A problem akin to the knight’s predicament has been discussed fitfully with no resolution in evolutionary biology journals under the name “rugged fitness landscapes.” 8 In the 1930s the mathematical biologist Ronald Fisher pictured evolution as an exercise in hill climbing. The idea is that a species would gradually evolve to get better and better— to become more “fit”— until it was as good as it could be under the circumstances. In a sense, the species would rise to the acme of an evolutionary hill. Once there, it would be stuck— going back down the hill means getting less fit, which in a Darwinian competition should almost always be prohibited. 9 Well, what if, more realistically, instead of a single hill, the evolutionary geography actually resembled a badlands: a whole rugged landscape filled with many hills— big ones, little ones, tiny ones? The tiny ones are by far the most common, bigger ones much less frequent. There is only one highest peak. If so, then in a rugged evolutionary landscape, it is much more likely that a species will climb a tiny hill and get stuck there, unable to become less fit, yet forever isolated from the surrounding peaks. Random mutation and natural selection can’t solve the rugged landscape dilemma— they actually cause the dilemma.
Even in the shadow of an evolutionary Mount Everest— the promise of some terrific new biological feature— the challenge of a rugged landscape would remain. In fact, that is where it would become especially difficult. The more complex and interactive a system, the more its simple variations will short-circuit evolutionary hill climbing. As a physical example, think of the goal of building a structure like Iacocca Hall. An evolutionary story might start with a small shack, useful as a shelter, and hope to build on that. But the materials one would use to build a shack (wood, straw, nails) are not the ones one would need for a larger structure (cement, steel). The shack would serve, for a while, but could not be altered into a large building without essentially being replaced. Yet tearing down the building would remove the only shelter available at the time. Even construction of a small building that improbably used cement and steel would not include spaces for future staircases, electrical wiring, and so on that would be needed for a larger building. A smaller building that did have space for them would very likely be less efficient and more costly than one that didn’t. {and we know that nature is very efficient when it comes to processes - and if it did incorporate 'space' for future upgrades, that would involved design!}
To mix metaphors, how many steps should we expect random mutation and natural selection to climb before getting stuck on a tiny hill of a rugged landscape? Very few. Using a sophisticated mathematical model, H. Allen Orr decided that the likeliest number for a single gene was between just one and two. 10 That count fits pretty well both with John Maynard Smith’s reasoning about proteins and with what we know from the best relevant data on evolution we have available— the effects of malaria on the human genome. The evolutionary response of the human genome to Plasmodium falciparum has been exactly what you’d expect of a Darwinian process— disjointed and incoherent. In one group of humans the G6PD gene is broken, in another band 3 protein is defective. Both are single steps to small, local adaptive peaks. The sickle mutation pops up once or a few times, and then, separately, alterations in fetal hemoglobin ameliorate its side effects— several steps to an unrelated adaptive peak. Like some blind knight stumbling through a castle maze, in the case of sickle/ fetal hemoglobin, Darwinism has managed to walk up two steps, but has become stuck in an evolutionary dead end. Random mutation and natural selection are operating at full steam, but they lead nowhere.
This is not the kind of process that could have coordinated the many proteins that work in concert in intraflagellar transport. It is not the kind of process that leads to any significant degree of coherence.