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The availability of long-lead ENSO-related climate forecasts has led many to speculate that such forecasts may benefit decision making in agriculture. To explore the conditions required for the effective use of climate forecasts, we conducted a pilot study focused on central-eastern Argentina. Historical records showed higher (lower) average precipitation during warm (cold) ENSO events in November–December. However, variability of the precipitation signal within ENSO phases was high. National-level yields of maize, soybeans and sorghum tended to be higher (lower) during warm (cold) events. A field survey was conducted to identify impediments for forecast adoption and learn how to communicate climate information. Most farmers surveyed know about ENSO, with the 1997–1998 event marking a “turning point” in their awareness of the phenomenon. Finally, various modeling approaches were used to explore outcomes of alternative management options (changes in crop management and land allocation) tailored to climate scenarios associated with each ENSO phase. Simulation exercises identified differences in optimal management between ENSO phases.

Using an on-farm approach, we investigated constraints to actual yield of sunflower in six agroecological zones within the Argentine Pampas during three growing seasons. In 249 large, grower-managed paddocks, we quantified a series of variables related to: (1) crop phenology, growth, and yield; (2) the physical and biological environment; and (3) management practices. Variation in yield among zones and seasons was analysed on the basis of four biologically-founded assumptions: (1) grain number accounts for a large proportion of the variation in yield; (2) grain number is associated with a photothermal coefficient, Q=R (T-Tb)−1, where R and T are average solar radiation and air temperature respectively, during the 50-day period bracketing anthesis; and Tb is a base temperature; (3) crop growth and yield are proportional to light interception, and therefore proportional to canopy ground cover; and (4) yield is proportional to the fraction of seasonal rainfall that occurs after anthesis. Average yield ranged from 1.1 to 2.7 t ha−1, grain number from 2400 to 5400 m−2, individual grain mass between 40 and 69 mg and grain oil concentration between 42 and 52%. Grain number accounted for 43% of the variation in average yield while Q accounted for 23% of the variation in grain number. Low yield was associated with deficient ground cover in 25% of the crops; part of the remaining variation in yield was accounted for by sets of measured variables particular to each zone, including soil shallowness, low available P, low initial water content, weeds and diseases — chiefly Verticillium wilt (Verticillium dahliae) and Sclerotinia head rot (Sclerotinia sclerotiorum). Across zones and seasons, the proportion of seasonal rainfall occurring after anthesis accounted for 28% of the variation in crop yield. A trade-off is highlighted whereby beneficial effects of rainfall that favours growth and yield may be offset by the detrimental effect of abundant moisture that favours major fungal diseases. We emphasised the value of combining experimental studies — which provide biological background in the form of working hypotheses — with on-farm research that realistically quantifies yield response to key factors.

The El Nino-Southern Oscillation (ENSO) contributes to the vulnerability of crop production to climate variability in the Pampas region of Argentina. Predictability of regional climate anomalies associated with ENSO may provide opportunities to tailor decisions to expected climate, either to mitigate expected adverse conditions or to take advantage of favorable conditions. Model analysis was used to explore the potential for tailoring land allocation among crops to ENSO phases at the farm scale in two sub-regions of the Pampas. The model identifies as a function of risk preferences and initial wealth the crop mix that maximizes expected utility of wealth at the end of a 1-year decision period based on current costs and prices, and crop yields simulated for each year of historical weather. The model reproduced recent land allocation patterns at the district scale under moderate risk aversion, and predicted increasing diversification with increasing risk aversion. Differences in land allocation among ENSO phases were consistent with known climate response to ENSO, and crop response to water availability. Tailoring land allocation to ENSO phase increased mean net farm income between US$5 and $15 ha −1 year −1 relative to optimizing the crop mixture for all years, depending on location, risk aversion and initial wealth. The relationship between potential value of ENSO information and risk aversion was not monotonic, and differed between locations. Crop mix and information value also varied with crop prices and initial soil moisture. There are potential financial benefits of applying this approach to tailoring decisions to ENSO phases.