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figure 6.20. Relationship between NISP and MNE values for caprine remains from
Neolithic pastoral site of Ngamuriak, Kenya. Best-¬t regression line (Y = “0.469X0.904 ;
r = 0.666) is signi¬cant (p = 0.002). Data from Table 6.17.
skeletal completeness, skeletal parts, and fragmentation 261


Table 6.18. Relationship between NISP and MNI per skeletal part or portion in twenty-two
assemblages

Assemblage Relationship r p Reference
= ’0.469X0.904
Ngamuriak Y 0.666 0.0026 Pilgram and Marshall (1995)
= ’0.083X0.762
Gatecliff Shelter Y 0.627 0.0001 Thomas and Mayer (1983)
= ’0.018X0.587
Boomplaas-Size I Y 0.769 0.0001 Klein and Cruz-Uribe (1984
= ’0.051 X0.53
Boomplaas-Size IV Y 0.888 0.0001 Klein and Cruz-Uribe (1984)
= ’0.034X0.492
El Juyo Red Deer-L. 4 Y 0.768 0.0001 Klein and Cruz-Uribe (1984)
= ’0.062X0.60
El Juyo Red Deer-L. 6 Y 0.701 0.0001 Klein and Cruz-Uribe (1984)
= ’0.083X0.705
Equus Cave-Size IV Y 0.888 0.0001 Klein and Cruz-Uribe (1984)
= ’0.097X0.70
Elandsfontein“Size I Y 0.874 0.0001 Klein and Cruz-Uribe (1991 )
= ’0.168X0.799
Elandsfontein“Size II Y 0.876 0.0001 Klein and Cruz-Uribe (1991 )
= ’0.395X0.977
Elandsfontein“Size III Y 0.905 0.0001 Klein and Cruz-Uribe (1991 )
= ’0.242X0.882
Elandsfontein“Size III Y 0.902 0.0001 Klein and Cruz-Uribe (1991 )
= ’0.189X0.84
Elandsfontein“Size V Y 0.855 0.0001 Klein and Cruz-Uribe (1991 )
= ’0.017X0.728
Klasies River Mouth“Size I Y 0.860 0.0001 Klein (1989)
= ’0.073X0.749
Klasies River Mouth“Size II Y 0.827 0.0001 Klein (1989)
= ’0.065X0.633
Klasies River Mouth“Size III Y 0.823 0.0001 Klein (1989)
= ’0.014X0.684
Klasies River Mouth“Size IV Y 0.748 0.0001 Klein (1989)
= ’0.017X0.582
Klasies River Mouth“Size V Y 0.779 0.0001 Klein (1989)
= ’0.102X0.877
El Castillo Cave“Mag & Sol Y 0.958 0.0001 Klein and Cruz-Uribe (1994)
= ’0.018X0.85
39FA82 Y 0.988 0.0001 White (1952)
= ’0.062X0.842
Bull Pasture bison Y 0.925 0.0001 White (1955)
= ’0.074X0.884
Bull Pasture wapiti Y 0.966 0.0001 White (1955)
= ’0.152X0.901
Buffalo Pasture Y 0.883 0.0001 White (1956)




CO N C L U S I O N


This chapter has concerned the MNE quantitative unit (and various units derived
from MNE) and properties it is thought to measure (e.g., skeletal-part abundances,
skeletal completeness, fragmentation). As Ringrose (1993:129) pointed out, MNE is a
quantitative unit “speci¬cally designed for the study of skeletal-part representation,
rather than taxonomic abundance.” This does not mean that MNE and MNI (or
NISP) are not mechanically or statistically related. MNI values are by de¬nition
(Table 2.4) based on the maximum MNE. Thus, White™s (Table 6.5) summed left
and right MNE values are strongly correlated with the MNI values for each of those
fourteen skeletal elements (Figure 6.21 ). This is because MNI per skeletal element
is merely the greater of the tally of left elements or the tally of right elements. MNI
quantitative paleozoology
262




(lefts + rights) and MNI per skeletal part. Diagonal
figure 6.21. Relationship between
shown for reference. Data from Table 6.5.


is a tally of redundant skeletal parts or portions, traditionally based on the greatest
MNE in a collection.
MNE seems, on the surface, to be a valuable quantitative unit. It may in fact be
valuable if it is clear that, say, femora are much more intensively and extensively
fragmented than are humeri. The quick way to determine this is to calculate the
relationship between NISP per skeletal part and the MNE per skeletal part. If the
two values are strongly correlated, there is little reason statistically to use MNE in
further analyses, such as determining if femora are more abundant than humeri;
NISP will provide the same ordinal scale information as MNE. MNE is a valuable
unit for measuring the intensity of fragmentation, de¬ned as the NISPi:MNEi ratio,
where i is a particular skeletal part. Based on analyses and arguments presented in this
chapter and elsewhere (Grayson and Frey 2004), MNE is not useful for measuring
skeletal-part frequencies. This is so because it is derived (de¬nition dependent), it is
in¬‚uenced by sample size (NISP), and it is in¬‚uenced by aggregation.
MNE has undergone a history similar to that of MNI. Both units were used to mea-
sure the value of a variable, then various potential problems with them were identi¬ed
skeletal completeness, skeletal parts, and fragmentation 263


and efforts were made to resolve those problems, for example, tallying units more
carefully and more consistently taking into account numerous factors (age/sex/size
differences; fragmentation differences and anatomical overlap). After various sorts
of potential additional steps to tallying specimens into MNI or MNE units were
identi¬ed and implemented, it was pointed out that perhaps the quantitative unit is
not salvageable despite various safeguards. The quantitative unit is not salvageable
because it is in fact a derived measure and it is at best ordinal scale; it is redundant
with NISP, a fundamental measure. As with MNI, it seems we have reached the point
with MNE where it may no longer be worth using it to the same degree that it once
was, particularly with respect to measuring skeletal-part frequencies.
There are other quantitative units similar to MNE. These include the minimum
number of butchering units (Lyman 1979; Schulz and Gust 1983), and the minimum
number of analytically speci¬ed anatomical regions (Stiner 1991, 2002). It is beyond
the scope of this discussion to explore the properties of these units, but it is logical to
suspect that they, too, will often be strongly correlated with NISP or sample size, and
heavily in¬‚uenced by aggregation and how they are de¬ned. This suspicion is based
on the fact that both the minimum number of butchering units and the minimum
number of anatomical regions are determined in the same manner as MNE and
MNI. The only difference is that the minimum number of butchering units and the
minimum number of anatomical regions are at skeletal scales of inclusiveness between
MNE and MNI as typically de¬ned. The most important thing to remember is that
MNE and similar units are often signi¬cantly in¬‚uenced by sample size, aggregation,
and de¬nition, just as is MNI. This simple fact suggests that NISP is to be preferred
over MNE and similar units, especially when MNE provides abundance information
that is redundant with NISP.
7
Tallying for Taphonomy: Weathering,
Burning, Corrosion, and Butchering

Taphonomy is a term coined by Russian paleontologist I. A. Efremov (1940) from
the Greek words taphos (burial) and nomos (law). Efremov meant for taphonomy to
specify the transition, in all details, of organics from the biosphere to the lithosphere.
In the context of this book (recall Figure 2.1 ), taphonomy concerns the agents and
process(es) that in¬‚uence an animal carcass from the moment of that animal™s death
until its remains (if any survive the vicissitudes of time) are recovered by the paleo-
zoologist, and also the kind and magnitude of those in¬‚uences. There are a plethora
of taphonomic agents and processes that variously disarticulate, disperse, alter, and
destroy carcass tissues, including bones and teeth (Lyman 1994c).
In this chapter, techniques for tallying what are sometimes referred to as tapho-
nomic signatures, features, or attributes evident on faunal remains are introduced.
Identifying the taphonomic agents and processes that in¬‚uenced an assemblage of
faunal remains assists interpretation of the remains. (If the agent is biological, then
the taphonomic feature is a trace fossil [Gautier 1993; Kowalewski 2002].) Do, for
example, those remains re¬‚ect what human hunters ate or do they represent a ¬‚u-
vially winnowed set of skeletons of animals that died during a seasonal crossing of
a river at ¬‚ood stage? Determination of the taphonomic history of a collection of
faunal remains may reveal aspects of paleoecology not otherwise evident among the
collection of remains, such as evidence of carnivore gnawing on ungulate bones when
no carnivore remains are recovered.
A taphonomic signature is a modi¬cation feature evident on a skeletal part that is
known (or believed) to have been created by only one process or agent (Blumenschine
et al. 1996; Fisher 1995; Gifford-Gonzalez 1991; Marean 1995). It is a signature because
it is unique to that agent or process. A taphonomic feature need not be a signature;
it is an artifact or epiphenomenon of an agent or process that modi¬ed a skeletal
specimen™s location, anatomical completeness, or appearance. Given the model of
an unmodi¬ed skeletal part as it would appear in a normal organism walking, ¬‚ying,
tallying for taphonomy 265


or swimming around the landscape, any perimortem or postmortem modi¬cation
to that skeletal part that was not created by physiological processes of the organ-
ism (e.g., a healed fracture [antemortem]) is a taphonomic feature. Instances of the
occurrence of that modi¬cation may be recorded during study of the remains because
by de¬nition such an attribute is not a normal feature of a bone or tooth. A modi-
¬cation feature need not have a speci¬cally identi¬able cause or creation agent, and
in fact many features do not, though that number is decreasing as our knowledge
of causal agents increases through actualistic research (e.g., Dom´nguez-Rodrigo
±
and Barba 2006; Kowalewski 2002). A taphonomic feature is created perimortem (at
death) or postmortem (after death). Tallying up, say, the frequency of specimens with
gnawing marks, or the frequency of gnawing marks, or both comprises tallying for
taphonomy.
Gnawing marks created by hungry carnivores, butchering marks created by hun-
gry hominids, burning damage created by fuel-hungry ¬‚ames, and various other
such taphonomic features can be tallied in various ways to decipher the taphonomic
history of a collection of animal remains. Intuitively, for instance, given two collec-
tions of bones that are otherwise quite similar (in terms of taxonomic abundances,
however measured, and in terms of frequencies of skeletal parts), the one with more
bones displaying carnivore gnawing damage is likely the one that underwent relatively
more carnivore-gnawing related attrition (consumption) of bone tissue. Tallying such
attributes may seem straightforward, but even if tallying is sometimes easy to do, it
is not always easy to understand or interpret the tallies. What a tally signi¬es may
well be obscure because a tally of taphonomic attributes (measured variable) may
have an unknown relationship to a particular taphonomic (target variable) agent
or process. How, for example, does the frequency of gnawed bones (measured vari-
able A) or the frequency of gnawing marks (measured variable B) relate to gnawing
intensity (target variable)? Many attributes are thus not signatures but are tallied in
hope that the quantitative data will reveal aspects of the taphonomic history of the
collection.
This chapter begins with some rather easily tallied taphonomic attributes that
many taphonomists and paleozoologists believe have well-understood relationships
to taphonomic agents and processes. The discussion progresses to complex attributes
for which little consensus exists as to how they should be tallied and/or what a tally
might mean with respect to a taphonomic agent or process. The goal of this chapter
is not to solve particular substantive problems, but rather to describe quantita-
tive units, illustrate how they are tallied, and exemplify how they might be ana-
lyzed. And given the topic of this chapter, another quantitative unit must ¬rst be
introduced.
quantitative paleozoology
266


YE T A N O T H E R Q U A N T I T A T IVE U N I T


There are two units not often mentioned in the quantitative paleozoology literature
that need to be identi¬ed. One unit previously mentioned in this book is the number
of specimens (NSP). NSP is the number of all specimens in an assemblage or collec-
tion (however de¬ned), including those that are identi¬able to taxon and those that
are not identi¬able. NSP is a fundamental measure just like NISP. NSP has been used
by name by several zooarchaeologists (e.g., Grayson 1991a; Stiner 2005). Another
unit, not previously identi¬ed in this book, used by fewer individuals is what Stiner
(2005:235) uniquely refers to as the number of unidenti¬ed specimens, or NUSP. For
any collection of faunal remains, NSP = NISP + NUSP, and NISP = NSP “ NUSP.
Why should NSP and NUSP be of concern? First, and less importantly, they need
to be mentioned because sometimes paleozoologists will refer to the ratio NISP/NSP.
The implication of the ratio is seldom stated explicitly, but it seems to be thought
that the higher the ratio (the greater the proportional value of NISP), the more
specimens were identi¬ed because they were not so badly preserved (corroded, frag-
mented) as to be unidenti¬able. The NISP/NSP ratio is thus thought to re¬‚ect general
aspects of the taphonomic history of a collection (e.g., fragmentation and destruc-
tion extent and intensity). Perhaps because the relationship of the NISP/NSP ratio
to preservational condition has never been empirically or critically examined, the
NISP/NSP ratio is seldom used analytically. Or, perhaps the ratio is seldom analyzed
because it could be a function of which skeletal parts are represented as some parts
are more easily identi¬ed than others. Whatever the case, if mentioned at all, the
ratio is often mentioned in a descriptive role. After all, it is simple to calculate and it
is based on two directly measured variables “ NISP and NSP “ that are readily deter-
mined. (NSP and NUSP are in¬‚uenced by fragmentation, though this is not generally
acknowledged.)
The second reason to mention NSP and NUSP is important and concerns the
fact that many of the features tallied for taphonomic purposes can be tallied for the
NISP of a collection, or for the NSP (= NISP + NUSP). Here taphonomic features are
discussed as if they are only tallied using NISP because that is the traditional manner in
which they are tallied. Distinguishing NISP and NUSP, and tallying the taphonomic
features using both, may be worth considering if, and this is important, there is
reason to believe that the taphonomic process or agent might be re¬‚ected differently
across identi¬ed specimens than it is across unidenti¬ed specimens. If there is no
reason to believe that this is the case, then if the sample of NISP is suf¬ciently large
(and we can ascertain that by sampling to redundancy [Chapter 4]), then tallying
taphonomic features across NISP will likely be suf¬cient to measure taphonomic
tallying for taphonomy 267


Table 7.1. Weathering stages as de¬ned by Behrensmeyer (1978)

Stage De¬nition
0 Greasy, no cracking or ¬‚aking, may have soft tissue attached.
1 Longitudinal cracking; articular surfaces with mosaic cracking; split lines
beginning to form.
2 Flaking of outer surface (exfoliation); cracks present; crack edges are angular.
3 Compact bone has rough, ¬brous texture; weathering penetrates 1 “1.5 mm;
cracked edges are rounded.
4 Coarsely ¬brous and rough surface; loose splinters present; weathering
penetrates to inner cavities; cracks are open.
5 Bone tissue very fragile and falling apart; large splinters present.


variables and the degree or extent of the in¬‚uence of the taphonomic processes and
agents of concern.


WE A T H E R I N G


In a classic paper, Behrensmeyer (1978) speci¬ed six stages through which a (mam-
mal) bone would pass during subaerial weathering (Table 7.1 ). She de¬ned weath-
ering as “the process by which the original microscopic organic and inorganic
components of bone are separated from each other and destroyed by physical and
chemical agents operating on the bone in situ, either on the [Earth™s] surface or within
[sediments]” (Behrensmeyer 1978:153). Weathering involves the natural decomposi-
tion and destruction of bone tissue, and Behrensmeyer recorded subaerial weather-
ing only “ weathering that occurs “on the [ground] surface.” To quantify weathering
damage, Behrensmeyer (1978:152) suggested that the analyst tally the number of bone
specimens that display each weathering stage. The weathering stage that a specimen
displays is, in turn, recorded as the maximum weathering stage evident on an area
comprising at least 1 cm2 of the surface of a specimen.
The maximum weathering displayed is used because the target variable of interest
concerns not how weathered (or unweathered) a specimen is, but rather the duration
of “surface exposure of a bone prior to burial and the time period over which bones
accumulated” (Behrensmeyer 1978:161). This means that the maximum weathering
stage evident is recorded rather than minimum or average weathering evident on a
specimen for two reasons. First, several variables mediate (slow) the rate of weathering
(Lyman and Fox 1989), thereby potentially weakening any statistical relationship
between weathering stage (the dependent variable) and the variable of analytical
quantitative paleozoology
268


Table 7.2. Weathering stage data for two collections of
mammal remains from Olduvai Gorge. Frequencies are
NISP (% of total NISP). Data from Potts (1986)

Stage FLK “Zinj” FLKNN L/2
0 771 (76) 105 (46)
1 147 (14) 59 (26)
2 63 (6) 24 (10)
3 36 (4) 39 (17)
4 0 (0) 2 (1)
5 1 (0) 1 (0)



interest (e.g., duration of exposure). The second reason that maximum weathering
is used is that there is a strong statistical relationship between date of death of the
animal contributing the maximally weathered bone and the maximum weathering
stage displayed by one or more bones of the carcass (Behrensmeyer 1978). The critical
interpretive issue, then, requires understanding the relationship between maximum
weathering stage displayed and the target variable of interest whether it be duration
of exposure, date of animal death, or something else.
Quantifying bone weathering is relatively straightforward. Count up how many
specimens in a collection display each of the six weathering stages. Then, present the
tallies in a table as absolute counts of specimens per weathering stage, as proportions
or percentages of specimens per weathering stage, or both. Data can also be presented
graphically. An example is provided by Potts™s (1986) data for assemblages of mammal
remains from Plio-Pleistocene archaeological sites in Olduvai Gorge, Tanzania. Data
for two assemblages are summarized in Table 7.2, and percentage frequency data for
the two assemblages are graphed in Figure 7.1 in what Lyman and Fox (1989:300) term
a weathering pro¬le, de¬ned as “the percentage frequencies of bone specimens in an
assemblage displaying each weathering stage.” Percentage frequency data eliminate
the effects of variation in sample size, thereby permitting differences between the
two assemblages plotted in the graph in Figure 7.1 to be interpreted in terms of
differences in weathering rather than in terms of difference in sample size. The fact
that one assemblage is nearly four and a half times larger than the other (Table 7.2)
is not apparent in Figure 7.1 .
Note that thus far the weathering data have been presented in tabular form
(Table 7.2) and in graphic form (Figure 7.1 ). How might those data be analyzed
further? χ 2 analysis indicates that specimens are not equally distributed within the
weathering stages across the two assemblages (χ 2 = 109.74, p < 0.0001). Analysis
tallying for taphonomy 269


Table 7.3. Expected frequencies (EXP) of specimens per weathering stage
(WS) in two collections (Zinj; L/2), adjusted residuals (AR), and
probability values (p) for each. Based on data in Table 7.2

WS Zinj EXP L/2 EXP Zinj AR L/2 AR Zinj p L/2 p
’8.95
0 714.6 161.4 9.09 <0.01 <0.01
’4.19
1 168.0 38.0 4.11 <0.01 <0.01
’2.31
2 71.0 16.0 2.30 <0.05 <0.05
’7.84
3 61.2 13.8 7.77 <0.01 <0.01
’2.90
4 1.6 0.4 2.95 <0.01 <0.01
’1.09
5 1.6 0.4 1.10 >0.1 >0.1



of adjusted residuals indicates that relative to the FLKNN L/2 assemblage, the FLK
“Zinj” assemblage contains more specimens displaying weathering stage 0 and fewer
displaying stages 1, 2, 3, and 4 than expected given random chance (Table 7.3). These
results identify the statistical signi¬cance of Figure 7.1 , but there is other variation
between the two weathering pro¬les that the χ 2 analysis does not capture. What
other kinds of analysis might be done?




figure 7.1. Weathering pro¬les for two collections of ungulate remains from Olduvai
Gorge. Data from Table 7.2.
quantitative paleozoology
270


A paleozoologist could also determine the richness of weathering stages in each,
and the evenness and heterogeneity of each as well. These values for FLK “Zinj” are 5
(richness), 0.489 (evenness), and 0.787 (heterogeneity); for FLKNN L/2 the values are
6, 0.730 and 1.309. The richness values do not tell us much by themselves. The evenness
value is greater for FLKNN L/2, indicating that it has a more even distribution of
specimens across the weathering stages than the FLK “Zinj” collection. Finally, the
heterogeneity index values conform with the combined richness and evenness values
for each and indicate that the FLKNN L/2 assemblage is more heterogeneous “ richer
and more even “ than the FLK “Zinj” assemblage. All of these values, and particularly
the evenness and heterogeneity index values, suggest that the FLKNN L/2 assemblage
is more weathered than the FLK “Zinj” assemblage, although the only way we know
this rather than it being the other way around is in light of Figure 7.1 .
Tallying so far has been straightforward. But if one were to interpret the data
in Tables 7.2 and 7.3 and the graph in Figure 7.1 as re¬‚ecting differences in bone
accumulation duration, as Potts (1986) did and Behrensmeyer (1978) hoped to do “
the basic presumption being that an assemblage with a more left-skewed weathering
pro¬le (tail to the left, maximum frequency to the right) took longer to accumulate
than an assemblage with a right skewed pro¬le (tail to the right, maximum frequency
to the left) “ a number of assumptions would have to be made. Behrensmeyer (1978)
perceived a positive relationship between how long a carcass had been lying on the
landscape (years since death) and the greatest weathering stage displayed by any one
of the bones of the carcass. The correlation between the two variables is indeed strong
and signi¬cant, as implied by Figure 7.2 (r = 0.872, p < 0.0001). Based on actualistic
research by numerous others, Lyman and Fox (1989) noted that there were a number
of variables that could reduce the correlation coef¬cient to considerably less than 1.0.
Few individuals subsequently presented, let alone interpreted, bone weathering data
as Potts (1986) had done. Rather, weathering data came to be used to gain insight
into other aspects of the taphonomic history of a bone assemblage.
Given Behrensmeyer™s (1978:153) observation that “bones are usually weathered
more on the upper (exposed) than the lower (ground contact) surfaces,” analysts
now examine which surface is more weathered and which is less weathered. Skyward
or upper surfaces should be more weathered than groundward or lower surfaces
because the upward surface is more directly exposed to sunlight, precipitation, and
other climatically related weathering agents. If the reverse is observed, if the ground-
ward surface is more weathered than the upper surface, then it is likely there has
been some postdepositional and perhaps postburial disturbance. If there are many
bones, then one could construct a weathering pro¬le like that in Figure 7.1 , but with
a distinction between the weathering stage displayed by the skyward surfaces and the

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