Moths and Frogs and E. coli, Oh My!: Agent-based Modeling of Evolutionary Systems

In evolution classrooms, introducing and reinforcing the idea of genetic drift and random selection can be challenging, as can be reinforcing appropriate mental models of evolution. Agent-based models offer students the opportunity to conduct a model-based inquiry into the impacts of different features on the outcomes in evolutionary systems, helping to build, test, and expand their mental models of evolution. In this lesson—through independent investigation, model-based inquiry, and discussions with peers—students are introduced to the ways that agent-based models can be used to make predictions and test hypotheses about evolutionary systems. This lesson uses the NetLogo modeling environment, which comes preloaded with several useful teaching models and can be manipulated in an easy-to-use graphical interface. We use three models: a model of peppered moths focused on environmental pressures and natural selection, a red queen model focused on the competitive coevolution of snakes and frogs, and a genetic drift model of E. coli. Together, these models help reinforce evolutionary concepts in a hands-on, student-driven environment while improving their understanding of the utility of computing in evolution research. This lesson can be modified to suit courses of varying student levels and has been successfully adapted to online or lecture-based learning environments. Citation: Garretson A, Crerar LD. 2021. Moths and Frogs and E. coli, Oh My!: Agent-based Modeling of Evolutionary Systems. CourseSource. https://doi.org/10.24918/cs.2021.35 Editor: William Morgan, College of Wooster Received: 7/20/2020; Accepted: 4/19/2021; Published: 11/3/2021 Copyright: © 2021 Garretson and Crerar. This lesson manuscript is released to the “public domain” under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Under this license, authors retain ownership of the copyright to their article, but allow anyone to download, reuse, reprint, modify, distribute, and/or copy the article, as long as the original authors and source are cited and the intended use is not for commercial purposes. It is considered professional etiquette to provide attribution of the original work if this data package is shared in whole or by individual components. The authors shall not be liable for any damages resulting from misinterpretation or misuse of the lesson manuscript or its components. The authors affirm that we own the copyright to the text, figures, tables, artwork, abstract, summaries, and supporting materials. Conflict of Interest and Funding Statement: This work was supported in part by the George Mason University STEM Accelerator Program and the National Science Foundation Graduate Research Fellowship Program under Grant No. 1842191. Neither of the authors has a financial, personal, or professional conflict of interest related to this work. Supporting Materials: Supporting Files S1. Agent-based modeling – Presentation slides; S2. Agent-based modeling – Pre-test; S3. Agent-based modeling – Laboratory procedure; and S4. Agentbased modeling – Post-test. *Correspondence to: alexis@garretson.net CourseSource | www.coursesource.org 2021 | Volume 08 1 Lesson