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Up scaling Africa RISING Interventions using Development domains

Up scaling Africa RISING Interventions using Development domains. Tunrayo Alabi Geospatial Laboratory, IITA. Outline of presentation. Concept of Development Domain Criteria for Development Domain Biophysical & Socioeconomic characteristics Domain map of West Africa

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Up scaling Africa RISING Interventions using Development domains

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  1. Up scaling Africa RISING Interventions using Development domains Tunrayo Alabi Geospatial Laboratory, IITA

  2. Outline of presentation • Concept of Development Domain • Criteria for Development Domain • Biophysical & Socioeconomic characteristics • Domain map of West Africa • Up scaling Research Results

  3. Concept of Development Domain • Development domain is the spatial representation of factors important for agric. development • Characterized using stratification criteria • Reduce complexity by prioritizing criteria based on its influence on production. • Example of simple domain • Agroecological zone • Farming systems map

  4. Farming systems

  5. Why Development domain approach? • Domain helps to dissect/stratify the complex region into geographical units in which similar agricultural problems or opportunities are likely to occur • Where are those geographic areas in which development problems and opportunities are likely to be most similar? • Where else can a successful tested technologies be employed. Where else can we replicate successes (up-scaling research results)

  6. Criteria for Development domains • The following 3 criteria were used • Agricultural Potential • Market access • Population density

  7. Agricultural Potential • Agricultural potential of any location is a strong indicator of its absolute advantage in agricultural production • the extent to which this might actually be realized or its comparative advantage is conditioned by other factors such as market access and population density (Pender et al. 1999). • It is not a static concept but changes over time in response to changing natural conditions (e.g climate change) and human-induced conditions (e.gland degradation )

  8. Length of Growing period • LGP was used to compute agric. Potential • Defined as the no of days in a year when sufficient water is available in the soil profile to support plant growth • It captures the complex interaction of rainfall, PET, temperature , solar radiation and soil properties. • It expresses the distribution of rainfall as well as its availability for crop growth when runoff and PET has been accounted for.

  9. Agricultural Potential Agric. potential • High: (LGP > 180 days ) • Medium: (LGP 90-180 days • Low :(< 90 days)

  10. Market access • Critical for determining the comparative advantage of a given location, given its agricultural potential. • It determines access to inputs and output outlets • e.g, a community with absolute advantage in producing perishable vegetables may have little or no comparative advantage (low profitability) in vegetable production if it is far from roads and markets.

  11. Market access • Computing market access involves travel time based on landuse, roads, places with population > 10,000 • High (< 2 hours); Medium (3-8 hours); Low (> 8 hours)

  12. Population density • Population pressure affects the labor intensity of agriculture by affecting the land/laborratio • Influences innovations in technology • Markets & institutions /investments in agric • Population density is high in the coastal belt of WA • Medium are scattered all over • Low density are more in the northern belt of WA the region

  13. Development Domain 27 Domain units produced LLL : 30% HLM : 11% LLM : 10%

  14. % Development domain WA

  15. Dev. Domain Ghana Africa RISING Intervention sites In Ghana are in 3 regions

  16. Intervention sites in Ghana & Domain 25 sites in Ghana falls within 5 Dev. Domains

  17. HHH Domain similarity Manguli & Sabulungo HHH occurrence Country (%) Ghana 9.8 Nigeria 10.4 West Africa 3.2 Research results from the 2 sites represent about 3.2% of West Africa

  18. HLM Domain similarity Natodori (Upper West) Country (%) Ghana 27.5 Nigeria 8.6 Guinea 49 Cote D’voire 34 West Africa 10.7 … represents about 11% of west Africa and 49 % Guinea, 34 % of Cote d’voire

  19. HLH Domain similarity 8 Sites in Wa West & Nadowli HHH occurrence Country (%) Ghana 10 Nigeria 3.8 Guinea 23.3 Liberia 15 West Africa 4.5

  20. HMH Domain similarity HMH occurrence Country (%) Ghana 4.4 Nigeria 4.9 West Africa 2.6

  21. HMM Domain similarity HMH occurrence Country (%) Ghana 4.4 Nigeria 4.9 West Africa 2.6

  22. Thanks for listening

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