big data from small farms
DESCRIPTION
Presented by Mark van Wijk, Romain Frelat, Randall Ritzema and Sabine Douxchamps at the ILRI@40 Livestock and Environment workshop, Addis Ababa, 7 November 2014TRANSCRIPT
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Big data from small farms
Mark van Wijk, Romain Frelat, Randall Ritzema and Sabine Douxchamps
ILRI@40 Livestock and Environment workshopAddis Ababa, 7 November 2014
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- Finding structure in variability in farming systems
- Understanding of systems functioning
- Targeting of interventions
Farming systems analysis and HH modeling for:
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However…
We did not deliver on the targeting promised:What works where for which farmer?
Typically we got stuck in in-depth site specific studies
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Here…
1. Ongoing work 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
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A key decision:
Go simple!!
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From food self-sufficiency towards food security
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Keep the analysis simple enough to be able to apply it across HH
characterization data collected in different surveys!
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
Food available
Consumed
Consumed
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
Cash available
Food available
Consumed
Consumed
Sold
Sold
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
Cash available
Food available
Buy staple crop
Expenses
Consumed
Consumed
Sold
Sold
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
Cash available
Food available
Food need
Buy staple crop
Expenses
Household size and composition
Consumed
Consumed
Sold
Sold
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Food crops produced
Cash crops produced
Livestock products produced
Off farm income
Cash available
Food available
Food need
Buy staple crop
Expenses
Household size and composition
Consumed
Consumed
Sold
SoldFood security ratio
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Lushoto, Tanzania (CCAFS)
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Rapid intervention analyses
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First findings:
Agricultural based interventions will not get the poorest 20-60% of the smallholder farmers food secure
Alleviation of problems! Goats are an important entry point
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First findings:
The upper 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
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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
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Ongoing activities
1. Expand the database (also CA and SEA)
3. Adapt and apply mini-survey, on tablet
2. Test results (both the big FS numbers, but also with farmers in field)
4. Super cheap survey instrument that is directly linked to an analysis framework: produce rapid results!
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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’
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Targeting
Can we identify 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?
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Generate bottom up based information to improve large scale impact assessment
exercises
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Look at changing livelihoods: from that perspective add to the land expansion / intensification – land sharing / sparing
debates
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Thanks!!