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| 5. |  | FRANCO, V.; VIERA, C.; MARTÍNEZ, S.; GARCÍA, L. F. Efectos de la historia de uso de insecticidas en la abundancia y diversidad de arañas (Araneae) en cultivos de arroz de Uruguay. Pósters: Ecología y comportamiento. In: Congreso Latinoamericano de Aracnología, 6., Museo Argentino de Ciencias Naturales, Buenos Aires, Argentina, 14?18 diciembre 2020. Libro de resúmenes, p.335-336. Financiamiento: Facultad de Ciencias, Universidad de la Republica, Lab. Ecología del Comportamiento IIBCE Montevideo, INIA, Treinta y Tres. Uruguay.| Biblioteca(s): INIA Las Brujas. |
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| 7. | | NÚÑEZ, E.; GARCÍA, L.; LACAVA, M.; BENAMÚ, M.; ESCALANTE, F.; MARTÍNEZ, S.; CARRASCO-LETELIER, L. Artrópodos como bioindicadores y biomarcadores para evaluar la sustentabilidad de rotaciones arroceras. Revista INIA Uruguay, 2019, no. 59, p. 61-65. (Revista INIA; 59)| Biblioteca(s): INIA Treinta y Tres. |
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| 9. | | GARCÍA, L. F.; NÚÑEZ, E.; LACAVA, M.; SILVA, H.; MARTÍNEZ, S.; PÉTILLON, J. Experimental assessment of trophic ecology in a generalist spider predator: implications for biocontrol in uruguayan crops. [Original contribution]. Journal of Applied Entomology, February 2021, Volume145, Issue1-2, p.82-91. Doi: https://doi.org/10.1111/jen.12811 Article history: Received: 22 April 2020; Revised: 15 July 2020; Accepted: 17 July 2020; First published: 05 September 2020.| Biblioteca(s): INIA Treinta y Tres. |
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| 12. | | CARRASCO-LETELIER, L.; BERETTA, A.; BASSAHÚN, D.; GARCÍA, L.; MUSSELLI, R.; TORRES, D.; TORRES, O. Survey of Uruguayan freshwater water quality for crop irrigation: abstract. Agrociencia Uruguay, v. 19, special issue "Inter-Regional CIGR Conference on Land and Water Challenges, 3., La Estanzuela, Colonia, UY. Tools for developing; "Dr. Mario García Petillo"", p. 73, 2015. En versión electrónica difiere la paginación: Agrociencia Uruguay, v. 19, special issue, p. 77, 2015.| Biblioteca(s): INIA La Estanzuela. |
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| 13. | | CARRASCO-LETELIER, L.; BERETTA, A.; BASSAHUN, D.; GARCIA, L.; MUSSELLI, R.; OTEN, R.; TORRES, D.; TORRES, O.; TELLECHEA, G. Aptitud de la calidad del agua para uso agropecuario: riego y preparación de pesticidas. Revista INIA Uruguay, 2015, n. 41, p. 45-48 (Revista INIA; 41)| Biblioteca(s): INIA La Estanzuela; INIA Tacuarembó. |
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| 14. | | Planificación, seguimiento y evaluación de la Investigación Agropecuaria, 2 : 1993 set27-oct 1 : Ibarra, Ecuador - Cheaz, J.; Horton, D.; Zapata, V.; Palomino, J.; Rivas, N.; García, L. (eds) Informe del Segundo Curso La Haya (Holanda): ISNAR, 1994. 110p.| Biblioteca(s): INIA Las Brujas. |
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| 15. | | RAEGAN HOEFLER; GONZALEZ-BARRIOS , P.; MADHAV BHATTA; NUNES, J.A.R.; BERRO, I.; NALIN, R.S.; BORGES, A.; COVARRUBIAS, E.; DIAZ-GARCIA, L.; QUINCKE, M.; GUTIERREZ, L. Do Spatial Designs Outperform Classic Experimental Designs?. Journal of Agricultural, Biological, and Environmental Statistics, 1 December 2020, volume 25, number 4, pag.523-552, 1 December 2020. OPEN ACCESS. Doi: https://doi.org/10.1007/s13253-020-00406-2 Article history: Received 15 October 2019/Accepted 01 July 2020/Published 29 August 2020. This project was partially funded through a USDA_AFRI_NIFA_2018-67013-27620 award and by the Hatch Act Formula Fund WISO1984 and WIS03002....| Biblioteca(s): INIA La Estanzuela. |
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| 16. | | DE SANTIAGO, F.; BARRIOS, M.; D'ANATRO, A.; GARCÍA, L.F.; MAILHOS, A.; POMPOZZI, G.; REHERMANN, S.; SIMÓ, M.; TESITORE, G.; DE MELLO, F.T.; VALTIERRA, V.; BLUMETTO, O. From theory to practice: can LEAP/FAO biodiversity assessment guidelines be a useful tool for knowing the environmental status of livestock systems? Sustainability, 2022, Volume 14, Issue 23, e16259. OPEN ACCESS. doi: https://doi.org/10.3390/su142316259 Article history: Received 6 November 2022; Revised 29 November 2022; Accepted 29 November 2022; Published 6 December 2022. -- Academic Editor: Andrea Pezzuolo. -- LICENSE: Licensee MDPI, Basel, Switzerland. This article is an open access...| Biblioteca(s): INIA Las Brujas. |
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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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