Abstract
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.
