R.D.B. Lefroy et al. Agriculture, Ecosystems and Environment 81 2000 137–146 139
the Center for Soils and Agroclimate Research, In- donesia, and 10 were non-collaborators. In Thailand,
seven farmers were selected from collaborators in the IBSRAMDepartment of Land Development soil con-
servation project and six had never participated in soil conservation projects.
Data were collected from a number of sources and using a number of techniques. Firstly, data from
previous studies were used, particularly from stud- ies in the IBSRAM network. Secondly, data from
the village level and above were collected in inter- views with heads of villages, communes, districts,
provinces, etc., and from various village groups, such as groups for women, youth, the elderly, etc. Thirdly,
household level data were collected in interviews with the individual farmers. Finally, rapid rural appraisal
and farmer participatory techniques were used with selected groups of farmers.
The information was collected at a number of lev- els and for a number of reasons. A primary reason
was to characterise the particular site, farming sys- tem, village community, etc. This is an essential step
in understanding the degree of universality or speci- ficity in evaluating SLM in different agroecological
and socio-cultural systems. The appropriate scale varies between characteristics. For some characteris-
tics, farming systems across a wide geographic range may be very similar. Equally, systems that are very
similar in many characteristics may be very different in a limited number of characteristics. Establishing
management domains relies on good characterisation. Secondly, the aim in data collection was to indicate
the constraints experienced in current practices and the potential for improvement. In part this involved
analysis of cause and effect, as well as evaluation of the advantages and disadvantages of alternative
land management systems. Thirdly, the aim was to develop evaluation factors and indicators of SLM and
to ascertain the critical thresholds of these indicators.
None of these activities are exclusive of each other. Information that characterises a farming system may
outline the constraints in the systems, may be useful as an indicator of SLM, or may be a modifier for
use with another indicator. For instance, soil type may be a characteristic of the system, and it may be a
modifier for an indicator of soil moisture constraints or of some aspect of soil fertility. Similarly, tenurial
status can be a characteristic of a system, a constraint to implementation of SLM, and an indicator for that
constraint. A practical protocol was established for use by the
researchers and their assistants from the collaborating NARES who conducted the case studies. Develop-
ment of the protocol was based on the action frame- work outlined by Smyth and Dumanski 1993 and on
guidelines for conducting FESLM case studies Du- manski, 1998. The practical techniques used included
open-ended questionnaires, for the collection of vil- lage and household level socio-economic data and
farm level biophysical data, as well as a range of par- ticipatory rural appraisal PRA techniques Bechst-
edt, 2000a,b. The PRA techniques included problem identification, ranking and solution finding, village
and resource mapping, time trends of crop yield, as- sessment of the innovation in soil improvement tech-
niques, seasonal labour-input calendars, and gender analysis of the division of labour and decision-making.
Information was collected at both the village or community level, and at the single household level,
to cover areas such as demography, history of the set- tlement and households, ethnicity and belief systems,
farming systems, cropping patterns, livestock pro- duction, forest and water management, conservation
strategies, tenurial status, marketing, agricultural and non-agricultural income and expenditure, road sys-
tems, education, health and nutrition, local organisa- tions and social co-operation, internal conflicts, major
problems and solutions to these problems, access to capital, and access to outside support services.
Evaluation of biophysical factors included detailed descriptions of the cropping systems, including inputs,
fallow periods, etc., the physical characteristics of the fields in terms of erosion, crusting, rills, runoff, com-
paction and salinisation, the fertility status, including fertility ranking and plant growth symptoms, the soil
water status, the weed, pest and disease management, and the quality of off-farm water.
3. Selection of indicators and thresholds
A large amount of data were collected by the NARES collaborators in the three case studies Phien
et al., 1997; Santoso et al., 1997; Wattanasarn et al., 1997. These data were used in combination with
earlier data from the network Sajjapongse, personal
140 R.D.B. Lefroy et al. Agriculture, Ecosystems and Environment 81 2000 137–146
Table 1 Productivity indicators and threshold ratings, with farmer rankings and comments
Indicator Qualitative ratings
Farmer importance ranking Farmer comments
Very Medium
Not Yield average of 7 years
≥ village mean
4 12
4 Average over 10 years
village mean by 0–25 village mean by ≈25
village mean by 25 Soil colour as an estimate of SOM
Dark soilhigh SOM 15
5 Soil depth
Brown soilmedium SOM Yellowishlow SOM
Plant growth Vigorous
10 10
Normal Stunted
Leaf colour Dark green
15 5
Normal Yellowish on whole leaf
Yellowish on tipsmargins Older leaves purple
Table 2 Security indicators and threshold ratings, with farmer rankings and comments
Indicator Qualitative ratings
Farmer importance ranking Farmer comments
Very Medium
Not Average annual rainfall
Excessive: 2400 mm per year 15
5 Rainfall distribution
Sufficient: 1200–2400 mm Limited: 1200 mm
Residue management returned 50 for 3 years or more
10 5
5 Use of organic manure
50 for 3 years 50 for 3 years or more
50 for 3 years Burnt or removed
Drought frequency 2 years continuously
16 4
2 years in 7 2 years in 7
Income from livestock 25 of total income
10 10
Normally 20–30 10–25 of total income
10 of total income
communication, with the aim of achieving a more structured approach to developing SLM strategies.
Partially as a result of the complex nature of the data, they were analysed qualitatively, rather than quan-
titatively. The data were used, with comments from researchers and feedback from the collaborating farm-
ers, to identify a suite of evaluation factors and indica- tors, with associated thresholds or qualitative ratings,
for each of the five pillars of the FESLM: productivity, security, protection, viability and acceptability. These
indicators have been used to develop a prototype decision support system DSS Rais et al., 1998a.
The selected indicators and thresholds are listed in Tables 1–5, along with rankings and comments made
R.D.B. Lefroy et al. Agriculture, Ecosystems and Environment 81 2000 137–146 141
Table 3 Protection indicators and threshold ratings, with farmer rankings and comments
Indicator Qualitative ratings
Farmer importance ranking Farmer comments
Very Medium
Not Topsoil eroded amount
in last 7 years 4.5 cm lost, rills on 50
20 Amount in last 10 years
0.7–4.5 cm lost, rills 25–50 0.7 cm lost, rills on 25
Cropping intensity and extent of protection
2–3 crops with conservation 20
2–3 crops, no conservation 1 crop with conservation
1 crop, no conservation Cropping pattern
Rice or corn then fallow 14
6 Include fruit gardens and agroforestry
Rice then corn Ricecorn then legume etc.
Ricecorn between perennial
Table 4 Viability indicators and threshold ratings, with farmer rankings and comments
Indicator Qualitative ratings
Farmer importance ranking Farmer comments
Very Medium
Not Net farm income
Rising B:C1.25 20
Total income of family Constant B:C=1
Declining B:C1 Fluctuating
Off-farm income 25 of total income
15 5
Normally about 10 10–25 of total income
10 of total income Difference between market and farm price
50 13
4 3
25–50 25
Availability of farm labour 2 full-time adults
10 6
4 Labour per land unit
1–2 full-time adults 1 full-time adult
Land holding size 1 ha
20 1.5–2 ha per family
1–2 ha 2 ha
Availability of farm credit 50 of requirement
15 5
25–50 of requirement 25 of requirement
Nil Percentage of farm produce sold in market
50 of produce sold 8
7 5
25–50 of produce sold 25 of produce sold
142 R.D.B. Lefroy et al. Agriculture, Ecosystems and Environment 81 2000 137–146
Table 5 Acceptability indicators and threshold ratings, with farmer rankings and comments
Indicator Qualitative ratings
Farmer importance ranking Farmer comments
Very Medium
Not Tenurial status
Full ownership 20
Long term user rights No official land title
Access to extension services Full technical support
12 7
1 Limited technical support
No support Access to primary schools
1 km 8
12 1–3 km
3 km Access to health centre
3 km 7
12 1
3–5 km 5 km
Access to agricultural inputs 5 km
5 18
7 5–10 km
10 km Subsidy for conservation practices
50 15
5 10–20 of total cost
25–50 25
No subsidy Training in conservation practices
Once in 3 years 18
2 School for young farmers
Once in 5 years None available
Village road links to major roads Full access
1 17
2 Limited access
No access
by the 20 Vietnamese farmer-collaborators when an early version of the DSS was first used to assess the
sustainability of their farming systems. The farmer rankings indicate their assessment of the importance
and relevance of the indicators and the qualitative ratings with respect to sustainability, while their com-
ments indicate alternative or additional indicators and alterations to threshold ratings.
4. Use and assessment of indicators