气候变化下大豆生产的响应与适应研究进展

Research progress on response and adaptation of soybean production to climate change

  • 摘要: 以气候变暖为主要特征的气候变化对全球范围内的大豆生产造成了重要影响。本文基于国内外相关文献, 归纳了目前应用于评估气候变化对大豆生产影响研究的主要方法, 综述了大豆物候与产量对气候变化的响应与适应, 得出以下主要结论: 1)气候变化影响大豆生产的研究方法主要包括田间试验观测、统计分析方法与作物模型模拟。其中, 田间试验观测方法最为准确, 但鉴于试验设计的局限性, 难于有效揭示不同气候变化或不同气候因子综合作用对大豆生产的影响; 一定程度上, 统计方法能够保障结果的可靠性与客观性, 但该方法对用于统计分析的观测数据的数量和质量有较高要求; 作物机理模型模拟方法虽然机理性强, 外推效果好, 但应用前需要对模型进行参数校正和评价。2)由于气候变化的区域差异性, 全球范围内大豆物候和产量对气候变化的响应程度具有显著的空间异质性。总体而言, 温度每升高1 ℃, 大豆全生育期缩短5.9 d, 产量下降6.85%; 降水量每降低10 mm, 大豆产量下降2.13%; 然而, CO2浓度每升高10 μmol∙mol−1 产量增加0.52%。3)为有效应对气候变化, 品种更新、播期调整、以及田间管理措施改善等均可提高大豆产量潜力, 减缓气候变化的负面影响。

     

    Abstract: Climate change, characterized by climate warming, has had a significant impact on soybean production worldwide. Based on a comprehensive review of relevant domestic and international literature, this study systematically summarizes current research methods on climate change and soybean production, illustrates the response of soybean phenology and yield to climate change, and proposes adaptive management suggestions. The main conclusions are as follows: 1) Research methods for the impact of climate change on soybean production mainly include field experiment observations, statistical analysis, and crop model simulation. The observation method of the field experiment is the most intuitive, and the statistical analysis method can guarantee the reliability and objectivity of the results. The model simulation method has strong mechanical rationality and a good extrapolation effect. Currently, artificial intelligence (AI) technologies such as machine learning, deep learning, and reinforcement learning can be utilized to enhance the accuracy of model simulations. Future research should integrate multiple methodologies to reduce the error of a single method and increase the accuracy of research on the response and adaptation of soybean production to climate change. 2) The impact of climate change on soybean production mainly stems from fluctuations in key climatic factors such as temperature, precipitation, radiation, and CO2 concentration. These factors directly affect the entire growth process of soybeans, not only causing changes in the phenological period and yield but also influencing quality. At present, research on the impact of climate change on soybean production has mainly focused on two aspects: changes in the growth period and fluctuations in yield. Due to regional differences in climate change, the degree of response of soybean phenology and yield to climate change worldwide shows significant spatial heterogeneity. Overall, for every 1 ℃ increase in temperature, the entire growth period of soybeans will be shortened by 5.9 days and the yield will decrease by 6.85%. Both precipitation and sunshine duration can shift the phenological period of soybeans. Meanwhile, for every 10 mm decrease in precipitation, the soybean yield decreased by 2.13%. However, owing to global warming, the concentration of CO2 continues to increase. The fertilization effect of CO2 can offset the negative impacts of climate change on soybean yield to some extent. Specifically, for every 10 μmol∙mol−1 increase in CO2 concentration, the yield will increase by 0.52%. 3) In terms of adjustment management measures, practices such as variety replacement, sowing date adjustment, and technology upgrades should be implemented to improve soybean yield potential and compensate for the negative impacts of climate change. In addition, policy subsidies, agricultural insurance, the application of the Internet of Things, and artificial intelligence technologies are important measures to compensate for the damage to soybean production caused by climate change

     

/

返回文章
返回