Evolution of reduced dispersal mortality and 'fat-tailed' dispersal kernels in autocorrelated landscapes.

Models describing the evolution of dispersal strategies have mostly focused on the evolution of dispersal rates. Taking trees as a model for organisms with undirected, passive dispersal, we have developed an individual-based, spatially explicit simulation tool to investigate the evolution of the dispersal kernel, P(r), and its resulting cumulative seed-density distribution, D(r). Simulations were run on a variety of fractal landscapes differing in the fraction of suitable habitat and the spatial autocorrelation. Starting from a uniform D(r), evolution led to an increase in the fraction of seeds staying in the home cell, a reduction of the dispersal mortality (arrival in unsuitable habitat), and the evolution of 'fat-tailed' D(r) in autocorrelated landscapes and approximately uniform D(r) in random landscapes. The evolutionary process was characterized by long periods of stasis with a few bouts of rapid change in the dispersal rate.

Sex ratio polymorphism: the impact of mutation and drift on evolution.

This paper addresses the question, which sex ratio will evolve in a population that is subject to mutation and drift. The problem is analyzed using a simulation model as well as analytical methods. A detailed simulation model for the evolution of a population's allele distribution shows that for the sex ratio game a wide spectrum of different population states may evolve from on the one hand a monomorphic state with one predominant allele and with all other alleles suppressed by the forces of selection, to on the other hand a polymorphism determined by recurrent mutations. Which of these states will evolve depends on the population size, the mating system and the rate of mutations. For the sex ratio game the evolutionary stable strategy (ESS), as defined by evolutionary game theory, can only predict the population sex ratio but not the underlying stable population state. A comparison of different approaches to the problem shows that false predictions of the stable population states might result from two simplifying assumptions that are fairly common in evolutionary biology: a) it is assumed that mutations are rare events and there is never more than one mutant gene present in a population at any one time; b) a deterministic relationship is assumed between the fitness assigned to an individual's strategy and the individual's contribution to the gene pool of future generations.