DNA

The real source of the evolution debate, part 1

PNRJ Logic of Kindness , , , , , , , , , , ,

Feb 9 JDN 2460716

The last few posts have been about evolution; but everything I’ve said in them has been very technical and scientific, and I imagine it is not very controversial or offensive to anyone. In fact, I would guess that anyone who believes in Creationism, upon reading my definition of evolution as “change in allele distribution in a population”, was thinking, “Of course we believe in that. But that’s not evolution.” Actually it is; evolution is change in allele distribution in a population. What people are objecting to isn’t really evolution.

There are however several propositions that people do object to, which are conceptually related, but not strictly implied by evolution. They are adaptationism, common descent, animalism, abiogenesis, and atheism respectively. They are all true—and in what follows I will offer a defense of each—but they are not necessarily entailed by evolution or the Modern Synthesis, and so they should be considered separately on their own merits. This post will deal with adaptationism and common descent, and I’ll save the others for a later post.

Adaptationism

Adaptationism is the principle that living organisms have the traits they do because these traits are adaptive, that is, that they are beneficial to fitness. It’s obvious that this isn’t completely true in every case; whales have hipbones despite having no apparent use for them, and the human appendix seems mostly useful for collecting toxins and occasionally exploding. There are also limits to how much an organism can change given its current structure; the emerging field of developmental evolutionary biology, or evo-devo, seeks to characterize these limits more precisely.

But in general, adaptationism is an incredibly powerful principle, one which makes sense of the diversity and complexity of life on Earth in a way no other theory can. Natural selection predicts that organisms will become more and more adapted over time; adaptationism is based on the fact that we have had plenty of time to adapt really, really well. In fact, it can be argued that adaptationism is really what evolutionary theory is about, that all this business about changes in allele distributions is useful but not really the point of the enterprise.

When we look at the world, we see that living things are extremely complex and well-suited to their environments; theologians used to say (in fact some still do) that this was evidence that living things were designed by a perfect God.

The problem with this argument was exposed almost immediately by David Hume: If complex things need designers, aren’t designers even more complex than what they design? But then, the designer needs a designer-designer, and the designer-designer needs a designer-designer-designer, and so on into an infinite regress! Another problem with this sort of Intelligent Design thinking is that it cannot explain the cases when adaptationism fails—in particular, why do so many species go extinct? Recently a theory of “Intelligent Recall” was proposed for this purpose; but this forces us to think of our designer as no more intelligent than a financial analyst or an automobile engineer! What kind of God would make mistakes in design?

And now we know better: The remarkable complexity and fitness of living organisms can be entirely explained by adaptationism. When we ask why dolphins have fins, why birds have wings, why centipedes have so many legs, why snakes are so long, or why humans have such enormous brains, adaptationism gives us the answer: organisms have these traits because having these traits benefited their ancestors. In some cases it’s pretty obvious how this would work (having fins lets dolphins swim faster, swimming faster has obvious benefits in catching fish and escaping sharks, so dolphin ancestors with more fin-like limbs survived better); in others we’re still working on the specifics (there is as yet no consensus on how humans got so incredibly smart compared to other animals); but in general adaptationism has explained a huge body of data that we couldn’t account for any other way.

Common descent

Common descent is the proposition that all living organisms on Earth are descended from a common ancestor. This implies, in particular, that human beings share a common ancestor with other animals. The former is strictly stronger, and not quite as certain; at least in principle it could be that some broad classes of organism do not share a common ancestor, but nonetheless it would still be quite clear that humans share a common ancestor with chimpanzees. In practice nearly all biologists agree with the strongest form of common descent, that all living organisms on Earth share a common ancestor. Recently the biochemist Douglas Theobald mathematically compared this strongest form of common descent (universal common descent) with several other models of phylogenetic history, finding that universal common descent was the most probable result by a factor of at least 102000—a 2001-digit number. That is, scientists are 99.999,999,999,999,999,999… (on with 1,980 more nines!) percent sure that universal common descent is right. This is not hyperbole; it is mathematically precise. At this point any sliver of uncertainty left in universal common descent needs to apply to all of our fundamental knowledge of physics and chemistry; in order to be wrong about this, we’d need to be wrong about everything.

How are we so sure? Nature presents us with a very consistent pattern of observations that simply make no sense any other way. Traits in living things (and, we are increasingly finding, genes) have distinct patterns, structural similarities that exist between species irrespective of their lifestyle; we call these similiarities homologues. (Similarities that are due to lifestyle—e.g., both dolphins and fish have fins—are called analogues.) Dolphin skeletons are more like dog skeletons than they are like fish skeletons, even though dolphins live more like fish. Bat skin is more like human skin than like bird skin, even though bats live more like birds. The most parsimonious explanation is that these traits were passed on from some common ancestor—that dolphins and dogs have similar skeletons because dolphins and dogs are actually genetically related somehow, and they differ from fish because they are more distantly related.

Once we began to understand DNA, we became able to detect even more compelling homologues. Many kinds of mutation are completely ineffectual; some involve a change to DNA that doesn’t do anything, others swap out two amino acids that are essentially the same; in fact because of the way genes code for amino acids, it’s possible to have a change in a gene that isn’t reflected in the resulting protein at all. All of these changes have no effect on the organism, but they are still passed on to offspring. When you find two organisms that have the same trait (e.g. bats and birds both have wings), if that trait does something important (lets you fly), then maybe it’s just a similarity in lifestyle; if that happens we call it convergent evolution. But when we’re looking at a DNA sequence that doesn’t do anything, lifestyle can’t be the reason—it must be either common ancestry or pure coincidence. Statistical analysis can rule out pure coincidence, and then we are left with only one possibility: common descent. A third option often proposed by Creationists simply doesn’t work: A common designer of sharks and dolphins would not give one a cartilaginous skeleton and gills and the other a bony mammalian skeleton and lungs. There is no reason for dolphin skeletons to be more like dog skeletons than shark skeletons—except that dogs and dolphins share closer common ancestry to each other than they do to sharks.

There are thousands of traits and genes that we can use to assess these relationships. When we do this, we find a remarkably consistent organizational structure, a pattern of a few common ancestors diversifying into a wide variety of descendants—it looks a bit like a tree, so we call it a phylogenetic tree. In some cases there is ambiguity about which species are more closely related, and we need to gather more evidence. This is a normal part of evolutionary biology research.

One thing is not disputed: Humans share a common ancestor with apes. This is simply too obvious from the morphological and genetic homologues. Human and chimp DNA coincides 95-98\%, depending on how you count insertions and deletions.

A standard measure of genetic distance is the Nei distance; a larger Nei distance implies more genetic differences, which in turn suggests that the common ancestor was further in the past. (Exactly how it’s calculated is a bit too technical for this post.)

Humans and chimps have a Nei distance of 0.45. This similarity between humans and chimps represents a closer similarity than that between dogs and foxes, who differ by a Nei distance of 1.1. Almost anyone can see that dogs and foxes are related animals; so why is it so hard to believe that humans and chimps are related too?

Creationists often claim that we never find the transitional forms predicted by evolutionary theory, but this is simply not true. We do in fact see many transitional forms; feathered dinosaurs mark the transition from reptiles to birds, ambulocetids mark the transition from land mammals to cetaceans, therapsids mark the transition from reptiles to mammals, and a huge variety of hominids marks the transition from apes to humans. It’s important to understand what this means: transitional forms are not bizarre combinations of their descendant organisms, but fully-functional lifeforms in their own right that have descendants very different from one another. Just as your grandparents are not a combination of half of you and half of your first cousin, common ancestors are not simply half-and-half combinations of their descendant organisms. Ambulocetids are not half-deer/half-dolphin, they are somewhat deer-like yet somewhat dolphin-like mammals whose ancestors were on average slightly more deer-like and whose descendants were on average slightly more dolphin-like. Different traits changed at different times, generations apart: Ambulocetids began to swim before they lost their legs, and even modern dolphins haven’t lost their lungs or hipbones.


This is such a deep, marvelous truth that Creationists are missing out on: All life on Earth is part of one family. We are kin with the dogs and the cats and the elephants, with the snakes and the lizards and the birds, with the beetles and the flies and the bees, even with the flowers and the bushes and the trees.

Scalability and inequality

PNRJ core principles, inequality, mathematical models, statistics , , , , , , , , , , , , , ,

May 15 JDN 2459715

Why are some molecules (e.g. DNA) billions of times larger than others (e.g. H2O), but all atoms are within a much narrower range of sizes (only a few hundred)?

Why are some animals (e.g. elephants) millions of times as heavy as other (e.g. mice), but their cells are basically the same size?

Why does capital income vary so much more (factors of thousands or millions) than wages (factors of tens or hundreds)?

These three questions turn out to have much the same answer: Scalability.

Atoms are not very scalable: Adding another proton to a nucleus causes interactions with all the other protons, which makes the whole atom unstable after a hundred protons or so. But molecules, particularly organic polymers such as DNA, are tremendously scalable: You can add another piece to one end without affecting anything else in the molecule, and keep on doing that more or less forever.

Cells are not very scalable: Even with the aid of active transport mechanisms and complex cellular machinery, a cell’s functionality is still very much limited by its surface area. But animals are tremendously scalable: The same exponential growth that got you from a zygote to a mouse only needs to continue a couple years longer and it’ll get you all the way to an elephant. (A baby elephant, anyway; an adult will require a dozen or so years—remarkably comparable to humans, in fact.)

Labor income is not very scalable: There are only so many hours in a day, and the more hours you work the less productive you’ll be in each additional hour. But capital income is perfectly scalable: We can add another digit to that brokerage account with nothing more than a few milliseconds of electronic pulses, and keep doing that basically forever (due to the way integer storage works, above 2^63 it would require special coding, but it can be done; and seeing as that’s over 9 quintillion, it’s not likely to be a problem any time soon—though I am vaguely tempted to write a short story about an interplanetary corporation that gets thrown into turmoil by an integer overflow error).

This isn’t just an effect of our accounting either. Capital is scalable in a way that labor is not. When your contribution to production is owning a factory, there’s really nothing to stop you from owning another factory, and then another, and another. But when your contribution is working at a factory, you can only work so hard for so many hours.

When a phenomenon is highly scalable, it can take on a wide range of outcomes—as we see in molecules, animals, and capital income. When it’s not, it will only take on a narrow range of outcomes—as we see in atoms, cells, and labor income.

Exponential growth is also part of the story here: Animals certainly grow exponentially, and so can capital when invested; even some polymers function that way (e.g. under polymerase chain reaction). But I think the scalability is actually more important: Growing rapidly isn’t so useful if you’re going to immediately be blocked by a scalability constraint. (This actually relates to the difference between r- and K- evolutionary strategies, and offers further insight into the differences between mice and elephants.) Conversely, even if you grow slowly, given enough time, you’ll reach whatever constraint you’re up against.

Indeed, we can even say something about the probability distribution we are likely to get from random processes that are scalable or non-scalable.

A non-scalable random process will generally converge toward the familiar normal distribution, a “bell curve”:

[Image from Wikipedia: By Inductiveload – self-made, Mathematica, Inkscape, Public Domain, https://commons.wikimedia.org/w/index.php?curid=3817954]

The normal distribution has most of its weight near the middle; most of the population ends up near there. This is clearly the case for labor income: Most people are middle class, while some are poor and a few are rich.

But a scalable random process will typically converge toward quite a different distribution, a Pareto distribution:

[Image from Wikipedia: By Danvildanvil – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=31096324]

A Pareto distribution has most of its weight near zero, but covers an extremely wide range. Indeed it is what we call fat tailed, meaning that really extreme events occur often enough to have a meaningful effect on the average. A Pareto distribution has most of the people at the bottom, but the ones at the top are really on top.

And indeed, that’s exactly how capital income works: Most people have little or no capital income (indeed only about half of Americans and only a third(!) of Brits own any stocks at all), while a handful of hectobillionaires make utterly ludicrous amounts of money literally in their sleep.

Indeed, it turns out that income in general is pretty close to distributed normally (or maybe lognormally) for most of the income range, and then becomes very much Pareto at the top—where nearly all the income is capital income.

This fundamental difference in scalability between capital and labor underlies much of what makes income inequality so difficult to fight. Capital is scalable, and begets more capital. Labor is non-scalable, and we only have to much to give.

It would require a radically different system of capital ownership to really eliminate this gap—and, well, that’s been tried, and so far, it hasn’t worked out so well. Our best option is probably to let people continue to own whatever amounts of capital, and then tax the proceeds in order to redistribute the resulting income. That certainly has its own downsides, but they seem to be a lot more manageable than either unfettered anarcho-capitalism or totalitarian communism.