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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
28/03/2016 |
Actualizado : |
24/09/2018 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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. |
Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Science, The Pennsylvania State University, USA. |
Título : |
How do various maize crop models vary in their responses to climate change factors? |
Fecha de publicación : |
2014 |
Fuente / Imprenta : |
Global Change Biology, 2014, v.20(7), p. 2301-2320. |
DOI : |
10.1111/gcb.12520 |
Idioma : |
Inglés |
Notas : |
Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014. |
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 |
Palabras claves : |
AGMIP; CARBON DIOXIDE; CLIMATE; CO2; GRAIN YIELD; MAIZE; MODEL INTERCOMPARISON; MODELIZACIÓN DE CULTIVOS; SIMULATION MODELS; TEMPERATURE. |
Thesagro : |
CLIMA; DIOXIDO DE CARBONO; INCERTIDUMBRE; MAÍZ; MODELOS DE SIMULACIÓN; TEMPERATURA. |
Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
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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1. | | AYALA, W.; BARRIOS, J.; SERRON, N.; PEREYRA, F.; SARAVIA, H.; MOREIRA, I.; DÍA DE CAMPO, PROYECTO IMPLANTACIÓN DE FESTUCA, 2017, SAN CARLOS, MALDONADO (UY). Ajuste del paquete tecnológico para la incorporación de pasturas permanentes en base a Festuca en suelos degradados del Este del país. Treinta y Tres, (Uruguay): INIA Treinta y Tres, CALIMA, 2017. 13 p.Biblioteca(s): INIA Treinta y Tres. |
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2. | | BERMÚDEZ, R.; AYALA, W.; SERRON, N. Control de gramilla en mejoramientos de Lotus Maku In: INIA TREINTA Y TRES. Jornada de divulgación de Producción Animal - Pasturas Treinta y Tres (Uruguay): INIA, 2009 p. 7-12 (INIA Serie Actividades de Difusión ; 591) Programa Nacional Pasturas y Forrajes: Ing. Agr., PhD. Walter Ayala, Director de Programa, Ing. Agr., MPhil. Raúl Bermúdez, Ing. Agr., MSc. Virginia Pravia, Lic., MSc. Felipe Lezama, Téc. en Sistemas Intensivos de Prod.Animal Ethel...Tipo: Actividades de Difusión |
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3. | | PEREYRA, F.; SERRON, N.; AYALA, W. Crecimiento durante el verano de Festuca arundinacea INIA Fortuna con o sin la inclusión de endófito AR584. In: Reunión del Grupo Técnico en Forrajeras del Cono Sur, Grupo Campos, 24, 2017, Tacuarembó, Uruguay; Ayala, W.; Boggiano, P.; Álvarez, O.; eds. Bioma campos : Retomando un camino de oportunidades para una producción ganadera sustentable. Memorias. Tacuarembó (Uruguay): Grupo Campos, 2017. p. 82-84 ver elect. La paginación electrónica difiere de la versión papel, paginación papel: p.87-89.Tipo: Abstracts/Resúmenes |
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6. | | BERMÚDEZ, R.; BARRIOS, E.; VELAZCO, J.; SERRÓN, N.; AYALA, W. Efecto de la carga animal en la performance de terneros pastoreando Trifolium vesiculosum In CONGRESO ARGENTINO DE PRODUCCIÓN ANIMAL, 33., 2010, Viedma, AR. Sistemas de producción. Revista Argentina de Producción Animal, v. 30, supl. 1, p. 155-156, 2010.Tipo: Trabajos en Congresos/Conferencias |
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Biblioteca(s): INIA Treinta y Tres. |
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11. | | BARRIOS, E.; SERRON, N.; AYALA, W. Efecto del manejo de defoliación en la morfología y población de Llantén (Plantago lanceolata L.). ln: Reunión del Grupo Técnico en Forrajeras del Cono Sur, Grupo Campos, 22, 2008, Minas, Uruguay. Ayala, W.; Lezama, F.; Barrios, E.; Bemhaja, M.; Saravia, H.; Formoso, D.; Boggiano, P., ed. Bioma campos : Innovando para mantener su sustentabilidad y competitividad. Memorias. Minas (Uruguay): Grupo Campos, 2008.Tipo: Abstracts/Resúmenes |
Biblioteca(s): INIA Treinta y Tres. |
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12. | | AYALA, W.; BARRIOS, E.; BERMÚDEZ, R.; SERRÓN, N. Effect of defoliation strategies on the productivity, population and morphology of plantain (Plantago lanceolata). ln: PASTURE PERSISTENCE SYMPOSIUM (2011, Hamilton, NZ). Papers. Dunedin, NZ: NZGA, 2011. p. 69-72. (Grassland Research and Practice Series, 15) Ejemplar donado por el editor, entregado por M. Rebuffo, 2012. - También disponible versión electrónica de acceso abierto en: Proceedings of the New Zealand Grassland Association, v. 73, p. 69-73, 2011.Tipo: Trabajos en Congresos/Conferencias |
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14. | | AYALA, W.; SERRON, N.; PEREYRA, F.; HERKEN, G.; OLANO, I.; RUETE, R.; ALMEIDA, M.; TARÁN, S. Festuca en sistemas ganaderos. Producción y persistencia. In: Día de Campo Unidad Experimental Palo a Pique, Oct. 2018. Treinta y Tres (Uruguay): INIA, 2018, p.3-6.Biblioteca(s): INIA Treinta y Tres. |
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15. | | CARRASCO-LETELIER, L.; TERRA, J.A.; ROEL, A.; AYALA, W.; BORDAGORRI, P.; SERRON, N.; MARTÍNEZ, S.; JORAJURÍA, P. Huella ecotoxicológica de rotaciones de arroz con diferentes grados de intensificación. Sustentabilidad. Revista INIA Uruguay, Junio 2023, no.73, p.82-85. (Revista INIA; 73).Tipo: Artículos en Revistas Agropecuarias |
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Biblioteca(s): INIA Treinta y Tres. |
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18. | | MACEDO, I.; CASTILLO, J.; SALDAIN, N.E.; MARTÍNEZ, S.; AYALA, W.; HERNANDEZ, J.; SERRON, N.; BORDAGORRI, P.; ZORRILLA DE SAN MARTÍN, G.; TERRA, J.A. Nuevas rotaciones arroceras: primeros datos de productividad Arroz, 2016, v.16, no. 88, p. 34-39.Tipo: Artículos en Revistas Agropecuarias |
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