2022 Early Hearing Detection & Intervention Virtual Conference
March 13 - 15, 2022
5/23/2019 | 3:00 PM - 3:15 PM | USING A MULTI-MODELING APPROACH TO DISENTANGLE THE EFFECTS OF HUMAN-DRIVEN FLOW ALTERATIONS ON BENTHIC COMMUNITIES IN RIVERS OF THE NORTH AND SOUTHEAST US | 250 CF
USING A MULTI-MODELING APPROACH TO DISENTANGLE THE EFFECTS OF HUMAN-DRIVEN FLOW ALTERATIONS ON BENTHIC COMMUNITIES IN RIVERS OF THE NORTH AND SOUTHEAST US
Quantifying the effects of changes in streamflow on aquatic community response is central to understanding the role humans play in shaping the aquatic environment. These changes represent a level of complexity that often impedes the identification of quantitative links between flow drivers and biological responses. Addressing complex relations, that occur at differing spatiotemporal scales, requires a multi-modeling approach that empowers the establishment of scientifically defensible relations. CART, BRT, LASSO, and Bayesian network models (BNMs) were used to provide multiple lines of evidence for identifying important links between flow and assemblage responses in the Delaware, Yadkin-Pee Dee, and Cape Fear basins. Basin-scale analyses revealed that links between invertebrate responses and flow-alteration metrics were often obscured, however, analyses in homogeneous sub-basins (Level III ecoregions) were better able to discern relations with flow. BRT and LASSO analyses indicate that some ecoregions could be combined into smaller subgroups for analysis. Trait-based metrics showed the same effects of regionalization that were observed for taxa metrics. Change scenarios are being tested in BNMs and findings will be incorporated into Decision Support Systems to provide water managers with the tools necessary to address 21st-century water resource challenges.
- Landuse
- Water Quality
- Invertebrate
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Presenters/Authors
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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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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