Carrie Mongle

Grant Type

Dissertation Fieldwork Grant

Institutional Affiliation

New York, Stony Brook, State U. of

Grant number

Gr. 9242

Approve Date

April 8, 2016

Project Title

Mongle, Carrie, S., Stony Brook U., Stony Brook, NY - To aid research on 'Modeling Hominin Variability: The Alpha Taxonomy of 'Australopithecus africanus',' supervised by Dr. Frederick E. Grine

Preliminary abstract: The recognition of species in the fossil record is of critical importance to understanding hominin evolution and diversity. A vast literature exists on species concepts, but process-based definitions cannot be easily applied to fossil species. Accordingly, levels of variation within purported hypodigms have typically been used to delineate hominin species, but such approaches rest on the problematic assumption that these parameters are comparable in extinct and extant species. Elsewhere in systematic biology, methods have been developed that utilize the structure of variance within a sample to detect the presence of discrete species. Despite continued controversy over hominin species delineation, these methods have yet to be employed in anthropology. Australopithecus africanus exemplifies this problem. Resolving its alpha taxonomy is critically important to interpreting human evolution, but it remains a contentious issue. The possibility that A. africanus subsumes two or more species has significant implications for the interpretation of the hominin phylogeny and the evolution of the genus Homo. The primary goal of this dissertation research is to quantitatively model species variation in extant primates and fossil hominins in order to re-evaluate the taxonomic heterogeneity of the A. africanus assemblage. This will be accomplished by using phylogenetic comparative methods to estimate an appropriate null hypothesis model of hominin variability. Shape and topographic data will be collected from high resolution 3D surfaces of extant primate and fossil hominin teeth using landmarks, semi-landmarks, and GIS-based approaches. The data from this study will provide the foundation for a detailed model of hominin variability using both mixture models and matrix correlation analyses.