摘要
Crop simulation models provide alternative, less time-consuming, and cost-effective means of deter- mining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat (Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (COa) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCR The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCR There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2℃ was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1℃ decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rain- fed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈ 3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to560ppm, and yield under YY increased linearly by ≈ 7.0% for the same increase in CO2 concentration.
Crop simulation models provide alternative, less time-consuming, and cost-effective means of deter- mining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat (Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (COa) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCR The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCR There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2℃ was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1℃ decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rain- fed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈ 3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to560ppm, and yield under YY increased linearly by ≈ 7.0% for the same increase in CO2 concentration.
基金
This study was supported by the National Natural Science Foundation of China (Grant No. 41401104), Natural Science Foundation of Hebei Province, China (D2015302017), China Postdoctoral Science Foundation funded project (2015M570167), and also supported by the Planning Subject of the "Twelfth five-year-plan" in National Science and Technology for the Rural Development in China (2013BAD11B03-2), and Science and Technology Planning Project of Hebei Academy of Science (15101). We are grateful to the editors and anonymous reviewers for their insightful inputs at the review phase of this work.