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2055 年南非玉米和小麦生产预计的气候影响:经验和机理建模方法的比较。

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches.

机构信息

Program in Science, Technology, and Environmental Policy, Woodrow Wilson School, Princeton University, Princeton, NJ, 08544, USA; Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, 08544, USA.

出版信息

Glob Chang Biol. 2013 Dec;19(12):3762-74. doi: 10.1111/gcb.12325. Epub 2013 Oct 21.

Abstract

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were -3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties.

摘要

作物模型特有的偏差是影响我们理解气候变化对农业影响的一个关键不确定性因素。越来越多的研究关注模型间的差异,但尽管这两种模型在该领域都被广泛应用,机制模型(MMs)和经验模型(EMs)之间的比较却很少。我们结合 MMs 和 EMs 来预测南非未来(2055 年)玉米和春小麦潜在分布(适宜性)和生产力的变化,这些预测是基于 18 个下推气候情景(2 种排放情景下运行的 9 个模型)得出的。与 MMs 相比,EMs 预测的产量损失更大或收益更小。EMs 预测的玉米和小麦产量变化中值分别为-3.6%和 6.2%,而 MMs 则分别为 6.5%和 15.2%。EM 预测玉米潜在种植面积减少 10%,而 MM 则预测增加 9%。两个模型都显示春小麦潜在生产区增加(EM = 48%,MM = 20%),但结果存在更多不确定性,因为两个模型(特别是 EM)都大大高估了当前的适宜性程度。MMs 在高 CO2 下模拟的大量用水效率提高,在很大程度上解释了 EM-MM 之间的差异,但 EMs 可能更准确地代表了作物对温度的敏感性。我们的研究结果与早期研究一致,表明 EMs 可能比 MMs 显示出更大的气候变化损失。作物预测工作应该扩大到包括 EM-MM 比较,以更全面地了解作物-气候响应的不确定性。

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