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Supporting data for Savoy et al. (2019): Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes
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Created: May 28, 2019 at 7:04 p.m. (UTC)
Last updated: Aug 19, 2019 at 7:47 p.m. (UTC) (Metadata update)
Published date: Aug 19, 2019 at 7:47 p.m. (UTC)
DOI: 10.4211/hs.eba152073b4046178d1a2ffe9a897ebe
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Abstract

This document describes several of the derived datasets used in Savoy et al. (2019) as well as Koenig et al. (2019). The analysis presented in Savoy et al. (2019) describes identifying similar characteristic regimes of gross primary productivity (GPP) across 47 U.S. streams and rivers through the use of clustering analysis. This resource contains basic site information about each of the sites used in this analysis as well as the resulting cluster membership for each site. Additionally, representative time series of GPP are provided for each of the sites. Please refer to the readme.md file for descriptions of the contents of each file and a brief overview of how the data contained within them was created. A full description of the methods and results can be found in Savoy et al. (2019).

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Related Resources

This resource is referenced by Savoy, P. , Appling, A. P., Heffernan, J. B., Stets, E. G., Read, J. S., Harvey, J. W. and Bernhardt, E. S. 2019. Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes. Limnol Oceanogr. https://doi.org/10.1002/lno.11154
The content of this resource references Appling, A. P., and others. 2018. The metabolic regimes of 356 rivers in the United States. Sci. Data 5: 180292. https://doi.org/10.1038/sdata.2018.292
The content of this resource references Appling, A. P., R. O. Hall, M. Arroita, and C. B. Yackulic. 2018. streamMetabolizer: Models for estimating aquatic photosynthesis and respiration. R package version 0.10.9. https://github.com/USGS-R/streamMetabolizer
This resource is referenced by Koenig, L. E., Helton, A.M., Savoy, P., Bertuzzo, E., Heffernan, J.B., Hall, R.O., Jr, and Bernhardt, E. S. 2019. Emergent productivity regimes of river networks. Limnology and Oceanography Letters 0. https://doi.org/10.1002/lol2.10115
The content of this resource references Appling, A. P., R. O. Hall Jr., C. B. Yackulic, and M. Arroita. 2018. Overcoming equifinality: Leveraging long time series for stream metabolism estimation. J. Geophys. Res. Biogeosci. 123: 624–645. https://doi.org/10.1002/2017JG004140
The content of this resource is derived from Appling, A. P., and others. 2018. Metabolism estimates for 356 U.S. rivers (2007-2017). U.S. Geological Survey. https://doi.org/10.5066/F70864KX.

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation Defining Stream Biomes to Better Understand and Forecast Stream Ecosystem Change EF 1442439
USGS Powell Center Continental-scale overview of stream primary productivity, its links to water quality, and consequences for aquatic carbon biogeochemistry None

How to Cite

Savoy, P. (2019). Supporting data for Savoy et al. (2019): Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes, HydroShare, https://doi.org/10.4211/hs.eba152073b4046178d1a2ffe9a897ebe

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
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