Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model

Adaptation in tunably rugged fitness landscapes: the rough Mount Fuji model.

Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by th...

Evolutionary accessibility in tunably rugged fitness landscapes

The adaptive evolution of a population under the influence of mutation and selection is strongly influenced by the structure of the underlying fitness landscape, which encodes the interactions between mutations at different genetic loci. Theoretical studies of such landscapes have been carried out for several decades, but only recently experimental fitness measurements encompassing all possible...

Some Notes on Organisational Adaptation on Rugged Fitness Landscapes

Adaptation on Rugged Landscapes

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Evolutionary trajectories in rugged fitness landscapes

We consider the evolutionary trajectories traced out by an infinite population undergoing mutation-selection dynamics in static, uncorrelated random fitness landscapes. Starting from the population that consists of a single genotype, the most populated genotype jumps from a local fitness maximum to another and eventually reaches the global maximum. We use a strong selection limit, which reduces...