Organizational Context
Smallholder agriculture in sub-Saharan Africa provides basis of rural livelihoods and food
security, yet farmers have to cope with land constraints, variable rainfall and unstable
institutional support. This study integrates a diversity of approaches (household typology and
understanding of farm trajectories, on-farm trials, participatory ex-ante trade-off analysis) to
design innovative farming systems to confront these challenges. We explored farm trajectories
during two decades (1994 to 2010) in the Koutiala district in southern Mali, an area experiencing
the land constraints that exert pressure in many other parts of sub-Saharan Africa. We classified
farms into four types differing in land and labour productivity and food self-sufficiency status.
During the past two decades, 17% of the farms stepped up to a farm type with greater
productivity, while 70% of the farms remained in the same type, and only 13% of the farms
experienced deteriorating farming conditions. Crop yields did not change significantly over time
for any farm type and labour productivity decreased. Together with 132 farmers in the Koutiala
district, we tested a range of options for sustainable intensification, including intensification of
cereal (maize and sorghum) and legume (groundnut, soyabean and cowpea) sole crops and
cereal-legume intercropping over three years and cropping seasons (2012-2014) through onfarm
trials. Experiments were located across three soil types that farmers identified – namely
black, sandy and gravelly soils. Enhanced agronomic performance was achieved when targeting
legumes to a given soil type and/or place in the rotation: the biomass production of the cowpea
fodder variety was doubled on black soils compared with gravelly soils and the additive
maize/cowpea intercropping option after cotton or maize resulted in no maize grain penalty, and
1.38 t ha−1 more cowpea fodder production compared with sole maize. Farm systems were redesigned
together with the farmers involved in the trials. A cyclical learning model combining
the on-farm testing and participatory ex-ante analysis was used during four years (2012-2015).
In the first cycle of 2012-2014, farmers were disappointed by the results of the ex-ante trade-off
analysis, i.e marginal improvement in gross margin when replacing sorghum with soybean and
food self-sufficiency trade-offs when intercropping maize with cowpea. In a second cycle in
2014-2015 the farm systems were re-designed using the niche-specific (soil type/previous crop
combinations) information on yield and gross margin, which solved the concerns voiced by
farmers during the first cycle. Farmers highlighted the saliency of the niches and the re-designed
farm systems that increased farm gross margin by 9 to 29% (depending on farm type and
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options considered) without compromising food self-sufficiency. The involvement of farmers in
the co-learning cycles allowed establishment of legitimate, credible and salient farm
reconfiguration guidelines that could be scaled-out to other communities within the “old cotton
basin”. Five medium-term contrasting socio-economic scenarios were built towards the year
2027, including hypothetical trends in policy interventions and change towards agricultural
intensification. A simulation framework was built to account for household demographic
dynamics and crop/livestock production variability. In the current situation, 45% of the 99
households of the study village were food self-sufficient and above the 1.25 US$ day-1 poverty
line. Without change in farmer practices and additional policy intervention, only 16% of the
farms would be both food self-sufficient and above the poverty line in 2027. In the case of
diversification with legumes combined with intensification of livestock production and support
to the milk sector, 27% of farms would be food self-sufficient and above the poverty line.
Additional broader policy interventions to favour out-migration would be needed to lift 69% of
the farms out of poverty. Other additional subsidies to favour yield gap narrowing of the main
crops would lift 92% of the farm population out of poverty. Whilst sustainable intensification of
farming clearly has a key role to play in ensuring food self-sufficiency, and is of great interest to
local farmers, in the face of increasing population pressure other approaches are required to
address rural poverty. These require strategic and multi-sectoral approaches that address
employment within and beyond agriculture, in both rural and urban areas.
Roles
Katrien Descheemaeker (daily supervisor PhD research)
Gatien Falconnier
AMEDD Mali
ICRISAT Bamko/Mali
Gatien Falconnier
Short and long term storage
All data will be stored on my local harddisk in a folder called Thesis.
Within this Thesis folder, I'll create per chapter the folders: Data, Model, Paper and Scripts. The Data folder has two sub-folders called: Raw and Processed.
Folder contents:
- Data - Raw sub-folder: Contains all raw data and meta-data (a description of your data).
- Data - Processed sub-folder: Contains all processed data.
- Model folder: Complete listing of the model and the model results & analysis.
- Paper folder: Text of a chapter / paper.
- Scripts folder: Contains all scripts used.
The complete content of my local Thesis folder will be stored on the backup server of PPS.
During periods I'm abroad, I'll backup the complete content of my local Thesis folder to a Dropbox Thesis folder and share the contents with my supervisor(s).
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Sharing and Ownership
I will upload the data available
The data will be uploaded
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IER owns the database on household monitoring (Chapter 2 of the thesis). The dataset should only be shared with WUR and Icrisat members
Thomas Alexander Van Mourik
Katrien Descheemaeker
Ken Giller
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