Examining the Maya Collapse through Ancient DNA

Summary

This is an abstract from the "The Movement of People and Ideas in Eastern Mesoamerica during the Ninth and Tenth Centuries CE: A Multidisciplinary Approach Part II" session, at the 88th annual meeting of the Society for American Archaeology.

Scholars have examined the causes and impacts of the Maya collapse for over a century, using every available line of evidence. In the last decade ancient DNA (aDNA) has proven to be a powerful tool in understanding large-scale population transformations during key time periods. This technology, however, has primarily been applied to archaeological questions about ancient Eurasia. Due to poor preservation, acquisition of ancient DNA in hot, humid places, such as the Maya region, has been extremely difficult. As of September 2022, only 25 ancient Maya genomes have been published. However, advances in ancient DNA technology have now made it possible to recover aDNA from challenging environments. This paper corrects the imbalance of aDNA research in the Maya region and explores the significant demographic events that occurred during the ninth–tenth centuries through the examination of over 300 individuals from the Maya Lowlands and Highlands, along with a coeval control population from Central America. Data from these individuals provide insight into ancient Maya familial structure, population size, inter- and intrasite population structure, and more during the Late and Terminal Classic periods. Such insights were possible only through the international collaboration of archaeologists, biological anthropologists, linguists, geneticists, students, and local communities.

Cite this Record

Examining the Maya Collapse through Ancient DNA. Jakob Sedig, Esther Brielle, Roslyn Curry, David Reich, Vera Tiesler. Presented at The 88th Annual Meeting of the Society for American Archaeology. 2023 ( tDAR id: 473820)

Keywords

Spatial Coverage

min long: -94.197; min lat: 16.004 ; max long: -86.682; max lat: 21.984 ;

Record Identifiers

Abstract Id(s): 36510.0