Back to the fundamentals: a reply to Basener and Sanford 2018

IF 2.2 4区 数学 Q2 BIOLOGY
Zachary B. Hancock, Daniel Stern Cardinale
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引用次数: 0

Abstract

Fisher’s fundamental theorem of natural selection has haunted theoretical population genetic literature since it was proposed in 1930, leading to numerous interpretations. Most of the confusion stemmed from Fisher’s own obscure presentation. By the 1970s, a clearer view of Fisher’s theorem had been achieved and it was found that, regardless of its utility or significance, it represents a general theorem of evolutionary biology. Basener and Sanford (J Math Biol 76:1589–1622, 2018) writing in JOMB, however, paint a different picture of the fundamental theorem as one hindered by its assumptions and incomplete due to its failure to explicitly incorporate mutational effects. They argue that Fisher saw his theorem as a “mathematical proof of Darwinian evolution”. In this reply, we show that, contrary to Basener and Sanford, Fisher’s theorem is a general theorem that applies to any evolving population, and that, far from their assertion that it needed to be expanded, the theorem already implicitly incorporates ancestor–descendant variation. We also show that their numerical simulations produce unrealistic results. Lastly, we argue that Basener and Sanford’s motivations were in undermining not merely Fisher’s theorem, but the concept of universal common descent itself.

回归基本面:2018 年对 Basener 和 Sanford 的答复
费雪的自然选择基本定理自 1930 年提出以来,一直困扰着群体遗传学理论文献,导致了无数种解释。大多数混乱都源于费雪本人晦涩难懂的表述。到了 20 世纪 70 年代,人们对费雪定理有了更清晰的认识,发现无论其实用性或意义如何,它都代表了进化生物学的一般定理。然而,Basener 和 Sanford(J Math Biol 76:1589-1622,2018 年)在《进化生物学杂志》(JOMB)上的文章却对这一基本定理描绘了一幅不同的图景,认为它受到假设的阻碍,而且由于未能明确纳入突变效应而不完整。他们认为,费雪将自己的定理视为 "达尔文进化论的数学证明"。在这篇答复中,我们表明,与巴斯纳和桑福德相反,费雪定理是一个适用于任何进化种群的一般定理,而且,与他们认为需要扩展的说法相去甚远,该定理已经隐含地包含了祖先-后代变异。我们还证明,他们的数值模拟产生了不切实际的结果。最后,我们认为巴塞纳和桑福德的动机不仅在于破坏费雪定理,而且在于破坏普遍共同世系的概念本身。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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