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Body size and joint posture in primates.

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Body Size and Joint Posture in Primates
John D. Polk,1* Scott A. Williams,1 and Jeffrey V. Peterson2
Department of Anthropology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
Department of Anthropology, San Diego State University, San Diego, California 92182
apparent density; subchondral bone; body size; joint posture
Body mass has been shown in experimental and comparative morphological studies to have a significant effect on joint posture in major limb joints. The
generalizability of experimental studies is limited by their
use of small sample sizes and limited size ranges. In contrast, while comparative morphological studies often have
increased sample sizes, the connection between joint posture and morphological variables is often indirect. The
current study infers joint postures for a large sample of
primates using an experimentally validated method, and
tests whether larger primates use more extended joint
postures than smaller species. Postures are inferred
through the analysis of patterns of subchondral bone apparent density on the medial femoral condyle. Femora from
94 adult wild-shot individuals of 28 species were included.
Apparent density measurements were obtained from CT
scans using AMIRA software, and the angular position of
the anterior-most extent of the region of maximum apparent
density on the medial femoral condyle was recorded. In general, the hypothesis that larger-bodied primates use more
extended knee posture was supported, but it should be noted
that considerable variation exists, particularly at small body
sizes. This indicates that smaller species are less constrained by their body size, and their patterns of apparent
density are consistent with a wide range of knee postures.
The size-related increase in inferred joint posture was
observed in most major groups of primates, and this observation attests to the generalizability of Biewener’s model
that relates body size and joint posture. Am J Phys Anthropol 140:359–367, 2009. V 2009 Wiley-Liss, Inc.
Body mass has profound effects on the biology of all
terrestrial and arboreal animals including primates, and
body size can influence variation in primate diet, physiology, and locomotor behavior amongst others (SchmidtNielsen, 1984; Calder, 1996). The relationship between
locomotor postures and body mass in primates and other
mammals has been investigated in theoretical, experimental, and comparative analyses. The current explanatory model for the effects of size on limb morphology and
locomotion was developed by Biewener (1989a,b, 1990,
1991). Biewener synthesized experimental data and
theory and concluded that the scaling expectations differed for animals of vastly different size. With increasing
body size for most primates (50 g–300 kg), Biewener’s
model predicts a slight positive allometry in limb bone
diameters and cross-sectional geometric properties, along
with the use of more extended limb postures and
changes in extensor muscle mechanical advantage.
While these changes likely act to maintain safety factors
and prevent bone breakage, they probably come with the
cost of decreasing agility, accelerations, and maximal
speeds in the largest species (Rubin and Lanyon, 1982,
1984; Alexander, 1985, 1989). This study investigates
the relationship between joint posture and body size in a
broad sample of primate species in order to test whether
primates conform to the general scaling trends that have
been proposed for other mammals (Biewener 1982, 1983,
1989a,b, 1990, 1991, 2005), and observed in smaller primate samples (Demes and Jungers, 1993; Jungers and
Burr, 1994; Jungers et al., 1998; Polk, 2002).
Several experimental studies have found support for
Biewener’s model, by demonstrating that larger animals
use more extended limb postures than smaller ones.
Such extended postures increase the effective mechanical advantage of the antigravity (i.e., extensor) musculature, and allow postures in larger animals to be maintained with relatively less muscle force. Experimental
studies have been conducted on diverse mammalian
samples over a very broad size range (0.01–300 kg;
Biewener, 1983, 1989b, 1990), and closely related species
of cercopithecine primates (4–24 kg; Polk, 2002) and felids (4–200 kg: Day and Jayne, 2007). While these experimental studies clearly demonstrate an effect of size on
locomotor postures, they are limited by the fact that
they include relatively few individuals of relatively few
species, and, with the exception of Biewener’s work, they
investigate scaling trends across limited ranges of animal size. Furthermore, some ambiguities remain in the
experimental data; for example, Polk (2002) observed
that the angles in many weight-bearing joints did not
change with increasing body mass for his sample of primates. Ankle angles, for example, may not change with
size due to functional constraints related to arboreality.
Another study of felids also found that, while body mass
did correlate with elbow posture, body size was not a
good predictor of posture in other limb joints (Day and
Jayne, 2007). The fact that the elbow angle at midstance
showed the only correlation with size is interesting
C 2009
Grant sponsor: National Science Foundation; Grant number: BCS
0693630 with REU Supplement. Grant sponsor: University of Illinois at Urbana-Champaign.
*Correspondence to: John D. Polk, Department of Anthropology,
University of Illinois Urbana-Champaign, 109 Davenport Hall, 607
S. Mathews Ave., Urbana, IL 61801, USA.
Received 12 November 2008; accepted 4 March 2009
DOI 10.1002/ajpa.21083
Published online 7 May 2009 in Wiley InterScience
because this is the joint at which one would expect the
greatest size effect. Felids support more of their body
weight on their forelimbs than hindlimbs, and this suggests that the elbow may play a crucial role in resisting
gravity. That other joints did not show the predicted
size-related trends may be due to other anatomical or
functional constraints in felids. Alternatively, size might
not be a good predictor of joint postures more generally.
The mixed results from both Polk (2002) and Day and
Jayne (2007) suggest that more research is necessary to
test whether Biewener’s model can be generalized.
Studies of comparative morphology have also been important for illustrating size-related trends. Galilei (1638)
was the first to propose a relationship between body size
and bone shape. Since that time, comparative studies of
long bone cross-sectional properties have included many
more individuals of many more species, and these studies indicate that bone cross-sectional properties scale
with slight but significant positive allometry (Biewener,
1982; Jungers and Burr, 1994; Jungers et al., 1998; Polk
et al., 2000). Furthermore, theoretical measures of bending and compressive strength scale with negative allometry (Demes and Jungers, 1993; Jungers and Burr, 1994;
Jungers et al., 1998) implying that larger animals may
have reduced bone safety factors. Alternatively, these
animals may modify either their joint postures or athletic output (or both) to reduce bone loads and retain
adequate safety factors (Demes and Jungers, 1993;
Jungers and Burr, 1994; Jungers et al., 1998). Thus,
while these data also appear to support Biewener’s
model, it is important to point out that cross-sectional
properties provide only an indirect indication of altered
joint posture. Therefore, this study will use a more direct
morphological indicator of joint posture—the analysis of
subchondral bone apparent density patterns—to evaluate Biewener’s model and test for the effects of body size
on knee joint posture in primates.
Subchondral bone, located between the articular cartilage and trabecular bone, serves to transmit and distribute forces from the joint surface to the trabecular bone,
and it may attenuate some of the forces as well (Radin
et al., 1970; Radin and Paul, 1971; Simon et al., 1972;
Hoshino and Wallace, 1987). Changes in the apparent
density of subchondral bone have been observed in many
comparative studies (see below) and increased density
may provide several biomechanical advantages. For
example, denser subchondral bone shows increased compressive and tensile strength, compressive modulus, fatigue life, and resistance to crack initiation (Carter and
Hayes, 1977; Wright and Hayes, 1977; Wall et al., 1979;
Currey, 1988; Rice et al., 1988; Currey, 2002).
Apparent density variation in subchondral plates has
been studied for a variety of clinical and comparative biological reasons. Changes in the density and stiffness of
subchondral bone was initially implicated in the etiology
of osteoarthritis (Radin et al., 1972, 1973), but whether
the subchondral changes precede or follow the osteoarthritis remains a matter of continuing debate (Burr and
Radin, 2003; Wang et al., 2005). Analyses of subchondral
apparent density have also been used to infer differences
between normal and pathological joint loading histories
in humans (Müller-Gerbl et al., 1992; Eckstein et al.,
1994; Von Eisenhart-Rothe et al., 1999). In other mammals, researchers have examined variation in subchondral apparent density in the elbow joint of dogs (Samii
et al., 2002), as well as the tibial plateau and wrist joint
of primates (Ahluwalia, 2000; Carlson and Patel, 2006;
American Journal of Physical Anthropology
Patel and Carlson, 2007), in order to characterize difference in load magnitude, load distribution, and posture.
Patel and Carlson (2008) have also examined similar
patterns in the wrist joints of sloths and anteaters.
Together, these studies demonstrate that subchondral
bone can provide information about the loading history
of joint surfaces (see also Fischer et al., 1995).
The relationship between the pattern of subchondral
apparent density and posture has been validated in an
experimental study (Polk et al., 2008). These researchers
induced postural differences between groups of sheep by
altering the orientation of the treadmills on which they
were exercised. After 45 days of exercise, kinematic
measurements of joint posture were obtained, and the
subchondral apparent density in their distal femora was
assessed using the methods outlined below. Knee joint
posture estimates derived from the position of the region
of maximum apparent density in the subchondral bone
on the medial femoral condyle closely matched the kinematic joint posture measurements. The primary implication of this study is that habitual joint posture can be
inferred reliably from the location of the position of maximal subchondral bone apparent density.
In the current study we analyze the patterns of subchondral bone apparent density in the distal femur of a
diverse sample of primate species. We test the hypothesis that larger bodied primates will use more extended
knee joint postures than smaller primates, and we
expect that this pattern will be displayed in all major
clades of primates. In this study, we focus on the medial
femoral condyle because the knee joint is one of the
major limb joints and the muscles that cross this joint
must help to support the weight of the body. The medial
femoral condyle (MFC) was selected for analysis because
in experimental studies of primate and other terrestrial
mammalian locomotion (e.g., sheep) where simultaneous
ground reaction force and 3D kinematic data were
obtained, the peak ground reaction force vectors pass
medial to the knee joint during walking and running
gaits (Polk et al., unpublished data; Taylor et al., 2006).
This implies that the MFC bears more weight than the
lateral femoral condyle.
Twenty-eight primate species were included in this
analysis. A list of the species and sample sizes are listed
in Table 1. All specimens were borrowed from the Museum of Comparative Zoology (MCZ) at Harvard University, and all specimens were from adult, wild-shot individuals that exhibited no visible osteological pathologies.
Right femora were preferred, but in some cases the left
was substituted. Only quadrupedal primates were
included in this analysis. Although orangutans may be
considered more quadrumanous climbers, they are
included in this study because they use quadrupedal
locomotion on terrestrial substrates.
In any discussion of density it is important to be
explicit about what quantities are being assessed. Computed tomography allows the quantification of apparent
density for composite biological materials like bone that
contain different types of tissue and biological materials.
Apparent density is distinguished from true density by
the fact that the latter can only be calculated for single
materials (i.e., mass/volume). In this study we quantify
apparent density of the subchondral bone in the medial
femoral condyle (MFC).
TABLE 1. Species and sample size
Female (n)
Alouatta caraya
Alouatta palliatea
Cercocebus albigena
Cercopithecus diana
Cercopithecus l’hoesti
Chlorocebus aethiops
Colobus guereza
Colobus polykomos
Daubentonia madagascariensis
Eulemur rubriventer
Gorilla gorilla
Leontopithecus rosalia
Macaca fascicularis
Macaca mulatta
Macaca nemestrina
Mandrillus leucophaeus
Mandrillus sphinx
Miopithecus talapoin
Nasalis larvatus
Nycticebus coucang
Pan troglodytes
Piliocolobus badius
Pongo pygmaeus
Presbytis hosei
Trachypithecus cristata
Trachypithecus phayrei
Trachypithecus vetulus
Varecia variegata
Male (n)
Data collection methods are described in detail elsewhere (Polk et al., 2008), but relevant aspects are
repeated here. Computed tomography (CT) scans were
obtained from all primate specimens. Scanning was conducted at the Mount Auburn Hospital in Cambridge,
MA, using a GE Lightspeed Plus CT scanner. Specimens
were scanned with the long axis of the bone perpendicular to the CT source/sensor plane in order to maximize
the number of slices obtained per specimen. Pixel size on
each slice was 0.234 mm 3 0.234 mm; slice thickness
was 0.625 mm. The CT reconstruction algorithm ensured
that the apparent density is linearly related to the intensity of grey in the CT images (black 5 air, white 5
increased density). Data were saved as 16-bit DICOM
images. Apparent bone density is quantified in Hounsfield units (H, also called CT number), where apparent
density values are expressed relative to water density
(water density 5 0H) (Ruff and Leo, 1986). Air has an
apparent density of 21,000H and apparent densities for
subchondral and compact bone range from about 25H to
more than 1,500H. The Mount Auburn CT system is calibrated daily to ensure the accuracy of density measurements. AMIRA (v. 4.1, Mercury Computing Systems,
Chelmsford MA) software was used to create virtual 3D
representations of the femora from the CT images,
thereby preserving the geometry of the entire bone.
Following Polk et al. (2008) we quantified the regions
of maximum density (RMD) on the MFC. To obtain these
measurements, a single, oblique, two-dimensional slice
was obtained through the long axis of the MFC for each
specimen (slice thickness 5 0.234 mm). To ensure consistency in slice orientation across individual subjects, the
plane of this slice was oriented to pass through (i) the
long axis of the MFC, and (ii) the medial lip of the patellar groove.
To distinguish among the 2 levels of grey stored in
16-bit DICOM images, color maps were applied to the
subchondral bone. AMIRA (v.4.1) permits users to manually select the range of Hounsfield units to display
(comparable to setting the CT level and window) and to
divide this range into a maximum of 256 separate colors
(bins). Maximum and minimum densities along the subchondral surface were assessed to the nearest 25H. Densities less than or equal to the minimum found on the
subchondral surface were assigned to bin 0, while densities greater than or equal to the maximum found on
the subchondral surface were assigned to bin 255. The
remaining density range (254 bins) was divided into 10
regions of differing density (the highest and lowest density regions had one fewer bin than did the remaining
eight). Images of the oblique 2D slice were exported for
digitizing in tpsdig2 (Rohlf, 2006). The position of the
RMD was measured on the MFC as the angle between
the posterior extent of the MFC (Fig. 1, inset point B),
the point at the center of the line segment connecting
the proximal and distal extents of the articular surface
on the MFC (Fig. 1, inset point C) and the anterior
extent of the RMD (Fig. 1, inset point E), since this
angle (y) most closely matched kinematically measured
joint angles in the experimental study of Polk et al.
(2008). Coordinate measurements from tpsdig2 were
exported, and angles were calculated using the law of
cosines. If discontinuities existed in the RMD, the anterior-most point on the anterior-most portion of the RMD
was digitized.
Digitizing was performed by two authors (SAW, JVP).
Specimens were digitized without reference to the species to which they belonged or the size of the individual,
thereby preventing observers inadvertently biasing the
results. In order to ensure that angle y could be measured accurately, and to assess the sensitivity to interobserver error, two tests were performed. First, the estimate of y obtained for the central slice through the MFC
was compared to adjacent parallel slices for a subset of
the subjects. No significant difference in joint angle was
detected. Interobserver error in measuring y was
assessed by having each researcher (SAW, JVP) obtain
measurements for ten specimens. Repeatability for the
angular measurement was high with only 5.9% of the
variation being attributable to different observers.
To determine the position of the RMD on the entire femur, and to estimate knee joint posture in a manner
that is more comparable to kinematic measurements, it
is necessary to quantify the location of the 2D slice on
each femur. This was accomplished by combining the
angle describing the position of the RMD relative to a
line connecting the proximal and distal ends of the MFC
(from the 2D oblique slice), with an angle that describes
the orientation of this line on the MFC relative to the
long axis of the bone (in 3D). Three-dimensional coordinate data were obtained from the CT data for each bone
using a combination of AMIRA, to generate a dense surface mesh, and Landmark (Wiley et al., 2005) to place
landmarks on this 3D surface. The 3D landmarks were
placed on the superior margin of the proximal end of the
greater trochanter (corresponding to the most posterodorsal projection of the greater trochanter when the femur is placed in anatomical position), and the proximal
and distal extents of the MFC (see Fig. 1). The midpoint
of the MFC was calculated from these coordinates and
this allowed calculation of the orientation of the medial
femoral condyle relative to the long axis of the femur.
American Journal of Physical Anthropology
Fig. 1. Methods for estimating joint posture. A color map is
applied to the grayscale image
to illustrate differences in bone
apparent density. Angle q,
describing the orientation of the
articular surface of the medial
femoral condyle relative to the
shaft of the bone is added to y
(inset). Angle y describes the
angular position of the anteriormost extent of the region of
maximum density on the medial
femoral condyle. Points A and B
are located on the anterior and
posterior extents of the articular
surface, with midpoint C. Point
E is located at the anterior-most
extent of the region of maximum density.
Fig. 2. Joint angle estimates
plotted against size estimates in
raw (nonlogged) space. Data
points are sex-specific species
means. Solid line is leastsquares regression, dashed line
is reduced major axis regression. Inset images show the
RMD in brown along the MFC
for G. gorilla (far right), T. vetulus (lower left), and C. aethiops
(upper left).
Fig. 3. Plot of estimated joint angle against size estimates in log-log space. Data points are sex-specific species means. Solid line
is least-squares regression, dashed line is reduced major axis. Joint posture is positively correlated with size. Regression coefficients
are found in Table 2.
Knee joint angles were estimated as the sum of the (a)
orientation of the MFC relative to the long axis of the femur (Fig. 1, q) and (b) angular position of the RMD relative to the MFC (Fig. 1, inset y).
Measurements were obtained of the maximal superiorinferior and anteroposterior (AP) diameters of the femoral
head and the maximal AP and mediolateral diameters of
the femoral midshaft. Because of the high correlation
between these measurements and body mass (Ruff, 1987,
1988; Jungers, 1988, 1991; McHenry, 1988; McHenry and
Berger, 1998), the geometric mean of these four measurements of the femoral head and midshaft were used as a
size variable for each specimen (Jungers et al., 1995).
Sex-specific species means for size and joint angle variables were used for all analyses. Angular and size variables were log-transformed prior to analysis to linearize
the allometric relationships and to reduce significant
right skew (due to the greater representation of smallbodied taxa). Reduced major axis (RMA) regression analyses were performed because error exists in the estimation of the size variable (Ricker, 1984; Rayner, 1985;
Sokal and Rohlf, 1995). Least-squares regression parameters and Pearson product-moment correlation coefficients are included for comparison. RMA regression
parameters were estimated using RMA.html (Bohonak,
2004). This software calculates the 95% bootstrapped
confidence limits for 10000 replicates. Because of the
small strepsirrhine sample (n 5 6), Spearman’s rankorder correlation coefficients were used to detect significant trends (Sokal and Rohlf, 1995). Hominoids were not
analyzed separately in this study since their small sample size (n 5 5) precluded detection of significant deviations from isometry. One-tailed tests of significance were
used because positive correlations between joint angle
estimates and body size were expected (Sokal and Rohlf,
1995). All statistical analyses of correlation coefficents
were performed in SPSS (v16), except the BreuschPagan tests for heteroscedasticity (Breusch and Pagan,
1979), which were performed using R (
Figure 2 shows a plot of the sex-specific species mean
knee joint angles plotted on the corresponding size estimate in raw (nonlog) space. These data demonstrate significant right skew (g1 5 2.062, SE: 0.374), but overall
there is a positive trend in which larger animals appear
to use more extended postures, while smaller species exhibit considerable variability in estimated joint posture.
Despite this apparent variability, significant heteroscedasticity was not observed (BP 5 0.7871, df 5 1, P 5
0.375). Inset images in Figure 2 illustrate some of the variation in the position of the RMD in different specimens.
Logarithmic transformation of the data improved the
normality of the distribution (see Fig. 3), and skew was
no longer significant (g1 5 0.583, SE: 0.374). Regression
parameters are listed in Table 2 and plots of the results
for each group are displayed in Fig. 3. As predicted, statistically significant and positive correlation was observed
between the size variables and the knee joint angle estimates for all primates (Fig. 3, Table 2). The positive
trend was denoted both by a significant correlation coefficient (P 5 0.006) and by the fact that bootstrapped confidence limits excluded horizontal (0) slope (Table 2).
Similar positive correlations were obtained for all
major groups of primates with the exception of strepsirrhines and cercopithecine monkeys (Table 2, Fig. 4). The
small sample of strepsirrhine primates showed a negative, but nonsignificant trend, while the cercopithecines
showed a positive trend that approached but did not
attain statistical significance (P 5 0.089) at the a 5 0.05
The results of this study support the general conclusion that larger primates use more extended joint postures than most smaller primates, and in this way, the
theoretical expectations of Biewener’s model appear to
American Journal of Physical Anthropology
TABLE 2. Regression coefficients relating estimated joint posture (Y) to body mass (X)
All primates
P values
Lower (95% CL)
Upper (95% CL)
(one tailed)
Variables were log-transformed before calculation of regression coefficients. Significant P values are indicated with bold font. The
correlation coefficient for the strepsirrhine analysis is a nonparametric Spearman’s rank-order.
LS 5 least squares, RMA 5 reduced major axis, Int. 5 intercept, CL 5 confidence limit.
Fig. 4. Plots of estimates for habitual knee joint angle against size for major phylogenetic groups of primates including (A) strepsirrhine, (B) anthropoid, (C) catarrhine, (D) cercopithecine, and (E) colobine primates. Data points are sex-specific species means.
American Journal of Physical Anthropology
be supported. It should be noted that there appears to be
greater mechanical constraint on the postures used by
larger animals, while smaller primates are less constrained in the postures they use. Indeed, several small
and midsized primates appear to use extended knee
postures comparable to those used by the largest species
(Fig. 2). This constraint on the larger species, but lack of
constraint on smaller species is consistent with
Biewener’s model since he had predicted that species in
the size range of primates should rely on some combination of allometric scaling of bone strength and alteration
of joint postures in response to size. The converse is not
observed; that is, the density patterns on the joint surfaces of larger primates are not consistent with significant
habitual loading of the knee joints in flexed postures.
The fact that positive trends were observed in most of
the major primate groups suggests that this trend of
increasing knee joint posture with size is generally supported. However, it is important to note that considerable variation exists within any particular group of primates. Furthermore, positive trends were not observed
in two groups, the strepsirrhines and cercopithecine
monkeys. In strepsirrhines, the power to detect a trend
is low, given the small number of sex-specific species
means (n 5 6), the limited range of body size, and the
fact that the largest species of quadrupedal strepsirrhine included in this study has an average body mass
of approximately 3.5 kg, which is fairly small for primates as a whole (Smith and Jungers, 1997). Thus this
sample of strepsirrhines may not be expected to exhibit
the size-related changes in posture. Instead they may
accommodate to increasing size by exhibiting either
allometric changes in bone strength (Demes and
Jungers, 1993) or allometric changes in muscle crosssectional properties. Demes and Jungers (1993)
observed positive allometry in bone cross-sectional
properties but noted that measures of bone strength
decreased with size, implying that size-related changes
in posture should be expected.
In cercopithecines, the trend approached but did not
attain statistical significance. In this case our power to
detect allometric changes in joint posture may also be
limited by sample size, and by the fact that we have not
adequately sampled all of the larger species of cercopithecine monkeys. We anticipate that broader sampling of
this group will permit detection of size-related changes
in posture that have been found in experimental studies
(Polk, 2002, 2004) and have been inferred by the comparative studies of Jungers and colleagues (Jungers and
Burr, 1994; Jungers et al., 1998).
Locomotor variation may help to explain some of the
differences between groups. For example, cercopithecines
tend to use more extended postures than colobines (compare Fig. 4D and E), and the largest colobine included in
this study, Nasalis, has a large negative residual (see
Fig. 4E). The more flexed postures of colobines are consistent with their more frequent use of leaping (Fleagle,
1999). The effect of locomotor variation on subchondral
density patterns will be explored in greater detail in a
forthcoming paper (Polk et al., in preparation).
The fact that the subchondral bone apparent density
patterns of larger species do not indicate habitual use of
flexed postures in no way means that these species were
incapable of using such postures. The totality of factors
contributing to the osteological response of the subchondral plate is not known. We know little about the thresholds for loading duration or magnitude that are required
to alter the patterns of bone density. Similarly, we know
little about the turnover rates for subchondral bone or
whether (and how quickly) the patterns alter with disuse. The experimental data of Polk et al. (2008) suggest
that relatively short-term exposure (45 days) to brief
but consistent postural changes (2 3 20 min/day) can
have significant effects on the position of the RMD on
the subchondral surface. It remains to be evaluated
whether other loading patterns can have comparable
effects on the position of the RMD. However, the data
presented here provide circumstantial evidence that certain loading conditions may not be sufficient to achieve
an osteological response. For example, chimpanzees are
well known to climb tall, vertical trees on a regular basis
(Pontzer and Wrangham, 2004) and in doing so they use
flexed knee postures, and are likely to generate considerable stress on their subchondral surfaces. The fact that
their RMD do not reflect the use of these postures
implies that these loading conditions are not sufficient to
generate a substantial osteological response. Instead, we
argue that the patterns of subchondral density are likely
to reflect longer-term patterns of habitual joint stress
(also see Müller-Gerbl et al., 1992; Carlson and Patel,
2006; Patel and Carlson, 2007), and that it may not be
possible to reconstruct short-term use of other postures
using this method.
In summary, while considerable variability exists in
the knee postures we infer for the species in this study,
this research demonstrates that size-related changes in
habitual knee joint posture can be detected using analyses of the patterns of subchondral bone apparent density.
The observed postural changes are consistent with the
interspecific scaling models and the results of previous
experimental and comparative research. More specifically, while there is a trend for larger primates to use
extended knee postures, smaller species are less constrained and may use a wide range of knee joint posture.
The authors are grateful for the assistance provided
by Judy Chupasko and her staff at Harvard’s Museum of
Comparative Zoology and Kevin Reynolds and his staff
at Mount Auburn Hospital. Daniel Weber, Janet Hanlon,
and Petra Jelinek assisted with training on AMIRA at
the Visualization, Media and Imaging Laboratory at the
Beckman Institute for Advanced Science and Technology.
Nathan Young provided advice for obtaining coordinate
data. Charles Roseman provided statistical advice and
assistance with the R statistical program. Daniel Lieberman, Brigitte Demes and Rebecca Stumpf provided
invaluable feedback at various stages. Additional assistance was provided by Campbell Rolian, Susy Cote, and
Maureen Devlin. The authors also thank the editorial
staff and two anonymous reviewers for their constructive
feedback on an earlier draft of this article.
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