Predicting Effects of Modifying Species Parameters in an Allometric Trophic Network Model
Oral Defence Date:
Committee: Profs. Ilmi Yoon, Hui Yang and Kaz Okada
The goal of modeling ecosystems is to find a tool that can be used to predict ecosystem behavior over time. The Allometric Trophic Network (ATN) model is designed to model the effects of feeding behavior in ecosystems. A major barrier to using such models is that it is hard to determine correct parameter values for specific ecosystems. We explored the use of gamification to address this problem. We developed a game that uses playersâ€™ visual reasoning to select prospective parameter values. Additionally, classification was used to analyze the effects of various parameter changes. Predictive visual features were identified that can be incorporated into the game as player recommendations. In particular, speciesâ€™ average biomass was found to respond in predictable ways to changes involving its own, predator, and prey parameters. These features may help players make more informed parameter changes.
Gamification, Science Discovery Games, Population Dynamics, Model Fitting, Prediction