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Population Structures Make Natural Selection Seem Inconsistent

Experts in multiple fields concur that natural selection is an idea that has changed over time and only resembles but does not match that which Darwin first theorized / Photo by Pavlo Vakhrushev via 123RF

 

Natural selection hasn’t been the easiest concept to explain in scientific discourse over the years. It’s a facet of evolutionary theory that seems to evince a pattern at times until you find several exceptions that force to rethink how it works. That’s what scientists have been doing for years—repeatedly rethinking the concept. In fact, experts in multiple fields concur that natural selection is an idea that has changed over time and only resembles but does not match that which Darwin first theorized. That said, a multidisciplinary team of researchers from Austria and the U.S. just published the findings of their new study in Communications Biology, and they put forward a mathematical model that makes sense of certain mechanics of natural selection.

Martin Nowak is the director of Harvard University’s evolutionary dynamics lab, and he spearheaded the American effort on the study. From the Institute of Science and Technology, the venerable computer scientist, Krishnendu Chatterjee, teamed up with Nowak to demonstrate how natural selection’s inconsistencies might still constitute the method many presume to find in its madness. They show how there are some population structures that can actually impinge measurably on the rate f natural selection while other structures expedite selection. To understand what’s at stake in the argument they make, though, one has to remember Darwin’s classic study of the finches in the Galápagos Islands. He had found finches to be a species with many phenotypic distinctions from one population to another, and he ultimately concluded that it had to do with the sizes of the islands and the fact that they were clustered together in an archipelago.

 

Mutations theoretically see better odds of survival in their respective populations if they aren’t crowded out by other advantageous mutations represented throughout the species / Photo by xbrchx via 123RF

 

This is a notion that has been challenged from many angles many different times, but essentially, the idea is that these islands create a relative isolation of multiple populations of a ubiquitous species. The point that Nowak and Chatterjee are making with mathematical proof to support it is that these isolations that split a species into so many separate populations significantly impact the chances of certain mutations gaining the opportunity to be selected. Selection ideally goes for mutations that prove advantageous to a species or, rather, to a population according to Darwin’s assessment. Mutations theoretically see better odds of survival in their respective populations if they aren’t crowded out by other advantageous mutations represented throughout the species. Isolated populations improve those odds of survival for some of the advantageous mutations that otherwise would have been to underrepresented to make it.

John Rennie published an article with Quanta on this Nowak-Chatterjee study and broke it down pretty well. “Picture a huge population of organisms all living together on one island, for example,” he wrote. “A mutation might get permanently lost in the crowd unless its advantage is great. Yet if a few individuals regularly migrate to their own islands to breed, then a modestly helpful mutation might have a better chance of establishing a foothold and spreading back to the main population.” Other factors can derail the improvement of odds for those modestly advantageous mutations, but that’s the long and short of it.

 

From there, though, Nowak reasoned “that cancer is an evolutionary process that the organism does not want.” By this, he meant that, once malignant cells emerge via mutation, they compete against each other for which ones are most capable of spreading, and those most capable are selected. “I asked myself: how would you get rid of evolution?” He knew just attacking selection wasn’t the solution. Biologists, however, have never really understood in much detail how population structures impact natural selection, so Nowak turned to graph theory. That’s also where Chatterjee comes into the picture. The study presents a math problem that establishes that the probability of an advantageous mutation achieving fixation (proliferating among hundreds to thousands of individuals in a massive population) is 1 – 1/r such that r = the mutation’s relative fitness.

This means, should the mutation’s fitness improve by five percent (r = 1.05), that mutation’s chance of fixation achievement will only be 4.7 percent. On the other hand, a mutation that boasts of a tenfold fitness advantage (p = 0.9) is almost guaranteed fixation whereas the former has only a 50/50 chance (p = 0.5). Still, the small fitness advantage is actually quite large if it’s in a much smaller population. The smaller the population, the greater the probability of achievement there is for mutations whose advantages are not great but are yet substantial. These things should be applicable, therefore, to other questions that researchers are asking in other studies about completely different animals.

Certain insects and snakes are venomous and can prey on others or defend themselves with their toxins. Having that advantage means that, in a life or death scenario, all a rattlesnake needs to do is get one good, venomous strike and outlast its opponent. Evolutionists recognize this and often pontificate on the origins of venom production as a mutation. There are some 100,000 venomous species in the world, but there’s no evidence that venom as a mutation is the product of a common, poisonous ancestor. For that matter, venom is attributable to multiple mutations, not just one. It has long been the consensus among evolutionists that, by and large, new abilities representative of multiple mutations result from environmental changes like a decline in the number of prey, a climate shift or resource deficiency.

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