Climatic information and decision-making in maize crop production systems of the Argentinean Pampas
- Autores
- Bert, Federico Esteban; Satorre, Emilio Horacio; Toranzo, Fernando Ruiz; Podestá, Guillermo
- Año de publicación
- 2006
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In many places, predictions of regional climate variability associated with El Niño Southern Oscillation (ENSO) phenomenon offer the potential to improve farmers' decision-making, i.e., mitigate negative impacts of adverse conditions or take advantage of favorable conditions. However, various conditions must be met for a forecast to result in enhanced decision-making. First, information has to be relevant to, and compatible with production decisions. Second, alternative options must exist for a given decision and these should result in different outcomes under different climate conditions. Third, decision-makers should be able to evaluate the outcomes of alternative actions. In this paper, we explored these conditions as part of a case study targeting maize production systems in the Argentine Pampas. The decision-making process was described via "decision maps" that (a) characterized the main decisions involved in maize production systems and their timing, (b) identified decisions sensitive to climate, and (c) provided a realistic set of options for each decision under different seasonal climate scenarios. Then, we used crop simulation models to assess the outcomes of tailoring crop management to predicted climate conditions. We found differences between the options selected by regional advisors for each climate scenario and those that maximized average profits in the simulation exercise. In particular, differences were most noticeable in preferred nitrogen fertilization rates. While advisors tended to lower fertilization in response to a forecast of dry spring conditions, associated with La Niña events, the simulation exercise showed a consistent drop in maize yields and profits with low N rates even in La Niña years. Advisors and producers' aversion to risk can be determining these differences, since the analysis showed that the probability of negative economic results are minimized under their decision rule. The procedure was effective to meet some of the conditions required to use climate information and to determine the value of incorporating ENSO-related information to effectively improve the maize decision process. However, results suggest that better knowledge of farmers decision rules are necessary when the value of using climatic information is estimated and interpreted.
Fil: Bert, Federico Esteban. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Satorre, Emilio Horacio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Toranzo, Fernando Ruiz. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; Argentina
Fil: Podestá, Guillermo. University of Miami; Estados Unidos - Materia
-
ARGENTINE PAMPAS
DECISION MAP
ENSO
MAIZE
VALUE OF CLIMATE INFORMATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/132087
Ver los metadatos del registro completo
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Climatic information and decision-making in maize crop production systems of the Argentinean PampasBert, Federico EstebanSatorre, Emilio HoracioToranzo, Fernando RuizPodestá, GuillermoARGENTINE PAMPASDECISION MAPENSOMAIZEVALUE OF CLIMATE INFORMATIONhttps://purl.org/becyt/ford/4.5https://purl.org/becyt/ford/4In many places, predictions of regional climate variability associated with El Niño Southern Oscillation (ENSO) phenomenon offer the potential to improve farmers' decision-making, i.e., mitigate negative impacts of adverse conditions or take advantage of favorable conditions. However, various conditions must be met for a forecast to result in enhanced decision-making. First, information has to be relevant to, and compatible with production decisions. Second, alternative options must exist for a given decision and these should result in different outcomes under different climate conditions. Third, decision-makers should be able to evaluate the outcomes of alternative actions. In this paper, we explored these conditions as part of a case study targeting maize production systems in the Argentine Pampas. The decision-making process was described via "decision maps" that (a) characterized the main decisions involved in maize production systems and their timing, (b) identified decisions sensitive to climate, and (c) provided a realistic set of options for each decision under different seasonal climate scenarios. Then, we used crop simulation models to assess the outcomes of tailoring crop management to predicted climate conditions. We found differences between the options selected by regional advisors for each climate scenario and those that maximized average profits in the simulation exercise. In particular, differences were most noticeable in preferred nitrogen fertilization rates. While advisors tended to lower fertilization in response to a forecast of dry spring conditions, associated with La Niña events, the simulation exercise showed a consistent drop in maize yields and profits with low N rates even in La Niña years. Advisors and producers' aversion to risk can be determining these differences, since the analysis showed that the probability of negative economic results are minimized under their decision rule. The procedure was effective to meet some of the conditions required to use climate information and to determine the value of incorporating ENSO-related information to effectively improve the maize decision process. However, results suggest that better knowledge of farmers decision rules are necessary when the value of using climatic information is estimated and interpreted.Fil: Bert, Federico Esteban. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Satorre, Emilio Horacio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Toranzo, Fernando Ruiz. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; ArgentinaFil: Podestá, Guillermo. University of Miami; Estados UnidosElsevier2006-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/132087Bert, Federico Esteban; Satorre, Emilio Horacio; Toranzo, Fernando Ruiz; Podestá, Guillermo; Climatic information and decision-making in maize crop production systems of the Argentinean Pampas; Elsevier; Agricultural Systems; 88; 2-3; 6-2006; 180-2040308-521XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0308521X05000570info:eu-repo/semantics/altIdentifier/doi/10.1016/j.agsy.2005.03.007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:42:16Zoai:ri.conicet.gov.ar:11336/132087instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:42:16.249CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| title |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| spellingShingle |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas Bert, Federico Esteban ARGENTINE PAMPAS DECISION MAP ENSO MAIZE VALUE OF CLIMATE INFORMATION |
| title_short |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| title_full |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| title_fullStr |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| title_full_unstemmed |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| title_sort |
Climatic information and decision-making in maize crop production systems of the Argentinean Pampas |
| dc.creator.none.fl_str_mv |
Bert, Federico Esteban Satorre, Emilio Horacio Toranzo, Fernando Ruiz Podestá, Guillermo |
| author |
Bert, Federico Esteban |
| author_facet |
Bert, Federico Esteban Satorre, Emilio Horacio Toranzo, Fernando Ruiz Podestá, Guillermo |
| author_role |
author |
| author2 |
Satorre, Emilio Horacio Toranzo, Fernando Ruiz Podestá, Guillermo |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
ARGENTINE PAMPAS DECISION MAP ENSO MAIZE VALUE OF CLIMATE INFORMATION |
| topic |
ARGENTINE PAMPAS DECISION MAP ENSO MAIZE VALUE OF CLIMATE INFORMATION |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.5 https://purl.org/becyt/ford/4 |
| dc.description.none.fl_txt_mv |
In many places, predictions of regional climate variability associated with El Niño Southern Oscillation (ENSO) phenomenon offer the potential to improve farmers' decision-making, i.e., mitigate negative impacts of adverse conditions or take advantage of favorable conditions. However, various conditions must be met for a forecast to result in enhanced decision-making. First, information has to be relevant to, and compatible with production decisions. Second, alternative options must exist for a given decision and these should result in different outcomes under different climate conditions. Third, decision-makers should be able to evaluate the outcomes of alternative actions. In this paper, we explored these conditions as part of a case study targeting maize production systems in the Argentine Pampas. The decision-making process was described via "decision maps" that (a) characterized the main decisions involved in maize production systems and their timing, (b) identified decisions sensitive to climate, and (c) provided a realistic set of options for each decision under different seasonal climate scenarios. Then, we used crop simulation models to assess the outcomes of tailoring crop management to predicted climate conditions. We found differences between the options selected by regional advisors for each climate scenario and those that maximized average profits in the simulation exercise. In particular, differences were most noticeable in preferred nitrogen fertilization rates. While advisors tended to lower fertilization in response to a forecast of dry spring conditions, associated with La Niña events, the simulation exercise showed a consistent drop in maize yields and profits with low N rates even in La Niña years. Advisors and producers' aversion to risk can be determining these differences, since the analysis showed that the probability of negative economic results are minimized under their decision rule. The procedure was effective to meet some of the conditions required to use climate information and to determine the value of incorporating ENSO-related information to effectively improve the maize decision process. However, results suggest that better knowledge of farmers decision rules are necessary when the value of using climatic information is estimated and interpreted. Fil: Bert, Federico Esteban. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Satorre, Emilio Horacio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Cerealicultura; Argentina. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Toranzo, Fernando Ruiz. Asociacion Argentina de Consorcios Regionales de Experimentacion Agricola.; Argentina Fil: Podestá, Guillermo. University of Miami; Estados Unidos |
| description |
In many places, predictions of regional climate variability associated with El Niño Southern Oscillation (ENSO) phenomenon offer the potential to improve farmers' decision-making, i.e., mitigate negative impacts of adverse conditions or take advantage of favorable conditions. However, various conditions must be met for a forecast to result in enhanced decision-making. First, information has to be relevant to, and compatible with production decisions. Second, alternative options must exist for a given decision and these should result in different outcomes under different climate conditions. Third, decision-makers should be able to evaluate the outcomes of alternative actions. In this paper, we explored these conditions as part of a case study targeting maize production systems in the Argentine Pampas. The decision-making process was described via "decision maps" that (a) characterized the main decisions involved in maize production systems and their timing, (b) identified decisions sensitive to climate, and (c) provided a realistic set of options for each decision under different seasonal climate scenarios. Then, we used crop simulation models to assess the outcomes of tailoring crop management to predicted climate conditions. We found differences between the options selected by regional advisors for each climate scenario and those that maximized average profits in the simulation exercise. In particular, differences were most noticeable in preferred nitrogen fertilization rates. While advisors tended to lower fertilization in response to a forecast of dry spring conditions, associated with La Niña events, the simulation exercise showed a consistent drop in maize yields and profits with low N rates even in La Niña years. Advisors and producers' aversion to risk can be determining these differences, since the analysis showed that the probability of negative economic results are minimized under their decision rule. The procedure was effective to meet some of the conditions required to use climate information and to determine the value of incorporating ENSO-related information to effectively improve the maize decision process. However, results suggest that better knowledge of farmers decision rules are necessary when the value of using climatic information is estimated and interpreted. |
| publishDate |
2006 |
| dc.date.none.fl_str_mv |
2006-06 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
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http://hdl.handle.net/11336/132087 Bert, Federico Esteban; Satorre, Emilio Horacio; Toranzo, Fernando Ruiz; Podestá, Guillermo; Climatic information and decision-making in maize crop production systems of the Argentinean Pampas; Elsevier; Agricultural Systems; 88; 2-3; 6-2006; 180-204 0308-521X CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/132087 |
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Bert, Federico Esteban; Satorre, Emilio Horacio; Toranzo, Fernando Ruiz; Podestá, Guillermo; Climatic information and decision-making in maize crop production systems of the Argentinean Pampas; Elsevier; Agricultural Systems; 88; 2-3; 6-2006; 180-204 0308-521X CONICET Digital CONICET |
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eng |
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