Building, applying, and communicating ecosystem understanding via freshwater forecasts over time and space
| dc.contributor.author | Woelmer, Whitney M. | en |
| dc.contributor.committeechair | Carey, Cayelan C. | en |
| dc.contributor.committeemember | Hanson, Paul C. | en |
| dc.contributor.committeemember | Thomas, R. Quinn | en |
| dc.contributor.committeemember | Hotchkiss, Erin R. | en |
| dc.contributor.department | Biological Sciences | en |
| dc.date.accessioned | 2023-09-06T08:00:55Z | en |
| dc.date.available | 2023-09-06T08:00:55Z | en |
| dc.date.issued | 2023-09-05 | en |
| dc.description.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. | en |
| dc.description.abstractgeneral | Human activities such as changing land use and climate have altered ecosystems around the world. As a result, many ecosystems no longer exhibit the same patterns from year to year as they have in the past, motivating the need for new tools to predict their future conditions. Among all ecosystems, freshwater lakes and reservoirs have been especially vulnerable due to human activities, threatening the critical services they provide to society, including drinking water and food, opportunities for recreational and cultural activities, and flood protection. Thus, because freshwater ecosystems are rapidly changing, forecasts of important water quality variables are needed. However, in order to use these forecasts effectively, a better understanding of how lakes and reservoirs change over space and time is needed, in addition to thoughtful communication of scientific findings for users. In my dissertation, I first addressed these needs by monitoring two reservoirs to examine how water quality varies over time and space. I found that water quality was more different over time (i.e., seasons) than over space (i.e., from one location to another within the reservoir). Second, I made ecological forecasts of water quality variables over space and time at different lakes. I forecasted phytoplankton levels in two drinking water reservoirs using a relatively simple model and water temperature and dissolved oxygen in a large clear-water lake using a more complex model. Comparing across forecasts in the three waterbodies, I found that my temperature forecasts provided valuable information above a baseline model up to 11 days ahead, oxygen forecasts up to 2 days ahead, and phytoplankton forecasts up to 14 days ahead. Third, because forecasts must be communicated effectively to be used as decision-making tools, I designed an educational module to teach forecast visualization and decision-making concepts. I found that students who completed the module better understood the benefits of forecasting for decision-making, and identified more ways to communicate forecasts after they completed the module. Overall, my dissertation shows the importance of measuring water quality over time and space to develop lake and reservoir forecasts, and demonstrates how forecast communication can help build students' understanding of the importance of forecasts for protecting and managing ecosystems. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:38395 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/116218 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| dc.subject | decision-making | en |
| dc.subject | ecological forecasting | en |
| dc.subject | forecasting education | en |
| dc.subject | lake and reservoir ecosystems | en |
| dc.subject | spatial and temporal variability | en |
| dc.subject | uncertainty | en |
| dc.subject | visualization science | en |
| dc.subject | water quality | en |
| dc.title | Building, applying, and communicating ecosystem understanding via freshwater forecasts over time and space | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Biological Sciences | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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