While a rich set of statistical models have been developed to study evolution using DNA sequence data, many biological questions require information from organisms which are only known from the fossil record. In this project, the investigators will build models that account for biases inherent in using trait data from fossil species. The models will be tested and evaluated using the exceptionally rich fossil record associated with two groups of trilobites. Existing statistical tools will be extended to take full advantage of the estimates of the age of fossils. The new methods will be incorporated into widely used, open source software. Online educational materials in the form of virtual labs will be developed and distributed on the web.

This project will improve the computational and statistical machinery required to integrate information from fossil species into studies of the evolutionary tree of life. This will allow researchers to study extinction and speciation with unprecedented precision. Understanding these processes is crucial to understanding how Earth's biota will respond to the current biodiversity crisis. The virtual labs will teach junior high school students what data from these beautifully preserved organisms teaches us about evolutionary processes.

Agency
National Science Foundation (NSF)
Institute
Division of Environmental Biology (DEB)
Application #
1256993
Program Officer
Simon Malcomber
Project Start
Project End
Budget Start
2013-05-01
Budget End
2019-09-30
Support Year
Fiscal Year
2012
Total Cost
$449,216
Indirect Cost
Name
University of Kansas
Department
Type
DUNS #
City
Lawrence
State
KS
Country
United States
Zip Code
66045