Macrosystems ecology is the study of ecological dynamics at multiple interacting spatial and temporal scales (e.g., Heffernan et al. 2014). For example, global climate change can interact with local land-use activities to control how an ecosystem changes over the next decades. Macrosystems ecology recently emerged as a new sub-discipline of ecology to study ecosystems and ecological communities around the globe that are changing at an unprecedented rate because of human activities (IPCC 2013). The responses of ecosystems and communities are complex, non-linear, and driven by feedbacks across local, regional, and global scales (Heffernan et al. 2014). These characteristics necessitate novel approaches for making predictions about how systems may change to improve both our understanding of ecological phenomena as well as inform resource management.
Forecasting is a tool that can be used for understanding and predicting macrosystems dynamics. To anticipate and prepare for increased variability in populations, communities, and ecosystems, there is a pressing need to know the future state of ecological systems across space and time (Dietze et al. 2018). Ecological forecasting is an emerging approach which provides an estimate of the future state of an ecological system with uncertainty, allowing society to prepare for changes in important ecosystem services. Ecological forecasts are a powerful test of the scientific method because ecologists make a hypothesis of how an ecological system works; embed their hypothesis in a model; use the model to make a forecast of future conditions; and then when observations become available, assess the accuracy of their forecast, which indicates if their hypothesis is supported or needs to be updated. Forecasts that are effectively communicated to the public and managers will be most useful for aiding decision-making. Consequently, macrosystems ecologists are increasingly using ecological forecasts to predict how ecosystems are changing over space and time.
Our interdisciplinary team is developing flexible classroom modules that introduce undergraduate students to the core concepts of macrosystems ecology and ecological forecasting. Each module utilizes long-term, high-frequency, and sensor-based datasets from diverse sources, including the Global Lakes Ecological Observatory Network, the United States Geological Survey, the Long Term Ecological Research Network, and the National Ecological Observatory Network.
Each module can be adapted for use in introductory, intermediate, and advanced courses in ecology and related fields, in order to enhance students' understanding of macrosystems ecology and ecological forecasting, their computational skills, and their ability to conduct inquiry-based studies.
Macrosystems EDDIE Modules
Climate Change Effects on Lake Temperatures
Introduction to Ecological Forecasting
Using Ecological Forecasts to Guide Decision Making
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:
- 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 ecological forecasting, 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
During 2017-2022, we will be using pre- and post-module student questionnaires and soliciting instructor feedback to assess whether our Macrosystems EDDIE modules are achieving their pedagogical goals. These assessments will allow us to determine whether the modules are helping increase students' understanding of macrosystems ecology and ecological forecasting skills, and will allow us to revise modules as needed to maximize their utility to instructors and students. Previous assessments of EDDIE modules found that students who completed EDDIE modules had significantly improved data manipulation skills, an increased understanding of how to use large datasets, and a greater appreciation for the value of high-resolution and long-term data. Thus, in addition to developing critical quantitative and modeling skills, working with high-frequency sensor datasets cements the real-world application of basic ecological concepts.
Publications and Presentations
Learn more about Macrosystems EDDIE by exploring our Publications and Presentations
Macrosystems EDDIE is supported by funding from NSF EF-1702506, DEB-1926050, DEB-1926050 and DBI-1933016.
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References and Resources
- Dietze, M. C., Fox, A., Beck-Johnson, L. M., Betancourt, J. L., Hooten, M. B., Jarnevich, C. S., Keitt, T. H., Kenney, M. A., Laney, C. M., Larsen, L. G., Loescher, H. W., Lunch, C. K., Pijanowski, B. C., Randerson, J. T., Read, E. K., Tredennick, A. T., Vargas, R., Weathers, K. C., & White, E. P. (2018). Iterative near-term ecological forecasting: Needs, opportunities, and challenges. Proceedings of the National Academy of Sciences, 115(7), 1424–1432. https://doi.org/10.1073/pnas.1710231115
- Heffernan, J.B., et al. 2014. "Macrosystems ecology: understanding ecological patterns and processes at continental scales." Frontiers in Ecology and the Environment 12.1: 5-14. Available: http://onlinelibrary.wiley.com/doi/10.1890/130017/abstract
- IPCC. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Page (T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley, Eds.). Cambridge University Press, New York, NY. Available: http://www.ipcc.ch/report/ar5/wg1/
- Weathers, K. C., P. M. Groffman, E. Van Dolah, E. Bernhardt, N. B. Grimm, K. McMahon, J. Schimel, M. Paolisso, R. Maranger, S. Baer, K. Brauman, and E. Hinckley. 2016. Frontiers in Ecosystem Ecology from a Community Perspective: The Future is Boundless and Bright. Ecosystems 19:753–770. Available: https://link.springer.com/article/10.1007%2Fs10021-016-9967-0