1. Farming systems analysis in Africa RISING Bernard Vanlauwe - IITA Jeroen Groot - WUR Carl Timler - WUR Lotte Klapwijk – IITA/WUR 28 May 2013 Lilongwe, Malawi

2. Contents Objectives and rationale Steps in the project, timeline Site selection, sample size Project organization, teams, roles Training: Tanzania + Malawi First results

3. Objectives To find options for sustainable intensification and targeted innovations at farm-level – Diagnose current whole-farm performance (RO1) – Explore trade-offs and synergies among ‘services’, or objectives, identifying farm performance gaps – Interactive re-design of farming systems, to close gaps – Inclusive project and stakeholder approach

4. Rationale (1) Based on household surveys, characterizations and previous engagements with farmers … … model-supported diagnosis and exploration of whole-farm options for sustainable intensification … … informing interactive adaptation and learning cycles conducted with farmers and other stakeholders.

5. Rationale (2) A farm-level approach allows to embed proposed and tested innovations Exploration, presentation and discussion of sets of options is needed to: – Analyze trade-offs and synergies (among objectives, etc.) – Support adoption processes by providing choices – Avoid lock-in onto undesirable development paths (= provide pathways out of poverty)

6. Describe Explain Design Explore Structural typology Functional typology Scenarios of change Stakeholder interactions Diagnosis & design phases Inputs and outputs

7. Describe Explain Design Explore Structural typology Functional typology Scenarios of change Drivers Stakeholder interactions Diagnosis & design phases Inputs and outputs

8. Survey Rapid characteriz. Detailed description Exploration innovations Functional typology Structural typology Systems (re)design Extrapolation n=500-1000+ n=50-100 n=10-50 Farm diagnoses Tradeoff analysis Farm innovations Potential impact

9. Supported by farm models Survey Rapid characteriz. Detailed description Exploration innovations Functional typology Structural typology Systems (re)design Scaling out n=500-1000+ n=50-100 n=10-50 Farm diagnoses Tradeoff analysis Farm innovations Impact

10. Exploration of innovations, tradeoffs Natural resources Gross margin Housing Intensive grassland Extensive grassland Maize Wheat Woodland

11. Farm DESIGN Describe Design Explore Explain Validate Groot et al., 2012. Agricultural Systems.

13. Site selection, sample size Tanzania, Malawi – Next growing season: Nov. 2013 – Results by: Sep. 2013 Ghana, Mali – Next growing season: Apr./May 2014 – Results by: Dec. 2013 Samples (dependent on capacity) – Rapid characterization 50-100 – Detailed diagnosis 10-50

14. Milestones, products per stage Rapid characterization  functional typology Detailed description  diagnosis per farm Exploration  T-S and promising options, discussions with farmers a.o. Re-design  implementation and demo plan for farm innovations

15. Timeline

19. Teams and roles National teams (NT’s) – Local recruitment (Number? Capacities?) Data collection, entry, checks Process with farmers Scientific team (ST) – 2 PhD students, 1 per region – 1 post doc researcher Instruct and train NT’s Data analysis typologies Perform modeling (diagnosis and exploration) Scientific supervision (SP) – Wageningen team Support trainings and all activities of ST

20. Training sessions On-farm data collection (ST  NT) Characterization, description (SP  ST) Exploration and re-design (SP  ST)

21. First results Training: April 2013 Tanzania – 2 teams of 4 enumerators – Surveys: 96 in Babati and 80 in Kongwa + Kiketo Malawi – 1 team of 4 enumerators – Surveys: 40 in Dedza and 40 in Ntcheu Sampling: Y-frame

22. Tittonell et al., 2013

23. Survey tool 8 main sheets: – People – Fields – Crops – Animals – Manures – Imports – Tools – Buildings

24. Household size

25. Farm size (acre)

26. To do: Check + clean 256 surveys Collect secondary data Build basic farms in FarmDESIGN Model runs and analysis of results Farm typologies (per country and region) Plan detailed characterization (sample = 10%) Inventory of ‘Innovation-Basket’ Cooperate: talk, meet, discuss, etc. (today) Identify entry-points (later) ….

27. Thanks for your attention!