Decision Support System for Risk Reduction in Agriculture: DSS for Eastern Paraguay and Rio Grande do Sul - Florida Climate Institute

Contact Person: Fraisse, Clyde

Collaborators: J.Baez, N. Breuer, J. M. Fernandes, C. A. Forcelini, C. Fraisse, W. Pavan

Institutions: Universidad Catolica Nuestra Senora de la Asuncion (Paraguay); University of Florida; University of Miami; Universidade de Passo Fundo (Brazil)

Funding Agency: Inter-American Institute for Global Change Research (IAI)

Start: April 2008    End: March 2011

Status: Funded

Filed Under: AgricultureExtension

Abstract: Climate variability caused by El Niño brings additional risk for soybean farmers in Southern Brazil and Eastern Paraguay. The main focus of this research project is to learn the needs of agricultural producers as related to climate information and forecast, to investigate the potential impacts of climate variability on crop production, more specifically soybean production, and to implement capacity building activities to introduce the application of crop model outcomes into stakeholders' decision making process. This project is developing a seasonal climate forecast system for use by producers and policy makers aimed at reducing the risks that farmers face with each season's planting. Researchers conducted surveys in several Brazilian and Paraguayan farmer cooperatives on members' knowledge of and attitudes to inter-seasonal climate variability and their expectations regarding climate forecasts. The results show that farmers' knowledge about the effects of El Niño is variable, which affects their willingness to apply climate forecasts for adapting their management practices. The research team found that soybean producers are very interested in understanding the effects of climate variability on crop yields. They were equally enthusiastic about the possibility of co-developing a decision support system available on the Internet to help them make better decisions about farm management; for example, if they knew with a high degree of certainty that La Niña year was coming, adjustments in planting dates, fertilization rates, and land preparation, might reduce some of the risks they face. The ability to adapt farm management upon seasonal climate forecasting depends on several factors, such as the flexibility and willingness of the farmers, the timing and accuracy of the forecast, and the effectiveness of the communication process. Climate information only has value when there is a potential response and a clearly defined benefit, once the information is applied.