Research School for Socio-Economic and
Natural Sciences of the Environment
Research School for Socio-Economic and
Natural Sciences of the Environment

Farming Systems and Rural Livelihoods - Pathways to sustainable development

Date: 16 September 2018 - 28 September 2018
Location: Fort Portal, Uganda, East Africa


Through the adoption of the Sustainable Development Goals (SDGs) the world has set ambitious aims, of which many are related to and affected by agriculture. SDG-2 is particularly relevant for rural livelihoods in sub-Saharan Africa as it aims to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture. Yet a number of trends and pressures complicate achieving SDG-2, including massive demographic growth, natural resource degradation and climate change. In this course, you will acquire skills and learn methods to deal with the complexity of smallholder agriculture and the many interlinkages with other SDGs towards carving out pathways for sustainable development of smallholder farming systems.

Typically, these skills and methods integrate agro-ecological analyses with understandings of the social-institutional organization of agricultural production, and the differential ways in which the wider socio-economic environment impacts on farming systems (e.g. the importance of rural-urban linkages, value chains, socio-cultural orientations in rural livelihoods). Special attention will be given to the vulnerability of agricultural production and aspects of food security and poverty in the face of global environmental, social and economic change. Multi-criteria approaches for assessing trade-offs in multiple domains of sustainability will be compared, as well as different tools and methods for analysing community diversity, going from typologies to distribution analysis.

Field observation of rural household activities, farms, and farm practices, serves not only to characterize different farming systems, but is informative also regarding the rural livelihoods of which they are part. What do farm and household observations tell us about rural households' dependence on farming, vis-a-vis others source of income, such as off-farm employment and urban remittances? In farming systems analysis, field data are often complemented with modelling, for a more powerful exploration of options feeding into the design of improved system configurations. Hence, you will learn how participatory methods for obtaining and conveying information can be combined with various modelling tools.

Linking farm and field observations on key livelihood indicators (income, food security, nutrition) with wider demographic, socio-economic and agro-ecological trends, we can better understand the historical dynamics of smallholder farming practices, and their changing significance in rural livelihoods systems in sub-Sahara Africa. This then informs the design of pathways towards sustainable development in which flourishing livelihoods are integrated within a healthy environment.

Learning objectives

After the course participants are able to:

  1. Understand farming system functioning and explain the theories underpinning farming systems analysis.
  2. Use simple (participatory) methods for data collection and characterization of farming systems.
  3. Interpret the concept of sustainable rural livelihoods, along with identifying and applying criteria, indicators and methods for its assessment.
  4. Analyse the contribution of agriculture to rural livelihoods and assess farm and farming system performance based on relevant indicators.
  5. Identify entry points, analyse trade-offs and evaluate opportunities for sustainable intensification, using scenario analysis and simple (optimization) models.
  6. Have insight and understanding of a wide range of methods for description and analysis of farming systems.

Course FrequencyOnce every 4 years
LevelPhD candidates, postdocs, and other academics
Intended credits3 ECTS
Course organisationThe C.T. de Wit Graduate School for Production Ecology and Resource Conservation (PE&RC)
More informationCourse website

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