| |
|
|
 | 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
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha actual : |
17/12/2020 |
|
Actualizado : |
06/09/2022 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Nacionales |
|
Circulación / Nivel : |
Nacional - -- |
|
Autor : |
BECOÑA, G.; LEDGARD, S.; ASTIGARRAGA, L.; LIZARRALDE, C.; DIEGUEZ, F.; HERMES, M. |
|
Afiliación : |
GONZALO BECOÑA, Instituto Plan Agropecuario, Montevideo, Uruguay.; STEWART LEDGARD, AgResearch, Hamilton, New Zealand.; LAURA ASTIGARRAGA, Universidad de la República, Facultad de Agronomía, Montevideo, Uruguay.; CAROLINA ANGELA LIZARRALDE PIQUET, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FRANCISCO DIEGUEZ, Universidad de la República, Facultad de Veterinaria, Montevideo, Uruguay.; MORALES HERMES, Instituto Plan Agropecuario, Montevideo, Uruguay. |
|
Título : |
EMAG - National model for evaluating environmental impacts of cattle production systems in Uruguay. [EMAG - Modelo nacional para evaluar impactos ambientales de sistemas de producción ganadera en Uruguay]. [EMAG - Modelo nacional de evaluação de impactos ambientais dos sistemas de produção pecuária no Uruguai]. |
|
Complemento del título : |
Section: Natural and environmental resources |
|
Fecha de publicación : |
2020 |
|
Fuente / Imprenta : |
Agrociencia Uruguay, 2020, 24(2): 1- 19. Article 48. Doi: https://doi.org/10.31285/AGRO.24.48 |
|
ISSN : |
e-ISSN: 2301-1548 |
|
DOI : |
10.31285/AGRO.24.48 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received09 May 2019; Accepted17 Jul 2020; Published17 Aug 2020.
APA Citation: Becoña, G., Ledgard, S., Astigarraga, L., Lizarralde, C., Dieguez, F., & Hermes, M. (2020). EMAG - National model for evaluating environmental impacts of cattle production systems in Uruguay. Agrociencia Uruguay, 24(2), 1- 19. https://doi.org/10.31285/AGRO.24.48 |
|
Contenido : |
ABSTRACT.
Cattle and sheep systems in Uruguay and worldwide are challenged to reduce their environmental footprint while increasing efficiency and production. To achieve this challenge, user-friendly tools are needed that can translate research findings into practical information that could improve decision making by farmers and advise different stakeholders. Despite this, there are a limited number of applied environmental models in other countries and they are typically based on productive, high-quality pasture/crop-feed systems with relatively high inputs. In contrast, cattle and sheep production in Uruguay is largely associated with extensive grazing systems on unique natural grassland systems of relatively poor feed quality and often with no nutrient inputs in fertilizers. Thus, there is a need for a model that can take account for these types of systems and bring together relevant country-specific data to provide information of relevance for Uruguay. The EMAG (Evaluación Medio Ambiental Ganadera) model accounts for multiple environmental and resource use indicators of nutrient (nitrogen and phosphorus) balances and losses, greenhouse gas emissions and use of fossil energy. Results are provided on a per-hectare and per-kg product basis. This decision support tool for cattle and sheep farmers systems is based on life cycle assessment (LCA) methodology from ?cradle-to-farm gate? for all resources use indicators. It uses national pa-rameters and in case of lack of information is supplied from international research in pastoral systems. The model use for environmental methodology tier 2 animal energy model to account for key animal productivity and management practices. EMAG is a user-friendly model that requires basic information for a farm system divided into land use (forage types used uniquely for natural grassland in Uruguay), animal management (beef cattle and sheep), farm inputs (fertilizers, supplementary feeds, seeds and agrochemicals) and fossil energy (fuel and electricity) used in the system. EMAG can help to identify hot-spots of emissions and resource use, as well as to evaluate changes over time. In addition, it can be used to test cattle or sheep management practices or evaluate mitigation options within the system. By providing multiple indicators, EMAG can be used to provide information to avoid ?trade-offs? between environmental impacts when assessing future options. As an example of usability, the paper reports a case study which showed potential benefits of improving environmental efficiency and note interesting result around negative P balance when increase productivity in a system. In summary, EMAG is a decision-support tool developed with the objective of evaluating the environmental performance of cattle and sheep systems, that would help farmers in decision making and different stakeholders according to their interest.
.-.-.-.-.-.-.-.
RESUMEN.
Los sistemas ganaderos en Uruguay y en todo el mundo tienen el desafío de reducir su huella ambiental al tiempo que aumentan la eficiencia y la producción. Para lograr este desafío, se necesitan herramientas fáciles de usar que puedan traducir los hallazgos de la investigación en información práctica que pueda mejorar la toma de decisiones de los productores y asesorar a diferentes actores interesados. A pesar de que existe un número limitado de modelos ambientales utilizados en otros países, por lo general, se basan en sistemas pro-ductivos donde existen forrajes de alta calidad/cultivos y con alto uso de insumos. En contraste, la producción ganadera en Uruguay está asociada en gran medida con sistemas de pastoreo extensivos, basados en el uso de forrajes únicos en el mundo donde la calidad del alimento es relativamente pobre y prácticamente sin agre-gado de fertilizantes. Por lo tanto, en este escenario existe la necesidad de un modelo que pueda tener en cuenta este tipo de sistemas y que reúna datos relevantes específicos nacionales con el objetivo de proporcio-nar información relevante para Uruguay. El modelo EMAG (Evaluación Medio Ambiental Ganadera) cuenta con múltiples indicadores ambientales y de uso de recursos de balances como: pérdidas de nutrientes (nitrógeno y fósforo), emisiones de gases de efecto invernadero y uso de energía fósil. Los resultados se proporcionan por hectárea y por kg de producto. Esta herramienta de apoyo a la toma de decisión para sistemas ganaderos (vacuno y ovinos) se basa en la metodología de evaluación de análisis de ciclo de vida (ACV) desde la "cuna a la portera del establecimiento" para todos los indicadores de uso de los recursos. Utiliza parámetros nacionales y, en caso de falta de información, se obtiene de investigaciones internacionales en sistemas pastoriles. El modelo utiliza para la metodología ambiental la referente de energía animal de nivel 2 para evaluar las prácticas clave de producción y manejo animal. EMAG es un modelo fácil de usar que requiere información básica de un sistema dividido en: el uso de la tierra (tipos de forraje utilizados exclusivamente para pasturas naturales en Uruguay), manejo de animales (ganado vacuno y ovino), insumos utilizados (fertilizantes, alimentos complementarios, semillas y agroquímicos) y energía fósil (combustible y electricidad) utilizada en el sistema. EMAG puede ayudar a identificar puntos altos de emisiones ambientales y uso de recursos natura les, así como evaluar cambios a lo largo del tiempo. Además, se puede utilizar para probar distintas prácticas de manejo de ganado vacuno y ovino o evaluar las opciones de mitigación dentro del sistema. Al proporcionar múltiples indicadores, EMAG se puede utilizar para proporcionar información para evitar «compensaciones» entre los impactos ambientales al evaluar las opciones futuras. Como ejemplo de usabilidad del modelo, el documento presenta un estudio de caso que muestra los beneficios potenciales de mejorar la eficiencia ambiental con un resultado interesante en torno al balance de fósforo negativo cuando se incrementa la productividad en un sistema. En resumen, EMAG es una herramienta de apoyo a la toma de decisiones desarrollada con el objetivo de evaluar el desempeño ambiental de los sistemas ganaderos que ayudaría a los agricultores en su toma de decisiones y a diferentes actores interesados. MenosABSTRACT.
Cattle and sheep systems in Uruguay and worldwide are challenged to reduce their environmental footprint while increasing efficiency and production. To achieve this challenge, user-friendly tools are needed that can translate research findings into practical information that could improve decision making by farmers and advise different stakeholders. Despite this, there are a limited number of applied environmental models in other countries and they are typically based on productive, high-quality pasture/crop-feed systems with relatively high inputs. In contrast, cattle and sheep production in Uruguay is largely associated with extensive grazing systems on unique natural grassland systems of relatively poor feed quality and often with no nutrient inputs in fertilizers. Thus, there is a need for a model that can take account for these types of systems and bring together relevant country-specific data to provide information of relevance for Uruguay. The EMAG (Evaluación Medio Ambiental Ganadera) model accounts for multiple environmental and resource use indicators of nutrient (nitrogen and phosphorus) balances and losses, greenhouse gas emissions and use of fossil energy. Results are provided on a per-hectare and per-kg product basis. This decision support tool for cattle and sheep farmers systems is based on life cycle assessment (LCA) methodology from ?cradle-to-farm gate? for all resources use indicators. It uses national pa-rameters ... Presentar Todo |
|
Palabras claves : |
CATTLE; ENVIRONMENT; GRAZING SYSTEMS; MEIO AMBIENTE; MODEL; Pecuária; Sistemas de pastoreio. |
|
Thesagro : |
GANADO; MEDIOAMBIENTE; MODELO; SISTEMAS DE PASTOREO. |
|
Asunto categoría : |
L02 Alimentación animal |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16745/1/Agrociencia-UY-2020-24-N2-48.pdf
|
|
Marc : |
LEADER 08049naa a2200349 a 4500
001 1061588
005 2022-09-06
008 2020 bl uuuu u00u1 u #d
022 $ae-ISSN: 2301-1548
024 7 $a10.31285/AGRO.24.48$2DOI
100 1 $aBECOÑA, G.
245 $aEMAG - National model for evaluating environmental impacts of cattle production systems in Uruguay. [EMAG - Modelo nacional para evaluar impactos ambientales de sistemas de producción ganadera en Uruguay]. [EMAG - Modelo nacional de evaluação de impactos ambientais dos sistemas de produção pecuária no Uruguai].$h[electronic resource]
260 $c2020
500 $aArticle history: Received09 May 2019; Accepted17 Jul 2020; Published17 Aug 2020. APA Citation: Becoña, G., Ledgard, S., Astigarraga, L., Lizarralde, C., Dieguez, F., & Hermes, M. (2020). EMAG - National model for evaluating environmental impacts of cattle production systems in Uruguay. Agrociencia Uruguay, 24(2), 1- 19. https://doi.org/10.31285/AGRO.24.48
520 $aABSTRACT. Cattle and sheep systems in Uruguay and worldwide are challenged to reduce their environmental footprint while increasing efficiency and production. To achieve this challenge, user-friendly tools are needed that can translate research findings into practical information that could improve decision making by farmers and advise different stakeholders. Despite this, there are a limited number of applied environmental models in other countries and they are typically based on productive, high-quality pasture/crop-feed systems with relatively high inputs. In contrast, cattle and sheep production in Uruguay is largely associated with extensive grazing systems on unique natural grassland systems of relatively poor feed quality and often with no nutrient inputs in fertilizers. Thus, there is a need for a model that can take account for these types of systems and bring together relevant country-specific data to provide information of relevance for Uruguay. The EMAG (Evaluación Medio Ambiental Ganadera) model accounts for multiple environmental and resource use indicators of nutrient (nitrogen and phosphorus) balances and losses, greenhouse gas emissions and use of fossil energy. Results are provided on a per-hectare and per-kg product basis. This decision support tool for cattle and sheep farmers systems is based on life cycle assessment (LCA) methodology from ?cradle-to-farm gate? for all resources use indicators. It uses national pa-rameters and in case of lack of information is supplied from international research in pastoral systems. The model use for environmental methodology tier 2 animal energy model to account for key animal productivity and management practices. EMAG is a user-friendly model that requires basic information for a farm system divided into land use (forage types used uniquely for natural grassland in Uruguay), animal management (beef cattle and sheep), farm inputs (fertilizers, supplementary feeds, seeds and agrochemicals) and fossil energy (fuel and electricity) used in the system. EMAG can help to identify hot-spots of emissions and resource use, as well as to evaluate changes over time. In addition, it can be used to test cattle or sheep management practices or evaluate mitigation options within the system. By providing multiple indicators, EMAG can be used to provide information to avoid ?trade-offs? between environmental impacts when assessing future options. As an example of usability, the paper reports a case study which showed potential benefits of improving environmental efficiency and note interesting result around negative P balance when increase productivity in a system. In summary, EMAG is a decision-support tool developed with the objective of evaluating the environmental performance of cattle and sheep systems, that would help farmers in decision making and different stakeholders according to their interest. .-.-.-.-.-.-.-. RESUMEN. Los sistemas ganaderos en Uruguay y en todo el mundo tienen el desafío de reducir su huella ambiental al tiempo que aumentan la eficiencia y la producción. Para lograr este desafío, se necesitan herramientas fáciles de usar que puedan traducir los hallazgos de la investigación en información práctica que pueda mejorar la toma de decisiones de los productores y asesorar a diferentes actores interesados. A pesar de que existe un número limitado de modelos ambientales utilizados en otros países, por lo general, se basan en sistemas pro-ductivos donde existen forrajes de alta calidad/cultivos y con alto uso de insumos. En contraste, la producción ganadera en Uruguay está asociada en gran medida con sistemas de pastoreo extensivos, basados en el uso de forrajes únicos en el mundo donde la calidad del alimento es relativamente pobre y prácticamente sin agre-gado de fertilizantes. Por lo tanto, en este escenario existe la necesidad de un modelo que pueda tener en cuenta este tipo de sistemas y que reúna datos relevantes específicos nacionales con el objetivo de proporcio-nar información relevante para Uruguay. El modelo EMAG (Evaluación Medio Ambiental Ganadera) cuenta con múltiples indicadores ambientales y de uso de recursos de balances como: pérdidas de nutrientes (nitrógeno y fósforo), emisiones de gases de efecto invernadero y uso de energía fósil. Los resultados se proporcionan por hectárea y por kg de producto. Esta herramienta de apoyo a la toma de decisión para sistemas ganaderos (vacuno y ovinos) se basa en la metodología de evaluación de análisis de ciclo de vida (ACV) desde la "cuna a la portera del establecimiento" para todos los indicadores de uso de los recursos. Utiliza parámetros nacionales y, en caso de falta de información, se obtiene de investigaciones internacionales en sistemas pastoriles. El modelo utiliza para la metodología ambiental la referente de energía animal de nivel 2 para evaluar las prácticas clave de producción y manejo animal. EMAG es un modelo fácil de usar que requiere información básica de un sistema dividido en: el uso de la tierra (tipos de forraje utilizados exclusivamente para pasturas naturales en Uruguay), manejo de animales (ganado vacuno y ovino), insumos utilizados (fertilizantes, alimentos complementarios, semillas y agroquímicos) y energía fósil (combustible y electricidad) utilizada en el sistema. EMAG puede ayudar a identificar puntos altos de emisiones ambientales y uso de recursos natura les, así como evaluar cambios a lo largo del tiempo. Además, se puede utilizar para probar distintas prácticas de manejo de ganado vacuno y ovino o evaluar las opciones de mitigación dentro del sistema. Al proporcionar múltiples indicadores, EMAG se puede utilizar para proporcionar información para evitar «compensaciones» entre los impactos ambientales al evaluar las opciones futuras. Como ejemplo de usabilidad del modelo, el documento presenta un estudio de caso que muestra los beneficios potenciales de mejorar la eficiencia ambiental con un resultado interesante en torno al balance de fósforo negativo cuando se incrementa la productividad en un sistema. En resumen, EMAG es una herramienta de apoyo a la toma de decisiones desarrollada con el objetivo de evaluar el desempeño ambiental de los sistemas ganaderos que ayudaría a los agricultores en su toma de decisiones y a diferentes actores interesados.
650 $aGANADO
650 $aMEDIOAMBIENTE
650 $aMODELO
650 $aSISTEMAS DE PASTOREO
653 $aCATTLE
653 $aENVIRONMENT
653 $aGRAZING SYSTEMS
653 $aMEIO AMBIENTE
653 $aMODEL
653 $aPecuária
653 $aSistemas de pastoreio
700 1 $aLEDGARD, S.
700 1 $aASTIGARRAGA, L.
700 1 $aLIZARRALDE, C.
700 1 $aDIEGUEZ, F.
700 1 $aHERMES, M.
773 $tAgrociencia Uruguay, 2020, 24(2): 1- 19. Article 48. Doi: https://doi.org/10.31285/AGRO.24.48
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
