EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/21/2018 | 11:15 AM - 11:30 AM | QUANTIFYING THE EFFECTS OF STREAM FLOW ON FISH AND BENTHIC MACROINVERTEBRATE COMMUNITIES – A BAYESIAN NETWORKS MODELING APPROACH | 410 B
QUANTIFYING THE EFFECTS OF STREAM FLOW ON FISH AND BENTHIC MACROINVERTEBRATE COMMUNITIES – A BAYESIAN NETWORKS MODELING APPROACH
Characteristics of fish and benthic macroinvertebrate communities are affected by anthropogenic (e.g., land-use, flow-alteration, and climate change) and natural environmental variables (e.g., elevation, stream size, and geological/soil characteristics). Establishing quantitative links between ecological characteristics and environmental variables is challenging because of the complex interactions among variables and variation in spatiotemporal scales. Consequently, we often lack the data to parameterize process-based models and the complex interactions and varying spatiotemporal scales can produce misleading correlations when developing empirical models. Bayesian network modeling can be used to establish quantitative links among multiple factors that affect stream communities using simplified mechanisms that represent scientific understanding and are appropriate for the data. We employ a continuous variable Bayesian network model to model interactions among environmental variables and effects on streamflow, fish, and benthic invertebrate communities. This model predicts changes arising from climate change and can be incorporated into a decision support system allowing managers to envision potential effects of flow changes on communities. We present the model-building process using data from two river basins in North and South Carolina and use simulation for prediction under various climate change scenarios.
- Climate Change
- Aquatic-terrestrial Linkage
- Landuse
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Presenters/Authors
Song Qian
(), The University of Toledo, song.qian@utoledo.edu;
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Jason May
(), U.S. Geological Survey, California Water Science Center, jasonmay@usgs.gov;
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Jonathan Kennen
(), U.S. Geological Survey, New Jersey Water Science Center, 3450 Princeton Pike, Suite 110, Lawrenceville, NJ 08648, jgkennen@usgs.gov;
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Thomas Cuffney
(), U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Rd., Raleigh, NC 27607, tcuffney@usgs.gov;
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