Time-scaled phylogenetic trees are an ultimate goal of evolutionary biology and a necessary ingredient in comparative studies. The accumulation of genomic data has resolved the tree of life to a great extent, yet timing evolutionary events remains challenging if not impossible without external information such as fossil ages and morphological characters. Methods for incorporating morphology in tree estimation have lagged behind their molecular counterparts, especially in the case of continuous characters. Despite recent advances, such tools are still direly needed as we approach the limits of what molecules can teach us. Here, we implement a suite of state-of-the-art methods for leveraging continuous morphology in phylogenetics, and by conducting extensive simulation studies we thoroughly validate and explore our methods’ properties. While retaining model generality and scalability, we make it possible to estimate absolute and relative divergence times from multiple continuous characters while accounting for uncertainty. We compile and analyze one of the most data-type diverse data sets to date, comprised of contemporaneous and ancient molecular sequences, and discrete and continuous characters from living and extinct Carnivora taxa. We conclude by synthesizing lessons about our method’s behavior, and suggest future research venues.

中文翻译：

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从多个连续性状进行系统发育的快速贝叶斯推断


时间尺度的系统发育树是进化生物学的最终目标，也是比较研究的必要组成部分。基因组数据的积累在很大程度上解决了生命之树的问题，但如果没有化石年龄和形态特征等外部信息，对进化事件进行计时仍然具有挑战性，即使不是不可能。将形态学纳入树木估计的方法落后于分子对应物，特别是在连续性状的情况下。尽管最近取得了进展，但当我们接近分子所能教给我们的极限时，仍然迫切需要这样的工具。在这里，我们实施了一套最先进的方法来利用系统发育学中的连续形态学，并通过进行广泛的模拟研究，我们彻底验证和探索了我们方法的特性。在保留模型通用性和可扩展性的同时，我们可以估计多个连续字符的绝对和相对发散时间，同时考虑到不确定性。我们编译和分析了迄今为止数据类型最多样化的数据集之一，其中包括同时代和古代的分子序列，以及来自现存和灭绝的食肉目分类群的离散和连续特征。最后，我们总结了有关我们方法行为的经验教训，并提出了未来的研究场所。