Talamo, S., Friedrich, M., Adolphi, F. orcid.org/0000-0003-0014-8753 et al. (9 more authors) (Cover date: 1 December 2023) Atmospheric radiocarbon levels were highly variable during the last deglaciation. Communications Earth & Environment, 4. 268. ISSN 2662-4435
Abstract
Radiocarbon dating provides a key chronological framework for studying past environmental changes. Raw radiocarbon ages measured in samples must be converted to calendar ages using an appropriate calibration curve. Tree-ring datasets provide the gold-standard for developing a precise curve of atmospheric radiocarbon levels over long-time scales. Here, we reconstruct atmospheric radiocarbon levels using a millennium-long section of tree-ring chronology segments that extend into the last glacial period. The samples were obtained from subfossil larch trees recovered from clay quarries at Revine, Italy. Our reconstruction shows higher variations in the amplitude of atmospheric radiocarbon between 18,475 and 17,350 calendar years before the present than that detected in the IntCal20 calibration curve. Comparing the new tree-ring based reconstruction with Beryllium-10 fluxes derived from ice cores, we hypothesise that these variations are driven by solar variability. Our results demonstrate the unique value of sub-decadal radiocarbon sequences derived from glacial tree-ring chronologies.
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Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/ licenses/by/4.0/. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/X032906/1 NERC (Natural Environment Research Council) NE/X009815/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Aug 2023 10:26 |
Last Modified: | 10 Aug 2023 10:26 |
Published Version: | https://www.nature.com/articles/s43247-023-00929-9... |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1038/s43247-023-00929-9 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202296 |
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