MARGINALIZATION (Different learners in Marginalized Group
A spatial analysis: creating similarity domains for targeted research sites in Zimbabwe. Andries Potgieter
1. A Spatial Analysis:
Creating similarity domains for
targeted research sites in
Zimbabwe
“Overcoming poverty is not a gesture of charity, it is an act of justice”
- Nelson Mandela, 2006
Photos – D Rodriguez
Andries Potgieter and many others
2. Objective
Aim:
This spatial analysis has been commissioned by ACIAR to supply
spatial data layers (including climate, production, market access
and population) to develop similarity domains (on specifically
climate and soil type) for research locations within the agricultural
land-use of Zimbabwe.
- To Enhance the uptake of targeted farming systems technologies
- To Assist funding bodies and policy makers to target those regions that
will have the highest impact from intervention and investment
Risks & Uncertainties:
- Lack of accurate agricultural information across temporal and spatial scales
- Climate variability and change
- Access to markets (input & output)
- Political instability
- High inflation
3. Did you know?
- Area: 39 million ha (the size
of Japan) flanked by RSA,
Botswana, Mozambique and
Zambia
- Population: 13 million
- Agriculture contributes 18%
of GDP
- Despite a 20% increase in
area planted over the last year,
1.68 million people are
currently in need food
assistance (FAO 2011)
NDVI AUC 1999,2000,2001
Inverse colours (blue low, red high)
4. Food Security
Global Food Production
0.35
Global per capita harvested area [ ha person -1]
Global cereal yields [kg ha-1]
3,000
0.25
2,000
1,000
0.15
source: Lui et al & FAO
1960 1970 1980 1990 2000 2010
6. Challenges
Likely impact of climate change on maize yields for Africa
Impact on maize yields by 2050 - Percent loss relative to 1990 (Schlenker and
Lobell, 2009)
8. Data
• CLIMATE: Worldclim 1.4 database (http://www.worldclim.org/current)
(Hijmans, Cameron et al. 2005)
• SOIL: The SOTER soil database (Batjes 2004)
• POPULATION: Population 2000 & 2005: SEDAC
(http://sedac.ciesin.columbia.edu/gpw/global.jsp)
• MARKET ACCESS: Cost distance grid for population greater than
10,000 (Kai Sonder and Gomez 2010)
• LAND USE: Global land cover - GLC2000
(http://bioval.jrc.ec.europa.eu/products/glc2000/products.php)
• CROP DISTRIBUTION: Gridded crop distributions
(http://harvestchoice.org:8080/geonetwork/srv/en/main.home)
• AGRICULTURAL POTENTIAL: Simulated maize yields (DSAT) from
Jawoo Koo (IFPRI, http://harvestchoice.org)
9. Approach
- Criteria for scaling out of locations to domains are (provided by CIMMYT):
- Growing season rainfall (GSR) November to March (summer)
- +/- 100mm precipitation in summer,
- +/- 2o max temp (summer),
- +/- 2o min temp (summer),
- Soils: select similar soil classes of maximum rooting depth and soil
texture to each location
- Agricultural potential
Simulated maize yields were generated using difference between Low
Technology inputs (LI) (manure, manual labour etc.) and High Technology inputs
(HI) (fertiliser, machinery etc.)
- Overlaying of Climate and Soil layers where used to create the similarity domains
while other data inputs where aggregated within each domain
10. Natural regions
Final Site Locations
- 3 sites moderate to high
- 1 site moderate
- 2 sites low
NRs II and III account for around 84% of
total maize production (FAO 2006)
16. Agricultural Potential
Low input (manure, manual labour etc.) High input (fertiliser, machinery etc.)
• Currently actual 3-year avg DOMAIN yield < 1.75 t/ha (FAO)
• Potential Yield Gap remains high across all regions
However, farmers who applied good management e.g. buying and applying seeds and fertiliser in
time, weeding and have access to hire machinery can get yields of more than 3 tonnes/ha (national
average ~0.58 tonnes/ha) as was the case in parts of Mashonaland West during the 2002/2003
season (FAO 2003).
17. Summary
Successfully extracted similarity domains for six locations/sites in Zimbabwe.
Most domains showed a relatively low average (~4 hours) travelling time to the
nearest market hub compared to the remainder of the country.
However, during some years farmers will need to travel even further to acquire
seed and fertiliser, which can constrain their management ability and thus leading to
much lower yield than what is achievable.
Yield Gap between what is currently achieved and what potentially can be achieved
remains high.
Identified spatial regions that will benefit the most from extrapolating targeted
farming systems technologies from the selected research locations and thus have
the highest impact from intervention and investment.
Participatory research targeting integrated farming systems is necessary to
determine more site specific and best fitted crop production risk and management
practices for especially maize-legume systems as is currently being undertaken
through the SIMLESA ACAIR funded project.