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通过大脑特征构建系统发育:由神经特征生成的树状图。

Phylogeny through brain traits: trees generated by neural characters.

作者信息

Kirsch J A, Johnson J I

出版信息

Brain Behav Evol. 1983;22(2-3):60-9. doi: 10.1159/000121507.

Abstract

Phylogenetic trees were computed by the Wagner algorithm from data on up to 15 brain characters scored on 154 specimens of 134 mammalian species. Because the data were not complete on all specimens, only one tree, of 18 taxa, was generated on all 15 features; a tree of 99 species was computed from 10 characters, and trees of 38 species from 10 and 12. The 38-taxon trees were considered best because they preserved most completely the integrity of mammalian orders. All trees consistently separated the subclasses of mammals and suggested that rodents, insectivores, and the tree shrew were most derived on the basis of brain characters. The trees' shapes are sensitive to small alterations in character scorings, largely because of the relatively few characters available and small differences in the number of states among them.

摘要

系统发育树是通过瓦格纳算法,根据对134种哺乳动物的154个标本的多达15个脑部特征的数据计算得出的。由于并非所有标本的数据都完整,因此针对所有15个特征仅生成了一棵包含18个分类单元的树;从10个特征计算出了一棵包含99个物种的树,以及从10个和12个特征计算出了包含38个物种的树。包含38个分类单元的树被认为是最佳的,因为它们最完整地保留了哺乳动物目之间的完整性。所有的树都一致地将哺乳动物的亚类区分开来,并表明啮齿动物、食虫动物和树鼩在脑部特征方面是最具衍生性的。树的形状对特征评分的微小变化很敏感,这主要是因为可用的特征相对较少,且它们之间状态数量的差异较小。

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