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  • Modelling climate change im...
    Falconnier, GN; Corbeels, M; Boote, KJ; Affholder, F; Adam, M; MacCarthy, DS; Ruane, AC; Nendel, C; Whitbread, AM; Justes, E; Ahuja, LR; Akinseye, F.M.; Alou, IN; Amouzou, KA; Anapalli, S.S.; Baron, C; Basso, B; Baudron, F; Challinor, AJ; Chen, Y; Deryng, D; Elsayed, ML; Faye, B; Gaiser, T; Galdos, M; Gayler, S; Gerardeaux, E; Giner, M; Grant, B; Hoogenboom, G; Ibrahim, ES; Kamali, B; Kersebaum, KC; Kim, SH; Laan, M van der; Leroux, L; Lizaso, JI; Maestrini, B; Meier, EA; Mequanint, F; Ndoli, A; Porter, CH; Priesack, E; Sida, T; Singh, U; Smith, W; Srivastava, A; Sinha, S; Tao, F; Thorburn, PJ; Timlin, D; Traore, B; Twine, T; Webber, H

    Global change biology, October 2020, Letnik: 26, Številka: 10
    Journal Article

    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 (i) benefited less from an increase in atmospheric CO2, (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison 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 practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.