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By Thomas G. Whitley

2012 In, "Life Among the Tides: Recent Archaeology of the Georgia Bight", Victor Thompson and David Hurst Thomas (editors), American Museum of Natural History Anthropological Papers, New York, NY.

The following study presents the methods and results of a Geographic Information Systems (GIS)-based analysis of prehistoric subsistence economies in the coastal region of the state of Georgia. The study area covers over 4 million acres, and consists of three distinct elements: (1) the Habitat Model (HM) - an interpretation of the intensity of the correlation between a given forage category (prey species, genus, or other grouping) and any map unit (a standard spatial area of 30x30 m or 900 m2) for each month of the year, based on the strength and distribution of key elements (spatial attractors) in their habitat; (2) the Available Caloric Model (ACM) - an interpretation of the total (and mean) number of calories that could be expected in any map unit, given a habitat model value, average size, gender ratios, useable meat weights, and population density estimates for each forage category for each month of the year; and (3) the Returned Caloric Model (RCM) - an interpretation of the total (and mean) calories for each forage category, each month, that could be extracted from any map unit, given the available calories, the technological limitations, the costs of acquiring, processing, and transporting the targets, and the selective restrictions of dietary preference.

Daily foraging radii around known and dated habitation sites are developed from the friction surfaces for both terrestrial and aquatic travel costs, and are used to calculate summary estimates for predicted caloric returns; based on their currently recorded temporal affiliation. By summarizing the habitat, available, and returnable calories for all of the known dated sites by time period, we can generate graphic representations of the predicted dietary sufficiency, diet breadth, carrying capacity, rates of return, caloric retention, and potential surplus for any given site, or averaged for all sites within a given time frame. This comparison allows us to see how people adapted to similar conditions given different habitation locales, seasonalities, technologies, and diets. It also allows us to see which sites could develop large, potentially storable or tradable, caloric surpluses, and which ones faced intense competition, may have maintained social control over neighboring sites, or were well positioned to maximize the benefits of regional transport options.

A more detailed examination of the distribution of each individual forage category around a specific site shows the point at which caloric expenditures exceed predicted returns for each month of the year; illustrating the effective foraging radius for a given species, and points at which that return can be modified by cooperative foraging, or pre-processing the resource. Turned into pseudo-topographic surfaces, the forage return rates can be used to generate predicted pathways from the site to the areas most likely to produce the best returns; i.e., resource collection paths. This allows one to build evidence that particular resource collection sites may be associated with specific habitation sites, and to predict where satellite sites and activity areas will occur (i.e. a local predictive model). On a larger scale, the RCM can be used to help generate a regional predictive model based on dietary preference and predicted caloric availability. This model can be targeted to specific temporal periods, site functions, or task areas.

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