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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/132087

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network_name_str CONICET Digital (CONICET)
spelling 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
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 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
identifier_str_mv 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
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0308521X05000570
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.agsy.2005.03.007
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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