A Bayesian multi-proxy contribution to the socioeconomic, political, and cultural history of late medieval Capitanata (southern Italy)

Autor: Cocozza C., Teegen W. -R., Vigliarolo I., Favia P., Giuliani R., Muntoni I. M., Oione D., Clemens L., Gross M., Roberts P., Lubritto C., Fernandes R.
Přispěvatelé: Cocozza, C., Teegen, W. -R., Vigliarolo, I., Favia, P., Giuliani, R., Muntoni, I. M., Oione, D., Clemens, L., Gross, M., Roberts, P., Lubritto, C., Fernandes, R.
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Scientific Reports
Popis: Medieval southern Italy is typically viewed as a region where political, religious, and cultural systems coexisted and clashed. Written sources often focus on elites and give an image of a hierarchical feudal society supported by a farming economy. We undertook an interdisciplinary study combining historical and archaeological evidence with Bayesian modelling of multi-isotope data from human (n = 134) and faunal (n = 21) skeletal remains to inform on the socioeconomic organisation, cultural practices, and demographics of medieval communities in Capitanata (southern Italy). Isotopic results show significant dietary differences within local populations supportive of marked socioeconomic hierarchies. Bayesian dietary modelling suggested that cereal production, followed by animal management practices, was the economic basis of the region. However, minor consumption of marine fish, potentially associated with Christian practices, revealed intra-regional trade. At the site of Tertiveri, isotope-based clustering and Bayesian spatial modelling identified migrant individuals likely from the Alpine region plus one Muslim individual from the Mediterranean coastline. Our results align with the prevailing image of Medieval southern Italy but they also showcase how Bayesian methods and multi-isotope data can be used to directly inform on the history of local communities and of the legacy that these left. Results - Faunal isotopic results. - Human isotopic results and Bayesian modelling Discussion Conclusion Methods
Databáze: OpenAIRE