Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa. (18th August 2020)

• Record Type: Journal Article
• Authors: Falconnier, Gatien N.; Corbeels, Marc; Boote, Kenneth J.; Affholder, François; Adam, Myriam; MacCarthy, Dilys S.; Ruane, Alex C.; Nendel, Claas; Whitbread, Anthony M.; Justes, Éric; Ahuja, Lajpat R.; Akinseye, Folorunso M.; Alou, Isaac N.; Amouzou, Kokou A.; Anapalli, Saseendran S.; Baron, Christian; Basso, Bruno; Baudron, Frédéric; Bertuzzi, Patrick; Challinor, Andrew J.; Chen, Yi; Deryng, Delphine; Elsayed, Maha L.; Faye, Babacar; Gaiser, Thomas; Galdos, Marcelo; Gayler, Sebastian; Gerardeaux, Edward; Giner, Michel; Grant, Brian; Hoogenboom, Gerrit; Ibrahim, Esther S.; Kamali, Bahareh; Kersebaum, Kurt Christian; Kim, Soo‐Hyung; van der Laan, Michael; Leroux, Louise; Lizaso, Jon I.; Maestrini, Bernardo; Meier, Elizabeth A.; Mequanint, Fasil; Ndoli, Alain; Porter, Cheryl H.; Priesack, Eckart; Ripoche, Dominique; Sida, Tesfaye S.; Singh, Upendra; Smith, Ward N.; Srivastava, Amit; Sinha, Sumit; Tao, Fulu; Thorburn, Peter J.; Timlin, Dennis; Traore, Bouba; Twine, Tracy; Webber, Heidi;
• Is Part Of: Global change biology. Volume 26:Number 10(2020)
• Page Start: 5942
• Page End: 5964
• Publication Date: 2020-08-18
• Subjects: crop simulation model -- ensemble modelling -- model intercomparison -- smallholder farming systems -- uncertainty; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.15261
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: 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. Abstract : 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 sub‐Saharan Africa, using an ensemble of 25 maize models. 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.