The evolution of functional disparity in the avian skull

With an initial focus on the Aequolitornithes, this project will investigate several performance metrics present in avian skulls using new and existing three-dimensional models from photogrammetry, structured light, and CT scanning. These scans will be used to conduct four-bar motion and morphological analysis of the highly kinetic palatal architecture and hinges of extant birds[8] to investigate how variation in each component affects the mechanical sensitivity of the system, and influences the overall performance output[9]. Metrics such kinematic transmission and mechanical advantage will then be compared with existing data on beak shape and diet in a phylogenetic framework to test the extent and nature of many-to-one mapping of structure to function, and gain insight into which aspects of morphology are actually connected with mechanics and diet. Specifically, it can be hypothesised that these performance metrics will be a better predictor of diet and beak use than beak shape is, and convergence in performance will show up even when morphological convergence does not.
This data will provide a greater understanding of force transmission in kinetic biological structures more generally, as well as laying the groundwork for a greater understanding of the evolution of cranial kinesis in stem birds. Further analysis will be done on the structural strength of different beak and palatal architectures using second moment of area and finite element analysis[10]. Once again, this data will be tested for the presence of many-to-one mapping, and in addition will provide insight into the engineering principles governing these strong but exceptionally lightweight and thin-walled biological structures.
This project will ultimately assess the extent to which species biodiversity and morphological disparity are indicative of disparity in dietary performance more generally. In so doing, it will offer new insights into the way in which we think of biodiversity measures within ecosystems, and the macroevolutionary context in which this diversity is acquired. It will also produce and make available digital morphological models[11], and fundamental biomechanical data of interest to a range of functional morphologists, macroevolutionary biologists, ecologists, palaeontologists, and biomimetic engineers. The student will receive training in 3D scanning and reconstruction of digital morphologies, working in museum collections, advanced techniques in computational functional morphology, and the use of R for data analysis within a phylogenetic framework.