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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 134:312–322 (2007)

Genetic, Geographic, and Environmental Correlates

of Human Temporal Bone Variation

Heather F. Smith, 1 * y Claire E. Terhune, 1 * y and Charles A. Lockwood 2

1 School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287-2402

2 Department of Anthropology, University College London, London WC1E 6BT, UK

KEY WORDS geometric morphometrics; molecular distance; cranial morphology

ABSTRACT Temporal bone shape has been shown to

reﬂect molecular phylogenetic relationships among homi-

noids and offers signiﬁcant morphological detail for distin-

guishing taxa. Although it is generally accepted that tem-

poral bone shape, like other aspects of morphology, has an

underlying genetic component, the relative inﬂuence of

genetic and environmental factors is unclear. To determine

the impact of genetic differentiation and environmental

variation on temporal bone morphology, we used three-

dimensional geometric morphometric techniques to evalu-

ate temporal bone variation in 11 modern human popula-

tions. Population differences were investigated by discrim-

inant function analysis, and the strength of the relation-

ships between morphology, neutral molecular distance,

geographic distribution, and environmental variables were

assessed by matrix correlation comparisons. Signiﬁcant

differences were found in temporal bone shape among all

populations, and classiﬁcation rates using cross-validation

were relatively high. Comparisons of morphological dis-

tances to molecular distances based on short tandem

repeats (STRs) revealed a signiﬁcant correlation between

temporal bone shape and neutral molecular distance

among Old World populations, but not when Native Amer-

icans were included. Further analyses suggested a similar

pattern for morphological variation and geographic distri-

bution. No signiﬁcant correlations were found between

temporal bone shape and environmental variables: tem-

perature, annual rainfall, latitude, or altitude. Signiﬁcant

correlations were found between temporal bone size and

both temperature and latitude, presumably reﬂecting

Bergmann’s rule. Thus, temporal bone morphology ap-

pears to partially follow an isolation by distance model of

evolution among human populations, although levels of

correlation show that a substantial component of variation

is unexplained by factors considered here. Am J Phys

Anthropol 134:312–322, 2007.

C 2007 Wiley-Liss, Inc.

Like other aspects of phenotype, cranial morphology

reﬂects a combination of genetic and environmental

inﬂuences (Moss, 1962, 1972). Within this framework,

some authors have suggested that particular portions of

the cranium may be less prone to variation due to envi-

ronmental variables, and therefore more phylogenetically

informative (Olson, 1981; Strait et al., 1997; Lieberman

et al., 2000a; Harvati, 2001; Wood and Lieberman, 2001;

Harvati and Weaver, 2006a,b). For hominins, traits asso-

ciated with heavy chewing have been argued to be homo-

plastic and consequently unreliable indicators of phylog-

eny (Walker et al., 1986; Wood, 1988; Skelton and

McHenry, 1992; Turner and Wood, 1993; McHenry, 1994,

1996; Lieberman et al., 1996; but see Strait et al., 1997;

Asfaw et al., 1999; Collard and Wood, 2001). The mor-

phology of the cranial base has especially been regarded

as a reliable reﬂection of genetic relationships, as it

forms very early during ontogeny and ossiﬁes endochon-

drally (Moore and Lavelle, 1974; Olson, 1981; MacPhee

and Cartmill, 1986; Lieberman et al., 2000a,b). The cra-

nial base also mirrors the shape of the developing brain,

which is relatively constrained (Houghton, 1996). Basi-

cranial characters may therefore be less inﬂuenced by

epigenetic forces than are the externally sensitive intra-

membraneous bones of the facial skeleton.

The morphology of the temporal bone, as part of the

cranial base, may also reﬂect neutral molecular distan-

ces within species and phylogenetic relationships among

species. However, the temporal bone also serves a vari-

ety of functional roles, such as posture, hearing, balance,

mastication, and formation of the braincase. Conse-

quently, this element can serve as a test case of the

ways in which cranial morphology covaries with molecu-

lar distances and environmental factors and a test of the

hypothesis that cranial base elements have a strong

genetic component.

Several recent studies of variation in the temporal

bone have demonstrated this region’s utility in distin-

guishing among species and subspecies of extant great

apes, and for quantifying levels of variation within and

between taxa (Harvati, 2001, 2003; Lockwood et al.,

2002, 2004, 2005; Terhune et al., 2007). In particular,

Lockwood et al. (2004) demonstrated that, using shape

distributions of coordinate data from modern humans,

orangutans, gorillas, chimpanzees, and bonobos, the re-

sultant phylogenetic tree of these taxa was identical to

the molecular phylogeny of these species. Similarly, sev-

Grant sponsors: AMNH Collections Study Grant and ASU Depart-

ment of Anthropology; Grant number: NSF BCS-9982022.

*Correspondence to: Heather F. Smith or Claire E. Terhune,

School of Human Evolution and Social Change, Arizona State Uni-

versity, Box 872402, Tempe, AZ 85287-2402, USA.

E-mail: heather.f.smith@asu.edu or claire.terhune@asu.edu

y These authors contributed equally to this work.

Received 12 December 2006; accepted 8 May 2007

DOI 10.1002/ajpa.20671

Published online 13 July 2007 in Wiley InterScience

(www.interscience.wiley.com).

2007 WILEY-LISS, INC.

TEMPORAL BONE VARIATION IN MODERN HUMANS

313

Fig. 1. Map of the world

showing the approximate lo-

cations of populations used

in the morphological analy-

sis (triangles), populations

used in the molecular analy-

sis (circles), and waypoints

(squares). Lines link the mor-

phological populations and

their genetic representatives.

eral recent studies (Harvati, 2001, 2003; Terhune et al.,

2007) have used the morphology of the temporal bone to

test hypothesized taxonomic divisions among fossil taxa.

Given this background, we sought to investigate the

association between temporal bone morphology and mo-

lecular distance among human populations, together

with geographic distance and external factors such as

environmental variables. Some recent studies have ex-

plicitly evaluated these inﬂuences on cranial anatomy

(Relethford, 1994, 1998, 2001, 2002; Gonzales-Jose et al.,

2004; Roseman, 2004). Linear dimensions of the skull

have been shown to reﬂect genetic relationships of

human populations, such that closely related populations

tend to be more similar in overall cranial form (Rele-

thford, 2001, 2002; Gonzales-Jose et al., 2004; Roseman,

2004). However, selective pressures acting on the skull

of certain human populations have also been identiﬁed

and can have a signiﬁcant impact on cranial morphology

of populations living in regions with extreme tempera-

tures, such as Siberia (Roseman, 2004). Diversifying re-

gional selection due to climate also affects the cranial

morphology of several other human populations (Carey

and Steegmann, 1981; Franciscus and Long, 1991; Rose-

man, 2004).

Harvati and Weaver (2006a,b) analyzed the correlation

between human morphological variation in three cranial

regions – the temporal bone, cranial vault, and facial

skeleton – with molecular distances and environmental

variables. They concluded that the morphology of the

temporal bone and cranial vault are correlated with mo-

lecular distance in human populations, while facial mor-

phology covaries more reliably with environment. The

correlation between temporal bone shape and molecular

distance was signiﬁcant but low, suggesting that other

factors also play a signiﬁcant role in patterns of tempo-

ral bone morphology in humans. In addition, temporal

bone centroid size was found to be correlated with tem-

perature, a ﬁnding that is consistent with environmental

variation in body size as ﬁrst outlined by Bergmann (1847).

Our goal is to use an independent dataset and an

expanded set of landmarks on the temporal bone to

replicate part of the study of Harvati and Weaver

(2006a). We also include additional environmental varia-

bles such as rainfall and altitude, and explore the rela-

tionship between morphology and geographic distance.

In general, we are testing the hypothesis that the tem-

poral bone follows an isolation by distance model of evo-

lution in human populations (Wright, 1943). More specif-

ically, three research questions were investigated:

Q1. Are modern human populations signiﬁcantly differ-

ent in temporal bone morphology?

Q2. What is the strength of the correlation between tem-

poral bone morphology and molecular distance

among populations of modern humans?

Q3. How do external variables such as environmental

differences or geographic distance covary with pat-

terns of temporal bone morphology in humans?

MATERIALS AND METHODS

Data collection

A total of 243 individuals from 11 modern human pop-

ulations were included in this study (Fig. 1, Table 1).

Specimens were housed at the American Museum of

Natural History and Arizona State University. Individu-

als with extensive antemortem tooth loss were generally

avoided to minimize the possibility of alveolar resorption

affecting the morphology of the temporomandibular joint

(TMJ). Following Lockwood et al. (2002), 22 landmarks

from the ectocranial surface of the temporal bone were

employed, which describe the morphology of the mandib-

ular fossa, tympanic, mastoid, and petrous portions of

the temporal bone (Fig. 2, Table 2). In comparison, Har-

vati and Weaver (2006a) used 13 landmarks.

An Immersion Microscribe point digitizer was used to

record the three-dimensional coordinates of each land-

mark. These three-dimensional data were then analyzed

using Morphologika (O’Higgins and Jones, 1998). First,

three-dimensional coordinate data were registered

through a generalized Procrustes analysis (GPA) (Gower,

1975; Goodall, 1991; Dryden and Mardia, 1998). Subse-

quently, variation in shape was investigated through

principal components analysis (PCA). Output from these

analyses (Procrustes residuals from the GPA and PC

scores from the PCA) was recorded and copied into other

statistical programs for further analysis. All three-

dimensional data were collected by the second author,

and intraobserver error for a subset of the data set used

here is reported by Terhune et al. (2007).

Data on 783 STRs in matched analogues of nine of the

human populations discussed earlier were used to obtain

American Journal of Physical Anthropology—DOI 10.1002/ajpa

314

H.F. SMITH ET AL.

TABLE 1. Modern human populations used in the morphometric analysis

Population a

Total Genetic representative Centroid size Average geographic coordinates

Alaskan Natives

20 None

106.43

68.4N, 166.7W

Australian Aborigines

21 Australians

94.69

34.8S, 138.5E

Hungarians (Medieval)

21 French

98.69

46.6N, 18.4E

Khoisan

19 San

98.21

20.5S, 19.5E

Malaysians

21 Cambodians

100.23

4N, 109.5E

Mongolians

18 Mongolians

103.43

46.9N, 103.8E

Native American (Grand Gulch, Utah)

20 Pima

102.91

37.6N, 109.8W

New Guineans

20 Papua New Guineans

97.52

6.4S, 150.2E

Nubians (Semna South, Sudanese Nubia)

43 Mozabite

98.63

20.0N, 30.1E

Pare (Tanzania)

19 Kenyan Bantu

98.35

4.3S, 38.1E

Southern Indians

21 None

94.64

13N, 77.56E

Total 243

a Specimens were housed at Arizona State University (Nubians) or the American Museum of Natural History (all others).

neutral molecular distances. STRs have been shown to

be particularly useful and appropriate for determining

genetic relationships of populations of Homo sapiens.

These loci are autosomal and evolve neutrally such that

shared mutations are accepted as evidence of common

ancestry. The dataset used here was originally used by

Ramachandran et al. (2005) and Rosenberg et al. (2005)

and consists of the largest and most inclusive STR data-

set published to date. Several of the populations meas-

ured in the craniometric study have not been typed for

STRs, particularly the archaeological samples (the

Nubians and Medieval Hungarians). In these cases, it

was necessary to substitute a representative population

from the same geographic region and/or linguistic group

(Table 1). This practice has been employed in previous

studies of the relationship between morphological and

molecular distances in modern humans (Relethford,

1994; Roseman, 2004; Harvati and Weaver, 2006a,b).

The Alaskan natives and southern India sample had to

be omitted from the molecular analysis as neither they nor

any other comparable population has been typed for a

sufﬁcient number of STR loci. However, these populations

were still included in all other analyses in this study.

Approximate geographic coordinates of population ori-

gins were estimated using an atlas and published infor-

mation for the samples. In the case that a range of coor-

dinates was obtained, an average location was used.

Data were also compiled on environmental variables in

regions from which the populations originated, using

data from nearby weather stations (New et al., 1999,

2000) and almanacs. These included rainfall, tempera-

ture, altitude, and latitude. The link between these envi-

ronmental variables and temporal bone morphology

could stem directly from local adaptations of cranial

shape or indirectly from behaviors mediated by the envi-

ronment, such as diet or activity levels.

Analytical methods

The ﬁrst research question examined the degree to

which the morphology of the temporal bone can discrimi-

nate among populations of Homo sapiens, and was eval-

uated in two ways. First, Procrustes distances between

groups were calculated, and the signiﬁcance of these

values was assessed via a permutation test (Good, 1993).

This form of signiﬁcance testing compares the observed

distance (i.e., test statistic) with a distribution of per-

muted distances, where individuals are randomly allo-

cated to each group and a mean distance is calculated.

A test statistic is considered statistically signiﬁcant

Fig. 2. Twenty-two temporal bone landmarks digitized in

the present study (following Lockwood et al., 2002). Refer to

Table 2 for landmark deﬁnitions. Open circles show the relative

positions of landmarks 1 and 18 when these landmarks are not

directly visible.

American Journal of Physical Anthropology—DOI 10.1002/ajpa

TEMPORAL BONE VARIATION IN MODERN HUMANS

315

TABLE 2. Deﬁnitions of landmarks used in the present study

No. Deﬁnition

1 Intersection of the infratemporal crest and sphenosquamosal suture

2 Most lateral point on the margin of foramen ovale

3 Most anterior point on the articular surface of the articular eminence

4 Most inferior point on entoglenoid process

5 Most inferior point on the medial margin of the articular surface of the articular eminence

6 Midpoint of the lateral margin of the articular surface of the articular eminence

7 Center of the articular eminence

8 Deepest point within the mandibular fossa

9 Most inferior point on the postglenoid process

10 Anteromedial apex of the petrous part of the temporal bone

11 Most posterolateral point on the margin of the carotid canal entrance

12 Most lateral point on the vagina of the styloid process (whether process is present or absent)

13 Most lateral point on the margin of the stylomastoid foramen

14 Most lateral point on the jugular fossa

15 Center of the inferior tip of the mastoid process

16 Most inferior point on the external acoustic porus

17 Most inferolateral point on the tympanic element of the temporal bone

18 Point of inﬂection where the braincase curves laterally into the supraglenoid gutter, in coronal plane of the mandibular fossa

19 Point on lateral margin of the zygomatic process of the temporal bone in the coronal plane of the postglenoid process

20 Auriculare

21 Porion

22 Asterion

After Lockwood et al. (2002).

95% of variation). The differentiation

among populations was then assessed using discriminant

analyses with jackknife cross-validation, where prior

probabilities were set equal to group size. Since the Nu-

bian sample was signiﬁcantly larger than all other sam-

ples used here (n

the values by a pooled within-group covariance matrix,

which assumes that all groups in the analysis have

similar covariance structures (Ackermann, 2002, 2005;

Klingenberg and Monteiro, 2005). This assumption is

tenuous given the sample sizes used here. In contrast,

since Procrustes distances are not scaled by the pooled

within-group covariance matrix, differences in covari-

ance structure between populations should not affect

these distances as drastically as they would affect

Mahalanobis distances. Also, Mahalanobis distances are

affected by uneven sample sizes, while no similar bias

has been noted for Procrustes distances.

The second research question addressed the degree of

concordance between temporal bone shape and genetic

relationships among human populations. This relation-

ship was tested by examining the correlation between

matrices of temporal bone morphology (i.e., size and

shape matrices) and molecular distances. Analogous

studies above the species level have compared phyloge-

netic trees based on morphology with those based on

molecular data (Lockwood et al., 2004; see also Collard

and Wood, 2001; Strait and Grine, 2004; Lycett and Col-

lard, 2005). However, within humans, a tree-like struc-

ture does not apply to population relationships for mor-

phological or molecular information (summarized by

Sherry and Batzer, 1997; Athreya and Glantz, 2003).

The current analysis is therefore restricted to matrix

correlation comparisons.

STR data were analyzed using Arlequin 3.0 (Excofﬁer

et al., 2005). Data on 783 STRs have been typed for

eight representative populations (Ramachandran et al.,

2005; Rosenberg et al., 2005), and a subset of 404 of the

same STRs has been typed in Native Australians. A ma-

trix of STR population distances was constructed using

Slatkin’s genetic distance, a distance measure analogous

to F ST but speciﬁcally designed for microsatellite loci in

assuming a stepwise mutation model (Slatkin, 1995).

The degree and signiﬁcance of the correlation between

the distance matrices from the molecular and morpho-

43), a reduced sample of 20 ran-

domly chosen individuals was used for this analysis.

DFAs were conducted using SPSS (version 11.0.1).

Although Procrustes superimposition scales all speci-

mens to the same unit centroid size, size related shape

changes (i.e., allometry) are not removed. Therefore, to

assess the role of allometry, a size matrix (i.e., a matrix

of the absolute differences in centroid size between

groups) was calculated and compared with the Pro-

crustes distance (or shape) matrix using a Mantel test

(Mantel, 1976; Smouse et al., 1986) in PopTools, an add-

on for Microsoft Excel. Additionally, correlations between

centroid size and shape were evaluated by regressing

the principal component axes on centroid size using

Morphologika.

For each analysis, morphological distances (i.e., size or

shape distance matrices) were compared to the variable

of interest (e.g., molecular or environmental distances).

Both Procrustes and Mahalanobis distances were calcu-

lated for all populations used here, and these two dis-

tance measures were found to be signiﬁcantly correlated

(r 5 0.662; P \ 0.001). Analyses using both of these dis-

tance measures were found to lead to the same general

pattern of results. However, while a number of authors

(Ackermann, 2002; Strand Viðarsd ´ ttir et al., 2002; Har-

vati, 2003; Harvati et al., 2004; McNulty, 2005; Harvati

and Weaver, 2006a,b) have previously used Mahalanobis

distances in analyses such as this, only Procrustes dis-

tances are reported here, as Mahalanobis distances

attempt to account for within group variation by scaling

American Journal of Physical Anthropology—DOI 10.1002/ajpa

(P-value 0.05) if it is reached or exceeded in less than

5% of the random permutations. Second, a discriminant

function analysis (DFA) was conducted using the ﬁrst 40

PC scores from the PCA of Procrustes coordinates (which

accounted for

[

316

H.F. SMITH ET AL.

TABLE 3. Structure matrix for the discriminant function analysis (ﬁrst 20 PCs only) showing the correlations

between each of the PC axes and discriminant functions

Function

PC1

0.131

0.439

2 0.088

2 0.105

0.145

2 0.127

0.230

0.034

0.113

2 0.052

PC2

0.140

0.057

0.182

0.246

2 0.033

0.312

2 0.200

2 0.196

0.051

0.056

PC3

0.076

2 0.211

2 0.061

0.063

0.327

2 0.118

0.071

0.122

2 0.124

2 0.169

PC4

2 0.022

2 0.068

0.070

0.043

0.164

0.316

2 0.005

0.203

2 0.133

PC5

2 0.037

2 0.010

0.124

0.149

2 0.028

2 0.381

0.102

0.037

2 0.052

0.309

PC6

0.189

0.018

2 0.238

0.379

2 0.051

2 0.153

0.031

0.094

2 0.113

0.144

PC7

2 0.069

0.228

2 0.073

0.186

0.142

0.152

2 0.062

0.165

2 0.357

2 0.068

PC8

0.029

0.022

0.141

2 0.136

0.193

0.037

2 0.049

2 0.069

2 0.033

2 0.093

PC9

0.138

2 0.055

0.013

0.060

0.172

0.014

0.175

2 0.137

0.023

0.009

PC10

2 0.173

0.079

0.029

0.287

0.133

2 0.005

0.149

0.038

0.223

0.018

PC11

0.053

0.035

0.149

2 0.091

0.043

0.060

0.130

0.165

2 0.094

0.286

PC12

0.012

0.037

0.006

0.059

2 0.080

2 0.049

0.141

0.087

0.164

PC13

0.061

0.028

0.039

0.140

0.066

0.156

0.135

0.445

0.081

0.062

PC14

0.102

0.094

0.208

0.224

0.125

0.022

0.050

0.064

0.056

0.244

PC15

0.105

0.015

0.192

0.121

0.023

0.035

0.044

0.042

0.071

0.053

PC16

0.020

0.030

0.084

0.046

0.010

0.211

0.206

0.012

0.065

0.242

PC17

0.019

0.085

0.032

0.023

0.127

0.072

0.143

0.225

0.390

0.093

PC18

0.011

0.098

0.015

0.037

0.182

0.123

0.142

0.025

0.029

0.250

PC19

0.010

0.033

0.196

0.001

0.110

0.092

0.070

0.210

0.034

0.096

PC20

0.049

0.073

0.018

0.037

0.150

0.015

0.086

0.276

0.129

0.064

logical analyses was assessed using a Mantel test, again

in PopTools.

Finally, environmental variables and geographic dis-

tances for populations were evaluated to determine how

they covary with temporal bone morphology. Environ-

mental distance matrices were generated for each envi-

ronmental variable: temperature, rainfall, latitude, and

altitude. A single overall environmental distance matrix

(Euclidean distance, incorporating data from all four

environmental variables) was also calculated in Pop-

Tools. To address the possibility that environmental fac-

tors inﬂuenced morphological difference, the morphologi-

cal distance matrices were compared to each environ-

mental matrix using a Mantel test.

To test the association between geography and mor-

phology, geographic great circle distances among popula-

tions were calculated. Great circle distances use latitude

and longitude and take into account the fact that these

coordinates are on the circumference of a sphere to cal-

culate distances between two locations. A geographic ma-

trix was generated using great circle distances and

including ﬁve waypoints (Fig. 1), geographic locations

through which populations would have had to travel

when migrating between two continents (Relethford,

2004; Ramachandran et al., 2005). This practice takes

into account the conclusion that most human migrations,

until recently, did not usually traverse large bodies of

water (Ramachandran et al., 2005). The inclusion of

waypoints, therefore, permits a more accurate estimate

of the migrational distance among populations, rather

than a line of minimal geographic distance that could

run across an ocean. The pairwise distance between any

two populations was calculated as the sum of the dis-

tance between Population 1 and the waypoint, and

between the waypoint and Population 2, plus any dis-

tances between waypoints if more than one waypoint fell

between the populations. Following Ramachandran et al.

(2005), waypoints included were Anadyr, Russia; Cairo,

Egypt; Istanbul, Turkey; Phnom Penh, Cambodia; and

Prince Rupert, Canada. Geographic distances among

populations on the same continent were calculated as

normal great circle distances. It is probable even within

TABLE 4. Eigenvalues, distribution of variance, and canonical

correlations for the discriminant function analysis

Function Eigenvalue

%of

variance Cumulative %

Canonical

correlation

6.39

40.81

0.93

2.78

17.75

58.56

0.86

1.44

9.18

67.74

0.77

1.29

8.23

75.97

0.75

1.21

7.74

83.71

0.74

0.91

5.82

89.53

0.69

0.58

3.69

93.22

0.61

0.45

2.87

96.09

0.56

0.33

2.11

98.20

0.50

0.28

1.80

100.00

0.47

continents that migrational distances are affected by

geographical barriers and are not simply great circle dis-

tances; this factor is considered later in discussing the

results. The hypothesis that temporal bone morphology

covaries with geographic distance was then assessed by

comparing the geographic matrix with the morphological

matrix using a Mantel test.

For all analyses, alpha was set at 0.05. All correlations

are reported as Pearson product moment correlation

coefﬁcients (r).

RESULTS

In the DFA, the ﬁrst function is inﬂuenced by a vari-

ety of principal components and accounts for just over

40% of variance among populations (Tables 3 and 4). As

expected, contributions of subsequent functions diminish

rapidly (Table 4).

Permutation tests of the Procrustes distances among

populations were all statistically signiﬁcant with P-val-

ues of less than 0.001 (Table 5). The DFA with crossvali-

dation demonstrates that the populations can be distin-

guished relatively well, with classiﬁcation rates between

56 and 85% (mean 73%) (Table 6). For 11 populations of

roughly equal sample size, the expected proportion of

correct random classiﬁcations is

9%, so these results

indicate high success rates.

American Journal of Physical Anthropology—DOI 10.1002/ajpa

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