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| Registros recuperados : 35 | |
| 6. |  | ZORRILLA DE SAN MARTÍN, G.; ACEVEDO, A. Semillas. ln: INIA Tacuarembó. Arroz: resultados experimentales zafra 1995-1996. Tacuarembó (Uruguay): INIA, 1996. cap. 7, p. 1-12 (INIA Serie Actividades de Difusión ; 107)| Biblioteca(s): INIA Tacuarembó. |
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| 7. | | ZORRILLA DE SAN MARTÍN, G.; BRITO, G. Presentación [SAD 751]. In: INIA TACUAREMBÓ. PROGRAMA NACIONAL DE ARROZ. Presentación resultados experimentales de arroz Zafra 2014-2015. Martes 4 agosto, Tacuarembó; 5 agosto, Artigas (UY). Tacuarembó (UY): INIA, 2015. p. 3-5 (Serie Actividades de Difusión; 751)| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 13. | | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; ZORRILLA DE SAN MARTÍN, G.; CASSMAN, K.G. Análisis de potencial y brecha de rendimiento en los sistemas de arroz irrigado en Uruguay y otros países. ln: Congresso Brasileiro de Arroz Irrigado, 11., 13-16 agosto, Camboriú, Brasil, 2019. 17 p.| Biblioteca(s): INIA Tacuarembó. |
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| 17. | | DEAMBROSI, E.; ZORRILLA DE SAN MARTÍN, G.; LAUZ, M.; BLANCO, P.H.; TERRA, J.A. Rompiendo el techo de rendimiento del cultivo de arroz. Proyecto ANII ALI_1_2012_1_3507 (INIA, GMA-COOPAR, ACA) Zafra 2015-2016. ln: JORNADA ANUAL ARROZ, 2016, INIA TREINTA Y TRES, TREINTA Y TRES, UY. Arroz: resultados experimentales 2015-2016. Treinta y Tres, (Uruguay): INIA, 2016. Cap. 2, p. 1-4. (INIA, Serie Actividades de Difusión; 765) Acceso a publicación y presentación oral.| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 19. | | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; ZORRILLA DE SAN MARTÍN, G.; CASSMAN, K. Yield gap analysis of irrigated rice in Uruguay and comparison with other rice producing countries. [Resumen]. ln: Congresso Brasileiro de Arroz Irrigado, 11., 13-16 agosto, Camboriú, Brasil, 2019. 4 p.| Biblioteca(s): INIA Tacuarembó. |
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| 20. | | CARRACELAS, G.; GRASSINI, P.; GUILPART, N.; CASSMAN, K.; ZORRILLA DE SAN MARTÍN, G. Yield gap analysis and prognosis of yield increase of irrigated rice in Uruguay. [Abstract]. In: Rice Technical Working Group, 37, 2018, Proceedings. Long Beach, California (USA): Rice Technical Working Group, 2018. p. 131-132.| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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 | Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha actual : |
30/05/2019 |
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Actualizado : |
23/09/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
RACHID, C.; MASONN, E.G.; WOOLLONS, R. |
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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). |
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Título : |
Using soil-based and physiographic variables to improve stand growth equations in Uruguayan forest plantations. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
iForest, v. 12, p. 237-245, 2019. |
|
DOI : |
10.3832/ifor2926-012 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: Jul 19, 2018; Accepted: Mar 16, 2019; online 2019-05-03. |
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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 |
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Palabras claves : |
EUCALYPTUS GRANDIS; FOREST MODELLING; PHYSIOGRAPHIC VARIABLES; PINUS TAEDA; SOIL VARABLES. |
|
Asunto categoría : |
K10 Producción forestal |
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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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