气候变化背景下中国玉米单产增速减缓的原因分析

采用集合经验模态分解方法,分析1981—2008年中国玉米单产的变化趋势,发现全国和15个省(自治区、直辖市)均出现了玉米单产增速变缓的现象.该研究选取10个出现玉米单产增速变缓的主产省(自治区、直辖市),基于Cobb-Douglas生产函数,构建了肥料、灌溉、其他物质投入和气候要素4类驱动因子与玉米单产之间的多元回归模型,分析各驱动因子对玉米单产的影响和贡献.结果表明:1)肥料、灌溉、其他物质投入和气候要素4类驱动因子与1981—2008年玉米单产均存在着显著的相关关系,其中肥料、其他物质投入和灌溉显著地促进了玉米单产的增长,当这些因子每增加1%时,将分别促进玉米单产增长0.39%、0.06...

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Bibliographic Details
Published in农业工程学报 Vol. 33; no. z1; pp. 231 - 238
Main Author 杨笛 熊伟 许吟隆 冯灵芝 张梦婷 刘欢
Format Journal Article
LanguageChinese
Published 中国农业科学院农业环境与可持续发展研究所,北京,100081%陕西省榆林市气象局,榆林,719099 2017
Subjects
气候变化;肥料;灌溉;玉米单产;Cobb-Douglas生产函数;驱动因子
Cobb-Douglas生产函数
Cobb-Douglas production function
驱动因子
maize yield
灌溉
irrigation
fertilizers
driving factors
气候变化
肥料
玉米单产
climate change
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2017.z1.035

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Summary:采用集合经验模态分解方法,分析1981—2008年中国玉米单产的变化趋势,发现全国和15个省(自治区、直辖市)均出现了玉米单产增速变缓的现象.该研究选取10个出现玉米单产增速变缓的主产省(自治区、直辖市),基于Cobb-Douglas生产函数,构建了肥料、灌溉、其他物质投入和气候要素4类驱动因子与玉米单产之间的多元回归模型,分析各驱动因子对玉米单产的影响和贡献.结果表明:1)肥料、灌溉、其他物质投入和气候要素4类驱动因子与1981—2008年玉米单产均存在着显著的相关关系,其中肥料、其他物质投入和灌溉显著地促进了玉米单产的增长,当这些因子每增加1%时,将分别促进玉米单产增长0.39%、0.06%和0.04%.气候要素中,降水对玉米单产也表现为促进作用,当降水每增加1%,玉米产量会增长0.21%;而气温和太阳辐射(云覆盖率)则对玉米单产产生负面影响,当温度每增加1%和太阳辐射每减少1%,将导致玉米单产下降0.99%和1.04%.2)1981—2008年,肥料对玉米单产增加的贡献最大(使玉米增产70.24%),其次是灌溉(9.44%),其他物质投入的贡献为5.43%.气候变化要素中,温度升高导致玉米产量降低了1.98%,而降水和辐射的减少则使玉米产量分别降低了1.08%和4.72%.3)肥料对2个玉米主产区(北方春玉米区和黄淮海夏玉米区)的产量增加均呈现显著的促进作用,灌溉对北方春玉米单产有显著的正面影响,其他物质投入对黄淮海夏玉米单产有显著的正面影响.气候因子中,气温上升能显著的促进北方春玉米单产增长;太阳辐射的减少对2个主产区玉米单产均有显著的负面影响.
Bibliography:11-2047/S
climate change;fertilizers;irrigation;maize yield;Cobb-Douglas production function;driving factors
Yang Di[1];Xiong Wei[1];Xu Yinlong[1];Feng Lingzhi[2];Zhang Mengting[1];Liu Huan[1]
China's maize yield has demonstrated a slowing growth since the end of last century, which has received great concerns for policy makers and agricultural scientists. Reasons for such phenomena are usually ascribed to decreasing fertilizer efficiency, land degradation, decreasing technology inputs such as new crop varieties, and climate change. However, none of the reasons has been clearly investigated and quantified to date, particularly at a very regional scale. Here a gridded and time series database of maize yield, areas, irrigation, fertilizer application, we apply an ensemble empirical mode decomposition (EEMD) analysis and examine the contribution of each factors on past yield growth and their changes along time. We discover that the slowing yield growth has been experienced at the whole China and 15 provinces (
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.z1.035