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dc.contributor.authorSabiiti, Geoffrey
dc.contributor.authorIninda, Joseph M
dc.contributor.authorOgallo, Laban A
dc.contributor.authorOuma, Jully
dc.contributor.authorArtan, Guleid
dc.contributor.authorBasalirwa, Charles
dc.date.accessioned2018-07-23T06:46:11Z
dc.date.available2018-07-23T06:46:11Z
dc.date.issued2018
dc.identifier.citationSabiiti, Geoffrey, et al. "Adapting Agriculture to Climate Change: Suitability of Banana Crop Production to Future Climate Change Over Uganda." Limits to Climate Change Adaptation. Springer, Cham, 2018. 175-190.en_US
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-319-64599-5_10
dc.identifier.urihttp://hdl.handle.net/11295/103481
dc.description.abstractThe aim of this study was to determine suitability zones of future banana growth under a changing climate to guide the design of future adaptation options in the banana sub-sector of Uganda. The study used high resolution (~1 km) data on combined bioclimatic variables (rainfall and temperature) to map suitability zones of the banana crop while the Providing Regional Climate for Impacts Studies (PRECIS) regional climate model temperature simulations were used to estimate the effect of rising temperature on banana growth assuming other factors constant. The downscaled future climate projections were based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs, 2.6, 4.5, 6.0 and 8.5) and Special Report on Emission Scenarios (SRES, A1B and A2) across the period 2011–2090. The methodology involved identification of banana-climate growth thresholds and developing suitability indices for banana production under the high mitigation (RCP 2.6, less adaptation), medium mitigation (RCP 4.5 and RCP 6.0, medium adaptation), no mitigation (RCP 8.5, very high adaptation) scenarios, SRES A1B and A2 scenarios. The FAO ECO-Crop tool was used to determine and map future suitability of banana growth. Banana production indices were determined using a suitability model in the Geographical Information System (GIS) spatial analyst tool. The non-linear banana-temperature regression model was used to assess the impact of future changes in temperature on banana growth. The results revealed unique and distinct banana production suitability and growth patterns for each climate scenario in the sub-periods. RCPs 2.6 and 6.5 are likely to be associated with higher levels of banana production than RCPs 4.5 and 8.5. The results further showed that projected temperature increase under SRES A1B will promote banana growth. In contrast, expected increases in temperatures under SRES A2 are likely to retard banana growth due to high moisture deficits. There is need to develop adaptation option for farming communities to maximize their agricultural production and incomes. The effectiveness of adaptation options needed to combat the impacts will be influenced by the magnitude of the expected climatic changes associated with each scenario, the timing of expected climate change extremes and sensitivity of the crop to climate. This study has provided critical information that will be useful for planning integrated adaptation practices in the banana farming subsector to promote productivity.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectClimate change Scenarios Agriculture Suitability Adaptation Banana crop Rainfall Temperatureen_US
dc.titleAdapting agriculture to climate change: suitability of banana crop production to future climate change over Ugandaen_US
dc.typeArticleen_US


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