Shellfish tending and harvesting has been central to Indigenous management of marine resources in California throughout the Holocene, and today's Indigenous stewards and archaeologists alike understand that the seasonal rhythms associated with these activities are key to their ecological effectiveness. In order to detect these rhythms, scholars have often looked to the oxygen isotope composition of archaeological shell, which tracks with seasonal variations in sea-surface temperature. These isotopic data are quantitative and the physical processes that condition them are well understood, yet analyses have generally relied on semi-qualitative expert assessments of isotope 'profiles' on a case-by-case basis, creating challenges for reproducibility and intercomparability of results.
We present here a fully modeled and automated framework for deriving statistically-sound and reproducible estimates of harvest seasonality on the basis of isotopic data (from California mussel, in this case). This approach allows detailed characterization of the uncertainties inherent in isotopic determinations of seasonality, facilitates analysis of larger samples necessary to address intra- and inter-site and diachronic variability, and offers a principle for triangulating among multiple lines of evidence in a manner recognizant of the relative uncertainties of each line.
The elaboration of an explicit analytical model such as this one also invariably precipitates insights into the basic theoretical and methodological questions that the model is designed to address. We will reflect on some of these insights, as well as report on nascent collaborations and next steps for this unavoidably multidisciplinary project.
Speaker: Jordan Brown, UC Berkeley
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