This study aims to clarify the spatiotemporal distribution patterns of the summer maize at the flowering stage before and after high temperatures in the North China Plain (NCP). A systematic investigation was also made to explore their impacts on the yield under climate change. Daily meteorological data were collected from 340 meteorological stations in the NCP (1981-2022). Phenology data of the summer maize were captured from 19 agricultural meteorological stations, and the high-temperature experimental data were from public literature. High-temperature thresholds of 32 ℃, 35 ℃, and 38 ℃ were selected to calculate the high-temperature indicators, including the extreme growing degree days (EDD) and the extreme heat days (EHD). An analysis was then made on their spatiotemporal distribution during the tasseling and grain-filling stages of summer maize in the NCP. Furthermore, an equation was used to assess the impact of the high temperatures before and after the flowering stage on the yield reduction rate of summer maize. The probability of the high-temperature occurrence was also calculated in the different provinces during various growth stages. The results showed that: 1) The high temperatures in the NCP were intensified under the background of climate warming. There was an increasing trend (P<0.05) in the EDD and EHD more than 32 ℃, 35 ℃, and 38 ℃ during the growing season of summer maize. The increasing rates were 13.8 ℃·d/10a and 4.0 d/10a, 4.0 ℃·d/10a and 2.3 d/10a, and 0.4 ℃·d/10a and 0.4 d/10a, respectively. 2) The occurrence of the high temperatures during the tasseling stage followed a pattern of more in the south and less in the north. In the grain-filling stage, the high temperatures shared a spatial distribution of more in the southwest and less in the northeast. High temperatures during the tasseling and grain-filling stages showed an increasing trend over the past four decades. According to the threshold temperature of 38 ℃, the significant warming occurred in the northern Henan province, with the increase rates of 0.4 ℃·d and 0.5℃ d per 10 years, respectively, during the tasseling stage. Significant warming was also observed in the southern Henan province and Renxian County in Hebei province, with the increase rates of 0.4 ℃·d/10a and 0.5 d/10a for the EDD and EHD, respectively. 3) Henan Province was found with the highest probabilities of the high temperatures above 32 ℃, 35 ℃, and 38 ℃ before and after flowering. The impact threshold of the high temperature was approximately 35℃ for the main maize varieties in the NCP. For each 1 ℃·d increase in the accumulated harmful temperature more than 35 ℃, and then the yield reduction rate of the summer maize increased by 0.45%. Furthermore, the impact of the high temperatures before and after flowering was particularly significant in Henan Province in the 2010s. Yield reduction rates ranged between 2% and 5% in the southern part of the province, such as Jiaozuo, and Huaibin in the southeastern. The findings can also provide scientific support to accurately assess the high-temperature risks and disaster reduction strategies at different growth stages of summer maize in the NCP under climate change.
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Accurate regional temperature projections in China are vital for climate change mitigation and adaptation. Since some of the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models are identified as “too warm” with a tendency to overestimate future warming, this study introduces an observational attribution-constrained projection method to reduce uncertainties in regional temperature projections. By applying this method to the CMIP5 and CMIP6 models, we establish a robust linkage between observed and projected temperature changes across China. Using the optimal fingerprinting technique, we demonstrate the dominant influence of anthropogenic activities on regional temperature changes. Through application of the optimal estimates of scaling factors derived from this method, we constrain future temperature projections. Under high-emissions Representative Concentration Pathway (RCP8.5) and Shared Socioeconomic Pathway scenarios (SSP5-8.5), the unconstrained annual mean temperature changes for 2081–2100 relative to 1995–2014 are projected as 4.47°C (5th–95th percentile range: 3.38–6.23°C, hereafter the same) by CMIP5 and 5.24°C (3.60–7.76°C) by CMIP6. After constraint implementation, these projections decrease to 3.90°C (2.98–4.48°C) for CMIP5 and 4.35°C (3.49–5.11°C) for CMIP6, with reduced uncertainty ranges compared to original projections. The constrained method improves consistency between CMIP5 and CMIP6 simulations, reducing inter-model uncertainties and enhancing the reliability of China’s temperature change projections.
As the world’s largest potato producer, China plays a crucial role in global food security. However, the impacts of climate change on both the potential planting regions and climatic suitability of potato cultivation in China remain poorly quantified. In this study, potato planting zones were delineated based on the thermal requirements of potato, utilizing the temperature data from 2177 meteorological sites during 1961‒2020. A comprehensive climatic suitability index (CCSI) was developed by integrating temperature, light, and precipitation suitability indices, weighted through Agricultural Production Systems Simulator (APSIM)-Potato model simulation. During 1991‒2020, compared to 1961‒1990, the unsuitable and single-season planting regions decreased by 18% and 8%, while the multi-season and winter planting regions expanded by 93% and 6%, respectively. During 1961‒2020, the CCSI was highest in single-season planting regions (e.g., Northeast China and the north agro-pastoral ecotone), followed by multi-season and winter planting regions. During 1991‒2020, compared to 1961‒1990, CCSI of potato planting in the single-season planting region showed a slight decrease, but it increased by 1%‒2% in the multi-season and winter planting regions. These findings demonstrate that the increase in potato climate suitability supports the expansion of potato planting area and implementation of the “Potato as Staple Food” policy. Increased precipitation and temperature identify Northwest and Southwest China as the potential expansion regions for potato planting.
In order to provide the important scientific reference for optimizing the layout of staple crops in Inner Mongolia, the adaptability of staple crops (maize, potato, oats, canola, oil and edible sunflower) was evaluated in four ecological regions of Inner Mongolia under different precipitation year types.
Four typical sites in four ecological regions were selected. The validated APSIM model was used to quantify the potential yields, rainfed yields and yield gaps of six crops. Yield reduction rates of rainfed yields relative to potential yields under different precipitation year types were calculated to evaluate the adaptability of staple crops. Crop water production functions were conducted to analyze crop water sensitivity.
RMSE between simulated and observed vegetative growth period, reproductive growth period, dry yield was 10.1 d, 8.9 d, and 1 322.4 kg·hm-2, respectively. NRMSE between observed and simulated vegetative growth period, reproductive growth period, and dry yield was 14.6%, 19.2%, and 22.6%, respectively. The validation results showed that APSIM could effectively simulate the growth, development, and yield of each crop in different regions. The potential dry yields of maize, potato, oats, canola, oil sunflower, and edible sunflower were 12 024±4 874, 7 315±806, 6 611±906, 2 424±326, 2 721±205, and 4 905±428 kg·hm-2, respectively. The potential yields of oats and edible sunflower reached the maximum values in the north foot of Yinshan Mountains while potential yields of other four crops reached the maximum values in the Loess Plateau. The rainfed dry yields of maize, potato, oats, canola, oil sunflower, and edible sunflower were 3 056±2 902, 3 337±1 608, 2 974±1 677, 912±511, 869±618, and 1 508±984 kg·hm-2, respectively. Average rainfed yields of the six crops increased from west to east and reached the maximum values in Da Hinggan Mountains. Yield gaps of maize, potato, oats, canola, oil sunflower, and edible sunflower were 8 968±5 844, 3 978±2 358, 3 637± 2 122, 1 512±832, 1 852±749, and 3 397±1 328 kg·hm-2, respectively. Except maize and oats, the yield gaps of four crops decreased from west to east and reached the minimum values in Da Hinggan Mountains. Taking the yield reduction rate from potential to rainfed conditions as the drought index under the rainfed condition and considering the variation coefficients of rainfed yields, it was not suitable to plant crops in any years in the Loess Plateau. In the north foot of Yinshan Mountains, crops were not suitable for planting in dry years. Potato was suitable for planting in normal years, while potato and oats were suitable for planting in wet years. At the foothills of Yanshan hilly area, crops were not suitable for planting in dry years. Potato and oats were suitable for planting in normal years while six crops were all suitable for planting in wet years. In Da Hinggan Mountains, potato, oats, canola, and edible sunflower were suitable for planting in dry years, while six crops were all suitable for planting in normal and wet years. The linear correlations between the relative evapotranspiration and the relative yield of the six crops were all significant (P<0.01) with R2 ranging from 0.84 to 0.99. The sensitivity of crop to water stress was in the order of oil sunflower, edible sunflower, maize, oats, canola, and potato.
This study revealed the adaptability of staple crops under different precipitation year types in the four ecological regions of Inner Mongolia. There was a large difference in water sensitivity of six crops. Under rainfed condition, potato were suitable for planting in normal and wet years in the north foot of Yinshan Mountains and the foothills of Yanshan hilly area, and in all year types in Da Hinggan Mountains. Oats were suitable for planting in wet years in the north foot of Yinshan Mountains, in normal and wet years in the foothills of Yanshan hilly area and in all year types in Da Hinggan Mountains. Canola and edible sunflower were suitable for planting only in wet years in the foothills of Yanshan hilly area and in all year types in Da Hinggan Mountains. Maize and oil sunflower were suitable for planting only in wet years in the foothills of Yanshan hilly area and in normal and wet years in Da Hinggan Mountains.
In order to improve simulation accuracy of maize kernel number under drought stress, the study simulated canopy silking dynamic of maize under drought stress and developed the relationships among anthesis-silking interval (ASI), canopy silking percentage and maize kernel number per unit area.
Firstly, this study measured the average plant growth rate (PGR) of maize around anthesis, daily canopy silking percentage of maize, ASI, the biomass accumulation of ear after anthesis, and the kernel number per plant under different treatments of soil water content based on drought stress controlling experiment at Jinzhou Agrometeorological Experimental Station. Secondly, the parameters of maize canopy silking dynamic model were determined with experimental data. Sensitivity analysis was conducted to investigate the impact of changes in average plan growth rate (PGRAVE) and standard deviation (PGRSD) on simulated canopy silking percentage. Thirdly, based on the ear biomass accumulation dynamic, the canopy silking dynamic was simulated under different drought stresses before and after anthesis by considering the differences in PGR among individual plants in the canopy. The quantitative relationship between ASI and kernel setting rate (the percentage of kernel number per plant to the maximum potential kernel number per plant) was developed based on experimental data. Finally, based on simulated canopy silking percentage after anthesis, maximum potential kernel number per plant, and the kernel setting rate by canopy silking dynamic model, the maize kernel number model was developed and validated under drought stress.
Sensitivity analysis of change in canopy silking percentage in response to changes in PGRAVE and PGRSD showed that PGRAVE had a greater impact on canopy silking percentage than PGRSD. The larger the PGRAVE and the smaller the PGRSD, the shorter the time for the canopy reaching silking percentage of 50%. The maize canopy silking dynamic model could accurately simulate daily silking percentage after anthesis under drought stress, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized mean square error (NRMSE) between simulated and observed canopy silking percentage ranged from 0.88 to 0.98, from 4% to 12%, and from 8% to 27%, respectively. Maize kernel number model could accurately simulate the kernel number of maize per unit area under drought stress, and R2, RMSE, and NRMSE between simulated and observed kernel number was 0.85, 185 kernel/m2, and 10%, respectively.
By introducing the canopy silking dynamic model, the study could simulate the key phenology (silking time, anthesis-silking interval, and silking percentage) and kernel number per unit area under drought stress. The result was an important foundation for the simulation of maize yield based on canopy silking dynamic under drought stress.
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