is hopelessness, then what we will end up getting is hopelessness, we will end up getting policies that don't get made, because the public gives up on the topic. And the consequence will be that we will share a much darker future than is necessary.

Cameron: I know that you have won a prize for excellence in media relations. How does a research scholar, a research oriented university professor best deal with the media? Do you cultivate individual relationships? Do you get coached on how to produce sound bites? What's the trick, Jeremy?

Jeremy: I'd love to know what the trick is. I don't know that there is a trick. I think it helps if you are empathetic. You need to be able to imagine how other people hear you speak. And if you just don't think about that when you communicate, it's going to be very difficult for non-specialists to follow along with potentially very technical arguments. This comes up routinely because almost everything we do as scientists involves something really technical in some way or other. But the technical stuff is rarely the message that gets media attention. The technical stuff is what gets you through the peer review process into a research journal. And having gotten to that point, your job is to convey the meaning of it in a broad media way, not to go through the nature of your statistical assumptions and that kind of thing. And those messages are not going to be as interesting to people in the general public, just because they're so hard to follow and so difficult to translate to anybody else's day-to-day experience. So I think empathy is something that really helps with this. And I like the idea that sound bites can be something that isn't pejorative. When people say sound bites, it's usually said in a slightly cynical way. When we say sound bites, it's like, well, that's just a sound bite, because you're trying to get attention. But what you're actually trying to do is say something true, in a memorable way. And so for me, when I use what I think of as a sound bite, what I'm trying to do is convey the truth in a way that people might actually remember. Or that might actually reach somebody. Because that's the purpose of communication is to be heard and to understand the people you're speaking with, you're not really talking at them. I think that's another thing that you need to remember in communication is, you're not talking at people you are speaking with them. And that implies a dialogue, even if it's a one way interview.

Cameron: Catherine, I'm interested in how you as a doctoral student ended up studying the specific things that you've chosen. Does the media appetite for stories about bees affect your choice of what to study? It's been said that pandas are so photogenic and that's why they get a lot of attention in climate change discussions. But there are a lot less photogenic animals that are also important and we don't tend to talk about those. Bumblebees are photogenic as well. Is that necessarily the species that you want to study, though? And how do you go about making up your own mind as a doctoral student on where are you going to devote your energy?

Catherine: I did study bumblebees for my master's thesis, and now as a PhD student, I actually assembled my own database. I had to do all of the work from the start, just as previous students have done for the bumblebee database in the lab. And I've assembled the database for Odonates, which is the group that consists of dragonflies and damselflies. And as to why I've selected that specific group, I don't have a specific why. I'm just passionate about Odonates. I just love them so much. I'm just very interested in studying how they're responding, what can we do to make the situation better? The model organism that you use also, it can be anything. It could have been butterflies, it could be any group for which we have information. And for me, that choice was obvious it was dragonflies and damselflies.

Cameron: Jeremy, tell me about the way that your lab and your funding is set up and how you're able to support students as they develop their research skills.

Jeremy: Like many Canadian researchers, I've benefited gigantically from the research funding model that exists for discovery-based research in Canada. That is the NSERC Discovery Grant Program. This lets you do work that is investigator-led, so it is not focused on a short term project outcome, it is intended to support a long term research program. And that has been the keys to the kingdom for me, because it doesn't constrain you to think in short term ways. Between the Discovery Grant and the Discovery Accelerator in 2015, one of the things that I got to think about was whether or not we could pursue research that sounded like it would be high risk, high reward, speculative stuff. Things like, "Well, let's see if we can figure out what the future for bumblebees looks like," and that's Catherine's work, or let's see if we can figure out what the proximate reasons for climate change being a problem for organisms, what that proximate reason might be. So the model that Canada has is, in many respects, the envy of the world. Whatever its funding limitations have sometimes been in the past, that funding has become much better in the last three or so years. And we are, I think, reaping the rewards very broadly in the Canadian research ecosystem. And I am most certainly experiencing those benefits in terms of my own research program. And the ways in which I have the luxury of letting students pursue their most passionately held interests. And that includes things like being very happy about letting Catherine pursue her own personal passions to think about global change and the conservation of dragonflies.

Cameron: Little nitty gritty question for you here, who gets to be first author on papers?

Catherine: [laughs] It depends on the paper, but for, for instance, my bumblebee paper, I was the first author. It was for my master's thesis. So I definitely did most of the work. It's definitely a team effort in terms of how that research actually comes about. There's a lot of conversation back and forth, in terms of editing, in terms of deciding on the methods that we're going to use. But ultimately, it's, especially if it's for a chapter for a degree, like master's or PhD degree, then it's the student who is first author.

Cameron: Right. Jeremy?

Jeremy: Who does the work? Who's really responsible for the work? And Catherine thoroughly earned her role as first author in that paper and there was never a moment's hesitation about whether she would take on the position that she'd earned in that work. And I was delighted to see her take such a leadership approach to discovery in that paper. And ever since it's been wonderful.

Cameron: Let me ask you one last question before you go. You've got a fair amount of funding for your research, what are you allowed to spend that on?

Jeremy: This is one of the wonderful things about the NSERC Discovery Grants Program. It gives you the latitude to spend those research resources in ways that maximum their benefit. In practice, most of those research funds are expended on supporting students directly for their graduate stipends, which they always receive. And that's a vital part of the picture. But we also have to pay for things like bringing students to conferences back in the days pre-pandemic, when anybody could go anywhere, it's not even possible to leave the town these days. But that's coming back. And we're going to want to have students have opportunities to experience real conferences where they interact with colleagues. And that's really vital in the training exercise. It may also pay for equipment and field costs going out to various sites around Ottawa or in the region and measuring numbers of butterflies or counting numbers of bees. There are costs associated with that as well. Those are the tangibles. And I think they're really important. And researchers I think, are generally pretty grateful for the support that they receive. But the intangibles matter as well. And I think one of the things that really matters a lot is whether you are able, in your best moments, to find ways to inspire people to care about science, and to use science or see that science can be used to make a difference. I try to bring that to the table. And it's not really for me to say whether that is largely successful or not. But I try really hard to identify ways that science can make a difference, and to then actually do so. And so that's on my list of intangibles, and it's part of the experience that I hope we can sustain in my research group and more broadly, around inspiring the next generation and getting people to actually want to choose science as a career.

Cameron: Right. Well, it sounds like a wonderful model. Catherine, I'm so happy that you were able to share your insights on your paper today. Appreciate it. Jeremy, I wish you all the best with your work and with your bevy of research students who are learning from you. I will keep myself posted on your progress, and I look forward to having conversations with you again in the future.

Jeremy: That would be delightful. Thank you.

Catherine: Thank you so much for having us.

Catherine Sirois-Delisle working in the field

Links

Jeremy Kerr’s faculty webpage at the University of Ottawa

Catherine Sirois-Delisle on LinkedIn

Sirois-Delisle & Kerr (2018). Climate change-driven range losses among bumblebee species are poised to accelerate

Soroye, Newbold & Kerr (2020). Climate change contributes to widespread declines among bumble bees across continents

Credits

Host: Cameron Graham
Producer: Cameron Graham,
Photos: University of Ottawa, UBC Press
Music: Musicbed
Tools: Squadcast, Audacity
Recorded: June 25, 2021
Locations: Ottawa and Toronto