Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia
Land degradation is a global challenge that affects lives and livelihoods in many communities. Since 1950, about 65% of Africa’s cropland, on which millions of people depend, has been affected by land degradation caused by mining, poor farming practices and illegal logging. One-quarter of the land a...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Cambridge University Press
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/107435 |
| _version_ | 1855540280240898048 |
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| author | Kibret, Kefyalew S. Haileslassie, Amare Mekuria, Wolde Schmitter, Petra S. |
| author_browse | Haileslassie, Amare Kibret, Kefyalew S. Mekuria, Wolde Schmitter, Petra S. |
| author_facet | Kibret, Kefyalew S. Haileslassie, Amare Mekuria, Wolde Schmitter, Petra S. |
| author_sort | Kibret, Kefyalew S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Land degradation is a global challenge that affects lives and livelihoods in many communities. Since 1950, about 65% of Africa’s cropland, on which millions of people depend, has been affected by land degradation caused by mining, poor farming practices and illegal logging. One-quarter of the land area of Ethiopia is severely degraded. As part of interventions to restore ecosystem services, exclosures have been implemented in Ethiopia since the 1980s. But the lack of tools to support prioritization and more efficient targeting of areas for large-scale exclosure-based interventions remains a challenge. Within that perspective, the overarching objectives of the current study were: (i) to develop a Geographic Information System-based multicriteria decision-support tool that would help in the identification of suitable areas for exclosure initiatives; (ii) to provide spatially explicit information, aggregated by river basin and agroecology, on potential areas for exclosure interventions and (iii) to conduct ex-ante analysis of the potential of exclosure areas for improving ecosystem services in terms of increase in above-ground biomass (AGB) production and carbon storage. The results of this study demonstrated that as much as 10% of Ethiopia’s land area is suitable for establishing exclosures. This amounts to 11 million hectares (ha) of land depending on the criteria used to define suitability for exclosure. Of this total, a significant proportion (0.5–0.6 million ha) is currently under agricultural land-use systems. In terms of propriety river basins, we found that the largest amount of suitable area for exclosures falls in the Abay (2.6 million ha) and Tekeze (2.2 million ha) river basins, which are hosts to water infrastructure such as hydropower dams and are threatened by siltation. Ex-ante analysis of ecosystem services indicated that about 418 million tons of carbon can be stored in the AGB through exclosure land use. Ethiopia has voluntarily committed to the Bonn Challenge to restore 15 million ha of degraded land by 2025. The decision-support tool developed by the current study and the information so generated go toward supporting the planning, implementation and monitoring of these kinds of local and regional initiatives. |
| format | Journal Article |
| id | CGSpace107435 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Cambridge University Press |
| publisherStr | Cambridge University Press |
| record_format | dspace |
| spelling | CGSpace1074352025-04-14T11:30:01Z Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia Kibret, Kefyalew S. Haileslassie, Amare Mekuria, Wolde Schmitter, Petra S. soil conservation land degradation exclosures decision support systems land use planning ecosystem services river basins watersheds lakes water conservation biomass carbon sequestration agroecology erosion models Land degradation is a global challenge that affects lives and livelihoods in many communities. Since 1950, about 65% of Africa’s cropland, on which millions of people depend, has been affected by land degradation caused by mining, poor farming practices and illegal logging. One-quarter of the land area of Ethiopia is severely degraded. As part of interventions to restore ecosystem services, exclosures have been implemented in Ethiopia since the 1980s. But the lack of tools to support prioritization and more efficient targeting of areas for large-scale exclosure-based interventions remains a challenge. Within that perspective, the overarching objectives of the current study were: (i) to develop a Geographic Information System-based multicriteria decision-support tool that would help in the identification of suitable areas for exclosure initiatives; (ii) to provide spatially explicit information, aggregated by river basin and agroecology, on potential areas for exclosure interventions and (iii) to conduct ex-ante analysis of the potential of exclosure areas for improving ecosystem services in terms of increase in above-ground biomass (AGB) production and carbon storage. The results of this study demonstrated that as much as 10% of Ethiopia’s land area is suitable for establishing exclosures. This amounts to 11 million hectares (ha) of land depending on the criteria used to define suitability for exclosure. Of this total, a significant proportion (0.5–0.6 million ha) is currently under agricultural land-use systems. In terms of propriety river basins, we found that the largest amount of suitable area for exclosures falls in the Abay (2.6 million ha) and Tekeze (2.2 million ha) river basins, which are hosts to water infrastructure such as hydropower dams and are threatened by siltation. Ex-ante analysis of ecosystem services indicated that about 418 million tons of carbon can be stored in the AGB through exclosure land use. Ethiopia has voluntarily committed to the Bonn Challenge to restore 15 million ha of degraded land by 2025. The decision-support tool developed by the current study and the information so generated go toward supporting the planning, implementation and monitoring of these kinds of local and regional initiatives. 2022-01 2020-03-10T04:36:10Z 2020-03-10T04:36:10Z Journal Article https://hdl.handle.net/10568/107435 en Open Access Cambridge University Press Kibret, K. S.; Haileslassie, Amare; Mekuria Bori, Wolde; Schmitter, Petra. 2022. Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia. Renewable Agriculture and Food Systems, 37(S1):S88-S102. (Special issue: Restoring Degraded Landscapes and Fragile Food Systems) [doi: https://doi.org/10.1017/S1742170520000034] |
| spellingShingle | soil conservation land degradation exclosures decision support systems land use planning ecosystem services river basins watersheds lakes water conservation biomass carbon sequestration agroecology erosion models Kibret, Kefyalew S. Haileslassie, Amare Mekuria, Wolde Schmitter, Petra S. Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title | Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title_full | Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title_fullStr | Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title_full_unstemmed | Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title_short | Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia |
| title_sort | multicriteria decision support system to assess the potential of exclosure based conservation in ethiopia |
| topic | soil conservation land degradation exclosures decision support systems land use planning ecosystem services river basins watersheds lakes water conservation biomass carbon sequestration agroecology erosion models |
| url | https://hdl.handle.net/10568/107435 |
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