The adoption of sustainable practices: Some new insights An analysis of drivers and constraints for the adoption of sustainable practices derived from research
July 2001
John Cary, Trevor Webb1 and Neil Barr2 1Social
Sciences Centre Bureau of Rural Sciences Canberra 2Department of Natural Resources and Environment Victoria
Land & Water Australia Project Reference Number:BRR19
Principal Investigator: Ass/Prof John Cary Social Sciences Centre Bureau of Rural Sciences PO Box E11 KINGSTON ACT 2604
Collaborators: Dr Trevor Webb Social Sciences Centre Bureau of Rural Sciences PO Box E11 KINGSTON ACT 2604 Dr Neil Barr Department of Natural Resources and Environment BENDIGO VIC 3550
Preferred way to cite this report: Cary, J.W., Webb, T. and Barr N.F. (2001) The adoption of sustainable practices: Some new insights. An analysis of drivers and constraints for the adoption of sustainable practices derived from research. Land & Water Australia, Canberra. This report does not represent professional advice given by the Commonwealth or any person acting for the Commonwealth for any particular purpose. It should not be relied on as the basis for any decision to take action or not to take action on any matter which it covers. Readers should make their own further enquiries, and obtain professional advice where appropriate, before making any such decision. The Commonwealth and all persons acting for the Commonwealth in preparing this booklet disclaim all responsibility and liability to any person arising directly or indirectly from any person taking or not taking action based upon the information in this booklet.
Contents CONTENTS
III
LIST OF TABLES
V
LIST OF FIGURES
V
EXECUTIVE SUMMARY
1
INTRODUCTION Project objectives Background The principal issues for sustainable practice adoption
3 3 3 4
SUSTAINABLE PRACTICES Sustainable resource management outcomes
5 6
A FRAMEWORK FOR APPRAISING SUSTAINABLE PRACTICES
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FORGOTTEN FOCUS – ATTRIBUTES OF SUSTAINABLE PRACTICES How landholders see NRM practices – the key issues The attributes of sustainable agriculture practices Categorising NRM practices A case example: phase farming with dryland lucerne
10 10 10 12 16
LEARNING ABOUT SUSTAINABLE PRACTICES Categorising the learning focus Reasons for learning Styles of learning
19 19 19 20
SOME RECENT AUSTRALIAN FINDINGS ON FACTORS ASSOCIATED WITH THE ADOPTION OF SUSTAINABLE PRACTICES Age Education Property size Farm business Stewardship Recent findings regarding attitudes Other characteristics
22 24 25 25 25 25 26 26
MODELING ADOPTION BEHAVIOUR FROM THE 1998-99 RESOURCE MANAGEMENT SURVEY Introduction Modelling farmer behaviour Findings Summary
28 28 28 30 34
ATTITUDES AND VALUES AND THE ADOPTION OF SUSTAINABLE PRACTICES Attitudes Beliefs Values A framework of environmental concern Values and the appraisal of sustainable management practices
35 35 35 35 36 37
INTERVENTIONS TO PROMOTE ADOPTION OF NRM PRACTICES Consequences for adoption of sustainable practices
39 40
IMPLICATIONS FOR THE FOCUS OF R & D
41
PERFORMANCE INDICATORS AND COMMUNICATION ACTION PLAN Performance indicators for assessing the effectiveness of adoption of R&D results Communication action plan
43 43 44
iii
REFERENCES
45
APPENDIX A ANALYSIS OF THE 1998-99 RESOURCE MANAGEMENT SURVEY Logistic regression Model estimation Results
49 49 49 49
APPENDIX B DESCRIPTION OF VARIABLES USED IN LOGISTIC REGRESSION ANALYSES
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List of tables Table 1 Characteristics of sustainable practices..................................................................................................................................... 13 Table 2 Solutions’ National Indicators ..................................................................................................................................................... 24 Table 3 Landholder and property characteristics with significant relationships with adoption of best practices ................................. 27 Table 4 Variables explored in analysis of Resource Management Supplementary survey.................................................................. 29 Table 5 Resource management practices investigated.......................................................................................................................... 30 Table 6 Characteristics significantly associated with practice adoption ................................................................................................ 31 Table 7 Factors which are associated with the adoption of sustainable management practices (shaded cells indicate association relationships in predicted direction).................................................................................................................................................. 32 Table A1 Logit regression results for the adoption of controlled flow bores in the pastoral zone. ....................................................... 50 Table A2 Logit regression results for the control of grazing pressure by excluding access to water in the pastoral zone................. 51 Table A3 Logit regression results for the adoption of monitoring pasture and vegetation condition in the pastoral zone.................. 52 Table A4 Logit regression results for the adoption of deep rooted perennial pasture in the wheat-sheep and high rainfall zones (broadacre industries only). .............................................................................................................................................................. 53 Table A5 Logit regression results for the adoption of soil/plant tests to determine fertiliser needs in the wheat-sheep and high rainfall zones (broadacre industries only). ....................................................................................................................................... 54 Table A6 Logit regression results for the establishment of trees and shrubs in the wheat-sheep and high rainfall zones (including dairy industries)................................................................................................................................................................................. 55 Table A7 Logit regression results for the regular monitoring of watertables in the wheat-sheep and high rainfall zones (including dairy industries)................................................................................................................................................................................. 55 Table A8 Logit regression results for the collection of dairy effluent (dairy industry only).................................................................... 56 Table A9 Logit regression results for the pumping of dairy shed effluent onto pasture (dairy industry only). ..................................... 57 Table A10 Logit regression results for laser graded layout on irrigated farms...................................................................................... 57 Table A11 Logit regression results for the use of irrigation scheduling tools on irrigated farms.......................................................... 58 Table A12 Logit regression results for monitoring of pasture and vegetation condition (all farms). .................................................... 59 Table A13 Logit regression results for preservation or enhancement of areas of conservation value (all farms)............................... 60 Table A14 Logit regression results for the exclusion of stock from degraded areas (all farms)........................................................... 61 Table A15 Logit regression results for the percentage of the farm under conservation tillage (all farms)........................................... 61
List of figures Figure 1 Model of Adoption of Sustainable Land Management Practices [Modified from Fenton, Macgregor & Cary (2000)]............ 7 Figure 2 Area of mixed lucerne pasture and adoption of mixed lucerne pasture in the North Central catchment region of Victoria: 1996-99 (Source: ABS)..................................................................................................................................................................... 18 Figure 3 A framework of environmental concern (after Stern et al. 1995). ........................................................................................... 36 Figure 4 Conditions for maximum influence of environmental values or attitudes on individual’s decision to adopt sustainable practices ............................................................................................................................................................................................ 38
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Executive Summary
The rate of adoption of sustainable practices derived from research depends on practices being economically attractive to adopt.
Effective R&D intervention means designing practices to provide external benefits to make environment-sustaining behaviour more likely. It is the inherent characteristics, or attributes, of practices derived from research which largely determine their rate of adoption by producers. Adoption of recommended sustainable practices depends largely on whether landholders think they are profitable. Sustainable NRM practices which provide economic and other advantages will be adopted more rapidly. Recent low commodity prices in the broadacre industries reduced the attractiveness of adoption of many practices. Landholders generally seek to reduce the risk of adopting a new practice. Sustainable NRM practices which are observable, trialable, and less complex are generally more quickly adopted than NRM practices which are unobservable, untrialable, and complex.
Rational self-interest predominates in human assessment of sustainable practices.
Humans are adaptive in implementing NRM practices rather than simply reactive to information, promotional appeals or exhortations to farm sustainably. The use of sustainable practices will depend on how landholders assess the value of recommended practices and their own and others’ experience with use of such practices. Characteristics of the practices – and their overwhelming influence on adoption – often confound the influence of other factors such as social characteristics.
Linkages between eventual sustainable outcomes and sustainable practices are often distant and uncertain thus reducing incentive to act.
It is often difficult for landholders to see the connection between recommended NRM practices and sustainability. The difficulty, for landholders, of observing linkages between many recommended NRM practices and desired sustainable outcomes reduces positive appraisals of NRM practices by landholders. As a result, they are often lukewarm about NRM practices that are promoted predominantly on the basis of making land use more sustainable.
Think locally and act locally.
There are obvious advantages in being able to promote sustainable practices with more universal or global applicability. However, given Australia’s diverse environment, there are few sustainable practices that meet the test of global applicability. Universally applicable practices are often less likely to have large impacts on reducing local land degradation problems. Increased effort needs to be applied to identify and develop locally applicable sustainable practices and effort made to resist the temptation to promote them beyond localities where their advantage has been established.
Select sustainable practices on the basis of attributes which enhance likelihood of adoption.
It is more effective, in the first instance, to look for sustainable practices with characteristics influencing more rapid adoption behavior rather than depending on pro-environmental values of landholders or on individual feelings, preferences, and perceptions for improving the land environment.
Social and perceptual factors influence adoption rates of sustainable practices.
Factors related to landholder characteristics that potentially influence capacity to change are: level of farm income, landholder age, landholder participation in training, having a documented farm plan and membership of landcare. There are often interactions between these characteristics; and the relationships with adoption behaviour are not always unequivocal. Personal financial capacity has been observed to be an important component in determining the capacity of landholders to adopt new practices. Landholders’ perceptions of their future financial situation were more often associated with practice adoption than were objectively measured indicators of current financial position. Landholders who feel secure in their financial 1
future are more likely to invest resources in adopting new resource management practices. Pro-environmental or ‘green’ values and attitudes have a relatively minor influence on the adoption of sustainable practices.
Pro-environmental or ‘green’ values and attitudes have a relatively minor influence on the adoption of sustainable practices. The effect of positive attitudes towards the environment is constrained by the influence of prevailing incentives or disincentives to adopt a sustainable practice. Positive attitudes towards the environment act in combination with external incentives or disincentives (such as costs, benefits, convenience, or uncertainty of outcome of a given practice) to determine adoption behaviour. The effect of strongly positive environmental attitudes on sustainable practice adoption tends to be influential when there are no strong external incentives (rewards) or disincentives (punishments) for undertaking the practice. Positive environmental attitudes have little effect on behaviour when external incentives are strongly positive or negative. In such cases it is the external factors which effectively compel or prohibit the behaviour in question. The strength of the external conditions determines the bounds of influence of positive environmental attitudes and values.
Principles which predict likely human behaviour can assist in selecting and promoting sustainable practices.
When assessing the characteristics of potential new sustainable practices, and when seeking to promote the use of such practices, there are a number of human behaviour principles that should be considered. If the ‘behaviour’ associated with the practice cannot be readily seen (ie it is not observable) by the individual and by others it will be ineffective to encourage it. It will be difficult to be monitored, to be seen as rewarded (or penalised, for its absence). As most human behaviour is undertaken to gain a positive consequence or avoid a negative consequence, humans learn more from their successes (which provide positive reinforcement) than they learn from their mistakes. The significant negative consequences of unsustainable consequences will not be experienced until long into the future. Research and development of on-farm sustainable practices needs to identify practices with relatively immediate positive consequences rather than less immediate, diffused, or short-term negative, consequences. Practices that have outcomes that are ‘soon’ and ‘certain’ will have the most powerful drivers for rapid adoption.
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Introduction Land & Water Australia (LWA) established the Social and Institutional Research Program (SIRP) to ensure that biophysical research and development (R&D) also takes into account social and institutional factors. LWA has identified a considerable gap in understanding the social, economic and institutional factors that are conducive to implementation and adoption of sustainable resource management practices (Mobbs & Dovers 1999). The LWA Strategic R&D Plan places greater emphasis on researching the social, institutional and economic issues which may be constraining the development and adoption of more sustainable natural resource management. The Strategic R&D Plan also seeks to identify opportunities to create a more enabling environment for sustainable natural resource management. This review and analysis of the drivers of, and constraints to, producer adoption of sustainable practices derived from research presents current knowledge on adoption influences, risks and processes as they relate to resource management R&D. We develop some new insights that should ensure more realistic assessments of the likely response of landholders to the problems of sustainable resource use. An important purpose of the project is to increase the effectiveness of future research and the adoption of research results by producers and landholders. The framework proposed by LWA for analysis of the drivers of, and impediments to, the adoption on R&D results includes:
Project objectives The major project objective was to review and analyse the drivers and constraints to adoption of sustainable practices in agriculture derived from research. More specifically the following objectives were to be achieved: • review existing knowledge • identify impediments and drivers for the adoption of sustainable practices from R&D • provide advice and options on strategies for overcoming impediments • key performance indicators for assessing the effectiveness of producer adoption of R&D • prepare a communication action plan for the project.
Background In 2000 the Bureau of Rural Sciences (BRS) completed a review of factors influential in determining individual NRM decisions (Barr & Cary 2000). That review established a number of important findings that provided a basis for the development of this Report:
• how they learn about, and understand, those resources and the management of them
• Encouraging the adoption of more sustainable practices by appealing to farmers’ stewardship ethic or altruism will have only limited impact. The presence of factors like the relative financial benefit or cost of the NRM practice, farm financial capacity, farmer skills and motivation are the necessary determinants as to whether sustainable management practices are likely to be adopted.
• how they actually manage them and incorporate new management approaches arising from research into their practices
• Policies aimed at changing motivation in the absence of meeting the other enabling conditions will achieve little.
• how they are influenced by the wider economic, social, legal, commercial, policy and institutional environment.
• Responses to messages about future threats of land degradation are likely to be limited.
The project embraces an integrated approach to focus on the relationships between developing awareness, values and understanding, acquiring required knowledge and skills, and adopting sustainable natural resource management (NRM) practices as part of integrated management systems.
• Australian research regarding how landholders perceive their environment and the threat of land degradation shows landholders generally underestimate the land degradation problems on their own farm.
• how producers and other land holders perceive and value their natural resources on a property level and wider catchment and regional scales
This project builds on these findings to develop a conceptual approach regarding the relationships between factors that are relevant in any assessment of likely adoption of sustainable practices derived from research and producer initiated and managed R&D.
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The principal issues for sustainable practice adoption The idea that there is a key to the adoption of sustainable practices is somewhat simplistic and unidimensional. It is implied in assertions such as “We just need to convince them to change”. The assumption is, if sustainable outcomes are to be achieved and appropriate sustainable practices are available, an understanding of human motivation will provide the touchstone to unlock human capacity to change. In fact, land managers differ significantly in different localities in Australia and, for many localities, there are few appropriate sustainable practices that meet criteria which would lead to ready adoption. Many of the desired outcomes of sustainable NRM programs do not come about autonomously. NRM programs present a policy challenge because of the range of constraints that discourage individual uptake of NRM practices. Constraints to change in NRM systems can be assessed from the perspectives of individual landholders, the characteristics of desirable management practices, the socio-economic structure of catchment communities and the broader institutional settings. A significant issue is that economic costs to a landholder of at least some NRM practices (particularly those which provide benefits desired by the wider community) may exceed the on-farm benefits on a short or long-term basis. The lack of immediate financial incentive in a dynamic farm economy may result in many landholders not adopting these practices. Identification of the social and economic factors that constrain the participation of individual land managers recognises that the significant decisions about land and farm management are made by ‘individual farmers, not by catchment groups or regional river management bodies’ (Pannell 2001a). Understanding some, if not all, of the factors that determine individual landholder decisions will ensure more realistic and more effective catchment and regional plans.
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Sustainable practices Sustainable land management practices are defined here as those which ameliorate unsustainable land use by rectifying biophysical constraints to agricultural production and conserve the resource base (SCARM 1998). The following list of sustainable management practices has been developed from SCARM (1998), Hamblin (1999), SCA (1991), management practice indicators for State of the Environment reporting (Saunders, Margules & Hill 1998) and other sources. It should be recognised that this is an incomplete list of sustainable management practices. Many of these practices were identified in the National Collaborative Project on Indicators for Sustainable Agriculture based on then available ABS and ABARE 1 statistics. Measures of the level of landholder adoption of sustainable management practices available from the current ABARE Australian Resource Management Supplementary surveys are identified with the superscript a.
• use of integrated pest management (reducing pesticide use)
• maintenance of soil cover
Irrigation farms
• establishing and monitoring ground cover targets – monitoring of pasture and vegetation condition a
• irrigation scheduling a
Cropping farms • use of reduced or zero tillage – minimum tillage a • stubble or pasture retention in ploughing – direct drilling a • use of crop or pasture legumes in rotations a • use of contour banks in cropland a • strip cropping a • adjusting crop sequences in response to seasonal conditions
• laser graded layout a
• nutrient balance accounting (soil and plant sampling) • soil and plant tissue tests to determine fertiliser needs
• slashing and burning of pastures
• storage and reuse of drainage water a a
• automated irrigation a
• regular soil testing
Rangelands
• fertilising of pastures
• control grazing pressure by excluding access to water a
• agricultural lands treated with gypsum
• control of water flow from bores a
• agricultural lands treated with lime
• piped water supplies for stock a
• regularly monitor water tables a
• pastoral land stocked at recommended rates
• use of deep-rooted perennial pastures a
• degraded pastoral land converted to less damaging use
• non-commercial tree and shrub planting a
• pastoral land destocked in low feed conditions
• commercial tree and shrub planting (farm forestry) a
Dairy farms
• preserve or enhance areas of conservation value a
• use of effluent disposal systems– collection of dairy effluent (ponds or drainage sump) a
• retention of vegetation along drainage lines a
• pump dairy shed effluent onto pasture a
• protection of land from stock by fencing – exclude stock from degraded areas a
Many of these farming practices are specific to particular environments or to particular farming systems. The SCA (1991) report identified the potential relevance of many of these practices for the sustainable management for 46 agro-ecological regions of Australia.
• protection of waterways from stock by fencing a • animal pest or weed control to control land degradation a
• pest and disease control in pastures 1
While ABARE farm surveys provide more reliable, in-depth information than ABS agricultural census data they are selective in industry coverage and geographic spread.
Not all the NRM practices listed above will, in isolation, lead to sustainable resource management (for example, fertilising of pastures). What might be sustainable on a farm might be unsustainable for rivers etc. Hence, the practices which effectively contribute to sustainability will depend on the context and the locality of their use. If one farmer
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adopts a ‘sustainable’ practice, it could be totally ineffective if neighboring landholders do not adopt complementary practices.
Sustainable resource management outcomes The use of the sustainable practices listed above are contended to lead to more sustainable resource management. The association is often constrained – it is likely to vary for different localities. The impact of use of a practice may also have long time lags before a more sustainable outcome is achieved. Broader conceptions of sustainable management embrace the need for strategies for sustaining both food security and the need to conserve natural resources. Definitions of sustainable resource management in agriculture are generally concerned with the need for agricultural practices to be economically viable, to meet human needs for food, to be environmentally benign or positive, and to be concerned with quality of life. Since these objectives can be achieved in a number of different ways, sustainable resource management is unlikely to be linked to any particular management practice. Rather, sustainable agriculture is thought of in terms of its adaptability and flexibility over time to respond to the demands for food and fibre, its demands on natural resources for production, and its ability to protect the soil, water and other natural resources. This goal requires an efficient use of technology in a manner conducive to sustainability (Wilson & Tyrchniewicz 1995). Because agriculture is affected by changes in markets and resource decisions in other sectors and regions, such changes often provide additional pressures leading to depletion of local agricultural resource bases. Assessments of the sustainability of a production system involve looking forward, to a future that is often not universally agreed. It is often easier to look backward, and assess the progress of production systems as they evolve from unsustainable states. The process is further complicated because a sustainable state of resource management is not a fixed or ideal steady state, but rather an evolutionary process of attempting to improve the management of systems, through improved understanding and knowledge. The process is not deterministic as the end point is not known in advance (Wilkinson & Cary 2001). Sustainable resource management is often an abstract state – which occurs in the future and may be hard to identify or measure. Sustainable practices (which lead to sustainable states or outcomes) are used as ‘indicators’ or proxies for sustainable management.
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A framework for appraising sustainable practices The development of a model of conceptual relationships helps to understand the place of sustainable practices that lead to more sustainable outcomes. Additionally it helps to focus on important factors influencing how landholders, or other decision-makers, might perceive these relationships. Any attempt to derive a complete predictive model which encompasses all possible environmental, behavioural, social and economic indicators, and which identifies the inter-relationships amongst possible relevant variables would be counter-productive and lead to confusion given the current state of knowledge and research in this area. Furthermore, given the heterogeneity of resource management situations, the development and application of a generalised predictive model at a national scale, which is meaningful in relation to all farming practices, would require more extensive knowledge and data than is currently available. The model in Figure 1 is a conceptual model rather than a predictive model. Figure 1 shows some broad groups of factors that influence the adoption of NRM practices that
are proposed to bring about more sustainable land management. The characteristics of locality and environment, and the characteristics of specific adoption practices, which are both extremely significant in landholder appraisal of NRM practices are specifically identified. The model also shows that there is usually more than one NRM practice that needs to be embraced to bring about more sustainable land management. Institutional characteristics incorporate the more formal structures that determine the ‘social’ environment in which landholders decide or anticipate decisions regarding adoption of sustainable practices. Institutional characteristics incorporate the regulatory environment, government agency support structures, and government policy reflected in incentive schemes and taxation arrangements. Individual and social characteristics include many factors such as age and education and cognitive factors that are largely instilled and maintained through social processes. No attempt is made here to further elaborate all the elements that might comprise individual and social characteristics.
Adoption of Recommended NRM Practice 1
Locality and Environmental Characteristics Characteristics of Practice j
Institutional Characteristics
NRM Practice j
Sustainable Land Management
Appraisal
Individual and Social Characteristics
NRM Practice n
PROCESSES
OUTPUTS
OUTCOMES
Figure 1 Model of Adoption of Sustainable Land Management Practices [Modified from Fenton, Macgregor & Cary (2000)]
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The model emphasises that adoption of sustainable NRM practices is not uni-dimensional, consisting of a potentially wide range of practices that are dependent upon appraisals by landholders. These appraisals are mediated by environmental, institutional, individual and social factors prior to any implementation. Central to the model presented in Figure 1 is the appraisal process undertaken by the individual adopter or group of adopters. Appraisal often involves a complicated psychological calculus by an individual to arrive at a decision. Appraisal has the elements of a ‘black box’ – it may be objectively difficult to know the relative influence of the factors that may determine an adoption or non-adoption decision. Social factors such as land manager attitudes and beliefs about specific NRM practices, and about broader natural resource management, will influence adoption of specific practices. Appraisal will also be influenced by land manager attitudes towards those organisations and institutions that may be promoting sustainable land management practices. Differences in appraisal are determined by a range of individual, institutional and contextual variables and by complex interactions amongst these variables. For example, negative attitudes towards the land, as in the belief that the land is ‘rubbish country’, is a component of appraisal which includes beliefs about land and land management which may act as a barrier to the adoption of sustainable land management practices. The existence of this belief may be due to specific individual characteristics, historical relationships between the farmer and those agencies promoting sustainable land management and specific environmental and locality characteristics in which farming occurs. To date there is limited understanding or research on the appraisal component and its relationship to the adoption of sustainable land management practices and, because appraisal is a complex process, there are no existing indicators of appraisal.
Human appraisal as an adaptive system Adaptation in biological usage is the process by which an organism fits itself to its environment. Complex adaptive systems are systems comprised of interacting agents who change their ‘rules of behaviour’ as their experience accumulates (Holland 1995). In a complex adaptive system a major part of the environment of any given adaptive agent (in this case landholders) consists not only of the biophysical environment but of other adaptive agents including institutions (Figure 1). The focus of an adaptive system is on improvement rather than optimisation (or the attainment of some equilibrium). The other focus of an adaptive system in areas such as evolutionary systems theory is the idea of an iterating process of stimulus and response (or learning). Human behaviour is characterised by continuous human learning and complex responses to stimuli that rarely produce observable constancy. This is because most human
behaviour occurs in environments where humans interact and respond – by actively changing environmental states – rather than simply reacting to them. This process can be described as reflexivity. Reflexivity emphasises the uncertainties involved in seeking to achieve more sustainable resource management (uncertainties which are generally inadequately acknowledged). Soros (2000), who has applied the concept of reflexivity to explain the failure of equilibrium theory in describing human behaviour in financial markets, provides a simple description of reflexivity: . . . our understanding of the world in which we live is inherently imperfect. We are part of a world we seek to understand, and our imperfect understanding plays an active role in shaping the events in which we participate. There is a two-way interaction between our understanding and these events that introduces an element of uncertainty into both. It ensures that we cannot base our decisions on (perfect) knowledge and that our actions are liable to have unintended consequences. The two effects feed on each other. I call this twoway feedback mechanism reflexivity . . .(p. xxii)
Another way of describing reflexivity is that thinking participants seek to understand the situation in which they participate and, as well, they participate in the situation that they seek to understand (Soros 2000, p. 7). Figure 1 is an example of an adaptive behavioural system which has been kept as simple as possible. Solid lines indicate more certain associations; broken lines indicate associations about which less is likely to be known, or where the association may be problematic or intermittent. Single arrows indicate a likely one-way or recursive relationship; double arrows indicate a likely two-way or nonrecursive (reflexive) relationship. There are important reflexive, or feedback, loops between appraisal and the adoption of given sustainable practices. Landholders assess such practices for potential adoption and any adoption of a practice either by the landholder, or by others who’s experience can be observed by the landholder, will influence how the appraising landholder subsequently views (appraises) the adoption of that practice and related practices. More importantly, there are few feedback loops between ultimate states of sustainable land management and NRM practices because there are usually long time lags from the implementation of an NRM practice to the outcome of a ‘sustainable state’. Thus landholders cannot be readily assured with reasonable feedback from their own observations that a practice produces a desired ultimate outcome. The process of appraisal deliberately subsumes the complex and differing human motivations that may influence NRM behaviour. The ability to choose one’s motivations distinguishes humans from other animals. As a
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consequence there can be no certainty about human motivations (Soros 2000).
Sustainable outcomes and NRM outputs The problem of the usually long time lag from the implementation of an NRM practice to the outcome of a sustainable state can be thought of as being represented by different levels of abstraction – the desired sustainable state is more difficult to observe (and to measure). This ‘end’ state can be considered an outcome. The means of approaching the end state is easier to observe (and to measure) and can be labeled an output. This acknowledges that states can be observed (and measured) at different levels of abstraction. Usually, the less abstract the state the easier is its measurement. Typically, outcomes will be represented by biophysical and ecological attributes that characterise sustainable systems. Outputs, such as appropriate vegetation cover, are posited to lead to desired outcomes. NRM practices are typically directed to producing outputs that subsequently lead to desired outcomes (Figure 1). Additionally, we can identify processes which (often more tenuously) contribute to outcomes. Processes include behaviours (eg participation in landcare) that contribute to desired outcomes, and also include attitudes and social learning, which are clearly social in nature. It should be noted that the distinctions between these categories may not always be clear-cut. Understanding some, if not all, of the factors that determine individual landholder decisions will ensure more realistic and more effective catchment and regional plans. In the next section we consider the factors which influence landholder capacity to change to more sustainable resource management practices.
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Forgotten focus – attributes of sustainable practices Sustainable practices have not been tried and found wanting, rather many have been found difficult and not tried.
(apologies to G.K. Chesterton)
How landholders see NRM practices – the key issues In order to understand the key influences determining whether sustainable land management practices are adopted it is necessary to understand both the nature of NRM practices and, more particularly, how landholders see particular NRM practices. Normally, adoption of a given sustainable practice is determined to a large degree by a landholder’s perceived self-interest. Profitability of a practice is an important element of self-interest, even for practices intended to improve land and resource conservation (Cary & Wilkinson 1997; Riley 1999; Drake, Bergstrom & Svedsater 1999; Marsh & Pannell 2000; Curtis et al. 2000). For different localities a particular natural resource management practice varies in terms of its relative profitability and appropriateness for a given farm situation. In other words, a given practice will have different profitability and differing attractiveness to farmers in different regions or localities (Barr & Cary 2000). This will largely reflect different technical, soil, climatic endowments and, probably, the 2 level of land degradation in different localities (Cary 2000). But it may also reflect that a management technology (such as a modified deep-rooted perennial) may be developed and elaborated for one area but not for another. Many practices to ameliorate salinity, for example, are not universally applicable and hence have different profitability in different localities. Additionally, the economic environment for a given farm activity (which influences on-farm implementation of recommended management practices) will in turn be influenced by both local conditions (drought or good seasons) and the external marketplace (expressed in product and commodity prices). Many broadacre farm businesses do not produce sufficient surpluses to allow for reasonable living standards, investments in the farm 2
Perversly, the value of some sustainable management practices is likely to be greater in situations where other factor endowments are high and likely to be less in situations of land degradation where one or other factor endowments are likely to be low.
business and investment in resource protection and the environment. In some regions current adjustment patterns are only slowly creating aggregated businesses more capable of generating appropriate surpluses.
The attributes of sustainable agriculture practices Rogers has summarised the results of the many adoption and diffusion studies conducted in the 1950s, 60s and 70s (Rogers 1962; Rogers & Shoemaker 1971; Rogers 1983). The general conclusions provide a means of analysing environmental innovations and exploring the reasons for the difficulties of promoting certain forms of sustainable agriculture. The importance of innovation characteristics was highlighted in major review of innovation adoption in Australian agriculture by Guerin and Guerin (1994). Important attributes influencing the rate of adoption of NRM practices are the relative advantage, the complexity, the compatibility, the trialability and the observability of a given practice (see Barr & Cary 2000). These attributes together with two other attributes – locality differentials in relative advantage and risk characteristics of a practice – are considered below.
Relative Advantage Relative advantage is normally interpreted in terms of financial advantage to the farm business or the adopter. The perceived financial advantages of environmental innovations (where they exist) have consistently been shown to be one of the best indicators of their subsequent adoption. There is little evidence to suggest that sustainable practices are any different to other agricultural practices in this respect. The nature of limited interaction of pro-environmental attitudes or stewardship values overriding, or compensating for, deficiencies in relative financial advantage of an NRM practice will be developed later in this review. In a review of the history of environmental innovations on Australian farms, Barr and Cary (1992) concluded that the clear lesson was that environmental innovations that were believed to be profitable were usually readily adopted. Innovations with a net financial cost were rarely adopted. The most studied adoption of an environmental innovation is the progress of conservation cropping on the US corn belt. In a review of Ohio research Carboni and Napier (1993) concluded economic factors were the greatest predictors of adoption.
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Locality differentials in relative advantage Frequently it is assumed that the relative advantage of an environment-enhancing practice, if positive, is of the same order of magnitude in different localities. Generally, this is unlikely to be the case. While little empirical evidence for improved resource management practices has yet been collected in Australia to support this common sense assumption, the early work of Griliches (1957, 1960) on the diffusion of the productive innovation of hybrid corn is clearly indicative. Griliches contended that the differences in rates of adoption of hybrid corn for different American states were largely explained by the relative advantage possessed by different geographic regions for growing corn. This reflected productivity of soils, consequential differential profitability of the crop, and differential possession of harvesting and handling resources. As a consequence, hybrid corn was ‘an innovation which was more profitable in the “good” areas than in the “poor” areas’ (Griliches 1960, p. 280). These geographical differences in relative advantage, and consequent differences in rates of adoption, when expressed as diffusion curves (for the same ‘innovation’) have different shapes and, more importantly, different slopes or rates of diffusion (see Cary 2000; Barr & Cary 2000). The important conclusion for the adoption of NRM practices is that the appropriateness and relative advantage of given NRM practices will vary in geographic space to a very large extent.
Risk The motivation of human behaviour is more complex than being simply profit driven. While there is much research demonstrating relationships between beliefs about profitability and adoption behaviour this is mediated by a great variation in attitudes towards business profit and a consideration of the risks that characterise much Australian agriculture. There is strong evidence that many Australian farmers are motivated by the balance between the need for profit and a satisfaction with a comfortable living which minimises risk (Dunn, Gray & Phillips forthcoming; Rendell, O’Callaghan & Clark 1996). Different attitudes to income needs, risk perception, dynastic expectations and cultural expectations of farming mean there are quite distinct groups of farmers. Many farms trade off profit maximisation for risk reduction (Howden et al. 1997; Marks & O’Keefe 1996; Reeve & Black 1993). For many farm operators relative advantage may be strongly moderated by minimisation of complexity and minimisation of risk. As a consequence the differing risk implications of different sustainable practices will be an important consideration in their adoption.
Complexity Sometimes innovations which appear simple may in fact imply significant and complex changes to the farm production system. Such innovations are less likely to be
adopted. Complexity increases the risk of failure; and it introduces increased costs in gaining knowledge (Vanclay & Lawrence 1995). Integrated pest management is an innovation that is constrained by the management complexity of its practise. Farmers often explain non-adoption of integrated pest management as being based upon concerns about its ease of use, speed and reliability (Bodnaruk & Frank 1997). Another example of this complexity characteristic is the planting of dryland lucerne. This is promoted in many catchment plans across Australia as a means of reducing watertable recharge. What appears to be a simple change to a system can imply major restructuring of the farm system. The complexity of adopting the sustainable practice of dryland lucerne and phase farming is explored as a case example later in this section.
Compatibility Compatibility refers to the extent to which a new idea fits in with existing knowledge and existing social practice. If a new idea fits easily into an existing system it will be adopted more quickly. There are usually two ‘systems’ against which the compatibility of a practice will be judged – the current system of farming on a given property and the social system embracing a farming community or broader cultural beliefs and values. An apparent example of a sustainability innovation failing this test can be seen in the low adoption of perennial pasture sowing amongst a substantial core of wool producers in the Western District of Victoria. Pasture renovation in this region can be profitable if combined with an increase in stocking rate. Local culture has held that higher stocking rates are incompatible with the region’s reputation as a producer of fine wool. This opposition is documented as early as the 1920s when subterranean clover was first promoted in the district (Barr & Cary 1992). These beliefs are now complemented by beliefs that improved perennial pastures and higher stocking rates are ecologically unsustainable (Marks & O’Keefe 1996). The promotion of pasture improvement has often been incompatible with the values of this cultural group. For many broadacre farmers beliefs about ‘good farming’ tend to encompass matters such as tidiness, having fences and gates well maintained and having good looking crops or stock (Nassauer 1995). Profitability and sustainable farming practices are less commonly seen as being indicative of good farming (Dunn, Gray & Phillips forthcoming; Phillips forthcoming; Wilkinson 1996; Wilkinson & Cary 1992). While these cultural values may be causing increasing frustration in industry bodies and the agribusiness sector (Clancy 1999), there is evidence that Australian agriculture is undergoing a period of detraditionalisation in which traditional agricultural occupational identities are being replaced by more complex and diverse cultures (Bryant 1999; Dunn, Gray & Phillips forthcoming). Current research gives little indication of the
11
impact of detraditionalisation upon changes in farm management practice.
Trialability Innovations which can be trialed on a small scale prior to full implementation are more likely to be adopted. Trialing enables decisions about the utility of an innovation with minimal risk. Typically, farmers can easily assess a new crop variety by sowing one paddock to the new variety before deciding upon more extensive adoption. The successful promotion of conservation cropping practices which is dependent upon major machinery changes has been encouraged by providing hire trash combines, thus allowing trialing without significant investment in machinery. In contrast, dryland salinity control is clearly not amenable to trialing. Because the benefits of salinity control may not be achievable for up to 50 years, a trial process will delay more extensive salinity control for a century. Trialability is in turn dependent upon observability.
Observability NRM practices whose advantages are observable are more likely to be adopted. Traditionally, new variety or crop is often quite visible to passing observers and this visibility has been used to advantage. Irrigation watertable control is not normally an observable achievement. The development of well flags (to indicate water levels) as part of water-table watch was an innovative method of making watertable levels visible to the passing observer. Many Landcare programs have attempted to locate demonstrations along major roads to enhance visibility.
• Risk – refers to uncertainty about likely benefits or costs associated with a sustainable practice, uncertainty about the effectiveness of the practice, uncertainty as to when the benefits might be realised and uncertainty regarding the social acceptability of the practice. • Complexity – implies that a practice comprises more than one or two simple elements and that its elements interact with each other and, in sometimes complicated ways, with elements of the farming system into which it is to be incorporated. • Compatibility – the extent to which a practice fits in with existing farm practices, or with existing knowledge or existing social practice. • Trialability – where practices can be implemented on a small, or pilot, scale decisions can be more easily made about the value of a new practice without the risks associated with full implementation. • Observability – practices whose impact or advantage is easily observable, or whose outcome is quickly realised, are more likely to be adopted.
Categorising NRM practices An inventory of recommended NRM practices is presented below (Table 1). The management practices in this inventory are categorised in terms of attributes that have been found to be important in determining whether management practices are readily adopted or not. Such an approach provides a method for assessing likely adoptability in given farm situations and provides a conceptualisation and categorisation of relevant NRM practices. The appropriateness and relative advantage of given NRM practices will vary in geographic space to a very large extent. In Table 1 the sustainable practices listed above are scored on their level of possession of the following attributes: • Geographic applicability– refers to relative appropriateness of a practice, in terms of whether it is effective or adapted to only specific localities or, more universally, across many localities. • Relative Advantage – the financial advantage or other convenience or personal advantage to the farm business or the adopter. 12
Protection of land from stock by fencing (exclude stock from degraded areas) a
Retention of vegetation along drainage lines
a
Preserve, enhance areas of conservation value
a
Commercial tree and shrub planting (farm forestry)
Non-commercial tree and shrub planting a
Use of deep-rooted perennial pastures a
Regularly monitor water tables a
Agricultural lands treated with lime
Agricultural lands treated with gypsum
Fertilising of pastures
Regular soil testing
a
Establishing and monitoring ground cover targets (monitoring of pasture and vegetation condition) a Nutrient balance accounting (soil and plant sampling) Soil and plant tissue tests to determine fertiliser needsa
Maintenance of soil cover
(Ideal rating)
Sustainable practice
Table 1 Characteristics of sustainable practices
Lo
Lo
Lo
M
M
Lo
M – Hi
Hi
M
M
M
M
Lo
Lo
Lo
Lo (locality)
Lo
M
M (locality)
Lo
Lo
Hi-M (locality)
M
Lo
Lo
M
M
Hi (temporal)
(Hi)
Relative advantage
Hi
Hi
(Hi)
Geographic applicability
Lo
Lo
Lo
Hi
Lo
M-Hi
Lo
M-Hi
M-Hi
M
Lo
Lo
Lo
Lo
Lo
(Lo)
Risk
M
M
M
M
Lo
M-Hi
Lo
Lo
Lo
Lo
Lo
Hi
Hi
M-Hi
M-Hi (locality)
(Lo)
Complexity
M
M-Lo
Lo
Lo
M-Hi
M (locality)
Lo
Hi
Hi
Hi
M
M
M
M
M
(Hi)
Compatibility
Hi
M
M
Lo
Hi
M
Hi
M
M
Hi
Lo
Lo
Lo
M
M
(Hi)
Trialability
Hi
M-Hi
M-Hi
Hi
Hi
Lo
M
M
M
Hi-M
Lo
Lo
Lo
M-Lo
M-Lo
(Hi)`
Observability
a a
Irrigation farms
Automated irrigation a
Storage and reuse of drainage water a
Laser graded layout a
Irrigation scheduling
a
Adjusting crop sequences in response to seasonal conditions
Strip cropping
a
Use of contour banks in cropland
a
Stubble or pasture retention in ploughing (direct drilling) a Use of crop or pasture legumes in rotations a
Use of reduced or zero tillage (minimum tillage) a
Cropping farms
Slashing and burning of pastures
Use of integrated pest management (reducing pesticide use)
Pest and disease control in pastures
Animal pest or weed control to control land degradation
Protection of waterways from stock by fencing
(Ideal rating)
Sustainable practice
M
M
Hi
M
Hi
M
M-Lo
M-Hi
M-Hi
M
M-Hi
M-Lo
M-Hi
Hi M
M
M
M-Lo
M-Lo
M-Hi (locality)
M
Lo
(Hi)
Relative advantage
M
Hi
Lo
Lo
M
Hi
Lo
(Hi)
Geographic applicability
M-Hi
M
Lo-M
Lo
M
M-Lo
M-Lo
M-Hi
M
M
M-Hi
M
M
M-Hi
(Lo)
Risk
Hi
M
M
M-Hi
M
M-Hi
M-Lo
M-Hi
M
Lo
Hi
M
M
Lo
(Lo)
Complexity
M-Lo
M
M-Lo
M-Lo
M-Lo
M-Lo
M-Hi
M
M-Hi
M
M
M-Hi
M-Hi
M
(Hi)
Compatibility
Lo
M-Lo
M
M-Lo
M-Lo
M-Lo
M
Hi-M
Hi
Hi-M
M-Lo
M-Lo
M
Hi
(Hi)
Trialability
14
Hi
M
Hi
Lo
Lo
M-Hi
M-Lo
M
M
Hi
M-Lo
M
M
Hi
(Hi)`
Observability
Rangelands
M-Lo
M
Lo
M
M-Hi
Lo
M
M
Lo
Lo
(Lo)
Risk
Lo = Low
M = Medium
Hi = High
Lo
M
Hi-M
M
M
Lo
Lo
M-Hi
(Lo)
Complexity
Some measure of the level of landholder adoption of the practice available from the ABARE Australian Resource Management Supplementary survey.
M-Lo
M-Hi
Lo
M
M-Lo
M-Lo
M
(Hi)
Relative advantage
Hi
Hi
M
Hi
Hi
Hi
M
(Hi)
Geographic applicability
(Comments in brackets refer to locality or temporal constraints on expression of attribute.)
a
Use of effluent disposal systems (collection of effluent; ponds or drainage sump) a Pump dairy shed effluent onto pasture a
Dairy farms
Pastoral land destocked in low feed conditions
Degraded pastoral land converted to less damaging use
Pastoral land stocked at recommended rates
Piped water supplies for stocka
Controlled of water flow from bores
a
Control grazing pressure by excluding access to water a
(Ideal rating)
Sustainable practice
M
M
Hi
M
Hi
Hi
Hi
M
(Hi)
Compatibility
Hi
M
M-Lo
M-Lo
M-Lo
M
Hi
M-Lo
(Hi)
Trialability
15
Hi
Hi
M
M
M-Hi
Hi
Hi
M-Hi
(Hi)`
Observability
Observations on the characteristics of sustainable practices The following features and conclusions regarding sustainable practices and their attributes can be identified: • There is no one sustainable practice which optimally comprises all the attributes by being widely applicable, having high relative advantage to the landholder, low complexity, high compatibility, high trialability and observability, and low risk. • Very few sustainable practices have widespread or universal geographic applicability. As a consequence, the identification, development and promotion of relevant sustainable practices needs to be locality or catchment specific. • The sustainable practices with wider geographic applicability (such as deep-rooted perennials) often provide only moderate relative advantage to the landholder. The relative advantage will be different in different localities. • The level of relative advantage is rarely independent of commodity prices. The relative advantage of many sustainable practices (such as deep-rooted perennials) will be temporally dependent on the value of rural commodities produced as a result of using the practice. Low commodity prices in the broadacre industries have reduced the relative advantage of many sustainable practices. • The relative advantage and risk attributes are the least mutable in terms of feasible policy interventions. Where relative advantage is low and risk is high, attempts to achieve wide-scale adoption will require large levels of external subsidy or insurance intervention. It will be more feasible to promote those sustainable practices which have higher relative advantage (and preferably lower risk) and to use policy interventions (such as extension and education programs) to overcome or ameliorate complexity and low compatibility and observability.
A case example: phase farming with dryland lucerne The watertable under the Murray Darling riverine plains has been rising since the last century. The long term solution for much of the plains is to develop a system of farming based on a productive and profitable, deep-rooted perennial crop. The most appropriate commercial plant is lucerne. Dryland lucerne has been known of for many years, yet only a few farmers grow significant areas of lucerne (Ransom & Barr 1993; Whittet 1929). The use of lucerne, a deep-rooted perennial species, is an example of an apparently simple sustainable management practice that has not been widely adopted. In most
circumstances of land degradation lucerne has a medium to low relative advantage, reflecting low prices for pastoral commodities (see Curtis et al. 2000). Lucerne is relatively complex to introduce into a pastoral management system, and there are considerable risks in its successful establishment. Farmers sowing lucerne do not have a guarantee they will successfully produce a crop of lucerne. The chance of failure is greater than most other pasture species. One way to minimise the financial risk of establishing lucerne, and to make up for time a paddock may be out of production, is to sow lucerne with a faster growing crop such as safflower. Farmers following this strategy may have to learn to grow new crops which are more compatible with lucerne (Barker 1992). Lucerne requires rotational grazing management. The majority of farms are currently managed with a regime of set stocking. Wool-producing farms typically run three flocks: ewes, weaners and wethers. Some run an additional flock of maiden ewes. Under the four-paddock rotation system, such a farm would need 12 or 16 paddocks. For farms previously ‘set-stocked’ this implies additional expensive fencing and more dams and reticulation to provide watering points in each paddock. Fencing at this intensity is likely to impede the easy management of cropping activity on the farm. Lucerne pasture is more productive than normal pasture, but wool producers will not make money merely by growing more pasture. There are complex ramifications in the farm system. More sheep will be required to utilise the extra pasture (Ransom 1992). The increased flock size will require extra capital, more work in sheep handling and an increased workload of rotational grazing. Higher sheep densities in paddocks may mean a greater need for control of intestinal parasites and increased use of veterinary chemicals or greater attention to rotational grazing systems to minimise parasite infestation (Coffey 1992). One means of maximising the benefit of lucerne is to abandon lambing in autumn in favour of spring lambing. This may mean a need to further re-arrange the farm timetable. Shearing will probably be moved to after the harvest season and before sowing. The risk of grass seed contamination will be higher. Grazing rotation strategies to minimise this risk will be needed. To maximise the benefits of prime lamb production, the farmer will often need to develop new marketing skills and develop relationships with export abattoirs. These changes have to be worked in with the continuing cropping enterprise. Lucerne can imply major changes in crop management. How does the farmer combine the new grazing rotation with the crop rotation side of the business? Whereas an annual pasture may have been grazed for a couple of years before cropping, there are good reasons to maintain a lucerne paddock for its full eight-year life after successful establishment. Consequently, the farmer may have to crop paddocks elsewhere on the farm for a longer period before putting them back into pasture. Forestalling 16
the depletion of soil nitrogen will inevitably mean introducing grain legumes into a rotation system that was predominantly based on wheat and pasture. This will require improved cropping skills, marketing skills and probably investment in cropping machinery. Lucerne will also introduce greater risk into cropping systems. The environmental advantage of lucerne is its ability to remove water from the soil profile to reduce recharge of the watertable. Traditional long fallow crop systems were successful in minimising risk by conserving soil moisture before a crop phase. Entering a crop phase after drying the soil moisture may increase crop production risk if the following season’s rainfall is below average. Currently in southern Australia climate forecasters are unable to provide useful forecasts to guide phase farming decision-making. Finally, a farmer considering integrating lucerne into the farming system may need to borrow capital in the early stages of the project. A bank is likely to require a business plan to analyse the financial implications of the plan before agreeing to the provision of loan finance.
The adoption of dryland lucerne in central Victoria Dryland lucerne has been promoted as a farming system for over a decade and the adoption of this system has been relatively well monitored. There has been a significant increase in the adoption dryland lucerne during this period. However, the rate of adoption is mediated by a number of factors which lead to the conclusion that full adoption is unlikely to be attained. In 1991 Agriculture Victoria conducted a survey of dryland lucerne adoption in north central Victoria. Using very conservative assumptions about the non-respondents, the investigators concluded that the area of lucerne had increased from 4.2 percent of farmland in 1984 to 7.6 percent in 1991. A segmentation analysis revealed adoption was limited to a small number of producers, but that there was a very high latent interest in growing dryland lucerne. • Established lucerne growers. This group consisted of six farmers who had a history of good lucerne establishment, management and a very positive attitude to lucerne. The established lucerne growers had on average 43 percent of their farm under lucerne. Fifty per cent of the lucerne in the catchment will be found on this relatively small percentage of farms. Farm sizes were higher than average. • Lucerne planners. This group of 29 farmers believed lucerne had a major role in their future farming plans and believed the practical problems associated with lucerne could be overcome.
• Deterred growers. This group of 31 farmers had little lucerne on their farms. They would like to have a larger area, but believed there were too many practical problems to make this a worthwhile goal. • Disinterested. This group consisted of 24 farmers who mostly believed there was little place for lucerne on their farms. This group were also less likely to be members of landcare type groups. Farm sizes were smaller than average. This segmentation revealed the importance of finding easily adoptable solutions to the technical and management challenges posed by the integration of dryland lucerne into the then traditional cropping/annual pasture mixed farming system used in the district. Lucerne is relatively complex to introduce into a pastoral management system, and there are considerable risks in its successful adoption. The risks and concerns revealed by the survey and informal interviewing were considered previously and are listed below: • • • • • •
establishment failure lucerne requires rotational grazing management heavier stocking densities significant changes to farm management systems competition with cropping program drought risk management.
The degree of interest in lucerne was demonstrated by the high degree of enthusiasm for an increased area of lucerne. It was estimated that 36 per cent of the region was suitable for dryland lucerne. Farmers indicated that they would like to see 25 per cent of farm area under lucerne if particular technical and management problems could be overcome. Even at the existing sowing rates, it was estimated the area of lucerne would rise to 11 per cent with no change in the current establishment success rate. Improvements in the establishment success rate to that obtained by the more experienced farmers would see the area of lucerne increase to 17 per cent of the farm area. A follow up survey in 1996 revealed some contradictory results (Oxley 1997). The overall adoption rate for dryland lucerne increased significantly. The number of farmers sowing more than 5 per cent of their farm area to lucerne rose from 27 per cent to 48 per cent. The average establishment success rate rose from 36 per cent to 60 per cent. However, there was no change in the total area of lucerne in the catchment. While more and more farmers had been sowing lucerne, farmers with existing paddocks of lucerne had been converting them to cropping in response to the more attractive returns from cropping. The obviously successful extension effort to promote the benefits of dryland lucerne had merely managed to maintain the existing area of dryland lucerne. Since the 1996 survey, there has been a steady increase in the area of lucerne sown in the North Central region (see Figure 2), reflecting a gradual improvement in the relative 17
underlining the difficulties of evaluating the adoption outcomes of an extension program based upon data from a short time period.
350
50000 48000 46000 44000 42000 40000 38000 36000 34000 32000 30000
300 250 200
No. of farmers
Pasture mix area (ha)
returns to livestock enterprises, particular prime lambs, in comparison to returns to cropping enterprises (Karunaratne & Barr 2001). The benefits of the lucerne extension program of the previous decade are still being reaped,
150 100 1996
1997
1998
1999
Mixture of lucerne and other pasture area Farmers reporting mixture of lucerne and other pasture
Figure 2 Area of mixed lucerne pasture and adoption of mixed lucerne pasture in the North Central catchment region of Victoria: 1996-99 (Source: ABS) A key conclusion is that dryland lucerne will not be adopted when its comparative advantage is less than that provided by cropping. Cropping has been a more profitable enterprise for the past decade. The need or desire to generate income has overridden any salinity control benefits. Over the past decade many farmers in north central Victoria have gained the necessary managerial skills to give them confidence in growing dryland lucerne. There has also been a recognition of its recharge benefits. This has been potentially a very positive story in the promotion of a sustainable agricultural practice. However, while the current relativity of cropping and grazing gross margins prevails, there is a very strong constraint on the extent to which lucerne can be expected to be adopted. The main motivation for adopting dryland lucerne is its potential for improving the profitability of grazing enterprises. This same profitability motivation will ensure that the needs of the cropping program will generally take precedence over recharge control objectives.
18
Learning about sustainable practices As is the case in most occupational groupings, there is a wide range of abilities and knowledge among farmers. There is also a wide range of formal education and knowledge about sustainable farm practices. These factors suggest that to encourage better understanding and implementation of sustainable management practices it is more important to focus on how farmers might learn about using these practices rather than to rely on exiting formal levels of education.
Categorising the learning focus Kilpatrick et al. (1999) recently carried out a major research project exploring how farmers’ learning for management and marketing can be improved. The research, funded by the Rural Industries Research and Development Fund (RIRDC), was motivated by the perception of experts that farmers did not participate in training, particularly in marketing and management, to their best advantage. Building upon previous research into the learning needs and styles of Australian farmers (eg Kilpatrick 1997; Kilpatrick & Williamson 1996; Reeve & Black 1998; Synapse Consulting Pty Ltd 1998), Kilpatrick et al. (1999) conducted two separate studies. The first was a national study involving qualitative interviews with 85 representatives of ‘farm management teams’ (the couple or group involved in on-farm management decisions) in five states. The second study was a Western Australia study involving interviews with a random sample of 197 farmers from eight agricultural regions of the south west. Kilpatrick (1996) highlighted the important role that 3 education and training play in assisting farmers to make changes in their farming practice. However not all farm managers learn in the same manner. Farm managers often differ in the learning sources they accessed, the manner in which information was available to them, and their motivations for learning. Kilpatrick et al. (1999) investigated both learning-for-change and on-going learning. On the basis of one specific change (learning-for-change) that the farm management team had implemented, and previous research, four learning pattern groups were developed. These were:
• Local focused The local focussed group seeks 4 information and advice only from local experts and local farmers. They do not participate in training, except for attendance at field days. • People focused Such farm businesses consult two or more people and use no more than one other learning source when making changes (eg training, media and observation). • Outward looking These farm businesses use a variety of sources, usually including one of training, media and observation in addition to one-on-one learning from other farmers, experts or agricultural associations/organisations. • Extensive networking These farm businesses consult a wide range of sources when learning for change, typically more than four sources including experts, training, other farmers, media, agricultural associations/organisations, and observations (Kilpatrick et al. 1999:33). Outward looking farm business dominated the national study sample (40%) followed by people focussed (23.5%), local focussed (18.8%) and extensive networking (17.7%) (Kilpatrick et al. 1999). While these categories were established on the basis of learning about farm management, they seem equally appropriate for the process of learning about more sustainable management practices. Farm management teams were also categorised according to their farm management skills. Three levels were developed with the farm businesses that exhibited higher levels of management skills and experience given Level A, and lower levels given Level C (Kilpatrick et al. 1999:29). There were no significant differences between the learning pattern and management category. However there were no Level A farm business that were local focused and no Level C farm businesses that were extensive networking in learning focus.
Reasons for learning Traditionally there has been a low level of formal education among Australia’s farmers, however levels of education have increased from 23 per cent with post-school
3
Education and training ‘includes all organised education and training activities, both non-formal and formal. . . . field days, farmer-directed groups, seminars, conferences and workshops, and non-accredited courses as well as formal education and training, all are included as education and training activities’ (Kilpatrick et al. 1999:xi).
4
An expert ‘includes those who have specialised information and skills of use to the farm business. Examples are government extension officers, accountants, buyers of farm product, company field officers, researchers, lawyers, rural counsellors, suppliers of inputs (such as rural merchants) and private farm consultants’ (Kilpatrick et al. 1999:xi). 19
qualifications in 1983 to 32 per cent in 1995. Though this is still less than the 49 per cent of the Australian labour force that has post-school qualifications (Synapse Consulting 1998). Importantly, those farmers with higher levels of formal education are more likely to seek out and participate in further education and training. However there is mixed evidence concerning the link between formal farmer education and good farm management (Bamberry, Dunn & Lamont 1997; Kilpatrick et al. 1999). Though Gould, Saupe and Kleme (1989) report that better educated farmers were more likely to adopt conservation practices and Reeve and Black (1993) found that they had more favourable attitudes towards using outside expertise in conservation practices. The motivations given by farmers for their learning were as follows: • improved farm business efficiency (52.9%) • improved farm business viability (29.4%) • acquisition of marketing information and skills (23.5%) • compliance with legal requirements (15.3%) • learning to better manage risk (14.1%) • environmental awareness (10.6%)
• fear of being exposed to new knowledge and skills (Kilpatrick & Rosenblatt 1998). Typically, farmers choose learning sources according to the need; thus other farmers were often sought out for background information and for information on practical issues related to farming, extension officers and consultants for detailed technical advice, and family and employees for support during change. Farmers learning to make a specific management change used a variety of sources (6 types) with experts being the most frequently accessed in learning-for-change situations. Of the experts that were sources for learning by farmers, government consultants were the expert source most often used (Kilpatrick et al. 1999). Experts were the most frequently used type of learning source for all learning pattern types, except for the extensive networkers where they were equal first with training. The manner in which experts were perceived was contrasted between farm management Levels A and B, where experts were perceived as a resource to aide decision-making about some change, and management Level C where experts were seen as decision-makers. Kilpatrick et al. (1999) differentiated between four types of change:
• personal development (7.1%) (Kilpatrick et al. 1999)
• starting a new enterprise
Importantly, environmental management motivates only a relative minority of farmers to learn, in contrast to business efficiency and viability.
• other strategic change • record keeping • tactical or technical changes.
Styles of learning Farmers draw upon a wide range of sources in their learning, and changes to farm management are typically influenced by a number of sources (Phillips 1985). Informal interaction with others and social networks are very important in farmer learning. Such interactions provide opportunities for farmers to compare views on how information could be applied to their own situations and to test each other’s values and attitudes towards making changes as a result of the information (Kilpatrick et al. 1999). People were cited as the most important sources (of support and information) for both learning-for-change and on-going learning. Informal sources of learning were preferred by farmers as they tended to have a: • preference for independence • familiarity with highly contextual learning mode • lack of confidence in working in training settings • preference for information from known sources
Farmers sought access to different learning opportunities for different types of change. Training was most frequently sought for record keeping changes, while experts (primarily government consultants) dominated other types of change. Other farmers were also a frequently used source of learning for tactical and technical changes as they were seen as having good local knowledge. Education and training, including field days, seminars, farmer-directed groups, and both accredited and nonaccredited courses, were also important sources of learning for some sections of the farming community. Field days and accredited courses were useful to approximately 75 per cent of farmers (Kilpatrick et al. 1999). Farmers with no post-school qualifications were most likely to draw upon field days, whilst those with agricultural qualifications drew upon accredited and non-accredited courses (Kilpatrick et al. 1999). When considering a specific change in farm management, non-accredited courses followed by accredited courses and field days were the most frequently used (Kilpatrick et al. 1999). Those farmers who identified environmental management as a motivation for learning drew upon two or three learning sources. In all cases these always included a farmerdirected group (such as community landcare). Community 20
landcare and other similar groups have been highlighted as an important source of information concerning sustainable farming practices (Cary & Webb 2000). Recent studies have highlighted the role that women play in Australian agriculture (Alston 1995; RIRDC/DPIE 1998), and learning for increased adoption of conservation practices on farms should be cognisant of the roles that women play in agriculture. The learning styles generally preferred by men and women may be different (Kilpatrick et al. 1999). Recent initiatives of the Women in Rural Industries Section of AFFA have highlighted the advantages of specifically targeting rural women in education and information programs (Webb 2000a, 2000b).
21
Some recent Australian findings on factors associated with the adoption of sustainable practices In recent years there have been a number of major reviews and studies that have explored the social aspects of adoption of best practices in Australian agriculture (eg. Fenton, MacGregor & Cary 2000; Barr & Cary 2000; Guerin & Guerin 1994; Reeve & Black 1993). Two more recent studies warrant further exploration. The first is a study carried out by Curtis et al. (2000) in the Goulburn Broken catchment of Victoria, the second is a benchmarking study carried out by Solutions Marketing and Research (1999) to monitor the achievement of goals in AFFA’s Agriculture – Advancing Australia (AAA) policy package, hereafter termed the ‘Solutions’ study.
The Solutions research involved a telephone survey of a representative sample of 2,043 Australian agricultural producers and a separate study utilising in-depth interviews with a non-probability sample of key community people. Here only the producer survey is discussed. Data were collected on producer behaviour (by measuring reported current usage and likely adoption within two years), producer skill (by measuring producer confidence in their current expertise to meet their needs now and in two years), producer awareness, knowledge and usage of AAA initiatives, producer attitudes, and demographic data (Solutions 1999).
The Curtis et al. (2000) study was in response to the realisation that the adoption of best practices in the Goulburn Broken Catchment was slower than is required to arrest dryland salinity. Using a mail survey Curtis et al. (2000) explored the key social factors affecting adoption of best practices among a random sample of rural properties 5 covering the 14 land management units of the catchment. Four hundred and eighty landholders completed the survey, which explored the relationships between the use, and nonuse, of best practices and a range of landholder, business and property characteristics. The practices explored in the survey were:
Solutions developed a series of five national indicators, linked to the goals of AAA, each comprising a series of between five and ten individual measures. Table 2 gives the five indicators and a general description of the types of measures that comprise each indicator. The current utilisation score is the average score across all measures for an indicator, and the score on a measure represents the percentage of respondents that respond positively to that measure. The maximum possible indicator score is 100 per cent, which means that ALL respondents were utilising ALL monitoring measures within an indicator.
• area sown to introduced perennial pastures • area of changed grazing/fertiliser regimes to encourage native perennial pastures • area of remaining native bush and waterways fenced • area of trees planted • number of ground water pumps installed • area of high density/intensive grazing. Curtis et al. ( 2000) found that the lack of financial capacity (level of net farm income) was a major constraint to adoption. Landholder age was not seen as a constraint to adoption, while property size, and its links to financial capacity, was likely to be a major influence on the area over which best practice was implemented. There is a more detailed discussion of the characteristics of those landholders who have adopted best practices below.
5
The natural resource management indicator comprises a number of measures of NRM behaviour; however most of these are not measures of direct on-ground conservation practice. Two measures of sustainable practice are included, these are: • action to reduce soil erosion in the past two years • the strategic planting of trees in the past two years (Solutions 1999). As an additional monitoring indicator of capacity for change and adoption of innovation, the adoption of new agronomic practices was recorded. This was a self-elicited response from which the following practices were identified: • minimum till/no tillage • new/improved/alternative water conservation/irrigation • farming resource conservation techniques/holistic management. While the Solutions research is limited in its selection of best practices, and other NRM measures, its representativeness and the development of a longitudinal
A land management unit is a area of land with common geological and hydrogeological characteristics. The impacts of salinity, its causes and downstream impacts, and the options for control are common to each land management unit (Curtis et al. 2000). 22
6
data set make it an important source of data on agricultural producer’s NRM behaviour and capacity to adopt innovations.
6
The Solutions survey has been repeated in 2000, and will be conducted again in 2002. 23
Table 2 Solutions’ National Indicators Indicator
Description
Current Utilisation Score
Skill Level
Strategic planning for future
Existence and contents of a yearly farm plan, succession plan and involvement in co-operative planning
46
40
Natural resource management
Comprising a range of NRM measures including fire insurance and prevention strategies, noxious weed control, land/water resource plan, tree planting, landcare activity, and climate monitoring
70
68
Financial self reliance
Monitoring the financial performance of farm activities, internal and external financial comparison of activities, superannuation, off-farm investments, and presence of retirement plan
59
54
Market competitiveness
Calculation of production costs, knowledge and investigation of marketing opportunities (domestic and export) and buyer specifications, QA systems, investigation of new on- and off-farm activities
26
28
Capacity for change and adoption of innovation
Attendance at field days, training activities, use of soil testing and advisers, and adoption of innovations, new technologies
62
72
(Source: Solutions 1999)
As indicated in the above table, producers scored highest on Solution’s NRM indicator. The strong performance is linked to the widespread adoption of key measures included in the indicator such as fire insurance (92% of respondents), control of noxious weeds (90%), land and water resource management plan (89%), fire prevention strategies (80%) and activity in landcare (80%). There were lower levels of adoption of the two best practices, with 63 per cent of respondents taking action to reduce soil erosion and 61 per cent planting trees in the two past years (Solutions 1999). For self-reported agronomic practices, 7 per cent identified their adoption of minimum tillage/no till, 3 per cent new/improved/alternative water conservation/irrigation, and 2 per cent farming resource conservation techniques/holistic management over the past two years. The first two practices are best practices that are sector specific and this explains in part the much lower overall levels of adoption. Adoption of minimum tillage/no till was at 24 per cent for cereal growers, while 10 per cent of cotton growers had adopted some water conservation. Furthermore these practices are self-reported and the categories were generated after the survey had been carried out. This is in contrast to the items in the indicators that were known to the respondents. Both Curtis et al. (2000) and Solutions (1999) record a range of farmer, farm business, property and other characteristics that may be linked to the self-reported NRM behaviour. The following deals with the major characteristics of those individuals who adopt best practices.
Age Younger farmers tend be more aware of land degradation on their farms. It is also hypothesised that age is likely have an impact upon the adoption of best practice in agriculture. In particular, the aging rural population linked with increasing out-migration from rural areas (Haberkorn et al. 1999) suggests a reduction in family farm succession, which in turn may lead to a reduced willingness to invest in best practice (Curtis et al. 2000). However there appears to be no clear correlation between age and best practice adoption. Curtis et al. (2000) found no significant 7 relationship between adoption and age , and thus the aging of the rural population was not considered a major constraint to adoption. However they found that younger farmers were more likely to have prepared farm management plans and budgets. Considering the composite NRM behaviour indicator that Solutions (1999) develop there was no significant relationship between age cohorts and their scores on the indicator (_2=1.446, df=5, p=0.919). However at the level of the two best practices there were significant age effects for both tree planting 7
Curtis et al. (2000) performed both bivariate and multivariate tests for relationships. In the discussion of Curtis et al.’s work only significant multivariate tests are reported. Where there is no significant relationship, a significant bivariate relationships may exist, for example in the case of age there were significant but very weak correlations between age and the area sown to introduced perennial pastures, and the area of native bush and waterways fenced. 24
(_2=78.608, df=5, p<0.001) and for action taken to treat erosion (_2=24.732, df=5, p<0.001). For tree planting there is an increase in adoption as age increases to a maximum adoption rate in the 45-55 age group, and then a decrease for age cohorts beyond this. The pattern is repeated for action to treat erosion, though the peak of adoption occurs in a younger cohort, the 35-44 age group, and declines as age increases.
of farm profit. The impact of financial viability on adoption is considered later. The Solutions research also recorded property size, though analysis of the adoption by property size was not performed.
Farm business Education There is mixed evidence regarding the relationship between farmers’ educational levels and their adoption of sustainable land management practices. In many Australian studies there are no direct relationships between adoption of best practices and the level of formal education. Curtis et al. (2000) found no significant relationship between formal education and adoption. Likewise analysis of the Solutions data shows no relationship between education and the NRM behaviour indicator (_2=3.772, df=4, p=0.438). However for the two best practices there is a significant effect. For tree planting, adoption increases with higher levels of formal education (_2=12.821, df=4, p=0.012). For the treatment of erosion, increased adoption occurs with increased formal education to a TAFE level and then subsequently decreases with tertiary education (_2=19.281, df=4, p<0.001).
Poor or low financial viability is a major constraint on the adoption of best practice (Barr & Cary 2000; Barr et al. 2000; Riley 1999). Curtis et al. (2000) found similar relationships. There was a significant positive relationship between reported on-farm profitability and the adoption of some best practices, namely the total area sown to introduced perennial pasture, changed grazing/fertiliser regimes and high density or intensive grazing. However there were no relationships between the proportion of the property under best practice and on-farm profitability. Similarly there were no significant relationships between total or proportion of property under best practice and either off-farm income or total income. The only financial data recorded in the Solutions study were estimates of on- and off-farm assets and gross value of production. Analysis of adoption by these variables was not available.
Property size
Stewardship
Property size was a major influence on the adoption of best practice in Curtis et al’s (2000) study. When the total area of the best practice (eg absolute area sown to introduced perennial pastures) was used there was a significant positive relationship between the adoption of best practice and property size. When the proportion of a property under a best practice was used there was a significant negative relationship between the adoption of best practice and property size. Curtis et al. (2000) explain that smaller properties were adopting some practices at levels representing higher proportions of their total property, while larger property owners had implemented most best practices over a larger area. Thus while property size influences adoption of best practices, there is interest and adoption among both large and small property owners (Curtis et al. 2000). Cary (1992) reported a similar inverse relationship between proportion of property planted to trees and property size, though no relationship with absolute number of trees and property size. Cary suggested that farmers plant a symbolic number of trees, thus those with smaller properties plant a greater proportion of their property to trees. Increased property sized is usually linked to increased financial viability, which in turn removes a major constraint to adoption. Curtis et al. (2000) did find a significant relationship between increased property size and the likelihood of returning an on-property profit and the level
The often tenuous link between pro-environmental attitudes (often subsumed in the value of stewardship) and proenvironmental behaviour has been observed in a number of studies in Australia, as well as in other countries. Attempts to establish links between measures linked to stewardship and NRM behaviour related to crop farming practices in Australian research studies have generally been unsuccessful. Harvey and Hurley (1990), in a study of crop farmers in Victoria found no statistical relationship between perception of erosion, or concern about erosion, and use of the conservation tillage techniques. A study of wheat producers in New South Wales found that adherence to a conservation ethic did not significantly differ between the adopters and non-adopters of conservation cropping (Sinden & King, 1988). Vanclay (1988) found farmers adhering to a conservation ethic were less likely to adopt conservation farming. These findings may reflect the measurement difficulties associated with measuring ‘stewardship’ in survey interviews; however it is more likely, for cropping farmers, cropping management decisions are essentially determined on the instrumental grounds of convenience and cost. One of the few Australian longitudinal studies of NRM ‘behaviour’ and community landcare membership provides some evidence of influence of membership on the complex relationship between attitudes and behaviour with respect to sustainable land management. The study of landholders
25
in central Victoria between 1988 and 1991 investigated the influence of economic, psychological and social factors on the adoption of the sustainable land management practices of tree planting and the planting of deep-rooted pasture (Wilkinson & Cary 1992; Cary & Wilkinson 1997; Cary 1999). Perception of long-term profit was an important predictor of the decision to use both practices, but was more important for the decision to plant trees. Trees were planted irrespective of whether salinity was perceived by the landholder as an environmental problem. In the case of phalaris pasture, recognition of salinity as an environmental problem increased the likelihood of planting.
Recent findings regarding attitudes Despite the implied simplicity of assumed relationships between attitudes and behaviour, the link is tenuous and complex. The tenuous nature of the link between attitudes and behaviour has been discussed above. Curtis et al. (2000) did not directly measure attitudes in their study, however respondents were asked a number of questions that act as proxy indicators of a stewardship ethic. These were:
restricted to attitudes to chemical use in Australian agriculture, this was a major focus of the survey. The survey did not record attitudes to specific best practices, though it included a range of statements to gain insights into, inter alia, land degradation and farmer’s conservation orientation. Unfortunately Reeve and Black did not collect data on the adoption or implementation of best practices and thus links between attitudes and adoption cannot be identified from this data. The Solutions research incorporated a series of 23 attitudinal statements that related to motivation, planning, advice, debt, marketing, time management, information requirements and commitment to the industry. The responses were cluster analysed resulting in five attitudinal groups. These were: • Committed, doing it tough, off farm income supported (26% of the population) • The older farmer prepared or preparing to leave (21%) • Questioning their long term involvement in farming (18%) • Confident established older farmer (15%)
• taking nature conservation values into account when planning work • willingness to work with government • importance of community cooperation • landcare participation. They found no significant relationship between taking into account nature conservation values and the adoption of best practice. However with 78 per cent of respondents indicating that they did take nature conservation values into account when planning there is likely to be a high level of support for a stewardship ethic. There were no significant relationships between adoption of best practice and either willingness to work with government or the importance of community cooperation. However respondents did acknowledge the importance of cooperation and were often willing to work with government to tackle salinity. There was a significant negative relationship between landcare participation and the area sown to introduced perennial pastures. This conflicts with earlier research where landcare participation has been linked to significantly higher levels of adoption (Curtis & De Lacy 1996). Reeve and Black (1993) carried out an extensive survey to explore farmer’s environmental attitudes. While not
• The business person (19%). On the NRM indicator the business person group scores higher than the remaining groups. This group is characterised by having more formal education, younger average age group, highest value of on-farm assets and gross value of production, but lower than average off-farm assets and not reliant on off-farm income. They tend to be committed to, and satisfied by, farming, and would like more accurate market information and are generally willing to pay for advice. The business person group scored highest on the best practice of strategic planting of trees, and equal highest with the questioning their long term involvement group on the best practice of action to reduce soil erosion.
Other characteristics Curtis et al. (2000) found significant relationships between best practice adoption and a number of other characteristics. Generally these relationships were significant with the adoption of just one best practice; except for farming as an occupation where there were significant negative relationships with the area of trees planted and the area of river and native vegetation fenced. These characteristics are shown in Table 3.
26
Table 3 Landholder and property characteristics with significant relationships with adoption of best practices Characteristic
Number of best practices
Property size (total area of best practice)
5
On-property profitability
3
Concern about salinity impacts
1
Concern about rising water tables being a threat to pasture production on respondent’s property
1
Property having plants showing signs of salinity
1
Work on property partially funded by Federal or State government
1
Value of all government contributions to work on property
1
Hours worked off-property
1
Property size (proportion of property under best practice)
1
Having a written property plan that involved a map or other documents
1
Having written personal and/or family goals to be achieved on property
1
Including the cost of work to address salinity in property budget
1
The property will be sold
1
All or most of the property will be leased
1
Number of children
1
Farming as an occupation (total area of best practice)
1
Landcare membership
1
(Source: Curtis et al. 2000)
27
Modeling adoption behaviour from the 1998-99 Resource Management Survey
Introduction The relationships between the adoption of sustainable farming practices and the available range of farm family, farm property and farm business characteristics are complex and sometimes tenuous. While some relationships have been found in empirical studies, (eg. CIE 2001; Curtis et al. 2000; Drake, Bergstrom & Svedsater 1999; Mues, Chapman & Van Hilst 1998; Cary & Wilkinson 1997), there is no widely accepted theoretical model of human adoption behaviour that can guide and direct empirical studies. Consequently research tends to be atheoretical and exploratory in nature. The Australian Bureau of Agriculture and Resource Economics (ABARE) was commissioned to undertake an analysis of data from the Resource Management Supplementary (RMS) survey for the 1998-99 financial year. While ABARE performed the analysis of unit data records and provided statistical advice, the determination of models to be tested and the interpretation of results was undertaken by the Social Sciences Centre. The general approach in the analysis was to model the association between a range of farm family, farm business and farm property characteristics and the reported adoption of various resource management practices. The testing of a priori hypotheses was not the intention of the analysis, rather we have inductively explored the associations between practice adoption and the range of characteristics where previous research has suggested relationships.
more sustainable land management practices. Building upon this review a number of landholder characteristics collected as part of ABARE’s RMS were selected for further analysis. While the following gives an overview of the analysis and findings, a more detailed discussion can be found in Appendix A. Data covering a range of landholder characteristics, and the reported adoption of sustainable land management practices were selected from the 1998-99 ABARE Australian Agriculture and Grazing Industries Survey (AAGIS) and the Australian Dairy Industry Survey (ADIS) (see Box 1). The surveys incorporated the RMS which collected data regarding resource management practices and land management, including the: • presence, extent and costs of degradation • participation in training • landcare membership and involvement in landcare activities • content and use of farm plans • cost of landcare capital works • adoption of best practices in farm management • area of crops sown with different tillage practices • recent changes to tillage practices • attitudes to degradation and conservation • farm forestry and functions of trees on farms.
Modelling farmer behaviour The previous chapter reviewed recent studies concerning landholder’s characteristics in relation to the adoption of
28
Box 1: ABARE Farm Surveys ABARE undertakes an annual survey of Australian farms throughout the broadacre industries AAGIS, and the dairy industry. AAGIS covers five industry types, namely: 1) wheat and other crops industry, 2) mixed livestock-crops industry, 3) sheep industry, 4) beef industry, and 5) sheep-beef industry. Data collected as part of these surveys covers a broad range of socioeconomic data concerning farm family, farm business and farm property characteristics. Data collected for the five broadacre industries in AAGIS are presented for three ABARE defined zones. These are the: •
Pastoral zone: which includes most of the northern tropical areas and the arid and semiarid regions of Australia. Agricultural land use in this zone is characterised by extensive grazing of native pastures. Although some cropping is undertaken, it is impractical on most farms because of inadequate rainfall.
•
Wheat-sheep zone: which has a climate and topography that generally allows the regular cropping of grains in addition to the grazing of sheep and beef cattle on a more intensive basis than in the pastoral zone. Rainfall is generally adequate for producing a variety of pasture species, usually as part of a crop-grazing rotation.
•
High rainfall zone: which forms the greater part of the coastal belt and adjacent tablelands of the three eastern mainland states, small areas in south eastern South Australia and south western Western Australia, and the whole of Tasmania. Higher rainfall, steeper topography, more adequate surface water and greater humidity make the high rainfall zone less suitable than the wheat-sheep zone for grains based cropping but more suitable for grazing and producing other crops (ABARE 2000).
Based upon their utility in understanding farmer adoption behaviour 16 landholder characteristics were selected for analysis. These characteristics are listed in Table 4, and definitions of each variable are provided in Appendix B.
nature of the farming enterprise and its location (see Table 1, Chapter 3). Some practices will only be relevant to particular types of industries, or to particular locations. Table 5 details the practices for which adoption was explored.
The potential range of sustainable resource management practices that could be adopted will be determined by the Table 4 Variables explored in analysis of Resource Management Supplementary survey Farm family characteristics: Farm financial characteristics:
Social and institutional contact: Education and training: Farm structure: Identification of problems: Age and experience: Attitudes:
state of residence farm cash income profit at full equity closing equity ratio landcare membership length of landcare membership recent training PMP participation farm size land use intensity farm plan age financial concern attitude financial outlook attitude technical concern attitude environmental concern attitude
29
Table 5 Resource management practices investigated WheatSheep
High Rainfall
deep rooted perennial pasture
x
x
tree and shrub establishment
x
x
x
regularly monitor water tables
x
x
x
soil/plant tissue test to determine fertiliser needs
x
x
x
Resource management practice
Pastoral
controlled flow bores
x
controlling grazing pressure by excluding access to water
x
monitoring of pasture and vegetation condition
x
Dairy Farms
collection of dairy effluent (ponds or drainage sump)
x
pump dairy shed effluent onto pasture
x
Irrigated Farms
laser graded layout
x
use irrigation scheduling tools
x
monitoring of pasture and vegetation condition
x
x
x
x
x
preserve/enhance areas of conservation value
x
x
x
x
x
exclude stock from degraded areas
x
x
x
x
x
Percentage conservation tillage
x
x
x
x
x
Findings The significant findings from the analysis are summarised in Tables 6 and 7. Table 6 presents the frequencies with which family, farm property and farm business characteristics were associated with adoption of the investigated management practices. In the majority of cases the direction of the relationship between practice adoption and characteristic as suggested by past studies and theoretical propositions was correctly predicted. Table 7 summarises the relationship between characteristics and individual practices. Symbols in a box indicate a significant association between the relevant characteristic and practice adoption. An addition (+) symbol indicates a positive relationship; as the characteristic increases so too does the likelihood of practice adoption. A minus (-) symbol indicates the converse. In the case of the state of residence an asterisk (*) indicates a significant association, though there is no inherent direction in the variable. Where the direction of a significant relationship is confirmed the cell is shaded. The significant findings are considered in the context of other recent studies. In particular we draw upon recent work carried out in the rangelands for the Audit by the CIE (2001), work by Curtis et al. (2000) in Victoria’s GoulburnBroken catchment and work by Mues, Chapman and Van Hilst (1998).
30
Table 6 Characteristics significantly associated with practice adoption Characteristic
state of residence financial outlook attitude farm plan recent training Environmental concern attitude land use intensity technical concern attitude closing equity ratio landcare membership (1998-99) length of landcare membership financial concern attitude PMP participation in last 3 years age farm cash income farm size profit at full equity
Frequency of significant associations predicted 9 7 6 6 6 4 4 1 3 1 1 2 2 1 0 1
not predicted 1 0 0 0 2 1 3 0 1 1 0 0 0 1 0
31
-
+ significant positive association at the 95% confidence level or higher - significant negative association at the 95% confidence level of higher * see individual models for nature of relationship 1 broadacre farms only 2 including dairy farms
PMP participation in last 3 years
+
*
*
State
Land use intensity
-
+
Farm plan
Farm size
+
Profit at full equity
+
*
+
+
Farm cash income -
+
Closing equity ratio
+
Recent training
+
Length of landcare membership
+
-
Landcare membership (1998-99)
+
-
+
Financial outlook attitude
+
-
Technical concern attitude
Financial concern attitude
+
Environmental concern attitude
Age
Farm family, farm property and farm business characteristics
+
*
+
+
-
+
+
+
+
-
+
-
-
*
-
+
*
+
+
+
+
+
+
+
-
-
*
+
-
-
+
*
-
+
32
-
*
+
-
Pastoral zone Wheat-sheep and high rainfall zones Dairy farms Irrigation farms All farms controlled flow controlling monitoring of deep rooted soil/plant tree and regularly collection of pump dairy laser graded use irrigation monitoring of preserve/enha exclude stock percentage pasture and perennial tissue tests to bores grazing shrub monitor water dairy effluent shed effluent layout scheduling pasture and nce areas of from conservation pasture1 pressure by vegetation determine establishment2 tables2 onto pasture tools vegetation conservation degraded tillage condition excluding fertiliser condition value areas access to needs1 water -
Table 7 Factors which are associated with the adoption of sustainable management practices (shaded cells indicate association relationships in predicted direction)
State of residence Though clearly not a driver of practice adoption, state of residence was commonly a significant explanatory variable in adoption behaviour. Farmers based in Queensland were typically less likely to adopt the practices explored than the Australian average. This may be due to structural and institutional arrangements that are unique to Queensland farmers, alternatively it may be a consequence of Queensland farming systems and the applicability of the practices explored. The finding certainly suggests the need for more detailed exploration of the Queensland situation, particularly as much previous research has focussed on the south-eastern states.
Age Age was significant for the adoption of two practices, with younger farmers more likely to adopt than older farmers. This is consistent with findings that suggest that younger farmers tend to be more aware of land degradation and recognise the need for the adoption of conservation practices (Fenton, Macgregor & Cary 2000).
Farm financial characteristics The financial outlook attitude variable reflects owner/operators’ perceptions about the future profitability of their farms. With the exception of one practice, the direction of the significant association was as expected. Those individuals who thought their future profitability would fall in the next five to 10 years were less likely to adopt the practice. To a much lesser extent, owner/managers who felt more able to afford to address land and water degradation were more likely to adopt practices. The findings confirm that financial capacity is an important component in determining the capacity of individuals to adopt new practices. Farmers who feel secure in their financial future are more likely to invest resources in adopting new resource management practices. Absolute measures of financial capacity (farm cash income and profit at full equity) were each positively related to adoption of only one practice. Those owner/managers who had higher equity, and thus greater financial flexibility to operate their farm businesses, were less likely to adopt particular practices. However in the case of controlling flowing bores the converse relationship was found. Overall, the relationship between equity and adoption was not as might be predicted. This suggests the possibility of other confounding effects associated with high equity and the need for more careful analysis of the adoption habits of those farming enterprises with high equity. It is possible that landholders with high equity in their properties are more risk averse and thus less inclined to adopt risky resource management technologies.
Education and training Recent involvement in training courses was consistently significantly associated with adoption in a positive direction. Those landholders who had attended more training courses
were more likely to adopt practices than those who had attended less. Training is clearly an important contributor to an individual’s capacity to change. Training was the characteristic most frequently linked to practice adoption in Mues, Chapman and Van Hilst (1998) study, though of less importance in the CIE (2001) study. In addition to the number of recent training courses attended, the more specific involvement in a Property Management Planning course or program was positively associated with the adoption of two practices. Training and participation in PMP may alleviate technical concerns that owner/managers have about resource management practices. While this direct relationship was not explored, those owner/managers who felt they did not have the technical resources to adequately address land and water degradation on their property were less likely to adopt resource management practices. This concern, and the impact that training has on adoption behaviour, suggest that training and overcoming any fears that owner/managers may have about resource management practices are an important aspect of an individual’s capacity to adopt. Technical concerns about the resources required to adequately address land and water degradation is likely to reflect the fact that many sustainable management practices are complex to integrate into farming systems and are often not adapted or appropriate for use in many localities. It should be noted that a generic education level variable was not incorporated in the models estimated due to difficulties in developing a meaningful measure and, more importantly, due to likely confounding effects with age. Furthermore the specific measures, just discussed, are likely to be a more accurate reflection of relevant training.
Farm structure and farm plan Land use intensity measured in sheep equivalents per hectare was associated with adoption for six practices. For four of these practices as the intensity of land use increased so too did the adoption of practices, while in the case of preserving or enhancing areas of conservation value and conservation tillage the association was negative. Mues, Chapman and Van Hilst (1998) also found a significant positive association with two practices they investigated. In general it may be argued that those owner/managers who farm most intensively would need to adopt resource management practices in order to maintain the productive capacity of their property. Those who did not may find the resource base is unable to withstand increased intensity of production. While Curtis et al. (2000) highlighted the importance of farm size in their work on practice adoption, this analysis found that farm size was only significantly associated with adoption of deep rooted perennial pasture in the wheatsheep and high rainfall zones.
33
The existence of a farm plan was significantly positively associated with the adoption of six practices. The importance of a farm plan was not demonstrated in either Mues, Chapman and Van Hilst (1998) or Curtis’ et al. (2000) studies, however it was the most frequently associated characteristic in the CIE (2001) study of the rangelands. The presence of a farm plan would suggest a more pro-active and prepared owner/manager who may take greater advantage of new farming techniques and approaches.
Landcare and environmental attitude Landcare membership has long been associated with greater adoption of resource management practices (eg Cary & Webb 2000; Mues, Chapman and Van Hilst 1998; Curtis & DeLacy 1996) and these findings, at least in some cases, also support that association. However the length of landcare membership was anomalous with both a positive and negative association found. Landcare membership and the length of that membership are sometimes used as a surrogate for commitment to a stewardship ethic or proenvironmental value position (eg Curtis et al. 2000). In this study an environmental concern attitude was able to tap this stewardship dimension, and the expected relationship was commonly found. Those owner/managers who considered land and water degradation as critical concerns in farm planning were also more likely to have adopted resource management practices.
concern and increase human capacity to implement resource management practices. Technical concern about the resources required to adequately address land and water degradation is also likely to reflect the fact that many sustainable management practices are complex to integrate into farming systems and are often not adapted or appropriate for use in many localities. The analysis produced some statistically significant findings which compare favourably with other studies, the differences between studies and some anomalous findings suggest more consideration needs to be given to the types of characteristics that will usefully explain the adoption of sustainable practices. Furthermore analysis such as these that tend to be based on a large zonal, or whole of Australia, approach which will frequently be confounded by the large variability that exists in Australian agriculture and the often locality-specific nature of many sustainable management practices. Understanding of farmer adoption behaviour could be advanced through more specific studies focussing on particular localities and industries.
Summary Personal financial capacity was an important component in determining the capacity of landholders to adopt new practices. Farmers who felt secure in their financial future were more likely to invest resources in adopting new resource management practices. Landholders’ perceptions of their financial situation were more often associated with practice adoption than were objectively measured indicators of financial position. An individual’s subjective assessment of their financial situation may be a better predictor of adoption than objective measures. This highlights the importance of perceived reality in adoption behaviour; similar associations between financial perceptions and business behaviour can be observed in the wider economy. More frequent landholder involvement in training courses and having a farm plan were commonly associated with adoption of resource management practices. Participation in training courses related to management and skills is an important contributor to an individual’s capacity to adopt sustainable practices. Landholders’ who considered they did not have the technical resources to adequately address land and water degradation on their property were less likely to adopt resource management practices. Training may reduce this 34
Attitudes and values and the adoption of sustainable practices Because of the often tenuous nature of the link of attitudes and values with behaviour it has always been difficult to predict individual behaviour as a consequence of an individual holding a particular value or having a particular attitude. A weakly, or moderately, held attitude or value will generally not result in a corresponding and consistent behaviour where that behaviour requires ‘strong’ commitment of self or personal resources.
Attitudes In many studies it has been observed that attitudes and behaviours are related to an extent that ranges from a small to a moderate degree. There is a general tendency for individuals, in the absence of constraints, to seek consistency between attitudes and behaviours. Another way for individuals to achieve psychological consistency is to publicly espouse ‘symbolic beliefs’ reflecting the relevant social norms but engage only in token behaviour, sufficient to provide apparent consistency (Cary 1991; Cary 1993). Instrumental beliefs, related to self-interest, are likely to be more powerful than (moderately held) symbolic beliefs in influencing substantive environmental behaviour. The attitude–behaviour relation is further complicated by the fact that causation is not one-way: behaviour can also determine attitudes. The link between behaviour and attitudes is complex because the relationship between attitudes and behaviour is commonly many-to-one; i.e., many different attitudes – of potentially differing strength and direction and including attitudes towards complying with social norms regarding the behaviour– may be associated with a particular desirable behaviour. Thus an individual may have some attitudes that are ‘positive’ towards a particular NRM behaviour (e.g. it is good for the environment) and other attitudes that are ‘negative’ towards the particular behaviour (e.g. it costs me money). An attitude exists within a personal knowledge structure comprised of beliefs, linked in associative networks. If all ‘attitudes’ in an individual’s belief system with respect to the behaviour are not taken into account it is unlikely behaviour can be successfully inferred.
of cognition. An assertion that planting trees will reduce groundwater accessions is a belief. More complex beliefs might embrace assertions about the length of time between planting trees and subsequent reduction in ground water accessions. Belief systems have much in common with broader social knowledge systems; but they are not identical. Belief systems belong to an individual and are idiosyncratic. Belief systems often include representations of ‘alternative’ worlds, typified as ideological beliefs (Abelson 1979). Belief systems are likely to include a substantial amount of episodic material from personal experience. And, beliefs can be held with varying degrees of certainty.
Values Values are more generalised aggregations of attitudes and beliefs; values allow more generalised responses to a wider range of entities. Values tend to be more strongly held and to be more stable than attitudes and hence they are changed less easily and less quickly. Changes in values and subsequent associated changes in behaviour are thus harder to observe. While there is mixed research evidence in the literature, there is a body of evidence indicating positive relationships between environmental values and environmentally protective actions. Ross (1999:29) has provided an assessment of the implications: • Values are closely related to people’s priorities. • They provide guidance – however loose – to people’s likely behaviour, including their adoption of new ‘technologies’. • They offer approaches for assessing what policy options people will accept, or perhaps reject.
Beliefs
In considering the adoption of more sustainable resource management practices the landcare ethic provides a useful characterisation of environmental values. The landcare ethic embraces a broad continuum of values. At one end – the ‘deeper green’ end – is a concern for the health of the land as an end in itself. At the other end is a more utilitarian or instrumental focus of protecting the land to ensure its continued productivity and thus economic benefit to the farmer (Cary & Webb 2000).
Beliefs are the knowledge base upon which attitudes are formed. The traditional, all-embracing tripartite conception of an attitude asserted that an attitude comprised emotional, cognitive and behavioural components. The cognitive component is better thought of as the relevant beliefs that underpin individuals’ attitudes. Beliefs can be thought of as assertions about the degree of association between objects which exist within, and comprise, a domain
Over the longer term aggregate changes in personal value systems and more strongly held attitudes become community norms. The resultant formation, or reinforcement, of norms – such as the norms embracing a landcare ethic – can lead to the strengthening of social movements and reinforce feedback loops for socially desirable personal (pro-environmental) behaviour and for 35
environmental concern and, potentially, adaptive behaviour can be described in Stern et al.’s (1995) sociopsychological framework (Figure 3). The framework we adapted here is one developed from work by Stern (1992), Stern et al. (1993), Stern and Dietz (1994) and Stern et al. (1995).
supporting social or legal regulation that prescribes or proscribes such behaviour.
A framework of environmental concern
The broad outline presented in Figure 3 shows interactions which occur between the various elements. While the interactions are often two-way, causation generally flows from top to bottom. The factors identified at the top of the framework are considered to be less mutable by the individual or through the life course than those at the bottom.
It is useful to develop a simple framework to depict how values and beliefs influence an individual’s appraisal process and potentially influence individual behaviour. The adaptive responses are complex and are mediated by wider social assessments that are changing over time and are multidimensional in nature. Values and beliefs which reflect
social culture institutional constraints incentive structure
values
general beliefs worldview
specific beliefs specific attitudes
behavioural commitments and intentions
behaviour
Figure 3 A framework of environmental concern (after Stern et al. 1995).
The framework highlights that individuals are located within a social ‘culture’ which influences the development of values, beliefs, attitudes and, ultimately, behaviours. Social culture factors play a large role in the shaping of an
individual’s early life (and later life) experiences and, general beliefs about the world.
36
Many values are formed through early family socialisation processes and these values are thought to be relatively stable in adults (Oppenheim 1992; Stern and Dietz 1994). Such existing pre-formed values are likely to be resistant to change; however ‘new’ (as opposed to earlier formed) values can be more easily embraced. At the next level Stern et al. (1995) place an individual’s general beliefs and worldview. These encompass an individual’s broad understanding of how the world operates. In the context of environmental issues this level of the framework comprises an individual’s understanding of the biophysical environment and its function, and also how the environment is affected by human actions. Stern et al. (1995) consider worldview to be causally antecedent to values. They argue that, in contrast to values that are formed during early family life, worldviews are more likely to be the result of broader experiences within the social and political world. Furthermore, while values tend to be largely immutable in adults, worldviews, being comprised of beliefs, are vulnerable to empirical challenge and may change. Notably worldviews and general beliefs at this level of the framework are distinguished from more specific or localised beliefs, such as those associated with a particular location. A key feature of Stern’s framework is the role that values and worldview play in the assimilation of new information by individuals. Values and worldview may operate as ‘social amplifiers’ in that a particularly strong value orientation may lead an individual to selectively seek information or attend selectively to information about the consequences of some action for the objects they value (Stern and Dietz 1994). Likewise values and worldview may act as ‘filters’ for information where individuals may more readily accept information that is congruent with their values and worldview. This function, particularly of value orientations, may work to attenuate the potential impact that any empirical challenge, through information provision, has upon beliefs. Specific beliefs and specific attitudes are located towards the bottom of the framework in Figure 3. These psychological variables are placed most proximate to behavioural intent and actual behaviour, and are considered to have greatest impact upon them. In the framework this is the position where attitudes towards a particular practice and beliefs about the impacts and consequences of those practices would be located. Stern and Dietz (1994) stress that the processes of construction of an individual’s attitudes towards specific environmental issues are important as these issues are, often, at least initially, unfamiliar to those who form attitudes about them. They argue that individuals tend to ignore details and issuespecific information, but rather classify a topic and then make reference to their more general beliefs and values in forming their specific attitudes and beliefs about that issue (Stern et al. 1995). When asked to express an attitude about a particular environmental issue, an individual will
review their beliefs about the issue and assess the likely impact upon the things they value. The final two components of Stern’s framework relate to behavioural intent and finally to actual behaviour. These are of particular interest to policy makers attempting to encourage more sustainable farming practices by farmers. Behavioural intent has typically been operationalised by Stern and colleagues through the use of responses to scales about likelihood to take political action and willingness to pay extra tax to ameliorate negative environmental consequences (Stern et al. 1993; Stern and Dietz 1994). The linking of actual behaviour to other components of the framework, rather than self-reported intentions, is arguably the least developed aspect of Stern’s framework. The framework (Figure 3) highlights the important role that social culture, values and beliefs play in the formation of specific attitudes and specific beliefs regarding a particular environmental issue.
Values and the appraisal of sustainable management practices Earlier a distinction was made between environmental or deeper green values and those which were more utilitarian or instrumental (see section on Values above). Typically for most people, apart from the most environmentally committed, utilitarian and instrumental values tend to predominate over environmental and non-instrumental values, in determining behaviour related to environment and the use of sustainable practices. We will now explore the conditions under which different values come into play. Guagnano et al. (1995) have enunciated the conditions under which positive environmental values and attitudes are most likely to influence, or be associated with, significant behaviour change. They found the environmental attitude−behaviour association to be strongest when the instrumental ‘context’ was weakest or neutral, for example where the environmental behaviours were not obligatory or tangibly rewarded. They found the environmental attitude−behaviour association approached zero when the instrumental or external forces were strongly positive or negative, effectively compelling or prohibiting the behaviour in question (Guagnano et al. 1995). We depict a schematic diagram of the conditions for maximum influence of environmental values or attitudes on individual’s decision to adopt sustainable practices in Figure 4. Guagnano et al.’s (1995) proposition implies that for personal behaviours that are not strongly favoured by being required or tangibly rewarded, the more difficult, timeconsuming, or costly the behaviour, the weaker is the dependence on attitudinal or environmental value factors. Values and attitudes have both direct and indirect effects on individual behaviour. The analysis above applies to the influence of personal attitudes and values on personal 37
behaviour and this can be considered a direct effect. The impact of many individuals’ values when expressed in social aggregates – as social norms – becomes more complex and their influence is potentially more powerful. This influence can be considered an indirect effect. Over the longer term aggregate changes in personal value systems and more strongly held attitudes become community norms. The reinforcement of norms – such as
the norms embracing a landcare ethic – can lead to the strengthening of social movements (such as the landcare movement) and reinforce feedback loops for socially desirable environmental behaviour (Stern, Dietz, Abel, Guagnano and Kalof 1999).
Maximum effect of values and attitudes on behaviour (when incentives or disincentives minimal)
Extent of behaviour change influenced by attitudes
Higher costs or disincentives
Higher rewards or incentives
Minimal effect of external incentives or disincentives on behaviour
Figure 4 Conditions for maximum influence of environmental values or attitudes on individual’s decision to adopt sustainable practices
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Interventions to promote adoption of NRM practices It is important to understanding the mechanisms by which values and attitudes may influence NRM behaviour and the adoption of sustainable practices. It is also important to recognise the relatively minor impact of ‘pro-environmental’ values and attitudes in bringing about sustainable practice adoption when there are significant costs and considerable uncertainty associated with the adoption of many NRM practices. For significant behaviour changes the impact of pro-environmental values and attitudes tends to be indirect (and considerably delayed, through social influence) rather than directly influencing individuals’ behaviour. The analysis of the influence of values and attitudes on behaviour in the previous chapter suggests that greater influence on sustainable practice adoption will be achieved by focusing on relevant behaviours and practices rather than personal attitudes and values. Thus it will be more useful to adopt a behaviour analysis approach to encouraging appropriate NRM behaviours. Geller (2001) has identified three behavioural principles that are relevant to encouraging the adoption of sustainable NRM practices. These principles focus on making any intervention, to change behaviour, more effective. The behaviour analysis approach is based on the behavioural intervention principles developed by B. F. Skinner (1953, 1974). Skinner’s behaviourism has been long established but, more recently, has been unfashionable because of its exceptionally narrow view of human behaviour as being as being a series of responses to external stimuli. Human behaviour is clearly much more adaptive and internally focused. However, a wider and more complex understanding of human behaviour does not preclude Skinner’s behavioural principles being relevant to explaining human behaviour.
Principle 1: Focus Interventions on Observable Behaviour If the behaviour cannot be readily seen by the individual (and by others) it will be ineffective to encourage it; it will be difficult to be monitored, to be seen as rewarded (or penalised, for its absence). Geller contends that behaviourbased intervention acts people into thinking differently, whereas person-based intervention thinks people into acting differently (Geller 2001). Person-based approaches are impractical for major interventions to change NRM practices because they are not cost-effective in community settings. Person-focused intervention requires extensive one-on-one interaction between a client and a trained intervention specialist (Geller 2001).
Many practices are not readily observable (see the section on observability in the chapter Characteristics of Sustainable Practices) and the outcomes from the practices are not apparent until a considerable time after the behaviour is initiated (see the discussion of Figure 1). The success of farm tree planting, particularly along roadside fences and in front paddocks, is an example of the effectiveness of this principle. Where a policy choice exists for intervention which involves observable behaviour it will be useful to select such interventions.
Principle 2: Look for External Factors to Improve Performance Because specific attitudes, perceptions and beliefs related to a given sustainable practice are difficult to identify and change directly it is likely to be more effective, in the first instance, to look for external factors influencing behaviour independent of individual feelings, preferences, and perceptions (Geller 2001). When interventions are implemented which lead to changed individual behaviour, indirectly, individuals change their attitude, commitment, and internal motivation reflecting the reciprocity between behavior and attitude (Bem 1970; Geller 2001). [See reciprocal arrows in Figure 3.]
Principle 3: Focus on Positive Consequences to Motivate Desired Behaviour Most human behaviour is undertaken to gain a positive consequence or to escape or avoid a negative consequence. Humans learn more from their successes (ie are more positively reinforced) than they learn from their mistakes (Geller 2001). Geller contends that recognizing people's environment-protective behavior will facilitate more learning and positive motivation than will criticizing their environment-damaging behavior. Ideally, to bring this principle into play for increasing the adoption of sustainable practices we need to identify NRM practices with relatively immediate positive consequences rather than less immediate, diffused, or short-term negative, consequences. Practices which have outcomes that are ‘soon’ and ‘certain’ will have the most powerful motivating consequences (Geller 2001). This suggests, that given the delay in achieving sustainable environmental outcomes from many NRM practices, the most effective practices will be those with more immediate productive outcomes and complementary (but more delayed) environmental outcomes.
There are constraints to applying this principle to the adoption of many recommended sustainable practices. 39
Consequences for adoption of sustainable practices A central tenet of the behaviourist or Skinnerian approach is that behaviour is determined by its consequences and, therefore, most people are unlikely to modify their behaviour as the result of information or advice alone, especially when the information pertains to a distant future (Skinner 1987; Geller 2001). This is the conundrum (or potential folly) for promoting sustainable practices, with low or negative immediate benefits, on the basis of appeals to future environmental sustainability. Although people will often follow advice when the advisor’s (or proponent’s) information previously led to reinforcing consequences, this situation requires people to experience the reinforcing consequences of following the advisor’s message. This type of learning . . . is especially difficult when the future consequences (reinforcing or punishing) are unclear, uncertain, or remote. (Geller 2001)
Primary appeals to broad world views or abstract values are unlikely to engender effective behaviour change because such views are considerably removed, or often disengaged, from everyday behaviour (see linkages in 8 Figure 3). Appeals such as ‘think globally, act locally’ are not as psychologically powerful as appeals to ‘think locally, 9 act locally’. In the final chapter we discuss some implications of these insights for research and development and the adoption of sustainable practices derived from research.
8
9
NRM practice promotional strategies, promoted primarily on the basis of instrumental and more immediate benefits, can be reinforced at an important secondary level by promotional information regarding the environmental rationale for adopting the practice. The secondary effect provides a long-term reinforcement (Boyce & Geller (2001)). And the global will obviously follow. The behaviourist view would reverse the order of thinking and acting in the exhortation. 40
Implications for the focus of R & D This chapter seeks to provide advice and options on strategies for overcoming impediments to the adoption of sustainable practices. The analysis in the previous two chapters indicates that the most effective means for encouraging sustainable practice adoption is to primarily focus on the relevant behaviours and practices that contribute to sustainable outcomes. Interventions to change values and attitudes should be a secondary focus because values and attitudes have indirect influence on behaviour and their influence is commonly constrained because NRM practices may often be complex or costly, time consuming or characterised by delayed rewards. Many practices may not be adapted or elaborated for local conditions.
Research and development programs need to develop NRM practices with relatively immediate positive consequences rather than less immediate, diffused, or short-term negative, consequences. Effective R& D intervention means designing practices to provide external benefits to make environment-sustaining behavior more likely (Principle 2 in previous Chapter). The most motivating consequences are ‘soon, certain, and sizable’ (Geller 2001). The fall-back (and much more expensive ) position is to otherwise change the external conditions in order to make environment-sustaining behavior more likely (Geller 2001). The latter strategy is only feasible for government or institutional intervention rather than R&D Corporations.
Adopters are adaptive Human behaviour related to implementing NRM practices is adaptive, rather than simply reactive, in its nature. Landholders and farmers adapt their behaviour on the basis of their experience. Appraisal and implementation of NRM practices will depend on assessment of, and experience with, the use of such practices. For landholders, the difficulty of observing linkages between many recommended NRM practices and desired sustainable outcomes is likely to further reduce positive appraisals of NRM practices by landholders.
The attractiveness of practices is not independent of the economic environment
Types of practices
Local adaptation
It is the inherent characteristics of sustainable practices that usually have the biggest influence on the rate of their adoption by producers. Sustainable practices that provide economic and other advantages will generally be adopted more rapidly. There is a need to develop or identify the practices that will produce desired sustainable outcomes and be inherently attractive to potential adopters.
The relative advantage of sustainable practices varies in different locations. It is dangerous to assume that a practice with comparative advantages in one location will yield the same level of advantage elsewhere. Few sustainable practices have universal applicability. (See the variation in geographic applicability for the sustainable practices listed in Table 1.)
Landholders generally seek to reduce the risk of adopting a new practice. Sustainable NRM practices which are observable, trialable, and less complex are generally more quickly adopted than NRM practices which are unobservable, untrialable, and complex. Sustainable NRM practices with environmental benefits are generally less advantageous to the producer, more complex, harder to trial and have benefits which are difficult to observe.
There are obvious advantages in being able to promote sustainable practices with more universal or global applicability. Firstly, messages can be simplified; secondly and more important, where a given practice or management behaviour is universally similar social pressure can be more clearly brought to bear to ensure behaviour maintenance. Social norms are easier to establish for practices that are widely used and understood than for locality specific behavior.
Pannell (2001b) has observed that the farm-level economics of currently available management practices for salinity prevention are adverse in many situations. As a consequence, Pannell recommended both better targeting of government programs, based on more rigorous analyses of proposed public investments; and, more significantly in the context of the discussion in this report, a greater emphasis on the development of improved technologies, both for salinity prevention and for adaptation to a saline environment.
The level of relative advantage is rarely independent of commodity prices. The relative advantage of many sustainable practices (such as deep-rooted perennials) will be dependent on the value of rural commodities produced as a result of using the practice. Low commodity prices in the broadacre industries have reduced the relative advantage of many sustainable practices. (See earlier case study of adoption of dryland lucerne.)
The advantage of generically global practices (for example, small scale tree planting in higher rainfall areas), for promoting and reinforcing sustainable practice adoption is seductively attractive. However, given Australia’s diverse environment, there are few sustainable practices which meet the test of global applicability. And universally applicable practices are often less likely to have large impacts on reducing local land degradation problems. The sustainable practices with wider geographic applicability, 41
such as currently available deep-rooted perennials, often provide only moderate relative advantage to the landholder. The relative advantage will be different in different localities. As a consequence, every advantage should be taken of sustainable practices that have widespread application. But, more importantly, increased effort needs to be applied to identify and develop locally applicable sustainable practices and effort made to resist the temptation to promote them beyond localities where their advantage has been established. When, or if, local sustainable practices are developed this approach can be thought of as locality branding of practices in the same way that certain agricultural products (such as wine) are locally branded. This is an example of think locally act locally.
elaboration) of conservation cropping techniques as part of the Soil Care program (Wilkinson & Cary 1993; Barr & Cary 1992). The demonstrations and pilot development are focused on local conditions, managed by a group of local property holders and the responsibility for success or failure is shared. Once the given practice is seen to be feasible and advantageous to implement, individuals can do so knowing the consequences are likely to be positive. Such approaches help identify any immediate and positive consequences of NRM practices which may not otherwise be readily apparent.
Assessing practices To improve the likelihood that improved NRM practices will be adopted by landholders R & D corporations have two options. First, improved management systems can be developed and adapted in conjunction with landholders in relevant localities. Second, potential improved practices being considered for promotion on farms, should be market tested with typical farmers or landholders at any early stage of their development. Such an approach encompasses long established on-farm trials. However such assessment should evaluate more than the traditional focus on technical feasibility. Potential new NRM practices should be assessed against each of the desired attributes of geographic applicability, relative advantage, risk, complexity, compatibility, observability and trialability considered in Table 1. Ideally, a recommended NRM practice should meet all these criteria for adoption in a particular locality. Realistically, a recommended NRM practice should meet as many of these criteria as is possible, particularly relative advantage and observability. After NRM practices are released and during early promotion individual practices derived from research need to be assessed – in terms of their attributes – as to why the practices are, or are not, adopted.
Reinforcing learning Given the outcomes from many NRM practices are not readily observable (see observability characteristics in Table 1) it is important to provide reinforcing learning experiences in any promotional or extension campaigns. Learning about, and adapting, NRM practices is especially difficult when the future consequences (reinforcing or punishing) are unclear, uncertain, or remote. Humans learn more from their successes than they learn from their mistakes and are more positively reinforced by their successes (Principle 3 above). Therefore landholders often need assistance to identify positive consequences of an NRM practice as early as possible and to short circuit early short-term failures. An example of this approach has been the use of small onfarm pilot demonstrations for the development (and local 42
Performance indicators and communication action plan
Performance indicators for assessing the effectiveness of adoption of R&D results Key performance indicators are, ideally, direct measures of desired producer behaviour related to sustainable NRM practices. Alternatively, surrogate indicators may be used which reflect correlations between selected indicators and desired outcomes of more sustainable management practices in relevant natural resources areas – including biodiversity, salinity, soil erosion. Useful indicators ideally should meet the following criteria: • relate unambiguously to intended policy use • the data are available at the required geographical scale and frequency • indicator can be easily understood • be generalisable over wide geographical scale. In practice selection of an indicator is usually determined by the measures or indicators that are available. The nonexhaustive list presented earlier in the section Sustainable Practices identified potential performance indicators of producer adoption. Currently ABARE, through its Resource Management Supplementary Survey, collects data, some of which provide measures which, with some constraints, may be appropriate indicators. This survey is ancillary to the Australian agricultural and grazing industry and Australian dairy industry surveys. The most recent Resource Management Supplementary Survey was 1998-99; however the Supplementary Surveys are irregular and currently not undertaken on an on-going basis. It should be recognised that the list presented earlier in the section Sustainable Practices is an incomplete list. Many of these practices were identified in the National Collaborative Project on Indicators for Sustainable Agriculture based on then available ABS and ABARE statistics. Measures of the level of landholder adoption of sustainable management practices available from the current ABARE Australian Resource Management Supplementary surveys were identified with the superscript a and cover generalised situations, cropping farms, irrigation farms, the Rangelands and dairy farms. The above practice indicators are essentially output indicators rather than outcome indicators (see Figure 1).
Research on social and other characteristics, based on useful indicators, which might indicate sustainable practice adoption is made difficult by the fact that sustainable practices have differential advantage to landholders in different localities and, often, differential advantage to different landholders within given localities. We are faced with the unsatisfactory choice of localised studies which lack uniformity in approach or more extensive studies (the ABARE RMS surveys) which currently collect simplified measures of the presence or absence of selected practices on properties rather than the extent of use of practices. As yet there is a very limited theoretical basis for postulating relationships, and guiding data collections, regarding adoption behaviour. Further work is required to design a suitable program of longitudinal data collection regarding adoption behaviour across and within localities to take account of the variability of Australian agriculture. The ideal we should be seeking is independently measured physical evidence of the extent of adoption of nominated practices, rather than of use of practices self-reported by landholders and collected by survey. The following issues, identified as important in relation to the adoption by producers of sustainable practices derived from research, present significant obstacles to establishing generalisable performance indicators: • importance of locality specificity • need to refine characteristics explaining adoption • need to focus on locality and complexity of individual NRM practices to explain adoption. As a consequence NRM resource questions included in the standard Australian Agricultural Census (AAC) question suite need to be segmented for localities and industries. It is likely that, in most cases, the industry specific questions in the ABARE RMS survey on sustainable practices are too broadly based to overcome the problem of locality specificity. The development of a suite of natural management resource questions as part of the standard AAC question suite is recommended. The inclusion of NRM questions within the AAC is for the most part dependent upon external user funding. NRM questions are not considered to be of prime importance in the development of the AAC. The need to capture this user funding, together with the relatively short timelines allowed for the development of the census form, means that the inclusion of a good suite of NRM questions is potentially a matter of circumstance rather than design. We recommend a reassessment of the relative importance of NRM issues in the census question suite to
43
adoption) when seeking to develop new sustainable practices.
ensure that a solid longitudinal data set of NRM management across Australia is achieved. 2.
Presentation of a seminar or workshop for rural R&D project managers to elaborate the findings of this project.
A communication action plan should comprise the following steps:
3.
• recognise the barriers to implementation of findings of and implications of this report
Identify more clearly the localities where given sustainable practices have a comparative advantage for landholders.
4.
Promote the idea of more integrated and formal ‘market testing’ of prototype sustainable practices in the development and local adaptation stages.
5.
Develop support systems to ensure more rapid ‘trial and error’ learning for landholders by the use of small on-farm pilot demonstrations, where appropriate, for the development and local elaboration of new developed sustainable practices.
Communication action plan
• identify areas where implications and findings from the report might be implemented • design a communication program to overcome these barriers.
Barriers to implementation of findings: The most important message to be communicated from this report is the achievement of desired sustainable outcomes depends on more widespread adoption and use of sustainable practices. Relatively few current sustainable practices possess attributes that make them attractive for widespread adoption by landholders. The rate of adoption of sustainable practices derived from research depends on practices being economically attractive to adopt. Newly developed sustainable practices need to provide observable and positive consequences for landholders over a short time frame. Most research for the development of sustainable practices is discipline driven. Thus the focus is on biological or technical feasibility rather than complementary consideration of adoptability. A broader focus requires one or more of clear directives in research objectives, a broader programmatic approach, or a systems approach to sustainable practice research. Linkages for on-farm commercial adaptation need to be established in such research programs. The impact of longer term commodity prices cannot be ignored in making assessments about implementation of sustainable practices.
Areas where findings can be implemented Land & Water Australia with its recent broader thematic R&D program with explicit social and institutional focus is well placed to respond to the findings of this report. However as much sustainable practice research and development is conducted in other industry-based R&D corporations it is important that the messages from this research are communicated to these bodies and other relevant research agencies.
Communication strategies 1.
Preparation of simple check-lists for assessing the attributes and characteristics required (for more rapid
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References
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Appendix A Analysis of the 1998-99 Resource Management Survey
Logistic regression Using data collected from their 1998-99 annual survey of Australia’s broadacre and dairy industries ABARE modelled the relationship between a range of farm family, farm property and farm business characteristics and reported adoption of sustainable land management practices. An overview of the analysis was presented earlier, with tables 4 and 5 indicating the independent (farm/farmer characteristics) and dependent (practice adoption) variables respectively. The dependent variable was represented as binary data (1=practice adoption, 0=no adoption). The independent variables were represented as nominal (including binary) and interval data (see Appendix B). In modelling a binary dependent variable a logistic regression technique is the most appropriate approach. The logistic model models the log odds ratio or “logit” of the dependent variable (that is ln[p/(1-p)] where p is the probability that adoption of a practice occurs) as a linear combination of a series of explanatory variables. This gives the following function: ln[p/(1-p)] = b0 + b1X1 + b2X2 + b3X3 + … + bkXk + e. Where Xi are the explanatory variables, bi are the coefficients to be estimated and e is an error term. In these analyses the logit of adoption is modelled as a linear combination of a range of farm family, farm property and farm business characteristics. This approach is considered superior to ordinary least squares regression (OLS) for modelling binary dependant variables. The logistic model guarantees that the predicted probability of adoption is between zero and one. Furthermore with a binary dependent variable, the assumptions of normally distributed and homoskedastic residuals required for OLS are both broken (Hosmer & Lemeshow 1989).
Model estimation ABARE surveys a sample of farms out of the total number of farms available. A survey sample of 1426 was selected for the 1998-99 survey, of which 197 respondents were interviewed by telephone with the remaining respondents interviewed in person. The sample covers the five broadacre industry types and the three farming zones. In order to reflect the actual composition of Australian farms the sample is weighted prior to data analysis. Sample weights are calculated so that population estimates of farm numbers, crop areas and livestock numbers in various
geographical regions and industries correspond as closely as possible to known Australian Bureau of Statistics census data (ABARE 2000). Prior to model estimation the samples were weighted so that the results could be inferred to the broader industries rather than just the survey sample. The models include two benchmark variables (sheep closing number and wheat area sown) which were used to ensure appropriate sample weighting. The farm sample is restricted by selecting the sample from those farms with an estimated value of agricultural operations (EVAO) of $22,500 or greater. Farms with an EVAO of less than this level were excluded from the survey. Accordingly the results presented here will be inaccurate to the extent that farms with an EVAO of less than $22,500 are excluded. The models were estimated using maximum likelihood regression. Prior to model estimation correlation matrices of continuous variables and frequency cross-tabulations of discrete variables were checked for high levels of correlation that may give rise to problems of multicollinearity. Where potential problems existed individual variables were removed from models to gauge impact. There were some issues of multicollinearity, however statistical advice from ABARE indicated it would not unduly affect the models. In estimating the models, Wald’s Chi-square and its corresponding probability were used to indicate the confidence level for which each independent variable is significantly associated with the logit function. For the purposes of this analysis a confidence level of 95% was chosen to indicate a significant association. The likelihood ratio test was used to indicate the significance of the overall model. The association of predicted probabilities and observed responses was also calculated as a measure of model ‘fit’. The higher the proportion of concordant associations the better the model is at predicting farmer behaviour based upon the variables included in the model.
Results Rather than explore the findings in terms of dependent variables as discussed earlier, this section details each individual model estimated. For each practice the logit regression results are provided. These indicate which explanatory variables were included in each model and the
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parameter estimates indicate the strength of the association between that variable and the logit function. Those in bold indicate a significant association between the characteristic and practice adoption as indicated by Wald’s Chi-square. Additionally we compare and contrast these findings with other recent comparable studies. In particular we draw upon recent work carried out in the rangelands for the Audit by the CIE (2001), work by Curtis et al. (2000) in Victoria’s Goulburn-Broken catchment and work by Mues, Chapman and Van Hilst (1998). Note that the measures of practice adoption may have been operationalised differently in each study, and that subsequent analyses performed were often upon different subsections of the farming community. Mues, Chapman and Van Hilst’s (1998) work is the most directly comparable, being based upon data collected during the 1995-1996 AAGIS/ADIS surveys and a landcare supplementary survey, though their model specifications were different. Thus while some relationships have been confirmed in different studies, differences can, in part, be explained as an artefact of study specificity and design.
Controlled flow bores in the pastoral zone
Overall the model was significant and gave 91.9% concordance between predicted probabilities and observed responses. Owner/managers with higher closing equity ratios (ie with lower relative debt burdens) were more likely to control flowing bores than those with lower equity levels. Owner/managers who thought the future profitability of their property was likely to drop were less likely to adopt than those who considered their future profitability to increases or remain the same in the next five to 10 years. Landcare membership was also positively associated with adoption. No other variables were found to be significantly associated with the decision to control flowing bores in the pastoral zone. Importantly the capping of bores is of primary relevance to Queensland pastoralists where uncontrolled bore flows are more of an historical artefact. However in this model the dummy variable for Queensland was found not to be significantly associated with practice adoption. CIE (2001) in its modelling of indicators of sustainable practice in the rangelands, while recording the practice, did not model this behaviour.
Three variables were significantly associated with the control of flowing bores in the pastoral zone (Table A1). Table A1 Logit regression results for the adoption of controlled flow bores in the pastoral zone. Effect
Unit
DF Parameter Estimate
Std Error
Intercept 1 -11.7300 542.2000 Age yrs 1 0.0302 0.0393 Environmental concern attitude 1 0.4479 0.4261 Financial concern attitude 1 0.0414 0.4945 Technical concern attitude 1 0.3535 0.5435 Financial outlook concern attitude 1 -1.0012 0.4330 Landcare membership- yes 1 1.7601 0.8578 Length of landcare membership yrs 1 0.3801 0.2126 Recent training 1 0.2114 0.4389 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 0.0523 0.0264 Farm plan / property manag plan - yes 1 0.1132 0.5084 Farm size 000/ha 1 -0.0027 0.0037 State 4 -NSW -0.6409 542.2000 -QLD 5.7524 542.2000 -SA 4.8158 542.2000 -WA -14.5163 2168.7000 Land use intensity se/ha 1 -1.6158 0.8584 PMP participation last 3 years - yes 1 0.02200 0.7973 Wheat area sown ha 1 0.0027 0.0033 Closing number of sheep no 1 -0.0001 0.0001 Sample size=125, adoptors=33. Model fit likelihood ratio test Chi-square=74.94, DF=21, P<0.0001 Association of predicted probabilities and observed responses: concordant=91.9%, discordant=7.9%, tied=0.2%
Chisquare
Prob
0.00 0.59 1.11 0.01 0.42 5.35 4.21 3.20 0.23 0.07 0.91 3.94 0.05 0.51 5.19 0.00 0.00 0.00 0.00 3.54 0.00 0.66 1.14
0.9827 0.4428 0.2931 0.9332 0.5154 0.0208 0.0402 0.0737 0.6301 0.7883 0.3396 0.0471 0.8238 0.4741 0.2684 0.9991 0.9915 0.9929 0.9947 0.0598 0.9780 0.4151 0.2841
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Controlling grazing pressure by excluding access to water in the pastoral zone
Research concerning practice adoption in the rangelands carried out by the CIE (2001) did not consider the control of grazing pressure by excluding stock access to water.
No variables were significantly associated with the control of grazing pressure by excluding access to water (Table A2). Table A2 Logit regression results for the control of grazing pressure by excluding access to water in the pastoral zone. Effect
Unit
DF Parameter Estimate
Std Error
Intercept 1 -0.7370 1.8381 Age yrs 1 -0.0113 0.0191 Environmental concern attitude 1 0.2931 0.2526 Financial concern attitude 1 -0.1086 0.3106 Technical concern attitude 1 0.3379 0.3206 Financial outlook concern attitude 1 -0.4422 0.2321 Landcare membership- yes 1 -0.4226 0.4229 Length of landcare membership yrs 1 0.0246 0.0916 Recent training 1 -0.1399 0.2478 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0003 0.0069 Farm plan / property manag plan - yes 1 0.1586 0.2567 Farm size 000/ha 1 0.0030 0.0024 State 4 -NSW 0.5355 0.4851 -QLD -0.5937 0.4370 -SA -1.3306 0.6734 -WA 0.8751 0.7238 Land use intensity se/ha 1 0.2104 0.2520 PMP participation last 3 years - yes 1 0.1696 0.3345 Wheat area sown ha 1 0.0005 0.0010 Closing number of sheep no 1 0.0000 0.0000 Sample size=186, adoptors=71. Model fit Likelihood ratio test Chi-square=41.40, DF=21, P=0.0050 Association of predicted probabilities and observed responses: concordant=68.3%, discordant=31.4%, tied=0.3%
Monitoring pasture and vegetation condition in the pastoral zone Seven variables were significantly associated with monitoring pasture and vegetation condition in the pastoral zone at the 95% confidence level (Table A3). Three financial variables, profit at full equity, closing equity ratio and financial outlook concern attitude were significantly associated with monitoring pasture and vegetation condition. However not all of the relationships were in the predicted direction. While owner/operators with increased profit levels were more likely to adopt the practice, those who had higher levels of debt and those that thought their future farm profitability would decrease were also more likely to adopt the practice.
Chisquare
Prob
0.16 0.35 1.35 0.12 1.11 3.63 1.00 0.07 0.32 0.87 0.89 0.00 0.38 1.47 9.18 1.22 1.85 3.90 1.46 0.70 0.26 0.23 0.08
0.6885 0.5551 0.2458 0.7266 0.2919 0.0567 0.3177 0.7884 0.5723 0.3513 0.3466 0.9687 0.5366 0.2240 0.0568 0.2696 0.1742 0.0482 0.2267 0.4037 0.6120 0.6308 0.7767
plans, to adopt the practice. State of residence was significantly associated with pasture and vegetation monitoring, with Queensland based owner/managers being significantly less likely to adopt than the Australian average and those in Western Australia more likely to adopt the practice. Two other attitude variables, the environmental concern and technical concern attitudes were significantly associated with adoption. Those owner/operators who considered water and land degradation to be a critical issue in their farm planning were more likely to adopt. Owner/operators who considered they did not have the technical resources to adequately address land and water degradation were less likely to adopt than those that considered they did have the technical resources.
Owner operators with a farm plan or a property management plan were more likely, than those without
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Mues, Chapman and Van Hilst (1998) considered this practice, however none of the variables they found to have significant associations (recent training, degradation, land use intensity and farm size) were significant in the model tested here.
state of residence with graziers resident in Western Australia more likely to adopt, and those from Queensland less likely to adopt. They also found a positive association between having a farm plan and practice adoption. CIE also found that age was significantly and negatively associated with practice adoption.
CIE (2001) considered pasture monitoring in its study in the rangelands. CIE found confirming results with respect to Table A3 Logit regression results for the adoption of monitoring pasture and vegetation condition in the pastoral zone. Effect
Unit
DF Parameter Estimate
Std Error
Intercept 1 -0.8746 2.0165 Age yrs 1 -0.0334 0.0212 Environmental concern attitude 1 0.7963 0.2553 Financial concern attitude 1 0.5074 0.3001 Technical concern attitude 1 -0.6737 0.3070 Financial outlook concern attitude 1 0.7454 0.2579 Landcare membership- yes 1 -0.1692 0.4469 Length of landcare membership yrs 1 0.0983 0.0972 Recent training 1 0.2385 0.2692 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0199 0.0081 Farm plan/property man plan - yes 1 1.3614 0.3286 Farm size 000/ha 1 -0.0019 0.0021 State 4 -NSW -0.5199 0.5393 -QLD -1.7715 0.5901 -SA -0.5725 0.6702 -WA 1.9204 0.6629 Land use intensity se/ha 1 0.0461 0.4443 PMP participation last 3 years - yes 1 -0.1794 0.3716 Wheat area sown ha 1 -0.0229 0.0214 Closing number of sheep no 1 0.0000 0.0001 Sample size=203, adoptors=82 Model fit Likelihood ratio test Chi-square=116.53, DF=21, P<0.0001 Association of predicted probabilities and observed responses: concordant=81.4%, discordant=18.2%, tied=0.4%
Deep rooted perennial pasture in the wheat-sheep and high rainfall zones (broadacre industries only) Seven variables were associated with the adoption of deep rooted perennial pasture in the wheat-sheep and high rainfall zone (Table A4). Farm size and closing equity ratio were both negatively associated with adoption. Owner/managers with larger farms or with lower debt ratios were less likely to adopt than those with smaller farms or higher debt ratios. Involvement in Property Management Planning in the last three years was significantly associated with higher levels of adoption. Three attitude variables were also significantly associated with adoption. Owner/managers who considered they did not have the technical resources to deal with water and
Chisquare
Prob
0.19 2.48 9.73 2.86 4.82 8.35 0.14 1.02 0.79 2.50 7.27 5.97 17.17 0.74 13.73 0.93 9.01 0.73 8.39 0.01 0.23 1.14 0.04
0.6645 0.1150 0.0018 0.0909 0.0282 0.0038 0.7049 0.3121 0.3756 0.1138 0.0070 0.0145 <.0001 0.3882 0.0082 0.3351 0.0027 0.3930 0.0038 0.9174 0.6294 0.2848 0.8399
land degradation or those who thought their farm profitability would drop in the next five to 10 years were less likely to plant deep rooted perennial pasture. However those who considered they did not have the financial resources to adopt were less likely to adopt than those who considered they did have the financial resources. State of residence was an important explanatory variable; New South Wales was more likely to adopt than the average for Australia. Victoria, Queensland and Western Australia were all less likely to adopt than the average for Australia. Cary and Wilkinson (1997) found an association between farm size and planting deep-rooted pasture species, and a weak association with length of Landcare membership. Curtis et al. (2000) found significant associations between
52
the area sown to introduced perennial pastures and a number of explanatory variables. However the practice was operationalised in a different manner, and this may explain differences between the findings. Curtis et al. (2000) found property size to be significantly related, however in their case larger properties were more likely to have planted greater areas to deep rooted perennial pasture, while in the
analysis of the RMS data here larger properties were more likely not to have made the discrete decision to adopt the practice. Curtis et al. (2000) also found landcare membership to be negatively associated with adoption, where the ABARE analysis did not find a significant association.
Table A4 Logit regression results for the adoption of deep rooted perennial pasture in the wheat-sheep and high rainfall zones (broadacre industries only). Effect
Unit
DF Parameter Estimate
Std Error
Intercept 1 1.5385 0.6976 Age yrs 1 -0.0007 0.0070 Environmental concern attitude 1 0.0060 0.0759 Financial concern attitude 1 0.1968 0.0787 Technical concern attitude 1 -0.3272 0.0857 Financial outlook concern attitude 1 -0.3150 0.0727 Landcare membership- yes 1 0.0942 0.1269 Length of landcare membership yrs 1 0.0311 0.0316 Recent training 1 -0.0274 0.0797 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0095 0.0031 Farm plan / property manag plan - yes 1 -0.1173 0.0954 Farm size 000/ha 1 -0.1341 0.0596 State 5 -NSW 1.0706 0.1536 -VIC -0.4970 0.1736 -QLD -0.4487 0.2256 -SA -0.2240 0.2189 -WA -0.4989 0.2184 Land use intensity se/ha 1 0.0331 0.0217 PMP participation last 3 years - yes 1 0.2792 0.1323 Wheat area sown ha 1 -0.0001 0.0003 Closing number of sheep no 1 0.0001 0.0000 Sample size=894, adoptors=403 Model fit Likelihood ratio test Chi-square=175.13, DF=21, P<0.0001 Association of predicted probabilities and observed responses: concordant=71.3%, discordant=28.5%, tied=0.2%
Soil/plant tissue tests to determine fertiliser needs in the wheat-sheep and high rainfall zones (broadacre only) Seven variables were associated with the use of soil or plant tissue tests to determine fertiliser needs (Table A5). Recent training, length of landcare membership, farm cash income, land use intensity and having a farm plan were all positively associated with practice adoption. While farm cash income is significantly associated the parameter estimate indicates the actual effect of farm cash income to be minimal. State of residence was also associated with
Chisquare
Prob
4.86 0.01 0.01 6.26 14.58 18.77 0.55 0.97 0.12 0.20 0.51 9.59 1.51 5.05 85.62 48.60 8.19 3.96 1.05 5.22 2.33 4.45 0.25 4.20
0.0274 0.9262 0.9372 0.0124 0.0001 <.0001 0.4582 0.3246 0.7310 0.6533 0.4737 0.0020 0.2190 0.0246 <.0001 <.0001 0.0042 0.0467 0.3061 0.0224 0.1268 0.0348 0.6172 0.0404
adoption, with owner/managers based in Queensland less likely to adopt the practice than the average for Australia. Those owner/managers who considered land and water degradation to be critical in farm planning were more likely to adopt tests for fertiliser needs. Mues, Chapman and Van Hilst (1998) investigated the adoption of regular soil testing by cropping specialists and found similar relationships, with training and land use intensity both associated with adoption. Additionally, they found closing equity ratio and farm size to be significantly related to regular soil testing.
53
Table A5 Logit regression results for the adoption of soil/plant tests to determine fertiliser needs in the wheat-sheep and high rainfall zones (broadacre industries only). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 -0.5124 0.5731 Age yrs 1 -0.0058 0.0060 Environmental concern attitude 1 0.1750 0.0666 Financial concern attitude 1 -0.0964 0.0719 Technical concern attitude 1 -0.0281 0.0758 Financial outlook concern attitude 1 -0.0532 0.0590 Landcare membership- yes 1 -0.0539 0.1159 Length of landcare membership yrs 1 0.0889 0.0331 Recent training 1 0.3202 0.0718 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0028 0.0028 Farm plan / property man plan - yes 1 0.2333 0.0841 Farm size 000/ha 1 -0.0420 0.0392 State 5 -NSW -0.2513 0.1395 -VIC -0.1940 0.1468 -QLD -0.8055 0.1897 -SA 0.2184 0.1922 -WA -0.0080 0.2049 Land use intensity se/ha 1 0.0658 0.0112 PMP participation last 3 years - yes 1 -0.1486 0.1169 Wheat area sown ha 1 0.0014 0.0004 Closing number of sheep no 1 0.0000 0.0000 Sample size=1224, adoptors=786. Model fit Likelihood ratio test Chi-square=269.11, DF=22, P<0.0001 Association of predicted probabilities and observed responses: concordant=69.6%, discordant=29.9%, tied=0.5%.
Tree and shrub establishment in the wheat-sheep and high rainfall zones (including dairy industries) Seven variables were associated with the establishment of trees and shrubs in the wheat-sheep and high rainfall zones (Table A6). Landcare membership, having a farm plan and land use intensity were positively associated with adoption. Three attitude variables: environmental concern, technical concern and financial outlook were also significantly associated. Owner/managers who considered land and water degradation to be critical in farm planning were more likely to establish trees and shrubs. Those with increased levels of concern regarding their technical resources were less likely to engage in the practice than those with lower levels of technical concern. Similarly, those owner/managers with a more negative financial outlook were less likely to plant trees and shrubs than those with a more positive financial outlook. Owner/managers in Queensland were less likely to adopt than the Australian
0.80 0.91 6.91 1.80 0.14 0.81 0.22 7.21 19.88 7.01 1.61 1.04 7.70 1.15 22.05 3.34 1.75 18.03 1.29 0.00 34.28 1.62 13.46 0.34
Prob 0.3713 0.3402 0.0086 0.1799 0.7110 0.3670 0.6422 0.0072 <.0001 0.0081 0.2050 0.3068 0.0055 0.2844 0.0005 0.0676 0.1863 <.0001 0.2557 0.9690 <.0001 0.2038 0.0002 0.5581
average and those in Western Australia were more likely to adopt. Curtis et al. (2000) considered the total area of trees planted in their study of the Goulburn–Broken catchment. The only common variable they found to be significantly associated with the practice was ‘having a written property plan that involved a map or other documents’. They found significant associations between the total area of trees planted and farm size. Mues, Chapman and Van Hilst (1998) considered the adoption of tree planting by livestock specialists in the wheat-sheep and high rainfall zones. They also found the presence of a farm plan to be significantly associated with practice adoption, however they also found training to be significantly related, a result which was not confirmed in the analysis here. The more selective industry analysis performed by Mues, Chapman and Van Hilst (1998) is likely to explain some differences in the findings.
54
Table A6 Logit regression results for the establishment of trees and shrubs in the wheat-sheep and high rainfall zones (including dairy industries). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 0.4799 0.5923 Age yrs 1 -0.0071 0.0062 Environmental concern attitude 1 0.1898 0.0673 Financial concern attitude 1 -0.0400 0.0739 Technical concern attitude 1 0.2188 0.0806 Financial outlook concern attitude 1 -0.1663 0.0604 Landcare membership- yes 1 0.4288 0.1264 Length of landcare membership yrs 1 0.0184 0.0352 Recent training 1 0.0253 0.0723 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0042 0.0028 Farm plan / property man plan - yes 1 0.2250 0.0889 Farm size 000/ha 1 -0.0274 0.0343 State 5 -NSW -0.0052 0.1336 -VIC 0.2790 0.1453 -QLD -0.9993 0.1878 -SA -0.0209 0.1847 -WA 0.8958 0.2199 Land use intensity se/ha 1 0.0459 0.0113 PMP participation last 3 years - yes 1 0.1529 0.1249 Wheat area sown Ha 1 -0.0003 0.0002 Closing number of sheep No 1 0.0000 0.0000 Sample size=1201, adoptors=717. Model fit Likelihood ratio test Chi-square=235.20, DF=22, P<0.0001 Association of predicted probabilities and observed responses: concordant=74.0%, discordant=25.8%, tied=0.2%.
0.66 1.32 7.95 0.29 7.37 7.59 11.50 0.27 0.12 0.10 0.25 2.16 6.41 0.64 42.91 0.00 3.69 28.30 0.01 16.59 16.51 1.49 1.77 0.65
Prob 0.4179 0.2507 0.0048 0.5882 0.0066 0.0059 0.0007 0.6012 0.7260 0.7528 0.6174 0.1418 0.0113 0.4234 <.0001 0.9689 0.0549 <.0001 0.9097 <.0001 <.0001 0.2209 0.1834 0.4189
not have farm plans. As land-use intensity increased, adoption also increased; and as equity increased the likelihood of adoption decreased. In contrast to these findings, Mues, Chapman and Van Hilst (1998) found landcare membership and training to be significantly associated with regular monitoring of water tables by mixed livestock-cropping enterprises, while having a farm plan, closing equity ratio and land use intensity were not significantly associated with adoption of the practice.
Regularly monitor watertables in the wheat-sheep and high rainfall zones (including dairy industries) Three variables were associated with the adoption of regularly monitoring water tables (Table A7). These variables were having a farm plan, closing equity ratio and land use intensity. Owner/managers with a farm plan were more likely to monitor their water tables than those that did
Table A7 Logit regression results for the regular monitoring of watertables in the wheat-sheep and high rainfall zones (including dairy industries). Effect Intercept Age Environmental concern attitude Financial concern attitude Technical concern attitude Financial outlook concern attitude Landcare membership- yes Length of landcare membership
Unit
yrs
yrs
DF Parameter Estimate 1 1 1 1 1 1 1 1
-1.5965 -0.0021 0.0644 0.0422 -0.0895 0.1149 0.1391 0.0372
Std Error
Chisquare
Prob
0.7725 0.0086 0.0929 0.0961 0.1056 0.0808 0.1400 0.0336
4.27 0.06 0.48 0.19 0.71 2.02 0.99 1.22
0.0388 0.8030 0.4878 0.6610 0.3971 0.1551 0.3203 0.2683
55
Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Recent training 1 0.0099 0.0871 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0109 0.0035 Farm plan / property man plan - yes 1 0.4103 0.1035 Farm size 000/ha 1 -0.2400 0.1274 State 5 -NSW -0.0895 0.2241 -VIC 0.2993 0.2121 -QLD 0.1046 0.3065 -SA 0.5820 0.2692 -WA 0.0498 0.2826 Land use intensity se/ha 1 0.0268 0.0125 PMP participation last 3 years - yes 1 0.0702 0.1429 Wheat area sown ha 1 0.0004 0.0004 Closing number of sheep no 1 0.0001 0.0001 Sample size=1147, adoptors=190. Model fit Likelihood ratio test Chi-square=94.44, DF=22, P<0.0001 Association of predicted probabilities and observed responses: concordant=69.6%, discordant=29.9%, tied=0.5%.
0.01 0.04 0.81 9.73 15.72 3.55 7.33 0.16 1.99 0.12 4.68 0.03 4.61 0.24 0.89 2.59
Prob 0.9099 0.8435 0.3685 0.0018 <.0001 0.0596 0.1971 0.6895 0.1582 0.7330 0.0306 0.8601 0.0318 0.6232 0.3461 0.1078
recent training and technical concern. As training increased the likelihood of collecting dairy effluent increased; and with increasing technical concern about inadequate resources to address land degradation the likelihood of collection of dairy effluent decreased.
Collection of dairy effluent (dairy industry only) Two variables were associated with the collection of dairy effluent by dairy farmers (Table A8). These variables were
Table A8 Logit regression results for the collection of dairy effluent (dairy industry only). Effect Intercept Age Environmental concern attitude Financial concern attitude Technical concern attitude Financial outlook concern attitude Landcare membership- yes Length of landcare membership Recent training Farm cash income Profit at full equity Closing equity ratio Farm plan / property manag plan - yes Farm size State -NSW -VIC -QLD -SA -WA Land use intensity PMP participation last 3 years - yes Wheat area sown Closing number of sheep
Unit
yrs
yrs $ $ % 000/ha
se/ha ha no
DF Parameter Estimate 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5
1 1 1 1
Std Error
Chisquare
Prob
1.0427 0.0018 0.0383 -0.0034 -0.5608 -0.0806 -0.5936 0.1183 0.6553 0.0000 0.0000 0.0026 0.0898 0.4491
1.4824 0.0139 0.1908 0.2013 0.2032 0.1389 0.3243 0.1151 0.2050 0.0000 0.0000 0.0081 0.2211 0.8234
-0.0005 0.1845 0.7661 0.4581 0.4367 0.0330 -0.2293 0.0111 -0.0008
0.3887 0.3121 0.3868 0.5204 0.7296 0.0196 0.2730 0.2000 0.0010
0.49 0.02 0.04 0.00 7.62 0.34 3.35 1.06 10.22 2.17 1.98 0.10 0.16 0.30 5.67 0.00 0.35 3.92 0.77 0.36 2.81 0.71 0.30 0.55
0.4818 0.8990 0.8410 0.9867 0.0058 0.5919 0.0672 0.3042 0.0014 0.1411 0.1590 0.7483 0.6845 0.5855 0.3402 0.9902 0.5545 0.0476 0.3788 0.5495 0.0935 0.4009 0.5809 0.4576
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Sample size=307, adoptors=237. Model fit Likelihood ratio test Chi-square=53.90, DF=22, P=0.0002 Association of predicted probabilities and observed responses: concordant=68.6%, discordant=31.0%, tied=0.3%.
Landcare membership was positively associated with pumping effluent, however owner/managers with longer membership of landcare were less likely to pump effluent than those who had been landcare members for shorter periods. State of residence was also significant with dairy farmers in Victoria and Queensland both more likely to adopt the practice than the Australian average.
Pump dairy shed effluent onto pasture (dairy industry only) Four variables were associated with the adoption of pumping dairy shed effluent onto pasture (Table A9). Owner/operators who considered their future farm profitability likely to increase were more likely to adopt the practice than those who thought farm profitability would fall.
Table A9 Logit regression results for the pumping of dairy shed effluent onto pasture (dairy industry only). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 3.1346 1.3824 Age yrs 1 -0.0095 0.0129 Environmental concern attitude 1 -0.1904 0.1607 Financial concern attitude 1 0.2537 0.1825 Technical concern attitude 1 0.0266 0.1843 Financial outlook concern attitude 1 -0.3404 0.1221 Landcare membership- yes 1 0.9697 0.3425 Length of landcare membership yrs 1 -0.2957 0.1129 Recent training 1 0.1989 0.1516 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0067 0.0075 Farm plan / property manag plan - yes 1 -0.2206 0.1827 Farm size 000/ha 1 -0.9747 0.7842 State 5 -NSW -0.1943 0.3446 -VIC 0.6949 0.2809 -QLD 1.0134 0.4006 -SA 0.0362 0.4855 -WA -1.2845 0.6650 Land use intensity se/ha 1 -0.0206 0.0175 PMP participation last 3 years - yes 1 -0.2772 0.2479 Wheat area sown ha 1 -0.0341 0.0303 Closing number of sheep no 1 0.0014 0.0011 Sample size=307, adoptors=187. Model fit Likelihood ratio test Chi-square=51.12, DF=22, P=0.0004 Association of predicted probabilities and observed responses: concordant=67.8%, discordant=32.0%, tied=0.2%.
5.14 0.54 1.40 1.93 0.02 7.77 8.02 6.86 1.72 0.32 0.01 0.80 1.46 1.54 13.84 0.32 6.12 6.40 0.01 3.73 1.39 1.25 1.26 1.75
Prob 0.0234 0.4645 0.2360 0.1644 0.8851 0.0053 0.0046 0.0088 0.1895 0.5692 0.9191 0.3724 0.2272 0.2139 0.0166 0.5729 0.0134 0.0114 0.9406 0.0534 0.2377 0.2634 0.2612 0.1858
water and land degradation as a critical concern in farm planning, the environmental concern attitude, was also positively associated with practice adoption. State of residence was also significantly associated with adoption, with Victorian farmers more likely to adopt the practice than the Australian average.
Laser graded layout (irrigated farms only) Three variables were associated with the use of laser graded layout in irrigation farming (Table A10). Having a farm plan was positively associated with adoption. Viewing
Table A10 Logit regression results for laser graded layout on irrigated farms. Effect Intercept Age
Unit
yrs
DF Parameter Estimate 1 1
-2.5899 0.0051
Std Error
Chisquare
Prob
2.0394 0.0172
1.61 0.09
0.2041 0.7656
57
Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Environmental concern attitude 1 0.4555 0.2174 Financial concern attitude 1 -0.0901 0.2268 Technical concern attitude 1 -0.3107 0.2071 Financial outlook concern attitude 1 0.2349 0.1683 Landcare membership- yes 1 -0.5664 0.3168 Length of landcare membership yrs 1 0.0578 0.0826 Recent training 1 0.0119 0.1989 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0093 0.0090 Farm plan / property man plan - yes 1 0.4758 0.2359 Farm size 000/ha 1 -0.2074 0.1590 State 5 -NSW 1.0609 0.8365 -VIC 2.0051 0.8368 -QLD -1.4671 1.0620 -SA 0.5854 0.9866 -WA 1.7234 1.2728 Land use intensity se/ha 1 0.0303 0.0237 PMP participation last 3 years - yes 1 -0.3706 0.3168 Wheat area sown ha 1 0.0060 0.0030 Closing number of sheep no 1 0.0001 0.0002 Sample size=323, adoptors=151. Model fit Likelihood ratio test Chi-square=72.67, DF=22, P<0.0001 Association of predicted probabilities and observed responses: concordant=78.6%, discordant=21.2%, tied=0.2%.
4.39 0.16 2.25 1.95 3.20 0.49 0.00 0.30 0.17 1.07 4.07 1.70 17.97 1.61 5.74 1.91 0.35 1.83 1.63 1.37 4.01 0.15
Prob 0.0362 0.6912 0.1335 0.1629 0.0738 0.4841 0.9524 0.5853 0.6772 0.3007 0.0436 0.1922 0.0030 0.2047 0.0166 0.1671 0.5529 0.1757 0.2013 0.2420 0.0451 0.6943
likelihood of using irrigation scheduling tools. However, participation in the Property Management Program in the previous three years was negatively associated with practice adoption. The results from this model should be interpreted cautiously as the overall model was not found to be significant.
Use of irrigation scheduling tools (irrigated farms only) Two variables were associated with the use of irrigation scheduling tools on irrigated farms (Table A11). Recent training was positively related to practice adoption, as the number of courses attended increased so too did the
Table A11 Logit regression results for the use of irrigation scheduling tools on irrigated farms. Effect Intercept Age Environmental concern attitude Financial concern attitude Technical concern attitude Financial outlook concern attitude Landcare membership- yes Length of landcare membership Recent training Farm cash income Profit at full equity Closing equity ratio Farm plan / property manag plan - yes Farm size State -NSW -VIC
Unit
yrs
yrs $ $ % 000/ha
DF Parameter Estimate 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5
Std Error
Chisquare
Prob
-7.1687 0.0104 0.2359 0.0035 0.0061 0.2458 -0.1936 -0.0108 0.8824 0.0000 0.0000 -0.0138 0.2570 0.0060
313.3000 0.0236 0.2816 0.2570 0.2686 0.2266 0.4403 0.1235 0.2363 0.0000 0.0000 0.0094 0.2665 0.1172
2.3606 2.0809
313.3000 313.3000
0.00 0.19 0.70 0.00 0.00 1.18 0.19 0.01 13.94 0.09 0.27 2.14 0.93 0.00 4.05 0.00 0.00
0.9817 0.6595 0.4021 0.9892 0.9818 0.2779 0.6601 0.9300 0.0002 0.7639 0.6052 0.1431 0.3349 0.9586 0.5418 0.9940 0.9947
58
Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
-QLD 2.1244 313.3000 -SA 3.3594 313.3000 -WA -13.8941 1566.3000 Land use intensity se/ha 1 -0.0150 0.0309 PMP participation last 3 years - yes 1 -1.2984 0.4895 Wheat area sown ha 1 -0.0006 0.0018 Closing number of sheep no 1 0.0000 0.0002 Sample size=332, adoptors=53. Model fit Likelihood ratio test Chi-square=32.26, DF=22, P=0.0731 Association of predicted probabilities and observed responses: concordant=74.7%, discordant=24.9%, tied=0.4%.
Monitoring of pasture and vegetation condition (all farms) Four variables were associated with the monitoring of pasture and vegetation condition when all types of farms are considered (Table A12). Recent training, land use intensity and having a farm plan were all positively associated with reported monitoring behaviour. Financial
0.00 0.00 0.00 0.24 7.04 0.10 0.03
Prob 0.9946 0.9914 0.9929 0.6277 0.0080 0.7487 0.8532
outlook was also significantly associated. Owner/managers who felt their farm profitability would fall in the next five to 10 years were less likely to adopt the practice. The earlier consideration of monitoring of pasture and vegetation condition in the pastoral zone only found significant associations with several financial and attitude variables, but no relationship with training and land use intensity.
Table A12 Logit regression results for monitoring of pasture and vegetation condition (all farms). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 -0.0874 0.6030 Age yrs 1 -0.0035 0.0064 Environmental concern attitude 1 -0.0404 0.0679 Financial concern attitude 1 -0.0882 0.0701 Technical concern attitude 1 0.0256 0.0760 Financial outlook concern attitude 1 -0.3023 0.0636 Landcare membership- yes 1 0.1184 0.1112 Length of landcare membership yrs 1 0.0492 0.0279 Recent training 1 0.3175 0.0665 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0026 0.0026 Farm plan / property man plan - yes 1 0.1921 0.0799 Farm size 000/ha 1 0.0053 0.0031 State 6 -NSW 0.0211 0.2505 -VIC -0.0984 0.2573 -QLD -0.0002 0.2679 -SA -0.2179 0.2939 -WA -0.6161 0.3000 -TAS 0.5266 0.4040 Land use intensity se/ha 1 0.0225 0.0102 PMP participation last 3 years - yes 1 0.0058 0.1067 Wheat area sown ha 1 -0.0001 0.0002 Closing number of sheep no 1 0.0000 0.0000 Sample size=1402, adoptors=391. Model fit Likelihood ratio test Chi-square=165.18, DF=23, P<0.0001 Association of predicted probabilities and observed responses: concordant=70.1%, discordant=29.5%, tied=0.3%.
0.02 0.29 0.35 1.58 0.11 22.58 1.13 3.11 22.77 0.23 0.54 0.96 5.78 2.90 8.47 0.01 0.14 0.00 0.55 4.22 1.70 4.85 0.00 0.19 0.14
Prob 0.8848 0.5902 0.5514 0.2086 0.7361 <.0001 0.2868 0.0779 <.0001 0.6325 0.4613 0.3260 0.0162 0.0885 0.2059 0.9330 0.7021 0.9995 0.4585 0.0400 0.1924 0.0276 0.9563 0.6576 0.7086
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Preserve/enhance areas of conservation value (all farms) Six variables were associated with the preservation or enhancement of areas of conservation value (Table A13). Recent training was positively associated with practice adoption. Land use intensity was negatively associated, as land use intensity increased adoption of the practice decreased. Environmental concern, financial concern and financial outlook attitude variables were significantly associated with practice adoption. All were related to adoption in the direction expected: as owner/managers became more concerned with water and land degradation in their farm planning they were more likely to preserve or enhance areas of conservation value; owner/managers who considered they did not have the financial resources to address water and land degradation were less likely to
adopt; and owner/managers who felt future farm profitability would increase were more likely to adopt the practice. The owner/managers’ state of residence was significantly associated with adoption; Tasmanian farmers were more likely to adopt than the average for Australia and Queensland-based farmers were less likely to adopt. Mues, Chapman and Van Hilst (1998) found training, landcare membership and farm size to have significant positive associations with the preservation of areas of conservation value for dairy farmers. In the Curtis et al. (2000) study the ‘area of remaining native bush and waterways fenced’ is the most comparable practice operationalisation to the preservation or enhancement of areas of conservation value. Of the variables in common, only property size was found to be significantly associated with the practice.
Table A13 Logit regression results for preservation or enhancement of areas of conservation value (all farms). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 -0.0172 0.5450 Age yrs 1 0.0077 0.0056 Environmental concern attitude 1 0.3375 0.0616 Financial concern attitude 1 -0.1333 0.0644 Technical concern attitude 1 -0.0703 0.0687 Financial outlook concern attitude 1 -0.1782 0.0545 Landcare membership- yes 1 0.0578 0.1035 Length of landcare membership yrs 1 0.0121 0.0273 Recent training 1 0.2112 0.0636 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0029 0.0023 Farm plan / property manag plan - yes 1 0.0155 0.0756 Farm size 000/ha 1 -0.0011 0.0022 State 6 -NSW -0.3022 0.2295 -VIC -0.0579 0.2378 -QLD -0.7075 0.2437 -SA -0.2168 0.2646 -WA 0.0056 0.2579 -TAS 0.8661 0.3926 Land use intensity se/ha 1 -0.0208 0.0094 PMP participation last 3 years - yes 1 0.0194 0.1026 Wheat area sown ha 1 0.0001 0.0002 Closing number of sheep no 1 0.0000 0.0000 Sample size=1306, adoptors=715. Model fit Likelihood ratio test Chi-square=137.83, DF=23, P<0.0001 Association of predicted probabilities and observed responses: concordant=65.4%, discordant=34.3%, tied=0.3%.
Excluding stock from degraded areas (all farms) Four variables were associated with the practice of excluding stock from degraded areas (Table A14). Age was negatively associated with practice adoption: younger
0.00 1.87 29.98 4.29 1.05 10.71 0.31 0.20 11.03 0.28 0.14 1.61 0.04 0.23 19.95 1.73 0.06 8.43 0.67 0.00 4.87 4.91 0.04 0.49 0.63
Prob 0.9748 0.1710 <.0001 0.0384 0.3062 0.0011 0.5769 0.6581 0.0009 0.5978 0.7055 0.2038 0.8379 0.6346 0.0028 0.1879 0.8078 0.0037 0.4127 0.9828 0.0274 0.0268 0.8501 0.4849 0.4285
farmers were more likely to exclude stock from degraded areas than older farmers. Environmental concern was positively associated with excluding stock; and poor financial outlook was negatively associated with adopting the practice. Queensland based farmers were less likely to
60
adopt the practice while Tasmanian farmers were more
likely to exclude stock from degraded areas.
Table A14 Logit regression results for the exclusion of stock from degraded areas (all farms). Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Intercept 1 -0.6034 0.5819 Age yrs 1 -0.0122 0.0060 Environmental concern attitude 1 0.3013 0.0655 Financial concern attitude 1 -0.0414 0.0661 Technical concern attitude 1 0.0480 0.0701 Financial outlook concern attitude 1 -0.1786 0.0579 Landcare membership- yes 1 0.2002 0.1043 Length of landcare membership yrs 1 0.0445 0.0274 Recent training 1 0.1134 0.0642 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 -0.0014 0.0024 Farm plan / property manag plan - yes 1 0.0953 0.0777 Farm size 000/ha 1 -0.0023 0.0029 State 6 -NSW 0.1000 0.2557 -VIC 0.0094 0.2642 -QLD -1.0421 0.2851 -SA -0.1697 0.2934 -WA 0.5009 0.2799 -TAS 1.0912 0.3929 Land use intensity se/ha 1 0.0047 0.0097 PMP participation last 3 years - yes 1 -0.1823 0.1056 Wheat area sown ha 1 0.0000 0.0002 Closing number of sheep no 1 0.0000 0.0000 Sample size=1306, adoptors=488. Model fit Likelihood ratio test Chi-square=179.44, DF=23, P<0.0001 Association of predicted probabilities and observed responses: concordant=69.9%, discordant=29.9%, tied=0.2%.
1.08 4.17 21.18 0.39 0.47 9.51 3.68 2.63 3.12 0.00 0.01 0.32 1.50 0.63 45.04 0.15 0.00 3.36 0.33 3.20 7.71 0.24 2.98 0.00 0.02
Prob 0.2998 0.0412 <.0001 0.5315 0.4934 0.0020 0.0549 0.1047 0.0774 0.9838 0.9373 0.5724 0.2202 0.4269 <.0001 0.6957 0.9715 0.0003 0.5630 0.0735 0.0055 0.6235 0.0842 0.9677 0.8848
of production. Owner/operators who felt they did not have the technical resources to address land and water degradation were also less likely to adopt than those who felt they had the technical resources. Recent training was positively associated with practice adoption. State of residence was also significantly associated with adoption, however no single state was significantly different from the Australian average.
Conservation tillage (all farms with a cropped area in 1998-99) Five variables were associated with the adoption of conservation tillage (Table A15). Age, technical concern and land use intensity were negatively associated with the adoption of conservation tillage. Older farmers were less likely to adopt the practice than younger farmers, as were those who operated their properties at more intensive levels
Table A15 Logit regression results for the percentage of the farm under conservation tillage (all farms). Effect Intercept Age Environmental concern attitude Financial concern attitude Technical concern attitude Financial outlook concern attitude Landcare membership- yes Length of landcare membership
Unit
yrs
yrs
DF Parameter Estimate 1 1 1 1 1 1 1 1
0.4042 -0.0268 0.0219 0.0611 -0.2121 0.0889 0.2027 -0.0036
Std Error
Chisquare
Prob
1.2100 0.0066 0.0691 0.0747 0.0812 0.0620 0.1120 0.0300
0.11 16.59 0.10 0.67 6.82 2.05 3.28 0.01
0.7402 <.0001 0.7516 0.4136 0.0090 0.1519 0.0703 0.9037
61
Effect
Unit
DF Parameter Estimate
Std Error
Chisquare
Recent training 1 0.2139 0.0683 Farm cash income $ 1 0.0000 0.0000 Profit at full equity $ 1 0.0000 0.0000 Closing equity ratio % 1 0.0008 0.0029 Farm plan / property manag plan - yes 1 0.1498 0.0828 Farm size 000/ha 1 -0.0580 0.0328 State 6 -NSW 0.1618 1.0706 -VIC 0.2578 1.0718 -QLD 0.0352 1.0810 -SA 0.7840 1.0766 -WA -0.1711 1.0835 -TAS -0.5823 1.1328 Land use intensity se/ha 1 -0.0299 0.0110 PMP participation last 3 years - yes 1 -0.1130 0.1175 Wheat area sown ha 1 0.0027 0.0004 Closing number of sheep no 1 0.0002 0.0000 Sample size=1154, adoptors=553. Model fit Likelihood ratio test Chi-square=305.47, DF=23, P<0.0001 Association of predicted probabilities and observed responses: concordant=78.5%, discordant=21.3%, tied=0.2%.
9.79 2.51 0.02 0.09 3.27 3.12 16.37 0.02 0.06 0.00 0.53 0.02 0.26 7.35 0.93 39.51 14.24
Prob 0.0018 0.1130 0.8937 0.7656 0.0705 0.0775 0.0119 0.8799 0.8099 0.9740 0.4665 0.8745 0.6072 0.0067 0.3360 <.0001 0.0002
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Appendix B Description of variables used in logistic regression analyses Farm family characteristics: state of residence: categorical variable with between five and seven levels as appropriate. Farm financial characteristics: farm cash income: difference between total cash receipts and total cash costs. profit at full equity: farm business profit, plus rent, interest and finance lease payments less depreciation on leased items. It is the return produced by all the resources used in the farm business. closing equity ratio: calculated as farm business equity (value of owned capital, less farm business debt at 30 June) as a percentage of owned capital at 30 June. financial concern attitude: ordinal variable with 5 levels (strongly disagree, disagree, neither agree nor disagree, agree and strongly agree) indicating response to the statement “I don’t have the financial resources available to adequately address land and water degradation on my property”. Treated as an interval level variable in the analyses.
land use intensity: intensity of land use measured in sheep equivalents per hectare. Farming or land management experience: age: interval level variable indicating the operator’s age in years. farm plan: binary variable indicating the presence of a farm plan or property management plan. technical concern attitude: ordinal variable with 5 levels (strongly disagree, disagree, neither agree nor disagree, agree and strongly agree) indicating response to the statement “I don’t have the technical resources available to adequately address land and water degradation on my property”. Treated as an interval level variable in the analyses. environmental concern attitude: ordinal variable with 5 levels (strongly disagree, disagree, neither agree nor disagree, agree and strongly agree) indicating response to the statement “Land and water degradation is a critical concern to me in farm planning”. Treated as an interval level variable in the analyses.
financial outlook attitude: ordinal variable with 5 levels (strongly disagree, disagree, neither agree nor disagree, agree and strongly agree) indicating response to the statement “I feel the profitability of my farm is likely to fall from current levels over the next 5 to 10 years”. Treated as an interval level variable in the analyses. Voluntary participation: landcare membership: binary variable indicating the membership of landcare in the year 1998-99. length of landcare membership: interval level variable measured in years. Education and training: recent training: number of courses or training activities undertaken in the last three years. PMP participation: binary variable indicating involvement in a Property Management Planning program. Farm structure: farm size: size of the farm measured in ‘000 Hectares.
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