2022
DOI: 10.1038/s41467-022-32506-7
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The Holocene temperature conundrum answered by mollusk records from East Asia

Abstract: Seasonal biases (the warm-season contribution) of Holocene mean annual temperature (MAT) reconstructions from geological records were proposed as a possible cause of the mismatch with climate simulated temperature. Here we analyze terrestrial mollusk assemblages that best reflect seasonal signals and provide quantitative MAT and four-season temperature records for northern China during the past 20,000 years. The MAT estimated from the seasonal temperatures of a four-season-mean based on mollusks shows a peak d… Show more

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Cited by 64 publications
(21 citation statements)
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“…As for the mean annual temperature, brGDGTs records from Gushantun and Hani peat in NE China (Zheng et al, 2017, 2018) show a cooling trend during Holocene (Figure 4e and f). In addition, the MAT records based on terrestrial mollusk assemblages from North China (Dong et al, 2022) and based on an extensive pollen dataset from the Northern Hemisphere (Zhang et al, 2022) (Figure 5d) suggested a trend of warming during the early-middle Holocene and cooling during the middle-late Holocene. The brGDGTs records from Gushantun and Hani peat contradicted the records based on mollusk and pollen probably because the brGDGTs records from NE China carried more summer-inferred temperature information rather than the MAT.…”
Section: Resultsmentioning
confidence: 99%
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“…As for the mean annual temperature, brGDGTs records from Gushantun and Hani peat in NE China (Zheng et al, 2017, 2018) show a cooling trend during Holocene (Figure 4e and f). In addition, the MAT records based on terrestrial mollusk assemblages from North China (Dong et al, 2022) and based on an extensive pollen dataset from the Northern Hemisphere (Zhang et al, 2022) (Figure 5d) suggested a trend of warming during the early-middle Holocene and cooling during the middle-late Holocene. The brGDGTs records from Gushantun and Hani peat contradicted the records based on mollusk and pollen probably because the brGDGTs records from NE China carried more summer-inferred temperature information rather than the MAT.…”
Section: Resultsmentioning
confidence: 99%
“…However, Pinus pollen percentages in NE China did not increase after ~2–3 cal ka BP, which is inconsistent with the atmospheric CO 2 that kept rising since ~7–6 cal ka BP (Bereiter et al, 2015) (Figure 5j). The MAT variability is the superposition of summer and winter temperature variability (Dong et al, 2022). Before ~7–6 cal ka BP, the annual insolation was changing very slowly at that time as the summer and winter insolation were following opposite trends (Laskar et al, 2004).…”
Section: Resultsmentioning
confidence: 99%
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“…These data were compared to regional climatic background information, that is, the mean annual temperatures reconstructed by mollusk records from the loess paleosol profile at Jingchuan, located at ca. 100 km north of Daye Lake (Figures 4c; Dong et al, 2022), together with the stalagmite records of Dongge and Haozhu caves, which are considered as the index of EASM (Figure 4d, Yuan et al, 2004;Zhang et al, 2018). Biofuel changes are also considered here indicated by the ratio of wood to herb burning from micro-charcoals (Figure 4f).…”
Section: Climate and Vegetation Influenced The Fire Activitymentioning
confidence: 99%
“…Figure 3. Comparison of climate indexes from the Chinese Loess Plateau and ML/MR ratio results: (a), (b) synthesized MCL/MCR ratios (SLR) of the five sites and synthesized herb pollen (SHP) across the Loess Plateau based on the LOWESS fitting (this study); (c) moisture reconstructed on the central (purple) and the western Chinese Loess Plateau (light blue) (Gao et al, 2019); (d) pollen-based annual precipitation (Pann) reconstructed from Gonghai Lake(Chen et al, 2015); (e), (f) mean annual temperature (MAT) reconstructed in Yaoxian and Jingchuan(Dong et al, 2022), where the red line represents the LOESS fitting; (g) the synthesized fire history across the Loess Plateau (this study); (h) the human influence index (HII) based on pollen data from Lake Tianchi on the Loess Plateau; (i) number of archeological sites on the Chinese Loess Plateau(Hosner et al, 2016). The green shaded areas and green hollow dots/triangles in (a) and (b) indicate 95% confidence intervals.…”
mentioning
confidence: 99%