Undergraduate Education

Conducting ecological research in a way that addresses complex, real-world problems requires a diverse, interdisciplinary and quantitatively trained ecology and environmental science workforce. We use ecological forecasting to show how ecology and environmental science undergraduate curriculum could be evaluated and ultimately restructured to address the needs of the 21st century workforce. We developed and implemented programs to increase the accessibility and comprehensiveness of ecological forecasting undergraduate education, including initiatives to engage specifically with Native American undergraduates and online resources for learning quantitative concepts at the undergraduate level.

In this module, students will generate an ecological forecast for a NEON site and explore how to use ecological data to improve forecast accuracy. This module will introduce students to the concept of data assimilation within an ecological forecast; how data assimilation can be used to improve forecast accuracy; how the level of uncertainty and temporal frequency of observations affects forecast output; and how data assimilation can affect decision-making using ecological forecasts.

Undergraduate and graduate students who completed the module showed increased familiarity with ecological forecasts and forecast uncertainty. Integrating ecological forecasting into undergraduate ecology curricula will enhance students’ abilities to engage and understand complex ecological concepts.

In this module, students will generate an ecological forecast for a NEON site and quantify the different sources of uncertainty within their forecast. This module will introduce students to the conceptof uncertainty within an ecological forecast; where uncertainty in a forecast comes from; how uncertainty can be quantified within a forecast; and how uncertainty can be managed.

In this module, students will apply the iterative forecasting cycle to develop an ecological forecast for a NEON site. This module will introduce students to the basic components of an ecological forecast; how a simple forecasting model is constructed; how changes to model inputs affect forecast uncertainty; and how productivity forecasts vary across ecoclimatic regions.

In this module, students will explore real ecological forecast visualizations, identify ways to represent uncertainty, make management decisions using forecast visualizations and learn decision support techniques. Lastly, students will then customize a forecast visualization for a specific forecast user’s decision needs.

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.