P R O ME T H E US P R E S S / P A L A E O N T O L O G I C A L N E T W O R K F O UN D A T I O N
(TERUEL)
2004
Journal of Taphonomy
VOLUME 2
Available online at www.journaltaphonomy.com
(ISSUE 3)
Stiner
A Comparison of Photon Densitometry and
Computed Tomography Parameters of Bone
Density in Ungulate Body Part Profiles
Mary C. Stiner*
Department of Anthropology, Building 30, University of Arizona, Tucson,
AZ 85721-0030, U.S.A
Journal of Taphonomy 2 (3) (2004), 117-145.
Manuscript received 4 October 2004, revised manuscript accepted 15 December 2004.
Biases in ungulate body part representation in archaeofaunas potentially reflect human foraging
decisions. However, the signatures of density-mediated attrition of body parts and human selectivity in
response to nutritional content can overlap to a significant extent. Zooarchaeologists’ techniques for
analyzing skeletal representation for density-dependent biases must either address differential resistance
among distinct skeletal macro-tissue classes, or compare skeletal representation within a narrower
density range that is widely distributed in the skeleton. This presentation examines the potential
comparability of bone density parameters obtained by photon densitometry (PD) and computed
tomography (CT) within limb elements and across regions of the whole skeleton. “Unadjusted”
parameters obtained by PD and CT techniques are in reasonably good agreement, and these parameters
yield similar results when applied to patterns of skeletal representation in Mediterranean faunas
generated by Paleolithic humans and Pleistocene spotted hyenas. More significant than the technique for
measuring density in modern mammal skeletons is whether the density parameter values have been
adjusted, arguably to compensate for problems of shape and the presence of large internal voids in limb
bone tubes. The results of systematic comparison of density parameter variation among published
sources, and their application to prehistoric cases accumulated by diverse agents, contradict the great
preservation differential between spongy and compact bone specimens suggested by certain captive
hyena experiments and the Mousterian fauna from Kobeh Cave (Iran). Only the adjustments made to the
CT parameters for limb shafts (BMD2) accommodate the latter cases.
Keywords: DENSITY-MEDIATED BONE ATTRITION, TAPHONOMY, ZOOARCHAEOLOGY,
VERTEBRATE BODY PART PROFILES, PHOTON DENSITOMETRY, COMPUTED
TOMOGRAPHY
Introduction
Patterns of prey body part representation are
of anthropological interest for what they
may tell us about human foraging decisions,
a question that has been explored by a wide
range of archaeologists (Binford, 1978;
Binford & Bertram, 1977; Brain, 1981;
Article JTa020. All rights reserved.
* E-mail:[email protected]
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Bone density parameters and ungulate body part profiles
Brink, 1997; Lupo, 1995; Lupo & Schmitt,
1997; O’Connell et al., 1988; Todd, 1987;
among others). However, bone fragility and
associations to food value generally are
correlated in animal carcasses (e.g.,
Grayson, 1989; Lyman, 1984), and thus
zooarchaeologists must ask whether the
observed biases in body part representation
could be explained by in situ attrition
mediated by variation in skeletal tissue
density. The potential for equifinality
among causes of skeletal biases in
archaeofaunas can be addressed only in part
by comparing the patterns of anatomical
representation in archaeofaunas to
independent standards (measurements) of
bone density in modern taxa. Such analyses
require reasonably accurate estimates of
density variation within and among skeletal
parts. Also significant is how the
anatomical data are partitioned in
comparisons of parameters to the
archaeofaunal patterns.
Much recent debate has focused on
the accuracy of bone density parameters
that are applied in research on
archaeofaunas. Investigators generally
accept that body part representation may be
compared at several scales—within
element, across element, and across bodily
regions of the prey anatomy. However, two
sources of bulk bone density reference
data—those obtained using photon
densitometry (PD) and those from
computed tomography (CT)—are said to
differ significantly with respect to accuracy
(Lam et al., 1999, 2003). Of particular
concern is how well these standards reflect
relative differences in the structural density
of compact limb bone shafts and limb
epiphyses. These disagreements also have
implications for the comparability of limb
density data to other areas of the prey
skeleton.
Marean & Kim (1998) and Lam et
al. (1999) propose that the density of
compact bone in limb elements is so much
greater than compact bone tissues
elsewhere in the ungulate anatomy that, as a
rule, only limb shaft portions should be
used to estimate MNE (minimum number
of elements) of ungulate limbs in faunal
assemblages. Do the PD and CT techniques
for measuring bulk density in fresh bone
have substantially different consequences in
archaeological applications?
This presentation examines
potential differences in the predictions of
ungulate bone survivorship based on bulk
bone density as estimated by PD technique
by Lyman (1984, 1994) and Kreutzer
(1992) and by CT technique by Lam et al.
(1999). In the case of the CT technique, two
types of parameters are considered—
unadjusted (BMD1) and adjusted (BMD2)
types—the latter of which is an attempt to
correct for the presence of large internal
voids in bone tubes. The comparisons are
undertaken at two anatomical scales: within
limb elements and across regions of the
prey anatomy.
Density-mediated attrition and body part
profiling
Human-modified faunas tend to be highly
fragmented, and nowhere is this more
evident than in foragers’ middens. Under
these conditions, skeletal element counts
must be estimated from the frequencies of
unique morphologic features that can
recognized from partial specimens, such as
the head of a femur, the nutrient foramen of
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a humerus, an occipital condyle of a
cranium or a prezygopophysis of a lumbar
vertebra. Coding systems for identifying
fragmented specimens vary and most
remain undocumented. In recognition of
this fact, this author’s coding system for
skeletal elements and portions-of-elements
is provided in Appendix 1 and illustrated in
a series of figures.
The potential resistance of bones and
bone fragments to consumers and to postdepositional processes is conditioned partly
by the “structural density” of bone tissues
(Brain, 1981; Lyman, 1994:235-238).
Existing techniques for analyzing body part
representation from fragmented faunal
material either (1) address the differential
survivorship of the full range of structural
density classes in the skeleton, or (2) focus
on comparisons of parts that fall within a
narrower density range that is well
represented in the vertebrate skeleton.
The more common approach to
body part profiling emphasizes withinelement comparisons of the relative
representation of compact and spongy bone
macrostructures (Figure 1). There are many
variations on the theme, but all withinelement comparisons require fairly
complete knowledge of structural variation
throughout the mammal skeleton.
Correlation statistics for bone portion
survivorship and independent standards of
structural density provide information on
the maximum amount of variation that
density might explain. Establishing a
Figure 1. Cross-sectioned humerus and femur of artiodactyl ungulate, showing the distribution of compact and
spongy macrostructures along the shaft (diaphysis) and ends (epiphyses). Some epiphyses are dominated by spongy
bone, but others are dominated by compact bone. The main nutrient foramen is located on the shaft.
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Bone density parameters and ungulate body part profiles
positive correlation of skeletal survivorship
to density is not proof of density-mediated
attrition, however, since consumer transport
and processing behaviors can produce
similar patterns (see Beaver, 2004). Such a
correlation merely indicates that densitymediated attrition can be among the
potential range of explanations for the
patterns observed.
The within-element approach has
been very important for research on
intensive carcass processing by humans
(e.g., Binford, 1978; Brain, 1981; Brink,
1997; Lupo, 1995; Munro, 2004; Stiner,
2003; Todd, 1987). In cases where bone
grease extraction is suspected, for example,
knowing the fate of all least-dense portions
in relation to very dense ones is essential to
the success of the study. This treatment of
body part representation data does not in
itself address questions about body part
transport decisions, except with respect to
possibility of pre-sectioning of limbs.
Cross-element comparisons in body
part profiling potentially address questions
about human decisions at the level of the
complete resource package (often the whole
carcass). Cross-element approaches often
standardize element counts to the natural
abundance of those represented in a
complete skeleton (e.g., minimum number
of animal units, MAU; Binford, 1978).
Some cross-element approaches are distinct
for their emphasis on skeletal portions
composed of compact bone, a tissue class
that is widely distributed in the vertebrate
skeleton (Stiner, 1991, 2002). This
procedure avoids or reduces the
confounding effects of density-mediated
bone attrition on estimates of the minimum
number of skeletal elements (MNE) by
narrowing the tissue density range to those
features that are dominated only by
compact bone. The approach is most useful
for examining broad biases, or the lack of
them, in transport decisions; the risks of
misinterpretation with respect of densitymediated attrition are quite different from
the first approach and arguably less
important (Stiner, 2002).
Rates of differential attrition
Bulk, or structural, bone density (sensu
Lyman, 1984) is a term more or less unique
to zooarchaeological studies. Bulk density
describes differences in bone
macrostructure—mainly the continuum
between compact and spongy bone—
because this is what interests
zooarchaeologists on account of their
reliance on macrostructural features for
taxonomic and anatomical identifications.
Bulk density does not reflect substantive
variation in the material composition
(mineral and organic) of bone, nor does it
bear a simple linear relation to the strength
of bone when loaded against its main axis
(Currey, 1984). Bulk density is mainly an
expression of variation in concentrated
mass of bone specimens that is semiindependent of bone tissue volume and
depends foremost on porosity.
Lyman’s (1984, 1991, 1994)
comprehensive review of skeletal
survivorship in relation to bulk bone
density in cultural and paleontological
contexts suggests a maximum potential of
differential destruction of 1:2 or 1:3 for
spongy to compact bone parts. This
destruction differential is supported by
empirical patterns of skeletal survivorship
in other archaeological and paleontological
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sites as well (Lyman, 1991; Stiner, 2002,
2005), and by experiments involving
mechanical (Binford & Bertram, 1977;
Brain, 1981; Lyman, 1994) and chemical
destruction (Margaris, 2004). By contrast, a
maximum survivorship differential of 1:8
for spongy to compact bone features is
implied by some feeding experiments
involving hyenas (Capaldo, 1997; Marean
& Spencer, 1991; Marean et al., 1992) and
by Marean & Kim’s (1998) refitting study
of the Mousterian ungulate fauna from
Kobeh Cave in Iran. Interpretation of the
latter case assumes that it represents a
completely recovered, unsorted collection.
The extreme difference in skeletal
survivorship found by these authors is
supported by the adjustments to CT limb
bone parameters published by Lam et al.
(1999), but not by the unadjusted CT
measurements. Lam et al. (1999, 2003)
insist that their adjusted parameters for
variation in bulk bone density are more
accurate for anticipating density-mediated
effects on limb bone survivorship across
archaeological and paleontological
circumstances.
Comparison of density ranges for limb
ends and shafts
How different are the predictions for
skeletal survivorship from PD and CT
parameters of bulk bone density? And how
different are the predictions of skeletal
survivorship from the unadjusted (BMD1)
versus adjusted (BMD2) CT measurements?
Figures 2 and 3 compare the range
of density measurements obtained for
modern ungulate limb bones by PD and CT
techniques, respectively. The solid line
Figure 2. Photon densitometry (PD) ranges and midpoints (scale 0-1.0) for the shaft and the two ends of
the same limb element. Data are for the scapula, humerus, radius, femur, tibia, and metapodials of Antilocapra, Odocoileus (Lyman, 1984), and Bison
(Kreutzer, 1992).
represents the range and midpoint for the
denser end in the case of limb epiphyses;
the dashed line at the lower end of the range
highlights the range for the particularly
spongy portions, although these are few in
number. PD standards in Figure 2 indicate
that shafts of medium and large ungulates
(Odocoileus and Bison in this case) are
somewhat denser than limb ends overall.
While the degree of difference between the
least and most dense portions of limb
elements can be as great as 1:4 if
exceptionally soft parts are considered, the
average difference is much less than this.
A comparison of unadjusted CT
(BMD1) parameters for shaft versus end
density for limb portions of three ungulate
taxa (Equus, Connochaetes, and Rangifer)
(Figure 3) yields similar means and ranges.
The unadjusted CT end and shaft density
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Bone density parameters and ungulate body part profiles
Figure 3. Computed tomography (CT) ranges and
midpoints (scale 0-1.2) for the shaft and the two ends
of the same limb element, based on BMD1 and BMD2
(shafts only) criteria. Data are for the scapula,
humerus, radius, femur, tibia, and metapodials of
Equus, Connochaetes, and Rangifer (Lam et al., 1999).
ranges are more similar to one another than
those obtained by the PD technique. The
unadjusted CT measurements for limb ends
vary somewhat more than those for shafts if
soft (less dense) ends are included, but not
if the softest ends are removed from
consideration. The ratio of survivorship
between limb shafts and the harder of two
ends is arguably of greatest concern for
recognizing parts at the scale of functional
elements, assuming that the elements (e.g.,
femur, tibia or radius) were not extensively
fragmented prior to transport. The
parameters of density examined thus far
suggest that the denser end of each element
should resist mechanical destruction about
as well as the shaft.
While the PD and unadjusted CT
parameters of bulk density in fresh bone are
similar to one another, Lam et al.’s (1999,
2003) adjustments to compensate for the
large empty area in the center of compact
bone shafts (BMD2 in Figure 3) yields a
very different expectation of relative
survivorship of all limb ends (including the
densest ones) to shafts. Now the differential
is 1:8 or higher, if the entire macrostructure
spectrum is considered, and 1:2 or perhaps
1:3 between limb bone shafts and the
denser of two ends (cf. sectioned humerus
and femur in Fig. 1).
Figure 4 presents a model of the
expected rates of attrition of two skeletal
tissue types with opposing densities
(following Stiner, 1994:99-103). The slope
of the line expresses the relative loss of one
type to the second type within the element,
such as between shaft-based and end-based
counts (MNE) of limb bones. The two
estimates must be auto-correlated to some
extent, because these portions occur
together in a whole element during life.
However, the strength of the correlation
between the two sources of MNE counts is
of interest with respect to the consistency in
preservation among stratigraphic units or
assemblages. Assuming an intercept of
zero, a slope of 1.0 represents ideal
preservation of the two classes of skeletal
material. A slope of less than or more than
1.0 indicates that one class of bone
macrostructure has suffered relative to the
other; a slope of 0.50, for example, means
that one tissue type is preserved only half as
often as the other on average, translating to
a survivorship ratio of 1:2. The slope
therefore describes the gross ratio of loss
and, at its greatest extreme, the maximum
potential survivorship differential between
the two tissue types.
Figure 5 compares the density
parameter values for the shaft and denser
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end of each type of limb element obtained
by PD and unadjusted CT (BMD1)
techniques. Shafts are slightly denser than
the ends of these bones according to the PD
standards (left), but the slope is close to an
ideal value of 1. Some of the values for
Antilocapra, the smallest ungulate referent
in the PD data set, tend to fall on the lower
end of the slope, presumably because the
animal possesses a lighter skeletal frame.
There is a poor correlation for the data set if
Antilocapra is removed (n = 14, r2 = 0.271,
slope = 0.904, intercept = 0.218, p = .06).
In fact the full set of points for Antilocapra,
Odocoileus and Bison form a single tight
cluster along the end-density (x) axis, but
are more scattered along the shaft-density
(y) axis. This finding suggests that endbased counts yield more consistent results
among limb elements and among ungulate
species when PD standards of density
variation are used. Unadjusted CT density
standards (right) for medium and large
ungulates (Equus, Connochaetes, and
Rangifer) are tightly distributed on both
axes, indicating that shaft features and the
denser ends of each limb type are equally
suitable for estimating limb MNE. None of
these results supports the idea that shaftbased MNE counts are much more reliable
than end-based counts for the construction
of body part profiles.
Relative attrition of limb end and
shaft features in diverse paleontological and
archaeological contexts is also informative
in that it can provide a better sense of the
natural range of skeletal survivorship
(Figure 6). The 19 Pleistocene ungulate
assemblages in this comparison are of
known origins in Italy, and all of the faunal
material was recovered by the excavators
and examined systematically (Stiner, 1991,
Figure 4. Modeled relations of relative attrition of
compact (most resistant) versus spongy (least resistant)
bone portions of the same element. The slope of the
line expresses the rate of relative loss of spongy bone
features to compact bone features. The strength of the
correlation reflects the consistency in preservation
among or within assemblages. Assuming an intercept
of zero, a slope of 1.0 corresponds to ideal
preservation of these two classes of skeletal material; a
slope of less than 1 indicates that spongy bone has
suffered relative to compact bone.
1994, 2005). The bone collectors and
modifiers range from Middle and Upper
Paleolithic humans to denning spotted
hyenas. MNE counts for shafts and the
more common end of each limb element in
these shelter faunas indicate no substantive
differences. The similarity in representation
of limb ends and shafts across agents is all
the more striking given the abundant tooth
drag marks, salivary rounding, crenellation,
and punctures on bones in the hyenacollected assemblages (Stiner, 1994). The
gnawing damage by hyenas seems not to
have rendered many elements of the head or
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Bone density parameters and ungulate body part profiles
Figure 5. Comparison of density parameter values for shafts and the denser end of the same limb elements in (left
pane) Antilocapra, Odocoileus, and Bison based on photon densitometry (PD) values; and (right pane) Connochaetes, Equus, and Rangifer based on computed tomography (CT BMD1) values. (*) There is a poor correlation for
the PD data set if Antilocapra is removed (N = 14, r2 = 0.271, p = .06).
Figure 6. Comparison of end-based and shaft-based MNE counts for the major limb bones of small, medium, and
large ungulates from assemblages collected by Pleistocene spotted hyenas, Middle Paleolithic humans, and
Epipaleolithic humans in Italian caves.
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Stiner
limb regions of red deer, fallow deer or
aurochs unrecognizable.
Greater differences are found
between end-based and shaft-based MNE
counts across ungulate body size classes
that were generated by a single agent—
Mousterian hominids at Hayonim Cave
(Levant) in this example (Figure 7). The
largest ungulate in the Mousterian
assemblages is aurochs (Bos primigenius),
the dominant medium sized ungulate is
fallow deer (Dama mesopotamica), and the
smallest ungulate is the diminutive
mountain gazelle (Gazella gazella). The
overall correlation between end-based and
shaft-based MNE counts is fairly strong (r2
= 0.472, p = 0.0001, n = 21), and a slope of
0.423 (intercept = 6.5) would suggest that
shafts are under-represented relative to the
more common end of the elements
considered (Spearman’s rho = 0.808 for
rank-ordered data, n = 19, p = 0.0001).
However, all of the major outliers to the
distribution belong to the smallest ungulate
species. The counts of end-based and shaftbased MNE counts for medium and large
ungulates are in nearly perfect agreement (n
= 14, r2 = 0.935, slope = 0.933, intercept =
1.61, p = 0.0001; Spearman’s rho = 0.964,
p = 0.0001).
The anomalies encountered for small
ungulates in the Levant cannot be
generalized to the medium-sized and larger
ungulates of the types that dominate
Mousterian faunas in Eurasia. This finding
also prohibits generalizations about limb
shaft versus end survivorship for the
skeletal parts of small domestic ungulates
fed to hyenas to survivorship for the
remains of larger, wild species (Klein &
Cruz-Uribe, 1998; Stiner, 2002). The
problem in the Levantine Mousterian cases
Figure 7. Comparison of end-based and shaft-based
MNE counts for the major limb bones of small,
medium, and large ungulates from the early
Mousterian units of Hayonim Cave, Israel.
is the difficulty in recognizing small shaft
features (e.g., nutrient foraminae and
muscle insertions) in fragmented material.
There was no difficulty in recognizing limb
end features, especially those of the denser
end of a given element. End-based MNE
counts therefore are less likely than shaftbased features to undercount the original
number of elements in an assemblage,
especially in assemblages that include small
ungulate species.
Another problem for the CT
BMD2 parameters is that of comparability
in assessments of bone survivorship across
major regions of the skeleton. If one
concludes that the BMD2 parameters are
more accurate than the unadjusted BMD1
parameters from shafts, then this fact would
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Bone density parameters and ungulate body part profiles
remove shafts from the list of parts
comparable to virtually all other areas of
the bony skeleton. Most anthropological
questions about prey body part
representation concern treatment of the
carcass as a whole, and which parts are
transported or processed in distinctive
ways.
Density range correspondences among
anatomical regions
Figure 8. Examples of portion-of-elements
representing limb shafts used to count elements
(MNE): (a) distal diaphysis of the scapula at its
narrowest section; exterior and interior views of
nutrient foraminae of (b) humerus, (c) femur, and (d)
tibia. Examples are from cervids, but the criteria also
apply to wild bovids.
The region-based approach to ungulate
body part representation pools MNE counts
in a way that helps to even-out variation in
structural density. The technique is directed
to inter-assemblage comparisons from
which only the most robust differences in
body part representation patterns usually
are sought. The minimum number of
elements (MNE) is estimated for each
skeletal member of a given taxon from the
most common morphologically unique
“portion” or feature in the assemblage.
Some portions will tend to yield higher
counts than others, presumably due to their
greater inherent resistance to mechanical
destruction. Limb end (epiphysis) and shaft
features (e.g., foraminae, Figure 8) are
considered by this author in estimating
MNE (Stiner, 1991, 2002). For the skull,
only bony portions are used in the
comparisons to post-cranial MNEs, because
tooth enamel is so much denser than any
kind of bone (Currey, 1984). Small,
compact features are favored for counting,
and many of these portions coincide with
Lyman’s photon densitometry scan sites
(1994:234-250; Elkin & Zanchetta, 1991;
Kreutzer, 1992; Lyman, 1984; Lyman et al.,
1992). The portion-of-element categories
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Stiner
Figure 9. Nine anatomical regions for the ungulate skeleton (from Stiner, 1991).
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Bone density parameters and ungulate body part profiles
Figure 10. Standardized bar chart for the nine anatomical regions of a theoretically complete skeleton (from Stiner,
1991). (1) antler/horn, (2) head, (3) neck, (4) axial, (5) upper front limbs, (6) lower front limbs, (7) upper hind
limbs, (8) lower hind limbs, (9) feet. Note that dental elements are not used to calculate the frequencies of head
parts. Standardized MNE (observed MNE/expected MNE for one complete skeleton) is equivalent to Binford’s
MAU (1978).
tend to be hierarchical, since fragment size
varies and a specimen may contain more
than one portion suitable for estimating
MNE (e.g., Stiner, 2002).
MNE counts are derived from the
most commonly represented portion of each
type of element and then condensed into an
array of nine anatomical regions (Figure 9):
(1) the horn/antler set, (2) head, (3) neck,
(4) the rest of the axial column including
the ribs and pelvis, (5, 6) upper and lower
front limbs, (7, 8) upper and lower rear
limbs, and (9) feet (Stiner, 1991). Speciesspecific identifications are pooled with
specimens of the appropriate ungulate body
size group to increase sample size and to
overcome the fact that some elements and
portions of elements are far more diagnostic
of taxon than are others.
For the purpose of bar chart
comparisons, body part representation can
be standardized against a whole skeleton
model (Stiner’s standardized MNE, 1991;
equivalent to Binford’s MAU, 1978) by
dividing the observed MNE for a skeletal
element or group of elements by the
expected MNE for the same element or
element group in one complete skeleton. If
skeletal representation is complete,
standardized values for all regions will be
equal (and the bars will be of equal height,
Figure 10), making major anatomical biases
among regions easy to detect. The thickness
of compact bone varies among elements,
but this variation in bulk density is of a
smaller order than between compact bone
and the other tissue classes named above.
One simply needs to know the locations of
compact bone tissues relative to the
distribution of the unique morphologic
features (“portions”) normally used to
estimate the MNE for each kind of element.
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Stiner
Figure 11. Lyman’s (1994) photon densitometry (PD) ranges and midpoints of variation for deer (Odocoileus)
across nine anatomical regions of the ungulate skeleton (from Stiner, 2002).
How much variation in the
observed MNE values among anatomical
regions could be explained by variation in
the density of the bone portions used for
counting? I begin by considering all of the
possible portions (spanning spongy and
compact tissue types) in deer (Odocoileus)
for which PD density estimates are
available (Lyman, 1994:Table 7.6). The
comparison is then narrowed to include
only those portions most commonly
represented in my analyses of diverse
Mediterranean faunas from 1985 to the
present.
Density value mid-points and
ranges in Figure 11, and the pair-wise
statistical comparisons of density values in
Table 1, indicate that the chances for
reduced recognizability of bone portions are
about the same for the head region and
various limb regions. An F-ratio statistic
indicates that there are no major differences
among the pooled cranial, limb, and foot
regions (n = 32, r2 = 0.27, p = 0.124). Upper
front limbs and foot bones have a somewhat
lower probability of preservation than heads
and other limb regions, but these
differences are minor. The chances for
reduced recognizability among cranial and
limb regions are closer still for those
portions most commonly used by this
author to estimate MNE in archaeological
assemblages from Mediterranean shelter
sites (n = 23, r2 = 0.330; F-ratio = 1.671, p =
0.195) (Table 2). Turning to a more
stringent nonparametric version of
ANOVA, a Kruskal-Wallis statistic yields
basically the same answer as the tests above
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Bone density parameters and ungulate body part profiles
Table 1. Differences in mean structural density for bony portions of elements by anatomical
region based on Lyman’s photon densitometry control data for deer.
a. Mean photon densitometry values for cranial, limb & foot regions:
Anatomical
region
N-portions
considered
Mean
density
S.d.
head
5
0.52
0.09
upper front limb
6
0.38
0.11
lower front limb
6
0.54
0.13
upper hind limb
3
0.42
0.14
lower hind limb
7
0.52
0.18
feet
5
0.36
0.12
b. Pair-wise tests for differences in density among cranial, limb & foot region pairs:
Anatomical region
pair
t
df
p
Difference
In means
head-upper front limb
2.251
9.0
0.051
0.138
head-lower front limb
-0.347
8.7
0.737
-0.023
head-upper hind limb
1.075
2.9
0.362
0.100
head-lower hind limb
-0.037
9.3
0.972
-0.003
head-feet
2.292
7.3
0.054
0.158
(8.393, df = 5, p = 0.136).
The conceptual basis for the
profiling technique is well supported by PD
estimates of variation in bone structural
density. The risks of over-interpretation in
this treatment of body part frequencies
center on the vertebral column alone
(“neck” & “axial”). The question of why
vertebral elements are rare in real
assemblages must be addressed in other
ways.
CT standards are said to be more
accurate than the available PD estimates of
bone density (Lam et al., 1999). The CT
BMD1 standards describe much of the
skeleton, including limb ends and shafts.
Density values provided by Lam et al. for
the skull are confined to the mandible and
the petrous bone, the latter of which
appears to be exceptionally dense and
therefore is omitted from this comparison.
The range and average CT BMD1 density
values for all skeletal portions of three
130
Stiner
Table 2. Pair-wise mean differences in structural density for (a) all potential
bone portions and (b) those portions most commonly used to estimate MNE
values in the Mediterranean cave faunas.
a. All potential portions:
Anatomical region
& code
(2)
head (2)
—
(5)
(6)
(7)
(8)
(9)
upper front limb (5) -0.138
—
lower front limb (6) 0.023
0.162
—
upper hind limb (7) -0.100
0.038
-0.123
—
lower hind limb (8) 0.003
0.141
-0.020
0.103
—
feet (9)
-0.020
-0.181
-0.058
-0.161
—
(6)
(7)
(8)
(9)
-0.158
b. Most commonly used portions:
Anatomical region
& code
(2)
head (2)
—
(5)
upper front limb (5) -0.114
—
lower front limb (6) -0.029
0.085
—
upper hind limb (7) -0.067
0.048
-0.037
—
lower hind limb (8) -0.033
0.082
-0.003
0.034
—
feet (9)
-0.080
-0.165
-0.128
-0.162
-0.195
ungulate taxa combined (Equus,
Connochaetes, and Rangifer) measured by
Lam et al. (Figure 12) are quite similar
across body regions—more similar than the
patterns seen for PD standards (see Figure
11). The same is true for a narrower range
of skeletal portions favored by this author
in studies of Mediterranean faunas (Figure
13). Finally, a comparison specific to
Rangifer (Figure 14) using the favored
portions also indicates similarity in ranges
and means among anatomical regions.
—
Conclusion
Many of the components of the skull and
limbs have relatively similar chances of
resisting mechanical sources of in situ
destruction. Macrostructure differences
certainly are relevant to understanding the
resistance of whole bone elements to a
variety of mechanical forces (Currey 1984).
Bulk density can also serve as a loose proxy
for differences in the resistance of
fragmented bone specimens to mechanical
131
Bone density parameters and ungulate body part profiles
Figure 12. Comparison of ranges and midpoints of variation in photon densitometry (PD) and computed tomography
(CT) estimates of bone structural density across nine anatomical regions. (open square) Lyman’s (1994) PD data for
Odocoileus; (solid square) Lam et al.’s (1999) CT BMD1 data for three ungulate taxa combined (Equus,
Connochaetes & Rangifer). Comparison includes all portions of elements for which density was measured.
destruction, despite significant changes in
size and shape that arise from breakage.
The assertion that head-dominated
patterns, or head-and-foot-dominated
patterns, in ungulate remains are likely to
be the product of density-mediated attrition
(e.g., Marean & Kim, 1998) is not
supported by documented variation in
structural density in the skeletons of
vertebrates, regardless of whether PD or
unadjusted CT (BMD1) parameters are
used. There are few important differences
in the general predictions of skeletal
survivorship provided by PD and the
unadjusted versions of the CT (BMD1)
parameters, especially if minor differences
in scaling between the two techniques are
taken into account. None of the differences
in bone density of head and limb regions
obtained by PD or CT (BMD1) techniques
is of the order needed to greatly bias MNE
estimates in the region-by-region profiling
technique.
The
only
outstanding
contradictions to comparability between PD
and CT parameters are the calculationbased adjustments for compact limb shafts
represented by Lam et al.’s (1999) BMD2
parameters. These density estimates set
limb shafts so far out of range from other
parts of the bony skeleton (except the
petrous of the cranium) that one may
question why or how one should use shafts
for body part profiling at all. The BMD2
standards are intended to solve a technical
problem posed by the exceptionally large
hole within a compact bone tube. The
adjusted measurement is taken as a proxy
for estimating differential bone strength at
the macro-scale. The discrepancy between
the adjusted CT (BMD2) parameters and
empirical patterns of bone preservation may
132
Stiner
reside in the calculations intended to perfect
estimates of bulk shape. In fact, the strength
of bone depends not only on the ideal
properties of the material but also on the
distribution and sizes of pores (including
small pores) therein, as the latter tend to
concentrate stresses (Currey, 1984).
Empirically derived patterns of
survivorship, such as those summarized in
Lyman (1991, 1994), suggest that the
BMD2 parameters overestimate the
resistance of limb shafts to mechanical
destruction. It is unclear whether models of
attrition should focus on the fracture
thresholds in whole bones or on the
resistance of fragmented but recognizable
features of elements.
The anatomical level at which
portion-of-element and MNE counts are
pooled also has consequences for the
potential effect of density-mediated biases.
They are least likely to manifest at the scale
of anatomical regions in the sense described
above, and particularly if the research
question is about bony components of
heads vs. limbs and feet (see also Bar-Oz &
Dayan, 2002; Rogers, 2000).
Misconceptions on this topic may stem
from the assumption that shafts of limb
elements resist decomposition far better
than any limb end (hard or soft); some limb
bone ends are as dense or nearly as dense as
limb shafts. The main source of confusion,
however, arises from a tendency to focus
upon portion representation within elements
in assessments of attrition effects, and then
generalizing those observations to larger
patterns of representation across the skeletal
Figure 13. Comparison of ranges and midpoints of variation in photon densitometry (PD) and computed tomography
(CT) estimates of bone structural density for nine anatomical regions. (open square) Lyman’s (1994) PD data; (solid
square) Lam et al.’s (1999) CT BMD1 data for three ungulate taxa combined (Equus, Connochaetes & Rangifer).
Comparison includes only those compact bone portions favored by Stiner (2002) for counting MNE.
133
Bone density parameters and ungulate body part profiles
Figure 14. Comparison of ranges and midpoints of variation in photon densitometry (PD) and computed tomography
(CT) estimates of bone structural density for nine anatomical regions. (open square) Lyman’s (1994) PD data; (solid
square) Lam et al.’s (1999) CT BMD1 data for Rangifer. Comparison includes only those compact bone portions
favored by Stiner (2002) for counting MNE.
anatomy. Pooling elements by anatomical
regions eliminates much of the potential
ambiguity originating from differential
bone density, and comparisons of portions
composed mainly of compact bone across
anatomical regions reduces the risks of
misinterpretation further still. Anatomical
regions may seem to be exceptionally
coarse divisions of the anatomy of large
prey animals, yet these regions are arguably
closer approximations, however imperfect,
of the butchering and transport units that
humans commonly create.
It remains true that humans and
other factors can produce similar (equifinal)
density-dependent biases in archaeofaunas.
An assessment of density-mediated bone
attrition assists in narrowing the
possibilities, but seldom excludes all
competing explanations. As such, the
comparisons of bone density standards and
applications to faunal assemblages
undertaken in this study indicate that the
accuracy of the density parameters
currently available meets or exceeds the test
requirements of most zooarchaeologists.
One’s selection of density parameters
generally does not “make or break” an
archaeological study.
134
Stiner
Though less widely discussed, there
is at least one more issue that influences the
outcomes of research on body part patterns
of prey animals. This issue concerns how
well any protocol for counting skeletal
elements on the basis of recognizable
features in fragmented material succeeds in
recovering the number of elements
originally present in the assemblage. Short
of totally reconstructing the skeletal
elements from fragments (sensu Marean et
al., 1992; Marean & Kim, 1998; Marean &
Spencer, 1991), the solution must lie in the
level of anatomical detail recognized and
recorded. The method for recording
portion-of-elements used by this author is
much finer grained than any of the
published scan site sets (Appendix 1 and
Figures 15-26); for example, this protocol
treats limb ends as potentially divisible to
four subsections; fewer diagnostic shaft
features are available, though these portions
are apparently among the most dense. Scan
sites, instead, tend to represent whole bone
cross-sections, whether positioned through
limb epiphyses, limb shafts, or other
elements. Because the scan sites describe an
average density for potentially divisible
morphologic subsets, the anatomical data
generated by scan site and portion-ofelement counts are not altogether
compatible. Total refitting of fragments is
more consistent with the use of scan site
parameters. It is also incredibly costly.
By estimating elements from
features on fragments, are we missing
significant numbers or types of skeletal
parts by avoiding the task of complete
refitting of bone fragments? A systematic
comparison of refitting and portion-based
reconstruction has yet to be undertaken.
Ideally it should be done on fragmented
material of known history, generated by
humans other than archaeologists, and
analyzed by diverse zooarchaeologists as a
safeguard for replicability. The outcome is
unlikely to provide a basis for rejecting
existing studies out of hand, but the new
information could allow refinements in
expectations for certain high-resolution
studies of body part representation in
archaeofaunas.
Acknowledgments
I thank, Natalie Munro and Guy Bar-Oz,
the organizers of the Montreal SAA
symposium in spring 2004 for providing a
stimulating forum in which to develop this
study. I also am grateful to Walter Klippel
and the vertebrate comparative collection at
the University of Tennessee, Knoxville, for
access to the Dama dama reference
specimen, to Levent Atıcı of Harvard
University for access to the Capra
aegagrus specimen, and to the Arizona
State Museum zooarchaeology comparative
collection, Tucson, for access to various
taxa, the bones of which are illustrated in
Figures 15 through 26. This publication has
benefited from comments by Bar-Oz,
Munro, and an anonymous reviewer. The
research was supported in part by a grant
from the National Science Foundation
(SBR-9511894).
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Bone density parameters and ungulate body part profiles
Appendix 1. Stiner’s faunal coding keys for skeletal elements and portions of elements in research on ungulate faunas. Portions can
occur singly or in combination with others, and thus the coding system is hierarchical (from Stiner 2002).
ELEMENTS
PORTIONS-OF-ELEMENTS
_________________________________________________________________________
HORN/ANTLER (10s):
11 horn core
12 antler
SKULL (20s):
21 half cranium, L or R
22 half mandible, L or R
NECK (30s):
31 atlas
32 axis
33 cervical vertebra
MAIN AXIAL COLUMN (40s):
40 vertebra, type unknown
41 thoracic vertebra
42 rib
43 lumbar vertebra
44 sacral vertebra
45 innominate (1/2 pelvis)
46 caudal vertebra
47 sternal segment
FRONT LIMB (50s & 60s):
51 scapula
52 humerus
53 coracoid (e.g., birds)
61 radius
62 ulna
63 carpal (type unknown)
64 metacarpal (bird=carpometacarpus)
65 cuneiform
66 magnum
67 lunate
68 scaphoid
69 unciform
HIND LIMB (70s & 80s):
71 femur
81 tibia
82 patella
83 astragalus
84 calcaneum
85 tarsal (type unknown)
86 metatarsal (bird=tarsometatarsus)
87 naviculo-cuboid
88 external & middle cuneiform
89 lateral malleolus
FEET (90s):
90 sesamoid
91 first phalanx
92 second phalanx
93 third/terminal phalanx
HORN/ANTLER:
10 rosette (base)
11 pedicle-braincase
12 shaft-rosette-pedicle-braincase
13 tip/tine (2=shaft fragment; 80=diaphysis section)
CRANIUM & MANDIBLE:
19 hyoid
20 premaxilla (or “incisive” of anterior mandible)
21 nasal
22 zygomatic (mastoid-squamous zone)
23 maxilla (~complete half)
24 maxilla fragment (241 anterior rim; 242 posterior rim)
25 petrous
26 auditory bulla
27 braincase fragment
28 occipital (dorsal rim)
29 occipital condyle (right or left)
30 frontal foramen (or anterior foramen of mandible)
31 orbit lower rim (or gonial angle of mandible)
32 lacrimal (foramen)
Other: 16 post margin of mandibular symphysis; 17 basi-cranium; 18 upper orbit
MANDIBLE, BASE MISSING:
33 middle horizontal ramus
34 mid-anterior horizontal ramus
35 anterior horizontal ramus (anterior alvaeolus of LP2)
36 mid-posterior horizontal ramus
37 posterior horizontal ramus (dorsal ridge behind LM3)
38 concavity between condyle-coronoid (or base of glenoid process of scapula)
39 base of horizontal ramus
40 condyloid process
41 coronoid process
42 condyle & coronoid
43 ascending ramus (431lingual foramen)
MANDIBLE, BASE INTACT:
44 horizontal ramus (whole)
45 middle horizontal ramus
46 anterior horizontaontal ramus
47 posterior horizontal ramus
48 mid-anteror horizontal ramus
49 mid-posterior horizontal ramus
INNOMINATE:
57 acetabulum fragment
58 acetabulum section—pubic body (581 anterior rim of symphysis; 582 ridge)
59 acetabulum, complete
60 acetabulum & ilium (~complete)
61 acetabulum section—iliac body fragment
62 acetabulum-iscium (~complete)
63 acetabulum section—ischial body fragment
64 iliac body (diaphysis)
65 iliac blade (651 dorsal tip; 652 ventral tip)
138
Stiner
GENERAL ELEM CATEGORIES:
1 metapodial (type unknown)
2 long bone shaft (type unknown)
3 flat bone (skull or scapula fragment)
4 carpal or tarsal (type unknown)
GENERAL ELEM. CAT., cont.:
5 spongy element (axial)
6 auxiliary third phalanx
7 auxiliary second phalanx
8 auxiliary first phalanx
9 auxiliary metapodial
TEETH (100s, mammals only):
9_ _ _deciduous tooth
100 from upper jaw
200 from lower jaw
300 dental position unknown
_10 incisor (type unknown)
_11 first incisor
_12 second incisor
_13 third incisor
_20 canine
_30 premolar (type unknown)
_31 first premolar
_32 second premolar
_33 third premolar
_34 fourth premolar
_40 molar (type unknown)
_41 first molar
_42 second molar
_43 third molar
66 ilium
67 ischial body
68 ischial blade (681 base or coxae; 682 lateral tuberosity)
69 ischium
VERTEBRAE:
50 epiphysis (501 anterior; 502 posterior)
51 centrum (body intact)
52 transverse process
53 pre-zygopophyses (53-53=intact pair)
54 post-zygopophyses (54-54=intact pair)
55 dorsal spine (also proximal “heel” of ulna olecranon)
56 half
57 anterior-ventral articulation
58 zygopophysis (type unknown)
LIMB BONES & RIB (LARGER PORTIONS:
70 proximal (P) epiphysis
71 P epiphysis fragment (see also 91-94)
72 P < 1/2
73 P 1/2
74 P > 1/2
75 distal (D) > 1/2
76 D 1/2
77 D < 1/2
78 D epiphysis fragment (see also portions 81, 84)
79 D epiphysis
LIMB BONE & RIB EPIPHYSIS PORTIONS:
81 medial distal (D) epiphysis
82 lateral D epiphysis
83 anterior D epiphysis
84 posterior D epiphysis
91 anterior proximal (P) epiphysis
92 posterior P epiphysis
93 medial P epiphysis
94 lateral P epiphysis (for calcaneum: 941 tuberosity, 942 tip)
LIMB BONE SHAFT & INNOMINATE FEATURES:
990 w/ foramen present
991 w/ proximal rim of attachment scar (radius or ulna)
992 waist (narrowest cross-section or collum) of diaphysis (scapula)
994 anterior "angle" (tibia or scapula)
995 muscle insertion or ligament scar
996 posterior rugosities (tibia or innominate)
997 interior diagonal lattice (humerus)
998 anterior groove (metapodials)
999 posterior groove (metapodials)
GENERAL PORTION CODES:
1 complete
2 nearly complete
56 half (561 lateral dimension; 562 vertical)
80 short diaphysis (tube)
85 long diaphysis (for rib, proximal diaphysis with dorsal ridge
86 diaphysis with foramen
90 shaft fragment
95 spongy bone fragment
97 flat bone fragment
139
Bone density parameters and ungulate body part profiles
NOTE: Position and character of a named portion may vary somewhat with taxon such that minor adjustments in definition are
needed. This system for classifying and counting distinct morphological features on bones is designed to reconstruct the number of
elements represented by fragmented material, and to facilitate simple quantification for body part analysis. Morphologic terms that
are unique to a particular element (e.g., processus anconaeus) are avoided in favor of terms that reflect commonalities in shape and
orientation (e.g., anterior, posterior; proximal, distal).
Figure 15. Examples of the minimum possible portions-of-elements (code number in italics) for the scapula of Ovis
aries as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT scan sites
(adapted from Lyman, 1984).
Figure 16. Examples of the minimum possible portions-of-elements (code number in italics) for the humerus of Sus
scrofa as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT scan sites
(adapted from Lyman, 1984).
140
Stiner
Figure 17. Examples of the minimum possible portions-of-elements (code number in italics) for the radius and ulna
of Capra aegagrus as represented in the body part coding system in Appendix 1. Line drawing represents PD and
CT scan sites (adapted from Lyman, 1984).
Figure 18. Examples of the minimum possible portions-of-elements (code number in italics) for the femur of Dama
dama as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT scan sites
(adapted from Lyman, 1984).
141
Bone density parameters and ungulate body part profiles
Figure 19. Examples of the minimum possible portions-of-elements (code number in italics) for the tibia of Ovis
canadensis as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT scan
sites (adapted from Lyman, 1984).
Figure 20. Examples of the minimum possible portions-of-elements (code number in italics) for the metatarsal of
Bos taurus as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT scan
sites (adapted from Lyman, 1984).
142
Stiner
Figure 21. Examples of the minimum possible portions-of-elements (code number in italics) for the cranium of
Dama dama as represented in the body part coding system in Appendix 1. No scan sites.
Figure 22. Examples of the minimum possible portions-of-elements (code number in italics) for the mandible of
Ovis canadensis as represented in the body part coding system in Appendix 1. Line drawing represents PD and CT
scan sites (adapted from Lyman, 1984).
143
Bone density parameters and ungulate body part profiles
Figure 23. Examples of the minimum possible portions-of-elements (code number in italics) for various cervical
vertebrae of Dama dama as represented in the body part coding system in Appendix 1. Line drawing represents PD
and CT scan sites (adapted from Lyman, 1984).
Figure 24. Examples of the minimum possible portions-of-elements (code number in italics) for the thoracic and
lumbar vertebrae of Dama dama as represented in the body part coding system in Appendix 1. Line drawing
represents PD and CT scan sites (adapted from Lyman, 1984).
144
Stiner
Figure 25. Examples of the minimum possible portions-of-elements (code number in italics) for the innominate
(pelvis) of Ovis aries as represented in the body part coding system in Appendix 1. Line drawing represents PD and
CT scan sites (adapted from Lyman, 1984).
Figure 26. Examples of the minimum possible portions-of-elements (code number in italics) for the phalanges, rib,
calcaneum, and astragalus of Dama dama as represented in the body part coding system in Appendix 1. Line
drawing represents PD and CT scan sites (adapted from Lyman, 1984).
145
Bone density parameters and ungulate body part profiles
146