Steve Schaffner
Posts: 13
Joined: June 2009
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Basically, he is applying reductions in heritability twice. The heritability function itself, and then this random procedure for selecting reproductive winners by re-ranking them before truncation and passing to the next generation. We could modify the divisor to some function(randomnum) and adjust the degree and type of randomness for picking winners {something like randomnum^N}. It's just another way of introducing random factors into the choice of winners and losers which should already have been accounted for in the heritability function.
The net result is a significant reduction in the effect of selection. |
It would make more sense if it were described in terms of some other phenotype with an effect on fitness. The phenotype has a genetic component and an environmental (or random) component, i.e. has a heritability. The phenotype then confers a fitness, which is the probability of successful reproduction. The number of successful offspring is also drawn from a random distribution, which is what's being done in this bit of code (I guess treated as a binomial distribution).
As a model of selection that seems reasonable (apart from the way the noise scales), but expressing it in terms of the heritability of fitness I find hard to understand -- fitness isn't a phenotype, it's a measure of the success of a phenotype. And the whole thing is pretty convoluted, when the essence of the model could be captured simply by assigning a fitness to the genotype and then calculating the number of offspring. This is a model of evolution written by a breeder rather than by a population geneticist, I would say.
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