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，生物学家已逐渐认识到，共同祖先（common ancestry, CA）理论得到了多类证据的强力支持。然而，尽管定性证据已然确凿无疑，我们仍需正式的统计方法，以量化共同祖先相较于独立起源（separate ancestry, SA）这一备择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。我们聚焦于共同祖先的两类备择假说：物种级独立起源（species SA，即每一个命名物种均为独立起源）与科级独立起源（family SA，即每一个科均为独立起源）。我们基于形态学、分子学及生物地理学数据构建了统计检验框架，并开发了两项全新的分析方法：其一为在校正混杂生态性状所引发的变异的同时，检验系统发育自相关（phylogenetic autocorrelation）的方法；其二为考察化石类群是否较现生类群具有更少衍生差异的方法。我们以极小的p值（p-value）压倒性地拒绝了物种级与科级独立起源两类假说。我们将本次研究结果与另外两篇配套论文的结论进行了对比，后者同样为所有灵长类动物的共同祖先理论提供了极强的证据支持；同时，我们还讨论了针对共同祖先这类历史假说开展统计检验时的未来研究方向与一般性哲学议题。