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A stream classification system for the conterminous United States

Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring...

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Autores principales: McManamay, Ryan A., DeRolph, Christopher R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371895/
https://www.ncbi.nlm.nih.gov/pubmed/30747915
http://dx.doi.org/10.1038/sdata.2019.17
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author McManamay, Ryan A.
DeRolph, Christopher R.
author_facet McManamay, Ryan A.
DeRolph, Christopher R.
author_sort McManamay, Ryan A.
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description Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring stream habitats is needed, as this provides a physical template upon which stream biodiversity is organized and maintained. To adequately represent the heterogeneity of stream ecosystems, such a classification needs to be spatially extensive where multiple stream habitat components are represented at the highest resolution possible. Herein, we present a multi-layered empirically-driven stream classification system for the conterminous US, constructed from over 2.6 million stream reaches within the NHDPlus V2 stream network. The classification is based on emergent natural variation in six habitat layers meaningful at the stream-reach resolution: size, gradient, hydrology, temperature, network bifurcation, and valley confinement. To support flexibility of use, we provide multiple alternative approaches to developing classes and report uncertainty in classes assigned to stream reaches. The stream classification and underlying data provide valuable resources for stream conservation and research.
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spelling pubmed-63718952019-02-13 A stream classification system for the conterminous United States McManamay, Ryan A. DeRolph, Christopher R. Sci Data Data Descriptor Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring stream habitats is needed, as this provides a physical template upon which stream biodiversity is organized and maintained. To adequately represent the heterogeneity of stream ecosystems, such a classification needs to be spatially extensive where multiple stream habitat components are represented at the highest resolution possible. Herein, we present a multi-layered empirically-driven stream classification system for the conterminous US, constructed from over 2.6 million stream reaches within the NHDPlus V2 stream network. The classification is based on emergent natural variation in six habitat layers meaningful at the stream-reach resolution: size, gradient, hydrology, temperature, network bifurcation, and valley confinement. To support flexibility of use, we provide multiple alternative approaches to developing classes and report uncertainty in classes assigned to stream reaches. The stream classification and underlying data provide valuable resources for stream conservation and research. Nature Publishing Group 2019-02-12 /pmc/articles/PMC6371895/ /pubmed/30747915 http://dx.doi.org/10.1038/sdata.2019.17 Text en Copyright © 2019, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
McManamay, Ryan A.
DeRolph, Christopher R.
A stream classification system for the conterminous United States
title A stream classification system for the conterminous United States
title_full A stream classification system for the conterminous United States
title_fullStr A stream classification system for the conterminous United States
title_full_unstemmed A stream classification system for the conterminous United States
title_short A stream classification system for the conterminous United States
title_sort stream classification system for the conterminous united states
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371895/
https://www.ncbi.nlm.nih.gov/pubmed/30747915
http://dx.doi.org/10.1038/sdata.2019.17
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