Collaborative Research: Advancing Bayesian Phylogenetic Methods for Synthesizing Paleontological and Neontological Data

将现存物种的数据与化石记录相结合，为理解自然界生物多样性产生的进化过程提供了丰富的视角。尽管结合这些数据的方法已经取得了重大进展，但这些方法仍然没有考虑到化石记录的完整性和采样，也没有考虑到现存物种和化石物种的地理分布。在这个项目中，研究人员将整合统计模型，以描述化石是如何随时间采样的，以及物种是在哪里发现的。这些估计物种关系的模型将在广泛使用的软件包中开发，使其他研究人员可以广泛地访问它们。这些新方法将使用模拟和真实数据集进行测试。具体来说，将研究两个具有丰富化石记录的脊椎动物群体：企鹅和鳄鱼形动物（鳄鱼、短吻鳄、大腹鳄和灭绝的近亲）。这项工作将有助于揭示这些物种的物种形成和灭绝速度是如何随着时间的推移而变化的。作为这个项目的一部分所开发的方法将在进化生物学家的研讨会上教授。此外，对现存企鹅和化石企鹅数据的分析结果将在康涅狄格州格林威治的布鲁斯博物馆的公共博物馆展出。近年来，系统发育推断方法的进展为整合化石和现存分类群提供了途径。这些方法可以同时估计现存物种和化石物种的分化时间和系统发育关系，从而充分利用形态和时间数据，而不仅仅是来自现存物种的分子序列数据。结合化石和现存分类群的方法为充分整合系统发育方法打开了大门，这些方法使用了更多的生物数据来源，包括地层学、采样和生物地理学。因此，需要一种综合的统计模型和方法来容纳这些信息。研究人员将开发新的贝叶斯统计模型，这是随机出生-死亡过程的扩展，它将整合化石记录和生物地理学的信息，用于考虑现存和化石分类群的系统发育方法。新模型将在RevBayes程序中实施。新的和先前描述的模型的性能和充分性将使用模拟和经验数据集进行评估。新的方法将用于研究两个典型分支的宏观进化模式：蝶形目（企鹅）和鳄鱼形目，解决关于系统发育关系、谱系多样化和生物地理学的关键假设。

Combining data from living species and the fossil record provides a rich perspective for understanding the evolutionary processes responsible for generating the biodiversity observed in nature. Although methods for combining these data have made significant advances, these approaches still do not consider the completeness and sampling of the fossil record or the geographical distributions of living and fossil species. For this project, the investigators will integrate statistical models for describing how fossils are sampled over time and where species are found. These models for estimating species relationships will be developed in widely used software packages, making them broadly accessible to other researchers. These new methods will be tested using both simulated and real datasets. Specifically, two vertebrate groups with rich fossil records will be studied: penguins and crocodyliforms (crocodiles, alligators, gharials, and extinct relatives). This work will help to uncover how rates of speciation and extinction have changed over time for these species. The methods developed as part of this project will be taught in workshops for evolutionary biologists. Additionally, results from analyses of data from living and fossil penguins will be contributed to a public museum exhibit at the Bruce Museum in Greenwich, CT. In recent years, advances in phylogenetic inference methods have provided ways to integrate fossil and extant taxa. These approaches allow simultaneous estimation of the divergence times and phylogenetic relationships of extant and fossil species, thus making full use of morphological and temporal data, rather than just molecular sequence data from living species. Approaches combining fossil and extant taxa have opened the door for fully integrative phylogenetic methods that use more sources of biological data, including stratigraphy, sampling, and biogeography. Thus, there is a need for comprehensive statistical models and methods that accommodate this information. The investigators will develop new, Bayesian statistical models, extensions of stochastic birth-death processes, that will integrate information about the fossil record and biogeography for use in phylogenetic methods that consider both extant and fossil taxa. The new models will be implemented in the program RevBayes. The performance and adequacy of new and previously described models will be evaluated using simulated and empirical datasets. New methods will be used to investigate macroevolutionary patterns in two exemplar clades: Sphenisciformes (penguins) and Crocodyliformes, addressing key hypotheses about phylogenetic relationships, lineage diversification, and biogeography.