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 down- cutting 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

1Abbreviation 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.

2Recently 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 mid-

Holocene (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 1996:72-

73).

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 funded- research 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.

3An 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 non-

modified 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 forest- heath 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 re-

scaled 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 time- sensitive 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 mid- slope 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 mid-

slope 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. This observation supports Wyss and Wyss

102 (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 single- component 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 broad- spectrum 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 non-

agricultural 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., mid- slope 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 point-

sampling 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.

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Weir, G. W. 1974b Geologic Map of the Slade Quadrangle, east-central Kentucky. Map GQ- 1183. 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. View of the North Fork of the Red River showing arch aeologicalsites in relation to four principal landform classes. 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

Env i r ons

35

Sites

30

25

20

percent

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

30

25

20

percent

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

15

13

11

percent

9

7

5 NNEESESSWWNW

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

20

15

percent

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

60

50

40 count

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

Env ir ons Sites

0.15

0.1

frequency

0.05

0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 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

80

60 count 40

20

0 Paleo E. Arch L. Arch M. Arch E. Wood L. Wood M. Wood L. Prehist period

Figure 13. Per period distribution of 319 components used to study diachronic landuse practices.

3

2.5

2

1.5

1

0.5

0 mean number of components Paleo E. Arch L. Arch M. Arch E. Wood L. Wood M. Wood L. Prehist 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

30

25

20 percent 15

10

5

0 1234567 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

330

325

320

315

310

305 mean elevation (m)

300

295 Paleo E. Arch L. Arch M. Arch E. Wood L. Wood M. Wood L. Prehist period

Figure 16. Mean elevations for components (n=319) belonging to each period class. The mean for the environment is 310 m.

154 10 9 8 7 6 5 4 3

slope (degrees) 2 1 0 Paleo E. Arch L. Arch M. Arch E. Wood L. Wood M. Wood L. Prehist 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

150 140 open-air rockshelters all sites 130

120

110

100

aspect index 90

80

70

60 Paleo E. Arch L. Arch M. Arch E. Wood L. Wood M. Wood L. Prehist 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

10

8

count

6

4

2

0 Paleo M. Arch L. Arch. E. Arch. L. Wood. E. Wood. L. Prehist M. Wood. period

Figure 19. Component counts per period for the low level (n=66) and lower slope (n=30) ecological strata.

16

14

12

10

8 count 6

4

2

0 Paleo M. Arch E. Arch. L. Arch. E. Wood. L. Wood. M. Wood. L. Prehist period

Figure 20. Component counts for the mid-slope stratum (n=40).

156

40

35

30 Up slope

25 Up lev el

20

count

15

10

5

0 Paleo M. Arch E. Arch. L. Arch. E. Wood. L. Wood. M. Wood. L. Prehist period

Figure 21. Component counts for the upland slope (n=95) and upland level (n=88) land strata.

0.7

0.6

0.5

0.4

0.3 hectares

0.2

0.1

0 Paleo L. Arch M. Arch E. Arch. E. Wood L. Wood M. Wood L. Prehist. period

Figure 22. Mean site area per period (n=319).

157 800

700

600

500

400

300 square meters

200

100

0 Paleo L. Arch M. Arch E. Arch. E. Wood L. Wood M. Wood L. Prehist. period

Figure 23. Minimum site area per period (n=319).

2 1.8 1.6 1.4 1.2 1 0.8 hectares 0.6 0.4 0.2 0 Paleo L. Arch E. Arch. L.Wood. M. Arch. E. Wood. M. Wood. L. Prehist 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

1.4 1.2 1 0.8 hectares 0.6 0.4 0.2 0 Paleo L. Arch E. Arch. L.Wood. M. Arch. E. Wood. M. Wood. L. Prehist period

Figure 25. Mean site area for components located in the lower slope ecological stratum (n=30).

0.5

0.45

0.4

0.35

0.3

0.25

hectares 0.2

0.15

0.1

0.05

0 Paleo L. Arch E. Arch. L.Wood. M. Arch. E. Wood. M. Wood. L. Prehist period

Figure 26. Mean site area for sites located within the mid-slope stratum (n=40).

159 0.4

0.35

0.3

0.25

0.2

hectares 0.15

0.1

0.05

0 Paleo L. Arch E. Arch. L.Wood. M. Arch. E. Wood. M. Wood. L. Prehist period

Figure 27. Mean site are per period for the upland slope ecological stratum (n=95).

0.5 0.45 0.4 0.35 0.3 0.25

hectares 0.2 0.15 0.1 0.05 0 Paleo L. Arch E. Arch. L.Wood. M. Arch. E. Wood. M. Wood. L. Prehist period

Figure 28. Mean site area per period for the upland level land stratum (n=88).

160

1

0.9

0.8

Paleo E. Arch. M. Arch.

0.7

0.6

0.5

hectares 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

1.2 E. Wood.

1

0.8

hectares

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

0.3 L. Wood.

0.25

0.2

hectares

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

1.4

1.2

1

hectares 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 Range (years B.P.) Phase/Culture Pre-Paleo before 12,000 Indian Early 12,000-11,000 Paleo Indian Middle 11,000-10,500 Late 10,500-10,000 Early 10,000-8,000 Archaic Middle 8,000-5,000 Late 5,000-3,000 Skidmore Early 3,000-1,800 Cogswell (Terminal Archaic) Woodland Middle 1,800-1,500 Adena-Hopewell Late 1,500-1,000 Newtown-like Early 1,000-800 Croghan Late Prehistoric Middle 800-600 Manion Late 600-450 Gist 450-250 Montour Early 250-200 Euro-American Historic Exploration/Replacement Middle 200-80 Agricultural Development Late 80-50 Resource Extraction-Agriculture Present 50-0 Industrial-Agricultural-Extractive- Tourism

170 Table 2. The most prevalent tree species according to landform type.

Tree Species Gorge1 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 Total 100 99 100 99 99 99.78

1 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 No. of Components Office of State Spatial, temporal, environmental site 1399 Archaeology (OSA) attributes Chronology Total 413 Unassigned prehistoric 248 Prehistoric w/ assigned period 124 Historic period components 63 Portable lithic artifacts Total 400 Non-portable rock Total 62 features 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 23 Spatial Analysis Data with spatio-temporal attributes 319 Database aggregated from above sources and merged with “cleaned” OSA Database

172 Table 4. Definition of the ecological (landform) grid.

Stratum Basis for Membership Percent of (substrata) (N, E, S, W, slopes) Study Area 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 Table 5. Diachronic considerations for the ecological model (Schuldenrein 1996 and Donahue and Adovasio 1990; Delcourt et al. 1998).

Period Geomorphology Vegetation/Ecology Pleistocene Low Level Land Stratum - Formation of Low Level Land Stratum - (Before 10,000 B.P.) large Quaternary age Terraces along the Volatile Riverine Forest System Red River, hydrological response to and/or open grasslands in pockets? glacial-induced changes along the Ohio River system. Meandering systems along larger river systems in study area. Massive flood events likely to have occurred.

Lower Slope Stratum - Formation of the upper portions of colluvial foot slopes; Lower Slope Stratum - Cool stabilization, except for biomantle, temperate forest type with many occasional sheet wash by beginning of the mixed mesophytic species present. Holocene.

Mid-Slope Stratum - Formation of rockshelters during the Illinoian and Wisconsin glaciation, when down-cutting of drainages established the Ohio River system.

Upper Strata - Continued erosion and Upper Strata - Boreal-like to cool down-cutting of the peneplain. temperate forest type, with mixed mesophytic species present. Early Holocene Low Level Land Stratum - Continued Low Level Land Stratum - (10,000-7,000 B. P.) flux along the floodplains of larger-order Continued instability of stream systems, beginning of riverine/floodplain vegetation entrenchment of larger streams. Large regime. flood events, meters of sediment deposited.

Lower Slope Stratum - Stabilization of upper ~0.5 m of colluvial foot slopes, with biomantle formation probably occurring; Lower Slope Stratum - increased sheet wash, landslides in some areas of representation of the establishment higher slope. of the mixed-mesophytic forest species. Upper Strata - Quasi-stable? Resembling later landforms? Continued landslides and Upper Strata - Cool temperate erosional episodes take place. forest becomes more mesophytic- like. Uplands dominated by spruce and white cedar. (Continued.)

174 (Table 5. Continued.)

Period Geomorphology Vegetation/Ecology Middle Low Level Land Stratum - Stabilization of Low Level Land Stratum - Reduced Holocene floodplains, high-order streams mostly volatility in the riverine/floodplain 7,000- entrenched, except for occasional regime, predictable wetland resources at 3,000 B. P. oxbow/channel reorientation biomantle floodplain/colluvial interface. formation processes mixed with little deposition of sediment from over-bank flooding. No more Upper Strata - Establishment of mixed than 0.6 m deposition. mesophytic composition. Increase in oaks, extension of the mixed-mesophytic Upper Strata - Biomantle formation on forest type into the uplands, replacing colluvial landforms hypothesized; relatively white cedar. Hemlock species greatly stable, except along areas with slope wash. reduced by ca. 4800 B. P., red cedar Occasional landslides on slopes. 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. Late Low Level Land Stratum - Continued quasi- Low Level Land Stratum - Same as Holocene stable floodplains, Artifacts minimally buried to Mid-Holocene. 3,000-200 exposed in surface contexts, probable biomantle B.P. formation coupled with infrequent low-level sediment deposition due to flooding. No more than 0.5 m of deposition.

Upper Strata - continued terminal Mid- Upper Strata - Same as Mid-Holocene, Holocene pattern. with increased presence of fire-tolerant species and reduction of red cedar. Increased representation of ash. Cultigen species present in palynological record.

Historic Low Level Land Stratum - creation of plow All Strata - deforestation due to period zones, draining of wetlands, major alteration of logging, introduction of foreign species. 200-0 B. P. drainage systems through re-channeling, Extinction of chestnut. damming, etc.

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 Max Mean Std. Min Max Mean Std. Dev. Dev. Elevation (m) 180.0 460.0 309.7 54.8 191.0 436.0 323.0 68.4 Slope (Degrees) 0.0 61.0 8.2 6.9 0.0 41.3 7.3 6.2 Facing Aspect 0.0 360.0 175.0 103.3 0.0 358 170.0 98.4 (360 degrees) Facing Aspect 0.0 180.0 91.8 51.6 0.0 180 97.0 54.0 ( 0-180)

Table 7. Frequencies of ecological strata compared to settings of archaeological sites.

Ecological Strata Background Environment Archaeological Sites (Land Classes) (Percent) (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 1 Gladie Creek (A. Mickelson 2001d) Middle Archaic biface data were added to the the portable tool lithic database.

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 0 .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

Total Ha 1.309 1.2705 1.785 3.4142 3.079 1.058 1.303 4.338 17.56

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 processing location (few, less diverse variants ) (many, more diverse variants)

Mobility residential logistical high low Technology generalized specialized (low assemblage diversity) (high assemblage diversity)

Storage Rates low high

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 %%% Pattern IV (Late Prehistoric) Large Sites % -- Small Sites %%%

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 Pattern IV (Late Prehistoric) Residential Base 1 3 3 Extractive Location 1 1 1 Processing Location 2 1 1 Level of certainty for presence: 1 - high; 2 - medium; 3 - low.

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