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

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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.