气候变化下我国粮食产量增速放缓的驱动机制及适应潜力研究

气候变化背景下，近年来全球主要粮食作物单产增长速度明显放缓，已引起世界各国的广泛关注。开展粮食单产增速放缓的物理驱动机制研究，探讨粮食单产增速变化的定量原因，提出气候变化背景下粮食单产增长的有效途径，有利于实现我国中近期粮食生产目标，保障国家粮食安全。研究以我国主要粮食作物为对象，基于作物模型的升尺度模拟技术，通过不同驱动因子的分离、抽样与情景模拟相结合等多种手段和方法，着重于：（1）主要粮食作物单产变化趋势的模型拟合；（2）主要粮食作物单产变化的驱动因子分离及贡献分析；（3）主要粮食作物单产增速放缓的物理机制分析；（4）气候变化背景下，农业技术和重点适应措施的增产潜力分析。预期通过4年研究，在理论上回答1980－2012年我国主要粮食作物单产增速放缓的驱动机制和定量原因；在方法上建立基于作物模型模拟的不同驱动因子分离技术；在应用上提出气候变化背景下保障粮食单产持续增加的有效技术和途径。

Worldwide evidence indicates an obvious reduction in the rate of yield growth for many key food crops since the end of the last century, which has received global concerns as it may decrease the ability of agriculture to support growing population. Understanding the causes for the yield stagnation is therefore important for devising relevant responding actions to secure the food supply in the future, particularly in China due to its fast loss of arable land and increasing food demand. However, very limited studies to date have tried to tackle this issue at both national and regional scales. This study attempts to investigate the reasons of observed yield slowing of the main food crops (rice, wheat, and maize) in China. We will explore the physical mechanisms for the observed slowing of yield growth through process-based models, based on a combination of a number of simulation methods such as up-scaling application of site-specific crop models, isolating simulation of affecting factors, re-sampling and scenarios-based mass simulation. The objectives of the study are: (1) to reproduce the actual changing trends of reported yields for China's main food crops, by using a couple of process-based crop models and a newly developed dynamic parameterization procedure; (2) to untangle and measure the contributions of five important affecting factors that have contributed to past yield growth (increase of fertilizer use, change of cultivation land, irrigation expansion and intensification, technology development, and climate change); (3) to understand the reasons and underlying mechanisms for the prevailing yield stagnation; and (4) to evaluate the possibilities of using climate change adaptation strategies to reverse the slowing of observed yield growth, gauge the maximum yield potential of specific adaptation options under a series of climate change scenarios. This 4-yr study are theoretically targeting on filling the gaps of our understanding, in perspective of what reasons and causes are behind the observed slowing yield growth for the major food crops. Additional endeavors are being emphasized on the development of a fussy simulation method by which the roles of different drivers for past crop yield growth could be easily isolated and explored. Furthermore, we will apply the method to quantitatively identify the potential of ongoing and proposed adaptation options in promoting the national crop yields, facilitating the implementation of climate-smart agriculture in the near future.