
Impacts of seismic activity and climatic change on Chinese history in the recent millennium
FAN Jiawei, JIANG Hanchao, XU Hongyan, ZHANG Wei
Journal of Geographical Sciences ›› 2022, Vol. 32 ›› Issue (11) : 2328-2348.
Impacts of seismic activity and climatic change on Chinese history in the recent millennium
General history of disasters in China suggests that China has frequently experienced two major natural disasters in its long history, one is from catastrophic earthquake events, and the other is from extreme climatic events, due to its unique active tectonic environment and climatic complexity. Although these two major natural disasters have caused great damage to human society, it remains unclear whether and how they affect Chinese dynasty alternation on decadal (emperor) timescales. Based on detailed comparisons between abrupt climatic changes, catastrophic seismic activities, and the history of Chinese dynasty alternation from 1000-2000 AD, we conclude that on decadal timescales, extreme drought (and/or flood) events could indeed significantly reduce agricultural production, cause severe food shortages and famine, and result in increases in population exile, rising food prices and inflation, and insufficient supplies for military defense, which could exceed social resilience and eventually lead to financial risks and social upheavals of the dynasties. In addition, catastrophic seismic events in the densely populated, agricultural areas of China, including the 1303 surface wave magnitude (Ms) 8.0 Hongtong earthquake, the 1556 Ms 8.25 Huaxian earthquake and the 1920 Ms 8.5 Haiyuan earthquake, caused more than 200,000 casualties and millions of victims to live in exile which was almost equivalent to the order of magnitude of those extreme climatic events-induced refugees. The secondary geological hazards related to the earthquakes (e.g., extensive landslides and soil erosion), which could last for decades, caused more casualties and reduced food production. Furthermore, great plague spread caused by the casualties could significantly increase psychological panic among the survivors, resulting in social instability. Therefore, catastrophic seismic events could also accelerate the collapse of the dynasties (e.g., the Ming dynasty) without immediate mitigation measures. This study indicates that catastrophic seismic activities, as well as extreme climatic events, could have great effects on the social structures and thus on the Chinese dynasty alternation on decadal timescales, which highlights the far-reaching implications of geological hazard research.
catastrophic seismic activity / extreme climatic event / agricultural production / social stability / Chinese dynasty alternation {{custom_keyword}} /
Figure 1 The climatic and seismic history in China from 1000-2000 AD. Chinese dynasty alternation is plotted against the (a) temperature anomaly based on a composite series of temperature variations (Ge et al., 2013), (b-h) wet/dry climatic conditions inferred from proxy indices (b: Chen et al., 2010; f: Tan et al., 2018; g: Chu et al., 2002; h: Selvaraj et al., 2012) and historical records (c: Chu et al., 2009 and references therein; d and e: Man, 2009), and (i) historical Ms ≥ 7.0 earthquakes in China from 1000-2000 AD (CEA, 1999a, 1999b). Purple data points in (d) and orange data points in (e) are the ~10-yr average δ18O values (‰, VPDB) of stalagmites from Qujia Cave in North China and Xiniu Cave in central China, respectively (Zhao et al., 2021). Red lines in (i) indicate earthquake casualties ≥ 10,000. |
Figure 2 Sketch maps of climatic characteristics in China during the two typical periods. (a) Medieval Warm Period (MWP), and (b) Little Ice Age (LIA). Climatic characteristics are compiled with a sketch map of the provincial-level administrative divisions of China (source data are from |
Figure 3 Tectonic background and major earthquake events in China from 1000-2000 AD. Holocene active faults in China and its adjacent area, and distribution of historical Ms ≥ 7.0 earthquakes are compiled with a sketch map of the five active-tectonic provinces of China (Xu and Deng, 1996). N. Song, Northern Song; S. Song, Southern Song; XTP, Xinjiang tectonic province; QTTP, Qinghai-Tibetan tectonic province; NECTP, Northeast China tectonic province; NCTP, North China tectonic province; SECTP, Southeast China tectonic province. Fault data were provided by the Active Fault Survey Data Centre at the Institute of Geology, China Earthquake Administration (Xu et al., 2016). Earthquake data are from China Earthquake Administration (1999a, 1999b). |
Table S1 Historical Ms ≥ 7.0 earthquakes in China from 1000-2000 AD |
No. | Dynasty (Capital) (Duration) | Datea (AD) | Magnitude (Ms) | Epicenter (Location) | Maximum intensity (MMI) | Death toll | |
---|---|---|---|---|---|---|---|
1 | Northern Song (Kaifeng) (960-1127) | 1038/01/15 | 7.25 | 38.4°N, 112.9°E (Dingxiang, Shanxi) | X | NA | |
2 | 1125/09/06 | 7.0 | 36.1°N, 103.7°E (Lanzhou, Gansu) | IX | NA | ||
3 | Southern Song (Hangzhou) (1127-1276) | 1216/03/24 | 7.0 | 28.4°N, 103.8°E (Leibo, Sichuan) | IX | NA | |
4 | Yuan (Beijing) (1271-1368) | 1303/09/25 | 8.0 | 36.3°N, 111.7°E (Hongtong, Shanxi) | XI | 270,000 + | |
5 | 1352/04/26 | 7.0 | 35.6°N, 105.3°E (Huining, Gansu) | NA | NA | ||
6 | Ming (Beijing) (1368-1644) | 1411/10/08 | 8.0 | 30.1°N, 90.5°E (Dangxiong, Xizang) | X-XI | NA | |
7 | 1500/01/13 | 7.0 | 24.9°N, 103.1°E (Yiliang, Yunnan) | IX | NA | ||
8 | 1501/01/29 | 7.0 | 34.8°N, 110.1°E (Chaoyi, Shaanxi) | IX | 170 + | ||
9 | 1515/06/27 | 7.75 | 36.7°N, 100.7°E (Yongsheng, Yunnan) | X | Thousands | ||
10 | 1536/03/29 | 7.5 | 28.1°N, 102.2°E (Xichang, Sichuan) | X | NA | ||
11 | 1548/09/22 | 7.0 | 38.0°N, 121.0°E (Bohai Sea) | NA | NA | ||
12 | 1556/02/02 | 8.25 | 34.5°N, 109.7°E (Huaxian, Shaanxi) | XI | ~830,000 | ||
13 | 1561/08/04 | 7.25 | 37.5°N, 106.2°E (Zhongwei, Ningxia) | IX-X | NA | ||
14 | 1588/08/09 | 7.0 | 24.0°N, 102.8°E (Jianshui, Yunnan) | IX | NA | ||
15 | 1597/10/06 | 7.0 | 38.5°N, 120.0°E (Bohai Sea) | NA | NA | ||
16 | 1600/09/29 | 7.0 | 23.5°N, 117.2°E (Nan’ao, Guangdong) | IX | 6 | ||
17 | 1604/12/29 | 8.0 | 25.0°N, 119.5°E (Quanzhou offshore) | NA | NA | ||
18 | 1605/07/13 | 7.0 | 19.9°N, 110.5°E (Qiongshan, Hainan) | X | 1200 + | ||
19 | 1609/07/12 | 7.25 | 39.2°N, 99.0°E (Jiuquan, Gansu) | X | 840 + | ||
20 | 1622/10/25 | 7.0 | 36.5°N, 106.3°E (Guyuan, Ningxia) | IX-X | 12,000 + | ||
21 | 1626/06/28 | 7.0 | 39.4°N, 114.2°E (Lingqiu, Shanxi) | IX | NA | ||
22 | Qing (Beijing) (1644-1911) | 1652/07/13 | 7.0 | 25.5°N, 100.6°E (Midu, Yunnan) | IX + | 3000 + | |
23 | 1654/07/21 | 8.0 | 34.3°N, 105.5°E (Tianshui, Gansu) | XI | 31,000 + | ||
24 | 1642-1654 | 7.0 | 30.8°N, 95.6°E (Luolong, Xizang) | IX | NA | ||
25 | 1668/07/25 | 8.5 | 34.8°N, 118.5°E (Tancheng, Shandong) | XI | 10,200 + | ||
26 | 1679/09/02 | 8.0 | 40.0°N, 117.0°E (Sanhe, Hebei) | XI | 12,677 + | ||
27 | 1683/11/22 | 7.0 | 38.7°N, 112.7°E (Yuanping, Shanxi) | IX | NA | ||
28 | 1695/05/18 | 7.75 | 36.0°N, 110.5°E (Linfen, Shanxi) | X | 52,600 + | ||
29 | 1709/10/14 | 7.5 | 37.4°N, 105.3°E (Zhongwei, Ningxia) | IX-X | 2000 + | ||
30 | 1713/09/04 | 7.0 | 32.0°N, 103.7°E (Maoxian, Sichuan) | IX-X | NA | ||
31 | 1718/06/19 | 7.5 | 35.0°N, 105.3°E (Tongwei, Gansu) | X | 40,000 + | ||
32 | 1725/08/01 | 7.0 | 30.0°N, 101.9°E (Kangding, Sichuan) | IX | NA | ||
33 | 1733/08/02 | 7.75 | 26.3°N, 103.1°E (Dongchuan, Yunnan) | X | NA | ||
34 | 1739/01/03 | 8.0 | 38.8°N, 106.5°E (Pingluo, Ningxia) | X + | 1000 + | ||
35 | 1786/06/01 | 7.25 | 29.9°N, 102.0°E (Kangding, Sichuan) | X | NA | ||
36 | Qing (Beijing) (1644-1911) | 1786/06/10 | 7.0 | 29.4°N, 102.2°E (Luding, Sichuan) | NA | NA | |
37 | 1789/06/07 | 7.0 | 31.0°N, 102.9°E (Huaning, Yunnan) | IX + | NA | ||
38 | 1792/08/02 | 7.0 | 23.6°N, 120.6°E (Jiayi, Taiwan) | IX | 100 + | ||
39 | 1799/08/27 | 7.0 | 23.8°N, 102.4°E (Shiping, Yunnan) | IX | NA | ||
40 | 1806/06/11 | 7.5 | 28.2°N, 91.8°E (Cuona, Xizang) | X | NA | ||
41 | 1812/03/08 | 8.0 | 43.7°N, 83.5°E (Nilek, Xinjiang) | XI | 58 | ||
42 | 1816/12/08 | 7.5 | 31.4°N, 100.7°E (Luhuo, Sichuan) | X | 2854 | ||
43 | 1830/06/12 | 7.5 | 36.4°N, 114.3°E (Cixian, Hebei) | X | NA | ||
44 | 1833/08/26 | 8.0 | 28.3°N, 85.5°E (Nielamu, Xizang) | X | NA | ||
45 | 1833/09/06 | 8.0 | 25.0°N, 103.0°E (Songming, Yunnan) | X | 6700 + | ||
46 | 1842/06/11 | 8.0 | 43.5°N, 93.1°E (Balikun, Xinjiang) | X | NA | ||
47 | 1846/08/04 | 7.0 | 33.5°N, 122.0°E (Yellow Sea) | NA | NA | ||
48 | 1850/09/12 | 7.5 | 27.7°N, 102.4°E (Xichang, Sichuan) | X | 20,652 + | ||
49 | 1867/12/18 | 7.0 | 25.3°N, 121.8°E (Jilong, Taiwan) | NA | NA | ||
50 | 1868/01/04 | 7.25 | 30.0°N, 99.1°E (Batang, Sichuan) | X | 1000 + | ||
51 | 1871/06/NA | 7.5 | 28.0°N, 91.5°E (Cuona, Xizang) | X | NA | ||
52 | 1879/07/01 | 8.0 | 33.2°N, 104.7°E (Wudu, Gansu) | XI | 9881 | ||
53 | 1883/10/NA | 7.0 | 30.2°N, 81.2°E (Pulan, Xizang) | IX | NA | ||
54 | 1887/12/16 | 7.0 | 23.7°N, 102.5°E (Shiping, Yunnan) | IX | 2000 + | ||
55 | 1888/06/13 | 7.5 | 38.5°N, 119.0°E (Bohai Sea) | NA | NA | ||
56 | 1893/08/29 | 7.0 | 30.6°N, 101.5°E (Daofu, Sichuan) | IX | 326 | ||
57 | 1895/07/05 | 7.0 | 37.7°N, 75.1°E (Tashkurgan, Xinjiang) | IX | NA | ||
58 | 1896/03/NA | 7.0 | 32.5°N, 98.0°E (Shiqu, Sichuan) | IX | NA | ||
59 | 1902/08/22 | 8.25 | 39.9°N, 76.2°E (Atushi, Xinjiang) | X | ~ 1420 | ||
60 | 1902/11/21 | 7.25 | 23.0°N, 121.5°E (Taidong, Taiwan) | NA | NA | ||
61 | 1904/08/30 | 7.0 | 31.0°N, 101.1°E (Daofu, Sichuan) | IX | 400 + | ||
62 | 1906/12/23 | 7.75 | 43.5°N, 85.0°E (Shawan, Xinjiang) | X | 285 | ||
63 | 1908/08/20 | 7.0 | 32.0°N, 89.0°E (Qilin Lake, Xizang) | NA | NA | ||
64 | 1909/04/15 | 7.25 | 25.0°N, 121.5°E (Taibei, Taiwan) | NA | 9 | ||
65 | Republic of China (Nanjing) (1912-1949) | 1920/12/16 | 8.5 | 36.5°N, 105.7°E (Haiyuan, Ningxia) | XII | ~ 240,000 | |
66 | 1927/05/23 | 8.0 | 37.6°N, 102.6°E (Gulang, Gansu) | XI | 40,000 + | ||
67 | 1931/08/11 | 8.0 | 46.7°N, 89.9°E (Fuyun, Xinjiang) | X | 10,000 + | ||
68 | 1932/12/25 | 7.6 | 39.7°N, 97.0°E (Changmapu, Gansu) | X | ~ 70,000 | ||
69 | 1933/08/25 | 7.5 | 32.0°N, 103.7°E (Maoxian, Sichuan) | X | 20,000 + | ||
70 | 1935/04/20 | 7.1 | 24.2°N, 120.8°E (Miaoli, Taiwan) | NA | 3276 | ||
71 | The People’s Republic of China (Beijing) (1949-) | 1950/08/15 | 8.5 | 28.5°N, 96.0°E (Chayu, Xizang) | XII | ~ 4000 | |
72 | 1951/10/22 | 7.3 + 7.1 | 23.7°N, 121.2°E (Hualian, Taiwan) | NA | 113 | ||
73 | The People’s Republic of China (Beijing) (1949-) | 1955/04/14 | 7.5 | 30.0°N, 101.9°E (Kangding, Sichuan) | NA | ~ 100 | |
74 | 1955/04/15 | 7.0 | 39.9°N, 74.7°E (Wuqia, Xinjiang) | NA | 18 | ||
75 | 1966/03/22 | 7.2 | 37.5°N, 115.1°E (Xintai, Hebei) | X | 8064 - | ||
76 | 1970/01/05 | 7.7 | 24.0°N, 102.7°E (Tonghai, Yunnan) | X | 15,621 | ||
77 | 1975/02/04 | 7.3 | 40.7°N, 122.8°E (Haicheng, Liaoning) | IX | 1328 | ||
78 | 1976/07/28 | 7.8 | 39.4°N, 118.0°E (Tangshan, Hebei) | XI | ~ 242,000 | ||
79 | 1985/08/23 | 7.4 | 39.4°N, 75.4°E (Wuqia, Xinjiang) | NA | 67 | ||
80 | 1988/11/06 | 7.6 + 7.2 | 22.9°N, 100.1°E (Lancang, Yunnan) + 23.4°N, 99.6°E (Gengma, Yunnan) | IX-X | 743 | ||
81 |
NA: No data.a: Earthquake data are from historical catalogues (CEA, 1999a, 1999b). |
Table 1 Historical Ms ≥ 7.0 earthquakes with death toll ≥ 10,000 in China from 1000-2000 AD |
No. | Datea (AD) | Dynasty (Duration) | Magnitude (Ms) | Epicenter | Maximum intensity | Death tollb |
---|---|---|---|---|---|---|
1 | 1303/09/25 | Yuan (1271-1368) | 8.0 | 36.3°N, 111.7°E (Hongtong, Shanxi) | XI | 270,000 + |
2 | 1556/02/02 | Ming (1368-1644) | 8.25 | 34.5°N, 109.7°E (Huaxian, Shaanxi) | XI | ~830,000 |
3 | 1622/10/25 | 7.0 | 36.5°N, 106.3°E (Guyuan, Ningxia) | IX-X | 12,000 + | |
4 | 1654/07/21 | Qing (1644-1911) | 8.0 | 34.3°N, 105.5°E (Tianshui, Gansu) | XI | 31,000 + |
5 | 1668/07/25 | 8.5 | 34.8°N, 118.5°E (Tancheng, Shandong) | XI | 10,200 + | |
6 | 1679/09/02 | 8.0 | 40.0°N, 117.0°E (Sanhe, Hebei) | XI | 12,677 + | |
7 | 1695/05/18 | 7.75 | 36.0°N, 110.5°E (Linfen, Shanxi) | X | 52,600 + | |
8 | 1718/06/19 | 7.5 | 35.0°N, 105.3°E (Tongwei, Gansu) | X | 40,000 + | |
9 | 1850/09/12 | 7.5 | 27.7°N, 102.4°E (Xichang, Sichuan) | X | 20,652 + | |
10 | 1920/12/16 | Republic of China (RC 1912-1949) | 8.5 | 36.5°N, 105.7°E (Haiyuan, Ningxia) | XII | ~240,000 |
11 | 1927/05/23 | 8.0 | 37.6°N, 102.6°E (Gulang, Gansu) | XI | 40,000 + | |
12 | 1931/08/11 | 8.0 | 46.7°N, 89.9°E (Fuyun, Xinjiang) | X | 10,000 + | |
13 | 1932/12/25 | 7.6 | 39.7°N, 97.0°E (Changmapu, Gansu) | X | ~70,000 | |
14 | 1933/08/25 | 7.5 | 32.0°N, 103.7°E (Maoxian, Sichuan) | X | 20,000 + | |
15 | 1970/01/05 | The People’s Republic of China (PRC 1949-) | 7.7 | 24.0°N, 102.7°E (Tonghai, Yunnan) | X | 15,621 |
16 | 1976/07/28 | 7.8 | 39.4°N, 118.0°E (Tangshan, Hebei) | XI | ~242,000 |
a: Earthquake data are from historical catalogues (CEA, 1999a, 1999b).b: “+” means “more than”. |
Figure 4 Distributions of major earthquake disasters in China from 1000-2000 AD. (a) Distribution of historical Ms ≥ 7.0 earthquakes with death toll ≥ 10,000 in different dynasties of China from 1000-2000 AD. Numbers 1-4 in blue circles represent the four earthquake disasters that occurred in the period of Kangxi emperor. (b) Seismic intensity maps of the 1303 Ms 8.0 Hongtong earthquake (United Group, 2003), the 1556 Ms 8.25 Huaxian earthquake (Yuan and Feng, 2010) and the 1920 Ms 8.5 Haiyuan earthquake (LIS et al., 1980). |
Figure S2 (a) The Anyi Pagoda in Shanxi Province was split from the top to the seventh floor in the 1556 Huaxian earthquake (Yuan and Feng, 2010). (b) The 61 stone statues of vassals were damaged by the 1556 Huaxian earthquake (Yuan and Feng, 2010). (c) The post-earthquake scenes of Haiyuan County (upper: EANHAR et al., 2010) and the living willow damaged by the 1920 Haiyuan earthquake (lower: Taken in September, 2021). |
Figure 5 Social response to extreme climatic events and catastrophic earthquakes in China from 1000-2000 AD. (a) Amount of collected grain on military farms, (b) average grain price in border regions, and (c) silver amount supplied to the border regions from 1400-1520 AD. Data in (a), (b) and (c) are from Han and Yang (2021). (d) Casualties caused by historical Ms ≥ 7.0 earthquakes in China from 1000-2000 AD. Available data are from China Earthquake Administration (CEA, 1999a, 1999b). Red dots represent earthquakes occurred in the densely populated, agricultural areas of China without effective mitigation measures. Blue dot represents earthquake occurred in the urban area with immediate mitigation measures. |
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[51] |
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[52] |
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[53] |
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[54] |
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[55] |
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[56] |
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[57] |
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[58] |
Northern East Asia was inhabited by modern humans as early as 40 thousand years ago (ka), as demonstrated by the Tianyuan individual. Using genome-wide data obtained from 25 individuals dated to 33.6-3.4 ka from the Amur region, we show that Tianyuan-related ancestry was widespread in northern East Asia before the Last Glacial Maximum (LGM). At the close of the LGM stadial, the earliest northern East Asian appeared in the Amur region, and this population is basal to ancient northern East Asians. Human populations in the Amur region have maintained genetic continuity from 14 ka, and these early inhabitants represent the closest East Asian source known for Ancient Paleo-Siberians. We also observed that EDAR V370A was likely to have been elevated to high frequency after the LGM, suggesting the possible timing for its selection. This study provides a deep look into the population dynamics of northern East Asia.Copyright © 2021 Elsevier Inc. All rights reserved.
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[59] |
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[60] |
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[61] |
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[62] |
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[63] |
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[64] |
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[65] |
The India-Asia collision has formed the highest mountains on Earth and is thought to account for extensive intraplate deformation in Asia. The prevailing explanation considers the role of the Pacific and Sunda subduction zones as passive during deformation. Here we test the hypothesis that subduction played an active role and present geodynamic experiments of continental deformation that model Indian indentation and active subduction rollback. We show that the synchronous activity and interaction of the collision zone and subduction zones explain Asian deformation, and demonstrate that east-west extension in Tibet, eastward continental extrusion and Asian backarc basin formation are controlled by large-scale Pacific and Sunda slab rollback. The models require 1740 ± 300 km of Indian indentation such that backarc basins form and central East Asian extension conforms estimates. Indentation and rollback produce ~260-360 km of eastward extrusion and large-scale clockwise upper mantle circulation from Tibet towards East Asia and back to India.
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[66] |
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[67] |
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[68] |
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[69] |
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[70] |
A strong earthquake, measuring 7.6 on the Richter scale, hit northern Pakistan on 8 October 2005, causing massive destruction, including an official death toll of 73,276. Four cross-sectional surveys were performed in late 2005 to assess mortality before the event, on the day, and subsequently. Two surveys were community-based and two were situated in camps for internally displaced persons. Crude mortality rates were low in the 3.5 months preceding the earthquake (less than 0.1 deaths per 10,000 per day) and slightly higher in the six-to-eight weeks after the earthquake (ranging from 0.10-0.43 per 10,000 per day). On 8 October 2005, approximately two per cent of the population in one community survey died and around five per cent in the other three surveys. Children less than five years and adults more than or equal to 50 years tended to have a higher risk of mortality on the day of the disaster. These results corroborate the high mortality caused by the earthquake.
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[71] |
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[72] |
Understanding climatic effects on cropland water use efficiency at different elevations is imperative for managing agricultural water and production in response to ongoing climate change in climate-sensitive areas with complex topography, such as southwestern China. We investigated climatic effects on cropland water use efficiency in southwestern China at each 100-m elevation bin during 2001-2017. The maximum water use efficiency was 1.71 gC kg-1 H2O for the 1900-1999 m elevation bin under the growing season temperature and precipitation of 14.58±0.32°C and 965.40±136.45 mm, respectively. The water use efficiency slopes were dominated by the evapotranspiration slopes at elevations below 1999 m but were controlled by the gross primary productivity slopes at elevations above 2000 m. This difference was caused by the substantial responses of evaporation to climate change at lower elevations and the increased climatic sensitivity of gross primary productivity at higher elevations. In comparison to those at other elevations, croplands at lower elevations were more vulnerable to extreme drought because of the dominant role fluctuating evapotranspiration played in water use efficiency. The findings will improve cropland water management in the study area. {{custom_citation.content}}
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[73] |
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[74] |
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[75] |
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[76] |
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[77] |
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[78] |
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[79] |
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[80] |
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[81] |
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[82] |
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[83] |
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[84] |
<p id="C3">The relationship between grain crop harvest and climate change (temperature and precipitation) has been a major topic in the research on social impact of climate change in the past. With 5099 records on poor and bumper autumn harvests kept in historical chorography, annual harvest grade at county scale is quantified using semantic differential method, and the poor/bumper autumn harvest index series in North China from 1739 to 1911 is reconstructed. The variable characteristics of autumn harvest and its relationship with climate change are analyzed, and the reliability and applicability of historical harvest records from chorography are discussed by comparing them with those of the records from official documents in the Qing Dynasty. Results show that, first, the poor harvest records from chorography are more reliable than the bumper ones, and the poor harvest index series can reflect the fluctuation of overall autumn harvest to some extent. At the centennial scale, the autumn harvest markedly turned worse in the 19th century than in the 18th century. Second, the poor harvest index series are significantly and negatively correlated with temperature change at 10- and 5-year scales. Therefore, the poor harvest is sensitive to temperature decline. At an annual scale, the poor harvest is also significantly and negatively correlated with precipitation change, and the correlation coefficient between the poor harvest and drought index is up to 0.71 (<i>p </i>< 0.001). That is, drought is a larger threat to crop production than flood in North China. Third, compared with the harvest records kept in official documents that are reported to the government by local officials, the records from chorography have some advantages in the reconstruction of historical harvest. The records on poor harvest from chorography are more reliable than those from official documents, thereby allowing the index series to describe extreme events of crop production drop exactly. The two historical data sources can be complementary to each other; however, direct interpolation without data rectification may increase the system errors. This study is expected to contribute to the method improvement in the usage of historical documents in reconstructing the social impacts of climate change and the deepening in scientific knowledge on the impact rules of climate change on the agricultural production in the past.</p>
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[85] |
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[86] |
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[87] |
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[88] |
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[89] |
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[90] |
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[91] |
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[92] |
The paper analyzed the spatial-temporal relationship between revolt and drought-flood, and influence of factors such as population, land tax and policy, in Shandong Province during the middle and late Qing Dynasty (1800-1911AD), in order to understand the regional adaptation to climate change. The results indicated that there was good spatial-temporal relationship between revolt and drought-flood. During 1800 to 1850, the relationship was the best, when climate change was the main factor that arose the revolt as an extreme and drastic response by peasants to the intolerable climate change in feudal society. During the 1850s-1870s, disasters occurred frequently, revolt broke out continually, and society contradiction became intensified. After then, the corresponding relationship between revolt and drought was not as better as before. It may be contributed to that Qing government's policy that abolished the ban of migration to Northeast China in 1861AD, which provided a new way to respond to the climate change for the people in Shandong Province and weakened the impact of climate change on revolt.
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[93] |
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[94] |
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[95] |
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[96] |
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[97] |
Droughts are the most frequent natural disaster in regions at the margins of the East Asian summer monsoon (EASM), which pose threats to agriculture, the economy, and human lives. However, the limitations of only approximately 60 years of meteorological observations hamper our understanding of the characteristics and mechanisms of local hydroclimate. Trees growing in the marginal region of the EASM are usually sensitive to moisture variations and have played important roles in past hydroclimatic reconstructions. Here, a 303-year tree-ring-width chronology of Pinus tabulaeformis from Mt. Lama, which is located in the junction of the Liaoning Province and Inner Mongolia, China, was used to reconstruct the May-August Palmer drought severity index (PDSI) in the marginal region of the EASM. The transfer function explains 48.0% (or 47.2% after adjusting for the loss of the degrees of freedom) of the variance over the calibration period from 1946 to 2012. A spatial correlation analysis demonstrates that our PDSI reconstruction can represent the drought variability on the northernmost margin of the EASM. The winter Asian polar vortex area index showed a delayed impact on the summer EASM precipitation in the following year. {{custom_citation.content}}
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[98] |
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[99] |
Although scientists have warned of possible social perils resulting from climate change, the impacts of long-term climate change on social unrest and population collapse have not been quantitatively investigated. In this study, high-resolution paleo-climatic data have been used to explore at a macroscale the effects of climate change on the outbreak of war and population decline in the preindustrial era. We show that long-term fluctuations of war frequency and population changes followed the cycles of temperature change. Further analyses show that cooling impeded agricultural production, which brought about a series of serious social problems, including price inflation, then successively war outbreak, famine, and population decline successively. The findings suggest that worldwide and synchronistic war-peace, population, and price cycles in recent centuries have been driven mainly by long-term climate change. The findings also imply that social mechanisms that might mitigate the impact of climate change were not significantly effective during the study period. Climate change may thus have played a more important role and imposed a wider ranging effect on human civilization than has so far been suggested. Findings of this research may lend an additional dimension to the classic concepts of Malthusianism and Darwinism.
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[100] |
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[101] |
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[102] |
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[103] |
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[104] |
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[105] |
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[106] |
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[107] |
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[108] |
As a key subfield in climatology, the study of climate changes is the research focus of physical geography in China. In this article, we review recent progress in such study, which focused on past climate changes and climate change impacts and adaptations in the context of present global warming. The highlights and results of the studies are summarized, especially on the following issues: reconstruction of past climate in China, analysis of the spatiotemporal patterns of climate changes and their impacts during historical times in China, characteristics of changes on climate regionalization in China under global warming since 1950, regional difference of impacts of recent global warming on natural ecosystems, water resources, and agriculture in China, and comprehensive climate change risk regionalization of China. These results provided a solid scientific basis for forming disciplinary development strategies and further studies of related issues in the field of physical geography in China. {{custom_citation.content}}
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[109] |
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[110] |
China Earthquake Administration (CEA), 1999a. Historical Strong Earthquake Catalog of China (2300 BC-1911 AD). Beijing: Earthquake Publishing House. (in Chinese)
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[111] |
China Earthquake Administration (CEA), 1999b. Recent Earthquake Catalog of China (1912-1990, Ms ≥ 4.7). Beijing: Chinese Sciences and Technology Press. (in Chinese)
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[112] |
Earthquake Agency of Ningxia Hui Autonomous Region (EANHAR), Haiyuan County Committee of the Communist Party of China, Haiyuan County People’s Government, 2010. Haiyuan Earthquake·1920. Yinchuan: Sunshine Press of the Yellow River Publishing & Media Group Company Limited. (in Chinese)
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[113] |
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We thank Prof. Jule Xiao from the Institute of Geology and Geophysics, Chinese Academy of Sciences (Beijing, China) and Prof. Xingqi Liu from the Capital Normal University (Beijing, China) for improving the English language of this manuscript.
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