Statistical evidence for common ancestry: application to primates

Since Darwin, biologists have come to recognize that the theory of descent from common ancestry is very well supported by diverse lines of evidence. However, while the qualitative evidence is overwhelming, we also need formal methods for quantifying the evidential support for common ancestry (CA) over the alternative hypothesis of separate ancestry (SA). In this paper we explore a diversity of statistical methods, using data from the primates. We focus on two alternatives to CA, species SA (the separate origin of each named species) and family SA (the separate origin of each family). We implemented statistical tests based on morphological, molecular, and biogeographic data and developed two new methods: one that tests for phylogenetic autocorrelation while correcting for variation due to confounding ecological traits and a method for examining whether fossil taxa have fewer derived differences than living taxa. We overwhelmingly rejected both species and family SA, with infinitesimal p-...

自达尔文时代起，生物学家已逐渐认识到，共同祖先演化理论（Common Ancestry, CA）已得到多类证据链的充分支持。尽管定性证据已然充分，但我们仍需形式化统计方法，以量化相较于独立起源假说（Separate Ancestry, SA），共同祖先假说所获得的证据支持程度。本研究以灵长类（Primates）数据为基础，探索了多样化的统计分析手段。我们聚焦于两种与共同祖先假说对立的独立起源变体：物种级独立起源假说（Species SA，即每个命名物种独立起源）与科级独立起源假说（Family SA，即每个科独立起源）。本研究基于形态学、分子生物学及生物地理学数据构建了统计检验方法，并开发了两种全新分析方法：其一可在控制混杂生态性状带来的变异的同时，检验系统发育自相关（phylogenetic autocorrelation）；其二可用于检测化石类群相较于现生类群，是否具有更少的衍征差异。本研究以压倒性的显著性水平拒绝了物种级与科级独立起源假说，其p值极小（原文此处未完整展示）