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dc.contributor.authorVandvik, Vigdis
dc.contributor.authorHalbritter, Aud H
dc.contributor.authorYang, Yan
dc.contributor.authorHe, Hai
dc.contributor.authorZhang, Li
dc.contributor.authorBrummer, Alexander B
dc.contributor.authorKlanderud, Kari
dc.contributor.authorMaitner, Brian S
dc.contributor.authorMichaletz, Sean T
dc.contributor.authorSun, Xiangyang
dc.contributor.authorTelford, Richard J
dc.contributor.authorWang, Genxu
dc.contributor.authorAlthuizen, Inge H J
dc.contributor.authorHenn, Jonathan J
dc.contributor.authorGarcia, William Fernando Erazo
dc.contributor.authorGya, Ragnhild
dc.contributor.authorJaroszynska, Francesca
dc.contributor.authorJoyce, Blake L
dc.contributor.authorLehman, Rebecca
dc.contributor.authorMoerland, Michelangelo Sergio
dc.contributor.authorNesheim-Hauge, Elisabeth
dc.contributor.authorNordås, Linda Hovde
dc.contributor.authorPeng, Ahui
dc.contributor.authorPonsac, Claire
dc.contributor.authorSeltzer, Lorah
dc.contributor.authorSteyn, Christien
dc.contributor.authorSullivan, Megan K
dc.contributor.authorTjendra, Jesslyn
dc.contributor.authorXiao, Yao
dc.contributor.authorZhao, Xiaoxiang
dc.contributor.authorEnquist, Brian J
dc.date.accessioned2021-01-09T03:17:33Z
dc.date.available2021-01-09T03:17:33Z
dc.date.issued2020-06-19
dc.identifier.citationVandvik, V., Halbritter, A. H., Yang, Y., He, H., Zhang, L., Brummer, A. B., ... & Enquist, B. J. (2020). Plant traits and vegetation data from climate warming experiments along an 1100 m elevation gradient in Gongga Mountains, China. Scientific data, 7(1), 1-15.en_US
dc.identifier.issn2052-4463
dc.identifier.pmid32561854
dc.identifier.doi10.1038/s41597-020-0529-0
dc.identifier.urihttp://hdl.handle.net/10150/650702
dc.description.abstractFunctional trait data enhance climate change research by linking climate change, biodiversity response, and ecosystem functioning, and by enabling comparison between systems sharing few taxa. Across four sites along a 3000-4130m a.s.l. gradient spanning 5.3 degrees C in growing season temperature in Mt. Gongga, Sichuan, China, we collected plant functional trait and vegetation data from control plots, open top chambers (OTCs), and reciprocally transplanted vegetation turfs. Over five years, we recorded vascular plant composition in 140 experimental treatment and control plots. We collected trait data associated with plant resource use, growth, and life history strategies (leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N and P content and C and N isotopes) from local populations and from experimental treatments. The database consists of 6,671 plant records and 36,743 trait measurements (increasing the trait data coverage of the regional flora by 500%) covering 11 traits and 193 plant taxa (ca. 50% of which have no previous published trait data) across 37 families. center dot type of treatment (e.g in situ warming experiments using an Open Top Chamber)en_US
dc.language.isoenen_US
dc.publisherNATURE PUBLISHING GROUPen_US
dc.rights© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/applies to the metadata files associated with this article.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titlePlant traits and vegetation data from climate warming experiments along an 1100 m elevation gradient in Gongga Mountains, Chinaen_US
dc.typeArticleen_US
dc.identifier.eissn2052-4463
dc.contributor.departmentUniv Arizona, Dept Ecol & Evolut Biolen_US
dc.contributor.departmentUniv Arizona, Univ Informat Technol Serven_US
dc.identifier.journalSCIENTIFIC DATAen_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleScientific data
dc.source.volume7
dc.source.issue1
dc.source.beginpage189
dc.source.endpage
refterms.dateFOA2021-01-09T03:17:47Z
dc.source.countryEngland


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© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/applies to the metadata files associated with this article.
Except where otherwise noted, this item's license is described as © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/applies to the metadata files associated with this article.