Human and social aspects of capacity to change ...

Human and Social Aspects of Capacity to Change to Sustainable Management Practices Combined Report for the National Land and Water Resources Audit Theme 6 Projects 6.2.2 and 6.3.4 June 2001

John Cary, Neil Barr,* Heather Aslin, Trevor Webb and Shannon Kelson * Department of Natural Resources and Environment Victoria

© Commonwealth of Australia 2001 ISBN

0 642 47561 X

This work is copyright. The Copyright Act 1968 permits fair dealing for study, research, news reporting, criticism or review. Selected passages, tables or diagrams may be reproduced for such purposes provided acknowledgement of the source is included. Major extracts or the entire document may not be reproduced by any process without written permission of the National Land and Water Resources Audit, GPO Box 2182, Canberra, ACT 2601.

The Bureau of Rural Sciences (BRS) is the science agency within the Commonwealth Department of Agriculture, Fisheries and Forestry – Australia. Postal address: Bureau of Rural Sciences PO Box E11 Kingston, ACT 2604 Internet: http://www.affa.gov.au/output/ruralscience.html This report does not represent professional advice given by the Commonwealth or any other person acting for the Commonwealth for any particular purpose. It should not be relied on as the basis for any decision to take action on any matter that it covers. Readers should make their own inquiries, and obtain professional advice where appropriate, before making any decision. The Commonwealth and all persons acting for the Commonwealth in preparing this report 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 report.

Social Sciences Centre

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Contents

Contents

ii

List of tables

v

List of figures

vi

Acknowledgements

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Executive summary

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1.

Introduction – capacity to change

1

2.

Capacity to change – human and social perspectives Key points Multiple perspectives What change: Sustainable agriculture practices Sustainable resource management – The bigger picture Conceptual relationships Whose capacity to change?

2 2 2 2 4 5 8

3.

Capacity to change – factors affecting the adoption of sustainable practices Key points 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 11 14 18

4.

How do landholders learn about sustainable practices? Key points Categorising the learning focus Reasons for learning Styles of learning

20 20 20 21 22

5.

Characteristics of landholders and sustainable practices Summary key points Framework Age and experience Key points Education and training Key points Farm financial characteristics Key points Farm family characteristics Key point Farm structure Key point Identification of land management problems

24 24 25 27 30 30 31 32 38 38 39 39 40 40


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Key points Sustainable practice Key points Social and institutional contact as sources of change Key points Remoteness Key point Other community level indicators Key point Individual and social characteristics as indicators

42 42 43 44 45 45 46 46 47 47

6.

An analysis of the ABARE 1998-99 Resource Management Survey Key Points Introduction Modelling farmer behaviour Findings Summary

49 49 49 50 52 56

7.

The capacity of community landcare to change sustainable practices Key points The nature of community landcare Community landcare members versus non-members Impact of community landcare Community landcare and social capital The constraints of community landcare

57 57 57 60 61 63 64

8.

The changing structure of Australian agriculture Key points

66 66

9.

Some major structural constraints Key points

69 69

10. Future landscapes –institutional and social issues Key points The long term nature of required change Economic forces Changing social values and structures Broader environmental factors Future social landscapes

71 71 71 72 73 76 77

11. Future research and data issues

79

12. References

82


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Appendix A Project objectives

93

Appendix B Adoption of sustainable practices –recent Australian findings Age Education Property size Farm business The tenuous influence of attitudes on behaviour Other characteristics

95 97 98 98 98 99 101

Appendix C Logistic regression analyses Logistic regression Model estimation Results

103 103 103 104

Appendix D Description of variables used in logistic regression analyses

119


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List of tables Table 1 Characteristics of sustainable practices

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Table 2 Indicator types and corresponding indicators and maps

25 a

Table 3 Median age of full-time farmers in Australia and comparable countries

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Table 4 Variables explored in analysis of Resource Management Supplementary survey

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Table 5 Resource management practices investigated

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Table 6 Characteristics significantly associated with practice adoption

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Table 7 Factors which are associated with the adoption of sustainable management practices 53 Table 8 Community landcare membership: all broadacre and dairy industries, by state

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Table 9 Length of membership in a community landcare group and extent of tree planting and deep-rooted pasture planting (Central Victoria) 61 Table B1 Solutions’ National Indicators

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Table B2 Landholder and property characteristics showing significant multivariate relationships with adoption of at least one best practice 102 Table C1 Logit regression results for adoption of controlled flow bores in the pastoral zone. 105 Table C2 Logit regression results for the control of grazing pressure by excluding access to water in the pastoral zone. 105 Table C3 Logit regression results for the adoption of monitoring pasture and vegetation condition in the pastoral zone. 107 Table C4 Logit regression results for the adoption of deep rooted perennial pasture in the wheatsheep and high rainfall zones (broadacre industries only). 108 Table C5 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). 109 Table C6 Logit regression results for the establishment of trees and shrubs in the wheat-sheep and high rainfall zones (including dairy industries). 110 Table C7 Logit regression results for the regular monitoring of watertables in the wheat-sheep and high rainfall zones (including dairy industries). 111 Table C8 Logit regression results for the collection of dairy effluent.

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Table C9 Logit regression results for the pumping of dairy shed effluent onto pasture.

113

Table C10 Logit regression results for laser graded layout on irrigated farms.

113

Table C11 Logit regression results for use of irrigation scheduling tools on irrigated farms.

114

Table C12 Logit regression results for monitoring of pasture and vegetation condition.

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Table C13 Logit regression results: preservation or enhancement of areas of conservation.

116

Table C14 Logit regression results for the exclusion of stock from degraded areas.

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Table C15 Logit regression results for the percentage of the farm under conservation tillage. 118


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List of figures Figure 1 Model of adoption of sustainable land management practices. ....................................... 8 Figure 2 Numbers of farmers by age group in 1991 and 1996..................................................... 29 Figure 3 Assumptions underlying community landcare programs................................................ 58


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Acknowledgements A number of people have provided help, advice and comments on aspects of this Report. We would like to thank, particularly, Gerald Haberkorn, Con Charalambou, Milly Lubulwa, Veronica Rodriguez and Colin Mues.


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Executive summary Human capacity to change to more sustainable NRM practices varies across the catchments and localities of Australia’s agricultural land. Effective catchment planning needs to take account of these differing social capacities. The suitability and characteristics of specific NRM practices, the characteristics of locality (which often determine the suitability of practices) and differing socio-economic characteristics of landholders are all significant in determining capacity to change to more sustainable practices. Humans are adaptive in implementing NRM practices rather than simply reactive. The use of NRM 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 social characteristics. It is often difficult for landholders to see the connection between recommended NRM practices and sustainability. As a result, they are often lukewarm about NRM practices. Adoption of recommended sustainable practices depends largely on whether landholders think they are profitable. Recent low commodity prices in the broadacre industries reduced the attractiveness of adoption of many practices. The characteristics that most influence landholders’ capacity to change are: level of farm income, landholder age, 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 can be complicated. Personal financial capacity is an important component in determining the capacity of landholders to adopt new practices. But more importantly, how landholders perceive their likely future financial situation is more closely associated with practice adoption than objective measures of current financial position. Landholders who feel secure in their financial future are more likely to invest in new resource management practices. Analyses of associations between socio-economic and other ‘indicator’ variables and the adoption of a range of NRM practices produced significant findings that enhance the findings of other studies. However the differences between studies and some anomalous findings suggest more consideration needs to be given to the types of characteristics that can usefully be used as indicators (or predictors) of the adoption of sustainable practices. Analyses based on large zonal approaches are frequently confounded by the large variability that exists in Australian agriculture and the locality-specific nature of many sustainable management practices. Understanding of farmer adoption behaviour will be advanced with studies focussing on particular localities and industries. There is a need in adoption research to improve the measurement of the extent, complexity and context of use of specific NRM practices. An examination of the impacts of structural changes in agriculture on the capacity of landholders to improve the sustainability of land use provides the following observations on Australian agriculture: •

In many of the more densely settled or higher rainfall localities there is often a mix of commercial farming and hobby or lifestyle farming; commercial farming dominates the less densely settled and extensive farming areas.

•

Australia has a large number of small farms that tend to be grazing properties concentrated close to the seaboard, in the hill country and surrounding major provincial centres.


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•

Increasing productivity through increasing scale is an option available to larger farms, but not available to smaller farms.

•

Off-farm income is crucial to the continued farming future of families on many small farms.

•

Families on mid-sized farms often experience the greatest pressure to adjust out of agriculture.

•

Farm consolidation occurs during buoyant seasons.

•

Major structural change in land management frequently occurs at the time of intergenerational transfer of farm ownership.

•

In regions dominated by small farms the consolidation path to productivity increase is often blocked by high amenity-based land values.

•

Changes in agricultural structure, if continued, will lead to some regions remaining clearly agricultural in their character and others moving towards emphasis on amenity agriculture where productivity does not determine land use decision making.

Given the potential for significant structural change within parts of rural Australia, and the implications this has not only for natural resource management, but also for community wellbeing in these regions, there is a need for improved monitoring of on-going structural change in rural Australia. It is recommended that the scope of the National Agricultural Census be expanded to cover characteristics of landholders and properties relevant to resource management, that the Agricultural Census incorporate geo-coding, and that the Population and Housing Census be linked to the Agricultural Census.


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1.

Introduction – capacity to change

Changing land uses and management practices will be the major tools for improving the sustainability of land management in Australia. Policy makers and land management agencies have recognised that land management problems need to be tackled at the catchment scale, and that effective decision making will be underpinned by information at these scales. Research activity has resulted in improved understanding of many of the processes that control landscape functioning and affect the status of Australia’s natural resource base. To identify the capacity for realistic land management changes in Australia, we need more refined and locality specific (spatial) information on the capacity of land managers to change land management practices. A core objective of Theme 6 projects 6.2.2 and 6.3.4 was to present an analysis of indicators of landholders’ capacity to implement more sustainable land and water management practices on privately owned, as opposed to publicly owned, land. The term capacity refers to the power, ability or possibility of implementing nominated management practices. Capacity itself is not a variable or indicator but represents a number of components which may be reasonably judged as affecting a farmer’s or land manager’s ability to adopt sustainable land management practices. For example, the level of farm profitability may reflect the farmer’s ability to adopt sustainable practices, with low levels of farm profitability leaving the farmer with little or no ability to fund sustainable land management practices. Closely allied to, but distinct from, the notion of capacity is the concept of motivation. Motivation to undertake a nominated behaviour may reflect complex internal needs (for success, security, etc.), social conditioning, or inclination to conform to the normative behaviour of a social reference group. Motivation may also reflect individuals’ inclinations to respond to financial or other incentives or to avoid undesirable outcomes. These deeper psychological elements which contribute to motivation are difficult to elicit and are not specifically considered in this Report. Readers may draw some inferences about more general motivating factors from some of the findings in the Report. It is important to recognise the distinction between capacity or ability and motivation when attempting to explain the adoption of sustainable land management practices. In many instances farmers may have significant capacity to adopt sustainable practices, but on the other hand no motivation to do so. Conversely, there maybe significant motivation amongst farmers for the adoption of sustainable practices, but they may have little or no capacity to implement these practices. The broad objective of project 6.2.2 was to develop a comprehensive set of geo-referenced social and economic indicators of capacity for change. Project 6.3.4 has documented past and current adjustment trends within Australia's rural industries, and models scenarios for future adjustment trends. The information from these projects provides a socio-economic profile of regions throughout Australia and provides valuable information to aid in natural resource management. Much of this social information is presented in separate reports for each of the projects. This report provides a more considered analysis of the descriptive material in the two associated reports. Within the broader framework of National Land and Water Resources Audit this report considers factors influencing the adoption of natural resource management (NRM) practices, rates of change in rural social structure and demography, and current and future impediments to human and social capacity to change to sustainable resource management practices. The report also considers social implications of recommended changes to NRM practices.


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2. Capacity to change – human and social perspectives Key points •

Capacity to change is not unidimensional. One individual’s capacity to change differs according to the changes being considered, the stage in a person’s life and, often, many other factors.

•

Human capacity to change is not equivalent across the catchments and localities of Australia’s agricultural land. From a catchment planning perspective there is a need to focus on these dimensions of human capacity to change at a locality and catchment level.

•

Human behaviour related to implementing NRM practices is adaptive, rather than simply reactive, in its nature. Appraisal of, and implementation of, NRM practices will depend on assessment of, and experience with, the use of such practices. The difficulty, for landholders, of observing linkages between many recommended NRM practices and desired sustainable outcomes also reduces positive appraisals of NRM practices by landholders.

Multiple perspectives The idea that human capacity to change is unidimensional is a common implicit assumption of policy to change land management practices, expressed in assertions such as “We just need to convince them to change”. The assumption is if capacity to change is a human attribute, humans are more or less the same everywhere and it is thus simply a matter of understanding the drivers and motivators that will unlock human capacity to change. In fact, the social characteristics of land managers differ significantly in different localities in Australia. These differences have been identified on gross scales in the Social Atlas of Rural and Regional Australia (Haberkorn et el. 1999) and studies by Barr et al. (2000). Some of the potentially significant indicators of capacity to change were identified by Fenton, Macgregor and Cary (2000). The farming community in Australia is not homogenous. An understanding of the diversity within rural communities and landholders in regard to social and economic factors is necessary before policies can be developed to change behaviour. For effective land management planning, differences in important social and economic attributes (which differ on a spatial basis) need to be identified on a more discriminating locality basis.

What change: Sustainable agriculture practices Sustainable land management practices are here defined 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


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these practices were identified in the National Collaborative Project on Indicators for Sustainable 1 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 are identified with the superscript a. •

maintenance of soil cover

•

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 needs a

•

regular soil testing

•

fertilising of pastures

•

agricultural lands treated with gypsum

•

agricultural lands treated with lime

•

regularly monitor water tables a

•

use of deep-rooted perennial pastures a

•

non-commercial tree and shrub planting a

•

commercial tree and shrub planting (farm forestry) a

•

preserve or enhance areas of conservation value a

•

retention of vegetation along drainage lines a

•

protection of land from stock by fencing – exclude stock from degraded areas a

•

protection of waterways from stock by fencing a

•

animal pest or weed control to control land degradation a

•

pest and disease control in pastures

•

use of integrated pest management (reducing pesticide use)

•

slashing and burning of pastures

Cropping farmers •

use of reduced or zero tillage – minimum tillage a

•

stubble or pasture retention in ploughing – direct drilling a

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.


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•

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

Irrigation farms •

irrigation scheduling a

•

laser graded layout a

•

storage and reuse of drainage water a

•

automated irrigation a

Rangelands •

control grazing pressure by excluding access to water a

•

control of water flow from bores a

•

piped water supplies for stocka

•

pastoral land stocked at recommended rates

•

degraded pastoral land converted to less damaging use

•

pastoral land destocked in low feed conditions

Dairy farms •

use of effluent disposal systems– collection of dairy effluent (ponds or drainage sump) a

•

pump dairy shed effluent onto pasture 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. 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 adopts a ‘sustainable’ practice, it could be totally ineffective if neighboring landholders do not adopt complementary practices.

Sustainable resource management – The bigger picture The use of the sustainable practices listed above are contended (and sometimes assumed) 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 state is achieved. Broader conceptions of sustainable management embrace the need for strategies for sustaining both food security and the need to conserve natural resources.


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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). Because sustainable resource management is often an abstract state – which occurs in the future and may be hard to identify or measure – in this analysis we focus on sustainable practices (which lead to sustainable states) or use them as ‘indicators’ or proxies for sustainable management.

Conceptual relationships The development of a model of conceptual relationships helps to understand the place of sustainable practices that lead to more sustainable states and 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. No attempt has been made to identify specific indicators within each of the two groupings of potential social and institutional indicators on the left hand side. 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 a state of more sustainable land management. It emphasises that adoption of sustainable NRM practices is not uni-dimensional, consisting of a potentially wide range of practices that are dependent upon appraisals of environmental, institutional, social characteristics by landholders prior to any implementation.


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Adoption of Recommended NRM Practice 1

Locality and Environmental Characteristics Characteristics of Practice j

Institutional Characteristics

NRM Practice j

Appraisal

Individual and Social Characteristics

POTENTIAL INDICATORS

Sustainable Land Management

NRM Practice n

PROCESSES

OUTPUTS

OUTCOMES

Figure 1 Model of Adoption of Sustainable Land Management Practices (Modified from Fenton, Macgregor & Cary (2000)) Central to the model presented in Figure 1 is the appraisal component which represents farmer and land manager beliefs about, and attitudes towards, natural resource management, land degradation and specific adoption practices. Appraisal also includes farmer and land manager attitudes towards those organisations and institutions that may be promoting sustainable land management. 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.


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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 a 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 two-way 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 non-recursive (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


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from other animals. As a 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 labelled 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.

Whose capacity to change? The primary focus of this report is the capacity of individual landholders to change farm management practices. Catchment management plans incorporating changed land management practices will be flawed if they do not acknowledge the importance of social and economic factors in constraining the participation of individual land managers and the broader community in natural resource management. 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 2001, p.24). 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. Farmers and landholders often face an apparent contradiction between goals of managing for economic profit or adequate family income and managing their land to provide environmental ‘services’ such as clean water and erosion mitigation which benefit the wider community or neighboring farmers (Furze 1992). Capacity to change needs to be considered in other contexts beyond that of the individual landholder. Structural barriers to (capacity to) change are closely linked to specific social and economic attributes. Recent research by Barr et al. (2000) suggests that barriers to change in farming practices in the Murray Darling Basin (MDB) were overwhelmingly structural. The Rangelands and pastoral uplands of the MDB have shown strong links between the need for structural change and the capacity to implement alternative management strategies. This suggests that an important facet of capacity to change is the ability of regional farming structures to adjust in a manner that increases the capacity of individual land managers to adopt sustainable management practices. These links are explored in later sections.


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Finally, capacity to change is a concept which might be applied to all Australians, not just owners and managers of agricultural land. At its simplest level, there is a question regarding the capacity of the nation to fund changes which may be beyond the financial capacity of individual landholders. A consequence of changed land management systems will generally result in changes in the industry and social structure of rural regions. Such changes have impacts beyond the lives of existing landholders. The social ramifications of changes in land management practices raise questions regarding the capacity of rural and regional communities to adjust to these changes. There are also consequential changes in income distribution, industry structures and landscape amenity. Such questions are at the core of the recent expansion of plantation forestry. In later sections some of these issues are discussed.


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3. Capacity to change – factors affecting the adoption 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)

Key points •

It is the inherent characteristics of natural resource management (NRM) practices which largely determine the rate of their adoption by producers. Sustainable NRM practices which provide economic and other advantages will generally be adopted more rapidly.

•

The relative advantage of a practice varies in different locations. It is dangerous to assume that a practice with advantages in one location will yield the same advantages elsewhere. Few sustainable practices have universal applicability.

•

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.

•

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.

•

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 broad-acre industries have reduced the relative advantage of many sustainable practices.

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 selfinterest, even for practices intended to improve land and resource conservation (Cary & Wilkinson 1997; Riley1999; 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


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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 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 compatability, 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.

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.


11

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.


12

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 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.


13

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.

•

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.


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Table 1 Characteristics of sustainable practices Geographic applicability

Relative advantage

Risk

Complexity

Compatibility

Trialability

Observability

(Hi)

(Hi)

(Lo)

(Lo)

(Hi)

(Hi)

(Hi)`

Maintenance of soil cover

Hi

Hi (temporal)

Lo

M-Hi (locality)

M

M

M-Lo

Establishing and monitoring ground cover targets (monitoring of pasture and vegetation condition) a

Hi

M

Lo

M-Hi

M

M

M-Lo

Nutrient balance accounting (soil and plant sampling)

Lo

Lo

Lo

Hi

M

Lo

Lo

Soil and plant tissue tests to determine fertiliser needsa

Lo

Lo

Lo

Hi

M

Lo

Lo

Regular soil testing

M

M

Lo

Lo

M

Lo

Lo

Fertilising of pastures

M

Hi-M (locality)

M

Lo

Hi

Hi

Hi-M

Agricultural lands treated with gypsum

M

Lo

M-Hi

Lo

Hi

M

M

Agricultural lands treated with lime

M

Lo

M-Hi

Lo

Hi

M

M

Regularly monitor water tables a

M

M (locality)

Lo

Lo

Lo

Hi

M

Use of deep-rooted perennial pastures a

Hi

M

M-Hi

M-Hi

M (locality)

M

Lo

M – Hi

Lo

Lo

Lo

M-Hi

Hi

Hi

Commercial tree and shrub planting (farm forestry) a

Lo

Lo (locality)

Hi

M

Lo

Lo

Hi

Preserve, enhance areas of conservation value a

M

Lo

Lo

M

Lo

M

M-Hi

Retention of vegetation along drainage lines a

M

Lo

Lo

M

M-Lo

M

M-Hi

Sustainable practice (Ideal rating)

Non-commercial tree and shrub planting a

Geographic applicability

Relative advantage

Risk

Complexity

Compatibility

Trialability

Observability

(Hi)

(Hi)

(Lo)

(Lo)

(Hi)

(Hi)

(Hi)`

Protection of land from stock by fencing (exclude stock from degraded areas) a

Lo

Lo

Lo

M

M

Hi

Hi

Protection of waterways from stock by fencing a

Lo

Lo

M-Hi

Lo

M

Hi

Hi

Animal pest or weed control to control land degradation a

Hi

M

M

M

M-Hi

M

M

Pest and disease control in pastures

M

M-Hi (locality)

M

M

M-Hi

M-Lo

M

Use of integrated pest management (reducing pesticide use)

Lo

M-Lo

M-Hi

Hi

M

M-Lo

M-Lo

Slashing and burning of pastures

Lo

M-Lo

M

Lo

M

Hi-M

Hi

Use of reduced or zero tillage (minimum tillage) a

Hi

M

M

M

M-Hi

Hi

M

Stubble or pasture retention in ploughing (direct drilling) a

M

M

M-Hi

M-Hi

M

Hi-M

M

Use of crop or pasture legumes in rotations a

Hi

M-Hi

M-Lo

M-Lo

M-Hi

M

M-Lo

Use of contour banks in cropland a

M

M-Lo

M-Lo

M-Hi

M-Lo

M-Lo

M-Hi

Strip cropping a

M

Adjusting crop sequences in response to seasonal conditions

Hi

M-Hi

M

M

M-Lo

M-Lo

Lo

Irrigation scheduling a

M

M

Lo

M-Hi

M-Lo

M-Lo

Lo

Laser graded layout a

Hi

M-Hi

Lo-M

M

M-Lo

M

Hi


Cropping farms

Irrigation farms


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Geographic applicability

Relative advantage

Risk

Complexity

Compatibility

Trialability

Observability

(Hi)

(Hi)

(Lo)

(Lo)

(Hi)

(Hi)

(Hi)`

Storage and reuse of drainage water a

M

M-Hi

M

M

M

M-Lo

M

Automated irrigation a

M

M-Lo

M-Hi

Hi

M-Lo

Lo

Hi

Control grazing pressure by excluding access to water a

M

M

Lo

M-Hi

M

M-Lo

M-Hi

Controlled of water flow from bores a

Hi

M-Lo

Lo

Lo

Hi

Hi

Hi

Piped water supplies for stocka

Hi

M-Lo

M

Lo

Hi

M

Hi

Pastoral land stocked at recommended rates

Hi

M

M

M

Hi

M-Lo

M-Hi

Degraded pastoral land converted to less damaging use

M

Lo

Lo

M

M

M-Lo

M

Pastoral land destocked in low feed conditions

Hi

M-Hi

M-Hi

Hi-M

Hi

M-Lo

M

Use of effluent disposal systems (collection of effluent; ponds or drainage sump) a

Hi

M-Lo

M

M

M

M

Hi

Pump dairy shed effluent onto pasture a

M

M-Lo

Lo

Lo

M

Hi

Hi


Rangelands

Dairy farms

a

Some measure of the level of landholder adoption of the practice available from the ABARE Australian Resource Management Supplementary survey.

(Comments in brackets refer to locality or temporal constraints on expression of attribute.) Hi = High M = Medium Lo = Low


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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 trialabilty and observability, and low risk.

•

Very few sustainable practices have widespead 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 widescale 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 fourpaddock 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


18

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 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.


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4. How do landholders learn about sustainable practices? Key points •

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 and, overall, farmers tend to have less formal education than other sectors of the labour force.

•

Farmers do not all learn about sustainable practices in the same manner. Styles of farmer learning vary from reliance upon a few key informants to styles which are based on extensive networks of sources and informants.

•

The major motivation for farmer learning tends to be for improved productivity and improved business performance.

•

The adoption of sustainable management practices often entails greater complexity in integrating the practice into existing farming systems and less certain outcomes. Learning how to master this complexity and accommodate the technical and financial uncertainty will often require locally adapted knowledge and the need for local networks or local professional sources of knowledge support.

•

The adoption of sustainable management practices is often slow because of their lower rates of observability and trialability. Where adoption needs to be increased, this suggests the need for external human capital investments, such as extension support, to facilitate learning by reducing such uncertainties.

•

Improved investment in farmer training, and the development of more advanced learning strategies for farmers, will enhance adoption of sustainable management practices. Decisions about the level or extent of support for such learning activities by government should be based on the extent of public good activity involved in such support.

Categorising the learning focus 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. Overall, farmers tend to have less formal education than other sectors of the labour force. There is also mixed evidence concerning the link between formal education and good farm management. 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. 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)


20

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. 3

Kilpatrick (1996) highlighted the important role that 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 information and advice only from local 4 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% with post-school qualifications in 1983 to 32% in 1995. Though this is still less than the 49% of the Australian labour force that has post-school qualifications (Synapse Consulting 1998). Importantly, those farmers with higher 3

4

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). 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).


21

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%)

•

personal development (7.1%) (Kilpatrick et al. 1999)

Importantly, environmental management motivates only a relative minority of farmers to learn, in contrast to business efficiency and viability.

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

•

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


22

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: •

starting a new enterprise

•

other strategic change

•

record keeping

•

tactical or technical changes.

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 as a 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 non-accredited courses, were also important sources of learning for some sections of the farming community. Field days and accredited courses were useful to approximately 75% 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 farmer-directed group (such as community landcare). Community 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).


23

5. Characteristics of landholders and sustainable practices Summary key points •

The more important landholder characteristics which are, or might be, useful indicators of capacity to change sustainable management practices are: age, participation in training, level of farm income, farms with a documented farm plan, proportion of farms carrying out landcare related work, and membership of landcare.

•

Age is an important social characteristic because it is an indicator of the structure of the agricultural workforce which is changing in Australia, and changing differentially in different localities. There is mixed evidence concerning the impact of age on adoption of sustainable practices; any relationship between age and the adoption of sustainable practices is unlikely to be linear, and may be confounded by other factors. In localities with an increasingly aged farmer population implementation of sustainable practices is likely to be low.

•

On the most recently available analysis 50% of farm owner-managers had completed 1-4 years of secondary school and 23% had completed 5-6 years; educational levels are related to age, with younger farmers generally having higher educational attainments than older ones. As a consequence of a large number of farmers having relatively low levels of formal education it is not surprising that education is not a particularly useful indicator of sustainable practice adoption. However, participation by farmers in courses or training activities is associated with adoption of sustainable practices. It is reasonable to assume, increasingly in the future, that more complex sustainable management practices will be more easily grasped and integrated into farming systems by those with higher levels of formal education.

•

Low farm incomes and high debt are likely to discourage adoption of sustainable practices which have low returns and long delays to achieving any benefits. Low incomes resulting from farm industry structural change, or because of extended low commodity prices or extended drought conditions, will frequently be geographically concentrated in specific localities with consequent adverse effects on resource management. While a measure such as annual farm cash income can significantly differentiate regions of low or high average income, it is not a discriminating indicator of capacity to change sustainable management practices by individuals within regions. The contribution of off-farm income to total farm family income has been steadily increasing for many of Australia’s farms.

•

Landholders in Australia generally now recognise significant land or water degradation problems; a quarter of the farms in most of the major farming regions of Australia experienced one or more significant land or water degradation problems in 1998-99. Recognition of a resource degradation problem is, usually, a necessary condition but, rarely, a sufficient condition for the adoption of sustainable practices.

•

The existence of a farm plan or property management plan is likely to indicate that property holders have received training or professional assistance in land management and business planning, are considering long-term planning horizons, and increase the likelihood that farms will be managed in an ecologically sustainable way. Having a farm plan was commonly associated with adoption of resource management practices.

•

In most areas of Australia landcare related work (such as erosion control, fencing of native vegetation or degraded areas, tree and shrub establishment) was undertaken on


24

more than a third of farms. In many of the more important farming regions landcare related work was undertaken on nearly 50% of farms.

Framework Many socioeconomic factors have been discussed by different authors as being relevant to landholders’ and farm families’ ability and willingness to change to more sustainable land management practices. In recent years there have been a number of major reviews and studies that have explored the social and other aspects of adoption of best practices in Australian agriculture (eg. Fenton, MacGregor & Cary 2000; Barr & Cary 2000; Guerin & Guerin 1994; Reeve & Black 1993). Two recent studies – the first in the Goulburn Broken catchment of Victoria undertaken by Curtis et al. (2000) and the second a national benchmarking study by Solutions Marketing and Research (1999) – are reviewed in some detail in Appendix B. In this project, the set of possible indicator types identified by Fenton et al. (2000) has been applied by identifying secondary data sources for as many indicators as possible, and depicting them in map form in a separate Social Atlas. Data sets have been limited to national ones, given the Audit’s national scope. Table 2 relates the data sets obtained for this report to the general indicator framework suggested by Fenton, Macgregor and Cary (2000). Table 2 Indicator types and corresponding indicators and maps (Map numbers refer to those used in the accompanying Social Atlas) Indicator type

Indicator data obtained

Map no.

Chart no.

Age and experience Age of farmer

Demography of the young

Median age of farmers and farm managers, 1996

1

Change in median age of farmers and farm managers, 1991-1996

2

Change in the population aged 15 to 24 years, 1991-96

3

Farmers aged 14-16 years when their schooling completed, 1996

4

Farmers aged 17-18 years when their schooling completed, 1996

5

Farmers with basic vocational qualifications, 1996

6

Farmers with skilled vocational qualifications, 1996

7

Farmers with higher qualifications, 1996

8

Participation in any course or training activity, 1996-1997 to 1998-1999

9

Median farm family income, 1996

10

Annual family income, 1996-1997 to 19981999

11

3

Annual farm cash income, 1996-1997 to 1998-1999

12

4

1

Education and training Level of farmer education and training

Level of farmer participation in management and relevant training

2

Farm financial characteristics Level of farm income


25

Indicator type


Map no.

Chart no.

Level of off-farm income

Off-farm income, 1996-1997 to 1998-1999

13

5

Level of farm business profit

Farm profit at full equity, 1996-1997 to 1998-1999

14

6

Level of household spending

Total household expenditure

15

7

Level of farm debt

Level of farm debt, 1996-1997 to 19981999

16

8

Farm equity ratio, 1996-1997 to 1998-1999

17

9

Farms with equity ratio less than 80%, 1996-1997 to 1998-1999

18

10

Farm families with dependent children, 1996

19

Median farm estimated value of agricultural operations (EVAO), 1996-1997

20

Farm area, 1996-1997 to 1998-1999

21

11

Estimated proportion of farmers who reported weed problems in 1998-1999

22

12

Estimated proportion of farmers who reported soil acidity problems in 19981999

23

13

Estimated proportion of farmers who reported significant land or water degradation, 1998-1999

24

14

Estimated proportion of farmers who reported dryland salinity problems, 19981999

25

15

Estimated proportion of farmers who reported irrigation salinity problems, 1998-1999

26

16

Estimated proportion of farmers who reported a documented farm plan or property management plan, 1998-1999

27

17

Estimated proportion of farms carrying out Landcare related work, 1998-1999

28

Cropping management practices, 19981999

29

18

Contact with Landcare and similar groups

Membership of Landcare in 1998-1999

30

19

Time spent in land management group participation

Length of Landcare membership (longest serving member)

31

20

Median length of Landcare membership

32

Farm family characteristics No. of children (family size) Farm structure Farm size

Identification of land management problems Identification of on-farm land degradation issues

Sustainable practice

Social and institutional contact as sources of change


26

Indicator type

Influence of landcare


Map no.

Chart no.

Involvement with Landcare influenced farm decisions in 1998-1999

33

21

Remoteness Settlement density

Farmer population, 1996

Ref. map (iii)

Farmer remoteness

Degree of accessibility/remoteness (ARIA), 1996

34

Socioeconomic Index of Rural Advantage (SEIFA), 1996

35

Socioeconomic Index of Disadvantage (SEIFA), 1996

36

Other community level indicators Socio-economic advantage/disadvantage

Age and experience Maps 1-3, Chart 1 Age is one farmer characteristic often investigated for its relevance to land management practices and willingness to adopt new practices. Measures used include average or median ages in particular farmer groups or geographical areas, changes in farming population age profiles, and the extent to which younger people or children of farm families are taking up farming and inheriting farms (inter-generational transfer). There has been longstanding concern that the average age of Australia’s farmers is increasing (eg. Barr 2001; Garnaut & Helali 1999). ABS Census data show that in 1996, the median age of farmers and farm managers in Australia was 48 years (Haberkorn et al. 1999). This means that in 1996, 50% of farmers and farm managers were older than 48 years, and 50% were younger than 48. In 1996, the median age of Australia’s non-metropolitan population was 34. In the south-west agricultural region of Western Australia, while the population was generally older than the national non-metropolitan population, it was not as old as in the south-eastern states. Farmers were younger in central sheep and cropping areas of Western Australia, except in the Great Southern and south-west coastal areas. Farmers were younger in pastoral South Australia and central west and south-west Queensland. ABARE farm survey (sample) data indicate that in 1997-98, the average age of broad-acre farmers, including pastoralists, was approximately 54 years, and that they are older than other types of farmers on average (Garnaut & Lim-Applegate 1998). However, in spite of these observations about the age of the farm population, the median age of Australia’s farmers is not as high as that of farmers in some comparable countries (see Table 3).


27

Table 3 Median age of full-time farmers in Australia and comparable countriesa Country

1970

1998

United States

51

57

Canada

49

51

Japan

47

60

1981

1996

44

49

Australia a

Source: Hugo (2000)

Based on ABS 1996 Census data, the oldest farmers tend to be located towards the coastal regions, particularly in the south-east of the continent, but generally from central Queensland to the South Australia border. In these areas the median age of farmers is between 47 and 51 years, and in significant pockets in some higher rainfall grazing areas, greater than 52 years (Barr et al. 2000). With some exceptions in the pastoral zone, median age tends to fall as one moves westward towards the South Australian and Northern Territory borders. However, median age decreased in some remote areas of Australia, including Far North Queensland, Tennant Creek and Darwin areas, north-eastern Northern Territory, and several Statistical Divisions in inland Western Australia and South Australia. This may be a result of greater numbers of Aboriginal Australians, who on average are younger than other Australians (Haberkorn et al. 1999), identifying themselves as farmers, possibly reflecting greater Aboriginal ownership of land and pastoral properties. Farmers’ average or median ages have been increasing more rapidly than those of some other occupational groups, and slightly more rapidly than the metropolitan population. On the basis of Census data, between 1991 and 1996 the median age of farmers increased from 46 to 48 years, whereas the median age of Australia’s metropolitan population increased by one year (Haberkorn et al. 1999). Garnaut and Helali (1999) concluded that the average age of principal decision makers in broadacre agriculture rose from 49 to 52 years over the period 1981-82 to 1997-96. There is considerable variation from area to area in the median age of farmers and considerable regional variation in the rate of farm population ageing. In some more sparsely settled rangeland areas of Australia, particularly western Queensland, the Northern Territory and Western Australia, median age of farmers increased six or more years between 1991 to 1996. (This increase has often been from a lower age base.) In the upper catchment Statistical Local Areas of the Murray Darling Basin, between 1986 and 1991 median age sometimes increased by four years or more (see Barr et al. 2000). It appears that the more marginal agricultural lands of Western Australia and South Australia are showing some decreases in median age. The changing proportions of farmers of different ages in 1991 and 1996 can be seen in Figure 2. There has been a proportionally larger decline in the younger 25-29 and 30-34 age groups than increase in the older 55-59 and 65+ groups. This suggests a declining number of new entrants into farming or increased exits out farming by younger farmers. These changes are related to an Australian population drift towards the coast (Haberkorn et al. 1999; ABARE 2000), that is particularly pronounced among 15-24 year olds.


28

Number of farmers 30,000

25,000

20,000

1991

15,000

1996 10,000

5,000

0 15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65+

Age

Figure 2 Numbers of farmers by age group in 1991 and 1996 (Source: ABS)

The 15-24 year age range is particularly interesting because it represents the younger generation leaving school and making choices about future careers or further education needs. Throughout most of the less remote regions of Australia, the percentage of 15-24 year olds decreased between 1991 and 1996, with greatest decreases being seen mainly in the wheatsheep belt. These decreases may reflect drought, low commodity prices and perceived poor prospects for these farming operations during the 1990s (ABARE 1999, 2000). In terms of changes in percentages of 15-24 year olds, there are marked differences between the pastoral zone and the rest of Australia, with percentages generally increasing in pastoral areas, particularly inland Western Australia, the Northern Territory, and south-western Queensland. Increases in these remote areas reflect substantial Aboriginal populations and possibly young people seeking temporary work in pastoralism, mining and tourism (Haberkorn et al. 1999). Research studies tend to show younger farmers to be more aware of land degradation on their farms and to recognise the need for conservation practices to be adopted (Fenton, Macgregor & Cary 2000). Curtis & Van Nouhuys (1999) found young farmers to be more likely to be members of community landcare groups, while Mues, Chapman and Van Hilst (1998) found that members were only two years younger than non-members – a difference that was unlikely to be significant. A number of studies have indicated that older farmers are less likely to adopt new sustainable practices because, it is thought, older farmers are generally more ‘traditional’ in their approaches to management and so less likely to embrace change. However, there are also studies demonstrating contradictory results, where older farmers were found to have higher degrees of stewardship. It has also been argued that older farmers have the necessary skills and experience to adopt more sustainable practices (Anosike & Coughenour 1990). In an analysis of the ABARE Resource Management Survey of Australian broadacre and dairy farmers, presented in a later section of this Report, younger farmers were more likely to


29

adopt the practices of excluding stock from degraded areas and using conservation tillage than were older farmers. There is evidence that farm exits are related to age, with farmers in younger (under 25 years) and older age groups (over 50) being more likely to leave farming (Barr 2001). Exits by older farmers are likely to be related to succession strategies and may be motivated by declines in health and fitness as well as the desire to retire. The conclusion is that few younger people are entering farming in the inland, and particularly the pastoral industry. A significant factor working against these generalisations may be increasing Aboriginal land ownership and more Aboriginal people becoming involved in pastoralism (see for example information on the web-site of the Indigenous Land Corporation, http://www.ilc.gov.au). Key points •

the more intensively farmed regions of Australia contain the older farming population

•

farming populations in these regions are ageing on average at a slower rate than populations in more remote pastoral regions

•

there is mixed evidence about the impact of age on adoption of sustainable practices; any relationship between age and the adoption of sustainable practices is unlikely to be linear, and will often be confounded by other factors.

Education and training Maps 4-9, Chart 2 Traditionally, Australia’s farmers have tended to have lower levels of formal education than the Australian average. For example, in 1995, 32% of Australia’s farmers had post-school qualifications whereas 49% of the Australian labour force as a whole had these qualifications (Synapse Consulting 1998). ABARE survey data from broadacre and dairy industry farmers show that in 1994-95, 50% of farm owner-managers had completed 1-4 years of secondary school and 23% had completed 5-6 years (Garnaut & Lim-Applegate 1998). Observations about relatively low levels of formal education apply more to farming men than to their spouses or to farming women. The ABARE study found that an estimated 10% of owner managers had completed a tertiary qualification in 1994-95 as compared with 19% of their spouses; and that 42% of female owner managers had completed a tertiary qualification (Garnaut & Lim-Applegate 1998). However, female owner managers comprised only 3% of all owner managers contacted in this ABARE study. Significant literacy problems have been reported in some farming areas, particularly where there are substantial numbers of farmers from non-English speaking backgrounds (Cumming, Erol & Mitsos 1995; Cumming & Hogan 1997). Educational levels are likely to be related to age, with younger farmers often having higher educational attainments than older ones. For example, the ABARE study found that almost two-thirds of owner managers aged less than 40 years had completed at least five or six years of secondary schooling, but this percentage declined significantly in older age groups (Garnaut & Lim-Applegate 1998). Younger farmers were more likely to have participated in training activities (Mues, Chapman & Van Hilst 1998). Educational levels are of particular interest because of an expected relationship between higher educational attainments and greater willingness to adopt new practices, or to seek further education or training as needed. Higher levels of formal education may also be important in enabling members of farm families to obtain off-farm income to supplement


30

farming returns, and hence enhance their financial capacity to adopt more sustainable practices. Garnaut et al. (1999), using data from ABARE 1996-97 farming surveys, found that farming women and men without post-school education were less likely than other farmers to have off-farm employment. As mentioned in elsewhere in this Report, Kilpatrick and her co-authors (Kilpatrick 1996, 1997; Kilpatrick & Williamson 1996; Kilpatrick et al. 1999), Reeve & Black (1998), and Synapse Consulting (1998) have investigated farmers’ learning needs and learning styles. The converse of this is investigating current levels of formal education among farmers, and examining whether educational attainments have any consistent relationship to farm performance and farm management practices. Using data from the ABS agricultural finance survey, Kilpatrick (1996) demonstrated that farm incomes tended to be higher in farm families where farmers reported greater participation in training activities. She also found that farm incomes were correlated with owner managers’ levels of formal education, and in particular that farm businesses run by people with agricultural qualifications returned higher average incomes (excluding interest payments) than those run by people without these qualifications. Relationships between formal education and farm business assets were much smaller than those between formal education and income. Data from recent ABARE farm surveys (Garnaut & Lim-Applegate 1998) showed that farm businesses in which the owner manager or spouse had a university or other tertiary qualification, tended to be larger in size (as averaged over 1992-93 to 1994-95) than those run by people with less formal education. However, in this 1998 study, no consistent relationship was found between farm performance and educational levels of owner managers or spouses. Reeve and Black’s (1993) national survey found that better-educated farmers had more favourable attitudes towards using outside expertise to assist with on-farm conservation practices. In a more specific study, Curtis et al.’s (2000) investigation of landholder willingness and capacity to manage dryland salinity in Victoria’s Goulburn Broken catchment found no significant relationship between higher education and adoption of best practices (see Appendix B). A survey conducted by Solutions Marketing and Research (1999) to monitor the performance of the Commonwealth Government’s Agriculture - Advancing Australia (AAA) program package includes five national indicators related to AAA goals, one of which is a natural resource management (NRM) behaviour indicator. From data collected during their study (based on a representative sample of 2,043 agricultural producers), Solutions found no significant relationship between formal educational attainments and their NRM indicator (see Appendix B). In the analysis of the ABARE Resource Management Survey of Australian broadacre and dairy farmers, presented later in this Report, more frequent participation in training is commonly association with the adoption of sustainable practices. The maps relating to educational attainments among Australian farmers in the accompanying Social Atlas (Maps 4-8), depict data from people who identified their primary occupation as ‘farmer’ or ‘farm manager’ in the 1996 Census. They are accompanied by one map (Map 9) showing participation in any courses or training activities over the period from July 1996 to June 1999, based on data from ABARE farm surveys. Key points •

a relatively high percentage of Australia’s farmers have no post-secondary education

•

relationships between formal educational attainments and adoption of sustainable NRM practices are unclear or weak


31

•

participation by farmers in courses or training activities is associated with adoption of sustainable practices

•

both the pattern of educational attainments among farmers, and their participation in courses and training activities, appear to be influenced by farm distance from educational institutions and farmers’ average ages, with older farmers and those in more remote regions being less likely to participate.

Farm financial characteristics Maps 10-18, Charts 3-10 Reviews of economic pressures affecting the depletion of natural resources on farms in Australia have indicated that since the 1950s, declining terms of trade have reduced primary producers’ per unit production margins significantly. Consequently, producers have looked to improvements in efficiency to make their enterprise more profitable and maintain a minimum net income and standard of living. However, often a consequence of this is degradation of the resource base. In overseas research studies (mainly in the United States), it has been found that the greater the level of gross farm income, the greater is the likelihood that conservation and land management practices will be implemented (Camboni & Napier 1993; Saltiel et al. 1994; Witter et al. 1996). An analysis, undertaken elsewhere in this report, of 15 sustainable practices in the 1998-99 ABARE Resource Management Supplementary survey indicated that annual farm cash income and profit at full equity were each only associated with one practice of those considered. Higher farm equity ratio was associated positively with one practice and negatively associated with three practices. Sustainable practices do not always cost more to implement: sometimes more sustainable management can be achieved by a change in the way farms are operated, at little cost. However, as with farm income, the level of farm profitability may reflect a property holder’s ability to adopt sustainable practices that do involve additional costs. In these cases, low levels of farm profitability leave the farmer with little or no ability to fund sustainable land management practices. For some practices, acceptable levels of farm profit are required to ensure property holders are able to bear any increased risk that might be associated with adopting more sustainable management practices. The security and level of cash income, less debt-servicing requirements, has a positive influence on adoption as it provides important capacity not only to afford the investment, but also because income security is not threatened by an investment that has an uncertain outcome. A number of measures of Australian farm financial characteristics are available. The ones used here are: •

farm family income (an ABS estimate) is estimated by the Census respondent in the fiveyearly ABS Population and Housing Census and for farm families includes income from all sources earned by all members of the family living on-farm, including government social service and other government payments (for example drought relief, exceptional circumstances) over an annual period

•

annual family income (an ABARE farm survey estimate) refers to family share of farm income plus any farm wages paid to the owner manager, spouse and dependant children, plus all off-farm income of owner manager and spouse. Farm business income is farm


32

cash income plus change in trading stocks, less depreciation and less any wages paid to the owner manager's family and other family members •

annual farm cash income (ABARE farm survey) is calculated by ABARE from details of expenses and receipts in farm account records data collected in farm surveys, and is defined as the difference between total cash receipts from the farm business and total cash costs incurred by the business over a given period (usually annually)

•

off-farm income, defined as income from wages, non-farm businesses, investments and social welfare payments. It is collected in ABARE farm surveys for the owner manager and spouse in family farms only, not for properties in corporate ownership

•

farm profit at full equity, defined by ABARE as farm business profit, plus rent, interest and finance lease payments, less depreciation on leased items - it measures return on all resources used in the farm business

•

farm debt (ABARE), which includes all liabilities related to the farm business which appear on balance sheets in financial accounts - this includes the farm mortgage, other term loans, business overdrafts, fully drawn advances, amounts owed to creditors and hire purchases related to the farm enterprise

•

farm business equity (ABARE) is the value of owned capital less farm business debt as measured at 30 June each year, and the farm equity ratio is the percentage of the farm’s owned capital (equity divided by total capital)

•

total household expenditure, which for farm households includes all non-farm-related household expenditure.

Each of these measures is briefly discussed below. Two sets of data are presented in the maps associated with financial estimates provided from ABARE surveys. The polygons are Statistical Divisions (SD) and are colored according to the estimated financial measure for the SD. In some maps a number is also displayed within each polygon. This represents the relative standard error (RSE) of the financial estimate for the SD, expressed as a percentage. For farm income, it is a measure of the likelihood that the survey estimate of farm income reflects the actual farm income for the Statistical Division. For example, if average total cash income is estimated to be $100,000 with a relative standard error of 6%, the standard error for this estimate is $6,000. This indicates there is roughly a two in three chance that the ‘census value’ (the value which would have been obtained if all farms in the target population had been surveyed) is within one standard error of the survey estimate (i.e. is between $94,000 and $106,000). There is roughly a nineteen in twenty chance that the census value is within two standard errors of the survey estimates. The RSE will be larger when the sample size is small and when the underlying income variability is large. The higher the RSE, the greater the likelihood that the data are not truly representative of the actual population. This must be considered when drawing conclusions from the survey estimates: for example, the RSE for annual farm cash income for the Northern Territory SD is 98%. It is often suggested that farm families with higher incomes or lower debt levels are in a better position to adopt sustainable land management practices, and some research evidence supports this view (eg. Saltiel, Bauder & Palakovich 1994, Witter, Robotham & Carrasco 1996; Curtis & De Lacey 1998; Curtis & Van Nouhuys 1999). Higher incomes may provide the ‘space’ for farm families to think longer-term; provide resources to address land degradation problems like salinity, soil erosion, weeds and pests; and allow families to focus on farm amenity as well as production values. For grazing properties, higher incomes may reduce pressure to overstock.


33

Lower farming returns since the 1950s (due largely to lower commodity prices and the effects of trading conditions), have also been suggested as having increased production pressure on many family farms and led to significant land degradation (Beal 1997). Variations in commodity prices are a major factor influencing on-farm incomes. Throughout most of the 1990s, wool prices were low (Barr 2001), reducing incomes in the wheat-sheep belt. Terms of trade for many other agricultural commodities also declined through the 1990s (ABARE 2000). Median farm family income provided by the ABS gives income data aggregated at the Statistical Local Area (SLA) level and by predetermined income categories (which change between Censuses). ABS estimates are likely to be less accurately estimated at the individual level, but represent estimates from all relevant population members. Annual family income reflects both on- and off-farm income from all sources. There are two levels of variability of on-farm income which need to be considered. Firstly, there is the variation for given properties between years. In some areas of Australia and for some farm enterprises this variation can be very large. Secondly, there is the variability of the estimate of the income for the SD of interest, measured by the RSE. As well, there can be scale and heterogeneity issues that introduce variation. Statistical Divisions can be very large areas and what may be true at one scale may not be true at another. For example, the farm income of pastoral properties on the Barkly Tableland in the Northern Territory is likely to be very much higher than in the southern, less-productive areas of the same SD. Annual family income has been examined in this project as a three year average for the period 1996-97 to 1998-99 by SD (Map 11). Using a three-year average tends to smooth out some variations due to seasonal conditions and may be a better indication of the base levels of family income. Map 11 indicates that annual family incomes tend to be related to property sizes, with returns from large pastoral properties generally higher than from small farming operations. The income of pastoral families is also more likely to be obtained solely from onfarm activities than is income in the more intensive agriculture areas where more opportunities are likely to exist for earning off-farm income. Similarly, median farm family income patterns for 1996 (Map 10) tend to suggest that pastoral families, particularly in parts of Western Australia and the Northern Territory, were earning good incomes, but that incomes were relatively low (below $40,000) throughout most of the wheat-sheep and intensive agriculture areas of eastern Australia. In some parts of remote Australia, higher family incomes appear to be associated with nearby mining operations, suggesting that mining-related activities are providing alternative employment opportunities for some farm family members. Annual farm cash income has been examined in this report as a three-year average for the period 1996-97 to 1998-99. It reflects both total incomes (on- and off-farm) as well as costs of farming operations. Costs in many farming businesses have been increasing steadily (for example fuel, labour, fertiliser, seed) (ABARE 2000). Results depicted on Map 12 need to be interpreted cautiously as many areas have high RSEs (for example the Northern Territory and northern Queensland) and the estimates may not be representative of populations of farmers in the respective SDs. On the basis of Map 12, there appear to be marked regional variations in annual farm cash income, but a property size effect also seems to exist, with families on larger pastoral and some wheat-sheep properties tending to earn highest cash incomes. The exception in the Northern Territory may be due to an unrepresentative sample or to structural factors (corporate ownership of cattle stations rather than family ownership, with the former not included in these ABARE statistics).


34

It appears that while annual farm cash income can differentiate significantly large regions of low or high average income, as currently collected it is not a sufficiently discriminating indicator of capacity to change sustainable management practices. In an analysis of sustainable practices in the ABARE Resource Management Supplementary survey level of annual farm cash income was associated (in the wheat-sheep and high rainfall zones) only with the use of soil or plant tissue tests to determine fertiliser needs. Any additional incomes from other businesses, investment and social welfare payments can help the farming enterprise invest in more sustainable practices. However, frequently, offfarm income (particularly in the form of wages) is seen as an indicator of otherwise low farm incomes and hence a general inability to adopt new practices. Off-farm income, which may be independent of the fluctuations associated with on-farm incomes, may reduce the risk associated with adopting more sustainable practices. The contribution of off-farm income to total farm family income has been steadily increasing in significance for many of Australia’s farms. In 1994-95 surveys of Australian broadacre farming households, on average, income from the farm business was only 37% of annual family income (Garnaut & Lim-Applegate 1998). It should be noted that this was a period when many of these farms were affected by drought, so on-farm incomes were likely to have been lower than usual and many farms in fact reported losses. Nonetheless, it is clear that offfarm income is a significant buffer against variability of on-farm income for many farm families, and that increasing numbers of farms are ‘lifestyle’ farms rather than businesses in which farm produce is the main income source (Garnaut & Lim-Applegate 1998). This is an important point, because it suggests that even among the subset of Australian landholders who identify themselves as farmers or farm owner operators (the focus of this study), significant numbers obtain much of their income from non-farm sources. In their survey of landholders in the Goulburn Broken area of Victoria, Curtis et al. (2000) found that self-identification as a farmer was significantly negatively associated with adoption of some best property management practices - in other words, non-farmer landholders tended to adopt these practices more frequently than farmers. Previous research has shown that off-farm wage income may have a positive or a negative impact depending on whether the negative effect of the time requirement of such work on time available for adopting new practices, outweighs the effect of greater resources to undertake such practices. Increasing commitment to off-farm work has been shown to reduce the effectiveness of community landcare groups. Some overseas studies suggest that more family members working on-farm, and therefore higher availability of adult labour, is associated with a higher probability that sustainable land management practices will be adopted (Carlson & Dillman 1988; Turrell & McGuffog 1997). Curtis et al.’s (2000) study found no significant associations between on-property hours worked and adoption of best practices property management; but did find a significant positive relationship between hours worked off-property and the area of remnant bushland fenced to manage stock grazing as a percentage of the total property. However, the same study found no significant relationship between total off-property income and adoption of best practice property management. Off-farm employment has been identified as important in allowing entry into farming. If one or more family members have off-farm income, this can help to ensure that family income needs are met during the farm establishment phase when on-farm income may be low or negative (Olfert, Taylor & Stabler 1993; ABARE 1997). Patterns of off-farm income shown in Map13 are based on three-year averages for those farms for which off-farm income information for both the owner manager and spouse was available. The high RSE’s for some areas suggest possible wide disparities in off-farm income within these areas.


35

Highest average off-farm incomes (above $32,000) were earned by families in the extreme South West of Western Australia, Northern Territory, Far North Queensland, Central West of New South Wales and Loddon area of central Victoria. Some of these areas also had large RSEs associated with the estimate of off-farm income. In south west Western Australia, the Northern Territory and Far North Queensland, high off-farm income may reflect tourismrelated activities. Lowest off-farm incomes (below $8,000) were in scattered areas of southern Western Australia, central Queensland, south of Sydney and northern Victoria. Intermediate levels of average off-farm income ($16,000-$32,000) were often found in areas near larger cities or regional centres. These patterns are not easy to interpret other than to observe that off-farm income can come from many sources. Some sources usually require proximity to towns and cities (alternative employment opportunities), whereas others do not (investment income, social security payments, exceptional circumstances payments). The importance of off-farm employment means that less-remote farms are likely to be significantly advantaged in obtaining off-farm income. Farm profit at full equity is calculated on the basis that a farm has no debt and therefore no interest has to be paid to lenders. In this project, the indicator data examined were a three-year average for the period 1996-1997 to 1998-1999, based on ABARE farm survey data (Map 14). There were high RSEs for data relating to parts of Queensland, Western Australia, and western New South Wales. The pattern of farm profit at full equity, 1996-97 to 1998-99, in some respects mirrors the pattern for annual farm family cash incomes for the same period. Those areas with lowest cash incomes tended to be those with lowest farm profits. Generally lowest profit areas ($8,000 loss or greater) were located in Far North Queensland and along the length of the south-east coast from southern Queensland to the Adelaide region. These areas are characterised by being more intensively settled, having smaller farms, being farmed by older farmers, and having many farmers engaged in higher rainfall grazing, cropping or horticulture. They are also areas where off-farm income is likely to be a significant contributor to total farm family income, suggesting that family efforts and interests may be directed away from the farm to a significant extent. Conversely, areas achieving highest farm profits are generally those where farms are larger and on-farm income is the major component of farm family income. This applies to areas like the central coast of Queensland, far western New South Wales, and the Western Australian Central and Midlands areas. In an analysis of sustainable practices in the ABARE Resource Management Supplementary survey farm profit at full equity was only associated with monitoring of pasture and vegetation condition in the rangelands. Total household expenditure is obviously related to family disposable income and thus both to total income and debt level. Household expenditure is likely to be affected by remoteness, as farm families in remote locations are likely to need to spend more on travel, goods and services than families in more densely settled areas. Education costs may also be considerable for farm families with dependent children living in remote areas. Overall size and age composition of farm families also influences expenditure patterns. Map 15 depicts total farm household expenditure for 1998-1999. Total expenditure tended to be highest (more than $50,000) on average in the pastoral and sheep-wheat zones (with the notable exceptions of the Kimberley and South Eastern areas of Western Australia, where expenditure was extremely low). Other low expenditure regions (less than $20,000) were the Northern and Mackay areas of Queensland, north-eastern New South Wales, the Illawarra,


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southern Tasmania and scattered areas of eastern and central Victoria. These areas are mainly well-serviced ones where costs of goods and services are likely to be comparatively low. The rationale for including farm debt among indicators related to ability to adopt more sustainable practices is generally the converse of the argument that higher levels of farm income may be related to increased adoption. High debt levels may reduce resources available for on-farm improvements and tend to encourage unsustainable land use in an attempt to maintain income levels needed to service debts, even in poor seasons. There is some evidence from overseas studies that higher debt levels are related to lower adoption of sustainable practices (Norris & Batie 1989; Witter et al. 1996); and that lower farm profits reduce investment in these practices (Curtis & De Lacey 1998; Curtis & Van Nouhuys 1999). From Map 16, highest debt levels were recorded in Western Australia’s South Eastern region, the Northern Territory, across central Queensland, and as something of an anomaly, in Victoria’s Barwon area (where land values may be high and borrowing needed to fund farm expansion). Average debt levels were comparatively high ($225,000 or more) in most of Western Australia for which data were available, with the exception of the extreme southwest. Debt levels were relatively low ($75,000-$150,000) in Far North and south-eastern Queensland; Far West and south-eastern New South Wales; and much of inland Victoria and South Australia. Overall, farm debt levels are related to property size as large pastoral properties, for example, are usually more valuable than small properties in more intensive agricultural areas, and so pastoral enterprises are likely to have larger mortgages. However, larger properties with lager farm incomes are more able to service larger debt. Farm equity is a measure of the farm’s owned capital and might be expected to reflect farm families’ commitment to and willingness to make further investments in their properties; but lower equity may reflect recent purchase of a farm property or of additional land. Farm equity is affected by changing land values as increasing land values lead to increases in the value of owned capital, counter-balancing debt. This is a significant factor, particularly in the more intensively farmed areas of coastal Australia. Mues, Chapman and Van Hilst (1998) found that higher equity ratios were associated with the adoption of regular soil testing by cropping specialists; however they were unable to establish an association between equity ratios and other sustainable practices. In an analysis, later in this report, of sustainable practices in the 1998-99 ABARE Resource Management Supplementary survey higher equity ratios were positively associated with use of controlled bores and negatively associated with monitoring of pasture and vegetation condition in the pastoral zone. Higher equity ratios were negatively associated with use of deep-rooted perennial pasture and monitoring water tables in the wheat-sheep and high rainfall zone. The measure used in this project was the farm equity ratio measuring the percentage of owned capital, averaged over the three-year period 1996-97 to 1998-99 (Map 17). High equity ratios (90-100%) were seen in south-west Western Australia, Far North Queensland, the Brisbane area, New South Wales coast and Far Western New South Wales, Ovens-Murray and Loddon areas of Victoria, and throughout South Australia except the Upper and Lower South East and Eyre Peninsula. Ratios were lower (below 85%) in much of inland pastoral Australia Lowest ratios (less than 80%) occurred in Western Australia’s South Eastern Division, Central West Queensland, and the Loddon and Barwon areas of Victoria. It is difficult to generalise about equity ratios other than to observe that property size, and the great disparity in size between pastoral and other farming properties, is a major factor in differentiating regional variations in farm equity. This has corresponding implications for any effects of equity on adoption of sustainable practices.


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Traditionally, Australian broadacre farmers have high equity ratios as a risk protection against highly variable farm incomes. A farm equity ratio of less than 80% (Map 18) is often considered a ‘trigger point’ in measuring farm resilience in the face of changes farm income farms with 80% or less equity are seen as being vulnerable to downturns in farm income. Such farms may have potential difficulty in servicing debt in adverse seasons or when commodity prices are low. Key points •

in Australia there have been few definitive studies which link objectively measured financial indicators to adoption of sustainable practices; however ‘financial constraints’ self reported by landholders are frequently cited in research studies as being an important barrier to the adoption of otherwise attractive innovations or management practices

•

common sense, and conventional understanding of human motivation, suggest that low incomes and high debt discourage adoption of sustainable practices which have low returns and long delays to achieving any benefits

•

variability of many farm financial measures often will be as great with a geographical locality as the variability between different areas; this sometimes makes it difficult to use income measures as geographically based indicators

•

low incomes resulting from farm industry and institutional structural change will frequently be geographically concentrated in specific localities

•

low incomes as a consequence of extended low commodity prices or extended drought conditions will also be geographically concentrated in specific localities.

Farm family characteristics Map 19 The ABS definition of a farm family is a family in which at least one member describes his or her major occupation as farming. Most of Australia’s farms are family farms, and family characteristics are clearly a key structural aspect of Australian agriculture and natural resource management. For example, recent surveys of the broadacre and dairy industries indicate that approximately one-third of farm owner manager households consist of couples only, and another third of couples with children aged 19 years or younger (Garnaut & Lim-Applegate 1998). Recognising the family business nature of much Australian farming, over the last decade there has been increasing interest in Australian farm women’s contributions, and better information is now available on farming’s gender dimensions (see for example Garnaut et al. 1999; Alston 1995, 2000; RIRDC/DPIE 1998). However, relatively few women identify themselves as farmers or farm owner operators (Garnaut & Lim-Applegate 1998; Barr 2001). Aspects of farm families examined in previous studies (and in some cases related to adoption of sustainable agricultural practices), include numbers of family members working on-farm; contributions of different family members to total farm income through off-farm work; family structures (including numbers of children); and family life cycles (Fenton, Macgregor & Cary 2000, Garnaut & Lim-Applegate 1998; Salmon et al. 1997; Saltiel, Bauder & Palakovich 1994). Stage in family life cycle (in particular number and ages of children) is likely to be an important influence on farm planning, expectations of inter-generational transfer of farms, and money spent on farm improvements. For example, some studies suggest that on-farm investment is less likely to occur where farm operators are older and have reached a family stage where it is apparent that their farms are not likely to be transferred to the next generation (Curtis 1995, 1996; Collier 1995; Barr & Cary 2000).


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Children’s education is often a major expense for farm families and may raise income needs or reduce money available for on-farm work. This is particularly so for families in more remote regions because their children may need to live away from home to attend schools, colleges or universities in regional centres or capital cities; or children remaining at home may incur substantial transport costs getting to and from educational institutions. On the basis of the 1996 Census data, as depicted in Map 19, highest proportions of farm families with one or more dependent children tend to be predominantly in the inland, including the pastoral and wheat-sheep zones west of the Divide in eastern Australia. Throughout much of the coastal, intensive agriculture area, less than 40% of farmers had dependent children in 1996. This pattern mirrors the fact that farmers on average tend to be older in coastal areas and so are likely to be at a later stage in family life cycle with their children independent. Key point •

while dependent children are an important factor in influencing farm families’ income needs and expenditure patterns, and are an indicator of family life cycle stage, there is relatively little geographical discrimination for this indicator across Australia apart from in some of the low population density areas of the pastoral interior.

Farm structure Maps 20 & 21, Chart 11 There is considerable evidence that the larger the farm in terms of its physical size, the more likely the farm manager is to adopt new and more sustainable farm management practices. The explanation for this is associated with economies of scale, i.e. the larger the property, the easier it is to manage profitably and the more resources available for improving land management. There is also some suggestion that smaller property sizes when coupled with the demands to create higher farm incomes also leads to over-use and depletion of resources. Sub-economic farm size has been identified as the main cause of over-grazing in the Western Division in New South Wales and the Mulga region in Queensland (CIE 2000). The estimated value of agricultural operations (EVAO) is a measure of gross farm income. However, EVAO is not an indication of enterprise profitability and so, in itself, does not indicate financial capacity to adopt sustainable practices. EVAO is correlated with farm (enterprise) size and has been used as an indicator of farm size as it is often a better measure of the scale of the farm business than is farm area. However, we must always consider the ‘ecological fallacy’ problem. Just because a correlation can be demonstrated between EVAO and farm size within a region, it does not mean that such a relationship necessarily exists between different regions and even within other regions. Barr (2000) noted a correlation between EVAO and farm sizes within the Murray-Darling Catchment - agriculturally, a fairly homogenous region. While it may be safe to assume that this relationship is also likely in the other agricultural and wheat-sheep regions of Australia, it would, however, be risky to extrapolate the same kind of relationship to the rangelands – particularly the more remote rangeland regions. It is conceivable that a correlation between EVAO and property size may exist in these regions but it seems unlikely to be similar to the one found in more intensive agricultural regions. The pattern of EVAO distribution in Australia does indeed suggest that EVAO can act as a surrogate for enterprise size. Lower median EVAOs correspond with the geographic distribution of the smaller, more intensive wheat-sheep properties, while the larger properties found in the rangelands clearly have a higher median EVAO.


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There are very large differences in farm property size (median farm area) in different geographical areas of Australia. A generalised geographical pattern of increasing farm size moving to the centre and to the north of Australia predominantly reflects decreasing rainfall and increasing unreliability of rainfall, as well as the difference between pastoral land uses and other types of farming. The range of farm sizes for Australia means that Australia-wide depictions of property area do not show differences within the more climatically favoured east, south-east coastal, and south-west Western Australia areas. Median farm area is depicted on a SD basis and thus is not an indicator that will discriminate capacity to change sustainable management practices. Key point •

EVAO is a more discriminating indicator of size of farm operations than is farm area; EVAO increases markedly as one moves inland from the eastern and south-western coastal fringes; however EVAO it is not a particularly discriminating indicator except on a zonal basis.

Identification of land management problems Maps 22-27, Charts 12-17 This indicator type was described by Fenton et al. (2000) as ‘Attitudes, perception towards and expectancies of change’. It is included because, generally, it is accepted that farmers and farm families need to acknowledge that land degradation and environmental problems exist on their properties, and understand the connection between these problems and their own 5 practices, before they are likely to change. While connections between awareness of problems and adoption of innovations are complex and strongly influenced by social norms and social structures, information on problem awareness may be an indicator of at least a preparedness to consider that change is needed. Cary (1994) and Cary and Wilkinson (1997) found that landholders in Central Victoria who recognised salinity as a land management problem were more likely to plant deep-rooted pasture species but no more likely to plant trees. Curtis et al. (2000) in their study of Victoria’s Goulburn Broken Catchment found no significant relationship between the attitudes they surveyed and the adoption of best land management practices. The identification of land management problems by landholders is important because landholders’ assessments of land management problems can be compared with the biophysical assessments reported in other Land and Water Resources Audit projects. At least in very general terms assessments can be made as to whether landholders perceive the problems to the same extent that scientists report them. More accurate assessment would require localised overlaying of landholder identification of land management problems with maps of biophysical assessments of nominated land management problems. The land degradation problems for which indicator data were obtained are weeds, soil acidity, salinity (dryland and irrigation), and ‘any land or water degradation’. In addition, data about numbers of farms with Property Management Plans were also examined as a possible indicator of awareness of need for sound business practices as part of achieving sustainability. (However, Curtis et al. (2000) found few significant links between planning and adoption of best practices – the only significant positive relationship was between having a property plan and the total number of trees planted on property.) The indicator data are derived from farmers’ responses to corresponding questions in ABARE farm surveys. It is important to

5

Note that a desirable sustainable practice which is perceived to have a relative advantage (in a production sense) can be adopted without the adopter recognising a resource degradation problem (see Cary & Wilkinson 1997).


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note that responses are farmers’ own perceptions and may not necessarily correspond with problems identified by other means or by other groups (for example extension staff, scientists, technical experts). Map 22 indicates that weed problems tended to be reported most frequently by farmers in the pastoral and wheat-sheep zones (data were not available for most of Western Australia however). This reflects the fact that grazing in the pastoral zone is mainly on native pasture and many pastoralists consider encroaching native woody shrubs to be a problem, particularly in northern Australia (this is often claimed to be due to reduced fire frequencies under European settlement). Weed problems tended to be reported less frequently in more intensive agriculture areas where native vegetation has been extensively cleared. There are high RSEs for some data depicted in this map, particularly for central eastern Queensland. Soil acidity arises as a consequence of fertiliser over-use, and is therefore most likely to be a problem in intensive agricultural and cropping areas. Map 23 indicates that highest percentages of farmers reporting soil acidity problems were in the Central and Midlands areas of Western Australia, Mid North Coast and Central West of New South Wales, and Gippsland and East Gippsland areas of Victoria. Few farmers in the Northern Territory, Queensland, Tasmania or South Australia reported acidity problems. Map 24 depicts reports of any significant land or water degradation problems, including the ones discussed above. Substantial percentages of farmers in all areas considered they had significant problems, with the notable exception of Tasmania and Far North Queensland. Highest percentages (>20%) were in Western Australia’s Lower Great Southern, Midlands and Central areas; Queensland’s Northern and Mackay areas; the Northern, Hunter and South Eastern areas of New South Wales; and the East Gippsland area of Victoria. Low percentages of farmers (20%) of farmers reporting dryland salinity problems were in Western Australia’s wheat-sheep areas in the Midlands and Lower Great Southern regions; the Central West of New South Wales; and the mainly irrigated agriculture and wheat-sheep areas of the Mallee, Wimmera and Loddon areas of central and western Victoria (Map 25). Higher percentages also correspond reasonably closely with cereal cropping areas in southern Australia, with the exception of north-eastern New South Wales and Queensland where high summer rainfall helps prevent this problem occurring. Very few farmers (20%) were in the Loddon Division of central Victoria, with percentages also high in the neighbouring Mallee (15-20%) and Goulburn Statistical Divisions (10-15%). Slightly lower percentages (5-10%) of farmers in the Murray Division of New South Wales also reported irrigation salinity problems. Values for the Proportions of farms with a Property Management Plan (Map 27) in some regions had relatively high RSEs, therefore the map needs to be interpreted cautiously. Highest percentages of farms with property management plans (>50%) were recorded in the North West and Mackay regions of Queensland, and the Barwon area of Victoria. Percentages were low (