Straightening the calibration curve

Michael Balter reports on a new radiocarbon calibration called INTCAL09. The calibration curve purports to provide a calendar age calibration up to 50,000 years ago for AMS radiocarbon dates.

Balter’s report gives a good account of the basics. The atmospheric concentration of carbon-14 varied over time, so that organisms from some ancient times started with a higher proportion and other times started with a lower proportion. The radiocarbon dating technique depends on knowing this initial carbon-14 proportion. But we can only figure this out by comparing the present carbon-14 proportion in things whose ages we know – like tree rings. Before 25,000 years ago, good non-radiocarbon chronologies are hard to come by, so up to now there has been no good calibration curve.

More recently, however, thanks to new and more accurate data from foraminifers, corals, and other sources--plus some fancy statistical treatments that help predict which way data gaps bend the curve--the INTCAL group has been able to resolve most of the discrepancies. "It took the group quite a while to come together and agree," says INTCAL team leader Paula Reimer, a geochronologist at Queen's University Belfast in Northern Ireland. But the new data, combined with what Reimer calls a "real sense of necessity" among team members to resolve the debates, won the day.

I’m skeptical when I see calibrated dates because they seldom report the calibration error. I like “fancy statistical treatments” that actually report their error. The entire reason a calibration model like INTCAL09 looks good is that it represents only one component of variability within a large set of separate chronometric datasets. The “debates” are more or less about whether that component is time, and if not what other factors must be controlled. Resolving the debates doesn’t mean that the model will reduce the error associated with calibrating a given date – it (hopefully) means that calibrated dates will be unbiased.

In principle, calibration is good because it facilitates comparison between radiocarbon and other dating methods, like OSL or ESR. It also gives a more accurate view of the temporal scale of events – the radiocarbon chronology compresses the period between 40,000 and 10,000 years ago into 25,000 radiocarbon years instead of 30,000 calendar years. It makes a difference, if for no other reason, because it makes the initial Upper Paleolithic look more rapid than it really was.

Julien Riel-Salvatore ruminates on similar issues (“Paleolithic radiocarbon legerdemain”)

The really bad dating problem happens at points where the atmospheric carbon-14 declined. Some declines occurred with nearly the same rate as actual decay of the carbon-14. A younger sample may then up with the same carbon-14 proportion as an older sample, with no way to tell between them. (I discussed this problem as applied to initial Upper Paleolithic-era dates in “Radiocarbon fudgery”.)

Because different datasets vary in their results, apparent declines in atmospheric carbon-14 seem more common in those individual datasets than in the model that reflects their common features. The atmospheric carbon should be better reflected by the model – after all, there’s only one atmosphere, so these datasets should reflect the same value.

But any single series of dates ought to have temporal stochasticity more like an individual dataset. When we take dates from bone collagen – which is not one of the kinds of data with chronological controls – there ought to be a separate, source-specific error that we can’t control by a calibration model.

Does it matter? I think we should assume the resolution of a 40,000-year-old calibrated radiocarbon date is no better than 3000 years. And in some cases more – depending on the atmospheric trend. If one date is 3000 years earlier than the other, I think there’s a very good likelihood that the earlier date really did happen first.

Too conservative? I’d like to see somebody run the numbers on it.