Category Archives: Morphometrics

Human craniofacial evolution

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.

Alannah Pearson



Pulling faces

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.


The journal of mammal zoology Hystrix has a new format and webpage. Here that good old 2013 volume on
Virtual Morphology and Evolutionary Morphometrics

Digital Endocasts

[Book]   [Post]

Sliding brains

Bruner E. & Ogihara N. 2018. Surfin’ endocasts: the good and the bad on brain form. Palaentologia Electronica 21.1.1A: 1-10.

[article]    [post]

Primate Cranial Complexes

The primate skull is comprised of complexes including the cranial base, vault and facial region. How these complexes respond to different developmental and growth processes as well as varied selective pressures like diet, locomotion and sexual selection have been investigated in terms of modularity and integration. The concepts of modularity and integration concern the co-variance or independence of these complexes.

Profico et al. used several recent statistical methods to test previous research conclusions suggesting the primate cranial base and facial complex are strongly integrated. The cranium from 11 extant species of the Cercopithecoidea and Hominoidea were studied utilizing geometric morphometrics to investigate shape variation, the presence of evolutionary allometry and modularity or integration.

Shape variation of the primate cranial base and facial complex was assessed by Principal Component Analysis. Among taxa, shape variation of the cranial base reflected patterns in locomotion, cranial base flexion and the size of the foramen magnum. The shape variation of the facial complex reflected size-related and sex-linked morphology, the degree of lower and mid-facial prognathism and associated changes to narrowing of the nasal-orbital regions. Evolutionary allometry was tested by multivariate regression of size on shape and indicated the facial complex but not the cranial base was influenced by evolutionary allometry. Modularity and integration was analyzed using Partial Least Squares to test the degree of co-variation between the facial complex and cranial base which proved to be low. These combined results suggested the cranial base and facial complex complied with the concept of modularity rather than integration contrasting with previous studies.

An important reminder that although a pattern of similarity was found between Pongo pygmaeus and Hylobates lar this does not imply a close biological relationship, rather these taxa share similar cranial base and facial block morphology, potentially as a by-product of orthograde posture and the absence of quadrupedalism found in the other primate taxa with the exception of modern humans which are obligate bipeds. In light of the current findings, a more comprehensive reconsideration may be necessary of the effects from variation in the facial complex and cranial base morphology throughout primate evolution.

Alannah Pearson


Fiorenza L., Bruner E. 2017. Cranial shape variation in adult howler monkeys (Alouatta seniculus). Am. J. Primatol. [link]

Close-range Photogrammetry or Surface Scanner?

postRecently, Evin et al. 2016 have published a study comparing the accuracy of the three-dimensional reconstruction of five wolf crania using both photogrammetry and high-resolution surface scanner. For the photogrammetric images acquisition, they used an 8-megapixel (DSLR) Canon EOS 30D camera, mounted with a Canon EF 24–105mmf/4 L IS USMlens. The scanner-based 3D models were created using a Breuckmann StereoScan structured light scanner ( The resulting 3D models were compared first through visual observation, and second with the computation of a mesh-to-mesh deviation map. The pairs of models were spatially aligned (using a least-square optimisation best-fit criterion), followed by a 3D landmark-based geometric morphometric approach using corresponding analyses. The results show that photogrammetric 3D models are as accurate in terms of coloration, texture, and geometry, as the highest-end surface scanners. Minimal differences between photogrammetric 3D models and surface scanner-based models have been only identified on intricate topological regions, such the tooth row. Photogrammetry is becoming a common tool in archaeological and anthropological research. The major advantage of this technique is the speed and ease of image acquisition and reconstruction. Photogrammetry is an equally good alternative and less expensive than other more common techniques, such as structured light or surface scanners. In terms of archaeological samples conservation, photogrammetry could be in the future an excellent alternative to provide accurate replica models that can be widely accessible for research, without affecting the original collections.

Gizéh Rangel de Lázaro

Hominin biomechanics


Hominin biomechanics

Virtual anatomy and inner structural morphology,
from head to toe
A tribute to Laurent Puymerail

Comptes Rendus Palevol 16 (2017)



Cortical and scalp development

In a recent study, Tsuzuki and colleagues analysed the co-development of the brain and head surfaces during the first two years of life using a sample of 16 infant MRIs, aged from 3 to 22 months. First, they digitized a set of cortical landmarks defined by the major sulci. Then they determined the position of cranial landmarks according to the 10-10 system, a standard method to place electrodes for electroencephalography, using  nasion, inion, and the pre-auriculars as a reference. Besides analysing the spatial variability of the cortical and scalp landmarks with age, they compared the variability of the cortical landmarks to the 10-10 positions, in order to evaluate the validity of the scalp system as a reference for brain development. For that, they transferred a given cortical landmark to the head surface by expressing its position as a composition of vectors in reference to the midpoint between the two pre-auriculars and to the three neighbor 10-10 points. The scalp-transferred landmarks were then transformed to the scalp template of a 12-month-old infant and depicted in reference to the 10-10 system.

Age-related changes in the cortical landmarks were most obvious in the prefrontal and parietal regions. As the brain elongates, the frontal lobe shifts anteriorly and the precentral gyri widen. In addition, the intraparietal sulci and the posterior part of the left Sylvian fissure move forward, suggesting relative enlargement of the parietal region in the anterior direction. The same result was obtained by our team by analyzing cranial and brain landmarks in adults: larger brain size is associated with a relative forward position of the parietal lobe. The scalp showed relative anteroposterior elongation and lateral narrowing with growth. Regarding the contrast between the cortical landmarks and the 10-10 system, the authors observed that the variability in the position of the former was much smaller than the area defined by 10-10 landmarks, indicating this system can be useful to predict the underlying cortical structures. Hence, they conclude that the changes in brain shape during development are well described by cortical landmarks and that the relative scalp positioning based on the 10-10 system can adjust to preserve the correspondence between the scalp and the cortical surfaces.


Sofia Pedro