Pathways towards sustainable restoration of agroecosystems The case Ethiopian highlands

Project: PhD

Project Details

Description

Global food production has seen a steady increase since the 1950s. However, losses of land and biodiversity resources are challenging the sustainability of the gains. This situation urges countries to mobilize resources toward the restoration of agroecosystems. Ethiopia is an example that mobilizes public resources to support the restoration of agroecosystems by communities. The government has also made reforms on the local governance of resources which gives more ownership and mandate to the local communities on the use and management of resources. However, the restoration performance varies across communities. Despite the number of studies conducted on the restoration practices, it is unknown why some communities have made substantially better progress (and maintained success); other communities have achieved little to no in the restoration. This research will investigate the main characteristics of the positive outliers, also known as “bright spots”: communities that have made better progress than expected. A “bright spots” framework will be applied, which uses positive outliers as the basis for understanding how to achieve quick restoration and sustainable management of agroecosystems and the transition pathways that other communities can learn. To this end, the research will; 1) define key features of the “bright spot” land restoration communities; 2) compare the transition pathways of community groups with different performances; 3) investigate the effects of change in local resource governance on the restoration performance of the communities and 4) build scenarios for the future trajectory of the performance groups. Ultimately, this thesis will contribute to the scientific knowledge on the restoration and sustainable transformation of stressed agroecosystems.
StatusActive
Effective start/end date1/09/21 → …

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.