Modelling profitable and sustainable farming systems in Central Queensland
Central Queensland’s dryland farming systems are subject to high levels of climatic variability, are seen as being relatively risky and also suffering falling profitability due (in part) to the rapid decline of nutrient content and physical structure of soils. This suggests that many farming practices in Central Queensland are not sustainable. A multi agency project that uses participatory on-farm research and development processes has been addressing the core issues that contribute to more sustainable and profitable farming systems in Central Queensland. A component of this research has been the enhancement of farming systems knowledge through combining relevant whole farm models with the biological model APSIM developed by the Agricultural Production Systems Research Unit (APSRU). The result of this simplified bio-economic modelling is that the profitability and sustainability of a range of farming systems has been simulated and evaluated over time and under varying environmental conditions. The suitability of this approach as a component of farming systems research aimed at changing farming practices is discussed.
|Date of creation:||Feb 2002|
|Contact details of provider:|| Postal: AARES Central Office Manager, Crawford School of Public Policy, ANU, Canberra ACT 0200|
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- Malcolm, Bill, 1990. "Fifty Years of Farm Management in Australia: Survey and Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 58(01), April.
- Pannell, David J., 1997.
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- Pannell, David J., 1996. "Sensitivity Analysis of Normative Economic Models: Theoretical Framework and Practical Strategies," 1996 Conference (40th), February 11-16, 1996, Melbourne, Australia 156444, Australian Agricultural and Resource Economics Society.
- Pannell, David J, 1996. "Sensitivity Analysis of Normative Economic Models: Theoretical Framework and Practical Strategies," Discussion Papers 232264, University of Western Australia, School of Agricultural and Resource Economics.
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