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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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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. |
|
Fecha actual : |
13/12/2022 |
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Actualizado : |
22/10/2024 |
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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 : |
AGUERRE, V.; BIANCO, M. |
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Afiliación : |
MARIA VERONICA AGUERRE ANTIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIELA BIANCO, Universidad de la República, Facultad de Agronomía, Departamento de Ciencias Sociales, Av. Garz´on 780, Montevideo, Uruguay. |
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Título : |
Co-innovation and socio-technological niche development: The case of livestock farming on natural grassland in Uruguay. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Journal of Rural Studies, January 2023, Volume 97, Pages 81-94. doi: https://doi.org/10.1016/j.jrurstud.2022.12.003 |
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ISSN : |
0743-0167 |
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DOI : |
10.1016/j.jrurstud.2022.12.003 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 12 January 2022; Received in revised form 10 November 2022; Accepted 4 December 2022; Available online 10 December 2022. -- Corresponding author: E-mail addresses: vaguerre@inia.org.uy (V. Aguerre), mbianco@fagro.edu.uy (M. Bianco). -- |
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Contenido : |
ABSTRACT.- Achieving sustainable food and nutritional security requires a transformation of the existing agrifood system. In livestock farming based on natural grassland in Uruguay, an ecological intensification strategy could play a radical role in the transition towards more sustainable systems. This study analyzes the continuity of interconnected projects that used co-innovation approaches to promote and evaluate ecological intensification strategies over a period of 15 years (2004-2019). The purpose of the article is to provide evidence on the development of a socio-technical niche in sustainable livestock farming and to identify anchoring points for further regime transformation. Our contention is that interactive research in the context of application based on a sequence of co-innovation projects has the potential to trigger a sustainability transition through ecological intensification of livestock farming based on natural grassland. The research followed a single-case study design with multiple units of analysis, based on the study of documents produced by the different projects and semi-structured interviews. In addition, network analysis was used to examine the linkage of persons and projects. Results show that a socio-technical niche in sustainable livestock farming base on natural grassland was developed in Uruguay, promoted by research institutions and progressively involving other social actors throughout the process. The continuity of projects over 15 years, was fundamental to achieve the three essential processes for a niche conformation: i) an alignment of expectations and the development of a common vision, linked to the sustainable development of family-farming; ii) the creation and expansion of a network of stakeholders, comprising researchers, farmers, extensionists, and other relevant actors; iii) the development of learning processes through interaction, accumulating knowledge around two main axes: a new way of promoting innovation through research in application contexts associated with co-innovation, and a new way of sustainable livestock farming associated with ecological intensification. This study reveals the importance of sequencing co-innovation projects and continuity in the negotiation of visions of change, the creation of a community committed with the direction of change, and the promotion of interdisciplinarity and interactive learning, that foster changes at a socio-technical level. Anchoring challenges, and therefore advancement of the transition process, face the need for significantly expanding trained research and extension personnel to implement co-innovation and ecological intensification practices in livestock systems, and the organization of an extension program to sustain long term transformation of livestock farming in Uruguay. © 2022 Elsevier Ltd. All rights reserved. MenosABSTRACT.- Achieving sustainable food and nutritional security requires a transformation of the existing agrifood system. In livestock farming based on natural grassland in Uruguay, an ecological intensification strategy could play a radical role in the transition towards more sustainable systems. This study analyzes the continuity of interconnected projects that used co-innovation approaches to promote and evaluate ecological intensification strategies over a period of 15 years (2004-2019). The purpose of the article is to provide evidence on the development of a socio-technical niche in sustainable livestock farming and to identify anchoring points for further regime transformation. Our contention is that interactive research in the context of application based on a sequence of co-innovation projects has the potential to trigger a sustainability transition through ecological intensification of livestock farming based on natural grassland. The research followed a single-case study design with multiple units of analysis, based on the study of documents produced by the different projects and semi-structured interviews. In addition, network analysis was used to examine the linkage of persons and projects. Results show that a socio-technical niche in sustainable livestock farming base on natural grassland was developed in Uruguay, promoted by research institutions and progressively involving other social actors throughout the process. The continuity of projects over 15 years, w... Presentar Todo |
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Palabras claves : |
Co-innovation; Ecological intensification; Innovation processes; Sustainability transitions; URUGUAY. |
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Asunto categoría : |
E50 Sociología rural y seguridad social |
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Marc : |
LEADER 03905naa a2200229 a 4500
001 1063839
005 2024-10-22
008 2022 bl uuuu u00u1 u #d
022 $a0743-0167
024 7 $a10.1016/j.jrurstud.2022.12.003$2DOI
100 1 $aAGUERRE, V.
245 $aCo-innovation and socio-technological niche development$bThe case of livestock farming on natural grassland in Uruguay.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 12 January 2022; Received in revised form 10 November 2022; Accepted 4 December 2022; Available online 10 December 2022. -- Corresponding author: E-mail addresses: vaguerre@inia.org.uy (V. Aguerre), mbianco@fagro.edu.uy (M. Bianco). --
520 $aABSTRACT.- Achieving sustainable food and nutritional security requires a transformation of the existing agrifood system. In livestock farming based on natural grassland in Uruguay, an ecological intensification strategy could play a radical role in the transition towards more sustainable systems. This study analyzes the continuity of interconnected projects that used co-innovation approaches to promote and evaluate ecological intensification strategies over a period of 15 years (2004-2019). The purpose of the article is to provide evidence on the development of a socio-technical niche in sustainable livestock farming and to identify anchoring points for further regime transformation. Our contention is that interactive research in the context of application based on a sequence of co-innovation projects has the potential to trigger a sustainability transition through ecological intensification of livestock farming based on natural grassland. The research followed a single-case study design with multiple units of analysis, based on the study of documents produced by the different projects and semi-structured interviews. In addition, network analysis was used to examine the linkage of persons and projects. Results show that a socio-technical niche in sustainable livestock farming base on natural grassland was developed in Uruguay, promoted by research institutions and progressively involving other social actors throughout the process. The continuity of projects over 15 years, was fundamental to achieve the three essential processes for a niche conformation: i) an alignment of expectations and the development of a common vision, linked to the sustainable development of family-farming; ii) the creation and expansion of a network of stakeholders, comprising researchers, farmers, extensionists, and other relevant actors; iii) the development of learning processes through interaction, accumulating knowledge around two main axes: a new way of promoting innovation through research in application contexts associated with co-innovation, and a new way of sustainable livestock farming associated with ecological intensification. This study reveals the importance of sequencing co-innovation projects and continuity in the negotiation of visions of change, the creation of a community committed with the direction of change, and the promotion of interdisciplinarity and interactive learning, that foster changes at a socio-technical level. Anchoring challenges, and therefore advancement of the transition process, face the need for significantly expanding trained research and extension personnel to implement co-innovation and ecological intensification practices in livestock systems, and the organization of an extension program to sustain long term transformation of livestock farming in Uruguay. © 2022 Elsevier Ltd. All rights reserved.
653 $aCo-innovation
653 $aEcological intensification
653 $aInnovation processes
653 $aSustainability transitions
653 $aURUGUAY
700 1 $aBIANCO, M.
773 $tJournal of Rural Studies, January 2023, Volume 97, Pages 81-94. doi: https://doi.org/10.1016/j.jrurstud.2022.12.003
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