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
Abstract
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.
Keywords
Forest Modelling, Soil Variables, Physiographic Variables, Pinus taeda, Eucalyptus grandis
Authors’ Info
Authors’ address
Forestry Research Programme, National Institute of Agricultural Research (INIA Uruguay), Road 5, Km 386, 45000 Tacuarembó (Uruguay)
Richard C Woollons
School of Forestry, University of Canterbury, Private Bag 48000, Christchurch (New Zealand)
Corresponding author
Paper Info
Citation
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
Copyright Information
© SISEF - The Italian Society of Silviculture and Forest Ecology 2019
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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