NSF Postdoctoral Fellowship in Biology FY 2014

Mitchell Rachel M, Seattle WA

Investigators

Abstract

This NSF Postdoctoral Fellowships in Biology to Rachel M. Mitchell supports research entitled `Using Hierarchical Bayesian Models to Predict Patterns of Diversity.` NSF Postdoctoral Fellowships in Biology combine research and training components to prepare young scientists for careers in emerging areas where biology intersects with other scientific disciplines; this research is at the intersection of biology and mathematics, specifically statistical modelling. Fellows are expected to be leaders of the nation`s scientific workforce of the future. The host institution for this fellowship is Duke University and the sponsoring scientists are Dr. Justin Wright and Dr. Alan Gelfand, who can help train Dr. Mitchell in building a hierarchical Bayesian model. Thus Dr. Mitchell is gaining valuable skills in hierarchical Bayesian modelling with applications to ecology. She is also expanding outreach and teaching opportunities; partnering with the Museum of Life and Science allows her to share with children from diverse backgrounds a hands-on activity directly related to the research question. She is also implementing an abbreviated science outreach and communication seminar for graduate students at Duke University. The last decade has seen a tremendous growth of interest in plant functional traits, which are measurable traits that impact plant fitness. These traits are now understood to be actively selected on by abiotic filters like rainfall, temperature, and soil conditions. Such selection is hypothesized to determine how plant communities form and explain why some areas have more species than others. Until recently, the trait variation among individuals within a species (= intraspecific variation) has been largely ignored, but recent research has revealed that this variation is substantial and ecologically important. Although plant traits and intraspecific variation are known to be critical in shaping communities, they have yet to be fully incorporated into models predicting patterns of species presence and diversity. The model being built by Dr. Mitchell incorporates plant functional traits, abiotic filters, and intraspecific variation to predict patterns of diversity at both large and small scales in the southeastern United States. This model - the first of its kind - is a significant contribution to the fields of both ecology and statistical modeling. This project has implications for conservation on local and global scales. The model quantifies how traits mediate species presence in response to abiotic conditions, an issue of importance under projected climate change scenarios. Furthermore, it serves to identify areas of high diversity in terms of both species identity and functional traits; such areas are of high conservation value in a changing world. It clarifies the link between species and functional diversity, a link that must be understood if ecosystems and the services they provide are to be preserved.