Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda
Coffee agroforestry systems deliver ecosystem services (ES) critical for rural livelihoods like food but also disservices that constrain livelihoods like fostering coffee-pests. Since such ES are tree-based, maximizing ES and limiting constraints requires knowledge on optimizing on-farm tree composi...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Springer
2019
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/93203 |
| _version_ | 1855513260049039360 |
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| author | Bukomeko, Hannington Jassogne, Laurence T.P. Tumwebaze, Susan Balaba Eilu, Gerald Vaast, Philippe |
| author_browse | Bukomeko, Hannington Eilu, Gerald Jassogne, Laurence T.P. Tumwebaze, Susan Balaba Vaast, Philippe |
| author_facet | Bukomeko, Hannington Jassogne, Laurence T.P. Tumwebaze, Susan Balaba Eilu, Gerald Vaast, Philippe |
| author_sort | Bukomeko, Hannington |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Coffee agroforestry systems deliver ecosystem services (ES) critical for rural livelihoods like food but also disservices that constrain livelihoods like fostering coffee-pests. Since such ES are tree-based, maximizing ES and limiting constraints requires knowledge on optimizing on-farm tree composition especially trees adapted to local conditions. The study was in three sites along a rainfall gradient in Central Uganda where we: assessed tree diversity in coffee agroforestry; ranked tree suitability for providing ES according to farmers’ knowledge; and then proposed an approach for optimizing on-farm tree composition for delivery of ES. We collected data on tree diversity and, farmers’ knowledge of tree species and the ES they provide. Farmers ranked ES in order of importance to their livelihoods (‘Needs rank’) and ranked trees according to suitability for providing ES. Using Bradley Terry modeling, we grouped trees into ‘ES groups’ according to suitability for providing different ES and ranked ‘ES groups’ according to tree diversity (‘Diversity rank’). Tree-suitability for providing ES and importance of ES to farmers varied with rainfall regime but tree diversity did not match farmers’ needs for ES. We propose the FaD–FaN (matching farm tree diversity to farmers’ needs) approach for optimizing tree species composition with respect to tree-suitability for farmers’ priority ES. Farmers locally prioritize ES needed and identify trees that best serve such ES. The approach then focuses on modifying on-farm tree diversity to match/suit farmers’ priority ES. The FaD–FaN approach caters for varying socio-ecological conditions; it’s adaptable for other coffee and cocoa-growing areas worldwide. |
| format | Journal Article |
| id | CGSpace93203 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace932032025-02-19T13:41:57Z Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda Bukomeko, Hannington Jassogne, Laurence T.P. Tumwebaze, Susan Balaba Eilu, Gerald Vaast, Philippe agriculture climate change coffee shade systems ecosystem forestry Coffee agroforestry systems deliver ecosystem services (ES) critical for rural livelihoods like food but also disservices that constrain livelihoods like fostering coffee-pests. Since such ES are tree-based, maximizing ES and limiting constraints requires knowledge on optimizing on-farm tree composition especially trees adapted to local conditions. The study was in three sites along a rainfall gradient in Central Uganda where we: assessed tree diversity in coffee agroforestry; ranked tree suitability for providing ES according to farmers’ knowledge; and then proposed an approach for optimizing on-farm tree composition for delivery of ES. We collected data on tree diversity and, farmers’ knowledge of tree species and the ES they provide. Farmers ranked ES in order of importance to their livelihoods (‘Needs rank’) and ranked trees according to suitability for providing ES. Using Bradley Terry modeling, we grouped trees into ‘ES groups’ according to suitability for providing different ES and ranked ‘ES groups’ according to tree diversity (‘Diversity rank’). Tree-suitability for providing ES and importance of ES to farmers varied with rainfall regime but tree diversity did not match farmers’ needs for ES. We propose the FaD–FaN (matching farm tree diversity to farmers’ needs) approach for optimizing tree species composition with respect to tree-suitability for farmers’ priority ES. Farmers locally prioritize ES needed and identify trees that best serve such ES. The approach then focuses on modifying on-farm tree diversity to match/suit farmers’ priority ES. The FaD–FaN approach caters for varying socio-ecological conditions; it’s adaptable for other coffee and cocoa-growing areas worldwide. 2019-04 2018-06-12T18:49:02Z 2018-06-12T18:49:02Z Journal Article https://hdl.handle.net/10568/93203 en Open Access Springer Bukomeko H, Jassogne L, Tumwebaze SB, Eili G, Vaast P. 2019. Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda. Agroforest System 9:755-770. |
| spellingShingle | agriculture climate change coffee shade systems ecosystem forestry Bukomeko, Hannington Jassogne, Laurence T.P. Tumwebaze, Susan Balaba Eilu, Gerald Vaast, Philippe Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title_full | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title_fullStr | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title_full_unstemmed | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title_short | Integrating local knowledge with tree diversity analyses to optimize on-farm tree species composition for ecosystem service delivery in coffee agroforestry systems of Uganda |
| title_sort | integrating local knowledge with tree diversity analyses to optimize on farm tree species composition for ecosystem service delivery in coffee agroforestry systems of uganda |
| topic | agriculture climate change coffee shade systems ecosystem forestry |
| url | https://hdl.handle.net/10568/93203 |
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