Abstract

In this paper, four strategies were proposed for modeling tree crown volume using as independent variable stem variables, crown variables, combination of stem and crown variables, and stem volume. We used a dataset comprised of 170 trees from 12 temporary plots located in forest stands in southern Brazil. Models composed of stem variables presented weaker predictive ability. The best model contained crown variables, which explained 78.95% of observed variability. However, implementation of such model is bounded by its independent variables, which are not often measured in forest inventories. The model composed by diameter at breast height and crown length proved to be an adequate modeling approach. The predictive capability was kept by model which is composed by most easily measured variable in a forest - diameter at breast height, also by the most easily acquirable crown variable - crown length. In our suggested model, estimates of and are coefficients that convert volume of a regular geometric solid – RGS is dbh² times crown length) - into crown volume, whilst estimate of is an allometric constant. Key words: Crown modeling, diameter at breast height, crown length, crown volume.

Highlights

  • Tree crowns are responsible for light interception, contribute to the regulation of individual growth, and stand yield (Burkhart and Tomé, 2012; Oliver and Larson, 1996; Cluzeau et al, 1995)

  • Tree crown is an important variable to elucidate what occurs in forest stands and its dynamics and, a great effort has been devoted towards quantification of tree crowns (Burkhart and Tomé, 2012), as well as to its modeling (Godin, 2000)

  • The observed relationships indicated that most of the chosen variables for this study presented potential to be effectively utilized for modeling crown volume

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Summary

Introduction

Tree crowns are responsible for light interception, contribute to the regulation of individual growth, and stand yield (Burkhart and Tomé, 2012; Oliver and Larson, 1996; Cluzeau et al, 1995). Tree crown is an important variable to elucidate what occurs in forest stands and its dynamics and, a great effort has been devoted towards quantification of tree crowns (Burkhart and Tomé, 2012), as well as to its modeling (Godin, 2000). Crown volume turns to be an adequate variable to assess forest dynamics and to improve.

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