David Stone

David Stone

Information

  • Email: dlstone@umich.edu
  • Phone: 734.764.0360
  • Office: 3245 Angell Hall
  • Mailing address: 2160 Angell Hall, Department of Classical Studies, University of Michigan, Ann Arbor, MI 48109-1003
  • Ph.D. 1997, University of Michigan
  • CV
  • Website

Research Interests

Topical/Theoretical

  • Field survey
  • Urbanism
  • Mortuary archaeology
  • Ancient economy
  • Roman empire
  • Spatial analysis and digital data

Geographical

  • North Africa
  • Greece

Research Description

My fieldwork explores patterns of urbanism in Greece and North Africa using surface survey methods. I conducted an urban survey at the site of Leptiminus to investigate the spatial and chronological variation at this poorly-known port city on the east coast of Tunisia. The resulting publication (Journal of Roman Archaeology Supplement 87) chronicled the ‘biography’ of Leptiminus, demonstrating phases of expansion and decline over 1200 years of Punic, Roman, Vandal, and Byzantine rule and contributing to current debates on the nature of Roman imperialism and the ancient economy. My work at Leptiminus has more recently stimulated similar investigations at other cities with the aim of writing additional ‘urban biographies’. I now serve as Director of the Field Survey for the Olynthos Project (Greece), which employs excavation, geophysics and surface survey to study this city and its immediate hinterland.

My library-based research has more broadly explored rural, mortuary, economic, and maritime landscapes of the Punic, Numidian, and Roman periods in North Africa. My PhD thesis led to articles on rural settlement and agricultural ideologies as well as the editorship of a volume on Mortuary Landscapes of North Africa. I continue to work on this material, and recently published an article on burial mounds and state formation in North Africa. My research on the ancient economy has operated at multiple scales, from the study of a corpus of materials (millstones, stamped amphoras), to the evaluation of the nature of growth and the types of models best suited to explaining artifact distribution patterns.