Post on 17-Jul-2015
Multi-functional assessment of nutrition-sensitive landscapes
Nester Mashingaidze et al.
4 March 2015
Humidtropics
Introduction
• Vulnerable populations are often food insecure
• Food security: – Sufficient calories
– Diverse nutrients
• Sources of food – farm production
– market
– Landscape
• Nutrition-sensitive landscapes – optimise production, NRM and nutrition
Objectives
1. Characterise the current landscape and
determine landscape performance in terms of
production, environmental outcomes and
nutrition.
2. Explore trade-offs and synergies of proposed
interventions at landscape level.
3. Identify and test entry points for improvements
in farming, diets and ecosystem services
provided by the landscape
The case studies
• Western Kenya
– Densely populated (1 044 persons km-2)
– Food crops (maize, beans)
– Cash crops (tea, vegetables)
– Food insecurity, land degradation, poverty
• Northwest Vietnam – Low smallholder agricultural productivity
– Degradation of natural resources
– Low income and access to markets
– Malnutrition
Site selection
1. Review of secondary sources & experts
2. Field visits to 10 sub-locations
- Mambai: tea-based & Masana: maize-based
3. Participatory mapping
4. Transect Walk
Landscapes in Vihiga County
• Mambai landscape - river + ‘forest’
- Impactlite survey to
10 households
• Masana sub-location - circumcision forest
-10 households
surveyed
Preliminary results
• Soil fertility Masana > Mambai
• Majority of land holdings < 0.5 ha
- Some Hhs had fields away from landscape
Mambai (50%) & Masana (30%)
• No major forests, nearby lakes or dams
• Hh size: Masana 5(±2.5) and Mambai 4.5 (±1.4)
Crop production
• Crop species: Mambai slightly > Masana
• Masana: maize > banana > napier
• Mambai: maize > tea > eucalyptus
• Vegetables < 0.04% of cropped area
Food – produced and purchased
• All farms produced food crops
– Beans purchase Masana > Mambai
– Banana purchase low
– Low consumption of traditional vegetables?
Way forward
• Building of farms into FarmDesign on-going
• Farms to be aggregated in LandscapeIMAGES
• Field visits for additional data collection
• Modeling and community feed backs