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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 : |
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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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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INIA Treinta y Tres (TT) |
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| Registros recuperados : 18 | |
| 3. |  | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; CASSMAN, K. Determinación del potencial y de la brecha de rendimiento en los sistemas de arroz en Uruguay. 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. 5-8. (INIA, Serie Actividades de Difusión; 765) GYGA: Globlal Yield Gap Atlas.| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 4. | | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; CASSMAN, K.G. Determinación del potencial y brecha de rendimiento en los sistemas de arroz en Uruguay. [Presentación oral]. In: Presentación resultados experimentales de arroz, 16 Agosto, Artigas; 17 Agosto, Tacuarembó (UY). INIA, University of Nebraska Lincoln, Global Yield Gap Atlas, 2016.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Tacuarembó. |
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| 8. | | 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.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Tacuarembó. |
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| 10. | | 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.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Tacuarembó. |
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| 11. | | 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.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 12. | | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; CASSMAN, K.G.; ZORRILLA DE SAN MARTÍN, G. Yield gaps and yield increase of irrigated rice in Uruguay. [Presentación oral]. In: Rice Technical Working Group, 37, 2018, Proceedings. Long Beach, California (USA): Rice Technical Working Group, 2018.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Tacuarembó. |
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| 13. | | CARRACELAS, G.; GUILPART, N.; CASSMAN, K.; GRASSINI, P.; ZORRILLA DE SAN MARTÍN, G. Yield potential and Yield gaps of irrigated rice in Uruguay and other rice producing countries. In: International Temperate Rice Conference, 6-9 de marzo, Griffith, NSW, Australia, 2017. 7 p.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 14. | | CARRACELAS, G.; GUILPART, N.; GRASSINI, P.; CASSMAN, K.G.; ZORRILLA DE SAN MARTÍN, G. Yield potential and yield gaps of irrigated rice in Uruguay and other rice producing countries. [Presentación oral]. In: International Temperate Rice Conference, 6-9 de marzo, Griffith, NSW, Australia, 2017.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
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| 15. | | YUAN, S.; LINQUIST, B.; WILSON, L.; CASSMAN, K.; STUART, A.; PEDE, V.; MIRO, B.; SAITO, K.; AGUSTIANI, N.; ARISTYA, V.; KRISNADI, L.; ZANON, A.; HEINEMANN, A.; CARRACELAS, G.; SUBASH, N.; BRAHMANAND, P.; LI, T.; PENG, S.; GRASSINI, P. A roadmap towards sustainable intensification for a larger global rice bowl Research Square, 2021. DOI: https://doi.org/10.21203/rs.3.rs-401904/v1 Acknowledgements: We would like to thank Dr. Russell Ford (former Head of Agronomic R&D at Sunrice) for providing data for rice in Australia and Dr. P.A.J. van Oort for performing the simulations of yield potential for African countries....| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Tacuarembó. |
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| 16. | | YUAN, S.; LINQUIST, B. A.; WILSON, L. T.; CASSMAN, K. G.; STUART, A. M.; PEDE, V.; SAITO, K.; AGUSTIANI, N.; ARISTYA, V. E.; KRISNADI, L. Y.; ZANON, A.J.; HEINEMANN, A. B.; CARRACELAS, G.; SUBASH, N.; BRAGMANAND, P. S.; LI, T.; PENG, S.; GRASSINI, P. Sustainable intensification for a larger global rice bowl. Nature Communications, December 2021, Article number 7163. OPEN ACCESS. doi: https://doi.org/10.1038/s41467-021-27424-z 11 p. Article history: Received: 7 April 2021; Accepted: 17 November 2021; Published online 09 December 2021.
Correspondence author: pgrassini2@unl.edu; speng@mail.hzau.edu.cn| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Treinta y Tres. |
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| 17. | | 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. How do various maize crop models vary in their responses to climate change factors? Global Change Biology, 2014, v.20(7), p. 2301-2320. Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
| Biblioteca(s): INIA Treinta y Tres. |
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| 18. | | MARCAIDA, M.; ASSENG, S.; EWERT, F.; BASSU, S.; DURAND, J.L.; LI, T.; MARTRE, P.; ADAM, M.; AGGARWAL, P.K.; ANGULO, C.; BARON, C.; BASSO, B.; BERTUZZI, P.; BIERNATH, C.; BOOGAARD, H.; BOOTE, K.J.; BOUMAN, B.; BREGAGLIO, S.; BRISSON, N.; BUIS, S.; CAMMARANO, D.; CHALLINOR, A.J.; CONFALONIERI, R.; CONIJN, J.G.; CORBEELS, M.; DERYNG, D.; DE SANCTIS, G.; DOLTRA, J.; FUMOTO, T.; GAYDON, D.; GAYLER, S.; GOLDBERG, R.; GRANT, R.F.; GRASSINI, P.; HATFIELD, J.L.; HASEGAWA, T.; HENG, L.; HOEK, S.; HOOKER, J.; HUNT, L.A.; INGWERSEN, J.; IZAURRALDE, R.C.; JONGSCHAAP, R.E.E.; JONES, J.W.; KEMANIAN, R.A.; KERSEBAUM, K.C.; KIM, S.-H.; LIZASO, J.; MÜLLER, C.; NAKAGAWA, H.; NARESH KUMAR, S.; NENDEL, C.; O'LEARY, G.J.; OLESEN, J.E.; ORIOL, P.; OSBORNE, T.M.; PALOSUO, T.; PRAVIA, V.; PRIESACK, E.; RIPOCHE, D.; ROSENZWEIG, C.; RUANE, A.C.; RUGET, F.; SAU, F.; SEMENOV, M.A.; SHCHERBAK, I.; SINGH, B.; SINGH, U.; SOO, H.K.; STEDUTO, P.; STÖCKLE, C.; STRATONOVITCH, P.; STRECK, T.; SUPIT, I.; TANG, L.; TAO, F.; TEIXEIRA, E.I.; THORBURN, P.; TIMLIN, D.; TRAVASSO, M.; RÖTTER, R.P.; WAHA, K.; WALLACH, D.; WHITE, J.W.; WILKENS, P.; WILLIAMS, J.R.; WOLF, J.; YIN, X.; YOSHIDA, H.; ZHANG, Z.; ZHU, Y. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas; INIA Treinta y Tres. |
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| Registros recuperados : 18 | |
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