Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale
Historical and future trends in net primary productivity (NPP) and its sensitivity to global change are largely unknown because of the lack of long-term, high-resolution data. Here the authors show that tree-ring isotopes can be used for inferring interannual variability and long-term changes in NPP...
Guardado en:
Autores principales: | , , , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/47cfaee88d5749c992d8185f4f09b0e8 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:47cfaee88d5749c992d8185f4f09b0e8 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:47cfaee88d5749c992d8185f4f09b0e82021-12-02T14:38:37ZTree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale10.1038/s41467-019-08634-y2041-1723https://doaj.org/article/47cfaee88d5749c992d8185f4f09b0e82019-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-08634-yhttps://doaj.org/toc/2041-1723Historical and future trends in net primary productivity (NPP) and its sensitivity to global change are largely unknown because of the lack of long-term, high-resolution data. Here the authors show that tree-ring isotopes can be used for inferring interannual variability and long-term changes in NPP.Mathieu LevesqueLaia Andreu-HaylesWilliam Kolby SmithA. Park WilliamsMartina L. HobiBrady W. AllredNeil PedersonNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-10 (2019) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Science Q |
spellingShingle |
Science Q Mathieu Levesque Laia Andreu-Hayles William Kolby Smith A. Park Williams Martina L. Hobi Brady W. Allred Neil Pederson Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
description |
Historical and future trends in net primary productivity (NPP) and its sensitivity to global change are largely unknown because of the lack of long-term, high-resolution data. Here the authors show that tree-ring isotopes can be used for inferring interannual variability and long-term changes in NPP. |
format |
article |
author |
Mathieu Levesque Laia Andreu-Hayles William Kolby Smith A. Park Williams Martina L. Hobi Brady W. Allred Neil Pederson |
author_facet |
Mathieu Levesque Laia Andreu-Hayles William Kolby Smith A. Park Williams Martina L. Hobi Brady W. Allred Neil Pederson |
author_sort |
Mathieu Levesque |
title |
Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
title_short |
Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
title_full |
Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
title_fullStr |
Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
title_full_unstemmed |
Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
title_sort |
tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale |
publisher |
Nature Portfolio |
publishDate |
2019 |
url |
https://doaj.org/article/47cfaee88d5749c992d8185f4f09b0e8 |
work_keys_str_mv |
AT mathieulevesque treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT laiaandreuhayles treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT williamkolbysmith treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT aparkwilliams treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT martinalhobi treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT bradywallred treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale AT neilpederson treeringisotopescaptureinterannualvegetationproductivitydynamicsatthebiomescale |
_version_ |
1718390947173105664 |