Table of Contents Author Guidelines Submit a Manuscript
International Journal of Forestry Research
Volume 2013, Article ID 646759, 8 pages
Research Article

Effect of Climate Variables on Monthly Growth in Modeling Biological Yield of Araucaria angustifolia and Pinus taeda in the Juvenile Phase

Federal University of Paraná (UFPR), Department of Forest Sciences (DECIF), Avenue Pref. Lothário Meissner, 900-Jardim Botânico-Campus III, 80210-170 Curitiba, PR, Brazil

Received 1 March 2013; Revised 16 August 2013; Accepted 30 August 2013

Academic Editor: Gilciano Saraiva Nogueira

Copyright © 2013 Naiara Teodoro Zamin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The aim of this study was to investigate the effect of climate variables on monthly growth in diameter and height of Araucaria angustifolia (Bert.) O. Kuntze and of Pinus taeda L., over a six-year period, as well as verifing the contribution of these variables in the composition of the Chapman-Richards model. To this end, we selected 30 trees of each species and measured monthly the diameter and height, between June 2006 and August 2012. The climate variables were obtained from two SIMEPAR meteorological stations near the plantings. A correlation matrix was constructed to determine the effect of climate variables on the monthly growth. Next a principal component analysis (PCA) was conducted to determine the climate variables to be included in the fit of the Chapman-Richards model. The results indicated that the climate variables with the highest correlation (about 0.6) with monthly growth in diameter and height of the species were temperature, photoperiod and atmospheric pressure, and precipitation for some years of the study. The fitted model that included climate variables showed reduced Syx% of about 0.8% compared to the traditional biological model. However, ANOVA showed no statistical difference between the production estimates obtained by both models.