Key Laboratory of Environmental Change and Natural Disaster MOE, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Key Laboratory of Environmental Change and Natural Disaster MOE, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Sci Total Environ. 2020 Aug 1;728:138614. doi: 10.1016/j.scitotenv.2020.138614. Epub 2020 Apr 15.
Crop growth conditions are being altered by ongoing climate change and the agronomic management practices should be adjusted accordingly and timely. In Chinese Maize Belt, climate change impacts are always compounded by agronomic management and the regional differences have yet to be well understood. How local farmers adapt to climate change is a big challenge and related adaptive strategies are urgently required. Based on detailed field experiments performed for >15 years, we applied the CERES-Maize model to disentangle the impacts of individual climate variables, quantify the contributions of three low-cost measures (cultivar, sowing date, and planting density) to yield variations, and design effective adaptation options in each zone. We found the patterns and impacts of climate change varied among the cultivated areas: yield increased by 0.39% per year in Northeast China (NEC) and 0.78% in the northwestern arid area (NWA) but decreased by 1.13% in the North China Plain (NCP). The results highlighted the considerable impacts of increased minimum temperature and decreased solar radiation on the changes of maize yield. CERES-Maize model reproduced the phenology and yield well with <9% bias and >81% yield explanation ability. The simulation results suggested that an appropriate delay in sowing date could mitigate climatic negative effects and enhance maize yields significantly. Planting cultivars of Nongda108 in NEC, Zhengdan958 in the NCP, and Shendan10 in the NWA substantially increased yield compared with planting the cultivars most widely used by farmers. The optimal planting density were 11.4, 12.3, and 12.7 plants/m respectively, which were generally higher than the local common levels. By optimizing genotype (G)-environment (E)-management (M) interactions, maize yield can be enhanced by at least 10%, especially in the NWA, implying that efforts to increase food production should be made in low-yielding zones. This study illustrated the patterns of climate change in different zones, and demonstrated an effective approach to develop sustainable intensification options and improve yield and stability with fewer economic-environmental costs by optimizing G × E × M interactions in the future.
作物生长条件正在受到持续气候变化的影响，农业管理措施应相应及时地进行调整。在中国玉米带，气候变化的影响总是与农业管理因素复合在一起，且区域差异尚未得到充分了解。当地农民如何适应气候变化是一个巨大的挑战，迫切需要相关的适应策略。基于超过 15 年的详细田间试验，我们应用 CERES-Maize 模型来区分各个气候变量的影响，量化三种低成本措施（品种、播期和种植密度）对产量变化的贡献，并为每个地区设计有效的适应方案。我们发现，不同种植区的气候变化模式和影响有所不同：中国东北（NEC）的产量每年增加 0.39%，西北干旱区（NWA）增加 0.78%，而华北平原（NCP）则减少 1.13%。研究结果强调了最低温度升高和太阳辐射减少对玉米产量变化的重要影响。CERES-Maize 模型对物候和产量的模拟结果较好，偏差小于 9%，解释能力大于 81%。模拟结果表明，适当推迟播期可以减轻气候的负面影响，显著提高玉米产量。在 NEC 种植农大 108、在 NCP 种植郑单 958 和在 NWA 种植先单 10，与农民普遍种植的品种相比，显著提高了产量。最优种植密度分别为 11.4、12.3 和 12.7 株/米，普遍高于当地常用水平。通过优化基因型（G）-环境（E）-管理（M）互作，可以至少提高 10%的玉米产量，特别是在 NWA，这意味着应该在低产地区努力提高粮食产量。本研究说明了不同地区气候变化的模式，并展示了一种有效的方法，通过优化 G×E×M 互作，未来可以开发可持续的集约化方案，以提高产量和稳定性，同时减少经济环境成本。
