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A Pinus cembra L. tree-ring record for late spring to late summer temperature in the Rhaetian Alps, Italy

Journal article
Authors R. Cerrato
M. C. Salvatore
B. E. Gunnarson
Hans W. Linderholm
L. Carturan
M. Brunetti
F. De Blasi
C. Baroni
Published in Dendrochronologia
Volume 53
Pages 22-31
ISSN 1125-7865
Publication year 2019
Published at Department of Earth Sciences
Pages 22-31
Language en
Links dx.doi.org/10.1016/j.dendro.2018.10...
Keywords Maximum latewood density, Swiss stone pine, Pinus cembra
Subject categories Climate Research

Abstract

Ongoing climate change strongly affects high-elevation environments in the European Alps, influencing the cryosphere and the biosphere and causing widespread retreat of glaciers and changes in biomes. Nevertheless, high-elevation areas often lack long meteorological series, and global datasets cannot represent local variations well. Thus, proxy data, such as tree rings, provide information on past climatic variations from these remote sites. Although maximum latewood density (MXD) chronologies provide better temperature information than those based on tree-ring width (TRW), MXD series from the European Alps are lacking. To derive high-quality temperature information for the Rhaetian Alps, Pinus cembra L. trees sampled at approximately 2000 m a.s.l. were used to build one MXD chronology spanning from 1647 to 2015. The MXD data were significantly and highly correlated with seasonal May-September mean temperatures. The MXD chronology showed a generally positive trend since the middle of the 19th century, interrupted by short phases of climatic deterioration in the beginning of the 20th century and in the 1970s, conforming with the temperature trends. Our results underline the potential for using Pinus cembra L. MXD to reconstruct mean temperature variations, especially during the onset and latter part of the growing season, providing additional information on parts of the growing season not inferred from TRW. Future studies on MXD for this species will increase the availability of temporal and spatial data, allowing detailed climate reconstructions. © 2018 The Authors

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