Sampling bias overestimates climate change impacts on forest growth in the southwestern United States

Sampling strategies may bias tree-ring datasets to not accurately represent the regional response to climate change. Here, Klesse et al. use a new representative dataset to show that the International Tree-Ring Data Bank in the U.S. Southwest overestimates climate sensitivity of forests by 41–59%

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Autores principales:	Stefan Klesse, R. Justin DeRose, Christopher H. Guiterman, Ann M. Lynch, Christopher D. O’Connor, John D. Shaw, Margaret E. K. Evans
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/fb2a22e2d7d542e89b3895880661ae15
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id	oai:doaj.org-article:fb2a22e2d7d542e89b3895880661ae15
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spelling	oai:doaj.org-article:fb2a22e2d7d542e89b3895880661ae152021-12-02T17:32:01ZSampling bias overestimates climate change impacts on forest growth in the southwestern United States10.1038/s41467-018-07800-y2041-1723https://doaj.org/article/fb2a22e2d7d542e89b3895880661ae152018-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-07800-yhttps://doaj.org/toc/2041-1723Sampling strategies may bias tree-ring datasets to not accurately represent the regional response to climate change. Here, Klesse et al. use a new representative dataset to show that the International Tree-Ring Data Bank in the U.S. Southwest overestimates climate sensitivity of forests by 41–59%Stefan KlesseR. Justin DeRoseChristopher H. GuitermanAnn M. LynchChristopher D. O’ConnorJohn D. ShawMargaret E. K. EvansNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-9 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Stefan Klesse R. Justin DeRose Christopher H. Guiterman Ann M. Lynch Christopher D. O’Connor John D. Shaw Margaret E. K. Evans Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
description	Sampling strategies may bias tree-ring datasets to not accurately represent the regional response to climate change. Here, Klesse et al. use a new representative dataset to show that the International Tree-Ring Data Bank in the U.S. Southwest overestimates climate sensitivity of forests by 41–59%
format	article
author	Stefan Klesse R. Justin DeRose Christopher H. Guiterman Ann M. Lynch Christopher D. O’Connor John D. Shaw Margaret E. K. Evans
author_facet	Stefan Klesse R. Justin DeRose Christopher H. Guiterman Ann M. Lynch Christopher D. O’Connor John D. Shaw Margaret E. K. Evans
author_sort	Stefan Klesse
title	Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
title_short	Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
title_full	Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
title_fullStr	Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
title_full_unstemmed	Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
title_sort	sampling bias overestimates climate change impacts on forest growth in the southwestern united states
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/fb2a22e2d7d542e89b3895880661ae15
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Sampling bias overestimates climate change impacts on forest growth in the southwestern United States

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