Daniel Contreras

Daniel Contreras is an Associate Professor in the Department of Anthropology at the University of Florida, within the College of Liberal Arts and Sciences. His work bridges anthropological geoarchaeology with computational approaches to understanding human-environment interactions across diverse landscapes and time periods.

Dr. Contreras received his PhD in Anthropological Sciences from Stanford University in 2007, an MA in Latin American Studies from Stanford University in 1998, and a BA in Religion with a Certificate in Latin American Studies from Amherst College in 1996.

His research focuses on anthropogenic components of dynamic landscapes and environmental change, with field-based and modeling projects spanning Peru, Utah, Jordan, France, and Greece. Contreras examines landscape change and its relationship to long-term human occupation, investigating how humans have both adapted to and caused environmental changes over millennia. His work integrates archaeological and geomorphic data to improve reconstruction of past population dynamics while accounting for landscape taphonomy.

His recent publications reveal a strong emphasis on methodological innovations in radiocarbon dating, landscape taphonomy, and the integration of geospatial technologies with archaeological inquiry. Contreras frequently applies Bayesian modeling to radiocarbon data to address chronological questions in Andean archaeology, particularly concerning the Chavín Phenomenon. His work also explores the relationship between past climate and prehistoric Mediterranean agriculture using process-based dynamic vegetation models.

Dr. Contreras leads or contributes to multiple international research projects including CHEAP (Chavín Human-Environment Project), SNAP (Stelida Naxos Archaeological Project), SCA (Scaling the Central Andes), GB14C, PIACCH, and RAPT. These projects investigate landscape taphonomy, paleoclimate data downscaling, communal action problems at Chavín de Huántar, and pastoral archaeology in Tanzania.

He has developed innovative approaches to archaeological data analysis, including the QuARI R Shiny Database Interface for lithic analysis and applications of Google Earth Engine for archaeological remote sensing. His teaching includes courses on R for archaeological data analysis and visualization, emphasizing statistical methods and data architecture for archaeological research.