Jeffrey West is a theoretical physicist whose primary interests have been in fundamental questions of physics and biology. He s a senior fellow at Los Alamos National Laboratory and a distinguished professor at the Santa Fe Institute, where he served as president from 2005 to 2009. He is the author of the book, Scale: The Universal Laws of Growth, Innovation, and Sustainability in Organisms, Cities, and Companies, and we talk about his book at length here. As you ll hear, Jeffrey is an extremely interesting guy. We ran into a few audio problems at the end, so apologies for that. We don t run ads on the podcast and therefore, therefore, are made possible entirely through the support of our subscribers. If you enjoy what we re doing here, please consider becoming a supporter of what we're doing here by becoming a subscriber. You'll get access to our full-length episodes of the podcast as well as access to all the podcast's premium features, including the most popular podcasting platform, The Making Sense Podcast, wherever you get your podcasts. Subscribe to the podcast today! To find a list of our sponsors and show-related promo codes, go to gimlet.fm/OurAdvertisers. To learn more about our sponsorships and how you can support the podcast, please go to our ad-free membership program, becoming a patron of the Making Sense podcast, becoming one of our platinum sponsor, and receive 10% off the first month's mail discount when you sign up! Subscribe for a year of $99 or more! You get 20% off your first month, plus a 2 months free, plus an additional 3 months free shipping when you become a patron gets the choice of 1 month for two months, and two months get a complimentary membership for the course, and a discount of $50 or two months for VIP access to the second year, plus they get a discount, they also get an ad-only offer, they can choose a complimentary rate of $39/month, and they get full access to make their choice of the making sense of the entire course starting from $99/choice, they get all that they choose, they'll get all of that option, plus all that gets you get, plus two months of the service, they decide, plus she gets a choice of $29/place they get, and she gets all that she gets, and all they also gets, they receive, and you get two months
00:02:37.320You have written this fascinating book called Scale, which links the underlying properties of complex systems to both biological and cultural phenomenon, really everything from cells to cities.
00:03:15.820Why do people die and companies die, but cities don't seem to die?
00:03:20.780And before we get into answering these questions, first tell our listeners how you got into this, because you're a theoretical physicist by training.
00:03:30.020And now you're focusing on biological and even socioeconomic questions.
00:03:34.360And it seems to have been inspired both by the death of the supercollider project in the U.S.
00:03:40.540and your growing sense of your own mortality.
00:03:42.880So give us the context of your investigations.
00:03:48.120You have pinpointed, so to speak, the genesis of this in that I was at some stage happily doing research into quarks and gluons and string theory and fundamental questions of physics, dark matter and so forth.
00:04:08.860And associated with that, of course, was this marvelous project of the superconductive supercollider to be built in Texas.
00:04:20.040And, of course, the vision was to open up new vistas at extremely high energies and, therefore, in very short distances and confirm some of our ideas about fundamental forces and the fundamental constituents of nature.
00:04:37.840But also, you know, just the usual search for, you know, new science, new physics.
00:04:45.180And sadly, that was canned in the early 90s.
00:04:48.380And I had been somewhat involved in it.
00:04:52.480And at the same time, I was into my 50s.
00:04:59.100And it so happens that I come from a line of short-lived males.
00:05:36.220And so I'd grown up with this idea that, you know, I'd probably die somewhere in my early 60s.
00:05:45.180That was sort of the lifespan of what was to be expected.
00:05:48.420And in my 50s, I began to realize that, my gosh, you know, I may only have five to 10 years at most to live.
00:05:57.040And it was the confluence of that and the death of the super collider and some of the things that were being said in terms of, so to speak, justifying why we shouldn't continue with this huge project.
00:06:16.420That got me to start thinking about some of these big questions in biology originally.
00:06:21.620And the one thing that really stimulated me and sort of got me emotionally was a statement that many people are familiar with that was being banded around, especially in the early 90s, was, you know, physics was the science of the 19th and 20th centuries, whereas biology is clearly going to be the science of the 21st century.
00:06:42.780And I must say it's sort of hard to argue with that, but there was a corollary to it that was sometimes actually made explicit, oftentimes just implicit.
00:06:54.100And that was that, you know, we know all the physics we need to know, and, you know, there's no point in, you know, going any further, kind of philistine view of the intellectual enterprise.
00:07:08.040And that really got me, you know, because even though, as I said, I agreed with the first part that no doubt biology was going to be significantly important during this century.
00:07:19.740Nevertheless, I arrogantly and out of ignorance, frankly, sort of came back with the statement that, well, yes, that may be the case, but it won't be a real science unless it starts to...
00:07:35.740Until it gets a proper case of physics envy.
00:07:38.000Exactly. Yeah, something like that. Yes, I was hesitating. But to really, you know, start to incorporate the paradigm of physics in terms of it being quantitative, more analytic, based on principles, and therefore more predictive.
00:07:59.920That kind of paradigm, that kind of paradigm, and also some of the techniques of physics and the question.
00:08:04.720So the big question is, you know, to what extent can biology be mathematized and put on a kind of principled basis beyond just, in quotes, the principle of natural selection, but to put that into a more solid foundation.
00:08:20.440That was where I was coming from before. And I must say, I knew almost no biology at the time.
00:08:27.080But it was that sort of emotional reaction that got me to start thinking at some stage, well, you know, maybe I should think about that seriously.
00:08:38.280Maybe I should actually start thinking about how you would, in fact, take this fantastic set of ways of thinking and tools that we've developed in physics.
00:08:49.620How could you take that to biology? And that's where it coupled up with the question of aging and mortality, that I started thinking a little bit about that.
00:08:59.560And the way I framed it in my head was not just what is the mechanism of aging and why do we die, but to make it slightly more quantitative and say, you know, where in the hell does 100 years come from for the lifespan of a human being?
00:09:16.420You know, what is that related to? We ought to have a theory, you know.
00:09:19.680So to begin, put it in this kind of arrogant physics way, if biology were a serious science, then, you know, you should be able to pick up a biology textbook and there would be a chapter about aging and mortality in which there'd be a little calculation that ends up with saying lifespan of a human being should be approximately 100 years.
00:09:42.100And by the way, the lifespan of a mouse should be of the order of two or three years, et cetera.
00:09:48.640And what I discovered as I started to take this more seriously and read not just biology textbooks, but read the literature on aging and mortality, gerontology in general, was that this was not a very well-developed area at that time.
00:10:06.320And in particular, as far as I could tell, no one seems to have asked the question in that form.
00:10:12.560And so I kind of, as a little exercise, so to speak, to, you know, spend my spare time in the evenings or the weekends, I thought, well, maybe I should start thinking about that.
00:10:25.920How would you go about trying to show that 100 years is the expected lifespan of an animal our size?
00:10:35.400And what that led me to, first of all, was, you know, if you're going to start thinking about aging mortality, you have to start thinking about what is it that's going wrong in terms of what's keeping you alive?
00:10:51.060I mean, apply that to any machine, for example, what is it that, so to speak, wears out or starts to become dysfunctional in terms of its, during its lifespan?
00:11:04.300And of course, you know, what's keeping you alive is metabolism.
00:11:09.220That is, you eat and metabolize food to form energy, ATP molecules, currency of energy.
00:11:16.160And so then I started reading about metabolism, and in so doing, discovered, I didn't discover, but I learned about these amazing scaling laws.
00:11:31.500And in particular, this remarkable scaling law for how metabolic rate, that is the amount of energy any organism needs, you know, per second or per hour to stay alive.
00:11:43.580How does that, how that scales with the size of an animal?
00:11:48.820And to my amazement, I learned that it was extremely simple and regular.
00:11:56.820Jeffrey, before we jump into biological scaling, let's just answer a couple of higher level questions here, because I don't even think people understand what is implied by the word scaling.
00:12:07.840Yes, I was going to come to this, absolutely.
00:12:09.520Yeah, so let's, let's, the big picture here is that you point out that the phenomenon that we, that really concern us, that form the space in which we live, span a range of more than 30 orders of magnitude, from molecules to cities.
00:12:27.880So, so first of all, just take organisms.
00:12:33.300We go from the smallest organism, which is mycoplasma, it's a, you know, tiny sub-bacterial kind of organism, all the way up to the blue whale, that's about 20 orders of magnitude, you know, 20 powers of 10.
00:12:51.660If you include, if you go down to molecules, you add several more orders of magnitude, and of course, if you go up to ecosystems and cities, many more.
00:13:01.420So, you know, I mean, you could even stretch this to 40 orders of magnitude in terms of the structure of life.
00:13:09.800You know, all of these things are, to some extent, living, I mean, even at the molecular level, you could talk about living, things that are doing things that we would call life, sort of primitive viruses.
00:13:23.200But all the way up to, as I say, a large ecosystem, and in particular, a city, which you can sort of think of for these purposes as a kind of pseudo-organism.
00:13:33.800So that's kind of amazing, because, you know, as I think I point out in the book, this is much greater scale than the relationship of us to the entire Milky Way, for example, or an electron to a cat.
00:13:51.820You know, these, we as life span much more than that, and it's kind of amazing.
00:13:57.560And so that's the range over which the phenomena I discuss in the book are discussed.
00:14:04.280But the phenomenon of scaling, that is usually called scaling, is how do the characteristics of, you know, let's say, let's just be a little more modest and stick to, say, just all mammals, for example.
00:14:21.580How do their characteristics scale as you change the size of a mammal?
00:14:26.360So mammals go from the smallest, which is a shrew, which sits easily on the palm of the hand, all the way up to the blue whale, which is as big as the building I'm sitting in.
00:14:38.620And that covers approximately eight orders of magnitude in its mass.
00:14:45.220And scaling asks the question, well, let's look at characteristics of these mammals, everything from the one I mentioned earlier, metabolic rate, to something a little more mundane, like the length of their aortas.
00:15:01.520The aorta is the first tube that comes out of the heart, or even, you know, the size of their hearts, or the length of a limb.
00:15:10.400But all these various things that you could measure, how long they live, how many offspring they have, and so on.
00:15:16.680So that's just the concept of scaling.
00:15:20.360And the remarkable thing is that when you look at any of these quantities, and, you know, one can list maybe 50 to 75 of such characteristics,
00:15:32.200and ask how do they change with the size of the mammal, they all scale, in that sense, in a very regular fashion.
00:15:41.720And not only in a very regular fashion, but all in a similar way, mathematically.
00:15:49.300And that's extremely surprising, naively, at a naive level, because, you know, we believe in natural selection.
00:15:58.280We believe that all of these organisms have evolved by natural selection, with highly contingent histories.
00:16:05.440Each subsystem of them, each organ, each cell type, each genome, has its own unique history.
00:16:15.620So you might have expected that if you plotted any characteristics, such as its metabolic rate versus size,
00:16:25.400you would get points scattered all over the graph.
00:16:30.600And quite the contrary, you find that there's a tremendous regularity.
00:16:35.440It gets revealed suggesting that underlying this extraordinary complexity, because, after all, something like metabolism is maybe the most complex process in the universe, for all we know,
00:16:47.620because it's sort of, you know, at its most primitive level, it takes, you know, matter, stuff, and creates life.
00:16:54.880That's what we're doing, you know, as we eat, and so on.
00:16:57.760You know, here's this unbelievably complex process, and yet, if you ask how it scales across this huge range of organisms, it scales in this very simple way.
00:17:10.540And the amazing thing is this even extends to cities that have different cultural histories and different geographies.
00:17:16.840Absolutely. So the same thing, after we did this work and explained where these scaling laws come from, it was very natural to ask the question, you know,
00:17:27.980are there other forms of life, such as, you know, more synthetic ones, so to speak, like cities, or even companies,
00:17:35.660that express similar kinds of regular systematic scaling.
00:17:41.480And, as I say, later following understanding the biological scaling, when we looked at the data on the scaling of cities,
00:17:53.360we found a similar kind of scaling, similar in the sense that there was a regular systematic behavior, and the mathematics was the same.
00:18:02.780The details of it are different, and the details are different in a very important and powerful way.
00:18:11.480But it was quite similar, and similarly, even with companies, you know, going from a small company of a couple of hundred employees to Walmart or General Motors,
00:18:27.000So, you know, there's this ubiquitous behavior that is quite surprising when you first meet it, that says that despite, you know, the daunting complexity and diversity that we see out there,
00:18:42.220underlying it seems to be a kind of simplicity, which can be expressed both graphically and mathematically in very powerful and simple terms.
00:18:56.560So maybe I should say a little bit about what the nature of that scaling is.
00:19:02.980So let's start with the case of biological scaling, and I just want you to go through the significance of the fact that this scaling tends to be nonlinear.
00:19:14.000It's either sublinear or superlinear on your account.
00:19:17.960Yeah, that's very important because, you know, if you ask yourself, well, look, if I double the size of an organism or if I look at an organism that's twice the size of another one,
00:19:30.560or in particular, let's take mammals, as I said, a mammal that's twice the size of another, then it contains, roughly speaking, twice as many cells.
00:20:20.740So if you double the size from 4 grams to 8 grams or 4 kilograms to 8 kilograms, it doesn't matter where you start.
00:20:32.460As long as if you double, you only need, roughly speaking, 75%, three quarters, roughly, the amount of energy.
00:20:39.520There's a 25% savings on the average every time you double.
00:20:44.240And that's called an economy of scale.
00:20:46.380That's a classic economy of scale and means, of course, that the individual cells, since they do scale linearly,
00:20:56.480it means that the energy needed to support an individual cell is systematically smaller by this 25% rule the bigger you are every time you double.
00:21:11.160And so, you know, your cells work less hard in a predictable way than your dogs or cats.
00:21:18.800But, you know, your horse or your elephant are working even less hard.
00:21:24.900So this is a pervasive phenomenon throughout biology, this economy of scale, and has far-reaching consequences.
00:21:35.960So that similar kind of scaling gets repeated across any measurable quantity, whether it's physiological, like the one I mentioned,
00:21:47.460just something sort of mundane like the length of an aorta, or something quite sophisticated,
00:21:54.020like the rates at which oxygen diffuses across membranes or how long an organism lives and so on.
00:22:01.140And these also are governed by an analog to this 25% rule.
00:22:08.640So time scales increase according to this 25% rule the bigger you are.
00:22:15.040And generically, the pace of life slows down.
00:22:18.960So that, in fact, you know, if you took an elephant and you followed these scaling laws for all its physiology and all its rates of life history
00:22:32.680and scaled it according to that and just kept scaling down, you would end up with a mouse.
00:22:39.020You know, a mouse is a scaled, you know, at this...