USE OF CLIMATE INFORMATION IN AGRICULTURE DECISION-MAKING: EXPERIENCE FROM FARMERS IN CENTRAL ARGENTINA - PowerPoint PPT Presentation

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USE OF CLIMATE INFORMATION IN AGRICULTURE DECISION-MAKING: EXPERIENCE FROM FARMERS IN CENTRAL ARGENTINA. Marta G. VINOCUR*, Andrea V. RIVAROLA and Roberto A. SEILER U NIVERSITY OF RÍO CUARTO- Argentina Paper prepared for the Second International Conference on Climate Impacts Assessment

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USE OF CLIMATE INFORMATION IN AGRICULTURE DECISION-MAKING: EXPERIENCE FROM FARMERS IN CENTRAL ARGENTINA

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USE OF CLIMATE INFORMATION IN AGRICULTURE DECISION-MAKING: EXPERIENCE FROM FARMERS IN CENTRAL ARGENTINA

Marta G. VINOCUR*, Andrea V. RIVAROLA and Roberto A. SEILER

UNIVERSITY OF RÍO CUARTO-Argentina

Paper prepared for the Second International Conference on Climate Impacts Assessment

June 28-July 2, 2004

*mvinocur@ayv.unrc.edu.ar

Project AIACC LA-29; Research funded by UNEP-GEF-TWAS


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Córdoba Province

Argentina

Study area


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OBJECTIVES

  • To understand farmers’ perceptions, needs and uses of climate information to improve crop production and resource management

  • To know how farmers incorporate climate information in their decision-making process, according to the political context and to the underlying levels of farmers’ vulnerability


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Materials and Methods

  • Four places belonging to different agro-ecological zones were selected for this study: Oncativo (North), Laboulaye (South), Río Cuarto (West) and Marcos Juarez (East).

  • In each place, a random sample of farmers representing the differences in farms/households types was chosen for:

    • Open ended individual interviews

    • a formal semi-structured field survey with open and close questions

  • Focus groups meetings with farmers and qualified groups of stakeholders (grain dealers, cooperative managers, local providers, regional farmers consortium managers, municipio authorities, etc.), with different decision levels were done to present the project and to communicate project’s findings in each place.

  • Representatives from different sectors of the four cities participated in a panel discussion.


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Materials and MethodsSurvey

  • Socio-economic characteristics of each household/farm (farm size, farm type, tenure, applied technology, access to resources, off-farm income, education, etc.)

  • Importance and sources of climate information; users’ knowledge of regional climate; users’ attitudes to climate forecast; users’ perception of the value of climate forecast (credibility, ability to respond, etc.); users’ preferences about timing, format and content of a climate forecast, etc.

  • Surveys’ compilation and data analysis were done using an statistical package (SPSS).


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Do you usually use climate information?


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Use of climate forecast and farm size


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Use of climate forecast and farmers’age


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Why do you not use climate information?

  • Not Credible or low credibility

  • Bad distribution channels/not access to the communication channels

  • Lack of interest

  • Difficult to understand/not clear enough

  • Very general

  • Lack of custom


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Characteristics of an useful climate forecast

  • Timing

    • One month before planting: 40%

    • Between 2-3 months before planting:34%

    • > 3 months: 15%

  • Format:

    • Graphs alone and with associated explanations: 52%

    • Tables alone and with associated explanations: 19%

    • Only Explanations (descriptive),maps: 29%

  • Other Content:

    • percentages

    • comparison with past years

    • above normal, near normal or below normal with the associated probabilities

    • Actual data, means and deviation from the mean


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Climate Information Required for Making Decisions at the Farm Level


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Which decisions would you be most likely to change to reduce climate risks?


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Socio-cultural aspects(conceptions, social constructions, perceptions, beliefs,etc.) (From Maurutto et al, 2003)

  • Learning matrix: the way in which each subject organizes and gives meaning to the universe of his/her experience and knowledge

  • “Naturalized” perception of climate.

  • Climate is a part of their daily life, their “quotidian life” related to their living reality and to their historical past.

  • The Quotidian life is built from a common cultural background stored by society which includes beliefs, basic values, historical and cultural references that conform a collective memory and its own identity (Ibanez, 1988).

  • Decision making is not a succession of rational stages but a process influence by principles that can generate and organize practices and representations (derived from the concept of habitus (Bourdieu,1991)


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Farmer’s own words

  • “ But look, as a farmer working in an ‘open sky enterprise’ you may be sure that climate is very important, basic, I would say that most farmers wake up in the morning and look at the horizon and go to sleep at night and look at the horizon, to see whether there is a storm, or the wind is going to blow from the south, whether it is cold, whether it is going to freeze or not, because everything depends on the weather from the day of sowing to the day of harvesting” -farmer, 47 years old, Rio Cuarto

  • “when one watches the ants coming and going, taking their little eggs up and down, a weather change is sure to happen”

  • “That comes from my father, from the countryside… we all around here look upwards and calculate, experience guides us. Years of practice!”, farmer, 73 years old, unfinished primary school, Laboulaye.

  • “During a drought, one nearby neighbour took all the saints and left them upside down, under the sun, to ask for rain. We also celebrate masses in the town to ask for rain, for example, every Wednesday the mass is to ask for rain”, farmer, 56 years old, primary school, Rio Cuarto


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CONCLUSIONS

Users of climate information required:

  • Forecast tailored to their needs

  • Improve accuracy, timing and format

  • Downscaled temporally and spatially to users’ specific locations

    To promote climate forecast use, it is necessary:

  • to improve users’ knowledge about regional weather and climate

  • to educate users about the differences between short term, long term/seasonal forecasts.

  • to analyze institutional ways of dissemination of climate information

  • to improve communication between researchers and end users


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