Reconstruction of climatic and environmental evolution in the Yinchuan Basin from MIS6 to MIS5 based on spore–pollen evidence
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摘要:
MIS6—MIS5是冰期向间冰期转变的典型时期，MIS5阶段的气候要素可以和现代暖期类比，对其演变过程进行研究可以更好地了解暖期气候变化过程和未来气候变化趋势。利用现代孢粉和气象数据以及季风边缘区银川盆地的地层孢粉和粒度指标，通过训练集选择、主控气候参数筛选、5种重建模型的交叉验证、区域对比、显著性检验和生态学解释后认为局部加权加权平均偏最小二乘法（LWWA-PLS）重建结果最为稳健。MIS6—MIS5阶段气候演变可分为6个阶段：157~131 ka时期，年平均降水量（Pann）为424.99 mm，7月平均温度（TJuly）为22.58 ℃，气候较湿冷，喜湿冷乔木类植被发育；131~119 ka时期，Pann为410.95 mm，TJuly为23.62 ℃，喜暖乔木、草本发育，气候转湿暖；119~111 ka时期，Pann为369.50 mm，TJuly为22.53 ℃，喜冷草本、乔木发育，气候干冷；111~98 ka时期，Pann为378.39 mm，TJuly为22.86 ℃，早期喜暖乔木含量高，后期喜冷乔木含量上升，气候整体干暖，温度先上升后下降；98~85 ka时期，Pann为278.24 mm，TJuly为22.01 ℃，喜冷乔木较发育，该阶段气候整体最为干冷；85~78 ka时期，Pann为364.21 mm，TJuly为23.45 ℃，乔木、草本均较发育，气候转湿暖。对重建的气候参数进行集合经验模态分解（EEMD），结果较好地响应于23 ka岁差周期，与北半球中、高纬地质记录对比后认为，受太阳辐射影响的北大西洋气候变动主要通过西风环流以及大洋传输带驱动东亚季风的变化，进而影响银川盆地的气候变化。
Abstract:MIS6 to MIS5 is a typical transition period from glacial to interglacial periods. The climate elements of MIS5 are similar to that of the current warm period, and studying its evolution process can better understand the climate change process of the current warm period and the future climate change trend. Based on modern spore–pollen and meteorological data, as well as stratigraphic spore–pollen and particle size indicators from the Yinchuan Basin in the monsoon margin area, the locally weighted average partial least squares method (LWWA-PLS) reconstruction results are considered to be the most robust after the selection of the training set, screening of the master climate parameters, cross-validation of the five reconstruction models, regional comparison, significance testing, and ecological interpretation. The climatic evolution from MIS6 to MIS5 can be divided into six stages. 157 to 131 ka, the climate was cold and humid, where wet and cold-loving arborvitae vegetation developed, with the average annual precipitation (Pann) being 424.99 mm and the average temperature in July (TJuly) 22.58 ℃. 131 to 119 ka, the climate turned wet and warm, and warm-loving trees and herbs developed; the Pann was 410.95 mm, and the TJuly was 23.62 ℃. 119 to 111 ka, the Pann was 369.50 mm, and the TJuly was 22.53 ℃; cold-loving herbs and trees developed in a cold and dry climate. 111 to 98 ka, the Pann is 378.39 mm, and the TJuly is 22.86 ℃; warm-loving trees account for a higher proportion in the early stage, and the number of cold-loving trees increased in the late stage; the climate was overall dry and warm, and the temperature increased first and then decreased. 98 to 85 ka, the Pann was 278.24, and the TJuly was 22.01 ℃; the overall climate was the driest and coldest, and cold-loving trees developed well. 85 to 78 ka, the Pann was 364.21 mm, and TJuly was 23.45 ℃; the climate turned warm and humid, and trees and herbs developed in this period. The reconstructed climate parameters' ensemble empirical mode decomposition (EEMD) results respond well to the 23 ka precessional cycle. Comparison with the mid- and high-latitude geologic record of the Northern Hemisphere suggests that solar radiation-influenced climatic variability in the North Atlantic primarily drives changes in the East Asian monsoon through the westerly wind circulation as well as the oceanic transport zone, which in turn influences climatic change in the Yinchuan Basin.
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表 1 LS01钻孔光释光测年结果（许可可等，2021）
Table 1. OSL ages and dating parameters of Borehole LS01(Xu et al., 2021)
编号 α系数 深度/m U/×10−6 Th/×10−6 K/% 含水率/% 剂量率/（Gy/ka） 等效剂量/Gy 年龄/ka LS01-OSL-1 0.04±0.02 15.3 2.71 14.38 2.17 25±5 3.78±0.21 300.64±11.84 79.58±5.42 LS01-OSL-2 0.04±0.02 26.5 1.95 11.24 1.84 29±5 2.91±0.16 296.12±11.32 101.72±6.67 LS01-OSL-3 0.04±0.02 41.7 1.90 11.33 1.72 28±5 2.35±0.07 262.22±2.11 111.58±3.49 LS01-OSL-4 0.04±0.02 60.2 2.55 10.00 1.75 20±5 2.61±0.09 325.65±1.61 124.91±4.17 LS01-OSL-5 0.04±0.02 75.4 1.83 7.71 1.74 29±5 2.12±0.07 301.41±1.32 142.17±4.60 LS01-OSL-6 0.04±0.02 102.8 2.17 4.92 2.13 20±5 2.93±0.15 445.38±43.82 151.85±16.81 
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表 2 气候参数选择结果
Table 2. Selection of climatic variables
气候
参数所有
参数移除
Tann移除
TJan移除
TJuly单气候变量解释度 解释度 贡献率% P Pann 2.68 2.61 2.68 2.60 1.10 55.50 0.002 TJuly 104.15 3.08 4.66 — 0.50 24.50 0.002 Tann 260.41 — 7.70 5.08 0.30 14.00 0.002 TJan 69.49 1.35 — 6.99 0.10 6.00 0.002
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表 3 不同重建模型交叉验证结果
Table 3. Cross-validation results of different reconstruction models
重建模型 Pann/mm TJuly/℃ 重建模型 Pann/mm TJuly/℃ RMSEP R2 RMSEP R2 RMSEP R2 RMSEP R2 MAT-500 km 75.46 0.77 1.96 0.77 LWWA(classical)-k=30 71.88 0.79 3.01 0.79 MAT-1000 km 95.71 0.89 2.68 0.82 LWWA(inverse)-k=40 66.19 0.82 2.61 0.84 MAT-1500 km 136.06 0.89 2.71 0.83 LWWA(classical)-k=40 74.44 0.78 3.14 0.78 WA(inverse)-500 km 94.61 0.61 2.51 0.62 LWWA(inverse)-k=50 67.17 0.81 2.63 0.84 WA(classical)-500 km 119.06 0.63 3.18 0.62 LWWA(classical)-k=50 76.21 0.78 3.23 0.77 WA(monotonic)-500 km 91.20 0.65 2.46 0.63 LWWA(inverse)-k=60 68.29 0.81 2.64 0.84 WA(expanded)-500 km 99.88 0.63 2.66 0.62 LWWA(classical)-k=60 78.64 0.77 3.32 0.77 WA(none)-500 km 114.62 0.63 2.97 0.62 LWWA(inverse)-k=70 68.85 0.80 2.69 0.83 WA(inverse)-1000 km 156.42 0.71 4.00 0.61 LWWA(classical)-k=70 78.60 0.78 3.45 0.75 WA(classical)-1000 km 184.77 0.71 5.11 0.61 LWWA(inverse)-k=80 69.74 0.80 2.71 0.83 WA(monotonic)-1000 km 151.50 0.73 3.78 0.65 LWWA(classical)-k=80 78.68 0.78 3.54 0.75 WA(expanded)-1000 km 162.79 0.71 4.23 0.61 LWWA(inverse)-k=90 70.48 0.79 2.74 0.83 WA(none)-1000 km 183.41 0.71 4.58 0.61 LWWA(classical)-k=90 79.86 0.77 3.66 0.73 WA(inverse)-1500 km 197.17 0.78 4.11 0.61 LWWA(inverse)-k=100 70.91 0.79 2.76 0.82 WA(classical)-1500 km 223.23 0.78 5.25 0.61 LWWA(classical)-k=100 80.19 0.77 3.73 0.73 WA(monotonic)-1500 km 193.36 0.78 3.91 0.64 LWW-PLS-k=20 58.89 0.86 1.67 0.85 WA(expanded)-1500 km 203.19 0.78 4.35 0.61 LWW-PLS-k=30 66.00 0.82 1.76 0.81 WA(none)-1500 km 231.71 0.78 4.67 0.61 LWW-PLS-k=40 66.22 0.82 1.78 0.81 WA-PLS(Comp5)-500 km 59.09 0.85 1.67 0.83 LWW-PLS-k=50 67.10 0.81 1.81 0.80 WA-PLS(Comp5)-1000 km 112.40 0.85 2.98 0.78 LWW-PLS-k=60 68.11 0.81 1.82 0.80 WA-PLS(Comp5)-1500 km 138.94 0.89 3.02 0.79 LWW-PLS-k=70 68.66 0.80 1.82 0.80 LWWA(inverse)-k=20 59.00 0.86 1.70 0.83 LWW-PLS-k=80 69.11 0.80 1.84 0.79 LWWA(classical)-k=20 68.29 0.81 2.86 0.81 LWW-PLS-k=90 70.21 0.79 1.86 0.79 LWWA(inverse)-k=30 66.22 0.82 2.59 0.84 LWW-PLS-k=100 70.60 0.79 1.89 0.78
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表 4 与其他地区重建模型交叉验证结果对比
Table 4. Comparison of cross-validation results with other regional reconstruction models
文献来源 研究区 年代 最优模型 重建参数 RMSEP R2 梁琛等，2020 青藏高原若尔盖地区 全新世 WA-PLS TJuly 2.04 ℃ 0.83 青藏高原若尔盖地区 全新世 WA-PLS TJuly 2.04 ℃ 0.81 青藏高原若尔盖地区 全新世 WA-PLS TJuly 1.91 ℃ 0.82 Zhao et al.，2021 青藏高原若尔盖地区 1.74 Ma以来 LWWA-PLS TJuly 3.06 ℃ 0.81 青藏高原若尔盖地区 1.74 Ma以来 LWWA-PLS Pann 158 mm 0.67 Lu et al.，2011 青藏高原沉措地区 全新世 LWWA TJuly 2.1 ℃ 0.78 青藏高原沉措地区 全新世 LWWA Pann 109 mm 0.89 陈建徽等，2018 黄土高原公海 14 ka以来 WA-PLS Pann 85.85 mm 0.84 黄土高原六盘山天池 6.2 ka以来 WA-PLS Pann 74.70 mm 0.87 Wen et al.，2013 内蒙古呼伦湖 全新世 WA-PLS Pann 53.9 mm 0.88 内蒙古呼伦湖 全新世 WA-PLS TJuly 1.46 ℃ 0.69 Xu et al.，2010 河南安阳 全新世 MAT Pann 79.00 mm 0.83 河南安阳 全新世 MAT TJuly 2.6 ℃ 0.52 河南安阳 全新世 WA-PLS Pann 70.00 mm 0.87 河南安阳 全新世 WA-PLS TJuly 2.3 ℃ 0.61 文中 银川盆地 MIS6—MIS5 LWWA-PLS Pann 58.89 mm 0.86 银川盆地 MIS6—MIS5 LWWA-PLS TJuly 1.67 ℃ 0.85 银川盆地 MIS6—MIS5 LWWA Pann 68.29 mm 0.81 银川盆地 MIS6—MIS5 LWWA TJuly 2.86 ℃ 0.81 银川盆地 MIS6—MIS5 WA-PLS Pann 59.09 mm 0.85 银川盆地 MIS6—MIS5 WA-PLS TJuly 1.67 ℃ 0.83 银川盆地 MIS6—MIS5 MAT Pann 75.46 mm 0.77 银川盆地 MIS6—MIS5 MAT TJuly 1.96 ℃ 0.77
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表 5 重建温度和降水量的IMF贡献率
Table 5. IMF (Intrinsic Mode Function) contribution rate of reconstructed temperature and precipitation
气候参数 特征 IMF1 IMF2 IMF3 IMF4 IMF5 TJuly 周期/ka 1.1 2.3 12 11 45 贡献率/% 0.2 0.3 55 43 1.5 排名 5 4 1 2 3 Pann 周期/ka 0.9 5 12 25 27 贡献率/% 0.1 0.2 55 42 2.7 排名 5 4 1 2 3
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