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Cranial variation in the Marquesas Islands.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 121:319 –331 (2003)
Cranial Variation in the Marquesas Islands
Vincent H. Stefan1* and Patrick M. Chapman2
1
2
Department of Anthropology, Lehman College, CUNY, Bronx, New York 10468
Department of Anthropology, South Puget Sound Community College, Olympia, Washington 98512
KEY WORDS
Marquesan; Marquesas Islands; craniometrics; cranial discrete traits
ABSTRACT
The Marquesas Islands have traditionally been divided into a northwestern and a southeastern
group, a division which reflects language dialect differences. Additionally, archaeological studies have also suggested that differences in material culture existed between the northwestern and southeastern islands. This
study examines Marquesan cranial discrete and metric
traits to evaluate the level of intra-archipelago heterogeneity, and to determine if a northwest/southeast division
is evident cranially.
The data consist of 28 cranial discrete traits and 49
craniofacial measurements of prehistoric Marquesans.
Male and female data are pooled for discrete trait and
metric data, following a Z-score standardization technique
adjustment. The data represent three island samples:
Nuku Hiva (northwest), Fatuiva (southeast), and a combined Tahuata/Hiva ‘Oa (southeast). Of the 28 discrete
traits, 16 are utilized in a mean measure of divergence
analysis that provides scores of 0.259 for FatuivaTahuata/Hiva ‘Oa, 1.850 for Nuku Hiva-Fatuiva, and
1.491 for Nuku Hiva-Tahuata/Hiva ‘Oa. Of the 49 craniofacial measurements, 46 are utilized in RMET/NORM
analyses, providing unbiased D2 values of 0.0433 for Fa-
tuiva-Tahuata/Hiva ‘Oa, 0.1328 for Nuku Hiva-Fatuiva,
and 0.0813 for Nuku Hiva-Tahuata/Hiva ‘Oa. The islands
of the southeastern group are closer to each other than
either was to the island of the northwestern group. When
a sample from ‘Ua Huka is included in the craniometric
analysis, the unbiased D2 values of 0.0829, 0.1175, and
0.0431 are calculated for ‘Ua Huka and Nuku Hiva, and
Fatuiva and Tahuata/Hiva ‘Oa pairings, respectively, indicating a close similarity of ‘Ua Huka to the southeastern
islands.
Mean measure of divergence analysis of cranial discrete
traits as well as RMET/NORM analyses of craniometric
variables reveal that differences exist between the islands
of the northwestern and southeastern Marquesas Islands.
These results support previous research that documented
linguistic and cultural differences between these regions
of the archipelago. However, the results indicate that ‘Ua
Huka, an island traditionally included in the northwestern Marquesas Islands, has an affinity to the southeastern
Marquesas Islands, possibly due to its pivotal position as
a waypoint in the Marquesas Island interaction sphere.
Am J Phys Anthropol 121:319 –331, 2003.
Osteological studies of the prehistoric Polynesians
have focused primarily on the location of their ancestral home and relationship to other Oceanic populations (e.g., Houghton, 1989; Howells, 1970; Pietrusewsky, 1976, 1977, 1983, 1984, 1990b,c, 1994).
Although large collections of Pacific osteological material are available in museums throughout the
world, questions concerning the variation of local
populations have largely been ignored, with a few
notable exceptions (Easter Island: Chapman, 1993;
Chapman and Gill, 1997; Gill and Owsley, 1993;
Stefan, 1999; Tigner and Gill, 1986; Zimple and Gill,
1986; Hawai‘i: Pietrusewsky, n.d.; New Zealand and
the Chatham Islands: Buranarugsa and Leach,
1993; Harlow, 1979, 1994; Houghton, 1980; Scott,
1893; Shima and Suzuki, 1967). Giles (1973, p. 400)
raised this point over two decades ago, suggesting:
“Osteological studies all seem to look through the
wrong end of the . . . telescope: none has been concerned with what one might call local populations.”
However, his comment has not yielded the desired
effect, and the search for the ancestral homeland of
the Polynesians continues in lieu of more detailed
analyses of local populations. This is surprising, be-
cause one of the observed trends in biological anthropology is the analysis of populations at the local
level (Buikstra et al., 1990).
Eastern Polynesia is an ideal region for the study
of population history because of the relative ease in
defining specific populations and their general isolation from non-Polynesian populations. Indeed,
Houghton (1980, 1989, 1990, 1991a, b) and Howells
(1979) described the region as biologically homogeneous, with minimal external gene flow limited primarily to Western Polynesia. In addition, the populations of the eastern Pacific share a common and
©
2003 WILEY-LISS, INC.
©
2003 Wiley-Liss, Inc.
Grant sponsor: Kon-Tiki Museum, Oslo.
*Correspondence to: Vincent H. Stefan, Department of Anthropology, Lehman College, CUNY, 250 Bedford Park Blvd. West, Bronx,
NY 10468. E-mail: vstefan@lehman.cuny.edu
Received 30 April 2001; accepted 29 January 2003.
DOI 10.1002/ajpa.10287
320
V.H. STEFAN AND P.M. CHAPMAN
recent ancestry (Bellwood, 1989; Green, 1993; Hagelberg and Clegg, 1993; Jennings, 1979; Marck, 1996;
Rolett, 1993), providing another advantage for the
study of population history within the region. There
are also relatively well-defined environmental differences. For example, the islands of the Tuamotu
Archipelago are primarily atolls, while the Society
Islands are high, volcanic islands, representing the
extremes of a broad spectrum of temperatures and
microclimates. Given that the Polynesian islands
have differing climates and resources, it may be
possible to discern specific environmental factors
influencing human biology. The assessment of population history focuses on relative similarities and
differences, either through the use of anthropological genetics which examines the factors affecting
genetic similarities between populations, or the use
of osteological studies examining the morphological
similarities between populations. Because osteological morphology is caused or influenced by either
genetic and/or environmental factors (Harpending
and Jenkins, 1973; Relethford, 1996), it is an appropriate means for studying Pacific populations and
their history.
This paper investigates the cranial morphology
and population history of one Eastern Polynesian
island group, the Marquesas Islands. The possible
division of the Marquesas population into northwestern and southeastern subpopulations is examined from a biological perspective. This study will
utilize both cranial discrete and metric data to evaluate the similarities and dissimilarities of prehistoric populations from various islands within the
Marquesas Islands. Given the similar climates and
environments of the islands within this group (Freeman, 1951), any differences observed between populations could be due to other evolutionary forces
such as isolation, genetic drift, and/or nonrandom
mating. The purpose of this study is to document
any interisland/intraarchipelago cranial morphological variation, in order to correlate this variation
with other aspects of Marquesas Islands culture and
population history.
BACKGROUND
Marquesas islands
Located approximately 1,400 km from Tahiti, the
Marquesas Islands are comprised of two distinct
groups: the northwest Marquesas and the southeast
Marquesas. The archipelago’s 10 main islands are
Ha៮ Tutu, ‘Ei ‘A‘o, Nuku Hiva, ‘Ua Huka, and ‘Ua Pou
(northwest Marquesas); Fatu Huku, Hiva ‘Oa,
Tahuata, Moho Tani, and Fatuiva (southeast Marquesas) (Freeman, 1951; Hughes and Fischer, 1998)
(Fig. 1). Linguistic studies (Green, 1966; Lavondès
and Randall, 1978) suggest a dialect differentiation
between the northwestern and southeastern islands
of the Marquesan archipelago. Lavondès and Randall (1978) noted regional differences in the names
of common fish utilized in these two regions.
Fig. 1. Marquesas Islands. Dashed line demarcates traditional division of archipelago into northwestern and southeastern
island groups.
Lavondès and Randall (1978) examined the Marquesan names for 83 types of fish from Nuku Hiva,
‘Ua Pou , ‘Ua Huka, Hiva ‘Oa, and Fatuiva. Some
general observations were made that were consistent with a previous identification of two regional
dialects (Biggs, 1971). Some observations included
phoneme changes, where the northwestern Marquesan (MQN) dialect used an /h/ instead of the /f/ used
in southeastern Marquesan (MQS), and the use of
/k/ in MQN in place of /n/ in MQS. Their conclusions
were that Nuku Hiva and ‘Ua Pou, in addition to ‘Ua
Huka, are in the northwestern group, and Hiva ‘Oa
(with Tahuata) and Fatuiva are in the southeastern
group. However, ‘Ua Huka also demonstrates a degree of affinity with the southeastern islands that
the other northwestern islands do not have
(Lavondès and Randall, 1978).
Archaeological studies also suggest that some differences in material culture existed between the
northwestern and southeastern islands (Handy,
1923; Linton, 1923, 1925; Sinoto, 1979), though as a
whole the material culture was rather uniform. In
an exhaustive study of the Marquesas material culture, Linton (1923, p. 445) concluded that “most of
these differences seem to have consisted in a greater
or less stressing of features common to the whole
culture rather than in a clear-cut absence or presence of traits.” Sullivan (1923c) further believed that
in view of the trade and intercourse that was known
to exist in the Marquesas during prehistoric times,
the fact that regional differences were still evident
at the time of his survey indicated to him that in
MARQUESAN CRANIAL VARIATION
prehistoric times, the local distinctions would have
been more pronounced. Regional differences were
noted in the design and construction of houses, the
style of dress and ornamentation, methods of stone
construction, design of ceremonial structures and
sculptures, sociopolitical structure, and in the handling and disposal of the dead (Linton, 1923). Handy
(1923, p. 21) generalized the cultural differences
between the northwestern and southeastern Marquesas Islands in the following major features: 1)
the northwestern Marquesans built with large
stones, and erected large house platforms, ceremonial structures, and dance areas; and 2) the southeastern Marquesans had a more highly developed
skill in the carving and sculpturing of stone and the
cutting of stone blocks, and the art of wood carving
and tattooing was centered in the south, which then
spread northward. Recent archaeological and cultural investigations of the Marquesas Islands indicate that many of these differences arose predominantly after the end of the Developmental Period
(AD 1300) (Rolett, 1989). A more detailed summary
of the local differences in the material cultures and
practices of the Marquesas Islands can be found in
Linton (1923, p. 445– 446)
Anthropometry studies by early nineteenth century physical anthropologists also identified physical differences between Polynesian populations.
These studies identified what they believed to be
three racial elements: a dolichocephalic Negroid
race, a dolichocephalic or mesocephalic race which
showed Caucasic affinities, and a brachycephalic
race with Mongoloid affinities which Sullivan
(1923b) called Indonesian. With regards to northwestern and southeastern Marquesans, Sullivan
(1923a) identified an “Indonesian physical type” in
the northwest and a “Polynesian physical type” in
the southeast. Handy (1923, p. 21) characterized the
southeastern Marquesans as having “longer heads,
curlier hair, shorter stature, and lighter skin.”
Other than these early observations, there is an
overall paucity of information on the interisland
morphological and anthropometric variation of the
Marquesas Islanders, due to a lack of research and
investigation by modern researchers.
As with the other islands of French Polynesia,
very little osteological information exists for the
Marquesas Islands. Pietrusewsky (1976) examined
archaeologically excavated skeletons from the Hane
Dune site on ‘Ua Huka. His report included cranial
and postcranial measurements and observations,
dental observations, and determination of paleopathologies. His analysis of 42 individuals yielded
one of the best archaeologically provenienced collections of an East Polynesian skeletal series. Multivariate analysis demonstrated that the Hane sample associates loosely with other East Polynesian
samples. Until this study, Pietrusewsky (1976) was
the only study of a Polynesian population that focused solely on the Marquesas Islands and that eval-
321
uated the morphology of individuals inhabiting
those islands.
Use of cranial metric and discrete traits
in population studies
A major difficulty in the analysis of prehistoric
populations or subpopulations is that they are often
poorly defined or represented in the archaeological
record. This obstacle is problematic to confront and
resolve. Ethnic groups, cemetery samples, and skeletal samples have often been, correctly or incorrectly, equated with biological populations (Cadien
et al., 1974). Because it is assumed that the skeletal
sample represents a sequence of related individuals,
these researchers suggest that skeletal samples can
be considered skeletal “lineages” reflecting the action of microevolutionary forces over time. However,
the time depth of the study sample could determine
the validity of this “sequence of related individuals”
assumption. If the sample encompasses only several
generations, the assumption may hold true, but if
the sample encompasses dozens of generations, the
existence of long-term gene flow could have significantly altered the pattern of relatedness (Konigsberg, 1990; Relethford, 1999). With the existence of
long-term gene flow, a population could display
greater affinity to the populations contributing
genes than to earlier generations of the same population prior to the onset of gene flow.
When analyzing past population structure, the
element of time within cemetery skeletal samples
makes analyses more difficult. Konigsberg (1987)
demonstrated that the genetic variance (measured
with Wright’s FST) estimated for several combined
generations is equivalent to the average of the genetic variance of each discrete generation, and noted
that even though a certain amount of phenotypic
variation within a skeletal sample is due to noncontemporaneous individuals, between-site analyses
should not be affected by within-site variation.
Therefore, skeletal samples or lineages can be considered equivalent to a biological population statistically.
Due to the fact that many studies investigating
the population biology of past peoples utilize skeletal samples of those prehistoric populations, the genetic variance of those populations cannot be directly measured. It was previously discussed that
phenotypic variation is a reflection of genotypic variation within groups, and this relationship is considered consistent among groups. Because genotypic
distances between populations cannot be calculated
due to the unavailability of their underlying genotypic variance structure, a viable solution is to use
phenotypic distances, calculated from population
phenotypic variances, as estimates of genetic relatedness among populations. Therefore, phenotypic
distances can be interpreted within a population
genetics framework because they are directly proportional to the actual genetic distances among populations in a consistent way, assuming that herita-
322
V.H. STEFAN AND P.M. CHAPMAN
bility is constant across populations (WilliamsBlangero and Blangero, 1989).
The literature is replete with the discussion of the
utility of cranial phenotypic variation (metric and
discrete) to represent genotypic variation (e.g.,
Berry and Berry, 1967; Berry, 1963, 1964; Cheverud, 1988; Grünenberg, 1963; Konigsberg and Ousley, 1995; Molto, 1983; Relethford and Blangero,
1990; Saunders, 1989; van Vark and Schaafsma,
1992; Williams-Blangero and Blangero, 1989), the
heritabilities of various traits (e.g., Bocquet-Appel,
1984; Byard et al., 1984; Cheverud, 1988; Cheverud
and Buikstra, 1982; Cheverud et al., 1979; Corruccini, 1974, 1976; Devor et al., 1986a,b; Donnelly et
al., 1998; Droessler, 1981; Howells, 1953; Kohn,
1991; Konigsberg and Ousley, 1995; Molto, 1983;
Najem, 1997; Ossenberg, 1977; Relethford, 1994;
Relethford and Harpending, 1994; Self and Leamy,
1978; Sjøvold, 1984,1986; Susanne, 1977; Susanne
et al., 1983; Vandenberg, 1962), and the population
genetics methodology developed to evaluate relatedness among populations. Therefore, a detailed discussion will not be provided here.
The effective use of both craniometric and discrete
traits in the investigation of prehistoric Polynesian
relationships, both intraisland and interisland, has
been repeatedly demonstrated. During the last 30
years, several researchers have been at the forefront
of Pacific bioanthropological research, including
Brace and Hunt (1990), Brace et al. (1989, 1990,
1991), Hanihara (1992, 1996, 1997), Chapman
(1993, 1998), Chapman and Gill (1997, 1998), Howells (1970, 1973, 1979, 1989, 1990, 1995), Katayama
(1987, 1990), Tagaya and Katayama (1988), Pietrusewsky (1971, 1976, 1977, 1983, 1984, 1988,
1990a,b, 1992, 1994, 1996, 1997), Pietrusewsky and
Ikehara-Quebral (2000), Pietrusewsky et al. (1992),
Stefan (1999, 2000), and Stefan et al. (1998). Each of
these researchers employed statistical techniques
designed to identify phylogenetic relationships, with
several having designed their analyses within a population genetics framework. This study further demonstrates the utility of cranial metric and discrete
data in the assessment of intraisland relationships.
MATERIALS AND METHODS
Three island samples were utilized in this study to
represent the Marquesas Islands regions: Fatuiva, a
combined Tahuata/Hiva ‘Oa representing the southeastern region, and Nuku Hiva representing the
northwestern region. Cranial nonmetric and metric
data were collected only from adult individuals, as
evidenced by a fused sphenooccipital sychondrosis
(Krogman and Iscan, 1986), and only the most complete crania were selected for data collection. Age
determination beyond that of “adult” was not
deemed necessary for the analyses to be conducted.
The sex of each cranium was determined utilizing
standard anthropological techniques (Bass, 1995;
Buikstra and Ubelaker, 1994).
The Marquesas Islands samples utilized in this
study are curated at the Bernice P. Bishop Museum
(BPBM, State Museum of Natural and Cultural History, Honolulu, HI); the American Museum of Natural History (AMNH, New York, NY); the Natural
History Museum (NHM, London, UK); and the
Laboratoire d’Anthropologie Biologique, Musée de
l’Homme (MH, Paris, France). The crania curated at
the BPBM were collected by the Bayard Dominick
Expedition in 1920 –1921, and by Y.H. Sinoto in
1964 –1965 from the Hane dune Site on ‘Ua Huka.
The level of the Hane Dune site from which human
remains were recovered, Level IV, has been dated to
AD 1110 ⫾ 110 –1635 ⫾ 90 (Sinoto, 1970). The crania at AMNM were collected by H.L. Shapiro during
the Templeton Crocker Pacific Expedition in 1934
and possibly during his participation in the B.P.
Bishop Museum Tuamotu Expedition in 1929. The
crania at the MH were collected by C.L. Clavel while
serving as medical officer on the French sloop Hugon
in 1881–1882. Exact provenience and dates for these
specimens are not available. However, it is believed
that these crania represent pre-European contact
individuals.
It should be noted that the authors collected their
data independent of one another and at different
times. Additionally, each author examined the same
crania curated at NHM and MH, but only one of us
(V.H.S.) examined the crania curated at BPBM and
AMNH. This explains the discrepancies that will be
observed in sample sizes from the various Marquesas Islands.
Cranial discrete traits
Cranial discrete trait data were collected for 28
traits, from a total of 101 adult crania, obtained from
various islands within the Marquesas Islands. This
study incorporated discrete traits of the cranial
vault and face as defined by Berry and Berry (1967),
Olivier (1969), Ossenberg (1969, 1970), and Pardoe
(1984). Detailed assessment and scoring methodologies for these traits are discussed in these references
as well. To avoid or minimize interobserver error, all
the cranial discrete data used in this study were
collected by one of us (P.M.C.). Sixteen of 28 traits
examined were analyzed using the mean measure of
divergence (MMD). The traits used are listed in Table 1 (for 10 of the 16 traits, data were collected for
both the right and left sides, which accounts for the
26 traits listed in Table 1). The remaining 12 traits
were eliminated due to phenotypic homogeneity (absolutely no variation), lack of replicability, or the
possibility of significant environmental influence
upon the attribute (for more information, see Chapman, 1998). The traits analyzed are similar to those
in other studies of a similar nature (Berry, 1974,
1975; Konigsberg et al., 1993; Molto, 1983; Ossenberg, 1969, 1970, 1976; Pardoe, 1984; Pietrusewsky,
1977, 1983, 1984; Prowse and Lovell, 1996; Sjøvold,
1984,1986).
323
MARQUESAN CRANIAL VARIATION
TABLE 1. Discrete trait frequencies for Marquesas Islands samples
Fatuiva
Nuku Hiva
Tahuata/Hiva ‘Oa
Trait
F
M
Total
F
M
Total
F
M
Total
Lambdoidal wormians (right)
Lambdoidal wormians (left)
Epactal ossicle
Parietal notch bone (right)
Parietal notch bone (left)
Asterion ossicle (right)
Asterion ossicle (left)
Mastoid ossicle (right)
Mastoid ossicle (left)
Epipteric ossicle (right)
Epipteric ossicle (left)
Sagittal ossicle
Divided hypoglossal canal (right)
Divided hypoglossal canal (left)
Accessory lesser palatine foramina (right)
Accessory lesser palatine foramina (left)
Infraorbital suture (right)
Infraorbital suture (left)
Accessory malar foramina (right)
Accessory malar foramina (left)
Palatine torus
Sagittal sulcus (right-branching)
Parietal foramen (right)
Parietal foramen (left)
Elliptic palate
Pharyngeal fossa
4/6
4/6
2/6
0/7
3/7
0/7
1/7
1/7
1/6
0/7
2/7
3/6
1/6
2/6
6/7
5/7
3/7
2/7
4/7
5/7
1/7
6/7
6/7
4/7
2/7
0/6
12/19
12/19
0/19
1/19
5/18
5/18
4/19
3/18
3/18
2/19
2/19
7/15
1/19
1/19
13/18
12/18
7/19
3/19
17/18
15/18
1/19
12/19
13/19
8/19
0/18
2/19
16/25
16/25
2/25
1/26
8/25
5/25
5/26
4/25
4/24
2/26
4/26
10/21
2/25
3/25
19/25
17/25
10/26
5/26
21/25
20/25
2/26
18/26
19/26
12/26
2/25
2/25
9/10
7/10
0/10
2/10
1/10
0/10
1/10
0/10
0/10
1/10
0/10
2/9
1/10
1/10
6/9
4/9
4/10
1/10
7/9
7/10
0/10
8/10
9/10
7/10
1/10
2/10
13/16
14/17
0/18
2/20
1/20
2/20
1/20
1/20
2/20
1/20
1/20
7/14
1/19
2/19
14/19
14/20
3/20
2/19
14/20
17/20
4/19
17/20
15/19
14/19
1/20
6/20
22/26
21/27
0/28
4/30
2/30
2/30
2/30
1/30
2/30
2/30
1/30
9/23
2/29
3/29
20/28
18/29
7/30
3/29
21/29
24/30
4/29
25/30
24/29
21/29
2/30
8/30
9/10
9/10
0/10
4/10
3/10
4/10
2/10
2/10
2/10
2/10
1/10
3/7
0/10
0/10
4/10
5/8
6/10
6/10
8/9
6/10
2/9
9/10
8/10
6/10
0/9
3/10
7/9
6/9
1/9
2/10
1/10
3/9
1/10
3/9
3/10
0/10
1/10
4/9
0/9
0/9
7/9
6/10
4/10
3/10
7/8
9/10
0/10
7/10
7/10
8/10
1/10
3/9
16/19
15/19
1/19
6/20
4/20
7/19
3/20
5/19
5/20
2/20
2/20
7/16
0/19
0/19
11/19
11/18
10/20
9/20
15/17
15/20
2/19
16/20
15/20
14/20
1/19
6/19
Most of the traits are bilateral, i.e., they can be
present on either or both the left and right sides.
There are a number of ways of dealing with bilateral
variables (Green et al., 1979; Korey, 1980; Saunders,
1989), each of which has its advantages. The three
most common ways of treating these data are: 1)
recording the trait as present if it is present on at
least one side of the individual (sampling by individual); 2) treating each side as a separate variable;
and 3) randomizing the side used for each individual. The first and third methods give equal weight to
unilateral and bilateral variables, whereas the second gives double weight to the bilateral variables,
with each side treated separately. Saunders (1989)
indicateD that there is a strong, but not perfect,
positive correlation between side interdependence,
suggesting that the second method artificially biases
the results. However, sampling by individual (method 1) increases the attribute frequency within each
population. This can create problems with statistical
analyses using angular transformations of the frequencies if the frequencies are close to 95% present
or absent. Therefore, this study uses method 3, randomizing the side used for each individual. This
method ensures that bilateral attributes are given a
weight equal to that of unilateral attributes without
inflating frequencies. For fragmentary remains
when data from both sides are not available, the side
for which information is available is used.
The mean measure of divergence (MMD) examines levels of similarity and difference between different samples and produces a distance measure.
The MMD statistic is a summed-difference-of-means
test of variable frequencies between two samples.
The frequencies undergo angular transformation to
obtain independence of variance (Pardoe, 1991, p. 5).
The resulting proportional difference is then divided
by a standard error with correction for sampling
variance, and then averaged for all variables analyzed. The MMD scores are then divided by the
standard deviation to produce standardized MMD
scores (de Souza and Houghton, 1977).
In order to ensure consistency in sample size, random samples were selected from the locations with
the largest number of crania (Nuku Hiva, Fatuiva,
and Tahuata/Hiva ‘Oa), thereby limiting the actual
number of crania included in this study (Tables 1
and 3). In order to create consistent sample sizes,
ranging from 19.4 –20.2, we combined neighboring
Tahuata and Hiva ‘Oa. Geographically these islands
are extremely close (approximately 5 km apart), indicating no major geographical barrier to gene flow.
Due to the demonstrable lack of significant differences between the sexes, male and female crania
were combined into one sample. Additional information concerning sample acquisition and composition
may be found in Chapman (1998).
Chapman (1998) illustrated that the MMD results
are significantly affected by sample size. Previous
nonmetric analyses of Polynesian populations (including Chapman and Gill, 1998; Katayama, 1987;
Pietrusewsky, 1977) using MMD may have produced biased results, given that the comparative
samples all had significantly varying sample sizes,
reflecting the influence of sample sizes in addition to
actual biological relationships. Therefore, to ensure
unbiased results, the sample sizes for each location
included in this study are consistent with one another, with the crania included chosen at random.
324
V.H. STEFAN AND P.M. CHAPMAN
TABLE 2. Cranial sample sizes for Marquesas Islands
craniometric analyses
Location
Female
Male
Total
Fatuiva
Nuku Hiva
Tahuata/Hiva ‘Oa
’Ua Huka
9
39
14
12
20
60
16
10
29
99
30
22
Craniometric traits
Cranial metric data were collected from a total of
210 adult crania from various islands within the
Marquesas Islands. This study incorporated measures of the cranial vault, face, and interorbital region, as defined by Bass (1995), Gill et al. (1988),
Howells (1973), and Martin and Saller (1957). The
list of 49 standardized measurements collected (with
their abbreviations) is provided in the Appendix. To
avoid or minimize interobserver error, all craniometric data used in this study were collected by one
of us (V.H.S.). Due to insufficient provenience information, only 185 individuals were included in this
initial data analysis. As a result of the state of preservation of specimens examined, the initial dataset
possessed 10.8% missing data, with 8,086 of 9,065
possible data points present. To reduce the percentage of missing data, five specimens were removed
from the dataset, and three variables (STB, MXB,
and MXS) were removed from the dataset due to
excessive missing data. This resulted in the reduction of missing data to 6.1%, with 7,774 of 8,280
possible data points present. The remaining 180 individuals (Table 2) and 46 variables were then used
in further multivariate analyses.
Multivariate analysis procedures require that
there be no missing data. Every observation must
have a value for each variable entered into the analysis, or else the observation is eliminated. Deleting
observations results in large amounts of information
being lost, and the remaining completely observed
cases would be unrepresentative of the population
that they were intended to reflect. The problem of
missing data needs to be addressed in order to optimize the number of observations utilized from each
sample. Considerable attention has been given to
the problem of missing data estimation, along with
the most appropriate procedures for estimating
missing data (e.g., Droessler, 1981). Traditionally,
three options have been available: substitution of
group means, substitution of grand means, or prediction of missing measurements by means of multiple regression. These alternatives have their associated advantages and disadvantages (Droessler,
1981, p. 80 – 84; Schafer, 1997).
This research utilizes the NORM 2.01 statistical
program (Schafer, 1999) for multiple generation of
incomplete multivariate datasets and techniques, as
described by Schafer (1997). The resulting datasets
are used to assess the validity in combining point
estimates and covariance matrices to be utilized in
the intragroup variability analyses discussed below.
These methods will minimize the problems inherent
in missing value estimations discussed above.
Detailed information on the computational methodologies utilized by NORM and the underlying statistical/mathematical foundations can be found in
Schafer (1997, 1999) and Rubin (1987).
For this study, each individual variable was corrected for size and sex, using the Z-score standardization techniques discussed by Howells (1973,
1989), following the estimation of missing values.
This method is desirable for removing the effects of
sexual dimorphism while retaining intrapopulation
variation. Samples could then be considered without
reference to their sex, thereby allowing combined
sex samples and effectively increasing comparative
sample sizes. This and similar procedures for the
removal of size and sex effects are now standard
procedures in studies of human phenotypic variation
(Key, 1983; Key and Jantz, 1990; Konigsberg and
Blangero, 1993; Relethford and Harpending, 1994;
Williams-Blangero and Blangero, 1989).
A stepwise discriminant function analysis was
conducted on the Z-score standardized data to determine which variables would provide the best discrimination between samples (SAS Institute, 1990).
The analysis revealed seven variables that best discriminated the samples (WCB, ZOS, EKB, BBH,
NLB, ALB, and ASB). The RMET analyses will be
conducted using both the complete dataset of 46
variables and the seven variables identified in the
stepwise discriminant function analysis, to assess
any difference that may be present due to the variables utilized.
This research utilized three imputed datasets
(justification discussed below), which were first corrected for size/sex effects (discussed above). Each
imputed size/sex-adjusted dataset was then analyzed with the RMET 4.0 program to produce unbiased, estimated genetic distance (D2) values and
their standard errors (Relethford and Blangero,
1990; Relethford et al., 1997). Though not exactly
equivalent to Mahalanobis distances, the estimated
genetic D2 values are proportional if all populations
are weighted equally. An equal population size
weighting scheme was utilized in this analysis. The
RMET program allows for the assignment of trait
heritabilities which produce conservative estimations of population distance, based on phenotypic
traits that are not under 100% genetic control. An
average heritability value of h2 ⫽ 0.55 was utilized
in this analysis (Relethford, 1994; Relethford and
Harpending, 1994). The D2 values were corrected for
bias, using a standard bias correction provided in
the program (Relethford et al., 1997).
The D2 values and associated standard errors calculated from the RMET analyses from the three
imputed datasets were then analyzed via the “MI
(Multiple Imputation) Inference: Scalar Estimands”
method in NORM 2.01. This method combines the
results (estimates and standard errors) from individual analyses into a single set of results (Rubin,
MARQUESAN CRANIAL VARIATION
TABLE 3. Standardized MMD scores for Marquesas Islands1
Location
n
Nuku
Hiva
Fatuiva
Tahuata/Hiva
‘Oa
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
20.2
19.7
19.4
0.000
1.850
1.491
0.000
0.259
0.000
n ⫽ total sample size. Sample size for each attribute is counted
separately, and then averaged to determine overall sample size
for each location.
1
1987; Schafer, 1997). When performing a multipleimputed analysis, the variation in results across the
imputed datasets reflects statistical uncertainty due
to missing data (Rubin, 1987). Rubin (1987) shows
that the efficiency of an estimate based on m imputations is approximately
冉
1 ⫹
␥
m
冊
⫺1
where ␥ is the estimated rate of missing information, a value calculated by NORM (for derivation of
␥, see Rubin, 1987). The estimated rate of missing
information is the relative increase in variance due
to nonresponse. The rate of missing information,
along with the number of imputations (m), determines the relative efficiency of the MI inference. The
percent efficiency achieved for the estimated results
was in excess of 98% (␥ ⬵ 0.061; m ⫽ 3).
RESULTS
Cranial discrete traits
The cranial nonmetric analysis focused on three
groups within the Marquesas Islands: the Fatuiva
and Tahuata/Hiva ‘Oa in the southeast, and the
Nuku Hiva in the northwest. The discrete trait frequencies for the samples are presented in Table 1.
The standardized MMD scores are displayed in Table 3, showing the general patterns of similarity.
Examination of the MMD scores matrix indicates
that Fatuiva is more similar to Tahuata/Hiva ‘Oa
than either is to Nuku Hiva. Statistically significant
MMD scores are conventionally those with values
greater than 2.0 (de Souza and Houghton, 1977).
None of the MMD scores were statistically significantly different from zero, yet the scores for the
Nuku Hiva-Fatuiva (1.850) and Nuku HivaTahuata/Hiva ‘Oa (1.491) pairings were nearly significant.
Craniometric traits
The cranial metric analysis focuses on the same
three island populations used in the analysis of cranial nonmetric traits. The averaged unbiased, estimated genetic D2 values and standard errors are
presented in Table 4. The values clearly indicate
that the Nuku Hiva sample was nearly equally divergent from the Fatuiva and Tahuata/Hiva ‘Oa
samples, while the Fatuiva and Tahuata/Hiva ‘Oa
samples were relatively close to each other. These
results support those obtained by cranial discrete
325
trait analyses. Each unbiased, estimated genetic D2
value was tested to determine if the value was significant using the Z-distribution test method, in
which the distance value is divided by its standard
error. The unbiased, estimated genetic D2 values for
the Nuku Hiva-Fatuiva (0.1328, 46-variable analysis; 0.2726, seven-variable analysis) and the Nuku
Hiva-Tahuata/Hiva ‘Oa (0.0813, 46-variable analysis; 0.2225, seven-variable analysis) pairings were
stastically significant, while the Fatuiva-Tahuata/
Hiva ‘Oa (0.0433; 0.0427) pairings were not statistically significantly different from zero, using the Zdistribution test method. The D2 value results
clearly indicate a greater difference between the
Nuku Hiva sample and the Fatuiva and Tahuata/
Hiva ‘Oa samples, than between the Fatuiva and
Tahuata/Hiva ‘Oa samples.
The results of the 46-variable analysis and the
seven-variable analysis provide similar patterns in
the similarity/dissimilarity of the Marquesas Islands samples analyzed. Though the unbiased, estimated genetic D2 values differ in terms of absolute
magnitude, they are quite similar in their relative
magnitudes, patterning, and significance (Table 4).
There does not appear to have been a loss of diagnostic information through the reduction of the
dataset from 46 variables to seven variables.
The relationship of ‘Ua Huka to northwest and
southeast Marquesas Island groups
Conventionally, ‘Ua Huka has been included with
the northwest Marquesas Island group. Comparisons between the archaeological material from the
Hane Site (‘Ua Huka) and the Ha‘atuatua (Nuku
Hiva) demonstrated similarity and continuity in culture on those two islands (Rolett, 1993), and were
the principal sources for establishing the northern
Marquesas cultural sequence (Sinoto, 1970). The
earliest colonization of the Marquesas Islands appears to have occurred in the northwest island
group, with subsequent dispersals into the southeast island group, yet both island groups appear to
have possessed a basically homogeneous material
culture (Rolett, 1993; Sinoto, 1970). The observed
cultural similarities between ‘Ua Huka and Nuku
Hiva might presume a correlate in the physical similarity of the islands’ inhabitants.
The cranial sample from ‘Ua Huka was not included in the discrete trait analysis due to insufficient sample size (n ⫽ 9). As discussed previously,
MMD analyses are susceptible to bias due to small
and unequal sample sizes between groups (Chapman, 1998). In order to maintain consistency, only
groups with sample sizes of 20 or more were included in the cranial discrete analyses. Additionally,
the samples analyzed were maintained at n ⫽ 20.
However, a sample from ‘Ua Huka was included in
analyses utilizing craniometric data (n ⫽ 22). The
methods used in the craniometric analyses take into
account differing sample sizes, and make the necessary bias corrections (Relethford et al., 1997).
326
V.H. STEFAN AND P.M. CHAPMAN
TABLE 4. Estimated genetic distance (D2) value estimates and standard errors for Marquesas Islands1
Location
n
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
97
29
30
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
2
0.2225 (0.0929)2
0.0427 (0.0762)
0.2726 (0.0718)
0.1328 (0.0270)3
0.0813 (0.0146)3
0.0433 (0.0185)
1
n ⫽ total sample size. Standard errors in parentheses. Values resulting from “MI (Multiple Imputation) Inference: Scalar Estimands”
method that combines results (estimates and standard errors) from individual analyses into a single set of results. Upper right
triangle, seven-variable analysis; lower left triangle, 46-variable analysis.
2
Significant estimated genetic D2 value: Z(0.05, 7) ⫽ 2.365.
3
Significant estimated genetic D2 value: Z(0.05, 46) ⫽ 2.015.
TABLE 5. Estimated genetic distance (D2) value estimates and standard errors for Marquesas Islands1
Location
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
’Ua Huka
n
97
29
30
22
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
2
0.1223 (0.0168)3
0.0732 (0.0200)3
0.0829 (0.0182)3
0.2577 (0.0936)
0.0713 (0.0196)3
0.1175 (0.0840)
0.2055 (0.0975)
0.0443 (0.0831)
2
‘Ua Huka
0.2251 (0.0834)2
0.1608 (0.2380)
0.0607 (0.0525)
0.0431 (0.0189)
n ⫽ Total sample size. Standard errors in parenthesis. Values resulting from “MI (Multiple Imputation) Inference: Scalar Estimands”
method that combines results (estimates and standard errors) from individual analyses into a single set of results. Upper right
triangle, seven-variable analysis; lower left triangle, 46-variable analysis.
2
Significant estimated genetic D2 value: Z(0.05, 7) ⫽ 2.365.
3
Significant estimated genetic D2 value: Z(0.05, 46) ⫽ 2.015.
1
The results of the analyses, including the ‘Ua
Huka sample, are presented in Table 5. Contrary to
expectations, it is evident that the ‘Ua Huka sample
has the closest similarity to the combined Tahuata/
Hiva ‘Oa sample from the southeast Marquesas Islands (0.0431; 0.0607), with the unbiased, estimated
genetic D2 value estimates for the ‘Ua Huka-Nuku
Hiva (0.0829; 0.2251) pairing being statistically significantly different from zero. These results may
indicate a level of intraisland interaction focused on
‘Ua Huka that is more complex then previously documented.
Several linguistic and archaeological peculiarities
have been noted on ‘Ua Huka that indicate a southeastern Marquesas Islands influence. It was noted
that the term “marae” was used to describe an entire
religious structure on Nuku Hiva, ‘Ua Pou, and
other northwest Marquesas Islands, while the word
“me’ae” was more commonly used in the southeast
Marquesas and ‘Ua Huka (Green, 2000, p. 86; Linton, 1925, p. 31). In an archaeometric analysis of
Marquesan lithic artifacts manufactured from phonolite and recovered from sites on ‘Ua Huka, Nuku
Hiva, and Tahuata (Rolett et al., 1997), researchers
concluded that there was a single source for the
phonolite material for these artifacts that could not
be positively located, but was likely from a quarry on
‘Ua Pou (northwest Marquesas) or Tahuata (southeast Marquesas). Whether the phonolite material
originated from a northwest or southeast Marquesas
quarry does not negate that fact that the artifacts
manufactured from this material were found on islands in the northwest and southeast Marquesas,
indicating material culture exchange in the island
group. Handy (1923) earlier speculated on some sort
of linkage between Nuku Hiva and ‘Ua Huka to Hiva
‘Oa to some degree. If that linkage existed, it is not
unreasonable to conclude that there would have
been some cultural and linguistic exchange between
them.
DISCUSSION AND CONCLUSIONS
Green (1966) separates the Marquesan language
into two dialects: Northwest (NW) Marquesan and
Southeast (SE) Marquesan. Evidence of archaeological differences between these two regions is not as
clear, although there were some cultural differences
between the northern and southern islands at European contact (Handy, 1923; Linton, 1925; Rolett et
al., 1997). Rolett (1989, p. 373) suggested a “widespread continuity in material culture throughout
the Marquesas” until the end of the Developmental
Period at about AD 1300. Rolett (1989, p. 374) further stated:
The transformation of the subsistence economy of the Developmental and Expansion cultures coincides with widespread
changes in technology that occurred at roughly the same time
throughout the northern and southern Marquesas.
Sinoto (1979, p. 131) suggested that there were also
differences in “diagnostic material culture” between
the northwestern and southeastern Marquesas Islands.
The results of the cranial discrete trait and metric
study suggest a close relationship between the two
southern locations, i.e., Fatuiva and the combined
Tahuata/Hiva ‘Oa sample. However, both of these
groups have a statistically significant estimated genetic D2 score with Nuku Hiva in the north. The
close relationship between the southern locations, to
the exclusion of Nuku Hiva, is in agreement with
linguistic studies (Green, 1966; Lavondès and Randall, 1978) suggesting that a degree of differentia-
327
MARQUESAN CRANIAL VARIATION
TABLE 6. Estimated geographic distance
for Marquesas Islands1
Location
Nuku
Hiva
Fatuiva
Tahuata/Hiva
‘Oa
Nuku Hiva
Fatuiva
Tahuata/Hiva ‘Oa
’Ua Huka
108
62
20
36
100
45
1
‘Ua
Huka
Distances are in nautical miles.
tion existed between the southeast and northwest
islands in Marquesan prehistory.
The biological differences discerned here between
the northern and southern Marquesas Islands may
reflect increasing isolation between the two locations, especially after the 14th century AD (Murdoch, 2000; Rolett et al., 1997). A Pearson’s correlation analysis of the estimated genetic distances (46variable analysis, Table 4) and the estimated
geographic distances for the islands of Nuku Hiva,
Fatuiva, and the combined Tahuata/Hiva ‘Oa (Table
6) show a strong correlation (r ⫽ 0.9974, P ⬍
0.0001). This significant correlation may reflect the
effect of isolation by distance on the population affinity analyses of the cranial samples from these
islands.
With regards to ‘Ua Huka, the linguistic, archaeological, and now biological evidence indicates an
influence from the southeastern Marquesas Islands.
Its geographical position between the northwestern
and southeastern Marquesas Islands would have
served well as a waypoint in the prehistoric system
of networking in the Marquesas. Though traditionally associated with the northern Marquesas Islands
group, ‘Ua Huka’s archaeology, linguistics, and
physical anthropology clearly indicate that it was a
player in the Marquesas Islands interaction sphere.
A Pearson’s correlation analysis of estimated genetic
distances (46-variable analysis, Table 5) and estimated geographic distances for the islands of Nuku
Hiva, Fatuiva, the combined Tahuata/Hiva ‘Oa, and
‘Ua Huka (Table 6) also shows a strong correlation
(r ⫽ 0.7692, P ⬍ 0.0001), though not as strong as the
one for the previous three-group analysis. However,
when just the estimated genetic and geographic distances between the island of ‘Ua Huka and the other
islands are examined, the resulting correlation is
not significant (r ⫽ 0.5000, P ⫽ 0.4000). These
results clearly indicate that some additional evolutionary force (gene flow), in addition to isolation by
geographic distance, influenced the population affinities of the northwestern and southeastern Marquesas Islands, and produced a closer association between the island of ‘Ua Huka and the southeastern
Marquesas Islands group, than with the northwestern Marquesas Islands group with which it is traditionally included.
This paper documents the interisland cranial morphological variation following the general pattern of
the traditional subdivision of the Marquesas Islands
into northwestern and southeastern groups, a pattern which has its correlate in the variation of other
aspects of Marquesas Islands culture. Yet the results presented also indicate that a simple model of
isolation by geographic distance is insufficient to
explain all the population affinity found in these
analyses, as demonstrated by the ‘Ua Huka example. This study clearly demonstrates the utility of
biological anthropology evidence combined with archaeological and linguistic evidence to clarify the
prehistory of the Marquesas Islands and Eastern
Polynesia and/or corroborate the results obtained
from the archaeological and linguistic evidence.
ACKNOWLEDGMENTS
The authors acknowledge the following individuals for their assistance and access to the skeletal
material examined in this study: Dr. Betty Tatar,
Kevin R. Montgomery, and Valerie J. Free (Bernice
P. Bishop Museum, State Museum of Natural and
Cultural History, Honolulu, HI); Dr. Ian Tattersall,
Dr. Kenneth M. Mowbray, and Joanne Grant (American Museum of Natural History, New York, NY);
Dr. Robert Kruszynski and Dr. Chris Stringer (Human Origins Group, Natural History Museum, London, UK); Professeur André Langaney, M. Philippe
Mennecier, Dr. Miya Awazu Pereira da Silva, Mme.
Simone Jousse, and Mme. Anne-Marie Bacon (Laboratoire d’Anthropologie Biologique, Musée de
l’Homme, Paris, France); and Mme. Maeva Navarro
and Mr. Mark Eddowes (Département Archéologie
du Centre Polynésien des Sciences Humaines, Tahiti). This research was supported in part by a grant
from the Kon-Tiki Museum (Oslo, Norway) to
P.M.C. We thank Dr. Steven R. Fischer (Director,
Institute of Polynesian Languages and Literature,
Auckland, New Zealand) for his reading and commentary on the manuscript, as well as those of the
anonymous reviewers whose comments and suggestions resulted in a much-improved article.
APPENDIX A
Standardized craniofacial measurements1
Maximum cranial length
Nasion-occipital length
Maximum cranial breadth
Maximum frontal breadth
Minimum frontal breadth
Bizygomatic breadth
Basion-bregma height
Basion-nasion length
Nasion-bregma chord
Bregma-lambda chord
Nasion-prosthion height
Nasion-alveolare2
H-GOL*
H-NOL*
H-XCB*
H-XFB*
B-WFB
H-ZYB*
H-BBH*
H-BNL*
H-FRC*
H-PAC*
H-NPH*
B-NAL
1
B, Bass (1995); GH, Gill et al. (1988); H, Howells (1973); M, Martin
and Saller (1957). Asterisk indicates measurement abbreviations
from Howells (1989). Other abbreviations developed by present authors for ease of data handling and analysis.
328
V.H. STEFAN AND P.M. CHAPMAN
Biasterionic breadth
Basion-prosthion length
Bistephanic breadth
Bijugal breadth
Foramen magnum length
Left orbital height
Left orbital breadth, dacrion
Left orbital breadth, max-f
Biorbital breadth
Nasal height
Nasal breadth
Bifrontal breadth
Biauricular breadth
Minimum cranial breadth
Auricular height
Porion-bregma height
Porion-nasion3
Porion-subnasale4
Porion-prosthion5
Basion-porion height
Maxillofrontal breadth
Maxillofrontal subtense
Zygoorbital breadth
Zygoorbital subtense
Alpha chord
Alpha subtense
Simotic chord
Bimaxillary breadth
Bimaxillary subtense
Mastoid length
Mastoid width
Cheek height
Malar length, inferior
Malar length, maximum
Palatal depth
Maxilloalveolar breadth6
Maxilloalveolar length
H-ASB*
H-BPL*
H-STB*
H-JUB*
H-FOL*
H-OBH*
B-OBD
H-OBB*
H-EKB*
H-NLH*
H-NLB*
H-FMB*
H-AUB*
H-WCB*
B-AUR
B-PBH
H-NAR*
H-SSR*
H-PRR*
B-BPH
GH-MXB
GH-MXS
GH-ZOB
GH-ZOS
GH-ALB
GH-ALS
H-WNB*
H-ZMB*
H-SSS*
H-MDH*
H-MDB*
H-WMH*
H-IML*
H-XML*
M-PAD
H-MAB*
B-MAL
2
Upper facial height (Bass, 1995).
Nasion radius.
4
Subspinale radius.
5
Prosthion radius.
6
Palate breadth, external (Howells, 1973).
3
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