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Scale invariant behavior of cropping area losses

机译:裁剪面积损失的规模不变行为

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摘要

This paper shows how crop losses, display Self-Organized Critical Behavior, which implies that under a wide range of circumstances, these losses exhibit a power-law dependence on frequency in the affected area whose order of magnitude approximates those reported for extreme climate events. Self-Organized Critical Behavior has been observed in many extreme climate events, as well as in the density and distribution of pests linked to crop production. Empirical proof is provided by showing that the frequency-size distribution of the cropland loss fits the Pareto and the Weibull models with scaling exponents that are statistically similar to the expected value. In addition, the test included comparisons of the expected value and the predicted value of the scaling exponents among different subsystems and among systems of the same universality class. Results show that the Pareto model fits the heavy-tailed distribution of losses mostly caused by extreme climate events, while the Weibull model fits the whole distribution, including small events. The analyses show that crop losses adopt Self Organized Critical Behavior regardless of the growing season and the water provision method (irrigated or rainfed). Irrigated systems show more stable behavior than rainfed systems, which display higher variability. The estimation is robust not only for calculating model parameters but also for testing the proximity to a power law-like relationship.
机译:本文展示了作物损失,显示自组织的关键行为,这意味着在广泛的情况下,这些损失在受影响的地区的频率上表现出幂律依赖性,其数量级近似于据报道的极端气候事件。在许多极端气候事件中观察到自组织的关键行为,以及与作物生产相关的害虫的密度和分布。通过表明农业损失的频率分布适合帕累托和威布尔模型,通过统计上类似于预期值的缩放指数来提供经验证据。此外,测试包括不同子系统中的预期值和缩放指数的预测值的比较,以及相同普遍性类的系统之间的缩放指数。结果表明,帕累托模型适合大多由极端气候事件造成的重型损失分布,而威布尔模型适合整个分布,包括小事。分析表明,无论不断增长的季节和水供应方法(灌溉或雨水),作物损失都采用自组织的关键行为。灌溉系统显示比雨量系统更稳定的行为,显示出更高的可变性。估计不仅适用于计算模型参数,而且用于测试靠近电力法律关系的鲁棒。

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