Modelling fossil and molecular data to establish the timescale of animal evolution

Abstract

Determining when animals evolved is a fundamental challenge of palaeontology. The fossil record is incomplete; most of the history of life on Earth is not represented in the fossil record, and less still has been discovered and researched. In particular, the fossil record of early animals is sparse and difficult to interpret. In this thesis, I use fossil and molecular data to estimate when metazoans originated. First, I investigate the Cambrian species Saccorhytus coronarius, originally described as the earliest deuterostome. Through tomographic analysis and detailed phylogenetic tests, I determine that it is a total-group ecdysozoan, increasing the known diversity of ecdysozoans in the earliest Cambrian. Building on this, I use the metazoan fossil record to develop new calibrations for a molecular clock analysis. Recent re-dating of key lagerstätten and increased understanding of early metazoan fossils allows for more precise calibrations and the molecular clock analysis estimates a younger, Ediacaran age for Metazoa. Next, I use a new model, the Bayesian Brownian Bridge (BBB) model, to investigate how the fossil record can be used to estimate clade ages without phylogenetic hypotheses or molecular data. To assess the efficacy of this model, I apply it to placental mammals, estimating a Late Cretaceous origin. This is in agreement with molecular clock studies and despite a lack of unequivocal Cretaceous placental mammal fossils, demonstrating that the model is accurately interpreting the fossil record. I then apply the BBB model to the animal fossil record, estimating metazoans originated in the Ediacaran. These analyses demonstrate that diverse modelling methods can be used to estimate divergence ages, resulting in congruent evolutionary histories. The results of my thesis suggest that through the analysis of all relevant data, it may be possible to resolve the many controversies arising from competing palaeontological and molecular approaches to establishing evolutionary timescales.

Date of Award	5 Dec 2023
Original language	English
Awarding Institution	University of Bristol
Supervisor	Philip C J Donoghue (Supervisor), Davide Pisani (Supervisor) & Zongjun Yin (Supervisor)