Plants, information, and the environment
I am interested in understanding how complex environments influence selection on organisms, and how organisms can respond adaptively to their environment. This is an exciting time in evolutionary biology: rapidly accumulating evidence on the effects of mutation at the molecular and developmental level is making the mapping from genotype to phenotype an increasingly tractable problem.
Selection sorts amongst organisms based on their physical characteristics (phenotype). However, there is a complex, often environmentally-dependent relationship of an organism's phenotype to its heritable material (genotype), which mediates the response to selection over time. To understand the outcome of evolution, we must understand genotypes, phenotypes, and the links between them. Thus, I study adaptation across a broad range of scales, incorporating genetic, developmental and physiological information into phenotypic selection analyses and mathematical models of life history. My work is largely based in the field, supplemented by greenhouse studies and theoretical models.
As a postdoc at Brown University, I am currently working on projects designed to explore how geographic variation in selection pressures shapes life history responses of Arabidopsis thaliana. For this large project, I -- along with a fantastic team of "post-bac" students that I supervise -- have maintained five common garden field sites distributed throughout Europe from near the Arctic Circle in Oulu, Finland to the Mediterranean coast in Valencia, Spain. In 15 total seasonal field plantings across the five common gardens in 2006-2008, we have collected life history data on a large set of genetically diverse lines drawn from throughout A. thaliana's range as well as controlled background genotypes with alternate alleles of key genes in flowering-time pathways. All together, we collected data on nearly 100,000 experimental plants!
Most recently, we have constructed a simple but powerful genetically-informed model that can accurately predict the flowering time of a variety of Arabidopsis genotypes based on day length and temperature inputs (Wilczek et al., Science, in press). Such models, which can predict phenology and life history as a function of environmental variables, will be critical to understanding the response of plants to changing climates.
Teaching and mentoring have played important roles in my scientific career thus far, and I look forward to future opportunities to involve students in the exciting and dynamic fields of evolutionary biology and ecology.
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