Tree species selection for land rehabilitation in Ethiopia: from fragmented knowledge to an integrated multi-criteria decision approach
- First Online:
- Cite this article as:
- Reubens, B., Moeremans, C., Poesen, J. et al. Agroforest Syst (2011) 82: 303. doi:10.1007/s10457-011-9381-8
- 753 Downloads
Dryland regions worldwide are increasingly suffering from losses of soil and biodiversity as a consequence of land degradation. Integrated conservation, rehabilitation and community-based management of natural resources are therefore of vital importance. Local planting efforts should focus on species performing a wide range of functions. Too often however, unsuitable tree species are planted when both ecological suitability for the targeted area or preferences of local stakeholders are not properly taken into account during selection. To develop a decision support tool for multi-purpose species selection, first information needs to be pooled on species-specific ranges, characteristics and functions for a set of potentially valuable species. In this study such database has been developed for the highly degraded northern Ethiopian highlands, using a unique combination of information sources, and with particular attention for local ecological knowledge and preferences. A set of candidate tree species and potentially relevant criteria, a flexible input database with species performance scores upon these criteria, and a ready-to-use multi-criteria decision support tool are presented. Two examples of species selection under different scenarios have been worked out in detail, with highest scores obtained for Cordia africana and Dodonaea angustifolia, as well as Eucalyptus spp., Acacia abyssinica, Acacia saligna, Olea europaea and Faidherbia albida. Sensitivity to criteria weights, and reliability and lack of knowledge on particular species attributes remain constraints towards applicability, particularly when many species are jointly evaluated. Nonetheless, the amount and diversity of the knowledge pooled in the presented database is high, covering 91 species and 45 attributes.