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Mapping hydrologic alteration and ecological consequences in stream reaches of the conterminous United States.

Authors :
McManamay, Ryan A.
George, Rob
Morrison, Ryan R.
Ruddell, Benjamin L.
Source :
Scientific Data; 7/28/2022, Vol. 9 Issue 1, p1-13, 13p
Publication Year :
2022

Abstract

Environmental flows are critical for balancing societal water needs with that of riverine ecosystems; however, data limitations often hinder the development of predictive relationships between anthropogenic modifications to streamflow regimes and ecological responses – these relationships are the basis for setting regional water policy standards for rivers. Herein, we present and describe a comprehensive dataset of modeled hydrologic alteration and consequences for native fish biodiversity, both mapped at the stream-reach resolution for the conterminous U.S. Using empirical observations of reference conditions and anthropogenically altered streamflow at over 7000 stream gauges, we developed a predictive model of hydrologic alteration, which was extended to >2.6 million stream reaches. We then used a previous nationwide assessment of ecological responses to hydrologic alteration to predict fish biodiversity loss in stream reaches resulting from streamflow modification. Validation efforts suggested hydrologic alteration models had satisfactory performance, whereas modeled ecological responses were susceptible to compounded errors. The dataset could ameliorate regional data deficits for setting environmental flow standards while providing tools for prioritizing streamflow protection or restoration. Measurement(s) hydrologic alteration, human alteration of streamflow regimes • fish biodiversity Technology Type(s) Random forest • Quantile regression techniques Factor Type(s) human disturbances in streams (land use, dam storage, water use) Sample Characteristic - Organism Freshwater fish Sample Characteristic - Environment stream Sample Characteristic - Location contiguous United States of America [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
9
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
158239242
Full Text :
https://doi.org/10.1038/s41597-022-01566-1