ABSTRACT:The El Niño Southern Oscillation (ENSO) is one of the main factors influencing global climate variability and consequently has a major effect on crop yield variability. However, most studies have been based on statistical approaches, which make it difficult to discover the underlying impact mechanisms. Here, using process-based crop model Model to Capture the Crop-Weather relationship over a Large Area (MCWLA)-Maize, we found a consistent spatial pattern of maize yield variability in association with ENSO between MCWLA-Maize model outputs and observations. During El Niño years, most areas of China, especially in the north, experience a yield increase, whereas some areas in the south have a decrease in yields. During La Niña years, there is an obvious decline in yields, mainly in the north and northeast, and a general increase in the south. In-depth analyses suggest that precipitation P rather than temperature T and solar radiation S during the maize growing season is the main cause of ENSO-induced maize yield variability in northern and northeastern China. Although a 2 ∘ C change of T can affect maize yields more than a 20% change of P, greater changes of P contribute more to maize yield variability during ENSO years. In general, maize yields in drier regions are much more sensitive to P variability than those in wetter areas. All changes in meteorological variables, including T, P, S, and vapour pressure deficit (V PD ) during ENSO years, affect yield variability mainly through their effects on water stress. Our results suggest that more effective agricultural information can be provided to government decision makers and farmers by developing a food security warning system based on the MCWLA-Maize model and ENSO forecast information.
The El Niño-Southern Oscillation (ENSO) is one of the most important contributors to global interannual climate variability, but the relationship between seasonal climate and crop yield variations associated with ENSO in China remains inconclusive. In this study, we investigated the impacts of ENSO on the yield of 3 staple crops (rice, wheat, and corn) at the provincial scale. We found that ENSO has significant impacts on wheat yields throughout China, and on rice and corn yields in major production areas. Specifically, more (less) rainfall during the wheat growing season in El Niño (La Niña) years leads to increases (decreases) in wheat yield, especially in southeastern China. Increases (decreases) in rice yield in northeastern China are due to warming (cooling) in El Niño (La Niña) years. In southern China, the variability of rainfall plays a more important role in rice yield than that in northern China. Corn yields in northern China are significantly affected by ENSO-induced changes in maximum temperature, solar radiation, and rainfall. Moreover, all of the staple crop yields are highly correlated with the ENSO index with a lead of at least 6 mo. For rice and corn in many provinces, the yields are typically most correlated with the index of the spring season during the ENSO developing years, suggesting that such yields can be predicted 1 yr before the growing season. The large variability in seasonal climate and agricultural production associated with ENSO warrants the application of ENSO information to food market management in China.
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