About this Project
Ecologists are increasingly using simulation models, based on large datasets of observations obtained through environmental sensor networks, to study ecosystems and predict future change. Conducting this modeling, as well as interpreting model results, requires skills in data analysis, quantitative reasoning, and computing. However, modeling and computational skills are rarely taught in undergraduate classrooms, representing a major gap in training students to tackle complex environmental challenges.
Macrosystems EDDIE modules will help students across the U.S. to learn the foundations of macrosystems ecology through simulation modeling. Through our modules, both students and their instructors will learn how to quickly and efficiently run millions of simulations by using new resources emerging from computer science. Thus, students will simultaneously learn the core concepts of macrosystems science and develop the skill sets needed to conduct the next generation of environmental research. Macrosystems EDDIE modules, which are centered on the frontier of macrosystems ecology, will enable undergraduate students to contribute to high-level macrosystems research. Engaging undergraduate students in hands-on modeling activities with real-world applications translates into a workforce with increased data science, systems thinking, and quantitative skills.
Our objective is to develop stand-alone, modular classroom activities for undergraduate students that use publicly-available, long-term, and high-frequency datasets to explore the core concepts of macrosystems ecology while developing quantitative literacy.
The Macrosystems EDDIE modules are specifically designed to help students achieve the following pedagogical goals:
- Improve students' ability to understand and predict how local, regional, and continental processes interact to mediate responses to human activities
- Gain computational skills through engagement in simulation modeling, computer programming, distributed computing, and the analysis of large datasets
- Develop hypotheses, conduct inquiry-based studies to test them, and evaluate if their hypotheses are supported or rejected by data
Where Do Our Data Sets Come From?
Macrosystems EDDIE modules utilize long-term, high-frequency, and sensor-based datasets from diverse, publicly-accessible sources. Click the links below to learn more about our data providers.
- Global Lakes Ecological Observatory Network: (GLEON)
- National Ecological Observatory Network: (NEON)
- Long Term Ecological Research Network: (LTER)
- United States Geological Survey (USGS): Water Data for the Nation
- National Oceanic and Atmospheric Administration (NOAA): National Centers for Environmental Information
Macrosystems EDDIE is supported by funding from NSF EF 1702506, and leverages additional support from NSF DEB 1245707 and ACI 1234983.