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Seeking simultaneous improvements in farm profit and natural resource indicators: a modelling analysis

2009; CSIRO Publishing; Volume: 49; Issue: 10 Linguagem: Inglês

10.1071/an09008

1836-5787

M. J. Robertson, Andrew D. Bathgate, Andrew D. Moore, Roger Lawes, Julianne M. Lilley,

Agricultural Economics and Policy

Natural resource indicators are used by catchment management organisations as targets for land use management. However, the nature of the trade-off function between natural resource management (NRM) outcomes and whole-farm profit is ill-defined, and varies between regions and according to the particular NRM indicator considered. Defining this function will assist catchment management organisations and farmers to evaluate the achievability of particular targets, and help determine the size of economic incentives required to offset any expected loss in farm profit associated with meeting targets. We addressed this issue by modelling representative farm businesses in two mixed farming regions (southern New South Wales and the central wheatbelt of Western Australia). The Agricultural Production Systems Simulator (APSIM) and GRAZPLAN farming systems models were linked and used to generate values of four NRM indicators (water leakage, nitrate leaching, groundcover and soil organic carbon change) for a wide range of crop–pasture rotations. The NRM indicator values were then incorporated into the Model of an Integrated Dryland System (MIDAS) whole-farm economic model to define the relationship with farm profit and farm cropping percentage. For some circumstances and indicators, the resulting trade-off functions were relatively flat; a wide range of enterprise mixes can lead to the same NRM outcomes but significant gains in the indicators may not be possible using current rotation options. For others, significant improvements could be achieved but at a substantial loss in whole-farm profit (through the selection of less profitable rotations). There were also examples where simultaneous gains in indicators and farm profit were possible. This analysis demonstrates an approach by which biophysical simulation models of the farming system can be linked to linear-programming representations of farming enterprises, and provides a method for deriving relationships between NRM targets and economic performance.