PhD: ‘Condylarths’ and the origin of odd-toed ungulate mammals

  • Institution: University of Edinburgh
  • More Information: https://www.findaphd.com/search/ProjectDetails.aspx?PJID=91347
  • Contact: Dr Stephen Brusatte (Stephen.Brusatte@ed.ac.uk)
  • Supervisors and Institutions: Dr Stephen Brusatte (University of Edinburgh), Dr Thomas Williamson (New Mexico Museum of Natural History and Science), Dr John Wible (Carnegie Museum of Natural History), Dr Michelle Spaulding (Purdue University Northwest), Dr Sarah Shelley (Carnegie Museum of Natural History)
  • Closing Date: 10 January 2018

Mammals are ubiquitous in today’s world, but how did they become so successful? The textbooks say mammals bided their time for over 100 million years and then explosively diversified after dinosaurs went extinct at the end of the Cretaceous, but this has been challenged by a competing idea that mammals gradually diversified alongside dinosaurs. This debate persists because we still know very little about those mammals that flourished during the ca. 10 million years after the end-Cretaceous extinction, during the Paleocene. These so-called ‘archaic’ mammals are now represented by a wealth of new fossils, so the time is ripe to study their anatomy, phylogeny, and evolution.This PhD project will focus on a key cluster of ‘archaic’ mammals: ‘condylarths’, a poorly understood group of primitive hoofed mammals. The particular focus of this project will be on three ‘condylarth’ subgroups: phenacodontids, hyopsodontids, and mioclaenids. Palaeontologists have long suspected some of these species to be closely related to modern perissodactyls, the hugely diverse group of odd-toed ungulates that includes horses, rhinos, and tapirs. The PhD student will work closely with an international team funded by an ERC grant, and will include examination of fossil specimens in museums (particularly the New Mexico Museum of Natural History and Science in Albuquerque and other US museums), fieldwork in the Paleocene of New Mexico, CT scanning of fossils, processing the CT scans to yield digital models, phylogenetic analysis, and statistical analysis of macroevolution.