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Investigating the form-function interface in African apes Relationships between principal moments of area and positional behaviors in femoral and humeral diaphyses.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 127:312–334 (2005)
Investigating the Form-Function Interface in African
Apes: Relationships Between Principal Moments of
Area and Positional Behaviors in Femoral and Humeral
Diaphyses
Kristian J. Carlson*
Department of Anatomical Sciences, School of Medicine, Stony Brook University, Stony Brook, New York 11794-8081
KEY WORDS
Gorilla
cross-sectional geometry; principal moment of area; locomoter behavior; Pan;
ABSTRACT
Investigations of cross-sectional geometry in nonhuman primate limb bones typically attribute
shape ratios to qualitative behavioral characterizations,
e.g., leaper, slow climber, brachiator, or terrestrial vs.
arboreal quadruped. Quantitative positional behavioral
data, however, have yet to be used in a rigorous evaluation
of such shape-behavior connections. African apes represent an ideal population for such an investigation because
their relatedness minimizes phylogenetic inertia, they exhibit diverse behavioral repertoires, and their locomotor
behaviors are known from multiple studies. Cross-sectional data from femoral and humeral diaphyses were
collected for 222 wild-shot specimens, encompassing Pan
paniscus and all commonly recognized African ape subspecies. Digital representations of diaphyseal cross sections
were acquired via computed tomography at three locations
per diaphysis. Locomotor behaviors were pooled broadly
into arboreal and terrestrial categories, then partitioned
into quadrupedal walking, quadrumanous climbing,
scrambling, and suspensory categories. Sex-specific taxonomic differences in ratios of principal moments of area
(PMA) were statistically significant more often in the femoral diaphysis than the humeral diaphysis. While it appears difficult to relate a measure of shape (e.g., PMA
ratio) to individual locomotor modes, general locomotor
differences (e.g., percentage arboreal vs. terrestrial locomotion) are discerned more easily. As percentage of arboreal locomotion for a group increases, average cross sections appear more circular. Associations between PMA
ratio and specific locomotor behaviors are less straightforward. Individual behaviors that integrate eccentric limb
positions (e.g., arboreal scrambling) may not engender
more circular cross sections than behaviors that incorporate repetitive sagittal movements (e.g., quadrupedal
walking) in a straightforward manner. Am J Phys Anthropol 127:312–334, 2005. © 2004 Wiley-Liss, Inc.
Strain gauges applied to bone surfaces are the
only direct means of measuring in vivo bone deformations during locomotion (e.g., axial compressive,
axial tensile, or bending loads). Initial in vivo strain
studies (Lanyon and Smith, 1969, 1970) and subsequent others (Biewener and Taylor, 1986; Biewener
et al., 1983; Davies et al., 1993; Rubin and Lanyon,
1982) identified bending as the predominant deformation force that limbs experienced during locomotor activities. These studies addressed how size variation across taxa, as well as changes in speed and
gait (e.g., walking and galloping), altered strain
loads. However, the locomotor behaviors in these
studies were limited to treadmill or runway locomotion, artificial settings in which limbs were restricted primarily to sagittal movements. Strain profiles (e.g., magnitude or orientation) appeared
relatively consistent across behavioral changes in
these studies.
As a greater array of locomotor behaviors was
investigated, the strain profiles became more variable. Burr et al. (1996) reported higher strain magnitudes in the human tibia during “zigzag” walking/
running on hillsides than during straight walking/
running on a hill or flat surface. They speculated
that a gait change created a new mechanical environment to which a bone would be less attuned, and
that it would be difficult to envision rapidly operating compensatory mechanisms responding to
equally rapid alterations in strain patterns. It fol-
©
2004 WILEY-LISS, INC.
Grant sponsor: National Science Foundation; Grant number: Doctoral Dissertation Improvement Grant BCS-0002686; Grant sponsor:
L.S.B. Leakey Foundation; Grant sponsor: Department of Anthropology, Indiana University; Grant sponsor: University Graduate School,
Indiana University.
*Correspondence to: Kristian J. Carlson, Department of Anatomical
Sciences, Health Sciences Center, School of Medicine, Stony Brook
University, Stony Brook, NY 11794-8081.
E-mail: [email protected]
Received 19 August 2003; accepted 15 June 2004.
DOI 10.1002/ajpa.20124
Published online 6 December 2004 in Wiley InterScience (www.
interscience.wiley.com).
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
lows that a locomotor behavior incorporating frequent directional shifts in the velocity vector of an
individual may promote the adaptation of a diaphysis to bending in multiple directions in order to
reduce any deleterious consequences of a new mechanical environment.
Nonhuman primates also demonstrated more
variable in vivo strain profiles when a wider variety
of locomotor behaviors was investigated. Gibbons
encountered “considerable variability in strain pattern and peak magnitude among swings . . . contrasting with the stereotypic patterns recorded in
walking and running animals” during brachiation
(Swartz et al., 1989, p. 270). A macaque exhibited
slightly higher average strain magnitudes in the
tibia during climbing compared to stereotypical
overground walking (Demes et al., 2001). Demes et
al. (2001, p. 262) also observed that “the direction of
bending [was] very consistent [during overground
locomotion], and major variation [was] evident only
for the few climbing cycles recorded for one animal.”
Thus, it appears that some arboreal locomotor behaviors may be more strongly associated with generating multi-oriented bending loads in limb bones
than some terrestrial locomotor behaviors.
Substrates/superstrates are positioned erratically
throughout three dimensions in arboreal settings,
but in terrestrial settings they are relatively continuously distributed in two dimensions. Accordingly,
it is reasonable to expect that limb position is variable during arboreal locomotion (i.e., limbs experience diverse movement planes), with limbs more
often abducted while supporting body weight. During terrestrial locomotion, in contrast, limb movements are expected to be comparatively more repetitive and predictable (i.e., limbs move consistently in
a narrow range of sagittal planes). These scenarios
appear consistent with the strain data, since at least
two arboreal behaviors (i.e., brachiation and climbing) exhibited greater variability in the direction of
bending than terrestrial behaviors (i.e., quadrupedal walking and running). Substrate reaction forces
(SRF) encountered by the forelimb of several monkeys, however, usually exhibited a more variably
directed mediolateral (ML) component during terrestrial rather than arboreal locomotion (Schmitt,
2003). It is unclear how to resolve a possible contradiction between greater variation in the forelimb ML
component of the SRF associated with terrestrial
rather than arboreal quadrupedal walking, which
presumably signals greater diversity in the direction
of the forelimb SRF vector during terrestrial quadrupedal walking, yet greater forelimb and hindlimb variation in principal strain orientations during arboreal locomotor behaviors relative to
terrestrial. Future studies that simultaneously collect strain and SRF data during arboreal and terrestrial quadrupedalism may shed light on this apparent disagreement.
While cross-sectional geometry does not assess
limb deformation loads directly, it is a useful means
313
of estimating bone adaptation to mechanical load
history (Martin et al., 1998). Application of crosssectional geometry to long bone diaphyses assumes
a relationship between bone organization and an
engineering beam model. Compelling in vivo research by Lišková and Heřt (1971) and Heřt et al.
(1969, 1971, 1972) provided experimental verification for proposed relationships articulated in earlier
work (Amtmann, 1971; Koch, 1917; Kummer, 1959;
Meyer, 1867; Pauwels, 1968, 1980; Roux, 1881;
Wolff, 1892). Subsequent experimental approaches
(e.g., Biewener et al, 1983; Bouvier and Hylander,
1981; Burr et al., 1996, 2002; Churches et al., 1979;
Goodship et al., 1979; Gross et al., 1992, 1997; Jones
et al., 1977; King et al., 1969; Lanyon, 1980; Lanyon
and Baggott, 1976; Lanyon et al., 1975, 1982; Loitz
and Zernicke, 1992; Martin, 1991; O’Connor et al.,
1982; Rubin and Lanyon, 1982, 1984b; Woo et al.,
1981; Young et al., 1979; reviewed by Burr, 1980;
Turner, 1998) have refined this relationship even
further. It is clear that long bone diaphyses adapt
their shape in response to dynamic rather than
static loads (Lanyon and Rubin, 1984). Dynamic
loads evoke adaptive responses in diaphyses even
when they are short in duration or infrequent (e.g.,
as few as five cycles per day) (Rubin and Lanyon,
1984a; Umemura et al., 1997). Though the current
synthesis of the response of bone cross-sectional
shape to mechanical loadings, historically known as
“Wolff’s law,” may have various levels of interpretations, here it is understood as the guiding principle
that cortical bone responds to stress created through
mechanical load-induced strains by adapting a
cross-sectional shape that minimizes stress, usually
with an economical amount of material.
Mathematical models for analyzing long bone diaphyses (Huiskes, 1982; Huiskes et al., 1981; Rybicki et al., 1972; Toridis, 1969; Valliappan et al.,
1977) and the pioneering use of computed tomography (CT) by Jungers and Minns (1979) were a boon
to cross-sectional geometry studies, which subsequently flourished (e.g., Bridges, 1989; Burr et al.,
1982, 1989; Carlson, 2002a,b; Churchill et al., 1996;
Connour et al., 2000; Cubo and Casinos, 1998;
Demes and Jungers, 1989, 1993; Demes et al., 1991;
Heinrich and Biknevicius, 1998; Jungers and Burr,
1994; Kimura and Takahashi, 1992; Larsen and
Ruff, 1991; Madar et al., 2002; Ohman, 1993; Polk et
al., 2000; Robling, 1998; Ruff, 1989, 2002; Ruff and
Hayes, 1983a,b; Ruff and Runestad, 1992; Runestad, 1994; Runestad et al., 1992; Selker and Carter,
1989; Stephenson and Seedhom, 1999; Terranova,
1995a,b; Trinkaus et al., 1994, 1999). Recent work,
however, established that the relationships between
cross-sectional shape and bone deformation were not
as simplistic as often assumed (Bertram and
Swartz, 1991; Daegling, 2002; Lieberman and
Crompton, 1998; Lovejoy et al., 2003). For example,
bone tissue in a given cross section was not always
distributed economically, as assumed with a beam
model, and the neutral axis of bending did not pass
314
K.J. CARLSON
Fig. 1. CT images of transverse cross sections from two gorilla humeral midshafts. Gray lines represent principal centroidal axes. Black lines represent centroidal axes about x- and
y-axes. Note in cross section on left that ratio of principal moments of area (PMAs) is about 1.75 times the ratio of second
moments of area (SMAs) about mediolateral and anteroposterior
axes. Compare this with a different cross section (right) in which
ratios are relatively similar. While PMA ratio accurately portrays
obvious shape (or circularity) differences of cross sections, Ix/Iy
does not discriminate between their shapes (or degrees of circularity).
through the centroid of a cross section when axial
and bending loads were superimposed (Demes et al.,
1998, 2001; Gross et al., 1997; Lieberman et al.,
2004).
Animals apparently encounter similar peak
stresses during locomotion, regardless of differences
in their body size (e.g., Biewener, 1982; Lanyon et
al., 1975). If an animal frequently travels in an
arboreal setting, it should adapt sufficient rigidity in
multiple planes in order to prevent failure (e.g., fracture) in any one particular bending plane of a given
diaphyseal cross section. An animal moving more
frequently in a terrestrial setting, on the other hand,
may adapt lower rigidity in particular planes from
which bending loads presumably are less likely to be
experienced. Maximum rigidity, which is expected to
reflect the magnitude of peak loads and is approximated by Imax of a cross section, may vary less than
minimum rigidity (approximated by Imin of a cross
section) for animals of a given body mass.
Schaffler et al. (1985) suggested that a ratio of
principal moments of area (i.e., Imax/Imin) provided a
good estimate of how a limb was used. While Ohman
(1993, Tables 34 –36, 39 – 41) reported second moments of area about principal axes (PMAs), most
studies emphasized ratios of second moments of
area (SMAs) about alternative axes (e.g., Ix/Iy). The
use of anteroposterior (AP) and mediolateral (ML)
anatomical axes rather than principal axes was often necessary for methodological reasons (e.g., data
were acquired via biplanar radiographs). Ratios of
PMAs and other SMAs can depict similar shapes
(e.g., similar degrees of circularity), but this is not
always the case (Fig. 1). When principal angles (i.e.,
the angle between the maximum centroidal axis and
the centroidal axis through the x-axis) approach 45°,
discordance between these ratios increases. Given
that principal angles of African apes vary within
and between subspecies (Carlson, 2002b), principal
axes rather than anatomical axes (e.g., AP and ML
axes) provide a more accurate measure of cross section shape (e.g., circularity) in the limb diaphyses of
African apes.
Since Keith (1923, 1934) and others (Gregory,
1927, 1928; Hooton, 1942; Morton, 1922) first employed ape models for understanding the evolution
of the hominid postcranium, attributing unique
characteristics of the ape postcranium to behaviors
has become more focused both from a behavioral and
a morphological standpoint (e.g., see Hunt, 1991b,
and references therein). Suspensory locomotion or
brachiation (sensu lato) (e.g., Ashton and Oxnard,
1963; Avis, 1962; Ellefson, 1974; Erickson, 1952;
Grand, 1972; Gregory, 1916; Keith, 1891; Lewis,
1965; Napier, 1963; O’Connor, 1975; Ripley, 1970;
Rose, 1974; Washburn, 1950), climbing (e.g., Cartmill and Milton, 1977; Fleagle et al., 1981; Jenkins
and Fleagle, 1975; Washburn, 1973), and quadrumanous climbing (e.g., Fleagle, 1976; Kortlandt,
1975; Sarmiento, 1985; Stern et al., 1977; Tuttle,
1975; Tuttle et al., 1979) have been identified at one
time or another as a unique evolutionary pressure
facing apes. Once behavioral repertoires of African
apes in their natural habitats were characterized
(e.g., Doran, 1989; Hunt, 1989; Remis, 1994), it became possible to more clearly identify which positional behaviors were potentially relevant for understanding ape morphology. Apes, especially
chimpanzees, demonstrated morphological adaptations to a variety of positional behaviors, including
postural behaviors such as arm-hanging (Hunt,
1991a, 1992, 1994, 1996). These behavioral studies
also documented not only species-specific patterns,
but intraspecific differences as well: Gombe chimpanzees were more terrestrial than Mahale chimpanzees (Hunt, 1989, p. 160); Gorilla gorilla gorilla
was more arboreal than G. g. beringei (Remis, 1995).
Positional behavior data (Doran, 1989, 1993, 1996;
Doran and Hunt, 1994; Hunt, 1989, 1991a,b, 1992;
Remis, 1994, 1995, 1998; Susman, 1984; Tuttle and
Watts, 1985) are currently available for all three
species of African ape (i.e., Pan paniscus, Pan troglodytes, and G. gorilla).
Yet another crucial revelation sprouting from the
behavioral studies was that a variety of behaviors
with potentially disparate functional implications
quadrupedal walking on inclined branches, such as
(e.g., Fleagle, 1976), vertical climbing (e.g., Fleagle
et al., 1981), and scrambling (e.g., Doran, 1996) often were pooled in a single quadrumanous climbing
category. Hunt et al. (1996) defined scrambling as
“upward (ⱖ45°) progression on multiple often oddly
angled supports, typically without a discernible gait
pattern.” Scrambling behaviors (i.e., vertical scramble (L8: c) in Hunt et al., 1996) incorporated more
315
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
eccentric, erratic limb positions than other behaviors grouped in the quadrumanous climbing behavior category (i.e., inclined quadrupedal walking and
vertical climbing). Such qualitative differences, with
potentially relevant functional consequences, between scrambling, quadrupedal walking, and vertical climbing suggest that scrambling should be
treated as a separate behavior in locomotor profiles.
Differentiation between cross-sectional properties
of fore and hind-limbs has been observed to varying
degrees among leapers, brachiators, arboreal quadrupeds, and terrestrial quadrupeds (Burr et al.,
1989; Demes et al., 1991, 1994; Ruff, 2002; Runestad
et al., 1992; Schaffler et al., 1985). These studies,
however, typically used qualitative characterizations of locomotor behaviors. Ruff (1987) and Ohman
(1993) provided the initial data on cross-sectional
properties of African ape limb bones, but their results reflected relatively small or homogenous samples of apes, respectively. The potential consequences of this limitation were articulated by
Carlson (2002a,b) and recently voiced by Ruff (2002,
p. 307), who “recogniz[ed] that some variability in
locomotor/positional behavior exist[ed] within . . .
African ape genera, where locomotor behavior can
vary significantly depending on the particular species/subspecies.” No study has combined a large
sample of all African ape taxa with quantitative
positional behavior data.
The present study serves two primary functions:
first, it expands the sample of African ape crosssectional properties from femoral and humeral diaphyses to a sufficiently large size that incorporates
existing taxonomic diversity; and second, it uses
quantitative positional behavior data rather than
qualitative descriptions for investigating form-function relationships. In pursuit of these goals, four
specific questions are addressed: 1) Does the
summed percentage of all arboreal locomotor behavior correlate negatively with the ratio of PMAs (Imax/
Imin) in femoral and humeral diaphyses? In other
words, as the summed percentage of all arboreal
locomotion increases, irrespective of changes in the
frequency of specific arboreal behaviors, does the
ratio of PMAs decrease (i.e., Imin approaches Imax,
and circularity increases)? In order to discern
whether specific arboreal locomotor behaviors are
differentially associated with PMA ratios, or
whether summing them into total arboreal locomotion and comparing this to total terrestrial locomotion is more insightful, three additional questions
are investigated: 2) Do PMA ratios correlate negatively with the percentage of an arboreal behavior
that presumably incorporates more varied limb positions during movements (e.g., scrambling)? 3) Do
PMA ratios correlate positively with the percentage of
an arboreal behavior that presumably induces more
repetitive sagittal limb positions during movements
(e.g. arboreal quadrupedal walking)? 4) Does bone
shape (i.e., circularity) potentially reflect the percentage of scrambling more than other arboreal behaviors?
TABLE 1. Taxonomic distribution of sample (n ⫽ 222)1
Gorilla
Pan
n ⫽ 102
F
M
G. g. beringei
G. g. gorilla
G. g. graueri
13
22
8
17
32
10
n ⫽ 120
P.
P.
P.
P.
t. schweinfurthii
t. troglodytes
t. verus
paniscus
F
M
13
26
9
10
27
27
3
5
1
Powell-Cotton Museum, Birchington, Kent, UK (14 individuals);
Museum für Naturkunde der Humboldt Universität, Berlin, Germany (21 individuals); Musée Royal de l’ Afrique Centrale, Tervuren, Belgium (69 individuals); Anthropologisches Institut und
Museum der Universität Zürich-Irchel, Zürich, Switzerland (23
individuals); American Museum of Natural History, New York,
NY (44 individuals); British Museum of Natural History, London,
UK (15 individuals); National Museum of Natural History, Washington, DC (36 individuals).
MATERIALS AND METHODS
Sample composition
Data were acquired from femora and humeri of
222 G. gorilla, P. paniscus, and P. troglodytes specimens. The sample encompassed the six commonly
recognized subspecies of African pongids beringei,
gorilla, graueri, schweinfurthii, troglodytes, and
verus (Table 1; background information for individual specimens listed in Carlson, 2002b, Appendix A).
All specimens were relatively complete (i.e., few
missing elements), skeletally mature, apparently
healthy (as assessed skeletally), and unaffected by
catastrophic injury (i.e., no visible evidence of healed
or unhealed fractures in any long bones). Among
smaller groups, the completeness criterion (i.e.,
number of missing long bones) occasionally was relaxed to ensure sufficient sample sizes, despite the
possibility that locomotor performance-altering fractures in the appendicular skeleton would have been
missed in such specimens. When sex was not indicated in museum records (n ⫽ 53), it was predicted
via a discriminant analysis using orbital, articular,
and diaphyseal metric measurements (Carlson,
2002b). The sample incorporated an approximately
equal number of left and right bones, with a femur
and humerus measured from the same side in each
individual. In a few instances (i.e., less than five), a
femur and contralateral humerus were matched in
order to bolster sample size. Single slice scans were
made at 35%, 50%, and 65% length for each pair of
bones (see below for definitions of length).
CT scan parameters
Critical user-selected CT parameters, such as field
of view (FOV), matrix size, and slice thickness, were
standardized to the extent possible (see values reported in Carlson, 2002b). Remaining user-selected
parameters (e.g., kV, mA, mAs, and scanning time),
while also standardized, varied more, since settings
often were specific to the CT manufacturer. All images were reconstructed using a bone algorithm,
since this facilitated edge-detection better than
other commercially available options (Ohman, 1993;
316
K.J. CARLSON
Ruff and Leo, 1986; C. Zollikofer, personal communication, 1999).
Since CT images are digital representations of the
scan field divided into a finite number of pixels,
maintaining a constant pixel size is necessary for
standardizing the resolution of images. Pixel length
in a CT digital image is calculated as the matrix size
(held constant as 512 ⫻ 512 pixels) divided into the
FOV (200 mm at all facilities save one, which used
180 mm). Digital image data acquired from 6 of the
7 CT facilities had equivalent pixel areas (approximately 0.39 ⫻ 0.39 mm ⫽ 0.15 mm2), while pixel
area from the seventh location differed by approximately 0.03 mm2. Voxels, pixel area multiplied by
slice thickness (2.0 mm at five facilities, 1.5 mm at
one facility, and 1.0 mm at one facility), represent
three-dimensional units of space in digital image
data. A voxel is assigned a CT number that represents the average of all CT numbers for objects occupying that discrete unit of space (e.g., bone, air,
and soft tissue). Each CT number corresponds to a
linear attenuation coefficient, which is a measure of
apparent density in Hounsfield units (HUs). The CT
number for water is conventionally 0 HUs, while air
is calibrated to ⫺1,000 HUs (Hendee, 1983). The CT
number for cortical bone is typically around 2,000
HUs (Ohman, 1993). Since all bones were scanned in
air, the only objects that factored into voxel CT
numbers were bone, air, and the rare desiccated
soft-tissue. Additional discussions of technical issues relevant to using CT in research appear elsewhere (Hendee, 1983; Newton and Potts, 1981; Ruff
and Leo, 1986; Sumner et al., 1985, 1989; Spoor et
al., 2000).
Given time and resource constraints, spatial resolution of each CT scanner could not be determined
precisely for a given set of parameters (e.g., line
pairs per centimeter; cf. Ohman, 1993). Equivalency
of CT numbers and object cross-sectional properties
at different CT facilities was assessed by scanning
two standard objects (a water-filled container and a
segment of a machined aluminum pipe) at each facility. Cross-sectional geometric properties for a reference object (i.e., the pipe) did not differ between
facilities by more than 5% (Table 3.2 in Carlson,
2002b). Thus, potential variation due to CT facility,
including a difference in pixel area or voxel volume,
was considered trivial.
Scanning preparations
Positioning and scanning required approximately
5 min per bone pair. Scan times were 2.0 sec or less
per slice. The majority of time required for generating CT digital image data was spent aligning specimens, as opposed to actual image acquisition and
reconstruction. Guide devices (e.g., lasers or lights
integrated into the scanner), which permit precise
alignment of bones, were available at all CT facilities. By positioning predefined reference axes of
specimens (i.e., AP, ML, and longitudinal) parallel
to these guide devices, second moments of area
(SMAs) about anatomical axes (e.g., Ix, Iy) could be
measured.
Femoral and humeral reference axes were defined
previously (Carlson, 2002b; Ruff, 1981, 2002). Scan
locations on a diaphysis were selected by identifying
35%, 50%, and 65% femoral mechanical length
(Carlson, 2002b; Ruff, 1981, 2002) or humeral maximum length (Carlson, 2002b; Ruff, 2002).
A femur and humerus from a single individual
were scanned simultaneously. Aligning and scanning a minimum number of bones (e.g., a pair) ensured that they could be placed as near to the center
of the gantry opening as possible. Center positioning
is important because objects positioned near the
edge of the scan field are more distorted than objects
positioned near the center (Newton and Potts, 1981;
Ruff and Leo, 1986). While scanning single elements
rather than pairs would have facilitated even
greater center positioning, and further reduced potential beam hardening artifacts, these concerns
were outweighed by practical issues (e.g., finite
scanning opportunities). The humerus was adjusted
between scans so that the humeral region of interest
(ROI) matched the femoral ROI in a CT digital image (i.e., 35%, 50%, or 65%). This facilitated image
analysis and archiving.
A sturdy styrofoam square (⬇ 2.25 cm thick) was
affixed to the scanner bed in order to create a flat
surface that could be moved with CT table controls.
An ordinary carpenter’s level was placed on the styrofoam surface, but out of ROI scan planes, to allow
continual assessment of the horizontal level of the
surface. The styrofoam platform was covered with
parallel lines for relatively quick, accurate positioning of a bone along its longitudinal axis. For larger
bones, a second piece of styrofoam was inserted under the original lined piece in order to avoid its
deformation. Styrofoam is more appropriate than
wood, metal, or plastic because it introduces fewer
“streaks,” e.g., clip artifacts, in an image (C. Zollikofer, personal communication, 1999). Once reference axes of a bone were aligned to CT guide devices,
proximal and distal reference points of a bone were
leveled in the ML plane (Ruff, 1981). Proximal and
distal reference points (Fig. 2; also see Ruff, 2002)
could be leveled to within 0.8 mm or less, using a
series of premeasured wooden blocks. Careful leveling prevented distortion in cross sections due to AP
curvature (Fig. 3). Humeri and femora were leveled
in the ML plane following the same protocol, although humeral adjustments were less frequently
necessary since they exhibited less AP curvature.
Three locations (35%, 50%, and 65% lengths;
Fig. 2) per diaphysis were chosen for analysis. Comparable data were available from the same ROIs in
ape femora and humeri (Ohman, 1993; Ruff, 1987,
2002). The midshaft diaphysis (50% length) is theoretically the location of the highest bending strains
according to a beam model (Biewener and Taylor,
1986; Mott, 1996). Neighboring areas of the diaphysis (e.g., 35% and 65% lengths) may exhibit rela-
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
Fig. 2. Approximate location of femoral and humeral regions
of interest (ROIs). For femur (a) and humerus (b) in lateral view,
longitudinal axis is level in ML plane when difference between
distances h1 and h2 is 0.8 mm or less. Approximate locations of
ROIs (35% (mid-distal), 50% (midshaft), and 65% (midproximal)
diaphyseal lengths) are displayed for femur and humerus. Approximate locations of proximal and distal AP/ML reference
points are depicted. *Deepest portion of patellar notch, which is
distal reference point of longitudinal axis in femur.
tively high bending strains as well. These locations
also were selected since they avoided areas of the
diaphysis that were likely to contain substantial
trabecular bone. When occasional trabecular bone
was observed, particularly in the mid-distal diaphysis of gorilla femora, this had negligible effects on
rigidity even if it could not be removed manually
from images (see Burr and Piotrowski, 1982; Ruff,
1983).
Image analysis
Compared to standard radiography, CT exhibited
greater accuracy and precision in reproducing geometric properties of a bone cross section (Ohman,
1993; Ruff, 1989). While potential sources of error
existed during image acquisition (e.g., beam hardening, Gibbs phenomenon, and “partial volume” artifacts) and image analysis (e.g., choice of image
display parameters, particularly window settings),
reasonable solutions have been proposed (Carlson,
2002b; Ohman, 1993; Ruff and Leo, 1986).
CT raw data were reconstructed into DICOM image files at each CT facility with the assistance of a
technician. Files were imported into two image analysis programs, Osiris 3.1 (Unité d’ Imageri Numerique, 1995) and Scion Image (release Beta 4.0.2),
each available as a free download on the worldwide
web. Scion Image is posted from NIH Image for the
317
Fig. 3. Effects of leveling vs. not leveling bones exhibiting AP
diaphyseal curvature. Solid lines represent periosteal envelope.
Dashed lines represent endosteal envelope. Dotted/dashed lines
represent region of interest from which data are acquired. Both
hypothetical long bones have the same dimensions, but differ in
orientation. a: Hypothetical bone is leveled by orienting its ML
plane (e.g., a coronal plane through proximal and distal diaphyseal midpoints of AP shaft diameter parallel to underlying surface), resulting in cross section to its left. b: Hypothetical bone is
not level on ML plane, resulting in cross section to its left. Comparing cross sections, width (e.g., intracortical envelope) at anterior and posterior regions is slightly expanded in b relative to in
a. Thus, more bone in anterior and posterior regions of cross
section b relative to a is an artifact of their different alignments.
Macintosh by Scion Corporation and available on
the Internet at http://www.scioncorp.com. Following
a recommendation to alter the traditional fullwidth-half-maximum (FWHM) threshold for determining the bone/air boundary (Ohman, 1993, p. 42–
45), a custom Scion Image macro was written to
calculate the mean FWHM (mFWHM) of a cross
section (see Carlson, 2002b, Appendix B). Replacing
the standard FWHM protocol with the mFWHM
protocol added approximately 30 sec to the time
required to complete the analysis of an image.
Briefly, the mFWHM threshold considers variation
within the CT numbers of a cross section, while the
FWHM threshold relies only on the single densest
voxel in an image (i.e., one CT number). The
mFWHM threshold tailors the actual bone/air
threshold to an individual cross section by embracing variation in optical density of that cross section
rather than ignoring it as the FWHM threshold
does. This is particularly relevant when multiple
objects (e.g., bones) are scanned simultaneously. If
318
K.J. CARLSON
TABLE 2. Locomotor behavior percentages
Locomotor
Taxon (Total)
1
G. g. beringei
(10.71)
(9.77)
G. g. gorilla
(15.73)
(8.53)
P. paniscus5
P. t. schweinfurthii
(15.75)
(15.97)
P. t. verus
(13.59)
(14.57)
2
Combined locomotor3
Arboreal4
Sex
Arb
Terr
Q walk
Q climb
Q scramble
Suspend
Bipedal
SU
B
Q
QS
QC
F
M
8.15
2.32
91.85
97.68
90.02
94.30
2.65
0.63
0.20
0.21
0.20
0.00
6.31
4.22
2.50
0.00
7.50
18.18
52.50
45.45
2.50
9.09
32.50
27.27
F
M
9.13
2.03
90.87
97.97
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
10.99
3.80
4.40
1.27
14.29
21.52
30.76
25.31
39.56
48.10
F
M
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
⫺
18.20
15.31
1.30
1.41
25.51
17.72
25.33
25.78
23.84
30.51
F
M
12.02
8.20
87.98
91.80
91.49
93.85
5.96
4.27
1.23
0.26
0.95
0.60
0.28
0.26
7.87
7.29
2.36
2.08
30.71
33.33
10.24
3.13
48.82
52.08
F
M
18.20
14.70
81.80
85.30
85.63
86.61
9.29
8.33
1.89
1.37
1.45
1.09
1.16
1.23
7.44
5.83
0.83
5.83
30.58
11.65
8.26
7.77
51.24
59.22
1
All locomotor behavior as a percentage (multiplied by 100) of total positional behavior repertoire.
Percentages (multiplied by 100) of arboreal (Arb) and terrestrial (Terr) locomotion.
3
Percentages of locomotor behaviors in pooled arboreal and terrestrial substrates/superstrates.
4
Percentage (multiplied by 100) of SU ⫽ suspend (includes brachiate, arm swing, and drop), B ⫽ bipedal (includes bipedal walk, run,
and stand), Q ⫽ quadrupedal walk (includes quadrupedal walk and run, tripedal walk and run, and knuckle-walking or palmigrade
quadrupedalism), QS ⫽ quadrupedal scrambling (includes scramble, bridge, fireslide, tree sway, and leap), and QC ⫽ quadrupedal
climbing (on vertical or inclined substrates) within arboreal locomotor behaviors only.
5
Bout sampling data.
2
the FWHM threshold is used when multiple objects
are scanned, one bone (i.e., the one containing the
voxel with the highest CT number) conceivably
could set the threshold for the other bone. Since
apparent density of bone (e.g., measured by CT
numbers) varies due to biological (Martin et al.,
1998) or diagenetic processes (e.g., curation techniques), even within a single cross section (Burr,
1979a,b; Ruff and Leo, 1986), an mFWHM threshold
is preferable to a FWHM threshold.
On occasion, preprocessing of cross sections was
necessary. For example, some cross sections contained trabecular bone, a nutrient foramen, or longitudinal cracks as a result of postmortem events.
Obvious trabecular bone was “erased” to the level of
the neighboring endosteal envelope, using pencil
and brush tools in Scion Image. If a nutrient foramen appeared in a cross section (e.g., at the humeral
midshaft), the image was adjusted (i.e., in less than
10 of the approximately 1,300 cross sections), depending on how much of the total area of the nutrient foramen was in the cortical wall (i.e., area relative to a line running through the foramen and
connecting the neighboring endosteal borders). If
more than 50% of the foramen lay within the cortical
wall, bone tissue separating the foramen from the
medullary space was considered cortical bone, and
no modification was made. If less than 50% of the
foramen lay within the cortical wall, bone tissue
separating the foramen from the medullary space
was considered trabecular bone and it was removed.
In the rare instance (i.e., in less than 5 of the approximately 1,300 cross sections) when cortical bone
in a cross section was interrupted by a longitudinal
crack in the diaphysis, the resulting gap in a cross
section prevented calculation of cross-sectional properties. In each case, it was clear that the crack was
a postmortem event. Crack openings at the perios-
teal and endosteal envelopes (⬇ 1 mm or less in
width) were bridged with minimal “bone,” using the
pencil tool in Scion Image. After continuous surfaces
were restored, the remaining intracortical portion of
the crack was left unfilled to minimize distorting
cortical area, SMAs, and PMAs.
Following thresholding and preprocessing adjustments, Scion Image macros modeled after the SLICE
program (Nagurka and Hayes, 1980) were used to
calculate standard cross-sectional properties.
Behavioral data
Percentages of locomotor behaviors occurring
within terrestrial and arboreal settings are derived
and discussed in depth elsewhere (Carlson et al.,
unpublished findings). Briefly, these data were calculated from Doran (1989, original data), Doran and
Hunt (1994, Tables 16.3, 16.4, and 16.5), Hunt
(1989, 1992, original data), and Remis (1994, Tables
4.4, 4.20, 4.21, and 4.22, 1995, 1998) (Table 2). Doran (1989) and Remis (1994) used instantaneous
focal sampling with 1-min intervals, while Hunt
(1989) used 2-min intervals with instantaneous focal
sampling. Given large sample sizes, rare behaviors
should be represented equally, regardless of
whether 1- or 2-min intervals are used (K. Hunt,
personal communication, 2002). The G. g. gorilla
data were pooled wet and dry season data, and
pooled lone and group male data (Remis, 1994, Tables 4.4, 4.20, 4.21, and 4.22). Percentages of arboreal
locomotion for G. g. gorilla females and males were
calculated by multiplying sex-specific values for total
locomotion (i.e., travel in Remis, 1994, Table 4.4) and
percentages of first contacts in which gorillas were
arboreal. Data on positional behavior repertoires for
G. g. graueri and P. t. troglodytes are unavailable.
To the extent possible, methodological differences
between behavioral studies were compensated by
319
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
TABLE 3. Group means for principal moment of area ratios1
G. g. beringei
G. g. gorilla
G. g. graueri
Bonobo
P. t. schweinfurthii
P. t. troglodytes
P. t. verus
1
2
Sex
n
F 35
F 50
F 65
n
H 35
H 50
H 65
F
M
F
M
F
M
F
M
F
M
F
M2
F
M
11
15
22
30
8
10
10
5
13
26
26
26
9
2
1.82
1.99
2.05
2.33
1.85
2.18
1.16
1.17
1.29
1.33
1.37
1.37
1.59
1.25
1.61
1.68
1.74
2.04
1.60
1.68
1.14
1.18
1.28
1.31
1.35
1.37
1.52
1.36
1.17
1.25
1.34
1.52
1.34
1.33
1.29
1.40
1.35
1.39
1.40
1.41
1.41
1.25
13
17
22
32
8
9
9
4
13
26
26
26
9
3
1.27
1.51
1.29
1.49
1.22
1.46
1.13
1.23
1.23
1.39
1.21
1.34
1.23
1.45
1.30
1.43
1.21
1.42
1.20
1.22
1.32
1.24
1.29
1.21
1.24
1.19
1.38
1.32
1.17
1.18
1.17
1.14
1.14
1.19
1.17
1.22
1.24
1.20
1.21
1.14
1.32
1.20
F, femur; H, Humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis.
Mid-proximal locations were sampled from only 25 individuals due to a scanning error.
collapsing or expanding behavioral categories, following suggestions of Hunt et al. (1996). It was not
possible to separate the frequency of individual acrobatic behaviors used by Remis (1994), so all acrobatic behaviors were pooled as scrambling behaviors. The scrambling category combined vertical
scrambling, bridging, leaping, tree sway, and firepole slide. Among the acrobatic behaviors, leaping,
tree sway, and firepole slide were comparatively
rare in chimpanzees and mountain gorillas. Quadrupedal walking combined tripedal or quadrupedal
walking/running, knuckle-walking, and palmigrade
quadrupedalism. The bipedal category pooled bipedal walking/running and assisted/unassisted bipedal standing. A majority of these observations were
likely bipedal standing, since most bipedalism in
African apes occurs posturally rather than during
locomotion (Hunt, 1994). The suspensory category
combined brachiation, arm swing, and drop.
Statistical analyses
Distributions of data were assessed with Kolmogorov-Smirnov normality tests. Sex-specific subspecies
distributions of PMA ratios did not depart significantly
from normal distributions. The Levene test for homogeneity of variances assessed equal variances. Since
data did not depart significantly from normal distributions, parametric statistical tests were chosen. Analysis of variance (ANOVA) was selected as the statistical
test to assess group differences in PMA ratios. A significant ANOVA result was explored further with a
Bonferroni (equal variances) or Tamhane’s T2 (unequal variances) post hoc test. The Bonferroni method
was preferable for its conservative nature (e.g., accounted for multiple comparisons). Pearson correlations were used to examine associations between PMA
ratios and locomotor behavior percentages. Statistical
significance was assigned when P ⬍ 0.05. Statistical
tests were performed with SPSS software, version
11.0.1 (SPSS, Inc., Chicago, IL).
RESULTS
One-way ANOVA results and descriptive statistics for group mean PMA ratios at genus- and spe-
Fig. 4. Line plot of principal moments of area (PMAs) ratio for
sex-specific group means reported in Table 5. Ratios, along y-axis,
plotted against femoral (F) and humeral (H) regions of interest
(ROIs) at 35%, 50%, and 65% diaphyseal lengths, along x-axis.
For each group, a line connects points from corresponding ROIs in
order to visualize diaphyseal trends, as well as to contrast femoral and humeral trends.
cies-level comparisons are reported elsewhere (Carlson, 2002b, Tables 7.1–7.4, summarized in Table
7.5). Sex exhibits a significant interaction with
taxon, hence sexes are treated individually within
taxa. In the absence of bilateral data from individuals, side differences are not emphasized (i.e., sides
are pooled).
Group differences in mean PMA ratios
Subspecific means for femoral and humeral ratios
are reported in Table 3 and are plotted by ROI in
Figure 4. Group mean PMA ratios are more variable
in the femoral than the humeral diaphysis (Fig. 4).
Variation between groups is lower in more proximal
ROIs of both diaphyses. Among female Pan groups,
the largest humeral ratios (i.e., least circular cross
sections) are observed at the midshaft. No taxon consistently exhibits smaller or larger ratios (i.e., lesser or
320
K.J. CARLSON
TABLE 4. One-way ANOVA results for comprehensive sample1
1
Location
F 35
F 50
F 65
H 35
H 50
H 65
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Females
Males
SS
df
MS
F
P
SS
df
MS
F
P
10.014
3.950
3.928
3.479
0.483
2.309
0.210
1.206
0.287
1.332
0.228
1.093
6
92
6
92
6
92
6
93
6
93
6
93
1.669
0.043
0.655
0.038
0.080
0.025
0.035
0.013
0.048
0.014
0.038
0.012
38.877
0.000**
42.185
0.000**
3.206
0.007**
4.681
0.000**
2.700
0.018*
3.324
0.005**
3.337
0.005**
12.067
0.000**
3.237
0.006**
3.882
0.052
1.766
0.042
0.146
0.031
0.101
0.030
0.219
0.018
0.015
0.008
0.000**
0.000**
6
107
6
107
6
106
6
110
6
110
6
109
74.293
17.313
23.294
5.591
10.594
4.478
0.875
3.304
0.606
3.342
1.312
1.993
0.091
0.887
1.858
0.095
1
F, femur; H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, midproximal diaphysis.
* P ⬍ 0.05.
** P ⬍ 0.01.
SS, sum of squares; MS, mean squares.
TABLE 5. Summary of post hoc ANOVA results1
G. g.
beringei
Fe
G. g. beringei
G. g.
gorilla
G. g.
graueri
F65*2
F65**2
G. g. gorilla
G. g. graueri
M
Bonobo
H35**3
P. t. schweinfurthii
P. t. troglodytes
P. t. verus
H50**2
F35**2
F50**3
F65**3
G. g. beringei
G. g. gorilla
G. g. graueri
H50*2
H50*2
Bonobo
P. t. schweinfurthii
P. t. troglodytes
H50*2
H50**2
H35*2
H50**2
H50**2
H50**2
H35*2
H50**2
F50**3
P. t.
schweinfurthii
P. t.
troglodytes
F35**2
F50**2
F35**2
F50**2
F35**2
F50**2
F65**2
F35**2
F50**2
F35**2
F50*2
F35**2
F50**2
F65**2
F35**2
F50**2
F35**2
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
F35**2
F50**3
Bonobo
F35**2
F50**2
F35**2
F50**2
P. t.
verus
F35**2
F35**2
F50*2
F35*2
F50**3
P. t. verus
1
Fe, female; M, male; F, femur; H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis.
Unequal variances post hoc test (Tamhane’s T2) was used when groups failed Levene test for homogeneity of variances.
3
Equal variances post hoc test (Bonferroni method) was used when groups passed Levene test for homogeneity of variances.
* P ⬍ 0.05.
** P ⬍ 0.01.
2
greater circularity of cross sections) throughout both
diaphyses when groups are compared. Less generalized trends, however, are apparent. Within the femoral diaphysis, gorilla subspecies typically exhibit
smaller ratios proximally (i.e., more circular cross sections), while Pan groups (except P. t. verus) exhibit
larger ratios proximally (i.e., less circular) (Fig. 4).
Bonobos usually exhibit the smallest femoral ratios
(i.e., most circular cross sections), while western lowland gorillas exhibit the largest (i.e., least circular).
One-way ANOVAs examining sex-specific taxonomic differences in group mean ratios are reported
in Table 4. At each ROI, females differ significantly
in group mean ratios, as do males (excluding the
mid-proximal humeral ROI). Post hoc analyses demonstrate significant differences between sex-specific
groups (Table 5). For females and males, a majority
of these differences occur between a gorilla and a
Pan group (see Table 5, upper right and lower left
quadrants for female and male sections).
In order to address the possibility that a difference
in body size between gorilla and Pan groups may be
obscuring variation within groups, a second set of
one-way ANOVAs is reported, in which Gorilla and
Pan are analyzed separately (Table 6). Gorilla subspecies differ significantly at the mid-distal and
321
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
TABLE 6. One-way ANOVA results for Gorilla and Pan samples analyzed separately1
Females
Genus
Location
Gorilla
F 35
F 50
F 65
H 35
H 50
H 65
Pan
F 35
F 50
F 65
H 35
H 50
H 65
Males
Variance
SS
df
MS
F
P
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
Between groups
Within groups
0.484
2.334
0.187
1.514
0.229
0.840
0.031
0.528
0.072
0.370
0.005
0.277
0.945
1.616
0.742
1.965
0.109
1.468
0.067
0.678
0.142
0.963
0.120
0.817
2
38
2
38
2
38
2
40
2
40
2
40
3
54
3
54
3
54
3
53
3
53
3
53
0.242
0.061
0.094
0.040
0.115
0.022
0.016
0.013
0.036
0.009
0.002
0.007
0.315
0.030
0.247
0.036
0.036
0.027
0.022
0.013
0.047
0.018
0.040
0.015
3.942
0.028*
2.348
0.109
5.187
0.010*
1.176
0.319
3.893
0.029*
0.353
0.705
10.529
0.000**
6.796
0.001**
1.337
0.272
1.743
0.169
2.609
0.061
2.602
0.062
SS
df
MS
F
P
1.129
4.379
1.793
3.091
0.814
1.718
0.013
1.341
0.311
1.323
0.031
0.372
0.184
1.213
0.174
1.388
0.049
1.586
0.121
2.001
0.050
0.670
0.050
0.514
2
52
2
52
2
52
2
55
2
55
2
55
3
55
3
55
3
54
3
55
3
55
3
54
0.564
0.084
0.897
0.059
0.407
0.033
0.007
0.024
0.155
0.024
0.016
0.007
0.061
0.022
0.058
0.025
0.016
0.029
0.040
0.036
0.017
0.012
0.017
0.010
6.704
0.003**
15.083
0.000**
12.328
0.000**
0.271
0.763
6.464
0.003**
2.321
0.108
2.779
0.050*
2.293
0.088
0.552
0.649
1.108
0.354
1.376
0.260
1.752
0.167
1
F, femur; H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis.
* P ⬍ 0.05.
** P ⬍ 0.01.
SS, sum of squares; MS, mean squares.
mid-proximal femoral diaphysis (females and
males), femoral midshaft (males only), and humeral
midshaft (females and males). Pan groups, in contrast, differ significantly only at the mid-distal femoral diaphysis (females and males) and femoral midshaft (females only). In four other diaphyseal
locations (three among females, one among males),
differences between group mean ratios approach
statistical significance (e.g., P ⬍ 0.11). Post hoc analyses of separated genera indicate significant differences between subspecies (Table 7). Those subspecific differences that are significant only after
separating genera in analyses include: female
mountain and western lowland gorillas at mid-distal
femoral and midshaft humeral diaphyses, male lowland gorilla subspecies at the mid-proximal femoral
diaphysis, female western and central chimpanzees
at the mid-distal femoral diaphysis, and male bonobos and central chimpanzees at the mid-distal femoral diaphysis (compare Tables 5 and 7).
Variability in group PMA ratios
Since ANOVA between-groups vs. within-groups
variance ultimately determines statistical significance, a significant result may be attributed to either remarkably high variation between group
means, or remarkably low variation between individuals within groups. Similarly, nonsignificant results may be attributable to the converse relationships. There is biological meaning in either scenario,
in that whether one of the two sources of variance
drives significance or nonsignificance is potentially
useful information.
Whether considering between-groups or withingroups variance (average square difference from the
mean), each is generally higher in the femoral than
the humeral diaphysis of Pan groups (Table 6). Nonsignificant ANOVA results of Pan mid-distal and
midshaft humeral diaphyses, in comparison to significant results for analogous femoral ROIs, exhibit
much lower humeral (e.g., factor of 5–10) betweengroups variance (sum of squares: for H35, 0.067
[F35 ⫽ 0.945]; for H50, 0.142 [F50 ⫽ 0.742]) and
only slightly lower humeral (e.g., factor of 2–3) within-groups variance (sum of squares: for H35, 0.678
[F35 ⫽ 1.616]; for H50, 0.963 [F50 ⫽ 1.965]). In
other words, group mean ratios from both the middistal and midshaft diaphyses are more similar in
the humerus than the femur, since variation between groups is lower in the humerus (see also, Fig.
4). Nonsignificant ANOVA results for Pan humeral
ROIs, when juxtaposed with significant ANOVA results for analogous femoral ROIs, appear related to
less divergence within the range of group mean
PMA ratios (i.e., individuals may vary in humeral
PMA ratios, but little of this is explained by group).
Pan groups exhibit a pattern in mid-proximal diaphyses (greater similarity in femoral and humeral between-groups variance than within-groups variance) that is opposite the pattern in more distal
locations of diaphyses.
While occasionally the magnitude of humeral
between-groups or within-groups variance exceeds
analogous femoral variances in the Pan sample,
gorilla humeral variances never exceed femoral
variances (Table 6). Gorilla sexes exhibit predom-
322
K.J. CARLSON
P. t. troglodytes
P. t. schweinfurthii
2
F35**3
F50**2
F35**3
F35*3
F35**3
F50**2
M
H50**3
P. t. verus
P. t. troglodytes
P. t. schweinfurthii
P. t. schweinfurthii
P. t. troglodytes
P. t. verus
Bonobo
G. g. graueri
G. g. gorilla
H50*3
Bonobo
Fe
1
F35**
F50**3
F65**3
M
F65**
F35*
F65**2
G. g. beringei
Fe
Fe, female; M, male; F, femur; H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis.
Unequal variances post hoc test (Tamhane’s T2) was used when groups failed the Levene test for homogeneity of variances.
3
Equal variances post hoc test (Bonferroni method) was used when groups passed Levene test for homogeneity of variances.
* P ⬍ 0.05.
** P ⬍ 0.01.
Do summed arboreal locomotor behaviors
correlate negatively with PMA ratios?
H50**3
Bonobo
F50**3
F65*3
G. g. graueri
3
G. g. gorilla
G. g. beringei
G. g. graueri
2
3
G. g. gorilla
G. g. beringei
TABLE 7. Summary of post hoc ANOVA results for Gorilla and Pan samples analyzed separately1
F35*3
P. t. verus
inantly the same variance patterns as Pan sexes:
humeral variances are absolutely lower than femoral variances, and between-groups variance is
usually much lower than within-groups variance
in the humerus, but this difference is less in analogous femoral variances. Female gorillas exhibit
much lower humeral between-groups variance at
the mid-distal and midproximal humeral diaphysis, rather than at the mid-distal and midshaft
diaphysis as do female Pan. Gorilla males, unlike
Pan males, have consistently much lower between-groups variance than within-groups variance in each of the humeral ROIs when comparing
analogous femoral and humeral variances (i.e.,
gorilla males vary little by group).
Correlations between group mean PMA ratios and
locomotor behaviors are reported in Table 8 (femoral)
and Table 9 (humeral). A negative correlation between
group mean ratios and percentages of total arboreal
locomotion is observed at each ROI, except at the midproximal humerus. Two of the five negative correlations (i.e., mid-distal femur and humerus) exhibit statistical significance, while a third (i.e., midshaft femur)
exhibits borderline statistical significance.
Analyzing Gorilla and Pan separately provides a
means of reducing potential confounding effects of
their body size differences. In gorillas, 5 of 6 correlations between PMA ratio and the percentage of
total arboreal locomotion remain negative, while the
mid-proximal humerus maintains a positive correlation (Tables 10 and 11). Negative correlations are
significant at the mid-distal and midshaft humerus.
In Pan groups, however, only 2 of 6 correlations are
negative (i.e., mid-proximal femur and mid-distal humerus). Neither negative correlation is significant.
Does PMA ratio correlate negatively with
scrambling percentage?
Among femoral ROIs, correlations between arboreal scrambling and group mean PMA ratio are positive (Table 8). In contrast, humeral ROIs exhibit a
negative correlation with arboreal scrambling, although coefficients are nonsignificant and relatively
low in strength (i.e., ⱕ0.3) (Table 9).
Gorillas exhibit negative correlations at 2 of 6
ROIs (midshaft and midproximal humerus) when
analyzed separately from Pan (Tables 10 and 11).
Neither correlation is significant. Pan, on the other
hand, exhibits negative correlations at all ROIs when
analyzed separately. The correlation for the femoral
midshaft, however, is the only significant one.
Does PMA ratio correlate positively with
arboreal quadrupedal walking percentage?
Mid-distal and midshaft diaphyses exhibit positive correlations between group mean PMA ratios
and percentages of arboreal quadrupedal walking,
while mid-proximal diaphyses exhibit negative cor-
323
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
TABLE 8. Pearson correlations between femoral PMA ratios and locomotor behaviors (comprehensive sample)1
F 35
Imax/Imin
r
n
Sign as
predicted
Correlation
rank2
F 50
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
F 65
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
% total
quad
walk
% total
quad
climb
% total
quad
scramble
% total
suspensory
% overall
arboreal
locomotion
% arboreal
quad walk
% arboreal
quad climb
% arboreal
quad
scramble
% arboreal
suspensory
0.270
6
Yes
⫺0.675
6
No
⫺0.476
6
Yes
⫺0.672
6
Yes
⫺0.690*
8
Yes
0.205
10
Yes
⫺0.053
10
No
0.187
10
No
⫺0.596*
10
Yes
4
1
3
2
2
4
3
1
0.040
6
Yes
⫺0.507
6
No
⫺0.325
6
Yes
⫺0.534
6
Yes
0.116
10
Yes
0.114
10
Yes
0.144
10
No
⫺0.635*
10
Yes
4
2
3
1
3
4
2
1
⫺0.072
6
No
0.516
6
Yes
0.504
6
No
0.641
6
No
⫺0.450
10
No
0.356
10
Yes
0.425
10
No
0.176
10
No
4
2
3
1
1
3
2
4
⫺0.6213
8
Yes
⫺0.082
8
Yes
1
F, femur; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis; quad, quadrupedal.
1, highest; 4, lowest.
3
P approaches 0.05.
* P ⬍ 0.05 (one-tailed).
2
TABLE 9. Pearson correlations between humeral PMA ratios and locomotor behaviors (comprehensive sample)1
H 35
Imax/Imin
r
n
Sign as
predicted
Correlation
rank2
H 50
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
H 65
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
% total
quad
walk
% total
quad
climb
% total
quad
scramble
0.390
6
Yes
⫺0.423
6
No
⫺0.447
6
Yes
⫺0.481
6
Yes
4
3
2
1
⫺0.193
6
No
⫺0.082
6
No
0.230
6
No
⫺0.067
6
Yes
2
3
1
4
⫺0.586
6
No
0.745*
6
Yes
0.848*
6
No
0.828*
6
No
4
3
1
2
% total
suspensory
% overall
arboreal
locomotion
⫺0.644*
8
Yes
⫺0.248
8
Yes
0.819**
8
No
% arboreal
quad walk
% arboreal
quad climb
% arboreal
quad
scramble
% arboreal
suspensory
0.042
10
Yes
0.337
10
Yes
⫺0.237
10
Yes
⫺0.757**
10
Yes
4
2
3
1
0.276
10
Yes
⫺0.038
10
No
⫺0.131
10
Yes
⫺0.507
10
Yes
2
4
3
1
⫺0.025
10
No
0.323
10
Yes
⫺0.300
10
Yes
0.145
10
No
4
1
2
3
1
H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis; quad, quadrupedal.
1, highest; 4, lowest.
* P ⬍ 0.05 (one-tailed).
** P ⬍ 0.01 (one-tailed).
2
relations (Tables 8 and 9). No correlations are significant.
Separating genera illustrates different patterns of
associations between PMA ratios and behaviors (Ta-
bles 10 and 11). Only 2 of 6 ROIs (i.e., midshaft and
midproximal humerus) exhibit positive correlations
among gorillas. Neither coefficient is significant. Four
of 6 ROIs exhibit positive correlations among Pan, but
324
K.J. CARLSON
TABLE 10. Pearson correlations between femoral PMA ratios and locomotor behaviors (separated Gorilla and Pan groups)1
% total
quad walk
F 35
Imax/Imin
r
n
Sign as
predicted
Correlation
rank2
F 50
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
F 65
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
% total
quad
climb
% total
quad
scramble
% total
suspensory
% overall
arboreal
locomotion
% arboreal
quad walk
% arboreal
quad climb
% arboreal
quad scramble
% arboreal
suspensory
Gorilla
(Pan)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
⫹(⫺0.479)
2 (4)
Yes (no)
⫺(0.525)
2 (4)
No (yes)
⫹(0.545)
2 (4)
No (no)
⫺(0.684)
2 (4)
Yes (no)
⫺0.586 (0.638)
4 (4)
Yes (no)
⫺0.722 (0.491)
4 (6)
No (yes)
0.817 (0.568)
4 (6)
Yes (yes)
0.726 (⫺0.629)
4 (6)
No (yes)
0.176 (⫺0.611)
4 (6)
No (yes)
(4)
(3)
(2)
(1)
3 (4)
1 (3)
2 (1)
4 (2)
⫹(⫺0.800)
⫺(0.815)
⫹(0.724)
⫺(0.854)
⫺0.549 (0.852)
⫺0.647 (0.193)
0.885 (0.732*)
2 (4)
Yes (no)
2 (4)
No (yes)
2 (4)
No (no)
2 (4)
Yes (no)
4 (4)
Yes (no)
4 (6)
No (yes)
4 (6)
Yes (yes)
0.642
(⫺0.771*)
4 (6)
No (yes)
0.129
(⫺0.782*)
4 (6)
No (yes)
(3)
(2)
(4)
(1)
2 (4)
1 (3)
3 (2)
4 (1)
⫹(0.258)
2 (4)
Yes (yes)
⫺(⫺0.195)
2 (4)
No (no)
⫹(⫺0.060)
2 (4)
No (yes)
⫺(0.053)
2 (4)
Yes (no)
⫺0.775 (0.568)
4 (6)
No (yes)
0.889 (⫺0.037)
4 (6)
Yes (no)
0.774 (⫺0.084)
4 (6)
No (yes)
0.278 (⫺0.055)
4 (6)
No (yes)
(1)
(2)
(3)
(4)
2 (1)
1 (4)
3 (2)
4 (3)
⫺0.476 (⫺0.031)
4 (4)
Yes (yes)
1
F, femur; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis; quad, quadrupedal. Numbers in parentheses
are for Pan (P); otherwise, they are for Gorilla, G.
2
1, highest; 4, lowest. Gorilla coefficient signs, but not magnitudes reported when n ⫽ 2.
* P ⬍ 0.05 (one-tailed).
TABLE 11. Pearson correlations between humeral PMA ratios and locomotor behaviors (separated Gorilla and Pan groups)1
% total
quad walk
H 35
Imax/Imin
r
n
Sign as
predicted
Correlation
rank2
H 50
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
H 65
Imax/Imin
r
n
Sign as
predicted
Correlation
rank
% total
quad
climb
% total
quad
scramble
% total
suspensory
% overall arboreal
locomotion
% arboreal
quad walk
% arboreal
quad climb
% arboreal quad
scramble
% arboreal
suspensory
Gorilla
(Pan)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
G (P)
⫹(0.074)
⫺(⫺0.167)
⫹(⫺0.469)
⫺(⫺0.443)
2 (4)
No (yes)
2 (4)
Yes (yes)
0.060
(⫺0.796*)
4 (6)
Yes (no)
⫺0.572 (⫺0.742)
2 (4)
No (no)
⫺0.009
(⫺0.323)
4 (6)
No (no)
0.040 (⫺0.706)
2 (4)
Yes (yes)
⫺0.982**
(⫺0.349)
4 (4)
Yes (yes)
4 (6)
No (yes)
4 (6)
Yes (yes)
(4)
(3)
(1)
(2)
4 (4)
2 (1)
3 (3)
1 (2)
⫹(⫺0.932*)
2 (4)
Yes (no)
⫺(0.962*)
2 (4)
No (yes)
⫹(0.991**)
2 (4)
No (no)
⫺(0.996**)
2 (4)
Yes (no)
0.314 (⫺0.044)
4 (6)
Yes (no)
⫺0.050 (0.137)
4 (6)
No (yes)
⫺0.293 (⫺0.047)
4 (6)
Yes (yes)
⫺0.821 (⫺0.119)
4 (6)
Yes (yes)
(4)
(3)
(2)
(1)
2 (4)
4 (1)
3 (3)
1 (2)
⫹(⫺0.564)
2 (4)
Yes (no)
⫺(0.630)
2 (4)
No (yes)
⫹(0.755)
2 (4)
No (no)
⫺(0.819)
2 (4)
Yes (no)
0.372 (0.324)
4 (6)
Yes (yes)
⫺0.865 (0.319)
4 (6)
No (yes)
⫺0.348 (⫺0.281)
4 (6)
Yes (yes)
0.003 (⫺0.380)
4 (6)
No (yes)
(4)
(3)
(2)
(1)
2 (2)
1 (3)
3 (4)
4 (1)
⫺0.968* (0.993**)
4 (4)
Yes (no)
0.388 (0.762)
4 (4)
No (no)
1
H, humerus; 35, mid-distal diaphysis; 50, midshaft diaphysis; 65, mid-proximal diaphysis; quad, quadrupedal. Numbers in parentheses are for Pan (P); otherwise, they are for Gorilla (G).
2
1, highest; 4, lowest. Gorilla coefficient signs, but not magnitude reported when n ⫽ 2.
* P ⬍ 0.05 (one-tailed).
** P ⬍ 0.01 (one-tailed).
none are significant. Only their mid-distal and midshaft humeral ROIs exhibit negative correlations.
Does bone shape (e.g., circularity) potentially
reflect scrambling more than other
arboreal behaviors?
Scrambling exhibits the second or third strongest
correlation with PMA ratio among four locomotor
behaviors (Tables 8 and 9). When compiling the average relative strength of all six correlation coefficients for each locomotor behavior (i.e., 1, strongest
correlation; 4, weakest correlation), scrambling is
surpassed in relative strength only by suspensory
behavior. The strength of correlations between the
percentage of scrambling and PMA ratios, however,
is generally low (r ⫽ 0.131– 0.425)
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
In analyses of separate genera, the relative pattern of correlation coefficient strengths differs between groups (Tables 10 and 11). Among gorillas,
quadrumanous climbing is followed in strength of
association by quadrupedal walking. Both surpass
scrambling in average strength of correlation coefficients. In Pan, scrambling has the same relative
position across the six ROIs as quadrumanous
climbing. Both locomotor behaviors are surpassed in
average position only by suspensory behavior.
DISCUSSION
Diaphyseal shape differences using PMA ratios
It is clear that Gorilla and Pan exhibited variable
shapes (e.g., different circularity as measured by
PMA ratio) in their femoral cross sections, particularly when viewing mid-distal and midshaft ROIs.
In the humeral diaphysis, significant shape differences between subspecies were observed only at the
midshaft, and only among gorillas. The midshaft of a
diaphysis theoretically encounters the highest bending loads. Thus, maximum femoral and humeral
bending loads presumably differ in orientation between African ape subspecies. Whether both genera
were included, or whether they were separated in
ANOVAs (compare Tables 5 and 7), several trends in
PMA ratios emerged (see below). Western lowland
gorillas and western chimpanzees (particularly females) exhibited the most distinct PMA ratios
among their respective genera.
Humeral PMA ratios exhibited substantially less
intergroup variability (between-groups variance)
than femoral PMA ratios when genera were analyzed separately. Femoral PMA ratios discriminated
between taxa more successfully than humeral ratios, for which between-groups and within-groups
variance diverged more, proportionately speaking,
throughout the diaphysis. This result appears
counterintuitive, since the forelimb would seem a
more likely candidate to differentiate groups during
arboreal locomotor behaviors than the hindlimb. If
primate hindlimb peak vertical forces usually exceed forelimb peak vertical forces (i.e., more weight
is carried on the hindlimbs than the forelimbs) during various arboreal forms of locomotion, as they
regularly do in primates during terrestrial quadrupedal locomotion (Demes et al., 1994; Kimura, 1985;
Kimura et al., 1979; Reynolds, 1985), then the hindlimb could experience a greater range of forces over
the full complement of locomotor behaviors. This
may contribute to the hindlimb apparently being a
better reflection of group differences in locomotor
behaviors than the forelimb.
Studies of other primates may offer a glimpse of
the SRFs encountered by African apes during locomotion. Old World monkeys remained hindlimbdominant during arboreal quadrupedalism, even after reducing the magnitude of SRF components
experienced by all limbs (Schmitt, 1998). Less reduction was observed in the hindlimbs than the fore-
325
limbs, but all forces were reduced below those encountered during terrestrial quadrupedalism.
Nonstrepsirhine primates experienced a larger vertical force component of the SRF in the hind limbs
than the forelimbs during vertical climbing
(Hirasaki et al., 1992). This distinction between
hind limbs and forelimbs, while less obvious, was
also observed in the horizontal force component (i.e.,
pushing or pulling against the vertical substrate). If
African apes are like other primates in this regard,
they also may experience greater SRF components
in their hind limbs than forelimbs during arboreal
locomotor behaviors (e.g., vertical climbing and
scrambling).
The humeral diaphysis apparently provides a signal that transcends group-specific behavioral patterns (i.e., much lower humeral between-groups
variance than within-groups variance when compared to the analogous femoral variances). This
could be related to greater individual-based than
group-based variation in forelimb segment configurations during locomotor behaviors of African apes.
Carlson et al. (2000) reported that both G. g. gorilla
and P. paniscus exhibited modal forelimb and hind
limb configurations during some positional behaviors, but not during others. Larger mammals exhibit
lower limb angles relative to SRFs during quadrupedal locomotion than smaller mammals, thus
avoiding excessively high bending moments generated by flexed limb postures (Biewener, 1983). It is
unclear, however, whether intrinsic variation within
a behavioral category (e.g., different limb segment
configurations within a locomotor mode) has an important effect on the associations between humeral
PMA ratios and percentages of locomotor behavior.
Forelimb cross-sectional properties in modern and
fossil human populations have been portrayed as
reflecting tool-use activities (e.g., Churchill, 1994;
Churchill et al., 1996; Trinkaus and Churchill, 1999;
Trinkaus et al., 1994). Humeral PMA ratios of apes
could also reflect the involvement of the forelimb in
nonlocomotor activities (e.g., tool use, and feeding or
postural behaviors). African apes, however, do not
exhibit tool manufacture or use activities to the
same extent as humans. Bending loads associated
with tool-making and tool use are almost certainly
less likely to impact the shape of a cross section in
the ape humeral diaphysis than bending loads arising during locomotor activities. Feeding or postural
behaviors in general, as typical “static” behaviors,
are also less likely to induce large bending loads in
the limbs than dynamic behaviors (e.g., locomotor
behaviors).
Group PMA ratios from midshaft ROIs that are
reported in the present study were broadly equivalent (i.e., similarly circular) to comparable data reported elsewhere. Previous studies of cross-sectional
properties in African apes were restricted to one
humeral ROI (Ohman, 1993) and one femoral ROI
(Ohman, 1993; Ruff and Runestad, 1992, ML/AP
ratios). While Ohman (1993) separated G. gorilla
326
K.J. CARLSON
sexes, he pooled P. troglodytes sexes, reporting only
a mid sex average. His African ape samples primarily represented P. t. troglodytes and G. g. gorilla. The
mid sex mean of the chimpanzee femoral PMA ratio
of 1.28 reported by Ohman (1993, Table 39) was
slightly lower (i.e., more circular) than a P. t. troglodytes mid-sex average (1.36) calculated from Table
3. Gorilla female (1.70) and male (1.80) femoral PMA
ratios reported by Ohman (1993) were also lower
(i.e., more circular) than comparable PMA ratios
reported in the present study (1.74 and 2.04, respectively). Humeral midshaft data reported by Ohman
(1993), on the other hand, exhibited more similarity
to data in the present study. Ohman (1993, Table
34) reported a mid-sex average for the humeral PMA
ratio of chimpanzees (1.24) that was close (i.e.,
equally circular) to the mid-sex average of female
and male P. t. troglodytes PMA ratios (1.22) calculated from Table 3. Mean female (1.23) and male
(1.37) gorilla PMA ratios reported by Ohman (1993)
were close (i.e., equally circular) to those reported in
the present study (1.21 and 1.42; Table 3). The low
femoral PMA ratios reported by Ohman (1993), relative to those presented here, could have reflected
idiosyncratic behavioral differences inherent to one
or both samples of G. g. gorilla.
Ohman (1993) also pooled sexes in his human
sample, reporting a higher average PMA ratio for
the humeral midshaft than the femoral midshaft
(i.e., a less circular humeral cross section). It is
interesting to note that Gorilla and P. troglodytes in
the present study exhibited the opposite pattern: a
higher PMA ratio for the femoral midshaft than the
humeral midshaft (i.e., less circular femoral cross
section), with one exception (P. t. schweinfurthii exhibited a greater humeral ratio, but by 0.01). Bonobo
females and males, however, were unique among
African apes in exhibiting the same pattern as H.
sapiens (i.e., humeral midshaft ratio ⬎ femoral midshaft ratio). A behavioral explanation for the similarity between humans and bonobos, to the exclusion of other African apes, is unclear.
A strong positive association at the femoral midshaft (r ⫽ 0.940) was reported between ML/AP bending rigidity ratios and body mass for a diverse range
of primates, including hominoids (Ruff and Runestad, 1992, their Fig. 5). An ML/AP ratio, however,
does not necessarily measure the same characteristic of a cross section as the PMA ratio. Figure 1
demonstrates that PMA ratios can provide a more
accurate assessment of cross section shape (e.g., circularity). Twenty of the 222 specimens (but only 18
of the 20 contributed humeral data) had associated
body mass data, most of which were chimpanzees. In
3 of 6 ROIs (F35: rs ⫽ 0.539, P ⬍ 0.05; F50: rs ⫽
0.647, P ⬍ 0.01; and H35: rs ⫽ 0.503, P ⬍ 0.05), PMA
ratio exhibited a significant correlation with body
mass. The other three ROIs exhibited weaker, nonsignificant correlations (F65: rs ⫽ 0.397; H50: rs ⫽
⫺0.292; and H65: rs ⫽ ⫺0.176). In the same 20
specimens (again, 18 for the humerus), ML/AP bend-
ing rigidity ratios usually exhibited a stronger correlation to body mass than PMA ratios. Correlations
between ML/AP ratios and body mass were significant at 4 of 6 ROIs (F35: rs ⫽ 0.605, P ⬍ 0.01; F50:
rs ⫽ 0.615, P ⬍ 0.01; H35: rs ⫽ 0.849, P ⬍ 0.01; and
H50: rs ⫽ 0.496, P ⬍ 0.05), while only two ROIs
exhibited nonsignificant correlation coefficients
(F65: rs ⫽ 0.235; and H65: rs ⫽ 0.135). Humeral
midshaft (H50) and midproximal (H65) ROIs exhibited negative (nonsignificant) correlations between
PMA ratio and body mass, but positive correlations
between ML/AP ratio and body mass (H50 was significant). Ratios of PMAs rather than ML/AP ratios
apparently reveal differences in locomotor repertoires more readily, apart from body mass differences, since ML/AP ratios appear more confounded
by differences in body mass.
It was not possible to determine the extent to
which body mass and PMA ratio were directly correlated in African apes independently of arboreal
locomotor behavior, or the extent to which they covaried due to a strong correlation between body
mass and arboreal locomotor behavior. It remains
unknown how much PMA ratio estimates arboreal
locomotion percentages vs. how much it estimates
body mass. A sample of individuals with associated
body mass, associated locomotor behavior, and associated cross-sectional properties is required before
these relationships can begin to be unraveled. Such
a sample could also ultimately prove more insightful
regarding within-groups variance and demonstrate
more clearly how strongly femoral or humeral diaphyseal PMA ratios are correlated with locomotor
behaviors. In the present sample, group PMA ratios
were correlated to group percentages of total arboreal locomotion in the proposed direction more often
than not, but this was less often the case when
specific arboreal locomotor behaviors were investigated.
Correlations between body mass and PMA ratio,
or ML/AP ratio for that matter, may be influenced by
correlations between body mass and arboreal locomotor behaviors. Group percentages of total arboreal locomotion exhibited a body mass trend, since
chimpanzee subspecies, for which behavioral data
exist, exhibited higher percentages of total arboreal
locomotion than gorilla subspecies with associated
behavioral data (Table 2). Mass-related trends
among specific arboreal locomotor behaviors may
have been muddled by potential bias reflected in P.
paniscus and G. g. gorilla behavior percentages.
Field studies that were the basis for these behavioral data reported that focal groups were not habituated fully at time of study (respectively, Doran,
1989, p. 194; Remis, 1994, p. 149). This was most
evident in an absence of terrestrial locomotor data
for both groups (but see Materials and Methods for a
description of how G. g. gorilla arboreal locomotion
percentage was estimated). However, these studies
minimized potential bias by discounting observa-
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
tions in which an individual was startled into fleeing
upon recognizing the presence of the observer.
PMA ratio and percentage of a
locomotor behavior
The first question posed (do PMA ratios correlate
negatively with arboreal locomotion?) is answered
with a tentative yes. Generally lower mean ratios
(i.e., a circular cross section) were associated with
higher percentages of total arboreal locomotion in
the combined genera comparisons. This trend remained visible when gorillas were analyzed separately, but was not particularly obvious when Pan
groups were analyzed separately. In fact, Pan exhibited negative correlations at only 2 of 6 ROIs (middistal femur and mid-proximal humerus). The PMA
ratio apparently responded differently to an increased percentage of total arboreal locomotion
among gorillas (decreased) and Pan (increased).
The second (are PMA ratios and scrambling negatively correlated?) and third (are PMA ratios and
arboreal quadrupedal walking positively correlated?) questions were answered more equivocally.
Inspecting the combined-genera sample, as well as
the separate analysis of gorillas, PMA ratios and
scrambling were seldom negatively correlated. Arboreal quadrupedal walking and PMA ratios frequently were correlated positively in the combined
sample, or when Pan was analyzed separately. However, when gorillas were analyzed separately, the
correlation between PMA ratios and arboreal quadrupedal walking often was not positive. This may
indicate that African ape arboreal quadrupedal
walking does not involve stereotypical limb movements as much as originally assumed.
The fourth question (is scrambling correlated to
PMA ratio more strongly than other arboreal locomotor behaviors?) was answered with a definitive
no. Gorillas, except at their humeral midshaft, exhibited the strongest correlations between group
PMA ratios and a behavior other than scrambling
(i.e., arboreal quadrupedal climbing). This underscores the importance of distinguishing scrambling
from quadrupedal climbing in behavioral studies.
No single arboreal locomotor behavior consistently
exhibited the highest correlation with PMA ratio in
Pan. While scrambling correlation coefficients exhibited a higher average position (1, highest; 4, lowest) in Pan (2.5) than in gorillas (2.8), suspensory
behaviors usually exhibited the strongest correlations in Pan. Arboreal scrambling and suspensory
behaviors often exhibited the highest positions in
Pan femoral ROIs, while arboreal quadrupedal
climbing and suspensory behaviors were regularly
the highest in their humeral ROIs. Quadrupedal
walking frequently exhibited low positions in both
genera, especially in Pan. The lack of a single clearcut behavioral correlate with PMA ratios in Pan, as
demonstrated by quadrupedal climbing in Gorilla,
could indicate that bending load orientations were
relatively similar (or similarly variable) during each
327
of their arboreal locomotor behaviors (i.e., each promotes a circular cross section to a similar degree), or
at least more similar than those encountered by
gorillas during the same arboreal locomotor behaviors. This speculation, however, must be verified
experimentally.
To the extent that group mean PMA ratios reflect
locomotor behaviors, the locomotor repertoires of G.
g. graueri and P. t. troglodytes may be estimated in
lieu of absent positional behavior data. These estimates do not reflect the amount of time spent in
arboreal vs. terrestrial settings (e.g., classification
as arboreal or terrestrial primates). Rather, they
correspond to the percentage of locomotion that occurred in each setting (e.g., travel). Femoral diaphyses of G. g. graueri exhibited a pattern in PMA
ratios that was more similar to gorilla subspecies
than Pan, but they exhibited magnitudes of PMA
ratios that were intermediate (i.e., between Pan and
other gorilla subspecies). Humeral PMA ratios of G.
g. graueri typically were lower than those of the
other gorilla subspecies. At the humeral midshaft,
G. g. graueri displayed the least sexual dimorphism
of all gorilla subspecies. Femoral and humeral bending load orientations in G. g. graueri were apparently the most variable of all gorilla subspecies (i.e.,
they usually exhibited the most circular cross sections). Gorilla g. graueri appears to have exhibited
less total arboreal locomotor behavior than G. g.
gorilla, but more total arboreal locomotor behavior
than G. g. beringei. To the extent that PMA ratios
reflected locomotor behavior profiles, sex-specific
characterizations of P. t. troglodytes generally were
most comparable to P. t. schweinfurthii. Female
femoral PMA ratios were intermediate to those of P.
t. verus and P. t. schweinfurthii females, and higher
than P. paniscus females. Male P. t. troglodytes exhibited the highest femoral PMA ratios of all Pan
males. In the humerus, P. t. troglodytes sexes exhibited lower ratios than sexes of other subspecies, but
higher ratios than P. paniscus sexes. Femoral PMA
ratios of P. t. troglodytes might indicate a lower
amount of variability in femoral bending regime orientations than experienced by most chimpanzees,
while humeral PMA ratios might indicate a higher
amount of variability in humeral bending regime
orientations.
Ruff (2002) was among the first to incorporate
positional behavior data in a study of cross-sectional
geometry of limb bones. The effects locomotor behavior repertoire may have had on long bone articular
dimensions and cross-sectional properties were discussed, but links to shape differences in cross sections were not explored. Ruff (2002, Table 2, p. 328,
331) characterized locomotor behavior in Pan as
“knuckle-walking, climbing, and some suspension”
and in Gorilla as “knuckle-walking, some climbing,
and infrequent suspension.” Such a generalized approach in partitioning behavioral repertoires (e.g.,
qualitative behavioral comparisons) masked important distinctions in the locomotor behavior profiles
328
K.J. CARLSON
of African apes that could be useful to interpretations of cross-sectional properties. For example, G. g.
gorilla females, but not males, apparently engage in
at least as much arboreal suspensory and arboreal
climbing behaviors as Pan females (Table 2 in the
present study; Remis, 1998, p. 102). Also, chimpanzees exhibit significantly more knuckle-walking
than climbing when comparing total locomotion percentages, but this pattern is reversed if only arboreal locomotor behaviors are considered (Table 2).
Knuckle-walking or, more generally speaking, quadrupedal walking is less frequently observed in arboreal settings than terrestrial settings. While a
generalized description of locomotor repertoires may
be sufficient depending on the question of interest,
such as a broad-ranging taxonomic comparison (e.g.,
Ruff, 2002), functionally relevant similarities and
distinctions are more readily available when behavioral comparisons use quantitative behavioral data.
There are several possible explanations for the
lack of consistent close correspondence between
group PMA ratios and group percentages of locomotor behaviors. The PMA ratio quantifies the amount
of uniformity between the maximum and minimum
bending rigidity for a diaphyseal cross section.
When femoral or humeral bending loads are experienced from multiple orientations, it is proposed that
PMAs should be more similar in magnitude than
when bending loads are more uniform in orientation
(e.g., Fig. 1). A relatively circular cross section, in
this sense, would be a preventative response that
may minimize failure (i.e., fracture) from large
bending loads oriented in any one of many directions. When bending load orientations are relatively
stereotypical in the limb of an individual, it is suggested that PMA magnitudes may diverge as minimum rigidity declines relative to maximum rigidity.
A relatively noncircular cross section, in this sense,
would be a preventative response to failure (i.e.,
fracture) from large bending loads that are oriented
over a relatively select range of directions. Studies
combining in vivo strain data and cross-sectional
geometric properties purported that PMAs assessed
relative to centroidal axes, as used in the present
analysis, may not have reflected maximum bending
loads accurately in ulnae and tibiae (Demes et al.,
1998, 2001; Lieberman et al., 2004). Lieberman et
al. (2004) reported that the experimental neutral
axis (NA) of a sheep tibia cross section diverged from
the centroidal axis (CA) to a variable degree during
treadmill walking. They suggested that cross-sectional properties (e.g., PMAs) calculated with respect to the CA in the sheep tibiae were less accurate than cross-sectional properties calculated with
respect to the NA. They recommended caution when
comparing properties calculated about CAs, and endorsed a more conservative approach, such as the
comparison of patterns rather than magnitudes.
Perhaps correlations between specific locomotor
modes and PMA ratios calculated about NA axes
would provide a clearer pattern of form-function relationships.
The femoral or humeral diaphysis of any African
ape did not exhibit a uniform pattern in response to
bending load regimes engendered during locomotor
behaviors (i.e., intradiaphyseal variation in correlation strengths was common). Whether bending regimes were in fact uniform along the diaphysis cannot be ascertained with the indirect evidence
presented here (i.e., in vivo strain data are necessary). The lack of uniform correlation coefficients in
a diaphysis could be indicative of bending load orientations being influenced by localized phenomenon
(e.g., muscle-bone interaction), as opposed to the
direction of SRF vectors. It is suspicious that where
bending load regimes theoretically should be the
highest, namely at midshaft diaphyses (e.g., Biewener and Taylor, 1986), behavioral correlations
were inconsistently the strongest. This was most
evident in the gorilla sample, especially in the humeral diaphysis.
Weiss (2003) reported that cross-sectional geometric properties were correlated significantly to humeral muscle attachments in a large sample of prehistoric Amerindians. Of all six ROIs in the
combined African ape sample, only the mid-proximal humerus displayed a positive (significant) correlation. The humeral midshaft, although displaying a negative correlation, exhibited a relatively
weak correlation. These two ROIs were located
within or near the insertion of the deltoid (Gregory,
1950; Swindler and Wood, 1973). As the percentage
of arboreal locomotion increased, more frequent
forelimb abduction could be reasonably anticipated
due to engaging in scrambling and suspensory behaviors, among other arboreal locomotor behaviors.
Greater use of the deltoid may have elevated its
impact on bending regimes specifically at these
ROIs, relative to the local impact of other muscles at
other ROIs. While it is conceivable that the contribution of a muscle to a local bending regime (e.g.,
ROIs) may vary in magnitude depending on how
many muscle fibers are recruited simultaneously,
the orientation of the muscle force is assumed to be
stereotypical (i.e., muscle attachments are assumed
to be statically positioned on a diaphysis). Thus, the
humeral midshaft and mid-proximal PMA ratios, if
primarily reflecting deltoid-generated bending
loads, may have increased (counter the original
proposition) as the percentage of arboreal locomotion rose. This could partially explain why these two
ROIs often did not exhibit the proposed relationships with locomotor behaviors.
Local bending regimes at femoral ROIs could be
affected by muscle attachment sites as well. Insertions of several small muscles (e.g., pectineus or
adductor brevis) intersected only the midproximal
femoral ROI, while larger muscles with more expansive origins (e.g., vastus intermedius or biceps femoris caput breve) or insertions (e.g., adductor magnus, adductor longus, or gluteus maximus) either
APE LONG BONE GEOMETRY AND LOCOMOTOR BEHAVIOR
intersected all three femoral ROIs, or only the two
more distal ROIs (Gregory, 1950; Swindler and
Wood, 1973). The relevance of muscle forces to local
bending regimes would seem considerably more
complex when multiple muscles were involved.
Whether muscle function (e.g., measured by electromyography or architectural properties) exerted substantive influence on local bending regimes in diaphyses, and if so, how they may influence crosssectional properties, are critical questions that
warrant investigation.
Since Lanyon et al. (1975, p. 267) initially issued
the challenge to identify “the mechanisms by which
continued intermittent deformation influences bone
structure . . . so the relative importance of large or
small deformation cycles and the significance of
their alignment [could be made less] speculative,”
our understanding of the response of bone to mechanical stimuli has deepened (Burr et al., 2002;
Martin et al., 1998). Considerably less attention,
however, has been devoted to documenting and understanding the variability in bending regimes that
arises during various modes of locomotion. In primate studies that used indirect assessments of
bending forces, such as SRFs and kinematic analyses, primarily quadrupedal or bipedal walking and
running were emphasized (D’Août et al., 2001, 2002;
Demes et al., 1994; Ishida et al., 1990; Kimura,
1985; Kimura et al., 1979; Reynolds, 1985; Schmitt,
1994, 1995, 1998, 2003). Among nonhuman primates, direct measurements of variability in the
orientation of bending regimes (i.e., in vivo limb
bone strains) were characterized only in gibbons
during brachiation (Swartz et al., 1989), and in macaques during overground quadrupedal walking and
galloping, with some anecdotal climbing data reported (Demes et al., 1998, 2001). The degree to
which additional locomotor behaviors, most notably
many arboreal behaviors, engender strains within
limb bones is largely unknown.
The relationship between bending strains generated during arboreal locomotion compared to
those generated during terrestrial locomotion also
has not been addressed. For example, does arboreal quadrupedal walking engender more variability in the orientation of bending strains than terrestrial quadrupedal walking? A more variably
oriented ML component of the SRF vector experienced by the forelimb during terrestrial quadrupedal walking compared to arboreal quadrupedal
walking may suggest that the forelimb ML bending regime could be comparatively less variable
during arboreal quadrupedal walking as well
(Schmitt, 2003). If arboreal quadrupedal walking
were to elicit a narrower range of bending orientations in the forelimb (e.g., the humeral diaphysis), this would lend support to the positive correlations between PMA ratio and the percent
arboreal quadrupedal walking for all three femoral ROIs and one humeral ROI in the separate
analysis of Pan. However, negative correlations
329
for all three femoral ROIs and one humeral ROI in
the separate analysis of gorillas would not be explained. The absence of a consistent association
between PMA ratios and specific arboreal locomotor behaviors (e.g., arboreal quadrupedalism, quadrumanous climbing, or suspensory behaviors)
highlights the need for additional experimental
data from more diverse ranges of locomotor behaviors and animals.
A growing body of literature supports the notion
that the distribution of cortical bone in a diaphyseal
cross section may not reflect the strain history of
long bones in a simple and straightforward manner.
Alternative views of results for many of the early
studies that provided experimental support for bone
adaptation to mechanical stimuli have been articulated (Bertram and Swartz, 1991). Recent in vivo
analyses (e.g., Demes et al., 1998, 2001; Lieberman
et al., 2004), along with the demonstration of strain
gradients in long bone diaphyseal cross sections
(e.g., Gross et al., 1997; Judex et al., 1997), present
persuasive evidence that the location of maximum
strain in a cross section does not always correspond
to the maximum PMA. The assumption of tissue
efficiency in “Wolff’s law” (see working definition in
the introduction) apparently may not always be the
case. An alternative nonmechanical explanation for
the shape of long bone diaphyses (developmental
determination) has been summarized recently by
Lovejoy et al. (2003).
CONCLUSIONS
Patterns in group PMA ratios were rarely consistent throughout femoral and humeral diaphyses.
Variability in bending load orientation, as assessed
by the circularity of cross sections, apparently was
not consistent throughout either diaphysis of African apes. Humeral ratios varied between groups
(e.g., subspecies) or within groups less than femoral
ratio, exhibiting less between-groups variance (e.g.,
differences between subspecies) than within-groups
variance (e.g., differences between individuals)
when femoral and humeral PMA ratio variances
were compared. Humeral PMA ratios presumably
reflected individual-based behavioral differences
(i.e., idiosyncratic behaviors) that transcended taxonomic boundaries. Femoral PMA ratios, on the
other hand, reflected group-based behavioral differences more readily. The expression of limb differentiation in humeral and femoral PMA ratios could be
related to greater group-specific functioning of the
hind limbs during locomotion, possibly influenced by
hind limb drive, that does not apply in the forelimb
where idiosyncrasies in limb segment positions may
arise more frequently.
Despite finding a nonuniform pattern in ROIs
(i.e., variation within a diaphysis was observed), a
few general observations can be made from correlations between PMA ratios and locomotor behaviors.
A negative association between mean PMA ratios
and percentages of total arboreal locomotion was
330
K.J. CARLSON
observed frequently, although less so in Pan when
African ape genera were analyzed separately. Group
mean PMA ratios provided a moderately reasonable
substitute for the degree of total arboreal locomotion
when comparing genera (e.g., gorillas and chimpanzees) or even subspecies (e.g., mountain gorillas and
western lowland gorillas). Thus, PMA ratios may
provide reasonable estimates for the degree of arboreal locomotion in ape taxa, extant or extinct, for
which locomotor behavior data are unavailable. No
single behavior (e.g., arboreal scrambling) consistently demonstrated the highest correlations with
femoral and humeral ratios. However, when analyzed separately, gorillas frequently exhibited the
strongest correlations between PMA ratios and quadrupedal climbing. Pan PMA ratios usually exhibited the strongest correlations with suspensory behavior, followed by scrambling and quadrupedal
climbing. Quadrupedal walking consistently exhibited some of the weakest correlations with PMA
ratios (i.e., diaphyseal circularity), whether genera
were combined or separated in analyses.
Additional direct (e.g., in vivo strain) or indirect
(e.g., substrate reaction force) primate data, particularly for arboreal locomotor behaviors, are needed.
Such investigations would provide critical data for
addressing whether the hypothesized relationships
between group mean PMA ratios and locomotor behaviors were accurate in assumptions regarding
variable bending load orientations engendered during arboreal locomotor behaviors. These data could
also address whether subspecies exhibited differences in locomotor behavior repertoires that could
not be observed with PMA ratios. For example, did
overlapping ranges of behavioral modes (i.e., all
groups used the same suite of behaviors) drown
quantitative behavioral differences (e.g., groups
used different percentages of behaviors within the
suite)?
ACKNOWLEDGMENTS
I acknowledge the extraordinary cooperation of
several museums, hospitals, and their staffs that
made this research possible. For granting access to
their collections and arranging specimen loans for
CT scanning, I express my gratitude to the American Museum of Natural History, New York, NY; the
Musée Royal de l’Afrique Centrale, Tervuren, Belgium; das Anthropologisches Institut und Museum
der Universität Zürich-Irchel, Zürich, Switzerland;
the National Museum of Natural History, Washington, DC; the Powell-Cotton Museum, Birchington,
Kent, UK; the Natural History Museum, London,
UK; and das Museum für Naturkunde der Humboldt Universität, Berlin, Germany. For granting
access to their CT facilities, I acknowledge Hammersmith Hospital, London, UK; QEQM Hospital, Margate, Kent, UK; Charité Hospital, Berlin, Germany;
Mount Sinai Hospital, New York, NY; Universitaire
Ziekenhuizen, Leuven, Belgium; Kantonsspital, Institut für Radiologie, Winterthur, Switzerland; and
the Department of Anthropology, Smithsonian Institution, Washington, DC. For their personal cooperation, I offer my sincerest gratitude to the numerous
CT technicians who assisted me: Stuart Daws, CT
Superintendent; Anja Boldt, M.T.A.R.; Justine DePonte, B.Sc. (Hons.), Diagnostic Radiography; Sandra Jones Dillard, R.T., CT; Marc Verburgh; and
Isuf Hoxha. Without their cooperation, this research
would not have been possible. I am also deeply
grateful to Kevin Hunt, David Burr, Brigitte Demes,
Della Cook, Jeanne Sept, Diane Doran, Christoph
Zollikofer, Marcia Ponce de León, and Jessica Satkoski for discussions, guidance, and support during
the course of this research. I thank Kevin Hunt for
help in drawing Figure 2, and Luci Betti-Nash for
her expert help in generating Figure 4. Brigitte
Demes, Jack Stern, Clark Larsen, and two anonymous reviewers provided insightful comments from
which the quality of this manuscript benefited tremendously.
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