Character mapping and cladogram comparison versus the requirement of total evidence: does it matter for polychaete systematics?

Q2 Agricultural and Biological Sciences
K. Fitzhugh
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引用次数: 14

Abstract

Fitzhugh, K. 2014. Character mapping and cladogram comparison versus the requirement of total evidence: does it matter for polychaete systematics? Memoirs of Museum Victoria 71: 67–78. The practice of partitioning data for the inferences of phylogenetic hypotheses has become a routine practice in biological systematics. Two popular approaches: (i) mapping ‘morphological’ characters onto ‘molecular’ phylogenies, and (ii) comparing ‘morphological’ and ‘molecular’ phylogenies, are examined in light of what is known as the requirement of total evidence. Inferences of phylogenetic hypotheses, indeed all taxa, occur by a type of non-deductive reasoning known as abduction. The intent of abduction is to offer at least tentative causal accounts that explain character data. The rational acceptance of abductively derived hypotheses is subject to conditions of the requirement of total evidence as a matter of the evidential support for those hypotheses. It is shown that both character mapping and comparisons of cladograms using partitioned datasets are procedures that severely reduce the credibility of phylogenetic hypotheses. This problem is alleviated by acknowledging the formal structure of the why-questions we ask in relation to character data, for which phylogenetic hypotheses serve as answers.
特征映射和枝状图比较与全部证据的要求:对多毛类分类学有影响吗?
菲茨休,2014。特征映射和枝状图比较与全部证据的要求:对多毛类分类学有影响吗?维多利亚博物馆回忆录71:67-78。在生物系统学中,对系统发育假说的推论进行数据划分已成为一种常规做法。两种流行的方法:(i)将“形态”特征映射到“分子”系统发生,以及(ii)比较“形态”和“分子”系统发生,根据所谓的总证据要求进行检查。系统发育假说的推论,实际上所有的分类群,都是通过一种称为溯因法的非演绎推理进行的。诱拐的目的是提供至少是尝试性的解释性格数据的因果关系。理性地接受外展推导出的假设,取决于对这些假设的证据支持的全部证据要求的条件。研究表明,字符映射和使用分区数据集的枝状图比较都是严重降低系统发育假设可信度的过程。通过承认我们提出的与性格数据有关的“为什么”问题的正式结构,系统发育假说可以作为答案,这个问题得到了缓解。
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
Memoirs of Museum Victoria
Memoirs of Museum Victoria Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
1.10
自引率
0.00%
发文量
5
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