27 lines
2.1 KiB
Plaintext
Executable File
27 lines
2.1 KiB
Plaintext
Executable File
TY - JOUR
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T1 - Local impacts of climate change and agronomic practices on dry land crops in Southern Africa
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JO - Agriculture, Ecosystems & Environment
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VL - 197
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IS -
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SP - 1
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EP - 10
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PY - 2014/12/1/
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T2 -
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AU - Zinyengere, Nkulumo
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AU - Crespo, Olivier
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AU - Hachigonta, Sepo
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AU - Tadross, Mark
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SN - 0167-8809
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DO - http://dx.doi.org/10.1016/j.agee.2014.07.002
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UR - http://www.sciencedirect.com/science/article/pii/S0167880914003624
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KW - Agronomic practices
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KW - Cereals
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KW - Climate change
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KW - Groundnut
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KW - Modeling
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AB - Abstract
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Climate change impact assessments on agriculture in Southern Africa are mostly carried out at large spatial scales, risking missing out on local impacts and adaptation potential that reflect the range of multiple and unique bio-physical and agronomic conditions under which farmers in the region operate. This study investigated how climate change may affect yields of various major food crops in specific locations in the region; maize and sorghum (Mohale’s Hoek – Lesotho and Big Bend – Swaziland), maize and groundnut (Lilongwe – Malawi). Using statistically downscaled climate projections from nine GCMs and the DSSAT crop model and simulating selected agronomic strategies practiced in each location, the study confirmed that impacts of climate change on crop yields in Southern Africa vary across locations and crops. Despite various uncertainties associated with such assessments, the results showed that crop yields were predominantly projected to decline in Big Bend (maize (−20%); sorghum (−16%)) and Lilongwe (maize (−5%); groundnut (−33%)). However, crop yields in Mohale’s Hoek, located in a high altitude region historically prone to cold related crop yield losses were on average projected to increase (maize (+8%) and sorghum (+51%)). The geographical variation of yield projections highlights the importance of location specific climate change impact assessments. The exploration of local agronomic management alternatives revealed prospects for identifying locally relevant adaptation strategies, which cannot easily be captured at larger scales.
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ER -
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