Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda

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dc.contributor.authorGram, Gil
dc.contributor.authorVaast, Philippe
dc.contributor.authorvan der Wolf, Just
dc.contributor.authorJassogne, Laurence
dc.date.accessioned2023-01-31T03:31:39Z
dc.date.available2023-01-31T03:31:39Z
dc.date.issued2018-12
dc.description© The Author(s) 2017. This article is published with open access at Springerlink.com and is licensed under the Creative Commons Attribution 4.0 International License - https://creativecommons.org/licenses/by/4.0/ . The Version of Scholarly Record of this Article is published in Agroforestry Systems, 2018, available online at: https://link.springer.com/article/10.1007/s10457-017-0111-8 . Keywords: Climate change; Ecosystem services; Smallholder farmer ranking; Famer perceptions; Local knowledge; Shade tree; Coffea arabica; Africa; Uganda.
dc.description.abstractArabica coffee (Coffea arabica) is economically important for many smallholder farmers in the Mount Elgon region of East Uganda, but its production is increasingly threatened by climate change. However, ecosystem services (ES) provided by companion trees in coffee agroforestry systems (AFS) can help farmers adapt to climate change. The objectives of this research were to develop agroforestry species recommendations and tailor these to the farmers’ needs and local context, taking into consideration gender. Local knowledge of agroforestry species and ES preferences was collected through farmer interviews and rankings. Using the Bradley-Terry approach, analysis was done along an altitudinal gradient in order to study different climate change scenarios for coffee suitability. Farmers had different needs in terms of ES and tree species at different altitudes, e.g. at low altitude they need a relatively larger set of ES to sustain their coffee production and livelihood. Local knowledge is found to be gender blind as no differences were observed in the rankings of species and ES by men and women. Ranking species by ES and ranking ES by preference is a useful method to help scientists and extension agents to use local knowledge for the development of recommendations on companion trees in AFS for smallholder farmers.
dc.description.sponsorshipThis research was conducted under the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and under the Program Forestry, Trees and Agroforestry (FTA). The study was supported by the Federal Ministry for Economic Cooperation and Development of Germany (BMZ). The authors of this paper wish to show their appreciation and gratitude for Franco Manget and Wilberforce Wodada for their valuable assistance in the field, Theresa Liebig for her help with the baseline data collection and advice on pests and diseases, Dr. Richard Coe (ICRAF) for his advices on Bradley Terry ranking analysis in R, Allan Heinze for the ranking analysis functions in R, Jenny Ordonez (ICRAF) for her contribution to the methodology, Metajua for digitising the surveys, Ewaut Kissel for his significant help in R programming, and Mandy Malan for her daily support and endless reviews.
dc.identifier.citationGram, G., Vaast, P., van der Wolf, J., & Jassogne, L. (2018). Local tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda. Agroforestry Systems, 92, 1625–1638. https://doi.org/10.1007/s10457-017-0111-8
dc.identifier.otherhttps://doi.org/10.1007/s10457-017-0111-8
dc.identifier.urihttps://hdl.handle.net/20.500.14096/218
dc.language.isoen
dc.publisherSpringer Nature
dc.titleLocal tree knowledge can fast-track agroforestry recommendations for coffee smallholders along a climate gradient in Mount Elgon, Uganda
dc.typeArticle

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