Second draft of Favorite Work: kingsley cave resource intensity
1. Grunder 0
Resource Intensification and Processing Intensity through
Time at Kingsley Cave, California
Uri A. Grunder
Department of Anthropology
Humboldt State University
April 1, 2013
Running Title: Resource Intensification: an experimental study of Kingsley Cave, California
2. Grunder 1
Abstract
This article explores food resource selection and processing intensification at the
prehistoric Kingsley Cave Site (CA-THE-01) within the Yana territory of Northern California.
The site is situated within the steep dominantly chaparral environment of Tehama county within
a rock shelter. Original evidence was provided by Baumhoff and supports occupation of the
Kingsley Cave site beginning approximately 4,000 year B.P. I hypothesize that post-contact
Yana groups were confined to smaller resource patches than their predecessors which abruptly
increased the diversity of faunal resources exploited by the occupants as well as a spike in faunal
resource processing intensity. Research was conducted through three methods. The first was an
analysis of the dominant taxon present within each level of one unit. The second was an analysis
of all fragments by dividing all fragments into arbitrary size classes (in centimeters) and
providing a score per fragment that signifies the extent to which it may have been utilized for
bone marrow or grease extraction (which is thought to correlate to processing intensity; Collins
2010 & Nagaoka 2005). The third method was conducted by taking the average weight value of
bone fragments per level with the intent of comparing mass by level. Trends in identifiable
faunal remains decreased through time however dominant resource selection remained constant
and did not appear to broaden. Rates of marrow and grease exploitation seemed to increase
through time however not in the abruptness displayed by the previous methods and bone size
classes ruled out the utilization of labor intensive grease extraction. Weight trends of
fragmentary bone supported similar conclusions as the second method. All of these methods
resulted in evidence supporting an increase in processing intensity of food resources through
time however rates of change suspiciously vary.
3. Grunder 2
Introduction
The introduction of Euro-American groups in this area and many others across North
America brought radical alterations and often violent cultural intolerance for Native groups. The
historical pattern of cultural interaction tended to follow Euro-American encroachment, the
disempowerment of indigenous people of their occupied territories, and the Euro-American
violent dismissal of indigenous cultural groups. These indigenous groups responded in a variety
of creative ways to survive these radical and often genocidal pressures. The area near Kingsley
Cave is a shallow cave shelter located within the tribal territory of the Yana, specifically a
subgroup called the Yahi who are thought to be composed of semi-sedentary hunter-gatherer
groups, near Red Bluff in Tehama County, California. The site has been found to have been
occupied for approximately 4,000 years prior to Euro-American contact. After which, territory
development and expansion beginning in the 1850’s led to a sharp decrease in the territorial
space and population size of the Yana people (Baumhoff 1957). A particular incident occurred
after several skirmishes between the Yana people and Euro-American settlers. A group of Euro-
American community members banded together in 1864 and massacred major Yana villages.
This series of massacres was thought to be so intense this ten years later it was thought to have
wiped out the entire cultural group and it’s subgroups. Contrary to belief however, the massacre
scattered the Yana into small pockets of survivors which continued to live over the next 60 years
hiding in sparse distributions amongst the rugged terrain of Tehama County (Baumhoff 1957).
While the history of Kingsley Cave is dark and violent it may provide an observable
example of longitudinal habitation and the effects of cultural intolerance leading to radical
changes in foraging behavior. With the site thought to be inhabited for 4,000 years B.P. in a
geographical location that remains stable enough to uncover faunal materials, I propose that this
4. Grunder 3
is a unique opportunity to examine the nature of foraging dynamics in this area over time from
initial habitation to after the encroachment of Euro-American cultural groups (Baumhoff 1957).
Martin Baumhoff excavated at the Kingsley Cave site in 1953, a time where collection of faunal
remains and soil screening were not looked upon as necessary or significant. I propose to analyze
the Kingsley Cave data set provided by Baumhoff to explore changes in food selection and
intensification over time using three main methods. The first is to examine taxonomic evidence
for alterations in prey selection through the analysis of taxonomic composition. Statistical
analysis of overall depth of identification may prove useful to exposing trends about resource
selection and processing intensification through time as a decline in accessible resource patches
may increase resource element utilization and fragmentation (Lyman 1992; Nagaoka 2005). A
gauge of bone fragmentation will correlate with the second methodology as processing intensity
is explored and projected in this context. I assume that confined native groups processed
acquired resources more intensely when stressed from outside cultural pressure. Using methods
derived from Collins (2010) the remains will be classified by degree of fragmentation and then
statistically analyzed to project the degree of bone processing intensity by layer. The third
method involves weighing each fragmented specimen in grams and calculating and comparing
the relative abundance of fragment weight per level of unit D5 (the most stratigraphically
complete until of the excavation).
This work retains elements compiled by Nagaoka’s work with New Zealand populations
depressing Moa food resources which in turn decreased foraging efficiency and intensified
resource utilization will be assumed. Nagaoka suggested that as foraging efficiency decreased
(encounter rates lowered or distance traveled to obtain – in this case - Moa resources increased)
bone intensification increased (Yesner 1981). The expected effects were that a greater amount of
5. Grunder 4
time was spent processing bone for marrow and, if stresses continued, grease (a more labor
intensive method of nutrient extraction that often provided low caloric returns). In order to obtain
these resources, significant damage to the bones themselves must be done. In this project a
comparison will be drawn between the depth of identification of individual faunal elements
through time with an expectation that if older strata had a lower resource processing intensity
identification could frequently be made to lower taxonomic levels (the lowest being the species
level). Whereas in newer post-contact strata if resource processing demands intensified the
remains are expected to be greatly fragmentary/damaged and only broadly identifiable – to the
class or order level (Lyman 1992 & Nagaoka 2005). In other words increased processing
intensity should be reflected in the levels of taxonomic identifiability.
Other major contribution are by Collins who developed a bone fragmentation test that
was thought to numerically express the degree of processing intensity observed within any
individual or compilation of faunal remains. Though the actual parameters of the test is relatively
difficult to understand efforts will be made to adapt Collin’s methods to this project.
Through these major theoretical contributors to Optimal Foraging Thoery I hope to glean
longitudinal information about the resource selection and processing patterns of the occupants of
the Kingsley Cave site. While a pattern will hopefully be uncovered throughout the 4,000 years
of occupancy, the primary goal is to understand changes during the cultural overlap between the
indigenous groups responding to expanding Euro-American pressures.
6. Grunder 5
Materials and Methods
As stated above, the sample I will be analyzing is one unit excavated by Baumhoff. This
sample was provided to me by the Eagle Lake Field School and in particular Chico State
University. Unit D5 is selected because it retains the most stratigraphic integrity of all the
available units. It has a nearly complete stratigraphic consistency from 0 – 60 inches below
ground with only the 6-12 inch bag of archaeofaunal data missing. The unit was dug at arbitrary
levels of six inches and all extracted faunal material was bagged in small plastic bags and labeled
with sharpie marker. Unfortunately the sediment that were moved during Baumhoff’s excavation
was not screened.
The faunal data itself is composed of approximately 519 fragmented faunal remains that
retained various amounts of fragmentary damage. The majority of these remains were
overwhelmingly medium artiodactyl and more specifically, for those fragments that could be
identified to the species level, Odocoileus hemionus (Mule deer). This data was analyzed with
the following hypotheses in question. The reduction in available resource range patches forced
the Yahi to select lower return resources as the higher return resources within their immediate
area became exhausted over time and that higher resource return fauna obtained would be more
intensely processed for nutrients (i.e. marrow and grease extraction) (Nagaoka 2005).
The first method I employed was to identify all the bones in the assemblage as
specifically as possible. If a reduction in resource range had occurred than it would be expected
that a higher prominence of lower caloric return resources would be more abundantly present in
the recent archaeofaunal strata than in older strata. I would also expect to find a greater degree of
fragmentary damage to the bones within the more recent strata than in older strata. This would in
7. Grunder 6
turn affect the degree of identification I would be able to provide per specimen which may also
reflect a trend of increasing need to further intensively process food resources for marrow and
grease. To receive accurate determination of identification a comparative faunal collection
provided to the students of Eagle Lake Field School by Chico State University will be used and
cross referenced with literature relevant to faunal identification (Lyman 1992 & Lawrence 1951).
The second method I employed was suggested by Outram (2001) and Collins (2010) and
is designed to distinguish bone fragmented to harvest marrow and grease. The idea behind this
method is that bone and grease extraction from bones was done while the bones were still
relatively fresh and so resulted in particular looking green breaks. It is suggested that the criteria
used here will distinguish bone affected by human actions to obtain marrow and grease from
other post-depositional processes. All fragmentary bones were taken and, indiscriminant of
taxon, were divided into size classes ranging in increments of 10 millimeters. They were also
given a score of 0-2 based on three criteria (totaling to 6 possible awarded points): fracture angle,
surface texture, and fracture outline. As Collins describes the criterion more specifically:
“…for fracture outline, a score of 0 means that there were only helical (or spiral) breaks, a
score of 1 denotes a mixture of fracture outlines and a score of 2 means an absence of helical
outlines. For fracture angle, a score of 0 is assigned if no more than 10% of the fracture surface
was perpendicular to the cortical surface, a score of 1 is assigned of between 10-50% was
perpendicular to the cortical surface, and a score of 2 is assigned of the right angles encompass
more than half of the fracture surface. For fracture surface texture, a score of 0 is assigned if the
surface is completely smooth, a score of 1 is assigned id the surface has some roughness, but the
texture is mostly smooth and a score of 2 is assigned if the fragment has mostly rough edges on
the fracture surface.” (Collins 2010)
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In summary lower scores are indicative of higher rates of marrow or grease harvesting in
fragmented bone. I used the Collins and Outram’s criteria for the Kingsley Cave Site because if
resource intensification did occur and bone marrow and grease were being exploited for
nutritional return than it would be expected that the archaeofaunal remains would be
dramatically impacted. This should reflect a greater degree of fragmentation in the more recent
strata and a lesser degree of fragmentation in older strata. Size classes, denoted by bone length,
will be indicative of marrow and grease extraction. Long fragments tend to be associated with
marrow extraction whereas the more intensive grease extraction is associated with very small
fragments (Collins 2010)
All bone fragments will be weighted during size classification. This will yield
information on the changes in abundance of bone fragments within unit D5 through time. It is
expected that bone weight will increase through time as resource intensification increases. All
together these methods should help define the changes in patterns of resource selection and
intensification of the Yahi people as Euro-American contact impacted their lifestyle.
9. Grunder 8
Results
The number of identified specimen by level is for the Kingsley Cave assemblage is
provided in table 1 and appendix 1. It shows the number of identified Mule deer elements, the
dominantly exploited faunal resource, drastically change through time. It appears as though there
was an abrupt decline in Stratum 8 (48-54 inches below ground) that dropped approximately
50% (Table 1 & Figure 1). The decline continues until stratum 4 (24-30 inches below ground)
where a small incline is observed until stratum 1 (0-6 inches below ground) where a sudden drop
is observed. However, this is not reflective of a decrease in Mule deer encounter rates or in
declining use. As figure 2 points out, comparing elements identified to Mule deer and those
identified to the broader Medium Artiodactyl, as average Mule deer identifications decrease
Medium Artiodactyl identifications increase. This may be indicative of increasing resource
processing intensity as bones are damaged further and further into ambiguity.
The second approach involved categorizing each bone fragment into sizes by length in
increments of 10 millimeters and giving each fragment a score based on the methodologies of
Outram and Collins described above. A scatter graph of the average score values per level was
plotted (refer to Figure 3) which revealed a very subtle increase in the number of bone fragments
likely used for marrow and grease extraction. This graph compared positively to the average
weight of bone fragments per level (Figure 4) conducted during the third phase of this project. A
comparison showed that there was an increase in bone weight in concurrence with an increase in
bone fragmentation likely associated with marrow/grease extraction (see Figure 4).
10. Grunder 9
After dividing the assemblage into arbitrary size classes of 10 millimeter increments
results showed that nearly all 9 levels within unit D5 retained the same dominant fragment size
class between 30 and 40 millimeters (see table 4) on average.
11. Grunder 10
Discussion
I have demonstrated that this analysis may have results that suggest a general rise in
faunal processing intensity through time. However it seems as though foraging efficiency did not
decline to the point of smaller and less caloric return faunal resources were sought out. The first
method of identifiable of faunal remains and calculating a percentage against the entire
assemblage was a great success. Plotting the results on a scatter graph revealed that older strata
retained higher species level identifiable bone fragments than did more recent strata. The graph
itself even revealed an abrupt drop of approximately 50% over the course of stratum 8 to stratum
7. Further revealed in figure 2 there is a direct relationship between Medium Artiodactyl and
Mule deer identified specimen. As the presence of Mule deer identification declines there is an
increase in the presence of Medium Artiodactyl identifications. This is not a reflection of lower
resource encounter rates but a reflection of an increase of resource bone intensification. Similar
to Nagaoka’s work mentioned in the introduction, the increases in resource processing intensity
result in increased damage to the bone which results in an identification of individual bone
specimen to drop to broader and more general taxonomic levels.
There were very few other represented fauna aside from Mule deer and no other tacon
came close to assemblage domination as Mule deer which suggests that groups of this area are
either not needing to or choosing not to exploit lower return fauna to sustain them. This may
suggest that over all encounter rates may not have changed dramatically through time and high
return rate resources remain the dominant represented fauna throughout this unit and others
(Baumhoff 1957). This scenario may be answered by the sharp decrease in the human population
exploiting these resources. If the Kingsley Cave site had an abrupt decrease in the human
population exploiting Mule deer resources and Euro-American populations hesitated to enter the
12. Grunder 11
rough and brushy territory of Tehema County then an increase in the resource population should
be observed and little overall change might occur in resource intensification by the remaining
indigenous population in hiding.
The second method of graphing the scores of bone utilization and average weights within
stratum were a little unexpected but supportive none the less. Although both the bone use graph
and the graphs of faunal identification are consistent with my hypothesis, the rate of change
seems rather inconsistent. The graphs of both Bone utilization and Average Weight per Level
show that as bone weight and processing intensity increase equally through time. With regards to
the marrow and grease extraction of fragmented bone score I question the validity of Outram’s
and Collin’s methodology. The criteria set in both of these authors reports seem a little too vague
for reproduction by other analysts and an substantial error margin seems may be prominent.
Dividing all bone fragments into size classes was very beneficial in understanding
whether bone marrow and/or grease extraction was being utilized. Analysis showed that almost
all 9 levels retained the same dominant size class of fragmentary bone, between 30-40mm. This
is indicative of bone marrow extraction which leaves behind fairly long fragments and is
relatively low in labor processing effort for caloric gain. Grease extraction on the other hand,
which is far more labor intensive would be indicated by smaller fragments than what was
observed suggesting that grease extraction was not generally utilized within this assemblage
(Collins 2010).
However, there are some critiques that I have for the hypothesis. My argument was
founded upon the idea that a reduction in resource patch range would directly influence
processing intensity and while the results did show a trend of increased bone processing
13. Grunder 12
intensity, it was not in at the scale I expected. A substantial problem regards the sense of time to
go with each level. Although there is the law of Superposition claims that the most recent
material is going to be nearest the top and the oldest nearest the bottom there are no radiocarbon
dates associated with any of the remains in unit D5. The decline in species identifiable bone
fragments at stratum 8 may correlate with the massacre of 1864 or it may be indicative of a much
earlier change; maybe an environmental shift that caused a need for resource intensification. In
such a case it may be the sharp drop observed at stratum 2 where Euro-American contact impacts
affected the Yahi people. My last critique concerns the rate of organic decomposition. If rate of
decomposition are high then smaller faunal remains may not have survived thus skewing an
accurate representation of foraging behavior. On that note remains determined to be significant
by the excavators may have leaned towards the collection of some faunal remains over others.
Overall this project remained insightful to a deeper understanding of the resource
processing intensification of the occupants of the Kingsley Cave site. With a few radio carbon
dates on the specimen within unit D5 a temporal framework could be matched with the strata and
an even greater understanding be experienced. This project provided evidence supporting a
hypothesis a sharp increase in resource processing intensity occurred though time. A greater
amount of individual high caloric return resources, Mule deer, were harvested for nutrients
leaving behind an increased amount of bone fragments that were not species identifiable as well
as an increased net weight of fragmentary bone and evidence for an increase in bone marrow
extraction.
14. Grunder 13
Acknowledgments
I would like to take this opportunity to express my thanks to all those who have helped
me along through this project. Thank you to Chico State University for providing me with the
sample that made all of my analysis possible and for providing a faunal comparative collection.
To Frank Bayham for pushing me to go above and beyond the small scope of work I had
reserved for myself. To Jordan Meyers for getting his work done so quickly and vigilantly. He
has been a power house to my study. To all the people around me who have jumped in to help
me with excel graphs. To all the lovely ladies wielding Mac computers who have put up with me
time after time to print and re-print rough drafts. Thank you to John and Tracy for providing us
the opportunities to study at the Eagle Lake Field School and cooking some of the best food I
have ever eaten three times a day every day! Thank you to Karuja, Loretta, and Janet for the
intellectual support to push through this project. Thank you to Nikki who has been the source of
my energy and encouragement to give my all into this class and who has been a second editor to
all of my work. And last but not least, a very special thanks to Professor Jack Broughton who
was instrumental in not only shaping my project but also aiding me in the full development of
this paper and all its results. Without him this project would have withered away.
15. Grunder 14
References
Baumhoff, M. A. (1957). An introduction to Yana archaeology. University of California
Archaeological Survey Report Number 40, 1-71.
Burger, O. et al (2005). The prey as patch model: optimal handling of resources with
diminishing returns. Journal of Archaeological Science, 32: 1147-1158.
Collins, G.E. (2010). Bone fragmentation as an indicator of subsistence stress in the north
coast ranges of California. Clairfornia State University, Chico.
Lawrence, B. (1951). Part II: post-cranial skeletal characters of deer, pronghorn, and
sheep-goat with notes on bos and bison. Papers of the Peabody Museum of American
Archaeology and Ethnology, Harvard University Report Number 4, Peabody Museum
press, Cambridge.
Lyman, R.L. (1992). Taxonomic identification of zooarchaeological remains. Journal of
Archaeological Science, 28: 377-386
Nagaoka, L. (2005). Declining foraging efficiency and moa carcass exploitation in
southern New Zealand. Journal of Archaeological Science, 32: 1328-1338
Outram, A. K. (2001). A new approach to identifying bone marrow and grease
exploitation: why the “indeterminate” fragments should not be ignored. Journal of
Archaeological Science, 28: 401-410.
Yesner, D.R. (1981). Archaeological applications of optimal foraging theory: harvest
strategies of Aleut hunter-gatherers.
16. Grunder 15
Figure Captions
Figure 1. NISP values for Odocoileus hemionus as a percent within the entire assemblage.
Figure 2. Percentage of Identification for Mule deer and Medium Artiodactyl fragments through
time.
Figure 3. The results of Outram’s and Collin’s methodology for measuring bone marrow and
grease extraction within bone fragments per level.
Figure 4. Average weight of bone fragments per level expressed in grams.
17. Grunder 16
0.20%
Identified Specimen to entire assemblege
0.15%
0.10%
0.05%
0.00%
0 1 2 3 4 5 6 7 8 9 10
Depth (Levels)
Figure 1. NISP values for Odocoileus hemionus as a percent within the entire assemblage.
18. Grunder 17
1.00%
NISP for Odocoileus
0.80% hemionus as a
Percentage of Identification
percentage per Level
0.60% Med Artiodactyl
0.40%
Linear (NISP for
0.20% Odocoileus hemionus
as a percentage per
Level)
0.00% Linear (Med
0 1 2 3 4 5 6 7 8 9 10 Artiodactyl)
-0.20%
Depth (Level)
Figure 2. Percentage of Identification for Mule deer and Medium Artiodactyl fragments through
time.
19. Grunder 18
Inverse Bone Utilization Score:
3
2.5
Bone Utilization
2
1.5
1
0.5
0
0 2 4 6 8 10
Depth (Level)
Figure 3. The results of Outram’s and Collin’s methodology for measuring bone marrow and
grease extraction within bone fragments per level.
20. Grunder 19
Average Weight per Level
3.50
Weight in Grams (Average)
3.00
2.50
2.00
1.50
Average Weight per Level
1.00
0.50
0.00
0 2 4 6 8 10
Depth (Level)
Figure 4. Average weight of bone fragments per level expressed in grams.
22. Grunder 21
Table 2. NISP for Odocoileus hemionus (Mule deer) as a percentage against the entire
assemblage per level.
Level (Inches) NISP for Odocoileus hemionus as a percentage per Level
0-6 0.01%
12-18 0.04%
18-24 0.03%
24-30 0.02%
30-36 0.04%
36-42 0.05%
42-48 0.08%
48-54 0.19%
54-60 0.20%
23. Grunder 22
Table 3. Average Bone Utilization Scores per Level
Level (Inches) Average Bone Utilization Score per Level
0-6 2.54
12-18 1.36
18-24 2.54
24-30 2.02
30-36 2.19
36-42 1.66
42-48 2.24
48-54 2.85
54-60 2.42
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Table 4. Average Dominant Bone Size Class Per level
Level Average Dominant Bone Size per Level
0-6 40-50
12-18 30-40
18-24 30-40
24-30 30-40
30-36 30-40
36-42 40-50
42-48 30-40
48-54 30-40
54-60 30-40
25. Grunder 24
Table 5. Average weight of bone fragments per level
Level (Inches) Average Weight per Level (grams)
0-6 3.05
12-18 2.98
18-24 2.11
24-30 2.64
30-36 3.00
36-42 2.23
42-48 3.16
48-54 2.51
54-60 2.52
26. Grunder 25
Appendix A. Raw Data describing NISP values for all Fauna per level.
Kingsley Cave Project 1-133431 Unit: D5 0-6 inches
Depth of Identification NISP Calcined Charred Butchering Marks Weight (in grams)
Odocoileus hemionus 11 0 1 2 84
Cervus Elaphus 1 0 0 0 7
Medium Artiodactyl 18 0 1 3 102.5
Unidentifiable Fragments 96 3 1 1 84
Sum 126 3 3 6 277.5
Kingsley Cave Project 1-133433 Unit: D5 12-18 inches
Depth of Identification NISP Calcined Charred Butchering Marks Weight (in grams)
Odocoileus hemionus 1 0 0 1 15
Medium Artiodactyl 2 0 0 0 12.5
Unidentifiable Fragments 19 0 0 0 38
Sum 22 0 0 1 65.5
30. Grunder 29
Kingsley Cave Project 1-133440 Unit: D5 54-60 inches
Depth of Identification NISP Calcined Charred Butchering Marks Weight (in grams)
Odocoileus hemionus 4 0 0 0 18
Medium Artiodactyl 2 0 0 1 5
Unidentifiable Fragments 14 0 0 1 25.5
Sum 20 0 0 2 48.5
31. Grunder 30
Appendix B. Raw average data for the second method of the project.
0-6 “ Depth
Size Class (mm) Average Total Value Frequency of Size Abundance Average Weight Count (grams)
0-10 6.00 1 3.05
10-20 4.20 15
20-30 3.48 21 Average Total Score by Level:
30-40 2.59 17 2.54
40-50 2.52 25
50-60 1.80 15 Dominant Bone Fragment Size (mm)
60-70 2.00 8 40-50
70-80 2.00 9
80-90 1.00 4
90-100 2.50 2
100-110 4.00 1
140-150 1.00 1
160-170 0.00 1
32. Grunder 31
12-18” Depth
Size Class(mm) Average Total Value Frequency of Size Abundance Average Weight Count (grams)
10-20 2.00 1 2.98
20-30 2.00 2
30-40 2.13 8 Average Total Score by Level:
40-50 1.00 2 1.36
50-60 0.50 2
Dominant Bone Fragment Size
60-70 1.75 4 (mm)
70-80 1.50 2 30-40
80-90 0.00 1
18-24” Depth
Size Class (mm) Average Total Value Frequency of Size Abundance Average Weight Count (grams)
10-20 4.00 7 2.11
20-30 3.10 10
30-40 1.83 24 Average Total Score by Level:
40-50 2.50 12 2.54
50-60 1.53 17
60-70 1.33 9 Dominant Bone Fragment Size (mm)
70-80 1.00 1 30-40
80-90 5.00 1
33. Grunder 32
24-30” Depth
Size Class (mm) Average Total Value Frequency of Size Abundance Average Weight Count (grams)
0-10 5.25 4 2.64
10-20 2.89 9
20-30 2.33 18 Average Total Score by Level:
30-40 2.50 28 2.02
40-50 1.44 16
50-60 1.50 16 Dominant Bone Fragment Size (mm)
60-70 2.17 6 30-40
70-80 0.00 2
80-90 1.50 4
90-100 2.67 3
130-140 0.00 1
30-36” Depth
Size class (mm) Average Total Value Frequency of Size Abundance Average Weight Count (grams)
10-20 2.00 5 3.00
20-30 2.00 8
30-40 2.88 8 Average Total Score by Level:
40-50 2.20 5 2.19
50-60 1.50 8
60-70 1.29 7 Dominant Bone Fragment Size (mm)
70-80 0.00 1 30-40
80-90 0.00 1
90-100 4.00 1
130-140 6.00 1
34. Grunder 33
36-42” Depth
Size Class (mm) Average Total Score Frequency of Size Abundance Average Weight Count (grams)
10-20 0.00 1 2.23
20-30 3.00 4
30-40 1.75 8 Average Total Score by Level:
40-50 2.30 10 1.66
50-60 2.40 5
60-70 0.50 2 Dominant Bone Fragment Size (mm)
40-50
42-48” Depth
Size class (mm) Average Total Score Frequency of Size Abundance Average Weight Count (grams)
10-20 6.00 3 3.16
20-30 1.50 2
30-40 1.92 12 Average Total Score by Level:
40-50 1.33 6 2.24
50-60 1.40 5
60-70 3.00 4 Dominant Bone Fragment Size (mm)
90-100 0.50 2 30-40
35. Grunder 34
48-54” Depth
Size Class (mm) Average Total Score Frequency of Size Abundance Average Weight Count (grams)
10-20 5.00 4 2.51
20-30 3.50 6
30-40 2.44 9 Average Total Score by Level:
40-50 2.25 4 2.85
50-60 1.75 4
70-80 0.00 1 Dominant Bone Fragment Size (mm)
90-100 5.00 1 30-40
54-60” Depth
Size class (mm) Average Total Score Frequency of Size Abundance Average Weight Count (grams)
20-30 4.00 3 2.52
30-40 3.00 7
40-50 2.50 4 Average Total Score by Level:
50-60 2.00 2 2.42
60-70 2.00 3
80-90 1.00 1 Dominant Bone Fragment Size (mm)
30-40
