Inbuilt age, residence time, and inherited age from radiocarbon dates of modern fires and late Holocene deposits, Western Transverse Ranges, California

Abstract

Radiocarbon dates from alluvial sections provide maximum deposit ages because of the time lag between formation of the dated material and deposition at the sample site, potentially producing decade- to century-long biases in the dates of historic events, paleoclimatic change, fire histories, and paleoearthquakes. This bias, called the inherited age, combines the inbuilt age distribution, which reflects the age composition of the vegetation of the source area, and the residence time distribution, which includes transport and interim storage prior to final deposition. We tackle inherited age and its components by comparing charcoal dates from two modern fires in southern California, the 2020 Bobcat Fire and the 2013 Grand Fire, with a well-dated late Holocene terrace deposit in the Pallett Creek watershed. Fifty-six radiocarbon dates from the modern fires provide an inbuilt age distribution with a median of 25 years pre-fire (320-year 95% range). An inherited age distribution calculated from 175 terrace deposit dates is older, with a median age of ~90 years (850-year 95% range). Comparing inherited ages calculated from organic-rich versus clastic terrace deposits reveals a slight facies dependence suggesting longer residence times in clastic deposits. We develop a modeled inherited age that incorporates larger calibration uncertainties in pre-1950s samples by combining the modern fire sample distribution with the pre-bomb portion of the calibration curve. The modeled inherited age is younger than the terrace deposit inherited age by only 21 years, indicating inbuilt age, not long residence times, dominates inherited age in this setting. The results imply that paleoearthquakes and climatic event age estimates in the Western Transverse Ranges are up to a century too old. More broadly, dating charcoal from modern fires can constrain inherited age and the resulting distributions can improve the accuracy of dates of past environmental and tectonic events.