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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha : |
12/11/2015 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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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. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. |
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ISSN : |
0168-1923 |
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DOI : |
10.1016/j.agrformet.2015.09.013 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. |
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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 |
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Palabras claves : |
Climate change; CROP MODEL; Emulator; MAIZE; Meta-model; MODELIZACIÓN DE LOS CULTIVOS; RICE; Statistical model; WHEAT; Yield. |
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Thesagro : |
ARROZ; CAMBIO CLIMÁTICO; MAÍZ; MODELOS ESTADISTICOS; TRIGO. |
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Asunto categoría : |
A50 Investigación agraria |
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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.
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
|
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Biblioteca (s) : |
INIA Las Brujas; INIA Tacuarembó. |
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Fecha actual : |
15/11/2015 |
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Actualizado : |
23/09/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
HIRIGOYEN, A.; RACHID, C. |
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Afiliación : |
ANDRES EDUARDO HIRIGOYEN DOMINGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANA CECILIA RACHID CASNATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Selecting diametric frequency distribution functions for pinus taeda, eucalyptus globulus and eucalyptus dunnii in Uruguay. [Selección de funciones de distribución de frecuencias diamétricas, para Pinus taeda, Eucalyptus globulus y Eucalyptus dunnii en Uruguay]. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Bosque, 2014, v.35, no.3, p. 369-376. |
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DOI : |
10.4067/S0717-92002014000300011 |
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Idioma : |
Español |
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Contenido : |
SUMMARY.
The aim of this study was to compare the accuracy of Weibull, reverse Weibull, SB Johnson, Gamma and Beta distributions, fitted with the method of moments and maximum likelihood, for describing diameter distributions in stands of Pinus taeda, Eucalyptus globulus, and Eucalyptus dunnii in Uruguay. Data from 429 permanent plots of P. taeda, 185 plots of E. globulus and 271 plots of E. dunnii were used. To compare the quality of fit for the probability distribution function (pdf), the Kolmogorov-Smirnov and Reynolds error indices were used. The function SB Johnson presented a better fit on the plots of P. taeda, while the inverted Weibull function was more accurate for Eucalyptus species. The method of moments was more accurate than maximum likelihood.
RESUMEN.
El objetivo de este estudio fue comparar la precisión de las distribuciones de Weibull, Weibull reversa, SB de Johnson, Gamma y Beta, ajustadas por método de los momentos y máxima verosimilitud, para describir distribuciones diamétricas de Pinus taeda, Eucalyptus globulus y Eucalyptus dunnii en Uruguay. Se utilizaron datos de un total de 429 parcelas permanentes de P. taeda, 185 parcelas de E. globulus y 271 parcelas de E. dunnii. Para compararla calidad del ajuste de las funciones de densidad de probabilidad (fdp) se utilizaron la prueba de Kolmogorov-Smirnov y el índice de error de Reynolds. La función SB de Johnson presentó un mejor ajuste en las parcelas de P. taeda, mientras la función Weibull reversa fue más precisa para las especies de Eucalyptus. El método de los momentos resultó con mayor precisión que el método de máxima verosimilitud. MenosSUMMARY.
The aim of this study was to compare the accuracy of Weibull, reverse Weibull, SB Johnson, Gamma and Beta distributions, fitted with the method of moments and maximum likelihood, for describing diameter distributions in stands of Pinus taeda, Eucalyptus globulus, and Eucalyptus dunnii in Uruguay. Data from 429 permanent plots of P. taeda, 185 plots of E. globulus and 271 plots of E. dunnii were used. To compare the quality of fit for the probability distribution function (pdf), the Kolmogorov-Smirnov and Reynolds error indices were used. The function SB Johnson presented a better fit on the plots of P. taeda, while the inverted Weibull function was more accurate for Eucalyptus species. The method of moments was more accurate than maximum likelihood.
RESUMEN.
El objetivo de este estudio fue comparar la precisión de las distribuciones de Weibull, Weibull reversa, SB de Johnson, Gamma y Beta, ajustadas por método de los momentos y máxima verosimilitud, para describir distribuciones diamétricas de Pinus taeda, Eucalyptus globulus y Eucalyptus dunnii en Uruguay. Se utilizaron datos de un total de 429 parcelas permanentes de P. taeda, 185 parcelas de E. globulus y 271 parcelas de E. dunnii. Para compararla calidad del ajuste de las funciones de densidad de probabilidad (fdp) se utilizaron la prueba de Kolmogorov-Smirnov y el índice de error de Reynolds. La función SB de Johnson presentó un mejor ajuste en las parcelas de P. taeda, mientras la función Weibull reversa fu... Presentar Todo |
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Thesagro : |
EUCALYPTUS. |
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Asunto categoría : |
K01 Ciencias forestales - Aspectos generales |
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Marc : |
LEADER 02308naa a2200157 a 4500
001 1054962
005 2019-09-23
008 2014 bl uuuu u00u1 u #d
024 7 $a10.4067/S0717-92002014000300011$2DOI
100 1 $aHIRIGOYEN, A.
245 $aSelecting diametric frequency distribution functions for pinus taeda, eucalyptus globulus and eucalyptus dunnii in Uruguay. [Selección de funciones de distribución de frecuencias diamétricas, para Pinus taeda, Eucalyptus globulus y Eucalyptus dunnii en Uruguay].$h[electronic resource]
260 $c2014
520 $aSUMMARY. The aim of this study was to compare the accuracy of Weibull, reverse Weibull, SB Johnson, Gamma and Beta distributions, fitted with the method of moments and maximum likelihood, for describing diameter distributions in stands of Pinus taeda, Eucalyptus globulus, and Eucalyptus dunnii in Uruguay. Data from 429 permanent plots of P. taeda, 185 plots of E. globulus and 271 plots of E. dunnii were used. To compare the quality of fit for the probability distribution function (pdf), the Kolmogorov-Smirnov and Reynolds error indices were used. The function SB Johnson presented a better fit on the plots of P. taeda, while the inverted Weibull function was more accurate for Eucalyptus species. The method of moments was more accurate than maximum likelihood. RESUMEN. El objetivo de este estudio fue comparar la precisión de las distribuciones de Weibull, Weibull reversa, SB de Johnson, Gamma y Beta, ajustadas por método de los momentos y máxima verosimilitud, para describir distribuciones diamétricas de Pinus taeda, Eucalyptus globulus y Eucalyptus dunnii en Uruguay. Se utilizaron datos de un total de 429 parcelas permanentes de P. taeda, 185 parcelas de E. globulus y 271 parcelas de E. dunnii. Para compararla calidad del ajuste de las funciones de densidad de probabilidad (fdp) se utilizaron la prueba de Kolmogorov-Smirnov y el índice de error de Reynolds. La función SB de Johnson presentó un mejor ajuste en las parcelas de P. taeda, mientras la función Weibull reversa fue más precisa para las especies de Eucalyptus. El método de los momentos resultó con mayor precisión que el método de máxima verosimilitud.
650 $aEUCALYPTUS
700 1 $aRACHID, C.
773 $tBosque, 2014$gv.35, no.3, p. 369-376.
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