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A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020
Distinguishing gross primary production of sunlit and shaded leaves (GPP(sun) and GPP(shade)) is crucial for improving our understanding of the underlying mechanisms regulating long-term GPP variations. Here we produce a global 0.05°, 8-day dataset for GPP, GPP(shade) and GPP(sun) over 1992–2020 usi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110750/ https://www.ncbi.nlm.nih.gov/pubmed/35577806 http://dx.doi.org/10.1038/s41597-022-01309-2 |
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author | Bi, Wenjun He, Wei Zhou, Yanlian Ju, Weimin Liu, Yibo Liu, Yang Zhang, Xiaoyu Wei, Xiaonan Cheng, Nuo |
author_facet | Bi, Wenjun He, Wei Zhou, Yanlian Ju, Weimin Liu, Yibo Liu, Yang Zhang, Xiaoyu Wei, Xiaonan Cheng, Nuo |
author_sort | Bi, Wenjun |
collection | PubMed |
description | Distinguishing gross primary production of sunlit and shaded leaves (GPP(sun) and GPP(shade)) is crucial for improving our understanding of the underlying mechanisms regulating long-term GPP variations. Here we produce a global 0.05°, 8-day dataset for GPP, GPP(shade) and GPP(sun) over 1992–2020 using an updated two-leaf light use efficiency model (TL-LUE), which is driven by the GLOBMAP leaf area index, CRUJRA meteorology, and ESA-CCI land cover. Our products estimate the mean annual totals of global GPP, GPP(sun), and GPP(shade) over 1992–2020 at 125.0 ± 3.8 (mean ± std) Pg C a(−1), 50.5 ± 1.2 Pg C a(−1), and 74.5 ± 2.6 Pg C a(−1), respectively, in which EBF (evergreen broadleaf forest) and CRO (crops) contribute more than half of the totals. They show clear increasing trends over time, in which the trend of GPP (also GPP(sun) and GPP(shade)) for CRO is distinctively greatest, and that for DBF (deciduous broadleaf forest) is relatively large and GPP(shade) overwhelmingly outweighs GPP(sun). This new dataset advances our in-depth understanding of large-scale carbon cycle processes and dynamics. |
format | Online Article Text |
id | pubmed-9110750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91107502022-05-18 A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 Bi, Wenjun He, Wei Zhou, Yanlian Ju, Weimin Liu, Yibo Liu, Yang Zhang, Xiaoyu Wei, Xiaonan Cheng, Nuo Sci Data Data Descriptor Distinguishing gross primary production of sunlit and shaded leaves (GPP(sun) and GPP(shade)) is crucial for improving our understanding of the underlying mechanisms regulating long-term GPP variations. Here we produce a global 0.05°, 8-day dataset for GPP, GPP(shade) and GPP(sun) over 1992–2020 using an updated two-leaf light use efficiency model (TL-LUE), which is driven by the GLOBMAP leaf area index, CRUJRA meteorology, and ESA-CCI land cover. Our products estimate the mean annual totals of global GPP, GPP(sun), and GPP(shade) over 1992–2020 at 125.0 ± 3.8 (mean ± std) Pg C a(−1), 50.5 ± 1.2 Pg C a(−1), and 74.5 ± 2.6 Pg C a(−1), respectively, in which EBF (evergreen broadleaf forest) and CRO (crops) contribute more than half of the totals. They show clear increasing trends over time, in which the trend of GPP (also GPP(sun) and GPP(shade)) for CRO is distinctively greatest, and that for DBF (deciduous broadleaf forest) is relatively large and GPP(shade) overwhelmingly outweighs GPP(sun). This new dataset advances our in-depth understanding of large-scale carbon cycle processes and dynamics. Nature Publishing Group UK 2022-05-16 /pmc/articles/PMC9110750/ /pubmed/35577806 http://dx.doi.org/10.1038/s41597-022-01309-2 Text en © The Author(s) 2022 https://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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Bi, Wenjun He, Wei Zhou, Yanlian Ju, Weimin Liu, Yibo Liu, Yang Zhang, Xiaoyu Wei, Xiaonan Cheng, Nuo A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title | A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title_full | A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title_fullStr | A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title_full_unstemmed | A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title_short | A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
title_sort | global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110750/ https://www.ncbi.nlm.nih.gov/pubmed/35577806 http://dx.doi.org/10.1038/s41597-022-01309-2 |
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