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首页> 外文期刊>Acta Biotheoretica >Revisiting the Relation Between Species Diversity and Information Theory
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Revisiting the Relation Between Species Diversity and Information Theory

机译:考察物种多样性与信息论之间的关系

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The Shannon information function (H) has been extensively used in ecology as a statistic of species diversity. Yet, the use of Shannon diversity index has also been criticized, mainly because of its ambiguous ecological interpretation and because of its relatively great sensitivity to the relative abundances of species in the community. In my opinion, the major shortcoming of the traditional perspective (on the possible relation of species diversity with information theory) is that species need for an external receiver (the scientist or ecologist) to exist and transmit information. Because organisms are self-catalized replicating structures that can transmit genotypic information to offspring, it should be evident that any single species has two possible states or alternatives: to be or not to be. In other words, species have no need for an external receiver since they are their own receivers. Therefore, the amount of biological information (at the species scale) in a community with one only species would be og22~1 = 1 species, and not log21 = 0 bits as in the traditional perspective. Moreover, species diversity appears to be a monotonic increasing function of log22~s (or S) when all species are equally probable (S being species richness), and not a function of log2 S as in the traditional perspective. To avoid the noted shortcoming, we could use 2~H (instead of H) for calculating species diversity and species evenness (= 2~H/S). However, owing to the relatively great sensitivity of H to the relative abundances of species in the community, the value of species dominance (= 1 - 2~H/S) is unreasonably high when differences between dominant and subordinate species are considerable, thereby lowering the value of species evenness and diversity. This unsatisfactory behaviour is even more evident for Simpson index and related algorithms. I propose the use of other statistics for a better analysis of community structure, their relationship being: species evenness + species dominance = 1; species diversity x species uniformity = 1; and species diversity = species richness x species evenness.
机译:Shannon信息函数(H)已在生态学中广泛用作物种多样性的统计数据。然而,香农多样性指数的使用也受到批评,这主要是因为其对生态学的解释不明确以及对社区中物种相对丰富度的敏感性较高。我认为,传统观点的主要缺点(关于物种多样性与信息论的可能关系)在于,物种需要外部接收者(科学家或生态学家)来生存和传播信息。由于生物是可以自我归化的复制结构,可以将基因型信息传递给后代,因此很明显,任何一个物种都有两个可能的状态或替代状态:存在或不存在。换句话说,由于物种是它们自己的接收器,因此不需要外部接收器。因此,只有一个物种的群落中的生物信息量(在物种规模上)将为og22〜1 = 1种,而不是传统观点中的log21 = 0位。此外,当所有物种都具有同等概率(S是物种丰富度)时,物种多样性似乎是log22〜s(或S)的单调增加函数,而不是传统观点中的log2 S的函数。为了避免上述缺点,我们可以使用2〜H(而不是H)来计算物种多样性和物种均匀度(= 2〜H / S)。然而,由于H对群落中物种相对丰富度的敏感性相对较高,当优势物种和下级物种之间的差异相当大时,物种优势的价值(= 1-2〜H / S)过高。物种均匀性和多样性的价值。对于Simpson索引和相关算法,这种不满意的行为更加明显。我建议使用其他统计数据来更好地分析社区结构,它们之间的关系为:物种均匀度+物种优势度= 1;物种多样性x物种均匀度= 1;物种多样性=物种丰富度x物种均匀度。

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