Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4777-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4777-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
28 Oct 2022
Data description paper |
| 28 Oct 2022
| 28 Oct 2022
Holocene spatiotemporal millet agricultural patterns in northern China: a dataset of archaeobotanical macroremains
Key Laboratory of Cenozoic Geology and Environment, Institute of
Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Houyuan Lu
Key Laboratory of Cenozoic Geology and Environment, Institute of
Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Innovation Academy for Earth Science, Chinese Academy of Sciences,
Beijing, 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
Jianping Zhang
Key Laboratory of Cenozoic Geology and Environment, Institute of
Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Innovation Academy for Earth Science, Chinese Academy of Sciences,
Beijing, 100029, China
Can Wang
School of History and Culture, Shandong University, Jinan, 250100,
China
Related authors
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Yunsen Lai, Shaoda Li, Yuehong Shi, Xinrui Luo, Liang Liu, Peng Yu, Guo Chen, Longxi Cao, Chunju Cai, Jian Sun, Shaohui Chen, Houyuan Lu, Xuanlong Ma, and Xiaolu Tang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-411, https://doi.org/10.5194/essd-2021-411, 2021
Manuscript not accepted for further review
Short summary
Short summary
Topsoil (0–5 cm) carbon isotopes (δ13C) was predicted using Random Forest by the published observations and gridded environmental variables across the Tibetan Plateau (TP). Soil β values were also calculated across the TP. Results showed that spatially topsoil δ13C and β varied greatly across the TP. The developed topsoil δ13C and β dataset provide an independent data-driven benchmark for biogeochemical cycling models to study SOC turnover under ongoing climate change.
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Short summary
Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic and Bronze ages in northern China. Temporally, millet agriculture underwent a dramatic transition from low-yield broomcorn to high-yield foxtail millet around 6000 cal. a BP under the influence of climate and population. Spatially, millet agriculture spread westward and northward from the mid-lower Yellow River (MLY) to the agro-pastoral ecotone (APE) around 6000 cal. a BP and diversified afterwards.
Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic...
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