The Coconut Research Institute of Sri Lanka (CRI) has sustained an improved prediction scheme for national coconut production for the last four years. Coconuts are an important source of food and raw materials and also provide income to millions in the tropics. Coconuts are the most important food crop after rice in Sri Lanka and are grown in home gardens and in plantations. Yield predictions are provided by October for the next year. A skillful prediction is possible because the coconut has a two-year long development phase enabling the use of monitored rainfall information. The CRI refined this prediction scheme in collaboration with the International Research Institute for Climate and Society (IRI), which is part of the Columbia Climate Center. These predictions are used by plantation managers and national level agricultural managers. A feature story on this project was published on the IRI website.
Although this project was supported by a fund for Climate Change, there was a demand for operational information on shorter decision-making time scales. The Secretary to the Sri Lanka Ministry of Plantation Industries who was the chief guest at the inaugural workshop spelled out the priority for immediate information going up to five years.
Through this project, capacity in climate assessment and impact analysis was developed at several local institutions. Staff of the Foundation for Environment, Climate and Technology worked closely with IRI. Two of the four young researchers working on this project went on to earn M.Sc degrees. The capacity building aspect was documented here or highlighted at SciDev. The final project report is available here. Related work on other aspects of climate adaptation are available as well here.
There is often a gap between the stated promises of societal benefit from modern knowledge in metropolitan centers and the benefits that poor, peripheral communities actually reap. In this context, the operationalization of a prediction system, its maintenance over several years and uptake of information stands out. By itself, a prediction system may not improve agricultural production or food security. However, the maintenance of a climate and agricultural monitoring system, the nurturing of demand for climate based prediction and its routine review by the affected are essential step towards uptake and future adaptation. In the case of coconut predictions, plantation managers have begun to base decisions on drought alleviation and plantation finances and national agricultural and food security officials are factoring in these predictions into decisions on “forward-contracts” for exports and imports and policies on fertilizer subsidies, taxes and levies related to the coconut industry.
