Category: Science

Coevolution and Artificial Selection

“The ancient relationship between bees and flowers is a classic example of coevolution. In a coevolutionary bargain like the one struck by the bee and the apple tree, the two parties acton each other to advance their individual interests but wind up trading favors: food for the bee, transportation for the apple genes. Consciousness needn’t enter into it on either side …”

***

In The Botany of Desire: A Plant’s-Eye View of the World Michael Pollan tells the story of four domesticated species—the apple, the tulip, cannabis, and the potato—and the human desires that link their destinies to our own.

“Its broader subject,” he writes, “is the complex reciprocal relationship between the human and natural world.”

It’s a simple question really: Did I choose to plant these tulips or did they make me do it? Pollan concludes that, in fact, both statements are true.

Did the plant make him do it? Only in the sense that the flower “makes” the bee pay it a visit.

Evolution doesn’t depend on will or intention to work; it is almost by definition, and unconscious, unwilled process. All it requires are beings compelled, as all plants and animals are, to make more of themselves by whatever means trial and error present. Sometimes an adaptive trait is so clever it appears purposeful: the ant that “cultivates” its own gardens of edible fungus, for instance, or the pitcher plant that “convinces” a fly it’s a piece of rotting meat. But such traits are clever only in retrospect. Design in nature is but a concatenation of accidents, culled by natural selection until the result is so beautiful or effective as to seem a miracle of purpose.

The book is as much about the human desires that connect us to plants as it is about the plants themselves.

“Our grammar,” Pollan writes, “might teach us to divide the world into active subjects and passive objects, but in a coevolutionary relationship every subject is also an object, every object a subject.”

Charles Darwin didn’t start out The Origin of Species with an account of his new theory, rather, he began with a foundation he felt would be easier for people to get their heads around. The first chapter was a special case of natural selection called artificial selection.

Artificial wasn’t used in the sense of fake but as in things that reflect human will. He wrote about a wealth of variation of species from which humans selected the traits that will be passed down to future generations. In this sense, human desire plays the role of nature, determining what constitutes “fitness.” If people could understand that, they would understand nature’s evolution.

Pollan argues that the crisp conceptual lie “that divided artificial from natural selection has blurred.”

Whereas once humankind exerted its will in the relatively small arena of artificial selection (the arena I think of, metaphorically, as a garden) and nature held sway everywhere else, today the force of our presence is felt everywhere. It has become much harder, in the past century, to tell where the garden leaves off an pure nature begins.

We are shaping things in ways that Darwin could never have imagined.

For a great many species today, “fitness” means the ability to get along in a world in which humankind has become the most powerful evolutionary force.

Artificial selection, it appears, has become at least as powerful as natural selection.

Nature’s success stories from now on are probably going to look a lot more like the apple’s than the panda’s or white leopard’s. If those last two species have a future, it will be because of human desire; strangely enough, their survival now depends on what amounts to a form of artificial selection.

The main characters of the book—the apple, the tulip, cannabis, and the potato—are four of the world’s success stories. “The dogs, cats, and horses of the plant world, these domesticated species are familiar to everyone,” Pollan writes.

Apples

In the wild a plant and its pests are continually coevolving, in a dance of resistance and conquest that can have no ultimate victor. But coevolution ceases in an orchard of grafted trees, since they are genetically identical from generation to generation. The problem very simply is that the apple trees no longer reproduce sexually, as they do when they’re grown from seed, and sex is nature’s way of creating fresh genetic combinations. At the same time the viruses, bacteria, fungi, and insects keep very much at it, reproducing sexually and continuing to evolve until eventually they hit on the precise genetic combination that allows them to overcome whatever resistance the apples may have once possessed. Suddenly total victory is in the pests’ sight — unless, that is, people come to the tree’s rescue, wielding the tools of modern chemistry.

Put another way, the domestication of the apple has gone too far, to the point where the species’ fitness for life in nature (where it still has to live, after all) has been dangerously compromised. Reduced to the handful of genetically identical clones that suit our taste and agricultural practice, the apple has lost the crucial variability — the wildness — that sexual reproduction confers.

The Tulip

The tulip’s genetic variability has in fact given nature–or, more precisely, natural selection–a great deal to play with. From among the chance mutations thrown out by a flower, nature preserves the rare ones that confer some advantage–brighter color, more perfect symmetry, whatever. For millions of years such features were selected, in effect, by the tulip’s pollinators–that is, insects–until the Turks came along and began to cast their own votes. (The Turks did not learn to make deliberate crosses till the 1600s; the novel tulips they prized were said simply to have “occurred.”) Darwin called such a process artificial, as opposed to natural, selection, but from the flower’s point of view, this is a distinction without a difference: individual plants in which a trait desired by either bees or Turks occurred wound up with more offspring. Though we self-importantly regard domestication as something people have done to plants, it is at the same time a strategy by which the plants have exploited us and our desires–even our most idiosyncratic notions of beauty–to advance their own interests. Depending on the environment in which a species finds itself, different adaptations will avail. Mutations that nature would have rejected out of hand in the wild sometimes prove to be brilliant adaptations in an environment that’s been shaped by human desire.

In the environment of the Ottoman Empire the best way for a tulip to get ahead was to have absurdly long petals drawn to a point fine as a needle. In drawings, paintings, and ceramics (the only place the Turks’ ideal of tulip beauty survives; the human environment is an unstable one), these elongated blooms look as though they’d been stretched to the limit by a glassblower. The metaphor of choice for this form of tulip petal was the dagger. … Though these … traits are not uncommon in species tulips, attenuated petals are virtually unknown in the wild, which suggests that the Ottoman ideal of tulip beauty—elegant, sharp, and masculine—was freakish and hard-won and conferred no advantage in nature.

All in all The Botany of Desire is one of the best books I’ve read on how our Apollonian desire for control and order increasingly butts up against the natural Dionysian wildness.

The Difference Between Science And Engineering

Eric Drexler is often described as “the founding father of nanotechnology.”

His recent book, Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization, includes a fascinating explanation of the difference between science and engineering.

At first glance, scientific inquiry and engineering design can seem the same. One important distinction, however, results from the flow of information.

The essence of science is inquiry; the essence of engineering is design. Scientific inquiry expands the scope of human perception and understanding; engineering design expands the scope of human plans and results.

Inquiry and design are perfectly distinct as concepts, but often interwoven in practice, whether within a field, a research program, a development team, or a single creative mind. Meshing design with inquiry can be as vital as hand-eye coordination. Engineering new instruments enables inquiry, while scientific inquiry can enable design. Chemical engineers investigate chemical systems, testing combinations of reactants, temperature, pressure, and time in search of conditions that maximize product yield; they may undertake inquiries every day, yet in the end their experiments support engineering design and analysis. Conversely, experimental physicists undertake engineering when they develop machines like the Large Hadron Collider. With its tunnels, vacuum systems, superconducting magnets, and ten-thousand-ton particle detectors, this machine demanded engineering design on a grand scale, yet all as part of a program of scientific inquiry.

But the close, interweaving links between scientific inquiry and engineering design can obscure how deeply they differ.

While interacting with the same physical world, the way you look at the problem — through the lens of design or inquiry — shapes what you see.

The Bottom-Up Structure of Scientific Inquiry

Scientific inquiry builds knowledge from bottom to top, from the ground of the physical world to the heights of well-tested theories, which is to say, to general, abstract models of how the world works. The resulting structure can be divided into three levels linked by two bridges.

At the ground level, we find physical things of interest to science, things like grasses and grazing herds on the African savannah, galaxies and gas clouds seen across cosmological time, and ordered electronic phases that emerge within a thousandth of a degree of absolute zero.

On the bridge to the level above, physical things become objects of study through human perception, extended by instruments like radio telescopes, magnetometers, and binoculars, yielding results to be recorded and shared, extending human knowledge. Observations bring information across the first bridge, from physical things to the realm of symbols and thought.

At this next level of information flow, scientists build concrete descriptions of what they observe. …

On the bridge to the top level of this sketch of science, concrete descriptions drive the evolution of theories, first by suggesting ideas about how the world works, and then by enabling tests of those ideas through an intellectual form of natural selection. As theories compete for attention and use, the winning traits include simplicity, breadth, and precision, as well as the breadth and precision of observational tests— and how well theory and data agree, of course.

Newtonian mechanics serves as the standard example. Its breadth embraces every mass, force, and motion, while its precision is mathematically exact. This breadth and precision are the source of both its power in practice and its failure as an ultimate theory. Newton’s Laws make precise predictions for motions at any speed, enabling precise observations to reveal their flaws.

Thus, in scientific inquiry, knowledge flows from bottom to top:

  • Through observation and study, physical systems shape concrete descriptions.
  • By suggeting ideas and then testing them, concrete descriptions shape scientific theories.

Here is a schematic structure of Scientific inquiry contrasted with the structure of engineering design.

The Antiparallel Structures of Scientific Inquiry
Source: Radical Abundance

The Top-Down Structure of Engineering Design

In scientific inquiry information flows from matter to mind, but in engineering design information flows from mind to matter:

  • Inquiry extracts information through instruments; design applies information through tools.
  • Inquiry shapes its descriptions to fit the physical world; design shapes the physical world to fit its descriptions.

At this level, the contrasts are often as concrete as the difference between a microscope in an academic laboratory and a milling machine on a factory floor. At the higher more abstract levels of science and engineering, the differences are less concrete, yet at least as profound. Here, the contrasts are between designs and theories, intangible yet different products of the mind.

  • Scientists seek unique, correct theories, and if several theories seem plausible, all but one must be wrong, while engineers seek options for working designs, and if several options will work, success is assured.
  • Scientists seek theories that apply across the widest possible range (the Standard Model applies to everything), while engineers seek concepts well-suited to particular domains (liquid-cooled nozzles for engines in liquid-fueled rockets).
  • Scientists seek theories that make precise, hence brittle predictions (like Newton’s), while engineers seek designs that provide a robust margin of safety.
  • In science a single failed prediction can disprove a theory, no matter how many previous tests it has passed, while in engineering one successful design can validate a concept, no matter how many previous versions have failed.

The Strategy of Systems Engineering

With differences this stark, it may seem a surprise that scientific inquiry and engineering design are ever confused, yet to judge by both the popular and scientific press, clear understanding seems uncomfortably rare.*

The key to understanding engineering at the systems level— the architectural level— is to understand how abstract engineering choices can be grounded in concrete facts about the physical world. And a key to this, in turn, is to understand how engineers can design systems that are beyond their full comprehension.

Seeking Knowledge vs. Applying Knowledge

Because science and engineering face opposite directions, they ask different questions.

Scientific inquiry faces toward the unknown, and this shapes the structure of scientific thought; although scientists apply established knowledge, the purpose of science demands that they look beyond it.

Engineering design, by contrast, shuns the unknown. In their work, engineers seek established knowledge and apply it in hopes of avoiding surprises. In engineering, the fewer experiments, the better.

Inquiry and design call for different patterns of thought, patterns that can clash. In considering the science in the area around an engineering problem, a scientist may see endless unknowns and assume that scarce knowledge will preclude engineering, while an engineer considering the very same problem and body of knowledge may find ample knowledge to do the job.

Radical Abundance “offers a mind-expanding vision of a world hurtling toward an unexpected future.”

Richard Feynman on The Key to Science

“If it disagrees with experiment, it is wrong.”

In this video from the 60s, Richard Feynman explains, very simply, the key to science with his timeless wisdom. It is the capacity to be wrong that moves us forward.

In general, we look for a new law by the following process: First we guess it; then we compute the consequences of the guess to see what would be implied if this law that we guessed is right; then we compare the result of the computation to nature, with experiment or experience, compare it directly with observation, to see if it works. If it disagrees with experiment, it is wrong. In that simple statement is the key to science. It does not make any difference how beautiful your guess is, it does not make any difference how smart you are, who made the guess, or what his name is — if it disagrees with experiment, it is wrong.

Scientists and researchers, or really, anyone who experiments, are wrong more often than they are right. After all, what is the purpose of a hypothesis? To test whether or not an idea is wrong or right; to carry us toward a definitive answer to a problem. By its very nature, it will yield more disappointments than breakthroughs. In science, if something “disagrees with experiment”, it gets tossed into the treasure trove of failed experiments. Adulation is not usually reserved for things proven to be false. In science, what’s true is more likely to survive the sands of time.

Ask anyone to name the top ten smartest people in the world, dead or alive, and Albert Einstein (Richard Feynman too) would probably appear on that list. His genius is eternal, forever changing the world, but he was not impervious to reaching incorrect conclusions. For example, we know that the universe is constantly expanding but in 1917, Einstein theorized that it was static (“temporally infinite but spatially finite”).

There is something beautiful about ignorance…as long as one has the desire to expand the limits of their knowledge so that ignorance remains ephemeral. Oxymoronic as it may be, being wrong leads us to a better understanding of the world and ourselves.

The Honeybee Conjecture: What Is It About Bees And Hexagons?

Why is every cell in this honeycomb a hexagon?

More than 2,000 years ago, Marcus Terentius Varro, a roman citizen, proposed an answer, which ever since has been called “The Honeybee Conjecture.” He thought that if we better understood, there would be an elegant reason for what we see.

“The Honeybee Conjecture” is an example of mathematics unlocking a mystery of nature. And luckily, NPR, with the help of physicist/writer Alan Lightman, (who wrote The Accidental Universe: The World You Thought You Knew) helps explains Varro’s hunch.

Why the preference for hexagons? Is there something special about a six-sided shape?

“It is a mathematical truth,” Lightman writes, “that there are only three geometrical figures with equal sides that can fit together on a flat surface without leaving gaps: equilateral triangles, squares and hexagons.”

So which to choose? The triangle? The square? Or the hexagon? Which one is best? Here’s where our Roman, Marcus Terentius Varro made his great contribution. His “conjecture” — and that’s what it was, a mathematical guess — proposed that a structure built from hexagons is probably a wee bit more compact than a structure built from squares or triangles. A hexagonal honeycomb, he thought, would have “the smallest total perimeter.” He couldn’t prove it mathematically, but that’s what he thought.

Compactness matters. The more compact your structure, the less wax you need to construct the honeycomb. Wax is expensive. A bee must consume about eight ounces of honey to produce a single ounce of wax. So if you are watching your wax bill, you want the most compact building plan you can find.

In 1999 Thomas Hales produced a mathematical proof, confirming that Varro was right.

Why are they all the same size?

For bees to assemble a honeycomb the way bees actually do it, it’s simpler for each cell to be exactly the same. If the sides are all equal — “perfectly” hexagonal — every cell fits tight with every other cell. Everybody can pitch in. That way, a honeycomb is basically an easy jigsaw puzzle. All the parts fit.

Update: I ran across this interesting paper, which argues the honeybee comb have a circular shape at first and then transform into the hexagon.

We report that the cells in a natural honeybee comb have a circular shape at ‘birth’ but quickly transform into the familiar rounded hexagonal shape, while the comb is being built. The mechanism for this transformation is the flow of molten visco-elastic wax near the triple junction between the neighbouring circular cells. The flow may be unconstrained or constrained by the unmolten wax away from the junction. The heat for melting the wax is provided by the ‘hot’ worker bees.

Still Curious? Learn more about The Honeycomb Conjecture.