ANTHROPOLOGICAL PAPERS OF THE AMERICAN MUSEUM OF NATURAL HISTORY

Number 98: 496 pp. June 14, 2013

Copyright © American Museum of Natural History 2013

ISSN 0065-9452

http://dx.doi.org/10.5531/sp.anth.0098

[PART 2 OF EPUB]

LIFE AMONG THE TIDES: RECENT ARCHAEOLOGY ON THE GEORGIA BIGHT

VICTOR D. THOMPSON

AND

DAVID HURST THOMAS

EDITORS AND CONTRIBUTORS

WITH CONTRIBUTIONS BY

Clark R. Alexander, Keith H. Ashley, Elliot H. Blair,

Ann S. Cordell, Kathleen A. Deagan, Chester B. DePratter, Scott M. Fitzpatrick, Ervan G. Garrison, Royce H. Hayes, Richard W. Jefferies, Deborah A. Keene, Ginessa J. Mahar, Rochelle A. Marrinan, Christopher R. Moore, Matthew F. Napolitano, Alexandra L. Parsons, Vicki L. Rolland, Matthew C. Sanger, Ryan O. Sipe, Amanda D. Roberts Thompson, Robert L. Thunen, John A. Turck, Neill J. Wallis, and Thomas G. Whitley

Proceedings of the Sixth Caldwell Conference

St. Catherines Island, Georgia

May 20–22, 2011

PART II: MODELING COASTAL LANDSCAPES

CHAPTER 6: PAST SHORELINES OF THE GEORGIA COAST

[1]

Chester B. DePratter and Victor D. Thompson

INTRODUCTION

At 160 km long, the Georgia coast is a diverse and geologically dynamic environment (fig. 6.1). Part of the larger Georgia Bight, which extends from the Outer Banks of North Carolina to Cape Canaveral in northeastern Florida, this low wave action coastline consists of a number of barrier islands, back-barrier islands (colloquially known as hammocks), an expansive marsh system (ca. 10 km wide) of sounds, tidal creeks, and rivers, and a portion of the mainland that borders the marsh system (see Hubbard, Oertel, and Nummedal, 1979; Thomas, 2008: chaps. 7, 32, and 35; Thompson and Turck, 2010). The barrier islands vary considerably in size, ranging from 5 to 15 km long and 1 to 5 km across (Hubbard, Oertel, and Nummedal, 1979), and formed during the Pleistocene (N = 8) as well as the Holocene (N = 7) (fig. 6.2). The back-barrier islands also have a similar varied geologic history (Hoyt and Hails, 1967; Hubbard, Oertel, and Nummedal, 1979). While some islands in the back-barrier area are quite large, the vast majority are smaller than 0.5 km2 (Thompson and Turck, 2010: 284). We do not offer an extensive overview of Georgia coastal geology here, as a nice summary of this can be found in Turck and Alexander (chap. 7; see also Turck, 2011). More detailed information can also be found in Thomas (2008: chap. 32), as well as in Bishop, Rollins, and Thomas’s (2011) recently edited volume on the geoarchaeology of St. Catherines Island. Our main concern in this chapter is to provide a preliminary assessment of paleoshorelines of the Georgia coast. To understand changes in paleoshorelines over time, two specific processes are important. The first is that sea level fluctuation has impacted the overall form and distribution of landforms along the Georgia coast for an extended time frame. For the purposes of this chapter, we are only concerned with the last 5000 years of this history, as this is when we can observe an intensive human presence on the coast (DePratter, 1977a; DePratter and Howard, 1981: 1289; Elliott and Sassaman, 1995: 18; Thompson and Turck, 2009, 2010; Williams et al., 2010; Thomas, 2011a; Thompson and Worth, 2011; Turck et al., 2011). The second process that we are concerned with is progradation/retrogradation. Advancing and receding coasts “may advance because of coastal emergence and/or progradation by deposition, or retreat because of coastal submergence and/or retrogradation by erosion” (Bird, 2000: 292). The Georgia coast experiences both progradation and erosion in various areas at present and has over the last 5000 years.

While a detailed discussion of sea level fluctuation and progradational/retrogradational processes is beyond the scope of this chapter, we can offer a brief sketch of how these processes operate along the Georgia coast and outline how they are directly relevant to the study presented here. There are several sea level curves for the Georgia Bight. However, we note that there is a great need for refinement of these curves. Currently, the data suggest that at about 4200 b.p., sea levels rose to about 1.2 m below present (mbp) (DePratter and Howard, 1981; Gayes et al., 1992; Turck, 2011: 11). It was during this time that much of the back-barrier areas became filled in with Holocene marsh sediment and the Holocene portions of the barrier islands formed (DePratter and Howard, 1981: 1289; Hayes et al., 1980: 286; see also chapters in Bishop, Rollins, and Thomas, 2011, and a good summary of this by Turck, 2011). By around 3100 b.p., or perhaps earlier depending on which sea level curve is used, there appeared to be a drop in sea level, thought to be as much as 3–4 mbp (DePratter and Howard, 1981; Colquhoun and Brooks, 1986). Regardless of exactly when this drop occurred, it also roughly coincided with a reduction in use of marsh resources by coastal inhabitants (DePratter, 1977a; Thompson and Turck, 2009, 2010). By around 2400 b.p. there was a return of the productivity of the marsh system, as indicated by people occupying the margins of back-barrier islands (DePratter and Howard, 1981: 12–14; see also Turck, 2011: 14–15 for a summary). Sea levels at this time are thought to have rebounded to around 1 mbp and continued to rise slowly until today with “negligible change in the marsh estuarine system” (Turck, 2011: 15; see also DePratter and Howard, 1980; Gayes et al., 1992).

Despite these changes in sea level, deltaic areas continued to prograde eastward due to sediment loading from the river systems that flow into the estuaries and ultimately into the Atlantic (DePratter and Howard, 1980, 1981; Turck, 2011: 191). Thus, in certain areas of the coast, many new landforms emerged as a result of these dynamic processes. We acknowledge that processes are more complex than we have outlined here, particularly for local islands and river systems (see Chowns, 2011; Potter, 2011; Rich et al., 2011; Rollins and Thomas, 2011; Turck and Alexander, this volume, chap. 7); however, this general outline does provide a brief understanding of the basic principles underlying the study presented here.

The purpose of this chapter is to provide some basic information on paleoshorelines of the Georgia coast. To do this, we use two datasets. The first are site locations and chronological information from shoreline and island surveys conducted by DePratter with James D. Howard in the late 1970s and early 1980s with support from the National Science Foundation. These data were used to create the initial shoreline maps presented here. Preliminary maps of these shorelines can be found in DePratter and Howard (1977a), Howard and DePratter (1980), and DePratter (1977a), as well as in unpublished sources. The shoreline maps published previously only relate to the northern portion of the coast. In this chapter, we expand this coverage to include areas farther to the south. In order to evaluate these original maps, we generated site distribution maps by time period, using the Georgia Archaeological Site File (GASF) database from May 2007. This allowed us to evaluate the original shoreline locations established by DePratter using updated information. These updated sites include all of the sites originally recorded by DePratter.

In general, we found a high correlation between the current data available for the Georgia coast and DePratter’s original maps. We suggest that the few discrepancies that we note are attributable to small recording errors in the GASF, mistyped ceramics from other researchers over the years (leading to erroneous chronologies for some sites), and possible local variations in shoreline progradation and erosion that require finer-grained data than that available in our current datasets (see Turck and Alexander, this volume, chap. 7). Finally, we note that the location and dating of the shoreline positions for some of the northern areas of the coast have been investigated and dated by both radiocarbon and optically stimulated luminescence (OSL) dating, which corroborate the archaeological findings (see Turck and Alexander, this volume, chap. 7).

BASIC PRINCIPLES

The basic principle used by DePratter to construct the original shoreline maps is a relatively straightforward concept. In areas that are progradational, landforms “move” seaward over time. That is to say, deposition in these areas causes new hammocks and sand ridges to form in succession, away from the coast. Many of these new landforms would have been located adjacent to, or surrounded by, newly developing marsh-estuarine systems. These new landforms would have provided access to marsh-estuarine habitats that would not have been as widespread in the local area prior to the development of such landforms. Since the beginning of the Late Archaic Period (ca. 4200 b.p.), the vast majority of faunal resources exploited by coastal populations are from marsh-estuarine habitats (Reitz, 1988; Colaninno, 2010; Reitz et al., 2010). Therefore, our assumption is that since these resources were highly valued, people would have taken advantage of them as soon as they were exploitable. In addition, since we observe a general population increase through time on the Georgia coast (Williams et al., 2010; Turck et al., 2011), new exploitable resources would have been particularly important. Therefore, our basic premise in creating the shoreline maps is that as soon as islands or landforms became stable, they were colonized and occupied by people.

Coastal Survey: 1976 to 1984

Surveys of the Georgia coast by DePratter during the 1970s and 1980s consisted of visiting islands, walking and inspecting exposed island shorelines at low tide, and probing for buried shell deposits. Samples of artifacts (predominantly ceramics) were collected and the site locations recorded. Additional sites were located by walkover surveys on the islands and examining exposed surfaces for shell middens, and shell and/or artifact scatters. DePratter used this archaeological information to create the original shoreline locations on paper maps. These maps were scanned and the data contained on them were digitized, put into a database, and used to create the updated shoreline maps presented in this chapter. Finally, in addition, subsurface testing by the American Museum of Natural History on St. Catherines Island (see Thomas, 2008, for a discussion) has helped to refine the shoreline maps for this area of the coast.

The chronological arrangement for the paleoshoreline maps is based on DePratter’s (1979, 1991; see also Williams and Thompson, 1999) ceramic sequence developed for the northern Georgia coast. The Georgia coastal ceramic sequence is perhaps one of the most complex in the region. At least 28 regularly located Native American ceramic types comprise what is normally recovered during archaeological investigations in the area, not to mention a host of other wares that occur in smaller quantities. These are recovered in addition to a number of historic ceramics found in the region. Some of the earliest ceramics in North America occur along the Georgia coast, and Sassaman (2004) suggests that the central Georgia coast may be the birthplace of ceramic vessel production. These earliest ceramics are known as St. Simons, and date as early as around 4400 radiocarbon years b.p. (DePratter, 1979, 1991; Sassaman, 1993; Thompson, 2007; Thomas, 2008). While earlier diagnostic materials are sometimes located along the Georgia coast, we take the 4400 radiocarbon years b.p. date as the starting point for our analysis, as it is at this time that an archaeologically visible settlement along the coast becomes ubiquitous on the landscape. We note that there are possibly earlier sites on inundated coastal landforms, but so far none have been discovered (see Turck, Williams, and Chamblee, 2011, for a discussion).

Table 6.1 summarizes the general period, phase, ceramic type, and age range for pottery of the Georgia coast. Here, we provide both uncalibrated ranges b.p. (i.e., 1950) as well as calibrated age ranges in b.c./a.d. format. This is to allow the dates provided on the shoreline maps to be correlated with calendar dates. The calibrated ages are derived from Thomas (2008); however, we note that while instructive and most helpful, the calibrated ranges should be used with caution as Thomas’s study was specific to St. Catherines Island and his dates for the ceramic sequence may not be applicable to the coast as a whole.

Despite our concerns regarding potential calibration issues, the relative dating of the ceramic sequence is well documented. In general, pottery traditions and attributes along the Georgia coast vary in paste, form, decoration, surface finish, and method of manufacture. A mixture of these stylistic and technological attributes varies over time and can be used as markers (much like index fossils) for geological events (e.g., past shorelines). Due to space limitations, we will not review all the attributes of the basic types listed in table 6.1; however, we do refer the reader to DePratter (1979, 1991), Williams and Thompson (1999), and Guerrero and Thomas (2008) for this information. Finally, we note that the original shoreline positions were drawn using a chronological ceramic sequence that is expressed in uncorrected radiocarbon years (see DePratter, 1991).

While this ceramic sequence is well established for this region, it is less applicable to the southernmost portion of the coast. Therefore, while DePratter conducted surveys on and below Jekyll Island, we did not attempt to posit paleoshorelines on this portion of the southern coast. We do note, however, that this should now be possible given the development of a refined ceramic chronology in association with new radiocarbon dating (Ashley, 2010; see also Ashley, Rolland, and Thunen, this volume, chap. 15) for this area.

Although a large number of islands and surface exposures were examined through the course of DePratter’s initial early surveys, there are many more refinements that could be made to the data in this chapter. Specifically, one of the difficulties in conducting archaeological surveys along the Georgia coast is the thick, dense, vegetation that often covers islands and obscures archaeological sites. Therefore, surface visibility is often low to nonexistent over large portions of the coast, except in specific areas (i.e., island beaches at low tide and other erosional surfaces). However, the other way that sites are often identified, as is the case with our survey data, is by highly visible shell middens and shell scatters that dot the islands and coastal mainland. Although this aids in the overall identification of sites, the results are biased toward those sites containing shell deposits. We know from intensive subsurface surveys that artifact distributions often extend beyond, and are found without, shellfish remains (DePratter, 1979; Thompson and Turck, 2010). Therefore, additional refinement of some of these paleoshoreline maps could be accomplished through intensive shovel-testing programs on islands as Thompson and Turck (2010) conducted on the small back-barrier islands just west of Sapelo Island (see also Turck and Alexander, this volume, chap. 7, for refinement using geological methods). These new techniques and methods will offer an additional systematic and complementary line of evidence to further evaluate the maps presented in this chapter.

The GASF Coastal Archaeological Database

As we stated at the outset of this chapter, the most recent site location data from the GASF were used to evaluate the original data and shorelines created by DePratter. We used two datasets to create the two sets of maps presented in the results section. The first is a hydrological dataset that we used as the base map of the Georgia coast. Using scanned images of DePratter’s original shoreline location maps, we transferred the position of the paleoshorelines to our current base map. Site location data for the site distribution maps are based on the GASF database,[2] University of Georgia Laboratory of Archaeology. These two datasets were then imported and meshed together into a Geographic Information Systems (GIS) computer program in the NAD 27 projection. As noted by Thompson and Turck (2009), such data cannot be used uncritically. In order to identify problems within the dataset, we created a companion database based on DePratter and Howard’s original survey information from field books, notes, and information collected during their survey project. This database served as a check on the GASF database.

Despite these database checks, there are a number of limitations with the site location datasets. Foremost among these are the fact that site data are currently only available in point form and, therefore, site size information is absent in the GASF data (Thompson and Turck, 2009). While we do have site size information for the DePratter and Howard database, this is not critical to the current analysis as we are primarily concerned with the location of sites vis à vis the prograding coastline. The other two main sources of bias within the GIS data are survey coverage and time period designations based on ceramics. As for the survey coverage, we discuss the potential limitations in our examination of the various areas surveyed in the following sections. It is important to note that there can also be problems with the locational information in site file data, and steps can be taken to correct for such discrepancies (Turck, 2011: 42–44).

Time period designations based on ceramics can present certain problems in site file data stemming from inconsistencies in pottery identification and chronological association. It is here that our companion database provides the necessary cross reference to the key sites (those located east from the mainland) that form the basis of our shoreline maps. Greg Palk analyzed ceramics from the DePratter and Howard (1980, 1981; Howard and DePratter, 1980) survey in a manner consistent with DePratter’s (1991) sequence for the northern Georgia coast.

PALEOSHORELINES

For data presentation, the Georgia coast is divided into three different sections from north to south. The first section is the Ossabaw, Wassaw, and Tybee islands portion of the coast, followed by the St. Catherines and Sapelo islands area, and finally the St. Simons and Little St. Simons islands section. The lines on the following maps only represent general trends and should not be taken as the exact location of the shoreline for the date provided. However, these lines represent a starting point for more detailed studies (Turck and Alexander, this volume, chap. 7) that could further refine our understanding of these processes given a better understanding of the geology, as well as larger and more intensive archaeological survey.

Ossabaw, Wassaw, and Tybee islands

The Ossabaw, Wassaw, and Tybee islands area indicates progradation over an extended time frame (fig. 6.3). Perhaps the most interesting portion of this map is the 4500 b.p. shoreline that extends into the marsh northward from Ossabaw Island. Along this portion of the coast, there is considerable divergence between the Pleistocene and Holocene landforms. In this case, the western portion of Ossabaw Island and all of Skidaway and Wilmington islands are part of the Silver Bluff Pleistocene barrier island shoreline that formed when sea levels were much higher than present, around 36,000 to 25,000 b.p. (Hoyt and Hails, 1967: 1541; but see Dockal, 1995; Garrison et al., 2008; and Turck and Alexander, this volume, chap. 7). In contrast, the eastern half of Ossabaw, as well as Wassaw and Tybee islands, is all Holocene formations. These Holocene deposits are part of the Savannah River delta with deposition deflected to the south via longshore drift.

We place the 4500 b.p. paleoshoreline in the area of the Holocene marsh sediments based on the fact that a number of sites are located in this area. Specifically, there are shell ring sites as well as shell middens found in the marsh (DePratter, 1975, 1977a). Shell rings are semicircular, circular, or arc-shaped shell-bearing sites (DePratter, 1976; Russo and Heide, 2001; Thompson, 2007) and the most recent scholarship for the Georgia coast suggests that these sites are occupied throughout the year (Thompson, 2006; Colaninno, 2010; Thompson and Andrus, 2011). Often these sites are situated on the high points of islands, such as the Sapelo Shell Ring complex (see Thompson, 2006).

The sites along the eastern edge of Skidaway and Wilmington islands are shell middens, indicating utilization of marsh resources. These resources would not have been available until sea level rose and stabilized west of a newly developed barrier island that would block off the ocean and allow marsh development to the east of Wilmington and Skidaway islands. There is no remnant of this barrier in existence today. While these data certainly provide insight, we note that the complete geological record is not present at surface due to changing sea level and resulting erosion. Sea levels would have been somewhat lower at the time of occupation, as indicated by middens located on landforms that are now submerged (DePratter, 1975; Marrinan, 1975).

During the subsequent Refuge period, we note a low stand, as previously discussed. This 2900 b.p. shoreline is also based on additional subsurface data, whereas all others are based on surface collections (DePratter and Howard, 1981). Little Tybee Island lacks shell midden sites in general. This is most likely due, in part, to the lowering of sea levels. This environmental change was accompanied by a concomitant shift in technology as well as settlement patterns (Marrinan, 1975; DePratter, 1977a; Thompson and Turck, 2009).

When we compare the paleoshoreline maps created with data from DePratter’s surveys with the contemporary site distributions based on the GASF database, we see a striking correlation (figs. 6.4, 6.5, and 6.6). For the Late Archaic, Refuge, and Deptford periods, only two sites from the modern data fall outside of the original shoreline placement. These two sites date to the Late Archaic and are located just east of the line (compare with figs. 6.3 and 6.4). Late Archaic ceramics (St. Simons wares) are distinctive, so we do not think these ceramics are misidentified. It could be that this area was a small spit of a newly forming barrier island that would later become the western portion of Ossabaw. We suggest that more work be conducted in this area to refine the placement of the shoreline. As for the other time periods, which include Savannah, St. Catherines, and Wilmington, all of the current sites in the GASF database fall in line with the original shoreline placements.

St. Catherines and Sapelo islands

St. Catherines Island and Sapelo Island are two of the more archaeologically well-known islands of the Georgia coast, largely because of the sustained long-term investigations by individuals and institutions. Sapelo research had tended to focus on specific sites (e.g., Crook, 1986; Thompson, 2007; Thompson and Andrus, 2011; Jefferies and Moore, this volume, chap. 13) and little systematic survey has been undertaken. In contrast, St. Catherines Island has been the focus of research by archaeologists from the American Museum of Natural History for more than 30 years and includes large-scale systematic survey of the entire island, as well as intensive testing and excavation projects (e.g., Thomas, 2008: chaps. 7, 32, and 35; Thomas and Sanger, 2010). Therefore, St. Catherines represents the largest dataset by which paleoshorelines can be inferred (fig. 6.7).

The 4500 b.p. shoreline is based on known site locations as well as recent dating of both the St. Catherines Island Shell Ring and the McQueen Shell Ring (Thomas and Sanger, 2010; Sanger and Thomas, 2010; Bishop, Rollins, and Thomas, 2011). The paleoshorelines map meshes well with new geological data from St. Catherines Island Shell Ring. Recently, Bishop, Rollins, and Thomas (2011) conducted vibracore transects in the vicinity of this site. Their results indicate that there was marsh development around this time frame (ca. 4500 b.p.) both to the north and western sides of St. Catherines Island (Bishop, Rollins, and Thomas, 2011: 201–202). This correlates well with the paleoshorelines map, which also suggests marsh in this area based on the distribution of archaeological sites. In addition, archaeologists recently working on St. Catherines Island identified an additional ring (McQueen) on the eastern side of the island near the northern end of the Back Creek Scarp. The position of this early site again corresponds well with the location of the 4500 b.p. paleoshorelines. Furthermore, its placement on the eastern side of St. Catherines suggests that there must have been a barrier island in place farther to the east to allow marsh development.

Unfortunately, while there is speculation of Holocene island development for eastern portions of St. Catherines Island, as stated earlier, we are missing both geological and archaeological data of such evidence due to erosion. For example, many of the recurved spits on the southern portion of the island may have extended even farther south at one time (see Chowns, 2011). This is also why St. Catherines does not have the “butterfly” configuration noted for islands to the north (Bishop et al., 2007: Thomas, 2008: chap. 32, 843). Thomas, Bishop, and colleagues (Bishop et al., 2007; Thomas, 2008: chap. 32: 843, chap. 35) propose a hypothesized secondary Holocene island, dubbed Guale Island, which would have sheltered areas on the eastern side of St. Catherines allowing for marsh development before it was lost to erosion.

Unlike St. Catherines, Sapelo Island has had less extensive survey, although DePratter visited and surveyed many areas of the island, as well as some of the smaller Sapelo hammocks for his shoreline survey project in the 1980s (see Turck, 2011, for the most recent research on this topic). Despite this, the 4500 b.p. shoreline seems to be parallel to the eastern edge of the island. Although three shell rings are located on Sapelo, they are grouped in a cluster on the western side of the island, adjacent to expansive marsh estuaries. However, it is possible that more shell matrix Late Archaic sites are located on the northeastern portion of the island, as marsh formation may have begun here by the end of the Late Archaic period (see Turck and Alexander, this volume, chap. 7). Unfortunately, we have limited survey data from Blackbeard Island; however, enough sites were located during DePratter’s initial survey to infer the paleoshorelines. We suggest that with additional survey, particularly in light of the ridge and swale topography of Blackbeard Island, shorelines in this area could be refined considerably.

When we compare the paleoshorelines maps created with data from DePratter’s surveys with the contemporary site distributions based on the GASF, we again see a striking correlation (figs. 6.8, 6.9, and 6.10). For all the time periods, the current sites in the GASF database fall in line with the original shoreline placements.

St. Simons, Little St. Simons, and Jekyll islands

Although there is some information on St. Simons and Little St. Simons islands, we need more data from this region. Despite this, survey data known thus far combined with historic maps (particularly for Little St. Simons Island, where there is limited survey) allow us to propose shorelines for this area (fig. 6.11). Like the other shell ring sites mentioned in the study, the 4500 b.p. shoreline to the east is based on data from Oatland and Cannon’s Point shell rings (see DePratter, 1979; Marrinan, 1975, 2010). From the 4500 b.p. line, the island prograded eastward, as this area is a deltaic environment. Further to the south is Jekyll Island, which has had relatively little survey and the Holocene deposits are limited to small beach ridge clusters on the north and south ends. Therefore, we do not posit paleoshorelines for this island. In contrast, DePratter surveyed a large portion of Little Cumberland Island. However, much of the pottery recovered from this island does not fit with the northern Georgia coastal pottery chronology that we rely on here. So we make no attempt to draw shorelines for Little Cumberland either.

When we compare the paleoshorelines maps created with data from DePratter’s surveys with the contemporary site distributions based on the GASF, we again see a correlation (figs. 6.12–6.14). For all periods, the current sites in the GASF database fall in line with the original shoreline placements.

IMPLICATIONS FOR ARCHAEOLOGY, ECOLOGY, AND GEOLOGY

Archaeologists have concentrated most of their research endeavors on the large barrier islands of the Georgia coast (e.g., DePratter, 1976; Pearson, 1979a, 1979b; Thomas, 1988, 2008; Thompson, 2006, 2007; Thompson and Andrus, 2011). These studies document important trends during the past 5000 years; however, we are still missing a large part of the picture—specifically the nature of human occupation along the smaller islands that dot the Georgia coast. Such landforms are important components of Native American economies (Thompson and Turck, 2010; Thompson and Worth, 2011; Turck, 2011; see also Keegan et al., 2008, for the Caribbean area). While small marsh islands may seem like a harsh environment, it is clear from the data presented in this study that coastal peoples used these landforms extensively and intensively. Our study of the past shorelines shows the value of archaeological research in the marsh and back-barrier environment. Furthermore, it informs us regarding human use of this area, which, in part, helps to fill in the knowledge gap in terms of both the geology and human ecology of the coast.

There are several key points that we note as a result of the present shoreline data. First, some areas of the Georgia coast have undergone progradation for more than 4500 years. During this time, new islands, hammocks, and marshes developed because of the changing coastline. At least one time during this period, there was a sea level lowstand (DePratter and Howard, 1980, 1981; Gayes et al., 1992). This lowstand most likely had a significant impact on the distribution of resources and estuaries along the coast (DePratter, 1977a). Furthermore, while this lowstand certainly influences the archaeological visibility of sites, it also affected where and how humans used the landscape (Thompson and Turck, 2009).

Another key point illustrated by the data is that shortly, at least in archaeological terms, after new islands or hammocks formed, humans utilized these landforms (Thompson and Turck, 2010; Thompson, Turck, and DePratter, in press; Turck and Alexander, this volume, chap. 7). Thus, it seems that geological processes, at least in part, were one of the primary drivers of human use on the landscape. Based on this observation, we offer the hypothesis that populations during some time frames were, in part, limited by the lack of formation of new islands and habitats, while during other time periods, other social and economic factors were driving use of these areas. We suggest that at least part of this variability in use may be due to various subsistence practices, including the increasing role of agriculture among coastal populations. We currently do not have the data to evaluate this statement. However, with the new surveys on the mainland (see Sanger, this volume, chap. 9) and along the marsh islands (see Napolitano, this volume, chap. 8), it should be possible in the near future to evaluate these hypotheses. Again, we underscore the value of more intensive archaeological inquiry on small islands (see Thompson and Turck, 2010; Turck, 2011) to provide a broader perspective into the coastal economy and society of Native American peoples.

The survey and documentation of small islands and archaeological sites provide not only important clues to the Georgia coast’s geological history, but also to its social history. While this study offers a departure point for archaeologists and geologists to consider some of the larger research questions in this area, much more work is needed if a more holistic picture is to be provided. Research on back-barrier marsh islands is a logistically difficult endeavor. Understanding these landforms is further complicated by the fact that they are situated within a dynamic environment where there has been great loss to erosion and some occupied landforms have been submerged due to rising sea level. In the near future (a.d. 2100), predictions of global sea level rise are on the order of between 20 and 200 cm (Erlandson and Rick, 2008: 167). In addition, development along coastlines is on the rise and even the small islands of the Georgia coast are not immune from residential and commercial building. Therefore, time is at a premium for this research and it is imperative that more work of this sort be carried out soon before the record is lost (see Robinson et al., 2010).

Figure 6.1. Map of the Georgia Coast showing the major islands and wetland areas.

Figure 6.2. Map of the Georgia Coast showing both Holocene and Pleistocene islands.

Figure 6.3. Paleoshorelines of the Ossabaw, Wassaw, and Tybee islands section of the Georgia coast.

Figure 6.4. Paleoshorelines of the St. Catherines and Sapelo islands section of the Georgia coast.

Figure 6.5. Paleoshorelines of the St. Simons and Little St. Simons islands section of the Georgia coast.

Figure 6.6. Site locations with St. Simons, Refuge, and Deptford period components of the Ossabaw, Wassaw, and Tybee islands section of the Georgia coast.

Figure 6.7. Site locations with Wilmington, St. Catherines, and Savannah period components of the Ossabaw, Wassaw, and Tybee islands section of the Georgia coast.

Figure 6.8. Site locations with Irene, Historic Native American, and Historic Non-Native American components of the Ossabaw, Wassaw, and Tybee islands section of the Georgia coast.

Figure 6.9. Site locations with St. Simons, Refuge, and Deptford period components of the St. Catherines and Sapelo islands section of the Georgia coast.

Figure 6.10. Site locations with Wilmington, St. Catherines, and Savannah period components of the St. Catherines and Sapelo islands section of the Georgia coast.

Figure 6.11. Site locations with Irene, Historic Native American, and Historic non-Native American components of the St. Catherines and Sapelo islands section of the Georgia coast.

Figure 6.12. Site locations with St. Simons, Refuge, and Deptford period components of the St. Simons and Little St. Simons islands section of the Georgia coast.

Figure 6.13. Site locations with Wilmington, St. Catherines, and Savannah period components of the St. Simons and Little St. Simons islands section of the Georgia coast.

Figure 6.14. Site locations with Irene, Historic Native American, and Historic non-Native American components of the St. Simons and Little St. Simons islands section of the Georgia coast.

TABLE 6.1. Summary of the General Period, Phase, Ceramic Type, and Age Range for Pottery of the Georgia Coast

Period

Phases

Ceramic Types

RCY b.p.

Cal b.c./a.d.

Irene

Altamaha

Altamaha Line Block

250

*a.d. 1700

Altamaha Check Stamp

Altamaha Red Filmed

Irene Incised

Irene Burnished Plain

Irene Plain

370

*a.d. 1580

Pine Harbor

Irene Complicated Stamped

Irene Incised

Irene Complicated Stamped

Irene Burnished Plain

Irene Plain

525

a.d. 1410

Irene

Irene Complicated Stamped

Irene Burnished Plain

Irene Plain

625

a.d. 1310−1390

Savannah

Savannah II

Savannah Cord Marked

Savannah Plain

Savannah Burnished Plain

Savannah Complicated Stamp

Savannah Check Stamped

700

a.d. 1300−1380

Savannah I

Savannah Cord Marked

Savannah Burnished Plain

Savannah Plain

800

a.d. 1280

St. Catherines Period

St. Catherines

St. Catherines Net Marked

St. Catherines Cord Marked

St. Catherines Burnished Plain

St. Catherines Plain

1000

a.d. 1050−1150

Wilmington Period

Wilmington

Wilmington Cord Marked

Wilmington Brushed

Wilmington Fabric Marked

Wilmington Plain

1400

a.d. 660

Walthour

Wilmington Cord Marked

Wilmington Plain

Walthour Complicated Stamped

Walthour Check Stamped

* Historic dates are uncalibrated.

TABLE 6.1 — (Continued)

Period

Phases

Ceramic Types

RCY b.p.

Cal b.c./a.d.

Deptford Period

Deptford II

Deptford Complicated Stamped

1500

a.d. 630

Deptford Cord Marked

Deptford Check Stamped

Refuge Simple Stamped

Refuge Plain

1700

a.d. 410

Deptford I

Deptford Linear Check Stamped

Deptford Cord Marked

Deptford Check Stamped

Refuge Simple Stamped

Refuge Plain

2400

400 b.c.

Refuge Period

Refuge III

Deptford Linear Check Stamped

Deptford Check Stamped

Refuge Simple Stamped

Refuge Plain

2900

1000 b.c.

Refuge II

Refuge Dentate Stamped

Refuge Simple Stamped

Refuge Plain

3000

1130−1210 b.c.

Refuge I

Refuge Simple Stamped

Refuge Incised

Refuge Plain

3100

1360 b.c.

St. Simons Period

St. Simons II

St. Simons Incised & Punctated

St. Simons Incised

St. Simons Punctated

St. Simons Plain

3700

1980−2030 b.c.

St. Simons I

St. Simons Plain

St. Simons Plain

4400

2750−2860 b.c.

CHAPTER 7: COASTAL LANDSCAPES AND THEIR RELATIONSHIP TO HUMAN SETTLEMENT ON THE GEORGIA COAST

John A. Turck and Clark R. Alexander[3]

INTRODUCTION

Local geomorphology and geology are important to understanding human settlement patterns (Rossignol, 1992; Stafford, 1995, 2004; Dodonov, A.W. Kandel, A.N. Simakova, et al., 2007). The geomorphology of a landscape reveals when elements of the landscape initially formed, the processes involved in their formation, and the processes involved in subsequent landscape changes over time. Understanding these factors allows for a better interpretation of the archaeological record. Ideally, the analysis of the archaeological record should be separate from the geomorphology, but they are sometimes so intertwined that it is necessary to analyze them simultaneously. This is especially true in dynamic coastal settings, where environmental changes can occur yearly, seasonally, and even daily (Wells, 2001; also see Jordan and Maschner, 2000; Peros, Graham, and Davis, 2006; Dickinson and Burley, 2007; Bicho and Haws, 2008; Pollard, 2009; Erlandson and Braje, 2011).

To refine our understanding of Georgia coastal evolution, a campaign of vibracoring, dating (radiocarbon and optically stimulated luminescence), and sediment analyses were performed in four diverse intertidal settings: back-barrier, nondeltaic interbarrier, deltaic interbarrier, and southern end barrier/recurved spit. The results were then compared to the archaeological records of these areas, noting the implication of landscape history for settlement patterns, as well as how archaeology can speak to geomorphological studies.

BACKGROUND

The present-day Georgia coast includes barrier islands, marsh islands (also called hammocks), tidal marshes, estuaries, river channels, tidal creeks, as well as tidally influenced areas of the mainland (fig. 7.1). The initial formation of some of these features occurred during the Late Pleistocene epoch, after the height of the previous interglacial period around 125,000 b.p. As temperatures decreased and sea levels fell over the next 100,000 years, barrier island shorelines and associated back-barrier areas were created and abandoned. Beginning around 18,000 b.p., temperatures and sea levels started rising, reflooding these former shorelines and creating a complex mix of Holocene-aged features adjacent to, and on top of, Pleistocene and earlier Holocene features.

At present, the coastal mainland is made up of two of these former barrier island/back-barrier shorelines: the Pamlico shoreline complex (formed when sea level was around 7.3 m higher than at present); and the Princess Anne (formed when sea level was around 4 m higher than at present) (Hoyt and Hails, 1967: 1541) (see fig. 7.2). A former Pleistocene shoreline, known as the Silver Bluff formation, makes up part of the present-day barrier island complexes. This shoreline formed initially when sea level was 1.4 m higher than at present (Hails and Hoyt, 1969; Howard and Frey, 1985: 78). In a recent study by Booth and Rich (1999), freshwater peat from a core extracted from the Silver Bluff section of St. Catherines Island was radiocarbon dated to earlier than 40,000 b.p. The peat was most likely deposited during a time of lowered sea level, indicating that Silver Bluff sections of the present-day barrier islands formed earlier than 40,000 b.p. (Linsley, Bishop, and Rollins, 2008). Wehmiller et al. (2004) report that the Silver Bluff islands are approximately 80,000 b.p. based on U/Th dating.

The present-day back-barrier area, then, will have a fairly complex sedimentary history. Complicating the matter further is that in any given area, some parts of the stratigraphic sequence are preserved and other parts may be missing. Howard and Frey (1985: 78) suggest that stratigraphic deposits here will follow an estuarine sequence (either riverine or salt marsh), not a lagoon-fill sequence. Basal layers will be coarser-grained, and may contain thin sequences of the offshore facies of the Pamlico and Princess Anne shorelines, or deposits of tidal inlet/tidal channel fill, etc. (Hayes et al., 1980: 289). Above this should be the Pleistocene marsh facies that formed contemporaneously with, and behind, the Silver Bluff shoreline. Lying unconformably on top of these marsh deposits should be an erosional unconformity, the evidence of subaerial exposure and terrestrial influences, as sea level remained at least 40 m lower than present levels since 80,000 b.p. (see Martinson et al., 1987). Overlying this should be Holocene marsh sedimentation from the last 4500 years. Marsh islands within the back-barrier area are assumed to be remnants of former shorelines formed sometime after the Princess Anne shoreline, but before the Silver Bluff shoreline. It is also possible that they were parts of the Princess Anne and/or Silver Bluff shorelines that have since been erosionally separated from these larger features. This, of course, excludes those marsh islands of recent historical formation created by the deposition of dredge spoil or ship ballast.

In addition to the Pleistocene-age sections of the present-day barrier islands, there are also Holocene-age beach ridge/dune complexes that formed within the last 4500 years (Hayes et al., 1980: 285). Most of these Holocene deposits are found seaward of, and in close proximity to, the Pleistocene islands. However, Tybee, Wassaw, Little St. Simons, and Sea islands are separated from their Pleistocene counterparts due to the relatively abundant sediment supply from the Savannah and Altamaha rivers (Hayes et al., 1980: 282), allowing seaward progradation of these deltaic coastlines (Hayes et al., 1980: 285).

Intertidal areas between these Pleistocene and Holocene islands have a different sedimentological history than the back-barrier areas between the Pleistocene barrier islands and the mainland, and thus will be termed Pleistocene–Holocene interbarrier areas. These interbarrier areas do not have an underlying Pleistocene marsh facies. Basal deposits typically consist of relatively coarse, Pleistocene sands, especially where marshes closely flank barrier islands (Edwards and Frey, 1977: 236; Frey and Basan, 1981: 118). Holocene marsh deposits (4500 b.p.–present) are found on top of these sands (Frey and Basan, 1981: 118). Marsh islands in interbarrier areas represent relict beach ridges and dunes and must have formed within the last 4500 years given the sea level history in the area. A recent hypothesis suggests that many of these interbarrier areas were originally inlets, but have since been abandoned after rising sea levels caused rivers to follow a more direct route (Chowns et al., 2008; Chowns, 2011).

DePratter and colleagues (DePratter, 1977a; DePratter and Howard, 1977; DePratter and Thompson, this volume, chap. 6) have used Native American ceramics to date archaeological sites, and thus date when upland landforms were present and utilized by humans. Using this technique in the deltaic Pleistocene–Holocene interbarrier area between Skidaway and Wassaw islands, DePratter (1977a) documented seaward-advancing shoreline positions dating to 1500, 1000, 675, and 100 b.p. These data revealed that this part of the coastline prograded eastward over time, with the inhabitants moving with it to access resources. Using cultural remains proved to be a valuable technique in documenting changes in coastline positions, at least for prograding coastlines. DePratter and Thompson (chap. 6) use more recent archaeological data to refine these shoreline positions, and infer the position of Holocene shorelines for the rest of the progradational portions of the Georgia coast.

METHODS

Vibracoring

Numerous sediment cores from various environments along the Georgia coast were extracted and analyzed to better understand coastal evolution. In the back-barrier area behind Sapelo Island, cores were extracted from Jack Hammock, Mary Hammock, Fishing Hammock, and the adjacent marsh (fig. 7.3). In the nondeltaic Pleistocene-Holocene interbarrier area between Sapelo and Blackbeard islands, cores were extracted along a transect that runs from the western side of the Holocene-age Bay Hammock (a landform made up of at least seven beach ridges just to the west of Blackbeard Island), into the marsh, over a small marsh island, and then into the marsh on the other side of the hammock (fig. 7.4). Cores were also collected in between Skidaway and Wassaw islands to examine coastal development in a deltaic Pleistocene-Holocene interbarrier setting (fig. 7.5). The last area of core extraction was between a Pleistocene barrier island and a Holocene accretionary recurved spit, found typically at the southern ends of barrier islands. These cores were extracted in a transect running from the southern edge of Sapelo Island, into the marsh, across a small marsh island, and into the marsh on the other side (fig. 7.6).

A vibracorer was used to collect 7.6 cm diameter core samples in aluminum barrels at all sites. The top sediment unit containing root mat (between 15 and 36 cm) was removed with a shovel or bucket auger at some locations prior to coring, to avoid increased friction and clogging in the core barrel. Before and after removal of the barrel from the ground, numerous measurements were taken (e.g., the amount of root removal, the length of core pipe sticking out of the ground, the ground surface on the inside of the core, etc.) to calculate the amount of compaction that occurred during coring. All cores were between 1.5 and 6.0 m lengths, and were cut into 1.5 m lengths and capped on site, prior to transportation to the laboratory facility.

Core Analysis

Cores were transported to the Applied Coastal Research Laboratory of Georgia Southern University on the campus of the Skidaway Institute of Oceanography in Savannah for analysis. Cores were split lengthwise to produce two halves: one for sampling (the working half) and one for archiving (the archive half). First, both halves of each core section were photographed to record the original core color and character. Second, X-radiographs were taken of each working half with a VR 1020 portable X-ray machine to identify discrete layers and sedimentary structures not visible to the naked eye (Edwards and Frey, 1977; Butler, 1992). This aided in sampling, and helped locate unique items in the core (e.g., organic/carbonate material for dating, cultural remains, etc.). Cores were then described visually and subsampled for later analyses (see below). Color, texture, grain size, bioturbation, layering, and inclusions downcore were part of the visual descriptions. The archive halves of the cores were put into D-tubes and immediately refrigerated at 4°C, as were the working halves after core sampling took place.

Samples for particle size analysis were extracted from the working halves at either 10 or 20 cm intervals. The coarse fraction (i.e., grains larger than or equal to 63 μm) was separated from the fine fraction and dry sieved. The pipette method was performed on the fine fraction (i.e., grains smaller than 63 μm) to quantify the distribution of silt and clay (following Galehouse, 1971; also see Folk, 1980).

Radiocarbon and OSL Dating

As an integral part of understanding the timing of the various geomorphological changes on the coast, several dating procedures were employed. Samples for radiocarbon (14C) dating (dominantly carbonate) were collected from cores where suitable material was present. Radiocarbon samples were cleaned, dried, and analyzed by accelerator mass spectrometry (AMS) at the Woods Hole, MA NOSAMS facility, as well as the UGA Center for Applied Isotope Studies in Athens, GA. Where appropriate, 14C ages were calibrated using the online version of Calib 6.0. For marine samples, the ΔR value from Thomas (2008: chap. 13, 359) of –134 ± 26.0 was applied, and calibrated using the marine calibration curve (Marine09).

No organic material was present in many of the cores, necessitating the use of another technique to provide temporal context to our core observations. Strategically located soil samples for optically stimulated luminescence (OSL) dating were collected with a hand auger from a number of locales mentioned previously, including Pleistocene and Holocene barrier islands, Holocene beach ridges, and marsh islands. OSL samples were analyzed in the lab of Dr. George Brook at the University of Georgia. To correlate these dates to the calibrated 14C dates (which are in years before a.d. 1950), a value of 60 years was subtracted from each of the reported OSL dates. Thus, all OSL dates reported in this paper are in relation to years before 1950.

RESULTS

Back-barrier Area: Behind Sapelo Island

Marsh: Visual inspection of cores from the marsh near Mary Hammock (MT-01 to 06, MH-03) and Fishing Hammock (PNi12-02 to 04) revealed three main facies (fig. 7.7). The uppermost facies is modern marsh, which extends from the marsh surface to between 31 and 108 cm below surface (cmbs). The characteristics of this layer include a live root system (mostly of Spartina alterniflora, but also of Salicornia sp., etc.), within a soft, very dark gray or greenish gray mud (i.e., silt and clay), which becomes sandier with depth. The middle facies is made up of a very dark grayish brown to gray sandy matrix, mottled with black streaks, diffuse dark stains, and clay inclusions. In some of the cores, this sandy layer also contains very dark brown to grayish brown concretions of muddy sand. The bottom facies is a dense, overconsolidated greenish gray clay layer, which is encountered between 163 and 304 cmbs. It contains iron-rich dark yellowish brown and/or brownish yellow stains surrounding preserved root casts. In many of the cores there is a thin transitional layer, where the sandy layer overlies the greenish gray clay layer. This interface, which typically exhibits an erosional character, manifests itself as either a dark yellowish-brown iron-stained layer, or dark yellowish-brown iron-stained clasts in a gray sandy matrix.

X-radiography and particle size analyses, for the most part, confirm the findings of the visual inspection. They also revealed significant bioturbation, with varying amounts of marsh mud mixed in with the sandy layer, as well as the destruction of any physical sedimentary structures. In general, the middle sandy layers contain 70% sand or more. In the upper marsh facies and the bottom clay layer, sand percentages are less than 20%, clay content is around 60%, and silt content is typically less than 30%. More detailed analysis of the sand fraction revealed that fine sands (250–125 μm) make up the majority of the sand component, except within the greenish gray clay layer, which is made up of mostly very fine sands (125–64 μm).

The only organic materials obtained from these cores that could be used for 14C dating were roots and root casts (see table 7.1), which have poor, indeterminate vertical positioning. One root sample (core MT-06) obtained from within the greenish gray clay layer, about 223 cmbs, was dated to between 4972 and 4629 cal b.p. Another sample (core MT-02) obtained from the sand layer, about 162 cmbs, was dated to 2952–2792 cal b.p. As another way of dating marsh formation in the area, Turck (2011) extracted a tree stump from ~130 cm below the marsh surface, and had a sample of it (stump-1) radiocarbon-dated. The date range reported for it was between 4427 and 4247 cal b.p.

Marsh Islands (Mary, Fishing, and Jack hammocks): Cores from the marsh islands (MH-01 and 02, JH-02, PNi12-01) in back-barrier settings display a stratigraphy similar to the back-barrier marsh cores, but without the upper marsh unit. Visual observations identify an upper sandy unit extending from the surface to 150–360 cmbs, underlain by the same overconsolidated clay unit observed in marsh cores. While this stratigraphy is typical, it is not always present. One core collected in this study from the eastern side of Mary Hammock (MH-01) displays a thick sequence of sandy deposits throughout its 5.25 m length, with no overconsolidated clay layer.

X-radiography and sediment texture observations show characteristics similar to the back-barrier marsh cores, with bioturbation present in the sandy unit and little preserved stratification, with the exception of heavy mineral laminae and coarser interbeds near the sand/overconsolidated clay boundary. As in the marsh, sandy sediments can be characterized as fine sands (~150 μm, or 2.75 phi units). These are found in the upper 1.5–3.6 m, and are made up of 80% sand or more, with 10% or less of silt and clay. The overconsolidated silty clays contain <10% sand, ~65% clay, and ~25% silt with a mean size of 1–2 μm. Textural data from samples collected with a hand auger during surveys of 20 Pleistocene Georgia back-barrier marsh islands displayed similar characteristics with an average size of 160 μm, and average contents of 82%, 10%, and 8% of sand, clay, and silt, respectively (Alexander, 2008). Core MH-01, from the east side of Mary Hammock, displays similar sand sizes (~150 μm) in the upper 264 cm of the core, but below that boundary, the stratigraphy is different than that observed on other marsh islands, displaying a broad range of mean sizes (~64 μm to ~4 μm) over short depth scales, common presence of mica, and concentrations of heavy minerals at the boundary between the upper and lower sand units. Radiocarbon analysis of possible marine shells (they look like Turritella sp.) found in this lower, distinctive sand unit at the base of core MH-01 provided ages of 49,274–46,484 cal b.p. (475 cmbs) and 43,221–41,975 cal b.p. (516 cmbs). A bulk carbon 14C date of the overconsolidated greenish gray clay from Jack Hammock (JH0609-02) provided an age of 9887–9520 cal b.p.

Nondeltaic Pleistocene-Holocene Interbarrier Area: Sapelo-Blackbeard Barrier Island Complex

Marsh: Cores within the nondeltaic Pleistocene–Holocene interbarrier marsh area (cores HNi1-02, 03, 04, 06, 07, and 08) show a consistent stratigraphy that differs from that of the back-barrier marsh. In all these cores, the upper unit (~100–175 cm thick) is a mixture of sand and varying amounts of mud, and exhibits coarsening with depth (see fig. 7.8). Cores on the fringes of the marsh have less mud content, and those in the middle of the marsh have more. Black staining and streaks, along with mud inclusions is also common. Below the sandy layer, all marsh cores exhibit a rapid transition to normally consolidated, Holocene muds. This grades downward into interbedded sands and muds. This is significantly different from cores from the back-barrier areas, where overlying sands transition rapidly into overconsolidated, Pleistocene muds (i.e., the greenish gray clay layer), below which we have not been able to penetrate.

Textural and X-radiographic data illustrate that the grain sizes and sedimentary structures observed in the nondeltaic Pleistocene-Holocene interbarrier marsh cores are actually fairly similar to that observed in the back-barrier marsh cores. Bioturbation is common in the upper unit, destroying sedimentary structures, whereas the fine-grained deposits below contain relict roots and inclusions of black organics. Grain sizes in the upper and lower units are similar to those in the back-barrier setting as well. The upper unit contains fine sands (~150 μm or 2.75 phi units), with slightly less mud observed (approximately 95–90% sand). The normally consolidated muds in the lower unit are silty clays with a mean size of 1–2 μm, and typically contain <5% sand, ~75% clay, and ~15% silt. The interbedded sands and muds exhibit variable mean grain sizes between 64 and 300 μm, and with 99–25% sand, 40–2% clay, and 7–1% silt. X-radiographs illustrate that the interface between the overlying sands and the underlying muddy deposits is erosional and that the interbedded sands and muds are cross-stratified and preserve graded bedding.

Radiocarbon dates from shell material in two cores in this region provide three ages that constrain the formation of the marsh. In core HNi1-03, a 14C age of 3976–3560 cal b.p. was determined in the lower part of the interbedded sands and muds near the base of the core at 438 cmbs. In core HNi1-08, a 14C age of 3997–3561 cal b.p. (sample HNi1-08 III) was determined in similar interbedded sands and muds at 423 cmbs. Higher up in this same core (at 99.5 cmbs), a 14C age of 3311–2904 cal b.p. (sample HNi1-08 I) was determined at the transition from the sandy mud layer to the consolidated Holocene mud layer. These ages constrain the initial development of Holocene marsh in the nondeltaic interbarrier area to after 3560 b.p., but prior to 2900 b.p.

Marsh Island (HNi1): The single marsh island core (HNi1-05) within the nondeltaic Pleistocene–Holocene interbarrier area exhibits a sandy upper unit about 265 cm thick. This unit overlies the same Holocene mud and interbedded sand and mud units described for the above marsh cores. The only significant stratigraphic difference is the additional thickness (~100 cm) of the overlying sandy unit, and the bedded, coarser sediments at the boundary between the upper (sandy) and middle (muddy) units.

Textural analysis shows that the upper sandy unit contains 97–100% sand, 0–2% clay, and 0–1% silt. It also indicates similar characteristics in the surrounding marsh cores (HNi1-01 to 04, and 06 to 08), exhibiting fine sands in most of the unit (~150 μm, or 2.75 phi units). The lowermost 50 cm of the unit coarsens significantly, from fine to coarse sand (~1000 μm) and exhibits obvious, well-preserved graded bedding. Textural data from samples collected with a hand auger during surveys of five Holocene marsh islands in a Pleistocene–Holocene interbarrier setting displayed similar characteristics with an average size of 190 μm and average sand, clay, and silt contents of 98%, 1%, and 1%, respectively (Alexander, 2008). X-radiographs highlight the obviously energetic zone between the overlying sand and the underlying mud by exhibiting the cross-bedded internal structure of the coarser layers, as well as the rough, erosive nature of the sand/mud interface.

One OSL date from this island (sample OSL01), collected from the sandy layer (~116 cmbs), provides a date range between 6240 and 4440 b.p. (see table 7.2). As mentioned above, the 14C method revealed that the underlying Holocene mud unit began forming between 3560 and 3311 cal b.p. The resulting age ranges from these two methods are not only out of sequence, they do not even overlap. This issue will be discussed later and requires further examination.

Holocene Barrier Island (Blackbeard): Two samples from a sandy beach ridge on the westernmost side of Blackbeard Island provide independent estimates of the island’s initial formation. One sample (OSL02) from 135 cmbs was determined to have an age range of 1340–1140 b.p. using the OSL method. The other sample (Blackbeard midden) was an oyster shell from a shell midden approximately 50 cmbs. The 14C method returned an age of 2000–1616 cal b.p. Similar to the abovementioned Holocene marsh island, there is a slight discrepancy between the OSL and 14C dates. However, in this case, the 14C date is older than the OSL date. There is also the added variable that this shell is from a cultural deposit. Again, this issue will be discussed later.

Deltaic Pleistocene-Holocene Interbarrier Area: Skidaway-Wassaw Barrier Island Complex

Marsh Islands and Barrier Islands: Four vibracores (OSL 7VA, 7VB, 8VA, and 8VB) and five auger cores (OSL07 through 011) were collected from marsh islands between Skidaway and Wassaw islands, and from the west side of Wassaw Island to examine the accuracy of the dating methodology of DePratter (1977a). In general, these marsh islands consist of a sandy unit up to 5 m thick, with one or two finer, isolated units contained within this sandy unit. Textural analyses for cores show that sediments are clean, fine sands (~150 μm), with 99–92% sand and 4–1% clay and silt. A few muddy interbeds were also noted in the cores. These layers are texturally varied, and consist of 64–7% sand, 61–21% clay, and 32–15% silt. Textural data from 15 other marsh islands in the deltaic interbarrier area that were collected with a hand auger displayed similar characteristics. The average grain size is 19 μm, with average sand, clay, and silt contents of 98%, 1%, and 1%, respectively (Alexander, 2008). The stratigraphy observed in all of these cores is very similar to what was documented in the cores from the marsh islands in the nondeltaic interbarrier area (discussed in the previous section). In terms of depositional units, then, the data provided by these cores are consistent and comparable.

Two OSL samples from the Silver Bluff-age Skidaway Island, SK-05B and SK-06B, returned ages of 46,440 and 45,740 b.p., respectively. These constrain the age of the last active period for geomorphologic change on Skidaway Island. Moving eastward from Skidaway, five OSL ages were produced from auger cores OSL07 through 011 on two marsh islands and Wassaw Island (fig. 7.9). Core OSL07, on DePratter’s (1977a) 1500 b.p. line, returned an OSL age of 1496 ± 220 b.p. Core OSL08, just east of the 1000 b.p. line, provided an OSL age of 865 ± 100 b.p. Core OSL09, on the 675 b.p. line, returned an age of 468 ± 50 b.p. Core OSL010, on the western edge of Wassaw Island just east of the 675 b.p. line, returned an age of 329 ± 60 b.p. Finally, Core OSL011, east of the 675 b.p. line, and west of the 100 b.p. line, returned an age of 75 ± 20 b.p. A second set of dates was produced using the 14C method from two of these OSL sampling sites, to independently check the dating of this area. A date of 2745–2374 cal b.p. (sample OSL-07VB) was produced from shell about 385 cmbs, from the same site as OSL07. Two 14C dates were produced from the same site as OSL08. A date of 1437–1126 cal b.p. (sample OSL-08VB II) was produced from shell about 220 cmbs, while a date of 1404–1094 cal b.p. (sample OSL-08VB III) was produced from shell at 378 cmbs.

Pleistocene Barrier/Holocene Recurved Spit Setting: Southern End of Sapelo Island

Pleistocene Barrier Island (Sapelo): The core from Sapelo Island (PCi29-00) exhibited only sandy sediments throughout its 250 cm length. Textural data show that the upper few meters of this core are similar to that observed in other cores throughout this study: fine sand with a mean size of ~150 μm. The lower meter of this core coarsens to a medium sand (~300 μm). An OSL date from 150 cmbs returned an age of 56,340 ± 9000 b.p. (sample OSL04).

Marsh: Cores from the marsh (PCi29-01 to 04, and 06 to 09) have highly variable stratigraphy. Along the island fringe, cores (PCi29-04, 06, 07, and 08) have stratigraphy similar to back-barrier and interbarrier areas. Upper sand units are 125–260 cm thick, made up of fine sands with a mean size of ~150 μm. Sands become finer with depth. Sand composes more than 93% of the sediments in these cores.

Cores farther out into the marsh (PCi29-01 to 03, and 09), farther from the island fringe, do not exhibit similar characteristics to the other cores examined in this study. Changes in texture occur relatively quickly, on length scales of 10–25 cm. The grain size changes are large as well. Mean grain sizes range from 1–700 μm over length scales of tens of centimeters. In addition, homogeneous beds intercalated with interbedded sands and muds were found in these cores. This sedimentological character is not similar to the other marsh cores examined in this study, and highlights the dynamic nature of the sound margin environment. Two 14C ages were determined from two of these marsh cores. A date of 44,369–41,070 cal b.p. (PCi29-02) was produced from shell at about 518 cmbs. A date of 2375–2001 cal b.p. (PCi29-09) was produced from shell at about 432 cmbs. Once again, this discrepancy in dates will be addressed below.

Marsh Island (PCi29): One core was extracted from the marsh island (PCi29-05). This core exhibits a distinct stratigraphy that again accentuates the dynamics of the sound margin environment. In addition, the sediments in this core are the coarsest observed in this study. Textural analyses show that the upper unit is about 100 cm thick and made up of fine sands of ~150 μm. Sediments coarsen to ~1000 μm, exhibiting interbedded medium and coarse sands between 125 and 250 cmbs. Below 250 cm, sediments span a range of sizes (2–64 μm) and occur as interbedded sands and muds, as well as thick beds of mixed sand and mud. X-radiographs show well-preserved sedimentary structures, including cross-bedding, graded bedding, erosional truncations of strata, and concentrations of shells.

Three dates were determined from this island core. One 14C age of 2318–1971 cal b.p. (PCi29-05 III) was determined at 410 cmbs. Another 14C age of 2442–2056 cal b.p. (PCi29-05 II) was determined higher up in the core, at 268 cmbs. An OSL date range of 2440–1840 b.p. (OSL03) was determined at this same site, at about 82 cmbs.

DISCUSSION

Back-barrier Area

Positing that the back-barrier area behind Sapelo Island had a fairly complex sedimentary history proved to be an understatement. The overconsolidated greenish gray clay layer found at the bottom of all but one of the cores from the back-barrier region may represent a relict Pleistocene marsh or other estuarine setting, deposited behind the Silver Bluff shoreline after it formed. The Holocene age of 4972–4629 cal b.p. (sample MT-06) can be discounted, due to the nature of the preserved root casts within this clay layer. These root casts represent plants that were living on a surface higher in the core than the level where the sample was obtained, representing young carbon contamination. The living surface of the plants was most likely in the sandy layer, above the greenish gray clay layer. Direct dating of the root (sample MT-06) only revealed that the greenish gray clay layer is older than 4629 cal b.p. This carbon contamination problem also affected the bulk carbon measured in the sample from Jack Hammock (sample JH0609-02). The age of 9887–9520 cal b.p. was also obtained with some organic material from root casts. A similarly compacted blue-green clay layer was found in the back-barrier area of Virginia (Finkelstein and Ferland, 1987: 149). Sandy peat underneath that clay layer has 14C dates of 23,550 and 30,870 b.p. (Finkelstein and Ferland, 1987: 147 and 151), suggesting that this type of layer is much older.

The sandy layer in between the Holocene marsh layer and the overconsolidated greenish gray clay layer most likely represents the former upland surface that was exposed prior to Holocene marsh deposition (Turck, 2011). The 14C date for the stump reveals a terminal date of 4427–4247 cal b.p. for this sandy layer, suggesting that saline conditions increased, and possible marsh formation occurred, in the vicinity of Mary Hammock at this time. The elevation of the tree (~130 cmbs) correlates well to the height of sea level at 4200 b.p. (see Turck, 2011: 132–133) as proposed by DePratter and Howard (1981) and Gayes et al. (1992).

The 14C determinations reported in this chapter for Mary Hammock are Pleistocene in age (MH-01 III and IV) and are found within probable intertidal channel deposits. That these dates were obtained from what look like marine shells is confusing. If they are indeed marine in origin, they may have eroded from earlier deposits into these deposits by tidal channel migration during the Holocene and may not be related to the formation of the marsh island. The only other date for back-barrier marsh islands in this area comes from shell collected from a “core hole” on Pumpkin Hammock (Hoyt, Henry, and Weimer, 1968: 385–386). Results from this shell support the older ages for the shells from Mary Hammock, as this shell had a finite age of >38,500 b.p. derived using an older, less sensitive 14C dating technique (Hoyt, Henry, and Weimer, 1968: 385–386).

From our current set of observations near Sapelo Island, it appears that most of the back-barrier marsh islands may be perched atop relict Pleistocene muds, indicating that the marsh islands formed after the Silver Bluff shoreline and after the formation of the marsh behind the Silver Bluff shoreline. If true, this indicates that the surface expression of these marsh islands does not represent erosional remnants of former Pleistocene shorelines. One possible explanation is that marsh islands represent features that were created by sea levels that were higher than present-day levels, sometime after the Silver Bluff highstand, but before 4500 b.p.

Another explanation is that these marsh islands did form before the Silver Bluff shoreline, but had a smaller area and were higher in elevation at the time. After the formation of the Silver Bluff shoreline and subsequent marsh deposition around these existing uplands, erosion deflated the marsh islands, and spread their sand on top of the Silver Bluff marsh. Thus, the original interface between the marsh and the island edge may be much closer to the center of the islands than the position of the present-day island edge. This premise could be tested with a series of closely spaced cores from the edge to the center of one of the back-barrier marsh islands, and/or with the use of geophysical techniques. It is also possible that the bottom clay layer does not represent relict Pleistocene marsh, another premise that needs to be tested.

As far as human settlement patterns are concerned, shovel test surveys of back-barrier marsh islands (Little Sapelo Island, Pumpkin Hammock, Mary Hammock, and Patterson Island; see Thompson and Turck, 2010; Turck, 2011; Thompson, Turck, and DePratter, 2013), as well as a shoreline survey of Jack Hammock by DePratter (Georgia Archaeological Site File database), reveal that Native American occupations basically span from 4200 to 250 b.p. (i.e., the Late Archaic through historic contact periods). That the earliest human occupation of these marsh islands began around 4200 b.p. seems to confirm the idea that these islands formed more recently. However, this pattern is typical of most of the Georgia coast. There are very few sites that date prior to 4500 b.p. (i.e., during the Paleo-Indian, Early Archaic, and Middle Archaic time periods) on landforms of any age (see Turck, Williams, and Chamblee, 2011). This is related, in part, to assumed lower population levels, to the lack of site visibility (e.g., no pottery or shell deposition occurred during these earlier periods), and to formation processes (e.g., possibly deeply buried sites). The 4427–4247 cal b.p. date range from the tree stump (Stump-1), indicating the time of initial flooding of the back-barrier upland by marine waters and initiation of marsh formation, lends support to the idea that coastal Late Archaic populations were tied closely to the establishment of the marsh-estuarine system. (Although, see Turck, 2012, for a discussion on the potential for Middle Archaic period marsh formation and its implication for Late Archaic period settlement.)

Nondeltaic Interbarrier Area

Holocene marsh formation first occurred in the area between Sapelo and Blackbeard islands sometime after 3560 cal b.p. up until about 2900 cal b.p. These underlying salt marsh deposits exhibit the expected transition from interbedded sand and mud representing tidal channel deposits to more homogeneous, bioturbated, overlying salt marsh silts and clays. This suggests that a Holocene barrier formed by 3560 b.p., protecting the area from wave action. This same marsh deposit can be traced stratigraphically in cores underneath the marsh island and the widespread upper sandy unit, suggesting that the island formed after the marsh. It is probable that energetic forces (e.g., storms or hurricanes) created an erosional unconformity on the marsh surface as they transported sand back onto the marsh, forming the island. It is also important to note that the timing of this unconformity (somewhere around 3311–2904 b.p.) is close in time to the drop/rise in sea level noted by DePratter and Howard (1981) and Gayes et al. (1992) (also see Turck, 2011: 13–14 for discussion). Since that time, the sandy layer has been capped by encroaching marsh and tidal waters, transporting in muddy sediment that has since bioturbated down into the sandy unit. The marsh island probably formed around 2904 cal b.p. (sample HNi1-08 I), which is the age at the base of the widespread sandy unit that truncates and caps the underlying salt marsh deposits. The older date (6240–4440 b.p.) for the island itself (sample OSL01), probably results from the observed presence of storm-derived, heavy mineral concentrates in the core, which have been shown to affect age calculations using the OSL technique.

While there is no evidence of human occupation on this particular marsh island, there are multiple archaeological sites on marsh islands directly to the north, as well as on Bay Hammock and Blackbeard Island to the east. Surveys by DePratter (1977a) and Marrinan (1980) on these nearby landforms revealed 39 sites with 51 components, none of which date to before 1500 b.p. (i.e., before the Late Woodland period). An OSL date of 1340–1140 b.p. (sample OSL02), and a 14C determination of 2000–1616 cal b.p. (Blackbeard midden) from the same sampling site on the western edge of Blackbeard Island are consistent with the archaeological data. The 14C date was obtained from an oyster shell from a human-deposited shell midden, so it is not surprising that this date corresponds with the archaeology. The OSL date, from 135 cmbs, reveals the age of the dune ridge formation itself.

Deltaic Interbarrier Area

The OSL and 14C dates between Skidaway and Wassaw islands, for the most part, support the technique of using Native American and historic ceramics to date shoreline positions (DePratter, 1977a; DePratter and Howard, 1977). There is general agreement between the archaeology-based timelines and the OSL samples on the marsh islands between Wassaw and Skidaway islands. However, the youngest archaeology-based shorelines proposed for Wassaw Island do not agree with the OSL constrained ages, which are consistent with historical records of shoreline position from old maps and charts.

Part of this discrepancy may be due to the fact that the shoreline dates are uncalibrated, making the comparison tenuous. However, this discrepancy also reveals the problem with only using archaeological data to interpret sea level history. The geomorphology of the beach ridges of Wassaw Island, in conjunction with the OSL dates reported here, indicate the island has been eroding on its north end and accreting toward the south for the past 300–500 years, thus showing that the island gets younger from north to south. The lack of dated archaeological sites on Wassaw Island makes it difficult, if not impossible, to locate former shorelines without taking into account such geologic information. This also underscores the need for thorough archaeological surveys. Without such surveys, the proper data needed for this technique to work will not be available. For example, a lack of sites noted in an area might be due to a lack of archaeological survey, not necessarily to the formation processes of the landforms.

DePratter and Thompson (this volume, chap. 6) offer more refined shoreline positions based on recent archaeological data, removing the 1500 b.p. shoreline and adding a 1400 b.p. shoreline to the east of Flora Hammock. This shoreline incorporates the Middle Woodland sites found on Flora Hammock, and fits better with the OSL (1716–1276 b.p.) and 14C (2745–2374 cal b.p.) age ranges (fig. 7.9). Although there were discrepancies between the 14C date and the OSL dates, the samples for 14C dating were found between 1.0 and 2.7 m deeper than the OSL samples. Deeper stratigraphic locations represent older surfaces, and thus older dates are expected. The transition from subtidal to intertidal to supratidal should be recorded by the sediment record, with the superposition of multiple features reflecting different sea levels.

The 14C dates (1437–1126 and 1404–1094 cal b.p.) just to the east of the 1000 b.p. shoreline are more difficult to interpret. It is possible that the 1000 b.p. shoreline should be moved eastward of the marsh island with these older dates. However, the 14C samples are from fairly deep below the feature (220 and 378 cmbs, respectively), and represent surfaces that would have been intertidal or below sea level at that time. Archaeological sites have been found on this marsh island, but were not dated (DePratter, 1977a: 16), indicating that more detailed archaeological and geomorphological studies need to be performed on this island.

Barrier/Recurved Spit Setting

The cores extracted from this area illustrate the dynamic nature of the inlet/sound environment, and contrast sharply with the cores from the back-barrier, nondeltaic, and deltaic areas. The upper deposits on Sapelo Island formed between 65,340 and 47,340 b.p. (OSL04). Well-preserved sedimentary structures found in the marsh and marsh island cores, including cross-bedding, graded bedding, erosional truncations of strata, and concentrations of shells, all suggest that sediments accumulated relatively rapidly, and that an energetic environment prevailed at the site during the initial formation of the marsh island (PCi29). Although at present Doboy Sound is about 925 m away, this location was an active sound margin in the past. While the dates for the marsh island (samples OSL03, PCi29-05 II, and PCi29-05 III) and the marsh (sample PCi29-09) are slightly out of sequence, their ranges overlap considerably, showing strong coherence. All four dates overlap within the range of 2318–2056 b.p., indicating that the area went from an active inlet to a protected marsh setting fairly rapidly (in a little more than 250 years). The 42,647 cal b.p. 14C age from deep in the marsh (core PCi29-02) is anomalous and represents an old shell, remobilized from Pleistocene deposits. The textural data indicate that Doboy Sound was directly adjacent to the southern edge of Sapelo Island at this time—such coarse sediments are not found along the beaches or other back-barrier islands.

The marsh island at this location was initially thought to be Pleistocene in age and to have potentially been a section of Sapelo Island, based on its proximity and its roughly circular nature. Holocene hammocks are typically elongate in character. Under this scenario, rising sea levels would have isolated the landform, and eventually filled the intervening areas with marsh sediment. The dating, as well as the archaeology, refuted this idea. While no formal archaeological survey has been performed on this marsh island (site 9Mc495), Turck and Thompson have performed two informal pedestrian surveys in conjunction with the coring activities reported in this chapter. The earliest occupation seems to be around 1500–1000 b.p. (i.e., Wilmington cord-marked pottery was noted), although shovel testing and/or excavation could reveal an earlier occupation. These documented ages coincide with the OSL and 14C dates for the island, and show the utilization of the upland surface soon after it was created.

CONCLUDING REMARKS

This chapter reveals that processes are not always consistent in a dynamic landscape. This inconsistency highlights the many difficulties encountered in generalizing changes in coastal landforms. Back-barrier marsh islands might not be remnants of former Pleistocene shorelines. Reworking of sediment and transport onto previously formed surfaces might describe more landform formation than once thought. Despite a close proximity to Pleistocene barrier islands, marsh islands can date to much more recent times. In short, the timing of landform creation cannot be estimated based solely on the position of that landform on the landscape. One implication for archaeology, then, is that different geological and geomorphological processes occurred within close proximity of each other on the landscape, allowing for a range of environments from which humans could choose when settling the coast. In addition, this study reveals that the timing of the human occupation of a landform should not be assumed without some form of archaeological ground-truthing (i.e., survey or excavation). As Turck (2011: 210–211) notes, each specific environment/habitat of the Georgia coast needs to be treated separately, and characterized both environmentally and archaeologically. Deltaic, nondeltaic, barrier, back-barrier, interbarrier, mainland, island, marsh, Pleistocene, Holocene, etc., are all characteristics that inform us of the environmental processes that formed the landscape. They are also variables related to how the landscape was affected by environmental changes over time (especially changes in sea level). Only after each landform is characterized, including their geomorphological changes over time, can we appreciate any subtle changes in human settlement and subsistence patterns that may be manifest on those landforms and begin to better understand the timing of (and reasons for) those patterns (Turck, 2011: 211).

This chapter also corroborated what others have noted previously, namely that the archaeological record can be used to effectively date landforms (DePratter, 1977a; DePratter and Howard, 1977; DePratter and Thompson, this volume, chap. 6). Our observations also corroborate an important aspect of human settlement patterns that has been noted before: coastal landforms were rapidly utilized by humans soon after the landforms developed (DePratter, 1977a; DePratter and Howard, 1977; also see Thompson, Turck, and DePratter, 2013). This continuity between landform development and utilization illustrates that archaeological studies of an area can be as good as radiometric dating at revealing the ages of landscapes, as long as pertinent geological and site formation processes are also considered. In addition, while surface surveys worked particularly well in areas of rapidly moving coastlines (DePratter and Howard, 1977), we suggest that subsurface surveys should be employed in areas where landform creation is slower and where there is currently no obvious erosion. This will allow deeper, unexposed, and possibly older, archaeological deposits to be found that might not be manifest on the surface.

One final point to be made is of the complementary nature of archaeological, geological, and geomorphological techniques. Although this chapter reveals how each can inform the others, it must be stressed that they are directly complementary and must be used together to best enhance interpretations. Comparison of the OSL dates from the Skidaway-Wassaw area with the shoreline ages proposed by DePratter (1977a) for the same area shows that geological, as well as archaeological, knowledge must be employed to get the most accurate estimates of former shoreline position and age. Together, these techniques can be used to understand processes that are not straightforward in either field individually, avoid circular arguments, and add a human dimension to physical landscape change.

Figure 7.1. Aerial photograph of the northern part of the Georgia coast, indicating the main islands discussed in chapter 7.

Figure 7.2. Three former shoreline complexes in relation to the present-day (Holocene) shoreline complex.

Figure 7.3. Back-barrier area between the mainland and Sapelo Island, indicating the locations of marsh islands discussed in the text as well as the locations of vibracores and 14C dates.

Figure 7.4. Interbarrier area between Sapelo and Blackbeard islands, indicating the locations of islands discussed in the text as well as the locations of vibracores, 14C dates, and OSL dates.

Figure 7.5. Interbarrier area between Skidaway and Wassaw islands, indicating the locations of 14C and OSL dates.

Figure 7.6. Barrier/recurved spit area off of the south end of Sapelo Island, indicating the locations of vibracores, 14C dates, and OSL dates.

Figure 7.7. Vibracore MT-03, an example of a back-barrier marsh core.

Figure 7.8. Vibracore HNi1-08, an example of an interbarrier marsh core.

Figure 7.9. Details of the Skidaway-Wassaw interbarrier area showing the locations of the OSL and 14C dates in relation to DePratter’s (1977) shorelines and known (as of 2010) archaeological sites.

TABLE 7.1. Radiocarbon Dates from Various Locations on the Georgia Coast

Abbreviation: cmbs = centimeters below the surface.

Lab/sample no.

Name/core no.

Provenience

cmbs

Material

δ13C (‰)

Adjusted 14C age b.p.

14C age b.p., calibrated (± 2σ)

Median age b.p.

UGAMS-5003

Stump-1

Marsh, by Mary Hammock

130.0

wood

-26.60

3920 ± 30

4427–4247

4357

UGAMS-5004

MT-02

Marsh, by Mary Hammock

161.5

plant frag.

-27.60

2780 ± 30

2952–2792

2878

UGAMS-5005

MT-06

Marsh, by Mary Hammock

223.0

plant frag.

-25.90

4270 ± 50

4972–4629

4843

NOSAMS-

71166

OSL-07VB

Marsh island, by Skidaway

384.5

shell

-0.54

2720 ± 15

2745–2374

2595

NOSAMS-

71167

OSL-08VB II

Marsh island, by Skidaway

219.5

shell

-0.9

1600 ± 15

1437–1126

1282

NOSAMS-

71168

OSL-08VB III

Marsh island, by Skidaway

377.5

shell

-0.93

1580 ± 20

1404–1094

1262

NOSAMS-

71163

PCi29-02

Marsh, by Sapelo

517.5

shell

0.85

38,400 ± 1100

44,369–41,070

42,647

NOSAMS-

71161

PCi29-05 II

Marsh island, by Sapelo

268.0

shell

-2.36

2450 ± 20

2442–2056

2246

NOSAMS-

71162

PCi29-05 III

Marsh island, by Sapelo

409.5

shell

-0.13

2360 ± 15

2318–1971

2152

NOSAMS-

71164

PCi29-09

Marsh, by Sapelo

431.5

shell

-0.9

2420 ± 25

2375–2001

2215

NOSAMS-

68513

Blackbeard midden

Blackbeard Island

50.0

shell

0.01

2090 ± 30

2000–1616

1820

NOSAMS-

68462

HNi1-03

Marsh, by Blackbeard

437.5

shell

0.84

3690 ± 35

3976–3560

3770

NOSAMS-

71165

HNi1-08 I

Marsh, by Blackbeard

99.5

shell

-4.99

3140 ± 20

3311–2904

3104

NOSAMS-

68500

HNi1-08 III

Marsh, by Blackbeard

422.5

shell

0.25

3700 ± 40

3997–3561

3782

NOSAMS-

74565

JH0609-02

Jack Hammock

212.0

bulk sed.

-24.95

8650 ± 70

9887–9520

9626

NOSAMS-

74484

MH-01 III

Mary Hammock

474.5

shell

-1.23

45,000 ± 440

49,274–46,484

47,870

NOSAMS-

74485

MH-01 IV

Mary Hammock

515.5

shell

0.2

38,400 ± 410

43,221–41,975

42,592

UGAMS-

R50537

Bethesda Shoreline A

Mainland, by Skidaway

150.0

shell

0.19

39,317 + 185

43,728–42,757

43,211

UGAMS-R50537B

Bethesda Shoreline B

Mainland, by Skidaway

150.0

shell

0.06

41,572 + 412

45,602–44,289

44,922

TABLE 7.2. Optically Stimulated Luminescence Dates from Various Locations on the Georgia Coast

Abbreviation: cmbs = centimeters below the surface.

Lab/sample no.

Name

Provenience

cmbs

Material

Years ago

Age b.p. (years before 1950)(a)

Age range b.p.

UGA08OSL-593

OSL01

Marsh island, by Blackbeard

115.5

quartz

5400 ± 900

5340

6240–4440

UGA08OSL-592

OSL02

Blackbeard Island

134.5

quartz

1300 ± 100

1240

1340–1140

UGA08OSL-594

OSL03

Marsh island, by Sapelo Island

82.0

quartz

2200 ± 300

2140

2440–1840

UGA08OSL-595

OSL04

Sapelo Island, south end

149.5

quartz

56,400 ± 9000

56,340

65,340–47,340

UGA02OSL

SK-03

Mainland

500.0

quartz

62,600 ± 13,000

62,540

75,540–49,540

UGA02OSL

SK-05B

Skidaway Island, south end

117.5

quartz

46,500 ± 9800

46,440

56,240–36,640

UGA02OSL

SK-06B

Skidaway Island, south end

117.5

quartz

45,800 ± 10,200

45,740

55,940–35,540

UGA03OSL

OSL07

Marsh island, near Skidaway

115.0

quartz

1556 ± 220

1496

1716–1276

UGA03OSL

OSL08

Marsh island, near Skidaway

115.0

quartz

925 ± 100

865

965–765

UGA03OSL

OSL09

Marsh island, near Skidaway

85.0

quartz

528 ± 50

468

518–418

UGA03OSL

OSL010

Wassaw Island, western side

115.0

quartz

389 ± 60

329

389–269

UGA03OSL

OSL011

Wassaw Island, south end

115.0

quartz

135 ± 20

75

95–55

(a) To correlate the OSL dates to the calibrated radiocarbon dates, 60 years were subtracted from the reported OSL date.

CHAPTER 8: The Role of Small Islands in Foraging Economies of St. Catherines Island

Matthew F. Napolitano[4]

INTRODUCTION

Although coastal environments were once marginalized in the anthropological literature as unproductive or inhospitable areas for subsistence and settlement (e.g., Osborn, 1977), they are now widely recognized as productive environments that have supported human populations for millennia, if not longer (see Erlandson, 2001; Erlandson and Fitzpatrick, 2006). Ecological diversity is important in understanding why populations thrive in coastal areas. For example, in coastal sections of southeastern North America, there are varieties of subsistence resources ranging from easily collected flora and fauna, such as nut mast and molluscs, to high-calorie, protein-rich wildlife, such as alligator, fishes, and white-tailed deer (e.g., Claassen, 1986; Reitz, 1988, 2008; Reitz, Larsen, and Schoeninger, 2002; Thomas, 2008; Reitz et al., 2010). Coastal waterways also offer efficient means of travel (e.g., Ames, 2002; Wheeler et al., 2003), allowing the use of canoes and other watercraft to increase the quantity of resources an individual can transport at one time and increase the distance covered (Thomas, 2008: chap. 10, 227).

Beyond simply documenting how aboriginal populations relied on coastal habitats, recent archaeological research also emphasizes the role such environments played in migration, population growth, social inequality, and connectivity between groups (see Erlandson, 2001; Rick, Erlandson, and Vellanoweth, 2001; Bailey and Milner, 2002; Mannino and Thomas, 2002; Fitzpatrick, 2004a; Moss, 2004; Erlandson and Fitzpatrick, 2006; Thomas, 2008; Thompson and Turck, 2009, 2010; Thompson and Worth, 2011). Indeed, within anthropological archaeology, coastal and island archaeology has emerged as a distinct subdiscipline. However, the majority of island archaeological research deals with large islands, thus creating a bias against smaller islands (Keegan et al., 2008; Thompson and Turck, 2010). This is problematic because, in many cases, smaller islands support many of the same resources as large islands, making them desirable to humans for occupation or exploitation (Keegan et al., 2008). Further, ethnographic data support the idea that travel between large and small islands was common (e.g., Moss, 2004). To understand the economies of coastal groups better, it is critical to understand the role of small islands within a larger regional context. One area where it is possible to study the role of small islands within a coastal forager economy is the Georgia coast where large barrier islands protect a productive back-barrier island complex of estuaries, tidal channels, and small marsh islands. The back-barrier islands are located close to large barrier islands for which there are subsistence and settlement models. Detailed subsistence and settlement models for barrier islands and coastal areas make the back-barrier island region an excellent study area (Thomas, 2008; Whitley, this vol., chap. 10).

This chapter examines the role of Bull Island Hammock, a small back-barrier island, in the economies of coastal foraging groups. To do this, systematic shovel test pit and shell probe surveys were conducted to evaluate aboriginal activity on the island. The distribution of shell deposits and material culture provides the baseline for assessing aboriginal activity. Data from these surveys are supplemented by four accelerated mass spectrometry (AMS) dates and stable isotope analysis of five archaeological shells. AMS dates were run when temporally diagnostic artifacts were not recovered archaeologically. Stable isotope data provide the season of capture for a shell, which offers a glimpse into the seasonal mobility patterns of aboriginal groups in the absence of other seasonal indicators (e.g., Andrus and Crowe, 2000, 2008; Keene, 2004; Thompson and Andrus, 2011; Andrus, 2012; Cannarozzi, 2012). While the stable isotope sample size is small, the season of capture data create a baseline dataset toward future work assessing how utilization of the hammock might have varied in different seasons.

Data from the Bull Island Hammock surveys are compared to results from similar surveys on the hammocks of Sapelo Island (Thompson and Turck, 2010) to increase our understanding of how small islands collectively play a role in forager economies. Finally, results of the survey are compared to settlement models for St. Catherines Island to show how small islands affect existing models (Thomas, 2008).

The temporal focus of this study is the aboriginal occupation of the coast beginning with the earliest known occupation (approximately 2500 b.c.) and continuing until the Spanish mission period, which began approximately in the 1580s. Dates for a given cultural period fluctuate depending on its location on the coast (i.e., northern Georgia versus southern Georgia; see Thomas, 2008: table 15.3). In order to compare the results of this study to others in the back-barrier island region, the cultural dates used by Victor Thompson and John Turck (2010) are used here; however the reader is referred to DePratter (1979: table 30, 1991: table 1) and Thomas (2008: table 15.3) for broader discussions with more regionally specific chronologies based on ceramic assemblages and radiocarbon inventories. Cultural periods are as follows: Late Archaic (locally known as St. Simons; 2500–1100 cal b.c.), Early Woodland (locally known as Refuge; 1100–400 cal b.c.), Middle Woodland (locally known as Deptford; 400 cal b.c.–a.d. 500), Late Woodland (locally known as Wilmington; cal a.d. 500–1000), Early Mississippian (locally known as Savannah or St. Catherines; cal a.d. 1000–1325), Late Mississippian (locally known as Irene; cal a.d. 1325–1580 radiocarbon years b.p.), and change to Spanish mission period (locally known as Altamaha; 1580–1700 radiocarbon years b.p.).

ARCHAEOLOGY OF BACK-BARRIER ISLANDS AND ST. CATHERINES ISLAND

Chester DePratter and James Howard conducted the first archaeological investigation of the back-barrier island region in the late 1970s and early 1980s. They identified hundreds of sites on large and small barrier and back-barrier islands with nonsystematic shoreline surveys. The sizes of sites vary and ages of the sites range from the Late Archaic to Spanish mission and colonial periods. While many of these sites were never systematically tested or excavated, DePratter and Howard’s work is important in establishing a baseline for evaluating aboriginal use of the Georgia coast (DePratter and Howard, 1977, 1980, 1981; see also DePratter, Paulk, and Thomas, 2008).

The back-barrier island region is receiving attention from archaeologists for the first time since DePratter and Howard’s surveys. Thompson and Turck (2010) conducted systematic shovel test pit surveys on four small islands between Sapelo Island and the mainland coast. They reason that small islands played a role in aboriginal economies and are important for understanding issues relating to subsistence, settlement/mobility, the development of social inequality, and other socioeconomic factors that up to this point have been largely overlooked (Thompson and Turck, 2010: 283–284). To test this, they conducted a shovel test pit survey across each hammock. From this, they analyzed aboriginal activity on the back-barrier island region and discussed the implications for coastal archaeology.

Their surveys revealed a range of aboriginal activity on each hammock (Thompson and Turck, 2010: 289–294). The degree of intensity to which aboriginal groups utilized hammocks varies. The authors found evidence of intensification on the hammocks over time, peaking in the Late Mississippian period. However, the specific distribution of material culture for each period was far from uniform. For example, there was minimal, if any, activity during the Late Archaic on Mary Hammock, but a significant Late Archaic presence on Little Sapelo Island and Patterson Island. It should be noted that hammock erosion plays a role in trying to understand aboriginal utilization of the back-barrier island region. The abundance of Late Archaic sherds (N = 42) collected during a shoreline survey of Pumpkin Hammock suggests that a section of the hammock that had a considerable Late Archaic component has eroded away (Thompson and Turck, 2010: 293). These results show that the history of occupation and utilization on the hammocks is extensive and the back-barrier region as a whole warrants more intensive survey.

The work of David Hurst Thomas (2008) on St. Catherines Island is certainly the most extensive survey to date and a number of his conclusions are significant for the current study. Thomas (2008: preface, 7) asks four “deceptively simple” questions to guide the long-term research on St. Catherines Island: (1) how and why did the human landscape (settlement patterns and land use) change through time? (2) to what extent were subsistence and settlement patterns shaped by human population increase, intensification, and competition for resources? (3) what factors can account for the emergence of social inequality in Georgia’s Sea Islands? and (4) can systematically collected archaeological evidence resolve the conflicting ethnohistorical interpretations of the aboriginal Georgia coast (the so-called Guale problem)?

To investigate these questions, Thomas employs human behavioral ecology to theoretically frame his research. Specifically, he uses central place theory, diet breadth, and patch choice modeling to predict how and where sites should be distributed around St. Catherines Island for each cultural period and then tested the models with a systematic transect survey of 20% of the island.

Thomas concludes that the majority of the aboriginal sites conform to the projections of central place theory, which is that foragers set up their residential bases to have the most access, quantity, and widest variety of resources within an effective foraging radius (Thomas, 2008: 211–233, 871, 929–931). With an effective foraging radius of approximately 10 km (Thomas, 2008: 1064; see Kelly, 1995), most optimal central places are on the east and west sides of the island where the edges of the maritime forest are adjacent to the saltwater marsh and tidal streams (Thomas, 2008: 859). From the various central places on St. Catherines Island, a forager could reach any collection spot on the island—the salt marsh, the St. Catherines and Sapelo sounds, or the Atlantic Ocean—and return home the same day (Thomas, 2008: 1064). A key factor to understanding what this means in terms of aboriginal subsistence strategies is that the location of central places changed over time as the geomorphology of St. Catherines Island changed (Thomas, 2008: chap. 29).

Not all sites identified in the transect survey conform to the central place theory projections. Sites were found along the Pleistocene core on the center of the island, away from marsh-side settlements areas. But recent work on the hydrology of St. Catherines Island shows that heavy well drilling for pulp production in Savannah significantly lowered the water table in the Georgia Bight in the 19th and early 20th centuries by approximately 3 m. Considering this, the center of St. Catherines Island was a lacustrine habitat, filled with freshwater ponds and meadows (Hayes and Thomas, 2008: 56–58). In terms of productivity, lacustrine habitats are on par with estuarine habitats. As confirmed by updated hydrological models, the sites found along the center of the island actually prove not to be outliers, but conform to the central place theory. Thomas presents lacustrine sites along the center of the island as outliers because they were not originally predicted in the initial central place theory modeling (Thomas, 2008: 893, 904, 915, 922, 929).

IMPLICATIONS FOR BACK-BARRIER ISLAND RESEARCH

Thomas’s work constitutes a significant contribution to the literature and provides a theoretical and empirical framework to test his research in other coastal areas in Georgia. By returning to two of the four “deceptively simple questions” that frame Thomas’s research, it is possible to demonstrate why an understanding of the aboriginal activity on nearby hammocks is so important.

The first question addresses how and why human land use changed over time. This question can only be adequately addressed by first looking at long-term environmental factors (e.g., seasonal wetness, sea level rise, etc.) and how that impacts island geomorphology and ecology. Using a suite of hydrological, geological, and archaeological data, Thomas reconstructed the changing shape of the island (see DePratter, Paulk, and Thomas, 2008; Thomas, 2008: chaps. 3–5, 16; Thomas, Rollins, and DePratter, 2008; Bishop, Rollins, and Thomas, 2011). These data were then used to interpret the distribution of sites across the island (Thomas, 2008).

While no geomorphologic reconstruction has taken place in the study area (but see Turck and Alexander, this volume, chap. 7, for hammock geological formation processes), the distribution of temporally diagnostic material culture speaks to how Bull Island Hammock might have changed over time. The change in land use evidenced by the distribution of material culture can be tested against the data from St. Catherines Island.

The second question, which addresses population increase, intensification, and competition for resources on St. Catherines Island, is a key question in contextualizing aboriginal use of the back-barrier island region. If populations increase on St. Catherines Island, resulting in increased competition for resources, then there should be a quantifiable increase in aboriginal activity on back-barrier islands.

THE BACK-BARRIER ISLANDS OF ST. CATHERINES ISLAND

There are three types of back-barrier islands in the Georgia Bight. The first type is Pleistocene in age and is a remnant of the former Pleistocene shoreline when sea levels were lower and composed of a mix of Pleistocene and Holocene components. DePratter and Howard (1981) argue that back-barrier islands are former barrier islands of a continuous beach ridge that are partially submerged or eroded. In this scenario, Holocene sediments are deposited on top of Pleistocene remnants. Oertel (1979: 279) argues that hammocks are discrete landforms that accrete individually. According to this model, hammocks form from coarse-grained sediments accreting together to form “marsh-encircled islands” and can be much younger in age than nearby barrier islands with Pleistocene components (Oertel, 1979: 276). A third is from modern dredge spoils and from shipping ballast (Emery et al., 1968; Thompson and Turck, 2010: 284).

Bull Island Hammock

There are two back-barrier islands to the west of St. Catherines Island: Moss Island and Bull Island. Moss Island has two hammocks on it and Bull Island has three. Bull Island Hammock is approximately 8 ha, making it the largest of the St. Catherines Island hammocks (fig. 8.1). Bull Island Hammock is small when compared to other hammocks in the surrounding area (see Thompson and Turck, 2010). Bull Island Hammock is located approximately 1.5 km to the west of Persimmon Point (formerly English Cut, the westernmost point on the island) near the site of Mission Santa Catalina de Guale (9Li274).

Following the “patch types” defined by Thomas (2008: 250–256), Bull Island Hammock is a maritime forest (mixed deciduous-pine forest) surrounded by salt marsh. The hammock was utilized for cotton farming during the 19th century and remnants of cotton rows, a drainage ditch, and a dyke are still present. The combination of a lightning fire within the past decade and no permanent deer population make the understory incredibly dense.

The soil type on Bull Island Hammock is an Echaw-Centenary blend (Looper, 1982). This blend contains some Mandarin-Rutledge soils in small amounts. Echaw-Centenary soils drain better when there is less Mandarin-Rutledge soil present. This soil blend is similar to the periphery of the Pleistocene core of St. Catherines Island (Reitz et al., 2008: 53–55). The soil in the tidal marsh area around the hammock is Bohicket-Capers (Looper, 1982). On St. Catherines Island, Bohicket-Capers is found in between the Holocene beach ridges.

At present, it is unknown whether the hammock had a source of water on it. Whether or not the hammock supported water in the past is a critical factor for predicting and understanding aboriginal activity. There is a topographically low area just to the west of the center of the hammock (fig. 8.2). A historic-period drainage ditch runs north to the marsh from this area. Given that the water table in the Georgia Bight was significantly higher, it is possible that the hammock supported fresh water seasonally or year-round. Like the lacustrine habitat in the central depression of St. Catherines Island, a freshwater resource would have provided a collection site for flora, fauna, and provided a source of potable water. If fresh water was not available, activity would be limited by the amount of time one could spend on the hammock.

Fieldwork and Laboratory Protocols

Shovel test pits were set at 20 m intervals with each shovel test pit labeled according to its coordinate location (fig. 8.3). Shovel test pits in topographically low areas (i.e., wetter areas along the marsh edges or in areas with standing water) were omitted. Each shovel test pit was 50 cm in diameter. Soil was excavated in 20 cm arbitrary levels. Soil was dry screened through 1⁄8 in. mesh. This screen size was chosen in an attempt to recover a variety of fauna, including small fishes. When shell was encountered, it was weighed from each level, mixed with the backdirt, and then put back in the test pit.

To map the distribution of shell, a probe survey was conducted at 5 m intervals. A crew of four, spaced 5 m apart from each other, walked in north-south transects with steel probes, probing the ground every fifth meter.

Four judgmental test pits were excavated off the 20 m grid in areas of interest. The location of each was chosen based on the results of the shovel test pit survey to further investigate possible aboriginal activity areas. Each test pit was 50 × 50 cm and excavated in 10 cm arbitrary levels.

During fieldwork, two aberrant areas north of Bull Island Hammock were investigated because they had higher elevations compared to the surrounding flat, tidal marsh. Each area looks like a small mound. The first area (Area 1) is located approximately 100 m north of the northeastern tip of Bull Island Hammock. The second area (Area 2) is approximately 250 m north of the hammock. Informal probing around both areas revealed a buried tree stump and/or root system at the edge of each area.

Ceramics were analyzed with the assistance of Chester DePratter of the South Carolina Institute of Archaeology and Anthropology, according to the standard typologies for the Georgia coast (see DePratter, 1979, 1991; Williams and Thompson, 1999; Guerrero and Thomas, 2008).

In order to understand the temporal range of aboriginal activity on the hammock, four samples were collected for AMS dating. Three samples were clam shells taken from large midden deposits with no temporally diagnostic artifacts (i.e., ceramics). The fourth sample sent for AMS dating was from the buried tree stump north of the hammock. A stump preserved in the marsh is significant because an AMS date from the tree stump will shed light on sea level rise around the hammock. The date indicates a point in time when there was enough fresh water for the tree to survive before the area was inundated by saltwater.

Dates from the clam shells were corrected using the reservoir correction developed for St. Catherines Island (Thomas, 2008; Thomas, Sanger, and Hayes, this volume, chap. 1). Reservoir corrections (ΔR) are commonly used to calibrate the age of marine shell dates. Marine shell dates need to be corrected because they will always date “older” than terrestrial samples (e.g., charcoal) of the same age (Thomas, 2008: 346). The St. Catherines Island reservoir correction was calculated using modern oysters of a known age and archaeological samples. When calculated, ΔR = –134 ± 26 (Thomas, 2008: 357–358). In this volume (chap. 1), Thomas, Sanger, and Hayes modified the reservoir correction with more samples from known-age oysters from mainland coastal Georgia. The updated reservoir correction is ΔR = –119 ± 16. The difference between these two corrections is statistically negligible so the first correction is used in this study.

In an attempt to understand how subsistence strategies vary according to season, oyster and clam shell samples were processed for stable isotope analysis. Shells were collected from Late Mississippian Period middens. Late Mississippian Period middens were sampled because the season of capture results from these shells could be contextualized with the existing models for Guale subsistence (Jones, 1978; Crook, 1986; Keene, 2004; Thomas, 2008).

Five shells were processed at the Department of Geological Sciences at the University of Alabama, Tuscaloosa by C. Fred T. Andrus. Twelve samples were collected from each shell using a microdrill, beginning with the terminal growth band of the clam or oyster and then moving further back to the older part of the shell. The goal was to collect samples that represented one year of growth for the shell. From this, the ratio of 16O to 18O (expressed as β18O) is determined. This is then correlated to salinity and water temperature during the life of the shell. Water temperature during the mollusc’s season of capture indicates which season the shell was collected in (Andrus and Crowe, 2000, 2008; Thompson and Andrus, 2011; Andrus, 2012). While the sample size is too small to evaluate seasonal mobility patterns, it serves as a first step to understand how the hammock was utilized in different seasons.

RESULTS AND ANALYSIS

The shovel test pit and shell probe surveys revealed the presence of aboriginal activity on Bull Island Hammock in each of the cultural periods found on the larger Georgia barrier islands. Positive shovel test pits had cultural material, shell, or both cultural material and shell. In total, more than 100 ceramics and a small amount of historic brick were recovered. The shell probe survey revealed 29 discrete shell deposits, ranging from isolated shell scatters to large, dense midden deposits indicating that processing of shellfish and faunal took place in varying degrees over time. Activity on the hammock appears to be minimal during the Late Archaic (only two sherds recovered) and Early Woodland (only one sherd recovered) periods. Utilization of the hammock increased during the Late Woodland and Mississippian periods before rapidly declining just after Spanish contact. The distribution of shell and cultural material across the hammock shows that shellfish processing was limited to specific areas on the hammock, suggesting a possible freshwater resource or different activity areas on the hammock.

Shovel Test Pit Survey: A total of 167 shovel test pits were excavated on Bull Island Hammock (table 8.1). The majority of the shovel test pits
(N = 107) were negative for evidence of aboriginal activity. Sixteen percent (N = 26) of the shovel test pits were positive for shell, but lacked cultural material, 10% (N = 16) of the shovel test pits were positive for cultural material, but lacked shell, and 11% (N = 18) were positive for both shell and cultural material. In positive shovel test pits lacking shell, cultural material was recovered between the surface and 40 cm. No cultural material was recovered from subsoil. Additionally, with the exception of one judgmental shovel test pit (see below), no artifacts were recovered from below the water table.

Cultural material and shell were concentrated in similar areas (fig. 8.4). Therefore, while some shovel test pits with shell contained no cultural material, ceramics were often recovered from adjacent shovel test pits. This does not suggest that cultural material is related to nearby shell deposits, however. When ceramics were recovered from shell middens, they often dated to a different cultural period than ceramics from adjacent test pits. It does suggest that the same areas of the hammock were repeatedly utilized by aboriginal groups.

Most shell deposits in shovel test pits were visible on the surface or began just below the surface. Shell middens that began on or near the surface generally terminated at approximately 40 cm below surface. The deepest middens encountered during the shovel test pit survey did not appear until approximately 20 cm below the surface and terminated at a depth of 50–80 cm below surface. Thickness of shell deposits (excluding shell scatters) ranged from 9 to 65 cm with an average of 34 cm. Like the distribution of cultural material, shell deposits are mostly found in the central and southern parts of the hammock (fig. 8.4).

Judgmental Test Pits: Three of the four judgmental test pits yielded little additional information. Test pit D was placed in the topographically low area near the center of the hammock. When fieldwork began, this area had standing water in it and the gridded shovel test pit was omitted from the survey. By the end of fieldwork, there was no longer standing water on the hammock. Probing in the topographically low area revealed a submerged shell deposit approximately 30–40 cm below surface.

Excavation hit the water table at approximately 20 cm below surface, which complicated digging. At 30–40 cm below surface, excavation revealed a midden composed of dense, crushed shell including oyster, clam, and ribbed mussel. Late Mississippian ceramics and fauna were mixed in with the shell. A wood fragment was recovered from the 40–50 cm level. The shell ended at approximately 70 cm below surface. It is thickest in the northeastern part of the test pit and thinnest in the southwestern part. In the east and south profiles, the shell deposit slumps with its lowest part in the southeastern corner.

Ceramic Analysis: A total of 104 aboriginal sherds were recovered in the survey, which spanned the entire known occupation along the Georgia coast (table 8.2). Over time, there is a general increase in the number of sherds per cultural period, peaking during the Late Mississippian and then decreasing precipitously during the Spanish mission (Altamaha) period. Late Mississippian ceramics account for 57% of the total ceramic count and 61% of the total weight (fig. 8.5A–B).

Ceramic density across the hammock varied little because, with the exception of one shovel test pit, no more than 10 sherds were recovered within a single test pit. Using ceramics as a proxy for aboriginal activity, more of the hammock was found to be utilized in later periods (fig. 8.6A–D). Many of the shovel test pits containing cultural material had more than one temporal period represented. Activity areas appear to be reused in multiple periods as well. Similar to the distribution of shell (see below), ceramics cluster around the topographically low part of the hammock, which may indicate a singular activity area utilized over multiple cultural periods.

Faunal Analysis: Faunal remains were recovered from three areas. Fauna came from middens dating to the Late Woodland or Late Mississippian periods (table 8.3). The majority of the faunal remains were freshwater or brackish turtles (table 8.4). Four different species of turtle were identified, although most were only identifiable at the taxon level. Most of the turtle fragments were plastron or carapace, which are the primary cuts when butchering turtles. Catfish and indeterminate mammal were recovered in small amounts.

Shell Probe Survey: The shell probe survey revealed 29 discrete shell deposits of varying sizes and densities (fig. 8.7). They range from light subsurface shell scatters to large sheet middens. The shell probe survey identified deposits not found in the shovel test pit survey.

The largest shell middens are in the south central part of the hammock. The densest middens are in the south central and southeastern part of the hammock. Shell deposits are also found on the far western and southeastern areas of the island, but are considerably less dense than other middens.

Two large areas of the hammock did not have any shell (or cultural material) at all. The first area is the topographically low area of the hammock. It is possible that this part of the island supported fresh or brackish water. The distribution of shell suggests that aboriginal activity (i.e., processing of shellfish) took place around this possible freshwater resource. The second area with no shell is the east side of the island. When shell deposits are present, they are restricted to the southern part of the island. Probing and shovel testing indicate that these middens are from 31 to 40 cm thick, which is average for Bull Island Hammock. It is possible that aboriginal activity took place in this area of the hammock but did not leave an archaeological signature. It is unlikely that farming during the 19th century obliterated all evidence of aboriginal activity in those areas because the entire island was utilized for farming and the cotton rows are present across the entire hammock. Unlike the topographically low area of the island, it is not plausible that the east part (a topographically higher part) of the island supported fresh water.

AMS Dates: Four samples were sent to Beta Analytic Laboratories for accelerated mass spectrometer (AMS) dating. Three of the samples were clam shells from aceramic middens and one was a wood sample from the buried tree stump in the marsh north of the hammock (see table 8.5). One of the sampled middens is on the far southeastern side of the hammock (N9260 E1140). The shell was sampled from the base of the midden, which was toward the bottom of the 40–60 cm level. The shell dates to cal a.d. 1050–1270, which puts it in the Early Mississippian (or St. Catherines) period. One clam shell from N9180 E1240 and another from N9220 E1180 returned nearly identical dates, at cal a.d. 680–890 and cal a.d. 660–870, respectively. These date to the Late Woodland (or Wilmington) Period.

The tree stump sample dated to 300 cal b.c.–cal a.d. 10, which is the Early Woodland (or Deptford) Period. While this sample is “noncultural” and does not directly indicate aboriginal activity on the hammock, it does provide a departure point for considering sea level rise around Bull Island and can be incorporated with the noncultural radiocarbon database for St. Catherines Island (see Bishop, Rollins, and Thomas, 2011: 379–381). The noncultural radiocarbon database facilitates the interpretation of archaeological site patterning and geomorphology on St. Catherines Island (Thomas, 2008: chaps. 32–35) and the date from Bull Island Hammock could eventually be used to test the geomorphological models for St. Catherines Island.

Stable Isotope Analysis: Three clam and two oyster shells were analyzed for stable isotope ratio in order to determine their season of capture (table 8.6). Shells were selected from two middens containing only Late Mississippian pottery. The five samples revealed a four-season presence on the hammock, with four seasons represented in one midden. More analysis and greater sample size are necessary before contextualizing these results into a broad activity model. It is worth noting, at the very least, that collections in summer and fall months have been reported in other stable isotope studies on St. Catherines Island and nearby islands (e.g., Andrus and Crowe, 2008; Thompson and Andrus, 2011; Cannarozzi, 2012.)

DISCUSSION

The Sapelo Island Surveys

Since the methods used in this survey are comparable with those used on the Sapelo Island hammocks, it is possible to compare the results of the Bull Island Hammock surveys to the others. Positive shovel test pits in the Sapelo Island hammock surveys yielded shell, pottery, or a combination of shell and pottery. The quality of aboriginal activity on Bull Island Hammock appears most similar to Pumpkin Hammock, the smallest of the four Sapelo hammocks that were surveyed. Bull Island Hammock is approximately 8 ha and Pumpkin Hammock is 3 ha. In terms of material culture, a total of 63 sherds were recovered on Pumpkin Hammock compared to the 104 on Bull Island Hammock and both assemblages indicate the same long-term utilization. Pumpkin Hammock is the only one of the four hammocks where the majority of the shovel test pits were negative. A total of 53% of the test pits on Pumpkin Hammock were negative while 64% of the shovel test pits on Bull Island Hammock were negative. Recent stable isotope analysis on shell samples from Pumpkin Hammock indicate that groups were active (i.e., processing shellfish) in all seasons, suggesting that groups lived on the hammock (Victor Thompson, personal commun., 2011). However, a caveat to season of capture studies is that presence during four seasons does not necessarily mean continued year-round use or that groups were settled on the hammocks.

The next hammock closest in size is Mary Hammock at 10 ha. The aboriginal activity on Mary Hammock is very different from that on Bull Island Hammock. Nearly three times as many ceramics were recovered (N = 269). The shell deposits are much larger and denser (Thompson and Turck, 2010: table 1, figs. 5–7). Mary Hammock also contained the most positive number of shovel test pits (68%), almost double the percentage on Bull Island Hammock (36%).

As the islands get larger, aboriginal activity becomes less similar to the activity on Bull Island Hammock. Patterson Island is 18 ha and the material cultural assemblage and shell distribution are remarkably different. Four times as many ceramics were recovered (N = 469) and 40% of shovel test pits were negative. In other words, it not only appears that the island was being utilized more intensively, but that more of the island was utilized. Finally, at 47 ha, Little Sapelo Island is by far the largest small island surveyed. A total of 841 ceramics were recovered, which dwarfs the Bull Island Hammock assemblage. Only 35% of the Little Sapelo Island shovel test pits were negative, indicating that larger sections of the island were being utilized.

The most significant similarity shared by Bull Island Hammock and the Sapelo Island hammocks is the dramatic increase in activity during the Early and Late Mississippian periods (see Thompson and Turck, 2010: fig. 7, table 2). The work on St. Catherines Island tells us that there was a large-scale population increase during this time (Thomas, 2008: chap. 35). With the exception of Pumpkin Hammock, activity on each of the hammocks appears to decrease precipitously during the Spanish mission period. The majority of sherds recovered from Pumpkin Hammock were Altamaha (N = 16) and accounted for one-third of the percentage by weight (33%) of sherds recovered (Thompson and Turck, 2010: table 2).

Each island surveyed had shovel test pits containing shell without pottery and pottery without shell. This underscores the importance of systematic survey on small islands because simply using shell to identify or delineate sites would miss a substantial segment of aboriginal activity (Thompson and Turck, 2010: 289).

The St. Catherines Island Dataset

There were multiple changes in aboriginal land use over time on St. Catherines Island that were partly caused by the shifting geomorphology of the island and estuarine habitat on the east side of the island. For example, during the Wilmington Period, sites shifted further south on the island as rising sea levels eroded Guale Island and changed the location of Guale Marsh. However, on the west side of the island, geomorphology changed little after the sea level regressed in the Early Woodland and then rose (Thomas, Rollins, and DePratter, 2008: 844; Thomas, 2011a). During this period, sites are found along the western margin of St. Catherines Island. This pattern continues for Woodland and Mississippian sites, the only difference being that site size and the quantity of sites increased (Thomas, 2008: chap. 32). Therefore, the west side of the island can be considered a central place for every cultural period except the Early Woodland (Refuge) Period. It appears that as long as sites were occupied along the western margin of St. Catherines Island, foragers were utilizing Bull Island Hammock. The effective foraging radius models that Thomas built for populations on St. Catherines Island posit that a forager can travel 10 km a day or 30 km by canoe and still return to the residential base (Thomas, 2008: 228, 1064; see also Ames, 2002: 47; Kelly, 1995: 135). The hammock also fits within the range of the effective foraging radius given the large distances one can travel using canoes and taking advantage of the twice daily tides. However, a freshwater source would create the possibility of the hammock serving as a temporary processing camp or residential site where foragers could stay longer.

To summarize, despite the changing distribution of sites across St. Catherines Island, sites were consistently found on the marsh edge of the western side of the island since the Early Woodland. As the number and size of sites increased throughout the Middle-Late Woodland and Mississippian on St. Catherines Island, so did intensification of activity on the hammock. Except for the scale of utilization, activity changed little over the course of millennia on Bull Island Hammock as the dominant activity area was centered around the topographically low part of the hammock. While there is no evidence for any kind of habitation on the hammock, it did serve as a collection and processing site for thousands of years.

The fact that utilization of Bull Island Hammock appears to have intensified throughout the Woodland and Mississippian periods underscores its importance in forager economies, specifically during the Late Mississippian. The importance of the hammock in forager economies is seen during the Late Mississippian period, when the population on St. Catherines Island increased exponentially (Thomas, 2008: 1050–1052). This is when Bull Island Hammock was utilized most extensively. This pattern is corroborated by the research off Sapelo Island (Thompson and Turck, 2010).

A consequence of population growth is increased taxation on subsistence resources. As Thomas (2008: 1060) argues, an increased population likely resulted in an increased consumption of shellfish, which may have depleted some shellfish beds on the island. While it is possible that shellfish beds were “managed” (i.e., older oysters were collected to prevent overharvesting, see Thomas, 2008: 1059–1060), groups could have relied on the shellfish beds in the marsh area around Bull Island Hammock to supplement the growing need for food without depleting the resources on St. Catherines Island. Shellfish beds might also have been “managed” for nonanthropological reasons. For example, times of unseasonal dryness, major storm activity, season of the year, and water temperature all impact shellfish availability (e.g., Rollins, Prezant, and Toll, 2008; Prezant, Rollins, and Toll, 2011; Rollins and Thomas, 2011: 322–337).

The Importance of Small Islands

Bull Island Hammock was utilized for more than four millennia. The presence of Late Archaic pottery indicates that at least a portion of Bull Island formed around the same time that Holocene beach ridges prograded to the north and south of the Pleistocene core of St. Catherines Island. Culturally, this is approximately when the shell rings on the east and west side of the island were in use.

When local sea level dropped around the Late Archaic–Early Woodland transition, it is believed that depleted estuarine resources led in part to a large-scale shift in settlement on St. Catherines Island. At present, it is unclear whether groups switched to more terrestrial-based foraging or depopulated the island and moved west to follow migrating estuarine resources (Thomas, 2008; see also Thompson and Turck, 2009). On Bull Island Hammock, there is a slight increase in Early and Middle Woodland ceramics, so it is unclear what role Bull Island Hammock played in this socioeconomic shift. However, the Early and Middle Woodland ceramics from Bull Island were not associated with any substantial middens. The lack of middens and artifacts dating to the Early and Middle Woodland periods mirrors what is seen during the Refuge/Deptford period on St. Catherines Island, albeit on a much smaller scale.

Aboriginal activity on Bull Island Hammock shifted during the Late Woodland Period. The presence of ceramics in the midden and two AMS dates from aceramic middens indicate that there is an increase in the amount of shellfish being processed. On St. Catherines Island, both marsh habitats on the east and west sides of the island were productive, yet groups consumed more fishes during the Late Woodland (Reitz, 2008). There is also a decrease in turtle remains from this period (Thomas, 2008: 1020). Interestingly, on Bull Island Hammock, one of the Late Woodland Period middens yielded the vast majority of fauna recovered from the hammock, almost all of which was turtle. There is also an increase in the number of ceramics recovered from the hammock during the Late Woodland.

The quantity of ceramics decreased on Bull Island Hammock during the Early Mississippian Period (which includes sherds from both Savannah and St. Catherines periods). One AMS date from an aceramic midden on the extreme southeastern edge of Bull Island Hammock is from the Early Mississippian period. On St. Catherines Island, data on seasonal rainfall indicate that there was a severe drought from approximately cal a.d. 1200–1300. The drought is believed to have caused, in part, a shift in subsistence strategies for St. Catherines Island populations, which resulted in fewer shell midden deposits (Blanton and Thomas, 2008: 801–802). It is not possible at this point to say if there was any correlating activity on Bull Island, however, the decrease in number of ceramics does indicate a change in utilization of the hammock. Thompson and Turck (2010: fig. 7) do not report a similar change on the Sapelo Island hammocks; therefore this pattern may be unique to the vicinity around St. Catherines Island.

The dramatic increase in Late Mississippian sherds on the hammock mirrors demographic changes occurring on St. Catherines Island. An exponential population increase led to heightened competition for resources, which in turn led to increased utilization of the hammock. A sharp rise in activity during the Late Mississippian periods has also been observed on the hammocks off Sapelo Island (Thompson and Turck, 2010).

During the period of Spanish occupation on St. Catherines Island, it appears that the hammock was used very little, if at all. This is not surprising given that populations at this point were engaged in large-scale intensive maize agriculture and lived within the immediate vicinity of Mission Santa Catalina de Guale (Thomas, 2008: 205–207; see also Bushnell, 1994; Milanich, 1999).

Importantly, one cannot assume that the groups that utilized Bull Island Hammock were residents of St. Catherines Island. It is likely that the hammocks were utilized by many different groups that may have lived on the mainland coast or other barrier islands. If freshwater outlets did exist on the hammock then people possibly stayed temporarily on the hammock. If one assumes an effective foraging radius on an individual or small group traveling by canoe to be 30 km (Ames, 2002; Thomas, 2008: 227), then Bull Island Hammock is within the effective foraging radius for a significant portion of the coastal area. However, since Bull Island Hammock is less than 2 km away from St. Catherines Island, it is appropriate to contextualize the Bull Island Hammock dataset to the St. Catherines Island dataset.

The aboriginal activity on Bull Island Hammock makes it clear that small islands played a role in the subsistence and settlement patterns of groups that occupied St. Catherines Island and other nearby coastal areas. Although it appears that this island did not play a significant role in aboriginal economy prior to the Late Woodland, this hammock was utilized more in the Mississippian period. In other words, while the pottery recovered is evidence for more than 4000 years of utilization, the hammock was probably used intermittently in each cultural period.

The results of this study corroborate other similar studies (Keegan et al., 2008; Thompson and Turck, 2010): small islands often played a role in the economies of groups that inhabited larger islands and in coastal zones. At present, small islands are not studied as commonly as large islands; however this study demonstrates that until archaeologists examine small islands with the same focus given to large islands, subsistence and settlement models remain incomplete.

This study creates a number of avenues for further research. In order to fully understand the nature of aboriginal activity on Bull Island Hammock and how it changed over time, in-depth geological and hydrological investigation is necessary. Expanding the work of Turck and Alexander (chap. 7) by vibracoring and dating the basal deposits from Bull Island will help elucidate the formation and age of the hammock. This will contribute to a better understanding of why the east half of Bull Island Hammock was not utilized the way the rest of the hammock was (i.e., for shellfish and vertebrate processing). Second, building hydrological models for the hammock will answer the question of whether there was the possibility of a freshwater outlet and a detailed soil analysis will also contribute to determining whether there was such an outlet on the hammock at any point. Also, analyzing the exact soil type ratio might determine whether different parts of the island drained better than other parts.

Shellfish samples collected from the middens can be used for multiple studies. Both oysters and clams can be studied for stable isotope analysis, which can be used to interpret the season of the year when groups were using the hammock. Sclerochronological analysis of clam samples can also be used for season of capture studies. Following Crook (1992), oysters from the hammock can be analyzed to determine their habitat. This is potentially important for determining the type of estuarine habitat around the hammock. If oyster bed growth (i.e., clusters, banks, or reefs) is significantly different in later periods, this may shed light on why utilization of the hammock was less intensive prior to the Late Woodland. This could also be affected by how the distribution of estuarine habitats changed over time following the movement of streambeds and river channels (Chowns, 2011). Hydrological, geological, and shellfish studies on and around Bull Island Hammock can be used to test such theories.

As the hammock appears to only be utilized periodically, exactly when groups were foraging and hunting on the hammock may prove interesting and may be a future research direction. More AMS dating and season of capture studies may provide a link between times of stress on the island and increased mobility (e.g., during the mid-16th century when Jesuit priests observed Irene populations engaged in a high degree of mobility caused by prolonged drought; Zubillaga, 1946).

Finally, island size appears to correlate in some way to aboriginal activity. The results of this study, when combined with the results from Thompson and Turck (2010), appear to show that aboriginal activity intensifies as island size increases. Further, the recent work on two hammocks smaller than Bull Island revealed almost no evidence for aboriginal activity (Sanger, chap. 9). It is possible to test in the future by comparing island size with the rate of positive and negative shovel test pits with shell and ceramic density.

Figure 8.1. St. Catherines Island and its associated islands, showing back-barrier islands and hammocks.

Figure 8.2. LiDAR image of Bull Island Hammock with white representing higher elevation.

Figure 8.3. The shovel test pit grid.

Figure 8.4. Results of the shovel test pit survey on Bull Island Hammock. Red indicates shovel test pits positive for cultural material; yellow, shell and cultural material; green, shell; and white, no shell or cultural material.

Figure 8.5. (A) Percentage of total sherd weight. (B) Percentage of total sherd count.

Figure 8.6. Distribution of sherds across various time periods. (A) Late Archaic; (B) Early Woodland and Early/Middle Woodland; (C) Late Woodland/Early Mississippian, Early Mississippian, and Early/Late Mississippian; (D) Late Mississippian, Late Mississippian/Historic, and Spanish mission period.

Figure 8.7. Results of the shell probe survey on Bull Island Hammock.

TABLE 8.1. Results of the Shovel Test Pit (STP) Survey on Bull Island Hammock

STP Content

STP (no.)

STP (%)

Pottery and shell

18

11

Pottery only

16

10

Shell only

26

15

Sterile

107

64

Total

167

100

TABLE 8.2. Aboriginal Ceramic Sherd Counts and Weights

Cultural period abbreviations: LA (Late Archaic), EW (Early Woodland), MW (Middle Woodland), LW (Late Woodland), EM (Early Mississippian), LM (Late Mississippian),

SM (Spanish Mission), UKN (Unknown).

Period

Sherds (no.)

Total (%)

Weight (g)

Total weight (%)

LA

2

1.92

10.0

1.52

EW

1

0.96

4.5

0.68

EW/MW

7

6.73

21.5

3.27

MW

1

0.96

2.3

0.35

LW

4

3.85

101.4

15.43

LW/EM

5

4.81

49.9

7.59

EM

5

4.81

16.9

2.57

EM/LM

9

8.65

6.3

0.95

LM

60

57.69

395.3

60.17

LM/HC

6

5.77

21

3.19

SM

3

2.88

27.7

4.21

UKN

1

0.96

0.5

0.07

Total

104

100.00

657.3

100.00

TABLE 8.3

Faunal Remains from Bull Island Hammock

Abbreviations: MNI = minimum number of individuals; NISP = number

of individual specimens present.

Taxon

Common name

NISP

MNI

Weight (g)

Ariidae

Sea catfishes

1

0.292

Ariopsis felis

Hardhead catfish

2

1

0.88

Testudines

Indeterminate turtles

44

51.979

Emydidae

Pond turtles

6

8.348

Deirochelys reticularia

Chicken turtles

2

1

6.341

Malaclemys terrapin

Diamondback terrapin

7

2

14.905

Terrapene Carolina

Box turtle

1

1

0.762

Mammalia

Indeterminate mammals

4

1

5.339

Total

67

6

88.846

TABLE 8.4. Faunal Remains by Test Pit and Number of Individual Specimens Present (NISP)

Unit

Level

(cm below surface)

Taxon

Common name

NSIP

N9180 E1240

20–40

Ariidae

Sea catfish

1

Ariopsis felis

Hardhead catfish

1

Deirochelys reticularia

Chicken turtle

2

Malaclemys terrapin

Diamondback terrapin

4

Mammalia

Indeterminate mammal

2

Testudines

Indeterminate turtle

37

40–60

Mammalia

Indeterminate mammal

1

N9302 E1280

20–40

Testudines

Indeterminate turtle

2

ST D

30–40

Ariopsis felis

Hardhead catfish

1

Emydidae

Pond turtle

4

Terrapene carolina

Box turtle

1

Testudines

Indeterminate turtle

5

50–60

Emydidae

Pond turtle

2

Malaclemys terrapin

Diamondback terrapin

3

TABLE 8.5. Accelerator Mass Spectrometry (AMS) Dates from Bull Island Hammock

Lab ID

Location

Sample type

Raw 14C year (b.p.)

13C/12C ratio

Conventional radiocarbon age (b.p.)

Radiocarbon age calibrated (±2σ)

Beta-281062

North of Bull Island

Wood

2250 ± 40

-22.2

2300 ± 40

300 b.c–a.d. 10

Beta-281063

N9180 E1240

Mercenaria

1080 ± 40

-0.9

1480 ± 40

a.d. 680–890

Beta-281064

N9220 E1180

Mercenaria

1120 ± 40

-1.5

1510 ± 40

a.d. 660–870

Beta-281066

N9260 E1140

Mercenaria

720 ± 40

-1.2

1110 ± 40

a.d. 1050–1270

TABLE 8.6. Results of Season of Capture Analysis

Sample Number

Unit

Level (cm below surface)

Sample type

Season of capture

110551_1

Shovel Test D

40–50

Mercenaria

Spring

110551_2

Shovel Test D

40–50

Mercenaria

Winter

110548

Shovel Test D

40–50

Crassostrea

Summer

110557

Shovel Test D

60–70

Crassostrea

Fall

110420

N9200 E1240

0–20

Mercenaria

Summer

CHAPTER 9: EVER-SHIFTING LANDSCAPES: TRACKING CHANGING SPATIAL USAGE ALONG COASTAL GEORGIA

Matthew C. Sanger[5]

SETTLEMENT STUDIES AND SURVEY DATASETS

Studying the spatial patterning of cultural materials across broad landscapes has been an important aspect of archaeological studies for more than 60 years. Beginning with Julian Steward’s (1937) research in the western United States and Gordon Willey’s (1953) work in Peru, archaeologists began to formally investigate the spatial organization of past peoples as a proxy for underlying social structures, behavioral patterns, and cultural adaptation to the surrounding environment (Anschuetz, Wilshusen, and Scheick, 2001). The distribution of archaeological materials across the landscape continues to be an important avenue of archaeological research as demonstrated by the wealth of publications focused on settlement studies in the last 40 years (for overviews see Trigger, 1967; Parsons, 1972, Evans and Gould, 1982; Billman and Feinman, 1999; Kowalewski, 2008).

Tracking the shifting nature of archaeological material distribution through time and across space continues to be used by archaeologists to investigate a wide variety of past ideological, economic, and social phenomena including: relationships between people and natural resources (Daniel, 1996; Jones et al., 2003), logistical organization and residential strategies (Savelle, 2001), the creation and maintenance of social territories (Dortch, 2002; Kowalewski, 2003; Peterson and Drennan, 2005), changing power relations (Hally, 1996, 1999, 2006; Williams and Shapiro, 1996), and demographic shifts (Feinman et al., 1985; Milner and Oliver, 1999; Scarre, 2001; Cobb and Butler, 2002; Kowalewski, 2003; Kintigh, Glowacki, and Huntley, 2004; Osborne, 2004).

Of primary importance to most settlement studies is a regional dataset drawn from a systematic survey project (Kowalewski, 2008). This chapter reports on the findings of a project undertaken in coastal Georgia during the summer of 2009. This project, deemed the Springfield Legacy Archaeological Project (SLAP), was a mixture of traditional field techniques, including field survey and intensive subsurface sampling, as well as newer techniques, such as using Light Detection and Ranging (LiDAR) to analyze topographic features and Geographic Information Systems (GIS) to create spatial models. Together, these techniques built a rich dataset through which we are beginning to understand how the past peoples of coastal Georgia interacted with their landscapes and how that interaction varied through time and space. As this project is the first systematic archaeological investigation conducted at the study area, it offers only the most preliminary insights into the shifting relationships between people and their landscape. Rather than offering decisive conclusions, this chapter will instead highlight different techniques that were beneficially applied, preliminary hypotheses to be tested, as well as potential research questions that can be pursued by future studies. Like most initial research programs, the work conducted by SLAP provides baseline empirical data on which further projects can build.

SPRINGFIELD LEGACY STUDY AREA

More than 9000 contiguous acres of privately held land between the town of Midway and Colonel’s Island in Liberty County, Georgia (located roughly 40 km south of Savannah) were presented for potential archaeological analysis by a local not-for-profit institution, the Springfield Legacy (fig. 9.1). This land includes coastal marshland, upland pine forests, and marsh islands—much of which has been heavily impacted by farming, road construction, and tree farming. While the property has been visited by both professional and amateur archaeologists in the past, no formal reports or publications have been produced and all work has been minimal by any respects.

The Springfield Legacy properties were divided into 10 analytical sections based on ecosystem, elevation, distance to waterways, and accessibility. This division allowed precision in terms of discussing the property as well as dividing it into portions that could feasibly be surveyed in single four-week seasons. Section 6 was chosen as the initial study area as it contained a variety of biozones, including marshes, freshwater streams, uplands, and marsh islands (fig. 9.2). Section 6 is located on the western edge of Colonel’s Island and contains 425 acres. To our knowledge, this project is the first archaeological investigation of any kind within this study area.

LiDAR DATA AND METHODS

The Springfield Legacy Archaeological Project (SLAP) was heavily dependent on airborne LiDAR data for project planning, wayfinding, model building, and postexcavation data analysis. Airborne LiDAR systems are based on the use of a laser scanner placed on a helicopter or airplane flying at relatively low altitudes. The laser scanner broadcasts pulses of energy toward the ground and records the time it takes to rebound and return to the scanner in order to assess the range between the aircraft and the surface below (Watkins, 2005; Weitkamp, 2005). In combination with Global Positioning System (GPS) technology, and an Inertial Measurement Unit (IMU), the distance between aircraft and reflective surface is transformed into topographical data of a well-defined location (Habib et al., 2005; Hollaus, Wagner, and Kraus, 2005; Reutebuch, Andersen, and McGaughey, 2005; Pfeifer and Briese, 2007).

The use of LiDAR for archaeological research purposes is becoming relatively common in Europe (especially Britain and the Netherlands) and is slowly growing in importance in the United States. Archaeologists have used LiDAR to both better understand large, topographically complex archaeological sites such as the Stonehenge environs (Bewley, Crutchley, and Shell, 2005) and historic plantation sites in Maryland (Harmon et al., 2006), and as a tool to survey broad areas in an attempt to recognize previously undiscovered sites (Gallagher and Josephs, 2008). LiDAR technology and analysis has progressed to a level where it is now possible to “remove” data associated with vegetation and to produce relatively reliable maps of the underlying ground topography (Lillesand, Kiefer, and Chipman, 2004; Raber et al., 2002; Sithole and Vosselman, 2004). While LiDAR has quickly become a major source of digital terrain information (Raber et al., 2007), numerous researchers have pointed out many inaccuracies that can affect the quality of data based on topography (Bowen and Waltermire, 2002), postprocessing methods (Lloyd and Atkinson, 2002), and quantity of vegetational interference (Dowman and Fischer, 2001).

Even with these potential sources of error, LiDAR remains a relatively accurate source of topographic data and was the backbone of the SLAP survey project. Previous to fieldwork, a visual analysis of the LiDAR data in conjunction with aerial photos allowed an accurate assessment of the size and shape of the project area, as well as a baseline from which transects could be superimposed; also, the quantity of test pits could be estimated. As we became more familiar with the terrain and vegetation, it was also possible to imagine field conditions throughout the study area based solely on the topographic data presented by LiDAR. Higher elevation areas with little slope were dominated by pine stands while poorly draining low-elevation areas were more likely to be filled with palmettos. Field conditions could have dramatic impacts on fieldwork, such as the difficulty in surveying a young pine stand intermixed with Devil’s Walkingstick (Aralia spinosa). The LiDAR data gave us the opportunity to assess those conditions prior to engaging in direct fieldwork and to plan our survey strategy accordingly.

Beyond providing a baseline topographic map of the area, LiDAR data were also utilized to discover less common natural features on the landscape that were of archaeological interest. Small waterways and dried up ponds were relatively easy to recognize using the LiDAR images even when they were difficult to see in the field because of surface vegetation. Such features suggest the presence and distribution of fresh water within the study area, an important natural resource that could have affected how past peoples interacted with their landscape. Along with natural features, the LiDAR data proved important in delineating portions of the landscape that were culturally modified. Drag lines used to drain marshland, old roadways and firebreaks, as well as mounds of sawdust from milling were visible in the LiDAR images (fig. 9.3). The LiDAR images also highlighted several topographic features that required more detailed field investigation, including three potential burial mounds as well as a large, rectangular depression that appears to have been used as a water retention feature (see the sites section of this chapter for more details).

PEDESTRIAN SUBSURFACE SAMPLING STRATEGY, METHODS, AND RESULTS

As mentioned earlier, a 425 acre section of the total 9000 acre project area was selected as the focus of our first research season. This portion of the project area was on the northwestern edge of Colonel’s Island—a 4000 acre plot of land that lies between mainland Georgia and the Intercoastal Waterway. We also selected three marsh islands as research locales. Each of these marsh islands was small (less than 15 acres), relatively easy to get to (we could walk to two of them, the third took a very short kayak ride to reach), and would provide an important comparison with our larger sample from Colonel’s Island. During the summer of 2009, a small crew of students from Columbia University and Barnard College, alongside more experienced staff members employed by SLAP, conducted a shovel test pit (STP) survey across both the 425 acre study area (Section 6) on Colonel’s Island and the three small marsh islands (A, B, and C) (fig. 9.4).

STP surveys have become a mainstay within archaeological research, especially in the Eastern Woodlands, since they were first formally described by William Lovis in 1976. While not without controversy (see Nance, 1979; Wobst, 1983; Lightfoot, 1986, 1989; Nance and Ball, 1986, 1989; Shott, 1989), STP surveys have proven to be a relatively economical and accurate method of tracking the distribution of cultural materials across the landscape. Because of various factors affecting discard practices, as well as taphonomic processes, care needs to be taken in suggesting that distributional data derived from STP surveys are equivalent to actual past landscape usage. Past experiments have shown that small sites are underestimated using STP data (Nance, 1979), and that the distribution and density of cultural materials within an archaeological site, regardless of size, can have a dramatic effect on the resultant STP dataset (Nance and Ball, 1986). While mathematical formulas are available to quantify the level of accuracy found within an STP survey (Sundstrom, 1993), they do not alleviate the partial and somewhat biased results obtained by this technique. With these limitations in mind, STP surveys are still a critical technique for areas, such as the southeastern United States, in which vegetation and subsequent soil deposition obscures the visibility of underlying archaeological signatures.

A three-tiered stratified systematic STP survey methodology was utilized at SLAP in which the study area was divided into sections based on assumed density of archaeological materials. Based on a small-scale pedestrian surface survey and a pilot shovel test pit project of the study area prior to our field season, it was clear that the density and occurrence of archaeological phenomena were positively influenced by proximity to waterways. Our first tier was therefore based on being adjacent to the marshland. Within the first tier we placed an STP every 10 m along a 100 m wide transect that mirrored the marsh line. Our second-tier research area was in the inland portions of Colonel’s Island, an area that our pilot projects suggested contained fewer archaeological remains. Within this area, we placed STPs every 20 m along 100 m wide east-west transects that were spaced 500 m apart. The three marsh islands were our third-tier research area. Previous visits suggested that these islands were relatively free of cultural remains. We were concerned with overlooking these small islands, a recurrent problem in coastal archaeology (see Keegan et al., 2008; Thompson and Turck, 2010; Turck and Alexander, chap. 7 and Napolitano, chap. 8, this vol.) and considered the possibility that the apparent lack of cultural materials was a sampling error. We therefore decided to pursue a very thorough survey of these small marsh islands. This portion of the project was very similar to that conducted near the marsh edge on Colonel’s Island. STPs were placed every 10 m across 100% of the island. All STPs excavated within this project were standard 50 cm circles, were excavated to the sterile C-horizon, and all materials were screened through ¼ in. screens.

In total, 1247 STPs were excavated within the study area. Of these, 827 STPs were placed in our first study zone, the 100 m wide transect following the marsh line, while 323 STPs were placed in the second study zone along three east-west transects, each 100 m wide, that cut through the interior of Colonel’s Island (table. 9.1). Another 97 STPs were excavated in the third study zone (the three marsh islands). The STPs near the marsh line of Colonel’s Island were highly productive in terms of recovering archaeological materials; 36% of these STPs were “positive” for containing archaeological materials (N = 299). Another 5% contained no artifacts, but excavators did encounter shell deposits. This is in direct contrast to the STPs placed within the interior of Colonel’s Island where only 8% were positive (N = 26). Even fewer cultural remains were encountered on the marsh islands where 3% were positive (N = 3).

By far the most common archaeological material encountered in all areas was ceramics of Native American manufacture. Less common finds included historic building materials (tabby and brick), stone tool debitage, shell tools, and assorted historic materials (primarily nails and glass). Not surprisingly, almost all of the archaeological materials discovered were found within the excavations as opposed to being located on the surface. Only two artifacts were found on the surface, which highlights both the lack of visibility and the geologically accretionary environment within the study areas.

ANALYTICAL UNITS: LANDSCAPE, SITE, AND COMPONENT

One of the ramifications of the rise in popularity of systematic surveys in the 1960s and 1970s was the slow acceptance that archaeological “sites” are exceedingly difficult to define in a manner that does justice to past events and practices as well as being useful to current archaeologists (Thomas, 1973, 1975; Thomas and Bettinger, 1976; Lewarch and O’Brien, 1981; Dunnell and Dancey, 1983; Dunnell, 1992). As systematic surveys encounter small pot drops, ephemeral lithic scatters, isolated finds, as well as artifact-rich habitation locales, the definition of archaeologically relevant spatial areas is difficult and largely dependent on the idiosyncrasies of the researcher and analytical goals of individual projects. This has led some archaeologists to call for a true “siteless” archaeology in which the distribution of objects is analyzed directly rather than from the analytical units derived from the empirical record (Ebert, 1992; Ebert et al., 1996; Galaty, 2005). While the goals of “siteless” archaeology are appreciated, it is impossible to pursue such a program within the coastal Southeast because of the difficulty in encountering archaeological materials without excavation. In areas in which archaeological materials are regularly encountered on the modern surface, it is feasible to recover a relatively accurate sample of past materials and to fill a distributional map with those results. Projects, such as the one conducted by SLAP, in which almost all of the materials are recovered from excavated contexts are necessarily skewed in ways that preempt any attempt to produce an accurate “siteless” map.

Instead, in an effort to increase cross-project comparability, SLAP has adopted the nomenclature and analytical partitioning used on nearby St. Catherines Island. From 1977 to 1979 the American Museum of Natural History team, under the direction of David Hurst Thomas, conducted an islandwide survey of St. Catherines Island, the results of which were published in a recent three-volume set (Thomas, 2008). Thomas, who was heavily involved in the widespread adoption of systematic surveys in the 1970s, as well as a reevaluation of how archaeologists define “sites” (Thomas, 1973, 1975), used three different terms to define spatially bounded areas of archaeological interest on St. Catherines Island—sites, components, and landscapes (2008: 875–876). Thomas’s tripartite division of archaeological locales allows a level of scalar flexibility in analyzing and presenting archaeological information that was found to be beneficial within this study and acts to structure our data presentation.

Twenty-four different archaeological sites were defined within the SLAP study area (fig. 9.5). Sites are “anyplace where material evidence exists about the Native American past” (Thomas, 2008: 875). As Thomas notes, the definition of archaeological sites is based on somewhat subjective judgment calls and different archaeologists can draw spatial delineations within archaeological data in diverse ways (2008: 520). In general, archaeological sites within the SLAP data are defined as areas with a “significant” amount of cultural material that is bounded by archaeologically “empty” space. Thomas defined an ordinal scale for site size based on horizontal extent of cultural materials in which areas are divided into small (less than 50 m2), medium (50–500 m2), and large (greater than 500 m2) sites (Thomas, 2008: 520). A similar division was followed within this analysis.

Thomas also provides definite parameters for recognizing temporal components within archaeological sites. A component is “a culturally homogeneous unit within a single archaeological site” (Thomas, 2008: 875). Single sites can, and often do, have multiple components if they show evidence of being used during multiple time periods. Thomas suggests a division between major and minor components based on the ratio of temporally diagnostic items found from each time period (2008: 520). Using Thomas’s methods, 47 components were recognized within the SLAP study area.

The final analytical unit used by Thomas is a “presence” or “occupation” based on a landscape approach to the data. Concerned with the potential that rare finds and ephemeral material traces would be ignored through his focus on sites and components, Thomas offered a broad and inclusive category that “incorporates the totality of all available archaeological indicators (termed a ‘presence’ or ‘occupation’), partitioned according to a specific temporal period and plotted across a well-defined and bounded geographical space” (Thomas, 2008: 875–876). Based on this definition, 65 occupations were found within the SLAP study area.

The following section will first detail the overall presence of temporally diagnostic items across the entire study area (the landscape approach) before delineating these areas into sites that are then further divided into components. Up to the historic period, all of the temporally diagnostic items recovered were ceramic sherds. While several lithic flakes (N = 18) and a whelk tool were found during the survey, they cannot be limited to a specific point in time and so play a minor role within this analysis.

CERAMIC CHRONOLOGY AND THE SLAP LANDSCAPE

Beginning with the work of Joseph Caldwell and Antonio Waring (1939a, 1939b), and continuing through the work of Lewis Larson (1958a, 1969, 1978, 1980a) and Chester DePratter (1977a, 1979, 1984, 1991, 2009), the chronological ordering of diagnostic ceramics from the Southeast has been refined for more than 70 years. The Springfield Legacy Archaeological Project utilized this chronology to track the changing usage of space over time.

The oldest ceramics found in the Southeast, as well as the study area, date to the Late Archaic. These ceramics, known locally as St. Simons, are recognizable by the vegetable fiber that was used for tempering (Waring, 1968; DePratter, 1978). St. Simons ceramics were encountered very rarely during our STP survey and they only make up less than 1% (N = 6) of the ceramic collection and are found in less than 1% of the total positive shovel test pits (see table 9.2). With such a small sample, it is difficult to discern any spatial distribution, but the few Late Archaic ceramics recovered are limited to three occupations in the northern section of the survey area (fig. 9.6).

After the Late Archaic, the Woodland Period begins and is largely recognized by the emergence of grit- and sand-tempered ceramics (Waring, 1968; DePratter, 1979). The earliest grit- and sand-tempered ceramics are the Deptford type, with Refuge ceramics occurring later in the sequence (Waring, 1968; DePratter, 1979). Other archaeologists have commented on the difficulty in differentiating between Refuge and Deptford ceramics because both utilize small- and medium-grade grit as well as sand for tempering (Thomas and Larsen, 1979; Thomas, 2008). While there are some decorative elements that are recognizable as being either Deptford or Refuge (such as Deptford Check Stamping), these decorations were rarely found within the SLAP STP collection. We have therefore combined the two types into a single analytical category that spans the Early to Middle Woodland. Fifteen percent of the recognizable ceramics from the STP survey and more than a quarter of the positive shovel test pits contain Refuge/Deptford ceramics (table 9.2). The 12 Refuge/Deptford occupations are focused along the marsh edge, with negligible evidence of any usage in the interior of the study area (fig. 9.7). The presence of Refuge/Deptford pottery along the marsh edge is concentrated in the northwestern portion of the survey area with a decrease in occurrence farther to the south. Beyond a small cluster that is immediately north of a relict waterway, the southern three-quarters of the project area contain only a couple of sporadic finds that date to the Early/Middle Woodland periods.

Following the use of grit and sand as tempering agents, pottery constructed during the Late Woodland/Early Mississippian periods is defined based on the use of ground ceramics as temper (Caldwell and Waring, 1939b; DePratter, 1979). This ceramic, or grog, tempered pottery can be further divided into three types: Walthour, St. Catherines, and Wilmington, based on the size of the grog being used as temper as well as the method of surface decoration (DePratter, 1979). Walthour pieces are recognizable as the only grog-tempered ceramics that are stamped (both complicated and check stamping) and as a rare pottery type within the SLAP STP collection, as well as for the Southeast in general (DePratter, 1979). Walthour ceramics are thought to occur only during the earliest portion of the Late Woodland (the Wilmington I phase) and were likely constructed for fewer than 100 years (Thomas, 2008: 383). The more common grog-tempered ceramics within the SLAP STP collection are the St. Catherines and Wilmington types. While it is possible to differentiate between the two types when looking at larger sherds, a significant portion of the SLAP collection is made up of very small ceramic fragments that are not large enough to determine their specific type. We could positively identify slightly more than half of the clay-tempered sherds as being either St. Catherines or Wilmington, with the vast majority being St. Catherines. The sherds that were too small to differentiate between St. Catherines and Wilmington are classified as being “grog-tempered” and are assigned to the broad temporal span of Late Woodland–Early Mississippian.

In total, a little more than a quarter of the SLAP ceramic collection from the STP survey was grog-tempered and a third of the positive STPs had grog-tempered ceramics within them (table 9.2). Seven St. Catherines and four Wilmington occupations can be defined, along with seven occupations defined by unidentified grog-tempered ceramics. This division overestimates the number of Late Woodland–Early Mississippian occupations in that many overlap with one another, but without larger samples of diagnostic ceramics it is impossible to further differentiate between these similar types. As with the preceding Early/Middle Woodland ceramics, the grog-tempered ceramics are largely found near the marsh edge, although there is a slight shift toward the interior within the southern portion of the study area (fig. 9.8).

A significant increase in the use of sand as a tempering agent defines the Savannah pottery type (DePratter, 1979). While there is little controversy in delineating Savannah pottery as a morphological type, recent work on St. Catherines Island has questioned whether this pottery type is isomorphic with a well-defined time period (Thomas, 2008: 430–432). Savannah pottery appears to span a temporal range (1200–700 b.c.) on St. Catherines Island that is related to both the St. Catherines Period on the early end and the Irene Period in the later portion (Thomas, 2008). This has led David Hurst Thomas to suggest that while there is a Savannah morphological type on St. Catherines Island, it is not directly related to a Savannah time period (Thomas, 2008). Other archaeologists have also attempted to better understand the temporal relation of Savannah ceramics (Crook, 1978a; Pearson, 1979a, 1984; DePratter, 1984; Braley, 1990; Saunders, 2000b) with little consensus. It would appear that Savannah ceramics are a ceramic type either used in conjunction with other types, temporally limited to a very small time period, or varying in usage and temporal placement based on region. Without a directly applicable radiocarbon record, this project has little to contribute toward this ongoing discussion beyond noting that there are Savannah type ceramics recovered within the study area, but they are relatively rare.

As with the other ceramic types, the Savannah occupations are found primarily within 100 m of the marsh line. The 10 Savannah occupations are relatively ephemeral in that many of them are made up of fewer than 10 sherds with only two locations, one in the southern section of the survey area and the other in the northwest, showing a significant presence of Savannah ceramics (fig. 9.9).

The most recent Native American ceramics found in coastal Georgia are tempered with relatively large grit (Caldwell and Waring, 1939; DePratter, 1991). Large grit-tempered ceramics can be further divided between an earlier Irene, which was initially burnished or stamped with a complicated pattern and then later was incised with more regularity, and a later Altamaha type, which is similar to the Irene type, but is often stamped with different patterns or painted with a red slip (DePratter, 2009: 21–35). While Irene ceramics dominate the SLAP assemblage, no recognizable Altamaha sherds were recovered during the survey (table 9.2). As with all of the cultural materials recovered during the STP survey, the Irene ceramics were more abundant closer to the marsh edge, with a significant decline toward the interior of the study area. Irene ceramics were a relatively common find throughout the marsh edge STPs, occurring in more than half of the positive STPs from this section. The ubiquity of Irene ceramics in the SLAP collection is demonstrated by the fact that there are 22 defined occupations from this time period including the only precontact occupation encountered on the marsh islands (fig. 9.10). Irene ceramics are the most common ceramic type found within coastal Georgia (Thomas, 2008; Thompson and Turck, 2009; Napolitano, chap. 8), so it comes as little surprise that they dominate the SLAP assemblage.

Artifacts dating to the historic period are very rare (found within 5% of total STPs) and are generally found in small, near-surface concentrations or as isolated items. Most of the historic period finds are small, unidentifiable ceramic sherds, along with numerous metal nails, fragments of window and bottle glass, as well as a small amount of tabby and brick. In total, the rarity of historic ceramics is surprising considering that this portion of Colonel’s Island has been occupied by European and African families for more than 300 years. While most of the historic period artifacts were found along the marsh line, a small number were also recovered within the interior, often in association with roadways.

SITE DESCRIPTIONS

As noted earlier, 24 distinct locales have been designated as sites based on the presence of archaeological materials. The site designation is purely a spatial division, which is then temporally divided into individual components. Many of the sites contain temporally diagnostic materials from numerous time periods—often within a single excavation unit—suggesting a great deal of continuity in landscape usage through time. In total, 47 individual components were defined within the survey area. Each site, and its attendant components, is summarized in table 9.3.

Several of the sites encountered during this survey are worthy of additional description because of their unique characteristics and potential importance for further research. The first one is a small clustering of three mounds (site 9Li1929). Mounds are relatively common within the American Southeast, first becoming common in the Early Woodland and continuing through historic time periods. The mounds that make up this site are modest in size, ranging from 1 to 2.5 m in height and 7–9 m in diameter. Two of the mounds are conical while the third appears to have been built in several stages as it has a “stepped” appearance to it unlike the smooth shape of the other two mounds. The largest of the conical mounds and the “stepped” mound each have depressions at their apexes, suggesting that they have been looted. The third, and smallest, mound appears untouched.

All of the mounds are covered with small pine trees and bushes, as are the surrounding environs. Investigating these mounds was considered outside the purview of this project, and so a minimal amount of effort was put into mapping the area and conducting a proper surface survey. In order to ensure that the current project did not impact the mounds, or any surrounding archaeological resources, a 100 m wide buffer was established within which no excavations took place. As per the request of the landowners, who fear further looting of the mounds, this site has not been marked on the map.

The second site that merits further discussion was discovered through an analysis of the LiDAR data and was then investigated through field visits and limited excavations. It is a large rectangular depression (site 9Li1935) roughly 4° off true north (fig. 9.11). Measuring 94.5 m along its north-south axis and 97.2 m east-west, this depression is almost a perfect square. There is a 15–20 cm rise along the edge of the feature before it quickly drops (roughly 18–20° slope) a meter in elevation. The interior is relatively level, with occasional low points that were filled with standing water during our visit. Within the feature, the vegetation was similar to that found beyond its edges (largely young pine trees) but was decidedly more open because of a lack of undergrowth and a greater spacing between trees.

The LiDAR shows that this square depression is related to a relict waterway that is linked to a low area within the interior of Colonel’s Island (see fig. 9.11). This low area in the interior is now dry, but the geology of the area along with historical records suggests that this was once wetlands. Much of coastal Georgia’s wetlands have been drained during the last 400 years in an attempt to reclaim the land for agricultural production and we assume that this interior area was likewise drained. The rectangular depression is at the confluence between a deep waterway, which leads to the marsh and these interior wetlands. At this point of confluence it appears that the waterways leading both into the interior of the island as well as those leading out toward the marsh have been either accentuated or created through anthropogenic means. The edges of the waterways were relatively steep, far more so than other natural streams encountered elsewhere on the property. The waterways near the depression took dramatic turns at times—lending credence to the possibility that they were modified through anthropogenic means. A visual surface and a subsurface survey over this entire feature were conducted, resulting in the discovery of 11 grog-tempered sherds along with two Irene ceramics. While the lack of historic artifacts does not mean this feature was constructed precontact, it does raise this interesting possibility. Other researchers in the Southeast have encountered precontact waterways that have been associated with trade, symbolic meaning, agricultural needs, and movement by canoe (Luer, 1989; Kidder and Saucier, 1991; Wheeler, 1998; Rodning, 2003).

While we have not discounted the possibility of precontact construction, our current working theory is that this rectangular depression was constructed during the historic period, possibly as a containment feature for overflow from the draining of the interior of Colonel’s Island. Perhaps this overflow was contained for agricultural usage. Another possibility is that this feature was not based on draining the interior of the island, but was instead a catchment for tidal waters coming up the river. These waters could have been trapped during high tides and then allowed to evaporate leaving behind a thin layer of salt that could be sold, traded, or used for personal consumption. All of these theories are “best guesses” and need to be directly tested by further fieldwork as well as a more detailed investigation of historical records—both of which were considered beyond the immediate goals of the current project.

LANDSCAPE USAGE THROUGH TIME

As with any survey project, SLAP has produced a wide array of data from multiple time periods. It is beyond the scope of this chapter to comment on every potential aspect of this dataset. Instead, I will highlight three points at which the SLAP data have suggested interesting avenues of further research. These avenues include: a deeper investigation into the demographic shifts associated with the transition between the Archaic and the Woodland periods within the coastal Southeast; the differential use of shellfish between the mainland and nearby islands prior to the Late Mississippian; and the long-term population trends found within the SLAP data.

Archaic–Woodland Transitions

The earliest evidence of human activity within the SLAP study area dates to the Late Archaic. Our evidence from this time period is based on a small handful of ceramics, which are found in several small concentrations in the northernmost portion of our study area. The rarity of Late Archaic artifacts can be contrasted with the dramatic increase of Woodland Period materials, as seen in the 105 pieces of Refuge/Deptford ceramics. As noted earlier in this paper, the Refuge/Deptford type used within this study is an amalgam of two different ceramics from consecutive time periods, so our temporal controls are not as robust as one would like. However, it is clear that a significant shift in artifacts has occurred with the onset of the Woodland, and is likely connected to a shift in population and settlement strategies.

These shifts are better understood on nearby St. Catherines Island where Late Archaic components were rarely found during the survey with a moderate increase in the number of components defined by Refuge/Deptford ceramics. While there is an increase in overall number of components between these two periods, the transition is far more complicated than a simple demographic increase. During the Late Archaic, there were three large sites on St. Catherines Island, including two shell rings (Thomas, 2008: 840; Sanger and Thomas, 2010). These two rings are similar to the nearly 50 other rings found throughout the coastal Southeast in that they were large-scale middens constructed through highly proscribed depositional practices (Russo, 2006). In terms of artifact density, quantity of food remains, and impact on the surrounding landscape, the shell rings on St. Catherines Island are significantly larger than any other archaeological site on the island until large village sites appear during the Mississippian. The presence of these two shell rings, which appear to be nearly contemporaneous (Sanger and Thomas, 2010), suggests an intensive use of the island during the Late Archaic.

Following the abandonment of the shell rings on St. Catherines Island and the end of the Archaic, there is a significant shift in usage of the island. Thomas found that there was a gap of 800–1000 years in the radiocarbon record starting around 1350 b.c. that corresponds to the Late Archaic and Early Woodland transition (Thomas, 2010a). This gap is attributed to humans abandoning the majority of the island as dropping sea levels destroyed local salt marshes, the main subsistence resource for the Late Archaic populations living on St. Catherines Island (DePratter and Howard, 1980, 1981; Gayes et al., 1992; Thomas, 2008).

During this gap, perhaps as early as 1000 b.c., the radiocarbon record shows that an Early Woodland population returned to St. Catherines Island, but unlike the Late Archaic populations that preceded them, they did not build shell middens. Instead, the primary evidence for any activity on St. Catherines Island between 1000 b.c. and 350 b.c. comes from mortuary contexts (Thomas, 2008, 2010a). It is unclear whether St. Catherines was home to many, or any, Early Woodland peoples, or if it was used only as a mortuary locale. It is not until around 350 b.c. that shell middens are again deposited on the island and evidence for villages is found.

Archaeological research conducted on Ossabaw Island, immediately to the north of St. Catherines (fig. 9.12), suggests that the findings on St. Catherines Island may reflect a broad trend across the region. While there are very few Late Archaic sites on Ossabaw, at least one of them, Cane Patch (9Ch28), is an extremely large shell midden that appears to be the result of long-term occupation (Pearson, 2001: 14–16). In contrast, there are no Early Woodland (Refuge) sites on the island and only 10 very small Middle Woodland (Deptford) sites (Pearson, 2001: 18). Likewise, while only limited surveys have taken place on St. Simons Island, located south of St. Catherines, evidence suggests that after the abandonment of two Late Archaic shell rings, the island did not support any significant habitation sites for a millennium (Marrinan, 2010: 97).

The findings on the barrier islands can be further contextualized by looking at Victor Thompson and John Turck’s (2010) work on the small marsh islands between the barrier islands and the mainland (fig. 9.12). Thompson and Turck surveyed four of these small marsh islands and found a small, yet significant, Late Archaic presence on all but one of the islands (Thompson and Turck, 2010). The presence of Late Archaic materials (N = 69) is greater than the following Early (N = 12) and Early-Middle Woodland periods (N = 27) (Thompson and Turck, 2010), suggesting a significant shift in landscape usage between these two periods that parallels the findings on St. Catherines and Ossabaw. Taken together, these works suggest that the Georgia islands, both large and small, were heavily utilized during the Late Archaic. With the end of the Archaic, the small islands along the Georgia coast appear to be visited less frequently, while St. Catherines Island, and likely other larger islands, were abandoned for significant periods of time before being used as mortuary sites, perhaps without accompanying residences or procurement camps.

The archaeological record of the mainland areas surveyed by SLAP portrays a very different account of landscape usage. The minimal number of Late Archaic ceramics in comparison with the 15-fold increase in Refuge/Deptford ceramics suggests a demographic shift that is the mirror opposite of what was found in the island contexts. The most plausible explanation is that sea level change occurring at the onset of the Woodland brought with it a movement of people away from the coast and into more mainland locales (DePratter, 1976, 1977a, 1978; DePratter and Howard, 1980; Thompson and Turck, 2010; Sanger, 2010). Other researchers working on the mainland routinely encounter Early Woodland sites, although they are often relatively small seasonal camps (Stoltman, 1974; Anderson, Cantley, and Novick, 1982; Sassaman et al., 1990; Sassaman, 1993b; Elliott and Sassaman, 1995; Sassaman and Anderson, 1995; Sassaman, 2010).

Not only did the transition between Late Archaic and Early Woodland bring with it a shift in landscape usage, but almost every aspect of the material culture, from pottery construction and style, lithic tool morphology, refuse disposal, and residential architecture changed between these two time periods, suggesting a dramatic realignment of social decision making. These changes are widespread along the southeastern coastline from South Carolina to Florida (Russo, 2010). The shift between Archaic and Woodland traditions is beginning to be unraveled by numerous researchers across the Southeast (see chapters within Thomas and Sanger, 2010). The research conducted by SLAP suggests that the coastal region of Georgia is an important point at which the Archaic–Woodland shift can be further investigated.

Shellfish Paradox Revisited

Regardless of time period, a consistent trend throughout the SLAP data is a positive relationship between proximity to marsh and quantity of archaeological materials. Ninety-six percent of precontact materials was found within 100 m of the marsh edge or relict waterway despite only 66% of the excavations taking place in this area. A similar relationship was recognized on St. Catherines Island and was considered a positive demonstration of the predictive power of central place foraging theory (Thomas, 2008: 930). Central place foraging models are based on the assumption that humans will choose specific residential locales in an attempt to maximize their access to highly ranked subsistence patches (Winterhalder, 2001). Based on a series of projects in which different subsistence resources were evaluated, Thomas built a settlement model for St. Catherines Island that suggested the two highest ranked resource patches available were salt marshes and the maritime forest (2008: chap. 31). Central place foraging theory modeling suggests that all things being equal, the residents of St. Catherines Island should establish their residences near the marsh line at the intersection of these two patches, a model that was borne out by Thomas’s survey results (2008) and generally replicated within this project. One of the primary resources drawn from the saltwater marshes is shellfish and their remains are ubiquitous within the archaeological contexts on St. Catherines Island (2008: 979).

This is in direct contrast with the results from the SLAP excavations in which marine shells are almost never found in conjunction with any material culture that predates the Late Mississippian (Irene). More than half of the sites within the survey area had substantial shell middens associated within them; however, all but two of the shell middens (at 9Li1919 and 9Li1925) were associated with Irene or historic period artifacts. Even the two associations between shellfish and pre-Irene ceramics are somewhat tenuous in that the stratigraphic integrity of these finds appeared mixed. On St. Catherines Island, shellfish remains are found in association with every ceramic type except Refuge/Deptford (2008: chap. 15). Likewise, shovel test pit surveys on nearby marsh islands routinely encountered shell middens associated with a wide range of ceramic types (Thompson and Turck, 2010; Turck and Alexander, chap. 7 and Napolitano, chap. 8, this volume). While changing sea levels are generally considered the cause of the lack of association between Refuge/Deptford sherds and shell (Thomas, 2008: chap. 5), they do not account for the general lack of shell middens predating the Irene in the SLAP survey area. Instead, it would appear that either other environmental factors precluded the development of shellfish beds in the study area or there was a purposeful selection against shellfish before the Late Mississippian.

While shellfish are currently present within the study area, and the archaeological evidence shows that they have been available since the Late Mississippian, it is possible that the environmental conditions necessary for their existence are a relatively recent occurrence. The presence of shellfish in middens dating from the Middle Woodland up to present day on nearby marsh and barrier islands suggests that there was no widespread environmental condition, such as temperature or sea level changes, which precluded the existence of shellfish throughout the region. Instead, any environmental condition that impeded the presence of shellfish would necessarily have been relatively limited in terms of spatial impact. The most likely environmental shift that would be this localized and yet highly effective in changing suitability for shellfish is a change in water flow, especially fresh water from the mainland. All shellfish have a limited range of salinity in which they can survive and reproduce (Galtsoff, 1964; Odum, Copeland, and McMahan, 1974). The primary factor in determining salinity within the study area is the amount of fresh water flowing down the rivers and tributaries from inland areas. While these waterways currently appear relatively stable, recent research suggests that they may be more dynamic than we imagine and have shifted course many times in the last 4000 years (Chowns, 2011).

While a local environmental shift could explain the lack of shellfish within the pre-Late Mississippian archaeological record, we currently have no evidence of such a change. A dramatic change in flow within a large waterway such as the Medway River, or even some of the smaller streams and creeks, should leave visible traces within the geological record. Currently, research into these waterways is minimal, and further work should be conducted to recreate their histories. In lieu of evidence for environmental change, it is wise to entertain other ideas, including the possibility that people were actively choosing not to subsist on shellfish prior to the Late Mississippian.

Thomas suggested a similar possibility in his recent work on St. Catherines Island when he asked why individuals would utilize shellfish at all. Working with the theories of human behavioral ecology, especially diet breadth, Thomas ranked the value of many of the foodstuffs found in the nearby environs based on the caloric return rate individuals could expect based on the amount of time they invested in acquiring and processing a given resource (2008: chaps. 6, 7, and 8). He found that shellfish were consistently ranked very low, which made their ubiquity within the archaeological record paradoxical (2008: 979). Thomas solved this apparent paradox by suggesting that a single ranking of foodstuffs based on energetic returns was not fine-grained enough to reflect the conditions presented to past peoples and that different groups of people valued foods differently. One of the largest divisions in terms of subsistence choices was between men and women, especially women who were engaged in care giving to small children (2008: 981–982; also see Claassen, 1991). Thomas suggests that men and women often have different goals when it comes to subsistence, with women often choosing foods based on their ubiquity and predictability, such as shellfish, while men went for the larger payoff, yet higher risk foods.

Accepting this hypothesis, the archaeological record from the SLAP study appears to suggest that the difference in the faunal record between St. Catherines Island and this portion of the mainland is based on the decision making of women. Rather than gathering shellfish, the women within the SLAP study area may have spent their energy on other subsistence tasks, such as hunting in the nearby forest or fishing in the salt marshes. What would cause such a significant difference in subsistence practices conducted by contemporary populations on the islands and the mainland is not clear. It seems unlikely that the past residents of the coastal mainland were either ignorant of shellfish consumption or opposed to it based on ideological reasons. It would seem more likely that there were other resources that were particularly valued, perhaps by women in particular, that were available to such an extent that they precluded the gathering of the lower valued shellfish. Unfortunately, our faunal collection is extremely sparse, so it is difficult to address this question directly. Perhaps future research will provide more evidence regarding what pre-Late Mississippian peoples were subsisting on in the absence of shellfish.

Long-term Demographic Changes

Attempting to reconstruct past demographic trends is a perennial goal within archaeology (Hassan, 1978; Milner and Oliver, 1999; Cobb and Butler, 2002; Kowalewski, 2003; Bandy, 2004; Kintigh, Glowacki, and Huntley, 2004; Osborne, 2004). Quantity of temporally sensitive objects, such as ceramics, is a common approach, which is not without its dangers. Of primary concern is whether ceramics were used in similar manners throughout the study’s temporal and spatial boundaries. This is of concern in all time periods, but perhaps even more so during the Late Archaic. Ceramics were first constructed during the Late Archaic and the archaeological record suggests that substantial populations did not use ceramics (Sassaman, 1993a). Research also suggests that hunter-gatherer groups who were engaged in pottery production, such as some of the Late Archaic peoples in coastal Georgia, produce fewer vessels per individual than agricultural peoples (Eerkens, Neff, and Glascock, 2002). Finally, we also know very little regarding how and where pottery was used and discarded during the Late Archaic. While we often assume that pottery was commonly used as daily cooking containers, it has been suggested that early pottery served a very particular symbolic function and was used in relatively limited social contexts (Hayden, 1995b; Rice, 1999). With these concerns in mind, a comparison of the relative frequency of ceramics is presented, along with potential demographic interpretations.

As noted previously in this chapter, the Late Archaic presence within the SLAP study area is ephemeral. Largely limited to several sites in the northern section of the surveyed area, the Late Archaic landscape would appear to be lightly occupied. With the emergence of the Woodland and Refuge/Deptford ceramics, the number of components increases and begins to be found further into the southern sections of the study area. However, these components are frequently defined by small numbers of ceramics, and it is very rare to find a significant concentration of Refuge/Deptford ceramics.

This is in direct contrast to the later grog-tempered ceramics, which are found in well-delineated areas in which they often make up the majority of the artifactual assemblage. These concentrations are then bounded by wide areas in which no contemporary remains were recovered. This concentration of grog-tempered ceramics in well-defined locales surrounded by “empty” space is suggestive of a consolidation of populations around dedicated settlement areas. A similar conclusion was drawn by Charles Pearson on Ossabaw Island based on a centralization of material remains from St. Catherines/Wilmington time periods (Pearson, 2001: 35).

Further research into the grog-tempered sites already encountered and additional survey work are needed to first confirm the apparent pattern of residential nucleation as well as pursue theories regarding its cause.

The distribution of grog-tempered ceramics also suggests that there is a great deal of continuity in landscape usage between peoples who made St. Catherines and Wilmington ceramics. In almost every context, the two types occur in close proximity. Currently, our dataset is too small to draw any conclusions regarding the cause or effect of such apparent nucleation and stability within and between these two time periods.

As noted earlier in this chapter, Savannah pottery may not correlate with a unique time period. Nonetheless, there is a significant number of Savannah sherds within the SLAP collection (N = 71), especially if the sherds were either a secondary ceramic type used in conjunction with other types, or if they date to a very small time period between grog-tempered and later Irene ceramics. The overall landscape usage seen within the distribution of Savannah ceramics is similar to that found with grog-tempered ceramics in terms of location but the Savannah ceramics are often found in more widespread, smaller concentrations, perhaps suggesting a dispersal of population from the very limited areas utilized previously.

The wide dispersal of Irene ceramics could be seen as a continuation of the redistribution of people across the landscape. Irene ceramics are by far the most common item found within this project and are often found in locations with no signs of previous usage, such as portions of the interior of the study area as well as one of the marsh islands. The Late Mississippian landscape (as defined by the distribution of Irene ceramics) was one in which new areas were clearly being utilized, but it is also a time of intensification of usage of areas that had been occupied previously.

As noted earlier in this chapter, at the onset of the Late Mississippian, and the beginnings of Irene pottery, shellfish began to be deposited in numerous middens within the SLAP study area. It is unclear what caused this shift toward a greater utilization of shellfish, but most likely, it is related to the general increase in population along the coast during the Late Mississippian. The dramatic increase in the number of Irene ceramics found in the SLAP study is mirrored by similar increases on nearby barrier (Pearson, 1979a, 1980, 2001; Thomas, 2008: 1035–1037) and marsh islands (Thompson and Turck, 2010; Napolitano, chap. 8, this vol.) and across coastal Georgia (Thompson and Turck, 2009). Generally, this increase in ceramics is thought to relate to an increased population during this time period (Thomas, 2008: Thompson and Turck, 2009). Increasing populations have numerous social repercussions, one of which is the increasing difficulty in acquiring highly valued food and finding desirable living space. The archaeological record from SLAP shows that during the Late Mississippian, there was a dramatic increase in usage of areas that had largely been left vacant. It seems likely that these areas were not used previously because they were thought to be less amenable to settlement, but as populations increased and the most desired locales were filled, these secondary locales began to be utilized. Likewise, diet breadth models suggest that as higher-ranking resources become less available, less valued resources enter the diet (Winterhalder, 2001). As noted earlier in this chapter, shellfish are often ranked very low in terms of caloric returns per hour of labor and were largely ignored as a food in the SLAP study area until the Late Mississippian. With an increase in population, high-ranking foods would likely become rarer, or were perhaps controlled and consumed by a limited portion of the population. In either case, accessibility of highly ranked and valued living locations and food resources appears to drop at the onset of the Late Mississippian not just within the study area, but also on the nearby barrier islands (Thomas, 2008).

CONCLUSIONS

As noted at the beginning of this chapter, this project is based on a single field season of research and has only begun to scrape the surface of the archaeological record. That being said, through the application of an STP survey, in combination with GIS applications and LiDAR data, several interesting patterns are apparent within the SLAP data that would appear to deserve further research. A wide subregional approach is suggested in which numerous geographic zones, including inland areas, coastal zones, and marsh and barrier islands, are seen not as separate social spheres bounded by impenetrable barriers, but instead as deeply interconnected portions of the landscape with numerous layers of relation between them. Environmental shifts along the coast can have broad social repercussions for more inland areas, as the analysis of the Archaic–Woodland transition suggests. A broad comparison within subregions also allows the recognition of anomalous results, such as the general lack of shell middens predating the Late Mississippian within the SLAP study area. The coastal Southeast, in particular the Georgia coast, is experiencing a revitalization in terms of archaeological research (see Thompson and Worth, 2011), as indicated by this volume, and shows remarkable promise for transcending geographical boundaries and attaining a deeper understanding of the social landscapes of past peoples.

Figure 9.1. SLAP study area.

Figure 9.2. Section 6 survey area.

Figure 9.3. LiDAR data showing topographically visible historic period features (red = high elevation, blue = low).

Figure 9.4. LiDAR data of study area.

Figure 9.5. Site locations (9Li1929 removed from map by request of the land owners).

Figure 9.6. Location of Late Archaic occupations.

Figure 9.7. Location of Early-Middle Woodland occupations.

Figure 9.8. Location of grog-tempered ceramics.

Figure 9.9. Location of Savannah occupations.

Figure 9.10. Location of Irene occupations.

Figure 9.11. LiDAR data for 9Li1935.

Figure 9.12. Overview of nearby studies.

TABLE 9.1

Shovel Test Pit Results from SLAP Survey

Survey Area

STP (no.)

Pottery (%)

Shell (%)

Both (%)

Sterile (%)

Tier 1 – Marsh line

827

28.17

5.07

7.9

58.86

Tier 2 – Interior

323

8.05

0

0

91.95

Tier 3 – Marsh Island

97

3.09

1.03

0

95.88

TOTAL

1247

21

3.44

5.3

70.26

TABLE 9.2. Shovel Test Pit Ceramic Count and Weight

(does not include untypable pottery, N = 22)

Ceramic type

Count

Count (%)

Weight (g)

Weight (%)

Positive STPs

Positive STPs (%)

St. Simons

6

.9

35.96

1.2

3

1

Refuge/Deptford

105

15.5

556.203

18.4

76

27.5

Refuge

14

–

62.1

–

12

–

Deptford

36

–

289.485

–

27

–

Unknown grit

55

–

204.618

–

40

–

Grog-Tempered

192

28.3

703.673

23.3

91

33

Wilmington

20

–

65.013

–

15

–

St. Catherines

94

–

363.687

–

60

–

Walthour

3

–

35.8

–

3

–

Unknown grog

75

–

239.173

–

41

–

Savannah

71

10.4

270.618

8.9

45

16.3

Irene

305

44.9

1456.231

48.2

153

55.4

TOTAL

679

–

3022.685

–

276

–

TABLE 9.3. Archaeological Sites and Their Attendant Components from SLAP Survey

Site Number

Site Size

Distance to Water (m)

Elevation (m)

Presence of Shell - Time Period Association

Primary (secondary components)

9Li1914

Medium

48

5.1

Yes - Irene

Irene

9Li1915

Large

23

2.2

Yes - Irene

Irene, Savannah (St. Catherines–Wilmington)

9Li1916

Medium

52

4.5

Yes - Irene

Irene

9Li1917

Small

24

3.6

No

Refuge-Deptford

9Li1918

Large

19

2.5

Yes - Historic

Irene (Refuge-Deptford)

9Li1919

Large

22

2.2

Yes - Irene and St. Catherines-Wilmington

Irene, St. Catherines–Wilmington, Refuge-Deptford (Savannah, St. Simons)

9Li1920

Large

78

3.1

Yes - Historic and Irene

Irene, Refuge-Deptford

9Li1921

Medium

26

2.5

No

Savannah (Irene, Deptford)

9Li1922

Large

52

3.5

Yes - Irene

St. Catherines, Irene, Historic (Wilmington, Savannah)

9Li1923

Small

21

3

No

Irene

9Li1924

Small

86

3.2

No

Irene

9Li1925

Large

21

3

Yes - Irene and Refuge-Deptford

Irene (Refuge-Deptford, St. Catherines–Wilmington)

9Li1926

Medium

126

4.1

No

St. Catherines–Wilmington

9Li1927

Small

12

3.5

Yes - Irene

Refuge-Deptford, Irene

9Li1928

Small

164

3.5

No

Historic

9Li1929

Medium

141

4.2

No

Unknown

9Li1930

Small

8

0.8

Yes - Irene

Irene

9Li1931

Medium

18

1.5

Yes - Irene

Irene (Historic)

9Li1932

Large

46

1.8

Yes - Historic

Irene, Historic

9Li1933

Large

41

4.1

No

Irene, Historic (St. Catherines–Wilmington, Savannah)

9Li1934

Small

6

1.6

No

Irene, Historic

9Li1935

Medium

72

3.5

No

St. Catherines–Wilmington (Irene)

9Li1936

Medium

31

1.9

No

St. Catherines–Wilmington

9Li1937

Small

456

4.1

No

Historic

CHAPTER 10: A PALEOECONOMIC MODEL OF THE GEORGIA COAST (4500–300 b.p.)

Thomas G. Whitley

INTRODUCTION

The study presented here is aimed at describing and analyzing the collection, storage, trade, and consumption of faunal and floral resources in the Georgia coastal region between 4500 and 300 years b.p. Its application is to the period prior to full European colonization (i.e., pre-1733) and refers specifically to Native American economic systems up through the Spanish Period, after which Native American groups were effectively removed from the coastal zone. The post-Spanish historic period is not included because comparing colonial and preexisting strategies may be inappropriate since new food sources and preferences were brought in, and the native ones were no longer relied upon. On the other end of the spectrum, prior to around 4500 b.p., modern sea level had not stabilized (although there is considerable debate on local sea level before 1500 b.p.—see the numerous discussion points in Thomas and Sanger, 2010, especially) and our knowledge of some of the baseline environmental variables, upon which this analysis relies, is fairly incomplete. It may be possible to recreate periods of lower shoreline by using bathymetry as a proxy for former topography, however the more recent Holocene barrier islands have fundamentally altered what that topography was, and geological reconstructions of the paleoshorelines are not currently sufficient to extend this analysis any earlier than 4500 b.p.

Because this study provides a theoretical and methodological framework, as well as simulations of different spatial surfaces, it is a model of past systems, not merely an analysis of them. The theoretical underpinnings for this derive from behavioral ecology; most notably from the combination of Optimal Foraging Theory (MacArthur and Pianka, 1966; and Emlen, 1966) and Central Place Theory (Christaller, 1933) known as Central Place Foraging (Orians and Pearson, 1979; Stephens and Krebs, 1986) and particularly its applications within archaeology (e.g., Simms, 1987; Jones and Madsen, 1989; Metcalfe and Barlow, 1992; Kelly, 1995; Zeanah, 1996; Bettinger, Malhi, and McCarthy, 1997; Bird, 1997; Grayson and Cannon, 1999; Winterhalder and Kennett, 2006); and especially the recent research in coastal Georgia (e.g., Thomas, 2008; Thomas and Sanger, 2010; Reitz et al., 2010). Additionally, theoretical studies such as the diet breadth model (Hames and Vickers, 1982; O’Connell and Hawkes, 1984; Winterhalder, 1987; Smith, 1991; and Grayson and Delpech, 1998) and Prospect Theory (Kahneman and Tversky, 1979; Tversky and Kahneman, 1992; Wakker, Timmermans, and Machielse, 2003) play a large role in driving the assumptions of this study. A more complete discussion of the theoretical basis for this is provided in Whitley (n.d.). The focus here is primarily to provide an overview of the methods involved and a presentation of the interpretive results.

Initially, the primary concern of any attempt at model building would be to find a standard unit of measure by which accurate comparisons could be derived. In many contemporary economic models, the unit of measure may be a monetary standard corrected for inflation or by exchange rate. In archaeological studies of prehistoric economies there is often no attempt made at extracting a standard unit of measure because the focus is usually on interpreting the sociopolitical relationships between people or groups, which is rarely reducible to anything more than broad generalizations. Typically the validation, or support, for such a theory of prehistoric economics will be based on the presence or absence of exotic, or prestige, goods or some other evidence for social stratification (such as monumental architecture or “elite” burials) with little understanding of what those items may have meant in terms of the specific energy cost to acquire, build, trade, or consume them.

This analysis is explicitly focused on understanding the relative energy costs of subsistence activities, and as such must use a standard unit of measure for nutritional energy: calories, or more properly, kilocalories (kcal—the energy needed to increase the temperature of 1 kg of water by 1°C). This is not to presume that prehistoric people used or understood the concept of calories, or that all food sources were treated only with respect to the quantity, or even the quality, of calories they provided. Obviously some foods were selected over others for reasons of personal or cultural preference. But it does assume that prehistoric people were able to make choices based on a relative understanding of the amount of energy, or nutrition, to be acquired from any particular source, and they were able to maximize their caloric benefit, dietary sufficiency, storage, and trade potential. Moreover, they were able to conceptualize, and predict, the spatial distribution of resources in the areas of their greatest familiarity. The model presented here is a digital reconstruction of how such knowledge was likely conceived of, and used, by prehistoric foragers.

On some level, this is also an exploratory analysis, so there is no attempt made to definitively address specific sociopolitical perspectives, even if they have been long accepted in the region. Rather, the model is designed to provide some different perspectives on the paleoeconomy of the Georgia coast, and may be interpreted in different ways or for different purposes. Because the concern is on subsistence, the model is at its heart a spatial analysis. This can only be carried out within a GIS framework—a representative spatial manifold with consistent geographic limits.

THE STUDY AREA

The study area includes the six coastal counties of Georgia, plus the next five immediately inland (fig. 10.1). This area is flat, wet, and heavily forested, and has probably been so for the last 10,000 years or more—or at least as far back as the extent of this model. The elevation ranges from mean modern sea level to no more than 56 m (183 ft) above mean sea level (amsl) at a point around 100 km inland. Steep slopes exist almost entirely along very narrow eroded river bluffs, and always occur as small breaks in elevation. Much more gradual slopes exist as wide, low interriverine ridges and particularly along the ridgelines formed by the remnants of Pleistocene shorelines and barrier islands (the Silver Bluff, Princess Anne, Pamlico, Talbot, Penholoway, and Wicomico shoreline complexes). There are currently at least 7027 known archaeological sites recorded within the terrestrial portion of the study area (GASF, 2011), and they represent more than 10,000 years of occupation.

Although the study area covers almost 1.9 million ha (4,669,484 acres), more than 1 million ha of it (about 57%) are marsh or wetlands. The named soil types are quite numerous, yet are very similar and tend toward either a very sandy or saturated clay texture. They are typically poorly drained in low elevations and excessively or well drained in the slightly higher ones. Historically, old growth live oak and hickory forests covered the higher, sandy elevations of the ancient and now land-locked Pleistocene barrier islands and former shorelines. Forests also occurred along the coast itself, as well as along dry bluffs overlooking salt marsh or rivers. In the interior of the mainland and larger barrier islands, longleaf, slash, and loblolly pine, along with cypress, dominated the wetter marshes, and expanses of low interriverine ridges. Today, modern logging has changed most of the upland climax growth forest (which would have had a fairly open pinegrass understory) to a denser scrub understory with mixed secondary or maintained evergreen and deciduous forest. Wetlands have remained largely unaffected, with the exception of the 18th- to 19th-century rice fields (now brackish marsh) within the narrow tidal rice agriculture zone, and cypress logging in the late 19th to early 20th centuries, largely in the Okeefenokee and Altamaha basins.

Along the coastal estuaries, protected by the barrier islands, lie vast expanses of salt marsh with shallow muddy tidal flats and emergent grasses. These brackish wetlands are often bordered immediately by mixed oak, pine, and hickory forest along with thick palmettos and other scrub. The eastern sides of the barrier islands typically exhibit long stretches of narrow, sandy beaches backed by dunes, scrubby deciduous trees, and sea oats. The ends of the islands give way to the fast-moving and variable tides at the mouths of the wide, slow flowing rivers (the Savannah, Ogeechee, Altamaha, Newport, Satilla, and St. Marys rivers) which traveled several hundred kilometers from the Piedmont or other parts of the Georgia Coastal Plain to empty into the Atlantic. The still visible historic modifications to these native landscapes include the former rice fields and logging canals in the wetlands, plus farms, roadways, small communities, a few urbanized areas, and military fortifications in the uplands or on islands.

This environment is not at all conducive to building a correlative (i.e., regression-based) archaeological predictive model. The absence of steep slopes entirely and the presence of fresh water almost everywhere make it impossible to use the two most common predictive variables (slope and distance to water) as a means to limit our expected distribution of settlement choice. The use of soil types in their raw form also does not strongly limit site placement because archaeological sites from all periods are known from virtually all soils that are not currently underwater.

Though there is a large sample of known sites, correlative analysis does not work for any portion of that population with these traditional environmental variables. The only generally accepted method to defining archaeological probability areas has been to use an intuitive model built upon the physical limitations of not being able to survey areas underwater with terrestrial methods (i.e., surveyable = high potential and unsurveyable = low potential). Consequently, the Coastal Plain has been largely thought of as predictably homogeneous with respect to prehistoric settlement choice; one place is environmentally almost as good as any other. However, when you consider that the key characteristics of moisture, salinity, water depth, cover, vegetation type, soil texture, and soil drainage work together as modifiers, or attractors, to the distribution of forage species, you begin to see the actual diversity of habitats that is present and can provide the framework within which an explanatory paleoeconomic model operates.

THE HABITAT MODEL (HM)

If we recognize that human foraging targets have specific requirements for food, shelter, water, and protection from predators, then we should be able to build weighted formulaic representations of the combination of environmental variables that are important to them (i.e., a predicted habitat model for each one). Moreover, individual formulas may change with the seasons as different species grow, reproduce, and protect their young in different ways throughout the year. The first step in modeling habitats is to define the categories of food items that were being sought prehistorically. For this analysis, I chose to define 37 forage categories (table 10.1); based largely on the same categories defined by Thomas (2008). Some of these categories are individual species (such as “white-tailed deer”) while others are combinations of numerous species based on family or genus groupings (such as “freshwater turtles”), or size/habitat limitations (such as “large saltwater fish”). These groupings include both wild faunal and floral resources, as well as domesticated (or semidomesticated) species.

The purpose of grouping foraging targets in this way was to try and reproduce as closely as possible the likely manner in which prehistoric individuals may have conceptualized food categories. This is as opposed to the way we would organize them—by species. For example, there are 27 species of freshwater turtle common to the Georgia coast (GDNR, 2010), and we could define habitats for each of them. However, prehistoric foragers would not likely have distinguished between them as distinctive populations, and may have considered them all more or less the same; they would have defined a habitat for the group rather than each individual species. The forage categories defined for this analysis have taken that into consideration, or at least made some reasonable assumptions about that. Additionally, the categories include several groups that were probably not frequent targets of foraging, but could have been supplemental, opportunistic, or even starvation foods, so as to add a range of different kinds of caloric sources to the analysis. Examples of these may be reptiles, amphibians, sea turtle eggs, and cattails. Notably, this is also not an exhaustive list of food sources. There are species or groups of them that may have been consumed at times (or even commonly), but are not included in the analysis, most notably manatees, coyotes, Florida panthers, and birds of prey, among others. But these tend to be species with different modern habitats, or for whom we do not know the extent of their distribution prehistorically, or that were probably very infrequently selected as part of the diet anyway, even if they were hunted for other reasons.

Ultimately, the goal was to be able to develop a GIS model surface for each forage category, for each month of the year that depicted the habitat suitability on a range of 0 to 1, where 0 represents no potential habitat and 1 represents the best potential habitat. All map units would have a decimal value in between that indicates the potential habitat for that forage category, at the highest resolution possible. To do this, the baseline variables that comprise the elements of habitat needed to be identified and standardized. This is essentially a predictive habitat model for each species for each month based on existing digitized environmental data.

The state of Georgia has already developed a series of habitat models for almost all of the species included in these forage categories (NARSAL, 2010). However, that series of models has some severe drawbacks for this analysis. First, it is strictly a dichotomous model. The habitat values are the equivalent of 0 and 1, rather than a decimal value between 0 and 1. In other words, you can assess whether habitat is present or absent but not the strength of that assessment. Second, the habitat assessment itself is not based on an explicit formula, but on collection records and generalized (typically unspecified) expert assessment for areas between collected specimens. This makes it hard to assess the likelihood of encountering a species in any given area, even when the habitat value is considered positive. Additionally, the resolution of the data is at 90 × 90 m map units (8100 m2; nearly a hectare)—too large to distinguish between many small stream areas, islands, hammocks, or other pockets of suitable habitat within larger expanses of unsuitable habitat.

For this analysis, the goal was to develop explicit formulas based on as many variables as possible, and with as high a resolution as possible. These formulas are behavioral models and are meant to include what a prehistoric forager could have conceptualized as attractors for the specific forage target she or he had in mind. The model’s limitations, though, are dependent upon the digital data available, and the ability to determine the presumed correlative relationships (especially as abstracted from modern data). There are several high-quality digital datasets available that proved invaluable for this:

(1) the U.S. Fish and Wildlife Service’s National Wetlands Inventory (NWI) maps,

(2) the Natural Resources Conservation Service’s Soils Survey Geographic (SSURGO) database,

(3) the U.S. Geological Survey’s National Elevation Dataset (NED),

(4) the National Oceanic and Atmospheric Administration’s Hydrographic Survey Dataset (HSD),

(5) the Georgia Department of Natural Resources’ Land Use/Land Cover (LULC) data, and

(6) the U.S. Environmental Protection Agency’s Level 4 Ecoregions (L4E) data.

The NWI and SSURGO datasets are polygon layers developed from a mixture of ground surveys and aerial imagery analysis. The NED dataset is a raster dataset with a pixel size of 30 × 30 m based on a seamless, and corrected, mosaic of smaller quadrangle-based digital elevation models derived from aerial imagery analysis and satellite data. The HSD is a point dataset of depth readings from more than 120 years of ship-based hydrographic surveys, using different methods and techniques. The LULC dataset is a raster surface based on aerial and satellite imagery analysis. The L4E dataset is a polygon layer based on evaluation of many of the other datasets and additional biological or environmental information.

Some elements were extracted from each of these variables to define secondary or “derived” datasets useful for this analysis. A detailed discussion of how each of the derived datasets was developed is presented in appendix 10.1. These secondary variables are the ones to which habitat is keyed, and the ones upon which the predictive formulas are based. They include:

Water availability (WA)—typical permanence of water

Water salinity (WS)—average percent of salinity

Soil texture (ST)—average grain size for the soil type

Soil fertility (SF)—mean soil productivity

Vegetation density (VD)—typical density regardless of vegetation type

Vegetation type (VT)—two variables:

VT1—the proportion of deciduous trees

in general

VT2—the proportion of live oaks

Water depth (WD)—three variables:

WD1—shallow water

WD2—medium depth water

WD3—deep water

Elevation zone (EZ)—five variables:

EZ1—salt marsh/sea level

EZ2—river bluff/shore margin

EZ3—Silver Bluff/Princess Anne

formations

EZ4—Talbot/Penholoway formations

EZ5—Trail Ridge/Wicomico formations

Ultimately, 15 derived environmental variables were created. Figures 10.2 through 10.5 illustrate close-up views of some of these datasets. They are all standardized as ranging between 0 and 1, and they are tied to natural limits at either end (WA, WS, ST, SF, VD, VT1, and VT2) or are represented by a normal curve centered on a target value with ends at ±4 m from the target (WD1, WD2, WD3, EZ1, EZ2, EZ3, EZ4, and EZ5). The predictive habitat formulas were based on both qualitative and quantitative assessments of preference for each of the modeled derived datasets extracted from Thomas (2008), Smith (1992), Reitz et al. (2010), NARSAL (2010), GDNR (2010), and other resources, such as the U.S. Fish and Wildlife Services Habitat Suitability Index Model Series (http://el.erdc.usace.army.mil/emrrp/emris/emrishelp3/list_of_habitat_suitability_index_hsi_models_pac.htm). Formulas were generated for each environmental variable, for each month of the year (table 10.2). A brief overview of the methods by which the modeled habitat surfaces were created is presented in appendix 10.1.

The results of the HM analysis are a series of 444 individual GIS surfaces (37 forage categories * 12 months), each of which covers all 4,669,484 acres with a resolution of 30 × 30 m (900 m2). Each of the 20,996,530 map units has a decimal value ranging between 0 and 1, which represents the predicted habitat suitability for each forage category for each month. Figures 10.6–10.8 are detailed views of several of the HM surfaces. Some habitats do not change monthly even when their productivity might, such as the plant forage categories. Chenopod habitat, for example, is always chenopod habitat throughout the year. However, available calories from chenopods may differ during different months based on their stage of development. This is the domain of the Available Caloric Model (ACM).

THE AVAILABLE CALORIC MODEL (ACM)

To transform the Habitat Model surfaces into caloric expressions, a series of additional variables were assessed (table 10.3), including ones based on population size, reproduction rates, average body mass, group size and range, and usable meat weights. All of these assessments were based on the same sources of information as the habitat preferences, or were projected as reasonable quantitative estimates where no specific data, or only qualitative data, were available. It should be noted again that the framework of this GIS model is not dependent upon the initial values chosen and inserting better, or alternative, data is always possible when it becomes available. The following were defined:

(1) Population—Each forage category was assessed for three population estimates: the total population in the state, the total in the study area, and the proportion in the study area. Because statewide population estimates are not commonly available for some species, a reasonable estimate was made for some based on density values by acreage (averaged from as many sources as possible and as close to the study area as possible), or from discussions in the biological or archaeological literature. Since the study area represents about 12% of the state, any forage category that occurs relatively evenly statewide (e.g., raccoon) was calculated to have about 12% of its statewide population represented in the study area. For any forage category that is limited to the Coastal Plain (e.g., alligator), its study area population was estimated to be around 50% of its total statewide population, because the study area represents about 50% of the Coastal Plain. The study area represents about 45% of the freshwater habitat statewide (excluding all modern reservoirs), so freshwater forage categories were set at 45%. Since all saltwater habitats within the state are included in the study area, saltwater forage categories have the same statewide and study area population estimates (100%).

Most of the statewide and study area population estimates are based on modern values (and GDNR, 2010, proved to be the most valuable source of information). However, several forage categories were changed to reflect probable higher or lower prehistoric populations. For example, the modern statewide deer population is approximately 1.2 million, but a somewhat higher population is probable prehistorically, so the estimate was made of ~250,000 in the study area, or just over 2 million statewide (an average of about 20 acres of nonoverlapping habitat per deer—well within modern estimates for the region; cf. Short, 1986). Likewise, the black bear population is currently estimated to be around 1500 in the study area. That was increased to ~4000 as a prehistoric estimate. This estimate is also reasonable, averaging almost 2 nonoverlapping square miles per bear (cf. Rogers and Allen, 1987). For any of the plant categories, or resources gathered in bulk (i.e., shellfish and sea turtle eggs) statewide or study area population estimates were excluded, as caloric values were based on a per kilogram assessment.

(2) Reproduction—Five reproduction variables were recorded: full birth/harvest range (in months), peak birth/harvest period, average number of offspring, average years to reach maturity, and survival rate (assuming a stable population). The first four variables were based on information available in the biological literature and particularly those sources already cited above. The fifth variable (survival rate) was calculated by dividing two by the average number of offspring, assuming that a stable population is one in which the reproducing pair of individuals ultimately replace only themselves in the population. All other offspring are eliminated from the population by predation, disease, or some other demise, without reproducing. Obviously, populations do not always function like this in real life; instead they go through cycles of spikes and crashes. However, over the long run, the assumption here is that at any given time from 4500 to 300 b.p., forage category populations are more or less internally stable. For those forage categories assessed on a per kilogram basis, only the first two variables (birth/harvest range and peak) are applicable.

(3) Resilience—Forage category resilience has a rather vague definition. Within the field of ecology, resilience was introduced as a measure of ecosystems to describe how quickly they bounce back from disturbance (Holling, 1973; Gunderson, 2000), which is usually from human-induced causes. Resilience has also been thought of as how much disturbance an ecosystem is able to absorb and still remain unaffected (Walker et al., 2004). Within this modeled context, resilience on the part of a single species or forage category is thought of as a relative assessment of how sensitive the population is to external stress from hunting or collection. To measure this, a resilience formula was developed:

where I = the number of individuals per 100 ha, S = the survival % rate, M = the length of time (in years) to reach maturity, O = the number of offspring per year, and P = 100% plus the percentage of yearly influx from external populations (for migratory and semimigratory species). A resilience (R) value was calculated for each forage category for each month; this is assuming that some species are more vulnerable during certain times of the year because of clustering or low population densities (table 10.4). A high R value represents populations that are generally not easily impacted by external pressures. These are typically high population, short maturation species, even those with low survival rates. The most resilient forage categories are very small saltwater fish (Rµ = 68.68), very small freshwater fish (Rµ = 49.30), and amphibians (Rµ = 43.57). The least resilient ones were low population, long maturation ones such as sea turtles (Rµ = 0.49), black bears (Rµ = 0.67), and alligators (Rµ = 1.35). Notably, this resilience measure does not account for sensitivity to drought or incidences of mass die-offs (such as from red tides, or chemical poisoning).

A proportional version of this resilience measure was also calculated as the specific R value divided by the maximum R value for all forage categories. Resilience and proportional resilience were used to help fine tune the HM maps (to derive the exponential multipliers), and as a means of interpreting some of the available and returned caloric assessments of foraging radii (used in the resilience maximums for estimating sustainable population). For bulk collected species the calculated resilience measure is not applicable and was not used; if a proportional resilience measure was required for any bulk species calculations, the average of all measures was used.

(4) Average Size—Average body mass was assessed for three categories: maximum (typically males), medium (typically females), and minimum (typically juveniles). These values were most readily available in pounds, but were also calculated in kilograms. Where possible, the average weights were taken from the Coastal Plain region and not elsewhere. For bulk forage items, a single value of 1 kg (2.2 lb) was used.

(5) Group and Range Size—Because some of the available calories are based on the clustering of individuals (e.g., some species can be gathered in multiple units at the same time), it was important to gather information regarding typical group size, and their effective foraging ranges. Three variables were assessed; average group size (as a range), and the maximum and minimum foraging ranges of the species. These estimates were all based on the available literature, or are reasonable estimates based on similar species.

(6) Caloric Content—The final category of assessed variables relates to their inherent caloric value. To record this, two assessments were made: the useable proportion of the animal (e.g., meat weight divided by body weight), and the number of calories per kilogram. This information is readily available from the sources already cited, and also online at several game nutritional calculators (e.g., http://www.gunnersden.com/index.htm.hunting-game-nutrition-value.html).

For the per kilogram forage categories, an estimate of kilograms per acre was calculated directly based on the available literature (primarily Smith, 1992, and Thomas, 2008), and a baseline established at the highest productivity that could be expected given an appropriate fallow cycle. For example, the assessment for maize assumes the highest density of maize one would expect to encounter for full-scale agriculture in the best potential habitat, but then divided by five (for a five-year fallow cycle; derived from two or three years of harvest within a 10+ year period; Thomas, 2008: 198). This assumes that at any given time, only one-fifth of the maize habitat would be in production as a maximum. Any count of available calories would then be based on the HM value multiplied by that estimate. This is further modified by seasonal availability and growth cycle and also corrected for domesticated species as a function of their date of introduction (discussed further later).

For the other categories, the population density is calculated by first summing the total values within the study area of each of the HM surfaces (this is the value of each 30 m map unit added together for the entire ~4 million acres) and dividing those values by the total number of 30 m map units in the study area. This provides the proportion of habitat that exists within the study area for any given forage category for each month. Then, the assumption is that the total population estimate within the study area must fall within that proportion of habitat. So a population density is then calculated by dividing the population estimate by that acreage, or ultimately their map units. The result is the estimated number of individuals one would expect to find in any given map unit for each forage category, for each month.

However, we know that the population does not directly translate into kilograms because there are different ratios of males to females to juveniles, plus there are population flows into, or out from, the project area at different times of the year for some species. To address this, the reproduction rate and group size values are used to define specific gender ratios for each month. The body mass statistics are then multiplied by those ratios to produce an average kilogram value per individual per month for each forage category. The same ratios are used to calculate a clustering factor—the number of individuals within an average group for that month divided by the minimum number of individuals in a group for the year. Additionally, a population multiplier was used for some specific categories that change drastically when populations arrive from outside the study area. (This is most important for migratory waterfowl, wading birds, sea turtles, and larger saltwater fish.)

The final number of calories one would expect to find in a given map unit is then based on either (1) the estimated population density modified by the clustering factor, and the population modifier, times the average useable kilogram, or (2) the bulk estimates from the baseline maximums. Table 10.5 illustrates the maximum calculated available calories by forage category and month, assuming climatic conditions similar to today and a stable (modern) sea level. The caloric values were then multiplied by each of the appropriate HM surfaces. The result is the transformation of each of the 444 surfaces into an expression of the ACM. The ACM is, in essence, a representation of the maximum exploitable ecological landscape by species and month.

One advantage of this simplest form of the ACM is its predictive capacity. Paleoeconomic modeling is essentially an analysis on the local scale, and as such involves modifications to the ACM based on local travel and transport costs, foraging radii, and technological capacities; all of which relate to specific known site locations and/or temporal periods. However, a regional scale predictive model is generally going to be applied to an unsurveyed area, and as such there is little information regarding specific sites. Traditionally, predictive models have used simple environmental variables as correlative proxies for identifying “rules” of site placement with varying success. (See Verhagen and Whitley, 2011, for a more detailed discussion about theoretical perspectives on predictive modeling that relate specifically to this study.) The ACM provides a new suite of variables that reflect resource procurement directly. The three most commonly used traditional predictive variables (distance to water, slope, and soil type) are generalized limitations based on broad assumptions about human behavior, namely that people need to be close to a source of drinking water, that people are uncomfortable (or expend an excessive amount of energy) living on steep slopes, and that certain soil types are better for agriculture. These “rules” may be broadly applicable and are occasionally useful for prediction, but they are not behaviorally explanatory; they are least common denominators. With the ACM, it is possible to develop predictive models keyed toward individual behavioral tasks, such as hunting, fishing, or collecting specific foraging targets, processing resources, or just for habitation sites in general. One would expect to find habitation sites, for instance, in locales that provided access to the best combination of all resources; this would likely vary depending on the diet and the season.

Because the ACM represents a broad range from 4500 to 300 b.p., it does not currently incorporate any modifications from existing paleoclimatic models. However, to address the often dramatic changes in climate that can affect a species’ population, some consideration of existing paleoclimatic data should be possible. Cook and Krusic (2004), for example, provide an annual estimation of the Palmer Drought Severity Index (PDSI) values for North America. The use of PDSI data has added considerably to the interpretation of cultural developments in similar regions (e.g., Benson, Pauketat, and Cook, 2009; Nolan and Cook, 2010). Within the study area, there are three data points that correspond approximately to the north coastal area (80°W, 32.5°N), the south coastal area (82.5°W, 30°N), and the interior (82.5°W, 32.5°N). Data from these points were downloaded from the Internet (http://iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html). The data provided yearly PDSI estimates ranging from 300 to 1644 b.p. These data were placed into an Excel file and several additional calculations were made, including 3 year, 5 year, 10 year, 20 year, 50 year, and 100 year averages (based on ranges of yearly estimates preceding the data value—i.e., a 100 year average for 300 b.p. is the average of all yearly values from 400 to 300 b.p.). No values exist for the period prior to 1644 b.p., but Webb et al. (1998) suggest that the study area was approximately 20% wetter than modern conditions at 6000 b.p. Proportional representation of that increase was approximated for 4500 b.p. through 1644 b.p. in the Excel spreadsheet. These data are currently not included in the model because ACM and RCM estimates discussed in the following analyses are based on 100 year increments, and it is unlikely that a 100 year average would truly represent a realistic population modifier for any of the forage categories. However, at some point in the future, when estimates may be based on specific years, it may be appropriate to incorporate the PDSI index as a population modifier, perhaps in combination with the resilience measure, temperature models (e.g., NOAA, 2006), and/or sea level analyses (e.g., Tanner, 1991).

THE RETURNED CALORIC MODEL (RCM)

In the meantime, we know that there are limitations to how much of the available calories are actually “returnable” or otherwise useable to prehistoric humans. To be useful in understanding the economics of specific sites and regions, available calories need to be transformed into a model for returned calories (those calories that could actually be consumed, and the extraction of which historically affected human subsistence). To do this, a third model (the Returned Caloric Model) was created based on understanding the costs of acquiring, processing, and storing calories.

In general, we can assume that proximity and technological innovation are the primary means by which acquisition, processing, and storage costs are reduced. Thomas (2008) provides a very detailed discussion of processing time and calories consumed for most of these forage categories on the Georgia coast during the Late Prehistoric, and his proportional return values (as expressions of calories per hour of effort) were assumed as a baseline, given modifications for earlier time periods where somewhat inferior methods may have been employed in resource acquisition success, or processing (particularly for harvested plant species). Once again, methods employed in using these variables are not dependent upon the initial values chosen, and changing them may lead to additional insight regarding the costs of acquisition, processing, and storage not discussed here.

The effect of proximity on the costs of acquiring calories is directly applicable to the landscape. Principally, this is the travel cost to go from one’s location to the place at which the calories are gathered, and back to the location of processing, consumption, and/or storage. Budgeting the travel costs associated with subsistence is a basic underlying assumption of both Optimal Foraging Theory and Central Place Foraging. Those calories most easily acquired and consumed are those closest at hand. To address this, two friction surfaces were created: foot travel (terrestrial) and canoe travel (aquatic). These represent the only applicable methods of travel used in the region prehistorically. Figures 10.9 and 10.10 show detailed views of a portion of these two travel cost surfaces.

Each map unit was given a value based on the caloric cost of crossing it, i.e., travel friction. In highly dissected areas, travel friction would be a function primarily of slope and vegetation density. Because of the lack of terrain slope in coastal Georgia, travel costs are instead a function of vegetation density, water depth, the strengths of tidal, river, and ocean currents, and the firmness of the substrate. Each of these constraints was modeled from the baseline variables employed in the HM in a way that made it possible to estimate the number of calories that would be consumed (by one person carrying a load of less than 20 kg) to cross any given map unit in the study area by foot and/or by canoe. That range included a minimum cost for crossing an open 30 m map unit unimpeded by vegetation on foot at 2 kcal and 1 kcal by canoe over open slow water. The upper limits reached 20 kcal for swimming across 30 m of deep tidal water, or for portaging a small canoe through relatively dense vegetation. Calories burned in this way were estimated from online calorie counters (http://www.exrx.net/Calculators/Calories.html and http://www.nutristrategy.com/activitylist4.htm are two examples) using smallish male adult size and weight characteristics (assuming that modern values are somewhat higher than would be expected prehistorically).

From any given point, the accumulated calories over distance (i.e., cost distance) by either foot or canoe travel is a representation of the “fall off” of available calories. For example, if one collected a deer within 120 m of home, it would represent an expenditure of at least 16 kcal for one person to travel to that location and carry the processed deer back. If that same deer were collected at 5 km away from the home site, it would have required more time traveling between the kill/processing point and back. The investment at 5 km would have been at least 667 kcal, or more if the terrain were difficult, sloping, or obstructed by vegetation. That expense is subtracted from the potential caloric return and would represent a loss to individual or family consumption, trade, and even time spent doing other tasks.

Given that some species provide only a modest number of calories, while others much more so, the cost distance (i.e., foraging radius) at which it is no longer efficient to collect them would vary depending on their probable caloric return, ability to be gathered in quantity, dietary attractiveness, potential for other uses, and the current caloric or nutritional stress of the foragers. Similarly, the cost distance radius at which it is more efficient to process the collected resource rather than bring it back whole (i.e., processing radius) would also be a function of its weight and its processing time or difficulty. Thomas (2008) provides a very detailed discussion of the probable foraging and processing radii for many species or forage categories in the coastal Georgia region. In general, he finds that for most species, an effective one-way daily foraging radius of 450 kcal consumed (or around 5 km in his estimation) is likely (Thomas, 2008: fig 11.12). He also charts processing radii as a function of distance and categorical thresholds (Thomas, 2008: table 10.7). With a friction surface we can model the actual radius more precisely, as a function of individual foot or canoe travel, or as a representation of shared caloric costs (such as multiple person canoes).

Additionally, we need to consider that the success of any foraging activity is a function of perception and terrain familiarity. The cognitive map employed by the forager to help her/him collect a given resource is going to be most complete and accurate in areas that they most commonly frequent. Even though we may have a fairly complete and accurate GIS model of the terrain for many miles around the site, the prehistoric individual living there has only the cognitive perception of their daily terrestrial and aquatic foraging areas and perhaps some distance outward. The accuracy of that perception diminishes further away from their central place. As a result, there should be a corresponding decrease in foraging success as the forager transitions from the immediate familiarity of using repeatedly successful locations to making decisions “on the fly” with regard to unfamiliar terrain. This particular kind of falloff in caloric returns is probably most notable with fishing where the underwater (and hence not visible) terrain has a great effect on the success of foraging. Successful fishing spots are recognized only over a long period of repeated use.

In contrast, the nontravel costs of acquiring calories are not directly applicable to a GIS landscape, but they can be subtracted from the ACM nonetheless. These break down into three primary caloric expenditures: maintenance, harvesting, and processing. For this analysis, maintenance is assumed to be all activities related to preparing to acquire a resource, establishing/maintaining habitats, or planting crops. For example, collecting lithic raw materials, making projectile points, hafting, and resharpening points are all activities related to the maintenance of deer hunting (as well as hunting other species). Making fish traps or small mammal snares are examples of other maintenance tasks. Similarly, burning undergrowth may be an activity related to preparing maize fields, but also establishing deer habitat. Harvesting is used here to describe tasks related to the collection of the resource, specifically time spent waiting, tracking, and actually dispatching hunted or fished prey, or collecting shellfish, turtle eggs, or plant resources, etc. Processing is the act of reducing the item from its raw form to its useable form; e.g., butchering meat, shucking oysters, stripping the husks from maize, but also cooking and serving it.

The range of nontravel acquisition costs for each forage category was modeled first by assuming a standard foraging time of one day. The assumption was made that a range between 1600 and 2000 calories would represent minimum and maximum daily expenditures for one person. This range may not be truly representative of all prehistoric occupations in the region, but it seems reasonable as the initial model input. Estimations were made for the percentage of maintenance, harvesting, and processing activities for each forage category, that could be representative of the overall use of that resource. In other words, it is not assumed that one would spend one day collecting or processing any resource. Rather, given a year spent collecting any one resource, the estimated proportion of time spent maintaining, harvesting, and processing that resource was multiplied by both 1600 and 2000 calories to come up with standardized daily minimum and maximum caloric investment (table 10.6). Additionally, the number of kilograms of each resource that could be collected with that range of investment was estimated, along with the proportional retention of collected calories for periods of one day, one week, one month, six months, and one year. The retention numbers are an estimate of storage capacity and attrition due to caloric decay, not consumption.

Based on these variables, the initial estimates for transforming the available calories into returned calories were made. Return rates were calculated that expressed the range in caloric efficiency given daily brackets of 1600–2000 kcal expended. This was done for each forage category and for each month. To simulate a return rate for each 100 year increment between 4500 and 300 b.p., the assumption was made that efficiency generally increased, and that the least efficient rate was at the earlier end of the temporal bracket, while the most efficient was at the latter. To include increases in efficiency based on technological innovations, several of these were modeled:

(1) Hunting—innovations in hunting technology included the introduction of dart points (at around 4000 b.p.), increasing availability of multipurpose lithic tools (around 3000 b.p.), and the bow and arrow (at 1600 b.p.).

(2) Fishing—fishing technology improved with the adoption of fishing nets (around 3200 b.p.), fish weirs/traps (around 2500 b.p.), and seaworthy canoes (around 1400 b.p.).

(3) Collecting—changes in collecting efficiency were modeled with improved (ceramic) storage containers (around 3000 b.p.), grinding stones (around 2000 b.p.), and above-ground corn cribs (around 1000 b.p.).

The temporal points of introduction are based on well-known assemblage-related interpretations, or are inserted as reasonable estimates. A formula was generated that increased the rate of return on any forage category upward in a stepped fashion at the introduction of any technological innovation that was useful for it specifically. This model assured that the transitions were gradual, and the initial minimum/terminal maximum range was never exceeded. Additionally, the rate of return for domestic species was zeroed out for all periods prior to their introduction (around 3000 b.p.), but increased exponentially as they were adopted.

Ultimately, the RCM can be calculated as two separate values. The first is a caloric return based on multiplying the ACM value in any given cell by the appropriate return rate (using any specific year, or the mean across a range of years). This is an expression of the RCM that does not assume travel costs given that we are not talking about a specific site location. This version of the RCM is useful for both predictive and analytical purposes. Second is a caloric return tied to travel costs from a specific locale. This is the ACM times the return rate that also subtracts the cumulative cost distance from any given point. The first RCM value is applied in an Excel spreadsheet that allows one to insert any year between 4500 and 300 b.p. and the result is an estimate of the mean kcal per map unit using a baseline assumption that the HM value is 1. Table 10.7 is an example that represents the ACM (see table 10.5) modified for the year 1237 b.p. (chosen randomly). The second RCM value is assessed based on specific site locations and was calculated on 100 year increments using a comparative and a local scale analysis.

COMPARATIVE ANALYSIS

The comparative paleoeconomic analysis began with the collection of known site information. Of the 7027 known archaeological sites from the study area currently recorded in the Georgia Archaeological Site Files (GASF, 2011), 278 of them have been specifically identified as Native American “habitation” sites (this includes camps, villages, or farmsteads). Of these, 113 sites have temporal designations between Late Archaic and Protohistoric/Historic Indian. There are no doubt other known dated sites that were habitations, but are not recorded as such in the GASF. Likewise, there are known habitation sites that have not been given dates within the GASF, but this does not mean they are not datable; only that their site forms may be incomplete. They too are excluded from the comparative analysis. This is not an ideal situation; however, it is the only dataset currently available.

Cost distance evaluations were made from each of the 113 locations using both the foot travel and canoe travel friction surfaces individually and for the two surfaces combined. The individual surfaces assume that travel is either on foot or by canoe (not both), whereas the combined surface uses the lowest cost of either one. The combined cost essentially assumes that one would be able to canoe across a river and then gather resources by foot travel from there and still return to the habitation site by canoe. Polygon buffers were created at 450 kcal (for both aquatic and terrestrial friction) and at 900 kcal (just for aquatic friction). The 450 kcal buffers represent a one-way one-day foraging radius for one person, either on foot or in a canoe. The 900 kcal buffer represents a one-way one-day foraging radius for a two-person canoe.

Some of the 113 polygon buffers were rejected. The reason for this was twofold: First, ArcGIS was unable to calculate summaries for several sites because too many other foraging buffers overlapped them. This could have been corrected by rerunning the analysis with those sites separated, but it was not done in this analysis. Second, several sites were located close to the edge of the study area and their foraging radii were artificially severed by its boundary. It is very likely that a large portion of utilized landscape falls outside the study area for those sites, and thus they were rejected for this analysis due to that edge effect. In the end, there were 101 sites that contributed to this comparative analysis (appendix 10.2).

For each of these locations several values were calculated in ArcGIS using the zonal statistics and geometric calculation tools. This includes: a count of the total number of map units that fell within the 450 and 900 kcal buffers, the total and mean caloric friction costs, the acreage of buffered terrestrial and aquatic foraging habitats, and the total and mean habitat values within each buffer for each of the 444 GIS surfaces. From these numbers it was possible to calculate, for any site or combination of sites:

(1) Total ACM Calories—Calculated for each forage category and each month by multiplying the sum of all HM values for the map units within the buffer by the monthly ACM estimate for the chosen period of analysis. The combined buffers representing 450 kcal of foot travel and 900 kcal of canoe travel were used.

(2) Mean ACM Calories—Calculated for each forage category and each month by multiplying the mean of all HM values for the map units within the buffer by the monthly ACM estimate for the chosen period of analysis. The purpose of using the mean values was to provide a standardized comparison between sites with different size foraging buffers. The primary comparative analysis (with a few exceptions) was based on mean values per map unit.

(3) Mean RCM Calories—Calculated by multiplying the mean ACM value by the mean RCM return rate for the chosen period of analysis and also subtracting twice the sum of all friction values in the buffer. It is assumed that the minimum travel cost for collecting any resource would be twice the friction value of the map unit that contains it (i.e., crossing the map unit in two directions—coming from and going back to a habitation site). By subtracting the friction costs of all map units, number of mean RCM calories gives an estimation of the travel costs if all of the ACM calories were returned. This represents the number of calories one would expect to be returned in an average map unit within the selected site’s buffer. On the local level this is calculated using a cost distance evaluation.

(4) Mean Selective Calories—This is a model for how many of the returnable calories would actually have been preferred and what proportion is likely to have been selected for consumption. To estimate this, a generalized dietary model was used. This model uses all 37 forage categories and is pinned at either end by generalized proportional estimates based on Late Archaic and contact period faunal and floral assemblages. The values in between are calculated as exponential or logarithmic percentages of the difference between the end values. This dietary model is not intended to definitively represent an archaeological interpretation of the range in past diet; rather it is meant to provide a simulation that can be used to express an overall impression of the transition from Late Archaic to contact period diet as we currently understand it. It would be possible to use specific recovered faunal proportions as a model instead, but those data are not currently available for most of these sites, and the generalized dietary model was used as a proxy. If the monthly forage category’s RCM value represented a lower proportion of the total RCM calories than the proportion represented by the dietary model, then all of those calories were estimated to have been consumed. If the RCM calories represented a higher proportion, then the dietary estimate was assumed to be the consumed portion, while the rest was considered potential surplus. The basic function of this rule was to make the model of selective calories as proportionally close to the dietary model as possible given the conditions within the foraging areas of the site(s).

(5) Mean Potential Caloric Surplus—This was calculated by subtracting the mean selective calories from the mean RCM calories. This represents the portion of available calories that were not immediately consumed, but which could have been collected and stored for later consumption or for trade.

(6) Mean Retained Caloric Surplus—This was calculated using the one day, one week, one month, six months, and one year retention percentages developed for the RCM, and multiplying them by the mean potential caloric surplus. This is an expression of the falloff rate for those calories stored (or traded) rather than consumed immediately. These caloric values are applied to the appropriate period later than the month in which they were collected. In other words, the surplus calories become available at the modeled rate to calculate sustainable population estimates.

(7) Caloric Efficiency—Calculated by dividing the selective calories by the ACM calories; this gives a proportion of calories captured for each forage category, for each month. The mean caloric efficiency is then the mean of all months for all forage categories. The maximum caloric efficiency is the maximum value for all months and all forage categories. Any category for which no ACM calories are available is excluded from the analysis. This is not the same as the RCM return rate, which is based on the amount of calories expended versus the amount returned for any one resource. The caloric efficiency is an expression of the amount of calories consumed versus the amount left on the table, so to speak.

(8) Sustainable Population—Several assumptions were made to generate a model for what the sustainable population would have been for any given site. Using the mean friction value for the combined buffer, an estimate was made of the number of map units that could be harvested in one day by one person. Then the minimum population was assumed to be the total number of calories (including retained surplus calories) that could be produced by a single forager within the daily foraging area divided by the number of required calories (minimally set at 1600 per person per day). In contrast, the maximum population was estimated by assuming all portions of the buffer could be harvested and all calories were available. The resilience limit is based on the maximum times the resilience proportion, which produced a population figure that simulated the point at which the forage category would theoretically begin to reach a serious stress point. Finally, using the caloric efficiency as a guide, sustainable population estimates were based on the mean and maximum caloric efficiencies. These were, in essence, the populations that could be supported strictly by the selective calories (i.e., no surplus was used), and if all of the surplus calories were used (but the resilience maximum was not reached).

A spreadsheet was developed that allows one to select any given site and the temporal range for the analysis and produce a series of charts and graphs that illustrate these calculations. The spreadsheet also summarizes the data for groups of sites based on selective attributes. In this analysis the categories used were: all habitation sites (HS, N = 101); habitation sites associated with a shell midden (SM, N = 20); habitation sites that included an earthen mound (MD, N = 47); and groups of each temporal period—Late Archaic (LA, N = 40), Early Woodland (EW, N = 22), Middle Woodland (MW, N = 48), Late Woodland (LW, N = 46), Early Mississippian (EM, N = 2), Middle Mississippian (MM, N = 29), Late Mississippian (LM, N = 33), and Protohistoric/Historic Indian (PH, N = 13).

Mean Foraging Areas and Travel Friction

Although the mean travel friction value for all of these groups tends to be between 5 and 6 kcal per map unit, there is a slight increase as one moves from the Late Archaic through the Early Mississippian, with a drop during the Middle Mississippian and a rebound during the Late Mississippian, only to fall again during the Protohistoric/Historic Indian period. When comparing the mean acreage of the terrestrial, aquatic, and combined foraging buffers, the average sizes are generally pretty much in the same range (with the exception of the Early Mississippian, which only has a sample size of two sites). However, there is a trend toward decreasing terrestrial foraging area over time. This is clear especially when you look at the proportional representation of the 450 kcal aquatic and terrestrial areas by temporal periods (fig. 10.11). With the exception of the Middle Mississippian, there is a gradual decrease in the terrestrial foraging area until the Protohistoric/Historic Indian period.

Aquatic friction in the vast estuarine portions of the study area tends to average slightly more than terrestrial friction because of the large amounts of salt marsh along with many small islands (considered portages); both salt marsh canoeing and portaging are calorically fairly high cost. So, aquatic foraging areas with lots of islands and salt marsh tend to have somewhat higher friction values per map unit than terrestrial ones, even though open-water canoeing is generally half the caloric cost of walking. But the more open water there is in the foraging zone, the lower the mean becomes. Beginning with the Late Archaic, it appears that a larger proportion of terrestrial foraging area helped reduce the mean cost of travel. As the amount of estuarine aquatic foraging increased, starting in the Early Woodland, mean friction costs tended to go up slightly. However, in the Middle Mississippian, it appears that there is a trend back toward a lower mean travel friction, and a jump in terrestrial foraging area (at least based on the 29 Middle Mississippian sites in the analysis). By the Late Mississippian, the trend reverses and decreasing terrestrial foraging, along with increasing overall travel friction, is reestablished.

This Middle Mississippian blip may be the result of a shift back toward more inland sites. The dataset appears to indicate that Middle Mississippian sites in the analysis do tend to fall more frequently in the interior than along the coast, or on the barrier islands. But is this a real settlement shift, perhaps toward interior riverine trade routes rather than coastal estuaries? Or is this the result of a tendency to define coastal sites as not Middle Mississippian? It’s hard to say because there is a real absence of Early Mississippian habitation site designations on the coast as well (there were only two examples used in the analysis). But the Early Mississippian sites did not change the trend, despite being such a small sample. There may also be some confusion over Middle Mississippian diagnostic indicators that could result in this pattern, for example, items that tend to be defined as Middle Mississippian in the interior, but Late Mississippian on the coast.

During the Protohistoric/Historic Indian period the trend goes back once more to a lower average travel friction, very similar to the Middle Mississippian. There is no corresponding shortage of sites on the barrier islands, however, as there is for the Middle Mississippian. Furthermore, the relative proportions of aquatic and terrestrial foraging areas are quite similar to the Middle Mississippian proportions, despite the fact that the Protohistoric/Historic Indian sites are clearly more coastal in nature. There may be two attributes that could account for this trend. First, greater access to more open water could reduce the overall travel friction costs by averaging in less marsh and small island areas. Placement of sites in locations more closely tied to the open ocean or deeper water could account for this. Additionally, the slight increase in terrestrial habitat over that seen in the Late Mississippian could be accounted for by movement of the primary settlements into more upland terrain away from the shoreline, but on the barrier islands, not in the interior of the study area. Both of these trends could result from native groups settling in close proximity to previously existing Spanish missions where deep-water ship access could have played a role in their locations, plus a greater emphasis placed by the Spanish on maize agriculture subsistence.

Mean and Monthly Dietary Components

To summarize the overall trends in subsistence by period and by month, a series of graphs was produced that illustrates trends both between aquatic and terrestrial faunal sources and between wild and domestic plant usage. Each of the faunal categories was defined as either a terrestrial resource (they spend most of their time on land) or an aquatic one (they spend most of their time in water). The proportion of calories was calculated for each resource for each month and multiplied by –1 if aquatic. The totals were summed for each month, with the result that the calculated decimal value ranged between –1 and 1, and represented the trend between an aquatic (negative) and terrestrial (positive) diet, with zero indicating a diet of even amounts of aquatic and terrestrial resources. There is no assumption made regarding the methods of foraging with respect to the nature of the resource; aquatic resources can be collected on foot just as terrestrial resources can be collected by canoe.

Each of the plant resources was assessed as either a wild (native) resource or a domesticated (introduced) one (i.e., maize, beans, and squash). For this analysis, semidomesticated resources (such as amaranth, or sumpweed) were classed with other native, or wild, species. The proportion of each wild resource was multiplied by –1, and the totals produced a decimal value between –1 (wild) and 1 (domesticated). A scatterplot was created for each temporal period, where the x-axis represents the range between aquatic and terrestrial fauna, and the y-axis the range between wild and domesticated flora, for each month. The mean values for the entire year were then calculated and applied to a single scatterplot (fig. 10.12). This analysis includes not only the resources consumed quickly upon collection (i.e., the selective calories) but also the retained surplus calories. For example, the increasingly high proportion of the diet contributed by domesticated plants during the winter over time is not from resources collected during that month, but from stored calories collected during the fall or late summer months. Bear in mind, though, that there is still considerable debate about when maize, beans, and squash were introduced to the Coastal Plain (especially the Sea Islands) and the dietary model used may be overemphasizing the trend toward increasing domestic plant usage, since it is not based on real archaeobotanical assemblages at any points other than the Late Archaic and the Protohistoric/Historic Indian period.

But, in general, the trends indicate an increase toward more aquatic faunal resources over time. The trend toward increasing domesticates (if not the actual date of introduction) is obviously expected. But the total ACM value (i.e., productivity) for maize, beans, and squash increases slightly, or remains at the same level, even though the overall trend in amount of terrestrial foraging area is decreasing, suggesting an intentional selection of better domestic plant habitat over time. The trend toward a greater mean aquatic diet is also expected given our knowledge of the regional history and the patterns built into the dietary model. But the general increase in the proportion of aquatic foraging area over time (discussed earlier, and which is based solely on travel friction, not on diet or the ACM or RCM values) reinforces this interpretation.

To investigate this, a second analysis was run in which the mean ACM calories were used, and all assumptions about caloric availability were kept even across the board. In other words, this secondary analysis does not include any considerations of return rates or dietary preference. If we assume that all calories are equally available across all temporal periods, then figure 10.13 illustrates the yearly mean aquatic/terrestrial ratio of just the available calories for all periods in the analysis. It also includes the mean values for all habitation sites, all shell middens, and sites with earthen mounds. The results clearly indicate that there is a real trend toward greater quantities of available aquatic resources over time, regardless of how they might have been exploited. This can also be accounted for by an overall movement toward the estuarine environments already suggested, but it independently reinforces the observed trend in the RCM and selective data.

The breakdown of the ACM analysis by month (fig. 10.14) shows, as expected, that the shell midden sites have a higher mean availability of aquatic fauna than all periods throughout the year. The sites with earthen mounds also have higher aquatic means than all temporal periods except the Early and Late Mississippian. The trends suggested by figures 10.12 and 10.14 indicate that, prior to the Middle Woodland, the bulk of the faunal resources available within the foraging buffers defined was terrestrial and collected in the winter, fall, and spring. By the Middle Woodland, the balance was almost even between terrestrial and aquatic resources. By the later periods, more aquatic resources were available through most of the year.

Caloric Efficiency and Sustainable Population

There is a gradual rise in mean caloric efficiency rates over time, from around 30% to about 40%. But, in general, the level of caloric efficiency derived from these buffer zones suggests that, from the Late Archaic through the Protohistoric/Historic Indian periods, people were exploiting the available resources at nearly the same rate. Excluding periods of drought or other climatic issues (which are yet not modeled), the amount of calories available per person in the Late Archaic (regardless of source) was not much less than that available to people in the Protohistoric/Historic Indian period—given the same level of effort. The focus may have been on more aquatic resources later on, but, in general, people from all periods focused their efforts on the forage categories that provided them the most efficient return (i.e., those with specific RCM return rates over 50%).

Given the previously mentioned stipulations regarding their calculation, table 10.8 shows the sustainable population estimates by month for each of the periods. The average estimated monthly population for all Late Archaic sites in the study ranges from 19 in January to 163 in September, while the mean value falls at 60. This suggests that a 450/900 kcal foraging radius around a typical Late Archaic habitation site could support about 60 people on average during most of the year, but permanent residents probably would only have been around a third of that number. Figure 10.15 illustrates the mean and minimum values by temporal period.

The population estimates rise fairly rapidly through the Early Mississippian (multiplying at factors between 1.6 and 2.2), but then drop again during the Middle Mississippian (the minimum population of which is only 73% of the Early Mississippian). The numbers for the Late Mississippian are comparable to those of the Early Mississippian. The Protohistoric/Historic Indian period increases slightly over the Late Mississippian. In this case, the anomaly in the analysis seems to be during the Early Mississippian. The two Early Mississippian sites appear to be somewhat better situated than what would have been expected if an average of more sites had been available.

Regardless, it appears that most Mississippian period habitation sites in coastal Georgia could comfortably support more than 200 people on average year-round, given the assumptions of maize agriculture and storage defined earlier. Spring and early summer appear to be the times in which the sustainable population is the lowest for all periods, with the exception of the Late Archaic (where midwinter has the lowest caloric availability). March through May is when the stored plant calories are beginning to run out, but the abundant resources of summer and fall are not yet available. If stored calories are not included in the mix, midwinter is then the least productive period. However, minimum population levels could also have been increased by pushing the stress limits on some of the available faunal resources during the spring and early summer, and by trading with other locales for supplemental calories. The Middle Mississippian sites in particular seem to be poorly situated for early summer resources, so they could have followed the trading strategy. Alternatively, the sustainable population could have been increased by planting a second crop during the year and harvesting in the spring, which is possible in the region, but was not considered in this analysis.

LOCAL-SCALE ANALYSIS

On the local scale, the goal was to provide more intensive examination of the foraging areas of a specific site and perhaps to examine the nature of resource collection activities during the year more directly. Whereas the comparative analysis focused on groups of sites and their temporal periods—and is presented primarily in table and graph form—the local analysis is an exercise in creating many interpretive GIS surfaces based on the 444 HM surfaces and the terrestrial and aquatic travel friction. For this analysis, site 9Cm471 is used as an example. Any other site in the analysis, or the GASF for that matter, can be analyzed, but 9Cm471 is excellent for illustrative purposes.

Site 9Cm471 is a village site located in Camden County at the margin of a remnant barrier island of the Pamlico shoreline complex. It has numerous associated small shell scatters and a large earthen mound. It is situated near the mouth of the Satilla River, but with good access to both terrestrial and aquatic foraging areas. The site dates from about 1600–500 b.p. (Late Woodland through Late Mississippian). Figure 10.16 shows the site and its 450 kcal terrestrial and aquatic (and 900 kcal aquatic foraging buffers) over the 15 minute USGS quadrangle map. The values defined for the site in tabular and graph form were used to derive estimates of returnable calories for each of the species for each month.

Effective Foraging Areas

A cost distance evaluation was conducted from site 9Cm471 based on the combined travel friction and translated into an accumulated caloric distance. Any map unit in the resulting surface was then a representation of how many calories it took to reach that location from 9Cm471 on foot and/or by canoe. Using map algebra, the accumulated caloric distance was doubled (simulating a round-trip from the site) and subtracted from the RCM surface (as a mean for the period between 1600 and 500 b.p.) for each forage category for each month. Any areas that were caloric deficits (i.e., where the cost of reaching that location exceeded the expected return) were then revalued to zero; these are made transparent in figures 10.17 and 10.18. Each final surface then illustrates the RCM calories for the time frame with an accurate representation of the costs of acquiring those calories considered. Rather than buffering the returns at a specific daily distance (as in the comparative analysis), it is assumed that once the travel costs exceed the expected returns the theoretical foraging limit has been reached (regardless of how long it may take to reach it).

Looking specifically at saltwater fish resources as an example, figure 10.17 shows the potential caloric returns for small, large, and all saltwater fish during the months of January and July predicted for approximately 500 b.p. The display is standardized to range between zero and a maximum of 2796 calories per map unit (the highest RCM value reached for any single saltwater fish category during any month at 9Cm471). The modeled surfaces indicate a restricted foraging area in January, expanding through the spring, but essentially not going much beyond the 900 kcal range at any time. During the fall and winter, the potential caloric returns begin to decrease and the effective foraging range contracts again. At no time during the year does the expected caloric return per map unit rise very high for small saltwater fish (never exceeding 630 kcal). But the area within which small saltwater fish are potentially available and would be worth the travel investment is fairly broad. In essence, small saltwater fish are a local resource probably collected by single individuals mostly in the summer months, but potentially year-round.

In contrast, the middle part of the image illustrates the same surfaces for large saltwater fish for the same temporal range and the same months, and also standardized to the same display values. Large saltwater fish are a productive resource very early in the spring even well beyond the 900 kcal range. By the summer months, the expected caloric return is very high well out into the Satilla River estuary, making it worthwhile for a forager to travel quite a distance to collect large saltwater fish. This suggests that three- or four-person canoes could easily have traveled into the estuary and still procured a positive caloric return within a single day’s foraging. It would have been more difficult for an individual forager, or even a two-person canoe, and might have required an overnight trip to make it worthwhile. Like the other saltwater fish resources, the potential return drops dramatically in the winter, and at that time, even large saltwater fish would likely have been collected locally and much less frequently, because the expense of traveling into the Satilla River estuary would have been inefficient.

For all of the saltwater fish categories combined, by springtime there is a wide range of calories available both within a short distance of the site, and well out into the estuary. This suggests that a broadly diverse diet could easily have been supported with daily aquatic foraging, but the caloric returns from saltwater fish alone (regardless of size) are still effectively low in winter. Low winter saltwater fish calories would have been supplemented by terrestrial resources, but probably also with shellfish. If shellfish are included in the aquatic analysis (along with freshwater fish), the caloric returns for January look somewhat different (fig. 10.18). The highest return rates are from shellfish in the Satilla River estuary, but also from mixed size brackish water fish close to the site. Acquiring shellfish could have been carried out by canoe, or it is very likely that the shellfish resources available beyond the 900 kcal foraging range could have been collected by people living at smaller communities who then traded them to larger settlements in exchange for maize or other terrestrial resources. There are numerous shell middens along Crews Point, Dover Bluff, and Black Point that may have traded with 9Cm471 or sites on Cumberland Island, Jekyll Island, and Hazzards Neck, in this way.

Resource Collection Pathways

The most productive pathways to acquiring any of the forage categories can be modeled using a modified hydrology analysis. Hydrology analysis uses directional terrain slope to determine the drainage characteristics of any map unit, projecting how many other map units flow into it, and in which direction surface water would flow out. Normally, a hydrology analysis uses a digital elevation model to recreate actual stream flows. However, if we translate the caloric surface into a pseudotopography, we can use the hydrology analysis in a different way as a means to determine the most productive paths into the resource collection areas.

Cost distance is an algorithmic accumulation of cost values (or friction) as one progresses outward from the point of origin. In this case we can modify the caloric surface by inverting it so that the higher calorie areas are lower values, while the lower calorie areas are higher. This can then be used as a friction surface, in the same way that terrestrial and aquatic caloric costs were used to generate real travel friction. A cost distance evaluation using the inverted RCM surface then gives an algorithmic accumulation of values as one progresses outward from 9Cm471. The result is a pseudotopography in which 9Cm471 represents “sea level” and the lower the caloric return, the higher the “elevation” in the model. When a hydrology analysis is conducted on this surface it produces a false stream network that follows the pathways that accumulate the highest total calories (i.e., the “valleys” in the analysis). The number of paths identified is dependent upon the cutoff value assigned: the lower the threshold, the more paths illustrated. This is essentially the same as stream order: higher-order streams accumulate more water from the surrounding terrain and smaller intersecting streams. Higher-order pathways defined in this model accumulate more calories in the same way.

Figure 10.19 shows some of the highest-order aquatic foraging pathways identified for all saltwater fish categories combined in the vicinity of 9Cm471 during June; notably this does not include shellfish. It is clear that the most productive paths are in the major stream channels, and they move eastward into the estuary. There are some cutoffs through dense marsh areas, but more than likely smaller saltwater fish and other marsh resources could have been exploited by short local (low order) paths used frequently, but that did not accumulate large caloric returns in a single episode. They also could have easily been exploited by terrestrial travel (see fig. 10.18 where the terrestrial foraging buffer overlaps marsh areas). It is possible to identify paths in this way that represent foraging for any given resource, or group of resources, both aquatic and terrestrial, for any given month, and any chosen period, or year, of analysis.

Defining resource collection paths in this way may help us to identify the associations between residential sites and activity areas. Many undated lithic scatters, for example, could be the remnants of hunting-specific resources that can be linked to pathways to and from known sites. A model can be developed that gives a probability value for the likelihood that one site is associated with any other one, perhaps allowing us to date or understand the function of the small quantity of material recovered. In many cases, the activity that is being modeled by resource collection paths may not have resulted in the deposition of any artifacts at all (or the artifacts are not recoverable, or were perishable), and therefore is not recognizable archaeologically; this is especially true for fishing locales. Knowing how people could have used their environment for a wide range of tasks can help us fill in the gaps of our archaeological knowledge. Integrating the PDSI values, or temperature models, on this level can help establish where resource stress may have occurred, and how people at any given site may have responded to it spatially.

The resource collection paths can also theoretically be used to define gender-based activity areas. For example, if we believe that females may have primarily foraged for plant resources or tended maize fields, we can define the pathways of highest productivity for such resources and build an argument that defines task landscapes for females—perhaps by season, as well. Similarly, hypothetical locational models of daily activities by gender or age group can be created by combining specific resource collection paths with other types of activities, such as ceramic raw material collection areas, areas defined as representing domestic activities, etc. The possibilities are numerous for additional research trajectories. Perhaps some of the most interesting are interaction, trade, and competition with neighboring groups.

Foraging Competition

As an example of modeling foraging competition, two other sites were added to the local analysis of 9Cm471. They are both habitation sites with earthen mounds; one (9Gn47) is located on Jekyll Island, the other (9Cm11) located on Cumberland Island. Neither of these two sites is included in the regional scale analyses because they are officially undated in the GASF. However, they (along with 9Cm471) are spaced almost equidistant from each other (~20 km) and all three are situated at the edge of the Satilla River estuary. It is also very likely that all three may have been occupied at the same time. For this analysis, the data were generated for June of 400 b.p., and the focus is only on aquatic resources.

First, a cost-distance evaluation was carried out from all three sites using aquatic friction. The intersection of foraging areas falls in the middle of the estuary, south of Horseshoe Shoal and near the south bank of the Satilla River. The threshold of caloric friction is around 1200 kcal, meaning most of the estuary is accessible from any of the three sites at a cost of about 1200 kcal (within a one-day foraging radius for a three-person canoe). Theoretically, the areas of most intense competition would fall near that threshold, and would be those locales that have the greatest potential caloric return. Intensity of foraging competition was then modeled by multiplying the RCM caloric surface for all saltwater fish by a modified version of cost distance from the 1200 kcal threshold (i.e., the more expected calories and the closer to an opposing foraging territory, the higher the potential for competing over the resource with someone else). Figure 10.20 illustrates this for June of 400 b.p.

The most intensive competition (at least for saltwater fish) would have been at Horseshoe Shoal and south of it and also at the tip of Cumberland Island. The main channel of the Satilla just offshore may have been less competitive because of strong tidal currents, which resulted in both poorer productivity and higher caloric friction. Superimposed over this competition surface are some of the higher-order resource collection paths. Where they intersect the 1200 kcal boundary, they are equidistant calorically from the sites. Even though they join together and can be seen as routes between the sites, they are based on the pseudotopography, not the aquatic travel friction alone. This means that they are not necessarily the same as the least-cost paths between the sites. Instead, they are, in essence, the highest productivity paths between the sites. Put into context with regard to trade and interaction, it is clear that control over the resources within the area of highest competition would have been extremely important either during certain times of the year or other periods of resource stress.

CONCLUSIONS

In general, this form of paleoeconomic modeling can be seen as analogous in some ways to weather forecast modeling. Spatial data are used to represent the initial conditions, specific variables are introduced, and standardized predictive surfaces are created. Our interpretations of these predictions (or in this case “retrodictions”) are compared between localities and put into the context of what we know about past behavioral activities (i.e., subsistence actions). There are several levels of feedback within the model, which help to bring out certain aspects that are important. In the final analysis, though, the model is only as good as the data and our assumptions about those data. As I have emphasized throughout the chapter, some of the initial variables are based on qualitative assessments and not quantitative ones. This means that better data could theoretically improve, or change, the results.

However, this framework was specifically designed so that better data could be incorporated with as little difficulty as possible. If a new HM weighting of any variable is chosen, then the ArcGIS syntax can be quickly generated and a new surface created. If changes to the ACM or RCM constants are required, then those variations are automatically incorporated by the spreadsheets into the outputs. Likewise, the dietary and return models can easily be changed to produce alternative results. Ultimately, the goal would be to incorporate all of these attributes into a more cohesive, programmatic tool that can be deployed in ArcGIS. This may also be integrated with simulation studies that incorporate agent-based modeling methods. The framework for the analysis need not change if new data are introduced, but such changes could have profound effects on the interpretations.

Obviously, there are numerous interpretive potentials to be derived from direct caloric paleoeconomic modeling presented here. But one thing not considered is how caloric surfaces may be used to represent noncaloric resources. For instance, lithic sources are important attractors to settlement, but lithics themselves do not obviously translate into calories. However, we can calculate caloric offsets for many resources in the same way that we calculate carbon offsets today. Buying a plastic item consumes a certain amount of carbon because carbon was generated in the process of making it. Planting a tree offsets some of that because trees consume atmospheric carbon. A carbon offset then is a representation of the amount of atmospheric carbon that was canceled out. In this case, the offset is used to express a standardized characteristic for activities that do not obviously relate to carbon generation.

The act of collecting lithics involves a caloric cost, which can be measured, but a source of lithic raw materials has no inherent caloric content that could be directly illustrated as a caloric landscape. However, the quality of the lithic material may represent an offset of the calories expended to collect it by increasing the caloric return rate of its use. If high-quality chert increases the amount of calories returned from hunting deer by a certain percentage (over poorer-quality quartzite, for example), then it has a measurable net caloric offset. Comparing the caloric cost to acquire a resource with its potential offset may be a way to standardize many different kinds of nonsubsistence resources (or even concepts such as trade, reciprocity, and political organization) and to spatially map and analyze them. Clearly, the potential uses for caloric surfaces are still yet to be explored.

Figure 10.1. Study area.

Figure 10.2. Water availability, mouth of Altamaha River.

Figure 10.3. Water salinity, mouths of the Ogeechee and Medway rivers.

Figure 10.4. Vegetation type 2, mouths of the Turtle and Satilla rivers.

Figure 10.5. Water depth 1, mouths of the Turtle and Satilla rivers.

Figure 10.6. January deer habitat, mouth of the Altamaha River.

Figure 10.7. June large saltwater fish habitat, Ossabaw, St. Catherines, and Sapelo islands.

Figure 10.8. Shellfish habitat, between the Altamaha, Turtle, and Satilla rivers.

Figure 10.9. Terrestrial travel friction, between the Altamaha and Turtle rivers.

Figure 10.10. Aquatic travel friction, between the Altamaha and Turtle rivers.

Figure 10.11. Ratio of aquatic to terrestrial foraging area.

Figure 10.12. Mean dietary balance as a function of temporal periods and site types.

Figure 10.13. Available caloric model (ACM) ratio of aquatic to terrestrial fauna by temporal period and site types.

Figure 10.14. Available caloric model (ACM) ratio of aquatic to terrestrial fauna by month by temporal period and site types.

Figure 10.15. Calculated sustainable population estimates (minimums and means) by period.

Figure 10.16. Site 9Cm471 location and calculated foraging buffers.

Figure 10.17. Caloric landscapes (ca. 500 b.p.) around 9Cm471 for January and July (small, large, and all saltwater fish).

Figure 10.18. Caloric landscapes (ca. 500 b.p.) around 9Cm471 for January (all aquatic resources).

Figure 10.19. Aquatic resource collection paths (ca. 400 b.p.) plotted with the caloric landscape of all saltwater (SW) fish in June at 9Cm471.

Figure 10.20. Aquatic resource collection paths (ca. 400 b.p.) plotted with the resource competition ratio of all aquatic resources in June at 9Cm471.

TABLE 10.1. Forage Categories Used in the Study

Forage Categories

Very large saltwater fish

Wading birds

Large saltwater fish

Sea turtles

Medium saltwater fish

Freshwater turtles

Small saltwater fish

Reptiles

Very small saltwater fish

Amphibians

Large freshwater fish

Shellfish

Medium freshwater fish

Sea turtle eggs

Small freshwater fish

Maize (Zea mays)

Very small freshwater fish

Bean (Phaseolus vulgaris)

White-tailed deer (Odocoileus virginianus)

Squash (Cucurbita pepo)

Black bear (Ursus americanus)

Amaranths (Amaranthus spp.)

Alligator (Alligator mississippiensis)

Sunflower (Helianthus annus)

Wild turkey (Meleagris gallopavo)

Maygrass (Phalaris caroliniana)

Raccoon (Procyon lotor)

Sumpweed (Iva annua)

Opossum (Didelphis virginiana)

Acorns (Quercus spp.)

Rabbits (Sylvilagus spp.)

Hickory nuts (Carya spp.)

Squirrels (Sciuris spp.)

Cattails/bullrushes (Typha spp.)

Upland birds

Chenopods (Chenopodium spp.)

Waterfowl

TABLE 10.2. Baseline Weights Used in the Habitat Modeling

See text for abbreviations.

Forage Category

WA

WS

ST

SF

VD

VT1

VT2

WD1

WD2

WD3

EZ1

EZ2

EZ3

EZ4

EZ5

Very large saltwater fish

10

9

0

0

0

0

0

-8 to 6

0 to 6

0 to 8

0

0

0

0

0

Large saltwater fish

10

8

0

0

0

0

0

-6 to 7

2 to 7

-1 to 4

0

0

0

0

0

Medium saltwater fish

10

7

0

0

1

0

0

-2 to 8

4 to 8

-2 to 0

0

0

0

0

0

Small saltwater fish

9

6

0

0

2

0

0

0 to 9

2 to 7

-6 to -3

0

0

0

0

0

Very small saltwater fish

9

5

0

0

3

0

0

2 to 10

0 to 6

-9 to -4

0

0

0

0

0

Large freshwater fish

10

-10

0

0

2

0

0

-2 to 8

2 to 7

-1 to 4

0

0

0

0

0

Medium freshwater fish

10

-9

0

0

3

0

0

0 to 9

4 to 8

-2 to 0

0

0

0

0

0

Small freshwater fish

9

-8

0

0

5

0

0

2 to 10

2 to 7

-6 to -3

0

0

0

0

0

Very small freshwater fish

9

-7

0

0

6

0

0

2 to 10

0 to 6

-9 to -4

0

0

0

0

0

White-tailed deer

-8

-2

4

3

1 to 6

4 to 8

3 to 8

0

0

0

0

0

0

0

0

Black bear

1

-4

2

0

2 to 5

2 to 6

0

0

0

0

0

0

0

0

0

Alligator

8

-3

2

0

-8 to 6

0

0

3

1

0

2

1

0

-2

-3

Wild turkey

-8

-8

6

1

-6 to 6

-2 to 2

0

0

0

0

-3

-1

1

2

3

Raccoon

-3

-2

2

1

2 to 5

5 to 8

4 to 8

0

0

0

0

0

0

0

0

Opossum

-8

-8

4

0

6

0

0

0

0

0

-4

-2

0

2

3

Rabbits

-5

-4

4

2

0 to 6

2

0

0

0

0

-2

-1

0

1

2

Squirrels

-9

-8

7

2

9

3

4 to 9

0

0

0

-4

-2

0

2

3

Upland birds

-8

-7

5

2

-4 to 5

-2 to 2

-2 to 2

0

0

0

-5

-3

-1

2

4

Waterfowl

8

-6

0

0

-4

0

0

0

0

0

0

0

0

0

0

Wading birds

8

1

0

0

-4

0

0

10

-10

-10

2

1

0

0

0

Sea turtles

9

10

8

0

-8

0

0

0

1

2

0

0

0

0

0

Freshwater turtles

9

-10

-3

0

-3

0

0

3

1

-2

0

0

0

0

0

Reptiles

-6

-8

6

0

4

6

0

1

0

0

-2

-1

0

0

0

Amphibians

8

-10

-4

0

0

0

0

7

-2

-5

-4

-1

0

0

0

Shellfish

10

6

-8

0

-9

0

0

9

0

0

10

0

0

0

0

Sea turtle eggs

-5

0

9

0

-8

0

0

0

0

0

8

5

0

0

0

Maize

-9

0

6

10

0

0

0

0

0

0

0

0

0

0

0

Beans

-9

0

6

9

0

0

0

0

0

0

0

0

0

0

0

Squash

-8

0

5

8

0

0

0

0

0

0

0

0

0

0

0

Amaranth

-5

0

2

6

-1

0

0

0

0

0

0

0

0

0

0

Sunflower

-7

0

4

5

-2

0

0

0

0

0

0

0

0

0

0

Maygrass

-5

0

2

2

0

0

0

0

0

0

0

0

0

0

0

Sumpweed

2

0

0

0

2

0

0

0

0

0

0

0

0

0

0

Acorns

-9

0

7

5

5

8

10

0

0

0

0

0

0

0

0

Hickory nuts

-9

0

6

4

6

10

0

0

0

0

0

0

0

0

0

Cattail/bullrush

7

0

-3

0

-3

0

0

3

-2

0

4

0

0

0

0

Chenopods

-2

0

2

2

2

0

0

0

0

0

0

0

0

0

0

TABLE 10.3. Population and Reproduction Estimates by Forage Category

Abbreviations: St. = study; SA = study area; Brth/harv. = birth rate or harvest rate; unk. = unknown; Ac. = acres.

Forage category

Population estimates

Reproduction harvest (year)

Average size: Max = male; Med = female; Min = juvenile

Groups/range

Caloric values

State

St. Area

% in SA

Brth/harv.

Peak

Offspring (no.)

Maturity

Survival (%)

Max. (lbs.)

Med. (lbs.)

Min. (lbs.)

Max. (kg)

Med. (kg)

Min. (kg)

Individ-uals (no.)

Ac. (max.)

Ac. (min.)

Usable (%)

kcal/kg

Very large saltwater fish

500,000

500,000

100

Apr–Jul

May–Jun

100

2.00

2.00

50.00

20.00

10.00

22.68

9.07

4.54

1 to 2

unk.

unk.

75

1100

Large saltwater fish

1,000,000

1,000,000

100

Apr–Jul

May–Jun

3,000

1.00

0.07

20.00

10.00

2.00

9.07

4.54

0.91

1 to 4

unk.

unk.

75

1100

Medium saltwater fish

2,000,000

2,000,000

100

Apr–Jul

May–Jun

10,000

1.00

0.02

10.00

4.00

1.00

4.54

1.81

0.45

1 to 20

unk.

unk.

75

1100

Small saltwater fish

3,000,000

3,000,000

100

year-round

May–Jun

50,000

0.50

0.004

2.00

0.60

0.20

0.91

0.27

0.09

1 to 100

unk.

unk.

75

1100

Very small saltwater fish

4,000,000

4,000,000

100

year-round

May–Jun

200,000

0.50

0.001

0.50

0.20

0.10

0.23

0.09

0.05

10 to 100s

unk.

unk.

75

1100

Large freshwater fish

1,111,111

500,000

45

Apr–Jul

May–Jun

3,000

1.00

0.07

30.00

4.00

2.00

13.61

1.81

0.91

1 to 4

unk.

unk.

75

1100

Medium freshwater fish

2,222,222

1,000,000

45

Apr–Jul

May–Jun

10,000

1.00

0.02

4.00

1.00

0.50

1.81

0.45

0.23

1 to 20

unk.

unk.

75

1100

Small freshwater fish

4,444,444

2,000,000

45

year-round

May–Jun

50,000

0.50

0.004

0.50

0.20

0.10

0.23

0.09

0.05

1 to 100

unk.

unk.

75

1100

Very small freshwater fish

6,666,667

3,000,000

45

year-round

May–Jun

200,000

0.50

0.001

0.10

0.05

0.02

0.05

0.02

0.01

10 to 100s

unk.

unk.

75

1100

White–tailed deer

2,083,333

250,000

12

May–Aug

June

4

0.50

50.00

200.00

125.00

20.00

90.72

56.70

9.07

3 to 12

1200

150

60

1200

Black bear

33,333

4,000

12

Jan–Feb

Late Jan

3

3.00

66.67

352.74

154.32

44.09

160.00

70.00

20.00

1 to 3

6250

1565

50

1610

Alligator

80,000

40,000

50

Aug–Oct

Sep

37

10.00

5.41

363.76

198.42

4.41

165.00

90.00

2.00

1 to 40

2500

500

43

1000

Wild turkey

1,250,000

150,000

12

May–Jun

Late May

10

0.50

20.00

20.00

10.00

2.00

9.07

4.54

0.91

4 to 15

1000

200

70

1600

Raccoon

1,000,000

120,000

12

May–Jun

Late May

4

0.50

50.00

20.00

8.00

2.00

9.07

3.63

0.91

1 to 3

800

200

70

1680

Opossum

2,000,000

240,000

12

year-round

Mar, Sep

14

0.50

14.29

6.00

4.00

1.00

2.72

1.81

0.45

1 to 8

350

160

70

1460

Rabbits

5,000,000

600,000

12

year-round

Jan, May, Sep

15

0.50

13.33

4.00

2.00

0.50

1.81

0.91

0.23

1 to 12

20

4

70

1140

Squirrels

4,166,667

500,000

12

Jan–Sep

Feb, Aug

5

0.50

40.00

3.00

0.80

0.20

1.36

0.36

0.09

1 to 4

10

1

70

1200

TABLE 10.3 — (Continued)

Forage category

Population estimates

Reproduction harvest (year)

Average size: Max = male; Med = female; Min = juvenile

Groups/range

Caloric values

State

St. Area

% in SA

Brth/harv.

Peak

Offspring (no.)

Maturity

Survival (%)

Max. (lbs.)

Med. (lbs.)

Min. (lbs.)

Max. (kg)

Med. (kg)

Min. (kg)

Individ-uals (no.)

Ac. (max.)

Ac. (min.)

Useable (%)

kcal/kg

Upland birds

5,833,333

700,000

12

Mar–Oct

May–Aug

12

1.00

16.67

0.50

0.30

0.10

0.23

0.14

0.05

5 to 20

200

10

70

1400

Waterfowl

333,333

150,000

45

Mar–Jul

Apr–Jun

10

1.00

20.00

5.00

2.00

0.10

2.27

0.91

0.05

4 to 12

unk.

unk.

70

1420

Wading birds

666,667

300,000

45

Feb–May

Mar–Apr

6

1.00

33.33

5.00

2.00

0.10

2.27

0.91

0.05

1 to 100s

unk.

unk.

70

1400

Sea turtles

3,000

3,000

100

Jul–Oct

Aug–Sep

110

20.00

1.82

200.00

150.00

20.00

90.72

68.04

9.07

1 to 2

unk.

unk.

80

890

Freshwater turtles

4,444,444

2,000,000

45

Jun–Oct

Aug–Sep

12

5.00

16.67

15.00

3.00

0.10

6.80

1.36

0.05

1 to 50

30

1

20

1300

Reptiles

16,666,667

2,000,000

12

Aug–Oct

Sep

10

1.00

20.00

1.00

0.30

0.10

0.45

0.14

0.05

1 to 12

15

1

50

1100

Amphibians

6,666,667

3,000,000

45

Sep–Nov

Oct

10,000

0.50

0.02

0.50

0.10

0.05

0.23

0.05

0.02

10 to 100s

2

1

70

1100

Shellfish

n/a

n/a

n/a

year-round

Aug–Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

500

1

1

100

720

Sea turtle e+A66ggs

n/a

n/a

n/a

Jul–Oct

Aug–Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

113

1

0.2

100

1995

Maize

n/a

n/a

n/a

Aug–Oct

Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

1500

Beans

n/a

n/a

n/a

Aug–Oct

Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

800

Squash

n/a

n/a

n/a

Sep–Nov

Oct

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

750

Amaranth

n/a

n/a

n/a

Jul–Oct

Aug–Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

1359

Sunflower

n/a

n/a

n/a

Jul–Oct

Aug–Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

489

Maygrass

n/a

n/a

n/a

May–Aug

Jun–Jul

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

457

Sumpweed

n/a

n/a

n/a

May–Aug

Jun–Jul

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

272

Acorns

n/a

n/a

n/a

Aug–Oct

Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

1214

Hickory nuts

n/a

n/a

n/a

Aug–Oct

Sep

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

2150

Cattail/bullrush

n/a

n/a

n/a

Apr–Jul

May–Jun

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

1745

Chenopods

n/a

n/a

n/a

May–Aug

Jun–Jul

n/a

n/a

n/a

2.20

0.00

0.00

1.00

0.00

0.00

n/a

n/a

n/a

100

433

TABLE 10.4. Resilience Calculations by Forage Category and by Month

Forage category

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Very large saltwater fish

9.31

10.74

12.22

14.48

16.50

18.76

18.76

16.50

14.48

12.22

10.74

9.31

Large saltwater fish

17.95

20.23

23.95

28.23

32.74

35.68

35.68

32.74

28.23

23.95

20.23

17.95

Medium saltwater fish

27.75

28.93

35.48

38.67

41.38

39.79

39.79

41.38

38.67

35.48

28.93

27.75

Small saltwater fish

52.75

54.53

57.53

60.09

62.40

64.36

64.36

62.40

60.09

57.53

54.53

52.75

Very small saltwater fish

68.45

68.91

69.15

69.01

68.55

68.00

68.00

68.55

69.01

69.15

68.91

68.45

Large freshwater fish

18.31

16.70

16.07

15.67

15.34

14.88

14.88

15.34

15.67

16.07

16.70

18.31

Medium freshwater fish

23.66

22.47

21.86

21.22

20.85

20.65

20.65

20.85

21.22

21.86

22.47

23.66

Small freshwater fish

42.14

41.74

41.05

40.72

40.33

40.17

40.17

40.33

40.72

41.05

41.74

42.14

Very small freshwater fish

49.93

49.69

49.48

49.12

48.91

48.66

48.66

48.91

49.12

49.48

49.69

49.93

White-tailed deer

12.32

12.32

12.32

12.14

11.72

11.82

12.43

13.17

13.73

13.55

13.11

12.58

Black bear

0.60

0.60

0.61

0.61

0.61

0.67

0.71

0.78

0.78

0.75

0.69

0.65

Alligator

1.32

1.32

1.48

1.61

1.61

1.48

1.32

1.24

1.20

1.16

1.20

1.24

Wild turkey

8.47

8.56

9.21

10.38

10.83

10.42

9.90

9.04

8.77

8.65

8.50

8.39

Raccoon

9.68

9.68

9.68

9.42

9.19

9.40

9.98

11.26

10.93

10.58

10.18

9.94

Opossum

10.40

10.40

10.40

10.40

10.40

10.40

10.40

10.40

10.40

10.40

10.40

10.40

Rabbits

16.34

16.61

16.94

16.61

16.12

16.34

16.61

16.34

16.23

16.47

16.77

16.61

Squirrels

15.89

15.97

15.89

16.50

16.50

16.83

16.83

17.16

17.16

16.83

16.83

16.50

Upland birds

10.27

11.80

13.46

15.18

16.81

18.57

18.27

16.42

14.70

13.26

11.77

10.27

Waterfowl

15.66

13.92

12.18

10.44

8.70

8.70

10.44

12.18

13.92

15.66

17.40

17.40

Wading birds

8.01

8.01

9.61

11.22

12.82

14.42

16.02

16.02

14.42

12.82

11.22

9.61

Sea turtles

0.18

0.18

0.37

0.55

0.73

0.92

0.92

0.73

0.55

0.37

0.18

0.18

Freshwater turtles

12.81

12.81

12.81

12.81

12.81

12.81

12.81

12.81

12.81

12.81

12.81

12.81

Reptiles

21.20

21.20

21.20

21.20

21.20

21.20

21.20

21.20

21.20

21.20

21.20

21.20

Amphibians

43.57

43.57

43.57

43.57

43.57

43.57

43.57

43.57

43.57

43.57

43.57

43.57

Shellfish

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Sea turtle eggs

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Maize

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Beans

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Squash

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Amaranth

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Sunflower

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Maygrass

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Sumpweed

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Acorns

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Hickory nuts

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Cattail/bullrush

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

Chenopods

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

TABLE 10.5. Available kcal/30 m2 Unit of Prime Habitat

Forage category

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Very large saltwater fish

1018

1356

1755

2462

3653

4723

4723

3653

2814

2006

1356

1018

Large saltwater fish

807

1025

1436

1995

2864

3614

3614

2864

2128

1532

1093

807

Medium saltwater fish

904

983

1478

2133

2729

3187

3054

3160

2384

1795

1123

969

Small saltwater fish

327

324

389

697

1078

1321

1216

1078

757

583

449

373

Very small saltwater fish

118

106

134

360

618

737

672

552

426

361

226

157

Large freshwater fish

951

791

733

697

707

703

703

707

738

776

838

951

Medium freshwater fish

235

212

200

246

273

358

340

328

283

261

254

258

Small freshwater fish

60

51

57

118

184

217

196

184

132

106

88

74

Very small freshwater fish

13

12

14

37

64

76

70

57

44

38

24

17

White-tailed deer

1804

1804

1804

1754

1734

1866

2292

2573

2656

2453

2170

1883

Black bear

32

35

36

36

36

43

49

54

55

50

42

38

Alligator

430

430

539

639

639

539

430

394

421

420

394

394

Wild turkey

123

125

145

184

254

309

268

195

167

145

140

128

Raccoon

157

157

157

148

162

190

214

258

243

214

198

177

Opossum

39

34

67

56

51

45

39

34

67

56

51

45

Rabbits

98

90

82

78

142

135

123

87

107

99

80

67

Squirrels

41

46

43

47

44

46

46

53

53

48

46

44

Upland birds

8

11

14

18

34

55

60

54

37

26

18

12

Waterfowl

173

137

106

80

58

61

86

114

145

178

217

214

Wading birds

45

45

66

93

124

153

187

184

147

115

88

64

Sea turtles

17

24

156

481

1089

2065

2065

1089

481

156

24

17

Freshwater turtles

390

390

390

390

390

395

399

412

416

408

403

395

Reptiles

33

33

33

33

33

33

38

48

58

53

48

38

Amphibians

63

52

45

45

45

45

45

45

100

119

119

82

Shellfish

4003

4003

4403

4804

5604

6405

7206

8006

8006

6805

5204

4403

Sea Turtle Eggs

0

0

0

0

0

985

1477

1642

1313

821

328

0

Maize

0

0

0

0

0

0

0

22684

28355

14178

0

0

Beans

0

0

0

0

0

0

0

9252

11564

6939

0

0

Squash

0

0

0

0

0

0

0

1668

6672

8340

4170

0

Amaranth

0

0

0

0

0

1904

7616

9520

9520

4760

0

0

Sunflower

0

0

0

0

0

979

3915

4894

4894

2447

0

0

Maygrass

0

0

0

0

732

1829

1829

1098

366

0

0

0

Sumpweed

0

0

0

0

436

1089

1089

653

218

0

0

0

Acorns

0

0

0

0

0

0

3037

5467

6075

4252

0

0

Hickory nuts

0

0

0

0

0

0

7531

13555

15062

10543

0

0

Cattail/bullrush

0

0

1746

4075

5821

5821

4657

3493

2328

1164

0

0

Chenopods

0

0

0

433

1011

1444

1444

1156

722

289

0

0

TABLE 10.6. Return Rate Estimates as a Function of One Day’s Activity

Forage category

Min. calories/day

Max. calories/day

Daily activity (%)

kcal/day

Individual/kg/day

Min. retention (%) after:

Max. retention (%) after:

Maint

Harvest

Process

Maint

Harvest

Process

Maint

Harvest

Process

Min.

Max.

Min.

Max.

1 day

1 wk

1 mth

6 mths

1 year

1 day

1 wk

1 mth

6 mths

1 year

Very large saltwater fish

320

640

640

400

800

800

20

40

40

1600

2000

0.50

4.00

80

0

0

0

0

100

50

0

0

0

Large saltwater fish

240

560

800

300

700

1000

15

35

50

1600

2000

1.00

10.00

80

0

0

0

0

100

60

0

0

0

Medium saltwater fish

160

480

960

200

600

1200

10

30

60

1600

2000

10.00

50.00

80

0

0

0

0

100

70

0

0

0

Small saltwater fish

160

480

960

200

600

1200

10

30

60

1600

2000

50.00

200.00

80

0

0

0

0

100

80

0

0

0

Very small saltwater fish

160

320

1120

200

400

1400

10

20

70

1600

2000

100.00

500.00

80

0

0

0

0

100

90

0

0

0

Large freshwater fish

240

720

640

300

900

800

15

45

40

1600

2000

1.00

5.00

80

0

0

0

0

100

60

0

0

0

Medium freshwater fish

160

640

800

200

800

1000

10

40

50

1600

2000

4.00

20.00

80

0

0

0

0

100

70

0

0

0

Small freshwater fish

160

480

960

200

600

1200

10

30

60

1600

2000

20.00

100.00

80

0

0

0

0

100

80

0

0

0

Very small freshwater fish

160

480

960

200

600

1200

10

30

60

1600

2000

100.00

200.00

80

0

0

0

0

100

90

0

0

0

White-tailed deer

80

800

720

100

1000

900

5

50

45

1600

2000

0.20

2.00

100

20

0

0

0

100

60

0

0

0

Black bear

80

960

560

100

1200

700

5

60

35

1600

2000

0.05

0.50

100

20

0

0

0

100

60

0

0

0

Alligator

80

640

880

100

800

1100

5

40

55

1600

2000

0.50

4.00

100

10

0

0

0

100

50

0

0

0

Wild turkey

80

720

800

100

900

1000

5

45

50

1600

2000

1.00

8.00

100

20

0

0

0

100

60

0

0

0

Raccoon

160

400

1040

200

500

1300

10

25

65

1600

2000

1.00

5.00

100

20

0

0

0

100

60

0

0

0

Opossum

160

320

1120

200

400

1400

10

20

70

1600

2000

4.00

8.00

100

20

0

0

0

100

60

0

0

0

Rabbits

160

320

1120

200

400

1400

10

20

70

1600

2000

6.00

12.00

100

15

0

0

0

100

50

0

0

0

Squirrels

160

320

1120

200

400

1400

10

20

70

1600

2000

6.00

16.00

100

15

0

0

0

100

50

0

0

0

Upland birds

160

400

1040

200

500

1300

10

25

65

1600

2000

15.00

25.00

100

15

0

0

0

100

50

0

0

0

Waterfowl

80

480

1040

100

600

1300

5

30

65

1600

2000

4.00

12.00

100

15

0

0

0

100

50

0

0

0

Wading birds

160

400

1040

200

500

1300

10

25

65

1600

2000

3.00

12.00

100

15

0

0

0

100

50

0

0

0

Sea turtles

32

480

1088

40

600

1360

2

30

68

1600

2000

0.40

2.00

100

20

0

0

0

100

60

0

0

0

TABLE 10.6 — (Continued)

Forage category

Min. calories/day

Max. calories/day

Daily activity (%)

kcal/day

Individual/kg/day

Min. retention (%) after:

Max. retention (%) after:

Maint

Harvest

Process

Maint

Harvest

Process

Maint

Harvest

Process

Min.

Max.

Min.

Max.

1 day

1 wk

1 mth

6 mths

1 year

1 day

1 wk

1 mth

6 mths

1 year

Freshwater turtles

160

400

1040

200

500

1300

10

25

65

1600

2000

4.00

16.00

100

20

0

0

0

100

50

0

0

0

Reptiles

80

640

880

100

800

1100

5

40

55

1600

2000

15.00

30.00

100

15

0

0

0

100

50

0

0

0

Amphibians

80

400

1120

100

500

1400

5

25

70

1600

2000

25.00

40.00

100

15

0

0

0

100

50

0

0

0

Shellfish

32

240

1328

40

300

1660

2

15

83

1600

2000

50.00

250.00

100

10

0

0

0

100

50

0

0

0

Sea turtle eggs

32

960

608

40

1200

760

2

60

38

1600

2000

10.00

200.00

100

15

0

0

0

100

30

0

0

0

Maize

640

400

560

800

500

700

40

25

35

1600

2000

2.00

12.00

100

90

60

20

0

100

100

90

70

40

Beans

560

400

640

700

500

800

35

25

40

1600

2000

2.00

12.00

100

80

30

0

0

100

98

80

50

20

Squash

560

400

640

700

500

800

35

25

40

1600

2000

3.00

18.00

100

70

20

0

0

100

95

70

20

5

Amaranth

80

800

720

100

1000

900

5

50

45

1600

2000

3.00

5.00

100

80

50

0

0

100

98

80

50

20

Sunflower

160

640

800

200

800

1000

10

40

50

1600

2000

5.00

8.00

100

90

50

10

0

100

100

85

60

25

Maygrass

240

720

640

300

900

800

15

45

40

1600

2000

5.00

8.00

100

80

50

0

0

100

98

80

30

10

Sumpweed

160

880

560

200

1100

700

10

55

35

1600

2000

8.00

12.00

100

80

40

0

0

100

95

70

20

5

Acorns

32

1200

368

40

1500

460

2

75

23

1600

2000

8.00

12.00

100

80

20

0

0

100

98

70

30

10

Hickory nuts

32

400

1168

40

500

1460

2

25

73

1600

2000

2.00

4.00

100

80

30

0

0

100

100

75

40

15

Cattail/bullrush

32

1040

528

40

1300

660

2

65

33

1600

2000

2.00

4.00

100

80

20

0

0

100

90

40

5

0

Chenopods

80

800

720

100

1000

900

5

50

45

1600

2000

6.00

8.00

100

80

40

0

0

100

95

70

20

5

TABLE 10.7 Returned kcal/30 m2 Unit of Prime Habitat (example: 1237 b.p.)

Forage category

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Very large saltwater fish

946

1260

1631

2288

3395

4389

4389

3395

2615

1864

1260

946

Large saltwater fish

745

947

1326

1843

2645

3338

3338

2645

1966

1415

1010

745

Medium saltwater fish

885

962

1446

2087

2670

3118

2989

3091

2332

1756

1099

948

Small saltwater fish

318

316

379

679

1050

1286

1185

1050

738

568

437

364

Very small saltwater fish

111

100

126

339

583

695

634

521

402

341

213

148

Large freshwater fish

867

721

668

635

644

640

640

644

672

707

763

867

Medium freshwater fish

199

180

170

209

232

304

288

279

241

221

216

219

Small freshwater fish

47

40

44

93

144

170

154

144

104

83

69

58

Very small freshwater fish

7

6

8

20

34

41

38

31

24

20

13

9

White-tailed deer

1745

1745

1745

1696

1676

1804

2216

2488

2568

2371

2098

1821

Black bear

29

31

32

32

32

39

44

49

50

45

38

34

Alligator

423

423

531

630

630

531

423

388

415

414

388

388

Wild turkey

116

119

138

175

241

293

254

185

158

137

133

122

Raccoon

146

146

146

139

151

177

200

240

227

200

185

165

Opossum

33

28

56

47

42

37

33

28

56

47

42

37

Rabbits

84

77

70

67

122

116

106

74

92

85

69

58

Squirrels

34

38

36

39

37

38

38

44

44

40

38

37

Upland birds

5

7

9

11

20

33

36

32

22

16

11

7

Waterfowl

155

122

95

72

52

55

77

102

129

159

194

191

Wading birds

39

39

58

81

109

135

164

162

129

101

77

57

Sea turtles

17

24

152

471

1065

2020

2020

1065

471

152

24

17

Freshwater turtles

338

338

338

338

338

342

346

357

361

353

349

342

Reptiles

20

20

20

20

20

20

23

30

36

33

30

23

Amphibians

37

30

26

26

26

26

26

26

58

69

69

47

Shellfish

3959

3959

4355

4750

5542

6334

7126

7917

7917

6730

5146

4355

Sea turtle eggs

0

0

0

0

0

954

1431

1590

1272

795

318

0

Maize

0

0

0

0

0

0

0

15205

19006

9503

0

0

Beans

0

0

0

0

0

0

0

4496

5620

3372

0

0

Squash

0

0

0

0

0

0

0

935

3739

4674

2337

0

Amaranth

0

0

0

0

0

1317

5270

6587

6587

3293

0

0

Sunflower

0

0

0

0

0

464

1858

2322

2322

1161

0

0

Maygrass

0

0

0

0

320

801

801

480

160

0

0

0

Sumpweed

0

0

0

0

169

422

422

253

84

0

0

0

Acorns

0

0

0

0

0

0

2621

4717

5241

3669

0

0

Hickory nuts

0

0

0

0

0

0

5531

9956

11062

7744

0

0

Cattail/bullrush

0

0

1175

2742

3917

3917

3133

2350

1567

783

0

0

Chenopods

0

0

0

195

455

651

651

520

325

130

0

0

TABLE 10.8. Sustainable Population Estimates by Temporal Period

Group

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Mean

Late

Archaic

19

21

21

27

33

38

81

136

163

115

47

20

60

Early Woodland

46

43

36

42

50

57

113

283

427

318

134

56

134

Middle Woodland

143

115

81

80

86

92

144

641

1137

912

432

194

338

Late Woodland

239

194

134

128

134

143

201

867

1535

1327

705

334

495

Early Mississippian

452

366

251

232

244

268

360

1476

2629

2320

1269

624

874

Middle Mississippian

377

301

201

180

173

171

230

1135

2089

1872

1059

530

693

Late Mississippian

470

379

257

235

231

242

318

1364

2478

2233

1286

658

846

Proto-/historic Indian

542

435

294

263

253

258

337

1501

2754

2503

1461

758

946

APPENDIX 10.1

GIS Methods Used in the Development of Specific Surfaces

Because this analysis is fundamentally based on map algebra (i.e., production of composite spatial probabilities by adding, subtracting, or multiplying surfaces together), the required model output is a raster dataset. The highest-resolution raster dataset is the USGS National Elevation Dataset (NED) with a pixel size of 30 × 30 m (LiDAR data was available only for a narrow strip along the modern shoreline and for a large section around Ft. Stewart, in the interior of Bryan and Liberty counties). Therefore, all the polygon data was converted to raster datasets at this resolution. The HSD point dataset was transformed through a surface analysis using splining (fitting a curve by polynomial interpolation) to produce a bathymetric grid at a resolution of 30 × 30 m. A somewhat better bathymetric model would have come from using kriging (a measure of distance weighting using least-squares estimation), but it proved too difficult to process the more than 9 million datapoints in the study area, repeatedly crashing ArcGIS. Nevertheless, the close spacing of hydrographic points was usually such that the entire underwater area (often including many miles upriver) had a high level of accuracy, even somewhat better than the above sea level digital elevation model. The LULC data is the most generalized raster surface (at 90 × 90 m), so it was resampled to a 30 × 30 m resolution. However, the LULC data were only used as a means to find correlations between soil and vegetation types and were not used in map algebra calculations.

Derived Variables

The secondary or derived datasets include the following:

Water Availability (WA): Each map unit was ranked as a decimal value between 0 (always dry) and 1 (permanent water) based on the National Wetlands Inventory (NWI) categorization as none, intermittent, seasonal, or permanent. This was moderated by depth classification (e.g., shallow wetlands being quicker to dry out than deeper ones), plus saturation/drainage characteristics from the SSURGO dataset (e.g., sandy soils hold water for shorter periods of time than clay ones), and a cost distance evaluation (using the NED) from permanent water sources, to capture the potential for uplands to retain water (e.g., flat areas near permanent water are likely to hold more water longer).

Water Salinity (WS): Decimal values were calculated from freshwater (0) to saltwater (1) based on a simple distance evaluation (connected water only) from the NWI saltwater zone to the furthest area of tidal influence, but also moderated by vegetation density (e.g., denser floating or flooded vegetation is less permeable to tidal flow than open water). This model is a generalization of the complex nature of salinity in an estuarine environment, but it is a significant key indicator of habitat, and more accurate spatial data is currently not available.

Soil Texture (ST): Decimal values range from the finest texture (clay, 0) to the coarsest (coarse sand, 1). This is based on ordering all 18 represented soil texture classifications from the SSURGO dataset by grain size (clay = 0, silty clay = 1, silty sandy clay = 2, sandy clay = 3, clayey silt = 4, … coarse sand = 17). The results were then given decimal values by simply dividing by the maximum value of 17. Anything coarser than coarse sand is not considered soil in this analysis, and does not occur in the study area anyway.

Soil Fertility (SF): Decimal values range from poor (0) to very good (1) based first on the categorical value presented by the SSURGO crop-capacity classes (poor, moderate, good, or very good). This is modified by adding in a reranking of the soil-texture values so that the loamiest soils ranked highest and the clay soils ranked lowest (sandy soils were in-between). Soil drainage was also added in as a secondary factor, with good (but not excessive) drainage improving fertility.

Vegetation Density (VD): Decimal values range from open (0) to dense (1). For the wetlands this is based on the NWI maps and their indications of open, emergent, scrub, and forested, plus their depth (deeper water being less likely to contain dense vegetation), and substrate (sandier substrates supporting less dense vegetation). For upland areas, vegetation density is derived from the open land, grassland, and forest capacity classes from the SSURGO dataset, as the LULC is not particularly suited to identifying prehistoric vegetation density.

Vegetation Type (VT): The goal was to define the specific vegetation types that function as attractors to different species at different times of the year. The primary attractor in this sense is deciduous trees; for the production of nuts and seeds (specifically hickory nuts and acorns). Additionally, live oak acorns are such a localized highly abundant resource, that one variable was specifically extracted to represent the density of live oaks. Two variables were derived:

VT1. The proportional ratio of deciduous trees, from none (0) to 100% (1). This evaluation is based on correlating the SSURGO soil names with the LULC, NWI, and L4E data to find the proportion of deciduous wetlands and forest types associated with each soil type, and then projecting those values to respective map units with that soil type (i.e., accuracy is derived from the SSURGO dataset not the LULC or L4E). By using the soil types in this way, it eliminates the problem of modern artifacts (such as roadways) and lower resolution found in the LULC dataset; the only assumption is that modern land practices (such as timbering) have not disproportionally affected specific soil types in a way that has fundamentally changed their ratio of deciduous trees. If this assumption is not supportable, the effect will very likely be inversely proportional to the rarity of the soil type; and thus common soils may still hold up well.

VT2. The proportion of live oaks, from none (0) to 100% (1). This variable was created using the same methods as VT1 to identify the proportion of live oaks associated with each soil type, and then projecting that to each map unit.

Water Depth (WD): The goal here was to define the depths at which fish and shellfish (those in the estuarine, marine, and freshwater environments included in this study) congregate, breed, and feed at different times of the year. The maximum depth in the study area is -11 m, while the average maximum depth for all underwater areas is -4 m. Neither water depth nor ground surface elevation is naturally “pegged” at either end by finite definitions (in the same way that water availability can be considered “absent” or “permanent”). Rather they are tied to a single measure (sea level) and are open on the other end (limited only by the maximum value found in the study area). To avoid rescaling effects that would be created by changing the limits of the analysis, the methods employed here were to define a particular target depth, assign it the value of 1, and then to calculate the decimal value for any map unit as a z-value on a normal curve that extends 4 m in either direction. Three variables were derived in this category:

WD1. Shallow water: the value of 1 was given to the splined HSD surface water depth of -1 m; the decimal values fall off along a normal curve in either direction (reaching 0 on the deeper side at -4 m).

WD2. Moderate depth: the value 1 is set at -2 m.

WD3. Deep water: the value 1 is set at -4 m.

Elevation Zone (EZ): Calculated in the same way as the water depth variables, the goal was to identify those elevation targets that were sought out or functioned as attractors on some level for the terrestrial species in the analysis. These were identified as the salt marsh/sea level, the bluffs of rivers or modern shorelines zones, the Silver Bluff and Princess Anne Shoreline complexes (which form the highest elevations of the next most recent Pleistocene barrier islands and are high in hickory/live oak woodlands), the Talbot and Penholoway formations (which form the most prominent ridgelines in the interior and which sit above the interior freshwater marshes), and the Trail Ridge and Wicomico complexes (which are the next prominent elevation breaks; the long ridgeline of which forms an excellent north-south travel corridor). Five variables were thus derived in this category:

EZ1. Salt marsh/sea level: the value of 1 was given to NED elevation of 0 m; the decimal values fall off along a normal curve until they reach 0 at 4 m.

EZ2. River bluff/shore margin: the value 1 is set at 3 m.

EZ3. Silver Bluff/Princess Anne formations: the value 1 is set at 11 m.

EZ4. Talbot/Penholoway formations: the value 1 is set at 21 m.

EZ5. Trail Ridge/Wicomico complexes: the value 1 is set at 31 m.

Habitat Surfaces

To prepare a habitat model (HM) for each forage category, the strength of the association was determined to be either positive or negative and based on its interpreted intensity. Each forage category was assigned a weight ranging between -10 and 10, which represented its strength of association for each environmental variable, for each month of the year. These attractor/repulsor strengths were the basis for the HM, but any one can be changed at any time and a revised surface can be recalculated without affecting the theoretical framework or other formulas.

To derive a habitat surface for each forage category for each month, a formula was created that followed a set format:

HM = Σ W (Vi)

n

i = 1

Each formula was transformed into ArcGIS syntax and calculated using the map algebra tool in ArcGIS’s Spatial Analyst extension. Weights (W) for neutral variables (V) were set at 0. Because the model is weighted additive in nature, negative correlations had to first be inverted by multiplying the negative weight by the variable and then adding the absolute value of the weight to the product. This allowed the inclusion of both attractor and repulsor type effects in a single formula. The weights are stored in an Excel spreadsheet where the ArcGIS syntax is automatically generated for them. An example of one formula (for turkey during May) generated in ArcGIS syntax is:

HM(turkey5) = (([wa] * -8) + 8) + (([ws] * -8) + 8) + (([st] * 6) + 0) + (([sf] * 1) + 0) + (([vd] * -6) + 6) + (([vt1] * 0) + 0) + (([vt2] * 0) + 0) + (([wd1] * 0) + 0) + (([wd2] * 0) + 0) + (([wd3] * 0) + 0) + (([ez1] * -3) + 3) + (([ez2] * -1) + 1) + (([ez3] * 1) + 0) + (([ez4] * 2) + 0) + (([ez5] * 3) + 0).

The resulting surfaces were each transformed exponentially as a factor of the forage category’s interpreted overall dependence on high-ranking habitat. This transformation was designed to inject the relative adaptability of the species into the final output and was largely based on the resilience factor (discussed in more detail in the main body of the chapter). Those forage categories with high resilience were assumed to have high adaptability, and less dependence upon pristine habitat. Those with low resilience were generally assumed to be more dependent upon pristine habitat elements.

After any exponential transformation of the results they were each multiplied by a masking surface to eliminate algebraic remainders. Because the formulas are additive and not multiplicative, there will always be some remaining very low-scoring values within habitat areas that are not suitable for the forage category at all. For example, a very low potential for maize in the open ocean is possible because the additive formula must include all areas of the water availability surface despite the fact that the soil texture surface makes maize habitat impossible in water. In other words, in an additive formula one restrictive surface will not cancel out the others as it would in a multiplicative formula. To correct for this, and eliminate such remainders, several surface masks were created. These were surfaces keyed to specific limitations including; marine (no salt marsh), marine (with salt marsh), marine (with beach), freshwater (no estuarine), freshwater (with estuarine), terrestrial (no water at all), and terrestrial (with freshwater and estuarine). They were valued as 0 for the masked area and 1 for the unmasked area then multiplied by the appropriate habitat surfaces. The resulting layers were then divided by their maximum value to produce a decimal surface (to six decimal places) that ranged from 0 to 1.

[1] The National Science Foundation supported DePratter’s original fieldwork for the shoreline project (NSF Oceanography Section Grant # OCE76-02320). This original work was conducted with Jim Howard, formerly of Skidaway Institute of Oceanography, Savannah, Georgia. The GIS and new mapping research portion of this chapter was supported, in part, by a grant in association with the Georgia Coastal Ecosystems Long Term Ecological Research project and the National Science Foundation Grant (NSF grant OCE-0620959). The Georgia Department of Natural Resources (GDNR), the Sapelo Island National Estuarine Research Reserve, Department of Anthropology at the Ohio State University, the South Carolina Institute of Archaeology and Anthropology at the University of South Carolina, and the Department of Anthropology at the University of Georgia. We would also like to thank Kimberly Swisher for her diligence in examining the maps for outliers and misplaced sites. The authors would like to thank John Turck, Amanda Roberts Thompson, Steven Pennings, Mark Williams, Merryl Alber, and Clark Alexander of Georgia Coastal Ecosystems Long Term Ecological Research project for their support of our past and ongoing research. The collections from this study are housed at the Laboratory of Archaeology at the University of Georgia. Finally, we thank the reviewers, Torben Rick, Thomas Pluckhahn, and Chris Rodning for their thoughtful comments.

[2] Thompson conducted the GIS analysis of the data in 2007; therefore records from the GASF for this year were used in this analysis. Upon completion of the paper in 2011, the authors again consulted the GASF to see if any additional sites would impact the current results. Few sites have been added to the site file in the study region since the original analysis and none that would alter the current interpretations in this chapter.

[3] The authors would like to thank the National Science Foundation for providing support for this work through grant OCE-0620959. We would also like to thank the Georgia Coastal Ecosystems Long Term Ecological Research project for their logistical and field support of the geological and archaeological research. We would also like to thank Andrew Ivester, George Brook, Mike Robinson, Nick Scoville, and Claudia Venherm for their help with sampling and analysis. John Turck would like to thank his dissertation committee, Ervan Garrison, David Hally, Stephen Kowalewski, and Victor Thompson, as much of his contribution was directly related to his dissertation. Thanks to Tom Pluckhahn, Torben Rick, Chris Rodning, and Chester DePratter for their comments and suggestions. Special thanks to Victor Thompson and David Hurst Thomas for inviting us to submit our recent research on the Georgia Coast to this volume.

[4] The author would like to thank the Edward John Noble Foundation, the St. Catherines Island Foundation, the American Museum of Natural History, and the University of West Florida for funding this project; Dave Thomas for support with this project; C. Fred T. Andrus, Sarah Bergh, and Christina Friberg for assistance with analysis. Additionally, the author acknowledges Royce Hayes and the St. Catherines Island staff for their help with fieldwork and island logistics. Since this project served as his master’s thesis at the University of West Florida, the author thanks his committee members: John Worth, Victor Thompson, Chester DePratter, and Norma Harris for their contributions, and the hardworking crew: Sarah Everhart, Brian Miller, John Turck, Hannah Morris, Amanda Roberts Thompson, Victor Thompson, Chester DePratter, and Elliot Blair.

[5] This work would not have been possible without the generosity of Springfield Legacy and the Devendorf family. Financial assistance was also provided by Columbia University and the Steigler Fund. The project was also heavily dependent on the crew of undergraduates from Columbia and Barnard College, as well as their supervisors drawn from across the discipline, all of whom can attest to the challenges of excavating more than a thousand STPs in coastal Georgia during the summer.