TEMPORAL TRENDS IN KENYAN SMALLHOLDER SETTLEMENT...
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TEMPORAL TRENDS IN KENYAN SMALLHOLDER SETTLEMENT SCHEME ALLOCATION (1962 – 2015)
Nina Mauney, John Scrivani, Kimberley BrowneDepartment of Geography and the Environment, University of Richmond, Richmond, VA
INTRODUCTION
OBJECTIVES• Determine temporal trends in settlement scheme properties such as:
o Smallholder plot size
o Allocated land characteristics
DATA & METHODOLOGY
Settlement Scheme Data:
Approximately 1,500 individual paper
maps were collected, catalogued,
georeferenced, and used to digitize the
boundaries of 350 smallholder settlement
schemes.
The polygons were then joined to
allocation data (Lukalo and Odari, 2016).
For this study, we examined the 143
known settlement schemes in the former
Rift Valley province of Kenya.
RESULTS
DISCUSSIONAllocated land characteristics: Aridity of allocated land tended to increase over time (Figures
1, 2, and 3). While earlier schemes were characterized by wet/moist bioclimate, there was an
increase in allocation of semi-dry land in later schemes.
Allocated land in 2009 was predominantly cropland (Figure 3). This reflects settlement and
cultivation by smallholders. In later settlement schemes, we see increases in allocated grassland
and forested land cover types.
Smallholder plot size: The average individual’s allocated plot in a settlement scheme tended to
decline in area over time in the former Rift Valley province (Figure 4). In addition to this region,
this trend was also prevalent throughout government-allocated smallholdings across Kenya.
REFERENCES
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Warm Semi-Dry Warm Moist Warm Wet
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Wet Cropland Wet Forest Wet Grassland Wet Swampy
Moist Cropland Moist Forest Moist Grassland Moist Swampy
Semi-Dry Cropland Semi-Dry Forest Semi-Dry Grassland Surface Water
Artificial/Urban
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Settlement schemes are government-allocated plots of land transferred from colonial
Europeans to Kenyan smallholders. The creation of smallholder settlement schemes played a
critical role in the postcolonial development of Kenya (Boone, 2011). Initially designed to
reallocate land from colonial powers to landless and unemployed Kenyans post-independence
(Boone, 2011; Leo, 1978), settlement schemes later became a highly contested issue as land
has become scarce.
This study focused on settlement schemes in the former Rift Valley province of Kenya,
specifically in the counties of Baringo, Bomet, Bungoma, Kakamega, Kericho, Laikipia,
Nakuru, Nandi, Trans Nzoia, and Uasin Gishu. In this region, the primary agricultural
products are maize, wheat, barley, oats, sisal, and livestock such as dairy cattle, sheep, pigs,
and poultry (Morgan, 1963).
Boone, C. (2011). Politically Allocated Land Rights and the Geography of Electoral Violence: The Case of Kenya in the 1990s. Comparative Political Studies, 44(10), 1311–1342.
Leo, C. (1978). The Failure of the “Progressive Farmer” in Kenya’s Million-Acre Settlement Scheme. The Journal of Modern African Studies, 16(4), 619–638.
Lukalo, F. K. & Odari, S. (2016). Exploring the status of settlement schemes in Kenya, NLC working paper series. National Land Commission, Nairobi.
Morgan, W. T. W. (1963). The “White Highlands” of Kenya. The Geographical Journal, 129(2), 140–155.
Sayre, R., Dangermond, J., Frye, C., Vaughan, R., Aniello, P., Breyer, S. P., … Comer, P. (2014). A new map of global ecological land units—An ecophysiographic stratification
approach. Retrieved from http://pubs.er.usgs.gov/publication/70187380
Analysis:
The average plot size of each settlement scheme was determined by dividing the polygon area
(GIS-derived) by the number of settler families (reported by Lukalo & Odari, 2016).
Ecological Land Unit data were reclassified to separate bioclimate, landform, lithology, and
land cover. Area in each class was tabulated and exported by settlement scheme.
Ecological Land Unit Data:(250 meter resolution is adequate for scale of our study)
Areas of “distinct bioclimate, landform,
lithology, and land cover” (Sayre et al., 2014).
• Bioclimate: interpolated from 50-year
averaged precip. and temp. data
• Landform: derived from DEM data
• Lithology: describe rock properties,
including unconsolidated sediments
• Land Cover: vegetative response to physical
environment, from GlobCover 2009 land
cover dataset
This research project is conducted in partnership between Dr. Fibian Lukalo of Kenya’s National Land
Commission, Prof. Catherine Boone of the London School of Economics (funded by UK Economic and
Social Research Council Grant # ES/R005753/1 'Spatial Dynamics in African Political Economy' under
Kenya NACOSTI Research Permits # NACOSTI/P/16/48539/13282 and /24668), and Professors
Kimberley Browne and Sandra Joireman at the University of Richmond. The data and maps have been
prepared for the purposes of academic and policy research; boundaries are estimates and not intended for
official use. Users outside the NLC should cite this work as F. Lukalo, C. Boone, K. Browne, and S. Joireman,
"Kenya Settlement Schemes Data Project,” Nairobi, London and Richmond: NLC, LSE, and UR, 2019.”
Lithology (Rows) 1. Unconsolidated Sediment
2. Carbonate Sedimentary
3. Mixed Sedimentary Rock
4. Non-Carbonate
Sedimentary
5. Evaporite
6. Pyroclastics
7. Metamorphic Rock
8. Acidic Volcanics
9. Acidic Plutonics
10. Non-Acidic Volcanics
11. Non-Acidic Plutonics
Land Cover (Columns)A. Bare Area
B. Sparse Vegetation
C. Grassland, Shrub, or Scrub
D. Mostly Cropland
E. Mostly Deciduous Forest
F. Mostly Needleleaf/Evergreen Forest
G. Swampy or Often Flooded
Figure 1: Ecological Land Units (Sayre et al., 2014) in Kenyan Rift Valley settlement schemes of (a) Laikipia, (b) Nakuru, (c) Uasin Gishu, and (d) Trans Nzoia Counties.
Figure 2: Rift Valley Settlement Scheme Bioclimates over time
Figure 3: Rift Valley Settlement Scheme land cover and aridity over time.
Figure 4: Rift Valley Settlement Scheme average plot size over time.
Map Legend (Sayre et al., 2014)