In evolutionary biology, microevolution and macroevolution impact on the variation and covariation between genotype and phenotype. A related concept is the biological ability of an organism to adapt and evolve, or its evolvability, which is of keen interest to evolutionary biologists. The quantification of genetic change is analysed via the genetic variance-covariance matrix (G-matrix) while phenotypic change is analysed via the phenotypic variance-covariance (P-Matrix). Under the assumption of a neutral evolutionary model with the absence of genetic drift, the G-matrix should be proportional to a P-matrix. Although there is potential for theoretical complications arising from organisms with higher evolvability biasing the rates of evolutionary change, this is not fully investigated and seems to warrant further empirical studies.
The diversity of craniofacial form observed in fossil species of genus Homo and modern humans has been examined in terms of craniofacial adaptation to various biomechanical and environmental stressors. The absence of recovered genomes from species of fossil Homo beyond Homo neanderthalensis and fossil Homo sapiens has required studies of fossil human phylogenetics to rely on high uncertainties in the estimation of fossil hominin phylogeny and further restricted by small sample sizes.
In a recent study, Baab (2018) used the rate of evolutionary change in populations of modern Homo sapiens to estimate evolutionary rates in species of fossil Homo, analyzing craniofacial shape change, diversification and evolvability in the genus Homo. Results were consistent with independent conclusions that a neutral evolutionary model was adequate to generate the diversity in craniofacial form observed in the genus Homo. Once accounting for the small fossil sample size and the degree of evolutionary rate being higher than chance, there was no statistically significant support for higher rates of evolvability generating more rapid rates of evolutionary change across the entire genus Homo.
In contrast, the more recent lineages showed some evidence for selection acting at a greater magnitude in H. neanderthalensis and early H. sapiens, generating a more rapid rate of evolutionary change. Baab (2018) suggests brain expansion may be a likely contributor influencing the more rapid evolutionary rate change in craniofacial shape as observed in early H. sapiens and H. neanderthalensis and why only the more recent lineages of the genus Homo were affected by such rapid changes in craniofacial form.
Since the early 2000s, the expansion of digital anatomy tools has been aided by advances in computational power and accessibility of medical imaging such as Computed Tomography (CT). The greater accessibility to digital imaging of fossil material has allowed the reconstructions of inner cranial cavities (endocasts), sinuses cavities, and dental reconstructions of the enamel-dentine junctions (EDJ) of fossilized teeth. Despite great accessibility, the segmentation processes used to generate digital reconstructions of inner cavities remain time-consuming and require specific expertise in computer analysis, anatomy, digital imaging.
Profico et al. (2018) provide two fully-automated digital methods to minimize these time-consuming digital segmentation tasks. Both of these methods rely on point-of-views (POVs) to delineate a region-of-interest (ROI). In the CA-LSE method, POVs were located outside a ROI and all areas beyond are subtracted from the final reconstruction. In contrast, the AST-3D method relies on a ROI defined by POVs placed inside a cavity and all external areas, subtracted from the final reconstruction. While both methods are similar and can be used to generate reconstructions of the inner cavities, each method has slightly different benefits. Profico and colleagues conducted a comparison of both methods to determine strengths and weaknesses of each approach. While both of these methods are available through the Cran R network, two different R packages were tested: Morpho and Arothron.
Results indicated that in the Morpho package, CA-LSE had no restrictions on where POVs could be placed, but using AST-3D method in Morpho, POVs had to be manually placed inside the internal cavity for successful reconstruction. In the Arothron package, CA-LSE method allowed fully-automated placement of POVs outside the ROI surface, however, the AST-3D method a ROI must be defined by manually placed POVs within the inner cavity. In general, accuracy of the AST-3D and CA-LSE methods were determined by each method, with AST-3D more reliable generating reconstructions of inner cavities (such as endocasts), while the CA-LSE was more suited to reconstructions of outer structures (such as skulls).
Although, automatic approaches offer time-efficiency and often allow larger sample sizes to be more quickly processed, many fossilized skulls are highly fragmentary and automated methods remain limited when fossilized remains are partially or entirely matrix-filled with anatomical and digital expertise still requiring manual segmentation. In these complex scenarios, further fine-tuning of automated methods would be invaluable with inclusion of fully-automated, semi-automatic and manual options.
Paleoneurology Lab at Atapuerca, July 2018
In a recent paper, Beaudet and colleagues analyze the cranial vault thickness of StW 578, a partial cranium of Australopithecus not yet assigned to a species. The authors explore the utility of cranial vault thickness and of the organization of the diploe and cortical tables as potential diagnostic criteria for hominin species. For that, they also analyze a comparative sample including other South African Late Pliocene-Early Pleistocene fossils, extant humans, and chimpanzee specimens. Fossils include specimens of Australopithecus and Paranthropus recovered from Sterkfontein, Swartkrans, and Makapansgat sites. Based on cranial landmarks, the authors defined homologous parasagittal and coronal sections on the CT scans, preferentially on the right hemisphere, which is better preserved in StW 578. The thickness of the diploe, the thickness of the inner and outer cortical tables, and the total thickness were measured automatically in various points sampled throughout the length of the sections. The proportion of each layer was computed by dividing the thickness by the surface area calculated between two successive points. Specimens that preserved only the left side were used for qualitative comparison. Results emphasize differences between Australopithecus and Paranthropus. The former genus tends to have thicker vaults, with a larger proportion of the diploic layer, while the latter tends to have thinner vaults, with a larger proportion of the inner and outer tables. The distribution of thickness also differs, as StW 578 and other Australopithecus crania from Sterkfontein display disproportionately thicker frontal and posterosuperior parietal regions, while Paranthropus (SK 46) and extant chimpanzees have thickest regions on cranial superstructures (supraorbital and occipital tori). As the authors suggest, thickening of the cranial vault in frontal and parietal regions needs further investigation, as to unveil a possible correlation between bone thickness and brain anatomy. Moreover, as the increase in thickness is associated with an increase in diploe proportions, variation in this layer might indicate physiological (thermoregulation) or biomechanical differences between Australopithecus and Paranthropus. In sum, cranial vault thickness patterns of StW 578 are equivalent to those of other specimens from Sterkfontein (StW 505 and Sts 71). The presence of a Paranthropus-like pattern in two of the three Mangapansgat specimens further indicates the presence of different morphs or species of Australopithecus in this site. This methodology and results provide a fine base for further studies on the taxonomic significance of the cranial vault thickness. The authors suggest beginning by including more Paranthropus specimens, and by evaluating chronological, geographic, and taxonomic variation.
Two different papers have been published this month on the evolution of the supraorbital anatomy in humans. The first article is on Neanderthal facial morphology, and it was coordinated by Stephen Wroe, of the FEAR lab. Here a comment on the Daily Mail. The second article, by Ricardo Miguel Godinho and coauthors, links supraorbital morphology and social dynamics, and it was commented in a News and Views by Markus Bastir.
Emeritus Professor Colin Groves was an internationally-recognized and respected taxonomist in Mammalogy and Primatology. After completing his PhD dissertation at University College London in 1966 on Gorilla skull variation and taxonomy, Colin was appointed as lecturer at the Australian National University (ANU). Colin was an integral part of the ANU Biological Anthropology Department, welcoming discussions with internationally recognized researchers and undergraduate students alike, always made himself available and believed in an “open-door” policy for teaching. For me, he was an inspirational and influential mentor, teacher, colleague and friend who was an irreplaceable part of the Australian and International Primatology and Anthropology community. An online condolence book has been organised for those wishing to pay their respects.
Virtual anatomy and inner structural morphology,
from head to toe
A tribute to Laurent Puymerail
Comptes Rendus Palevol 16 (2017)
The Finite Element Method (FEM) was developed within the framework of Engineering but has become a popular tool in bio-mechanical studies. It is natural that computational bio-mechanics and Finite Element Analysis (FEA) became increasingly promising in fossil studies where there are no examples of some taxa still living. To study the bio-mechanical responses of fossil hominids, modern humans and non-human primates are often used as comparative samples for which there are already known values. Despite this, precisely how accurately computational bio-mechanics compares with physical studies is still not well understood. The biological composition of bone and dentition is hard to replicate in computational terms with the cranium a mixture of trabecular and cortical bone while teeth comprise variable layers of enamel and dentine. The resolution required from Computed Tomography (CT) scans to accurately capture these finer biological compositions is not feasible for the heavy demands on software to analyze such FEA models with flow-effects for the number of specimens that can be included into any single study.
Godinho et al investigated the validity and sensitivity of Finite Element (FE) models using a direct comparison with a human cadaver. Results were particularly affected if the model was simplified by assigning all materials as cortical bone, including dentition and trabecular bone components. Results showed that the real and virtual skull showe d no differences in strain magnitude; differences in strain pattern (high or low strain distribution) were only partially different; simplifying the virtual model decreased the strain magnitude; simplifying the virtual model partially affected the strain pattern with the regions near the dentition, particularly the alveolar ridge, most affected.
For bio-mechanical studies, by not simplifying virtual models and attempting to designate dental and bone tissues properly acknowledges the underpinning biology of the cranium while potentially revealing sensitive adaptations of this biological structure. By adopting these changes, new variations between living and fossil humans, that have so-far been obscured by less time-consuming computational methods, could reveal unique adaptational trends that have real significance for human evolution.