By Neema Tavakolian, 2021 IIASA Science Communication Fellow
Young Scientists Summer Program (YSSP) participant Lyndsie Wszola explores how human interactions with warming freshwater systems have affected the evolution of fish species through the lens of the North American walleye.
The effects of climate change have intensified over the past few years, especially in our oceans, and human based activities contributing to it are now being taken more seriously. While the warming of our oceans is indeed troubling, many forget that freshwater systems are also being influenced, and that this is affecting the growth and evolution of the species that reside in them.
2021 YSSP participant Lyndsie Wszola wants to explore changes in freshwater systems using human-natural modeling systems at IIASA.
Growing up with a conservation officer father, Wszola is a second-generation conservationist. Knowing she wanted to enter this field at an early age, she realized that she had to get into research and academia first. Her main interests while studying at the University of Nebraska have been the interactions between humans and wildlife.
While researching the relationships between hunters and ring-necked pheasants, she discovered an affinity for quantitative research. This curiosity went even further after she discovered literature on harvest induced evolution and mathematical ecology specifically pertaining to fish populations. Together, this initial desire to explore human and wildlife interactions and her newfound interest in mathematical ecology, led Wszola to take a closer look at North American freshwater systems and how we as humans are influencing its ecology. Her research specifically delves into the growth and evolutionary changes seen in the North American walleye (Sander vitreus) – a popular fish in Canada and the United States. The reason for its fame is its palatable taste as a freshwater fish and its status among anglers, making it both a commercially and recreationally fished species.
Walleye was chosen as the subject of Wszola’s research for many reasons. First, walleye, like many fish, are ectotherms meaning that their body processes and behaviors are directly linked to their body temperature, which is in turn directly linked to the temperature of the water. Unlike other fish however, there is already plenty of research and data on the relationship between the walleye’s growth and temperature. This information makes it much easier to simulate the walleye’s eco-evolutionary growth dynamics in the context of human driven harvests in warming waters. Wszola will also be working with very large datasets spanning multiple latitudes ranging from Ontario, Canada down to Nebraska, USA. The datasets include up to six million fish with four million of those being walleye.
“My goal is to model the influence of temperature on fish harvests based on size. Due to their ectotherm nature, we can observe the changes in body size in annual harvests. As waters warm, walleye grow much faster. We also know that intensely harvested fish often evolve to reach maturation at smaller sizes. When coupled with rising temperatures, this relationship between harvest induced and temperature induced evolution can be fascinating, as we now have two sources working together to change the growth evolution of this fish,” she explains.
Due to warming temperatures, many natural resources are at stake with some of the most sensitive being aquatic in nature. Research like this is important as it allows us to look at our relationships with the environment to be able to react accordingly.
“I hope that the research I do yields fascinating enough results so that from a practical standpoint, future fisheries policies can include climate change dynamics in addition to fish and human dynamics,” Wszola concludes.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Mikko Heino is a researcher in the IIASA Evolution and Ecology Program who over the past 18 years has worked on the problem of fisheries-induced evolution, showing that selective harvesting of bigger fish can lead to evolutionary changes towards smaller and faster-maturing fish populations. A new review by Heino and colleagues explores the accumulated evidence on the topic, and future directions for new research.
What is fisheries-induced evolution? In agriculture we are used to thinking about selective breeding: farmers select the best animals or plants to breed, in order to improve their fitness or select for certain traits in the next generation. They are intentionally trying to improve the stock used for breeding. In fisheries, the opposite happens: fishermen usually try to catch the fish that are more valuable—bigger and heavier. Consequently, those valuable kinds of fish are less likely to reproduce and contribute to the next generations.
It’s not intentional, and maybe because we don’t see the fish that are left behind, people are not used to thinking of this as selective breeding—and they may not realize that in the long term it could harm the productivity of the whole fishery.
What kinds of evolutionary changes do your research show that you would see from fisheries? Most of our data comes from fisheries institutions. We have a lot of data on maturation—the age at which fish start to reproduce. Studies show that heavily harvested fish populations may mature faster and start reproducing earlier. There’s also some data on growth, showing that fisheries pressures can lead to slower growth rates, with fish staying smaller.
In recent years, experimental studies have shown that fishing is also selective with respect to behavioral traits. Some fish are bolder than others and those bolder fish may be more likely to be captured by gillnets or traps, because bold fish are more explorative, they like to investigate things, and by doing so they may end up in a trap. But at the same time, they may be better in escaping fishing gear like a trawl.
Why is it important that we understand what’s happening with fisheries-induced evolution? At one level it’s important because changes in these kind of traits will affect the productivity of fish stocks—and based on our current knowledge, these changes are often negative, leading to lower productivity. However, some parts of these changes may be positive in the short term, because they may enable fish stocks to tolerate higher levels of fishing without collapsing. Yet in the long term, we would expect fisheries-induced evolution to lead to reduced productivity, and lower yields. And that’s quite worrying, because fish are an important part of the human diet, especially in many coastal developing countries.
What are the major questions remaining in this research? One big question arises from the fact that evolution of course implies genetic change. In fisheries, we are observing this evolution at the level of phenotypes—visible, directly measurable characteristics. To be sure that we really observe evolutionary change, we also need to understand the genetic basis for these kinds of changes.
How can you do that? There are ongoing projects trying to look at it the genetics of fisheries-induced evolution. But it’s a lot more difficult than it sounds because life-history traits and behavioral traits are affected by many genes. It’s not like there’s one gene for early maturation. There are probably tens if not hundreds of genes that have some influence on maturation. And that means that at the level of a single gene we may not see very much change at all. And trying to identify those changes and separate those from random drift, and from changes caused by other factors, is actually quite difficult.
Sequencing genomes is easy nowadays, but finding a signal in the resultant large amounts of data is not simple. If you have more data, you also get more false positives. Basically, either you need to sequence a lot of individuals, so you can separate the different signatures. The other possibility is to try to analyze data from selection experiments, because in an experiment you can try to exaggerate the changes. That’s maybe the most fruitful avenue in the short term.
Evidence for fisheries-induced evolution: research shows fisheries-induced evolution in many fish populations, including marine and freshwater species. (Credit: Heino & Dieckmann, 2015)
What can fisheries managers do to avoid unintended evolutionary changes? We’re currently exploring that question. We more or less know that it’s not possible to avoid all types of evolutionary responses. But we can still try to minimize harmful changes, by fishing in a way that does not cause much negative change in productivity.
Of course, fisheries-induced evolution will not be the only thing we care about when managing fish stocks. It has to be seen together with other objectives. Yet the simplest way of reducing unwanted evolutionary changes is to keep fishing pressure at moderate levels. That’s the single easiest and most certain way of reducing unwanted evolution, and that’s in agreement with what scientists recommend from other perspectives too.
What are the dangers of failing to account for fisheries-induced evolution? The danger is that it’s much easier to cause these changes than to reverse them—on practical time scales, these changes are more or less irreversible. So whatever changes we cause, will be around for many generations to come. That’s a reason to be precautionary. We don’t have absolute certainty that this is happening, but there’s a large body of research showing that it is quite likely to happen, and since if it’s happening it’s more or less irreversible, then we should avoiding it even before we have full scientific certainty.
There is quite a similarity between climate change and fisheries-induced evolution. Both processes happen on long timescales—at the level of a few years, the change is not much. But it is a change that will accumulate, and if you let that happen for longer periods, you end up having very significant changes. So it’s easy and attractive to ignore it in the short term, but that’s a dangerous position in the long term.
Princeton University Professor Simon Levin—IIASA council chair 2003-2008–has won numerous awards for his interdisciplinary research in environmental sciences, economics, and evolutionary biology. On 10 November, Levin gave a public lecture at IIASA, at which he was named an IIASA Distinguished Visiting Fellow.
Simon Levin speaks at the fifth IIASA/OeAW Public Lecture in Laxenburg on 10 November. Credit: IIASA/Matthias Silveri
IIASA: Your research explores issues such as environmental degradation, human inequality, and climate change. Why are global problems such as these so difficult to address? Simon Levin: To a large extent, many of these are problems not well addressed in market-based systems. The problem is that for public goods and common-pool resources, the incentives for individual actions are misaligned with the interests of society. Equity gaps and discounting of the future add to these problems, and make it difficult to achieve consensus, especially at global levels for which the feedback loops associated with individual and local actions are weak.
What kinds of approaches are needed to understand such complex, global environmental and social problems? Certainly we need systems approaches to deal with the linkages and scaling problems within these complex adaptive systems. We need interdisciplinarity, and we need more study of how to achieve cooperation at national and international levels. These are all problems central to the agenda of IIASA.
What new insights has your research brought to these problems? I have long been impressed with the power of using what we learn in one set of systems to address analogous problems in others, and have benefited greatly from what I have learned from colleagues in other disciplines. I feel that I have been able to get a great deal of mileage out of translating and adapting those lessons to environmental problems, and feel that my ecological and evolutionary perspective in particular, and what I have learned from how evolution has dealt with challenges, has allowed me to bring useful perspectives to the management of coupled biological and socioeconomic systems.
How can models of complex environmental systems inform our understanding of human systems such as the economy? We learn from such systems what makes them robust, and what makes them vulnerable to collapse; the importance of diversity, redundancy, and modularity to the ability of systems to adapt in variable environments; the importance of flexible and adaptive governance.
“We learn from [environmental] systems what makes them robust, and what makes them vulnerable to collapse” Credit: PhotonQ via Flickr
What can studies of cooperation in nature tell us about cooperation in human societies? Cooperation in nature is strongest in small groups; and as those groups become larger, agreements, social norms and institutions become increasingly important. Nobel Prize winner Elinor Ostrom led in adapting those principles to the management of small societies, and I agree with her on the importance of polycentricity—building up from smaller agreements—in addressing global environmental problems.
How can we apply such findings to find practical solutions for the problems we face? We need research, but we also need partners outside of science. Increasingly, business leaders have looked to biological systems for models as to how they can deal with challenges; we now similarly need to partner with government leaders if we are to address the grand challenges in achieving a sustainable future.
A new study by researchers from McGill University and IIASA provides insight into how environments promote biodiversity. McGill University evolutionary biologist Ben Haller, who led the study, started the work as part of IIASA’s Young Scientists Summer Program in 2010. In this interview he talks about his new study and his continued collaboration with IIASA.
Nexus: What was the broad question you were trying to answer in this work? Ben Haller: We are interested in the origins of biodiversity. The world contains quite a large number of different species. There are about 400,000 different known species of beetles alone. And beyond beetles, of course, the world is full of different kinds of plants and animals and fungi and bacteria and so forth.
Perhaps the central question of evolutionary biology is what led to all this biodiversity. Although Darwin supplied the biggest piece of the puzzle with his theory of evolution by natural selection, there is still much left that we don’t understand about the origin of species.
More specifically, our question was how variation in the environment might generate biodiversity. Landscapes vary in temperature, in elevation, in rainfall, and in all sorts of other environmental variables. Environments vary biotically, too; some forests are dominated by conifers, while other forests are dominated by deciduous trees, for example, and that creates very different environments for all of the birds and mammals and insects and so forth that live in those forests. We know that this environmental variation promotes biodiversity; organisms in different environments will evolve to “fit” the environment they are in, and this can lead to the development of new species.
Previous theoretical models have simulated this process. Simulated organisms would be placed into a simulated environment that had some sort of variation in it, and the simulated organisms would evolve divergently and become different species. But these models only looked at extremely simple, artificial environments. We wanted to look at more realistic environments, with more random variation in environmental conditions, to see whether a sort of patchy quilt of different environments across a landscape had a different effect on biodiversity than the simple forms of variation used in earlier models.
In your paper you found something called a “refugium effect.” What do you mean by that? We found that complex environmental variation promotes the creation of new biodiversity, through a phenomenon that we have called the “refugium effect”. A refugium is a place of refuge.
Imagine the sort of simple environment that has been studied before, with a smooth, continuous gradient from environment type A to environment type B. Maybe a gradient in elevation, for example; our model does not make any assumption about what aspect of the environment is varying, but we can think of it as elevation. If a species is adapted to a particular elevation in this environment, it can be hard for that species to move around in the landscape. It lives at its optimal elevation, and if it ventures outside of that zone, it encounters conditions that it is not well-adapted to, and it has trouble establishing new populations and colonizing the landscape. As a result, that species might never diversify into other species adapted to other elevations.
Now imagine a landscape with a more complex topographic profile, with high points and low points scattered somewhat randomly across the landscape. That’s the sort of environmental variation that we modeled in this study. A species adapted to a particular elevation can find spots that have that elevation in many places in the landscape. These are refugia. The species can immediately disperse into those refugia and establish new colonies. Those colonies will be largely isolated from each other, however, due to their geographic separation, so they can follow independent evolutionary trajectories. And importantly, the refuge provided by a refugium is limited, because the refugium is surrounded by different habitat; land at a different elevation, here. A population might scrape out a living in a small refugium, but many of its offspring are going to end up in that surrounding environment, and so there will be a strong pressure to become better-adapted to that surrounding environment. While the refugium provides an initial foothold, in other words, the pressure is ultimately to leave the refugium and become adapted to the surrounding conditions. And when that happens, a new ecotype, or perhaps a new species, has been created.
You created a model of an environment in order to investigate how complexity can affect biodiversity. What kind of environment does your model represent and what kinds of organisms live there? Well, it’s really fairly abstract. While we’re trying to bring our model closer to the real world, I don’t want to give the impression that we are simulating anything like real environments and real organisms. In our model, the environment varies in just a single characteristic, and the pattern of variation, while relatively complex, is still much simpler than the variation in the real world. Similarly, the organisms in our model vary in just a single trait, corresponding to the single axis of variation in the environment.
At present our model is also of asexual organisms that disperse at birth; this is similar to many plants, for example, but is less applicable to most animals. The model is never going to be a sort of hyper-realistic model of real-world environments and organisms; that would not actually be desirable, as it would then be just as impossible to analyze and understand as the real world is!
The power of theoretical work is that you can distill a real-world question down into a very simple, abstract form and get a very simple, abstract answer, uncluttered by all of the complications that exist in the real world. At the same time, though, the specific things I’ve just mentioned are things we’d like to work on next: looking at landscapes and organisms that vary in more ways than one, and looking at sexual organisms with perhaps more animal-like movement behaviors.
Besides the refugium effect, were there other new findings from the study? We also showed that environmental variation is a bit like the story of Goldilocks and the Three Bears; for promoting biodiversity, you can have too little variation (which doesn’t promote diversification), or too much variation (which makes it too difficult to diversify), or the variation can be “just right”. That had been shown before for very simple environments, but we generalized that result to a broader class of landscapes and variation, which is an important result.
And finally, we showed that the spatial scale of environmental variation is important to diversification. Imagine a landscape with very fine-grained variation, and a species with a very long dispersal distance. The species will not be able to adapt to fit different local conditions, because it doesn’t “fit into” any one local patch in the environment. Now imagine a landscape with broad-scale variation, continent-scale variation perhaps, and a species with a much shorter dispersal distance. Now whole populations of the species will “fit into” different local patches with different local conditions, and so those populations will diverge and become different ecotypes or different species.
Three views of one run of the model: Left: a complex landscape, generated by a method described in the paper. Center: A population of organisms that have adapted to local conditions in the environment. Right: The evolutionary history of the population depicted in the center panel, with time proceeding from left to right and phenotype shown on the y-axis.
How does this research apply to the real world? I think it’s important in two ways. First it’s very important that we work to conserve the biodiversity that exists today, and it’s very hard to conserve something that you don’t even understand. Humans are presently causing a vast wave of extinction around the planet, because of activities from deforestation and climate change to overfishing and industrial agriculture. We would like to find ways to moderate those negative effects on the biosphere; but to do that, we need to really understand how the biosphere works and how it responds to our actions. Our study is a very small piece in that puzzle.
The other way is more speculative but perhaps more direct. Our model is a model of how environmental variation promotes biodiversity. It is also possible, however, that the factors that we have found are important for maintaining biodiversity, as well as for producing it. If we homogenize the environment, as humans often do – think of cutting down rainforest to make soybean plantations, or draining wetlands to make cities, for example – we might be removing the environmental variation that maintains existing biodiversity. It’s not a new idea from an ecological perspective, but I think it’s a fairly new idea from the evolutionary perspective. Even if a species can persist in an ecological sense – even if it has sufficient habitat left to survive – it might not persist for evolutionary reasons.
We tried hard to connect our research to the real world, to make it concrete and testable. In particular, although we used simulated landscapes in our model, we measured their characteristics using metrics that could equally well be applied to real-world landscapes. So when our results indicate that refugia have such-and-such a quantitative effect in promoting biodiversity in a landscape, that result is expressed in a way that field biologists could go out and test, or perhaps laboratory biologists could test using an experimental system like bacteria or yeast. We’d very much like to see our theoretical results tested empirically; that back-and-forth between theory and experiment is at the heart of science.
You started this work as part of IIASA’s Young Scientists Summer Program. How has that experience influenced your research? For one thing, it brought me into contact with my collaborators on this research, Ulf Dieckmann and Rupert Mazzucco. I have learned an enormous amount from them, and their ideas have profoundly influenced my scientific trajectory. This was particularly important for me because my PhD supervisor is primarily a field biologist, not a theorist. Working with Dr. Dieckmann and Dr. Mazzucco in the YSSP gave me experience in working in a more theory-focused environment, and that was very important for my development during my PhD.
Another thing is that the YSSP has opened up international collaboration for me in a way that would not otherwise have been likely to happen. I’m American, and it can be hard to get funding to go to conferences and initiate collaborations with scientists “across the pond”. The YSSP, and the funding I received for it from the National Academy of Sciences, let me break through that barrier. Now, in addition to ongoing work with Dr. Dieckmann and Dr. Mazzucco, I am also involved in research with a group in Zurich, and I have made connections with scientists in Sweden, Japan, Finland, France, South Africa, Germany, Hungary, Greece, the Netherlands, and on and on. The YSSP is wonderfully international, and so it is a great way to break into the international community of science. That’s an immensely valuable thing, since the cross-fertilization of ideas from different perspectives drive our thinking forward.
It has also advanced my career in very concrete ways. As a result of my YSSP project, I ended up with a publication in a major journal, a chapter in my PhD thesis, and a possible place for a postdoc down the road, and famous scientists from whom I can get recommendations when I start looking for a tenure-track job.
But most importantly, I would say that participating in the YSSP made me think about my research in a much broader context than I otherwise would have. In the YSSP, I was surrounded by fellow graduate students who were not evolutionary biologists, but rather were researching issues of land use and politics and global hunger and sustainability and climate change and deforestation and nuclear disarmament and all of the other things that IIASA works on. That experience really encouraged me to think about how my work in evolutionary biology connects to all of those other things. It promoted a big-picture perspective, an interdisciplinary outlook that has stayed with me.