Jordan Brown and Gabriel LewisPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p>The problem of accurately and reliably estimating the annual distribution of seasonally-varying human settlement and subsistence practices is a classic concern among archaeologists, which has only become more relevant with the increasing importance of holistic studies of social and ecological systems aimed at establishing deep historical baselines to ground current practical work in socioenvironmental management. In this paper, we present a novel approach to the analysis of shellfishing seasonality using stable isotope measurements on biogenic carbonate (e.g., mollusk shell). Our approach uses a Bayesian mixture model framework to construct an estimate of the annual distribution of shellfish harvesting activity (within some particular historical context) on the basis of isotope measurement sets from a sample of shell specimens (derived from some corresponding archaeological entity). This framework enables two major advances beyond current isotope sclerochronological methods for archaeological seasonality analysis: (1) flexible specimen-level seasonality assignments that may be as precise or diffuse as the data warrant and may respond to unforeseen seasonal signatures, unrelated to conventional seasons and perhaps only recoverable by mathematical analysis, and (2) full characterization of uncertainty accompanying the estimated density of shellfish harvesting activity at all points throughout the year, all of which may be displayed concisely in a single plot with an estimated density curve and uncertainty envelope. These features of our approach focus analysis and interpretation on the seasonally-varying human practice under study, as well as on exactly the state of our knowledge regarding the annual pattern of variation in that practice, including the portions of this pattern that remain poorly constrained. By treating these issues clearly, we address some common obstacles to the advancement of archaeological seasonality research, particularly as regards the appraisal of sampling adequacy requirements at various scales of analysis and the principled integration of diverse and possibly contradicting lines of evidence in broadly transdisciplinary research in the historical sciences. We hope that further elaboration of the methodological core presented here will aid the ongoing development of the creative and collaborative traditions of scholarship that have emerged around studying local and regional histories of social and ecological relationships, with the aim of healing and strengthening these relationships in the present and future.</p>
archaeomalacology, Bayesian statistics, historical ecology, mollusks, paleoclimatology, sclerochronology, seasonality, shellfishing, shells, stable isotope analysis, zooarchaeology
Archaeometry, Computational archaeology, Environmental archaeology, North America, Palaeontology, Paleoenvironment, Zooarchaeology
Michael Kempf suggested: Margaux Depaermentier:, Michael Kempf suggested: m.depaermentier@unibas.ch, Alejandro Sierra Sainz-Aja suggested: Asier Garcia Escárzaga - asier.garcia@uab.cat, Alejandro Sierra Sainz-Aja suggested: Andre Colonese - andrecarlo.colonese@uab.cat, Alejandro Sierra Sainz-Aja suggested: Igor Gutierrez - fernandoigor.gutierrez@unican.es, Sam Leggett suggested: Alice Rose - alice.rose@durham.ac.uk, Sam Leggett suggested: Paul Szpak - paulszpak@trentu.ca, Sam Leggett suggested: Chris Cheung - christina.cheung@cuhk.edu.hk
No need for them to be recommenders of PCIArchaeology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct Iza Romanowska, Eduardo Herrera Malatesta, Alejandro Sierra Sainz-Aja, Sam Leggett, Christianne Fernee, Anonymous, Asier García-Escárzaga , Paul Szpak , Maria Elena Castiello , Jasmine Lundy , Tansy Branscombe
