The timing and modes of macroevolutionary change: molecules, morphology, and simulations

项目概述：可以使用真实世界(经验)数据和计算机模拟来研究宏观进化。这个项目将通过结合这些方法来识别和研究深入的进化模式。它将使用真实世界系统发育数据的荟萃分析，结合定制的进化模拟软件来探索进化速度、物种和支系历史中的常见模式，以及它们背后的进化变化机制。方法：以已发表的形态和分子(即全证据)系统发育研究的形式提供了丰富的数据，这些数据可以被重新用于研究宏观进化。这个博士学位的一个关键目标将是对这些进行荟萃分析。学生将收集系统发育数据，然后用分离的形态和分子分支长度得出贝叶斯系统发育图(例如，Beast，Mr Bayes)。化石校准点然后可以用来恢复速率，这些速率将使用R语言和一系列统计方法在不同的分支上进行比较。这将使学生能够识别和量化常见的模式。然后可以评估比率和潜在驱动因素之间的关系--例如环境变化期、物种灭绝和进化新颖性的出现。这些因素对发病率的不同影响(以及这种影响在表型和基因之间的差异)也将使用定制软件REvoSim进行研究。这是由监督小组(RJG和MDS)成员在过去八年中开发的，并于最近出版。例如，它已经显示了速率和物种形成事件之间潜在的令人兴奋的关系--以及这些与环境变化速率之间的关系。项目目标：1.使用结合分子和形态数据集的荟萃分析(时间校准的贝叶斯系统发生图)测量表型和基因型进化速率，并描述这些速率的模式和相互关系。2.检验与进化转移的相对时间相关的假设，例如分支的起源、主要的转变/新奇和灭绝事件。3.在REvoSim中进行进化模拟，以确定在经验数据中观察到的模式在Silico中复制的参数，并研究修改这些参数的效果。

Project overview: Macroevolution can be studied using real-world (empirical) data, and computer simulations. This project will identify and investigate evolutionary patterns in deep time by combining these approaches. It will use a meta-analysis of real world phylogenetic data coupled with a custom-built evolutionary simulation software to explore evolutionary rates, common patterns in species and clade history, and the mechanisms of evolutionary change underlying them. Methods: There is a wealth of data available in the form of published morphological and molecular (i.e. total-evidence) phylogenetic studies that can be repurposed to investigate macroevolution. A key objective for this PhD will be to conduct a meta-analysis of these. The student will collect phylogenetic data, and then derive Bayesian phylogenies (using e.g. BEAST, MrBayes) with uncoupled morphological and molecular branch lengths. Fossil calibration points can then be used to recover rates, which will be compared across clades using the R language and a range of statistical approaches. This will allow the student to identify and quantify common patterns. The relationships between rates and potential drivers - such as periods of environmental change, extinctions, and the appearance of evolutionary novelties - can then be assessed. The differing impact of these factors on rates (and how this varies between the phenotype and genotype) will also be studied using the custom-built software REvoSim. This has been developed over the last eight years by members of the supervisory team (RJG and MDS) and was recently published. It already shows potentially exciting relationships between rates and speciation events, for example - and how these relate to the rate of environmental change.Project objectives: 1. Measure phenotypic and genotypic evolutionary rates using metaanalysis of combined molecular and morphological datasets (time-calibrated Bayesian phylogenies) and characterise the patterns and interrelationships of these rates. 2. Test hypotheses relating to the relative timing of evolutionary shifts such as the origin of clades, major transitions/novelties, and extinction events. 3. Conduct evolutionary simulations in REvoSim to identify the parameters under which patterns observed in the empirical data are replicated in silico, and study the effects of modifying these.