Building, applying, and communicating ecosystem understanding via freshwater forecasts over time and space

Abstract

Accelerating rates of change in ecosystems globally heighten the need for improved predictions of future ecological conditions. Freshwater lakes and reservoirs, which provide numerous ecosystem services, are particularly threatened by global change stressors and have already exhibited substantial changes to their physical, chemical, and biological functioning. Thus, to provide useful predictive tools for managing freshwater resources in the face of global change, we must improve our ability to build, apply, and communicate understanding of lake and reservoir ecosystem dynamics. To address this, I first built ecosystem understanding by conducting multiple whole-ecosystem surveys to quantify the spatial and temporal variability of biogeochemistry in two reservoirs over a year. We found that temporal heterogeneity was higher than spatial heterogeneity for most biogeochemical variables, with the stream-reservoir interface as a consistent hotspot of biogeochemical processing. Second, I applied ecosystem understanding by producing ecological forecasts of physical (water temperature), chemical (dissolved oxygen), and biological (chlorophyll-a) variables across three waterbodies using diverse modeling methods. I developed daily, weekly, and fortnightly forecasts of chlorophyll-a at two drinking water reservoirs using a Bayesian linear model, and found process uncertainty dominated total forecast uncertainty. Additionally, I produced forecasts of water temperature and dissolved oxygen in an oligotrophic lake using a hydrodynamic-ecosystem model and found that water temperature was more predictable than oxygen despite variable performance over depth and between years. Across these two forecasting studies, forecast skill relative to a null model varied among water quality metrics: water temperature forecasts outperformed the null model up to 11 days ahead, oxygen forecasts outperformed the null model up to 2 days ahead, and chlorophyll-a forecasts outperformed the null model up to 14 days ahead. Third, to communicate forecasts for decision-making, I developed an educational module for undergraduate ecology students which taught important concepts on visualization and decision science. Following completion of the module, students' ability to identify methods for uncertainty communication increased significantly, as well as their understanding of the benefits of ecological forecasting. Overall, my dissertation provides insight into how reservoirs function in global biogeochemical cycles, the predictability of multiple water quality variables, and deepens our understanding of how to communicate ecosystem science for improved management and protection of ecosystems.