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Climbing Mount Improbable

Page 31

by Richard Dawkins


  Vicarious selection is a novel idea and it provides the answers to even more subtle problems. Fig genes and wasp genes are partners, locked together in a fast waltz through geological time. Most of the many species of fig have, as we've seen, their own private species of wasp. Figs and their wasps have evolved together — ‘co-evolved’ — in step with each other and out of step with other fig and wasp species. We have seen the advantage of this from the figs’ point of view. Their private species of pollinating wasp is the ultimate magic bullet. By cultivating one, and only one, species of wasp, they target their pollen strictly to female figs of their own species and no other. They do not waste pollen the way they would if they had to share the same species of wasp, one species that promiscuously visits all fig species. Whether such strict loyalty to one fig species also benefits the wasps is less clear, but they probably have no choice. For reasons that we need not go into, species occasionally evolve away from one another, splitting into two species. In the case of fig trees, when they diverge in evolutionary time they may well change the chemical passwords by which wasps recognize figs, and perhaps also such lock-and-key details as the depth of their tiny flowers. Wasp species are forced to follow suit. For instance, gradually deepening flowers on the fig (lock) side of the coevolution impose gradually lengthening ovipositors on the wasp (key) side of the co-evolution.

  Now comes a peculiar problem recognized by Grafen and Godfray. Let's expand the lock-and-key analogy. Fig species evolve away from each other by changing their locks, and wasps follow suit with their keys. Something like this must have gone on when ancestral orchids {324} diverged into bee orchids, fly orchids and wasp orchids. But there it is easy to see how the coevolution took place. Figs raise a very special and very tantalizing problem, and it is the last problem I shall tackle in this book. If the story went according to the usual co-evolutionary plan, we should expect to see something like the following. Genes for deeper flowers, say, would be selected among the female figs. This would set up a selection pressure in favour of longer ovipositors among wasps. But because of the odd circumstances of these figs, this normal story of co-evolution can't work. The only female flowers that pass on genes are the true female ones in female figs, not the pseudo-female florets in male figs; while the only female wasps that pass on genes are the ones that lay eggs in pseudo-female flowers, not the ones that lay eggs in real female flowers. So those individual wasps that happen to have long ovipositors and succeed in reaching the bottom of the long female flowers wont pass on the genes for long ovipositors. Those individual wasps whose long ovipositors reach the bottom of the pseudo-female flowers will pass their own genes on. But here the genes for making long flowers won't be passed on. We have a riddle.

  Once again, the answer seems to lie in vicarious selection — accurate simulators for pilots. Male figs ‘want’ the wasps that they export to be good at pollinating true female flowers. Therefore, in our hypothetical example, they would want them to have long ovipositors. The best way for a male fig to ensure this is to allow only mothers with long ovipositors to lay eggs in their pseudo-female flowers. Expressing the idea in terms of this particular example runs the risk of making it sound too purposeful, as though the male figs ‘know’ that female flowers are deep. Natural selection would do it automatically by favouring those male figs whose pseudo-female flowers resembled true female flowers in all respects, including depth.

  Figs and fig wasps occupy the high ground of evolutionary achievement: a spectacular pinnacle of Mount Improbable. Their relationship is almost ludicrously tortuous and subtle. It cries out for interpretation in the language of deliberate, conscious, Machiavellian calculation. Yet it is achieved in the complete absence of any kind of deliberation, without brain power or intelligence of any kind. The point is rubbed home {325} for us by the very fact that the players are a tiny wasp with a very tiny brain on the one hand, and a tree with no brain at all on the other. It is all the product of an unconscious Darwinian fine-tuning, whose intricate perfection we should not believe if it were not before our eyes. There is a form of calculation going on, or rather millions of parallel calculations, of costs and benefits. The calculations are of a complexity to tax our largest computers. Yet the ‘computer’ that is performing them is not made of electronic components, not even made of neural components. It is not located in a particular place in space at all. It is an automatic, distributed computer whose data bits are stored in DNA code, spread over millions of individual bodies, shuttling from body to body, via the processes of reproduction.

  The famous Oxford physiologist Sir Charles Sherrington compared the brain to an enchanted loom in a famous passage:

  It is as if the Milky Way entered upon some cosmic dance. Swiftly the brain becomes an enchanted loom where millions of flashing shuttles weave a dissolving pattern, always a meaningful pattern though never an abiding one; a shifting harmony of subpatterns.

  It was the rise of nervous systems and brains that brought designed objects into the world. Nervous systems themselves, and all designoid objects, are the products of an older and a slower cosmic dance. Sherrington's vision helped him to become one of the leading investigators of the nervous system in the first part of this century. We may profit by borrowing a parallel vision. Evolution is an enchanted loom of shuttling DNA codes, whose evanescent patterns, as they dance their partners through geological deep time, weave a massive database of ancestral wisdom, a digitally coded description of ancestral worlds and what it took to survive in them.

  But that is a train of thought that must wait for another book. The main lesson of this book is that the evolutionary high ground cannot be approached hastily. Even the most difficult problems can be solved, and even the most precipitous heights can be scaled, if only a slow, gradual, step-by-step pathway can be found. Mount Improbable cannot be assaulted. Gradually, if not always slowly, it must be climbed. {326}

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  Index

  acacia trees, and ants, 266

  accident, and design, 6

  A
dams, Douglas, 257–8

  aeroplane wings, 127

  Agaonidac, 300

  altruism, male fig wasps, 308–9

  Ampelisca, 183 (fig.)

  animal(s)

  artefacts, 18

  big, as scaled up small, 111

  land, return to water, 130–3

  flying, problems of size, 112

  small, ability to float, 112

  ‘statues’, 9

  ant(s)

  and acacia trees, 266

  accommodation for, 265 (fig.)

  ‘gardens’, 264 ant-loving plants, 265

  ant-mimicking beetle, 7–8 (fig.)

  segmentation, 241–2

  Araneus diadematus, web building, 43–4

  artefacts, animal, 18

  arthromorphs

  artificial selection, 249

  zoo, 250 (fig.)

  computer, 243–4

  genetic effects, 246 (fig.)

  segments, 245 (fig.)

  arthropods

  bodies, 243

  kaleidoscopic genes, 254

  repeated segments, 241 (fig.)

  variation of segments, 254 (fig.)

  artificial life, journal, 69

  Artificial Natural Selection, 72

  artificial selection

  animals, 29 (fig.)

  arthromorphs, 249

  computer biomorphs, 30–4

  and natural selection, 34–5

  plants, 27 (fig.)

  shells, 215 (fig.)

  Asimov, Isaac, 78

  asymmetry, possible evolution, 229

  bacteria, as example of TRIP robots, 286–7

  banana, usefulness of, 258

  Batbylychnops exilis, eye evolution, 196 (fig.)

  Bauplan, 228

  bees

  mason, pot nests, 16

  nectar, 258–9

  ultraviolet vision, 259–60

 

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