Theoretical and Applied Climatology

, Volume 123, Issue 1–2, pp 233–245 | Cite as

Sensitivity of tree ring growth to local and large-scale climate variability in a region of Southeastern Brazil

  • Alejandro Venegas-GonzálezEmail author
  • Matheus Peres Chagas
  • Claudio Roberto Anholetto Júnior
  • Clayton Alcarde Alvares
  • Fidel Alejandro Roig
  • Mario Tomazello Filho
Original Paper


We explored the relationship between tree growth in two tropical species and local and large-scale climate variability in Southeastern Brazil. Tree ring width chronologies of Tectona grandis (teak) and Pinus caribaea (Caribbean pine) trees were compared with local (Water Requirement Satisfaction Index—WRSI, Standardized Precipitation Index—SPI, and Palmer Drought Severity Index—PDSI) and large-scale climate indices that analyze the equatorial pacific sea surface temperature (Trans-Niño Index-TNI and Niño-3.4-N3.4) and atmospheric circulation variations in the Southern Hemisphere (Antarctic Oscillation-AAO). Teak trees showed positive correlation with three indices in the current summer and fall. A significant correlation between WRSI index and Caribbean pine was observed in the dry season preceding tree ring formation. The influence of large-scale climate patterns was observed only for TNI and AAO, where there was a radial growth reduction in months preceding the growing season with positive values of the TNI in teak trees and radial growth increase (decrease) during December (March) to February (May) of the previous (current) growing season with positive phase of the AAO in teak (Caribbean pine) trees. The development of a new dendroclimatological study in Southeastern Brazil sheds light to local and large-scale climate influence on tree growth in recent decades, contributing in future climate change studies.


Tree Growth Geopotential Height Tree Ring Standardize Precipitation Index Drought Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Priscila Amaral de Sá, Priscila Garcia Geroto and Graziela Meneghel de Moraes for the field and laboratory work. We would also like to thank Dr. Silvio Ferraz for support in calculating WRSI and Dr. Clóvis Angeli Sansigolo for contributions to this study, the National Counsel of Technological and Scientific Development (CNPQ) for financial support (Project 561910/2010-3), and the National Commission for Scientific and Technological Research of Chile (CONICYT- PAI/INDUSTRIA 79090016). We also thank the Department of Biosystems Engineering, from ESALQ-USP, for providing the meteorological data used in this study, and the two reviewers and associate editor for valuable comments to the manuscript.


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Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  • Alejandro Venegas-González
    • 1
    Email author
  • Matheus Peres Chagas
    • 1
  • Claudio Roberto Anholetto Júnior
    • 2
  • Clayton Alcarde Alvares
    • 3
  • Fidel Alejandro Roig
    • 4
  • Mario Tomazello Filho
    • 1
  1. 1.Department of Forest Sciences, College of Agriculture “Luiz de Queiroz”University of São PauloPiracicabaBrazil
  2. 2.Postgraduate Program of Inter-units in Applied Ecology CENA/ESALQUniversity of São PauloPiracicabaBrazil
  3. 3.Forestry Science and Research Institute (IPEF)PiracicabaBrazil
  4. 4.Department of Dendrochronology and Environmental History, IANIGLACCT CONICET MendozaMendozaArgentina

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