Politicians make the policy. But it’s often left to business to implement it. For this reason RioPlus Business is featuring submissions from the private sector across the globe in the lead up to Rio+20.
Today we look at how a public-private partnership between IAI and Paraguayan farmers aims to raise crop yields and improve community resilience to climatic events.
By Clyde W. Fraisse & Norman Breuer
2011-12 was a difficult season for Paraguayan farmers.
A La Niña event with its colder than normal sea surface temperature along the equator in the central and eastern Pacific Ocean, brought drier weather to most of the country. Initial estimates of the resulting crop losses by the Ministry of Agriculture and Livestock indicate that about half the soybean crop has been lost, reducing this year production to about 4.6 million metric tons from last year’s 8.4 million metric tons.
It is well known that climate variability caused by the El Niño Southern Oscillation (ENSO) risk to farmers of southeastern South America. However its mechanisms and effects were not well understood and not communicated with enough lead time to allow policy makers and farmers to implement adaptation strategies to reduce production risks.
Now this is changing thanks to a project funded by the Inter-American Institute for Global Change Research (IAI) IAI that is developing a climate information and decision support system aimed at reducing the climate risks farmers face with each season’s planting.
Scientists in this project surveyed several Paraguayan farmer cooperatives on members’ knowledge of, and attitudes to seasonal climate variability, and on their expectations from climate forecasts. The results show that farmers have widely differing knowledge about the effects of ENSO.
Accordingly, their willingness to apply climate forecasts to adapting their management practices also varies widely. A computer-generated crop growth model was used to evaluate adaptive management options under different ENSO scenarios, for example planting different soybean varieties and varying the planting dates. The team also developed strategies for communicating risks, including a web-based decision support tool.
Automated weather stations
The research team found that farmers are very interested in understanding the effects of climate variability on their 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.
This enthusiasm led the Federation of Cooperatives in Paraguay (Fecoprod) to invest in deploying a network of automated weather stations across the country and co-develop the web-based climate information and decision support system. A total of 33 cooperatives and about 18,000 farmers are members of Fecoprod, proving the broad reach of the project.
To communicate with farmers, the team worked with cooperatives, technical support staff and a network of agronomists. They not only conducted research but organized workshops to train researchers, students and agronomists on the use of crop simulation models.
Many producers already use weather and climate information from several sources including the Internet. The majority of the farmers believed that seasonal climate forecasts would be useful to them. They mentioned several management practices that might be altered in light of reliable seasonal forecasts. These include fertilization rates, variety selection, and type of land preparation, among others.
Seasonal climate variability is a major cause of production risks faced by farmers. In recent years, the science of forecasting seasonal climate has improved significantly. Basic research has improved understanding of major systems that influence climate variability, including the El Niño phenomenon, which is a main driver of climate variability in the southern cone of South America.
This improved ability in predicting anomalies in the seasonal weather, has resulted in a large number of studies that examine the potential of climate forecasting to reduce the risks agricultural businesses are facing.
The utility of seasonal climate forecasting for farm management depends on such factors as the flexibility and willingness of farmers to adapt their farming operations to the forecast, the timing and accuracy of the forecast, and the effectiveness of the communication process. Climate information only has value when there is the possibility of a response and a clearly defined benefit from applying the information.
It is important to recognize that the use of climate information in farming means making economic and agronomic decisions that take a probabilistic forecasts into account. Rather than looking for a clear-cut, yes or no “use“ of climate forecast, we should aim at encouraging farmers to experiment with adaptations incorporating the use of climate information in an incremental nature that mimics their approach for the incorporation of new technologies.
The research in eastern Paraguay demonstrated that the challenge of providing farmers with trusted, useful, science-based information, upon which they can make informed decisions, can be best met by developing and implementing climate-based decision support systems in close cooperation with local cooperatives.
By using a combination of participatory techniques, qualitative methods, and interactive exercises to elicit end-users’ perspectives and feedback we obtained a better understanding of the complexities of farmer’s decision-making processes and the role that climate information plays in them.
This understanding has provided the team with the necessary tools to more effectively communicate risks to agricultural producers in the region and has resulted in a strong partnership of researchers and the farmers’ cooperatives to develop solutions that can effectively reduce crop production risks associated with climate variability.
The IAI is an intergovernmental organization supported by 19 countries in the Americas dedicated to pursuing the principles of scientific excellence, international cooperation, and the full and open exchange of scientific information to increase the understanding of global change phenomena and their socio-economic implications.