| |
|
|
 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
|
Fecha : |
12/11/2015 |
|
Actualizado : |
09/10/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
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. |
|
Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
|
Título : |
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. |
|
Fecha de publicación : |
2015 |
|
Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. |
|
ISSN : |
0168-1923 |
|
DOI : |
10.1016/j.agrformet.2015.09.013 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. |
|
Contenido : |
ABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2].
© 2015 Elsevier B.V. All rights reserved. MenosABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in... Presentar Todo |
|
Palabras claves : |
Climate change; CROP MODEL; Emulator; MAIZE; Meta-model; MODELIZACIÓN DE LOS CULTIVOS; RICE; Statistical model; WHEAT; Yield. |
|
Thesagro : |
ARROZ; CAMBIO CLIMÁTICO; MAÍZ; MODELOS ESTADISTICOS; TRIGO. |
|
Asunto categoría : |
A50 Investigación agraria |
|
Marc : |
LEADER 05363naa a2201417 a 4500
001 1053856
005 2019-10-09
008 2015 bl uuuu u00u1 u #d
022 $a0168-1923
024 7 $a10.1016/j.agrformet.2015.09.013$2DOI
100 1 $aMARCAIDA, M.
245 $aA statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration.
260 $c2015
500 $aArticle history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015.
520 $aABSTRACT. Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2]. © 2015 Elsevier B.V. All rights reserved.
650 $aARROZ
650 $aCAMBIO CLIMÁTICO
650 $aMAÍZ
650 $aMODELOS ESTADISTICOS
650 $aTRIGO
653 $aClimate change
653 $aCROP MODEL
653 $aEmulator
653 $aMAIZE
653 $aMeta-model
653 $aMODELIZACIÓN DE LOS CULTIVOS
653 $aRICE
653 $aStatistical model
653 $aWHEAT
653 $aYield
700 1 $aASSENG, S.
700 1 $aEWERT, F.
700 1 $aBASSU, S.
700 1 $aDURAND, J.L.
700 1 $aLI, T.
700 1 $aMARTRE, P.
700 1 $aADAM, M.
700 1 $aAGGARWAL, P.K.
700 1 $aANGULO, C.
700 1 $aBARON, C.
700 1 $aBASSO, B.
700 1 $aBERTUZZI, P.
700 1 $aBIERNATH, C.
700 1 $aBOOGAARD, H.
700 1 $aBOOTE, K.J.
700 1 $aBOUMAN, B.
700 1 $aBREGAGLIO, S.
700 1 $aBRISSON, N.
700 1 $aBUIS, S.
700 1 $aCAMMARANO, D.
700 1 $aCHALLINOR, A.J.
700 1 $aCONFALONIERI, R.
700 1 $aCONIJN, J.G.
700 1 $aCORBEELS, M.
700 1 $aDERYNG, D.
700 1 $aDE SANCTIS, G.
700 1 $aDOLTRA, J.
700 1 $aFUMOTO, T.
700 1 $aGAYDON, D.
700 1 $aGAYLER, S.
700 1 $aGOLDBERG, R.
700 1 $aGRANT, R.F.
700 1 $aGRASSINI, P.
700 1 $aHATFIELD, J.L.
700 1 $aHASEGAWA, T.
700 1 $aHENG, L.
700 1 $aHOEK, S.
700 1 $aHOOKER, J.
700 1 $aHUNT, L.A.
700 1 $aINGWERSEN, J.
700 1 $aIZAURRALDE, R.C.
700 1 $aJONGSCHAAP, R.E.E.
700 1 $aJONES, J.W.
700 1 $aKEMANIAN, R.A.
700 1 $aKERSEBAUM, K.C.
700 1 $aKIM, S.-H.
700 1 $aLIZASO, J.
700 1 $aMÜLLER, C.
700 1 $aNAKAGAWA, H.
700 1 $aNARESH KUMAR, S.
700 1 $aNENDEL, C.
700 1 $aO'LEARY, G.J.
700 1 $aOLESEN, J.E.
700 1 $aORIOL, P.
700 1 $aOSBORNE, T.M.
700 1 $aPALOSUO, T.
700 1 $aPRAVIA, V.
700 1 $aPRIESACK, E.
700 1 $aRIPOCHE, D.
700 1 $aROSENZWEIG, C.
700 1 $aRUANE, A.C.
700 1 $aRUGET, F.
700 1 $aSAU, F.
700 1 $aSEMENOV, M.A.
700 1 $aSHCHERBAK, I.
700 1 $aSINGH, B.
700 1 $aSINGH, U.
700 1 $aSOO, H.K.
700 1 $aSTEDUTO, P.
700 1 $aSTÖCKLE, C.
700 1 $aSTRATONOVITCH, P.
700 1 $aSTRECK, T.
700 1 $aSUPIT, I.
700 1 $aTANG, L.
700 1 $aTAO, F.
700 1 $aTEIXEIRA, E.I.
700 1 $aTHORBURN, P.
700 1 $aTIMLIN, D.
700 1 $aTRAVASSO, M.
700 1 $aRÖTTER, R.P.
700 1 $aWAHA, K.
700 1 $aWALLACH, D.
700 1 $aWHITE, J.W.
700 1 $aWILKENS, P.
700 1 $aWILLIAMS, J.R.
700 1 $aWOLF, J.
700 1 $aYIN, X.
700 1 $aYOSHIDA, H.
700 1 $aZHANG, Z.
700 1 $aZHU, Y.
773 $tAgricultural and Forest Meteorology, 2015$gv.214-215, p. 483-493.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
| Registros recuperados : 103 | |
| 1. |  | ALONSO, M.; DÍAZ, P.; CARBALLO, S.; PAGANI, C. Contaminación microbiana en lechugas y tomates ln: Congreso Nacional de Horticultura, 8.; Seminario Regional de Frutilla, 2001, Salto, Uruguay. Resúmenes. Montevideo (Uruguay): SUH; INIA, 2001. p. 40 Sociedad Uruguaya de Horticultura; Instituto Nacional de Investigación Agropecuaria, Uruguay.| Biblioteca(s): INIA Las Brujas; INIA Salto Grande; INIA Tacuarembó; INIA Treinta y Tres. |
|    |
| 15. | | Carballo, S. Manejo poscosecha de cebolla dulce Las Brujas, Canelones (Uruguay): INIA, 1995. p. 174-193 (INIA Serie Actividades de Difusión ; 46) INIA Las Brujas| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
| |
| 16. | | Carballo, S. Manejo poscosecha en lechuga Las Brujas, Canelones (Uruguay): INIA, 1995. 7 p. (INIA Serie Actividades de Difusión ; 61)| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
| |
| 17. | | CARBALLO, S. Manejo poscosecha de melón. ln: INIA Las Brujas. Programa Horticultura. Evaluación y variedades de poscosecha de melón y lechuga. Canelones (UY): INIA Las Brujas, 1994. p. 13-23 (INIA Serie Actividades de Difusión ; 10)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
| 18. | | CARBALLO, S. Manejo postcosecha de boniato. JORNADA DE DIVULGACIÓN, 10 JUNIO, INIA TACUAREMBÓ, TACUAREMBÓ, 1994. Tacuarembó, Uruguay: INIA, 1994. 5 p. (INIA Serie Actividades de Difusión ; 15)| Tipo: Actividades de Difusión |
| Biblioteca(s): INIA Tacuarembó. |
| |
| 19. | | CARBALLO, S. Manejo del cloro para el lavado de frutas y hortalizas. In: Carballo, S.; Betancur, P.; Sollier, S. (eds.). Calidad e Inocuidad de frutas y hortalizas frescas. Curso de actualización técnica, INIA Las Brujas. Canelones (Uruguay): INIA LB, 2004. p. 53-57 (INIA Serie Actividades de Difusión ; 376)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
| 20. | | CARBALLO, S. Riesgos de contaminación de frutas y hortalizas frescas In: Carballo, S.; Betancur, P.; Sollier, S. (eds.). Calidad e Inocuidad de frutas y hortalizas frescas. Curso de actualización técnica, INIA Las Brujas. Canelones (Uruguay): INIA LB, 2004. p. 18-23 (INIA Serie Actividades de Difusión ; 376)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
| Registros recuperados : 103 | |
|
| No hay resultados para la expresión de búsqueda informada registros. |
|
|
