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 CA 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.
Byrne F,
Bathgate A,
Robertson MJ, Hoque Z
(2008) Economic prospects for lucerne in farming systems in Southern and Western Australia. Australasian Agribusiness Review in press. ,
[Verified 20 July 2009]
Findlater PA,
Carter DJ, Scott WD
(1990) A model to predict the effects of prostrate ground cover on wind erosion. Australian Journal of Soil Research 28, 609–622.
| Crossref | GoogleScholarGoogle Scholar |
Freer M,
Moore DA, Donnelly JR
(1997) GRAZPLAN: decision support systems for Australian grazing enterprises II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS. Agricultural Systems 54, 77–126.
| Crossref | GoogleScholarGoogle Scholar |
Keating BA,
Carberry PS,
Hammer GL,
Probert ME, Robertson MJ ,
et al
.
(2003) An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18, 267–288.
| Crossref | GoogleScholarGoogle Scholar |
Kopke E,
Young J, Kingwell R
(2008) The relative profitability and environmental impacts of different sheep systems in a Mediterranean environment. Agricultural Systems 96, 85–94.
| Crossref | GoogleScholarGoogle Scholar |
Meyer-Aurich A
(2005) Economic and environmental analysis of sustainable farming practices – a Bavarian case study. Agricultural Systems 86, 190–206.
| Crossref | GoogleScholarGoogle Scholar |
Moore AD,
Donnelly JR, Freer M
(1997) GRAZPLAN: decision support systems for Australian grazing enterprises III. Growth and soil moisture submodels, and the GrassGro DSS. Agricultural Systems 55, 535–582.
| Crossref | GoogleScholarGoogle Scholar |
Moore AD,
Holzworth DP,
Herrmann NI,
Huth NI, Robertson MJ
(2007) The common modelling protocol: a hierarchical framework for simulation of agricultural and environmental systems. Agricultural Systems 95, 37–48.
| Crossref | GoogleScholarGoogle Scholar |
Moore AD,
Bell LW, Revell DK
(2009) Feed gaps in mixed-farming systems: insights from the Grain & Graze program. Animal Production Science 49, 736–748.
| Crossref | GoogleScholarGoogle Scholar |
Pannell DJ
(1997) Sensitivity analysis of normative economic models: theoretical framework and practical strategies. Agricultural Economics 16, 139–152.
| Crossref | GoogleScholarGoogle Scholar |
Pannell DJ, Glenn NA
(1999) A framework for economic evaluation and selection of sustainability indicators in agriculture. Ecological Economics 33, 135–149.
| Crossref | GoogleScholarGoogle Scholar |
Pannell DJ,
Marshall GR,
Barr N,
Curtis A,
Vanclay F, Wilkinson R
(2006) Understanding and promoting adoption of conservation practices by rural landholders. Australian Journal of Experimental Agriculture 46, 1407–1424.
| Crossref | GoogleScholarGoogle Scholar |
Probert ME,
Dimes JP,
Keating BA,
Dalal RC, Strong WM
(1998) APSIM’s water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems. Agricultural Systems 56, 1–28.
| Crossref | GoogleScholarGoogle Scholar |
Reuter DJ
(1998) Developing indicators for monitoring catchment health: the challenge. Australian Journal of Experimental Agriculture 38, 637–648.
| Crossref | GoogleScholarGoogle Scholar |
Robertson MJ,
Carberry PS,
Huth NI,
Turpin JE,
Probert ME,
Poulton PL,
Bell M,
Wright GC,
Yeates SJ, Brinsmead RB
(2002) Simulation of growth and development of diverse legume species in APSIM. Australian Journal of Agricultural Research 53, 429–446.
| Crossref | GoogleScholarGoogle Scholar |
Russelle MP,
Entz MH, Franzluebbers AJ
(2007) Reconsidering integrated crop-livestock systems in North America. Agronomy Journal 99, 325–334.
| Crossref | GoogleScholarGoogle Scholar |
Sattler C,
Schuler J, Zander P
(2006) Determination of trade-off functions to analyse the provision of agricultural non-commodities. International Journal of Agricultural Resources, Governance and Ecology 5, 309–325.
Schwenke GD,
Reuter DJ,
Fitzpatrick RW,
Walker J, O’Callaghan PO
(2003) Soil and catchment health indicators of sustainability: case studies from southern Australia and possibilities for the northern grains region of Australia. Australian Journal of Experimental Agriculture 43, 205–222.
| Crossref | GoogleScholarGoogle Scholar |
Stoorvogel JJ,
Antle JM,
Crissman CC, Bowen W
(2004) The tradeoff analysis model: integrated biophysical and economic modelling of agricultural production systems. Agricultural Systems 80, 43–66.
| Crossref | GoogleScholarGoogle Scholar |
van Calker KJ,
Berentson PBM,
de Boer IMJ,
Giesen GWJ, Huirne RBM
(2004) An LP-model to analyse economic and ecological sustainability on Dutch dairy farms: model presentation and application for experimental farm “de Marke”. Agricultural Systems 82, 139–160.
| Crossref | GoogleScholarGoogle Scholar |
van de Ven GWJ, van Keulen H
(2007) A mathematical approach to comparing environmental and economic goals in dairy farming: Identifying strategic development options. Agricultural Systems 94, 231–246.
| Crossref | GoogleScholarGoogle Scholar |
Wang E,
Robertson MJ,
Hammer GL,
Carberry PS,
Holzworth D,
Meinke H,
Chapman SC,
Hargreaves JNG,
Huth NI, McLean G
(2002) Development of a generic crop model template in the cropping system model APSIM. European Journal of Agronomy 18, 121–140.
| Crossref | GoogleScholarGoogle Scholar |
Weersink A,
Jeffrey S, Pannell D
(2002) Farm-level modelling for bigger issues. Review of Agricultural Economics 24, 123–140.
| Crossref | GoogleScholarGoogle Scholar |
