Figure 1
 Figure 2
 Figure 3
 Figure 4
 Figure 5
 Table 1
 Table 2
 Table 3
 Table 4

Title: Sustainability and on-farm experiments
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00094277/00001
 Material Information
Title: Sustainability and on-farm experiments ways to exploit participatory and systems concepts
Physical Description: 18 p. : ill. ; 28 cm.
Language: English
Creator: Lightfoot, Clive
Noble, Reg
Publication Date: 1992
Copyright Date: 1992
Subject: Sustainable agriculture -- Developing countries   ( lcsh )
Agriculture -- Research -- On-farm -- Developing countries   ( lcsh )
Genre: non-fiction   ( marcgt )
Spatial Coverage: Developing countries
Bibliography: Includes bibliographical references (p. 16-18).
General Note: "ICLARM, Philippines."
General Note: Caption title.
General Note: Typescript.
Statement of Responsibility: Clive Lightfoot and Reg Noble.
 Record Information
Bibliographic ID: UF00094277
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 434841915

Table of Contents
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    Figure 1
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    Figure 2
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    Figure 3
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    Figure 4
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    Figure 5
        Page 7b
        Page 8
        Page 9
    Table 1
        Page 9a
    Table 2
        Page 9b
        Page 10
    Table 3
        Page 10a
    Table 4
        Page 10b
        Page 11
        Page 12
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        Page 17
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Full Text


Clive Lightfoot and Reg Noble. ICLARI, Philippines.


Over the past ten to fifteen years On-Farm Experimentation (OFE) in
Farming Systems Research (FSR) have concentrated on improving
commodity yields, or other aspects of their performance. While many
experiments were conducted with a systems perspective, few tested
hypotheses at the level of the whole farm system. Many of these
experiments were conducted with farmers but few were designed and
tested by them. Experiments of this nature are important and
necessary for disciplinary and commodity pursuits, however, they have
done little to further the concepts of farmer participation and
holistic treatment of farming problems. Indeed, this imbalance of
single-enterprise, researcher-managed, on-farm experiments versus
whole farm, farmer-managed experiments has, in our view, contributed
to current disenchantment with FSR. Moreover, disenchantment has
spread into our own ranks. Participatory Rural Appraisal,
Participatory Technology Development, Low External Input Agriculture,
and Agroecosystems Analysis distance themselves from FSR.


Enter sustainable agriculture. An object of study that correctly
interests agricultural researchers of all stripes. Economists,
agronomists and microbiologists are busy setting up new exciting work
(Batie 1989, Edwards et al 1990, Harrington 1991).

Will FSR practioners again mimic the research of disciplinary and
commodity scientists or will they fashion programs that are uniquely
participatory and holistic? Our task is formidable as notwithstanding
lengthy farm system description, constraints analysis, design of
interventions to overcome constraints, and on-farm experiments to
evaluate interventions research agendas invariably break down into
researcher-managed, component technology research on varieties,
fertilizers, green manures, etc.. Indeed, we must avoid the fate of
US sustainable agriculture research where "Whole-farm studies and
studies combining crops and livestock were comparatively uncommon, so
it usually would not be possible to analyze how production
efficiencies might be increased through integrating all components of
a farm or by combining crops and livestock." (Anderson and Lockeretz,

Perhaps the new articulation of sustainable agriculture can inspire
more farmer participation in our on-farm experiments and more
holistic scope in our tests. Where in all the rhetoric of
sustainability can we find help?


Conventional goals for sustainable agriculture invariably seek to,
maintain or increase biological and economic productivity, enhance
efficiency of inputs used, increase stability of production, increase
resilience to environmental changes, minimize adverse environmental
impacts, and ensure social compatibility. While these goals offer
scope for many disciplines to work they provide scant operational

Operational hints can be found in Conway's definition of
sustainability which is couched in terms of the ability of a farming
system to "maintain its productivity when subject to stress or
perturbation" (Conway 1986). Conway and others, most notably Altieri
and Francis, have gone on to suggest that sustainability is enhanced
through system diversity of enterprises over space and time and
recycling of energy and nutrients thereby reducing need for external
inputs (Altieri 1987).

Farming systems research practioners must now find ways for farmers
to participate in the generation of new farming systems that will
promote these characteristics. Fortunately, today many farmer
participatory techniques exist for FSR practioners to draw on
(Chambers, Pacey & Thrupp 1989; Haverkort, van der Kamp & Waters-
Bayer, 1991)


Our challenge then is to fashion a type of on-farm experimentation
that will not only generate farming systems that enhance diversity
and recycling, but also develop ways to measure these
characteristics. But, even before this can be done the 'how do I
improve enterprise performance' perspective of researchers and
farmers will have to be changed. Sustainable farming systems are
more likely to emerge from a 'how do I regenerate my farm resource
base' perspective.


This paper attempts to contribute to this challenge in three ways.
Firstly, we present some ideas on protocols for on-farm experiments
in sustainable resource management. Secondly, we look at ideas to
assess the impact of these systems. Thirdly we look at ideas to
evaluate them in terms of our definition and characteristics of
sustainability. We end the paper with a discussion on anticipated
problems for the years ahead.



Small-scale, low-resource farming systems are complex, diverse
environments where agricultural production is risk-prone and very
much dependent on the whim of the climate, particularly availability
of water. Such farming systems dominate the rain-fed tropics,
especially sub-sahelian Africa. However, risk can be reduced and
production increased by enhancing, exploiting and combining the
diverse elements which comprise such farming systems, or by
introducing elements which can aid this process such as multipurpose
trees, crop-fish systems etc.

In order to develop management practices which will stabilize and
sustain agricultural production in such environments, local knowledge
is an essential prerequisite for understanding such complex systems.
Therefore the farmers are the most appropriate people to develop new
management practices and experiment in manipulating their farming

Unfortunately small-scale farmers are often under heavy pressure from
research and extension personnel to accept management practices which
are commodity oriented and have as their goal enterprise
profitability. Such practices often result in simplification of the
environment which invariably leads to reliance on expensive external
and often non-renewable inputs in order to maintain production. Under
the fragile socioeconomic and environmental conditions of most small-
scale farmers in sub-sahelian Africa, high, external-input farming is
not sustainable and will increase risk rather than reduce it.

An alternative approach is to develop a protocol for enabling farmers
to experiment in designing resource management systems that are
appropriate for their local environment. Farmers have the expert
knowledge of their local resources and the skills to initiate and
manage a range of innovations concurrently. What is needed is a
methodology which enhances these abilities and gives farmers a
holistic appreciation of their environment and the potential for
integrating its elements, or incorporating new ones which will aid
this process.

The first step is to establish how farmers classify and perceive
their natural and agricultural resources and proceed in such a way
that the farmers are able to visualize their whole farming system and
the interrelationships of its elements.

Local farming communities often classify their environment based on
soil type, topography and water resources. Such categorization
recognizes the habitat diversity that provides a spectrum of
potential for agricultural production and exploitation of natural

Participatory exercises involving several groups of twenty or so
farmers are the most successful approach to understanding how rural
communities classify their local resource systems. Most of the
community should be involved in this activity. One such approach is
to encourage villagers, to express in forms of simple maps and
transects, the resource classification of their surrounding
environment. This provides a simple mechanism for rapid rural
assessment and farmers learn to think in terms of the total resource
system rather than individual farm enterprises.

The most appropriate setting for resource mapping is in the farmer's
own home. Groups provide a better dynamic than individuals by
allowing wider discussion and consensus on the indigenous
categorization of their local resources. Usually, the most successful
approach is to allow villagers to first lead the researcher through
their farming area and then afterwards draw maps illustrating the
resource systems identified on the walk.

Maps are usually drawn on the ground using whatever materials are
available. Indigenous names for resource systems, soils, enterprises.
etc. are used as far as possible. Local terms can be very descriptive
and reveal information on the nature of the resource system, its use
and importance. Drawing also does not require a person to be
literate. Stones, plant and animal material etc. can be placed on the
ground to symbolize different resources and aspects of topography and
hydrology. Drawing also enables farmers to obtain a broad overview of
their environment which they often have not visualized in its
totality before (Lightfoot and Minnick, 1991).

Figure 1 illustrates a map as drawn by a group of ten, men and women
villagers from Zomba District in Malawi. The broad classification of
resource systems is into mtunda (upland/sloping land), munda (flat
cropland), dimba (low lying gardens with high water table) and dambo
(seasonally flooded areas which are uncultivated). Within these broad
categories, more subtle distinctions are made based on soil type and
water resource as illustrated in the transect in Figure 2. Areas of
similar soil type are used for different crops depending on whether
it is rain or spring fed. The transect is a composite cross section
of the farming area in Figure 1 showing all the resource system
categories in relation to each other.

Zomba Mountain Slopes





---- Paths
Katondo Sandy red
soil-free draining
Chilongowata Clay-based soil
used for moulding
lyeswela Sandy loam
ni lyeplliwu

Utaka lyeswela

Utaka lyepllwu

(white sandy
free draining

(black loam soil
found In dimbas
and dambos)


Utaka lyepillwu
(Black loam)



Namagono River

Beans Rice
Maize Green

Land Transect of Village in Chinseu Area,

Zomba District, Malafwi
January 1990

aim sgrlhupo)lle.
piguwn pe, om pmlM
b-a, pump, poppf

uafmw. pppm.ng

Maia. pump
XW. aiaM6W.
bemkr, cumpdM
iwapoMll, ang
Mk rim caum.
mist os asan

Make Apmph ben
Ingw mI lb.wf
wam t. pgam ps


Such mapping provides the researcher with a detailed picture of the
diversity and distribution of land, soil and water resources from the
perspective of the rural community. Farmers will also have
visualized, often for the first time, a complete representation of
their own farm's relationship within the rural community and its
agroecological environment.


Having established a map and transect showing the broad resource
categories for a village and its locality, interested farmers are
then encouraged to make similar drawings for their own farms
(Lightfoot, Noble & Morales, 1991). The majority of farmers are
usually interested. These drawings should follow a logical sequence
to ensure that farmers do not simply draw enterprise maps. Resource
systems are sketched in first, then their respective enterprises.
Following this sequence, helps the farmer to change their thinking
away from enterprise profitability to rehabilitation of the farming
system's natural resource bases. Resource systems are not restricted
to those within the boundaries of the farm. Common grazing land and
water sources utilized by the farming household should be included.
This provides a more accurate picture of the total resource base of
the smallholding. A picture that is often very different from a
conventional idea of a farm.

Finally, the farmer and household members draw arrows on the diagram
indicating movement of on-farm materials e.g. maize bran from the
cropland to chicken house, manure from the chicken house to the
vegetable garden etc. This provides a very clear picture of the level
of integration between and within resource systems.

Often farmers will tend to make drawings that cover all activities,
enterprises and bioresource flows that occur in an annual
agricultural cycle. A more accurate picture of annual operations can
be obtained if drawings are made at different times of the year to
show the seasonal variations in farming activities and flows of

Figure 3 shows a typical farmer's model from Ndoka village (Zomba
District, Malawi). This drawing is by a woman who has just started to
incorporate fish ponds on her farm. The picture shows qualitative
outputs from resource systems to the household and market with some
of their related cash flows.

An interesting point to note on the drawing is that only the fish
ponds have links with other resource systems and enterprises.
Agricultural residues (e.g. maize bran, waste vegetable material etc)
are beginning to be processed through the pond as feed and
fertilizer. No other enterprises appear to create these types of
interlinkages and material recycling within the farming system. Most
of the arrows on the drawing are simply showing outputs from systems


Expenses -391$ 0
Money accured = 375$

sa. 9Pa.e Net income
s o $252

er Munda Maketat


and occasional inputs (e.g. fertilizer) rather than bioresource
recycling flows. The latter may increase with time if the farmer
starts to recycle more on-farm materials.

Such a farm model can provide a basis for further research and be
used to make suggestions about integration and improvement in
recycling of bioresources. Farmers can also use drawings as a
management tool for indicating areas they feel need change or further
study. In this way, research agendas can be developed through mutual
cooperation between farmer and researcher.

So far, ten farmers are using the model they have drawn both as a
teaching aid on farm management for their family, and as an
experimental tool for planning new farming strategies. Frequently,
drawings are displayed prominently in farm households as a focal
point for family discussion.

Successful drawing and modelling by farmers is best achieved when
farmers work together. The ideal group size is around fifteen to
twenty which allows all farmers to have an impact within the group.
Such groups provide a valuable forum for exchange of ideas and
exposure to a diverse array of farm management options.

A very useful approach is to have farmers model their current farming
system and then possible future scenarios which include culturing
fish. Group interaction often generates intense discussion and is
more likely to lead to formulation of integrated farming strategies
appropriate to local agricultural systems. The role of the
researchers at the workshop is simply to facilitate and stimulate
farmer discussions.


Modelling workshops are also a useful precursor to exposing farmers
to demonstrations of integrated aquaculture-agriculture systems and
their related biotechnology.

In Malawi, farmers who have been involved in modelling workshops on
their farms have been invited to see demonstrations of integrated
crop-fish systems at the National Aquaculture Research Station. In
December 1990, 17 farmers, who were practicing aquaculture, were
invited to see rice-fish systems at the station. At that time, no
farmers in Malawi had been practicing rice-fish culture even though
many had rice paddies adjacent to their ponds. The farmers were
treating each enterprise in terms of strict commodity production and
not as resource systems which could enhance each other if integrated.

The usual practice is to grow one crop of rice per year between
December and June. The farmers who were visiting in December 1990
were seeing rice which had been grown during the period of the
hottest, driest months of the year (August-December). This was
possible because the rice was grown in ponds.

Farmers were impressed by the arrangement whereby two crops (rice and
fish) were gathered from the same pond also that rice could be grown
during the dry season. After viewing the harvest, they led a workshop
to discuss the demonstration and its relevance to their farming
environment, the result was a series of drawings of farmer-designed
systems (Figures 4 and 5), very similar to those used in south-east
Asia. Common to all of these designs were simple drainage
arrangements for decoupling rice and fish. Prior exposure to farm
mapping workshops of potential or actual integrated aquaculture-
agriculture systems enabled the farmers to quickly design elegant and
simple rice-fish arrangements appropriate for their rural

Without further input or encouragement from the researchers, 11 of
these farmers experimented and developed their own unique rice-fish
systems over the succeeding 12 months. These systems all incorporate
sloping pond bottoms and drainage which allows easy withdraw of water
from the rice paddy and collection of fish in a deep water refuge.
Now, farmer-to-farmer technology transfer is occurring such that 40
farmers are practicing rice-fish culture who had not attended the
open day. A further development is that many farmers are now growing
dry season crops of rice in their ponds. This new development in
integrated resource management has been the result of a one-day
modelling workshop on farm in combination with a one-day
demonstration of the technology on station.

Further open days are now conducted partly on station and partly on
farm where farmers actively involved in development of integrated
systems incorporating vegetable-fish, rice-fish, etc. can relate
their experiences to novices to the technology.

A valuable outcome of these workshops and demonstrations is that
farmers do not simply consider ponds as fish production units, but
also as water storage for irrigating crops, watering livestock and
household use. Secondly, farmers have realized that if agricultural
residues are recycled through ponds then highly fertile mud is
produced which can be transferred to adjacent vegetable gardens and
reduce the need to use chemical fertilizers.

Thus, the modelling and mapping workshops, together with the
demonstrations, provide farmers with a forum for peer exchange and
discussion about new ways to reallocate and integrate their resources
and enterprises. Farmer experimentation resulting from this
participatory process leads to increased efficiency in utilization

FI wRE 4 Dambo
Unused Dimba
Farm A '


Maize. cassava, cowpea, beans
ground nuts. sweet potato
Wet season crops

Farm A



P Income


and recycling of on-farm residues, rehabilitation of exhausted soils
and reclamation of marginal land for agricultural production.


As farmers experiment in manipulating resource systems and
enterprises, the problem remains as to how and what should be
measured as indicators of sustainable improvement on the farm. Any
evaluation or monitoring program will require full participation of
the farmers in its design if it is to be effective in capturing the
evolution of small-scale farming systems.

Farmer bioresource models illustrating in their totality, resource
systems, enterprises and their interrelationships provide an
effective format for developing a monitoring system. Farmers can
update their models on a regular basis using the initial plan diagram
of their farm. Changes in flows within and between resource systems,
outputs from them and external inputs to them, can all be captured
when farmers produce time series models of their farming operations.

Drawings will include the resource flows for the preceding time
period since the last diagram was drawn. Wherever possible, the
amount of material, frequency of flow and its monetary value are
recorded. Quantities can be given in local terms and then converted
into kilos or reasonable estimates attempted.

This procedure enables both the farmer and researcher to monitor
progress and change. Such a process also provides farmers with a tool
for improving their decision making and skills in resource


Integration of enterprises and improved recycling of on-farm
bioresources should lead to increased efficiency of energy and
nutrient utilization with concomitant rehabilitation of farming
ecosystems. Greater stability in agricultural production should ensue
with a corresponding reduction in vulnerability to environmental

Time series modelling of farms as mentioned in section 2 provides one
method for capturing some of these changes and assessing if increased
diversification of linkages between elements in the farm system
really stabilizes and improves farm production.


In Malawi, a joint research program with farmers has just started to
assess the impact of integrated aquaculture-agriculture development
on small-scale farming systems. Detailed results are not yet
available but some preliminary work seems to indicate that ponds
linked to rice and vegetables may generate significant improvements
for the farming household and its surrounding environment.

Using methodology described in section 2, farmers have been exposed
to various crop-fish integration, particularly rice-fish as
described in Noble and Rashidi (1990). Interest in integration is
intense and many farmers have altered their farming environment
quickly, often too fast for researchers to capture the process.

To understand the full impact of these changes, as a preliminary
sample, five farmers who are relatively new to aquaculture systems
were asked to make drawings of their farms before and after
incorporation of fish ponds. Figures 6 and 7 illustrate the changes
that have occurred in one farm system due to presence of fish ponds.

Significant alterations have taken place in farm management due to
the incorporation of ponds. The farming system now has increased
linkages between its elements with the rice-fish ponds acting as the
focus of flow for on-farm bioresources. Marginal land has been
brought into production for rice and fish and has increased the
household income directly through sale of fish from the revitalized
dambo resource system. These patterns were common to four of the
farms sampled and in each case, there were bioresource linkages to
adjacent dimba vegetable gardens with flows operating in both
directions between the pond and dimba systems. Although these dambo
and dimba wetlands are individually small, often less than 0.5ha, if
added together, they comprise from 10-20% of total land area in
African savannas (Scoones 1991).

Table 1 summarizes the information obtained from the farm drawings.
In every case, the presence of ponds result in initiation of
integration creating formation of linkages through recycling of farm
residues. The contribution such systems make to household nutrition
has not been assessed as yet but all of the farmers indicated that
significant output from both rice and fish goes to the household.
Farmers commented that having ponds reduced their need to buy fish
and the latter were often used for reciprocal exchange for goods and
services provided by neighbors.

On three sets of drawings farmers provided detailed information on
cash flows coming from each resource system before and after
introduction of fish ponds. Table 2 summarizes this information.
Rice-fish ponds' contribution to gross income varies widely from 10
to 62%. This variation reflects differing levels of investment and
length of time their aquaculture systems have been running.

Table 1
Comparison of changes between farming system prior to integrated aquaculture
development and afterwards based on farmers drawings.


1. Marginal wet land unutilized

2. No integration between resource
systems or farm enterprises

3. Crop residues not recycled

4. Water shortage for vegetable garden
in late dry season

5. Households reliant on uncertain water

6. Reliant either on fertilizer for
vegetable garden or overutilize
exhausted soils

7. Buy fish; rarely eat fish

8. Marginal wetland does not provide
food and income for household

9. Rice either not grown or only one crop
per year


Marginal land brought into productive

Ponds serve as a focal point for direct
or indirect links between resource

Crop residues such as maize bran and
green leaf waste used as pond input

Ponds placed adjacent to gardens
provide water for irrigating vegetables

Households use pond as water
catchment for domestic use and
watering livestock

Use pond as processing unit for
converting low quality crop waste into
fertile mud for transfer to garden;
reduced fertilizer use

Ready supply of fish for household
consumption; rarely buy fish now

Conversion to ponds provides food
and income

Rice-fish ponds provide two crops of
rice per year; rice arown for first time


Note: All farmers above are classified by Malawi Government as in the low income index bracket
of less than $30/month.

Average income of Malawian small-scale farmers was reported as $130/year in 1989 (World
Bank 1989).

Farm 1

Three cropland areas (munda) which had been borrowed, were
repossessed from the farmer by their owners. To offset this loss of
productive lands, the farmer converted marginal dambo land into an
integrated rice-fish system. Decline in income due to loss of
productive munda is more than compensated by income from the
rehabilitated dambo (Table 2) even though the dambo area is smaller
in size than the original three munda areas that were lost. The
farmer does incur expenses associated with the rice-fish enterprise
of about $23, giving a net income of $148.

However, the full value of rice and fish from the ponds is not
reflected in Table 2. The household eats produce from the ponds and
also provide free fish to relatives. The estimated market value of
consumed fish alone is approximately $43. Therefore the total net
value of produce from the ponds is around $190.

Farm 2

Rehabilitation of the dambo area for rice-fish ponds provides an
additional income to the household which is equivalent to or even
slightly more than the income from the munda, raising total gross
family earnings from $134 to $155. Again, the total value of produce
from the ponds is not reflected in the table. Consumption of rice and
fish by the family was valued at approximately $8, raising the total
value of produce from the ponds to just over $160/year. The farmer
has only just started rice-fish and is still in the process of
developing the system.

Farm 3

Marginal dambo was rehabilitated and provided additional income and
food for the household. This cash was used to purchase fertilizer for
the munda, resulting in increased crop production and more than a
doubling of income from the munda crops. Recycling of pond mud to the
dimba raises the latter's income from $46 to $83, although as a
percentage of total income it declines slightly.

On all three farms, presence of ponds seems to have markedly altered
the farm system and earning potential of the household. Average
incomes prior to adoption of aquaculture was $155/year and increased
to $235/year afterwards. Experiment in International Living (1991)
reported that average annual incomes for rural households in Malawi
was $130. Although one cannot draw any firm conclusions from three
farms, it would appear that integrated aquaculture systems may have
the potential to significantly raise rural incomes.
Tables 3 and 4 provide more detailed data on production and income
from 14 rice-fish systems in Malawi. The majority of farmers have a
200m2 ponds of which half is planted with rice. Such systems have the

Table Average production of rice grain and straw from rice-fish integrated
ponds in Zomba District, Malawi, 1991/92/

1. Rice Harvest Weight
kgs grain = 28 (15) [8-60]. straw = 97 (61) [26-197]
kg/100m2 grain = 26 (8) [13-42]. straw = 81 (37) [38-198]
kg/100m2/yr grain = 55 (20) [35-96]. straw = 190 (115) [86-478]
*Mean value of rice grain = 41 K ($13)/100m2/yr

2. Pond statistics
Total Area = 259 (167) [42-751]
Rice Area = 124 (91) [40-386]
% Rice = 56 (29) [16-100]
Mean growing period (days) = 164 (27) [1143-256]
Number of ponds = 14;

() = standard deviation; [ ] = range
*last harvests were sold in May 1992 (1 kg rice = 0.72 K)
US$1 = 3.2 K May 1992. National Statistical Bulletin. May 1992 issue, Publ.
National Statistical Office. 27 p.

Table 4. Average fish production and harvest value from rice-fish ponds in Zomba
District, Malawi, 1992.

1. Fish Production, Harvest weight


- 13
- 27



2. Fish Production, Harvest values
Mean value of fish/200m2/year = 82 K

= 165 K
Mean price/kg = 3.03 K


1 harvest
2 harvests*

3. Pond Statistics
Mean area m2 = 211 (19) [181-232]
Mean growing period (mths) for 1 harvest = 5 (2) [3.4-9.4]
Number of ponds = 5
() = standard deviation; [ ] = range; = 2 harvests is very common
($1 = 3.7 K August 1992)

potential to generate incomes ranging from approximately $120 to $250
per annum depending on whether farmers operate one or two cycles of
rice and fish in their ponds. This income range is just for rice-fish
on its own and does not include earnings from other resource systems
on the farm.

This earning potential represents a mean annual production of about
50 to 100 kg of rice and 25 to 50 kg of fish. The average number of
people per rural household is 4.3 (National Statistical Office 1987,
1992). Therefore rice-fish systems potentially can provide 12-23 kg
of rice and 6-12 kg of fish per person per annum. Msiska (1985)
reported that by the mid 1980s, annual per capital consumption of fish
in Malawi had declined by 54% from 18 kg in 1972 to less than 10 kg
in 1984. The rice-fish systems developed by farmers in Zomba District
have the potential to substantially reduce this shortfall in fish
available for home consumption. ICLARM-GTZ (1991) stated that the
average daily protein requirements for an adult is 35-43g or 12.8-
15.7 kg/capita/year. Rice-fish can produce almost the total protein
requirement for a family of four.


There is only indirect on-station evidence that development of
integrated crop-fish systems may have a beneficial impact on resource
systems. Detailed on-farm analysis has yet to be done. Chimatiro
(1992) did carry out some on-farm studies coupled with on-station
experiments that demonstrated that ponds act as efficient converters
of low quality, vegetable waste into nutrient rich pond mud.
Chimatiro found that the ecological efficiency with which vegetable
waste was converted into fish flesh in farm ponds, was only 0.8%. He
assumed that probably a large portion of plant material was being
incorporated into the detritivore subsystem of the pond and
accumulating in the sediments.

He carried out a simple test of this hypothesis on-station. Sediments
from ponds that had received grass inputs for six months, were used
as fertilizer to grow head cabbages on ordinary top soil and compared
with cabbages grown on top soil without the addition of pond mud.
Cabbages grown on soil receiving pond sediments had yields equivalent
to 1.2 t/100m2/year, a 50% increase over the 0.8 t/100m2/year
produced on ordinary dambo soil. Chikafumbwa (unpublished data)
demonstrated that even higher yields could be achieved of 2
t/100m2/year with Chinese cabbage. These two simple experiments
indicate that soils adjacent to ponds can be rehabilitated by
fertilization with pond mud and produce economic crops of vegetables.

From the Chinese cabbage experiment, approximately 0.7 t/100m2/year
of leaf waste was produced which could be recycled back into the
ponds as feed and fertilizer. This operation regenerated the pond
muds which could then be recycled back on to the garden soils.

Farmers have adopted these practices of recycling pond mud into the
dimba garden system. In the case of Farm 3 (section 3.1), transfer of
pond mud to the dimba garden has raised the latter's income by almost

Even building a pond itself on marginal land will improve the
fertility of that land by accumulation of rich pond sediments. If
that is coupled with recycling of part of those sediments to other
adjacent marginal areas, then there is real potential for system
rehabilitation and possible stabilization of agricultural production.


Although the data from rice-fish ponds and farmer's models seem to
indicate improvement in farm production because of adoption of
integrated aquaculture-agriculture systems, there is no evidence as
yet that these systems are necessarily sustainable.

Defining sustainability is a complex issue. As Conway (1991)
comments, definitions vary between disciplines and almost anything
goes if it fits within the broad umbrella of self sufficiency,
integration, traditional farming etc. Harrington (1991) cautions that
approaches to evaluation and measurement will be strongly influenced
by how sustainability is defined and interpreted.

For small-scale farmers in Africa, their major problem is maintaining
the integrity of their farming system in the face of rapidly
degrading socioeconomic and ecological conditions. A reasonable
measure of sustainability under these circumstances would be the
resilience of a farming system to such environmental perturbations.
Conway (1986) defines resilience as the ability of an agricultural
system to "maintain its productivity when subject to stress or

If one settles on resilience as the criterion of sustainability, how
and what should be measured to evaluate whether a farming system is
resilient? Harrington (1991) points out that measuring a system's
resilience will depend on developing reliable quantifiable indicators
of resilience and diversity which can be measured easily.

Giampietro et al (1992) emphasise that the stability or resilience of
systems relative to internal or external fluctuations is an important
parameter to assess. They take a strictly ecological approach and
state that energy flow and storage are critical parameters to measure
in assessing a system's stability and sustainability. They coin the
term "biophysical capital" i.e. the ability of a ecosystem to use
solar energy to run biophysical processes that stabilise system
structure and functions, i.e. maintain resilience.

Conway's definition of resilience is based on the premise that
diversity within systems will enhance their ability to withstand

perturbation. Diversity spreads risk so that if one enterprise fails,
others will still operate and thus maintain productivity of the
system. But diversity also implies links, integration, recycling and
efficient use of nutrients, etc. in order to reduce risk. Therefore,
a measure of these attributes and how they change over time may
provide researchers with some guide as to the sustainability of a
farming system.

In the context of the methodology described in section 2 and 3,
resilience might be measured through the medium of time series
modelling by farmers. Table 1 already provides some indication of the
parameters which might be used. The decision as to what is meaningful
to measure can be a joint decision of the researcher and farmer.

From farm models, change in number and type of enterprises can be
monitored over time. Regular counts can be made of bioresource flows
and the quantities of materials they represent. Outputs and inputs in
terms of labor and fertilizer etc can be estimated from drawings with
the farmer's help. The following criteria could be used to measure
improvement in sustainability of farming systems.

1. Measure productive output of marginal lands. Increase in
agricultural output will signify rehabilitation.

2. Measure increase in number of interlinkages between and within
resources systems. Increase in linkages will indicate that more
material is being recycled within the system and there is possibly
less dependence on external inputs.

3. Measure quantities of bioresources flowing between resource
systems. This will give an indication of allocation and efficiency
of nutrient and/or energy flow within the farming system.

4. Measure output from resource systems and see if combined outputs
remain stable or increase.

5. Measure net cash income flows on farm diagrams, if they are
increasing or maintaining their value relative to inflation, then
sustainability of the farming system has increased.

6. Measure net flows of produce to household as food. If these are
stable or increasing, then changes in the farm system are having a
significant impact on household nutrition.

7. Measure labor allocation relative to productive output and income
generation from different resource systems and enterprises. If
returns to limited labor are increasing, then system
sustainability is probably increasing.

8. Measure output from resource systems relative to input. If output
efficiency is greater in energy or nutrient terms, then
integration is improving sustainability of the system.

9. Measure increase in flows and linkages of materials, labor etc.
between the farm household and those of neighbours and relatives.
If linkages are improving efficiency of nutrient, cash and labor
use not only on the farm implementing the changes but is
benefiting other socially, closely linked households, then
sustainability of the system is probably increasing.

This is not an exhaustive list of possibilities but is an indication
of what information could be gleaned from farmer diagrams where the
farmer is an active participant in monitoring change and perceives a
benefit in the process.

Using time series farmer models of their farm systems for evaluation
of sustainability also addresses the problem of dealing with real
world complexity. Often quantification of sustainability is rejected
because researchers are often choosing criteria which are
quantifiable but not necessarily as crucial as conceptually more
important "non-quantifiable" ones (Harrngton 1991). This situation is
avoided with farmer models because the farmer can indicate on
diagrams "non-quantifiable" changes such as increased social linkages
and reciprocation with neighbours and relatives as people and/or
materials and cash, flow within and between farming systems.

Farmer drawings also alleviate some of the problems associated with a
total factor productivity approach (TFP) to measuring sustainability.
TFP relates total outputs (0) to total inputs (I) as TFP = O/I and
assumes that system sustainability is increasing if O>I. This
approach does not readily measure changes in quality of the resource
base or change in diversity of components within the system whether
they be social, economic or environmental. Time series models of
farms, using a variety of drawings to indicate different component
changes in the farming system, have the potential to capture and
quantify, to some extent, changes not picked up by a straight TFP

Likewise, data collected from drawings can be converted into biomass
and energy flows which will enable one to measure the "biophysical
capital" of Giampietro et al(1992) They state that stability of
living systems is related to their ability to maintain their
structure and function by replacing the flow of energy and matter
discarded by systems with new energy and matter. In a strict
ecological sense, for a farming system to be stable or sustainable,
the criteria laid down by Giampietro et al is essential. The
evaluation procedures indicated above have the potential to measure
these criteria.



While this research maybe considered in its infancy several positive
signs have emerged. Signs that encourage further work. Like many
others we have witnessed an empowerment of farmers through
participatory research. Given that farmers are the managers of
natural resources this can only be encouraging. We have seen farmers
change decisions away from enterprise profitability to favour
resource system rehabilitation. This may be an unstudied hunch but
one begging for further study. We have observed that managing water
and living aquatic resource provides an entry point for sustainable
farming system development. We have grasped the utility of
quantifiable sustainability indicators for comparing performance of
different farming systems. Through ICLARM's research in other
countries in Africa and Asia we have uncovered the universality of
resource systems. A vital output at this stage of our understanding
of sustainable agriculture is to find out the commonalities from
multi regional evaluations. Commonalities will lead to
generalizations about sustainable agriculture that can then be
empirically tested and thus a set of principles for sustainable
agriculture can emerge.

On farm experiments for sustainable agriculture do not look like
conventional experiments. Our experiments in resource management have
a new sequence of 1) resource inventory and analysis; 2) exposure to
alternative resource use techniques; 3) monitoring farming system
transformation. These experiments have the objective of changing
resource management decisions in a favorable direction. Here,
favorable means towards less reliance on non-renewable resources,
less environmental degredation, increased whole-farm profitability,
reduced pollution, and reduced adverse social and economic effects.
Researchers monitor indicators that we hypothese will lead to
sustainable farming systems. A hypothesis that still has to be
tested. Nevertheless, we do know the impact of these experiments on
households and resource systems. How long this kind of research must
run for hypotheses to be tested we do not know. Thus, we share an
idea in its early stages and not a finished product. Other
shortcomings we anticipate follow.


We feel insufficient attention has been given to measurement of
environmental effects. If resource systems are to be valued then we
need to know more about biological and ecological processes that
underly their degredation and rehabilitation. Concommittant with this
need is a failing to analyse off-farm social and economic effects. At
some time we must work at heirarchies greater than the farm and the
resource manager. Particularly important here will be studies of
markets, policies, and equity. We do, however, appreciate that
research cannot address all issues in the same test. Nevertheles,
resource management experiments as we have envisioned them must open
doors for others issues to be studied through collaborate research
efforts. If what we have written is worth following up on then
technical issues will pale in comparison with the institutional
hurdles that face us.


Experiments of the kind described need wide scale farmer
participation. Establishing a large population of farmers requires
the skills of grass root NGOs. We see little chance of this kind of
work being done without partnerships between GO and NGO institutions.
Linkages within research institutions themselves that we see as vital
are: links between on-station research and on-farm researchers, links
between social and biological science research working at higher and
lower levels in the agricultural systems hierarchy. Links with policy
makers is also vital if policies to protect and promote sustainable
systems are to be formulated. Over and above all these institutional
constraints we see the greatest hurdle of reluctance being that of
scientists to change research styles that they have used for years
and that are reinforced by peers, journals and professional


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Thanks to ICLARM technical assistants Mr. A. Montjeza and Mr. R.
Selemani and field assistant/driver, Mr. W. McLorry for data
gathering on rice-fish ponds. Thanks to Fredson Chikafumbwa for
making available his material on vegetable-fish integration. Thanks
also to Emma Mafuleka, Fredson Chikafumbwa of ICLARM and Mr.
Kalumpha, Fisheries Department for assistance in farmer modelling

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