Major
Biology
Anticipated Graduation Year
2021
Access Type
Open Access
Abstract
Experimental evolution is the study of evolutionary processes occurring in experimental populations under controlled laboratory conditions. Our research studies fitness in a long-term evolution experiment that observes evolutionary ecological interactions between previously isolated populations. Fitness refers to which evolutionary strains have the highest levels of reproductive success. We used fitness measurements for individual E. Coli populations to predict the dynamics when eleven populations were grown together. The differences between our predictions and results suggest there are complicated interactions occurring between the populations. Understanding these interactions could lead to a better comprehension of evolutionary biology and advance future predictions of adaptations.
Faculty Mentors & Instructors
Caroline Turner, Department of Biology, Loyola University Chicago
Supported By
Michael Wiser, Michigan State University; Vaughn Cooper, University of Pittsburgh; Richard Lenski, Michigan State University
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Survival of the Fittest in the Long-Term Evolutionary Experiment
Experimental evolution is the study of evolutionary processes occurring in experimental populations under controlled laboratory conditions. Our research studies fitness in a long-term evolution experiment that observes evolutionary ecological interactions between previously isolated populations. Fitness refers to which evolutionary strains have the highest levels of reproductive success. We used fitness measurements for individual E. Coli populations to predict the dynamics when eleven populations were grown together. The differences between our predictions and results suggest there are complicated interactions occurring between the populations. Understanding these interactions could lead to a better comprehension of evolutionary biology and advance future predictions of adaptations.