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An Information-Theoretical Measure of Taxonomic Diversity

机译:分类学信息的信息理论测度

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Traditional diversity indices are computed from the abundances of species present and are insensitive to taxonomic differences between species. However, a community in which most species belong to the same genus is intuitively less diverse than another community with a similar number of species distributed more evenly between genera. In this paper, we propose an information-theoretical measure of taxonomic diversity that reflects both the abundances and taxonomic distinctness of the species. Unlike previous measures of taxonomic diversity, such as Rao's quadratic entropy, in this new measure the analyzed taxonomic properties are associated with the single species instead of species pairs.
机译:传统多样性指数是根据现有物种的丰富度计算得出的,并且对物种之间的分类差异不敏感。但是,从直觉上说,大多数物种属于同一属的社区,其多样性要比另一个物种相似数量的社区更均匀地分布在另一个社区中。在本文中,我们提出了一种分类理论的信息理论方法,该方法既可以反映物种的丰度,又可以反映物种的分类独特性。与以前的分类学多样性测度(例如Rao的二次熵)不同,在此新测度中,分析的分类学性质与单个物种而不是物种对相关。

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