Australian Natural Resources Atlas

Natural Resource Topics

People - Future structure of agriculture & catchment communities

Future structure of agriculture & catchment communities

The long term nature of required change

The control of dryland salinity should focus our attention on the future structure of rural landscapes. Dryland salinity poses some serious challenges for natural resource policy. In many parts of the landscape, stabilising of watertables would require significant changes to the landscape. In the Kamarooka region of Victoria, watertable stability requires a significant increase in the area of lucerne and a decrease in the area of crop and annual pastures (Hekmeijer et al. 2001; Short et al. 2001). This change may be conceivable within current farming systems and economic structures (Read Sturgess and Associates 2001a; Read Sturgess and Associates 2001b). Watertable stability will only be achieved in other regions at the cost of a major change in the use of the landscape based upon broadscale increases n tree cover (Baker et al. 2001; Stauffacher et al. 2001). These changes are clearly not within the capacity of the existing community and its resources (Read Sturgess and Associates 2000). It is easy to conclude they are not in the interests of the existing catchment community. Major changes in catchment landscape will always be redistributive, having significant social impacts. There may be major social costs. Policies to implement these changes would need to be gradual in their application. Even if, as a nation, we are able to achieve such landscape changes, there will be a lag of between fifty and several hundred years between implementation and observable outcomes.

Some extremely important implications can be drawn from these characteristics of the salinity policy challenge. If we choose to follow a path of investment in salinity control through landscape change, then we are seeking outcomes not for the current generation, but for future generations. We may need to ask ourselves what aspects of the landscape are these future generations most likely to value? What social or environmental costs are likely to be of most concern to them?

Any decision to implement significant changes to the landscape will only be achieved with policies which generate changes in land management over a long period of time. Policies aimed to change landholder behaviour will need to be designed not only for landholders of the present, but the likely landholders of the future. This raises the question of whether future landholders will have the capacity or incentive to respond to the signals or incentives which are relevant to todayÕs landholders? We need to ask whether we are planning just for the current social and economic landscape of our catchments. Rural Australia is experiencing significant structural change. This is rapidly changing the character of some rural areas and the agricultural industries that inhabit them. The social and economic landscapes will be changed by financial and social forces long before the policies we start to implement will have an impact on watertables.

Any long term commitment to salinity control should presuppose a capacity to predict the future social and economic landscape with some degree of confidence. While predicting the future is fraught with difficulty, the least that can be done is to understand the current pressures for change in rural Australia and use this understanding to plan catchment strategies. It is important to be aware of the contemporary social and economic forces at work in this landscape, the trends underway and the implications of these trends for the catchment landscape. In the following sections we briefly review some of the factors which may catalyse significant change in the structure of rural Australian landscapes over the period of time we would need to stabilise watertables by landscape change, should we choose to embark on this course.

Of course, demographic change within rural catchments has implications well beyond natural resource management. Increasing farmer age in agricultural landscapes has generated concern across the developed world. In the agricultural regions of the United States the changing age profile of farm communities is being driven by much the same processes as in Australia. Prolonged out-migration of young families is leading to high proportions of elderly (Gale 2000b; Rathge & Highman 1998). This disproportionate rural ageing is leading to concerns about the viability of local communities (Glasgow 2000; Rogers 1999). Whilst Australian regions have a lower dependence upon local taxes to provide health and welfare services, and the rate of ageing in Australian farm areas is lower than that in the USA, Canada, Europe or Japan, there is still concern at the implications for Australian rural society. One estimate is that by 2026 18% of the population of capital cities will be over 65, compared with 25 per cent of the rural population (Alston 2000). There will be significant implications for services in rural towns which will make greater demands upon aged care service delivery (Frencken 2000; Rogers 1999).

Building a model of farm demographics

The analysis of census data reported in this publication provides an opportunity to develop some scenarios of demographic change on farms based upon observed behaviour during the period 1986 to 1996. Our scenarios of demographic change are based upon observed levels of entry and exit from farming within each Local Government Area across Australia. A simple stock and flow model was created with farmers allocated in 5-year age cohorts using 1996 population data. Age cohorts ranged from a minium of 15 to 19 years to a maximum age cohort of 80 years or more.

It is assumed that the patterns of exit for each age group remain fixed over time. That is, a cohort of farmers within a Statistical Local Area who are aged 35 to 39 in 1996 will have similar exit patterns in 2006 to that displayed by farmers aged 45-49 in that same Statistical Local Area in 1996.

Entry to farming is assumed to be mediated by the rate of exit from farming. If there is no exit from farming, then there will be no farms available for entry. This simplifying assumption overlooks the potential for new farms to be created by major agricultural developments. The rate of entry is based upon past ratios of new entrants to exiting farmers. If the past rate of entry to farming was 50 per cent of the number of exits, then this rate of entry is assumed into the future. The projected number of entrants is then allocated to each age cohort according to past relative rates of entry of each age group.

In Statistical Local Areas where low counts of farmers lead to unreliable estimates of exit or entry rates, entry and exit rates are substituted using the rates calculated for the Statistical Sub-Division in which the relevant Statistical Local Area is located. In the rare case where this still leads to unreliable estimates, rates are substituted from the relevant Statistical Division. Median ages are calculated from the projected age distribution using assumptions of uniform distribution within each age cohort. The model is calculated until 2020.

Low adjustment and high adjustment scenarios

The evidence of previous sections shows us that demographic structure of the farm community in only one of the important factors influencing the rate of structural change. Other major factors are commodity prices and demographic structure of the wider community.

During the period 1986-96 the impact of late age entry to farming was limited in scale and in location to Statistical Local Areas around some regional centres and along the coast of eastern and south west Australia. From 2001 the first of the age cohort of baby boomers will reach age 55 years. Those born in 1946 will have reached 55 years of age, and have passed the age of compulsory preservation of their superannuation. The baby boomers will pass into retirement at an increasing rate over the following 15 years. By the 2016 census, the 1950 birth year cohort will have passed 65 years of age. It is possible there will be increased rates of early retirement entry to farming during this period. Whether this will be into grazing, or small-scale vineyards we will have to wait and see. The impact of baby boomer retirement has not been modelled.

An even greater impact on adjustment rates is change in commodity prices. Stable and high commodity prices are associated with an increased rate of exit from farming as more potential exiters take the opportunity to realise a higher price on the sale of their property. The period 1986-96 provides us with data from two inter-censal periods. The first of these was characterised by a period of higher commodity prices in the grazing industries, and was also characterised by higher rates of exit and farm consolidation. The second inter-censal period was a time of lower commodity prices for the major grazing industries and of relatively low rates of exit from farming. These two inter-censal periods provide data for testing low adjustment and high adjustment scenarios on the demographic model.

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