A map of autumn precipitation for the third millennium BP in the Eastern Iberian Peninsula from charcoal carbon isotopes

Abstract

Carbon isotope composition ( δ 13C) in tree-rings has become routinely used in palaeoclimatic research for the assessment of changes in plant water availability in seasonally dry climates. However, the distribution of long tree-ring records around the world is very limited. Alternatively, the original climate signal of wood δ 13C is well preserved in fossil charcoal and, accordingly, charcoal δ 13C can be used to quantify past changes in water availability (e.g. precipitation). We report a case study on spatial palaeoclimate reconstruction which aims to characterize the transition between Bronze and Iron Ages, the so-called Iron Age Cold Epoch (ca. 900–300 BCE), using charcoals of Quercus ilex/coccifera from a set of 11 contemporary archaeological sites of eastern Spain. Climatic inferences were obtained after calibrating a linear model predicting seasonal precipitation from δ 13C of Q. ilex wood samples obtained across a rainfall gradient. The best regression model corresponded to September–December (autumn) precipitation ( P aut), in agreement with the fact that Q. ilex is able to exploit previous-year water reserves thanks to very effective water uptake. Subsequently, we estimated P aut from the δ 13C of fossil charcoal to infer spatial patterns in water availability. Overall, estimated past P aut was about 19% higher (296 mm) than present-time values averaged across archaeological sites (249 mm). However, a clear geographic pattern of differences in precipitation could be observed in which the inner continental regions of eastern Spain were characterized by more humid conditions in the past, whereas the coastal strip of the Mediterranean Sea barely differed in past and present P aut values. The quite uniform distribution of archaeological sites over eastern Spain allowed development of contour maps of absolute and relative (to present) past P aut using gridded interpolation methods implemented in a GIS, highlighting the potential of this approach for reconstructing high-resolution spatial patterns of past climate.