Prediction of seasonal climate-induced variations in global food production
Prediction of seasonal climate-induced variations in global food production
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DOI：
10.1038/nclimate1945
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发表时间：
2013-10-01
影响因子：
30.7
通讯作者：
Yamagata, Toshio
中科院分区：
文献类型：
--
作者：
Iizumi, Toshichika;Sakuma, Hirofumi;Yamagata, Toshio
消费者，包括许多国家的穷人，越来越依赖粮食进口(1)，因此面临世界主要粮食生产地区产量、产量和出口价格变化的影响。因此，各国政府和商业实体越来越关注重要粮食出口国的播种预测以及本国的粮食生产。鉴于粮食市场波动加剧以及影响粮食生产的极端气候发生率上升，未来几年粮食价格飙升的可能性可能会加大(2-4)。在这里，我们通过将集合季节性气候预测与统计作物模型联系起来，对两个提前期内主要作物歉收后报的可靠性进行了全球评估。我们发现，如果气候预测近乎完美，那么这些作物收获面积的相当大比例（26-33%）的中度至显着产量损失是可以可靠预测的。然而，只有水稻和小麦的产量可以利用季节内后报可靠地预测收获前三个月的产量。不同作物的估计可靠性差异很大——水稻和小麦产量是最可预测的，其次是大豆和玉米。估计可靠性变化的原因包括作物对气候的敏感性的差异以及作物生产地区使用的技术。我们的研究结果表明，利用季节性气候预报来预测农作物歉收将有助于监测全球粮食生产，并将鼓励粮食系统适应极端气候。
Consumers, including the poor in many countries, are increasingly dependent on food imports(1) and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years(2-4). Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33%) of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop-rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems to climatic extremes.