A formation record of modern Nitraria tangutorum nebkhas on the Ordos Plateau of northern China based on optically stimulated luminescence dating

Quaternary Geochronology(2024)

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摘要
Nebkhas, as special biologically mediated aeolian landforms, play an important role in indicating regional aeolian activities and aeolian environmental changes. The Ordos Plateau is located in arid and semiarid regions of northern China that have a wide distribution of Nitraria tangutorum nebkhas. There are few chronological records of nebkha formation, so the history of the formation and evolution of nebkhas in the plateau is still unclear. In addition, the optically stimulated luminescence (OSL) dating method, which has been widely used in the dating of Holocene aeolian sediments, has not yet been applied to the dating of nebkha sediments in the Ordos Plateau. In this study, OSL methods were used to discuss the formation age and relevant aeolian activities of Nitraria tangutorum nebkhas in the Ordos Plateau. The results demonstrated that (1) the coarse-grained quartz OSL signals of nebkha sediments were insensitive and thus were inapplicable by the single aliquot regenerative (SAR) protocol. (2) The luminescence characteristics of the K-feldspar fraction and internal checks of the post-infrared infrared-stimulated (pIRIR) dating indicated that the pIR50IR170 protocol with 200 °C of preheating was applicable for De determinations of nebkha sediments. (3) The residual doses of the pIRIR170 signals ranging from 0.02 to 0.14 Gy should be considered when calculating De values. (4) Bayesian age-depth models were used for the Nitraria tangutorum nebkha sedimentary sequences. The formation of nebkhas occurred during a relatively dry climate period accompanied by strong aeolian activity. That ∼0.38 ka was the main growth period of Nitraria tangutorum nebkhas. This study is the first report of the formation age of nebkhas of more than one hundred years in the region.
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关键词
Nitraria tangutorum nebkhas,Luminescence dating,Ordos Plateau,Nebkha sediments,Bayesian age-depth model
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