Mapping the dynamic Barotse Floodplain of Zambia
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Transcript of Mapping the dynamic Barotse Floodplain of Zambia
Trade-offs and synergies between sustainable food production and other critical ecosystem services for women and men in the changing and dynamic Barotse Floodplain, ZambiaNatalia Estrada-CarmonaBioversity International
Phot
o: K
rishn
asis
Ghos
h
International Food Policy Research Institute (IFPRI)
Searchinger et al., (2015). High carbon and biodiversity costs from converting Africa’s wet savannahs to cropland. Nature Climate Change, 5(May). doi:10.1038/nclimate2584
Cattle in the floodplain during the dry season
Temporal villages (fisherman)
Reeds to make mats
Cropping with high risk of floods
Fishing
Wildlife habitat
Lealui
Nalitoya
Mapungu
Package of research questions and methods
To what extent do diets meet nutrient requirements of women and children in different seasons?
Food Consumption – CGIAR Research Program on Aquatic Agricultural Systems Value Chain Survey, adults
Check out our recently-published map with the land types http://arcg.is/1Gz92wx
How and why is the landscape used by # groups for their diets?
Does matter where food is produced? Trade-offs?
Materials for construction Habitat for wildlife
Cattle grazing
Fish
Water for agriculture
Droughts/Floods control
Pest control
Mulapo
Sitapa
Land conversion
Mulapo
Exploring options and evaluation of interventions and tradeoffs and synergies
What is the potential of the landscape to improve diets?
What are environmental and economics cost and benefits of different options?
Area (%) Crop or Crop rotation
12 Sorghum61 Eggplant local 0 Watermelon
0
Sweet potato/Tomato/Cabbage/Rape/Groundnuts
1 Cassava/Cowpeas26 Maize/Pumpkin/Rice
How can options go to scale?Learn more: http://bit.ly/BarotseMap
Discussion and take-away messagesOur goal is to find agriculture-nutrition pathways for healthy communities and landscapes through:
• Trade-offs, synergies and scenarios analysis with communities
• Integrating ecosystem services, food systems and nutrition variables in multi-objective landscape and farming models