Why evolution gets it wrongSaturday, 19 July, 2008
In Richard Dawkins’s book Climbing Mount Improbable, he uses the analogy of climbing a mountain in mountain range for evolution a particular complex organ. At the tops of the peaks are the best solutions to a given problem, and as one goes down the slope there are many less optimal designs until one reaches the flat at the bottom where no solution exists at all. This is the concept of the adaptive landscape.
If I had written the book, I would have asked readers to imagine a group of climbers, who are blindfolded so they can only take random steps. The climbers wisely only take slight steps, because a big step would very likely take the climber off the mountain, but this also makes even small cliffs very hard to scale. Climbers would be rewarded for taking a step up the slope, but punished for stepping down the slope.
In evolutionary terms, mutations cause each individual to differ randomly from its parents. Mutations usually are very slight, because large mutations are usually very bad. But this means that it is almost impossible to evolve some feature, like an eye, with just a small number of large mutations. And if the mutation was beneficial then by natural selection it will be preserved (the organism will be more successful), and if the mutation was detrimental it will be selected against.
Returning to the analogy of the mountain again, it is clear descending the mountain is actually very unlikely. Dawkins says this:
[T]here can be no going downhill – species can’t get worse as a prelude to getting better.
Strictly speaking they can get worse, but they will be under a selective pressure to not do so, and therefore going downhill will not last for long. It would be as if for every step downhill a stone was added to the climber’s pack (with heavier stones added for large drops, and light stones for very slight descents). They may be able to step down a few times, but with each step they would be slowed down until they had to stop and start heading back up the slope. In evolutionary terms, organisms may be slightly worse than their peers for a generation or two, provided they can still survive and reproduce long enough for another mutation to put their offspring at an advantage.
With climbers moving randomly and (almost) exclusively uphill, mostly taking small steps, how likely is it that these climbers will reach the summit of Mt. Everest? Answer: Not likely at all. They will reach a peak of some other hill, but not the greatest peak.
As Richard Dawkins says of eye evolution:
A case could be made that, absolutely all other things being equal, it might have been better if our retinas were the right way around. it is perhaps a good example of the fact that Mount Improbable has more than one peak, with deep valleys in between. Once a good eye has started to evolve with its retina back-to-front, the only way to ascend is to improve the present design of eye. Changing to a radically different design involves going downhill, not just a little way but down a deep chasm, and that is not allowed by natural selection.
Therefore, if one finds oneself at the top of a lesser peak, all one can do is wait for one of those rare big random leaps to take you to a higher point (it is this period of waiting, followed by a sudden leap, that is called ‘punctuated equilibrium’ – a distorted version of which was the premise for the fictional X-Men characters).
We humans are smart enough to be able to reflect on the evolved designs of our bodies and compare them to that of other organisms. It is as if the climbers finally have the blindfolds removed, and can now see where the other climbers are and roughly where the other peaks are on the mountain. And in many cases we see that we, and many other climbers, ended up at a sub-optimal peak. We may not know the exact altitudes of each peak (i.e. we don’t know for sure how much seeing in ultraviolet or having gills will be advantageous), but we can still investigate these other peaks. And we should. We are smarter than evolution; evolution (call it nature, Mother Nature or whatever) does not know best.