The 82nd Annual Meeting of the American Association of Physical Anthropologists (2013)


Complex patterns of selection and constraint explain the evolution of the hominin hip bone

MARK W. GRABOWSKI1 and CHARLES C. ROSEMAN2.

1Center for the Advanced Study of Hominid Paleobiology, George Washington University, 2Department of Anthropology, University of Illinois

Thursday 1:30-1:45, Ballroom C Add to calendar

Human and fossil hominin pelves are strikingly different from those of other apes, with numerous large-scale changes in bony morphology hypothesized to play major roles in bipedal behavior. But playing a functional role in a behavior does not mean that a trait has evolved as the result of selection for that behavior, or even that a trait was under directional selection at all. If the same genes influence multiple traits - pleiotropy - selection on one trait can lead to a correlated responses in other traits, and thus morphological differences between species may not be a reliable indicator of past selective forces. This study uses evolutionary quantitative methods based around patterns of integration (POI) to reconstruct the selection pressures that led from the hypothesized hip morphology of the last common ancestor (LCA) of chimpanzees and modern humans, to a sample of fossil hominins, and up to modern humans. We demonstrate that though a small number of traits hypothesized to play a major functional role in bipedalism have actually evolved due to correlated evolution, the selective hypotheses of past researchers were fairly accurate overall. We also show that individual traits were under contrasting selection pressures during the non-human hominid to hominin evolutionary transition, though a human-like POI significantly reduces constraints on evolution. Finally, a human-like POI facilitates evolution along the LCA - fossil hominin - modern human trajectory. Overall, our results suggest a complex pattern of selection and constraint during hominin hip evolution.

National Science Foundation Doctoral Dissertation Improvement Grant (BCS-1028699), National Science Foundation Grant (BCS- 0962903 C.C. Roseman), Sigma Xi Grants-in-Aid of Research grant, Beckman Institute Cognitive Science/AI award, and a University of Illinois Summer Research Assistance award.

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