advertisement
Science News
from research organizations

A statistical fix for archaeology's dating problem

Date:
September 15, 2021
Source:
Santa Fe Institute
Summary:
Archaeologists have long had a dating problem. The radiocarbon analysis typically used to reconstruct past human demographic changes relies on a method easily skewed by radiocarbon calibration curves and measurement uncertainty. And there's never been a statistical fix that works -- until now.
Share:
advertisement

FULL STORY

Archaeologists have long had a dating problem. The radiocarbon analysis typically used to reconstruct past human demographic changes relies on a method easily skewed by radiocarbon calibration curves and measurement uncertainty. And there's never been a statistical fix that works -- until now.

"Nobody has systematically explored the problem, or shown how you can statistically deal with it," says Santa Fe Insitute archaeologist Michael Price, lead author on a paper in theJournal of Archaeological Scienceabout a new method he developed for summarizing sets of radiocarbon dates. "It's really exciting how this work came together. We identified a fundamental problem and fixed it."

近几十年来,考古学家increasingly relied on sets of radiocarbon dates to reconstruct past population size through an approach called "dates as data." The core assumption is that the number of radiocarbon samples from a given period is proportional to the region's population size at that time. Archaeologists have traditionally used "summed probability densities," or SPDs, to summarize these sets of radiocarbon dates. "But there are a lot of inherent issues with SPDs," says Julie Hoggarth, Baylor University archaeologist and a co-author on the paper.

Radiocarbon dating measures the decay of carbon-14 in organic matter. But the amount of carbon-14 in the atmosphere fluctuates through time; it's not a constant baseline. So researchers create radiocarbon calibration curves that map the carbon-14 values to dates. Yet a single carbon-14 value can correspond to different dates -- a problem known as "equifinality," which can naturally bias the SPD curves. "That's been a major issue," and a hurdle for demographic analyses, says Hoggarth. "How do you know that the change you're looking at is an actual change in population size, and it isn't a change in the shape of the calibration curve?"

When she discussed the problem with Price several years ago, he told her he wasn't a fan of SPDs, either. She asked what archaeologists should do instead. "Essentially, he said, 'Well, there is no alternative.'"

That realization led to a years-long quest. Price has developed an approach to estimating prehistoric populations that uses Bayesian reasoning and a flexible probability model that allows researchers to overcome the problem of equifinality. The approach also allows them to combine additional archaeological information with radiocarbon analyses to get a more accurate population estimate. He and his team applied the approach to existing radiocarbon dates from the Maya city of Tikal, which has extensive prior archaeological research. "It serves as a really good test case," says Hoggarth, a Maya scholar. For a long time, archaeologists debated two demographic reconstructions: Tikal's population spiked in the early Classic period and then plateaued, or it spiked in the late Classic period. When the team applied the new Bayesian algorithm, "it showed a really steep population increase associated with the late Classic," she says, "so that was really wonderful confirmation for us."

The authors produced an open-source package that implements the new approach, and website links and code are included in their paper. "The reason I'm excited for this," Price says, "is that it's pointing out a mistake that matters, fixing it, and laying the groundwork for future work."

This paper is just the first step. Next, through "data fusion," the team will add ancient DNA and other data to radiocarbon dates for even more reliable demographic reconstructions. "That's the long-term plan," Price says. And it could help resolve a second issue with the dates as data approach: a "bias problem" if and when radiocarbon dates are skewed toward a particular time period, leading to inaccurate analyses.

advertisement

Story Source:

Materialsprovided bySanta Fe Institute.注:内容可以编辑为圣yle and length.


Journal Reference:

  1. Michael Holton Price, José M. Capriles, Julie A. Hoggarth, R. Kyle Bocinsky, Claire E. Ebert, James Holland Jones.End-to-end Bayesian analysis for summarizing sets of radiocarbon dates.Journal of Archaeological Science, 2021; 135: 105473 DOI:10.1016/j.jas.2021.105473

Cite This Page:

Santa Fe Institute. "A statistical fix for archaeology's dating problem." ScienceDaily. ScienceDaily, 15 September 2021. .
Santa Fe Institute. (2021, September 15). A statistical fix for archaeology's dating problem.ScienceDaily. Retrieved August 3, 2023 from www.koonmotors.com/releases/2021/09/210915161409.htm
Santa Fe Institute. "A statistical fix for archaeology's dating problem." ScienceDaily. www.koonmotors.com/releases/2021/09/210915161409.htm (accessed August 3, 2023).

Explore More
from ScienceDaily

RELATED STORIES