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中国气候变化下水稻和玉米生产的实证分析。

Empirical analysis of rice and maize production under climate change in China.

机构信息

Gongqing Institute of Science and Technology, Jiujiang, China.

Nanchang University, Nanchang, China.

出版信息

Environ Sci Pollut Res Int. 2022 Oct;29(46):70242-70261. doi: 10.1007/s11356-022-20722-z. Epub 2022 May 19.

DOI:10.1007/s11356-022-20722-z
PMID:35585461
Abstract

The past few decades of extreme drought and flooding caused by changing climate conditions have significantly affected agricultural production globally. This study focuses on two vital crops in China-maize and rice-and provides a comprehensive analysis of how these crops are affected by climate change-induced factors over the periods 1978Q1-2015Q4. Four key findings were obtained. First, using a nonparametric approach to estimate actual and observed trends of climatic variables, the results show a significant positive trend in average temperature from February to October. On the other hand, seasonal temperature increases during spring, summer, and autumn. Second, the results show no significant change in the monthly, seasonal, and annual rainfall patterns when examined over the study period. Third, using an autoregressive distributed lag (ARDL) model, we find that while temperature and rainfall do not significantly support rice production in the long and short run, they play a substantial role in maize production in China. Finally, we find no significant difference in the results for rice when the quantile regression (QR) technique that controls for distributional asymmetry effects is employed. However, the impact of temperature on maize decreases at higher quantiles. Given the outcomes of our study, we argue that an advanced irrigation system is crucial and must be encouraged to minimize the effects of climate change on crop production.

摘要

过去几十年由气候变化引起的极端干旱和洪涝灾害对全球农业生产产生了重大影响。本研究聚焦于中国的两种重要作物——玉米和水稻,并全面分析了这些作物在 1978Q1-2015Q4 期间如何受到气候变化因素的影响。研究得出了四个关键发现。首先,使用非参数方法来估计气候变量的实际和观测趋势,结果表明从 2 月到 10 月平均温度呈显著正趋势。另一方面,春、夏、秋三季的季节温度都在升高。其次,在研究期间,考察月度、季节性和年度降雨模式时,没有发现显著变化。第三,使用自回归分布滞后(ARDL)模型,我们发现,虽然温度和降雨在长期和短期都没有显著支持水稻生产,但它们在中国玉米生产中起着重要作用。最后,当使用控制分布不对称效应的分位数回归(QR)技术时,我们发现水稻的结果没有显著差异。然而,温度对玉米的影响在较高分位数时会降低。鉴于我们研究的结果,我们认为先进的灌溉系统至关重要,必须加以鼓励,以将气候变化对作物生产的影响降到最低。

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