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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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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
16/10/2017 |
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Actualizado : |
13/08/2018 |
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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 : |
CRUZ, G.; BAETHGEN, W.; BARTABURU, D.; BIDEGAIN, M.; GIMÉNEZ, A.; METHOL, M.; MORALES, H.; PICASSO, V.; PODESTA, G.; TADDEI, R.; TERRA, R.; TISCORNIA, G.; VINOCUR, M. |
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Afiliación : |
G. CRUZ, Universidad de la República (UdelaR)/ Facultad de Agronomía; WALTER E. BAETHGEN, Universidad de Columbia/ IRI (International Research Institute for Climate and Society); D. BARTABURU, IPA (Instituto Plan Agropecuario); M. BIDEGAIN, INUMET (Instituto Uruguayo de Meteorología); AGUSTIN EDUARDO GIMÉNEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; M. METHOL, MGAP/ OPYPA (Oficina de Programación y Política Agropecuaria).; H. MORALES, IPA (Instituto Plan Agropecuario); V. PICASSO, Universidad de la República (UdelaR)/ Facultad de Agronomía; Universidad de Wisconsin-Madison; G. PODESTA, University of Miami, Rosenstiel School of Marine and Atmospheric Science; R. TADDEI, Federal University of São Paulo (UNIFESP); R. TERRA, Universidad de la República (UdelaR)/ Facultad de Ingeniería; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; M. VINOCUR, Universidad Nacional de Río Cuarto (UNRC), Facultad de Agronomía y Veterinaria. |
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Título : |
Thirty years of multi-level processes for adaptation of livestock production to droughts in Uruguay. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Weather, Climate, and Society (WCAS), 2017. |
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DOI : |
10.1175/WCAS-D-16-0133.1 |
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Idioma : |
Inglés |
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Notas : |
Publicado en el 2018: WCAS, jan.,2018, v. 10, p. 59-74. Article history: Received: 22 December 2016; Final Form: 2 Octobre 2017; Published online: 13 December 2017. |
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Contenido : |
ABSTRACT.
Most countries lack effective policies to manage climate risks, despite growing concerns with climate change. We analyzed the policy evolution from a disaster management to a risk management approach, using as a case study four agricultural droughts that impacted Uruguay?s livestock sector in the last three decades. A transdisciplinary team of researchers, extension workers, and policy makers agreed on a common conceptual framework for the interpretation of past droughts and policies. The evidence presented shows that the set of actions implemented at different levels when facing droughts were mainly reactive in the past but later evolved to a more integral risk management approach. A greater interinstitutional integration and a decreasing gap between science and policy were identified during the period of study. Social and political learning enabled a vision of proactive management and promoted effective adaptive measures. While the Government of Uruguay explicitly incorporated the issue of adaptation to climate change to its agenda, research institutions also fostered the creation of interdisciplinary study groups on this topic, resulting in new stages of learning. The recent changes in public policies, institutional governance and academic research, have contributed to enhance the adaptive capacity of the agricultural sector to climate variability, and in particular to drought. This study confirms the relevance and need to work within a transdisciplinary framework to effectively address the different social learning dimensions, particularly those concerning the adaptation to global change.
@2017 American Meteorological Society MenosABSTRACT.
Most countries lack effective policies to manage climate risks, despite growing concerns with climate change. We analyzed the policy evolution from a disaster management to a risk management approach, using as a case study four agricultural droughts that impacted Uruguay?s livestock sector in the last three decades. A transdisciplinary team of researchers, extension workers, and policy makers agreed on a common conceptual framework for the interpretation of past droughts and policies. The evidence presented shows that the set of actions implemented at different levels when facing droughts were mainly reactive in the past but later evolved to a more integral risk management approach. A greater interinstitutional integration and a decreasing gap between science and policy were identified during the period of study. Social and political learning enabled a vision of proactive management and promoted effective adaptive measures. While the Government of Uruguay explicitly incorporated the issue of adaptation to climate change to its agenda, research institutions also fostered the creation of interdisciplinary study groups on this topic, resulting in new stages of learning. The recent changes in public policies, institutional governance and academic research, have contributed to enhance the adaptive capacity of the agricultural sector to climate variability, and in particular to drought. This study confirms the relevance and need to work within a transdisciplinary framew... Presentar Todo |
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Palabras claves : |
AGRICULTURA; CLIMATE CHANGE; CLIMATE VARIABILITY; DROUGHT; POLICY; PUBLIC POLICIES; SOCIAL SCIENCE; SOUTH AMERICA. |
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Thesagro : |
CAMBIO CLIMÁTICO; URUGUAY. |
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Asunto categoría : |
P40 Meteorología y climatología |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10993/1/wcas-d-16-0133.1.pdf
https://journals.ametsoc.org/doi/pdf/10.1175/WCAS-D-16-0133.1
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Marc : |
LEADER 02913naa a2200409 a 4500
001 1057659
005 2018-08-13
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1175/WCAS-D-16-0133.1$2DOI
100 1 $aCRUZ, G.
245 $aThirty years of multi-level processes for adaptation of livestock production to droughts in Uruguay.$h[electronic resource]
260 $c2017
500 $aPublicado en el 2018: WCAS, jan.,2018, v. 10, p. 59-74. Article history: Received: 22 December 2016; Final Form: 2 Octobre 2017; Published online: 13 December 2017.
520 $aABSTRACT. Most countries lack effective policies to manage climate risks, despite growing concerns with climate change. We analyzed the policy evolution from a disaster management to a risk management approach, using as a case study four agricultural droughts that impacted Uruguay?s livestock sector in the last three decades. A transdisciplinary team of researchers, extension workers, and policy makers agreed on a common conceptual framework for the interpretation of past droughts and policies. The evidence presented shows that the set of actions implemented at different levels when facing droughts were mainly reactive in the past but later evolved to a more integral risk management approach. A greater interinstitutional integration and a decreasing gap between science and policy were identified during the period of study. Social and political learning enabled a vision of proactive management and promoted effective adaptive measures. While the Government of Uruguay explicitly incorporated the issue of adaptation to climate change to its agenda, research institutions also fostered the creation of interdisciplinary study groups on this topic, resulting in new stages of learning. The recent changes in public policies, institutional governance and academic research, have contributed to enhance the adaptive capacity of the agricultural sector to climate variability, and in particular to drought. This study confirms the relevance and need to work within a transdisciplinary framework to effectively address the different social learning dimensions, particularly those concerning the adaptation to global change. @2017 American Meteorological Society
650 $aCAMBIO CLIMÁTICO
650 $aURUGUAY
653 $aAGRICULTURA
653 $aCLIMATE CHANGE
653 $aCLIMATE VARIABILITY
653 $aDROUGHT
653 $aPOLICY
653 $aPUBLIC POLICIES
653 $aSOCIAL SCIENCE
653 $aSOUTH AMERICA
700 1 $aBAETHGEN, W.
700 1 $aBARTABURU, D.
700 1 $aBIDEGAIN, M.
700 1 $aGIMÉNEZ, A.
700 1 $aMETHOL, M.
700 1 $aMORALES, H.
700 1 $aPICASSO, V.
700 1 $aPODESTA, G.
700 1 $aTADDEI, R.
700 1 $aTERRA, R.
700 1 $aTISCORNIA, G.
700 1 $aVINOCUR, M.
773 $tWeather, Climate, and Society (WCAS), 2017.
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