Abschlussarbeit

TRANS-SAHARA project- Spring 2026
Bachelor- oder Masterarbeit
This master’s thesis is part of the TRANS-SAHARA project which aims to harness Water-Energy-Food-Ecoysystem (WEFE)-Nexus innovations alongside traditional ecological knowledge to support agroforestry in climate-vulnerable areas of ‘Greater Northern African Region’ (GNAR), encompassing North Africa, the sub-Saharan Sahel and the Horn of Africa. The thesis will directly contribute to development of a multi-objective optimization model for land use allocation, designed to support local agroforestry and land use decision-making. The first iteration of the model will be demonstrated for the project’s Living Lab in Yirgacheffe (Gedeo Zone, Ethiopia). The region is characterized by a long-established tradition of coffee-based agroforestry but is increasingly challenged by pressures such as climate change, land degradation, and land fragmentation. The model aims to: • Evaluate socioeconomic and ecological benefits and trade-offs associated with alternative land-use options; • Identify optimal land-use allocation strategies that align with farmers’ and local stakeholders’ priorities under uncertain future market, productivity, and environmental conditions; • Explore policy instruments that could support traditional land-use systems while reducing financial or institutional barriers to land-use adaptation strategies. To maximize accessibility to decision-makers and enable flexible use in other GNAR contexts, the model will be translated by project partners into an online, open-source decision-support tool. Supervised by a PhD student working within the TRANS-SAHARA project, the thesis will focus on quantifying specific socioeconomic and/or ecological ‘indicators’ (outcomes) of alternative land-use scenarios and assessing how these may evolve under future conditions. Depending on project priorities, data availability, and the student’s skills and interests, potential tools and methods may include: • The InVEST ecosystem service valuation model and social cost-benefit analysis; • Plot-scale biophysical yield models or machine-learning approaches; • Benefit transfer methods. Minimum requirements: basic statistical/economic knowledge and interest in agroforestry/forest topics. The thesis will ideally be written in English. To apply, interested students should email their CV (no more than 2 pages) and a short motivation statement to Eleanor.gardner@tum.de
Bearbeiter: Hier könnte Ihr Name stehen!	Betreuer: Gardner, E., Gardner, E.
Beginn: ab sofort