Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Abstract

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

An Economy-Climate Model for Quantitatively Projecting the Impact of Future Climate Change and Its Application

“…A total of 72.2% of the country's mean annual grain production comes from 13 main grain-producing areas in China (Figure 4), and their mean annual grain production concentration from 1981 to 2015 totaled 73.8% [29]. According to previous studies, the main grain-producing areas can be divided into the North and South regions [26]. The North region includes Heilongjiang…”

“…The C-D-C model is based on the C-D production function model and adds climatic factors to construct an econometric model to evaluate the impact of climate change on the economic system [23]. In addition, with this study, we introduce into the model the comprehensive climate factor (CCF), a new factor constructed in previous studies, and analyze the economic impact of changes in the comprehensive climate factor on the yields of different crops in China's main grain-producing areas over the past 35 years (1981-2015) [5]; [26]. The C-D-C model represents the functional relationship between the number of input factors and the economic output in the production process over a long period of time (more than 10 years), and its formula is shown in Eq.…”

“…However, due to the randomness and uncertainty of the economic development laws of the country and society, it is difficult to obtain future economic data. Therefore, the C-D-C model has been widely used to assess the impact of historical climate change on food production [26][27][28]. To solve the difficulty of predicting the impact of future climate change, it is necessary to further explore a new method based on the C-D-C model.…”

“…Essentially, it does not focus on the natural science of climate change itself but uses climate change as an economic factor to analyze its contribution to economic development. Its effectiveness has been tested mostly on wheat, maize, and rice in China's grain-producing areas [25,26]. The climate change impact assessment part of the model focuses on analyzing the impact of climate change on economic output based on the output elasticity of climatic factors.…”

“…The climate change impact assessment part of the model focuses on analyzing the impact of climate change on economic output based on the output elasticity of climatic factors. In recent years, studies have used the C-D-C model to analyze the effects of temperature and precipitation changes on the rice yield in different regions [27,28], initially developed the concept and method of "the yield impact of climate change" [24], and assessed the regional sensitivity of crop yields to changes in comprehensive climate factors [26]. The persistent improvement in the simulation capabilities of climatic models and the continuous emergence of future prediction data of CMIP6 have enabled the use of the C-D-C model, and prediction data have made it possible to quantitatively predict the impact of future climate change.…”