Using the Archaeological Record to Better Understand Models: An Australian Case Study

Summary

In Australia’s desert regions, different conceptual models are sometimes used to explain patterning in late Holocene surface deposits. Among these patterns are distributions of radiocarbon determinations, which have been concurrently explained as generated by intermittent occupation by hypermobile foragers, or growing semi-resident populations of broad-spectrum hunter-gatherers. This paper shows how models connected to the language and logic of record formation can help resolve competing archaeological interpretations. We constructed an agent-based model to explore how cultural and sedimentary deposition and erosion can combine to form patterns in a record of heat-retainer hearths visible on the surface. Initial results suggest that explanations invoking population dynamics or geomorphic processes have the capacity to produce qualitatively similar outcomes. A second chronometric proxy, optically-stimulated luminescence dates on hearth stones, was then used to assess expectations derived from the model based on how the process forms the pattern. These show patterning consistent with geomorphic model expectations to the exclusion of models invoking population dynamics. These findings have implications for interpreting Australian prehistory, contrasting with regional narratives of intensification, while also demonstrating how the formational approach applied here allows the archaeological record to inform back on model mechanics, presenting opportunities for models to be reassessed and reused.

Cite this Record

Using the Archaeological Record to Better Understand Models: An Australian Case Study. Benjamin Davies, Simon Holdaway, Patricia Fanning. Presented at The 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia. 2017 ( tDAR id: 431515)

Keywords

Geographic Keywords
Oceania

Spatial Coverage

min long: 111.973; min lat: -52.052 ; max long: -87.715; max lat: 53.331 ;

Record Identifiers

Abstract Id(s): 16736