We discuss a simple methodology to enable a statistical comparison of human population with the vegetation of North America over the past 13,000 years. Nonparametric kernel methods are applied for temporal and spatial smoothing of point data obtained from the Neotoma Paleoecology Database and the Canadian Archaeological Radiocarbon Database, which results in sequences of maps showing the development of population and different plant taxa during the Holocene. The estimation of smooth spatial and spatio‐temporal cross‐correlation functions is proposed in order to detect relationships between population and vegetation in fixed time intervals. Furthermore, the effects of varying environment on demographic changes as well as potential impacts of populations on plant taxa over time are analyzed. Pointwise confidence bands for cross‐correlation functions are computed and a robustness analysis is performed to assess the significance of obtained results. Considering the example of oak, an interpretation of our results for eastern North America shows the value of this methodology.

中文翻译：

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北美史前人口与植被的时空相关性估算

我们讨论了一种简单的方法，可以对过去13,000年间人口与北美植被的统计进行比较。非参数核方法被应用于从Neotoma古生态数据库和加拿大考古放射性碳数据库获得的点数据的时间和空间平滑，这导致了一系列地图，显示了全新世期间种群和不同植物分类的发展。为了检测固定时间间隔内人口与植被之间的关系，提出了平滑的空间和时空互相关函数的估计。此外，分析了环境变化对人口变化的影响以及随着时间推移人口对植物分类群的潜在影响。计算互相关函数的逐点置信带，并进行鲁棒性分析以评估所获得结果的重要性。以橡木为例，对我们对北美东部地区结果的解释说明了这种方法的价值。