AIDA, Univ Montpellier, CIRAD, Montpellier, France.
CIMMYT, Nairobi, Kenya.
Glob Chang Biol. 2020 Oct;26(10):5942-5964. doi: 10.1111/gcb.15261. Epub 2020 Aug 18.
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 [CO ], 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 [CO ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO ]; (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.
撒哈拉以南非洲(SSA)的小农目前以有限的投入(包括肥料)种植雨养玉米。气候变化可能会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产量的潜在影响,但目前缺乏对这些低投入系统中模拟准确性和不确定性的综合多模型评估。我们使用 25 个玉米模型的集合,评估了不同 CO 、温度和降雨条件对玉米产量的影响,研究了五个 SSA 环境(包括埃塞俄比亚凉爽的半湿润地区、卢旺达凉爽的半干旱地区、加纳炎热的半湿润地区以及马里和贝宁炎热的半干旱地区)中不同氮(N)投入(0、80、160 kg/ha)下的情况。通过对每个国家 2 年试验中的实测籽粒产量、植物生物量、植物 N、叶面积指数、收获指数和季内土壤水分进行模型校准,评估模型模拟观测产量的能力。探讨并比较了模型对气候变化因素的模拟响应。校准后的模型很好地再现了实测籽粒产量的变化,平均相对根均方误差为 26%,尽管模型预测的不确定性很大(CV=28%)。模型集合的准确性高于任何随机选择的模型。氮施肥控制了对大气[CO ]、温度和降雨变化的响应。没有氮肥投入,玉米(a)从大气[CO ]增加中获益较少;(b)受较高温度或降雨量减少的影响较小;(c)受降雨量增加的影响较大,因为氮淋失更为关键。模型间的比较表明,模拟日土壤 N 供应和氮淋失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。气候变化和氮投入的相互作用对 SSA 地区稳健适应方法的设计具有重要意义,因为如果农民通过平衡养分管理来加强玉米生产,低投入系统中气候变化的影响将发生变化。