Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

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

Michael Robertson A D , Andrew Bathgate B , Andrew Moore C , Roger Lawes A and Julianne Lilley C
+ Author Affiliations
- Author Affiliations

A CSIRO Sustainable Ecosystems, PMB 5, PO Wembley, WA 6913, Australia.

B Farming Systems Analysis Service, 41 Trebor Road, Albany WA 6330, Australia.

C CSIRO Plant Industry, GPO Box 1600, Canberra, ACT 2061, Australia.

D Corresponding author. Email: michael.robertson@csiro.au

Animal Production Science 49(10) 826-836 https://doi.org/10.1071/AN09008
Submitted: 13 January 2009  Accepted: 25 April 2009   Published: 16 September 2009

Abstract

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.

Additional keywords: APSIM, GRAZPLAN, groundcover leakage, nitrate leaching, profit, soil organic carbon.


Acknowledgements

This work was carried out as part of the Grain & Graze program of research, development and extension; joint funding from Meat and Livestock Australia, the Grains Research and Development Corporation, Australian Wool Innovation, and Land and Water Australia is gratefully acknowledged. The authors thank Lindsay Bell and David Pannell for constructive comments on an earlier draft.


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