Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO₂], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO₂], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO₂]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low‐input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

中文翻译：

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在撒哈拉以南非洲低氮输入条件下模拟气候变化对玉米产量的影响。

撒哈拉以南非洲（SSA）的小农户目前种植雨养玉米，但肥料有限。气候变化可能加剧当前的生产限制。作物模型可以帮助量化气候变化对玉米单产的潜在影响，但是目前缺乏对这些低投入系统中模拟准确性和不确定性的全面多模型评估。我们评估了变化的[CO ₂]，温度和降雨条件对玉米产量的影响，包括SSA五个环境下不同氮素输入量（0、80、160 kg N / ha），包括凉爽的埃塞俄比亚，凉爽的半干旱卢旺达，炎热的加湿和加纳半干旱马里和贝宁使用25种玉米模型的合奏。使用来自每个国家的2年实验的实测谷物产量，植物生物量，植物氮，叶面积指数，收获指数和季节土壤含水量对模型进行校准，以评估其模拟观测产量的能力。探索了对气候变化因素的模拟响应，并在模型之间进行了比较。尽管模型预测的不确定性很大（CV = 28％），但经过校准的模型可以很好地再现实测的谷物单产，平均相对均方根误差为26％。模型合奏比随机抽取的任何模型都具有更高的准确性。氮肥控制了对[CO₂ ]，温度和降雨。没有氮肥的投入，玉米（a）从大气[​​CO ₂ ]的增加中获得的收益较少；（b）受高温或降雨减少的影响较小；（c）受降雨增加的影响更大，因为氮的淋洗更为关键。模型的比较表明，模拟每日土壤氮的供应和氮的淋溶在模拟低投入系统的气候变化影响方面起着至关重要的作用。气候变化和氮素输入的交互作用对于整个SSA的稳健适应方法的设计具有重要意义，因为如果农民在平衡的养分管理下加强玉米生产，那么气候变化对低投入系统的影响将得到改善。