End-to-end Bayesian analysis of14C dates reveals new insights into lowland Maya demography

ABSTRACT Archaeologists and demographers increasingly employ aggregations of published radiocarbon ( 14 C) dates as demographic proxies summarizing changes in human activity in past societies. Presently, summed probability densities (SPDs) of calibrated radiocarbon dates are the dominant method of using 14 C dates to reconstruct demographic trends. Unfortunately, SPDs are incapable of converging on their true generating distributions even as the number of observations gets large. To overcome this problem, we propose a more principled alternative that combines finite mixture models and Bayesian inference to identify the generating distribution of a set of radiocarbon dates. Numerical simulations and an assessment of the statistical identifiability of our method demonstrate that it correctly converges on the generating distribution. We apply this novel end-to-end Bayesian approach to reconstruct prehistoric Maya demographic growth using a recently compiled Mesoamerican radiocarbon database. Our results show that the Maya Lowlands experienced a century of rapid growth rates (1%) during the Late Classic, followed by a rapid decrease in population during the Terminal Classic, and a subsequent more-modest resurgence in population during the Postclassic. Additionally, a detailed population reconstruction of the important political center of Tikal verifies that slow population growth between the Preclassic and Early Classic gave pace to rapid growth starting around AD 500 and peaking at the beginning of the eight century. Our proposed method verifies previous reconstructions based on settlement patterns and ceramics, but with far more precise time-resolution and characterization of uncertainty than has been possible.