CHANGES IN PREHISTORIC SETTLEMENT PATTERNS AS A RESULT OF
SHIFTS IN SUBSISTENCE PRACTICES IN EASTERN KENTUCKY
DISSERTATION
Presented in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy in the Graduate
School of the Ohio State University
By
Andrew M. Mickelson, M.A.
*****
The Ohio State University
2002
Dissertation Committee:
Dr. William S. Dancey, Advisor
Approved by
Dr. Kristen J. Gremillion
Dr. Paul J. Sciulli
________________________
Advisor
Department of Anthropology
Copyright by
Andrew M. Mickelson
2002
ABSTRACT
This study examines the role of prehistoric subsistence change and its impact upon
settlement systems in Eastern Kentucky. Eastern Kentucky’s rockshelters are well-known
for their preservation of normally perishable organic plant remains. Archaeobotanical remains
from rockshelter contexts have played a key role in the establishment of the region as an
independent center of agricultural origins. By 4,000 to 3,000 years before the present (B.P.),
prehistoric populations along the western edge of the Appalachian Mountains were engaged
in the cultivation of weedy plants such as goosefoot, maygrass, sunflower, and squashes. The
incorporation of domesticated plants into the diet has not received detailed examination in
terms of its impact upon prehistoric settlement systems. This study acquired regional scale
data to evaluate whether or not such an impact can be discerned. The results document that
changes in the subsistence base did affect settlement configurations. Increased diet breadth
throughout the Late Archaic period in upland contexts resulted in a reorientation of the
settlement pattern in order to better fulfill subsistence requirements. In the case of the more
rugged upland portion of the study area, prehistoric populations took advantage of mid-slope
rockshelters to locate residential bases. Location of residences within rockshelters afforded
foragers an even access to a heterogeneous environment. By gaining access to all available
ecological strata, foragers were able to sustain a broad spectrum subsistence pattern in areas
ii
where richer floodplain settings were lacking. With the incorporation of cultigens into the
subsistence base during the Early Woodland period, the use of rockshelters continued to be
an energetically efficient settlement strategy. With the appearance maize by the end of the
Late Woodland period, utilization of rockshelter settings as residences was no longer tenable.
The advent of a field agricultural subsistence strategy based upon maize by the Late
Prehistoric period marked the end of rockshelters used as permanent or semi-permanent
residences.
.
iii
Dedicated to the Mickelson and the Robinson Families
iv
ACKNOWLEDGMENTS
I would like to thank my advisor, Dr. William S. Dancey, for his guidance on
methodological and conceptual issues encountered on the way to completion of this study.
His assistance in keeping me on track, and his patience with this research project are greatly
appreciated. I would also like to thank him for my initial introduction to Ohio Valley
archaeology.
I would like to acknowledge Dr. Gremillion for initiating me to the archaeology of
the Cumberland Escarpment and for fieldwork opportunities in the region. I would also like
to thank her for insight on the underpinnings of optimal foraging theory. I would like to
thank Dr. Sciulli for his comments on this research project as well as for providing assistance
with statistical issues. Dr. Marble of the Department of Geography at OSU provided
theoretical insight into developing GIS models of human walking.
I would like to thank Cecil Ison, Johnny Faulkner, and Don Fig of the USDA Forest
Service for sharing their knowledge of the culture history of the region. I would also like to
thank Cecil Ison for his support in obtaining funding for me to investigate the Gladie Creek
site. Dr. Sissel Schroeder, then of the Kentucky Office of State Archaeology, provided me
with a copy of the archaeology GIS dataset. GIS data support was enthusiastically
v
provided by Dan Carey of the Kentucky Division of Water, and Kevin Wente and Warren H.
Anderson, both of the Kentucky Geological Survey. Rick Thomas provided access to a fast
computer at a critical time, which facilitated a portion of this analysis.
I am indebted to members of the Licking County Archaeology and Landmarks Society
for initiating me to the excitement of archaeological fieldwork. In particular I would like to
thank Paul Hooge. I would also like to thank Dr. Paul Pacheco and Dr. Dee Anne Wymer
for allowing me to participate in the fieldwork enterprise with them.
I would also like to acknowledge the generous support and hospitality granted to me
by residents of the North Fork of the Red River. I am forever indebted to Tee and Lois
Skidmore for granting me access to conduct research on their property, for giving me lodging,
for friendship, and for warm conversations on cold fall nights. Dwaine Anderson also
provided access to conduct fieldwork and supplied knowledge of the area. Shirley Crabtree
cheerfully shared his knowledge of the archaeology of the region with me.
Finally, I would like to thank my wife for sharing in fieldwork and the dissertation
enterprises; she made them bearable, possible, and a source of unmitigated pleasure.
vi
VITA
1990. . . . . . . . . . . . . . . . . . . . . . . . . . . . B.A. Anthropology, Beloit College
1991-1992 . . . . . . . . . . . . . . . . . . . . . . . Contract Research Management Archaeologist
1992-1994 . . . . . . . . . . . . . . . . . . . . . . . Archaeologist, West Virginia Department
of Highways
1994 . . . . . . . . . . . . . . . . . . . . . . . . . . . . M.A. Anthropology, The Ohio State University
1994-2000 . . . . . . . . . . . . . . . . . . . . . . . .Graduate Teaching and Research Associate,
The Ohio State University
PUBLICATIONS
1.
A. Mickelson, “Mitigation of the Upper Portions of the Gladie Creek Site
(15MF410), Red River Gorge Geological Area, Daniel Boone National Forest, Stanton
Ranger District, Menifee County, Kentucky.” Report Submitted to the USDA, Forest
Service, Winchester, Kentucky (2002).
2.
A. Mickelson, “The Salt Wall: A Probable Woodland Period Earthwork in
Granville Township, Licking County, Ohio.” Ohio Archaeological Council Newsletter
13:1, 19-20 (2001).
3.
A. Mickelson, “Recent Excavations at the Spring Creek Site. Greenbrier County,
West Virginia.” West Virginia Archeologist (1999).
4.
A. Mickelson, K. R. Mickelson, M. E. Mickelson, G. Crothers, C. Swedlund and
R. Ward. “An Archaeological and Historical Review of Nitre Mining at Mammoth Cave,
Kentucky.” In Proceedings of the 1997 Mammoth Cave National Park Science
Conference, Mammoth Cave (1997).
vii
5.
A. Mickelson, “Phase I and Phase II Report on the Columbia Gas KA Line in
Wyoming County West Virginia.” Gray and Pape Cultural Resources Consultants.
Richmond, Virginia (1995).
6.
A. Mickelson, “Phase I Cultural Resource Assessment of the Proposed Corridor
L (US Route 19) Four- Lane Upgrade: Hico to Mt. Nebo, Fayette and Nicholas Counties,
West Virginia.” West Virginia Division of Highways, Charleston (1992).
7.
A. Mickelson, “The Development of Ethics in Socio-cultural Anthropology: The
Thailand Controversy Examined." Paper prepared for a National Endowment to the
Humanities Grant. Copy on file at the Beloit College Department of Anthropology
Library (1989).
FIELDS OF STUDY
Major Field: Anthropology
viii
TABLE OF CONTENTS
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Vita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
Chapter 1: Research Question . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Chapter 2: Research Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Methodological Issues: the GIS Environment . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.1 GIS Vector Data Coverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.2 GIS Raster Coverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2 Definition of the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Archaeological Data Acquisition Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4 Construction of the Archaeology GIS Database . . . . . . . . . . . . . . . . . . . . . . 14
2.5 Acquisition and Development of Environmental Data Layers . . . . . . . . . . . 16
2.6 Acquisition of Environmental Context for Sites . . . . . . . . . . . . . . . . . . . . . . 17
2.7 Distributional Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.8 Synthesis of Distributional Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.9 Summary of the Research Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Chapter 3: Background to the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.1 Environmental Background of the Study Area . . . . . . . . . . . . . . . . . . . . . . . 24
3.1.1 Physiography and Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.1.2 Bedrock Geology and its Control over Study Area Terrain . . . . . 26
3.1.3 Climactic and Geomorphological Considerations . . . . . . . . . . . . . 27
3.2 Flora and Fauna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.1 Flora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.2 Fauna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3 Culture History of the Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
ix
3.3.1 Paleo Indian Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3.2 Archaic Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3.2.1 Early Archaic Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.3.2.2 Middle Archaic Period . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3.2.3 Late Archaic Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.3.3 Woodland Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.3.3.1 Early Woodland Period . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.3.3.2 Middle Woodland Period . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.3.3.3 Late Woodland Period . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.3.4 Late Prehistoric Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.4 Previous Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.4.1 Relief Era Archaeology (1929-1939) . . . . . . . . . . . . . . . . . . . . . 47
3.4.2 Reservoir and Gorge Archaeology (1964-1977) . . . . . . . . . . . . . 49
3.4.2 The Cultural Resource Management Era (1977-2002) . . . . . . . . 51
3.4.3 Summary of Previous Research . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Chapter 4: Archaeological Data in GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.1 Approach to the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.2 Archaeology GIS Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.3 Attributes of Archaeology Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.3.1 The Spatial Analysis Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Chapter 5: GIS Environmental Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.1 Data Types and Processing Consideration . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.2 Vector Environmental Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.3 Raster Environmental Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.3.1 Digital Terrain Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
5.3.2 Digital Elevation Model Derived Coverages . . . . . . . . . . . . . . . . . 71
5.3.3 An Ecological Model of the Study Area . . . . . . . . . . . . . . . . . . . . . 72
5.3.4 Other Background Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.4 Analytical Approach to the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Chapter 6: Distributional Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.1 Environmental Attributes of Archaeological Sites . . . . . . . . . . . . . . . . . . . . 80
6.2 Temporal Trends Observed in Site Distributions . . . . . . . . . . . . . . . . . . . . . 84
6.2.1 Capabilities of the Spatial Analysis Database . . . . . . . . . . . . . . . . 85
6.2.2 Distributional Trends of Environmental Variables . . . . . . . . . . . . . 86
6.2.3 Distributional Trends of Archaeological Variables . . . . . . . . . . . . 88
6.2.3.1 Site Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
6.2.3.1 Assemblage Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.3 Summary of the Distributional Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Chapter 7: Synthesis of Distributional Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
x
7.1 Synthesis of Site Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
7.1.1 Pattern I: Paleo Indian Through Middle Archaic Periods . . . . . . 101
7.1.2 Pattern II: Late Archaic and Early Woodland Periods . . . . . . . . . 101
7.1.3 Pattern III: Middle Woodland and
Late Woodland Periods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
7.1.4 Pattern IV: Late Prehistoric Period . . . . . . . . . . . . . . . . . . . . . . . . 103
7.1.5 Summary of the Distributional Data . . . . . . . . . . . . . . . . . . . . . . . 104
7.2 Statistical Analysis of Site Area Distributions . . . . . . . . . . . . . . . . . . . . . . 105
7.3 Development and Application of a Model of Settlement Practices . . . . . . . 106
7.4 Application of the Forager–Collector Concepts . . . . . . . . . . . . . . . . . . . . . 110
7.4.1 Pattern I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
7.4.2 Pattern II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.4.3 Pattern III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
7.4.4 Pattern IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Chapter 8: Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8.1 Summary of the Distributional Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8.2 Future Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8.3 Evaluation of the GIS Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
8.4 Toward a Continuous Archaeology Coverage: A Requisite
Methodological Reorientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
List of References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Appendix A: Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Appendix B: Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
Appendix C: Code Sheets for Database Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
xi
LIST OF FIGURES
Figure
Page
1.
Location of the study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
2.
Relationships between ecological strata, bedrock, and elevation . . . . . . . . . . . 145
3.
View of the North Fork of the Red River showing site locations . . . . . . . . . . . 146
4.
Hypsography and hydrography of the study area . . . . . . . . . . . . . . . . . . . . . . . 147
5.
Illustration showing the ecological stratification of the environment . . . . . . . . 148
6.
Schematic depicting stratification of the environment . . . . . . . . . . . . . . . . . . . 149
7.
Histogram: Prehistoric site distribution and elevation . . . . . . . . . . . . . . . . . . . . 150
8.
Histogram: Prehistoric site distribution and slope . . . . . . . . . . . . . . . . . . . . . . . 150
9.
Histogram: Prehistoric site distribution and facing aspect . . . . . . . . . . . . . . . . 151
10.
Histogram: Prehistoric site distribution and ecological strata . . . . . . . . . . . . . . 151
11.
Histogram: Site types and ecological strata evaluated . . . . . . . . . . . . . . . . . . . 152
12.
Histogram: Distance to water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
13.
Histogram: Temporal distribution of prehistoric sites . . . . . . . . . . . . . . . . . . . . 153
14.
Histogram: Multicomponent nature of sites in the archaeology database . . . . . 153
15.
Histogram: Number of components per locus . . . . . . . . . . . . . . . . . . . . . . . . . . 154
16.
Histogram: Elevation of sites per period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
17.
Histogram: Mean slope value per period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
18.
Histogram: Facing aspect of sites per period . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
xii
Figure
Page
19.
Histogram: Site counts per period for the lower ecological strata . . . . . . . . . . . 156
20.
Histogram: Site counts per period for the mid-slope ecological stratum . . . . . 156
21.
Histogram: Site counts per period for the upper ecological strata . . . . . . . . . . . 157
22.
Histogram: Mean site area per period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
23.
Histogram: Minimum site area per period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
24.
Histogram: Mean site area for the low level land stratum . . . . . . . . . . . . . . . . . 158
25.
Histogram: Mean site area for the lower slope stratum . . . . . . . . . . . . . . . . . . . 159
26.
Histogram: Mean site area for the mid-slope stratum . . . . . . . . . . . . . . . . . . . . 159
27.
Histogram: Mean site area for the upland slope stratum . . . . . . . . . . . . . . . . . . 160
28.
Histogram: Mean site area for the upland level land stratum . . . . . . . . . . . . . . 160
29.
Histogram: Site area of Paleo Indian,
Early Archaic, and Middle Archaic sites . . . . . . . . . . . . . . . . . . . . . . . . 161
30.
Histogram: Site area for the five ecological strata for Late Archaic,
and Early Woodland sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
31.
Histogram: Site area for the five ecological strata for Middle Woodland,
and Late Woodland sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
32.
Histogram: Site area for the five ecological strata for Late Prehistoric sites . . 162
33.
Centered bar graph: site frequency per ecological strata . . . . . . . . . . . . . . . . . 163
34.
Centered bar graph: ecological strata per period . . . . . . . . . . . . . . . . . . . . . . . . 164
35.
Correspondence analysis of sites per stratum per period . . . . . . . . . . . . . . . . . . 165
36.
Correspondence analysis of sites per stratum
per period (row and column data) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
xiii
Figure
Page
37.
Consolidation of ecological strata for synthesis purposes . . . . . . . . . . . . . . . . . 167
38.
Diagram of change in settlement patterns through time . . . . . . . . . . . . . . . . . . 168
xiv
LIST OF TABLES
Table
Page
1.
Cultural chronology of the region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
2.
Tree species according to landform class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
3.
General database characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
4.
Definition of the ecological grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
5.
Diachronic considerations for the ecological model . . . . . . . . . . . . . . . . . . . . . 174
6.
General characteristics of archaeological sites . . . . . . . . . . . . . . . . . . . . . . . . . 176
7.
Frequencies of ecological strata and archaeological occupation . . . . . . . . . . . . 176
8.
Lithic diversity index for 52 sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
9.
Combined lithic and ceramic data for diversity index . . . . . . . . . . . . . . . . . . . . 177
10.
Site count data for center bar graph creation . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
11.
Percentage data derived from Table 10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
12.
Mean site area (hectares) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
13.
Salient features of the forager and collector concepts . . . . . . . . . . . . . . . . . . . 179
14.
Inferred distributions of sites across the landscape . . . . . . . . . . . . . . . . . . . . . . 180
15.
Schematic for four settlement patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
xv
CHAPTER 1
RESEARCH QUESTION
This dissertation addresses the question of whether or not changes in subsistence
strategy also affected landuse and settlement practices in the prehistory of Eastern Kentucky
along the western Cumberland Escarpment (Figure 1). Evidence of subsistence change from
the region consists of well-preserved domesticated plants (cultigens) from dry rockshelters
dating to 3,000 to 4,000 before the present (B.P.). This interval is commonly termed the Late
Archaic period (Table 1). Because of substantive evidence of domesticated plants from
rockshelters, the study area is well-suited to examining facets of settlement change vis-à-vis
subsistence change. Decades of research have resulted in the accumulation of a large
database of archaeological sites throughout the region. However, to date, these data have
not been systematically evaluated.
The hypothetico-deductive method involves the development of a set of hypotheses
to test a research question. In the present case the null hypothesis (H0) is: Shifts in landuse
patterns consequent to changes in subsistence practices are not observable. Specifically, no
particular trends across space and through time are observable; landuse patterns documented
for periods prior to and during the utilization of cultigens remain the same. Frequency
distributions of archaeological deposits across space will continue to exhibit the same
1
pattern(s) for different time periods. Failure to reject the null hypothesis would mean that
either the data are insufficient to answer the research question, or that changes in subsistence
practices did not substantively alter settlement patterns. The alternate hypothesis (H1) may
be stated as: Changes in the subsistence base did have a measurable impact upon settlement
practices. For H1 to be tenable, frequency distributions of archaeological sites across space
and through time must exhibit observable fluctuations. Further, these fluctuation must be
temporally associated with the incorporation and subsequent continued use of domesticated
plants in the diet. Failure to reject the null hypothesis renders H1 untenable. If the null
hypothesis is rejected, the mechanism(s) of change require further evaluation. The purpose
of this dissertation is to employ existing data from the study area to assess the validity of the
null hypothesis.
Initially the research question was to be addressed via the systematic collection of data
via the siteless survey research design as promulgated by Dunnell and Dancey (1983).
Unfortunately, the siteless survey approach could not be operationalized due to a lack of
funding and the lack of access to federally managed lands within the study area. Alternately,
the question was approached by constructing a database of previously recorded
archaeological sites within the study area. Imperfect though the data are, as they were
collected for disparate purposes over seventy years, the research question can be at least
rudimentarily evaluated. The database for the study area , then consists of nearly 1,400 sites
recorded mainly by federally mandated Cultural Resources Management (CRM) projects.
Historically Eastern Kentucky rockshelters are well-known to archaeologists because
of the rich deposits of normally perishable prehistoric artifacts found in them. The area’s
2
rockshelters were first systematically investigated by Webb and Funkhouser (Funkhouser and
Webb 1929, 1930; Webb and Funkhouser 1936). They recovered organic items such as
vegetal fiber bags, textiles, slippers, cordage, human paleofeces, and plant food remains.
Botanical analysis (Jones 1936) of samples collected by Webb and Funkhouser supported the
proposition based on data from the Ozarks (Gilmore 1931) that eastern North America
constituted a locus of independent agricultural origins (Smith 1986; Smith 1992). Like the
early 20th century research bias toward burial mound and shell matrix sites elsewhere in the
Ohio Valley, the uniqueness of materials present in rockshelters has affected subsequent
research in the study area. Research questions are generally oriented to evaluating issues of
subsistence change. Data applied to these questions come solely from rockshelters; no
systematic collections of paleoethnobotanical materials from other contexts exist for study.
Applegate (1997), in a detailed analysis of Rockbridge rockshelter in this region, concluded
that questions regarding subsistence and settlement change in the region cannot be evaluated
from rockshelter data alone; alternate sources of data are required. This dissertation follows
her lead.
The purpose of this dissertation is not to address issues concerning the origins of
agriculture in the region. However, settlement and subsistence patterns are related. There
much is to be learned if subsistence and settlement practices are considered independently.
Therefore, this research project is concerned with compiling and synthesizing the available
information on settlement patterns for the study area.
One independent source of related information is data pertaining to past environments.
These data document environmental conditions at the same time that cultigens materialize in
3
the archaeological record (e.g., Delcourt et al. 1998). Paleoenvironmental data consisting
of pollen cores and charcoal samples from several ponds within the Appalachians place initial
human impact on the environment as early as ca. 6,000 B.P. The environmental record
indicates that increased disturbance of natural habitats intensified ca. 4,000 to 3,000 B. P. and
continued throughout the rest of prehistory. Evidence suggests that human-set fires in the
uplands resulted in the persistence of fire-tolerant oak and chestnut at the expense of other
species. Based upon paleoethnobotanical data from rockshelters, alterations of the forest
canopy in the uplands is postulated by some archaeologists to be a form of prehistoric
silvaculture (e.g., Gardner 1997:177). In any case, it is clear that prehistoric populations were
already playing a role in enhancing the productivity of their environment prior to the
appearance of the first cultigens in the diet.
As changes (4,000 to 3,000 B.P.) in forest composition affecting mast resources
continued, upland rockshelter occupations intensified (Delcourt et al. 1998:276).
Concomitant with more intense rockshelter occupations, evidence for mast storage features
has been found (Gremillion 1996). Following the Late Archaic period, the Woodland period
(3,000 to 1,000 B.P.) documents ever-increasing reliance upon cultigens, perhaps at the
expense of mast resources. By the end of the Woodland period, an agricultural food
production system dependent upon cultigens is established. Culmination of the agroecology
in the region follows during the incorporation of tropical plants such as maize at the end of
the period. Clearly, archaeologists have established that the study area contains evidence for
the emergence and intensification of food production practices (e.g., Cowan 1984, 1985,
1997; Gremillion 1993, 1994, 1995, 1996; Ison 1991).
4
This study was undertaken specifically to understand the relationships between
settlement and subsistence strategies within an ecological perspective. Previous studies that
considered settlement change did so mainly in passing, and were limited to the Red River
region. These studies principally had site discovery and inventory priorities (e.g., Cowan
1984, 1976, 1975; Wyss and Wyss 1977). Settlement data from the 1970s suggest that large
occupations existed on or next to floodplains during the Late Archaic period. By the Early
Woodland period, large floodplain sites were replaced by small ephemeral deposits. In the
uplands, ephemeral Late Archaic rockshelter deposits were supplanted by greater numbers
of larger and more stable Early Woodland period sites (Cowan 1984). Middle Woodland
sites were located closer to the floodplains (Wyss and Wyss 1977). Applegate’s (1997) work
indicates that rockshelter occupations were probably less intense in the Late than in the Early
Woodland.
Shifts in settlement during the Early Woodland period might correspond to use of
rockshelters for storing crops and mast resources in rockshelters (Gremillion 1994, 1993;
Cowan 1984), but perhaps on a seasonal basis (Cowan 1997:84). Alternately, rockshelters
might represent year-round habitations (Cowan 1985; Ison 1988; Purrington 1967; Wyss and
Wyss 1977; ). Some researchers hypothesized that the storage of crops buffered against
unpredictable shortfalls in mast harvests (Cowan 1984; Gremillion 1996). Garden localities
were perhaps more easily established in uplands than in floodplain settings that were sheltered
from solar radiation by steep valley walls (Ison 1991). While substantial Early Woodland
period rockshelter occupations contain cultigens, domesticates contributed little to the
prehistoric diet for the first 1,500 years of consumption (Gremillion 1996).
5
This study is oriented toward determining whether or not the incorporation of
domesticated plants into the diet ca. 4,000 B.P. significantly changed human landuse patterns.
What impact did a changing subsistence base have upon foragers’ settlement, social, or
technological systems, if any? Previous research in the study area has been oriented toward
understanding issues of subsistence change from data acquired largely from rockshelters. No
syntheses of prehistoric settlement and subsistence systems incorporating data from all site
contexts within the study area, as attempted here, have appeared in 20 years (e.g., Cowan
1984; Wyss and Wyss 1977).
Methodological issues are presented in Chapter 2. Chapter 3 presents the relevant
background to the research question. The background section for the study area covers: (1)
ecological considerations; (2) known archaeology; (3) and previous archaeological research.
The archaeological database developed from existing sources is presented in Chapter 4.
Chapter 5 contains a Geographic Information Systems (GIS) model of the study area
environment. The environmental model is required to evaluate the archaeological data
discussed in Chapter 4. Chapter 6 examines the spatial and temporal distributions of the
archaeological data. Synthesis of the distributions is found in Chapter 7. Chapter 8
summarizes the results of the approach employed here and recommendations regarding future
research are suggested. Specifically, this research project demonstrates the need to reorient
how data are collected in the field, what kinds of information are collected and recorded, how
these data are reported, and the kinds of information that should be routinely entered into GIS
archaeology databases.
6
CHAPTER 2
RESEARCH DESIGN
The purpose of this section is to present the approach taken in this study. This
chapter covers seven key aspects: (1) technical and methodological considerations; (2)
definition of the study area; (3) acquisition of information appropriate to the research
question; (4) construction of an archaeological database from this information; (5)
development of an environmental background database to evaluate the archaeological
database; (6) temporal and spatial distributional analysis of archaeological data; and (7)
synthesis of distributional data in terms of a site classificatory framework specific to the
research question. Elaboration on each of the seven points follows below.
2.0 METHODOLOGICAL CONSIDERATIONS: THE GIS ENVIRONMENT
To address the research question, large amounts of spatial data must be analyzed to
determine whether or not shifts in settlement practices occurred. This study employs a
Geographic Information System (GIS) to manage and analyze archaeological and
environmental data. Development and analysis of GIS-based databases constitutes the means
by which this study addresses the research question. As a result, methodological and data
requirements are affected by GIS framework demands. A GIS is any system that stores
7
spatially-referenced information. On the most rudimentary level, an address book or a paper
map both contain spatial information and are examples of GIS. Maschner (1996:2) defines
a GIS as “simply spatially referenced databases--points or areas on a map having a direct link
to a particular record in a database.”
This study employed a computer-based GIS.
A computer-based GIS may be
conceived of as four subsystems (Maschner 1996:2; Marble 1990): (1) a data entry system
that transfers analog and digital data to (2) a storage device; (3) software which performs
analysis and manipulations functions on the stored data; (4) a data visualization and reporting
subsystem. The data entry subsystem may consist of keyboard entry, scanners, digitizing
tablets, or even Global Positioning Systems (GPS). The data manipulation and analysis
software consists of statistical and GIS packages. Many GIS software packages contain
routines for geostatistical analysis, or the ability to transfer data to other statistical software
packages. Data visualization and reporting is accomplished via graphical means either on a
monitor or through plotting and printing.
A Windows 95 platform desktop computer system running Environmental Systems
Research Institute’s (ESRI) ArcView 3.2 software was used for this study. The selection of
ArcView 3.2 was based upon the fact that it is the industry standard. Data may be shared
across many different platform types from handheld devices like GPS data loggers, PCs, and
workstations. Many analytical capabilities of ArcView 3.2 were developed from the more
robust ArcInfo platform. ArcView 3.2 provided sufficient database management and
construction capabilities, as well as spatial analysis capabilities through numerous
supplemental applications like the Spatial Analyst extension.
8
The ArcView 3.2 GIS environment contains two main components. The primary
component is its ability to graphically display information that has at least two dimensional
spatial attributes (e.g., both a Northing and an Easting coordinate). Any data that has a
spatial component in terms of coordinates is georeferenced. The second component is its
relational database. A relational database contains georeferenced data. The GIS can display
and analyze information that is stored in a traditional computer database that consists of
columns (fields) and rows. At a minimum, two fields must supply coordinate information.
Data collected for this study must fulfill the spatial requirements demanded by the GIS
environment.
2.1.1 GIS VECTOR DATA COVERAGES
GIS data are commonly termed layers or coverages. This dissertation employs two
types of coverages: archaeological and environmental. Data layers can be created from
database files. Points delineating the location of archaeological sites is such an example.
Environmental or background layers can also be obtained from existing sources or they can
be created independently. Through the course of this study new environmental layers were
collected from various state and federal agencies. Fewer than five years ago, several of the
data layers employed in this study did not exist. As computing storage capacity increases and
microprocessors become faster, the ability to generate higher resolution analytically robust
datasets increases.
9
There are three main types of data formats in the GIS environment. The first type of
data format is the vector format. Data are stored within a given coordinate system as one of
three types of features: points, lines, or polygons. In ArcView GIS, vector data layers or data
coverages have their characteristics or attributes stored in database files termed attribute
files. Each class or type of features possesses its own attribute table. For each feature in a
coverage, there is at least one record (ArcView Online Manual 1998).
The topology, or spatial relationships between points, is maintained through storage
of Cartesian (X, Y, Z) coordinates for each point. Archaeological sites may be expressed as
points. However, archaeological sites are often best represented as polygons since they often
cover large areas. Utility poles, fence posts, a single artifact, or gas wells are the best
examples of point data.
Linear features in ARC/INFO terminology are termed arcs. Arcs are sequences of
connected points. Examples of arcs are contour lines, roads, streams, or utility lines. Within
this project, archaeological sites are not expressed as linear features. A special type of linear
feature is the route. Routes may be transportation networks like roads or trails or streams.
Routes are linear features which contain at least on or more arcs or parts of an arc (ArcView
Online Manual 1998).
The third type of coverage or data layer in ArcView GIS is polygon data. Polygons
are areas that are enclosed by a boundary. Examples of polygons include countries, soil
types, or archaeological sites. Polygons may contain label points. Label points possess the
same attributes as the polygons in which they fall. The advantage of label point coverages is
that they may express polygons in terms of different symbols. For example, rockshelter sites
10
may be displayed as triangles while floodplain sites may be plotted as squares. The relative
areas of sites may be expressed as different sizes of symbols (ArcView Online Manual 1998).
A special type of polygon is the region. Regions may be subclasses of polygon types. For
example state polygon coverages might contain the polygon subclass county.
Lines (arcs) and polygon features both contain nodes. Nodes are defined as endpoints
of the arcs that makeup those features. Nodes are found at either end of a dangling line
(unconnected arc), or where two arcs intersect. Polygons also have nodes. By stipulating
the beginning and ending of a polygon, the inside area of a polygon is defined.
Finally, the vector coverages also may contain an annotation. Annotations may
constitute feature labels. Annotations may be text strings. Information pertaining to label
information, text type, location of the label is stored in the annotation attribute file (ArcView
Online Manual 1998).
11
2.1.2 GIS RASTER DATA COVERAGES
A raster database stores spatial data in a format where space is divided into square
cells. Each cell stores a numeric data value. ArcView with the Spatial Analyst extension
employs the ARC/INFO GRID format. In the GRID format, raster data are stored in a Value
Attribute Table (VAT). The numeric data may be either integer or floating-point (decimal)
data, although some analytical operations require integer data. Raster or grid data are
maintained within a Cartesian coordinate system. Grid rows correspond to an X axis while
columns correlate with a Y axis. The numeric data stored in each cell may represent
environmental data such as soil or vegetation type. Or, each cell may represent a particular
color for digital images like scanned maps. Digital photographic images are raster data.
Aerial digital photographs in GIS are digital images where the coordinate system and map
projection for the rows and columns of cells (pixels) is specified. The resolution of a raster
data layer is dependent upon the cell size.
2.2 DEFINITION OF THE STUDY AREA
The study area is located in east-central Kentucky about 50 km southwest of
Lexington. As per GIS spatial requirements, the area is delineated as a rectangle: 83° 30' to
84° West longitude and 37° 30' to 38° North latitude (Figure 1). The study area is 60 km
East-West and 47 km North-South, covering 2820 km2. Geopolitically it encompasses
Breathitt, Estill, Lee, Menifee, Powell, and Wolfe Counties. Physiographically, the region
covers portions of the Cumberland Escarpment, Eastern Coal Fields, Knobs, and a sliver of
12
the Outer Bluegrass. From a hydrographic perspective, the study are is drained by the North
Fork of the Kentucky River, and its tributary, the Red River. From a larger standpoint, the
study area falls within the Middle Ohio Valley. Although this area is centered around the
Cumberland Escarpment zone, the delineation of a broader study area allows for the capture
of landform variability accessible to prehistoric populations.
2.3 ARCHAEOLOGICAL DATA ACQUISITION STRATEGY
For this study a large, detailed database of archaeological attributes of the study area
was desired. The database was constructed by acquiring all reasonably available reliable
information on the archaeology of the study area. Inclusion of information in the database,
at a minimum, required spatial attributes and a site identification code. The Kentucky Office
of State Archaeology (OSA) has recently digitized the site files database for GIS applications.
The OSA database that covers the study area served as the minimal level of archaeological
information for the study. The database contains inventory records on nearly 1400
archaeological sites. Originally, these data were supplied by researchers on paper site
inventory forms to the OSA. The OSA uses the traditional trinomial site designation system
developed originally for river basin surveys. The use of this number allows for the
identification of sites on a county level. Since the trinomial number is used consistently by
archaeologists, sites referenced in archaeological literature could be matched with sites within
the OSA database. The OSA database fulfilled the spatial data requirements demanded by the
GIS environment. Further, the data were provided in ArcView format.
13
Simultaneous with the acquisition of the OSA database, a reasonable effort was made
to collect all available information on the archaeology of the study area. This strategy
consisted of obtaining copies of published literature from journals, institutional reports, and
monographs. More difficult to obtain reports from federally mandated Cultural Resource
Management (CRM) were also acquired. Information derived from private collections or
from institutions without a formal trinomial site designation was not included in this study.
Since the data within the OSA archaeology database was collected for inventory purposes,
it lacks more detailed archaeological attributes. The acquisition of archaeological information
in published format, including CRM reports, served to make the OSA database more robust
in terms of artifacts present at particular sites.
2.4 CONSTRUCTION OF THE ARCHAEOLOGY GIS DATABASE
Archaeological data were coded into several databases for GIS analysis. The
databases were created in ArcView 3.2, following the native dBASE format. Database rows
consisted of site records. Database columns, commonly termed fields, contained site attribute
data. For the ease of data entry and manipulation several databases were created separately.
Each of the databases could be merged, joined, or linked together depending upon analytical
demands. The ability to join, link or merge database files relied upon a numeric site
identification field common to each of the eight databases. By keeping each of the databases
separate, the data was more manageable. Eight databases contained 65 fields in which
attributes pertaining to archaeological sites were coded and entered.
14
The archaeology databases were built upon the locational and identification attributes
originally coded in the OSA database. In effect, the OSA facilitated database construction
by providing crucial site identification numbers and X and Y coordinates in the Universal
Transverse Mercator projection. A second important aspect of the OSA data is the feature
coverage, or shape file in ArcView 3.2 format, consisting of site limits delineated as polygons.
each polygon feature contains an identification number that allows it to be referenced to a
particular row entry in a database file.
The OSA database fulfilled data management or record-keeping demands; other
databases were constructed to account for archaeological attributes of the sites in the OSA
database. The OSA database was primarily designed for maintaining a list of reported sites,
their location, and potential National Register of Historic Places significance. The only
archaeological attributes that the OSA database contained were temporal affiliation,
“archaeological culture,” site type, and site area. Data pertaining to kinds of artifacts present
at a particular locus are not present in the OSA database.
Because the OSA database lacks information pertaining to artifacts present at a site,
five additional databases were created. These databases consist of: (1) portable lithic
artifacts; (2) non-portable rock features; (3) prehistoric ceramics; (4) biotic artifacts (plant
and animal remains); and (5) human-modified biotic artifacts (e.g., leather, wooden tools,
textiles). Once the data were sorted into the above five databases, a chronological database
was created. The chronological database essentially performed the function of collating all
available time sensitive information from the above databases. For example, projectile points
or ceramic types were used to infer a site’s temporal affiliation(s). The chronology database
15
improved the resolution of the OSA database by nearly fifty percent. The improvement in
temporal resolution is largely a result of data from site reports not being recorded on site
inventory forms; the OSA database is derived from these site inventory forms. Finally, a
spatial analysis database was created tor explicitly address the research question regarding
settlement shifts through time. Pertinent fields from the above seven databases were
extracted to create the spatial analysis database. Details of database construction and their
contents are presented in Chapter 4.
2.5 ACQUISITION AND DEVELOPMENT OF ENVIRONMENTAL DATA LAYERS
Environmental or background data layers in GIS provide the context to evaluate
locational trends in the study area’s archaeological record. There are three approaches that
may be taken to obtain environmental data for GIS projects: (1) acquire existing data layers;
(2) collect environmental data directly from the field; and (3) construct new data layers from
existing ones via map calculations in GIS. For this study, the first and third alternatives were
employed.
At the beginning of this project, few data layers for the study area existed; by
completion, several previously inconceivable data layers were available. The primary sources
of environmental data for GIS applications are state and federal agencies. In particular, the
United States Geological Survey (USGS) has spent the last decade producing a variety of
digital data layers of utility to archaeological applications. The Kentucky Geological Survey
and the Kentucky Water Resources Cabinet have also developed coverages used in this study.
16
The primary data employed in this project were Digital Elevation Model (DEM) data
developed by the USGS. A DEM is a cell-based or raster data layer. Each cell is assigned
an elevation value. The lattice or grid that results is a continuous sampling of elevation values
for a particular area. DEMS used in this study have a 30 m cell size. DEMS were generated
from paper maps by sampling the hypsography (contours) from scanned 7.5 minute series
topographic maps. By performing map algebra on DEMs in GIS other environmental layers
can be created. Slope, facing aspect, hydrography (stream networks), insolation (solar
radiation), and ecological data layers were entirely or partially generated from DEMs.
Data layers from sources other than raster-based DEMs consist of vector datasets.
Vector datasets are comprised of points, lines, or polygons rather than grid cells. Examples
of vector environmental data used in this study include hydrology, physiography, and geology
layers. Hydrology data for the study originated as a Digital Line Graph (DLG). Hydrography
DLGs at the 1:24,000 scale were acquired and converted for use here.
2.6 ACQUISITION OF ENVIRONMENTAL CONTEXT FOR SITES
One of the great GIS utilities for archaeological studies is the rapid capture of
environmental characteristics of sites. In GIS, the environmental and the archaeological
coverages overlap.
The primary means of acquiring environmental attributes of
archaeological sites in GIS is by overlaying archaeological site locations, either defined as
points or polygons, on top of a given environmental data layer. Data in one coverage can
17
be added to another via map algebra (addition, subtraction, multiplication), or by merging
coverages together. Additionally, relational databases may be queried. Queries of databases
may be stored as new coverages.
ArcView 3.2 with the Spatial Analyst Extension has the capability of displaying raster
and vector formats simultaneously. It is also now possible to convert between raster and
vector formats. This process allows for easier data capture. The procedure employed here
was to use querying operations and map calculations. Within the Spatial Analyst Extension,
the Map Calculator option allows for queries to be developed using set theory. For example,
all sites of a given time period and below a certain elevation threshold may be queried. The
resulting output may be saved as a new data layer. This process was used to acquire data
from environmental layers that was then added as new fields to the spatial analysis
archaeology database described above.
2.7 DISTRIBUTIONAL ANALYSIS
Once the archaeological and environmental databases were constructed, spatial
analysis was completed. The goal of spatial analysis was to examine the distribution of
artifact classes across space and through time in relation to the environment. Single or
multiple artifact classes may be evaluated. Specifically for this study, the goal was to
determine if temporal shifts in artifact distributions occurred. Ideally, a goal was to examine
the distribution of temporally sensitive chipped stone bifaces, ceramics, and plant remains
across space.
However, due to uneven collection strategies conducted by previous
archaeologists, the examination of the distribution of specific artifact classes other than lithic
18
debitage produced equivocal results (e.g., all 16 sites containing cultigens are rockshelter
contexts). By combining temporally sensitive data, distributions of sites of a given period
were examined across space.
The distributions of archaeological materials across space and through time are
presented in the form of tables, histograms, and other display devices. Of particular value in
GIS analysis is that, unlike the archaeology database for a region, environmental layers are
continuous across space for the entire study area. Therefore, the environmental data layers
represent the known universe in statistical terms (Kvamme 1992:128). Environmental
characteristics of archaeological sites can be contrasted against the background environment.
Differential distributions of archaeology “environments” with respect to environmental factors
may indicate prehistoric locational preferences.
The results are equivocal when the
archaeological site environmental characteristics match the background environment.
Consider the example where 70 percent of archaeological sites are on south facing landform,
while at the same time, 70 percent of all landforms are south facing. Any inferences regarding
preferences for south facing landforms are questionable since the archaeology matches the
background.
2.8 SYNTHESIS OF DISTRIBUTIONAL DATA
The goal of this study is to determine whether settlement patterns changed or not
when domesticated plants entered the prehistoric subsistence system. Archaeobotanical
research in the study area has established that cultigens entered the subsistence base by the
Late Archaic period. Given changes in subsistence, was there a simultaneous change in
19
settlement patterns during or after this period? Minimally, three temporally discrete
settlement patterns need to be discerned: (1) for the time prior to the appearance of cultigens
in the diet; (2) during the interval when cultigens were incorporated into the subsistence base;
and (3) after the incipient use of cultigens when they begin to play a more central role in the
diet.
Therefore, the issue becomes one of discerning changes in site structure. At a
minimum, differences in site structure must be observed for each of the above three time
intervals. To evaluate site structure, the following factors are analyzed: (1) site area; (2)
diversity of artifacts present at a site; (3) the frequency of sites with a particular size or level
of artifact diversity. The three variables are then examined across space and through time.
A site typology specific to the research problem is constructed; its purpose is to evaluate
structural changes in landuse.
The classificatory scheme adapts concepts developed by Binford (1980) from what
is known as the forager--collector model. Specifically, Binford’s view of mobility as a
continuum is appropriated. At one end of the continuum, foragers are viewed as residentially
mobile groups who move residences regularly to “map-on” to resources. At the other end
of the continuum, residentially stable collectors solve resource acquisition problems by being
logistically mobile. Logistically mobile groups use specialized task
groups to move resources back to stationary populations. Application of the forager-collector model is also suitable here because of the low-level resolution of the archaeological
database available for study.
20
The synthesis of distributional data requires that a site typology be created specific to
answering the research question. The variables of site frequency, area, and artifact diversity
are employed to categorize sites. The goal of utilizing a typological framework is to examine
the distributional data on the basis of shifting mobility strategies.
Two site types are derived from Binford’s concepts. The first site type is termed the
residential base. The second type is termed the location. Binford (1980:9) defines the
residential base as the “hub of subsistence activities, the locus out of which foraging parties
originate and where most processing, manufacturing, and maintenance activities take place.”
A location is defined as “a place where extractive tasks are exclusively carried-out.” In
addition to the location, the collector strategy also has field camps, stations, and caches in
their site type repertory.
In this study the collector strategy is simplified by modifying the concept of the
location to include two types: (1) extractive locations; (2) processing locations. The
processing location requires further elaboration. Binford’s field camp, cache, and station,
may be viewed as special kinds of processing locales. The field camp is an example of
logistical procurement of resources. Logistical procurement implies the collection and
processing of resources away from the residential base. Resources from the field camp are
then transported to the residential base. Or, resources may be cached. Cached resources are
usually processed first. The station, like the field camp, is a site type between the location
and the residential base. The station is where information is gathered and processed before
resources are extracted at the location; the station is a special kind of processing location.
21
The three site types, residential base, the location, and processing location, might be
deduced from the archaeological record in three ways. The variable site area will be
expressed differently at the three different site types. Residential bases will have large site
areas while processing locations, and extractive locations will have much smaller areas. The
variable artifact diversity will also be expressed differently. Residential bases are expected
to have high diversity rates than are extractive and processing locations. Finally, the relative
frequencies of large and small sites as well as low and high diversity sites might be expected
to change through time. For example, if a shift from a forager to a collector strategy occurs,
a shift to fewer larger sites might indicate reduced residential mobility. Increases in logistical
procurement might be reflected in the archaeological record by an increase in small, low
diversity sites scattered across the landscape.
If differences in settlement patterns through time are detectable (there is no a priori
reason why they should be),the site types predicted by the forager-collector model should
assist in identifying these changes. However, the model does not explain why settlement
practices were altered. Again, the research question posed here goes only as far as trying to
determine if any change in settlement patterning occurred at all.
In order to sufficiently answer the research question, only time-sensitive
archaeological sites are used in the analysis. Therefore, settlement patterns will be inferred
from the differential distribution and frequencies of a stipulated site type through time and
across space. As discussed above, study area space can be stratified according to
environmental characteristics. Archaeologists have traditionally thought that human locational
decisions are partially based upon economic considerations like access to potable water, level
22
land, arable soils, etc. The distributions of sites types are examined across several different
stratified environmental coverages: elevation; slope; facing aspect; distance to water; and
ecological data.
2.9 SUMMARY OF THE RESEARCH DESIGN
This research is geared toward the distributional analysis of archaeological deposits
across space and through time to discern changes in settlement practices. The research
design presented here is organized to collect and compile pertinent data in a format that can
receive distributional analysis. A synthesis of the distributional data follows. Chapter 3
provides the requisite background to: understand the ecology and environment of the study
area for modeling purposes; understand the research question in culture historical terms;
understand the nature of the archaeological database from the perspective of previous
research goals and practices.
23
CHAPTER 3
BACKGROUND TO THE STUDY AREA
The goal of this chapter is to present the background to the research question in the
following order: (1) ecology and environment; (2) culture history; and (3) previous research
conducted within the study area. Ecology and environmental information illuminate
geomorphological and biotic facets of the study area.
Focusing entirely upon what is
currently known of settlement and subsistence practices throughout prehistory in the study
area is the domain of the culture history section. Examination of previous research is geared
toward understanding the biases and historically contingent events that have directed what
is known about the study area’s prehistory.
3.1 ENVIRONMENTAL BACKGROUND OF THE STUDY AREA
This section is organized into two parts: (1) physiography, geology, and
geomorphology; (2) biotic composition (flora and fauna). The goal is to understand the
composition of the study area so that it may be modeled for distributional study. GIS Spatial
analysis of archaeological sites on a regional scale requires stratification of the terrain along
24
relevant variables. The variables of slope, elevation, and distance to water were discussed in
the previous chapter. Understanding of the study area environment is attained by knowing
how landforms, and hence resources, are distributed across space.
3.1.1 PHYSIOGRAPHY AND GEOLOGY
The study area (Figure 1) lies in the Cumberland Escarpment and Plateau region of
eastern Kentucky (Fenneman 1938). The terrain has deeply entrenched V-shaped drainages
that have eroded away the plateau, leaving only narrow ridgetops. The remainder of the
landsurface mainly contains steep slopes, bedrock outcrops, saddles, benches, and small
alluvial landforms along low-order stream courses. Level land is seldom found in locales
proximate to the Red River Gorge itself. Abundant level alluvial land lies along the Red River
system, a tributary to the North Fork of the Kentucky River. East of the main portion of the
study area is the Eastern Kentucky Coal Field. This subregion contains rugged terrain but
lacks the sandstone escarpment. The Knobs and Outer Bluegrass regions, which contain
more gently rolling to level terrain, are located to the West.
The Cumberland Plateau consists of Pennsylvanian (310-270 mya1) and Mississippian
(350-310 mya) age sedimentary rocks that are oriented nearly horizontally. Uplift of the
Cincinnati Arch tilted these deposits slightly (5.7 m per km) to the southeast (Dever and
Barron 1986:46). The variability in resistence of the bedrock has allowed for massive downcutting to occur. The result is that the eastern and central portions of the study area contain
narrow ridges, steep valleys, and small floodplains. The western portion of the study area has
1
Abbreviation for million years ago.
25
larger floodplains of Quaternary alluvium, and less forbidding terrain. The Cumberland
Escarpment serves as a dividing line through the middle of the study area diagonally
southwest to northeast.
The western edge of the Cumberland Plateau is delineated by the Pottsville
Escarpment. The escarpment consists of a sandstone cap rock underlain by shales which are
less resistant to erosional forces (Dever and Barron 1986:43-46). The cap rock consists of
the Corbin Sandstone Member of the Lee Formation in the East; to the west it is capped by
the Upper Member of the Breathitt Formation. The Lower Tongue of the Breathitt formation
underlies the Corbin Sandstone. The Breathitt and Lee Formations are Pennsylvanian-age
deposits that formed from deltaic and fluvial sediments. The underlying Mississippian-age
Newman Limestone and Borden Formations are also of sedimentary origin.
The
Mississippian-Pennsylvanian boundary represents a regional disconformity (Dever and Barron
1986:44; Weir and Richards 1974)2.
3.1.2 BEDROCK GEOLOGY AND ITS CONTROL OVER STUDY AREA TERRAIN
For purposes of this distributional archaeology study, it is best to stratify the study
area by utilizing stable environmental variables (Dunnell and Dancey 1983). Stable
environmental variables include bedrock geology, soil types, and drainage systems. Unstable
variables such as vegetational regimes are best avoided when studies of great time-depth are
conducted. Variability in bedrock geology controls the structure of the study area terrain.
2
Recently the bedrock stratigraphy has undergone refinement (Ettensohn et al. 1984) but
has little bearing on this discussion; it is not presented here.
26
Bedrock variability is the main determinant of hydrology, hypsography (terrain contours),
edaphic (soil) conditions, and vegetational composition. The nearly flat deposition and
maintenance of bedrock strata have structured the landscape in a vertical manner. Numerous
overhangs, commonly termed rockshelters, are almost exclusively restricted to the Corbin
Sandstone. The sandstone stratum is confined to between 1000 feet (305 m) and 1250 feet
(381 m) above mean sea level. Similarly gentle colluvial slopes found along valley margins
are underlain by less-resistant shales of the Borden Formation (209 to 217 m above mean sea
level).
3.1.3 CLIMACTIC AND GEOMORPHOLOGICAL CONSIDERATIONS
It has been established that the first humans occupied the Americas by the Late
Pleistocene. The end of the Pleistocene (ca. 10,000 B.P.) was marked by the retreat of the
Wisconsin glacier North of the study area. This retreat marked the establishment of a warmer
moister Early Holocene climate.
Major geomorphological and biotic adjustments to the Post-Pleistocene environment
occurred in the Southeast. Drainage systems adjusted to new base levels established by rising
sea levels following glacial retreat. Branson and Batch (1974:42) observe that the Red River
is now adjusted to “marked channel aggradation of the Ohio and Kentucky rivers which
occurred from extensive outwash from the Wisconsin glaciation.” Regionally, Early
Holocene hydrography was dominated by high-energy braided-stream systems. By the midHolocene (ca. 7,500 B.P.), the hydrographic pattern shifted to meandering systems
(Schuldenrein 1996:9).
27
During the Hypsithermal (ca. 8,000-5,000 B.P.), climate in the Southeast became
warmer and wetter (Delcourt 1998). Elsewhere in North America, the climate became
warmer and drier. The period was characterized by large-scale flood events triggered by
violent storms. Major erosion in the uplands supplied sediments for floodplain aggradation
(Schuldenrein 1996: Figure 1-2). Riverine habitats gradually expanded along the larger
floodplains. Stabilization of landforms occurred at the end of the Hypsithermal (ca. 5,000
B.P.).
Regional changes in geomorphological elements has directly affected the visibility of
the archaeological record. Erosion of uplands undoubtedly resulted in the degradation of
archaeological deposits, especially during the early to mid-Holocene. Floodplain instability
alternately resulted in the burial or removal of archaeological deposits there. The remaining
archaeological record is a combination of geomorphological factors as much as it is a function
differential human activities scattered across the terrain.
3.2 FLORA AND FAUNA
3.2.1 FLORA
The region is covered by forests of the Mixed Mesophytic type, which is associated
with the unglaciated Appalachian Plateau south of Pennsylvania (Braun 1950:39). The Mixed
Mesophytic Forest, a descendant of the Mixed Tertiary Forest, is the oldest and most complex
of the Deciduous Forest Formations. The Mixed Mesophytic Forest is dominated by a
canopy of dozens of hardwood species. The understory consists of a variety of shrubs, ferns,
28
and herbaceous growth. Several variants of the mixed Mesophytic Forest exist due to
localized geology and soil characteristics. Within the study area, the Cliff Section containing
the Pottsville Escarpment is one such variant (Braun 1950:97). The Cliff Section is
predominately comprised of hemlock, beech, oak, tulip poplar, maple, and basswood.
Two surveys of forest composition (Braun 1950; Thompson et al. 2000) have
established the relationships of facing aspect, elevation, and bedrock geology to the
vegetational composition of particular landforms (Table 2). In gorge areas, where steep
slopes are common, hemlock dominates. Southwest facing landforms are prevalently covered
by oaks. Such predictable variation of flora across the landscape may have structured
prehistoric landuse.
Elevation also plays a role in dividing the area’s vegetation into distinct zones (Figure
2). The upland plateau often has an oak-pine forest/heath regime, occasionally with open
grassy areas. Slopes generally conform to the Mixed Mesophytic type. The rockshelter zone
contains several unique species such as lichens and mosses. Colluvial foot slopes located
along the valley margins contain Mixed Mesophytic species also. However, edges of colluvial
slopes often intermingle Mixed Mesophytic species with wetlands species, creating areas of
high biodiversity. Floodplains along the larger streams contain a riverine forest. The riverine
forest is made-up of river birch, sycamores and wetland species (Thompson et al. 2000).
Although vegetation is often temporally and spatially unpredictable in distributional
terms, the above data indicate that vegetation types follow predictable patterns upon the basis
of underlying geology, elevation, and facing aspect. As a result, vegetational zones may be
modeled within the GIS methodology.
29
Economically, the region’s flora provided abundant raw materials and seasonal
availability of subsistence resources. Mast resources like hickory, walnut, and oak played an
important subsistence role throughout prehistory. Other plants like blackberries and
raspberries are also found in archaeobotanical collections from the region’s sites. Trees
provided sources for structural materials, and fuel for fires. Other plants such as rattlesnake
master and river cane provided a source for cordage, fabric, clothing, and baskets.
3.2.2 FAUNA
The study area contains a diverse fauna (Barbour 1974). The area is home 36 species
of mammals, 105 non-migratory birds, 30 reptiles, and 36 amphibians. Branson and Batch
(1974:17) documented 74 species of fish within the red River drainage system. The most
important economic species include white-tailed deer, elk, squirrel, beaver, rabbit, wild
turkey, duck, and other small game (Wyss and Wyss 1977:25). The fauna are not evenly
distributed across the environment. For example, many of the larger species of fish are only
found within the larger trunk streams, like the Red River. During the fall many different
species of fauna are attracted to mast resources commonly found along south-facing slopes.
30
3.3 CULTURE HISTORY OF THE STUDY AREA
The purpose of this section is to outline the current knowledge of the prehistory of
the study area. Four aspects of prehistoric lifeways are examined: (1) settlement patterns;
(2) subsistence practices; (3) technology and material culture; (4) social organization.
Temporally, the study area’s prehistory is divided into four major intervals (Table 1): (1) the
Paleo Indian period (12,000 to 10,000 B.P.); (2) the Archaic period (10,000-3,000 B.P.); (3)
the Woodland period (3,000-1,000 B.P.); and (4) the Late Prehistoric period (1,000-450
B.P.). Discussion of each period follows below.
3.3.1 PALEO INDIAN PERIOD
Humans probably reached the Americas sometime after 30,000 B.P. The earliest
definitive evidence of human occupation of the region is marked by the appearance of fluted
points temporally diagnostic of the Paleo Indian period dating to 11,500 B.P. Little evidence
exists for Paleo Indian occupations in the study area. Evidence for Paleo Indian period
activity in the study area largely consists of isolated finds of Clovis bifaces found in surface
contexts. An exception to this rule is Enoch Fork rockshelter located in nearby Perry County
(Evans 1996). Enoch Fork was radiometrically dated to 13,480 ± 350 B.P. A single probable
Late Paleo Indian projectile point was recovered from the site; the remainder of the materials
there apparently date to the Early Archaic period (Evans 1996:123). Big Bone Lick State
Park, located North of the study area has yielded Clovis and later Paleo Indian projectiles
(Tankersley 1996). The site is located adjacent to a natural salt spring which attracted
31
humans and wild game to the area.
Meltzer (1993;1998) thinks that Paleo Indian populations followed a variety of
subsistence strategies, specific to local conditions. The view of Paleo Indians as hunters of
Pleistocene megafauna (large game excepting perhaps caribou) has been largely discredited
both on theoretical and empirical grounds. Meltzer (1993) promotes the proposition that
Paleo Indians were generalized foragers who exploited a variety of small animals and plant
resources; they were only opportunistic scavengers of large game. Paleo Indian groups were
probably organized along the scale of nuclear families or bands. These groups were more
mobile than later groups, traveling through territories of between 40 and 300 km in radius
(Meltzer 1998; 1993). Paleo Indian lithic assemblages tend to support a generalized
subsistence strategy due to its diversity. The durable portion of Paleo Indian material culture
consists of fluted projectile points, prismatic blades, end scrapers, and perforators (Tankersley
1996:33).
3.3.2 THE ARCHAIC PERIOD
The Archaic period (10,000-3,000 B.P.) as a temporal unit comprises nearly one-half
of the region’s prehistory. The term Archaic was first employed by Ritchie (1932) to denote
a pre-ceramic, pre-agricultural lifeway based on work at sites in New York (Schwartz
1967:80). Archaic was adopted by Webb and Haag (1942) in reference to non-ceramic shell
mound sites located along the Green River (Schwartz 1967:83). The first major synthesis of
the Archaic period was completed by Lewis and Kneberg (1959). Over the following three
decades the Archaic temporal sequence of projectile points was established through the
32
excavation of stratified deposits along floodplains (e.g., Broyles 1971; Chapman and Crites
1987; Nance 1988) and at rockshelters (e.g., Fowler 1959). Within the study area, pertinent
sites include Enoch Fork (Evans 1996), Cloudsplitter (Cowan et al. 1981) Mounded Talus
(K. Mickelson 2002; Gremillion and Mickelson 1996), and Seldon Skidmore (Cowan 1976).
3.3.2.1 EARLY ARCHAIC PERIOD
Early Archaic (10,000-8,000 B.P.) groups were mobile, generalized hunter-gatherers.
Social organization was probably oriented along the lines of small transhumant bands that
ranged across large territories. Foraging ranges were large as compared to later periods.
The wide distribution of projectile points produced from non-local raw materials constitutes
the evidence for inferring high mobility. Early Archaic deposits tend to lack any substantial
midden deposits, features, or burials. Sites are thought to represent ephemerally occupied
camps (Jefferies 1996:40). Early Archaic material culture consists of temporally diagnostic
bifaces of the Kirk, Kanawha stemmed, and bifurcate types such as LeCroy. Other items
include chipped stone drills and scrapers. Burials from Kentucky sites are often in the flexed
position with grave goods including projectile points and dog canine or beaver incisor
necklaces (Jefferies 1996:46).
Early Archaic sites in the study area include rockshelters (Cloudsplitter and Enoch
Fork) and open-air sites. Deposits at Cloudsplitter (Cowan et al. 1981) date from 8,250 to
11,300 B.P. Cloudsplitter contained LeCroy style projectiles. Enoch Fork rockshelter
contained Kirk and Kanawha stemmed projectiles dating to as early as 11,000 B.P. (Evans
1996:92). Non-rockshelter evidence for Early Archaic occupations includes Gladie Creek
33
(15MF410) where several Kirk and bifurcate projectiles were recovered from surface contexts
(A. Mickelson 2001a). Rockshelter deposits appear to be more ephemeral than occupations
within the floodplains and valley margins.
The only Early Archaic subsistence data come from Cloudsplitter rockshelter. The
data indicate that large mammals and deer dominated the faunal assemblage; small animals
comprised only a small fraction. Botanical data from Cloudsplitter indicate low-level (when
compared to later periods) consumption of mast resources including walnut, butternut,
chestnut and hickory. Two, small undomesticated squash seeds (Cucurbita, sp.) were also
found in sealed deposits and might date to 10,000 B.P. (Cowan 1981;1997).
3.3.2.2 MIDDLE ARCHAIC PERIOD
Middle Archaic (8,000 to 5,000 B.P.) subsistence and settlement continued trends
observed for the previous sub-period. Sites are located along the floodplains and in upland
rockshelters. Along larger floodplains in Kentucky, dense Middle Archaic deposits cap thin
Early Archaic occupations ( Nance 1986, 1987). This evidence suggests that Middle Archaic
groups were more sedentary than earlier groups (Jefferies 1996).
Middle Archaic
manifestations are recognized by Eva, Morrow Mountain, Big Sandy II, Cypress Creek,
Matanzas, and Godar projectile points (Nance 1987; Jefferies 1988). Other materials include
ground stone axes and adzes, pitted stones, pestles, grinding stones, and atlatls (Jefferies
1996:48). Axes and adzes are thought to indicate the construction of more substantial
structures during this sub-period.
34
Few sites dating to this period are found within the study area. No large sites like
those reported elsewhere in the Midcontinent have been reported for the region. Rockshelter
deposits of this period were found at Mounded Talus and Cloudsplitter. Surface remains
along valley margins adjacent to wetlands have been documented at Gladie Creek (A.
Mickelson 2001a) and at 15PO46 (Cowan 1976). Structural remnants, hearths, prepared
surfaces, and the caching of raw materials were found at Mounded Talus (Gremillion and
Mickelson 1996).
Mounded Talus rockshelter (15LE77) has the only subsistence record for the Middle
Archaic sub-period in the region (K. Mickelson 2002; Gremillion and Mickelson 1996).
Radiocarbon dates place deposits there between 7,400 and 5,000 B. P. No substantial faunal
remains were recovered from sealed deposits. However, a fairly comprehensive set of
botanical remains were found. Mast resources included black walnut, butternut, hickory,
chestnut, acorn, hazelnut, black gum, and beech. Other economic plants include raspberry,
blueberry, grape, sumac, huckleberry, elderberry, poke, and panic grass. Undomesticated
varieties of sumpweed (Iva annua), goosefoot (Chenopodium, sp.), squash (Cucurbita, sp.),
and knotweed (Polygonum, sp.) were also reported from Mounded Talus. The subsistence
data indicate the possibility that the site was occupied throughout the year (K. Mickelson
2002).
Faunal remains from Middle Archaic deposits elsewhere in the Southeast indicate
continued reliance upon deer and turkey. Where available, aquatic resources are added to
the diet in greater numbers; in upland areas away from sources of aquatic animals, small
mammals and reptiles are added to the diet (Styles and Klippel 1996:133; Stafford et al.
35
2000). Overall the subsistence data seem to indicate expanded diet breadth during this period.
Expanded diet breadth is based upon subsistence data suggesting that more species of plants
and animals were exploited during this period than previous periods.
Formal cemetery areas established during the Middle Archaic period throughout the
region, suggesting increased social complexity (e.g., Charles and Buikstra 1983). Within
east-central Kentucky, 32 burials were found at the KYANG site (Granger 1988:175).
Individuals were placed in bowl shaped pits in the flexed position. Grave goods included bone
pins, animal tooth necklaces, and ground and chipped stone tools.
3.3.2.3 LATE ARCHAIC PERIOD
The Late Archaic period (5,000-3,000 B.P.) is marked by three major trends: (1)
broadening plant and animal exploitation; (2) increased sedentism; (3) utilization of
domesticated plants for the first time. Late Archaic period groups in the study area share
traits with what has been termed the Central Ohio Valley Archaic (Vickery 1980; Cowan
1984:15). Groups during this period practiced a broad spectrum subsistence strategy in terms
of both plants and animals. Substantial, long-term, and perhaps permanent occupations are
found in the floodplains (e.g., Skidmore, White sites). More ephemeral occupations are
found in rockshelters (e.g., Cloudsplitter, Cold Oak), and perhaps along valley margins (e.g.,
Gladie Creek). Material culture of the Late Archaic period includes Merom-Trimble,
McWhinney, and Cogswell projectile points. Other items include
36
endscrapers, bifaces, drills, utilized flakes, grooved axes, and pestles. Features found at
Skidmore (15PO17) included storage pits, earth ovens, and substantial midden deposits
(Cowan 1976).
Cowan (1984: Table 50) delineated three different types of Late Archaic occupations
within the study area: (1) large camps; (2) small camps; (3) rockshelters. Large camps are
located within the valley margins and are between 1,000-6,000 m2. The full suite of Late
Archaic durable material culture is found at large camps. Large camps include the Skidmore
and White sites. Small camps are up to 3900 m2, but are generally less than 1000 m2 in area.
Small camps contain subsets of the Late Archaic toolkit: projectiles, flakes, cores, and
scrapers. Examples of small camps are 15PO14, 15PO34, and 15PO49. Late Archaic
rockshelters contain artifact assemblages similar to those found at small camps: projectiles,
scrapers, bifaces, utilized flakes, and hearths. Late Archaic rockshelters seem to represent
ephemeral occupations. However, by the terminal Late Archaic period, rockshelters like Cold
Oak might serve as permanent residential bases (Ison 1988).
Subsistence data from Late Archaic sites indicates the addition of domesticates to the
subsistence base. The evidence for cultigens/crops is greatest for the terminal Late Archaic
period. A squash rind dating to 3,800 B.P. was found at Cloudsplitter rockshelter (Cowan
1981:74-75). Excavations at terminal Late Archaic site of Cold Oak (Ison 1988) rockshelter
recovered substantial subsistence remains which confirm substantial diet breadth. Faunal
remains included deer, turkey, squirrel, black bear, box turtle, mussels, snakes, and crayfish.
37
Botanical remains included several thousand nutshell remains consisting of hickory, oak, and
chestnut.
Cultigens from Cold Oak include sunflower, goosefoot, erect knotweed,
sumpweed, bottle gourd, squash, and probably maygrass.
Gremillion (1993c) conducted further excavations at Cold Oak rockshelter. This
work was directed toward clarifying the role of cultigens in the diet during the Late Archaic
and Early Woodland periods. She found that late Archaic crops were present in only small
quantities. But during the subsequent Early Woodland period, cultigens/crop plants were
abundant as were storage features. Rockshelter occupations were more intense at Cold Oak
in the Early Woodland period as opposed to the Late Archaic period. Overall, mast resources
was the most common plant food type represented at Cold Oak (Gremillion 1993).
In summary, the study area Archaic period is characterized by three major trends.
First, evidence suggests that diet breadth (especially in terms of plant exploitation) increased
throughout the period. Second, evidence for increased sedentism also appears at this time.
Seasonality indicators and architectural remains at Mounded Talus suggest increasing
sedentism as early as the Middle Archaic period. Large camps with substantial middens along
the floodplains indicate greater sedentism by the Late Archaic period. Third, the settlement
data for the Late Archaic period indicate an increase in the variety of site types; some locales
were probably specialized processing-extractive locations. A greater number of Late Archaic
period sites in the study area suggests that population increase occurred (Jefferies 1996:7273).
38
3.3.3 WOODLAND PERIOD
The Woodland period (ca. 3,000 B.P. to 1,000 B.P.) in eastern North America is
distinguished from the Archaic period by the appearance of ceramic technology, the increased
presence of cultigens in the diet, exotic grave goods, and mound construction. Cultigens
including squash, goosefoot, sumpweed, bottle gourd, maygrass, and erect knot weed and are
all found in sites within the study area. The phenomena of exotic grave goods and of mound
construction are generally lacking in the study locale. In the study area, the Woodland period
is divided into three sub-periods. The Early Woodland period (3,000-2,200 B.P.) is
sometimes termed Adena. The Middle Woodland period (2,200-1,500 B.P.) is equivalent to
the Hopewell period elsewhere in the East. The Late Woodland period (1,500-1,000 B.P.)
represents the culmination of an agricultural system built upon the indigenously domesticated
cultigens. The Woodland period ends at 1,000 B.P. when maize becomes a staple in the diet.
The Adena concept was first employed by Mills (1902) following his excavation of
the type site near Chillicothe, Ohio. Shetrone (1920) developed the Adena into an
archaeological culture. In Kentucky, Webb expanded on the concept of the Adena culture
(Webb and Snow 1945; Webb and Baby 1957). Adena in the Middle Ohio Valley has been
established as an early Woodland manifestation. According to Railey (1996:98), Adena in
Kentucky is best conceived of as a Middle Woodland cultural manifestation; it is a post 1,500
B.P. phenomenon. Railey (1996:98) states that “the relationship between Adena and
Hopewell is more a cultural than a chronological problem.”
39
3.3.3.1 EARLY WOODLAND PERIOD
The Early Woodland period (3,000-1,800 B.P.) is the best known interval of the
region’s prehistoric record.
Early Woodland rockshelter deposits containing unique
perishable artifacts including cultigens initially attracted archaeologists to the region. Much
research has been focused upon rockshelters. Subsequently, a rockshelter bias clearly exists.
This bias has directed research away from other portions of the region’s landscape and away
from periods other than the terminal Late Archaic-Early Woodland. Further, the bias towards
recovery of non-carbonized plant remains has served to direct research to questions regarding
the origins of agriculture to the exclusion of other lines of inquiry.
The Early Woodland period in the study area contains two of the hallmarks found
throughout the East: ceramics and cultigens. Ceramics are present by 2,800-3,000 B.P.
Evidence for cultigens (squash, gourds, goosefoot, sumpweed, maygrass, and erect
knotweed) are present in numerous rockshelter deposits. Missing from the typical Early
Woodland material culture of the Middle Ohio valley are exotic grave goods and mound
construction. Distinctive artifacts dating to the terminal Late Archaic-Early Woodland period
are bedrock mortars (colloquially termed hominy holes) situated in rockshelters. Petroglyphs
carved into bedrock at dozens of shelters in the study area probably date to this period too
(Delcourt et al. 2000). Railey (1996:247) observes considerable material culture continuity
between the Late Archaic and Early Woodland periods in the area. Early Woodland
assemblages consist of scrapers, knives, drills, celts, wedges hoes, groundstone
40
abraders, atlatls, pitted stones, pestles, hammer stones, bone awls, bone pins, and ceramics.
Projectile point types resemble Adena stemmed, Wade, and Watts Bar types (Railey
1990:295).
The first ceramics in the study are consist of thick-walled vessels. Tempering agents
include grit, quartz, chert, limestone, and sand (Cowan 1976:125). The vessels are often
ascribed to the Fayette Thick type designation common across the Middle Ohio Valley.
Surface treatments include cord marking, plain, and fabric impressed varieties. Early
Woodland vessels found in the Red River Valley have “Adena-like” traits observed elsewhere
in the region (Wyss and Wyss 1977:33).
Early Woodland settlement and subsistence practices mirror terminal Late Archaic
patterns. Terminal Late Archaic Cogswell phase projectiles are often found at the same sites
(e.g., Courthouse Rock rockshelter) suggesting Terminal Late Archaic to Early Woodland
continuity. Substantial amounts of cultigens found at Early Woodland rockshelters suggest
that these sites were residential bases. Many of the rockshelters excavated by Funkhouser and
Webb (1930) contained thick midden and ash deposits. Ison (1991) has hypothesized that
Early Woodland groups were cultivating plants in upland contexts adjacent to rockshelters.
The hypothesis appears substantiated by pollen data from Cliff Palace pond. Pollen from
domesticated plants was found in cores extracted from the pond (Delcourt et al. 1998).
Reports of rockshelter excavations by Funkhouser and Webb (1930) constitute the
only record of burials found in the study area. Early Woodland period inhumation along the
back walls of rockshelters was probably a common practice judging from the presence of
looters’ trenches. Excavations at Red Eye rockshelter uncovered 14 individuals, the largest
41
sample from the region (Webb and Funkhouser 1930:54-56).
Five of the burials were
infants, two were children, one was adolescent, three were adult females, and sex was
indeterminate on three additional adults. If rockshelters functioned as residential bases, it is
not unexpected to find low mobility individuals (infants and children) there. The presence of
female but not male burials might indicate a matrilocal settlement pattern. Burial 4 from Red
Eye consisted of an adult female who was interred with a broken banner stone, a grooved axe,
and a wooden pestle. Two other wooden pestle were also found at Red Eye; they fit bedrock
mortars present at the site (Funkhouser and Webb 1929). Evidence from burial 4 indicates
that women were probably responsible for the entire realm of labor associated with
subsistence--forest clearance (axes) as well as processing (pestles) duties.
3.3.3.2 MIDDLE WOODLAND PERIOD
In the Middle Ohio Valley, the Middle Woodland period (2,200 - 1,500 B.P.) is
synonymous with Hopewell. However, Railey (1996) observes that within east-central
Kentucky, there is a problem of cultural “overlap” with Adena and Hopewellian traits. The
study area lacks mounds and earthworks, which are features of Hopewellian groups
elsewhere. Mounds and earthworks are found to the west in the Inner and Outer Bluegrass
regions. Adena-style burial mounds are also found to the East along the Big Sandy Drainage.
The Old Fort Earthwork located south of Portsmouth across the Ohio River in Greenup
County is of Hopewellian style, but contains Adena Plain ceramics and boatstones. The Biggs
site also located in Greenup County contained Adena-like artifacts in a Middle Woodland
period burial mound circumscribed by a ditch (Railey 1996:108). The late Middle Woodland
42
Brisbin mound located in Boyd County along the Big Sandy River contained a crematorium
and artifact caches. The caches contained typical Middle Woodland artifacts including
prismatic bladelets, a groundstone gorget, and Baker’s Creek and Lowe projectiles.
According to Railey (1996:110) Middle Woodland settlements were dispersed communities
linked socially by ritual activities at mortuary sites.
Few sites in the study area are ascribed to the Middle Woodland period. Wyss and
Wyss (1977: Table 8) determined that the Middle Woodland sites that they located were
significantly closer to the Red River than sites from any other period. Rockshelters do
continue to be occupied by Middle Woodland groups. The only site in the study area to
contain Hopewellian-like artifacts was Dillard Stamper Shelter No.1. Dillard Stamper
contained Robbins type projectiles, a single cremation, 15 ovate bifaces, and a celt
(Funkhouser and Webb 1930:274). Floodplain occupations during the Middle Woodland
period also occur. For example, 15PO42 located along the Red River contained Middle
Woodland style ceramics from midden contexts (Cowan 1976).
Subsistence data are lacking for the Middle Woodland period in the study area.
Therefore, no inferences may be made regarding the status of cultigens in the prehistoric diet
during this interval. Though, Middle Woodland period deposits were documented at Cold
Oak ranging from 2060 ± 70 to 1910 ± 50 B.P. (uncalibrated). These deposits lacked
associated subsistence data (Gremillion 1995:13-14). The Middle Woodland period
subsistence data gap represents a serious issue when examining the affects of cultigens upon
settlement practices. That this data gap can be attributed to the rockshelter bias is undeniable.
43
3.3.3.3 LATE WOODLAND PERIOD
Variability in settlement strategies is present across the Middle Ohio Valley during
the Late Woodland period (1,500-1,000 B.P.).During this period, settlement nucleation takes
place (Seeman and Dancey 2000). Settlements outside of the study area consist of a few
nucleated households situated around a small plaza (e.g., Pyles). Other nucleated settlements
in West Virginia and Ohio contain household units within a D-shaped ditch and embankment
adjacent to steep river banks, clearly suggesting a defensive posture. Late Woodland material
culture in the study area includes Newtown-like ceramics and Jack’s Reef projectiles (Pollack
and Henderson 2000:631; Cowan 1976). Late Woodland sites also contain cultigens that had
first appeared during the Late Archaic and Early Woodland intervals.
Within the study area, Late Woodland occupations are known only through
rockshelter investigations (Pollack and Henderson 2000). After reduced utilization during
the Middle Woodland period, rockshelters are once again occupied, albeit at a lower intensity
(Applegate 1997). Haystack, Rogers, and Rockbridge rockshelters located in the Red River
Gorge area are the only systematically excavated Late Woodland sites (Cowan 1979;
Gremillion; Applegate 1997). These three sites share several common traits. First, all three
sites are located in nearly inaccessible rock overhangs, suggesting a defensive posture. The
defensive (hidden) settings of these sites seem to reflect interregional instability as do the
nucleated settlements within the Middle Ohio Valley. Cultigens consisting of sumpweed,
maygrass, sunflower, squash, bottle gourd, and giant ragweed are
44
found at Haystack and Rogers; a single Cucurbita seed was recovered from Rockbridge.
Unfortunately, no systematic investigation has taken place along the floodplains of the
Kentucky and Red River drainages.
3.3.4 LATE PREHISTORIC PERIOD
The Late Prehistoric period (1,000-450 B.P.), or alternately the Fort Ancient period,
in the Middle Ohio Valley represents settled village life supported by maize agriculture. The
triad of maize, beans and squash dominates the subsistence base. Many indigenous crops are
supplanted by tropical cultigens, although some plants (such as sunflower) are retained. The
bow and arrow becomes the primary hunting weapon, as indicated by distinctive triangular
projectile points ubiquitous throughout the region. Ceramic wares are thinner walled and
shell tempered. Fort Ancient populations along the larger drainages of the Middle Ohio
Valley constructed circular palisaded villages. Houses were located between a defensive wall
and a central plaza. Large bell-shaped storage pits are often found close to houses.
Fort Ancient occupations in the Red River Gorge were numerous. This is based on
the presence of shell-tempered pottery and triangular project points found throughout the
study area. Wyss and Wyss (1977:35) reported ten rockshelter and nine floodplain sites. No
palisaded village remains have been found in the study area. Rockshelter occupations appear
to be rather ephemeral and of low intensity. Floodplain sites such as 15PO40 (Cowan 1976)
might represent single household units situated along valley margins adjacent to floodplains.
Fort Ancient groups living within the Escarpment might have been organized along the lines
of nuclear families or in hamlets as opposed to villages. In a similar setting, Dunnell (1972)
45
documented several Late Prehistoric villages along the rugged valleys of the Levisa Fork in
eastern Kentucky. The nearest known village site is that of Eskippakithiki 70 km West of
the study area (Beckner 1932; Cotterill 1954:28). The lack of reported Fort Ancient villages
within the Red River drainage has not received systematic evaluation.
The ubiquity of Fort Ancient sites in the study area suggests population increase
following the adoption of a maize-based agricultural practice. Dunnell documented an
expansion of Ohio Valley Fort Ancient groups upstream the Big Sandy River into the Fishtrap
area. Whether the same process occurred in the study area is not completely clear. Evidence
for in situ cultural transition is indicated by the gradual replacement of other ceramic
tempering agents by shell (Wyss and Wyss 1977). However, the triangular projectiles of the
period resemble the more northern Levanna types, suggesting continuity with Fort Ancient
groups in the Middle to Upper Ohio River Valley rather than with those to the south in the
Cumberland River drainage.
3.4 PREVIOUS RESEARCH
Three distinct periods of archaeological research have taken place within the study
area. The first period covers the 1920s and 1930s federal Relief Program work when Webb
and Funkhouser conducted investigations of rockshelters. The second period spans from the
1960s to the 1970s and consists of federally mandated research carried-out for the proposed
Red River Lake. Archaeological work was conducted by Fryman (1967) and Cowan (1975,
1976) under the Federal River Basin Salvage Program. The third period covers the 1980s
to the present. It consists largely of federally mandated Cultural Resources Management
46
(CRM) projects in the Daniel Boone National Forest and of research projects oriented
towards recovering domesticated plant remains from rockshelters.
3.4.1
RELIEF ERA ARCHAEOLOGY (1929-1939)
Formal archaeological research within the study are was initiated by University of
Kentucky professors W. D. Funkhouser and W. S. Webb in 1929. They conducted
excavations of six rockshelters within Lee County. The most important of these sites are Red
Eye Hollow, Little Ash Cave, and Big Ash Rockshelter. These “so-called ash caves”
contained well-preserved normally perishable non-carbonized artifacts including fabric,
cordage, wood, gourds, and leather (Funkhouser and Webb 1929). The following year they
conducted excavations at rockshelters along the south side of the North Fork of the Red
River in the Gorge area (Wyss and Wyss 1977:46). The most important of these sites were
the Dillard Stamper rockshelters No. 1 and No. 2, and the Steven DeHart rockshelter
(Funkhouser and Webb 1930).
In 1935 Webb and Funkhouser (1936) returned to the region and investigated eleven
more rockshelters. The most significant of these sites is Newt Kash rockshelter. Newt Kash
contained significant archaeobotanical evidence for prehistoric subsistence. Some of the
archaeobotanical remains were sent to Volney Jones (1936), an ethnobotanist at the
University of Michigan. Jones identified prehistoric maize from the upper deposits of Newt
Kash. From the lower, older deposits he identified Chenopodium sp. (goosefoot), Cucurbita
pepo (warty squash), Helianthus annuus (sunflower), Iva annua (sumpweed or marshelder),
Phalaris caroliniana (maygrass), and Ambrosia sp. (Jones 1936-148-151). The Newt Kash
47
materials provided further evidence for a prehistoric agricultural tradition. The first such
evidence came from rockshelters in the Ozarks and was studied by Gilmore (Jones 1936).
Even within historical context, Webb’s and Funkhouser’s rockshelter excavations
were unsystematic (Schwartz 1967). Workers merely shoveled archaeological deposits out
of shelters, beginning at the dripline and proceeding to the back wall. Sediments were only
cursorily examined before they were pitched down-slope out of the rockshelters. Revisits to
the rockshelters (Gremillion and Mickelson 1997) indicate that deposits were often churned
in place, resulting in reversed stratigraphy.
Webb and Funkhouser did not maintain
excavation notes. Unlike archaeological work conducted by Webb elsewhere, no vertical or
horizontal control was maintained over excavations. Once materials were brought back from
the field to the University of Kentucky, the collections were poorly maintained and most of
the significant materials have been lost (Wyss and Wyss 1977).
The termination of the first period of research is marked by work carried out at
Hooton Hollow rockshelter in 1939 by W. G. Haag. Haag maintained stratigraphic control,
took detailed notes, and produced maps. Sadly, all of the records of the excavation were
loaned out during World War II and were never returned (Cowan 1975:9-10). Purrington’s
(1967) inventory of lithic tools and Gremillion’s (1995) descriptions of human paleofecal
specimens recovered there constitute the only reports on the site.
48
3.4.2
RESERVOIR AND GORGE ARCHAEOLOGY (1964-1977)
A function of federally mandated reservoir basin surveys, research resumed after a
lapse of 25 years. The first study took place at nearby Cave Run for a proposed reservoir.
Purrington and Smith (1967) documented nearly sixty sites within the proposed Cave Run
Lake flood pool. Test excavations were conducted at several sites: Roberts (15BH7), Zilpo,
and Deep Shelter (Wyss and Wyss 1977:48). Work at Cave Run rockshelters led Purrington
(1967) and Dorwin and Worholic (1970:139) to posit that Adena period occupations were
permanent rather than seasonal. The proposition that Early Woodland occupations were
seasonal had been postulated by Webb and Baby (1957). Purrington’s (1967) thesis was also
the first work to synthesize regional settlement data for the eastern Kentucky mountains.
In 1962, the U.S. Army Corps of Engineers proposed the construction of the Red
River Lake along the North Fork, a sister project to the Cave Run project. The dam and
reservoir were advocated as a flood control project for the towns of Stanton and Clay City
located tens of kilometers downstream (U.S. Army Corps of Engineers 1974:1).
Archaeological survey of the proposed flood pool was conducted in 1966 by Fryman (1967).
Fryman conducted fieldwork for two weeks and located 21 sites. Fryman investigated only
floodplain and valley margin landforms; no rockshelters were investigated. The most
significant site that was inventoried was Seldon Skidmore (15PO17).
Controversy over the proposed Red River Lake project erupted in 1967. Due to
concerns over impact to the Red River Gorge, the location of the earthen dam was moved
almost 9 km downstream. A second reservoir survey was required. Cowan conducted the
49
National Park Service-funded survey over a month and a half in 1973 (Cowan 1975). Cowan
located 21 new sites within the Red River floodplain. He also returned to Seldon Skidmore
and obtained data on site stratigraphy. The following year he conducted follow-up
excavations at Seldon Skidmore and at the Anderson site (15PO31). Work at Skidmore
provided the first data on Late Archaic occupations of the region. In addition to work at
floodplain sites, Cowan also conducted excavations at Haystack rockshelter (15PO47B). At
Haystack he recovered important data regarding Late Woodland cultigen exploitation.
In 1975 Julian Carroll, then Governor of Kentucky, requested that the Kentucky
Heritage Council assess the eligibility of the Red River Gorge for its potential National
Register of Historic Places eligibility. The request was a function of lawsuits filed by
environmentalists and concerned citizens. The lawsuits challenged that the U.S. Army Corps
of Engineers had failed to adequately account for the dam’s potential impact on
archaeological resources within the Red River Gorge (Cowan and Wilson 1977:6).
In the spring of 1975, Mayer-Oakes and Hughes were retained by the Corps to assess
the Gorge’s potential archaeological significance. They determined that the Gorge would
probably qualify as a National Register Historic District. With the cooperation of the Forest
Service, Cowan and Wilson conducted field work in the spring of 1975 within the Gorge.
Over three weeks Cowan and Wilson (1977:13) documented sixteen prehistoric rockshelters
and 34 historic sites, including Cloudsplitter rockshelter. Based upon their survey, the
Kentucky Heritage Council recommended that the entire Gorge be nominated to the National
Register. During the summer of 1975, Turnbow (1976) recorded 35 rockshelter sites and
also recommended that the area be nominated to the National Register.
50
Between the fall of 1976 and the spring of 1977 Wyss and Wyss (1977: viii)
conducted an archaeological survey of 6,000 acres of the newly formed Red River Geological
Area. Their survey recorded 106 prehistoric and 24 historic sites; mainly rockshelters. Their
work represents the first attempt to discern settlement patterns in the study area.
3.4.2
THE CULTURAL RESOURCE MANAGEMENT ERA (1977-2002)
The current period of research is dominated by Cultural Resource Management
(CRM) undertakings. CRM research is an expansion of public archaeology beyond the scope
of the river basin surveys that dominated the last period. The shift to CRM type projects is
due to compliance requirements mandated by federal legislation passed in the 1960s and
1970s. On a localized level, this legislation created archaeologist positions within the Daniel
Boone National Forest to deal with compliance issues.
The shift in archaeological research occurred after 1976, when the Commonwealth
of Kentucky removed its support for the Red River Lake project, effectively scuttling it (U.S.
Army Corps of Engineers 1977:67). For the first time since the 1930s, areas outside of the
Red River drainage received attention by archaeologists. Since the inception of CRM, the
known inventory of archaeological sites has grown from a few hundred to nearly 1,500.
However, as Applegate (1997:44) notes, the CRM boom has been a “mixed bag” in terms of
quality.
In addition to CRM projects, Kentucky Heritage Council, universities, and other
organizations conducted research in the study area. County-wide surveys and other projects
were conducted by the Kentucky Heritage Council in Powell, Floyd, Greenup, Bell, and Knox
51
counties (Weinland and Sanders 1977; Meadows 1977; Sanders and Gatus 1977; Gatus and
Sanders 1978; DeLorenze 1979; Maynard and Gatus 1979; DeLorenze and Weinland 1980).
The Kentucky Heritage Council supported research that also included a resurvey of
rockshelters first examined by Funkhouser and Webb in the 1930s (Gremillion and Mickelson
1997). This survey consisted of revisiting Great Rock House (15LE6), Little Ash Cave
(15LE2), and Red Eye Hollow (15LE1). More significantly, this study also consisted of a
systematic distributional study (siteless survey). Unlike other surveys, all overhangs along
contiguous sections of cliffline were recorded, thus allowing generalizations to be made
regarding the cliffline environmental zone. A total of 113 overhangs was documented; 21
contained evidence of prehistoric occupation.
In the early 1980s Daniel Boone National Forest Service archaeologists conducted
numerous surveys and excavations. The surveys were completed for compliance purposes
for timber sales tracts, logging roads, land exchanges and recreation facilities. Knudsen
(1983) returned to the Big Sinking drainage for the first time since Funkhouser and Webb
worked there fifty years earlier. Within Lee County Knudsen documented several rockshelters
including Cold Oak and Pine Crest. Ison (1988) and Gremillion (1993, 1995b) conducted
excavations at the Late Archaic period Cold Oak rockshelter. Ison and Faulkner (1995)
returned to the Big Sinking Drainage to monitor archaeological sites first documented by
Knudsen. In the process they tested Mounded Talus rockshelter. National Register evaluation
of Mounded Talus was conducted on the Middle to Late Archaic deposits in 1995 (Gremillion
and Mickelson 1996). Multi-disciplinary research conducted at Cliff Palace Pond to the south
in Jackson County provided crucial palynological data regarding the presence of cultigens in
52
the uplands (Delcourt et al. 1998). Gremillion et al. (1999) conducted research at
Courthouse Rock rockshelter located near Haystack rockshelter excavated by Cowan in the
mid-1970s.
Considerable academic research has also taken place during the current period.
Cowan’s (1984, 1981, 1979) excavations oriented toward agricultural origins at Cloudsplitter
rockshelter were funded by the National Science Foundation (NSF). National Geographic
funding allowed Gremillion (1995) to return to Cold Oak rockshelter to conduct detailed
paleobotanical research on cultigens at the Late Archaic-Early Woodland interval. Applegate
(1997) conducted a detailed lithic analysis on materials from Cold Oak and Rockbridge
rockshelters. She determined that Early Woodland occupations were more intense than Late
Woodland habitations. Further, she argued for conducting studies regarding settlement
practices outside of the rockshelter realm. K. Mickelson (2002) conducted studies of
geochemical issues regarding the preservation of organic materials in dry rockshelters at
Mounded Talus rockshelter. In 2000 and 2001, Gremillion returned to Seldon Skidmore,
Anderson, 15PO46, and 15PO42 first excavated by Cowan (1975, 1976). Her NSF fundedresearch was oriented toward studying cultigen utilization outside of the rockshelter environs.
53
3.4.3
SUMMARY OF PREVIOUS RESEARCH
After seven decades of research, little is known concerning the distributions of
archaeological deposits outside of the rockshelter environment. Over the last three decades,
greater knowledge of rockshelter deposits comes from technological and methodology
advances applied to them. Notwithstanding archaeobotanical and radiometric advances,
research questions addressed in the region surprisingly have advanced little beyond that of
Jones (1936), with a few exceptions (e.g., Gremillion 1995; Cowan 1984). For example,
issues concerning the impact of cultigens upon the subsistence system beyond Late Archaic
or Early Woodland contexts have been inadequately addressed. Changes in settlement
practices have only received speculative work because archaeologists continue to be
enamored with rockshelter archaeology. Only incidentally, because of CRM and other federal
mandates, has any information beyond the rockshelters been obtained. The only exception
is Gremillion’s NSF-funded research. Much of the settlement data for floodplain settings
stem from research projects related to reservoir related work nearly thirty years ago. The
result is a crude database that lacks systematically collected data. Despite these problems, the
sheer volume of information collected primarily through CRM projects might yet yield some
insight to settlement patterns.
54
CHAPTER 4
THE ARCHAEOLOGY GIS DATABASE
This dissertation employs previously collected archaeological data. The data were
collected not by the author, but by archaeologists working in the region over the last 75 years.
The data were compiled in such a manner as to address the question of settlement change.
Specifically, settlement practices are examined with respect to existing evidence of alteration
of the subsistence base during the Late Archaic period. An archaeology GIS database was
created from existing archaeological literature and from data provided by the Kentucky Office
of State Archaeology.
General details of the database construction and contents were
already described previously (Chapter 2, Research Design). The goals of this chapter are to:
(1) discuss the approach to the data; (2) provide the salient features of the databases; and (3)
discuss the capabilities and limitations of the databases.
4.1 APPROACH TO THE DATA
The goal of this research is to understand how humans extracted resources from the
environment. Therefore, the focus of this study is upon determining if there are changes in
how the archaeological record is patterned vis à vis the environment. If a shift in settlement
practices is documented, it might constitute independent evidence for the impact of cultigens
55
on the prehistoric lifeway. That is, barring the influence of some process other than change
in subsistence practices. Settlement pattern data have the potential to corroborate the
archaeobotanical and paleoenvironmental databases in documenting the impact and trajectory
of subsistence change through prehistory in the study area.
Since the research question being addressed employs an economics-based explanatory
framework, archaeological site data are examined within their environmental context. That
is, human decisions regarding resource acquisition are evaluated. The approach taken here
is deductive. A deductive approach does not employ the distributional data of archaeological
deposits in a predictive manner per se. Rather, this avenue of research attempts to infer the
overall behavior system that led to the selection of a particular location by humans. Kohler
and Parker (1986:432) state that for the deductive approach to work, mechanisms governing
human locational decisions must be accounted for. Site selection decisions are thought to be
primarily economic-based, with the goal being to meet basic subsistence requirements.
Therefore, the environmental component of a given site may indicate how humans solved
subsistence requirements. The distributional qualities of archaeological deposits across the
landscape might display patterning. This patterning may be inferred to indicate how humans
organized themselves to solve a variety of subsistence needs.
4.2 ARCHAEOLOGY GIS DATA TYPES
The archaeology GIS database contains two components. One component is the
relational database containing rows and fields (columns) in which site attributes are codified.
The second component consists of vector data layers delimiting site locations. Generally
56
speaking, vector data are points, lines, or polygons. The archaeological data in this study are
either polygons or points. In this case, points are centroids of polygons. Centroids are
calculated by creating a bounding-box around each polygon and calculating the center of the
bounding box. Centroid point coverages are label point features as discussed earlier. The
advantage of label point coverages is that different symbols or sizes of symbols are draw
upon to convey information. Label point features might use different sizes of dots to express
the relative number of lithics at sites. Or, different symbols such as squares, circles, and
triangles might represent different types of ceramic tempering agents for ceramics distributed
across the landscape.
Delineating archaeological site data as polygons rather than points has several
advantages. The primary advantage is due to the fact that polygon data have the added
dimension of area expressed spatially while point data do not. Although polygon areas may
be transferred to database files and stored in a field with other point data, points still do not
convey the horizontal extent of a site. Site attribute data stored in attribute tables (databases)
can be shared between label point and polygon features.
4.3 ATTRIBUTES OF ARCHAEOLOGY DATABASES
An objective of this study was to collect as much information on the region’s
archaeology as possible in order to create a detailed archaeology GIS database.
The
backbone of this study’s database is the spatial information coded within a database supplied
by the Kentucky Office of State Archaeology (OSA). Though the OSA database contained
reliable spatial information, it lacked details regarding artifact recovery at those site locations.
57
The OSA archaeology database contained fields for each archaeological site which consisted
of five main categories: (1) space; (2) time; (3) archaeological characteristics; (4)
environment; and (5) record keeping-- federally mandated information. Spatial information
for each site (comprising a single row) consisted of Universal Transverse Mercator (UTM)
coordinates: The UTM Zone, Easting (X), and Northing (Y) were provided as individual
fields. Additionally the database file is linked to a vector data layer which contained polygons
delineating site boundaries.
Temporal attributes for each site were also coded into fields following colloquial
temporal divisions. Fifteen fields covered the following periods: (1) Paleo Indian, (2) Early
Paleo Indian, (3) Middle Paleo Indian, (4) Late Paleo Indian, (5) Archaic, (6) Early Archaic,
(7) Middle Archaic, (8) Late Archaic, (9) Woodland, (10) Early Woodland, (11) Middle
Woodland, (12) Late Woodland, (13) Late Woodland--Mississippian, (14) indeterminate
prehistoric, and (15) Historic. No radiocarbon data are included, nor are lists of temporally
sensitive artifacts recorded in the database.
A site’s span of occupation is presumably
determined upon these types of index fossils and radiometric data; though there is no way of
knowing from the fields within the OSA database.
Several fields coded for archaeological attributes previously recorded on paper
inventory forms. One of these attributes is site type, such as rockshelter, open air, mound,
cave, etc. A second set of fields are coded for phase or “archaeological culture” designations;
a third field coded for site area. The fourth type of data present in field form consists of site
environmental characteristics. However, because of the lack of metadata (information about
how data how were acquired or created), much of the environmental data is of dubious
58
quality. The lack of detailed information on how the environmental data were acquired or
generated rendered them of little utility. Environmental fields included: (1) facing aspect, (2)
soil association, (3) physiographic province, (4) slope, (5) general landform type, and (6) type
of nearest source of water (e.g., pond, stream, ephemeral stream, etc.).
The last type of data in the OSA database consists of record keeping and management
related fields. These fields include: (1) research institution responsible for collection of data,
(2) location of collections, (3) reliability of information, (4) National Register of Historic
Places determinations, and (5) ownership status. Most of these fields within the OSA
database do not pertain to the research question and were excluded.
4.3.1 THE SPATIAL ANALYSIS DATABASE
To address the research question proposed in Chapter 1 of this dissertation, a spatial
analysis database had to be created. The spatial analysis database provides data pertinent to
identifying changes in settlement practices. The spatial analysis database appropriated the
identification code (trinomial site designation code), spatial fields, temporal fields, and site
type data from the OSA database. Since the OSA database lacks information pertaining to
the type of artifacts found at a particular site, relevant data had to be entered by hand. Seven
individual databases were created to systematically encode the archaeological literature into
a format appropriate for GIS analysis. The seven databases (Table 3) consist of: (1) portable
lithic artifacts; (2) non-portable rock features; (3) prehistoric ceramics; (4) biotic artifacts;(5)
modified biotic artifacts; (6) chronological data; and (7) a spatial analysis database. The
spatial analysis database was created by selecting fields from one of the above six databases
59
or the OSA database. The fields that were selected for the spatial analysis database contained
data pertinent to the research question. Additionally, environmental data were added to the
spatial analysis database. These environmental data were created specifically for the research
project and are discussed in the following chapter.
Several problems were encountered in the development of the archaeological
databases.
The first problem concerns the idiosyncratic nature of the reporting of
archaeological data over the last several decades. Different recovery goals, field methods, lab
methods, and technologies have produced databases that vary widely in quantity and quality.
A second problem is that the archaeological data reported could not be double-checked;
hundreds of collections would require reevaluation. A third problem is the fact that the
“rockshelter bias” has led to an uneven coverage of the study area’s landsurface. As a result,
the spatial extent of the database is limited. Fourth, most of the data were recovered from
surface survey contexts and lack temporal resolution. Surface acquired data also are biased
towards more durable items, primarily lithic artifacts. Nearly 100 temporally unassigned
lithic scatters were removed from further consideration. Fifth, the data available in a variety
of different documents are not systematically reported. Lastly, the available data are subject
to local idiosyncracies in terms of typological units. Classificatory problems stem from the
traditional lack of developing formal class definitions; stipulations for membership are not
generally provided.
Despite these problems, 413 archaeological sites3 were coded into
databases.
3
An archaeological deposit is anything whose locational or formal attributes are the
products of human activity.
60
The GIS databases were created in three stages. The first stage consisted of acquiring
archaeological data with the necessary spatial attributes. Stage two consisted of transcribing
the archaeological literature into a tabular format compatible for GIS manipulation.
Transcription consisted of examining existing archaeological literature and creating databases
with appropriate fields. Sixty-five fields were created. For ease of data entry and
manipulation, the fields were split among the seven aforementioned databases (Table 3).
Each of the databases could be linked or joined with another database via the site
identification code number originating from the OSA database. Different field attributes were
coded via an alpha numeric system to allow for database querying. Lastly, code sheets for
each database were created.
Code sheets consist of lists of alpha-numeric designations for attributes within each
field that was created. Within the ArcView environment several different types of analytical
procedures may be employed. These procedures require data that are consistently coded.
Analytical operations included data querying and data calculation routines. Querying
operations employ the logic of set theory. Calculation routines utilize algebraic expressions.
Query operations may be performed upon data that are either string (word or character) based
or either numeric in format. Map calculations require numeric data. Examples of string data
fields include artifact type, bibliographic citation, raw material type, and lithic artifact type.
Examples of numeric data are site area, distance to water, facing aspect, and elevation.
The portable lithic artifact database consisted of nineteen fields including the site
identification number. Lithic debitage and flakes were coded into a debitage field; lacking
density data for most sites, total counts were recorded in this field. Debitage raw material
61
type constituted a separate field. Chipped-stone lithic artifacts above the level of waste
material were divided into two separate groups. One group consisted of bifacially modified
artifacts. Bifaces were defined as having flake scars on their dorsal and ventral sides forming
two primary faces, extending to meet to form a single edge. Artifacts traditionally termed
bifaces, spear points, arrowheads, projectile points, adzes, hoes, and axes were placed in this
field. Artifact type designations denoted by researchers were retained in the code sheet
system. For temporally sensitive bifaces, a field was created to code for the temporal
information. The traditional ordinal scale time interval designations as used in the OSA
database were retained in this field, but were coded differently. The last two fields relating
to bifaces consisted of counts and raw material type. The secondary lithics field accounted
for non-bifacially chipped lithics artifacts and groundstone artifacts.
The following
colloquially termed artifacts were included in the secondary lithics field: modified flake, core,
graver, nodule, chunk, uniface, spokeshave, hammerstone, fire-cracked rock, abrader, nutting
stone, perforator, pipe, grooved axe, celt, adze, hafted end scraper, drill, chopper-core, mano,
metate, and anvil. Another field was created to keep track of the number of each secondary
lithic artifact from a particular site. A bibliographic citation field was maintained to track the
origination of the information for each entry. The citation field became critical when multiple
researchers conducted studies at the same site. Lastly, a diversity field was developed to
track the number of different items at a site.
The non-portable rock feature database contained records for sites with bedrock
mortars, pecked depressions, and petroglyphs. Fields in this database consisted of bedrock
mortar count, petroglyph count, and account of other depressions. Fields for petroglyph
62
motif types were also created. These motif types were broken down into geometric forms,
tracks (e.g., human footprints or bird tracks), and lastly depictions of organisms (plants,
insects, mammals).
A third database consists of a record of prehistoric ceramics reported from sites within
the study area. The fields for the ceramics database included count, tempering agent, surface
treatment, and temporal designation. The temporal designation used the same code system
as the portable lithics database. The fourth database consisted of fields relating to nonmodified biotic materials recovered from archaeological deposits. Fields pertaining to faunal
remains include species, element recovered, and number of fragments. Fields for floral
remains from sites included species, plant part, domesticatory status, and count. The fifth
database contained fields pertaining to biotic materials that contained evidence of human
modification. Fields for the modified biota database included the species, the nature of the
modification (e.g., drilled, leather, split, polish), and what portion of the animal was used.
Fields for modified floral remains included the nature of modification, the taxa, and what
portion of the plant was used.
The final database consisted of a chronology database. Once data entry and error
checking were completed on the above databases, sites with temporally diagnostic artifacts
were compiled into a single database. Time interval assignments used the traditional period
and sub-period designations (e.g., Early, Middle, and Late Woodland periods). Temporal
assignments were made on the presence of radiometric dates and temporally sensitive artifacts
such as ceramics and lithics. The chronology database contained information in up to seven
fields concerning times of occupation for multicomponent sites. Comparing overlapping sites
63
in the chronology database to sites in the OSA archaeology database, temporal resolution for
OSA data was improved by nearly 50 percent. The implication being that not all available
temporal data is codified in the OSA database that exists for each site.
A spatial analysis database was compiled from the above seven databases and from
data acquired via environmental data layers developed for this dissertation. The spatial
analysis database contained 319 sites with temporal attributes. Along with fields for temporal
attributes, the spatial analysis database contained fields concerning the environmental setting
(e.g., facing aspect, elevation, slope, insolation values, distance to water, and ecological
setting), and fields concerning site type (e.g., mound or rockshelter), and site area.
Environmental variables were “captured” from coverages created specifically for the study.
64
CHAPTER 5
GIS MODELS OF THE ENVIRONMENT
This chapter presents the environmental data layers created explicitly for this study.
Within the research design, the environmental data were merely described. The goals of this
chapter are to describe: (1) what GIS models of the environment exist in the public domain;
(2) how they are acquired, constructed, and manipulated; and (3) the role of environmental
data in distributional analysis.
5.1 DATA TYPES AND PROCESSING CONSIDERATION
As discussed earlier, there are two types GIS data coverages; raster data and vector
data. Each type has its respective limitations and advantages (Maschner 1996). Recall that
raster data are grids or lattices that contain cells. Each cell or grid square contains a single
value that stands for a particular variable. Columns and rows in raster data contain coordinate
information for the environmental values. Vector data are comprised of points lines and
polygons. In the past, vector and raster data were incompatible. GIS software packages
were either raster-based or vector-based. From a methodological standpoint was thought that
conversion between data types was not possible. Today software packages like ArcInfo and
ArcView allow for the conversion between the two data types. As Maschner (1996:4)
observes, most archaeological applications in the past employed the raster approach
65
due to it low cost. But the raster approach also has quantitative advantages desirable to
archaeologists (e.g., Kvamme 1992). Most environmental data acquired for this study are of
the raster configuration.
Another consideration of data types is that of scale or resolution in relation to
hardware capabilities. As resolution is increased, the data become larger in scale. A
consequence of the increase in resolution is greater size, hence storage and manipulation
requirements increase. Larger coverages, have greater storage and processing demands. At
the present level of technology, for this type of study, hardware constraints at the desktop
computer scale is not an issue. As this project was conceived, reliable GIS processing on a
desktop personal computer (PC) was just becoming available; previously larger mainframe
platforms were required. Today GIS can be deployed in the field on hand-held or laptop
computing devices. Processing speed is also no longer a limitation for large-scale analysis.
Analyses that previously took days (e.g., Machovina 1996) of processing time are now
completed in a matter of minutes. GIS analysis for this study was completed on a PC with
circa 1997 technology; 255 megahertz Pentium processor, 64 megabytes of RAM, and eight
gigabytes of storage space. Processing of some very high resolution large-scale data layers
for the entire study area were prohibited from analysis due to storage and processor speed
limitations. The raster data are at a 30 m cell size.
66
Most environmental data for this study were available at no cost via the internet. The
data that were available for processing were those at a 1:24,000 and smaller scale generated
by the United States Geological Survey (USGS), the Kentucky Geological Survey, and the
Kentucky Water Resources Cabinet. Other data were available at minimal cost via the above
agencies and were supplied on CD-ROMS.
5.2 VECTOR ENVIRONMENTAL DATA
Two vector data layers were employed in this study for environmental modeling and
analytical purposes. The first data layer consisted of hydrography data in Digital Line Graph
format (DLG). The DLG hydrography data consisted of streams, ponds, and other sources
of surface water. The hydrography data were produced by the USGS via digitizing
hydrographic information from existing 7.5 minute paper quadrangle maps (Figure 4). The
second data layer consisted of bedrock and Quaternary geology. The geological data was
acquired via digitizing paper 7.5 minute geological quadrangle maps by the Kentucky
Geological Survey. Both coverages are 1:24,000 in scale. The hydrography layer created
from USGS DLGs consists of lines. The geology layer consists of polygons.
After the hydrography coverage was converted from DLG format to ArcView format,
it was used obtain distances from archaeological sites to water. Simple routines in ArcView
allow the determination of linear distance from one particular type of feature to another. The
data were then stored in a relational database. The data were employed in two ways. First,
simple linear distance could be used. Second the distance to water field was categorized into
50 m intervals for analytical simplification.
67
The geology data were supplied via CD-ROM from the Kentucky Geological Survey.
Coverage of the study area by the geology data had only occurred by 2001 and sample data
were provided to the author. The data layer contained polygons delimiting the locations of
Quaternary alluvium along with bedrock geology. The Quaternary alluvium data were
selected and extracted to create a new layer, simply termed alluvium. The distance to
archaeological sites from alluvium could then be determined. Additionally the amount of
alluvium within a given radius could also be obtained through map algebra calculations within
ArcView Spatial Analyst.
5.3 RASTER ENVIRONMENTAL DATA
Raster coverages provide an analytically more robust format for archaeological
analysis (Maschner 1996:4). The cell-based configuration the raster format allows for easier
quantitative analysis. Environmental data are often termed the background in archaeological
studies (Kvamme 1992). A raster background dataset, from the statistical perspective
represents a “cumulative distribution of a continuous variable over the entire area of study”
(Kvamme 1992:128). Therefore, the background distribution of archaeological sites may be
contrasted against the entire distribution of the variable across the study area. Environmental
data, since all values are known, can be treated as a universe from the sampling standpoint.
Trends in archaeological site location can be evaluated with the overall distribution of a
particular variable in the background. Statistics are employed to determine whether the
distribution of archaeological sites varies significantly from the background environment.
68
The variable facing aspect provides a good demonstration of the statistical advantage
of the continuous nature of background data. Presumably south-facing landforms (in the
Northern hemisphere) provide thermal properties which are advantageous to humans in winter
months in temperate climates. Additionally, landforms receiving greater levels of insolation
(solar radiation) might also contain greater amounts of biomass. Therefore, the location of
sites located in these richer resource areas might be expected to occur.
Consider two hypothetical examples as an illustration. The first hypothetical situation
is where 70 percent of archaeological sites face south, while the background contains south
facing landforms at the same frequency. In first case, no reliable statement may be made
regarding facing aspect as a site selection criterion in prehistory; both the archaeology and
background coverages possess the same distributions. The second hypothetical case is one
where 20 percent of the background is south facing, while 80 percent of archaeological sites
contain south facing aspect values. In the second example an argument might be made for
prehistoric populations selecting landforms with south facing characteristics this trait is
desirable for some reason.
Another advantage of raster data is that they lend to easy data manipulation and
classification. Raster data layers may be manipulated via a map calculation utility which
allows for the generation of new land units from existing data. The map calculation and data
querying utilities employ mathematical set theory and algebraic equations for these operations.
The resulting land class units are unambiguous and their requirements for membership are
explicitly stipulated. ArcView Spatial Analyst map algebra routines were derived from
ArcInfo software, which is theoretically based upon work by Tomlin (1990).
69
5.3.1 DIGITAL TERRAIN MODELS
There are several options available for digitally modeling a landsurface. Beyond the
raster and vector formats, there are also the more robust Triangular Irregular Networks
(TINs). Ideally, TINs require vector (contour line) data for their construction. Hypsography
(contour line) data at 1:24,000 scale did not exist at the time data were acquired for this
study. Raster format Digital Elevation Models (DEMs) for the study area were available and
were acquired for the creation of Digital Terrain models of the study area (Figure 4). DEMs
are produced by sampling contour data on paper quadrangle maps through a scanning or
digitizing process.
United States Geological Survey DEMs were acquired via the internet. DEMs were
then converted in ArcView GRID raster format. USGS DEMs (prior to 2002) were
produced as tiles which covered the same extent as 1:24,000 USGS quadrangle maps. The
USGS 1;24,000 DEM data have a cell size of 30 m square. USGS DEM tiles required
merging to cover the study area. Once the tiles are merged together and cleaned for
anomalies and edge matching problems, a seamless elevation data layer is produced. From
this base layer several other data layers may be generated.
70
5.3.2 DIGITAL ELEVATION MODEL DERIVED COVERAGES
As noted above, several different types of data layers may be produced from DEMs.
The layers that may be produced from DEMs include, but are not limited to: slope, facing
aspect, stream networks, insolation, ecology, and landform type. The data layers produced
for this study are: (1) slope, (2) facing aspect, (3) insolation, and (4) ecology. Most of the
aforementioned coverages require a slope grid to be produced first.
In ArcView Spatial Analyst, slope coverages either in percent or degrees, are
calculated via the nearest neighborhood operation. The default neighborhood setting in
ArcView is a 3 by 3 cell moving window. In this case, the neighborhood is defined as the
eight cells that surround the center cell in the window. The roving window which calculates
slope based upon changes in elevation. A positive slope value for each of the center cells in
the window is obtained and stored in a new coverage; in this case, slope in degrees.
Once a slope data layer is constructed several other data layers, either totally or
partially, may be produced. Slope layers contain two important pieces of data. Beyond the
value for the slope itself, the data layer also contains coordinate information. The two pieces
of data serve to derive directional grids. Examples of directional raster grids include facing
aspect, flow direction, and insolation. A facing aspect grid in ArcView is obtained by using
coordinate and slope values to determine the direction that a given landform (cell) is oriented.
The direction that a cell is facing is reported in degrees from Grid North. For hydrographic
modeling, and the creation of stream networks, a flow direction grid can be created. The flow
direction grid specifies the downhill direction that water would flow. Insolation grids can be
71
produced by accounting for the location of the sun at a specific time of day and year. The
data pertaining to the sun’s location is then applied to the facing aspect grid to obtain an
energy value. The energy value corresponds to the level of intensity of sunlight hitting a
particular location.
Other models that may be constructed include viewsheds and cost surfaces. From
viewsheds, lines of sight between locations may be determined. Or, the area visible from a
site can be determined. Cost surfaces are principally derived from slope, or other impedance
surfaces (like vegetation or hydrology). Cost surfaces can model the degree to which other
landforms are accessible from a particular location facing a given direction. Additionally,
least cost paths between two locations can be modeled (e.g., Machovina 1996). One
application of the least cost model would be the prediction of prehistoric trail networks.
5.3.3 AN ECOLOGICAL MODEL OF THE STUDY AREA
An ecological grid coverage was created by utilizing the variables of slope, elevation,
and facing aspect. The purpose of creating an ecological model was to contend with the
rockshelter bias discussed previously. Nearly 65 percent of the sites recorded for the study
area are in rockshelter contexts. In an attempt to better evaluate prehistoric locational
preferences an ecological layer was created. Sites need not be classified either as open-air or
as rockshelters. Nor must they solely be evaluated along classes of slope, elevation, facing
aspect, and distance to water. Sites may also be evaluated through a combination of some
of the above mentioned background variables, hence the ecology grid.
72
By combining the variables slope, facing aspect, and elevation via map algebra
calculations, an ecology coverage was created (Figures 5 and 6). Through the manipulation
of the above three variables, the botanical zones recognized by past vegetational surveys are
modeled (Braun 1950; Thompson et al. 2000). The primary benefit of the ecology coverage
is that rockshelter sites may be examined with respect to several different ecological zones;
rockshelters are not relegated to a “cliffline stratum” per se. Rather rockshelter sites may be
found in a variety of environmental contexts. The ecological model is most appropriate for
areas near the Red River drainage system, as it gradually loses predictive power toward the
south and west of this area. Precedence for a model such as this may be found in descriptions
of the study area by Wyss and Wyss (1977).
As noted earlier, differential weathering of bedrock controls for much of the variation
in the study area’s terrain. Since bedrock strata are oriented nearly horizontally and are
“stacked” one upon each other, elevation is one variable that can be used to model the terrain.
Differential weathering affects a landform’s slope. Further, the facing aspect of a slope
influences how much a landform is affected by weathering (e.g., freeze-thaw cycles).
Therefore, the variables slope and elevation combine to create a new coverage.
This
ecological model facilitates a second way in which to examine the location and distributional
characteristic of archaeological deposits. The coverage is termed an ecological coverage
because it is based upon the geological characteristics of the study area. The area’s terrain
is controlled by the underlying geology. The configuration of the terrain also plays a role in
how biotic resources are distributed.
73
Five strata comprise the ecological grid coverage (Table 4). Four substrata for each
of the five strata may also be delineated upon the basis of facing aspect. The four substrata
are not employed in this study. The five strata of the ecological grid are: (1) low level land;
(2) lower slope; (3) mid-slope; 4 upper slope; and (5) upper level land.
The low level
land stratum is defined upon the basis of slope being less than five degrees and elevation is
less than 310 m. Nearly 18 percent of the study area falls within this class. This stratum
captures most of the larger sections of floodplain along larger drainages within the study
area. Low level land mainly consists of areas of Quaternary alluvium. From the biotic
standpoint, this stratum contains the Riverine Forest regime of floodplain and wetland flora
and fauna. Small portions of slopes along the valley margin, including colluvial slopes, are
within this stratum. Therefore, a small amount of the stratum also contains Mixed
Mesophytic flora and Lower Slope fauna. Open-air sites are predominately found within this
stratum.
Proceeding up the profile in elevation, the lower slope stratum is encountered next.
The lower slope stratum is defined upon the basis of having an elevation of over 310 m and
a slope of greater than five degrees. About 28 percent of the study area consists of the lower
slope stratum. The lower slope stratum contains small portions of the floodplain along its
boundaries adjacent to the low level land stratum. Primarily, the stratum consists of steeper
colluvial foot slopes and slopes resting upon Borden Formation shales. From the biotic
perspective, the lower slope stratum consists of Mixed Mesophytic flora and associated fauna.
74
The mid-slope stratum comprises approximately 19 percent of the study area. This
stratum is defined upon the basis of having a slope of greater than five degrees and elevation
of between 310 m and 348 m. From a geological standpoint, this stratum consists of Breathitt
Formation and Corbin Sandstone bedrock. Within this landform class falls most of the
region’s rockshelters, although some of the upper strata also fall within this stratum along its
boundaries due to averaging routines in GIS. From the biotic standpoint, this stratum consists
of Gorge Area flora (as defined by Braun 1950) and its associated fauna. Areas of lesser slope
values within this stratum may be miss-classified, again due to averaging of slope values
between grid cells.
Upper slope stratum landforms makeup about 17 percent of the study area. Definition
of the Upper Slope stratum is upon the basis of slope being greater than 5 degrees. Elevation
values are over 348 m. Bedrock within this unit consists of rocks belonging to the Breathitt
Formation and Corbin Sandstone members. Upper slope landforms usually contain Mixed
mesophytic plant communities and their associated faunal assemblages. The upper slope
stratum also contains a high proportion of the region’s rockshelter sites.
Intermingled with and above the mid-slope and upper slope strata is found the upper
level land stratum. Upper level land is defined upon having an elevation of 310 m or more
and of possessing slope values of five degrees or less. Nearly 18 percent of the study area
falls within this class. Upper level land landforms mainly consist of plateau remnants or
ridgetops. Flora within this stratum (on ridgetops) is mostly made-up of the upland forestheath type. However, areas of the Mixed Mesophytic type may also be found within this
75
stratum. This stratum also contains benches and saddles not associated with the upper-most
level plateau remnant. Open-air sites and a few rockshelters fall within this stratum.
Diachronic considerations for the ecological model consist of changing
geomorphology and consequent biotic responses. The ecological model is probably most
appropriate for the period from the end of the Middle Holocene to the present (Table 5).
However, the model might retain utility for earlier portions of the Holocene. The primary
changes that occurred have been discussed in the background section regarding the study area
environment. The main points to reiterate are the processes of upland erosion and floodplain
aggradation; both occurred during the end of the Pleistocene and continued through to the
Middle Holocene. Considerations of these processes and their consequences are covered in
Table 5. Despite the fact that the strata are spatially defined, their composition in temporal
perspective contains a degree of flexibility.
5.3.4 OTHER BACKGROUND DATA
Other background data employed for visualization but not analytical purposes
consisted of raster format graphic files. There are two main types of raster graphics. The first
image type is known as a Digital Raster Graphic (DRG). A DRG consists of pixels or cells
of a given size resolution. In comparison to DEMs for example, the pixel can code for a
particular color as opposed to an elevation value. Scanned images of 7.5 Minute USGS
Topographic Series maps are DRG files. These files vary in pixel resolution; earlier scanned
76
files generally are lower in resolution as compared to later, second generation images. DRGs
are georeferenced to a variety of projections and coordinate systems. The USGS originally
produced DRGs which were georeferenced to the UTM coordinate system.
The second type of image data that facilitates visualization of the landscape consists
of Digital Orthographic Quarter Quadrangles (DOQQs). These files are the digital equivalent
of Photo-orthographic Quadrangles produced by the USGS for the generation of 7.5 Minute
Series Topographic maps. DOQQs consist of digital aerial photographs that have been
rectified to remove distortions in the photographic process. Distortions arise as one moves
away from the center of the photograph; objects are viewed from an angle rather than from
directly overhead. Splitting the traditional quadrangle map into four tiles has the advantage
of reducing the distortion problem. It also facilitates the storage and transfer of large digital
data files; original USGS DOQQs for a single 7.5 Minute Quadrangle consumed
approximately 100 megabytes of space. DOQQs are of the one meter level resolution. This
means that each pixel represents one square meter on the ground. Like DRGs, DOQQs are
also georeferenced to a variety of projections and coordinate systems; mainly the UTM
system.
The utility of image data like DOQQs and DRGs is in the verification process during
model building, error checking of site locational data, and checking the accuracy and
reliability of other GIS data layers. During the process of model building the GIS analyst
needs to confirm that the model being constructed does resemble reality. The image files
provide a non-fieldwork method of accomplishing this task by comparing data layers visually.
77
In the case of the OSA archaeological site data, site locations and their extent were
coded from USGS 7.5 Minute Series Quadrangle maps. Centroid points of site polygons
were then captured and used as the locational reference fields in the database file. This
method was used rather than employing UTM coordinates reported on site inventory forms
due to their high level of inaccuracy. The image data also were employed to ensure that other
data layers were properly digitized or projected.
5.4 ANALYTICAL APPROACH TO THE DATA
The environmental data, whether vector or raster, serve as the background to the
distribution of archaeological data across space and through time. The archaeological
database for this particular study essentially constitutes a grab or haphazard sample of the
area’s archaeological record (Orton 2000), whereas the background databases are continuous
distributions of particular environmental parameters across space. Since the background data
are continuous across space, they may be considered in statistical terms as the sample universe
as discussed previously (Kvamme 1992).
Conceived of as such, distributions of
archaeological sites may be compared with the distributional characteristics of a given
environmental parameter.
In the next chapter distributions of the discontinuous
archaeological database are generated and compared vis à vis background layers. The goal
of this evaluation of the distributional characteristics of the archaeology and environment is
to determine whether or not settlement patterns changed through time.
78
CHAPTER 6
DISTRIBUTIONAL CHARACTERISTICS OF ARCHAEOLOGICAL DEPOSITS
This chapter presents the results of the spatial analysis of the archaeological database
with respect to the environmental coverages. The results of spatial analysis of the
archaeological database are presented in several formats including tables, histograms, and
centered bar graphs. Additionally descriptive statistics of archaeological site distribution with
respect to the environment are presented. The distributional patterns observed as a result of
this analysis indicate that a change in settlement practices occurred concomitantly with an
alteration in subsistence patterns. Shifts in settlement patterns through time are tracked via
three variables: (1) site area; (2) diversity of artifacts present; and (3) per period site counts
within each ecological stratum. First, this chapter examines environmental attributes of sites
in the spatial analysis database. Second, this section discusses archaeological attributes within
the spatial analysis database.
79
6.1 ENVIRONMENTAL CHARACTERISTICS OF ARCHAEOLOGICAL SITES
Several trends regarding the locational characteristics of archaeological sites and the
background were observed. The following discussion pertains to all archaeological sites
(n=319) within the spatial analysis database for all periods. Background variables that are
evaluated include: (1) elevation; (2) slope; (3) facing aspect; (4) distance to water; (5) and
ecological setting. Tables 6 and 7 and Figures 7 through 12 present descriptive statistics
regarding archaeological site environmental characteristics.
Evaluation of archaeology
against the environment in a broad manner serves to illuminate the salient features of the study
area. Further, a general examination of key variables provides a foundation for examining
distributional trends through time.
Two variables, elevation and slope, were obtained from the 30 m cell size DEM
coverage for the study area. Mean elevation for archaeological sites is 323 m above mean sea
level as opposed to 310 m for the background (Table 6, Figure 7). The higher mean elevation
for archaeological deposits probably reflects the rockshelter bias in the database. A one
sample t-test was performed on the data, where the population mean from the database of
cells was used, as discussed by Kvamme (1990:373). At "=0.05, with critical t value of
1.968, a t value of 4.34 indicates that the elevation of sites does significantly deviate from the
background environment. Nevertheless, higher mean elevation does indicate that many sites
are located in upland settings.
80
A slope grid coverage was calculated from the DEM. Slope values were calculated
in degrees. Mean slope for archaeological sites is 7.3 degrees while the background is 8.2
degrees. Over 50 percent of the archaeological sites in the sample possess slopes of less than
six degrees (Figure 8). As with the elevation data, a t-test was run on the slope data. At
"=0.05, with critical t value of 1.968, a t value of -2.331 indicates that the slope of sites does
significantly deviate from the background environment. These data support the notion that
level land is a desirable site characteristic.
Archaeologists often employ facing aspect as a measure of a landform’s exposure to
solar radiation. In fact, facing aspect is only a measure of the orientation of a sloped land
surface. Insolation is a measure of the amount of solar radiation that a particular landform
receives. Archaeologists often assume that facing aspect values indicating a more southerly
site orientation means that the location receives more solar radiation. This may be true, but
the measure does not account for a location’s viewshed (i.e., hills or other impediments may
block sunlight). Nor does facing aspect account for annual changes in the location of the sun
with respect to the earth. The variable facing aspect serves as a proxy for insolation values.
In temperate climates and where access to landforms where solar radiation is uneven across
the landscape, south-facing landforms might be a locational factor considered by prehistoric
populations.
In mountainous terrain, agricultural societies might select south-facing
landforms to locate gardens or fields. Such settings might provide protection against frost
damage to crops. Landforms receiving greater insolation will also encourage plant growth.
81
Vegetational surveys (Thompson et al. 2000, Braun 1950) observed that there are
distributional trends among facing aspect and mast resources in the study area. For example,
oaks and hickories tend to favor south-facing slopes; chestnuts prefer north-facing slopes.
Because south-facing slopes tend to receive higher levels of insolation, they may also have
greater amounts of biomass. More biomass along south facing landforms might act to attract
a variety of fauna to these locations.
Facing aspect in ArcView GIS is calculated as an azimuth value in degrees from the
Grid North of the facing aspect grid. When facing aspect is considered in this manner, the
background appears to be more southerly oriented than are archaeological sites (Table 6).
When facing aspect is presented in degrees azimuth, there is no scale to the data indicating
maximum North or South. Facing aspect may be re-coded on an interval scale where
maximum North is zero and maximum South is 180 (Klippel and Hall 1988). On this scale,
a value of 90 represents an East or West facing landform. Therefore, values below 90
indicate a more northerly facing landform while values greater than 90 denote a more
southerly facing landform. When facing aspect values are re-scaled to between zero and 180,
the background has a mean value of 91.8 and archaeological sites has a mean value of 97.0.
The results indicate a slight southerly orientation for archaeological sites; the background is
nearly even. T-test results on facing aspect data for the spatial analysis database sites (n=319)
was performed. At "=0.05, with critical t value of 1.968, a t value of 1.857 indicates that the
facing aspect of sites does not significantly deviate from the background environment.
82
When a larger sample size of sites in the Cumberland Escarpment are selected from
the OSA database (n=859), facing aspect distributes normally with a peak favoring
southeasterly site locations. Figure 9 indicates a southeasterly distributional trend within the
spatial analysis database. The background is even across facing aspect classes. Background
facing aspect ranges between 11 and 14 percent for each class. The larger OSA sample
suggests a southeasterly site orientation preference. When actual aspect values were obtained
for 840 of the 859 sites from the OSA sample, instead of using the categorical data (e.g., N,
NE, E, SE, SW, W, NW) a clearer picture emerges. Aspect values were extracted by
overlaying the OSA sites upon the aspect grid coverage and obtaining aspect values for each
site’s polygon centroid. Nineteen values could not be obtained for this analysis because of
the manner how point data overlay grid data in ArcView. The aspect values were then rescaled so that maximum north equaled zero (0) and maximum south equaled 180. The mean
value for the 840 OSA sites is 105.3 with a standard deviation of 48.7. When compared to
the background environment via a t-test, at "=0.05, with critical t value of 1.965, a t value
of 8.03 indicates that the facing aspect of sites does significantly deviate from the background
environment with the larger sample size.
The ecological coverage divides the study area into five strata to examine whether or
not shifts in landuse occurred. Except for the lower slope stratum, the environment is nearly
evenly represented (Figures 10 and 11; Table 7). Archaeological sites are most prevalent in
the upland and low level land strata. The middle two strata possess the fewest archaeological
83
sites. At the very least, these data indicate substantial occupation of the uplands. More
detailed analysis of the ecological characteristics of the distribution of archaeological sites
follows below.
Another variable thought to structure human use of the landscape is distance to
potable water (Figure 12). Data analyzed for this study consists of 1:24,000 DLG files.
Unfortunately, many seeps, springs and small order streams escape being mapped at this scale.
The results concerning distance to water are apparently equivocal. The inconclusive results
are probably a function of DLG resolution; it lacks finer-grained detail necessary to capture
small, but permanent sources of water. Larger scale mapping of water sources, or remote
sensing data might provide sufficient data to address the distance to water question in the
future.
Site distance to water was examined by determining the shortest linear distance to the
closest stream. The linear distances were then divided into class of increasing 50 m intervals.
Nearly 25 percent of the landscape falls within 50 m of a stream. Archaeological sites are
generally located within 100 m and 150 m of mapped streams. Over 50 percent of all sites
are within 250 m of a stream.
6.2 TEMPORAL TRENDS OBSERVED IN SITE DISTRIBUTIONS
Distributional analysis was conducted on 319 archaeological components coded in the
spatial analysis database. Sites are temporally classified within one of eight prehistoric
periods or sub-periods which are ordinal in scale (refer back to Table 1). Component counts
per period are as follows: Paleo Indian (n=8), Early Archaic (n=28), Middle Archaic (n=19),
84
Late Archaic (n=53), Early Woodland (n=48), Middle Woodland (n=35), Late Woodland
(n=17), Late Prehistoric (n=111). The site distributions per period are provided in Figure 13.
The six variables examined through time for each period are: (1) elevation; (2) slope; (3)
facing aspect; (4) ecological setting; (5) site area; and (6) durable artifact diversity. Site area
and artifact diversity variables are archaeological site attributes while the remaining variables
are environmental attributes. Environmental variables are discussed first, while archaeological
attributes (site area and diversity) are presented last. Before discussing the distributional
results, the limitations and capabilities of the spatial analysis database requires elaboration.
6.2.1 CAPABILITIES OF THE SPATIAL ANALYSIS DATABASE
One major drawback of the spatial analysis database is that is does not represent a
statistically valid sample. An obvious reason for this is the over-sampling of rockshelter sites
in the region. Dated rockshelter deposits usually fall in the Early Woodland or Late Archaic
periods. The temporal distribution of the spatial analysis database (Figure 13) clearly
indicates a bias toward these two periods.
Other factors are less obvious. Poorly defined
temporal units may contribute to the problem by emphasizing some periods while obscuring
others. Research goals in the past were oriented away from questions concerning earlier
Archaic and Paleo Indian period and later Woodland and Late Prehistoric subsistence and
settlement issues. Consequently, fewer sites are known for these intervals. Finally, temporal
designations of components within the database were done largely upon the basis of timesensitive artifacts. Often temporal designations are based upon morphological attributes of
lithic bifaces; formal analysis of such artifacts has not occurred in the study area.
85
A related issue is that of the multicomponent composition of the majority of deposits
coded in the spatial analysis database. The majority (57 percent) of sites in the database have
more than one component (Figure 14). However, 77 percent of multicomponent sites have
three or fewer components (Figure 15). This issue also potentially impacts the variable site
area. Multicomponent sites are expected to be larger in area because of greater visitation by
more people over time. Mean site size values might be exaggerated as a result. However,
many rockshelter deposits are limited in their spatial extent because of natural barriers to
human occupation. Factors such as boulders from roof falls and formation processes that
established walls and driplines limit available floor space in shelters. Per period, Middle
Archaic components are most often found at multicomponent deposits. Late Prehistoric sites
are most often single component deposits. One obvious problem in identifying Middle
Archaic components is that they are most often associated with temporally mixed
multicomponent deposits.
6.2.2 DISTRIBUTIONAL TRENDS OF ENVIRONMENTAL VARIABLES
Examination of the environmental context of archaeological deposits affords a way
to track diachronic landuse changes. Elevation, slope, facing aspect, and ecological attributes
pertaining to site location are the variables evaluated here. As observed earlier, overall site
elevation (323 m) is greater than the background (309 m). From the diachronic perspective,
mean elevation increases beginning in the Late Archaic period (Figure 16). Slope values for
sites remains flat from the Paleo Indian period though the Middle Archaic periods (Figure 17).
Slope values for the following periods increase. The variables elevation and slope are
86
tracking greater occupational intensity in rockshelter contexts beginning during the Late
Archaic period. Higher slope values indicate proximity to nearly-vertical rock outcrops
containing rockshelter habitats.
By the Early Woodland period, slope values peak.
Rockshelter occupations decline in intensity for the periods following the Early Woodland.
However, slope and elevation values remain high as rockshelters and other upland venues are
occupied.
Analysis of facing aspect followed the re-scaled method developed by Klippel and Hall
(1988) as presented in Chapter 5. Recall that facing aspect values are scaled so that a value
of zero represents maximum north while 180 indicates maximum south. In GIS, it is possible
to obtain facing aspect values indicating perfectly level terrain; for analytical purposes flat
values (n=11) were discarded from analysis. Flat values were discarded because grid cells
with such values are perfectly level and are not oriented in any particular direction.
Facing aspect analysis was conducted upon all 319 loci within the spatial analysis
database. Per period facing aspect analysis was completed, but is not presented because the
results failed to show any within period trends, mainly because of limited sample sizes.
Throughout prehistory, there appears to be a trend toward selecting southerly oriented
landforms (Figure 18). Rockshelter sites are more southerly oriented than are open-air
occupations. One possible factor is that rockshelters are found in extremely steep, narrow
valleys. The terrain serves to block much of the solar radiation from penetrating most
rockshelters. Prehistoric groups probably selected south-facing rockshelters for their access
to greater insolation. Recall that most rockshelter occupations date to the Terminal Late
Archaic and Early Woodland periods; the same time interval when crops and cultigens are
87
added to the subsistence base. If cultigens were being planted near rockshelter locales,
south-facing landforms would be more desirable settings for garden plots.
Diachronic distributional changes are observed for the ecological setting of
archaeological deposits. The results are displayed in three separate histograms (Figures 19
to 21). Prehistoric occupations within the lowest two strata appear to be relatively even
through time. Increased habitations within the lower slope strata occur by the Late Archaic
period and are retained throughout the remainder of prehistory. Occupations within the midslope stratum do not become manifest until the Late Archaic period (Figure 20). The upper
two strata appear to have been occupied regularly throughout prehistory (Figure 21). Upland
occupations are nearly at the same proportion as the total number of sites for each given
period. This seems to indicate fairly constant use of upland locales throughout prehistory.
6.2.3 DISTRIBUTIONAL TRENDS OF ARCHAEOLOGICAL VARIABLES
Two variables within the spatial analysis database pertain to the distributional
attributes of archaeological deposits within the study area. The two variables are site area and
artifact diversity. Examination of site area and diversity through time are thought to be of
utility for tracking differences in site function. Discerning site function, even at a rudimentary
level, would allow for the application of Binford’s forager--collector concept (Binford 1980)
in a limited fashion. For example, larger sites with high levels of diversity might be
interpreted as representing residential bases. Small sites with low artifact diversity might
indicate logistical locations.
88
6.2.3.1 SITE AREA
Site area was measured in hectares or square meters. Square meters is only used for
reporting minimum site area. Site area was obtained from the OSA data coverage. The OSA
coverage contained features (polygons). Polygons presumably delineate site limits. A field
was added to the database table for area. A database calculation returned the area covered
by each polygon feature. All sites with four or more components were excluded from analysis;
inclusion of large multicomponent sites was minimized. The remaining 246 sites had three
or fewer components and were utilized in this analysis. Site area is in effect an alternate
measure for occupational intensity given the fact that density estimates are lacking. Had
artifact density estimates of sites been available, occupational intensity could be better
addressed. Obviously it does matter that different groups may have occupied different
portions of sites at different times. However, given the nature of the data, this issue can not
currently be addressed. Another failing of the site area measure might come into play when
the constricting spaces of rockshelter sites are examined. Smaller rockshelter sites might have
been used more intensely at different times, as a result site are will be insensitive to this fact
in such contexts. The site area data are presented via two histograms (Figures 22 and 23).
One major trend is toward more smaller sites through time as indicated by minimum site area
in Figure 23.
89
Low level land stratum sites are some of the larger sites in the study area. Mean site
area in this stratum exceeds 1.0 ha only during the Late Archaic and Late Prehistoric periods
(Figure 24).
Middle Archaic sites approach the 1.0 ha level. However, Middle Archaic
remains are most often part of multicomponent sites; the area reported is probably inflated.
Late Prehistoric sites in the low level land stratum are the largest, with a mean area of 2 ha.
The largest sites for all periods except the Early Woodland are located within the low
slope stratum (Figure 25). The low slope stratum is adjacent to the low level land stratum.
Due to the 30 m resolution of the data, lower portions of this stratum contain landforms that
should be mapped within the low level land stratum. Interfaces between the two strata are
often delineated by colluvial foot slopes which are outside of the floodplain. These landforms
are desirable for occupation because they are not subject to flooding. At the same time,
colluvial sites are often located adjacent to rich wetland resource patches. Late Prehistoric
deposits within the low slope stratum are just under 2 ha in area, similar to low level land
occupations. The next largest set of sites within this stratum belong to the Early Woodland
period. Early Woodland sites have a mean area of approximately 1 ha.
Late Archaic and Early Woodland deposits dominate the mid-slope stratum (Figure
26). Mean site area for both periods is between 0.4 to 0.5 ha. Most mid-slope occupations
are within often constricting rockshelter contexts. In this case, the ideal measurement of
occupational intensity would be density of materials per unit area or volume (perhaps
excepting quarry or workshop sites). Late Archaic and Early Woodland rockshelter
occupations are at least four times greater in area than Middle Woodland and Late Prehistoric
habitations. This evidence suggests that later rockshelter occupations were structurally
90
different than earlier ones. Reduced site area suggests that intensity of use was also lower
during later as opposed to earlier periods. These data support Applegate’s (1997) analysis.
Her study of lithic assemblages from two rockshelters observed that Early Woodland deposits
at Cold Oak seemed to be more intense than those at the Late Woodland Rockbridge
occupation.
Upper slope landforms include both open-air and rockshelter sites and diachronic
trends are observed for upland slope and upland level strata. The largest sites belong to the
Middle Archaic to Early Woodland periods (Figures 27 and 28). For all periods, mean site
area is about 0.2 ha. Early Woodland sites have an area of 0.4 ha. Following the Early
Woodland period, upland deposits decrease in area by nearly a factor of two. Middle
Woodland through Late Prehistoric sites all have mean areas below 0.2 ha.
Changes in landuse are best illustrated by examining mean site area per period across
all five strata simultaneously. When the data are displayed in this manner, distributional
qualities of landuse are delineated (Figures 29 to 32). Again histograms are the display device
with the X-axis consisting of the variable landform strata. The Y-axis is mean site area per
landform for each given period. From a temporal perspective, the following periods are
grouped together: (1) Paleo Indian, Early Archaic, Middle Archaic; (2) Late Archaic and
Early Woodland; (3) Middle Woodland, Late Woodland, (4) and Late Prehistoric is presented
separately. Presumably, the four groups represent the following intervals: (1) pre-cultigen
utilization; (2) incipient cultigen consumption; (3) increased
91
reliance upon cultigens; (4) maize-based agriculture. A second rationale for displaying
particular periods together is that in most cases, landuse patterns appear to be similar to each
other from adjacent groupings. However, it is arguable that a continuum is represented.
Figure 29 presents data pertaining to the Paleo Indian through Middle Archaic
periods. Landuse during this interval appears to be oriented along lowland and alternately
upland occupations. Few sites are located within the middle strata. Site areas per period per
landform stratum are nearly the same. Larger lowland occupations are contrasted with
smaller middle strata sites. Upland occupations are about one-half the size of those in the
lowlands. Low slope and mid-slope strata sites are approximately four times smaller than
those in the upland level strata.
Data for the Late Archaic and Early Woodland periods are presented in Figure 30.
For both periods, site area consistently decreases when moving vertically from the lowlands
to the uplands. Mid-slope to upland strata occupations are substantially smaller than those
in the lowlands. However, this can not necessarily be taken as a measure of occupational
intensity, as rockshelters are smaller, more confined spaces.
Little data exist for Middle Woodland and Late Woodland period occupations (Figure
31). In comparison to earlier periods, site area is nearly two to three times smaller, even for
the lower strata. It is uncertain whether or not this is matter of sample bias. Late Woodland
sites are absent from the low slope and mid-slope strata. A slight increase in site area occurs
at some point along the upper-slope-upland level strata boundary. Upland level stratum site
area for the two periods remains consistent with the Late Archaic and Early Woodland
periods.
92
A completely different picture of settlement patterns is present for the Late Prehistoric
period (Figure 32). The largest sites are found within the two lowest strata. Within the
Upper strata, mean site area is uniformly small. Site areas for occupations in the uplands are
nearly 10 to 20 times smaller than those in the lowlands. These data indicate substantial
residential bases in the lowlands from which forays were launched into the uplands.
6.2.3.2 ASSEMBLAGE DIVERSITY
A rudimentary diversity measure (assemblage richness) was devised to examine
changes in artifact assemblages across space and through time (e.g., Rafferty 1994; Banning
2000:110). Diversity is a measure of an assemblage’s characteristics; it is a measure of
dispersion rather than of central tendency. The concept has been appropriated by
archaeologists from ecology where it is termed richness(Lennstrom and Hastorf 1992:210).
Measures of diversity go beyond a list of individual species or types of items recovered from
a site.
The goal of estimating assemblage diversity through time was to attempt to
differentiate functional changes in toolkits present at sites. Simply put, low diversity would
indicate fewer activities being performed at a locus; higher diversity levels would denote that
more activities were performed at a particular site (e.g., Banning 2000:110). Low diversity
levels also would indicate a more specialized toolkit. Higher values would denote a more
generalized strategy of resource procurement. In other words, high diversity artifact
assemblages might indicate a technology geared to a broad spectrum acquisition strategy of
a larger number of plant and/or animal species. A lower diversity estimate might indicate
93
fewer species are included in the diet, hence suggesting a narrower spectrum diet.
The simplest method of calculating diversity is by counting the number of different
classes present (Lennstrom and Hastorf 1992:210). For this study, a diversity index was
created by determining the number of different bifaces, projectile points, other lithic tools, and
ceramics for each site. The total number of (nominal) classes of artifacts at a site was divided
by the number of components present to attempt to account for multicomponent deposits.
For example, if a particular site had nine different artifact types and three distinct temporal
components, a diversity index of three (3) would be assigned to that site. Therefore, the
results can be considered to be somewhat imprecise for multicomponent sites. Imprecision
results in some cases because diversity indices for some components will be artificially
deflated. In other cases the diversity index will be inflated.
Two indices were calculated. First, only stone tools counts were employed (Table 8).
Second, ceramics were added to stone tool counts (Table 9). The count method of figuring
diversity lacks the ability to assess assemblage evenness, but is effective in accounting for
assemblage variety (Lennstrom and Hastorf 1992:210). Such simple count measures of
diversity are sensitive to small sample sizes. The study’s sample in particular has many Late
Archaic (n=5), Early Woodland (n=12), and Late Prehistoric sites (n=22); other Archaic,
Paleo and Woodland period sites are more poorly represented with one or two cases each.
However, the Late Prehistoric sample size, while the diversity index is lower than Late
Archaic and Early Woodland figures. In fact, mean lithic diversity for the Late Prehistoric
sample is the lowest of all eight time classes.
94
The resulting diversity index seems effective for diachronic analysis, but small sample
size for some periods precluded distributional investigation. Through time, assemblage
diversity is lowest during the Paleo Indian to Middle Archaic periods. Mean diversity
increases during the Late Archaic period and peaks within the Early Woodland. Following
the Early Woodland period, mean diversity declines. It is thought that the diversity
measurement is reliable in tracking overall assemblage diversity per period though time. One
implication is that expansion of the toolkit might indicate broadening diet breadth; more,
different resources are being acquired and processed. The diversity data suggest that
maximum generalization occurred during the Late Archaic and Early Woodland periods, the
same time that cultigens are added to the diet. Reduction of the diet breadth due to the
incorporation of cultigens following the Early Woodland period is probably represented by
the decline in assemblage diversity. The reasoning being that as cultigens become dietary
staples by perhaps the Middle to Late Woodland periods, less reliable species begin to drop
out of the diet.
6.3 SUMMARY OF THE DISTRIBUTIONAL RESULTS
In summary, discernable diachronic changes in prehistoric landuse were detected.
General environmental and archaeological data analysis provided a picture of the composition
of the study area. Specific data concerning each of the eight prehistoric periods enabled
changes in patterning to be observed. The three primary variables that isolated changes in
settlement practices were: (1) site count per period across ecological strata; (2) site area per
period across ecological strata; (3) assemblage diversity through time. Initially in the Paleo
95
Indian, Early Archaic, and Middle Archaic periods, landuse was concerted toward lowland
and alternately upland locations. During the Late Archaic and Early Woodland periods,
landuse expanded into mid-slope locales. Large sites predominate within the lower level land
stratum throughout prehistory, except for the Early Woodland period. During the Early
Woodland period the largest sites are found in the lower slope stratum. Late Archaic and
Early Woodland sites dominate the mid-slope stratum. By the Late Prehistoric period, the
largest sites are in the lowlands while the smallest sites are in the remaining strata. By the
Late Prehistoric period landuse became focused within lowland land strata. Assemblage
diversity peaks during the Late Archaic and Early Woodland periods. Diversity gradually
decreases throughout the remainder of prehistory. By the Late Prehistoric period lithic tool
diversity levels fall below those for the Pale through Middle Archaic periods. The results
indicate that even with the limitations inherent in the spatial analysis database, that formal
stratification of the study area’s landform allowed for discerning synchronic patterns of
landuse. The goal of this chapter was to present the distributional data. Interpretation of
these results are discussed in the next chapter.
96
CHAPTER 7
SYNTHESIS OF THE DISTRIBUTIONAL DATA
The goal of this chapter is to organize the distributional data for the purposes deriving
models of prehistoric settlement practices. As mentioned in the Research Design (Chapter
2), the explanatory framework consists of an incorporation of Binford’s (1980) concepts of
logistical mobility and residential mobility which are a part of his forager-collector model.
As previously discussed in section 2.7, three site types were derived from Binford’s mobility
concepts. The three sites are extractive locations, processing locations and residential bases
(Binford 1980). This tripartite typology categorizes sites upon the basis of location, size,
and artifact diversity. The goal is to ascertain whether or not shifts in mobility occurred.
Changes in mobility patterns might indicate how settlement practices changed. For example,
if a shift from a forager to collector strategy occurred, a shift to fewer larger sites might
indicate reduced residential movement. Such a pattern might be bolstered by the appearance
many small, low density or low diversity sites. These small sites might be representative of
logistical resource procurement. Alternately, a settlement pattern observed to consist of few
small sites and more larger sites across the landscape might be interpreted to be a residentially
mobile pattern.
97
Consolidation of the distributional data presented in Chapter 6 is required to delineate
changes in settlement patterns. The aggregation of distributional data occurs along the
temporal dimension. The eight temporal classes utilized in the production of histograms are
grouped into four new units. The four units tend to share internal similarity with respect to
distributional variables. The primary variables were site frequencies per ecological stratum,
site area per ecological stratum, mean site area, and minimum site area. The four groups are:
(Pattern I) Paleo Indian, Early Archaic, Middle Archaic periods; (Pattern II) Late Archaic and
Early Woodland periods; (Pattern III) Middle Woodland and Late Woodland periods;
(Pattern IV) the Late Prehistoric period.
7.1 CONSOLIDATION OF DISTRIBUTIONAL DATA
The distributional data presented in the previous chapter indicate that changes in
settlement practices occurred within the study area. Three variables isolated trends in landuse
patterns: (1) site count per period; (2) site area per period; (3) assemblage diversity per
period. The first two variables were examined across space. In this case study, space was
stratified along stable geomorphologically-based parameters. Stratification along ecological
lines allowed for tracking diachronic changes in site frequency and area across space. The
third variable, assemblage diversity measured the degree to which a generalizing or
specializing subsistence strategy existed for a particular period. In synthesizing the
distributional data, the first two variables in particular require further discussion. Since
98
assemblage diversity could only be ascertained for a small sample of sites (n=54 for lithic
artifacts)site diversity is considered over time between landuse patterns, but not across space
for each of the four landuse patterns.
Centered bar graphs are employed to present distributional data regarding site area
and frequency data across space and through time. The benefit of employing centered bar
graphs to display the distributional results is that it is a visual device. As a visual device,
trends in forty different time-space units may be displayed at once. These charts are not to be
confused with frequency seriations utilized by archaeologists in tracking the frequency of
“genetically” related traits through time (O’Brien and Lyman 1999:116). The ecological
strata are not analogous to classes of historically contingent artifact types or classes. The
only similarity with frequency seriations is that one axis of the centered bar graph tracks time.
Centered bar graph frequency distributions were created from the spatial analysis
database (Tables 10-14; Figures 33 and 34). The centered bar graphs display the histogram
data in a way that is more manageable for visualization purposes; the same data were
presented as a series of histograms (e.g., Figures 19-21). The ecological coverage stratified
space into five classes. Temporally, the archaeological record is divided in to eight classes.
The result is a matrix consisting of forty time-space classes. To address the research question
regarding distributional changes in prehistoric landuse, two centered bar graph distributions
were created. Both were created to examine distributional changes in archaeological variables
through time. First, the frequency of components per time interval across ecological strata
are examined. Second, proportional mean site area per ecological stratum per period is
evaluated.
99
A critical variable in discerning changes in prehistoric settlement practices is that of
mean site area. Figure 33 consists of a centered-bar graph containing of per stratum data on
mean site area per period. The bars, per stratum add-up to 100 percent of mean site area for
all periods. The proportional contribution of each period to the total mean site area was
converted to a percent. For example, the Early Woodland period’s mean site area constitutes
nearly 25 percent of the total mean site area for the mid-slope stratum. However, the data
presented in this form cannot be compared across strata. That is, Early Woodland sites in the
mid-slope stratum are not necessarily larger in area as their low slope stratum counterparts.
Distributional data presented in the form of histograms should be consulted for between strata
area variability. The site area data are particularly revealing of settlement practices when
considered in light of the site frequency data presented in the preceding sections. In fact, there
appears to be site area--frequency relationship.
Utilizing distributional data generated from the spatial analysis database four distinct
landuse patterns are inferred. Each pattern consists of a discrete time sequence. Pattern I is
that of the Paleo Indian through Middle Archaic periods. Pattern II consists of the Late
Archaic and Early Woodland periods. Pattern III contains the Middle and Late Woodland
periods. The Late Prehistoric period comprises Pattern IV.
100
7.1.1 PATTERN I: PALEO INDIAN THROUGH MIDDLE ARCHAIC PERIODS
Paleo Indian, Early Archaic, and Middle Archaic period sites exhibit continuity in
three ways. First, the largest concentration of sites is located within the low level land
stratum. Second the lowest frequency of sites is found within the middle strata, specifically
the mid-slope and lower slope strata. Third, there are also higher numbers of sites within the
upper slope and upland level land strata. These data suggest that resource acquisition during
this time interval was oriented towards alternating settlement between the lowlands and the
uplands. Pattern I is suggestive of a dichotomous landuse pattern with occupations
alternating between the uplands and lowlands.
For Pattern I, the largest sites are located in the uplands and lowlands respectively.
The smallest sites are located within the middle strata. Of particular note is that this time
frame contains the largest upland level land stratum mean site area for all of prehistory. Mean
site area in the uplands and lowlands generally appears to be about three times greater than
sites located in the middle strata. Further, when considering the frequency distribution of
sites, there are more, larger sites in the uplands and alternately in the lowlands. There are
fewer small sites located in the middles strata.
7.1.2 PATTERN II: LATE ARCHAIC AND EARLY WOODLAND PERIODS
Both the Late Archaic and Early Woodland periods exhibit considerable occupation
across the entire landsurface. Frequencies of Late Archaic and Early Woodland sites within
the middle strata are also considerably higher than for Pattern I. These data suggest that Late
101
Archaic-Early Woodland populations expanded their landuse to include more, different types
of landforms. The high concentration of mid-slope stratum Early Woodland sites tracks the
increasing importance of rockshelter habitations; only are later Late Prehistoric period midslope site frequencies greater. Similarly, Late Archaic period upland occupational frequency
is unrivaled until the Late Prehistoric period. Collectively, the Late Archaic and Early
Woodland periods indicate concerted mid-slope and upland landuse. On the basis of site
frequency data, exploitation of the lowland strata probably is maintained as in Pattern I.
Pattern II area distributions indicate considerable middle strata habitation/exploitation.
For example mean site area for the mid-slope stratum for this interval comprises over 50
percent of all prehistory. Site area for mid-slope time unit-landform class is the greatest of
all prehistory. During this period exploitation of the uplands and lowlands continues as in the
previous period. However, low-slope stratum occupations proportionally constitute nearly
one-half of the total for this stratum.
7.1.3 PATTERN III: MIDDLE WOODLAND AND LATE WOODLAND PERIODS
The Middle and Late Woodland periods consist of the most poorly recorded episode
of the study area’s prehistory. However, from the proportional site count data, continued
exploitation of all landforms is indicated. Pattern III resembles Pattern II in site frequencies
across landform strata, excepting mid-slope occupations. Mid-slope stratum occupations are
lower in frequency. Middle Woodland period site distributions tentatively indicate a focus
upon lower strata as opposed to upper strata.
102
This observation supports Wyss and Wyss
(1977) who inferred a Middle Woodland landuse shift to terrain closer to the Red River
floodplain from the uplands.
Pattern III upland strata site area seems to be proportional to previous patterns.
However, mid-slope stratum mean site area is greatly reduced when compared to the Pattern
II. Referring back to Figure 31, the largest sites belonging to the Middle and Late Woodland
periods are found in the low level land stratum. Smaller sites are found within all other
strata. Pattern III foreshadows the final distribution.
7.1.4 PATTERN IV: LATE PREHISTORIC PERIOD
Pattern IV consists solely of the Late Prehistoric period. As observed in the previous
chapter, the greatest number of sites in the spatial analysis database date to the Late
Prehistoric period. Concomitantly, the Late Prehistoric period also has the most singlecomponent sites of all periods. The distribution of Late Prehistoric period sites indicates
considerable numbers of occupations across all strata. Sites located in the uplands are
considerable during this period.
Pattern IV contains the largest mean site areas in the lowest two strata. When
compared to previous patterns, sites located in the mid-slope, upland slope, and upland level
strata are proportionally much smaller. However, site frequency data indicate that there are
many more sites located in the uplands than in the lowlands. In essence, there are many more
smaller sites located in the uplands. Fewer, larger sites are located in the lowlands. Even for
the mid-slope stratum, there are many more sites located there than for period two consisting
of the Late Archaic and Early Woodland periods.
103
7.1.5 SUMMARY OF THE DISTRIBUTIONAL DATA
In summary, the site frequency data across ecological strata indicate three major
trends. First, during the Pattern I, sites are distributed unevenly across the landscape. Pattern
I site distributions suggest lower levels of exploitation/occupation of middle slope strata.
Pattern II indicates expansion into the middle slope strata; especially the mid-slope stratum
by the Early Woodland period. During Pattern II, many more sites are located in the uplands
as opposed to the lowlands. Middle Woodland and Late Woodland period sites constitute
Pattern III. Although the data are sketchy, more sites are located in the lowlands, when both
periods are considered together. Overall, the pattern suggests a fairly even distribution of
sites across the landscape. Lastly, Pattern IV indicates a fairly even distribution of sites
across all landform strata. But upland sites are much smaller than for all previous iterations.
Overall, the data, when viewed in a diachronic perspective, suggest that during the
Archaic period, an increase in different types of landforms that were used. Though, even in
the Paleo Indian and Archaic periods, overall there appears to be a generalized landuse
practice in effect. The generalizing landuse pattern because accentuated within the Late
Archaic period. Once the trend is established, it is maintained in varying forms throughout
the remainder of prehistory.
7.2 STATISTICAL ANALYSIS OF SITE AREA DISTRIBUTIONS
A correspondence analysis was completed of the variables mean site area per period
per ecological strata. Correspondence analysis was selected to evaluate these datasets
104
because the statistic is particularly effective when the data consists of counts in rows and
columns. Further in correspondence analysis, the data cases may consist of multiple scale
types (i.e., ranked and ordinal classes may be included in the same dataset). Correspondence
analysis is a graphical method of displaying and analyzing tabular data. The procedure is
graphically related to the scatter plot. The variables are ranked, or ordinal in scale; there is
not an equal interval between classes. Chi-square values of independence are generated and
partition the cases to generate coordinates for graphical display. Correspondence analysis
produces a two-dimensional plot. The plot shows the relative clustering or dispersion of the
data cases (Greenacre 1993). In correspondence analysis more than two axes are generated
to indicate the relationships among data classes. Three types of plots may be generated: (1)
one showing the clustering or dispersion of row data; (2) one display showing the clustering
or dispersion along the lines of columnar data; and (3) a plot of both (1) and (2). Robust
results from correspondence analysis occur when the first two axes can account for the
majority of the variation within the data.
The results of examining mean site area across five ecological strata and through eight
time classes is displayed in Figure 35. Overall, the two axes account for 90.47 percent of the
variation within the data. Axis one accounts for nearly 55 percent, while axis two accounts
for 36 percent of the variation. The graph indicates two clusters with three cases each. Two
case fall outside of any clusters. On the lower right corner of the graph, Paleo Indian, Early
Archaic and Middle Archaic cases cluster along axis one. The second cluster
contains the Early Middle and Late Woodland periods along the right-center portion of the
chart. The Late Archaic and Late Prehistoric cases do not fall within either of the two
105
clusters. Lines on Figure 35 indicate the cases that fall closest together along axis one.
Correspondence analysis on the variables site area per time period across ecological
strata, produced four different groupings. The groups are: (1) Paleo Indian, Early Archaic,
and Middle Archaic; (2) Late Archaic; (3) Early, Middle, and Late Woodland periods; and
(4) the Late Prehistoric period. Correspondence analysis indicates close agreement with the
four patterns stipulated at the beginning of this chapter; the only exception being the
grouping of the Early Woodland period with the Late Archaic period. The reason for
separation of the Late Archaic data case is probably due to lack of temporal resolution;
Terminal Late Archaic sites had to be grouped with all Late Archaic sites.
Several relationships are observed when comparing the per period row data against
the distribution of landform strata column data (Figure 36). First, earlier sites are grouped
with the upland strata. Later sites are grouped with the lower strata. Late Archaic sites are
clustered with the mid-slope stratum. Presumably, larger, later sites are located proximate
to richer alluvial land for growing crops. The correspondence analysis again demonstrates
the significance of the uplands to the Paleo Indian and Archaic inhabitants of the region.
7.3 A MODEL OF SETTLEMENT PRACTICES
The purpose of this section is to develop an explanatory framework which can be
applied to the distributional data. The goal of the application of the model to understand how
each of the observed four patterns structured human landuse. Binford (1980) has developed
the forager--collector concept to outline two alternate ways in which humans structure their
landuse patterns. The forager--collector model is an analytical framework which views
106
hunter-gatherer systems on the basis of mobility. At one end of the spectrum are foragers
who are highly mobile hunter-gatherers (Table 13) and are residentially mobile. At the other
end of the continuum are collectors who are sedentary and are logistically mobile (Bettinger
1991:64).
Application of the explanatory framework requires making distinctions about the
patterning of the archaeological record. As discussed previously, the most succinct way to
accomplish this task is to categorize archaeological sites into one of three classes: (1)
residential bases; (2) extractive locations; and (3) processing locations.
Binford (1980) denotes two main site types for foragers; the residential base and the
location (Table 13). The residential base is the locus of subsistence activities. The residential
base is the point from which forays for the extraction of resources is initiated. Once acquired,
resources are returned to the residential base for consumption. Locations are loci where
resources are procured and/or processed. Two types of locations may be distinguished: (1)
extractive locations and; (2) processing locations. It should be noted that Binford does not
make this distinction. Extractive locations represent points-of-encounter where resources are
found. Processing locations may occur at points-of-encounter. Or, resources may be
processed elsewhere between the point-of-encounter and the residential base. Where a high
mobility pattern exists, foragers will tend to move their residential base to “map-on” to
resources (Bettinger 1993:66-67). As a result, the processing of resources is expected to
occur at the residential base. One consequence of residential mobility being fewer processing
loci, and subsequently a reduced variety of archaeological deposits associated with foragers.
107
Collectors are considered to possess a logistical rather than a residential mobility
pattern. One of the key differences between foragers and collectors is that of storage.
Collectors engage in storage more often. Storage reduces resource acquisition risk in
spatially or temporally patchy environments. However, storage also acts as an “anchor” to
keep populations at the locus of stored items (Bettinger 1993:68). The result is a reduction
in residential mobility and an increase in logistical mobility. A consequence of logistical
mobility is that there is a greater variety of logistical sites. Collector sites, in addition to
acting as locations and residential bases also include caches, stations, and field camps. For
simplicity’s sake, these site types are considered here to be special kinds of processing
locations; this study’s database is too imprecise to distinguish between Binford’s variety of
non-residential collector type sites. For example, stations are locations were information on
resources is collected and processed. Compared to foragers, collectors will have a greater
diversity of non-residential sites.
One feature that distinguishes forager from collectors is that of technology (Table 13).
Under the forager--collector model, foragers are expected to have a more generalized toolkit
where a few tools perform a greater variety of tasks. This is contrasted to the collector
toolkit, which is thought to be specialized. Specialized tools are limited to tasks geared
toward a particular resource. One consequence is that collector toolkits might contain a
greater variety of tools to perform several different tasks. From the archaeological visibility
standpoint, the collector strategy might be indicated by increased diversity in artifact
assemblage composition.
108
Because of the rudimentary level of the database at hand, ascertaining different classes
of sites must be accomplished using only three variables. The three variables are ecological
strata, site area, and time class. Initially, the study area was stratified into for ecological
classes.
To simplify matters here, the five classes are collapsed into three where
generalization is deemed beneficial. The three land classes in relation to the previous five are
diagramed in Figure 37. Site area is examined on the basis of large or small sites within each
of the four previously stipulated landuse patterns. Again the patterns are organized
temporally in the following way: (Pattern I) Paleo Indian, Early Archaic, Middle Archaic;
(Pattern II) Late Archaic and Early Woodland; (Pattern III) Middle and Late Woodland;
(Pattern IV) Late Prehistoric.
The variables mean and minimum site areas per settlement pattern group constitute
the basis for classifying sites. The data principally come from histograms presented in the
previous chapter (e.g., Figures 29-32). Large sites are simply interpreted as representing
residential bases. Small sites are interpreted as processing locations. Depending upon the
positioning of the residential bases, processing locations are inferred as being either extraction
types or as process types. Examples follow in the sections below (see also, Tables 14 and 15
and Figure 38).
109
7.4 APPLICATION OF THE FORAGER-COLLECTOR CONCEPTS
7.4.1 PATTERN I
Pattern I contains the time classes of Paleo Indian, Early Archaic, and Middle Archaic
periods. The largest mean site area falls between 0.3 and 1.0 ha for this group. All sites of
this size class are either located in the low level or upland level ecological strata. Small sites
are between 700 square meters and less than 0.3 ha. Small sites are located within the middle
three strata: low slope, mid-slope, and upper slope (Table 14). The distributional data
indicate that residential bases were most often located in the lowlands and secondarily in the
uplands. Extractive locations were probably located across all ecological strata. Within the
mid-slopes, processing locations may have existed along with a few extractive locations.
Because there appear to be two locations for residential bases, mobility for Pattern I is
inferred to be higher than later patterns. From the standpoint of the model mobility is
residential rather than logistical. That is, residences are moved to map-on to resources.
From the landuse perspective, Pattern I exhibits a less generalized pattern than later
ones; fewer ecological strata are exploited at this time. During the Pattern I period artifact
diversity is quite low, indicating a more generalized technological strategy. A more
generalized technology tracks with the landuse data in that a low diversity of resources were
exploited during Pattern I.
110
Pattern I is the period least impacted by cultigen/crop plants; bottle gourd is the only
candidate. Paleoenvironmental data also support this inference. The study area environment
probably contained low level anthropogenic alterations; the landscape was more even than
patchy from the human perspective.
7.4.2 PATTERN II
Temporally, Pattern II corresponds to the period of the initial incorporation of crops
and cultigens into the diet. Large Pattern II sites possess a mean site area of between 0.4 and
1.7 ha. Residential bases are found within the lowlands and mid-slope strata. Unlike Pattern
I, residential bases are not located in the upland level land stratum. Smaller mid-slope
residential bases are probably a function of spatial constraints within rockshelters. After all,
mean site area in the mid-slope zone is greatest during the Late Archaic and early Woodland
periods. This indicates that rockshelters (primarily), functioned differently during this time
interval than any other period (e.g., Figure 33).
As discussed in the culture history section, artifact assemblages found in rockshelters
and lowland setting seem to be redundant and highly diverse. Diversity suggests that a wide
range of activities were conduct at rockshelter and floodplains alike. That rockshelter
assemblages, by the terminal Late Archaic period contain similar items as are found at
floodplain sites, indicate that they are functionally redundant. This evidence suggests that by
the terminal Late Archaic and Early Woodland periods, that rockshelters were occupied as
residential bases. The location of residential bases both in the lowlands and the mid-slopes
suggests that two sub-patterns might exist. Where access to lowland landforms exists,
111
residential bases are established there. Residential bases are established in the rockshelters
where floodplain access in not available.
Small sites are above 250 square meters and under 0.4 ha in area. Small sites are
found scattered across all landscape strata. They are the only site type found within the
upland portions of the study area (Tables 14 and 15). When residential bases are established
in the lowlands, fewer processing locations are situated there as well; more processing
locations are found within the mid-slope and upland strata. When residential bases are
established within the mid-slopes (i.e., rockshelters), few processing locations are placed
there; processing locations are found in the lowlands where available and alternately in the
uplands. Regardless of the location of residential base, extractive locations are found across
the landscape.
Overall, Pattern II exhibits a very generalized landuse practice. Many more landforms
are exploited under Pattern II than area under Pattern I. It seems likely that there is a link
with greater assemblage diversity and broader landuse practices. Assemblage diversity for
the Late Archaic and Early Woodland periods is at the highest levels for all of prehistory.
High assemblage diversity suggests that a very specialized set of tools fulfilled
a wider range of extractive and processing demands.
These demands indicate that
assemblage diversity increased as a wider variety of landforms were exploited to fulfill broadspectrum subsistence needs.
A shift from residential mobility to logistical mobility is inferred to occur from Pattern
I to Pattern II. The shift probably occurred within the Late Archaic period itself. Pattern II
exhibits large sites in the lowlands with smaller sites located in the mid-slopes and uplands.
112
The dominate configuration is probably one of residential bases in the floodplains. The
secondary pattern is that of locating residential bases within the mid-slopes (rockshelters).
With increasing sedentism, home ranges were reduced. Smaller foraging ranges supported
by a broad spectrum diet would enable groups along smaller-order drainage systems to utilize
rockshelters as residential bases. Their downstream counterparts located residential bases
within the floodplains available to them. In more constricted upstream valleys in the study
area, the rockshelter pattern probably persisted in reduced form though to the Late Woodland
period.
7.4.3 PATTERN III
Pattern III was developed from distributional similarities between Middle Woodland
and Late Woodland sites. One problem is that very little data pertaining to Middle and Late
Woodland occupations exists for the study area; these results are tentative. Pattern III
diverges from Pattern II in that rockshelter (mid-slope) occupations become greatly reduced.
However, exploitation of the uplands continues. The largest mean sites are found in the
lowlands. These sites have areas of about 0.4 ha. Sites of nearly similar size are also found
within rockshelters located in the uplands. Sites in the uplands have areas of between 0.2 and
0.3 ha. Again the reduced area is probably accountable to cramped space available for
utilization in rockshelters. Small sites are located across the landscape. Small sites are about
0.1 ha in area, one-half to one-fourth the size of large sites. Small sites are mainly
113
located in the middle to lower-slope ecological strata. The largest sites for Pattern II are
significantly smaller than for either Pattern II or III: It is uncertain whether or not there are
sufficient data for this interval.
If the data may be interpreted with reliability, then Pattern III seems to indicate
continuity with Pattern II. Larger sites, probably representing residential basis are located in
the lowlands, specifically in the floodplains. Smaller extractive and processing locations are
located along the mid-slopes and lower slopes, as well as in the uplands. Slightly larger sites,
about twice as large as sites located in the mid-slopes, are located in the uplands. These sites
are mainly rockshelters located in upland contexts rather than mid-slope contexts.
Upland rockshelter sites might represent less-intensely occupied residential bases. The
smaller rockshelter sites might indicate persistence of the bifurcated residential base pattern.
In the more remote upland, headwaters areas, rockshelters were still utilized as residential
bases. Applegate (1997) determined from lithic evidence that later Woodland period
rockshelter occupations were less intense than earlier Woodland period habitations.
Reduction in the site area parameter from pattern II to Pattern III seems to agree with
Applegate’s findings.
The trend of logistical rather than residential mobility as seen in Pattern II continues
into Pattern III. Logistical sites throughout the mid-slopes are nearly one-half the size as
those for Pattern II. This suggests that more activities were being performed at the residential
base. Assemblage diversity declines for the first time during this interval. Reduced artifact
diversity might indicate that a reduced variety of resources were exploited. This suggests a
diminishing of a generalizing or broad-spectrum subsistence system. The reduction in
114
mobility might indicate increases in patches of cultigens adjacent to residential bases.
Increased reliance on domesticated plants might be responsible for the reduction in
assemblage diversity. However, the low data resolution for Middle and Late Woodland sites
in the study area render these statements somewhat conjectural.
7.4.4 PATTERN IV
Pattern IV represents the final settlement configuration for the study area and consist
only of the Late Prehistoric period4. The largest sites are between 1.8 ha and 2.0 ha. The
smallest sites are less than 0.2 ha in area. Large Pattern IV sites area solely found in the
lowlands (low level and low slope strata). The large sites located within the low slope
stratum are generally found along the boundary with the low level stratum. Small sites are
found scattered across the entire landsurface.
For Pattern IV, residential bases are represented by the large sites in the lowlands.
The location of residential bases in the lowlands had precedence in Patterns II and III.
Although, within the lowlands, the smaller sites are probably indicators of extractive
locations; processing occurred at the residential base. Unlike elsewhere in the Ohio Valley,
residential bases for this period do no represent palisaded villages or communities of
households. Rather, they probably represent single household units. The residential bases are
undoubtedly located within or adjacent to floodplains for soil fertility required for maize
agriculture.
4
Historic period settlements share attributes of this pattern.
115
Small sites representing extractive and processing locations are found throughout the
mid-slopes and the uplands in significant frequencies. Most of the Pattern IV sites are small
deposits in the uplands. The primary difference between Pattern III and Pattern IV is the lack
of any evidence for residential bases in the uplands. It seems likely that with the establishment
of more permanent residential bases in the lowlands, that extractive activities for nonagricultural resources in the uplands, thus displacing the remaining groups utilizing
rockshelters as residential bases. Small sites with slightly larger mean area (approaching the
0.2 ha limit) are found within the upland level stratum. These sites might indicate processing
locations.
Logistical mobility characterizes Pattern IV.
Resources extracted, and possible
processed elsewhere on the landscape were returned to lowland residential bases. That,
smaller sites are found well-into the uplands suggests that Pattern IV groups extended their
range farther away from floodplain localities than their predecessors. Assemblage diversity
stabilizes at this time, remaining at comparable levels for Middle and Late Woodland period
sites.
7.5 SUMMARY
The goal of this chapter was to synthesize the distributional data in a manner so that
an explanatory framework could be imposed upon it. Development of a simplified model
from the forager--collector concepts of Binford documents a shift from a residentially mobile
settlement system to that of logistical mobility. The shift occurs during the Late Archaic
period.
116
The major contrast being in settlement models is between Pattern I and II. Although,
the resolution of the database is low, there is an indication of a bifurcation in the settlement
practices within the study area. Pattern II is the manifestation of alternate settlement practices
within the study area. One branch is oriented toward locating residential bases within lowland
settings adjacent to floodplains/alluvial land. The second branch indicates an orientation
towards the utilization of rockshelters, where floodplains are minimal and rockshelters are
abundant. Pattern III is less well resolved than the previous two models. However, there is
evidence for continued trends documented in Pattern II. The evidence for larger sites in the
lowlands suggests that lowland occupations becoming more dominate than upland
occupations. However, upland rockshelter loci may have still served as residential bases,
albeit at a reduced intensity. Pattern IV is characterized by residential bases located within
the floodplains and logistical access to the remainder of the landscape.
At this time
occupations of more remote upland rockshelters as residential bases appears to be untenable.
Rockshelter residential bases are replaced by logistical deposits.
Minimally, the assemblage diversity data support the shifts in landuse, as predicted by
the forager--collector concepts. Temporally, Pattern I contains an assemblage diversity that
is lower than proceeding configurations. This parameter is an indicator that a more
generalized toolkit was being utilized to extract and process resources. The following
patterns contain assemblage diversities that are higher. Higher artifact assemblage diversities
seem to support the notion that Patterns II through IV were more logistically oriented.
117
CHAPTER 8
SUMMARY AND CONCLUSIONS
8.1 SUMMARY OF THE DISTRIBUTIONAL RESULTS
The goal of this dissertation was to determine if the incorporation of cultigens into the
prehistoric diet affected prehistoric settlement practices within the study area. Because of the
nature of the research question distributional archaeology data were required. Once the data
were acquired, the first step was to determine if the distributional data exhibited any
heterogeneity through time. Histograms presented in Chapter 6 facilitated identification of
trends in the distributional archaeological data through time and across space. Some
variables, like facing aspect and distance to water, proved to be of little utility. Other
variables such as site area and ecological setting were found to track shifts in landuse.
Chapter 7 presented a synthesis of distributions generated from the GIS archaeology
database vis à vis the GIS environmental data . The synthesis utilized a series of centered-bar
graphs to demonstrate that the variables site area, and site frequency are not evenly
distributed across space or through time. In fact, the trends observed in the distributions
indicate that a shift from residential mobility to logistical mobility occurred through time
118
within the study area. The timing of the change in settlement practices is evident within
Pattern II. Pattern II, consists of the Late Archaic and Early Woodland period site data.
The Late Archaic and Early Woodland distributions shared several characteristics (i.e., midslope occupations) that lent to their grouping. However, correspondence analysis indicates
that Late Archaic period sites might constitute their own settlement type class. Regardless,
the results suggest that within or by the Late Archaic period the shift had occurred from
residential to logistical mobility.
The importance of the shift in settlement practices dating to the Late Archaic period
is that it corresponds to incorporation of cultigens into the diet. Identification of the shift in
settlement patterns is significant in that it demonstrates a link between settlement systems and
subsistence practices. Further, the shift in settlement patterns can be attributed to very small
changes in subsistence practices; initially cultigens played a small role in the diet.
The distributional character of the data tentatively indicate highly localized solutions
to a shift in mobility strategies. Patterns II and III seem to indicate that where floodplain
settings existed, residential bases were established there. Where such landforms were
unavailable in the uplands, rockshelters were occupied as residential bases. This finding
suggests that considerable occupations might exist away from large floodplain settings
elsewhere in the Middle Ohio Valley.
Higher assemblage diversities for Pattern II, along with upland residential
occupations, may indicate a generalized subsistence strategy. The upland settlement strategy
was probably supported by considerable diet breath. Broad spectrum diets through the Late
Archaic period included, the new cultigens at relatively low levels (e.g., Gremillion 1993,
119
1996). With wide diet breadth, several items in the diet will be relatively low-ranked.
Therefore, a shift from richer resource patches in floodplain settings to poorer resource
patches upland settings was probably buffered by adding then newly available, low-ranked
upland items to the diet; perhaps cultigens played such a role.
Lower assemblage diversity levels follow for Patterns III and IV. These settlement
patterns were seemingly dependent upon a logistical mobility procurement strategy. During
this interval subsistence practices had one or two millennia to further integrate and intensify
the role of cultigens.
By the time Pattern IV emerges, it appears that a subsistence-
settlement system based upon indigenous crops was reoriented by maize mostly. Not only
did diets substantially change following the ca. A.D. 1,000 shift to the widespread economic
importance of maize, but so to did the settlement system. Within the study area, the Late
Prehistoric period exhibits the impact of subsistence change upon settlement practices.
Primarily, the change seems to be one where residential bases were solely located within the
low level land stratum. Presumably, the location of residential bases only within lowland
settings is due to the requirements of maize for alluvial soils.
Dunnell (1972) observed a similar correlation with Fort Ancient sites being located
upon highly productive floodplain soils in the Levisa Fork region East of the study area.
Further, this analysis supports Dunnell’s view that there were two types of Fort Ancient sites:
camps and villages (or, in this case, permanent residential bases and logistical sites). Sharp
(1996:177) states that the relationships between these two types is “unclear.” Application of
the forager--collector model to the settlement problem clarifies the relationship among the site
types. A logistical strategy in effect at this time structured landuse practices. The explanation
120
is that the logistical sites (camps) are related to the residential bases (villages) in that they
served as resource acquisition loci; Resources were then returned from the logistical sites to
the residences for consumption.
8.2 FUTURE RESEARCH QUESTIONS
On a general level, one of the most important aspects of this study is that it has
demonstrated uninterrupted occupation of the uplands throughout prehistory. The nature
of upland occupations needs to receive further attention for all periods. Specifically, Paleo
Indian through Middle Archaic period subsistence and settlement practices need concerted
research. The results of this study indicate that substantial upland sites for the interval
consisting of the Paleo Indian through Middle Archaic periods exist; that these sites may have
served as residential bases needs further evaluation. It is during this 6,000 year span that
residential mobility was the inferred landuse pattern.
Special attention is necessary regarding Middle Archaic period settlement patterns,
for it is during this time that the initial trend toward logistical mobility may have started. The
results presented here suggest that residential mobility may have been in decline during the
Middle Archaic; following this period, logistical mobility emerges. One implication is that
Middle Archaic populations were more sedentary than previously acknowledged.
Much is known about the Late Archaic-Early Woodland periods for the study area,
at least from rockshelter contexts. Yet, this portion of the database appears suspended in a
vacuum. Resolution of this problem requires research into non-rockshelter contexts; primarily
floodplain investigations along the Kentucky River system. This study and previous research
121
(Wyss and Wyss 1977) indicate that Middle and Late Woodland populations oriented
themselves along larger drainage systems. Questions regarding the subsistence base during
the later half of the Woodland cannot currently be addressed. Elsewhere in the Middle Ohio
Valley, settlement nucleation occurred during the end of the Woodland period; what was the
trend in the study area? Even for the following Late Prehistoric period, the study area lacks
basic subsistence and settlement data. Substantial occupations within the region exist (e.g.,
Muir in the Bluegrass Region) which suggest that some indigenous cultigens were retained
within the subsistence base. The settlement data from this study indicate floodplain-anchored
populations; reliance upon maize agriculture is inferred, but no substantive evidence exists for
such a subsistence practice. The only substantive evidence is of logistical sites in rockshelter
contexts.
Due to the rudimentary nature of the database that was constructed for this study,
more precise statements of the nature of the relationship between settlement patterns and
subsistence practice cannot be made. That the research question could be evaluated with the
given database should be considered a success. However, this study also demonstrates that
the way archaeological data is collected in the field, reported in the literature, and compiled
into electronic databases, is of limited utility. One would think that now, as nearly a century’s
worth of archaeological data becomes accessible via electronic databases, that these products
could be of more utility than they are.
122
8.3 EVALUATION OF THE GIS APPROACH
The success of this research project lies not in the quality of the database, but in the
sheer quantity of information available. The substantial quantity of data, largely a result of
federally funded or mandated projects, provided a few pertinent variables with which the
research question could be addressed. That this project was possible at all is largely due to
the work of the Kentucky Office of State Archaeology’s effort to code inventory data into
electronic format. There is no denying the need for spatially referenced archaeological data
and the OSA’s data provided that crucial element. The spatially referenced OSA data made
possible the construction of research question-oriented databases.
Unfortunately, the quality of the OSA database suffers from the lack of archaeological
information that is currently contained within it. Even after considerable time was taken to
augment the database with information available in the literature, the results were less than
desirable. The main problem stems from the way that archaeological data are reported in
publications, and on archaeological inventory forms. Complex questions often require
complex solutions.
Databases providing only the basic information regarding an
archaeological deposit fail to be of utility when applied beyond record-keeping tasks. Now
that archaeologists possess tools to conduct sophisticated spatial analyses, it is clear that
OSA- type databases at present, cannot fulfill the analytical requirements. If anything was
learned from this GIS implementation, it is that the background environmental data provide
a model for how archaeological databases should be constructed for spatial analysis in GIS.
123
8.4 TOWARD A CONTINUOUS ARCHAEOLOGY COVERAGE: A REQUISITE
METHODOLOGICAL REORIENTATION
Archaeological research questions are fundamentally distributional in nature because
archaeological deposits have spatial attributes. Like the environmental data developed for this
study, archaeological data are continuous across space. However, archaeologists seldom
acknowledge this fact. A formal articulation of the continuous quality of the archaeological
record, termed siteless survey, was promulgated nearly 20 years ago by Dunnell and Dancey
(1983). The approach is alternately known as non-site, distributional, or off-site survey
(Dancey 1971, 1973, 1974; Thomas 1975; Nance 1980, 1981, 1983; Dunnell and Dancey
1983; Ebert 1994; Orton 2000; Mickelson 2000). Despite decades of small-scale application
of the methodology in archaeology, it is seldom employed today. There are several
advantages to the distributional or siteless survey archaeological approach. Drawing upon
the environmental data coverages utilized in this study as an analogy, the benefits of the
approach are discussed below.
Dunnell and Dancey (1983) stipulate that the justification for the siteless survey
research design consists of: (1) the archaeological record is essentially continuous across
space; (2) surface archaeological deposits constitute valuable information in their own right.
Another aspect of the siteless survey approach that is of utility to GIS applications is the
conception of the role of environmental data in making sense of the distribution of
archaeological materials across space and through time. The relative clustering or dispersion
of artifacts
124
vis à vis environmental variables provides important information regarding past prehistoric
landuse. What resources were being targeted? How were populations structuring their
landuse patterns to target specific resources?
The GIS environmental data employed in this survey possess the attribute of a
continuous distribution across space that the archaeological data lacked.
Because the
environmental data were continuous in nature, they were much more statistically robust than
their archaeological counterpart. The necessity, then is to properly obtain archaeological data
from a region that lends to being manipulated like environmental data in GIS. Clearly in this
study, definite statistical statements could be made about the distributional characteristics of
a background parameter because of its continuous nature. Such could not be said with
reliability about an archaeological parameter. This does not mean that “total survey” of a
large area is required. After all, many GIS background datasets were acquired via a pointsampling strategy. Sampling is clearly demanded here.
The primary means in accomplishing the siteless survey methodology is in collecting
a large scale dataset within a region. However defined, the region is stipulated by the
research question in mind. A variety of sampling techniques from transects, to quadrats,
polygons, and point samples may be used in field data collection (see Orton 2000 for a full
discussion). Depending upon field conditions, surface collection, aerial photography
inspection, or test units of varying sizes may be suitable methods of data acquisition.
Whatever the method of data acquisition, strict spatial control must be maintained. The main
requirement is that the reliable density estimates of a artifact or feature be obtained, hence the
need for spatial control. The problem of reliable georeferencing of archaeological data is no
125
longer an issue with Global Positioning Satellite (GPS) technology. The location and
recording of data electronically (paperless data collection) and uploading to a GIS for spatial
analysis solves several problems that required considerable time and energy a decade ago.
One recent project in the study area (A. Mickelson 2000) collected data at the 40 m
grid size across 60 acres of land via a sampling strategy design in a GIS. The point sample
locations were then downloaded to a sub-meter accuracy GPS. A navigation utility within
the GPS allowed for easy location of the sampling unit in the field. In fact, the 40 m sampling
grid was never formally laid-out in the field. Once sampling units were located, and
excavated, artifact recovery along with environmental data was input to the GPS data
recorder. Upon returning to the lab, the data were uploaded to the GIS for spatial analysis.
This example fell short of a regional-scale application, as only two out several landforms were
tested. However, this study demonstrates the applicability of such an approach, its feasibility,
and cost-effectiveness as Orton (2000) predicted. Currently, with low-cost GPS receivers
possessing a 2-5 m level of precision, such methods should be employed ubiquitously in
archaeology survey.
A prime candidate for such an approach is federally mandated Cultural Resources
Management (CRM) survey-level work. After all, this is the research program responsible
for generating the bulk of the data utilized in this study. Although such work often contains
a research design formulated little beyond discovery goals, the siteless survey methodology
could be a boon to researchers. Traditional transect-level sampling techniques commonly
applied in CRM surveys are ideal for the siteless survey approach.
126
A change must occur in the reporting of the data to useable by others. We are no
longer talking about site inventory forms, but of georeferenced data from controlled surface
collections, or near-surface sampling (e.g., shovel test pits). The data cannot merely be
reported on the level of a site inventory form; each sampling unit or collection point must
carry with it locational information. A large amount of data are generated by this approach,
but its compilation and storage are fast, simple, and cost effective an issue under the GIS
environment.
Inexpensive storage of large volumes of data have been available for over a decade
now; there is no reason that the information should be left out of a report, perhaps included
on a CD-ROM. Even better, access to the data could be facilitated via the internet. At least
in eastern North America, the resulting database would not consist of sites delineated as
polygons, or of points indicating isolated finds. The database would contain the locations of
tens of thousands of shovel tests and surface data points with corresponding information on
artifact recovery and local environmental variables. Dozens of unrelated survey-level data
accumulated in this manner across a region would allow for researchers to address
innumerable research questions. In a realistic vein, such data collection programs will not
occur unless there is a policy change at the federal level, specifically a change in the current
Department of Interior Standards. But, data collection strategies, as promulgated by State
Historic Preservation Offices need to recognize that as guidelines currently stand, much is
being lost.
127
Recognizing that the above scenario is not currently likely to receive much
consideration, there are a few “low-tech” ways that data collection and reporting may be
improved. The first improvement in field methodology would be to abandon the common
uncontrolled grab sample technique. This technique is often termed haphazard sampling
(Orton 2000). The only conceivable utility in the grab sample would be in emergency
archaeology situations where a deposit faces imminent destruction. Once the grab sample is
discarded from the archaeologist’s toolkit, simple transect sampling, either surface or
subsurface, should be implemented. Importantly, this technique must capture density
estimates that are reported along with artifact recovery. Density estimates either in terms of
artifacts per unit area or artifacts per unit volume are all that are necessary.
The first generation of regional-scale archaeology databases have now been completed
by several state historic preservation offices throughout the Midcontinent. The utility of such
databases as record keeping instruments is obviously invaluable. The question then arises as
to how to make these databases of utility to answer broad archaeological research questions.
It is only a matter of time before today’s GIS’s will be updated; now is the time to start
planning the second generation.
128
LIST OF REFERENCES
Applegate, D.
1997 Lithic Evidence of Prehistoric Rockshelter Use in Eastern Kentucky.
Unpublished Doctoral Dissertation. Department of Anthropology. The Ohio
State University.
Banning, E. B.
2000 The Archaeologist’s Laboratory: The Analysis of Archaeological Data.
Kluwer Academic/Plenum Publishers, New York.
Barbour, R. W.
1974 Vertebrates of the Red River Area, Kentucky. In Environmental Impact
Statement, Red River Lake, Kentucky River Basin. U. S. Army Corps of
Engineers.
Bettinger, R. L.
1991 Hunter-Gatherers. Archaeological and Evolutionary Theory. Plenum Press,
New York.
Binford, L.
1980
Willow Smoke and Dogs’ Tails: Hunter-Gatherer Settlement Systems and
Archaeological Site Formation. American Antiquity 45:4-20.
Branson, B. A. and D. L. Batch
1974 Fishes of the Red River Drainage. The University Press of Kentucky,
Lexington.
Braun, L.
1950
Deciduous Forests of Eastern North America. The Blakiston Company,
Philadelphia.
Broyles, B. J.
1966 Preliminary Report: The St. Albans Site (46 Ka 27), Kanawha County, West
Virginia. The West Virginia Archaeologist 19:1-43
129
Caldwell, J.
1962
1958
Eastern North America. In Courses Toward Urban Life, R. J. Braidwood and
G. R. Willey, editors, pp. 288-308. Aldine Publishing Company, Chicago.
Trend and Tradition in the Prehistory of the Eastern United States. Illinois
State Museum Scientific Papers 10, and American Anthropological
Association
Memoir 88.
Collins, M. B.(editor)
1979 Excavations at Four Archaic Sites in the Lower Ohio Valley Jefferson County,
Kentucky. Occasional Papers in Anthropology No. 1. Department of
Anthropology, University of Kentucky.
Cotterill, R. S.
1954 The Southern Indians. University of Oklahoma Press, Norman.
Cowan, C. W.
1997 Evolutionary Changes Associated with the Domestication of Cucurbita pepo:
Evidence from Eastern Kentucky. In People, Plants, and Landscapes, edited
by K. J. Gremillion, pp. 63-85. The University of Alabama Press, Tuscaloosa.
1985
Understanding the Evolution of Plant Husbandry in Eastern North America:
Lessons from Botany, Ethnography and Archaeology. In Prehistoric Food
Production in North America, R. I. Ford, editor, pp.149-204.
Anthropological Papers No. 75. Museum of Anthropology, University of
Michigan, Ann Arbor.
1984
From Foraging to Independent Food Production: Subsistence Change and
Continuity on the Cumberland Plateau of Eastern Kentucky. Unpublished Ph.
D. Dissertation. University of Michigan, Ann Arbor.
1979
Excavations at the Haystack Rockshelter, Powell County, Kentucky.
Midcontinental Journal of Archaeology 4:1-33.
1976
Test Excavations in the Proposed Red River Lake, Kentucky: 1974 Season.
Report Submitted to the National Park Service, Atlanta Georgia. University
of Kentucky, Museum of Anthropology.
1975
An Archaeological Survey and Reconnaissance of the Proposed Reservoir in
Powell, Wolfe, and Menifee Counties, Kentucky. Report Submitted to the
National Park Service, Tallahassee, Florida. University of Kentucky, Museum
of Anthropology.
130
Cowan, C. W., H. E. Jackson, K. Moore, A. Nickelhoff, and T. L. Smart
1981 The Cloudsplitter Rockshelter, Menifee County, Kentucky: A Preliminary
Report. In Southeastern Archaeological Conference Bulletin No. 24.
Cowan, C. W. and F. T. Wilson
1977 An Archaeological Survey of the Red River Gorge Area. The Kentucky
Heritage Commission, Frankfort.
Crawford, G.
1982 Late Archaic Plant Remains from West-central Kentucky: A Summary.
Midcontinental Journal of Archaeology 7(2): 205-224.
Dancey, W. S.
1971 The Archaeological Survey: A Reorientation. Paper Presented at the 36th
Annual Meeting of the Society for American Archaeology, Norman,
Oklahoma.
1973
Prehistoric Landuse and Settlement Patterns in the Priest Rapids Area,
Washington. University Microfilms, Ann Arbor.
1974
The Archaeological Survey: A Reorientation. Man in the Northeast 8:98112.
Delcourt, P. A. and H. R. Delcourt
1998 The Influence of Prehistoric Human-set Fires on Oak-Chestnut Forests in the
Southern Appalachians. Castanea 63:337-345.
Delcourt, P. A., H. R. Delcourt, C. R. Ison, W. E. Sharp, and K. J. Gremillion.
1998 Prehistoric Human Use of Fire, The Eastern Agricultural Complex, and
Appalachian Oak-Chestnut Forests: Paleoecology of Cliff Palace Pond,
Kentucky. American Antiquity 63:263-278.
Delorenze, G. N.
1979 A Reconnaissance and Evaluation of Archaeological Sites in Bell County,
Kentucky. Kentucky heritage Council Archaeological Survey Reports 12.
Kentucky Heritage Council, Frankfort.
Delorenze, G. N. and Weinland, M.
1980 A Reconnaissance and Evaluation of Archaeological Sites in Knox County,
Kentucky. Kentucky Heritage Council Archaeological Survey Reports 13.
Kentucky Heritage Council, Frankfort.
.
131
Dever, G. R. and L. S. Barron
1986 Red River Gorge Geological Area (Daniel Boone National Forest) and
Natural Bridge State Park, east-central Kentucky. Geological Society of
America Centennial Field Guide- Southeastern Section. Geological Society
of America, Boulder.
Donahue, and J. Adovasio
1990 Evolution of Sandstone Rockshelters in Eastern North America; A
Geoarchaeological Perspective. Archaeological Geology of North America.
Centennial Special Volume 4. The Geological Society of America. Boulder,
Colorado.
Dorwin, J. T., and Worholic, D. T.
1970 Archaeological Investigation of the Deep Shelter, Cave Run Reservoir Area,
Rowen County, Kentucky. National Park Service, Southeast Region,
Tallahassee.
Dunnell, R. C.
1972 The Prehistory of Fishtrap, Kentucky. Yale University Publications in
Anthropology Number 75. Department of Anthropology, Yale University.
New Haven.
1971
Systematics in Prehistory. The Free Press, New York.
Dunnell, R. C. and W. S. Dancey
1983 The Siteless Survey: A Regional Scale Data Collection Strategy. In Advances
in Archaeological Method and Theory Volume 6, M. B. Schiffer, editor, pp.
267-287. Academic Press, New York.
Ebert, J. I.
1992
Distributional Archaeology. University of New Mexico Press, Albuquerque.
Ettensohn, F. R., C. L. Rice, G. R. Dever, Jr., and D. R. Chesnut
1984 Slade and Paragon Formations- New Stratigraphic Nomenclature for
Mississippian Rocks along the Cumberland Escarpment in Kentucky. U.S.
geological Survey Bulletin 1605-B. Contributions to Stratigraphy. U. S.
Geological Survey, Boulder.
Evans, J. B.
1996
Raw Material Procurement and Lithic Technology at Enoch Fork Shelter
(15PE50), Kentucky. Unpublished Masters Thesis, University of Kentucky,
Lexington
132
Fenneman, N. M.
1938 Physiography of Eastern United States. McGraw-Hill Book Company, Inc.,
New York.
Fryman, F. B., Jr.
1967 An Archaeological Survey of the Red River Reservoir in Wolfe, Powell, and
Menifee Counties, Kentucky. A project of the Inter-Agency Archaeological
and Paleontological Salvage Program. Contract No. 910-728. Department
of the interior, Southeastern region, Richmond, Virginia.
Funkhouser, W. D. and W. S. Webb
1930 Rockshelters of Wolfe and Powell Counties, Kentucky. The University of
Kentucky Reports in Archaeology and Anthropology, No. 4. Publications of
the Department of Anthropology and Archaeology, university of Kentucky,
Lexington.
1929
The So-Called "Ash Caves". In The University of Kentucky Reports in
Archaeology Vol. I:2.
Gardner, P. S.
1997 The Ecological Structure and Behavioral Implication of Mast Exploitation
Strategies. In People, Plants and landscapes, edited by K. J. Gremillion,
pp.161-178. The University of Alabama Press, Tuscaloosa.
Granger, J. E.
1988 Late/Terminal Archaic Settlement in the Falls of the Ohio River Region of
Kentucky: An Examination of Components, Phases, and Clusters. In
Paleoindian and Archaic Research in Kentucky, edited by C. D.
Hockensmith, D. Pollack, and T. N. Sanders, pp. 153-204. Kentucky
Heritage Council, Frankfort.
Greenacre, M. J.
1993 Correspondence Analysis in Practice. Academic Press, New York.
Gremillion, K. J.
1996 Early Agricultural Diet in Eastern North America: Evidence from Two
Kentucky Rockshelters. American Antiquity, 61(3):520-536.
1995a Archaeological and Paleoethnobotanical Investigations at the Cold Oak
Shelter, Kentucky. Report submitted to the National Geographic Society,
Grant No. 5226-94.
133
1995b Botanical Contents of Paleofeces from Two Kentucky Rockshelters. In
Current Archaeological Research in Kentucky: Volume Three, edited by J.
F. Doershuk, C. A. Bergman, and D. Pollack, pp. 52-69. Kentucky Heritage
Council, Frankfort.
1994
Evidence of Plant Domestication from Kentucky Caves and Rockshelters.
In Archaeological Origins and Development in the Midcontinent, edited by
William Green, pp. 87-104. Office of the State Archaeologist, University of
Iowa, Report 19.
1993a Crop and Weed in Prehistoric Eastern North America: The Chenopodium
Example. American Antiquity, 58(3):496-509.
1993b The Evolution of Seed Morphology in Domesticated Chenopodium: An
Archaeological Case Study. Journal of Ethnobiology 13(2):149-169.
1993c Plant Husbandry at the Archaic/Woodland Transition: Evidence from the Cold
Oak Shelter, Kentucky. Midcontinental Journal of Archaeology, 18(2):161189.
Gremillion, K. J. and K. R. Mickelson
1997 Archaeological Survey and Assessment in Portions of the Big Sinking Creek
Drainage, Lee County, Kentucky. A report of investigations conducted by the
Ohio State University and supported by a Survey and Planning Grant
administered by the Kentucky Heritage Council.
1996
National Register Evaluation of the mounded Talus Shelter (15LE77), Lee
County, Kentucky. Report prepared for USDA, Forest Service, Winchester,
by the Ohio State University.
Gremillion, K. J. and K. D. Sobolik
1996 Dietary Variability among Prehistoric Forager-Farmers of Eastern North
America. Current Anthropology, 529-539.
Hall, C. and W. E. Klippel
1988 A Polythetic-Satisficer Approach to Prehistoric Natural Shelter Selection in
Middle Tennessee. Midcontinental Journal of Archaeology 13:159-186.
High, E. C.
1984
Past Titan Rock: Journeys into an Appalachian Valley. The University Press
of Kentucky, Lexington.
I
134
son, C. R.
2001
1991
The Use of Rock Art in Identifying Shifting Social Organization. Paper
present at the 66th Annual Meeting of the Society for American Archaeology,
New Orleans.
Prehistoric Upland Farming along the Cumberland Plateau. In Studies in
Kentucky Archaeology, edited by C. D. Hockensmith, pp. 1-10. Kentucky
Heritage Council, Frankfort.
1988 The Cold Oak Shelter: Providing a Better Understanding of the Terminal
Archaic. In Paleoindian and Archaic Research in Kentucky. Edited by, D.
Hockensmith, D. Pollack and T. N. Sanders, editors, pp. 205-221. The
Kentucky Heritage Council. Frankfort.
Ison, C. R., and J. Faulkner
1995 Documenting Inventory Strategies: Monitoring the Big Sinking Drainage, Lee
County, Kentucky. Draft on file, USDA Forest Service, Winchester,
Kentucky.
Ison, C. R. and G. D. Knudsen
1985 A Cultural Resource Assessment of the Smith and Isaacs land Exchange
Tracts, Jackson County, Kentucky, Berea District, Daniel Boone National
Forest, USDA Forest Service.
Jefferies, R. W.
1996 Hunters and Gatherers After the Ice Age. In Kentucky Archaeology, R. B.
Lewis, ed., pp 39-78. University of Kentucky Press, Lexington.
1988
Archaic period Research in Kentucky: Past Accomplishments and Future
Directions. In Paleoindian and Archaic Research in Kentucky, edited by C.
D. Hockensmith, D. Pollack, and T. N. Sanders, pp. 185-126. Kentucky
Heritage Council, Frankfort.
Jefferies, R. W. and M. B. Lynch
1983 Dimensions of Middle Archaic Cultural Adaptation at the Black Earth Site,
Saline County, Illinois. In Archaic Hunters and Gatherers in the American
Midwest, edited by J. L. Phillips and J. A. Brown, pp. 299-322. Academic
Press, New York.
Jones, V. H.
1936 The Vegetal Remains of Newt Kash Hollow Shelter. In Rockshelters of
Menifee County, Kentucky. Edited by W. S. Webb and W. D. Funkhouser,
pp.147-155. Reports in Anthropology and Archaeology No. 3. University of
Kentucky, Lexington.
135
Knudsen, G. D.
1983 Cultural Resource Inventory, Big Sinking Creek Oil Field, Daniel Boone
National Forest, Kentucky. USDA, Forest Service, Daniel Boone National
Forest.
Kreisa, P. P. and C. Stout
1991 Late Woodland Adaptations in the Mississippi and Ohio Rivers Confluence
Region. In Stability, Transformation, and Variation: The Late
Woodland
Southeast, edited by M. S. Nassaney and C. R. Cobb, Plenum
Press, New York.
Kvamme, K.
1990 One Sample Tests in Regional Archaeological Analysis: New Possibilities
Through Computer Technology. American Antiquity 55:367-381.
Lennstrom, H. A. and C. A. Hastorf
1992 Testing Old Wives’ Tales in Paleoethnobotany: A Comparison of Bulk and
Scatter Sampling Schemes from Pancán, Peru. Journal of Archeological
Science 19:205-229.
Lewis, R. B.
1996 Kentucky Archaeology. University of Kentucky Press, Lexington, Kentucky.
Machovina, B. J.
1996 Modelling of Pedestrian Mobility Across a Natural Landscape Using a
Geographic Information System. Part II of the Final report submitted under
National Park Service contract 6115-4-8031. Principal Investigator, D. F.
Marble, Department of Geography, The Ohio State University, Columbus.
Maschner, H. D. G.
1996 Geographic information Systems in Archaeology. In New Methods, Old
Problems: Geographic Information Systems in Modern Archaeological
Research, edited by H. D. G. Maschner, pp. 104-126. Center for
Archaeological Investigations, Occasional Paper No. 23. Southern Illinois
University at Carbondale.
Maynard, D. R. and T. W. Gatus
1979 A Reconnaissance and Evaluation of Archaeological Sites in Greenup County,
Kentucky. Unpublished Manuscript, Kentucky Heritage Council, Frankfort.
Marquardt, W. H. and P. J. Watson
1983 The Shell Mound Archaic of Western Kentucky. In Archaic Hunter and
Gatherers in the American Midwest, edited by J. L. Phillips and J. A. Brown.
Academic Press, New York.
136
Meadows, L. G.
1977 Chert Resources in Powell County in Concurrence with Aboriginal Use. In
A Reconnaissance and Evaluation of Archaeological Sites in Powell County,
Kentucky, edited by M. K. Weinland and T. N. Sanders, pp.98-122. Kentucky
Heritage Commission, Frankfort.
Meltzer, D. J.
1993 Is There a Clovis Adaptation? In From Kostenki to Clovis: Upper
Paleolithic-Paleo-Indian Adaptations, edited by O. Soffer and N. D. Praslov,
pp. 293-310. Plenum Press, New York.
1988
Late Pleistocene Adaptations in Eastern North America. Journal of World
Prehistory 2(1):1-52.
Mickelson, A. M.
2001a Mitigation of the Upper Portions of the Gladie Creek Site (15MF410). Red
River Gorge Geological Area, Daniel Boone National Forest, Stanton Ranger
District, Menifee County, Kentucky.
2001b Computer-Automated Data Collection from the Ground Up: A Distributional
Archaeology Pilot Study from the Cumberland Escarpment. Paper Presented
at the Kentucky Heritage Council Archaeology Meeting, Northern Kentucky
University.
2001c Integrated Use of GIS and GPS in a Distributional Archaeology Survey
Located in the Upper Red River Valley, Kentucky. Manuscript in possession
of the author.
2001d Plant Domestication and the Origins of Agriculture in Eastern North America:
A GIS perspective of Prehistoric Land Use from the Red River Valley in
Eastern Kentucky. Poster presented at the 66th Annual Meeting of the Society
for American Archaeology, New Orleans.
2000a Measuring the Facing Aspect of Archaeological Sites: GIS and Traditional
Methods Compared. Poster presented at the 65th Annual Meeting of the
Society for American Archaeology, Philadelphia.
2000b Doctoral Dissertation Improvement Grant: Plant Domestication and the
Origins of Agriculture on the Cumberland Escarpment, Eastern Kentucky.
Proposal submitted to the National Science Foundation.
137
Mickelson, K. R.
2002 Formation Processes, Macrobotanical Preservation, and Middle Archaic Plant
Exploitation: A Geochemical Approach to the Understanding of Plant
Preservation From Dry Deposits at the Mounded Talus Rockshelter, Eastern
Kentucky. Unpublished Dissertation. Department of Anthropology, Ohio
State University, Columbus.
2001a Issues in Archaeobotanical Preservation: A Geochemical Approach. Paper
Presented at the 66th Annual Meeting of the Society for American
Archaeology, New Orleans.
2001b The Application of Phytolith Analysis to Archaeology: eastern Kentucky in
Context. Paper presented at the Kentucky Heritage Council Archaeology
Meeting, Northern Kentucky University.
2000
Nance, J. D.
1988
Sediment Composition and the Preservation of the Macrobotanical Remains
at mounded Talus Rockshelter (15LE77), Lee County, Kentucky. Paper
presented at the 65th Annual Meeting of the Society for American
Archaeology, Philadelphia.
Archaic Period Research in the Lower Tennessee-Cumberland-Ohio Region.
In Paleoindian and Archaic Research in Kentucky. Edited by, D.
Hockensmith, D. Pollack and T. N. Sanders, pp. 127-153 . The Kentucky
Heritage Council. Frankfort.
1987 The Archaic Sequence in the Lower Tennessee-Cumberland-Ohio Region.
Southeastern Archaeologist 6:129-155.
1986
The Morrisroe Site: Projectile Point Types and Radiocarbon Dates from the
Lower Tennessee Valley. Midcontinental Journal of Archaeology 11(1):1150.
O’Steen, L. D., K. J. Gremillion, and R. J. Ledbetter
1991 Archaeological Testing of Five Sites in the Big Sinking Creek Oil Field, Lee
County, Kentucky. Report prepared for the USDA, Forest Service,
Winchester.
Pollack, D. and G. Henderson
2000 Late Woodland Cultures in Kentucky. In Late Woodland Societies: Tradition
and Transformation across the Midcontinent, edited by T. E. Emerson, D. L.
McElrath, and A. C. Fortier, pp.613-642. University of Nebraska Press,
Lincoln.
138
Purrington, B. L.
1967 Prehistoric Horizons and Traditions in the Eastern Mountains of Kentucky.
Unpublished Master’s Thesis. University of Kentucky, Lexington.
Purrington, B. L. and D. G. Smith
1967 Preliminary Excavations at the Roberts Site, Bh-7, Bath County, Kentucky.
National Parks Service, Southeast Region, Tallahassee.
Rafferty, J.
1995
Gradual or Step-Wise Change: The Development of Sedentary patterns in
Northeast Mississippi. American Antiquity 59:405-425.
Railey, J. A.
1996 Woodland Cultivators. In Kentucky Archaeology, edited by R. B. Lewis, pp
79-127. The University Press of Kentucky, Lexington.
1990
Rossen, J. R
1988
Woodland Period. In The Archaeology of Kentucky: Past Accomplishments
and Future Directions, Vol 1. Edited by D. Pollack. Kentucky Heritage
Council, State Historic Preservation Comprehensive Plan report No. 1,
Frankfort Kentucky.
Botanical Remains. In, Muir, An Early Fort Ancient Site in the Inner
Bluegrass. Archaeological Report No. 165. Program for Cultural Resource
Assessment, Department of Anthropology. University of Kentucky,
Lexington
Sable, E. G. and G. R. Dever
1990 Mississippian Rocks in Kentucky. U. S. Geological Survey Professional paper
1503. U. S. Government Printing Office, Washington.
Sanders, T. N.
1976 Archaeological Survey and testing Excavations in the Proposed Paintsville
Lake Reservoir Project , Museum of Anthropology, University of Kentucky,
Lexington.
Sanders, T. N., and T. W. Gatus
1977 A Reconnaissance and Evaluation of Archaeological Sites in Floyd County,
Kentucky. Kentucky Heritage Council, Frankfort.
Sassaman, K. E. and R. J. Ledbetter
1996 Middle and Late Archaic Architecture. In Archaeology of the Mid-Holocene
Southeast, edited by K. E. Sassaman and D. G. Anderson, pp.75-98. Florida
Museum of Natural History, University of Florida Press, Gainesville, Florida.
139
Schuldenrein, J.
1996 Geoarchaeology and the Mid-Holocene Landscape History of the Greater
Southeast. In Archaeology of the Mid-Holocene Southeast, edited by K. E.
Sassaman and D. G. Anderson, pp. 3-27. Florida Museum of Natural
History, University of Florida Press, Gainesville, Florida.
Schwartz, D. M.
1967 Conceptions of Kentucky Prehistory: A Case Study in the History of
Archaeology. Studies in Anthropology No. 6. University of Kentucky Press,
Lexington.
Seeman, M. F.
1992 Woodland Trends in the Midcontinent. Research in Economic Anthropology,
Supplement 6, pp. 3-46. JAI Press Inc.
Seeman, M. and W. S. Dancey
2000 The Late Woodland in Southern Ohio: Basic Issues and Prospects. In Late
Woodland Societies: Tradition and Transformation across the Midcontinent,
edited by T. E. Emerson, D. L. McElrath, and A. C. Fortier, pp. 583-612.
University of Nebraska Press, Lincoln. .
Sharp, W. E.
1997 Management Summary of a Phase I Cultural resource Survey of the Berea
North Timber Sale and Associated tracts, Jackson County, Kentucky, Berea
Ranger District, Investigations 96-13-MS3. Report on file at Daniel Boone
National Forest, Winchester.
1996
Fort Ancient Farmers. In Kentucky Archaeology, edited by R. B. Lewis, pp
161-182. The University Press of Kentucky, Lexington.
Smith, B. D. and C. W. Cowan
1987 Domesticated Chenopodium in Prehistoric Eastern North America: New
Accelerator Dates from Eastern Kentucky. American Antiquity, 52(2):355357.
Tankersley, K. B.
1996 Ice Age Hunters and Gatherers. In Kentucky Archaeology, edited by R. B.
Lewis, pp 21-38. The University Press of Kentucky, Lexington.
Thompson, R. L., R. L. Jones, J. R. Abbott, W. N. Denton
2000 Botanical Survey of Rock Creek Research Natural Area, Kentucky. United
States Department of Agriculture, Forest Service. Northeastern Research
Center Technical Report NE-272.
140
Tomlin, C. D.
1990 GIS and Cartographic Modeling. Prentice-Hall, New York.
Turnbow, C. A.
1976 An Archaeological Survey of the Red River Gorge Geological Area in Daniel
Boone National Forest in Powell, Wolfe, and Menifee Counties, Kentucky.
Report submitted to the National Forest Service, Winchester, Kentucky.
Contract No. 38-2830.
Turnbow, C. A. and W. E. Sharp
1988 Muir, An Early Fort Ancient Site in the Inner Bluegrass. Archaeological
Report No. 165. Program for Cultural Resource Assessment, Department of
Anthropology. University of Kentucky, Lexington.
U. S. Army Corps of Engineers
1977 Kentucky Water resources Development. U. S. Army Corps of Engineers,
Ohio River Division.
1974
Final Environmental Impact Statement, Red River Lake Project, Kentucky.
Prepared by U. S. Army Engineer District, Louisville.
USDA Forest Service
1974 USDA Forest Service Environmental Statement, Red River Gorge Unit-12,
Daniel Boone National Forest, Winchester. [Final Environmental Impact
Statement.]
Vickery, K.
1999
The Archaic Period in Ohio. Paper presented at the 7th Ohio Archaeological
Conference on Archaeology. Cincinnati.
Watson, P. J.
1991 Early Plant Cultivation in the Southwest and the Eastern Woodlands: Pattern
and Process. In Puebloan Past and Present, Papers in Honor of Stewart
Peckman, edited by M. S. Duran and D. T. Kirkpatrick. The Archaeological
Society of New Mexico: 17.
1988 Prehistoric Gardening and Agriculture in the Midsouth. In Interpretations of
Culture Change in the Eastern Woodlands during the Late Woodland Period.,
edited by R. Yerkes, pp. 39-67. Department of Anthropology. Ohio State
University, Columbus.
1985
The Impact of Early Horticulture in the Upland Drainages of the Midwest and
the Midsouth. In Prehistoric Food Production in North America, edited by
R. I. Ford, pp. 99-148. Museum of Anthropological Papers No. 75.
University of Michigan, Ann Arbor.
141
1974
Archaeology of the Mammoth Cave Area. Academic Press. Orlando.
Webb, W. S., and R. Baby
1957 The Adena People No. 2. Ohio Historical Society, Columbus.
Webb, W. S. Webb and W. D. Funkhouser
1932 Archaeological Survey of Kentucky. The University of Kentucky Reports in
Archaeology and Anthropology. Volume II.
1936
Rockshelters of Menifee County, Kentucky. Reports in Anthropology and
Archaeology No. 3. University of Kentucky, Lexington.
Webb, William S. and C. E. Snow
1945 The Adena People. In The University of Kentucky Reports in Archaeology.
Vol. 6.
Weinland, M. K. and T. N. Sanders
1977 A Reconnaissance and Evaluation of Archaeological Sites in Powell County,
Kentucky. Kentucky Heritage Council, Frankfort.
Weir, G. W.
1974a Geologic Map of the Stanton Quadrangle, Powell and Estill Counties,
Kentucky. Map GQ-1182. United States Geological Survey, Reston,
Virginia.
Weir, G. W.
1974b Geologic Map of the Slade Quadrangle, east-central Kentucky. Map GQ1183. United States Geological Survey, Reston, Virginia.
Weir, G. W. and P. W. Richards
1974 Geologic Map of the Pomeroyton Quadrangle, east-central Kentucky. Map
GQ-1184. United States Geological Survey, Reston, Virginia.
Wyss, J. D. and S. K. Wyss
1977 An Archaeological Assessment of Portions of the Red River Gorge, Daniel
Boone National Forest, Kentucky. Ohio Valley Archaeological Consultants.
Report prepared under contract 38-3040 for the USDA, Forest Service,
Daniel Boone National Forest, Winchester.
142
APPENDIX A: FIGURES
143
Figure 1. Location of the study area.
144
Figure 2. Stratigraphic profile of the geology of the North Fork of the Red River valley.
145
Figure5.ViewoftheNorthForkoftheRedRivershowingarchaeologicalsitesinrelationtofourprincipallandformclasses.
Figure 6. Schematic illustrating the division of the landsurface into discrete land classes
upon the basis of slope, elevation, and facing aspect (see also Table 6).
149
45
40
Environs
35
Sites
percent
30
25
20
15
10
5
0
180-215
216-250
251-285
286-320
321-355
356-390
391-425
426-460
elevation (m)
Figure 7. Histogram illustrating prehistoric site distribution (n=319 components with
respect to the environment for the variable elevation.
45
40
Environs
35
Sites
percent
30
25
20
15
10
5
0
180-215
216-250
251-285
286-320
321-355
356-390
391-425
426-460
elevation (m)
Figure 8. Histogram illustrating prehistoric site (n=319 components) distribution
with respect to the environment for the variable slope.
150
19
17
percent
15
13
11
9
7
5
N
NE
E
SE
S
SW
W
NW
facing aspect
Environs
Sub-sample
OSA sites
Figure 9. Histogram presenting prehistoric site distribution with respect to the
environment for the variable aspect. OSA sites (n=859) taken from the Escarpment
region only. Subsample (n=319) are sites from the Spatial Analysis database. Note that
the environment is nearly constant for each aspect class, ranging between 11 and 14
percent.
30
25
Environs
Sites
percent
20
15
10
5
0
Low Level
Low er Slope
Mid-Slope
Upper Slope
Upland Level
ecological setting
Figure 10. Histogram illustrating prehistoric site (n=319 componentsdistribution
with respect to the five ecological strata (refer back to Table 7.1).
151
90
80
70
count
60
50
40
30
20
10
0
Low level
Low er slope
Mid-slope
Upper Slope
Upland level
ecological strata
Open-air
Rockshelter
Figure 11. Histogram illustrating the distribution of the site classes open-air (n=123)
and rockshelter (n=319) across the five ecological strata.
0.25
0.2
frequency
Environs
Sites
0.15
0.1
0.05
750
700
650
600
550
500
450
400
350
300
250
200
150
100
50
0
distance to water (m)
Figure 12. Histogram illustrating site distributions (n=319 components) with
respect to landform (cell) distributions for the variable distance to water. Stream
data is at 1:24,000 scale as shown on USGS topographic maps.
152
120
100
count
80
60
40
20
L. Prehist
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch
Paleo
0
period
3
2.5
2
1.5
1
0.5
L. Prehist
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch
0
Paleo
mean number of components
Figure 13. Per period distribution of 319 components used to study diachronic landuse
practices.
period
Figure 14. Degree of temporal overlap in the archaeological record as measured by mean
number of components per location (site). The mean for the entire dataset (n=319) is 2.2
components per locus. The highest rate of mixing occurs for the Middle Archaic period.
153
45
40
35
percent
30
25
20
15
10
5
0
1
2
3
4
5
6
7
number of components per locus
Figure 15. Percent of loci (sites) with one to seven components. Loci with less than
three components constitute 77 percent of the total sample (n=319).
335
mean elevation (m)
330
325
320
315
310
305
300
L. Prehist
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch
Paleo
295
period
Figure 16. Mean elevations for components (n=319) belonging to each period
class. The mean for the environment is 310 m.
154
10
slope (degrees)
9
8
7
6
5
4
3
2
1
L. Prehist
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch
Paleo
0
period
Figure 17. Mean slope value for 319 components belonging to given time class. The
mean for the background environment is 8.2 degrees.
160
open-air
130
rockshelters
all sites
M. Wood
aspect index
140
E. Wood
150
120
110
100
90
80
70
L. Prehist
L. Wood
L. Arch
M. Arch
E. Arch
Paleo
60
period
Figure 18. Aspect indices for components within each time class (n=319). A value
of zero indicates maximum North. A value of 180 indicates due South. Rockshelter
occupations are more southerly oriented than open-air occupations.
155
16
Low level
14
Low slope
12
count
10
8
6
4
2
L. Prehist
L. Wood.
M. Wood.
E. Wood.
L. Arch.
M. Arch
E. Arch.
Paleo
0
period
Figure 19. Component counts per period for the low level (n=66) and lower slope
(n=30) ecological strata.
16
14
12
count
10
8
6
4
2
period
Figure 20. Component counts for the mid-slope stratum (n=40).
156
L. Prehist
L. Wood.
M. Wood.
E. Wood.
L. Arch.
M. Arch
E. Arch.
Paleo
0
40
count
35
30
Up slope
25
Up level
20
15
10
5
L. Prehist
L. Wood.
M. Wood.
E. Wood.
L. Arch.
M. Arch
E. Arch.
Paleo
0
period
Figure 21. Component counts for the upland slope (n=95) and upland level (n=88)
land strata.
0.7
0.6
hectares
0.5
0.4
0.3
0.2
0.1
pe riod
Figure 22. Mean site area per period (n=319).
157
L. Prehist.
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch.
Paleo
0
800
700
square meters
600
500
400
300
200
100
L. Prehist.
L. Wood
M. Wood
E. Wood
L. Arch
M. Arch
E. Arch.
Paleo
0
period
Figure 23. Minimum site area per period (n=319).
2
1.8
1.6
hectares
1.4
1.2
1
0.8
0.6
0.4
0.2
L. Prehist
L.Wood.
M. Wood.
E. Wood.
L. Arch
M. Arch.
E. Arch.
Paleo
0
period
Figure 24. Mean area per period for sites located in the low level land stratum (n=66
components).
158
2
1.8
1.6
hectares
1.4
1.2
1
0.8
0.6
0.4
0.2
L. Prehist
L.Wood.
M. Wood.
E. Wood.
L. Arch
M. Arch.
E. Arch.
Paleo
0
period
Figure 25. Mean site area for components located in the lower slope ecological stratum
(n=30).
0.5
0.45
0.4
hectares
0.35
0.3
0.25
0.2
0.15
0.1
0.05
L. Prehist
L.Wood.
M. Wood.
E. Wood.
L. Arch
M. Arch.
E. Arch.
Paleo
0
period
Figure 26. Mean site area for sites located within the mid-slope stratum (n=40).
159
0.4
0.35
hectares
0.3
0.25
0.2
0.15
0.1
0.05
L. Prehist
L.Wood.
M. Wood.
E. Wood.
L. Arch
M. Arch.
E. Arch.
Paleo
0
period
Figure 27. Mean site are per period for the upland slope ecological stratum (n=95).
0.5
0.45
0.4
hectares
0.35
0.3
0.25
0.2
0.15
0.1
0.05
period
Figure 28. Mean site area per period for the upland level land stratum (n=88).
160
L. Prehist
L.Wood.
M. Wood.
E. Wood.
L. Arch
M. Arch.
E. Arch.
Paleo
0
1
0.9
0.8
Paleo
E. Arch.
M. Arch.
hectares
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
low level
low slope
mid-slope
upslope
up level
ecological strata
Figure 29. Mean site area per period for the five ecological strata (n=319
components).
1.8
1.6
1.4
L. Arch
E. Wood.
hectares
1.2
1
0.8
0.6
0.4
0.2
0
low level
low slope
mid-slope
upslope
up level
ecological strata
Figure 30. Mean site area for Late Archaic (n=53) and Early Woodland (n=48)
periods for the five ecological strata.
161
0.45
0.4
0.35
M. Wood
L. Wood.
hectares
0.3
0.25
0.2
0.15
0.1
0.05
0
low level
low slope
mid-slope
upslope
up level
ecological strata
Figure 31. Mean site area for Middle Woodland (n=35) and Late Woodland (17) periods
across five ecological strata.
2
1.8
1.6
hectares
1.4
1.2
1
0.8
0.6
0.4
0.2
0
low level
low slope
mid-slope
upslope
up level
ecological strata
Figure 32. Mean site area for Late Prehistoric components (n=111) across the five
ecological strata.
162
Figure 33. Centered bar graph showing the degree to which dated components are represented for a given landform class
(see also Tables 10 and 11). For each row, the sum of all bars is 100 percent. For example, the low level land class contains the
following distribution (percent) per period: Paleo Indian (4.5), Early Archaic (15.2), Middle Archaic (13.6), Late Archaic
(12.1), Early Woodland (12.1), Middle Woodland (15.2), Late Woodland (4.5), and Late Prehistoric (22.7). Therefore, the Late
Prehistoric period has the highest number of components for the low level land class. Each column indicates the relative landuse
pattern for each period. For example, the Paleo Indian period pattern is dichotomous between the lowlands and the uplands.
Figure34. Centered bar graph illustrating the proportion of mean site area per period for each land class (Tables 11 and 12). The
bars in each row sum to 100 percent. Sites located in the low level land class tend to be more even throughout prehistory. Site
Each column indicates the relative site area for each period across the five landform strata. For example, the Paleo Indian period
Contains larger sites in the Upland level land and Low level land classes. The Late Prehistoric period has significantly smaller
sites in the uplands than in the lowlands.
Figure 35. Correspondence analysis plot for the variables mean site area per period for each
land class or ecological stratum.
165
Figure 36. Correspondence analysis plot for the variables mean site area per period for each
land class or ecological stratum.. Row data are the archaeological periods and the column
data are landform strata.
166
Figure 37. Consolidation of landform strata for purposes of discussion and analysis.
167
Figure 38. Schematic representing hypothesized landuse changes through time within the
study area.
168
APPENDIX B: TABLES
169
Table 1. Cultural chronology of the region.
Period
Sub-period
Pre-Paleo
Indian
Paleo
Indian
Archaic
Woodland
Late
Prehistoric
Range (years B.P.)
before 12,000
Early
12,000-11,000
Middle
11,000-10,500
Late
10,500-10,000
Early
10,000-8,000
Middle
8,000-5,000
Late
5,000-3,000
Skidmore
Early
3,000-1,800
Cogswell (Terminal Archaic)
Middle
1,800-1,500
Adena-Hopewell
Late
1,500-1,000
Newtown-like
Early
1,000-800
Croghan
Middle
800-600
Manion
Late
600-450
Gist
450-250
Montour
Early
250-200
Euro-American
Exploration/Replacement
Middle
200-80
Agricultural Development
Late
80-50
Resource Extraction-Agriculture
50-0
Industrial-Agricultural-ExtractiveTourism
Historic
Present
Phase/Culture
170
Table 2. The most prevalent tree species according to landform type.
Tree Species
N Slope1 NE Slope2
S Slope1 SW Slope2 Total %
Tsuga canadensis
32.15
29.25
31.3
38.55
10.9
28.5
Fagus grandifolia
28.8
23.65
23.5
16.75
12.7
21.1
Quercus sp.
1.0
0.5
4.4
20.45
32.8
11.8
Liriodendron sp.
12.8
13.95
10.3
8.1
8.6
10.8
Acer saccharum
3.2
3.9
12.9
5.5
0.9
5.3
Tilia sp.
2.15
14.05
-
-
8.2
4.9
Acer rubrum
9.15
2.2
5.9
1.9
-
3.8
Magnolia sp.
0.45
5.0
5.1
1.75
2.3
2.9
Betula lenta
3.95
-
4.0
0.85
2.7
2.3
Nyssa sylvatica
1.25
-
-
4.3
4.6
2.0
Pinus sp.
-
-
-
0.6
7.3
1.5
Juglans nigra
-
-
-
0.85
6.4
1.5
Aesculus sp.
1.05
2.8
0.4
-
-
0.8
Castanea dentata
1.7
2.2
-
-
-
0.8
Ilex opaca
2.2
-
1.1
-
.04
0.7
Oxydendrum sp.
0.45
-
0.4
-
1.8
0.5
Carya sp.
-
0.5
0.7
.3
-
0.3
Fraxinus sp.
-
0.6
-
-
-
0.1
Ulmus americana
-
0.6
-
-
-
0.1
Sassafras albidum
-
-
-
-
0.4
0.08
100
99
100
99
99
99.78
Total
1
Gorge1
Data derived from Braun (Table 15). 2 Data derived from Thompson et al. (2000: Tables 2 and 3).
171
Table 3. General Database Characteristics.
Database Name
Description/Characteristics
Office of State
Archaeology (OSA)
Spatial, temporal, environmental site
attributes
1399
Chronology
Total
413
Unassigned prehistoric
248
Prehistoric w/ assigned period
124
Historic period components
63
Portable lithic artifacts
Total
400
Non-portable rock
features
Total
62
Petroglyphs
36
Bedrock mortars
30
Both petroglyphs and mortars
8
Prehistoric ceramics
Total
78
Biotic artifacts
Total
155
Components with fauna data
136
Components with flora data
74
Components with both flora and fauna
54
Modified biotic artifacts
Spatial Analysis
Database
No. of
Components
23
Data with spatio-temporal attributes
aggregated from above sources
and merged with “cleaned” OSA
Database
172
319
Table 4. Definition of the ecological (landform) grid.
Stratum
(substrata)
Basis for Membership
(N, E, S, W, slopes)
Low Level Land
< 310 m elevation, # 5° slope
17.8
Lower Slope
< 310 m elevation, >5° slope
27.8
Middle Slope
$ 310 m elevation, # 348 m elevation, >5° slope
18.9
Upper slope
> 348 m elevation, >5° slope
16.9
Upper Level Land
$ 310 m elevation, # 5° slope
18.3
173
Percent of
Study Area
Table 5. Diachronic considerations for the ecological model (Schuldenrein 1996 and
Donahue and Adovasio 1990; Delcourt et al. 1998).
Period
Geomorphology
Vegetation/Ecology
Pleistocene
(Before 10,000 B.P.)
Low Level Land Stratum - Formation of
large Quaternary age Terraces along the
Red River, hydrological response to
glacial-induced changes along the Ohio
River system. Meandering systems along
larger river systems in study area. Massive
flood events likely to have occurred.
Low Level Land Stratum Volatile Riverine Forest System
and/or open grasslands in pockets?
Lower Slope Stratum - Formation of the
upper portions of colluvial foot slopes;
stabilization, except for biomantle,
occasional sheet wash by beginning of the
Holocene.
Lower Slope Stratum - Cool
temperate forest type with many
mixed mesophytic species present.
Mid-Slope Stratum - Formation of
rockshelters during the Illinoian and
Wisconsin glaciation, when down-cutting
of drainages established the Ohio River
system.
Early Holocene
(10,000-7,000 B. P.)
Upper Strata - Continued erosion and
down-cutting of the peneplain.
Upper Strata - Boreal-like to cool
temperate forest type, with mixed
mesophytic species present.
Low Level Land Stratum - Continued
flux along the floodplains of larger-order
stream systems, beginning of
entrenchment of larger streams. Large
flood events, meters of sediment deposited.
Low Level Land Stratum Continued instability of
riverine/floodplain vegetation
regime.
Lower Slope Stratum - Stabilization of
upper ~0.5 m of colluvial foot slopes, with
biomantle formation probably occurring;
sheet wash, landslides in some areas of
higher slope.
Upper Strata - Quasi-stable? Resembling
later landforms? Continued landslides and
erosional episodes take place.
174
Lower Slope Stratum - increased
representation of the establishment
of the mixed-mesophytic forest
species.
Upper Strata - Cool temperate
forest becomes more mesophyticlike. Uplands dominated by spruce
and white cedar.
(Continued.)
(Table 5. Continued.)
Period
Geomorphology
Vegetation/Ecology
Middle
Holocene
7,0003,000 B. P.
Low Level Land Stratum - Stabilization of
floodplains, high-order streams mostly
entrenched, except for occasional
oxbow/channel reorientation biomantle
formation processes mixed with little deposition
of sediment from over-bank flooding. No more
than 0.6 m deposition.
Low Level Land Stratum - Reduced
volatility in the riverine/floodplain
regime, predictable wetland resources at
floodplain/colluvial interface.
Upper Strata - Biomantle formation on
colluvial landforms hypothesized; relatively
stable, except along areas with slope wash.
Occasional landslides on slopes.
Late
Holocene
3,000-200
B.P.
Historic
period
200-0 B. P.
Upper Strata - Establishment of mixed
mesophytic composition. Increase in
oaks, extension of the mixed-mesophytic
forest type into the uplands, replacing
white cedar. Hemlock species greatly
reduced by ca. 4800 B. P., red cedar
increases after this period, especially on
mid-slopes. Appearance of some wild
species of future domesticates at the
beginning of the period; domesticated
varieties appear during the last half of
the period.
Low Level Land Stratum - Continued quasistable floodplains, Artifacts minimally buried to
exposed in surface contexts, probable biomantle
formation coupled with infrequent low-level
sediment deposition due to flooding. No more
than 0.5 m of deposition.
Low Level Land Stratum - Same as
Mid-Holocene.
Upper Strata - continued terminal MidHolocene pattern.
Upper Strata - Same as Mid-Holocene,
with increased presence of fire-tolerant
species and reduction of red cedar.
Increased representation of ash.
Cultigen
species present in palynological record.
Low Level Land Stratum - creation of plow
zones, draining of wetlands, major alteration of
drainage systems through re-channeling,
damming, etc.
All Strata - deforestation due to
logging, introduction of foreign species.
Extinction of chestnut.
Lower Slope Stratum - farming in the 19th 20th centuries - erosion of colluvial slopes at
rapid rate.
Upper Strata- exploited for timber, erosion as
a result.
175
Table 6. General statistics pertaining to all archaeological sites (n=319) with respect to the
background environment. Data used are from the Spatial Analysis Database.
Background Environment
Archaeological Sites
Variable
Min
Min
Elevation (m)
180.0
460.0
309.7
54.8
Slope (Degrees)
0.0
61.0
8.2
Facing Aspect
(360 degrees)
0.0
360.0
Facing Aspect
( 0-180)
0.0
180.0
Max
Mean
Std.
Dev.
Max
Mean
Std.
Dev.
191.0
436.0
323.0
68.4
6.9
0.0
41.3
7.3
6.2
175.0
103.3
0.0
358
170.0
98.4
91.8
51.6
0.0
180
97.0
54.0
Table 7. Frequencies of ecological strata compared to settings of archaeological sites.
Ecological Strata
(Land Classes)
Background Environment
(Percent)
Archaeological Sites
(Percent)
Low Level Land
17.8
26.0
Lower Slope
27.8
9.4
Mid-Slope
18.9
12.5
Upper Slopes
16.9
29.8
Upper Level Land
18.3
27.6
176
Table 8. Lithic diversity index for 52 components coded in the portable lithic artifact
database.
Period
Mean Diversity Max Diversity
Std. Dev.
Count
Paleo Indian
3.5
3.5
0.0
1
E. Archaic
2.5
2.8
0.4
2
M. Archaic1
3.0
3.0
0.0
1
L. Archaic
3.2
8.5
3.1
5
E. Woodland
3.4
8.0
1.9
12
M. Woodland
2.9
7.0
2.1
8
L. Woodland
3.0
5.0
2.8
2
L. Prehistoric.
2.4
4.0
1.0
22
Total
53
Gladie Creek (A. Mickelson 2001d) Middle Archaic biface data were added to the the
portable tool lithic database.
1
Table 9. Measures of diversity including both ceramics and stone tools.
Period
Mean Diversity
Max Diversity
Std. Dev.
Count
E. Woodland
4.3
9.0
2.5
8
M. Woodland
3.4
8.0
2.3
8
L. Woodland
3.1
5.0
2.6
2
L. Prehistoric
3.0
5.0
1.1
14
Total
37
177
Table 10. Site count data used to create centered bar graph Figures 33 and 34.
Landform
Paleo
E. Arch. M. Arch. L. Arch. E. Wood. M. Wood. L. Wood. L. Prehist. Total
Low level
3
10
9
8
8
10
3
15
66
Low slope
0
3
0
5
7
4
1
10
30
Mid-slope
1
2
0
5
10
5
2
15
40
Up slope
2
6
5
16
14
7
6
39
95
Up level
2
7
5
19
9
9
5
32
88
Total
8
28
19
53
48
35
17
111
319
.
Table 11. Percentage data used to create centered bar graph Figures 33 and 34.
Landform Paleo
E. Arch. M. Arch.
L. Arch.
E. Wood. M. Wood. L. Wood. L. Prehist. Total
Low level
4.5
15.2
13.6
12.1
12.1
15.2
4.5
22.7
100
Low slope
0
10.0
0
16.7
23.3
13.3
3.3
33.3
100
Mid-slope
2.5
5.0
0
12.5
25.0
12.5
5.0
37.5
100
Up slope
1.0
7.4
5.3
16.8
14.7
7.4
6.3
41.1
100
Up level
2.2
8.0
5.7
21.6
10.2
10.2
5.7
36.4
100
Table 12. Mean site area in hectares per period per landform.
Landform Paleo
E. Arch. M. Arch. L. Arch. E. Wood. M. Wood. L. Wood. L. Prehist. Total
Low level .749
.567
1.01
1.744
.852
.400
.436
1.941
7.699
Low slope
.151
0
.652
1.140
.107
.354
1.887
4.291
Mid-slope .078
.105
0
.398
.477
.124
.150
.110
1.442
Up slope
.09
.0855
.295
.3172
.381
.122
.203
.180
1.6737
Up level
.392
.362
.480
.303
.229
.305
.16
.220
2.451
1.2705
1.785
3.4142
3.079
1.058
1.303
4.338
17.56
0
Total Ha 1.309
178
Table 13. Salient features of the forager and collector model.
Parameter
Forager
Collector
Environment
even
patchy
Settlements
residential base
residential base
extractive location (many)
extractive location (many)
processing location
(few, less diverse variants )
processing location
(many, more diverse variants)
residential
logistical
high
low
generalized
(low assemblage diversity)
specialized
(high assemblage diversity)
low
high
Mobility
Technology
Storage Rates
179
Table 14. Distributions of sites based on site size across landform strata.
Stratum
Site Type
Lowlands
Mid-slopes
Uplands
Pattern I (Paleo Indian, Early Archaic, Middle Archaic)
Large Sites
%
-
%
Small Sites
-
%
-
Pattern II (Late Archaic, Early Woodland)
Large Sites
%
%
-
Small Sites
%
%
%
Pattern III (Middle Woodland, Late Woodland)
Large Sites
%
-
%
Small Sites
%
%
%
Large Sites
%
-
-
Small Sites
%
%
%
Pattern IV (Late Prehistoric)
180
Table. 15. Schematic for four settlement patterns inferred from distributional data.
Stratum
Site Type
Lowlands
Mid-slope
Uplands
Pattern I (Paleo Indian, Early Archaic, Middle Archaic)
Residential Base
1
3
1
Extractive Location
1
2
1
Processing Location
3
2
3
Pattern II (Late Archaic, Early Woodland)
Residential Base
1
1
3
Extractive Location
1
1
1
Processing Location
2
2
2
Pattern III (Middle Woodland, Late Woodland)
Residential Base
1
2
3
Extractive Location
1
1
1
Processing Location
2
2
1
Residential Base
1
3
3
Extractive Location
1
1
1
Processing Location
2
1
Level of certainty for presence: 1 - high; 2 - medium; 3 - low.
1
Pattern IV (Late Prehistoric)
181
Appendix C: Code Sheet Keys For Database Files
182
Chronology Database Code Sheet
Description:
This database code sheet is for the chrono.pdf data base.
Database Contents: This data base contains records regarding temporal affiliation(s) of
sites. Data acquired from lithport.pdf, ceramics.pdf, and from OSA files for 425 sites.
Temporal Period reported by previous researchers:
-1 - Historic/ Modern
0 - none (no artifacts counted)
1 - unidentified/undetermined
1.5 - Late Prehistoric- Historic Transition
2 - Late Prehistoric/ Ft. Ancient
2.5 - Transitional between 2 and 3
3 - Late Woodland
3.5 - Transitional between 3 and 4
4 - Middle Woodland
4.5 - Transitional between 4 and 5
5 - Early Woodland
5.5 - Transitional between 5 and 6
6 - Terminal Late Archaic
6.5 - Transitional between 6 and 7
7 - Late Archaic
7.5 - Transitional between 7 and 8
8 - Middle Archaic
8.5 - Transitional between 8 and 9
9 - Early Archaic
9.5 - Transitional between 9 and 10
10 - Late Paleo
10.5- Transitional between 10 and 11
11 - Middle Paleo
11.5- transitional between 11 and 12
12 - Early Paleo
12.5- transitional between 12 and 13
13 - Pre-Clovis
21 - Woodland
22 - Archaic
23 - Paleo
100- indeterminate prehistoric
183
Multicomponent Site Codes: numbers represent combinations of above listed periods.
101 - 100 + OSA woodland=1
102 - 21 + 2
103 - 21 + 22
104 - 2.5 or 2 + 3
105 - 21 + 7 or 6
106 - 4 + 2
107 - 9,8,7,5,4,2
108 - removed
109 - 22, 21, 5, 10
110 - 2, -1
111 - 21, 5
112 - 7,3,-1
113 - 7,5,4
114 - 21, -1
115 - 100, -1
116 - removed
117 - 22,2
118 - 5,2
119 - 7, 5, -1
120 - removed
121 - 9,8,7,6,5,3,2
122 - 8,7
123 - 21,22,2
124 - 7,4,2,-1
125 - 6 or 7, +5
126 - 21,9,2
127 - 9,7,5,2
128 - 8,21
129 - 7,5
130 - 8,7,-1
131 - 5, -1
132 - 22,4
133 - 3,4
134 - 5,3
135 - 5, 4, 3, 2
136 - 5, 4, 2
137 - 10, 9
Data Field: Absolute dates (ABS prefix) radiometric dates for sites
Note: All other data fields are compiled from the OSA database.
184
Portable Lithic Artifacts Database Code Sheet
Description:
This data base code sheet is for the portlitht.pdf data base
Data base Contents: This data base contains records regarding portable
stone objects found at sites within the study area.
See noport.pdf for non-portable stone artifacts.
Data Field: Trinomial- Office of State Archaeology(OSA) site number.
Data Field: Site ID- OSA GIS database site identification number (linking field).
Data Field: Site Type: OSA Site Type
1- Open Air
3- Rockshelter
Data Field: Debitage/Flakes (FLAKES_DBT) - debitage counts reported in literature
Data Field: Raw Material Type (FDRAW_MTRL) - raw material type for flake counts
0- none (no artifacts counted)
1- unidentified chert raw material/ either unidentified chert or no data on attribute
2- Breathitt Chert
3- St. Louis Chert
4- St. Genevieve Chert
5- Boyle Chert
6- Haney Chert
7- Paoli Chert
8- 6 and 7
9- 3 and 5
10- 20 (left blank intentionally)
21- limestone
22- iron-bearing sandstone
23- shale (greenish)
24- sandstone
25- iron ore
26- limonite
27- red ocre
28- coal
29- hemetite
30- siderite
35- slate (black)
40- unidentified stone/non-chert
50- igneous rock (unidentified)
185
50.1- granite
60- mica
Data Field: Biface (BIFACE)- bifacially chipped stone artifacts.
Note: "T" designates previously identified artifact type by other investigators:
B=Biface,P=Projectile
0- none (no artifacts counted)
1- unidentified biface/fragment
2- unidentified projectile point/fragment
8- Late Woodland Type "Lowe" (Weinland and Sanders 1977:Type 5; Tune 1992:104)
10- Raccoon notched type Woodland (Tune 1991:42)
12- Early Woodland Stemmed (e.g., Webb and Funkhouser 1929:52; Red Eye Shelter)
15- Adena
20- Merom Trimble Late Archaic
50- Big Sandy
70- LeCroy
75- Kirk (Tune 1991:52)
PT1- triangular blade, straight stem: Early Woodland (Cowan 1975:14-17;Cowan 1976; Wyss
and Wyss 1977:55)
PT2- contracting stem, narrow shoulders: Late Archaic Cogswell Type (Cowan:1973;1976;
Rolingson and Rodeffer 1968:16-18; Wyss and Wyss 1977:56)
PT3- ovate blade, straight stem: Middle Woodland (Cowan 1975:18; Wyss and Wyss
1977:61)
PT4- ovate blade, stubby parallel sides: Late Archaic (Cowan 1975:18-19; Wyss and Wyss
1977:57)
PT5- triangular, expanding. stem: Middle Woodland (Cowan 1976:124; Wyss and Wyss
1977:57)
PT6- Deeply Side notched (Cowan 1975:14-23)
PT7- small expanding stem (Cowan 1975:14-23)
PT8- shallow side notched (Cowan 1975:14-23)
PT9- small triangular (Cowan 1975:14-23): Ft. Ancient/ Late Prehistoric (Cowan
1975:21-22; Wyss and Wyss 1977:58; Weinland and Sanders 1977:Type 6)
PT10- stubby serrated (Cowan 1975:14-23)
PT11- deeply corner notched (Cowan 1975:14-23)
PT12- stubby blade parallel sided stem (Cowan 1976:7)
PT13- small expanding stem (Cowan 1976:9)
PT14- triangular blade, side notch (Cowan 1976:10)
PT15- (Cowan 1976:10)
186
PT16- Early Archaic (Cowan 1976:12-13; Wyss and Wyss 1977:60)
PT17- broad triangular blade- Late Archaic-like "Broad Spears" (Cowan 1976:14; Weinland
and Sanders 1977; Type 3)
PT18- shallow side-notched incurvate base (Cowan 1976:14)
PT19- ovate blade, shallow side-notched (Turnbow 1976:14)
PT20- triangular blade, side notched (Turnbow 1976:14)
PT21- Middle Woodland? (Wyss and Wyss 1977:61; Cowan 1975:18)
PT22- (Wyss and Wyss 1977:61)
B1- thick crude (Cowan 1975:23; Tune et al 1991:116-117)
B2- thin leaf-shaped (Cowan 1975:26; Tune et al 1991:116-117)
B3- thick ovate (Cowan 1975:26)
B4- thin triangular, "tenuous" Woodland period" (Cowan 1975:27; Cowan 1976:74)
B5- elongate excurvate (Cowan 1975:27)
BE- fragments (fragment, Cowan 1975:27)
B1A- large triangular (Wyss and Wyss 1977:65-66)
B1B- small triangular (Wyss and Wyss 1977:65-66)
B1C- narrow ovate (Wyss and Wyss 1977:65-66)
B1D- ovate biface (Wyss and Wyss 1977:65-66)
B1E- fragments(Wyss and Wyss 1977:65-67)
B2A- leaf-shaped (Wyss and Wyss 1977:67)
B2B- ovate (Wyss and Wyss 1977:69)
B2C- straight base parallel sides (Wyss and Wyss 1977:69)
B2D- miscellaneous, untyped variants (Wyss and Wyss 1977:69)
B2DBA- biface-adze (Wyss and Wyss 1977:69)
B2E- fragments (Wyss and Wyss 1977:70)
2D- Biface-adze-hoe (Cowan 1976Wyss and Wyss 1977 after Cowan)
T2- Cogswell type
T4- Late Archaic (Wyss and Wyss; Cowan)
T2E- Cowan Type 2e
PT9- Cowan Type 9
PT21- Cowan Type 21
x- undescribed type, relic collector reported.
Data Field: Biface Count (BIFCOUNT)- reported counts for each biface type.
Data Field: Biface Raw Material Type (BIFRAW_MATR)- See Raw Material Type
above for appropriate code.
187
Data Field: Diagnostic (BIFDIAGNOST)Temporal attribute reported by previous
researchers for given temporally diagnostic biface(s).
-1- Historic/ Modern
0- none (no artifacts counted)
1- unidentified/undetermined
1.5- Late Prehistoric- Historic Transition
2- Late Prehistoric/ Ft. Ancient
2.5- Transitional between 2 and 3
3- Late Woodland
3.5- Transitional between 3 and 4
4- Middle Woodland
4.5- Transitional between 4 and 5
5 Early Woodland
5.5 - Transitional between 5 and 6
6- Terminal Late Archaic
6.5- Transitional between 6 and 7
7- Late Archaic
7.5-- Transitional between 7 and 8
8- Middle Archaic
8.5- Transitional between 8 and 9
9- Early Archaic
9.5-- Transitional between 9 and 10
10- Late Paleo
10.5 transitional between 10 and 11
11- Middle Paleo
11.5- transitional between 11 and 12
12- Early Paleo
12.5 transitional between 12 and 13
13- Pre-Clovis
21- Woodland
22- Archaic
23- Paleo
100- indeterminate prehistoric
Data Field: Flakes/Debitage - debris
Numbers in field represent counts
188
Data Field: Non-biface Materials (Lithic 2)- other stone artifacts.
0- none (no artifacts counted)
1- unidentified/miscellaneous (Wyss and Wyss 1977 re: miscellaneous); (Fryman 1967"tool
fragment"; scraper)
2- modified flake
3- cores
4- gravers
5- 2 and 3
6- prismatic blades (Turnbow 1976:20)
7- chunk/nodule
8- uniface
9- spokeshave
10- core-hammerstone
11- hammerstone
12- Fire-Cracked Rock (FCR)
13- abrader
14- nutting stone
15- perforator
16- stone pipe fragment
17- Banner stone
18- net sinker (Webb 1929)
19- pestle (Webb 1929)
20- groundstone, not distinguished
21- grooved axe
22- celt
23- adze
24- drilled stone (unidentified)
25- grinding slab
30- hafted end scraper
31- drill
32- core-chopper (Fryman 1967)
33- mano(s)
34- metate
35- anvil (Fryman 1967:44)
36- 3/4 grooved axe
37- hoe (Webb and Funkhouser 1929;Red Eye)
38- gorget
Data Field: Counts for non-biface lithics (LI2COUNT)
Data Field: Raw Material Type for non-biface lithics (LI2RAMTRL)- See Raw Material
Type above for appropriate code.
189
Data Field: Notes (NOTES)- remarks made during data entry.
Data Field: Citation- (CITATION)- source of information for data entered in row.
Data Field: Diversity (DIVERS)-calculated diversity index number for particular record.
Data Field: Number of components (CMPNTS)- number of components.
190
Non-Portable Rock Artifact Database Code Sheet
Description: This code sheet is for database file nonport.pdf.
This data base consists of non-portable materials such as rock art, basin features and mortars
(hominy holes).
Data Field: Site (SITE)- OSA Trinomial Designation for each site
Data Field: Site Identification Number (Site_ID)- number in text format assigned in OSA
data base, used here for linking purposes.
Data Field: Mortar Count (MRTCNT) -number of mortars reported (hominy holes).
Data Field: Processing/Other Non-petroglyph/petrograph Features (PRCSS)
0- none
1- basin (metate-like)
2- hemispherical (nutting?)
3- stairs- hand/foot holds
Data Field: Count of Processing/Other Non-petroglyph/petrograph Features (PRCNT)
Data Field: Composite Codes for all non-petroglyph/petrograph features
(COMP):consolidation of data in above fields present at a site
0- none
1- mortars only
2- basins only
3- hemispheres only
4- 1 and 2
5- 1 and 3
6- 2 and 3
7- indeterminate
8- stairs
191
Data Fields: Petroglyphs/Pictographs (3 categories)
Data Field: Tracks- representations of animal tracks (TRAKS)
0- none
1- indeterminate (prehistoric)
2- bird
3- hoof
4- Paw/pad, non-hoof non-human (e. g., bear or cat)
5- human foot
6- human hand
7- 1 and 2
8- 1 and 3
9- 1 and 4
10- 1 and 5
11- 2 and 3
12- 2 and 4
13- 2 and 5
14- 4 and 5
15- 3 and 4
16- 3 and 5
Data Field: Representations of animals or plants(ORG)- full/part of plant or animal
depicted
0- none
1- plant
2 -insect
3- reptile
4- mammal (non-human)
5- human
6- human head
7- fish
8- bird
9- 5 and 7 and 8
10- 5 and 6
192
Data Field: Geometric representations (GEO)
0- none
1- circle
2- chevron
3- complex geometric, multiple elements
4- lines, straight, grooved (e.g., tally marks)
5- lines, curvilinear
6- indeterminate
7- curvilinear and chevron (2 and 5)
Data Field: Rock Art Count (ART_NO) - count of particular glyph type, etc.
Data Field: Site Type (SITE_TYPE)- OSA Site type Code
1- open air
3- rockshelter
Data Field: Count (COUNT)- absolute or estimated number of particular feature;0-9
absolute count, fairly certain (Coy et al. 1997, only estimates e. g., several=3, numerous =5);
10-ten or more present (Coy et al.; Fryman 1967:23 (15PO11) Data only).
193
Ceramics Database Code Sheet
Description: This Code Sheet Corresponds to the ceramics.pdf file.
Data Field: Site (SITE)- OSA Trinomial Designation for each site
Data Field: Site Identification Number (Site_ID)- number in text format assigned in OSA
data base, used here for linking purposes.
Data Field: Prehistoric Ceramics (CERAMICS)- artifact type
0- ceramics not reported/ absent
1- ceramics (prehistoric vessel fragment reported)
2- raw material daub/glob, fired
3- non vessel unidentified
4- non-vessel figurine
5- loop handle, prehistoric ceramics
6- lug appendage handle, prehistoric ceramics
7- handle not stipulated
Data Field: Tempering Agent (TEMPER)- non-clastic elements noted.
0- none (no ceramics reported)
1- no tempering present
2- unidentified tempering agent present
3- 10 left blank for future additions
11- limestone
12- chert
13- shell
14- 11 and 12
15- 11 and 12 and 13
16- 11 and 13
17- grit- (grog- crushed ceramic temper)
18- sandstone
19- sand
20- quartz
21- 11 and 20
22- 12 and 18
23- 13 and 18
24- 17 and 2
25- 17 and 20
194
26- 19 and 17
27- 13 and 17
28- 17 and 19
29- 11 and 17
30- 11 and 18
Data Field: Surface Treatment (SURFACE)- reported modifications to surface.
0- none (no ceramics reported)
1- unidentified
2- roughened
3- eroded
4- plain
5- smooth
6- burnished
7- finger/thumb
8- finger/thumb nail
9- incised (unidentifiable tool)
10- cordmarked
11- fabric impressed
12- net impressed
13- cordmarked and incised
14- simple stamped
20- 9 and 10
21- cordmarked and smooth
Data Field: Diagnostic Temporal Period (DIAGN)- reported by previous researchers
-1- Historic/ Modern
0- none (no artifacts counted)
1- unidentified/undetermined
1.5- Late Prehistoric- Historic Transition
2- Late Prehistoric/ Ft. Ancient
2.5- Transitional between 2 and 3
3- Late Woodland
3.5- Transitional between 3 and 4
4- Middle Woodland
4.5- Transitional between 4 and 5
5 Early Woodland
5.5 - Transitional between 5 and 6
6- Terminal Late Archaic
6.5- Transitional between 6 and 7
7- Late Archaic
21- Woodland
195
Biotic Code Sheet
Description: This code sheet corresponds to the biotic.pdf database file.
This database contains records of non-worked macrobiotic materials reported from sites.
Data Field: Site (SITE)- OSA Trinomial Designation for each site
Data Field: Site Identification Number (Site_ID)- number in text format assigned in OSA
data base, used here for linking purposes.
Data Field: Fauna Taxa/Taxon (FAUNA) - reported animals.
0- none
1- unidentified bone
2- unidentified mammal
3- unidentified avian
4- unidentified reptile
5- unidentified amphibian
6- unidentified crustacean
7- unidentified mollusk (bivalve, mussel)
8- unidentified gastropod
9- unidentified ichthyos
10- deer (Odocoileus virginianus)
11- elk
12- bear (Ursus americanus)
13- squirrel-chipmunk(Sciuridae/Sciurus, sp.)
13.1- Scuirus niger
14- turtle
14.1- Eastern box turtle (Terrapene carolinia)
14.2- soft shell turtle
14.3- snapping turtle
14.4- painted turtle
14.5- Testudinae
15- opossum
16- rabbit (Sylvigus, sp.)
17- fox
18- wolf
19- beaver
20- raccoon (Procyon lotor)
21- turkey
22- river otter
23- crayfish
24- groundhog/woodchuck (Marmota monax)
196
30- human remains (burial inferred)
31- human burial (relic collector evidence)
32- human burial extended
33- human burial flexed
34- human burial bundle
35- human burial cremation
36- human burial intentional partial
40.0- fish- gar (Lepisosteus)
40.1- fish catfish
50- unidentified arthropod
51- insecta
60.0- mussel- Lampsilis ventracosa
60.1- mussel- Amblema plicata
60.2- mussel- Elliptio, sp. (filter mussle)
70- true toads (Bufo, sp.)
71- true frogs (Rana, sp.)
72- snakes, generic
73- Milk Snakes and King Snakes (Lampropeltis, sp.)
73.1- Common King snake - lampropeltis getulus
73.2- black racer (Colubridae, sp)
80- muskrat (Ondatra zibethicus)
81- voles (microtus, sp.)
82- Eastern chipmunk (Tamias striatus)
83- Mole (Talpidae)
84- Mouse (Peromyscus sp.)
85- Hispid Cotton Rat (Sigmodon hispidus)
86- Wood Rat (Neotoma, sp.)
90- canus -dog
100- feces (unidentified)
101- feces human
Data Field: Faunal Element (FAFRAG)
0- none
1- cranial
1.1- tooth
1.2- mandible
2- forelimb/arm
2.1- scapula
3- hindlimb/ leg
4- thorax
5- keratic (antler/horn)
6- scale
197
7- fin
8- unspecified post cranial
9- caripace
10- egg shell
11- insect galls
20- Long bone shaft fragment (LBSF)
25- vertebra
Data Field: Flora Taxa/Taxon (FLORA)
0- none
1- unidentifed wood (charcoal)
2- unidentified uncarbonized wood
3- charcoal (unidentified)
4- unidentified non-carbonized
10- Maple (Acer, sp.)
11- birch (Betula)
12- Pine (Pinus sp.)
12.1-pitch pine
13- elm
14- Oak (Quercus)
15- hickory (Carya)
16- butternut (Juglens cinerea)
17- black walnut (Juglens nigra)
18- hazel nut
19- chestnut (Castenea dentata)
20- beech (fagus)
21- persimmon (Dryopiosis virginiana)
22- sumac (Rhus)
23- tulip poplar (Yellow poplar)- Liriodendron tulipifera
24- dogwood (Cornus florida)
25- sycamore
26- cedar
27- chinquapin (Castanopsis)
28- black gum
29- pawpaw (Anonaceae)
30- Plum (Prunus americana)
31- sourwood
32- wild cherry/plum/ground cherry (Prunnus sp.)
33- Wood sorrel (Oxalis)
34- honey locust (Gleditsia triacanthos)
35- sassafras
36- Mountain Ash (Sorbus)
198
37- Clematis
38- mulberry (Moruus rubus)
39- hornbeam
40- wild bean (Fabaceae)
41- panic grass (Panicum sp.)
42- Aneime (Aneime sp.)
44- bullrush
45- hackberry
46- sedges
50- brambles (generic Rubus)
51- greenbriar (Smilax)
52- rasberry (Rubus)
53- blackberry (Rubus)
54- elderberry (sambucus)
55- strawberry (Fraxinus)
60- blueberry (Vaccin)
61- huckelberry (gaylus)
62- grape (vitis)
63- barberry
64- Purselane (Portul)
65- poke (Phytolacca americana)
66- beggars tick (Desmodium)
67- bedstraw (Galum)
68- ragweed (Ambrosia sp.)
70- moss/lichens
71- moss
72- lichen
73- Holly (ilex)
80- ferns and Allies
90- River Cane (Arundinaria)
91- Euphorbia (spurge)
92- grass (generic) Poaceae
92.1- Little Bluestem (Andropogon scoparius)
92.2- Paspalum/Seteria
93- Asteraceae Aster family
94- henbit (Lamium)
95- magnolia
96- Rhododendron
97- Myrtle
98- Compass plant
100- bottle gourd (lagineria)
101- squashes, general (Cucurbita pepo)
101.1- squash, pumpkin (Cucurbita pepo var. ovifera)
199
102- sunflower (Helianthus annuus)
103- chenopod, goosefoot (Chenopodium berlandari)
104- sumpweed/marshelder (Iva annua)
105- knotweed (polygonum)
106- maygrass (Phalaris calorinia)
107- amaranth (Amaranthus)
108- giant ragweed (Ambrosia trifida)
120- bean (Phaseolus)
130- corn (Zea mays)
140- tobacco (Nicotiana rustica)
131-199 reserved for domesticates/cultivated, incl. historic
200- fungus
Data Field: Domesticated Plants (DOM)
0- not domesticated
1- yes plants
2- yes animal
3- plant, quasi domesticate or status indeterminate
Data Field: Floral element (FLFRAG)
0- none
1- not identified/ unknown
2- unidentifiable
3- shell
4- husk
5- stem/stalk
6- bark
7- wood
8- wood/bark
9- nut meat
10- seed
10.1-seed coat
11- rind
12- fruit (may contain seeds)
13- pine cone part
14- bracts (involucres)
15- tendril
16- flower
17- achene
18- pericarp
19- leaf
19.1- blade
200
19.2- thorn
19.3- frond
19.4- pine needle
20- cap
21- kernal
22- cob
23- pit/stone
24- inflorescence
25- culm
26- root/tuber
201
Modified Biotic Materials Database Code Sheet
This Code Sheet Accompanies the modbiot.dbf database file.
Data Field: Site (SITE)- OSA Trinomial Designation for each site
Data Field: Site Identification Number (Site_ID)- number in text format assigned in OSA
data base, used here for linking purposes.
Data Field: Modified Faunal Remains (MODFAUNA)-Modified faunal remains
0- none
1- indeterminate/unspecified modification
2- cut
3- incised
4- glyph
5- drilled
6- split
7- polished
8- 9 intentionally left blank
10- graver (Fryman 1967)
20- leather
21- leather with holes
22- leather- stitched
23- leather with cordage
30- leaher with pigment
40- split quill
41- bone pin
42- bone awl
43- bone "handle" (Webb 1929:51)
Data Field: Fauna Taxa/Taxon (FAUNA) - reported animals.
0- none
1- unidentified bone
2- unidentified mammal
3- unidentified avian
4- unidentified reptile
5- unidentified amphibian
6- unidentified crustacean
7- unidentified mollusk
8- unidentified gastropod
202
9- unidentified ichthyos
10- deer
11- elk
12- bear
13- squirrel
14- turtle
14.1- Eastern box turtle
15- opossum
16- rabbit
17- fox
18- wolf
19- beaver
20- raccoon
21- wild turkey
22- river otter
Data Field: Modified Fauna Part (MODFAUNAPRT)-identified element
0- none
1- cranial
2- forelimb/arm
3- hindlimb/ leg
4- thorax
5- keratic (antler/horn)
6- scale
7- fin
8- unspecified post cranial
9- skin
10-shell
Data Field: Modified Flora (MODFLORA)
0- none
1- indeterminate/unidentified
2- cordage
2.5- knotted cordage
2.55- knotted cordage w/feathers
3- gourd
4- board
5- prepared bark
6- quid
7- split cane (basketry remant?)
8- split cane
203
9- fabric
10-moccasin/slipper
11-pestle (wooden)
12- fabric bag
Data Field: Flora Taxa/Taxon (FLORA)
0- none
1- unidentifed wood (charcoal)
2- unidentified uncarbonized wood
3- charcoal (unidentified)
4- unidentified non-carbonized
5- non tree unidentified (herbacious)
10- Acer (maple)
11- birch
12- Pinus
13- elm
14- Quercus (oak)
15- Carya (hickory)
16- butternut
17- Jugleuns nigra (black walnut)
18- hazel nut
19- chestnut
20- beech (fagus)
21- persimmon
22- sumac
23- tulip poplar
24- dogwood
25- sycamore
26- cedar
50- brambles (generic)
51- greenbriar
52- rasberry
53- blackberry
60- blueberry
61- huckelberry
62- grape (vitis)
70- moss/lichens
80- ferns and Allies
90- Arundia, (cane)
100- lagineria (bottle gourd)
101- Cucurbita
102- Helianthus
204
103- Chenopodium
104- Iva Annua (sumpweed)
105- knotweed (polygonum)
106- maygrass (Phalaris calorinia)
120- Phaseolus
130- Zea mays
Data Field: Floral element (FLORAFRAG)
0- none
1- not identified/ unknown
2- unidentifiable
3- shell
4- husk
5- stem
6- bark
7- wood
8- wood/bark
9- nut meat
10- seed
10.1-seed coat
11- rind
12- fruit (may contain seeds)
13- pine cone part
14- bracts
15- tendril
16- flower
17- achene
18- pericarp
19- leaf
19.1- blade
19.2- thorn
205
Spatial Analysis Database Code Sheet
This Code Sheet Accompanies the spatial.pdf database file.
This database contains data aggregated from other databases. Data were also extracted from
environmental layers. Note: UTM coordinate fields have been removed to maintain site
confidentiality.
Data Field: Site (SITE)- OSA Trinomial Designation for each site
Data Field: Site Identification Number (Site_ID)- number in text format assigned in OSA
data base, used here for linking purposes.
Data Field: Time Class (TIME CLASS)
2 - Late Prehistoric
3 - Late Woodland
4 - Middle Woodland
5 - Early Woodland
7 - Late Archaic
8 - Middle Archaic
9- Early Archaic
10 - Paleo Indian
Data Field: Number of Components Present (MULTICOMP)
Data Field: Summary of Periods present (PERIODSUM)
101 - 100 + OSA woodland=1
102 - 21 + 2
103 - 21 + 22
104 - 2.5 or 2 + 3
105 - 21 + 7 or 6
106 - 4 + 2
107 - 9,8,7,5,4,2
108 - removed
109 - 22, 21, 5, 10
110 - 2, -1
111 - 21, 5
112 - 7,3,-1
113 - 7,5,4
114 - 21, -1
115 - 100, -1
116 - removed
206
117 - 22,2
118 - 5,2
119 - 7, 5, -1
120 - removed
121 - 9,8,7,6,5,3,2
122 - 8,7
123 - 21,22,2
124 - 7,4,2,-1
125 - 6 or 7, +5
126 - 21,9,2
127 - 9,7,5,2
128 - 8,21
129 - 7,5
130 - 8,7,-1
131 - 5, -1
132 - 22,4
133 - 3,4
134 - 5,3
135 - 5, 4, 3, 2
136 - 5, 4, 2
137 - 10, 9
Data Field: Slope in Degrees (SLOPE_DEGR) - slope of landform
Data Field: Elevation (ELEVATION) - meters above mean sea level
Data Field: Facing Aspect (ASPECT) - azimuth angle in degrees
-1 - flat facing aspect value
0-360 degrees from Grid North
Data Field: Ecology Value/Landform Class (ECOLOGY_VA) - landform type
1 - Low Level Land
10 - Low Slope, North Facing
20 - Low Slope, East Facing
30 - Low Slope, South Facing
40 - Low Slope, West Facing
50 - Mid-Slope
100 - Upper Slope, North Facing
200 - Upper Slope, East Facing
207
300 - Upper Slope, South Facing
400 - Upper Slope, West Facing
500 - Upland Level Land
Data Field: Site Area (Area_Poly) - site area in square meters, extracted from OSA vector
polygon data
Data Field: Site Type (TYPE)
1 - open air (or value other than 3, special site type)
3 - rockshelter
Data Field: Distance to water in 50 meter increments (DISTH20_50)
Data Field: Stream Order (STR_ORD) - nearest 1:24,000 scale mapped stream order,
State of Kentucky hydrology data.
Data Field: Linear Distance to Water (LH2O)- shortest straight line distance to body of
water on 1:24,000 scale mapping.
208