Initial Publication Date: December 12, 2017

About this Project

Ecologists are increasingly using models, based on large datasets of observations obtained through environmental sensor networks, to study ecosystems and forecast future change. Developing forecasts requires skills in data analysis, ecological modeling, 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 modeling and forecasting. Through our modules, both students and their instructors will learn how to quickly and efficiently run ecological models and generate forecasts for multiple NEON and GLEON sites. Thus, students will simultaneously learn the core concepts of macrosystems science and develop the quantitative 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 ecological research. Engaging undergraduate students in hands-on modeling and forecasting activities with real-world applications translates into a workforce with increased data science, systems thinking, and quantitative skills.

Project Goals

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 and ecological forecasting while developing quantitative literacy.

The Macrosystems EDDIE modules are specifically designed to help students achieve the following pedagogical goals:

  1. Improve students' ability to understand and predict how local, regional, and continental processes interact to mediate responses to human activities
  2. Gain computational skills through engagement in modeling, ecological forecasting, computer programming, distributed computing, and the analysis of large datasets
  3. 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.

Project Partners

Project Support

Macrosystems EDDIE is supported by funding from NSF EF-1702506 and DEB-1926050.