Investigating evolutionary relationships in passerine birds using a total-evidence approach

Passeriformes (passerines) comprise over 6,000 living species of birds-over half of extant avian diversity. However, their comparative morphology is poorly illustrated and understood, limiting the extent to which the fossil record can confidently be brought to bear on understanding the antiquity of the group, and the evolutionary patterns that have resulted in such an extraordinary degree of extant biodiversity. This project will characterise key anatomical features across the living diversity of passerines, insights from which will be used to confidently diagnose putative passerine fossils from around the world and more definitively evaluate the antiquity and phylogenetic relationships of this extraordinary avian clade.

Passerines are by far the most diverse extant avian Order, yet their comparative morphology and fossil record are poorly understood. Large-scale phylogenetic studies of passerines are only now being conducted (Oliveros et al. in review), providing a critical intellectual framework for characterising anatomical variation across the group, and identifying shared derived features diagnosing major subclades. To fill this knowledge gap, this project will generate three-dimensional anatomical atlases for major passerine subclades.

Alone, passerines comprise over 6,000 species-more than all ~42 other extant avian orders combined. The student will CT scan passerine specimens from across the living diversity of the group, primarily from the Cambridge Museum of Zoology. 'Digital dissection' techniques will be applied in the Field lab using computing resources and software that are already in place in order to characterise morphological variation across the group, and identify anatomical synapomorphies of major passerine subclades. These insights will be applied to the understudied passerine fossil record, in order to generate phylogenetically and stratigraphically vetted minimum age calibrations for passerines to be applied in molecular divergence time analyses.