Directory UMM :Data Elmu:jurnal:A:Agriculture, Ecosystems and Environment:Vol81.Issue2.Oct2000:

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Indicators for sustainable land management based on farmer

surveys in Vietnam, Indonesia, and Thailand

Rod D.B. Lefroy

a,∗,1

, Hans-Dieter Bechstedt

a,1

_{, Mohammad Rais}

a,b,1

a_{International Board for Soil Research and Management (IBSRAM), PO Box 9-109, Jatujak, Bangkok 10900, Thailand}

b_{National Institute of Science Technology and Development Studies (NISTADS), CSIR, Dr K.S. Krishnan Road, New Delhi 110012, India}

Abstract

The current pressure on land resources necessitates the development of sustainable land management (SLM) systems. The process of developing such systems requires that methods are available to assess sustainability easily. Indicators of SLM need to include indicators of soil quality and land quality, but in addition they must take account of the environmental setting and include the more human aspects of land management: the social, economic and political aspects.

Three case studies were undertaken to assess the sustainability of different land management systems practised by farmers on sloping lands of Indonesia, Thailand and Vietnam. Using the framework for evaluating sustainable land management (FESLM), detailed socio-economic and biophysical surveys were undertaken of 53 farms. The surveys aimed to characterise the land management systems, outline their constraints and potentials, and identify indicators and thresholds of sustainability in line with the five pillars of sustainability in the FESLM: productivity, security, protection, viability, and acceptability.

The data were used to develop a suite of SLM indicators, with associated thresholds. These indicators have been included in a prototype decision support system (DSS). Feedback on the indicators was obtained from the farmers after the DSS was used to evaluate their farming systems. The indicators are highly specific as well as simplified, but they make a useful first step towards the development of a more generic system for evaluating SLM and for more accurate site specific and integrated evaluation. Evaluation of this structured and systematic approach yielded encouraging results in a separate study in Nepal. © 2000 Elsevier Science B.V. All rights reserved.

Keywords: Sustainability assessment; Sustainability indicators; Farm surveys; Southeast Asia; Decision support system

1. Introduction

Currently, there is enormous pressure on the land resources of the world, particularly in developing countries. These pressures arise from population growth (Pinstrup-Andersen and Pandya-Lorch, 1994), the need to improve on current standards of nutri-tion (Borlaug and Dowswell, 1994), and dwindling

∗_{Corresponding author. Tel.:}_{+66-2-941-2500;}

fax:+66-2-561-1230.

E-mail address: [email protected] (R.D.B. Lefroy).

1_{www.ibsram.org.}

reserves of quality arable land (Alexandratos, 1995). The decline in reserves of quality arable land result from the significant loss of agricultural land through degrading land management practices (Scherr and Yadav, 1996), from competition for these reserves for use in forestry, watershed management, maintenance of biodiversity, etc., and from the diversion of arable land for urban and industrial use. There is a need to develop sustainable land management (SLM) sys-tems, and this requires the development of methods which can be used by researchers, extension workers, local planners, and progressive farmers, to assess the sustainability of different land management systems.

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1.1. Maintaining soil quality or developing sustainable land management systems?

There has been a critical transition from a focus on soil quality, to land quality and finally to SLM. The maintenance of soil quality is a vital component of the maintenance of land quality, however, defining soil quality, which is an essential first step to maintaining soil quality, is very complex (Carter, 1996), involving a myriad of physical, chemical, and biological factors. The transition from a focus on soil quality to land quality involved broadening the criteria to include factors such as climate and cropping system, as there is much more to land husbandry than soil husbandry. Similarly, although identifying useful land quality indicators (LQIs) is requisite for SLM, there is much more to developing SLM systems than maintaining land quality. An important aspect of the development of SLM is an approach to land management that is not just concerned with output, but encompasses the need for long term preservation of the resource base to allow adequate future food production in a manner that is socially acceptable, economically viable and environmentally sound. The framework for evaluat-ing sustainable land management (FESLM) (Smyth and Dumanski, 1993) attempts to connect all aspects of land use under investigation with the interacting conditions of the natural environment, the economy, and socio-cultural and political life. The aim of the FESLM is to develop a tool for identification of un-sustainable and un-sustainable systems and which will produce a structured and interrelated checklist of variables and factors which can be used to systemat-ically evaluate the sustainability of a wide range of agroecological systems.

The objective of this study was to assess whether such a structured approach to evaluating the sustain-ability of land management could produce accurate and efficient assessments of the sustainability of farm-ing systems on slopfarm-ing lands of Southeast Asia.

1.2. Farmer involvement in developing sustainable land management

The development of LQI and indicators of SLM re-quires major involvement by the farming community. Firstly, they possess an intimate knowledge of their land and have access to the important temporal

com-ponents of land quality; they can monitor how their system has changed. Secondly, it is the farming com-munity, the human element, that is the essential step in broadening from land quality to SLM. Thirdly, as managers of the land, it is the farming community that observes and responds to the various indicators of SLM.

The concept of sustainability is a dynamic concept in the sense that what is sustainable in one area may not be in another, and what was considered sustainable at one time may no longer be sustainable today or in the future because conditions or attitudes have changed. In addition, sustainability varies with the frame of ref-erence in which it is considered, particularly with re-spect to socio-cultural, economic and political factors. What one group considers sustainable may not be sus-tainable for another group. The aim is to merge the knowledge of farmers, extension workers, and scien-tists to gain a broader perspective on the constraints and potential of land management systems. Due to the different perspectives of these groups, however, it is possible that consensus is not reached easily, if at all; assessment of sustainability is a compromise based on negotiation. This process should develop criteria and indicators for evaluating whether land management and agricultural practices should lead towards or away from sustainability. The complete involvement of the farming community will ensure the recommendations that arise are realistic, efficient and acceptable for the end users.

2. Methods for case studies in Vietnam, Indonesia, and Thailand

Implementation of the FESLM in this study was at-tempted in three countries in Southeast Asia. The areas chosen in Vietnam, Indonesia, and Thailand were in villages on sloping land that have been involved in soil conservation activities in the IBSRAM ASIALAND Management of Sloping Lands network. In each case study, one group of farmers was selected from those who had been collaborating with activities in soil con-servation networks, and the other group was selected from non-collaborators in the same village. In both Vietnam and Indonesia, 10 families were chosen from the group of collaborators, from projects with the Na-tional Institute of Soils and Fertilizers, Vietnam, and

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the Center for Soils and Agroclimate Research, In-donesia, and 10 were non-collaborators. In Thailand, seven farmers were selected from collaborators in the IBSRAM/Department 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

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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 soil/high SOM 0 15 5 Soil depth Brown soil/medium SOM

Yellowish/low SOM

Plant growth Vigorous 10 10 0

Normal Stunted

Leaf colour Dark green 0 15 5

Normal

Yellowish on whole leaf Yellowish on tips/margins 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 0 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 0

2 years in 7 <2 years in 7

Income from livestock >25% of total income 10 10 0 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

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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 0 0 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 0 0 2–3 crops, no conservation

1 crop with conservation 1 crop, no conservation

Cropping pattern Rice or corn then fallow 14 6 0 Include fruit gardens and agroforestry Rice then corn

Rice/corn then legume etc. Rice/corn 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:C>1.25) 20 0 0 Total income of family

Constant (B:C=1) Declining (B:C<1) Fluctuating

Off-farm income >25% of total income 15 5 0 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 0 0 1.5–2 ha per family

1–2 ha >2 ha

Availability of farm credit >50% of requirement 15 5 0 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

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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 0 0

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 0 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 0 10–20% of total cost 25–50%

<25% No subsidy

Training in conservation practices Once in 3 years 18 2 0 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 4.1. Choosing appropriate indicators

When data were collected from the field, the use of complex measurements was, as far as possible, avoided so extension workers can use the

methodol-ogy in the future. This had particular bearing on the biophysical data. The collection and analysis of soil and plant samples and the accurate measurement of yield, nutrient inputs, erosion and runoff would have enabled more direct comparisons between farmers in the same and in different areas, but such analyses are beyond the resources of most groups involved in im-plementing SLM strategies. Comparisons of the more practical descriptive analyses collected in these stud-ies are more difficult and less precise.

This problem highlights the need to develop and use reasonably accurate surrogate indicators of im-portant characteristics of farming systems, such as soil fertility, nutrient balance, and erosion, runoff and leaching (Fairhurst et al., 1998). Such surrogate indi-cators would enable extension workers and farmers to develop and implement improved land management

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strategies without recourse to laboratory analyses, and enable them to assess the relative sustainability of different farming systems. On reflection, the inclusion of more specific measurements in these case studies may have been a useful step to develop improved surrogate measures, using correlation analyses, that could be used as indicators of SLM.

Gomez et al. (1996) used correlation analysis to choose appropriate indicators from a suite of biophys-ical factors. Through this process, they identified in-dicators that represented what they considered to be major components of sustainability: indicators that ex-hibited sufficient variance to indicate sensitivity to changes in management, were highly correlated with associated indicators, poorly correlated with indica-tors of other components of sustainability, and were relatively cheap and easy to measure.

Another problem with data of this nature is that it is highly inter-related. In many cases, the indicators identified in this study are pre-indicators or evalua-tion factors, which need to be integrated to develop appropriate indicators. For instance, information on inputs of fertiliser and organic residues are not good indicators, but when used together, and in conjunction with information on residue management and yield, they can result in an estimate of nutrient balance, which can be used as an indicator. Similarly, while farm income is important, it must be interpreted along with information on subsistence food production, debt servicing, and other expenditure.

Assessment of the socio-economic factors from the site in Thailand highlights a number of these complex interactions and trends. By identifying these factors and characteristics, and by establishing and under-standing their interactions and trends, it is hoped that single evaluation factors can be combined and repre-sented by an indicator that reflects more accurately the sustainability of a particular land-use in a defined locality. Threshold levels of these selected integrated indicators can then be developed to cover a range of systems.

An example of the problems that arise with sin-gle factor analyses is the assessment of political involvement by villagers. For instance, within the macro-political framework, the villagers were as-sessed to have a low degree of political participation and an unclear legal status, due to their status as an ethnic minority group. Their presence as farmers on

marginal land claimed by the state is tolerated, al-though their freedom of movement is sometimes lim-ited. Due to the low degree of political participation, the upland minorities are supported by Thai NGOs, which are allowed to operate freely and provide de-velopment assistance. NGOs and other groups, such as academics, have become influential advocates for the interests of minority groups, and, in some cases, have lobbied successfully to improve their legal status and their access to resources and infrastructure. Thus, although the answers to some questions indicate their direct political participation is limited, their situation, as revealed through more integrated PRA techniques, is not as serious as if they had no influential advo-cates. Developing an indicator for this situation is very complex, but especially when this is attempted with a single factor as the sole measure.

Similarly, the issues of labour, farm income, and debt are very complex and inter-linked. Until the impact of the current economic downturn, there was an acute labour shortage in northern Thailand due to the labour intensive nature of upland farming and the opportunities for off-farm employment in one of the country’s booming urban areas or abroad. As a result of off-farm employment, farm incomes increased in recent years, with mixed impact on farming systems. While some farmers invested part of their increased earnings in purchasing modern inputs for their farms or improving their farming systems, others, quite un-derstandably, acquired consumer goods or built a new existence in their new, mostly urban surroundings. As such, assessment of off-farm income is only a component of the direct impact on farming systems. Evaluation factors like labour, income, and debt need to be translated into more meaningful, integrated or composite indicators.

4.2. Development of a prototype decision support system to assess sustainability

A prototype DSS was developed, to assess the sta-tus of each of the five pillars, using the responses to 26 questions based on the indicators listed in Tables 1–5. The answers to each question are characterised as hav-ing a weighted impact on the particular pillar to which they are associated in terms of four discrete categories: (i) meeting the requirements of sustainability, (ii) be-ing marginally above the threshold for sustainability,

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(iii) being marginally below the threshold, or (iv) not meeting sustainability. Summation of the various in-dicators translates to a score between 0 and 1 for each pillar. The overall sustainability of the system is then assessed on the status of the five pillars, and most par-ticularly on the status of the least sustainable pillar.

The aim of this exercise was to assess the sustain-ability of smallholder farmers in sloping uplands of SE Asia. As was expected, highly site-specific indi-cators were developed. In addition, the relevance of some of these indicators to these specific sites was limited due to the effort to maintain simplicity. While many of these indicators can be made more general, it is unlikely that a truly generic approach to SLM assessment will eventuate.

Validation of indicators of SLM and of the DSS is not easy due to the complex nature of sustainability and the necessity for medium to long-term evaluation; they cannot be verified with a precise measure of sus-tainability. Feedback from the farmers and researchers helped to increase confidence in the process. In a sub-sequent study, the prototype was adapted for use in the middle hills region of Nepal with input from farmers,

Table 6

Results of sustainability assessments using two related versions of the DSS in (a) sloping lands of Vietnam (V) and Indonesia (I), and (b) the middle hills region of Nepal (N)a,b

Pillars Assessment categories

Meets sustainability Marginally above threshold Marginally below threshold Not sustainable

Productivity V2, V3, V5 V1, V4

I1, I2

N3, N4, N5, N7 N1, N2, N6, N9 N10 N8

Security V1, V3, V4 V2, V5

I1, I2 N1, N2, N3, N4, N5, N6, N7, N8, N9 N10

Protection V1, V2, V4, V5 V3

I1, I2

N1, N2, N3, N4, N5, N6, N7, N8, N9, N10

Economic viability V1 V2, V3, V4, V5

I1, I2

N1, N4, N5, N6, N7 N2, N3 N8, N9, N10

Social acceptability V1, V2, V3, V4, V5 I1, I2

N1, N2, N3, N4, N5, N6, N7, N8, N9, N10

a_{Bold symbols indicate the farms assessed as sustainable for all five pillars of sustainability.} b_{Source: data for Nepal from Rais et al. (1998b).}

extension officers and researchers (Rais et al., 1998b). The same basic structure was used with changes to the questions to suit the agroecological and socio-cultural systems. One indicator was added, to take into ac-count the potential damage from hail and windstorms, the answers and/or thresholds of 18 questions were changed to suite the different farming systems and environment, and eight essentially remained the same. In this Nepali study, the use of the DSS structure as a process to quickly adapt a system of SLM evaluation was deemed successful. Of course, the accuracy with which sustainability was assessed could not be veri-fied. These assessments indicated only three out of 10 farms as sustainable, with the majority of unsustain-able farms being considered so in terms of economic viability, and no farms considered unsustainable in terms of social acceptability (Table 6). These results compare with those of five farmers in the Vietnam study and two in the Indonesia study. Although none of these seven farming systems were assessed as meeting the requirements of sustainability for all the five pillars, all were at least marginally above the threshold for sustainability. In contrast, some of the

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Nepali farms were assessed as being marginally be-low the threshold, or not meeting the requirements for sustainability.

5. Conclusions

Evaluation of the indicators and of the DSS, in com-bination with more retrospective theoretical evalua-tions, indicate a number of shortcomings with respect to the indicators used and the structure of the DSS.

As many of the indicators are referred to more ac-curately as evaluation factors, or pre-indicators, these should be developed to attain more cumulative and integrative, or composite indicators. Good examples of more integrative indicators that may prove useful in subsequent SLM evaluations are nutrient balances and yield gap analyses (e.g. Bindraban et al., 2000). Similarly, useful surrogate indicators need to be iden-tified to take the place of some of the more complex indicators.

In addition to problems with respect to the indica-tors being used, there are a number of limitations in terms of the way they are used, as a result of the struc-ture of the DSS. Firstly, each factor or indicator is assumed to be independent of other factors, and only influencing one of the five pillars of sustainability. Clearly, some factors will impact on various compo-nents of sustainability at the same time and may be affected by other indicators, either positively or neg-atively. The use of true indicators, rather than factors, may reduce this problem, however, the structure of the DSS needs to be modified so the value of one indicator can affect the outcome of another. Secondly, the rank-ing of indicator outcomes into discrete categories may cause problems when the degree to which an indicator or factor is satisfied has minimal impact on the rat-ing. Thirdly, there is limited basis for the weightings ascribed to the different outcomes, especially where the degree of satisfaction of the factor or indicator is minimised through the use of discrete categories.

The main problems with the current DSS prototype are that the evaluation factors need to be developed into true SLM indicators that are more complex and integrative, and the simple linear structure of the DSS needs to be converted into a more complete and com-plex expert system. Despite these shortcomings, the process of a structured and systematic evaluation of

farming systems, with involvement of a wide range of stakeholders, shows significant promise.

Acknowledgements

The work discussed in this paper would not have been possible without the support and collaboration of the farmers and NARES in Vietnam, Indonesia, Thai-land and Nepal. Staff at IBSRAM, including Fabrice Renaud, Pay Drecshel and, most particularly, Adisak Sajjapongse, contributed to the process of identify-ing the biophysical evaluation factors and indicators and the associated thresholds. A number of donors provided financial support to this, and related activi-ties. The International Development Research Centre (IDRC) provided funding for this specific activity, and for one of the authors (MR).

References

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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 0 0 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 0 0 2–3 crops, no conservation

1 crop with conservation 1 crop, no conservation

Cropping pattern Rice or corn then fallow 14 6 0 Include fruit gardens and agroforestry Rice then corn

Rice/corn then legume etc. Rice/corn 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:C>1.25) 20 0 0 Total income of family

Constant (B:C=1) Declining (B:C<1) Fluctuating

Off-farm income >25% of total income 15 5 0 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 0 0 1.5–2 ha per family

1–2 ha >2 ha

Availability of farm credit >50% of requirement 15 5 0

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

(2)

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 0 0

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 0 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 0 10–20% of total cost

25–50% <25% No subsidy

Training in conservation practices Once in 3 years 18 2 0 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

4. Use and assessment of indicators

4.1. Choosing appropriate indicators

When data were collected from the field, the use of complex measurements was, as far as possible, avoided so extension workers can use the

(3)

4.2. Development of a prototype decision support system to assess sustainability

(4)

Table 6

Results of sustainability assessments using two related versions of the DSS in (a) sloping lands of Vietnam (V) and Indonesia (I), and (b) the middle hills region of Nepal (N)a,b

Pillars Assessment categories

Meets sustainability Marginally above threshold Marginally below threshold Not sustainable

Productivity V2, V3, V5 V1, V4

I1, I2

N3, N4, N5, N7 N1, N2, N6, N9 N10 N8

Security V1, V3, V4 V2, V5

I1, I2 N1, N2, N3, N4, N5, N6, N7, N8, N9 N10

Protection V1, V2, V4, V5 V3

I1, I2

N1, N2, N3, N4, N5, N6, N7, N8, N9, N10

Economic viability V1 V2, V3, V4, V5

I1, I2

N1, N4, N5, N6, N7 N2, N3 N8, N9, N10

Social acceptability V1, V2, V3, V4, V5 I1, I2

N1, N2, N3, N4, N5, N6, N7, N8, N9, N10

a_{Bold symbols indicate the farms assessed as sustainable for all five pillars of sustainability.} b_{Source: data for Nepal from Rais et al. (1998b).}

(5)

Nepali farms were assessed as being marginally be-low the threshold, or not meeting the requirements for sustainability.

5. Conclusions

farming systems, with involvement of a wide range of stakeholders, shows significant promise.

Acknowledgements

References

Alexandratos, N., 1995. World Agriculture: Towards 2010. An FAO Study, Food and Agriculture Organization of the United Nations, Wiley, UK, 488 pp.

Dumanski, J. (Ed.), 1998. Guidelines for conducting case studies under the international framework for evaluation of sustain-able land management. http://www.ciesin.org/lw-kmn/slm/ guideslm.html.

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Montpellier, France, August 1998. ISSS/CIRAD, CD-ROM, Symposium 12.

Smyth, A.J., Dumanski, J., 1993. FESLM: An International Framework for Evaluating Sustainable Land Management. World Soil Resources Report no. 73, FAO, Rome.

Directory UMM :Data Elmu:jurnal:A:Agriculture, Ecosystems and Environment:Vol81.Issue2.Oct2000:

Indicators for sustainable land management based on farmer

surveys in Vietnam, Indonesia, and Thailand

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