This week we conclude our two-part discussion with ecologist Mark Ritchie of Syracuse University on how he and his SFI collaborators are starting to rethink the intersections of thermodynamics and biology to better fit our scientific models to the patterns we observe in nature. Most of what we know about the enzymatic processes of plant and animal metabolisms comes from test tube experiments, not studies in the context of a living organism. What changes when we zoom out and think about life’s manufacturing and distribution in situ?
Starting where we left off in in Episode 62, we tour the implications of Mark’s biochemistry research and ask: What can studying the metabolism of cells tell us about economics? How does a better model of photosynthesis change the way we think about climate change and the future of agriculture? Why might a pattern in the failure of plant enzymes help biologists define where to direct the search for life in space?
A better theory of the physics of biomolecules — and the networks in which they’re embedded — provides a clearer understanding of the limits for all living systems, and how those limits shape effective strategies for navigating our complex world.
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
If you value our research and communication efforts, please subscribe, rate, and review this show at Apple Podcasts, and/or consider making a donation at santafe.edu/give. You can find numerous other ways to engage with us at santafe.edu/engage. Thank you for listening!
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Related Reading & Listening:
Ritchie Lab at Syracuse University | Mark’s Google Scholar Page | Mark’s soil ecology startup
Reaction and diffusion thermodynamics explain optimal temperatures of biochemical reactions
by Mark Ritchie in Scientific Reports
Thermodynamics Of Far From Equilibrium Systems, Biochemistry, And Life In A Warming World [Mark Ritchie’s 2021 SFI Seminar + @SFIscience Twitter thread on Mark’s talk]
Scale and information-processing thresholds in Holocene social evolution
by Jaeweon Shin, Michael Holton Price, David H. Wolpert, Hajime Shimao, Brendan Tracey & Timothy A. Kohler
Generalized Stoichiometry and Biogeochemistry for Astrobiological Applications
by Christopher P. Kempes, Michael J. Follows, Hillary Smith, Heather Graham, Christopher H. House & Simon A. Levin
Complexity 4: Luis Bettencourt on The Science of Cities
Complexity 5: Jennifer Dunne on Food Webs & ArchaeoEcology
Complexity 17: Chris Kempes on The Physical Constraints on Life & Evolution
Complexity 35: Scaling Laws & Social Networks in The Time of COVID-19 with Geoffrey West
Complexity 41: Natalie Grefenstette on Agnostic Biosignature Detection
Alien Crash Site 15: Cole Mathis on Pathway Assembly and Astrobiology
Podcast theme music by Mitch Mignano.
Cover artwork adapted from photos by Peter Nguyen and Torsten Wittmann (UCSF).
Mark Ritchie (0s): As we change temperature, it's not about how that's affecting production and that's part of the issue. But the other part of the issue is how are we changing the nutritional content of our plants and how can we get around doing that? And so what can we even do about? And because we're talking about these fundamental physical properties, it may not be something that you can get around with genetics. We'll just bioengineer a plant that can grow at hot temperatures, but it's also a high quality. Well, the genetics are happening in this physical context.
And so those thermodynamics are sort of irrevocable, then genetics isn't going to permanently solve the problem.
Michael Garfield (1m 1s): Welcome to Complexity, the official podcast of the Santa Fe Institute. I'm your host, Michael Garfield and every other week we'll bring you with us for far ranging conversations with our worldwide network of rigorous researchers, developing new frameworks, to explain the deepest mysteries of the universe. This week, we conclude our two-part discussion with ecologist, Mark Ritchie of Syracuse University on how he and his SFI collaborators are starting to rethink the intersections of thermodynamics and biology to better fit our scientific models to the patterns we observe in nature.
Most of what we know about the enzymatic processes of plant and animal metabolisms comes from test tube experiments, not studies in the context of a living organism. What changes when we zoom out and think about life's manufacturing and distribution in situ. Starting where we left off in episode 62, we tore the implications of Mark's biochemistry research and ask what can studying the metabolism of cells tell us about economics. How does a better model of photosynthesis change the way we think about climate change and the future of agriculture?
Why might a pattern in the failure of plant enzymes help biologists define where to direct the search for life in space? A better theory of the physics of bio-molecules and the networks in which they're embedded provides a clearer understanding of the limits for all living systems and how those limits shape effective strategies for navigating our complex world. If you value our research and communication efforts, please subscribe, rate, and review this show at Apple Podcasts and/or consider making a donation at santafe.edu/give.
You can find numerous other ways to engage with us at santafe.edu/engage.
Michael Garfield (2m 48s): Thank you for listening
Mark Ritchie (2m 51s): Cell can't just be full of insights because if the enzymes in the middle that they make a product that has nowhere to go, because there's no empty space for it to be able to move in and out of the cell. And so we have this fundamental problem of the cell, the more work it does, presumably the more divisions it makes or whatever. So you can imagine that cells that do lots of work would be favored by natural selection, but at the same time, it can be full because it needs to have space for stuff to move through.
So the problem we were looking at was how much space is really required. And so we then get down into issues about like, if something is moving through a fractal-like distribution of obstructions, what actually determines the likelihood that it will leave or the rate at which something will leave from some mean position in the middle of the cell. So in the end, we ended up combining some of the work that I'd done thinking about fractal distributions and fractal objects and the ways of describing those with work that Chris had been doing with how many ribosomes were in a cell.
And so like, how much should we say machinery is in the cell, that's doing work. So we have succeeded in solving the problem, but only with numerical simulations at this point. So we're still looking for a more analytical solution, which I think is out there. I just haven't had time to get to it. And Chris has also worked on it. But fundamentally what we then discovered was that these kinds of first principles would generate something that had been sort of out there, but unexplained. So when people started measuring metabolic rates of single cell organisms, all the way down to the smallest bacteria, what they found was that instead of like what Geoffrey West found, especially mostly for vertebrae data, was that metabolic rate tends to increase with mass to the 0.7, five or three quarters power.
So the original science paper that in 1997 and all the subsequent work has been about trying to understand why that exponent is three quarters as opposed to two thirds or something else. But when people looked at bacteria, they found that that relationship curved. So nobody really understood why it curved and nobody understood why it was so steep. So that even at the smallest sizes, you were actually scaling with an exponent greater than one. So this is called super linear scaling. And so it turns out that exactly what you were describing. When you start off small enough, you don't have a problem of diffusing your products.
Like the very smallest cells are barely big enough to hold some of the more standard enzymes that are used in tablets. So once they produce a product, it takes almost no time at all for that to be able to leave the cell. But as the cell gets bigger and bigger and bigger, if the enzymes are uniformly or randomly distributed throughout the cell, then you end up with this dead zone in the middle where it stuff can't get out. So then that means that you're going to favor cells that aren’t full of enzymes. They are going to have a lot of empty space in there because then each one of those enzymes that is remaining can sort of act in its full capacity and you can do more total work.
And so it turns out that the scaling of those things then gives you the super linear scaling of the smaller sizes because as you add size, you sort of like double or triple the number of enzymes that you can have as you expand in the scale, because the enzymes are discrete thing. So it's kind of like if I have a trash can and I have cubes of a certain size, they don't just automatically all perfectly fill up with a circular trashcan. You're going to have some empty spaces and stuff, but the bigger the trash can, the more likely you are to be able to more tightenly pack those in.
So that's what generates a super linear scaling. Then it just starts to bend around as you get to this point. And it turns out interestingly to be that point at which it starts to bend around and become the exponent less than one is about the point at which you have the largest bacteria kind of reach the general upper limit. There are a few exceptions which are kind of interesting, but you switch over to eukaryotes at that point. And so eukaryotes and there's like four or five different major theories about how and why they evolved to be the way they are, but they compartmentalize.
So they basically then creates these specialized organelles that do certain jobs. And they also have a lot of their enzymes on structures that are themselves fractal-like and people have actually measured the fractal dimension of these things in they're definitely not just uniformly distributed throughout the cell. So why compartmentalize? What's the advantage of doing that? The ultimate thing that happened was as you get bigger and bigger and bigger, then the exponent just settles down right to three quarters.
But the interesting thing is that we haven't made any assumptions about like a vascular network or any of those kinds of scaling arguments. It strictly comes out of the fact that you're optimizing the amount of work that the cell can do, given that it has to move stuff in and out. And so it's just about how much empty space. It doesn't really say anything about the particular configuration of the space. Other than that, we're assuming that the particles are moving according to a random walk as they bounce around inside the cell. So we're really close to having a paper finished that pulls all these concepts together.
That includes thermodynamics, which goes back to the issue that the reactions reverse, if you can't dissipate products and the idea of fractal organization and the trade-off between needing to move stuff and do work. And so it would extend almost beautifully cause the curve that is one of the interesting things is if you just put in all the standard thermodynamic parameters and diffusion coefficients and stuff like that, that people have measured for cell, just take an average and you've plugged those right into the math. Then you get a curve that sits right through the data points.
You don't have to fit it. So basically it provides an alternative explanation for what's happening at single cells that don't have organized or pressurized vascular systems, but that seamlessly merges into the theory of [complex organisms] in which you do have pressurized vascular systems. And so then it asks these really cool questions like why are you forced to use pressurized vascular systems when you get up to about a mass of about a grant and there are organisms that use them and even smaller sizes, but that sort of seems to be the limit of which you hit that.
Why do eukaryotes compartmentalize things or the other way of saying it is? How is it that bacteria are still around given that they can only get up to a certain size? And it also begs the question of, so is that what viruses problem is? Is that because they're so small, they can't fit enough enzymes. So they have to borrow somebody else's space in order to do the work so that they really are the ultimate parasite, which I guess that's everyone sort of thinks is a virus that way but basically what we're arguing is that there's a physical explanation for why that happens in a certain site.
So that's some cutting edge stuff that we're doing and it's really, really cool and it kind of does synthesize a lot of the work that both of us we've been doing over the past decade or so.
Michael Garfield (10m 4s): You would be then I think the right person to, to pose a question that I posed to Geoffrey West in episode 36 and which to which he kind of just threw up his hands because his work predicts that the ongoing acceleration of cities as the demographic shifts continues and the human population grows that you get into the accelerating innovation crisis cycles, where you're constantly creating the externalities that then come back to bite you and you have to solve your way out of the problem that was created by the unintended consequences of your last innovation.
So he plots this on this sort of ever steepening stair-step into the finite time singularity where he's like, this is the point where we either come up with a new internet level innovation every six months or civilization collapses. Those are your options. But when I look at this and everybody in the tech world seems to be trying to innovate their way out of the crisis created by innovation at the sort of meta level. But to me, listening to you talk about, well, there's a natural, upper bound set by thermodynamics on the size of a bacterium.
And, you know, and we talked about that with Chris in episode 17, how that kind of sets the stage for these transitions into complex cells and that you see a similar, not identical, but something like that is going on in the transition from single cell eukaryotes to multi-cellular complex life. And so it kind of suggests to me, first of all, that human population, when people talk about collapse, people think of it in very sort of binary terms. Like we're either going to solve all of these problems and we're taking this to the stars or it's the end of human civilization and possibly the biosphere, and there's no sensitivity here to like the sign wave that we might be on, or the fact that all of this is precipitating some kind of major evolutionary transition in the structure of human civilization, which work by David Wolpert and Tim Kohler and others at SFI, Hajime Shimao, et cetera, have looked at this kind of thing through history happening again and again and again, that, you know, population scales to a point that begs a new information architecture.
And at any rate, I'm just curious if you feel like this work that you're doing with Chris offers a possibly predictive model for the bounds of the size of cities and of the pace, the upper limit for the pace of civilization and whether it's suggests not equilibria per se, but reliable, quantitative thresholds that we should shoot for or mind over the decades to come.
Mark Ritchie (13m 1s): Yeah. I mean, since we're speculating, but one of the things that the theory predicts is that in fact, the three quarters exponent, isn't like at least from the mechanism that we're looking at is that really some hard and fast geometric rule. The number you get is still a function of the thermodynamics. So it turns out that in fact, that exponent is actually decreasing slightly as you get bigger and bigger and bigger. And so you can actually calculate the point that like how big of a metabolic entity you can have to the point where you get where the thing is strictly surface to volume ratio.
It's basically about heat dissipation complete. Well, it turns out the size of that is something like six times 10 to the eighth, bigger than the biggest dinosaur. Now you can say when you get that big, you have vascular system. So your model shouldn't even really work. But my point was, if you did create vascular systems so that you could increase the speed of movement and things, then that presumably means that you could have a metabolic entity that could be much, much bigger than that.
So what that to me suggests is that if we think of the planet is like an organism that's like spread super thin. So we think about the atmosphere and the surface of the earth setting the upper and lower bounds as a geometric object. But if you think about it as an entity, as a metabolic entity or whatever, that, I don't think that there may be limits step, but those limits are probably set by the speed at which you can move materials with them. And it would also suggest that there's a certain amount of space that has to be allocated to that movement.
If we're just thinking about all I'm thinking about is sustaining metabolic and like the work that people are doing. So you can think about it and money flows. That's essentially how the internet has provided the cheat code. Because as we discovered during COVID, we can sit in the same chair in the same spot day, day after day, and still function at some level. And why, because we can get somebody to bring food to our house. Point is that at some point we're still limited by the ability to get materials to our own bodies, but we're able to multiply that same material into like 15, 5500 times much economic activity, because we can use essentially the information flows of the internet.
I mean, we've known since the seventies, Paul Ehrlich's population bomb and all of the massive amount of work that's been done by NGOs across the developing world that may have a thermodynamics problem of how much solar energy can be converted into metabolically useful energy, because there's all those inefficiencies that we’d have to deal. So a lot of people focus on how much agricultural land can we even have, and is there a way to increase the efficiency of the land you're using? So there's that issue, but then the other issue is distribution.
So if you ever fly, I don't know, most people forgotten flying somebody on a call today who was at an airport. He's like, wow, I forgot what an airport even sounded like. But anyway, but if you ever fly over one of those so-called mega cities, things that are like 20 million people, what you see is that there's part of the city is connected by fast moving hubs, allows really rapid movement of materials at well over the speed that's required to deliver it and support metabolic activity of humans.
But a large fraction of those cities are we would call them like shantytowns or they have various names. But basically if you look at those, you can't even see how people move in and out of them, it's just basically like a solid wall and roofs, which is almost analogous to the cells that Chris and I were imagining of just being full of things that do work, but there's no way for them to get their products out. So you look at those and those are like massive centers of poverty. And they're self-organized because nobody came in and said, okay, you put your shack here or your house there.
They just sort of built in a self-organized way. But because the flow of materials and stuff is so low because of the word nature of them, then you don't have to sustain such a rapid movement of things because the activity is low, but then you can't accelerate that because it doesn't have the capacity to deal with a greater amount of economic activity. And so to the extent that you get positive feedbacks in these things, so the roads are so narrow that you can literally touch doorways with your arms, to having four lane freeways moving in and out of the city center or mass transit things that move rapidly in and out.
So you have the two alternate feedback. So then you build up this inequity of the ability to sustain metabolic activity. So if people say, well, we want to develop alternative livelihoods and markets and stuff in these poor areas. It's really hard to do because you can't, I mean, I don't know about the math, I'm just speculating here, but you just simply can't move things in and out of those systems as rapidly as you can other places. And so it might behoove from a very, very, very high up level about this whole issue about distribution networks and the inequity in those networks maybe the thing that's actually limiting our ability to produce things as humans, not because we've designed it that way on purpose, because most of these things are self-organize. So for me, the question is that if you just let people self-organize on what they're doing, then the amount of economic activity that they're engaged in will end up producing feedbacks that lead to these big discrepancies. And then you have this ever-growing larger portion of the population that can't participate in the rapid economy. And then you have this huge disparity in revenues and income and so on.
So it kind of goes back to the points that you were making that is our limit, some physical limit, like in terms of we can design the world and then ideal fashion, could we be doing more than what we're doing? I'm pretty sure we could, but letting local self-organization principles that are operating under different constraints play out, then produces these discrepancies in the ability of things to move in and out of human systems. So that ultimately on a per capita basis puts a limit on our productivity.
So I don't know, I'm trying to play along here and extending the things that we're learning about what's going on inside a cell, to the work that people have been doing with how cities are organized. And I'm probably trampling on top of people's sites. If you don't know what the hell you're talking about, because we all know that X, Y, and Z. So I, you know, I get it, but I'm just saying that I'm not sure that people often think that things like the internet and communication networks are still somehow ultimately constrained by material networks.
And we still have to get raw materials to build houses, to eat, to drink. And people point out that one of the biggest environmental problems, aside from the global warming issue, as things like fresh water or access to health care, all of those things are related to physical networks like healthcare. I can tell you better things to do over Zoom, but ultimately there's really no substitute from having healthcare professional and person meet face to face. You just can't ever really truly get around that.
So you still have to be able to move people around and people have to have access to things. And I know people who if the only place I could go to find a doctor is to go downtown New York City. I would never see a doctor because I just don't. I'd rather die than have to deal with that environment because it's just like they can't mentally process it. Whereas people from New York City, if I have to go sit in a log cabin for three months until the pandemic is over, that would probably have equal mental stress and strength. So if a connection it's probably due to what leads to the inequity in these distribution networks.
And to what extent does that inequity put a constraint on the behavior of the whole system. So you can have all the innovations you want, but if they only apply to an increasingly smaller and smaller proportion of the population, eventually there's a tipping point at which the larger proportion of the people are not being supplied with materials, goods, and services they need, which you can really ultimately think of is like an unacceptable level of entropy in the system. So then it just kind of collapsed because it can't stay organized.
Michael Garfield (21m 24s): Well, a couple things there. One is New York City. Have I ever been anywhere where the challenges of diffusion transport across the membrane of a city are not more obvious. The amount of effort it takes to get out of New York when you're in it is unbelievable. And to that point that you were making about slums and shantytowns and so on. When we had Luis Bettencourt on the show, back in episode four, he was talking about exactly this thing. You stage an intervention by using network models, to identify where in a slum streets should go for better transport of materials and people and so on.
But you're right. It is an interesting analogy to chew on that people tend to think in terms of the sort of ideal of what is possible given top-down technocratic management, but that always bumps up against precisely the kind of hidden limits and constraints that you're identifying in this paper. I think about that in terms of this is not just about how do we properly refrigerate our server firms so that we can continue to grow the surface area of the planet for better dissipation in our computations.
But there's this other piece that you spoke to. And I think that this is where it really comes back down to earth in this conversation. In your talk you spoke about how the decline in the availability of elements with increasing temperatures reduces trophic transfers and ecosystems. It gets to this point of like, well, you might have the best idea in the world, but if you can't recruit the resources required to execute it, it's never going to happen. And I would love to hear you speak to this piece of it in particular, because this is sort of where the buck stops in terms of the implications of this application of thermodynamics to biochemistry.
You say the nutrient density of crops is declining with global warming. So we can't just make this place hotter and hotter and somehow still apply a perfect solution to it because the material substrate upon which those decisions depend is falling out from under us. And I'd love to hear you speak to these two curves.
Mark Ritchie (23m 37s): This is something that we study in trophic interactions and ecological systems. So we have one place where you have this high amount of rainfall, massive amounts of productivity, and relatively little of that productivity ever gets consumed by another animal. So most tropical rain forest, while they’re massively good at decomposing dead materials, most of the productivity that's produced in them is never consumed. It just dies and then decomposes. So how do I compare a system like that that's massively productive.
But if I actually look at how many things in sort of the total mass of things that are being supported by that productivity, it's much lower than if I go to let's say a grassland like Serengeti or the Great Plains in North America, where historically, or even still currently the animals that are in an equilibrium with the resource that at least according to the numbers are eating anywhere from 40 to 70% of what's produced. So the question is why and how do we get these differences? Well, the differences are driven by what is the nutrient content of the plants.
And so then the question is, we have environmental factors that are controlling nutrient content, as well as environmental factors that are controlling the total amount of production. So any crop agricultural system is faced with that same dilemma in the sense that I can grow massive amounts of sugar cane, huge biomasses that far exceed the production of corn or anything like that, huge biomasses. But most of what's produced is inevitable to people.
Whereas you can get these huge densities of animals and Serengeti living on something that only grows this tall and their differences, the nutrient content. So an agricultural systems and agricultural research organizations and universities and programs have for years been focused on production, like how much crop can you produce? And not that much work has really focused on the idea that well, as environments change or across different kinds of soils and rainfall and that kind of thing, then how has that actually changing the nutritional content?
And I think mostly that's because nobody has ever, and especially with temperature, nobody ever really put the idea together that if I changed the temperature that the optimal nutrient content for the plant to grow at those higher temperatures is actually lower than would be if it was cooler. That's just a hypothesis. It doesn't really have a current physiological explanation, even though people have started to notice the patterns. And so the reaction diffusion thermodynamics would predict that that should happen. And the reason is, is because as it gets hotter and you have this bigger problem of trying to dissipate heat and products, then each enzyme can much, or as much more likely to be able to produce as much product as you can handle without having the internal entropy of the system increased too much.
So therefore I don't need as many enzymes, I don't need as high a concentration of enzymes. And since much of the nutrition in a plant comes from things like chlorophyll and other proteins and stuff, they're all related to the amount of work that plant leaf can do. Then that means that those plant leaves and to some extent, by proxy to things like seeds. So if you're talking about corn or you're talking about wheat rice, then there's essentially less nutrients in the plant to be able to put into those crops. So that's the connection between the biochemistry and crop thing. Again, there's a whole button where people would be screaming at me like, well, there's a whole bunch of leaps you just made there that you don't really have good experimental evidence one way or the other for that because nobody's bothered to look or if they had, it was just as one of the steps and they didn't see how they all fit together. So I think the thing that we have to realize for me, that's the main thing. It's just thinking that as we change temperature, it's not about how that's affecting production and that's part of the issue. But the other part of the issue is how are we changing the nutritional content of our plants and how can we get around doing that? And so what can we even do about that? And because we're talking about these fundamental physical properties, it may not be something that you can get around with genetics.
I mean, that's the thing is everybody's, we'll just bioengineer a plant that can grow at hot temperatures, but it's also a high quality. Well, if that causes the plant to suffer from it dynamically, for reasons that have nothing to do with the particular genetic, I mean, the genetics are happening in this physical context. And so those thermal dynamics are sort of irrevocable, then genetics isn't going to permanently solve the problem because you're going to have plants that don't do that, that ended up doing better than the plants are doing. So it's just something that we have to keep in mind and to recognize that by the same token, cold temperate areas that never used to be able to grow crops because of the growing seasons are too short, maybe come are prime agricultural areas now because they're still cool enough to raise high quality plants.
And now they're warm enough to have a long enough season that you can actually produce a crop. The downside is most of those areas because they had short growing seasons they often hold high carbon stocks because they have these seasons of productivity. There's carbon that goes in the ground. But because it's so cold, most of the year microbes don't break down the organic matter. So the organic matter builds up year after year after year after year. So you get these areas with really high carbon stock. So now I'm going to convert those into farm fields. Then all of that carbon that was stored, there just goes right to the atmosphere.
So it's kind of like, there's like all these multiple unintended consequences that you have. So that's what makes ecology so fun and also so frustrating because policy people say, well, just tell me what solution I can use. Like, well, you need to try out like 15 different things and see which one actually works because there's too many variables for us to tell you the one right now. That's just some of my thoughts about it. But in terms of like engineering, how we deal with global warming, we need to be prepared. I think that there may be some fiscal inevitability that are built into the fundamental biochemistry of photosynthesis and the way that organisms do work that might cause us to have to rethink how we're going to respond to that.
That's like, can we expand the corn growing region far enough northward, fast enough to keep up with climate change or does cultural barriers to doing that, make it hard for someone in Canada, who's never been able to farm corn because of the growing season. Now you have to think about farming corn instead of wheat. Those are other social issues that influence how things change. But I think that we have to ask those kinds of big questions. They cross national boundaries. They make us think more in terms of like whole biomes and very, very large landscape ecosystem type questions, rather than thinking about it from a biotech point of view, which is, well, I just need to engineer the gene and the plant that will make it do what I want in this particular environment.
Michael Garfield (30m 38s): I mean, that's not even mentioning how much more nuance you have here than the brute force. Let's just throw a bunch of calcium carbonate up in the atmosphere. And let's say, I had, I guess, a last comment on what you just said, it's funny how much deeper the discipline of ecology has become since we realized. And you know, a lot of historians peg the sort of advent of cybernetics to World War II, targeting computers, but also to the nuclear bomb and the recognition that fallout gets up into the jet stream and blows all over the world.
And there is no outside anymore. Just to kind of tie a bow on this, I think your work is so fascinating in that if you propose as you kind of hinted at a moment ago that the earth is something approximating the upper bound of one of these surface area maximizing intelligent living systems, where does it export it's like where are we at some point the conceit that we can control everything bumps up against the real physical membranes that we're dealing with here, and one of the things I love about the conversation going on right now at SFI around what engineering and design look like in light of all of this is it's not some sort of omniscient control of the markets or of architecture, but a tango with this adaptive intelligence that lies all around us and is distributed through all these systems.
And super glad that we got the opportunity to talk. And I would love to know what, if anything, have we not discussed today that is the cutting edge for you. Like where is your curiosity tugging you right now?
Mark Ritchie (32m 28s): So I guess we could start the argument that a lot of people have argued that basically beef is bad. So if we want to change the climate and we all have to stop eating beef or things that are produced on factory farms because of the inefficiency and because of the particular case of ruminant animals, the methane that's produced. And then there's also calculations people have made that people have suggested that in fact, beef is also produces a lot of nitric oxide, which if we convert it to the equivalent, CO2 is a major thing.
So one of the things that goes back way in time in ecology has been this idea that we have kind of like this production in the absence of consumers. And then if we have consumers, they just sort of reduce that production down to some level, whether it's just a little bit like in the rainforest and talking about earlier a whole lot, like in any grasslands. So one of the big questions has been, is it possible to take the 40% of the Earth's land surface that's considered rangelands? So these are lands that are too dry for crops, generally speaking, or they're on incredibly poor soil.
So they're too nutrient poor for crops. Even if we put in massive amounts of fertilizer, they often get too much rain and the nutrients just leach out of the soil. So you have these massive areas across the blood surface that really the only way as we know of it now for humans to gain functional calories and nutrients from those systems is to raise them with animals. So the question is, is the methane of those animals, is that the only thing that we need to worry about?
Well, so one of the things that I've been working on in the last decade is this idea that when animals graze the system, they only have episodic effects, which then allow the system to recover. So from a very SFI point of view, we have the network of trophic exchanges that then is essentially disrupted by a heavy amount of, you know, so some parts of that network are massively disrupted, but only for a short period of time. And then the network has the opportunity to be resilient to that.
And so long ago, Sam McNaughton working in the Serengeti when he was sitting there looking at it, he made measurements that suggested that when we have this kind of episodic grazing, it actually leads to higher production of the system because the whole ability of the system to gather, so say assimilate carbon dioxide, and through photosynthesis, you basically go through that same process. And the reason is because you're putting the system back into a place where the plants are no longer resource limited again. So the net thing is that, so when you have this episodical herbivory and you have this regrowth of grass that follows the herbivory, the total amount of photosynthesis over the whole of the season is higher, under grazing than it would be without.
So there's been this huge moment in the agricultural field, and it has like a ton of different names. It's gone from rotational grazing. What I call it now as short duration identity, the idea that we get a bunch of animals, we keep them together. We move them around relatively rapidly. So they're never in one place very long, but they have a really strong impact when they're there, but then they're gone and there's all this time and plants to like resource to regrow. And so if you convince systems like this, that you can actually increase the amount of carbon that's assimilated by the system and therefore increase the amount of carbon that's in the soil.
So in a few of the cases now that people have studied, and again from a lot of scientists are not really on board with this because it hasn't been done in controlled experiments, but we have lots and lots of little test cases that would suggest that when you implement this kind of, and it's actually a form of mimicking natural systems, because a lot of the natural systems are migratory, but we've lost that because we've encroached on all their space. So when we mimic the natural systems, which are engaged in this episodic trophic transfer, followed by resilience and recovery, then the amount of carbon being captured in the soil far exceeds the methane is produced by the animals that are doing work.
So a while back, I formed this little company called Soils for the Future, which eventually sort of settled into being a consulting company where I basically would make some measurements and do some modeling exercises and do things. And we worked on this project in Northern Kenya, where we got local pastoralists to start having their animals mimic the movements of wildlife so they were much more migratory and never stayed in the same place for very long. So we've actually got that point to the thing where we can demonstrate that the improvement of practices is actually sequestered way more carbon in the soil than the methane that the animals are produced.
And so now everyone is trying to figure out how they can apply that to their system. So my little company that used to just get a couple months of summer salary equivalent of income, because now the deluge by people that are interested in trying to see if they can do this, even to the point that the whole country of Uruguay, the government of Uruguay wants to basically turn their entire country into a grazing management carbon project. So the key to all of this new work that's been doing was there was a student named Jacob Penner at Syracuse who went to Yellowstone and he did this experiment where he clipped plants each plant exactly by 50%, most tedious thing I can ever possibly imagine.
And then he measured the productivity of those things after the clipped. And he showed quite clearly that there was an increase in production that came from doing this 50% clippings. So he had brought in this one paper that had some math about it, and I was looking I'm like, well, this paper's like missing the whole thing about plants. They grow up bigger, biomass become much more resource limited. So how is it he changed that? And then when I did that, then all of a sudden how popped all of these outcomes that were measured 30 years before by Sam McNaughton and Serengeti, so I'm sitting there going, okay, and then I'm thinking what, ecologists, I've never really looked at trophic interactions in this way.
They always just kind of assume that if there's something out there eating it, they're kind of always eating. So everything is kind of at a steady state and it's described by differential equations. So there's this rate of removal and a rate of production. And so everything is sort of always happening all at the same time. So when you change that up and so things become happening as episodes are in discrete time intervals, then the whole dynamics of the system change. And I'm sure there's like hundreds of people out there studying networks and how they respond to pulses of disturbance and all kinds of other things like this.
But in really complex systems, it's really hard to study that except in like specific simulations where you're like, okay, I'm going to mimic a certain kind of network and I'm going to do stuff to it computation because you can't really study it with differential equations because you have to know the time dependent function of change. I did it analytically, but I used simplest possible functions you can possibly use. They're missing a lot of stuff we're not going would say, so we normally don't have any college time dependent functions or anything. So it's really hard to study how these episodes play out other than in simulations.
So to me, the thing that we need to get together moving forward is thinking about this in a broader context, way beyond grazing and soil carbon, and thinking about how necessary is it that we accommodate the idea that we build networks, that they ultimately have to go through cycles where they get disturbed, and then they have to show some kind of resilience and that the total amount of work done by these networks systems is much greater when that actually happens then if we just assume that they're constantly at some sort of steady state. And I'm sure there's people that have studied this, and I just haven't had time to go look at the general literature, but to me that it's like a great potential connection between solving some real world problem of, should we eat beef is a way to eat beef in a way that's friendly to the climate, not to studying fundamental properties of networks and how much work they do and the necessity for resilient episodes for their function.
Michael Garfield (40m 23s): I mean, just to link it again, relentlessly to other SFI research, it sounds a lot like the work that Stephanie Crabtree and Jen Dunn did on the Martu and fire foraging and the way that some indigenous peoples actually create biodiversity rather than just hammering the same thing over and over and eroding the top soil and destroying the terrific networks. Anyway, Mark, this has been totally fabulous. I thought it was really interesting. We just shared an article, a press release on some of Chris campus's work with the NASA agnostic biosignatures lab, trying to use scaling laws and stoichiometry to figure out the elemental ratios where you might find life.
And I was just like, oh God, I want to ask you based on these dynamics, the decline in certain kinds of elemental availability suggests that there are probably even further constraints on top of the ones that Chris and Simon Levin and others just posed like, should we be looking on colder worlds than we would have otherwise thought for life? Or like, how does this change the way that we think about the Goldilocks zone and that kind of stuff.
Mark Ritchie (41m 26s): Thermodynamics would definitely have something to say about that. And probably there's an interaction between the temperature and the element ratios, meaning that certain element ratios would allow you to function in cooler environments, potentially assuming that you overcame the issue of freezing water. So if you have a different solvent that doesn't freeze it in a certain thing, but there are those speculations about life that depend on different solvents, then that opens up a whole different world of different possible limiting elements and stoichiometry that then probably depending on how those different elements play in building catalyst.
I think if we're looking at life, we're always going to be looking at right along with whether you have a substrate that can generate energy. You've got to have catalysts of some kind, and we use organic chemicals mostly for those catalysts, except that at the core of them, there are certain elements like manganese, magnesium, copper, cobolt. So all of those so-called vitamins and minerals that we always have to take, most of those are metals that lie at the core of those enzymes. And you can show, for example, nitrogen fixing plants, and certain places actually been shown to the limited by molybdenum because that's the core metal that sits in the nitrogenous enzyme.
So there are a lot of places they're not, but there are places where they have been shown to be limited by that So there are a lot of places they're not, but there are places where they have been shown to be limited by thatparticular element. So what I'm saying is that if we're thinking about work and life exists, we have to think about where do we have substrates? So we have to have electron donors and all that stuff, but we also have to have the catalytic bio molecules that can do that. And whether those things are like pure metals, like chemical companies use all the time, or whether there's some kind of organic metallic and what that metal is and what those properties would be.
To me, that's just a huge universe for exploration possibilities because of the interaction with temperature.
Michael Garfield (43m 17s): It just makes me think that the global economy is only going to get as big as we have enough cobalt and palladium. You know, like at what point do we start harvesting asteroids in order to keep making phones.
Mark Ritchie (43m 32s): Papers that argue that this, the search for phosphorous, that that's the thing that's ultimately going to limit our agricultural production. I've seen a couple of papers in the last couple of years about that. And especially one of my grad students just discovered by looking at data from Serengeti. And in fact it looks like the impact of the herbivores may be limited by phosphorus in the Serengeti, not by nitrogen, which is what everyone or sodium that everyone has always assumed or speculated on. And most people who studied terrestrial ecology, unless they work in really old soils, like in Australia or Africa, they don't really pay that much attention to phosphorus in natural systems.
And so things that make bones are highly vulnerable to the total amount of phosphorus they can accumulate over our lifetime. So we don't have a problem with it because we've massively shifted phosphorus from these pools in the earth. You've mined it effectively and put it on our crops and our crops have taken it up. But at some point, if we run out of that kind of fertilizer, then again, we get back to this plant nutrition rather than production as being the issue that limits us. So yeah, even on our own planet, we're still trying to figure out what elements are really limiting life.
Michael Garfield (44m 41s): So Florida sits on a huge phosphorus deposit.
Mark Ritchie (44m 44s): Well, I mean, eventually it'll be like fracking, except you're fracking for phosphorus because you'll find a technology that when phosphorus becomes sufficiently expensive, then it's worth doing that technique to mine it out
Michael Garfield (44m 57s): For parts. We don't need it.
Mark Ritchie (44m 58s): Yeah. It's like phosphorus is kind of like oil was in the seventies were ruined, predicted that we run out of it, but then we never have, because we keep inventing new technologies that allow us to access different pools anyway. Yeah. This is super fun. Super fun. I'm so glad that you invited me to chat.
Michael Garfield (45m 15s): Thanks for taking an extra long time with us. Way, way beyond the book tower.
Mark Ritchie (45m 20s): Yeah, you too.
Michael Garfield (45m 22s): Thank you for listening. Complexities produced by the Santa Fe Institute, a nonprofit hub for complex systems science located in the high desert of New Mexico. For more information, including transcripts research links and educational resources, or to support our science and communication efforts. Visit