A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020. Bi, W., He, W., Zhou, Y., Ju, W., Liu, Y., Liu, Y., Zhang, X., Wei, X., & Cheng, N. Scientific Data, 9(1):213, December, 2022. ![A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020 [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Abstract 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.
@article{bi_global_2022,
title = {A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020},
volume = {9},
issn = {2052-4463},
url = {https://www.nature.com/articles/s41597-022-01309-2},
doi = {10.1038/s41597-022-01309-2},
abstract = {Abstract
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.},
language = {en},
number = {1},
urldate = {2022-11-21},
journal = {Scientific Data},
author = {Bi, Wenjun and He, Wei and Zhou, Yanlian and Ju, Weimin and Liu, Yibo and Liu, Yang and Zhang, Xiaoyu and Wei, Xiaonan and Cheng, Nuo},
month = dec,
year = {2022},
pages = {213},
}
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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.","language":"en","number":"1","urldate":"2022-11-21","journal":"Scientific Data","author":[{"propositions":[],"lastnames":["Bi"],"firstnames":["Wenjun"],"suffixes":[]},{"propositions":[],"lastnames":["He"],"firstnames":["Wei"],"suffixes":[]},{"propositions":[],"lastnames":["Zhou"],"firstnames":["Yanlian"],"suffixes":[]},{"propositions":[],"lastnames":["Ju"],"firstnames":["Weimin"],"suffixes":[]},{"propositions":[],"lastnames":["Liu"],"firstnames":["Yibo"],"suffixes":[]},{"propositions":[],"lastnames":["Liu"],"firstnames":["Yang"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Xiaoyu"],"suffixes":[]},{"propositions":[],"lastnames":["Wei"],"firstnames":["Xiaonan"],"suffixes":[]},{"propositions":[],"lastnames":["Cheng"],"firstnames":["Nuo"],"suffixes":[]}],"month":"December","year":"2022","pages":"213","bibtex":"@article{bi_global_2022,\n\ttitle = {A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020},\n\tvolume = {9},\n\tissn = {2052-4463},\n\turl = {https://www.nature.com/articles/s41597-022-01309-2},\n\tdoi = {10.1038/s41597-022-01309-2},\n\tabstract = {Abstract \n \n Distinguishing gross primary production of sunlit and shaded leaves (GPP \n sun \n and GPP \n shade \n ) 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 \n shade \n and GPP \n sun \n 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 \n sun \n , and GPP \n shade \n over 1992–2020 at 125.0 ± 3.8 (mean ± std) Pg C a \n −1 \n , 50.5 ± 1.2 Pg C a \n −1 \n , and 74.5 ± 2.6 Pg C a \n −1 \n , 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 \n sun \n and GPP \n shade \n ) for CRO is distinctively greatest, and that for DBF (deciduous broadleaf forest) is relatively large and GPP \n shade \n overwhelmingly outweighs GPP \n sun \n . This new dataset advances our in-depth understanding of large-scale carbon cycle processes and dynamics.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-21},\n\tjournal = {Scientific Data},\n\tauthor = {Bi, Wenjun and He, Wei and Zhou, Yanlian and Ju, Weimin and Liu, Yibo and Liu, Yang and Zhang, Xiaoyu and Wei, Xiaonan and Cheng, Nuo},\n\tmonth = dec,\n\tyear = {2022},\n\tpages = {213},\n}\n\n\n\n","author_short":["Bi, W.","He, W.","Zhou, Y.","Ju, W.","Liu, Y.","Liu, Y.","Zhang, X.","Wei, X.","Cheng, N."],"key":"bi_global_2022","id":"bi_global_2022","bibbaseid":"bi-he-zhou-ju-liu-liu-zhang-wei-etal-aglobal005datasetforgrossprimaryproductionofsunlitandshadedvegetationcanopiesfrom1992to2020-2022","role":"author","urls":{"Paper":"https://www.nature.com/articles/s41597-022-01309-2"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/zotero/tereno","dataSources":["cq3J5xX6zmBvc2TQC"],"keywords":[],"search_terms":["global","dataset","gross","primary","production","sunlit","shaded","vegetation","canopies","1992","2020","bi","he","zhou","ju","liu","liu","zhang","wei","cheng"],"title":"A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020","year":2022}