close

Вход

Забыли?

вход по аккаунту

?

Brief communication Correcting overestimation when determining two-dimensional occlusal area in human molars.

код для вставкиСкачать
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 145:327–332 (2011)
Brief Communication: Correcting Overestimation
When Determining Two-Dimensional Occlusal Area
in Human Molars
Christopher Schmidt,1* Stephen Ousley,2 and Molly Schmidt3
1
Department of Anthropology, University of Indianapolis, Indianapolis, IN 46227
Department of Anthropology/Archaeology, Mercyhurst College, Erie, PA 16546
3
Department of Biology, University of Indianapolis, Indianapolis, IN 46227
2
KEY WORDS
dental metrics; dental morphology; robustness index
ABSTRACT
The robustness index (RI) is determined
by multiplying dental mesiodistal and buccolingual diameters, and is used to estimate occlusal area. However,
because teeth are not rectangular its calculation consistently causes overestimations. Moreover, teeth, in particular molars, are not identically shaped so overestimations
vary. The current study seeks to determine the extent to
which overestimations are affected by tooth shape and to
improve RI’s efficacy. Initially, 120 molars were sorted
into six shape groups, which were determined by hypocone/hypoconulid expression. Three maxillary and three
mandibular shape groups were set using the Arizona
State University Dental Anthropology System. ANOVA
results determined that RI overestimations, which averaged around 20%, were not the same for each shape category. Maxillary molars with large hypocones and mandib-
ular molars with no hypoconulids were overestimated significantly less than the other molar groups. Regressionbased correction formulae were generated and applied to
the original sample. These formulae far more precisely
estimated tooth area than RI and there were no differences in estimation based upon tooth shape. A subsequent
validation study of 24 additional molars was undertaken
to test the formulae on teeth not from the original sample. Overestimation/underestimation averaged 0.5% and
was about the same for each of the tooth shape groups.
Finally, six new correction formulae were generated using
all 144 molars. The correction formulae provide, what is
termed here, an adjusted robustness index (ARI), and it
is recommended that ARI is used in future studies of
molar occlusal area. Am J Phys Anthropol 145:327–332,
2011. V 2011 Wiley-Liss, Inc.
The dental robusticity index (RI) is calculated by multiplying mesiodistal (MD) and buccolingual (BL) diameters (e.g., Goose, 1963; Wolpoff, 1971; Mayhall, 2000)
and is used to approximate two-dimensional dental surface areas, usually of molars. It has been known for
some time, however, that this measurement does not
provide an accurate surface area estimate (i.e., Wolpoff,
1971). An obvious limitation is that the RI assumes teeth
are quadrangular. Teeth are not perfect squares or rectangles, rather, they have rounded corners, and as a
result their surface areas are always overestimated with
the RI. Moreover, the more a tooth deviates from a quadrangular shape, the more overestimated the RI is likely
to be. Although dental texture and topography, 3D geometric morphometrics, microcomputed tomography, high
resolution x-ray computer tomography, and other means
of 3D study are currently being pursued by researchers
in bioarchaeology primatology and paleoanthropology
(e.g., Boughner and Dean, 2004; Scott et al., 2005, 2006;
el Zaatari, 2007; Gantt et al., 2007; Keiser et al., 2007;
Olejniczak et al., 2007; Ungar, 2007; Schaefer et al.,
2008; Zolnierz and Schmidt, 2008), analysts continue to
study 2D dental data collected with various instruments
(e.g., calipers, digitizers, and reflex microscopes) and in
a variety of manners including standard metric comparisons, 2D geometric morphometrics, and elliptic Fourier
analysis (e.g., (Hills et al., 1983; Wood and Abbott, 1983;
Wood et al., 1983; Morris, 1986; Sekikawa et al., 1988;
Calcagno, 1989; Keiser, 1990; Strait, 1993; Suwa et al.,
1994; Peretz et al., 1997; Ferrario et al., 1999; Swindler,
2002; Bailey, 2004; Hill, 2004; Alemseged et al., 2005;
Martinón-Torres et al., 2006; Gómez-Robles et al., 2007;
Moggi-Cecchi and Boccone, 2007; Pilbrow, 2007; Cuozzo,
2008; Pinhasi et al., 2008), all of which necessitate
improvement of the RI.
We propose an adjustment to correct the RI with regression formulae that reduce RI bias. The first step in this
study was to estimate to what extent RI was biased in
molars of different shapes, specifically those with large,
small, and no hypocones/hypoconulids. This step was important because if the RI overestimates were all the same,
it would not be imperative to develop a correction. Once
differences were found, the second step was to create an
adjusted index, ARI—adjusted robusticity index, via
regression that was applied to the sample from which the
formulae were derived, as well as to a validation sample.
C 2011
V
WILEY-LISS, INC.
C
MOLAR SHAPE
Although nonpathological human molars can assume a
variety of shapes, the authors were able to categorize
*Correspondence to: Christopher Schmidt, Archaeology and Forensics Laboratory, University of Indianapolis, 1400 E. Hanna Avenue, Indianapolis, IN 46227. E-mail: cschmidt@uindy.edu
Received 13 August 2010; accepted 28 December 2010
DOI 10.1002/ajpa.21511
Published online 5 April 2011 in Wiley Online Library
(wileyonlinelibrary.com).
328
C. SCHMIDT ET AL.
Fig. 1. Maxillary (above) and mandibular (below) molars with increasingly larger hypocones and hypoconulids, respectively,
from left to right. Mesial is up.
molar shapes based upon the presence and expression
of the hypocone and hypoconulid in maxillary and mandibular molars, respectively. Hypocones and hypoconulids are the most variable cusps in terms of size and
shape, although all cusps can affect overall tooth morphology. The hypocone is the distolingual cusp of maxillary molars, and it is isolated from the other cusps by
the lingual groove and oblique ridge. When the hypocone is absent, maxillary molars take on a triangular
shape. By contrast, when the hypocone is large, maxillary molars take on a rhomboidal appearance. The
hypoconulid is the most distal cusp on mandibular
molars, bordered by the distolingual and distobuccal
grooves. Mandibular molars with no hypoconulid have a
squarish occlusal outline. If the hypoconulid is strongly
expressed the outline is more oblong (Fig. 1). However,
using geometric terms to describe occlusal outline was
imprecise for setting up the molar shape groups used
herein. The following section provides details on how
the groups were defined.
MATERIALS AND METHODS
One hundred and twenty healthy molars (60 upper
and 60 lower) were sorted into six groups based upon
hypocone/hypoconulid expression. There were three maxillary (no, small, and large hypocone) and three mandibular groups (no, small, and large hypoconulid), each of
which corresponded with particular hypocone/hypoconulid scores using the Arizona State University Dental
Anthropology System (Scott and Turner, 1997). Maxillary molars with no hypocone had an ASUDAS score of 0
or 1. Those with a small hypocone scored a 2 or 3, and
those with a large hypocone scored a 4 or 5. The mandibular molars with no hypoconulid scored a 0 or 1, those
Abbreviations
ARI
BL
MD
RI
adjusted robustness index
buccolingual
mesiodistal
robustness index
American Journal of Physical Anthropology
with a small hypoconulid scored a 2 or 3, and those with
large hypoconulids scored a 4 or 5.
The sample included adult molars from osteological
collections representing Amerindian and Euroamerican
groups, the former being archeological and the latter
being both archeological and recent. The teeth were
either lightly or unworn. The sample excluded teeth
with anything more than minor dentin exposure, teeth
with extra cusps like Carabelli’s trait or protostylids,
and teeth with pathological conditions that affect shape
(e.g., fusion, occlusal hypoplasia, amelogenesis imperfecta, etc.). Most of the teeth came from very young
adults, teens, and some children who had unerupted but
completely formed adult molar crowns.
There were 20 molars per group; each was photographed with a mounted Sony Mavica digital camera in
macro mode. A bubble level was placed on the camera
body to ensure that it was level and parallel to the occlusal plane of each tooth. Great care was taken to make
sure that the widest margins in both the mesiodistal and
buccolingual planes were visible before the picture was
taken. This was accomplished by marking the greatest
curvature of the mesial, distal, buccal, and lingual surfaces with a dot. Once all of the dots were visible, the occlusal surface was considered parallel to the camera
lens. Also in the image was a scale graduated in millimeters placed at the level of the tooth’s widest diameter
(see Wood and Abbott, 1983; Wood et al., 1983; Morris,
1986; Sekikawa et al., 1988; Suwa et al., 1994; Peretz
et al., 1997; Bailey, 2004; Martinón-Torres et al., 2006;
Bailey and Wood, 2007; Moggi-Cecchi and Boccone, 2007;
Pilbrow, 2007; and Gómez-Robles et al., 2007 for similar
approaches to collecting 2D images).
The digital images were processed with ScionImage
software [which is based on NIH’s Image J (www.scion
corp.com)]. The scale in each image was used to calibrate
the measurement tool in the software. A mouse-driven
pointer was used to measure maximum length and width
diameters that were compared to measurements taken
with calipers. If the ScionImage measurements of a particular tooth differed from those taken with the calipers,
CORRECTING OVERESTIMATION IN MOLAR AREA
329
TABLE 1. Initial study: Summary of molar data for actual
area, the robusticity index (RI), and the RI overestimation
as a percentage of actual area
Group
1
2
3
4
Actual area
RI
RI overestimation
(%)
Mean
SD
80.7
11.0
101.5
15.7
25.5
5.0
Mean
SD
89.8
9.9
110.5
11.8
23.1
4.7
Mean
SD
105.7
12.2
125.3
14.2
18.6
2.9
Mean
SD
94.3
9.4
106.8
12.6
13.1
3.5
Fig. 2. Box plot of difference between the robustness index
(RI) and the actual area.
5
Mean
SD
101.4
9.4
118.2
11.6
16.5
3.4
6
Total
Mean
SD
109.7
8.1
130.6
10.3
19.1
4.2
Mean
N
SD
97.0
120
14.0
115.5
120
16.3
19.3
120
5.7
The groups are: 1: maxillary without hypocone; 2: maxillary
with small hypocone; 3: maxillary with large hypocone; 4: mandibular without hypoconulid; 5: mandibular with small hypoconulid; 6: mandibular with large hypoconulid.
N 5 20 for each group.
Mean and SD values for Actual Area and RI are in mm2.
that tooth was excluded. Once fully calibrated, the occlusal outline was traced three times and the two-dimensional occlusal area was calculated using the software.
The three areas were averaged for each tooth. The area
computed with ScionImage was termed the ‘‘Actual Area’’
and mean values were calculated for each tooth shape.
Linear regression was used to calculate correction formulae, resulting in an adjusted RI (ARI). The formulae
were derived for each tooth shape using actual area as
the dependent variable and RI as the independent variable. Tooth shape-based overestimations of uncorrected
RI and ARI were each compared using one-way ANOVAs
with a Tukey’s Post Hoc test and an a of 0.05. All statistics were computed with SPSS 16.
RESULTS
Table 1 summarizes the comparative data. The RI
overestimates the occlusal area of every molar, on average, by about 20%. Upper molars are overestimated by
an average of 22.4%; mandibular molars are overestimated by an average of 16.2%. The greatest overestimations, by about 25%, were for maxillary molars with no
hypocone, which have a triangular appearance. Maxillary molars with a small hypocone were overestimated
by an average of 23%, and maxillary molars with a large
hypocone were overestimated by 18.6%. In mandibular
molars without a hypoconulid, the RI overestimated the
actual area by 13.2%, those with a small hypoconulid
were overestimated by almost 17%, and those with a
large hypoconulid were overestimated by 19%.
Analysis of variance tests of mean RI values revealed
statistically significant differences in the percentages of
overestimation (df 5 5, F 5 3,334.18, sig 5 0.000). Specifically, maxillary molars with a large hypocone were
different from those with a small or no hypocone. A
tooth with a large hypocone is squarer and produces
smaller overestimates than the other teeth that are
more triangular. For the lower molars, a statistically
significant difference was found between those with no
hypoconulid and those with a small or large hypoconulid. Again, it was the more square-shaped teeth
(those with no hypoconulid) that were different from
the rest, which had larger hypoconulids and more elongate or oblong occlusal outlines (Fig. 2 for box plots of
RI overestimations).
Based on the ANOVA results, six linear regression
formulae were calculated, three for the maxillary and
three for the mandibular molars. Correcting the RI values reduced the average overestimation to zero with a
range of 20.5% to 0.3%. This improvement was substantial, but was generated by applying the regression
formulae to the same set of teeth from which the formulae were derived. Therefore, a validation sample of
24 additional teeth, with four teeth for each of the six
tooth shape groups, was analyzed. Again, the RI overestimation averaged 20%. After correction with the
regression formulae, the RI overestimation improved to
an average of about 0.5%, with a range from 21.1% to
2.9% (Table 2). ANOVA tests were run on the corrected
overestimations to see if they differed significantly
based upon shape. No statistically significant differences in mean bias were present, meaning that all of the
teeth were corrected to about the same extent (df 5 5,
F 5 2.07, sig. 5 0.117). For the creation of the final
correction formulae, the original and the validation
samples were combined (total N 5 144). Figures 3 and
4 illustrate the linear relationships between the actual
areas, the RI index values and the ARI values, respectively, using the combined samples.
American Journal of Physical Anthropology
330
C. SCHMIDT ET AL.
TABLE 2. Validation study: Summary data for actual area, the
adjusted robusticity index (ARI), and the ARI overestimation
Group
1
Actual area
ARI
ARI
estimation (%)
Mean
SD
75.9
14.1
77.9
13.1
2.9
2.3
Mean
SD
90.9
1.4
92.7
11.8
1.9
2.3
3
Mean
SD
102.0
13.6
102.2
11.6
0.4
3.1
4
Mean
SD
104.5
11.2
104.2
10.8
20.2
0.5
5
Mean
SD
101.4
9.8
100.4
8.4
20.8
1.5
Mean
SD
106.3
1.3
105.1
1.6
21.1
2.6
97.0
24
14.0
115.5
24
16.3
2
6
Total
Mean
N
SD
Fig. 3. Linear relationship between the actual area and
robustness index (RI). Notice the overestimation of the robustness index values and the dispersal of points. Values are in
mm2. Reference line is y 5 x.
0.5
24
2.5
The groups are: 1: maxillary without hypocone; 2: maxillary
with small hypocone; 3: maxillary with large hypocone; 4: mandibular without hypoconulid; 5: mandibular with small hypoconulid; 6: mandibular with large hypoconulid.
N 5 4 for each group.
Mean and SD values for actual area and ARI are in mm2.
Presented here are the final correction formulae:
Maxilla:
Formula 1: No hypocone (ASU 0–1): (0.685)(MD)(BL)
1 11.25
Formula 2: Small hypocone (ASU 2–3): (0.785)(MD)(BL)
1 3.13
Formula 3: Large hypocone (ASU 4–5): (0.840)(MD)(BL)
1 0.47
Mandible:
Formula 4: No hypoconulid (ASU 0–1): (0.722)(MD)(BL)
1 17.21
Formula
5:
Small
hypoconulid
(ASU
2–3):
(0.775)(MD)(BL) 1 9.84
Formula
6:
large
hypoconulid
(ASU
4–5):
(0.710)(MD)(BL) 1 16.99
It is hoped that these formulae are of value to dental
researchers who are able to score tooth shape. However,
when mining data from earlier studies it may not be possible to determine original tooth shape. Therefore, two
additional formulae are provided, one for all maxillary
molars and one for all mandibular molars. These formulae also are capable of producing a very low bias,
although they are not as precise as using the shape specific formulae above.
American Journal of Physical Anthropology
Fig. 4. Linear relationship between the actual area and the
adjusted robustness index (ARI). Notice the similarity in the
estimations for each point and the narrower distribution of
points when compared to Fig. 3. Values are in mm2. Reference
line is y 5 x.
Formula
7:
(0.861)(MD)(BL)
Formula
8:
(0.698)(MD)(BL)
‘All
maxillary
2 4.653
‘All
mandibular
1 19.061
teeth’
formula:
teeth’
formula:
DISCUSSION
Improving the precision with which tooth area is
determined should bolster all efforts directed toward an
understanding of dental size. For example, it will help to
clarify how molars have reduced in size throughout
much of the Holocene (e.g., Frayer, 1978; Calcagno,
1989). Hill (2004) found that maxillary molars reduced
in size from about 5,000 to 1,000 years ago using standard diameters. However, these measurements do not
usually include the hypocone. Currently, a study is
CORRECTING OVERESTIMATION IN MOLAR AREA
underway to score occlusal outlines among the teeth
studied by Hill so that the ARI can be used to see if the
reduction is actually greater than so far detected. In primatology, the ARI should significantly improve our
understanding of tooth size in relation to diet and body
size. Primate teeth vary significantly in shape (e.g.,
Swindler, 2002), yet studies do not always take that
shape into account. Applying the ARI to studies that use
tooth size as an indicator of dimorphism and diet or those
that seek to understand dental development and size differences between wild and captive primates should be
able to ascertain more precise molar area estimates (e.g.,
Schuman and Brace, 1954; Swindler et al., 1963; Swindler and Orlasky, 1974; Swindler et al., 1998; Hlusko and
Mahaney, 2003, 2007; Cuozzo and Yamashita, 2006;
Hlusko et al., 2007). In paleoanthropology, researchers
use dental metrics in a variety of ways, including species
determination and documenting sexual dimorphism. ARI
will benefit these pursuits because more realistic occlusal
area values will be produced, which should allow
researchers to easily revisit studies regarding the relationship of tooth size to body size (e.g., McHenry, 1988).
Finally, the ARI formulae provided here should help to
correct RI in those instances where researchers are
studying populations whose occlusal outlines are similar
to those used in this study, i.e., are not dominated by
extra cusps and odd shapes. Thus, most human populations, past and present, should be suitable candidates for
our ARI formulae. However, for those populations,
human or otherwise, whose teeth commonly have extra
cusps or have shapes that are markedly dissimilar to
those described here, researchers are encouraged to
develop population/species-specific correction formulae.
CONCLUSION
The standard robusticity index significantly overestimates tooth area and those overestimates vary according
to tooth shape. Our regression-based correction formulae
produce an adjusted RI, or ARI, that remove the RI bias.
Although the validation study was small, it clearly indicated a marked improvement in occlusal area estimates
when using the ARI. Moreover, the ARIs had mean inaccuracies that did not differ statistically based upon tooth
shape. Thus, the correction formulae should provide
superior molar area estimates than what is currently
provided by the robusticity index alone. This improved
method will facilitate more accurate odontometric studies in several realms of dental anthropology.
LITERATURE CITED
Alemseged Z, Wynn JG, Kimbel WH, Reed D, Geraads D, Bobe
R. 2005. First hominin from the Basal Member of the Hadar
Formation. Dikika, Ethiopia and its geological context. J Hum
Evol 49:499–514.
Bailey SE. 2004. A morphometric analysis of maxillary molar
crowns of Middle-Late Pleistocene hominins. J Hum Evol
47:183–198.
Bailey SE, Wood BA. 2007. Trends in postcanine occlusal morphology within the hominin clade: the case of Paranthropus.
In: Bailey SE and Hublin J-J, editors. Dental perspectives on
human evolution. New York: Springer. p 33–52.
Boughner JC, Dean MC. 2004. Does space in the jaw influence
the timing of molar crown initiation? A model using baboons
(Papio anubis) and great apes (Pan troglodytes. Pan paniscus). J Hum Evol 46:253–275.
331
Calcagno JM. 1989. Mechanisms of human dental reduction: a
case study from Post-Pleistocene Nubia. University of Kansas
Publications in Anthropology, No. 18.
Cuozzo FP. 2008. Using extant patterns of dental variation to
identify species in the primate fossil record: a case study of
middle Eocene Omomys from the Bridger Basin, southwestern
Wyoming. J Primatol 49:101–115.
Cuozzo FP, Yamashita N. 2006. Impact of ecology on dental
adaptations of extant lemurs: a review of tooth function,
variation, and life history. In: Gould L, Sauther ML, editors. Lemurs: ecology and adaptations. New York: Springer.
p 69–98.
el Zaatari S. 2007. Ecogeographic variation in Neanderthal dietary habits: evidence from microwear texture analysis. PhD.
dissertation, Stony Brook University, New York.
Ferrario VF, Sforza C, Tartaglia GM, Colombo A, Serrao G.
1999. Size and shape of the human first permanent molar: a
Fourier analysis of the occlusal and equatorial outlines. Am J
Phys Anthropol 108:281–294.
Frayer DW. 1978. Evolution of the dentition in Upper Paleolithic and Mesolithic Europe. University of Kansas Publications in Anthropology, No. 10.
Gantt DG, Kappelman J, Ketcham RA. 2007. HRXCT analysis
of hominoid molars: a quantitative volumetric analysis and
3D reconstruction of coronal enamel and dentin. In: Bailey
SE, Hublin J-J, editors. Dental perspectives on human evolution. New York: Springer. p 321–343.
Gómez-Robles A, Martinón-Torres M, Bermúdez de Castro JM,
Margvelashvili JM, Bastir M, Arsuaga JL, Pérez-Pérez A,
Estebaranz F, Martı́nez LM. 2007. A geometric morphometric
analysis of hominin upper first molar shape. J Hum Evol
53:272–285.
Goose DH. 1963. Dental measurement: an assessment of
its value in anthropological studies. In: Brothwell DR, editor.
Dental anthropology. New York: Pergamon Press. p 125–148.
Hill MK. 2004. Dental reduction and diet in the prehistoric
Ohio River Valley. Dent Anthropol 17:34–44.
Hlusko LJ, Do N, Mahaney MC. 2007. Genetic correlations
between mandibular molar cusp areas in baboons. Am J Phys
Anthropol 132:445–454.
Hlusko LJ, Mahaney MC. 2003. Genetic contributions to
expression of the baboon cingular remnant. Arch Oral Biol
48:663–672.
Hlusko LJ, Mahaney MC. 2007. A multivariate comparison of
dental variation in wild and captive populations of baboons
(Papio hamadryas). Arch Oral Biol 52:195–200.
Keiser JA. 1990. Human adult odontometrics. New York: Cambridge University Press.
Keiser JA, Waddell JN, Raju S. 2007. The uniqueness of the
human anterior dentition: a geometric morphometric analysis.
J Forensic Sci 52:671–677.
Martinón-Torres M, Bastir M, Bermúdez de Castro JM, Gómez
A, Sarmiento S, Muela A, Arsuaga JL. 2006. Hominin lower
second premolar morphology: evolutionary inferences
through geometric morphometric analysis. J Hum Evol 50:
523–533.
Mayhall JT. 2000. Dental morphology: techniques and strategies. In: Katzenberg MA, Saunders SR, editors. Biological
anthropology of the human skeleton. New York: Wiley-Liss.
p 103–134.
McHenry HM. 1988. New estimates of body weight in early
hominids and their significance encephalization and megadontia in ‘‘Robust’’ Australopithecines. In: Grine FE, editor. Evolutionary history of the ‘‘Robust’’ Australopithecines. New
York: Aldine de Gruyter. p 133–148.
Moggi-Cecchi J, Boccone S. 2007. Maxillary molar cusp morphology of South African australopithecines. In: Bailey SE,
Hublin J-J, editors. Dental perspectives on human evolution.
New York: Springer. p 53–64.
Morris DH. 1986. Maxillary molar occlusal polygons in five
human samples. Am J Phys Anthropol 70:333–338.
Olejniczak AJ, Grine FE, Martin LB. 2007. Micro-computed tomography of primate molars: methodological aspects of threedimensional data collection. In: Bailey SE, Hublin J-J, editors.
American Journal of Physical Anthropology
332
C. SCHMIDT ET AL.
Dental perspectives on human evolution. New York: Springer.
p 103–116.
Peretz B, Nevis N, Smith P. 1997. Morphometric variables of
developing primary maxillary first molar crowns in humans.
1997. Arch Oral Biol 42:423–427.
Pilbrow V. 2007. Patterns of molar variation in great apes and
their implications for hominin taxonomy. In: Bailey SE,
Hublin J-J, editors. Dental perspectives on human evolution.
New York: Springer. p 9–32.
Pinhasi R, Eshed V, Shaw P. 2008. Evolutionary changes in the
masticatory complex following the transition to farming in the
Southern Levant. Am J Phys Anthropol 135:136–148.
Schaefer A, Schmidt CW, Klaus HD, Centurion J. Dental topography of sacrifice victims from Lambayeque, Peru. 2008.
Paper presented at the Annual Meeting of the Midwest Bioarchaeology and Forensic Anthropology Association, Grand
Rapids, MI.
Schuman EL, Brace CL. 1954. Metric and morphologic variations in the dentition of the Liberian chimpanzee; comparisons with anthropoid and human dentitions. Hum Biol
26:239–268.
Scott GR, Turner CG II. 1997. The anthropology of modern
human teeth. Cambridge: Cambridge University Press.
Scott RS, Ungar PS, Bergstrom TS, Brown CA, Childs BE, Teaford MF, Walker A. 2006. Dental microwear texture analysis:
technical considerations. J Hum Evol 51:339–349.
Scott RS, Ungar PS, Bergstrom TS, Brown CA, Grine FE,
Teaford MF, Walker A. 2005. Dental microwear texture analysis shows within species diet variability in fossil hominins.
Nature 436:693–695.
Sekikawa M, Kanazawa E, Ozaki T, Brown T. 1988. Principal
component analysis of intercusp distances on the lower
first molars of three human populations. Arch Oral Biol
33:535–541.
American Journal of Physical Anthropology
Strait SG. 1993. Differences in occlusal morphology and molar
size in frugivores and faunivores. J Hum Evol 25:471–484.
Suwa G, Wood BA, White TD. 1994. Further analysis of mandibular molar crown and cusp areas in Pliocene and early
Pleistocene hominids. Am J Phys Anthropol 93:407–426.
Swindler DR. 2002. Primate dentitions. Cambridge: Cambridge
University Press.
Swindler DR, Emel LM, Anemone RL. 1998. Dental variability
of the Liberian chimpanzee. Pan troglodytes verus. Hum Evol
13:235–249.
Swindler DR, Gavan JA, Turner WM. 1963. Molar tooth variability in African monkeys. Hum Biol 35:104–122.
Swindler DR, Orlosky FJ. 1974. Metric and morphological variability in the dentition of colobine monkeys. J Hum Evol
3:135–160.
Ungar PS. 2007. Dental topography and human evolution with
comments on the diets of Australopithecus africanus and Paranthropus. In: Bailey SE and Hublin J-J, editors. Dental perspectives on human evolution. New York: Springer. p 321–343.
Wolpoff M. 1971. Metric trends in hominid dental evolution.
Case Western Reserve University Studies in Anthropology,
No. 2.
Wood BA, Abbott SA. 1983. Analysis of the dental morphology
of Plio-Pleistocene hominids. I. Mandibular molars: crown
area measurements and morphological traits. J Anat
136:197–219.
Wood BA, Abbott SA, Graham SH. 1983. Analysis of the dental
morphology of Plio-Pleistocene hominids. II. Mandibular
molars—study of cusp areas, fissure pattern and cross sectional shape of the crown. J Anat 137:287–314.
Zolnierz M, Schmidt CW. 2008. Dental texture analysis of Late
Archaic Amerindians from southern Indiana. Am J Phys
Anthropol (Suppl) 46:229.
Документ
Категория
Без категории
Просмотров
0
Размер файла
242 Кб
Теги
two, determinism, dimensions, occlusal, molar, area, correction, brief, communication, human, overestimation
1/--страниц
Пожаловаться на содержимое документа