Abstract

Small farms are a growing sector of Victoria’s rural landscape. It is acknowledged that small property owners can have a major impact on the landscape and regional prosperity (Black et al. 2000; Colman et al. 2002; Barr & Karunaratne 2001). There has been concern raised over this sector’s level of knowledge of how to manage the landscape in a more sustainable fashion (Black et al. 2002). Extension has traditionally targeted farmers who derive most income from the farm. There is now a need to ensure extension strategies also engage the small farm sector. This sector does not rely on farm income so heavily and therefore is not necessarily interested in extension promoted as production boosting. Currently, two research projects at the Department of Primary Industries (DPI)-Rutherglen, Victoria, are investigating the small farm sector. The research aims to understand the needs of the sector and develop appropriate extension strategies with rural service providers and the community. The research has adopted a social paradigm and as a part of its methodology, secondary data analysis of the small farm sector is being conducted. Using Geographical Information Systems (GIS) generated in ArcView 8.0 allows the research team to conceptualise some bio-physical characteristics of the regions dominated by small farms. This paper will demonstrate how rainfall layers, topographical maps, and agricultural census data can be displayed to aid the social research process by identifying characteristics of areas dominated by this sector. A richer picture of the target subject can be developed with the addition of qualitative data.

The key messages of the paper:

• Improved extension strategies can be informed by an understanding of the target sector through social research
• The small farm sector makes up a significant proportion of farm establishments in Victoria and tends to be located in regions with high rainfall and high topography
• GIS can be used as a tool to inform the social research process.

Media summary

Social research combined with GIS data can help to improve our understanding of the small farm sector in Victoria.

Keywords

Small farms, social research process, geographical information systems and informed extension.

Introduction

The growing small farm sector affects the social, economic, and environmental well being of rural Victoria. For this paper a small farm is defined as a farm establishment with an estimated value of agricultural operations between $5,000 - $75,000¹. In the past the small farm sector has not been specifically targeted or engaged in many extension programs. Concern has been raised over this sector’s level of knowledge and skills to manage their property in an environmentally sustainable way. This issue was recognised by the Rural Industries Research and Development Corporation (RIRDC) and the Victorian State government, resulting in the funding of two research projects specifically exploring how extension providers can better engage the small farm sector (refer also to Hollier et al.; this conference). This paper will create a conceptual framework in which to begin viewing the small farm sector and briefly discuss extension. It shall then introduce how the two research programs at Rutherglen are utilising mapping as a part of the research methodology. A socio-economic map revealing the locations of high percentages of small farms was constructed in ArcView 8.0 (based on Barr & Karunaratne 2001) and has been overlayed with other bio-physical maps, revealing some specific trends. The role of mapping and qualitative research in informing extension is discussed. The paper concludes by discussing the role of mapping and qualitative research in informing extension.

Social, economic and environmental importance of the sector

In Victoria, and across Australia, small farms are beginning to dominate certain parts of the rural landscape (Barr & Karunaratne 2001; Lindsay & Gleeson 1997). Although small farms contribute far less, from an economic perspective, than larger farms to the value of agricultural production (Barr & Karunaratne 2001), small farms can play an important role in the social, environmental and economic sustainability of rural communities.

The economic, social and environmental aspects of a rural community share complex inter-dependant relationships (Jeffreys & Munn 1996). The last two decades have been identified as some of the hardest for rural country towns (Gray & Lawrence 2001; Monash 2001). Small farms offer the potential to positively impact on the rural crisis. A large number of small farmers in rural communities, supporting or increasing the community’s population may contribute to the development of higher levels of healthcare, council, and other public services. The injection of skills and population into rural communities, which smaller farmers offer potential to raise, may ensure longer-term security for local community institutions, such as Landcare or local sporting clubs. Small farmers can contribute to the ability of rural communities to manage and deal with change into the future (social capability) thus ensuring their survival.

Small farmers also can offer new markets and opportunities for the local economy. These increased economic opportunities may allow rural towns that are dependent upon local agriculture for their survival, to increase their diversity and resist or manage the ‘economic’ global misfortune affecting many rural towns (Gray & Lawrence 2001).

Apart from the potential economic and social benefits of the small farm sector, there also exists a case for environmental gains to be made from the sustainable management of their properties. The maintenance of biodiversity provides an essential ecological service for farmers by providing natural regeneration processes for primary production (Altieri 1993). Small farmers can offer biological diversity in a landscape that, if left to international markets, could quickly become an industrialised monoscape (Pretty 1995). These biodiversity gains can stem from the ‘alternative’ industries small land managers tend to adopt, offering the potential to create a mosaic landscape. A number of smaller farmers chose not to be involved in agricultural production but rather manage the block for conservation reasons. Additionally, because some smaller farmers derive the majority of their income off-farm, they may be more likely to manage the larger proportions of the land for environmental and biodiversity gains.

Extension and the small farm sector

As economic efficiency is sought after in agricultural extension (Vanclay 1994), state governments have begun to move away from one-to-one extension activities towards more group facilitated often-coined, ‘participatory approaches.’ These approaches, borrowing on participatory techniques rather than the ‘true’ participation theory (Cooke & Kothari 2001), have experienced a relative success in the reaching their desired outcomes (Coutts et al. 2001). It has been suggested that government’s dedication to group approaches, with rhetoric to self actualisation and farmer empowerment, are based on limited finances rather than a commitment to a more sustainable agriculture (Vanclay & Lawrence 1995). Although the ‘Decade of Landcare’ has seen relatively great success in the management of Australia’s natural resources, Landcare groups are also beginning to be challenged as state extension services are wound back (NHT 2000).

The increased pressure from economic efficiency has meant that some extension agencies have moved towards segmenting their client base (Vanclay & Lawrence 1995). The rationale behind such an approach could be fuelled by the need to achieve maximum benefit from scare financial resources. This in turn means focusing extension dollars on larger farmers. The pathways that some extension providers have moved into mean that sometimes the small farm sector has been left behind in the provision of extension by the state. This is not to say that small farmers are not engaged in any extension programs, but generally speaking, extension has been focused at larger producers. This has lead to concerns over the levels of knowledge by the small farm sector in the context of the sustainable land management. A low level of knowledge can lead to land management problems at the catchment level, such as increasing numbers of weeds, soil degradation, and loss of biodiversity.

The two research projects being conducted in north-east Victoria are seeking to explore the ‘human component’ of the small farm sector in order to better inform extension providers and agencies about how to better target the sector to improve knowledge and skills relating to sustainable land management.

Research approach

The research team has chosen a mixed method approach, combining both qualitative and quantitative methods. The latter research focuses on the quantification of data; the transformation of natural and social dynamic systems into numbers. Mapping has been one of the main tools selected for the quantitative approach into researching the sector. Qualitative research places emphasis on understanding of human behaviour as interpreted from the social actor’s perspective. Semi-structured interviewing and discussion groups are being used as the methods for the collection of qualitative data. Through the adoption of a mixed methods approach, the researchers aim to capitalise on the strengths that both methods offer in understanding rural society.

With the advances in the ease of accessing data and user friendly mapping software, mapping has become an important tool for visualising quantitative data. Mapping has allowed the research team to identify the broad geographical locations that the small farm sector currently occupies. Overlaying socio-economic data with layers of bio-physical characteristics allows identification of possible ecological issues facing the small farm sector.

The quantification of social and ecological characteristics alone does not provide insight into what small farmers are experiencing on the land. At the centre of any ecological problems is the ‘human component’ to land management. People’s knowledge and understanding of the land are socially constructed; what land managers understand and believe about the bio-physical is a function of their own unique contexts and pasts (Pretty 2002). Because the ‘human’ component is important in understanding land management often the best way of going about researching the process is by talking to the farmers themselves, extracting qualitative data. Stories or narratives are often the primary way individuals communicate and share experience with one-another (Richardson 1990). Farmers communicate their farm experiences, placing meaning into the reasons why particular land management practices are carried out, which is why semi-structured interviewing and discussion groups are the preferred methods for obtaining qualitative data.

When studying the human component of farming systems it is impossible to construct iron laws of cause and effect (Furze et al. 1996). The research aims at generating a meaningful understanding of the small farm sector in north-eastern Victoria in which to inform extension. Because land management involves both physical and social components, it is through the fusion of quantitative and qualitative data that a more accurate understanding of the issues may be developed. In addition, after this understanding has been developed within the north-east, mapping can then be used to identify catchments with similar characteristics in which the research findings may apply.

Integration of GIS with socio-economic information

Usage of global information systems layers

ArcView 8.0, a geographical information system (GIS) software package, was used to visualise and analyse particular attributes correlated to the distribution of the Victorian small farm sector. DPI has a wide range of GIS layers that can be overlayed to create specific maps for Victoria. Each of the three layers used in the project (small farm locations, rainfall and topography) is linked to a tabular data set. Tabular data is used as a raw form for storing geographical data. It contains the information of locations of the particular features represented in the geographical format. The two bio-physical map layers were overlayed on top of the small farms layer, generated from the data extracted from the 2001-2002 Agricultural Census. Each layer was in the same projection², ensuring precision when overlaying the maps. The tabular data, from the two bio-physical layers was combined with the socio-economic data from the small farms layer, and analysed.

Small farms layer – Victoria

The method for constructing a visual representation of small farms in Victoria is based on the process used by Barr and Karunaratne (2001). This involved inputting percentages of farm operations that are small farm operations, (defined as operations with an EVAO³ between $5,000 - $75,000) within each statistical local area (SLA) refer Figure 1.0. SLAs are geographical regions used by the Australian Bureau of Statistics (ABS) as a base unit for summarising data, which is responsive to the changing population distribution. SLAs are based on Local Government Areas (LGAs) however, generally speaking, LGAs are usually larger in size than SLAs.

Figure 1.0 Small farms as a percentage of all farms within each SLA in Victoria.

Annual rainfall layer – Victoria

The rainfall layer is based on averaged data collected over a period between 1961-1990 at 6000 weather stations across Victoria (BOM 2003b). As can be seen in Figure 2.0, Victoria is characterised by a range of different climate zones. The extreme of these climate zones extends from the dry Mallee region in the north-west of the state, where median annual rainfall ranges from less than 250 mm, to the alpine regions of north-east Victoria, which averages in excess of 2200 mm (BOM 2003a).

Figure 2.0 Average annual rainfall across Victoria.

Digital elevation model layer - Victoria

The Digital Elevation Model layer (DEM) represents the average elevation of Victoria on a 1:250,000 scale. The DEM is computed from topographic information including point elevation data, elevation contours, stream lines and cliff lines. Tests have indicated an accuracy of around 25 metres of standard deviation for a sample area which varies from flat to rugged (Australian Surveying & Land Information Group 2003). Figure 3.0 illustrates the elevation of Victoria based on this data.

Figure 3.0 Victoria’s elevation (in metres).

Results from GIS

The integration of the tabular data and visual assessment of the layers reveals a strong correlation between high percentages of small farms in areas of high elevations and high rainfall, quantifying previous work undertaken by Hollier et al. (2001). When the average rainfall data in each SLA (indicated on y-axis of Figure 4.0) is aggregated with the percentage of small farms in each SLA (x-axis) a trend can be seen. As the percentage of small farms increases (moving right along the x-axis) the average rainfall begins to steadily, although not consistently, increase.

Figure 4.0 Percentages of small farms in relation to average rainfall of each SLA.

There is a slightly larger and more consistent increase in Figure 5.0, depicting the correlation between a rise in elevation and higher percentage of small farms. A sharp difference was not expected between the percentage of small farms across higher rainfall and higher elevations, because higher rainfall is generally associated with higher elevations.

Figure 5.0 Percentage of small farms in relation to average elevation of each SLA.

When referring visually to Figure 1.0 there is a high percentage of small farm establishments corresponding by and large where the Great Dividing Range is located. This is not to suggest that small farms only occupy these regions or will continue to do so in the future, however these areas are currently the most populous for the sector. The presence of a high percentage of small farms around Melbourne and the northern Mallee (small horticultural establishments along the Murray River) areas of low elevation and rainfall, are outliers of this trend.

Qualitative data from north eastern Victoria

Over the last 16 months the research team in north-eastern Victoria have undertaken the collection of qualitative data through discussion groups and semi-structured interviewing with small farmers. The sample was stratified, rather than random so that a diverse group of people involved in a range of different land management practices, time spent on their land, and various locations within the north-east. To date, only preliminary data analysis has been conducted, however, there have been some broad trends developing within this level of analysis.

As the small farm sector relies on off-farm income, there is less emphasis on money being produced from the farm this inturn influence the goals and aspirations of the small farm sector. Following on from the preliminary work of Hollier et al. (2001) the data suggests that there has been a renaissance of rural life in Australia as people begin to seek the ‘rural lifestyle’. Out of all people interviewed the decisions for living on a rural property were strongly influenced by the lifestyle offered in the country setting. Responses ranged from the alternative opportunities offered by living in a regional setting such as growing ‘natural’ and or organic food, generating some income off the property, as a self actualisation activity, and or the natural beauty and serenity offered in regional settings.

Discussion

Reflections on the data

There are limitations with the socio-economic data in that it only records enterprises within an EVAO between $5,000 - $75,000. This does not account for the land managers within the sector whom do not generate an income off the property. The research currently being conducted in the pilot region indicates that the numbers of small landowners could be much higher than captured by the statical data. Unfortunately to date there are no figures which accurately measure the sector, however, there is some interest in developing a national and more accurate definition of small farms which will include the smaller lifestyle land manager (Colman et al. 2000). Although the figures used in this research may not capture the lifestyle end of the market, they do provide a useful starting point for the research team to begin to understand the locations of the sector.

Implications for extension

The information provided through GIS mapping provides an indication of the possible ecological problems facing the small farm sector. Areas of high rainfall and high elevation are not only correlated with small farm presence, but have been identified as regions with high soil acidity, prone to water and gully erosion, and make a significant contribution to ground water recharge (DPI 2003). In addition, due to the diverse flora and fauna species associated with these climatic regions, it has been identified as an area with high biodiversity significance (NHT 2002). This needs to be considered when designing and implementing extension packages. It is recognised that the ecological problems facing the sector as mapped are broadly based, whilst more detailed mapping will provide more specific data within particular regional catchments.

The technical information for resolving the environmental problems prone to these locations (soil acidity, erosion, ground water recharge and threats on biodiversity) is relatively easily accessible. However, previous extension research has found that access to information is not enough to change land management behaviour (Rolling et al. 1998; Vanclay 1992; Veldhuizen 1997). Pretty (2002) has argued that sustainability should be seen as a process of social learning focused on building the capacity of land managers and their communities. There is a growing body of literature (Vanclay & Lawrence 1995; Pretty 2002; Becker et al. 1999 & Roling et al. 1998) that suggests that understanding the social context of agriculture, focusing on social learning and community capacity building of land managers and their communities, within a conducive political framework, is the process towards a more sustainable agriculture. To ensure practice change within the small farm sector the provision and access of technical information needs to be followed up by facilitation within locally specific systems (Roling et al. 1998). In addition, previous research has argued that farmers are more unlikely to adopt conservation practices on their property, but rather production orientated innovation practices (Vanclay & Lawrence 1995). In the context of the small farm sector this may not necessarily be the case. The preliminary qualitative data analysis has indicated that particular small farmers have strong environmental and land stewardship ethics, with goals and aspirations not inclined to production enterprises.

The research presented here has concentrated on quantifying broad natural and social characteristics into number systems for data analysis, with some preliminary qualitative data. It is important to remember that people, with various cultures, sub-cultures, practices and norms (Furze et al. 1997; Vanclay & Lawrence 1995) populate the landscape. As well as policies and social institutions having an indirect effect, it is these social phenomena which ultimately impact on the land (Roling et al. 1998). The diversity and richness of humans cannot be captured or reduced to figures. Quantifying the broad characteristics of the sector is important to the research process in creating a holistic conceptual framework for the project. However, for an understanding to be developed, research needs to ground the conceptual framework and by talking to the important people; small farmers and extension providers. This type of information, when gathered and interpreted through a sociological perspective will be able to inform extension agencies and providers to help them engage the small farm sector. Mapping serves as a useful tool within the social sciences but is not an end in itself.

There are many opportunities for further integration of GIS and qualitative research. Future research with GIS and qualitative data could involve using more detailed and specific bio-physical layers (eg weed locations) to examine other correlations with small farm locations. There is also an opportunity to perform cross analysis on qualitative data and bio-physical data. An example being of how farmers respond to a weed management program across two differing regions, one mapped with high weed populations and another mapped with a low weed population. There has been some work undertaken on the fusion of geo-spatial data, generated in ArcView, with qualitative data, analysed in

N-Vivo, in the United States (Durrant 2003).

Conclusion

GIS has the potential to be a valuable tool to inform extension when integrated with social research. It also offers the opportunity for a relationship to be constructed between the bio-physical component of landscapes and the social component of farming. Qualitative research focusing on people’s experiences, opinions, feelings, knowledge and behaviours can both enhance, and be enhanced by, connection to and integration with GIS mapping. The generation of information on both the bio-physical and ‘human’ components of farming is essential to improve understanding of the sector and to inform extension agencies and extension providers with designing and implementing programs to cater for sector. Areas of high percentages of small farms are correlated with regions of high rainfall and high elevation. From these locations, environmental problems that may be facing the sector can be inferred. It is important that extension providers and agencies recognise these issues and begin to actively engage the sector in extension programs.

Acknowledgments

The authors of this paper would like to acknowledge the Rural Industry Research and Development Corporation (RIRDC) and the Victorian State Government for the funding of this research. The views expressed and the conclusions reached in this publication are those of the authors and not necessarily those of RIRDC or the Victorian State Government.

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¹ The paper has adopted this definition due to the constraints imposed by the socio-economic data. See discussion for further information.

² The features on a map reference the actual locations of the objects they represent in the real world. The positions of objects on the earth's spherical surface are measured in geographical coordinates. To overcome measurement difficulties, data is often transformed from three-dimensional geographic coordinates to two-dimensional projections.

³ The Australian Bureau of Statistics (ABS) uses the data collected within its Farm Census to create a measure of farm size called Estimated Value of Agricultural Operations. The resulting constructed measure is a proxy for the gross farm income.