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Methodological Concerns For Analysis Of Phytolith Assemblages:does Count Size Matter?

机译:分析植石组合的方法论问题:计数大小是否重要?

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In quantitative phytolith analysis, chance error associated with insufficient counts can affect the robustness of the interpretation, whether it is vegetation reconstruction or taxonomic differentiation. It is therefore vital to choose a count size that will ensure statistically reliable results, while minimizing the time expended. Numerical statistical methods (bootstrapping) that have become available over the past few decades have made it possible to model even complex phytolith assemblages with relative ease. This study used bootstrapping as well as analytic statistical formulas to evaluate the influence of count size on vegetation reconstruction by means of two commonly used indices, D/P (tree cover index) and I_(ph) (aridity index). The analysis indicates that the count size needed to ensure statistical precision depends on the question as well as the observed assemblage composition. Importantly, it is the count of specimens relevant to a specific ratio or other index ("index-specific" count) that matters, whereas the total count is less important. Based on these results, some general guidelines for choice of count size and for the use of statistics in phytolith analysis are suggested.
机译:在定量植石分析中,与计数不足相关的偶然误差会影响解释的稳健性,无论是植被重建还是分类学区分。因此,至关重要的是选择一个计数大小,以确保统计结果可靠,同时最大程度地减少花费的时间。在过去的几十年中可用的数字统计方法(自举)使得相对复杂地对复杂的植石组合建模成为可能。这项研究使用自举法和分析统计公式,通过两个常用指标D / P(树木覆盖指数)和I_(ph)(干旱指数)来评估计数大小对植被重建的影响。分析表明,确保统计精度所需的计数大小取决于问题以及所观察到的组合物组成。重要的是,重要的是与特定比率或其他指标(“特定于指标”的计数)相关的标本计数,而总计数则不那么重要。基于这些结果,建议了一些关于计数大小选择和在植石分析中使用统计数据的通用指南。

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