Modeling Evolution
My work focuses on the development of population-genetic models, using analytical and numerical techniques to infer what evolutionary changes are possible and under what conditions.
Over the next three years, research performed in my lab will investigate three unresolved questions in evolutionary biology:
How does the balance between haploid and diploid phases of a life cycle evolve?
The haploid and diploid phases of sexual life cycles are extremely variable in length, ranging from little development in one or the other phase to equal development in both.
We do not yet understand, however, the factors that favor different life cycles.
I will develop evolutionary models that include ecological factors and population structure, factors that may play a central role in governing the evolutionary transition between haploidy and diploidy.
How does sexual selection affect evolution when both sexes have mating preferences?
Models of sexual selection have focused on mating preferences in one sex of a species (generally in females).
We know little, however, about when evolution will favor mating preferences in both sexes.
Even if both sexes have mating preferences, when does one sex tend to evolve stronger preferences?
Are predictions made from models with only female mate choice sensitive to the inclusion of male mate choice?
I will incorporate male and female choice into evolutionary models of sexual selection.
Why has recombination evolved?
This question has been of central interest to evolutionists for some time, yet we still do not know the answer.
Theoretical analyses have found that evolution can favor increased recombination, but that it often favors decreased recombination.
The essential problem is that recombination acts as a double-edged sword, both creating and destroying advantageous gene combinations.
I will incorporate stochastic processes (e.g. random genetic drift and random mutations) into models that investigate the evolution of recombination rates.
It is likely that recombination will be more broadly favored in these models.
The results of these analyses will both enhance our understanding of evolution and provide specific predictions that can be tested experimentally.