iForest - Biogeosciences and Forestry


Using soil-based and physiographic variables to improve stand growth equations in Uruguayan forest plantations

Cecilia Rachid-Casnati (1)   , Euan G Mason (2), Richard C Woollons (2)

iForest - Biogeosciences and Forestry, Volume 12, Issue 3, Pages 237-245 (2019)
doi: https://doi.org/10.3832/ifor2926-012
Published: May 03, 2019 - Copyright © 2019 SISEF

Research Articles

Information provided by traditional growth models is an essential input in decision making processes for managing planted forests. They are generally fitted using inventory data guaranteeing robustness and simplicity. The introduction of explanatory factors affecting tree development in age-based sigmoidal growth and yield equations attempts not only to improve the quality of predictions, but also to add useful information underpinning forest management decisions. This study aimed to assess the use of the following soil-based and physiographic predictors: potentially available soil water (PASW), elevation (Elev), aspect (α) and slope (β) in a system of empirical stand equations comprising: dominant height (hdom), basal area (G), maximum diameter at breast height (dmax), and standard deviation of diameters (SDd). Augmented models were compared with the base models through precision and bias of estimations for two contrasting species: Pinus taeda (L.), and Eucalyptus grandis (Hill ex. Maiden), planted commercially in Uruguay. Soil-based and physiographic information significantly improved predictions of all the state variables fitted for E. grandis, but just hdom and G for P. taeda. Only PASW was consistently significant for the augmented models in P. taeda and E. grandis, while the contribution of other predictors varied between species. From a physiological point of view, predictors on the augmented models showed consistency. Models with such augmentation produced decrease of errors between 3 to 10.5%, however decreases in the prediction errors calculated with the independent dataset were lower. Results from this study contributed to add information to the decision-making process of plantations’ management.


Forest Modelling, Soil Variables, Physiographic Variables, Pinus taeda, Eucalyptus grandis

Authors’ address

Cecilia Rachid-Casnati 0000-0002-8621-7061
Forestry Research Programme, National Institute of Agricultural Research (INIA Uruguay), Road 5, Km 386, 45000 Tacuarembó (Uruguay)
Euan G Mason 0000-0001-9024-9106
Richard C Woollons
School of Forestry, University of Canterbury, Private Bag 48000, Christchurch (New Zealand)

Corresponding author

Cecilia Rachid-Casnati


Rachid-Casnati C, Mason EG, Woollons RC (2019). Using soil-based and physiographic variables to improve stand growth equations in Uruguayan forest plantations. iForest 12: 237-245. - doi: 10.3832/ifor2926-012

Academic Editor

Emanuele Lingua

Paper history

Received: Jul 19, 2018
Accepted: Mar 16, 2019

First online: May 03, 2019
Publication Date: Jun 30, 2019
Publication Time: 1.60 months

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