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Mathematical bounds on Shannon entropy given the abundance of the ith most abundant taxon

机译:香农熵的数学界限,给定第 i 个最丰富的分类单元的丰度

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摘要

Abstract The measurement of diversity is a central component of studies in ecology and evolution, with broad uses spanning multiple biological scales. Studies of diversity conducted in population genetics and ecology make use of analogous concepts and even employ equivalent mathematical formulas. For the Shannon entropy statistic, recent developments in the mathematics of diversity in population genetics have produced mathematical constraints on the statistic in relation to the frequency of the most frequent allele. These results have characterized the ways in which standard measures depend on the highest-frequency class in a discrete probability distribution. Here, we extend mathematical constraints on the Shannon entropy in relation to entries in specific positions in a vector of species abundances, listed in decreasing order. We illustrate the new mathematical results using abundance data from examples involving coral reefs and sponge microbiomes. The new results update the understanding of the relationship of a standard measure to the abundance vectors from which it is calculated, potentially contributing to improved interpretation of numerical measurements of biodiversity.
机译:摘要 多样性的测量是生态学和进化研究的核心组成部分,其广泛应用跨越多个生物学尺度。在种群遗传学和生态学中进行的多样性研究利用了类似的概念,甚至使用了等效的数学公式。对于香农熵统计量,群体遗传学多样性数学的最新发展对统计量产生了与最常见等位基因频率相关的数学约束。这些结果表征了标准度量依赖于离散概率分布中最高频率类的方式。在这里,我们扩展了香农熵的数学约束,这些约束与物种丰度向量中特定位置的条目有关,按降序列出。我们使用涉及珊瑚礁和海绵微生物组的例子的丰度数据来说明新的数学结果。新的结果更新了对标准测量值与计算标准量关系的理解,可能有助于改进对生物多样性数值测量值的解释。

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