  Predicting adaptive evolutionary trajectories is a primary goal of
evolutionary biology. One can differentiate between forward and backward
predictability, where forward predictability measures the likelihood of the
same adaptive trajectory occurring in independent evolutions and backward
predictability measures the likelihood of a particular adaptive path given the
knowledge of starting and final states. Recent studies have attempted to
measure both forward and backward predictability using experimental evolution
in asexual haploid microorganisms. Similar experiments in diploid organisms
have not been conducted. Here we simulate adaptive walks using Fisher's
Geometric Model in haploids and diploids and find that adaptive walks in
diploids are less forward- and more backward-predictable than adaptive walks in
haploids. We argue that the difference is due to the ability of diploids in our
simulations to generate transiently stable polymorphisms and to allow adaptive
mutations of larger phenotypic effect. As stable polymorphisms can be generated
in both haploid and diploid natural populations through a number of mechanisms,
we argue that inferences based on experiments in which adaptive walks proceed
through succession of monomorphic states might miss many of the key features of
adaptation.
