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biological distances among the groups that were compared to molecular distances among the
same or similar groups. The coordinate data were subjected to GPA and the projected coor-
dinates were used to compute PC scores which were analyzed with the program RMET (R
matrix analysis) for the purposes of generating biological distance matrices. The anatomical
units with the highest correlations with the neutral molecular distances were the basicra-
nium, temporal bone, upper face, and the entire cranium, suggesting these may be the
best regions of the cranium for assessing population structure and relationships based on
morphological data.
With a similar goal,
von Cramon-Taubadel (2009)
tested the shape of the temporal bone
against other individual cranial bones to ascertain if other elements show a pattern of selec-
tive neutrality similar to the temporal bone. Employing coordinates observed on landmarks
from 7 individual cranial bones as well as the entire cranium from 15 samples of modern
humans, biological distance matrices were calculated in RMET based on PC scores from
GPA registered coordinates. These matrices were compared to molecular distance matrices
and results indicated that the temporal bone does show the strongest correlation with neutral
genetic data; nevertheless, the shape of the sphenoid, frontal, and parietal bones also shows
significant correlations with the molecular data.
In another study utilizing coordinate data from cranial landmarks,
von Cramon-Taubadel
(2011)
tested the efficacy of functional and developmental cranial units for reconstructing
human population history and delineating suitable cranial units related to congruence
with neutral molecular data. She tested to see if the basicranial region is more reliable to
reconstruct population history than other regions of the human cranium. The study also
tested the hypothesis that cranial regions associated with a single sensory function are less
reliable indicators of neutral genetic history. The results showed little support for the “basi-
cranium hypothesis” as other regions of the cranium showed just as much genetic congru-
ence. She also found less support for defining cranial regions on the basis of anatomical or
functional complexity as this did not provide a consistent way to predict phylogenetic rela-
tionships or population history. Overall, she suggested future research should be focused on
identifying areas that are particularly unreliable (such as the zygomatic and occipital bones)
and removing these from analyses.
Martinez-Abadias et al. (2012)
studied the question of morphological integration of the
cranium by applying geometric morphometrics and quantitative genetic theory to the study
of a sample from the Hallstatt, Austria ossuary that are individually identified. Results sug-
gested that the face, cranial base, and cranial vault should not be seen as independent units,
but rather are strongly integrated structures. Their methodology has an advantage over
previous research that used phenotypic covariance structure as a proxy for genetic data
(
Smith et al., 2007; von Cramon-Taubadel, 2011
). Instead, they estimated a genetic covariance
matrix directly from the quantitative traits of the Hallstatt sample, since associated genealog-
ical information is available for this sample. They found strong integration for cranial shape
throughout the entire skull as genetic variation was concentrated in only a few dimensions,
thus indicating a strong genetic component and integration to overall cranial shape change.
This means that, overall, the skull behaves as a composite, and changes in one region will
produce correlated phenotypic changes in other regions, similar to studies in mouse and
newt skulls (
Ivanovic and Kalezic, 2010
), and previous studies of the human skull (
Bookstein
et al., 2003; Bastir et al., 2010
).
