Temples through time: a radiocarbon-based chronology for the Bronze to Iron Age temple sequence at Pella (Jordan)
Dr Lyndelle Webster1, Dr Stephen Bourke2, Ms Anne Dighton3, Dr Quan Hua4, Dr Geraldine Jacobsen4
1Austrian Academy Of Sciences, Vienna, Austria, 2University of Sydney, Sydney, Australia, 3University of Queensland, Brisbane, Australia, 4ANSTO, Kirrawee DC, Australia
The sequence of temples at Tabaqat Fahil (Pella) is among the largest and best-preserved in the southern Levant. Its six phases of architecture – exposed in recent decades by the University of Sydney – exemplify the longevity of sacred precincts and documents how temple designs and cult practices developed over time. Pella offers a unique chance to investigate these structures with up-to-date approaches and techniques, since many parallel examples were exposed in the early–mid-20th century (e.g. Megiddo, Shechem and Beth Shean). Pella’s six consecutive temple phases are particularly well-suited to AMS radiocarbon-based dating with a Bayesian approach.
Samples for 14C dating were collected throughout the seasons of excavation, and a substantial dataset developed in collaboration with ANSTO and other partner institutions. This paper will present an analysis of the presently available data, comparing the results of a 14C-based chronology with the traditional dating of each phase, and exploring implications for wider chronological issues.
Lyndelle is a postdoctoral researcher at the Austrian Academy of Sciences, her research focusing on radiocarbon-based approaches to Bronze and Iron Age chronology in the Near East. She is currently responsible for 14C dating on the project “Tracing Transformations in the Southern Levant” directed by Dr Felix Höflmayer which, through cooperation with multiple excavation projects and AMS laboratories, has developed large new datasets from key sites, including Pella, Lachish, Gezer and Azekah. Lyndelle’s recently completed PhD provides the first detailed assessment of Late Bronze Age chronology in the southern Levant using 14C data and Bayesian analysis.