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Big data from small farms
The document discusses the challenges and ongoing efforts to analyze and improve food security among smallholder farmers, emphasizing the importance of employing simple, cross-dataset analyses. It highlights initial findings suggesting that agricultural interventions may not adequately secure food for the poorest farmers, while noting that certain interventions can benefit medium and high population density areas. Ongoing activities aim to expand data collection, implement gender components, and develop a more sophisticated household model to identify effective strategies across various socio-economic scenarios.
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Big data from small farms
- 1. Big data fromsmall farms Mark van Wijk, Romain Frelat, Randall Ritzema and Sabine Douxchamps ILRI@40 Livestock and Environment workshop Addis Ababa, 7 November 2014
- 2. Farming systems analysisand HH modeling for: - Finding structure in variability in farming systems - Understanding of systems functioning - Targeting of interventions
- 3. However… Typically wegot stuck in in-depth site specific studies We did not deliver on the targeting promised: What works where for which farmer?
- 4. Here… 1. Ongoingwork on bringing together HH level characterization data 2. Present a simple analysis of farm household level food security that can be used across many datasets
- 5. A key decision: Go simple!!
- 6. From food self-sufficiencytowards food security
- 7. Keep the analysissimple enough to be able to apply it across HH characterization data collected in different surveys!
- 8. Food crops produced Cash crops produced Off farm income Livestock products produced
- 9. Food crops produced Cash crops produced Off farm income Livestock products produced Food available Consumed Consumed
- 10. Food crops produced Cash crops produced Off farm income Livestock products produced Cash available Food available Consumed Consumed Sold Sold
- 11. Food crops produced Cash crops produced Off farm income Livestock products produced Cash available Food available Consumed Buy staple crop Expenses Consumed Sold Sold
- 12. Food crops produced Cash crops produced Off farm income Livestock products produced Cash available Food available Food need Buy staple crop Expenses Household size and composition Consumed Consumed Sold Sold
- 13. Food crops produced Cash crops produced Off farm income Livestock products produced Cash available Food available Food need Buy staple crop Expenses Household size and composition Consumed Consumed Sold Sold Food security ratio
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- 17. First findings: Agriculturalbased interventions will not get the poorest 20-60% of the smallholder farmers food secure Alleviation of problems! Goats are an important entry point
- 18. First findings: Theupper 20 – 50% is intensifying, and linking up to markets In mixed crop-livestock systems this group owns cattle: interventions focusing on cattle productivity address poverty but not so much food security
- 19. First findings: 20– 60% of the farmers: agricultural interventions can make a difference for getting farmers more food secure In high population density areas with small farm sizes: crop interventions can make this difference In medium / low population density areas both livestock and crop intervention can make this difference: production/availability of enough fodder resources
- 20. Ongoing activities 1.Expand the database (also CA and SEA) 2. Test results (both the big FS numbers, but also with farmers in field) 3. Adapt and apply mini-survey, on tablet 4. Super cheap survey instrument that is directly linked to an analysis framework: produce rapid results!
- 21. Ongoing activities 5.Implement gender component 6. With the mini-survey we fill gaps in the database, but also set up some permanent monitoring sites 7. For more in-depth analyses: use existing tools, but also develop an ‘intermediate complexity HH model’
- 22. Targeting Can weidentify robust interventions that cut across systems and socio-economic scenarios? (what works where for which group of farmers) Can we upscale the strategies to quantify investment needs in interventions?
- 23. Generate bottom upbased information to improve large scale impact assessment exercises
- 24. Look at changinglivelihoods: from that perspective add to the land expansion / intensification – land sharing / sparing debates
- 25.