Ecological forecasting is an emerging sub-field of ecology which has the potential to both test basic ecological theory and provide much needed decision support tools for managing changing ecosystem services. Through my PhD research, I have used a variety of modeling approaches to develop ecological forecasts of several water quality variables of importance for decision-making.

This includes probabilistic forecasts of water temperature, dissolved oxygen, and phytoplankton concentrations in small eutrophic drinking water reservoirs and a large oligotrophic lake, examining questions about predictability across time scales, lake characteristics, and water quality variables

Relevant publications
Near-term phytoplankton forecasts reveal the effects of model time step and forecast horizon on predictability
Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
Increased adoption of best practices in ecological forecasting enables comparisons of forecastability
10 simple rules for training yourself in an emerging field

Reservoirs are typically considered to be spatially heterogeneous, but these patterns are often inconsistent across biogeochemical variables and across different reservoir ecosystems. Concurrently, seasonal drivers are also known to be important in altering biogeochemical cycles and influencing reservoir function. We collected surface water samples of carbon (C), nitrogen (N), and phosphorus (P) along a continuum from incoming streams to the lacustrine region of two reservoirs across seven months. We estimated changes over both space and time in biogeochemistry and processing within each reservoir to address fundamental questions about spatial and temporal heterogeneity in reservoirs.

Because of increased variability in populations, communities, and ecosystems due to land use and climate change, there is a pressing need to know the future state of ecological systems across space and time. Ecological forecasting is an emerging approach which provides an estimate of the future state of an ecological system with uncertainty, allowing society to preemptively prepare for fluctuations in important ecosystem services. However, forecasts must be effectively designed and communicated to those who need them to realize their potential for protecting natural resources.

I designed an educational module within the Macrosystems EDDIE program to address this gap. This module is part of a suite of Macrosystems EDDIE Modules which teach concepts related to ecological forecasting (more information about Macrosystems EDDIE can be found here). The overarching goal of this module is for students to understand how forecasts are connected to decision-making of forecast users, or the managers, policy-makers, and other members of society who use forecasts to inform decision-making.

In the module, students 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.

For more information about this module, other Macrosystems EDDIE modules, or to access the module teaching materials please visit here.