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13. |  | SORIA, J.; PISANO, J.; CARRAU, F. Variedades de ciruelo en Uruguay. In: INIA (Instituto Nacional de Investigación Agropecuaria); Programa Fruticultura. Actualización Técnica en el Cultivo del Ciruelo. Seminario Regional, 27 mayo 2003, INIA Las Brujas, Canelones (Uruguay). Canelones (Uruguay): INIA Las Brujas, 2003. p. 99-114 (INIA Serie Actividades de Difusión ; 315)Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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 | Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
30/05/2019 |
Actualizado : |
23/09/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
RACHID, C.; MASONN, E.G.; WOOLLONS, R. |
Afiliación : |
ANA CECILIA RACHID CASNATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; EUAN G. MASON, School of Forestry, University of Canterbury, Christchurch (New Zealand).; RICHARD C. WOOLLONS, School of Forestry, University of Canterbury, Christchurch (New Zealand). |
Título : |
Using soil-based and physiographic variables to improve stand growth equations in Uruguayan forest plantations. |
Fecha de publicación : |
2019 |
Fuente / Imprenta : |
iForest, v. 12, p. 237-245, 2019. |
DOI : |
10.3832/ifor2926-012 |
Idioma : |
Inglés |
Notas : |
Article history: Received: Jul 19, 2018; Accepted: Mar 16, 2019; online 2019-05-03. |
Contenido : |
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 (?) and slope (?) 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. MenosInformation 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 (?) and slope (?) 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 o... Presentar Todo |
Palabras claves : |
EUCALYPTUS GRANDIS; FOREST MODELLING; PHYSIOGRAPHIC VARIABLES; PINUS TAEDA; SOIL VARABLES. |
Asunto categoría : |
K10 Producción forestal |
Marc : |
LEADER 02492naa a2200229 a 4500 001 1059793 005 2019-09-23 008 2019 bl uuuu u00u1 u #d 024 7 $a10.3832/ifor2926-012$2DOI 100 1 $aRACHID, C. 245 $aUsing soil-based and physiographic variables to improve stand growth equations in Uruguayan forest plantations.$h[electronic resource] 260 $c2019 500 $aArticle history: Received: Jul 19, 2018; Accepted: Mar 16, 2019; online 2019-05-03. 520 $aInformation 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 (?) and slope (?) 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. 653 $aEUCALYPTUS GRANDIS 653 $aFOREST MODELLING 653 $aPHYSIOGRAPHIC VARIABLES 653 $aPINUS TAEDA 653 $aSOIL VARABLES 700 1 $aMASONN, E.G. 700 1 $aWOOLLONS, R. 773 $tiForest$gv. 12, p. 237-245, 2019.
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