Abstract
Important methodological advances have led to the availability of high-resolution datasets relating to environment, settlement, and chronology in archaeological studies. Such advances in resolution can lead to new understandings, but they also create new issues. In this chapter, we discuss synthetic datasets and their utility in identifying and understanding large-scale population movements. We focus on the 14th and 15th century AD Savannah River Valley as a case study given its position as one of the earliest, synthetic explorations of the multi-faceted relationship between settlement, mobility, climate, and culture in the archaeological literature of the Eastern Woodlands. We begin by outlining some of the history of synthetic approaches to settlement and demographic analysis in Eastern North America and discuss how this tradition of study has successfully and productively made the leap to the digital realm in recent years, using the Digital Index of North American Archaeology (DINAA) as an example. We then demonstrate how the types of data indexed by DINAA can be used to identify regional population shifts and investigate the demographic and social trajectories in play. This approach provides an alternative to traditional methods of identifying episodes of migration, such as the various analyses applied to artifact assemblages or to ancestral remains. Due to the nature of the archaeological record in this region, which we will return to, these more traditional analytical approaches are not always applicable or available. Using newly created digital datasets, we present evidence for a large-scale immigration to the neighboring coastal region of Georgia, using methods that we believe can be widely and productively applied elsewhere to document large-scale population movements.
Elements of this chapter have previously appeared in Ritchison (2018).
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Notes
- 1.
Dates resulting from Bayesian modeling are presented as cal. (in italics) to distinguish them from non-modeled dates following recommendations of Hamilton and Krus (2018) and the Society for American Archaeology Style Guide.
- 2.
Note that a previous iteration of the following model was reported in Ritchison (2018); the iteration here excludes dates from ancestral remains that were created without the knowledge or consent of the descendant community.
- 3.
Capitalized forms of Phase and Date represent elements of the coding language (Chronological Query Language; CQL2) used in OxCal 4.4.
- 4.
All modeled date ranges in the text are reported at the 68.3% highest probability density interval.
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Acknowledgements
We would like to thank the editors, and our co-contributors, for bringing together this important set of work under a singular banner and for their efforts in seeing it along to its final form. Figures 9.1, 9.2, 9.3 and 9.4 are used courtesy of the Eastern States Archaeological Federation. Joshua J. Wells is to be thanked for producing versions of Figs. 9.5 and 9.6 using the DINAA dataset. Large scale analyses are, of course, a team effort, and the information reported here reflects the work of dozens of colleagues over more than a century of archaeological research. As we move forward, working with indexed and integrated legacy data will be increasingly important and we thank those whose assistance has, and will continue to be, invaluable in making accessible the products of archaeological inquiry.
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Ritchison, B.T., Anderson, D.G. (2022). “Vacant Quarters” and Population Movements: Legacy Data and the Investigation of a Large-Scale Emigration Event from the Savannah River Valley to the Georgia Coast. In: Cook, R.A., Comstock, A.R. (eds) Following the Mississippian Spread. Springer, Cham. https://doi.org/10.1007/978-3-030-89082-7_9
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