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 4)
Madrigal
The Derivation and Application of White-Tailed
Deer Utility Indices and Return Rates
T. Cregg Madrigal*
New Jersey Dept. of Environmental Protection, PO Box 425, Trenton, NJ 08625-0425
Journal of Taphonomy 2 (4) (2004), 185-199.
Manuscript received 27 September 2004, revised manuscript accepted 6 December 2004.
Utility indices have long been used to interpret ungulate body part representation at archaeological sites.
The use of return rates, which are a more appropriate measure for studies of foraging efficiency, have
been used less frequently. Until recently, zooarchaeologists interested in the prehistoric use of whitetailed deer were forced to use utility indices developed from other species. In this paper, the derivation
and application of utility indices and return rates for white-tailed deer are discussed and two recently
derived white-tailed deer utility indices are compared.
Keywords:
AMERICA
DEER, UTILITY INDICES, BODY PART REPRESENTATION, MARROW, NORTH
Introduction
Patterns of ungulate body part
representation have long been used to infer
transport of animals or animal parts. In
prehistoric Eastern North America, where
the ungulate being transported was usually
white-tailed deer (Odocoileus virginianus),
there is also a related interest in examining
the differential representation of deer body
parts for evidence of ritual feasting,
provisioning, or status differences (e.g.,
Bogan, 1982; Jackson & Scott, 1995a,
1995b, 2003; Kelly, 1997; Welch, 1991). In
order to interpret differences in the
abundance of different deer bones at an
archaeological site, it is important to have
an idea of how much meat, marrow, and
other nutrients can be obtained from each
body part, and how much time it takes to
remove those nutrients from the bones. This
is the justification for the development of
utility indices, which rank body parts by
their nutritional value. In the over twentyfive years since Binford’s (1978) pioneering
work with caribou and sheep, a veritable
menagerie of animals has been butchered,
weighed, and otherwise manipulated in
order to create taxon-specific utility indices
(e.g., Blumenschine & Caro, 1986;
Blumenschine & Madrigal, 1993; Brink,
1997; Diab, 1998; Emerson, 1990; Friesen
et al., 2001; Lupo, 1998; Lyman et al.,
1992; Mengoni-Goñalons, 1991; Outram &
Article JTa023. All rights reserved.
* E-mail:[email protected]
185
White-tailed deer utility indices and return rates
Rowley-Conwy, 1998; Savelle & Friesen,
1996; Savelle et al., 1996).
Parallel to the development of utility
indices, there has been an increasing
interest among many zooarchaeologists in
the use of behavioral ecological principles
(Blumenschine et al., 1994; Cavallo, 1991;
O’Connell, 1995), which seek to explain
behavior by determining how an individual
maximizes its fitness within certain
constraints (Krebs, 1978; Krebs & Davies,
1987). Within behavioral ecology, optimal
foraging models are predicated on the
assumption that foraging efficiency is an
accurate proxy of reproductive fitness.
Because different carcass parts have
different energy yields, utility indices
provide a way to measure foraging
efficiency. Traditional utility index studies,
however, are not actually applications of
foraging theory because utility indices
provide a measure only of the benefits, in
terms of the weight of meat, marrow, or
grease, of a body part, but not the cost, in
terms of the time it takes to process the
animal (Marean & Cleghorn, 2003:18). In
other words, traditional utility indices by
themselves do not contain the information
needed to evaluate foraging efficiency. A
more appropriate unit of measurement is
the post-procurement return rate, which
estimates both the costs and benefits of a
body part. Studies of animal body part
return rates are much more rare than utility
indices (e.g., Lupo, 1998; Madrigal & Holt,
2002).
Until recently, neither utility
indices nor return rates were available for
white-tailed deer, forcing zooarchaeologists
interested in examining prehistoric deer use
to rely on indices created for other species.
The Food Utility Index (FUI), derived by
Metcalfe and Jones (1988) from the original
caribou utility index (Binford, 1978), was
itself later modified by some researchers in
an attempt to make it more suitable for use
with a different, albeit closely related,
species (Purdue et al., 1989). This
transformation, in which body parts are
grouped into either a low, mid, or high
utility group and then their relative
abundance is compared, may increase the
risk of equifinality or uncertainty regarding
the underlying cause of patterns that may be
evident.
In the past several years, two
separate studies have examined white-tailed
deer meat and marrow yields (Jacobson,
2000; Madrigal & Capaldo, 1999; Madrigal
& Holt, 2002). Both studies recorded meat
and marrow weights for deer body parts,
and one study (Madrigal & Holt, 2002) also
recorded butchery times, from which return
rates were calculated. These studies provide
data with which to study both
archaeological assemblages of deer bone
and Purdue and colleagues’ transformation
of the FUI.
Gross Yields
In this paper, the weight of a particular unit
of meat or marrow is termed the gross
yield. This is the standard unit of utility
indices, although these weights are usually
transformed into an index value. Such
transformations, however, can
unnecessarily obscure the actual data and
are not used in this study.
Kilocalorie (kcal) yield estimates
can be derived by multiplying the gross
yield, in grams, by the number of
kilocalories of energy per gram. A study of
186
Madrigal
70
60
Weight (kg)
50
40
30
20
10
12
V
O
F
09
7
-2
13
V
11
2
O
M
10
1
F
M
59
7
-1
-1
-1
79
8
11
2
F
O
F
04
0
M
11
2
M
M 11
N
J1
11 01
20
97
M -1
O
V
11
F
N
J1
F
0
RU 2
17
/1
F 8
RU
F
RU 10
12
F
04 /13
07
99
F
11 -1
27
9
F
10 8-1
15
97
F
RU -1
M 14 /
11 15
20
97
-2
100
90
80
70
60
50
40
30
20
10
0
RU
Weight (kg)
79
9
V
09
7
-1
11
0
M
M
six white-tailed deer ranging in age from
fawns to adults used adiabatic bomb
calorimetry to determine the energy content
(kcal/g) of various deer body tissues
(McCullough & Ullrey, 1983). Long bone
marrow provides an average of 9.37 kcal/g,
while skeletal muscle (not including
separable fat) has an average energy
content of 6.09 kcal/g (McCullough &
Ullrey, 1983:434). Obviously, the actual
energy content of meat or marrow from a
single deer will vary, depending mainly on
the condition of the deer and the amount of
fat present (see Blumenschine & Madrigal,
1993; Madrigal & Capaldo, 1999, for
discussion of marrow variability). The
conversion of gross yields to kilocalorie
yields makes it possible to directly compare
the energy yields of deer to energy yields of
other plants and animals, which is not
possible with traditional utility indices.
The three New Jersey deer for
which meat gross yields and return rates
were determined (Figure 1a) consist of one
male yearling with a dressed body weight
(entire carcass minus internal organs and
blood) of 54.3 kg, a female fawn with a
dressed weight of 18.6 kg, and a male fawn
with a dressed weight of 37.2 kg (Madrigal
& Holt, 2002). The eight New Jersey deer
from which marrow weights were obtained
(Figure 1b) include three males (two
yearlings and one fawn) and five females
(two fawns, two yearlings, and one adult).
Estimated body weights range from 40.3 to
86.7 kg (Madrigal & Capaldo, 1999).
Jacobson (2000) studied five deer
from Tennessee. The Tennessee sample is
comprised of a single male fawn (0.5 years)
and four adults: a 6.5 year old female, a 3.5
year old male, a 3 year old female, and a
2.5 year old female (Jacobson, 2000:31).
Figure 1. Comparison of dressed weights of New
Jersey (filled bars) and Tennessee (empty bars) deer.
Data from Jacobson, 2000:31 and Madrigal & Holt,
2002. A) deer used to determine meat yields B) deer
used to determine marrow yields. M=male; F=female
Dressed weights ranged from 24.1 kg to
57.9 kg (Figure 1). For each deer, “The
meat weight [of each body part] was
divided by the weight of the skinned and
gutted carcass, and the amount multiplied
by 100 percent” (Jacobson, 2000:43) to
obtain the meat utility index value. A
standardized meat utility index (SMUI) was
also calculated by averaging the MUI
values of all five deer. Likewise, a marrow
utility index (MAUI) was also created “by
dividing the weight of the whole bone
187
White-tailed deer utility indices and return rates
Table 1. Average meat gross yield (kcal) of
New Jersey and Tennessee white-tailed deer.
Data derived from Madrigal & Holt, 2002;
Jacobson, 2000.
Table 2. Average marrow gross yield (kcal) of
New Jersey and Tennessee white-tailed deer.
Data derived from Madrigal &Holt, 2002:Table
4; Jacobson, 2000.
Element
Average Gross Yield
Element
NJ dry
TN wet
NJ
TN
Tibia
171.5
258.7
Femur
18,404.0
32,006.2
Femur
91.5
185.7
Thoracic
10,694.0
18,975.3
Radius
63.0
100.6
Rib
9,867.8
24,588.2
Cervical
9,658.7
14,371.3
Metatarsal
52.6
104.0
Scapula
6,644.2
12,395.0
Humerus
46.1
121.1
Pelvis/Sacrum
4,811.1
22,439.7
Metacarpal
30.1
59.8
Tibia
3,599.2
9,632.6
Mandible
10.4
-
Humerus
3,313.0
9,270.4
1st Phalanx
5.3
-
Radio-ulna
1,542.8
4,802.6
2nd Phalanx
4.6
-
Lumbar
1,307.3
16,286.9
minus the weight of the bone without
marrow by the weight of the skinned and
gutted carcass, multiplying it times two
(since there are two of each element), and
then multiplying the result times 100
percent” (Jacobson, 2000:54). The five
Tennessee deer were also averaged to
create a standardized marrow utility index
(SMAUI). This differs from procedures
used for the New Jersey deer, where
marrow was directly removed from bones
and weighed (to obtain a “wet weight”),
then dried to determine the actual fat
content (“dry weight”). Jacobson
determined the percent marrow fat for each
long bone using the reagent-dry assay
method (Verme & Holland, 1973).
Jacobson provides carcass weights
for each deer and meat and marrow utility
index values (but not actual meat and
marrow weights) for each body part. Using
Jacobson’s MUI and MAUI formulas, I was
able to calculate the actual meat weights
and marrow wet weights. Kilocalorie
estimates were then calculated for the
Tennessee deer, using energy content data
from McCullough & Ullrey (1983), for
comparison with the New Jersey sample
(Tables 1 & 2).
The Tennessee deer are, on
average, older and larger than the New
Jersey deer for which meat yields are
available and consequently have higher
gross energy yields (Figure 2). For
example, the average gross yield of femur
meat for Tennessee deer is almost twice
that of the New Jersey deer. There is less of
a difference when Tennessee deer body size
188
Madrigal
NJ Deer
35,000
TN Deer
30,000
Kcal
25,000
20,000
15,000
10,000
5,000
0
Femur
Rib
Scapula
Tibia
Radio-ulna
Element
Figure 2. Comparison of average meat gross yield, by element, of New Jersey and Tennessee deer. NJ=New Jersey
deer; TN=Tennessee deer.
is compared to the larger sample of New
Jersey deer for which marrow gross yields
were obtained, and, in fact, the largest deer
in either sample is a male yearling from
New Jersey. The Tennessee sample has
higher marrow gross yields (Figure 3)
because kilocalorie yields were calculated
from marrow wet weights (i.e., including
fat, water, and non-fat cell residue), while
the New Jersey yields are derived from dry
weights (i.e., fat only). Madrigal & Capaldo
(1999) presented deer kilocalorie yields
based on both marrow wet weight (which
was considered an estimate of the ideal
maximal marrow yield possible in an
unstressed individual) and dry weights.
There is also variation in the
butchery methods used and the manner in
which meat was assigned to skeletal
elements. For New Jersey deer, butchery
emphasized the efficient removal of meat
“packets” for storage and later
consumption. Meat was often removed at
the location of muscle attachments, rather
than at the ends of individual bones. This
made it difficult, in some cases, to decide
how to assign meat to a bone. In particular,
the meat gross yield for lumbar vertebrae in
New Jersey deer is low because Madrigal
and Holt assign only the tenderloin (psoas
major) to this body part. The loin
(longissimus thoracis and
longissimus
lumborum), which runs the length of both
the thoracic and lumbar vertebrae on their
dorsal sides, was arbitrarily assigned solely
to the thoracic vertebrae (Madrigal & Holt,
2002:747). In contrast, Jacobson cut
through muscle masses, so that meat
weights for Tennessee deer are more
closely associated with individual bones,
189
White-tailed deer utility indices and return rates
300
250
NJ Deer
TN Deer
Kca
200
150
100
50
M
et
ac
ar
pa
l
H
um
er
us
M
et
ata
rsa
l
Ra
di
us
Fe
m
ur
Ti
bi
a
0
Figure 3. Comparison of average marrow gross yield, by element, of New Jersey and Tennessee deer.
regardless of the location of muscle
attachments (Jacobson, 2002:39).
These differences in methods help
explain the difference in the ranking of deer
body parts by meat energy yield (Table 1).
In both samples, the femur provides the
greatest amount of meat energy. In the New
Jersey sample, the thoracic vertebrae
provide the second-greatest amount of meat
while the lumbar vertebrae have the lowest
energy yield. In the Tennessee sample, in
contrast, the thoracic vertebrae are ranked
fourth, after the ribs and the pelvis/sacrum,
and the lumbar vertebrae are ranked fifth.
Despite these differences, kilocalorie gross
yields for deer meat in the Tennessee and
New Jersey samples are positively and
significantly correlated (r=.79, p=.006;
Figure 4).
As noted above, there are also
important differences in the way marrow
yield was determined. Values presented for
New Jersey deer are dry weights, which
represent actual fat content (see
Blumenschine & Madrigal, 1993; Madrigal
& Capaldo, 1999 for additional details),
while Tennessee deer marrow yields are
wet weights, which include both fat and
water (marrow fat percentage values for
individual deer bones were also presented
by Jacobson). As Jacobson has also noted
(2002:60), kilocalorie estimates based on
wet weights overestimate the actual energy
content of marrow.
The tibia and the femur are the two
bones with the greatest marrow yield in
both the New Jersey and Tennessee
samples, although there are some
differences in the relative rankings of other
elements. Among New Jersey deer, the
femur is followed by the radius, metatarsal,
and humerus, while for Tennessee deer, the
situation is reversed, with the humerus
providing the third greatest marrow yield,
followed by the metatarsal and radius.
Despite these differences, New Jersey and
Tennessee marrow gross yields are also
highly correlated (r=.96, p=.002).
190
Madrigal
Meat
TN Gross Yield (k
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
0
5,000
10,000
15,000
20,000
NJ Gross Yield (kcal)
Figure 4. Comparison of average meat gross yield (kcal). Data from Table 1.
Return Rates
The net yield, or post-procurement return
rate, is derived by dividing the gross yield
of a part in kilocalories by the time it takes
to remove the meat or marrow from the
bone, and is reported as kilocalories per
hour (kcal/hr). Different processing
techniques, of course, may result in
different return rates. The New Jersey deer
were butchered using metal knives for meat
removal and hammerstones to break bones
for marrow (Madrigal & Capaldo, 1999;
Madrigal & Holt, 2002). Butchering times
were not recorded in Jacobson’s study, so
return rates could not be calculated for
Tennessee deer.
A comparison of marrow gross yield
to marrow return rate for New Jersey deer
shows that the two are highly and
significantly correlated (r=.91, p=.006;
Figure 6). This may be an indication that
the time it takes to hammerstone fracture
any given long bone is roughly the same,
although bones with relatively narrow
marrow cavities, like the radius, may have
slightly higher extraction times.
There is also a positive correlation
between meat gross yield and meat return
rate, although this is not statistically
significant (r=.50, p=.14; Figure 7), and
there clearly are differences in the relative
ranking of different body parts (Table 1 and
3). The femur has the greatest gross yield,
but falls to second place behind the thoracic
vertebrae when return rates are calculated.
The ribs, in contrast, drop from third place
in gross yield to last place in terms of return
rate.
Riders
A further transformation commonly made
with utility indices is to factor in the
perceived transport value of so-called
191
White-tailed deer utility indices and return rates
Marrow
TN wet weight gross yield
300
250
200
150
100
50
0
0
50
100
150
200
NJ dry weight gross yield (kcal)
Figure 5. Comparison of average marrow gross yield (kcal). Data from Table 2.
“riders”. Binford (1978) created the
Modified General Utility Index (MGUI)
because he thought that “parts of lower
value may be thought of as ‘riders’ in that
they are being transported not as a function
of their consumable potential but in relation
to the value of the adjacent parts when
transport considerations do not force totally
maximizing decisions” (Binford, 1978:74).
Note that even here, Binford realizes that
the transport potential of a bone element is
not a constant – that is, he recognizes that
sometimes “riders” will be transported not
because they are riders, but because the
transporters actually want the nutrients they
contain.
The MGUI value of axial and
proximal appendicular parts is the same as
their General Utility Index (GUI) value.
The MGUI for more distal appendicular
bones (e.g., tibia, radius/ulna, metapodials)
is the mean of the GUI of that part and the
next proximal part. Metcalfe & Jones
(1988) used the same rider transformation
to create their Food Utility Index (FUI).
Table 3. Average meat and marrow return rates
(kcal/hr) for New Jersey deer.
Element
Thoracic
Femur
Pelvis/Sacrum
Cervical
Radius
Scapula
Lumbar
Tibia
Humerus
Rib
Metatarsal
Metacarpal
Mandible
1st Phalanx
2nd Phalanx
192
Meat
232,399.1
213,927.9
209,261.5
194,557.3
152,528.4
139,554.5
120,402.7
117,965.9
114,323.6
81,110.4
-
Marrow
4,844.8
1,824.4
5,498.4
3,163.2
1,822.3
997.8
1,122.5
163.2
104.2
Madrigal
The rider transformation is not based on
any actual data on the relative costs of
abandoning a part versus transporting it.
Instead, it assumes the likelihood that a part
with relatively low utility will be
transported as a rider is the same for all
parts. In actuality, it seems reasonable that
the riderability of a part is variable – like
any transport decision, it will depend on the
characteristics of the parts themselves: the
weight of the rider and the ridee, the
difficulty in disarticulating the parts; the
nutritional condition of the animal; and on
the needs of the people doing the
transporting.
An inherent flaw of the rider
transformation is that it makes the mistake
of fixing as a constant precisely those
variables that archaeologists are most
interested in studying (Chase, 1985). One
of the most important, and common,
reasons for studying body part profiles is to
determine which body parts were
transported or butchered, and why.
Labeling some bones as “riders” forces
zooarchaeologists to assume that if low
utility parts were transported, they were
transported not because hunters were
interested in their food (or other) value, but
because it was easier to bring them along
than to spend the time removing them.
Chase concludes that the MGUI (and
consequently the FUI) “can in no way be
taken as a measure of the utility and
transportability of a body part” (1985:298).
In fact, the riders transformation
appears to be a way to make utility indices
conform more closely to preconceived
notions about how important different body
parts should be. But if low utility bones are
present in an assemblage, especially in one
that appears, from other evidence, to
represent a transported assemblage, then
they need to be explained – not just
assumed to be riders.
Marrow
7,000
6,000
kcal/h
5,000
4,000
3,000
2,000
1,000
0
0
50
100
150
200
kcal
Figure 6. Comparison of marrow gross yield and return rate for New Jersey deer.
193
White-tailed deer utility indices and return rates
Meat
250,000
kcal/h
200,000
150,000
100,000
50,000
0
0
5,000
10,000
15,000
20,000
kcal
Figure 7. Comparison of meat gross yield and return rate for New Jersey deer.
Applications of Utility Indices to Whitetailed Deer
Zooarchaeologists have often interpreted
the differential representation of whitetailed deer remains in terms of transport,
provisioning, status differences, or ritual
feasting. Systematic provisioning of elites
by commoners may result in elite bone
accumulations with a greater abundance of
meat-bearing bones in general, and highranked bones in particular, compared to
lower-status accumulations (Jackson &
Scott, 1995a, 1995b, 2003). For example,
Bogan (1983) argues that at the
Mississippian Toqua site in Tennessee, the
front leg of the deer was preferentially
distributed to higher-status individuals,
while lower-status sites contain “less
meaty” deer portions such as the skull and
lower legs (Bogan, 1983:317). Other
studies suggest that an abundance of
hindlimbs may be indicative of
provisioning (e.g. Jackson & Scott, 1995b;
Welch, 1991). Interestingly, most studies
put little emphasis on the presence or
absence of ribs and vertebrae, which have
some of the highest gross yields and return
rates. Clearly, studies such as these would
benefit from white-tailed deer-specific
utility indices and return rates.
After the publication of the original
utility indices, many archaeologists,
intrigued by the potential insights they
could provide, attempted to use the indices
developed from caribou and sheep to
interpret the bones of other species (e.g.,
Speth, 1983; Thomas & Mayer, 1983).
Some zooarchaeologists, justifiably
concerned that the FUI values derived from
a single caribou may not have been directly
applicable to the white-tailed deer remains
they were studying, further modified
Metcalfe and Jones’ FUI by dividing body
parts into three groups: those with high,
medium, and low FUI values (Purdue et al.,
1989). Under this scheme, high utility (FUI
> 3000) parts are comprised of the sternum,
femur, and tibia and tarsals; mid utility
(1000 < FUI <3000) parts are the vertebrae
(except the atlas and axis), pelvis and
sacrum, ribs, scapula, humerus, radius and
194
%NISP
Madrigal
50
45
40
35
30
25
20
15
10
5
0
Range
Boschert
High FUI
Mid FUI
Low FUI
Figure 8. Percent NISP of deer bones from the Boschert and Range sites by utility group. Data from Purdue et al.,
1989:Table 4.
ulna, and metatarsal; low utility (FUI <
1000) are antler, skull, mandible, teeth,
atlas and axis, metacarpal and carpal, and
phalanges (Purdue et al., 1989:160). This
method has since been used by other
Midwestern
and Southeastern
zooarchaeologists (e.g., Holt, 1996; Jackson
& Scott, 2003; Kelly, 1997).
Purdue and colleagues compared
two sites, Boschert (23SC609), a Late
Woodland upland site near the Mississippi
River in St. Charles County, Missouri, and
Range, a Late Woodland site in the
American Bottom of Illinois. Deer bones
were quantified using NISP and comprised
132 specimens from Boschert and 363 from
Range. The number of deer specimens in
each of the three utility groups was then
totaled and the %NISP of each of the three
utility groups were compared. Using these
methods, high utility elements appear to be
underrepresented and low utility elements
overrepresented at Boschert, with 47% of
deer bones in the low utility group, 41.7%
in the mid utility group, and only 11.4% in
the high utility group. At Range, 31.4% of
bones are in the low utility group, 46.8%
are in the mid utility group, and 21.9% are
in the high utility group (Figure 8). Based
on these results, Purdue and colleagues
argue that the Boschert site was a
“preliminary processing site” (Purdue et al.,
1989:153) and high utility deer parts were
transported away from Boschert.
Unfortunately, because of the way
data was aggregated, the Boschert and
Range site data cannot be easily compared
to the gross yields and return rates
presented here. For example, NISP counts
for tibia and tarsals are combined, as are all
vertebrae aside from the atlas and axis. A
comparison of the high, mid, and low FUI
categories with New Jersey white-tailed
deer (Figure 9), however, indicates that
there is no real relationship between the
three categories and actual meat gross yield
or return rate. For example, the high-yield
femur is lumped with the tibia, which is
ranked seventh out of ten body parts in
terms of meat gross yield, and eighth in
195
White-tailed deer utility indices and return rates
terms of return rate, and with the tarsals,
which have no meat or marrow directly
associated with them.
The mid utility group contains a
range of body parts. The vertebrae and ribs
actually contain large amounts of meat, and
in fact the thoracic vertebrae have the
highest return rate of any body part. The
humerus and radius/ulna, which are two of
the lowest-ranked meat-bearing body parts,
are also included in this group, as is the
metatarsal, which contains little to no meat
and whose primary food value comes from
its marrow.
The low utility group consists
primarily of the head, including teeth and
antlers. Unfortunately, meat from the head
was not included in either of the deer utility
index studies, but the head actually contains
a fair amount of meat, as well as the brain
20,000
and tongue (tongue weights are included in
Jacobson’s [2000] study), which are both
valuable sources of energy. Other “low
utility” elements include the atlas and axis
(even though the cervical vertebrae as a
whole have the fourth-highest meat gross
yield) and the metacarpals and phalanges.
The lack of agreement between the
two rankings of deer parts is due in large
part to the use of a utility index, the FUI,
that includes a transformation for riders, as
well as to differences in the ranking of body
parts of deer and caribou. Collapsing a
utility index that incorporates a
transformation for riders into a tripartite
division of high, medium, and low utility
will overestimate the importance of some
elements and underestimate the value of
others. As a result, this method increases
the risk of equifinality as the analyst cannot
"High FUI"
18,000
Meat Gross Yield (K
16,000
14,000
12,000
"Low FUI"
10,000
8,000
6,000
"High FUI"
4,000
2,000
Lu
m
ba
r
Ra
di
oul
na
H
um
er
us
Ti
bi
a
Pe
lv
is/
Sa
cr
um
Sc
ap
ul
a
Ce
rv
ic
al
Ri
b
Th
or
ac
ic
Fe
m
ur
0
Figure 9. NJ Deer average meat gross yield. Hollow bars are considered "Mid FUI" by Purdue et al., 1989; other
elements are as labeled. Purdue & colleagues consider the first two cervical vertebrae as "Low FUI" and all
remaining vertebrae as "Mid FUI".
196
Madrigal
determine whether the patterns seen are due
to selective transport, differential
destruction, or a combination of these and
other factors.
This can be seen by looking at the
three body parts that comprise the high
utility group. The sternum is extremely
susceptible to density-dependent
destruction, and is rarely found in
archaeological sites. The femur has
epiphyses that are moderately dense
(although the shaft is, like all long bone
shafts, resistant to destruction), while the
tibia (in particular the distal epiphysis) and
tarsals (especially the astragalus and
calcaneum) are resistant to destruction,
relatively large, and easy to identify.
Therefore, an assemblage with a large
proportion of high utility bones could
actually be dominated by astragali and
calcanea, as a result of density-dependent
destruction; be a specialized marrow
processing assemblage dominated by tibia
fragments; be dominated by femur
fragments as the result of selective transport
of high meat yield bones; or be some
combination of these.
Conclusion
Data on gross yield and return rate
contribute to the interpretation of ungulate
body part representation and provide
another tool to resolve equifinalty in the
interpretation of skeletal body part profiles.
Meat and marrow yields may help explain
much of the patterning seen in
zooarchaeological assemblages, but they
must be used in conjunction with bone
density, bone modification studies, and
other taphonomic analyses.
Relative gross yields, despite
differences in processing techniques, are
similar in New Jersey and Tennessee deer,
even though the samples are separated by
over 500 miles, are from different
environments, and represent different age
groups. In fact, white-tailed deer in
Tennessee are generally considered to be a
separate subspecies (Odocoileus
virginianus virginianus) from New Jersey
deer (Odocoileus virginianus borealis).
There are age and sex differences that
clearly result in differences in the total
yield, but, especially considering the
difficulty in aging and sexing fragments of
deer bone from archaeological sites, an
averaged index is probably the best allaround index to use.
Ideally, future
research will increase the geographic
distribution and age range of deer sampled,
and more closely investigate the energy
yields of those body parts traditionally
considered to have low yields, primarily the
head and feet.
The return rates presented here are
derived from a specific butchery technique
and do not take into account the variation
possible from using different butchery and
cooking techniques. Because steel knives
were used for butchery, the return rates may
be most applicable to Historic-Period
archaeological assemblages. It is also not
known how raw material type or tool
technology may affect return rates, or how
much butchery techniques may have varied
through time and by culture, although I
would expect that butchery would tend to
be efficient, regardless of the technology
used. Future research could profitably
examine the effect of different techniques
and technologies on the ranking of body
part return rates.
197
White-tailed deer utility indices and return rates
Utility indices and return rates
provide a frame of reference with which to
study zooarchaeological assemblages and
explore butchery technique, processing
decisions, transport decisions, and food
sharing. With the availability of these data
sets on white-tailed deer gross yield and
return rate, a reliance on a reduction of the
caribou FUI into a three-part system is
unnecessary. Utility indices and return
rates, in combination with other
information such as bone modification and
density data, provide baseline data for
identifying, examining, and perhaps
explaining the variability in behavior
encoded in zooarchaeological assemblages.
Acknowledgements
An earlier version of this paper was
presented at the 2004 Society for American
Archaeology conference symposium
Ungulate Body-Part Representation and
Zooarchaeological Research: Addressing
Issues of Equifinality. I thank Natalie
Munro and Guy Bar-Oz for inviting me to
submit this paper, and Jodi Jacobson for
providing me with a copy of her thesis.
Natalie Munro, Guy Bar-Oz, Jodi Jacobson,
and an anonymous reviewer provided
comments on an earlier draft of this paper.
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