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| 3. |  | ALVARIÑO, S.; BOCCO, A.; TERRA, R.; BIDEGAIN, M.; CRUZ, G. Caracterización de la variabilidad espacial y temporal de la evapotranspiración de referencia (ET0) en Uruguay. In: Zorrilla, G.; Martínez, S.; Terra, J. A. Saravia, H. (Eds.) Arroz 2018. Montevideo (UY): INIA, 2018. (INIA Serie Técnica; 246)| Biblioteca(s): INIA Treinta y Tres. |
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| 4. | | Saldanha, S.; Saravia, C.; Krall, E.; Cruz, G.; Salvarrey, L. Efecto del estrés térmico estival en el comportamiento de pastoreo de vaquillonas Holando y Jersey ln: Reunión del Grupo Técnico Regional del Cono Sur en Mejoramiento y Utilización de los Recursos Forrajeros del Area Tropical y Subtropical, Grupo Campos, 20., 2004, Salto, UY Saldanha, S.; Bemhaja, M.; Moliterno, E.; Olmos, F.; Uriarte, G., ed. Sustentabilidad, desarrollo y conservación de los ecosistemas : memorias. Salto: UdelaR. Regional Norte, 2004. p. 311-312| Biblioteca(s): INIA La Estanzuela. |
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| 8. | | MAZZILLI, S.; BONILLA, C.; SIRI, G.; ARBELETCHE, P.; RUBIO, V.; BASIGALUZ, P.; TAKS, J.; GARCÍA, M.; COBAS, P.; MONDELLI, M.P.; ASTIGARRAGA, L.; CRUZ, G.; PICASSO, V.; URUGUAY. CENTRO INTERDISCIPLINARIO DE RESPUESTA AL CAMBIO Y VARIABILIDAD CLIMÁTICA (CIRCVC) Sensibilidad y capacidad adaptativa de la agricultura de secano y el arroz frente al cambio climático: resultado [parcial] del proyecto: TCP/URU/3302 Nuevas Políticas para la Adaptación de la Agricultura al Cambio Climático. Montevideo, UY: FAO/MGAP, 2013. 63 p. (Clima de Cambios: Nuevos Desafíos de Adaptación en Uruguay, 5).| Biblioteca(s): INIA La Estanzuela. |
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| 9. | | BARTABURU, D.; MORALES, H.; DIÉGUEZ, F.; LIZARRALDE, C.; QUIÑONES, A.; PEREIRA, M.; MOLINA, C.; MONTES, E.; MODERNEL, P.; TAKS, J.; DE TORRES, F.; COBAS, P.; MONDELLI, M.; TERRA, R.; CRUZ, G.; ASTIGARRAGA, L.; PICASSO, V.; URUGUAY. CENTRO INTERDISCIPLINARIO DE RESPUESTA AL CAMBIO Y VARIABILIDAD CLIMÁTICA Sensibilidad y capacidad adaptativa de la ganadería frente a los efectos del cambio climático; resultado [parcial] del proyecto: TCP/URU/3302 Nuevas Políticas para la Adaptación de la Agricultura al Cambio Climático. Montevideo, UY: FAO-MGAP, 2013. 54 p. (Clima de Cambios: Nuevos Desafíos de Adaptación en Uruguay, 3) Equipo del proyecto: Tomás Lindemann, Vicente Plata, Walter Oyhantçabal, Diego Sancho.| Biblioteca(s): INIA La Estanzuela. |
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| 10. | | BARTABURU, D.; MORALES, H.; DIÉGUEZ, F.; LIZARRALDE, C.; QUIÑONES, A.; PEREIRA, M.; MOLINA, C.; MONTES, E.; MODERNEL, P.; TAKS, J.; DE TORRES, F.; TERRA, R.; CRUZ, G.; ASTIGARRAGA, L.; PICASSO, V. Sensibilidad y capacidad adaptativa de los agro-ecosistemas [sic] frente a los efectos del cambio climático: 3.2 ganadería. In: OYHANTÇABAL, W.; SANCHO, D.; GALVÁN, M. (Ed.). Resultado del proyecto: TCP/URU/3302 Nuevas Políticas para la Adaptación de la Agricultura al Cambio Climático. Montevideo, UY: FAO-MGAP, 2013. p. 103-133. (Clima de Cambios: Nuevos Desafíos de Adaptación en Uruguay: Compilado)| Biblioteca(s): INIA La Estanzuela; INIA Treinta y Tres. |
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| 11. | | MAZZILLI, S.; SIRI, G.; ARBELETCHE, P.; RUBIO, V.; BASIGALUZ, P.; TAKS, J.; GARCÍA, M.; CRUZ, G.; ASTIGARRAGA, L.; PICASSO, V.; URUGUAY. CENTRO INTERDISCIPLINARIO DE RESPUESTA AL CAMBIO Y VARIABILIDAD CLIMÁTICA (CIRCVC) Sensibilidad y capacidad adaptativa de los agro-ecosistemas [sic] frente a los efectos del cambio climático: 3.4 agricultura de secano. In: OYHANTÇABAL, W.; SANCHO, D.; GALVÁN, M. (Ed.). Resultado del proyecto: TCP/URU/3302 Nuevas Políticas para la Adaptación de la Agricultura al Cambio Climático. Montevideo, UY: FAO-MGAP, 2013. p. 154-172. (Clima de Cambios: Nuevos Desafíos de Adaptación en Uruguay, Compilado)| Biblioteca(s): INIA La Estanzuela; INIA Treinta y Tres. |
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| 12. | | CRUZ, G.; BAETHGEN, W.; BARTABURU, D.; BIDEGAIN, M.; GIMÉNEZ, A.; METHOL, M.; MORALES, H.; PICASSO, V.; PODESTA, G.; TADDEI, R.; TERRA, R.; TISCORNIA, G.; VINOCUR, M. Thirty years of multi-level processes for adaptation of livestock production to droughts in Uruguay. Weather, Climate, and Society (WCAS), 2017. Publicado en el 2018: WCAS, jan.,2018, v. 10, p. 59-74. Article history: Received: 22 December 2016; Final Form: 2 Octobre 2017; Published online: 13 December 2017.| Biblioteca(s): INIA Las Brujas. |
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| 14. | | CRUZ, G. Utilización de frutos de algarrobo en el Perú: Experiencias de comercialización, innovación y biocomercio. In: Bennadji, Z.; Ferreira,F.; Panizzolo, L. Simposio internacional, 25 de junio, Tacuarembó, 2015. Biomateriales forestales: Productos, tenologías, cadena de valor y mercados. Tacuarembó: INIA, 2015. p. 6-7 (Serie Actividades de Difusión; 749)| Biblioteca(s): INIA Tacuarembó. |
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| Registros recuperados : 15 | |
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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
28/03/2016 |
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Actualizado : |
24/09/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
BASSU, S.; BRISSON, N.; DURAND, J.L.; BOOTE, K.; LIZASO, J.; JONES, J.W.; ROSENZWEIG, C.; RUANE, A.C.; ADAM, M.; BARON, C.; BASSO, B.; BIERNATH, C.; BOOGAARD, H.; CONIJN, S.; CORBEELS, M.L; DERYNG, D.; SANTIS, G. DE; GAYLER, S.; GRASSINI, P.; HATFIELD, J.; HOEK, S.; IZAURRALDE, C.; JONGSCHAAP, R.; KEMANIAN, A.R.; KERSEBAUM, C.KIM, S-H.; KUMAR, N.; MAKOWSKI, D.; MÜLLER, C.; NENDEL, C.; PRIESACK, E.; PRAVIA, V.; SAU, F.; SHCHERBAK, I.; TAO, F.; TEXEIRA, E.; TIMLIN, D.; WAHA, K. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Science, The Pennsylvania State University, USA. |
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Título : |
How do various maize crop models vary in their responses to climate change factors? |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Global Change Biology, 2014, v.20(7), p. 2301-2320. |
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DOI : |
10.1111/gcb.12520 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014. |
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Contenido : |
Abstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. MenosAbstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2]... Presentar Todo |
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Palabras claves : |
AGMIP; CARBON DIOXIDE; CLIMATE; CO2; GRAIN YIELD; MAIZE; MODEL INTERCOMPARISON; MODELIZACIÓN DE CULTIVOS; SIMULATION MODELS; TEMPERATURE. |
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Thesagro : |
CLIMA; DIOXIDO DE CARBONO; INCERTIDUMBRE; MAÍZ; MODELOS DE SIMULACIÓN; TEMPERATURA. |
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Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
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Marc : |
LEADER 03684naa a2200769 a 4500
001 1054517
005 2018-09-24
008 2014 bl uuuu u00u1 u #d
024 7 $a10.1111/gcb.12520$2DOI
100 1 $aBASSU, S.
245 $aHow do various maize crop models vary in their responses to climate change factors?$h[electronic resource]
260 $c2014
500 $aArticle history: Received 7 June 2013 and accepted 2 December 2013, published 2014.
520 $aAbstract: Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
650 $aCLIMA
650 $aDIOXIDO DE CARBONO
650 $aINCERTIDUMBRE
650 $aMAÍZ
650 $aMODELOS DE SIMULACIÓN
650 $aTEMPERATURA
653 $aAGMIP
653 $aCARBON DIOXIDE
653 $aCLIMATE
653 $aCO2
653 $aGRAIN YIELD
653 $aMAIZE
653 $aMODEL INTERCOMPARISON
653 $aMODELIZACIÓN DE CULTIVOS
653 $aSIMULATION MODELS
653 $aTEMPERATURE
700 1 $aBRISSON, N.
700 1 $aDURAND, J.L.
700 1 $aBOOTE, K.
700 1 $aLIZASO, J.
700 1 $aJONES, J.W.
700 1 $aROSENZWEIG, C.
700 1 $aRUANE, A.C.
700 1 $aADAM, M.
700 1 $aBARON, C.
700 1 $aBASSO, B.
700 1 $aBIERNATH, C.
700 1 $aBOOGAARD, H.
700 1 $aCONIJN, S.
700 1 $aCORBEELS, M.L
700 1 $aDERYNG, D.
700 1 $aSANTIS, G. DE
700 1 $aGAYLER, S.
700 1 $aGRASSINI, P.
700 1 $aHATFIELD, J.
700 1 $aHOEK, S.
700 1 $aIZAURRALDE, C.
700 1 $aJONGSCHAAP, R.
700 1 $aKEMANIAN, A.R.
700 1 $aKERSEBAUM, C.KIM, S-H.
700 1 $aKUMAR, N.
700 1 $aMAKOWSKI, D.
700 1 $aMÜLLER, C.
700 1 $aNENDEL, C.
700 1 $aPRIESACK, E.
700 1 $aPRAVIA, V.
700 1 $aSAU, F.
700 1 $aSHCHERBAK, I.
700 1 $aTAO, F.
700 1 $aTEXEIRA, E.
700 1 $aTIMLIN, D.
700 1 $aWAHA, K.
773 $tGlobal Change Biology, 2014$gv.20(7), p. 2301-2320.
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