The evolution of hominoid cranial diversity: A quantitative genetic approach

Abstract

Hominoid cranial evolution is characterized by substantial phenotypic diversity, yet the cause of this variability has rarely been explored. Quantitative genetic techniques for investigating evolutionary processes underlying morphological divergence are dependent on the availability of good ancestral models, a problem in hominoids where the fossil record is fragmentary and poorly understood. Here, we use a maximum likelihood approach based on a Brownian motion model of evolutionary change to estimate nested hypothetical ancestral forms from 15 extant hominoid taxa. These ancestors were then used to calculate rates of evolution along each branch of a phylogenetic tree using Lande's generalized genetic distance. Our results show that hominoid cranial evolution is characterized by strong stabilizing selection. Only two instances of directional selection were detected; the divergence of Homo from its last common ancestor with Pan, and the divergence of the lesser apes from their last common ancestor with the great apes. In these two cases, selection gradients reconstructed to identify the specific traits undergoing selection indicated that selection on basicranial flexion, cranial vault expansion, and facial retraction characterizes the divergence of Homo, whereas the divergence of the lesser apes was defined by selection on neurocranial size reduction.

Multivariate morphometrics, quantitative genetics, and neutral theory: Developing a “modern synthesis” for primate evolutionary morphology

“…In contrast, human skin pigmentation presents a very different pattern of among‐population variance apportionment consistent with the strong influence of natural selection in generating among‐group differences in skin color. A comparison of cranial variance apportionment in humans and common chimpanzees found that chimpanzees show much lower among‐subspecies cranial differentiation than expected under neutrality, which is consistent with relatively strong stabilizing selection acting on chimpanzees (and other hominoid taxa) …”

“…This suggests that dissociating the human cranium into individual linear measurements may not be the most accurate means of estimating patterns of additive genetic variance relative to phenotypic variance, due to the effects of morphological integration . As noted recently by Weaver and Gunz, there is also a disconnect between the GM approach adopted by most evolutionary morphologists and the current methods for comparing directional selection gradients or detecting deviations from neutrality, which tend to be based on individual linear measurements . Hence, new methods that combine the power of GM methods for statistical shape comparison with an analytical approach based on quantitative genetic principles such as that developed by Weaver and Gunz will be important for the future development of evolutionary morphology.…”

Look in the trees: Hylobatids as evolutionary models for extinct hominins

“…Since the molecular divergence of H. sapiens and the genus Pan (5–7mya) occurred at a similar time to the molecular divergence of hylobatids (5–7mya)—then the rates of morphological and genetic diversification between these two clades can be effectively compared. For example, there is evidence that cranial evolution in Homo sapiens is characterized by directional selection relative to the genus Pan , while the lineage leading to Hylobates is consistent with drift . This quantitative genetics approach, which relies on genetics together with morphology, could be extended to include hylobatid crania of all species to serve as a high‐resolution comparator for rates of hominin cranial evolution in the absence of DNA.…”

Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation

“…In contrast, even in recent studies for which landmark data were collected, selection gradients are commonly calculated from linear measurements (e.g., Kelly ; Schroeder et al. ; Schroeder and von Cramon‐Taubadel ), which divorces them from GM visualizations of morphology. The main exception has been the studies by Klingenberg and colleagues (Klingenberg and Leamy ; Klingenberg and Monteiro ; Klingenberg et al.…”

“…Furthermore, existing methods for detecting deviations from neutrality (e.g., Ackermann and Cheverud ; Weaver et al. ) are not well suited to handle the large number of variables inherent to landmark data, and they often require making assumptions about parameters such as effective population sizes and split times (e.g., Schroeder and von Cramon‐Taubadel ; Weaver et al. ; Weaver and Stringer ), for which we typically have little or imprecise information.…”