Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

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Castillo Díaz, Jorge del
Aguilera, MònicaAguilera, Mònica - ORCID ID
Voltas Velasco, JordiVoltas Velasco, Jordi - ORCID ID
Ferrio Díaz, Juan PedroFerrio Díaz, Juan Pedro - ORCID ID
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Stable isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes) and (2) deriving precipitation maps from Δ13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex topography and climate (MAP = 303–1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N = 38; Quercus ilex L.; N= 44; pooling period: 1975–2008). By combining multiple regression and geostatistical interpolation, we generated one Δ13 C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding Δ13C-isoscape (September–November from Q. ilex; December–August from P. halepensis). Our approach showed a predictive power for MAP (RMSE = 84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE = 80–83 mm, N= 65), being only outperformed when using a much denser meteorological network (RMSE=56–57 mm, N=340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks.
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Journal of Geophysical Research: Biogeosciences, 2013, vol. 118, p. 352-360