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Award Abstract #1308885

NSF Postdoctoral Fellowship in Biology FY 2013

Div Of Biological Infrastructure
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Initial Amendment Date: July 17, 2013
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Latest Amendment Date: July 17, 2013
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Award Number: 1308885
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Award Instrument: Fellowship
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Program Manager: Michael Vanni
DBI Div Of Biological Infrastructure
BIO Direct For Biological Sciences
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Start Date: October 1, 2013
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End Date: September 30, 2016 (Estimated)
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Awarded Amount to Date: $207,000.00
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Investigator(s): Jamie Oaks (Principal Investigator)
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Sponsor: Oaks Jamie R

Lawrence, KS 66045-7593
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NSF Program(s): Inters Biol and Math and Phys
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Program Reference Code(s): 7137, 7174
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Program Element Code(s): 8054


Developing novel methods for testing models of shared evolutionary history

Understanding the processes that generate biodiversity is a fundamental goal of biology. To achieve this goal, it will be critical to account for mechanisms that influence the evolution of entire communities of co-occurring species, such as changes to the environment. The advancement of next-generation sequencing (NGS) technology provides opportunities to examine evolutionary history in unprecedented detail using genome-wide data from multiple species. However, there are currently no methods for analyzing NGS data in a comparative framework to test hypotheses about shared evolutionary history. The goal of this project is to develop Bayesian statistical models that can utilize NGS data for estimating the temporal pattern of speciation events across co-distributed taxa. These novel methods will be applied to NGS data from species across West-Central Africa to infer the effect of past aridifi cation cycles on the diversifi cation of

Afro-tropical rainforest fauna.

Broader impacts include the development of novel computational tools made freely available as open-source software. These tools will be of general interest across multiple disciplines, including biodiversity science and evolutionary medicine, by providing statistical approaches to estimate models of co-diversifi cation across landscapes and co-evolutionary dynamics between host taxa and their associated microbiomes. The former is critical for understanding global biodiversity, and the latter is important for understanding the evolutionary history and assembly of host-associated microbiota, including pathogens. Training objectives include mastering the mathematical, computational, and bioinformatic skills necessary for advancing research at the nexus of mathematics, statistics, and biology. This project will also use an evidence-based approach to develop classroom strategies for improving undergraduate education in the foundational concepts of evolution and the scienti fic method. This project will follow the principles of Open Notebook Science; all progress will be recorded in real time via version-control software and made publicly available on the Internet.


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Oaks, Jamie R.. "An Improved Approximate-Bayesian Model-choice Method for Estimating Shared Evolutionary History," BMC Evolutionary Biology, v.14, 2014, p. 150. 

Oaks, Jamie R., Charles W. Linkem, and Jeet Sukumaran. "Implications of uniformly distributed, empirically informed priors for phylogeographical model selection: A reply to Hickerson et al.," Evolution, v.68, 2014, p. 3607. 

Lira-Noriega, A., O. Toro-Nunez, J. R. Oaks, and M. E. Mort. "The roles of history and ecology in chloroplast phylogeographic patterns of the bird-dispersed plant parasite Phoradendron californicum Nutt. (Viscaceae) in the Sonoran Desert," American Journal of Botany, v.102, 2015, p. 149. 


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