Natural selection insures that the surviving lineage will be the fittest of many competing lineages. In probabilistic terms, natural selection picks “extreme values” from a population’s underlying fitness distribution. Extreme value distributions are famously robust to the underlying parent distribution, as are inter-arrival distributions for the timing of extreme events (in this case adaptive fixations).  Is there any way we can use these facts to make predictions about adaptive evolution that do not rely on specific information about individuals in the adapting population?

Lineages that have elevated mutation rates are likely to acquire beneficial mutations before lineages that do not have elevated mutation rates. If these beneficial mutations remain linked to the elevated mutation rate that produced them, then they will drive the elevated mutation rate to fixation. So it is easy to see how ever-higher mutation rates might evolve in adapting populations, especially in populations with low rates of recombination. There is now plenty of evidence – both theoretical and empirical – in support of such mutation-rate instability in asexual systems. What happens in such systems as mutation rate approaches the error threshold? Will mutation rate eventually stabilize, or will it remain unstable and thereby push the mutation rate over the threshold? Are there implications for anti-microbial treatment strategies?