Modeling insect outbreaks in forest canopies: Integration of virtual simulations with hands-on ecology for undergraduates

Abstract

One of the new challenges facing STEM education is to integrate emerging technologies with inquiry-based environmental science (Lowman and Mourad 2010). On the one hand, ecological literacy of Americans is decreasing, perhaps in part due to “nature-deficit disorder” (Louv 2006). On the other hand, students are more apt to experience virtual ecosystems through gaming and computers than experience the outdoors firsthand (Balmford et al. 2002). We propose activities of modeling environmental issues to inspire students to seek careers in science and also to learn about their local ecosystem dynamics. This exercise requires some knowledge of ecology, math, computers, entomology, and climate change. By modeling insect outbreaks or other applied ecological issues, students have an interdisciplinary approach to problem-solving and also are motivated by using virtual and real systems. In this project, we develop an interdisciplinary approach to biology teaching. We created an activity that allowed students to change the parameters of insect outbreaks and the underlying canopy structure of a virtual tree to understand possible outbreak patterns. The learning curve is not steep and the basics of the model can be mastered within a single class with subsequent projects assigned to be completed in a week. This approach is of particular relevance to a biology teacher, since different outbreak scenarios can be considered with relatively short computer runs providing an outstanding supplement to the available historical data on forests and insect pests. In short, this is an interaction that can be observed in the school yard, garden, or at a national scale. From the modeling point of view, our approach is an extension of cellular automata models for fire and decease propagation but applied to tree structure. This approach gives our ecology/biology students a valuable exposure to contemporary agent-based modeling. First, we review some relevant work on the subject and then proceed to describing the algorithm and results.