Abstract A total of 245 modern pollen samples available in the East Asian Pollen Database and our unpublished pollen data (n = 204 and 41, respectively) were compiled to determine the correlation between modern pollen rain and vegetation in the watershed regions along the upper and middle Yellow River (UMYR) using principle component analysis (PCA). Despite considerable geographical differences and an uneven spatial vegetation distribution, pollen assemblages could differentiate major vegetation and climate zones. The PCA result reveals a high correlation between pollen taxa and key environmental factors, suggesting the high potential of this database for quantitative climate reconstruction. After screening, 199 samples were finally used to quantitatively reconstruct climate parameters with three methods namely, the weighted averaging partial least squares (WA-PLS) method, locally weighed weighted averaging (LWWA) method, and modern analogue technique (MAT).The comparison of multiple reconstructions indicates that WA-PLS provides quite accurate climate reconstructions from limited pollen data, whereas LWWA and MAT appear more suitable for large pollen datasets associated with a broad geographic range. We also discovered that the selection of sub-divided watershed areas yielded significant reduction in prediction errors and, in turn, improved accuracy of the quantitative climate reconstruction. The statistical results indicate that the transfer functions are reliable for both climate variables and elevation that is controlled mainly by the lapse rate of the altitudinal temperature. The current study provides evidence that modern pollen data in the UMYR can be used as a reliable reference dataset for pollen-based quantitative climate reconstructions.

中文翻译：

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沿黄河中上游海拔梯度的现代花粉雨、植被和气候：定量环境重建的数值方法

摘要 收集了东亚花粉数据库中的 245 个现代花粉样本和我们未发表的花粉数据（分别为 n = 204 和 41），以确定现代花粉雨与沿上游和中部流域地区植被之间的相关性。黄河 (UMYR) 使用主成分分析 (PCA)。尽管存在相当大的地理差异和空间植被分布不均，但花粉组合可以区分主要植被和气候带。PCA 结果揭示了花粉类群与关键环境因素之间的高度相关性，表明该数据库在定量气候重建方面具有很高的潜力。经过筛选，最终使用199个样本，通过三种方法对气候参数进行了定量重构，加权平均偏最小二乘 (WA-PLS) 方法、局部加权加权平均 (LWWA) 方法和现代模拟技术 (MAT)。多次重建的比较表明 WA-PLS 从有限的花粉数据提供了相当准确的气候重建，而 LWWA 和 MAT 似乎更适合与广泛地理范围相关的大型花粉数据集。我们还发现，细分流域区域的选择显着减少了预测误差，进而提高了定量气候重建的准确性。统计结果表明，传递函数对于气候变量和主要受海拔温度递减率控制的海拔都是可靠的。