Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands.
FutureWater, Cartagena, Spain.
Sci Rep. 2019 Feb 4;9(1):1277. doi: 10.1038/s41598-018-38091-4.
Studies show that climate variability drives interannual changes in meteorological variables in Europe, which directly or indirectly impacts crop production. However, there is no climate-based decision model that uses indices of atmospheric oscillation to predict agricultural production risks in Europe on multiple time-scales during the growing season. We used Fast-and-Frugal trees to predict sugar beet production, applying five large-scale indices of atmospheric oscillation: El Niño Southern Oscillation, North Atlantic Oscillation, Scandinavian Pattern, East Atlantic Pattern, and East Atlantic/West Russian pattern. We found that Fast-and-Frugal trees predicted high/low sugar beet production events in 77% of the investigated regions, corresponding to 81% of total European sugar beet production. For nearly half of these regions, high/low production could be predicted six or five months before the start of the sugar beet harvesting season, which represents approximately 44% of the mean annual sugar beet produced in all investigated areas. Providing early warning of crop production shortages/excess allows decision makers to prepare in advance. Therefore, the use of the indices of climate variability to forecast crop production is a promising tool to strengthen European agricultural climate resilience.
研究表明,气候变率驱动欧洲气象变量的年际变化,这直接或间接影响作物生产。然而,目前还没有基于气候的决策模型,该模型使用大气振荡指数来预测欧洲生长季节多个时间尺度上的农业生产风险。我们使用快速决策树来预测甜菜的产量,应用了五个大气振荡的大规模指数:厄尔尼诺南方涛动、北大西洋涛动、斯堪的纳维亚型、大西洋东部型和大西洋东部/俄罗斯西部型。我们发现,快速决策树在 77%的调查地区预测了甜菜的高/低产量事件,占欧洲甜菜总产量的 81%。对于这些地区的近一半,高/低产量可以在甜菜收获季节开始前的 6 或 5 个月预测,这大约占所有调查地区平均年甜菜产量的 44%。提前预警作物生产短缺/过剩可以使决策者提前做好准备。因此,利用气候变率指数来预测作物产量是增强欧洲农业气候弹性的一种有前途的工具。