Eli: “I’d be surprised to learn that sex had no effect on the velocity of evolution. It looks like it should increase the speed and number of substituted adaptations, and also increase the complexity bound on the total genetic information that can be maintained against mutation.”
Without crossover, the average rate of fitness gain with optimal mutation rates is 1⁄2 bit per genome per generation, and the maximum tolerable error rate is one error per genome per generation. For a fixed error probability m of each bit being flipped in reproduction, the largest possible genome size is of order 1/m.
With crossover, both the average rate of fitness gain and the tolerable errors per generation are equal to the square root of the genome size in bits; the largest possible genome size is of order 1/(m^2).
So yes, sex has an effect, and it’s enormous. Rather than work out the math here and probably get it wrong, I’ll point to an excellent (and downloadable) textbook that discusses the issue: MacKay’s “Information Theory, Inference, and Learning Algorithms” at http://www.inference.phy.cam.ac.uk/mackay/itila/ . Chapter 19 contains the discussion of sexual vs. asexual evolution.
Eli: “I’d be surprised to learn that sex had no effect on the velocity of evolution. It looks like it should increase the speed and number of substituted adaptations, and also increase the complexity bound on the total genetic information that can be maintained against mutation.”
Without crossover, the average rate of fitness gain with optimal mutation rates is 1⁄2 bit per genome per generation, and the maximum tolerable error rate is one error per genome per generation. For a fixed error probability m of each bit being flipped in reproduction, the largest possible genome size is of order 1/m.
With crossover, both the average rate of fitness gain and the tolerable errors per generation are equal to the square root of the genome size in bits; the largest possible genome size is of order 1/(m^2).
So yes, sex has an effect, and it’s enormous. Rather than work out the math here and probably get it wrong, I’ll point to an excellent (and downloadable) textbook that discusses the issue: MacKay’s “Information Theory, Inference, and Learning Algorithms” at http://www.inference.phy.cam.ac.uk/mackay/itila/ . Chapter 19 contains the discussion of sexual vs. asexual evolution.
--Jeff