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Congruence of distance matrices based on cranial discrete traits cranial measurements and linguistic-geographic criteria in five Alaskan populations.

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BRIEF COMMUNICATION
Congruence of Distance Matrices Based on Cranial Discrete
T r a its, C r ania I Meas urement s, and Linguist i c-G eog r a phic
Criteria in Five Alaskan Populations
N. S. OSSENBERG
Department ofAnatomy, Queen's University, Kingston, Ontario, Canada, K7L 3N6
KEY WORDS Discrete traits . Skull
. Eskimo . Aleut
-
Biological distance
-
Correlation
ABSTRACT
Biological distances (C.A. B. Smith's Measure of Divergence)
based on 25 nonmetric skull variants have been compared with distances
(Mahalanobis' D2) based on cranial measurements of four Eskimo populations
representing the Yupik subdivision of the Eskaleut linguistic stock, and one
Aleut population. The ranking of Measures of Divergence (pooled-sex samples)
for ten pairwise comparisons is significantly correlated (Spearman's r,) with
both the male and female rankings of the F-values of D'. In addition, the nonmetric distances showed stronger concordance than the metric distances with a
hierarchy based on linguistic and geographical affinities. These findings indicate
that, depending upon the particular battery of variants used, discrete traits provide valid taxonomical information in the study of extinct human populations.
A battery of nonmetric cranial variants
demonstrated to be taxonomically valid in
terms of its power to discriminate within- and
between-race distances (Ossenberg, '76) is
being used in a current project to trace prehistoric relationships in Western North America.
Five of the approximately 35 Amerind groups
represented in the project are among those
analyzed craniometrically by Zegura ('71,
'75), permitting a further test of the validity
of this particular trait battery.
The purpose of the present paper is t o
examine the congruence of distance matrices
based on cranial discrete traits, cranial measurements, and linguistic-geographic attributes in these five populations.
MATERIALS AND METHODS
Samples
One Aleut and four Eskimo samples housed
in the U.S. National Museum furnished the
data for this study. Table 1lists for each sample the geographical derivation, approximate
time level, putative linguistic classification,
and size of that portion of the total retrieved
sample employed for nonmetric observations
AM. J. PHYS. ANTHROP.. 47: 93-98
and measurements, respectively. Owing to the
inclusion of male and female, subadult and
fragmentary specimens, more individuals are
represented in the portions of the samples
used for nonmetric analysis.
Pooled-sex nommetric data are used since it
has been demonstrated that distance measures based on this particular trait battery
are not greatly distorted by a component due
to sex. Separate male and female distance
analysis for t h e three largest (Kodiak,
Nunivak and Dakota Sioux) of 16 samples included in the earlier study (Ossenberg, '76) revealed that for each of the three samples:
the male-female distance is not significantly
greater than zero, males of the population are
closer to their own females than to any one of
the other 15 pooled-sex samples, and the rank
correlation between male and female distance
measures vs 15 pooled-sex samples is significant a t the 0.001 level. The rationale for inclusion of subadult data for certain features
has also been discussed previously (Ossenberg, '69, '76).
Many of the Kodiak skulls exhibit slight occipital flattening; the other series are undeformed.
93
94
N. S. OSSENBERG
TABLE 1
The samples
Number of individuals
in sample
Group and lncation
Approximate time
depth
Aleut, Kagamil Island
Eskimo, Kodiak Island
(upper level, Uyak Bay)
Eskimo, South Mainland Alaska
Eskimo, Nunivak Island
Eskimo, St. Lawrence Island
'
A.D. 1,500-1,700
(Turner, '67)
A.U. 1,000-1,500
(Clark, '66)
A.D. 1,700-1,900
(Collins, '63)
A.D. 1,700-1,900
(Collins, '63)
A.D. 1,700-1,900
(Collins, '63)
Linguistic
classification
IDumond. ' 6 5 )
Nonmetric
study
male and
femalr
Metric study
(Zegura.
'71, '763
Male Female
Aleut
111
28
32
Yupik: Suk
100
24
14
Yupik: Yuk
173
18
12
Yupik: Cux
102
39
32
76
71
38
Yupik: Yupak
' Includes sites frnm the regions of Rristol Bay, Nushagak River, and Kushokwim River below Old Bethel. The portioii of the
sample used for the metric study dprwei from the latter reDon only.
L in& istic-geographic ranking of the
samples
A nonbiological ranking of these populations is derived fundamentally from a scheme
of internal Eskaleut linguistic relationships,
refined according to geographical criteria.
Figure 1 is based on Dumond's ('65) hypothetical reconstruction of evolutionary relationships within t h e Eskaleut linguistic
stock. Krauss ('73) along with other authorities would oppose, on theoretical grounds, a
Stammbaum scheme such as the one represented in figure 1. Nevertheless, in the particular case of Eskaleut the affinities defined
by Krauss appear to correspond in general to
those implicit in Dumond's scheme. Both
agree that the first order dichotomy is between Eskimo and Aleut, the second between
Yupik and Inupik; and that Yupak is more
distinct from Suk and Yuk than the latter two
are from each other.
One important difference is that, whereas
Dumond considers Yuk and Cux to be separate
languages, Krauss places them together,
regarding Nunivak Island speech (Cux) as a n
aberrant dialect within a single Central
Alaskan Yupik language community. The latter definition would alter the diagram by
shifting Cux from the status of equidistant
branching with Yuk from the Yupik stem up
to a subbranch of Yuk.
Owing to lack of data on the relevant cognate percentages, quantitative ordering of all
ten pairwise comparisons in linguistic terms
is not possible. However, taking into account
the analyses of both Dumond and Krauss, one
may construct a crude hierarchy in which the
closest linguistic affinity is between Yuk and
Cux, and the most distant between Aleut and
each of the other four groups, as follows:
1. Yuk: Cux
2. Suk: Yuk and Cux
3. Yupak: Yuk, Cux and Suk
4. Aleut: Suk,Yuk, Cux and Yupak
I have drawn upon geographical and, to
some extent, archaeological and ethnohistorical considerations (Oswalt, '67) to refine the
hierarchy, as follows:
1. Yuk: Cux
2. Suk: Yuk
3. Suk: Cux
4. Yupak: Yuk
5. Yupak: Cux
6. Yupak: Suk
7. Aleut: Suk
8. Aleut: Yuk
9. Aleut: Cux
10. Aleut: Yupak
It should be emphasized that this scheme is
a linguistic-geographic composite. Thus, for
example, the clustering of all Aleut comparisons a t the bottom is linguistic; but within that cluster the order is geographical and
does not imply linguistic affinity.
Traits
To the 24 features analyzed previously
(Ossenberg, '76) I have added odonto-occipital
articulation, a n anomaly represented by a
95
CRANIAL DISCRETE TRAITS IN POPULATION STUDIES
Aleutian
Islands
Pacific
Region
Kodiak
Island
f
South
Mainland
Alaska
Siberia
and
St.Lawrence
Island
Nunivak
Island
I
I
1
Seward
Peninsula
to
Greenland
I
INUPIK
YUPIK
ALEUT
ESKIMO
I
ESKALEUT
Fig. 1 Diagram representing internal Eskaleut linguistic relationships (after Dumond, '65)
facet for articulation with the dens of the axis
on the anterior margin of the foramen magnum (Ossenberg, '691, giving a total of 25
traits.
StatisticaE methods
The distance measure used for discrete
traits is the Measure of Divergence (MD) devised by C. A. B. Smith (Grewal, '62; Berry,
'631, modified according to the recommendation of Green and Suchey ('76) using the Freeman-Tukey inverse sine transformation of
trait frequencies. The standard deviation of
MD is calculated according t o the formula
recommended by Sj~vold('73). MD is statistically significant when equal to or greater
than twice its standard deviation.
The distance statistic employed by Zegura
('71, '75) for the cranial measurements is
Mahalanobis' D2. A battery of 59 linear and 15
angular measurements were reduced to 11
canonical variates used in the computation
of D2.
An important caveat pertaining t o the comparisons in this report is that the alignment of
D' pertains to the dimensionality of a 12-sample analysis, heavily weighted towards Inupik
Eskimo not represented by any of the five
samples in this study. Rigorous methodology
would require computation of a new variancecovariance matrix. Though Zegura found that
a 10-sample analysis (excluding 2 deformed
series) produced almost identical inter-group
dispersion within 2-dimensional canonical
variate plots as the 12-sample analysis, it is
possible that a 5-sample analysis might produce a different dispersion and alter the rank
order of D2.
The F-statistic was employed by Zegura
('71) to test the significance of D2.As the Fvalues proved to be more highly correlated
than D2with the linguistic-geographic ranking described above, I have used F-values for
the comparisons in this study.
Spearman's coefficient, r, (Siegel, '561, was
used to test rank correlation between orderings of ten pairwise comparisons based on: linguistic-geographic criteria, F-values of D2 for
measurements, and MD values for discrete
traits.
RESULTS
The geographic-linguistic ranking, F-values
and MD's for the ten pairwise comparisons are
listed in table 2. The Spearman rank correlation coefficients are in table 3.
DISCUSSION
As expected, the highest correlation obtains
96
N. S . OSSENBERG
TABLE 2
Rank order of lingulstzc-geographicrelationships, and biological distances based on cranlal
measurements and cranial discrete traits in one Aleut and four Eskimo
samples. Standard deuiation o f M D an parenthesis
Measurement distance
Male
Group comparison
Linguisticgeographic
rank
SMA ': Nunivak
1
Female
____
F-value
of D'
4.1
Discrete trait
distance
F value
Rank
1
of D'
2.1
Rank
MD
Rank
1
0.051
3
(0.003)
Kodiak: S M A '
2
5.2
3
3.0
2
Kodiak: Nunivak
3
11.0
8
6.6
7
4
4.4
2
3.3
3
St. Lawrence: SMA
'
0.016
(0.003)
0.060
(0.004)
0.034
1
4
2
(0.003)
St. Lawrence: Nunivak
5
13.3
10
7.1
8
S t . Lawrence: Kodiak
6
6.8
6
4.1
5
Kagamil: Kodiak
7
5.7
4
3.5
4
Kagamil: SMA
8
5.8
5
5.4
6
Kagamil: Nunivak
9
12.0
9
13.4
10
10
10.0
7
10.3
9
Kagamil: St. Lawrence
0.120
(0.004)
0.066
(0.004)
0.088
(0.004)
0.067
(0.003)
0.138
(0.0041
0.114
(0.0041
9
5
7
6
10
8
' South Mainland Alaska
TABLE 3
Spearman 5 rank correlation coefficients,r,, for
rankings in tablet? Probability
leuels in parentheses
Linguisticgeographic
F-value male
F-value female
MD
F-value
male
F value
female
0.92
(p<0.011
0.77
(p<O.Ol)
0.84
(p<O.Ol)
0.50
(nsJ
0.75
(p<O.Ol!
0.78
(pi0.01i
for the male-female hierarchy of F-values.
The r, (0.92) for 5 groups is identical to that
reported by Zegura for male-female ranking
of D2 for 12 groups. This implies similarity of
inter-group metric distances in a multidimensional framework regardless of sex.
The nonmetric distances are significantly
correlated with the metric distances for both
males and females; more strongly with the
latter.
The correlation of linguistic-geographic
with biological distances is equally good for
nonmetric and female metric data (r, 0.78 and
0.75 respectively), but not significant for male
metric data (rs 0.50). The better overall concordance of nonmetric variables could be due
partly to larger sample size.
The slight occipital flattening of skulls in
the Kodiak series may account for the discrepancy between the metric and linguisticgeographic rank of Kodiak:Nunivak and
Kagami1:Kodiak (table 2). However, there are
no discordant ranks for Kodiak that might
be attributed t o the effect of this type
of artificial cranial deformation on discrete
traits.
The most marked deviation from the linguistic-geographic hierarchy is St. Lawrence:Nunivak, ranked fifth. In contrast,
three sets of cranial data agree closely, ranking this comparison tenth (male metric),
eighth (female metric) and ninth (nonmetric).
It may be that linguistic-geographic criteria
in this case underestimate the genetic consequences of isolation of one island from
another.
In contrast to the findings in this study,
Zegura ('75) reported rather low taxonomic
congruence between distances based on measurements and distances based on 15 discrete
traits in 12 Eskimoid populations. Moreover,
CRANIAL DISCRETE TRAITS IN POPULATION STUDIES
when concordance between biological and
linguistic relationships was examined, cranial
measurements performed better than discrete
traits. Factors to be considered in comparing
my findings with those of Zegura for nonmetric traits include the different distance
measures (MD vs Balakrishnan and Sanghvi's
B2),composition and size of samples, and trait
batteries.
Other cases of poor concordance have been
reported: for North American Plains (Jantz,
'701, North American Southwest (El-Najjar,
'74) and Africa (Rightmire, '72).
I t is possible that unsatisfactory performance of discrete traits in some instances
could be attributable-not to this type of
variable per se-but to the particular battery
of traits used. More than 200 variants have
been described on the human skull. Several
factors could account for certain traits being
possibly of less value than others (Sjavold,
'73; Corruccini, '74; Zegura, '75; Suchey, '75).
That different batteries produce different
group alignments is shown by the present 25trait analysis contrasted with Zegura's 15trait analysis. Only five features are common
to both traitlists.
Absence of correlation between biological
and nonbiological data in any particular instance would not, in itself, justify dismissing
the biological measures as untrustworthy.
This is particularly true for skeletal studies
where, as pointed out by Zegura, there is no
way of verifying the language spoken by the
people. Furthermore, there are well-known
cases among living peoples of lack of correspondence between cultural attributes and
racial identity, owing to factors such as migration, cultural diffusion and assimilation of
one group by another; for example, in Siberia
(Dolgikh, '65). The use of skeletal analysis for
historical reconstruction is limited also by
the fact that our samples represent lineages,
not biological populations in the strict sense
(Cadien et al., '76). Nevertheless, where cultural, geographical and biological data do
concur, the evidence for group relationships is
considerably reinforced.
CONCLUSION
Significant correlations between distances
based on 25 discrete cranial attributes, cranial measurements, and linguistic-geographic
criteria indicate that this battery of non-
97
metric variants is useful for the study of extinct North American populations.
ACKNOWLEDGMENTS
The cranial series were studied a t the U.S.
National Museum with the aid of a National
Research Council of Canada doctoral fellowship, 1963-64; and a grant from the Boreal
Institute of the University of Alberta, 1970.
The help and advice of Doctor J. L. Angel,
Doctor H. B. Collins, Doctor D. Ortner, Doctor
T. D. Stewart and Doctor L. St. Hoyme of that
Museum are gratefully acknowledged.
Data analysis is funded by Canada Council
Grant S75-0074.
I am grateful to Doctor S. Zegura for permission to use his thesis data, and for his helpful criticism of the manuscript.
LITERATURE CITED
Berry, R. J . 1963 Epigenetic polymorphism in wild populations of Mus rnusculus. Genet. Res., 4: 193-220.
Cadien, J. D., E. F. Harris, W. P. Jones and L. J. Mandarin0
1976 Biological lineages, skeletal populations and microevolution. Yearbook of Phys. Anthrop., 18: 194-201.
Clark, D. W. 1966 Perspectives in the prehistory of Kodiak
Island, Alaska. Am. Antiq., 31: 358-371.
Collins, H. B. 1963 Personal communication.
Corruccini, R. S. 1974 An examination of the meaning of
cranial discrete traits for human skeletal biological
studies. Am. J. Phys. Anthrop., 40: 425-445.
Dolgikh, B. 0. 1965 Problems in the ethnography and
physical anthropology of the Arctic. Arctic Anthrop., 3:
1-9.
Dumond, D. E. 1965 On Eskaleutian linguistics, archaeology and prehistory. Am. Anthrop., 67: 1231-1257.
El-Najjar, M. Y. 1974 People of Canyon de Chelly: A Study
of their Biolom
.," and Culture. Ph.D. dissertation. Arizona
State Univ., Tempe.
Green, R. F., and J. M. Suchey 19'76 The use of inverse sine
transformations in the analysis of non-metric cranial
data. Am. J. Phys. Anthrop., 45: 61-68.
Grewal, M. S. 1962 The rate of genetic divergence of sublines in the C57 BL strain of mice. Genet. Res., 3: 226237.
Jantz, R. L. 1970 Change and Variation in Skeletal Populations of Arikara Indians. Ph.D. dissertation, Univ.
Kansas, Lawrence.
Krauss, M. E. 1973 Eskimo-Aleut. Current Trends in
Linguistics, 10: 796-902.
Ossenberg, N. S.1969 Discontinuous Morphological Variation in the Human Cranium. Ph.D. dissertation, Univ.
Toronto.
1976 Within and between race distances in population studies based on discrete traits of the human skull.
Am. J. Phys. Anthrop., 45: 701-716.
Oswalt, N. H. 1967 Alaskan Eskimos. Chandler Publishing
Co., San Francisco.
Rightmire, G. P. 1972 Cranial measurements and discrete
traits compared in distance studies of African Negro
skulls. Hum. Biol., 44: 263-276.
Siegel, S. 1956 Nonparametric Statistics for the Behavioral Sciences. McGraw-Hill, New York.
98
N. S. OSSENBERG
Sjevold, T. 1973 The occurrence of' minor non-metrical
variants in the skeleton and their quantitative treatment for population comparisons. Homo, 24: 204-233.
Suchey, J. M. 1975 Biological Distance of Prehistoric Central California Populations Derived from Non-metric
Traits of the Cranium. Ph.D. dissertation, Univ. California, Riverside.
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_ _ 1975 Taxonomic congruence in Eskimoid populations. Am. J. Phys. Anthrop., 43: 271-284.
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