Data from: 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-values. We compare these results with those from two companion papers, which also found tremendously strong support for the CA of all primates, and discuss future directions and general philosophical issues that pertain to statistical testing of historical hypotheses such as CA.自达尔文以来，生物学家逐渐认识到，共同祖先（common ancestry，以下简称CA）演化理论得到了多类证据的强力支持。然而，尽管定性证据已极具压倒性，我们仍需正式的统计方法，以量化CA相较于独立起源（separate ancestry，以下简称SA）替代假说的证据支持强度。本研究以灵长类动物的数据为基础，探索了多种统计分析方法。我们聚焦于两种与共同祖先相悖的替代假说：物种水平独立起源（species SA，即每一个命名物种均为独立起源）与科水平独立起源（family SA，即每一个科均为独立起源）。我们基于形态学、分子生物学及生物地理学数据构建了统计检验方法，并开发了两种全新的分析手段：其一为在校正混杂生态性状导致的变异的同时，检验系统发育自相关（phylogenetic autocorrelation）的方法；其二为评估化石类群（fossil taxa）的衍征差异是否少于现生类群的方法。我们以极小的p值（p-values）压倒性地拒绝了物种水平与科水平独立起源两种假说。我们将本次研究结果与另外两篇同期发表的配套论文进行了对比，后者同样发现了支持所有灵长类动物拥有共同祖先的极强证据；同时我们还讨论了后续研究方向，以及诸如共同祖先这类历史演化假说的统计检验所涉及的一般性哲学议题。