Low External Input Strategies for Sustainable Small-Scale
Farming in Kenya: A Systems Dynamic Approach
Yengoh, G. Tambang. & Svensson, M.G.E.
Lund University Centre for Sustainability Studies, LUCSUS, Lund University,
PO Box 170, SE-221 00 Lund, Sweden (+46-46-2220513/+46-46-2220475)
yengoh.genesis@lucsus.lu.se, mats.svensson@lucsus.lu.se
The 26th International Conference of The System Dynamics Society
July 20 - 24, 2008 Athens, Greece
ABSTRACT
This study sets out to assess the significance of the implementation of low extemal input
strategies on small-scale farming households in rural Kenya. Data collected on two surveys
was used to develop a conceptual model of the system and establish links between different
internal components within it. This enabled relationships to be made between changes in
soil nitrogen (a limiting physical factor to agriculture) and household incomes (a socio-
economic attribute). A system dynamic model was developed and used to test the influence
of low extemal input strategies on small-scale farming under different scenarios. It is found
that adopting low external input strategies or optimizing its practice could create several
positive reinforcing feedback effects on small-scale Kenyan agriculture. It is also found that
food crop cultivation is more sustainable in terms of net annual soil nitrogen balance than
cash crop cultivation.
INTRODUCTION
It has been recognized that agricultural production in Kenya East A frica is characterized by
a negative nutrient balance (Roy et al, 2003; De Jager et al, 1998). The situation in Kenya
is only a microcosm of what is happening in Africa as a whole. According to Sanchez
(2002) Africa’s food insecurity is directly related to insufficient food production (not a
crisis of distribution or lack of purchasing power as is the case in other parts of the
developing world). Insufficiency of food production can be associated to two main causes:
declining soil fertility and the problems of crop pests, weeds and diseases.
With regard to the problem of declining soil fertility, it has been estimated that the average
annual rate of depletion of essential soil nutrients in Africa stands at 22kg of nitrogen,
2.5kg of phosphorus, and 15kg of potassium per hectare of cultivated land (Sanchez, 2002).
The most common way of addressing this problem is through the use of mineral fertilizers.
However as Sanchez (2002) and Ruben and Lee (2000) point out, small scale African
farming households lack the financial resources to procure these fertilizers which are much
more expensive in A frica than in North America, Europe or Asia. The second cause relates
to problems associated with pests, weeds and diseases. Weed infestation, disease outbreaks
and attack of food crops by pests have become more frequent (Oswald et al., 1996) with a
fall in agro diversity and climate change. As is the case with chemical fertilizers, farmers
lack the financial and technical resources needed to cope with this problem.
Given the limited financial resources farmers have for meeting the above challenges,
government agencies, international and national non-governmental organizations have been
looking into ways of overcoming these hurdles to agricultural productivity using local
resources and technologies that demand minimum financial investments (Manyong et al.,
1
1997; Giller and Cadisch, 1995; Reinjtjes et al., 1992). To be successful, such strategies
must meet two objectives: i) ameliorate the extent to which farmers can improve food
production and raise income with low-cost, locally-available technologies and inputs, and
ii) obtain this in an environmentally sustainable manner (Ruben and Lee, 2000). A number
of strategies have been developed and have undergone different levels of trials and tests
with varying degrees of success. Some of these have been applied at varying scales in
tropical agriculture with varying results: Y oung (1998), Palm (1995), and Cooper et al.
(1996) present some results of agroforestry trials; Kwesiga and Coe (1994) present
outcomes of short-term rotation with sesbania (Sesbania sesban); Gan et al. (2003) and
Sullivan (2003) present the outcomes of intercropping.
Many studies have explored the place and role of different input optimization strategies in
tropical agriculture. Some have focused on the role these strategies can play in improving
particular aspects of soil processes like nutrient cycling (Kapkiyai, 1996; Brouwer and
Powell, 1995; Giller and Cadisch, 1995). Others have investigated the impact of these
technologies on soil fertility generally and hence the potential for increasing yields through
them (Woomer and Swift., 1997; Probert et al., 1995; Reinjtjes et al., 1992; Bationo and
Mokwunye, 1991). Some still, have looked at the impact of the adoption of these
technologies on the economics of rural farming livelihoods (Molua, 2005; Shepherd, and
Soule, 1998); It has been found that it is possible and practicable to optimize the use of
nutrients in tropical agriculture through the use of affordable agronomic technologies like
agro-forestry, intercropping and crop rotation (Reinjtjes et al. (1992). Most of these studies
have limited the scope of their analysis on the adoption and use of only one out of the many
agronomic technological options available. While this brings simplicity to the
understanding of how individual technologies can help (or in the case of field trials, have
helped) in improving agriculture, it is quite limiting in its representation of reality in
tropical agriculture. One of the main features of agriculture in sub-Saharan Africa is the
fact that there is a mixture of techniques and cultivated crops principally to serve as a bet-
hedging strategy (Binswanger and McIntire, 1987). Hence one will likely find the practice
of intercropping being associated with crop rotation, fallowing, some form of agro-forestry,
and some livestock rearing or other practices.
There is therefore, need to examine the entire process of incorporation of agronomic
technologies into tropical agriculture as a system with a much more holistic picture. For
this reason, the agronomic technologies under consideration in this study will be
agroforestry, crop rotation and intercropping. They will otherwise be collectively called
low external input strategies (below called LEIS). Furthermore, while giving priority to soil
fertility, the research agenda has given limited attention to human and sociological aspects
of the adoption of innovative agronomic technologies (Nair, 1997). Hence aspects such as
the costs and benefits of adopting different technologies, issues of access to and up-scaling
innovations, and the role of adopting innovations on the socioeconomic situation of
households has received limited attention. A few studies have made attempts at
understanding the processes of decision-making that lead to the adoption of innovative
agronomic technologies (Franzel et al., 2003; Manyong et al., 1997)
OB) ECTIVES
This study set out to use a model of Kenya’s small-scale farming household in assessing the
significance low external input strategies could play in small-scale farming systems in rural
Kenya. This goal can be broken down to two objectives:
1. Examine the feasibility of incorporating and or optimizing the benefits of LEIS in small-
scale farming systems in rural Kenya.
2. Assess the extent to which the incorporation of such practices could affect the soil
nitrogen and socioeconomic situation of farming households and thus the sustainability of
small-scale farms.
SCOPE AND LIMITATIONS
The socioeconomic context of farming households involves complex processes of income
acquisition and expenditure (Ellis, 1998a; 1998b; and 1991; Dose, 1997). This study will
limit its analysis to household income as an indicator of the socioeconomic situation of
farming households. Within this context, inputs to household income and expenditures
from it will be limited to income from, and expenditures to the agricultural activities. In the
same light, farming practices involve complex interactions with the physical landscape. The
outcome is a complex modification of the physical environment (Houghton, 1994). The
study will limit its analysis to the effects of different agronomic practices on soil nitrogen
(an indicator of the physical environment) and household income (an indicator of the
socioeconomic situation of farming households). The unit of focus will be the individual
small-scale farming household because it is the level at which land use and management
decisions are taken (Tschakert, 2003; Golan, 1990). There is a short-term time limitation to
the data collected and the analysis made of it. However, the model developed in this study
could be used to forecast long-term trends.
MATERIALS AND METHODS
Data Collection in Case Study
Mumias is a district in the Western Province of Kenya with a size of 3606km’; average
annual precipitation of 960mm; and annual average temperature of 20°C. According to
Dose (1997), the population pressure on land resources in this district is high with as much
as 76% of its land area under cultivation by small-scale farmers. Nyandarua on the other
hand is located in the central province of Kenya. With a size of 3260km’, this district in the
Kenyan Highlands has generally cooler temperatures 15°C; and lower precipitation 960mm
(IWMI, 2008). The choice of Mumias and Nyandarua as case study sites for this study was
made principally because they have been well established as research sites. It follows that,
significant social networks have been created which could assist in gathering data. The
socioeconomic contexts of most of its residents also provide most of the data desired by
this study.
Data for this study was collected in a two-phase cross-sectional survey carried out in 2006
and 2007. To get an objective and representative survey, the services of agricultural field
extension workers were used. Backed by a knowledge of farmers’ land holding status;
cropping patterns; attitude towards information sharing; willingness to participate in
surveys; and other such attributes, field extension workers identified farmers who would be
interviewed. Questionnaires used for the collection of data in the 2007 survey were
designed using among other things, the experience of the 2006 fieldwork. Through deep,
semi-structured interviews information on farm household types, farm operations, financial
flows, investments, as well as nutrient management was collected. Some data was gathered
through farm walks and group interaction with farmers and farmers’ groups (Y in, 2003).
Tools and Approaches
Data obtained through the two surveys was complemented by published secondary data at
district, regional and national level on Kenya. Tools of systems analysis were also used for
the study. They include causal loop diagramming, feedback loop analysis and model
simulation using STELLA software Version 9.0.1. The choice of systems analysis as an
approach for this study is grounded in the justification given by Tschakert (2003, pp. 19).
This author holds that systems analysis is a method that has proven to be “helpful in
proceeding from a conceptual systems understanding of household resource allocation to a
dynamic systems model”. This view is supported by Shepherd and Soule (1998) who see
the importance of systems analysis as a tool for ex-ante assessments of complex natural
resource management practices over long time scales.
Model Description
To benefit from the whole perspective offered by the systems approach, four crops and four
livestock types were combined into a model. This method of integration is partly inspired
by Ellis, (1998a; 1998b), who saw the mean household income portfolio of most small-
scale tropical farmers to be made up of resources from livestock, food crops, off-farm
income and cash crops. The four crops include two food crops (potatoes and maize) and
two cash crops (sugarcane and sugar beet). The food crops were chosen on the basis of their
being widely cultivated in the study area (Table 1 shows the different crop parameters used
in the model). While sugarcane is the main cash crop in Mumias, sugar beets are chosen
because they are the main competing cash crop to sugarcane, though yet not well
established. Their cultivation is presently under trial in both study areas.
Table 1 Parameter Table for Crop Sub-Model
— Parameter Description, | Valueand Units —_|
Crop yields per hectare“ Maize 1.6 tons/ha
Potatoes 15.4 tons/ha
Sugar beets 55 tons/ha
Sugarcane 75 tons/ha
Economic costs of Labour costs
production * Fertilizer costs Kenyan Shillings/hectare
Seed costs
Pesticide/Herbicide costs
Biophysical factors of Rainfall
production * Soil type 5-class fertility scale
Crop residues” Residues tons residues/ton yield
Nutrient (nitrogen) Maize grains 16.8 kg/ton
content of harvested crops Maize residues 9.7 kg/ton
and residues © Potatoes 4.4 kg/ton
Potato residues 2.3 kg/ton
Sugarcane 0.6 kg/ton
Sugarcane residues 0.3 kg/ton
Sugar beets 4 kg/ton
Beet residues 1.5 kg/ton
Questionnaires
Source: *=and b Ministry of Agriculture K enya (2003; 2004; 2005); ® = Acland (1986); ° =FAO (2004); =
Four dominant livestock types kept by Kenyan small-scale farmers (cattle, goats, sheep and
chicken) are used. Parameters used in the livestock sub-model are listed in Table 2. The
reason for integrating four livestock types to food crops is because it is the minimum for
achieving a balance between complexity and simplicity while still capturing the reality in
tural Kenya’s small-scale farming households. To complete the model, two other sub-
systems are added - the nutrients and household economy sub-systems (Figure 1 and Figure
3 respectively).
Table 2 Parameter Table for Livestock Sub-Model
Parameter Description, Value and Units |
Value and Units
Livestock production Milk production Liters/animal/year
* and? Cost prices Kenyan Shillings/animal
Birth & death rates Varies
Economic costs of Labour costs
production * Feeding costs Kenyan Shillings/animal
Medical costs
Manure production* —_ Manure per animal tons/animal/year
Nutrient content of Cattle dung 0.30%
manure © Goat/sheep dung 0.65%
Chicken manure 2.8%
Source: * Ministry of Agriculture Kenya (2003; 2004; 2005); = Questionnaires; °= Roy et al 2006
The main characteristics of small-scale rural farming households in Kenya that the model
design intends to include: the production of several crops at a time; the rearing of small
numbers of animals alongside crop production; carrying out farm operations on generally
small holdings with relatively poor but varying levels of fertility; the limited use of
chemical fertilizers and other agricultural inputs; heavy reliance on family labour with the
employment of outside labour only if household labour is insufficient; and where
household consumption needs overrides cash profit maximization (Shepherd and
Soule,1998; De Jager et al, 1998; Dose, 1997; Oswald et al 1996; Probert et al., 1995;
Binswanger, and McIntire, 1987).
To decide the timescale over which the model would be run, a compromise had to be made
between: the length of time small-scale farmers may need to justify their economic
decisions; and the time it could take to observe meaningful biophysical changes on farms
after the implementation of a change in an agricultural practice. From deep interviews, on
the field, it was evident that small-scale farmers generally make plans for no longer than
five years ahead. The physical environment on the other hand responds much more slowly
to subtle stimuli like changes in agricultural patterns. Response times could range from a
few decades to hundreds of years. A length of simulation of 30 years was therefore chosen
as a rough compromise between these two extremes.
Crop Income from
Production Crop
ry
Land size Household
Income
Livestock Income from
Production Livestock
Figure 1 Stock-and-Flow Diagram of the Household Income Sub-System
Plant sub-systems consist of biophysical crop growth determinants (soil type and rainfall);
economic inputs in crop production (cost of fertilizers, seeds, labour, pesticides, etc); a
computation of crop losses that may be incurred during harvesting, transportation and
storage; income from crop sales; and the accumulation of residues from crop harvest (see
Table 1). Soils have been divided into five classes - very clay; clay; loam; sandy; and very
sandy. The response of crops to precipitation was based on rainfall data from IWMI (2008)
and crop response factors to water stress based on Acland (1986).
Livestock sub-systems consists of three main sectors (Table 2): animal production (young
animals, eggs, milk, etc); economic costs of production (expenditures incurred in labour,
supplementary feed, medical care and others); and livestock income (from the sales of
animals and associated products). In livestock sub-systems (as with plant sub-systems),
income from these activities is the main driver of the household decision to engage in
production (Figure 1).
Atmospheric Gaseous
Deposition [~] >| Losses
Fertilizers =| Runoff &
| Erosion
Riolocical L,| Soil Nutrient
iological Pool | A
Fixation | >| Leaching
Livestock Crop
Manure [| | Harvesting
Green Organic Residue
Wastes _ >| Removal
Figure 2 Structure of the Nitrogen Sub-System
The nutrients sub-system computes nutrient (nitrogen) balances in the system at farm scale.
The main reason for using nitrogen as a proxy for the soil fertility is because nitrogen has
been identified as being the most limiting nutrient in small-scale agricultural productivity in
Kenya (Shepherd, and Soule, 1998; Smaling et al, 1997; Stoorvogel, and Smaling, 1990).
In this sub-system, inputs and outputs of nutrients are balanced from natural and
anthropogenic processes as shown in Figure 2.
RESULTS
The Small-Scale Farming System in Kenya (Business as Usual Scenario)
Limited household income constitutes a hindrance to increased crop and livestock
production in small-scale farming households in rural Kenya. The fact that low external
input practices are not optimized means that farmers have to depend on chemical fertilizers
to increase crop yields. They also have to depend on herding or the purchase of forage to
increase livestock production. The fact that this category of farmers has small incomes
limits growth of agricultural productivity which in turn limits growth in household income.
This is the scenario presented in Figure 3.
Crop waste as =
gis
Crop production
; Figg
livestock
Manure as Gs
Purchase of, ~~
fertilizer eS Ani) Household’ income @s ee OP Byeeition
SS ee
Figure 3 Constraints of Fertilizer and Purchased
Forage on the Growth of Household Income
In Figure 3 R1 represents increases in crop production that should be expected if access to
chemical fertilizers was not a constraint; B1 represents constraints imposed by limited
household income on the use of chemical fertilizers. R2 represents increase in livestock
production that could be obtained if access to fodder were not limited by household
income; B2 represents the constraint imposed by limited household income on access to
fodder. R3 represents the mutual relationships between the two sub-systems of agricultural
productivity in rural Kenya. This relationship is built on the fact that in the face of limited
household income, farmers tend to depend on manure for soil fertilization and on crop
wastes for animal feed. Since increases in crop production and access to bought fodder are
limited by household income, animal feed is limited and livestock production cannot grow.
A stagnation in livestock production means manure for fertilizing the soil is limited and so
crop production cannot be ameliorated. The challenge of sustainable agriculture is among
other things to, strike a balance between soil conservation (environmental protection) and
economic profitability (Buresh and Tian, 1997; Cooper et al., 1996; Young, 1989; Carsky
et al, 1999; Kwesiga and Coe, 1994).
Minimizing the Fertilizer-Dependent Cycle
The need to face up to the challenge of limited economic resources to ameliorate the
conditions of low soil fertility in tropical regions has called for much attention in recent soil
management research Ruben and Heerink (1995).
Rotational Intercropping
Crop rotation moves agriculture from a simple monoculture to a complex system of
diversification, and in the process, breaks cycles of weed and pest infestations while
providing supplementary fertilization to crops (Dima and Odero, 1997; Sullivan, 2003).
Recent research on crop rotation has laid emphasis on estimating the amount of inorganic
nitrogen that may be “required following a non-legume crop to produce another non-
legume crop with an equivalent yield to that obtained following a legume” (Wani et al.
1995). This gives a quantitative estimate of the contribution of a leguminous crop to the
nitrogen requirements of a non-leguminous crop that precedes it and is termed differently
by different authors as “fertilizer N replacement value” (Carsky et al., 1999), and “N
residual effect” (Gan et al., 2003). These values have been computed for certain crops and
stands as evidence to the fact that soil nitrogen conditions can be enhanced by undertaking
rotations of leguminous and non-leguminous crops. Table 3 shows the fertilizer nitrogen
replacement values derived from preceding legumes on maize yield.
A well planned rotation will besides increasing soil nitrogen also reduce the build-up of
crop diseases pests, improve soil texture, ameliorate soil biodiversity, enable crops benefit
from residual herbicide carryover, and reduce soil erosion (Carsky et al, 1999; Kwesiga and
Coe, 1994; Reinjtjes, et al., 1992). Experimental data on trials with different crops
including maize, sugar beets and wheat has proven that when a crop precedes itself, yields
are usually lower than when it precedes another crop even in mono-cropping systems
(Wani et al, 1995; Kwesiga and Coe, 1994).
Table 3 Residual Effect of Preceding Legume on
Maize Yields in Terms of Fertilizer N Equivalents
Preceding _—Followin Fertilizer N
Legume Cereal __ Equivalent (kg ha-1)
Chickpea Maize 60-70
Cowpea Maize 60
Lablabbean Maize 33
Pigeon pea Maize 20-67
Peas Maize 20-32
Groundnuts Maize 9-60
Soybean Maize 7
Wani et al. (1995), (a compilation of results from different studies).
Small-scale farmers in rural Kenya (as in most parts of sub-Saharan Africa) do not
commonly practice crop rotation by rotating individual food crops over a specific area
under cultivation. Instead, they cultivate a number of food crops at the same time
(intercropping) on the same piece of land. They may however rotate this set of intercrops
over different fields if they have enough land, or over the same field as dictated by seasons.
This form of rotational intercropping is driven by the need to secure diversity in household
food supply as well as diversify risks of crop failure over a wide number of crops. The
practice of farming purely cash crops however imposes rotational mono-cropping on
farmers and is practiced mainly but not exclusively by large-scale farmers.
Green Manure
Single tropical species like leucaena and sesbania can significantly change the level of
deficiency suffered by small-scale agricultural systems in Kenya. Table 4 shows the
contributions to soil nitrogen that can be added through the complete incorporation of four
common plant species into the soil from hedgerow prunnings.
Table 4 Some Green Manure Crops and Their Nitrogen
Contribution to the Soil Under Optimal Conditions
Sesbania (Sesbania rostrata) 100
Sesbania (Sesbania bispinosa) 80
Tpil-ipil (Leucaena leucocephala) 125
Gliricidia (Gliricidia sepium) 80-100
Source: Roy et al., 2006
It is possible to estimate the effects that such levels of nitrogen contribution would have on
the small-scale farmer in terms of contribution to crop yield increases. By estimating that as
much as 30% of nitrogen from prunnings reaches the crop, Y oung (1989) was able to ball-
park an estimate of 30-80 kg N/ha/year as being the likely contribution to crops from
hedgerow prunnings of leucaena. Y oung (1989) argued that by multiplying this amount by
10-15, hedgerow prunnings alone could raise cereal yields by as much as 300-1200 kg/ha.
Prospects for Sustainable Small-Scale Farming (Best C ase Scenario)
By introducing low external input strategies (LEIS) into Figure 3, the outcome is a system
as shown in Figure 4. Here one sees that through the use of different strategies of low
external input soil erosion can be controlled and nutrient runoff associated with it will then
be checked. Other benefits include: the accumulation of green fertilizers will ameliorate the
soil organic nutrient content which will improve crop yields; the biological fixation of
nitrogen would ameliorate the soil’s nitrogen content; and biological weed control which
leaves farmers with more time that could be used for other non-farm income generating
activities. Benefits from biological weed control mean fewer plant pests and need for
spending on pesticides. There is greater availability of forage which saves household
income that would have been spent on buying fodder. It also saves time, labour and
financial resources that would have been spent on herding.
Household
, an decisions to “NS 4
; LEIS
Soil nutrient level. + > Fodder >
¥ GA (3A A R 4)
(of a
+ Crop yield Livestock (8 /
Chemical
fertilizer Seas oe arch
@A
cn Household income
Figure 4 The Role of Low External Inputs on Household Income
By upgrading Figure 3 with low external input strategies, two important new reinforcing
loops emerge. R3, the low external input driven crop system represents the system in which
dependence on chemical fertilizers for increased crop production is off-set by the provision
of soil nutrients through low extemal input practices. R4 represents the low external input
driven fodder system in which low external input practices off-set the dependence on
10
purchased forage for expanding livestock productivity. Figure 5 shows the different levels
of benefits that can be made from the adoption of low external input practices.
Scopes for the Optimization of Low External Input Strategies
Figure 6 shows that intercropping is the most widespread low external input practice in
Nyandarua (practiced by 85% of farmers: N = 35) and Mumias (practiced by 100% of
farmers: N = 26). At least 95% of farmer associate intercropping to one or more other low
external input practices. Together with crop rotation and agroforestry, these three form the
most widespread practices of low external input strategies in the study areas.
Farm Production Benefits
Low Input Strategies Organic fertilization
Education Agroforestry ‘ Aggregate Economic Benefits
; Reduced nutrient runoff Nitrogen fertilizer savings
Crop Rotation a . fe
Resources : Reduced incidence of leaching Reduced herbicide costs
Intercropping . . . ee ee
. Biological nitrogen fixation Reduced pesticide costs
Policies Mulching Bo
Biological weed control Reduced labour costs
Composting ‘ .
Reduction of crop diseases
External Input Strategies
Livestock forage
Fuelwood supply
. f Household Income
Live fencing
Figure 5 Direct and Indirect Benefits of Introducing and/or optimizing Low Input Practices
To understand why there should be a negative nutrient balance when a majority of the
farming population is practicing at least one or more forms of soil improvement practices,
one may tend to question the seriousness with which these practices are undertaken. The
acquisition of basic skills to undertake crop rotation, intercropping and agroforestry may be
needed to ensure that the right resources and the right methods are used in the
implementation of these practices. It is found that most farmers have had little exposure to
these skills. In Mumias for example, only 9 out of 28 (approximately 32%) of farmers have
had any exposure to a forum in which basic skills of low external input practices was
discussed. In Figure 7 which shows the number of days spent in training on low extemal
input strategies for farmers in the study areas, one finds that the bulk of farmers have had
no training at all.
11
Low External Input Strategies Practiced in
Nyandarua and Mumias
o FF gS & Practices
wr a Nyandarua (N=35)
mi Mumias (N=26)
Figure 6 Percentage of Farmers Practicing Low External Input Strategies
Source: Questionnaire 2007
It follows that the low extemal input practices that are being undertaken may not be based
on formally researched principles. If the right materials and methods are not used, the
output of such practices may be quite minimal. A combination of the right materials,
methods and informed consent could optimize benefits from these practices.
Duration of training in Low External input Strategies
Received in Mumias (N=26) and Nyandarua (N=35)
100
80
i 60
§ 40
“3 ian ff
0 ] —_ J
None 1to5 6to 10 More than 11
Number of Days of Training
mo Mumias
m Nyandarua
Figure 7 Duration of Training on Low
External Input Strategies in Nyandarua and Mumias
Source: Questionnaire 2007
More insights into the problems associated with optimizing benefits from low input
strategies are presented in Figure 10 The fact that the lack of technical know-how is ranked
the most important factor influencing the practice of low external input strategies goes to
support the fact that the limited exposure to training on these practices is a problem. Other
factors which rank high are lack of resources, limited labour, limited land and information.
12
Exploring Scenarios in Small-Scale Kenyan Farming Systems
Fluctuating prices have been described as one of the main problems affecting the
incomes of small-scale farmers in developing countries (Naiman and Watkins, 1999). For
small-scale farmers, the impacts of price fluctuations are much more severe given that their
small agricultural capital cannot easily absorb the shock of negative price fluctuations.
They are then forced to make choices on the allocation of production resources in order to
minimize the impact of such fluctuations either when they occur or are expected.
8a: Without LEIS
140000 0
@ 120000 -10
§ 100000 20 g
= 0000 -30 §
3 60000 -40 &
q 40000 -50 7
2 20000 -60
0 | , -10
D A> AO AO AY adh A\ oO ch oO oO
IPP SP Dr MP ah GP 8
APP APP APE AP” AP" AP" APY APY AP? af? 49
Years
Annual Net Household Income
Annual Net Soil Nitrogen Balance
8b: With LEIS
140000 0
£ 120000 -10
8 100000 -20 9
5 2
= 80000 -30 §
2 60000 -40 §
% 40000 -50 2
2 20000 -60
0 Ir ferent , -10
DAD nO AO Gy gh A oD ob oO
SYSY SY SY
PPP PMH MP os?
Years
—— Annual Net Household Income
— Annual Net Soil Nitrogen Balance
Figure 8 Effects of LEIS on Cash Crop Income and Net Nitrogen Balance
However, in the face of uncertainty, farmers will choose to invest in food crops - the
surpluses of which can be stored for consumption in times of poor harvests if they cannot
be sold. Prices and the profitability of production tend to be the most outstanding factors
that determine the allocation of land between different uses even for small-scale farmers
(Fieldwork, 2007). Figure 8a and 8b show the effects of LEIS (represented by an addition
of 60kg nitrogen per hectare per year) on household income if only cash crops are
cultivated. Low external inputs are seen to have very little effects on net household income
from cash crops. While the net nitrogen balance seems to be a little improved, in real terms
13
the deficit is still high (Figure 8a and 8b). On food crops, low external input practices lead
to modest increases in net annual household income. They also lead to significant gains in
the net soil nitrogen balance of farms (Figure 9a and 9b). Even though the balance remains
negative, it stabilizes at a smaller deficit. This could partly be explained by the fact that
cash crop yields are transported out of the farm system (together with the nutrients
contained in them) while most food crops (and the nutrients they contain) are recycled
within the farm system. By comparing the curves of net soil nitrogen balance for the two
cropping systems (8a;b and 9Ya;b), one finds that cash crops will lead to a more rapid
depletion of soil nitrogen than food crops. Cash crops tend to show signs of not being
sustainable even with the same level of intensity of low external input strategies.
9a: Without LEIS
100000 0)
90000
80000
70000 -20
60000
50000 -30
40000 z
30000
20000
10000
Household Income
&
é
ag RR RR ER AR
Years
Annual Net Household Income
Annual Net Soil Nitrogen Balance
9b: With LEIS
100000 0
90000
80000 ald
70000 58
g
£ 60000 f
B 50000 -30 4
9 40000 2
2 -40
30000
2
20000 50
10000
0 -60
—— Annual Net Household Income
—— Annual Net Soil Nitrogen Balance
Figure 9 Effects of LEIS on Food Crop Income and Net Nitrogen Balance
When land for cash crops (sugar beets and sugarcane) is converted to food crops (maize
and potatoes), there is a significant fall in household income. This should be due to the fact
14
that food crops generally fetch a lower market price per unit area cultivated than cash crops.
This is because the system under study had sugarcane which is a “semi-permanent cash
crop” with a four-year cycle.
DISCUSSIONS
The practice of low external input agriculture is a common feature in the Kenyan rural
landscape (see Figure 6). With over 95% of farmers associating intercropping with one or
many other low external input practices, one tends to wonder why the soil nitrogen balance
in Kenya is still negative (De Jager et al., 1998; Stoorvogel and Smaling 1990; FAO,
2004). Data on the level of exposure to information and/or training on low input strategies
reveal that very few farmers have had education of any kind on these practices. Where
people have had some level of exposure to such information, it has been for very limited
periods of time (see Figure 7). Undertaking these practices is therefore more an issue of
custom than a conscious and educated effort to reap the full benefits that the practices stand
to offer. To optimize the benefits offered by low external input strategies, the acquisition of
some level of technical know-how seems to be indispensable. According to De Costa and
Sangakkara (2006) access to the right technical know-how, planting resources and related
materials to undertake low external input practices is not accessible to smallholder farmers
of the tropics today. The need to strengthen farmers’ knowledge base on some of the basic
information and skills in the practice of agriculture had been emphasized by Tschakert,
(2003). While noting that farmers did understand that practices like crop rotation and
fallowing would increase production, she noted that there was a significant lack of
knowledge on how these practices could be effectively practiced to optimize benefits from
them.
Ranking the Importance of Factors Limiting the
Implementation of Low External Input Practices,
Figure 10 Limits to the Practice of Low External Input Strategies
Source: Fieldwork 2007
The best case scenario of a full-scale adoption of a low external input system could be
criticized too for being over-ambitious. However, as argued by Altieri et al (1999), the lack
of access to chemical fertilizers in Cuba has led to an agricultural revolution in which the
entire system is almost reliant on organic agriculture. Even though this may not be
immediately translated into significantly high increases in income for the small-scale
15
farmer, a net positive soil nitrogen balance supports the view that a carefully planned set of
low external input practices could be used to address some of the problems of low soil
nitrogen in small-scale tropical agriculture. Given that LEIS offers opportunities for
increasing household income beyond crop and livestock production (such as providing
fuelwood, building and other materials which could be converted to money), one may
remind that in the long-term, LEIS may have a positive impact on household income.
Figure 9a and 9b also show that low external input strategies may stabilize incomes for the
small-scale farmer. Stable incomes could be a useful tool for decision making in many
aspects of agricultural production.
Previous studies have identified some benchmarks that have to be used to assessed the
sustainability of low external input strategies: De Jager et al. (2001) concluded after a study
of a conventional farm and one under low extemal input practices in Machakos, Kenya that
besides improving soil nutrient conditions, the positive impact of LEIS can only be felt if it
reduces nutrient losses through leaching and gaseous losses as well; Shepherd and Soule
(1998) in a study in the Vihiga District of Kenya came to the conclusion that LEIS must be
able to increase the quality of farm outputs while opening up opportunities for non-farm
income as well as raise nutrient inputs at low labour and financial costs. Some of these
benchmarks have been tested on individual crops (Wani et al, 1995; and Kwesiga and Coe,
1994) and on individual practices (Peel, 1998; and Oswald et al. 1996). The present study
has given an opportunity of testing two of the benchmarks (soil nitrogen/fertility and
household income) in a more holistic perspective.
Other studies have questioned in which areas tropical agriculture should be optimized (De
Costa and Sangakkara, 2006). This study identifies practices of sustainable agriculture that
are already common in the Kenyan rural landscape, outlines scientific arguments for their
choice as viable low external input practices and identifies constraints to their optimal
application.
CONCLUSION
Crop rotation, agroforestry, and intercropping are the most widely practiced of the low
external input practices in the rural Kenyan districts of Nyandarua and Mumias. However,
minimal benefits are being reaped from their practice. Low education on the proper
implementation of these practices is one of the main hindrances to reaping optimal benefits
from these practices. An analysis of the system confirms that it is possible to increase the
level of soil nitrogen using low external input practices. However, improving soil nitrogen
may not necessarily mean an increase in household income. Within a thirty year period of
simulation, the adoption of low external input practices is less sustainable as an option in
cash crop production. In food crop cultivation on the other hand, low extemal input
strategies can lead to modest increases in household income and an amelioration of the net
balance of soil nitrogen. It is however argued that in the long-run, household income could
eventually increase as the low external input system gets mature and begins providing
altemative sources of income through sources like fuel wood production.
16
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APPENDIX
A: Process window of the Nitrogen Subsystem
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APPENDIX
Process window of the Nitrogen Subsystem
B: Model View
