Abstract Depositional and paleoenvironmental studies using organic geochemical proxies often present the temporal evolution of several compounds. Despite the importance of using several proxies to understand how the surrounding environment changed through time, this large amount of data usually hampers interpretations. In this scenario, the use of statistical tools for time series analysis can help simplify and interpret large data sets, even if they were not initially developed for molecular marker data. In this study, we show the benefits of using two different cluster analyses in order to: (i) group compounds with similar sources; and (ii) identify temporal zones. Cluster analysis using SAX (Symbolic Aggregate approXimation) representation groups together different proxies with similar sources (whether anthropogenic or natural, autochthonous or allochthonous), based on their temporal evolution. Temporal zones, on the other hand, can be identified by using a constrained cluster analysis, in which samples (sediment layers) are grouped according to the temporal variability of the organic compounds. These two approaches were successfully applied to organic proxy datasets from two sediment cores, retrieved from distinct environments and with distinct temporal recoveries. Based on these analyses, we were able to identify the probable source of compounds with multiple sources, and to show how the terrestrial and marine organic matter presented distinct patterns over time. These techniques do not replace the study of the temporal evolution of compounds individually but synthesize a large amount of information and may indicate which compounds of an assemblage yield the most robust information in environmental studies.

中文翻译：

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基于有机地球化学代理的时间序列聚类分析

摘要 使用有机地球化学代理进行的沉积和古环境研究通常会呈现几种化合物的时间演变。尽管使用多个代理来了解周围环境如何随时间变化很重要，但如此大量的数据通常会妨碍解释。在这种情况下，使用统计工具进行时间序列分析可以帮助简化和解释大型数据集，即使它们最初不是为分子标记数据开发的。在这项研究中，我们展示了使用两种不同的聚类分析的好处，以便：(i) 对来源相似的化合物进行分组；(ii) 识别时区。使用 SAX（符号聚合近似）表示的聚类分析将具有相似来源（无论是人为的还是自然的，本土或异地），基于它们的时间演变。另一方面，时间带可以通过使用约束聚类分析来识别，其中样本（沉积层）根据有机化合物的时间变化进行分组。这两种方法已成功应用于来自两个沉积岩芯的有机替代数据集，这些数据集是从不同的环境中检索到的，并且具有不同的时间恢复。基于这些分析，我们能够确定具有多种来源的化合物的可能来源，并展示陆地和海洋有机物质如何随着时间的推移呈现出不同的模式。