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Decision Support
Published in Yeqiao Wang, Terrestrial Ecosystems and Biodiversity, 2020
The A.T. Decision Support System (DSS), or A.T.-DSS, is an Internet-based implementation and dissemination toolset accessible at www.edc.uri.edu/ATMT-DSS. The design of the A.T.-DSS was to facilitate decision support for management of the A.T. with the monitoring, reporting, and forecasting capacity from remote sensing-based Earth observations and geospatial modeling. It was also designed to provide a means to convey meaningful information to the American public. The National Park Service (NPS) Inventory and Monitoring (I&M) program is designed to develop and implement long-term natural resource monitoring and create a targeted decision support system aimed at selecting a suite of reliable and representative metrics, or vital signs, to provide long-term data on changes in ecosystem health (Shriver et al., 2005). Among the vital signs defined by the I&M program and A.T. MEGA-Transect partners, the A.T.-DSS targets phenology and climate change, forest health, and landscape dynamics for system development, data preparation, and modeling, in order to provide time-series and ecological forecasting information for an improved decision support process.
Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
Published in Inland Waters, 2022
Cayelan C. Carey, Whitney M. Woelmer, Mary E. Lofton, Renato J. Figueiredo, Bethany J. Bookout, Rachel S. Corrigan, Vahid Daneshmand, Alexandria G. Hounshell, Dexter W. Howard, Abigail S. L. Lewis, Ryan P. McClure, Heather L. Wander, Nicole K. Ward, R. Quinn Thomas
The emerging discipline of ecological forecasting provides a novel approach for preemptively managing lakes and reservoirs in the face of increasing water quality variability. Ecological forecasting, or the prediction of future ecosystem properties with quantified uncertainty (sensu Clark et al. 2001, Luo et al. 2011, Dietze et al. 2018; Table 1), provides a useful tool for managers. Forecasts provide managers with probabilistic estimates of future water quality conditions in their focal lake or reservoir, thus allowing them to take preemptive management actions to mitigate or prevent water quality impairment.