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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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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
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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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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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha actual : |
27/04/2021 |
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Actualizado : |
28/04/2021 |
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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 : |
RUGGIA, A.; DOGLIOTTI, S.; AGUERRE, V.; ALBICETTE, M.M.; ALBÍN, A.; BLUMETTO, O.; CARDOZO, G.; LEONI, C.; QUINTANS, G.; SCARLATO, S.; TITTONELL, P.; ROSSING, W. A.H. |
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Afiliación : |
ANDREA PAOLA RUGGIA CHIESA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Farming Systems Ecology, Wageningen University and Research, Wageningen, the Netherlands; SANTIAGO DOGLIOTTI, Universidad de la República, Facultad de Agronomía, Departamento de Producción Vegetal, Montevideo, Uruguay; MARIA VERONICA AGUERRE ANTIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA MARTA ALBICETTE BASTRERI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALFREDO SANTIAGO ALBÍN FERREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSCAR RICARDO BLUMETTO VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GERONIMO AGUSTIN CARDOZO CABANELAS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CAROLINA LEONI VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GRACIELA QUINTANS ILARIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SANTIAGO SCARLATO GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PABLO TITTONELL, Instituto Nacional de Tecnología Agropecuaria (INTA), Grupo de Agroecología, Ambiente y Sistemas de Producción, San Carlos de Bariloche, Argentina; WALTER A.H. ROSSING, Farming Systems Ecology, Wageningen University and Research, Wageningen, the Netherlands. |
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Título : |
The application of ecologically intensive principles to the systemic redesign of livestock farms on native grasslands: A case of co-innovation in Rocha, Uruguay. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Agricultural Systems, June 2021, Volume 191, Article 103148. OPEN ACCESS. Doi: https://doi.org/10.1016/j.agsy.2021.103148 |
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ISSN : |
0308-521X |
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DOI : |
10.1016/j.agsy.2021.103148 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 30 November 2020; Received in revised form 5 April 2021; Accepted 6 April 2021.
Editor: Guillaume Martin.
The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Corresponding author at: Instituto Nacional de Investigaci´on Agropecuaria (INIA), Estación Experimental INIA Las Brujas, Ruta 48 km 10, Canelones, Uruguay
and P.O. Box 430, 6700 AK, Wageningen, The Netherlands. Corresponding author: Andrea Ruggia - E-mail: aruggia@inia.org.uy, andrea.ruggia@wur.nl Corresponding author: Santiago Dogliotte - E-mail: sandog@fagro.edu.uy |
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Contenido : |
ABSTRACT.
CONTEXT: Family-run cow-calf farms based on native grasslands exhibit low economic and social sustainability, as reflected in low family incomes and high workloads. Experimental results have shown that pasture?herd interaction management could improve native grasslands and animal productivity.
OBJECTIVE: This paper analyzes the extent to which the sustainability of family-run livestock farms based on native grasslands could be enhanced by a systemic redesign informed by ecological intensification practices. The research questions address the initial state of farm sustainability, key bottlenecks to improving farm sustainability,
and changes in sustainability criteria achieved over three years of farm redesign.
METHODS: The study was executed as part of a multi-level co-innovation project in Uruguay in which a team of scientist-practitioners and seven farm families participated in farm characterization, diagnosis, and redesign. The farm characterization took the form of indicators to describe the farms' management and bio-physical subsystems. Redesign plans were negotiated between the research team and the farmers. Frequent monitoring and evaluation cycles enabled finetuning across the years of implementation. |
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Palabras claves : |
Monitoring and evaluation; Native grasslands; Participatory approach; Pasture-herd interactions; Reflexivity; Systems thinking. |
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Asunto categoría : |
P01 Conservación de la naturaleza y recursos de La tierra |
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URL : |
https://www.sciencedirect.com/science/article/pii/S0308521X21001013/pdfft?md5=b2bbe53881026f740faf29e35f3350ce&pid=1-s2.0-S0308521X21001013-main.pdf
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Marc : |
LEADER 03040naa a2200361 a 4500
001 1062001
005 2021-04-28
008 2021 bl uuuu u00u1 u #d
022 $a0308-521X
024 7 $a10.1016/j.agsy.2021.103148$2DOI
100 1 $aRUGGIA, A.
245 $aThe application of ecologically intensive principles to the systemic redesign of livestock farms on native grasslands$bA case of co-innovation in Rocha, Uruguay.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 30 November 2020; Received in revised form 5 April 2021; Accepted 6 April 2021. Editor: Guillaume Martin. The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Corresponding author at: Instituto Nacional de Investigaci´on Agropecuaria (INIA), Estación Experimental INIA Las Brujas, Ruta 48 km 10, Canelones, Uruguay and P.O. Box 430, 6700 AK, Wageningen, The Netherlands. Corresponding author: Andrea Ruggia - E-mail: aruggia@inia.org.uy, andrea.ruggia@wur.nl Corresponding author: Santiago Dogliotte - E-mail: sandog@fagro.edu.uy
520 $aABSTRACT. CONTEXT: Family-run cow-calf farms based on native grasslands exhibit low economic and social sustainability, as reflected in low family incomes and high workloads. Experimental results have shown that pasture?herd interaction management could improve native grasslands and animal productivity. OBJECTIVE: This paper analyzes the extent to which the sustainability of family-run livestock farms based on native grasslands could be enhanced by a systemic redesign informed by ecological intensification practices. The research questions address the initial state of farm sustainability, key bottlenecks to improving farm sustainability, and changes in sustainability criteria achieved over three years of farm redesign. METHODS: The study was executed as part of a multi-level co-innovation project in Uruguay in which a team of scientist-practitioners and seven farm families participated in farm characterization, diagnosis, and redesign. The farm characterization took the form of indicators to describe the farms' management and bio-physical subsystems. Redesign plans were negotiated between the research team and the farmers. Frequent monitoring and evaluation cycles enabled finetuning across the years of implementation.
653 $aMonitoring and evaluation
653 $aNative grasslands
653 $aParticipatory approach
653 $aPasture-herd interactions
653 $aReflexivity
653 $aSystems thinking
700 1 $aDOGLIOTTI, S.
700 1 $aAGUERRE, V.
700 1 $aALBICETTE, M.M.
700 1 $aALBÍN, A.
700 1 $aBLUMETTO, O.
700 1 $aCARDOZO, G.
700 1 $aLEONI, C.
700 1 $aQUINTANS, G.
700 1 $aSCARLATO, S.
700 1 $aTITTONELL, P.
700 1 $aROSSING, W. A.H.
773 $tAgricultural Systems, June 2021, Volume 191, Article 103148. OPEN ACCESS. Doi: https://doi.org/10.1016/j.agsy.2021.103148
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