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SFS Annual Meeting

Poster Details

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Due to recent advancements in model design and sensor technology, long-term monitoring of stream metabolism is more practical and affordable than ever before. Still, general understanding of what drives variation in metabolism across time and space has been hampered by a lack of consistency in methodologies for collecting and modeling stream data. The StreamPULSE project provides a central, web-based platform for the submission, storage, retrieval, and analysis of data acquired from streams and rivers worldwide. It also promotes an adaptable set of standard procedures for data collection and analysis, and for the interpretation of model outputs. Here we show developments to the platform over the last year, including tools for visual quality control, outlier detection, and gap filling. Upcoming features include versatile anomaly detection via decision trees and elastic, on-demand cloud modeling.

Michael Vlah (Co-Presenter/Co-Author), Duke University,;

Matthew Cohen (Co-Presenter/Co-Author), University of Florida,;

Nancy Grimm (Co-Presenter/Co-Author), Arizona State University,;

Robert Hall (Co-Presenter/Co-Author), Flathead Lake Biological Station, University of Montana,;

Jim Heffernan (Co-Presenter/Co-Author), Duke University,;

Ashley Helton (Co-Presenter/Co-Author), University of Connecticut,;

William H. McDowell (Co-Presenter/Co-Author), University of New Hampshire,;

Brian McGlynn (Co-Presenter/Co-Author), Duke University,;

Jordan Read (Co-Presenter/Co-Author), US Geological Survey,;

Emily Stanley (Co-Presenter/Co-Author), University of Wisconsin - Madison,;

Emily Bernhardt (Primary Presenter/Author), Duke University,;