Simões Tiago R, Caldwell Michael W, Palci Alessandro, Nydam Randall L
Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
Cladistics. 2017 Apr;33(2):198-219. doi: 10.1111/cla.12163. Epub 2016 Apr 24.
Giant morphological data matrices are increasingly common in cladistic analyses of vertebrate phylogeny, reporting numbers of characters never seen or expected before. However, the concern for size is usually not followed by an equivalent, if any, concern for character construction/selection criteria. Therefore, the question of whether quantity parallels quality for such influential works remains open. Here, we provide the largest compilation known to us of character construction methods and criteria, as derived from previous studies, and from our own de novo conceptualizations. Problematic character constructions inhibit the capacity of phylogenetic analyses to recover meaningful homology hypotheses and thus accurate clade structures. Upon a revision of two of the currently largest morphological datasets used to test squamate phylogeny, more than one-third of the almost 1000 characters analysed were classified within at least one of our categories of "types" of characters that should be avoided in cladistic investigations. These characters were removed or recoded, and the data matrices re-analysed, resulting in substantial changes in the sister group relationships for squamates, as compared to the original studies. Our results urge caution against certain types of character choices and constructions, also providing a methodological basis upon which problematic characters might be avoided.
在脊椎动物系统发育的分支分析中,巨大的形态学数据矩阵越来越常见,所记录的性状数量前所未见或超乎预期。然而,对数据规模的关注通常并未伴随对性状构建/选择标准同等程度的关注(若有关注的话)。因此,对于此类有影响力的研究而言,数量是否与质量并行这一问题仍无定论。在此,我们提供了一份我们所知的最大的性状构建方法和标准汇编,这些方法和标准源自先前的研究以及我们自己全新的概念构想。有问题的性状构建会抑制系统发育分析得出有意义的同源性假设的能力,进而影响准确的分支结构。在对当前用于检验有鳞目系统发育的两个最大形态学数据集进行修订时,在分析的近1000个性状中,超过三分之一被归类到我们所定义的在分支研究中应避免的至少一类“性状类型”中。我们去除或重新编码了这些性状,并对数据矩阵重新进行分析,结果显示,与原研究相比,有鳞目的姐妹群关系发生了重大变化。我们的研究结果敦促人们在选择和构建某些类型的性状时要谨慎,同时也提供了一个可避免有问题性状的方法基础。