Register      Login
Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
Shopping Cart: ( empty )
You are here: Home > Journals > AN > AN23407
RESEARCH ARTICLE (Open Access)
Contents Vol 64(7)

Identifying high-value tactical livestock decisions on a mixed enterprise farm in a variable environment

Michael Young https://orcid.org/0000-0002-6072-5439 A B * , John Young https://orcid.org/0009-0009-5557-5585 C , Ross S. Kingwell https://orcid.org/0000-0003-0324-9488 A D E and Philip E. Vercoe https://orcid.org/0000-0002-3061-1908 A B
+ Author Affiliations
- Author Affiliations

A School of Agriculture and Environment, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia.

B Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia.

C Farming Systems Analysis Service, Kentdale, WA, Australia.

D Australian Export Grains Innovation Centre, South Perth, WA, Australia.

E Department of Primary Industries and Regional Development, South Perth, WA, Australia.

* Correspondence to: youngmr44@gmail.com

Handling Editor: Dean Thomas

Animal Production Science 64, AN23407 https://doi.org/10.1071/AN23407
Submitted: 18 December 2023  Accepted: 15 April 2024  Published: 3 May 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY)

Abstract

Context

Australia is renowned for its climate variation, featuring years with drought and years with floods, which result in significant production and profit variability. Accordingly, to maximise profitability, dryland farming systems need to be dynamically managed in response to unfolding weather conditions.

Aims

The aim of this study is to identify and quantify optimal tactical livestock management for different weather-years.

Methods

This study employed a whole-farm optimisation model to analyse a representative mixed enterprise farm located in the Great Southern region of Western Australia. Using this model, we investigated the economic significance of five key livestock management tactics. These included timing of sheep sales, pasture-area adjustments, rotational grazing, crop grazing and sheep nutrition adjustments.

Key results

The results showed that, on the modelled dryland mixed-enterprise farm in the Great Southern region of Western Australia, short-term adjustments to the overall farm strategy in response to unfolding weather conditions increased expected profit by approximately 16%. Each tactic boosted profit by between A$7704 and A$53,171. However, we outline several complexities that farmers must consider when implementing tactics.

Conclusions

The financial gains from short-term tactical management highlighted their importance and farmers’ need to develop and apply those skills. The tactical skills promote business resilience and adaptability in the face of climate uncertainties.

Implications

The study highlighted the economic value of dynamic livestock management in response to climate variations, offering farmers in the Great Southern region the means to underpin profitable and sustainable farm practices.

Keywords: AFO, Australian Farm Optimisation Model, discrete stochastic programming, economic optimisation modelling, farming systems, sheep management, tactical farm management, weather variability.

References

Abrecht DG, Robinson SD (1996) TACT: a tactical decision aid using a CERES based wheat simulation model. Ecological Modelling 86, 241-244.
| Crossref | Google Scholar |

Anderson WK, Brennan RF, Jayasena KW, Micic S, Moore JH, Nordblom T (2020) Tactical crop management for improved productivity in winter-dominant rainfall regions: a review. Crop and Pasture Science 71, 621-644.
| Crossref | Google Scholar |

Azam-Ali S (2007) Agricultural diversification: the potential for underutilised crops in Africa’s changing climates. Rivista di Biologia/Biology Forum 100, 27-28.
| Google Scholar |

Bathgate A, Revell C, Kingwell R (2009) Identifying the value of pasture improvement using wholefarm modelling. Agricultural Systems 102, 48-57.
| Crossref | Google Scholar |

Chen W, Bell RW, Brennan RF, Bowden JW, Dobermann A, Rengel Z, Porter W (2009) Key crop nutrient management issues in the Western Australia grains industry: a review. Soil Research 47, 1-18.
| Crossref | Google Scholar |

Cowan L, Kaine G, Wright V (2013) The role of strategic and tactical flexibility in managing input variability on farms. Systems Research and Behavioral Science 30, 470-494.
| Crossref | Google Scholar |

Dalgliesh N, Cocks B, Horan H (2012) APSoil-providing soils information to consultants, farmers and researchers. In ‘16th Australian Agronomy Conference, Armidale’, NSW, 2012.

Doole GJ, Weetman E (2009) Tactical management of pasture fallows in Western Australian cropping systems. Agricultural Systems 102, 24-32.
| Crossref | Google Scholar |

Feng P, Wang B, Macadam I, Taschetto AS, Abram NJ, Luo J-J, King AD, Chen Y, Li Y, Liu DL, Yu Q, Hu K (2022) Increasing dominance of Indian Ocean variability impacts Australian wheat yields. Nature Food 3, 862-870.
| Crossref | Google Scholar |

Godfrey S, Nordblom T, Ip R, Robertson S, Hutchings T (2019) Using GrassGro® with@ RISK® Merino ewe/first-cross lamb enterprise risk profiles with variable prices and weather. In ‘Annual Conference of the Australasian Agricultural and Resource Economics Society’.

Heberger M (2011) Australia’s millennium drought: impacts and responses. In ‘The world’s water’. (Ed. PH Gleick) pp. 97–125. (Island Press)

Kandulu JM, Bryan BA, King D, Connor JD (2012) Mitigating economic risk from climate variability in rain-fed agriculture through enterprise mix diversification. Ecological Economics 79, 105-112.
| Crossref | Google Scholar |

Kingwell R (2011) Managing complexity in modern farming. Australian Journal of Agricultural and Resource Economics 55, 12-34.
| Crossref | Google Scholar |

Kingwell R, Pannell D (1987) ‘MIDAS, a bioeconomic model of a dryland farming system.’ (PUDOC)

Kingwell RS, Pannell DJ, Robinson SD (1993) Tactical responses to seasonal conditions in whole-farm planning in Western Australia. Agricultural Economics 8, 211-226.
| Crossref | Google 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 | Google Scholar |

Laurie A, Curtis M, Heath R, Mcrobert K, Darragh L (2019) ‘Australian agriculture: an increasingly risky business.’ (Australian Farm Institute)

McGrath S, Virgona J, Allworth B (2016) The cost of hitting lifetime ewe targets in scanned and unscanned Merino flocks-a simulation using a dynamic model, AusFarm. In ‘2016 Graham Centre Sheep Forum’. pp. 22–26.

Meat and Livestock Australia (2022) 7.6 million lambs to hit the market this spring. Available at https://www.mla.com.au/news-and-events/industry-news/7.6-million-lambs-to-hit-the-market-this-spring/#:~:text=The%20largest%20breeding%20ewe%20population,NSW%20at%204.8%20million%20head [accessed January 2023]

Mecardo (2023) Percentiles – April 2023. Available at https://mecardo.com.au/percentiles-april-2023/ [accessed January 2023]

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 | Google Scholar |

O’Connell M, Young J, Kingwell R (2006) The economic value of saltland pastures in a mixed farming system in Western Australia. Agricultural Systems 89, 371-389.
| Crossref | Google Scholar |

Pannell DJ (1996) Lessons from a decade of whole-farm modeling in Western Australia. Applied Economic Perspectives and Policy 18, 373-383.
| Crossref | Google Scholar |

Pannell DJ, Malcolm B, Kingwell RS (2000) Are we risking too much? Perspectives on risk in farm modelling. Agricultural Economics 23, 69-78.
| Google Scholar |

Planfarm/BankWest (2019) Planfarm Bankwest Benchmarks: 2018-2019. Available at https://static1.squarespace.com/static/5cd3c30baf468328f012b132/t/5d522fec77ab8300016a097b/1565667337641/Planfarm+Benchmarks+2018-2019.pdf [accessed January 2023]

Poole ML, Turner NC, Young JM (2002) Sustainable cropping systems for high rainfall areas of southwestern Australia. Agricultural Water Management 53, 201-211.
| Crossref | Google Scholar |

Thamo T, Kingwell RS, Pannell DJ (2013) Measurement of greenhouse gas emissions from agriculture: economic implications for policy and agricultural producers. Australian Journal of Agricultural and Resource Economics 57, 234-252.
| Crossref | Google Scholar |

Trompf J, Young J, Ferguson M, Anderson G, Tocker J, Vogt S, Herbert A, Ritchie A, Hill J, Thompson A (2014) ‘More lambs more often – bullet proofing your business against variable seasons.’ (Rural Industries Skill Training: Hamilton, Vic., Australia)

Young J (1995) ‘MIDAS: model and documentation for the Great Southern Model (version GSM92-3).’ University of Western Australia, Nedlands, Western Australia.

Young JM, Thompson AN, Kennedy AJ (2010) Bioeconomic modelling to identify the relative importance of a range of critical control points for prime lamb production systems in south-west Victoria. Animal Production Science 50, 748-756.
| Crossref | Google Scholar |

Young JM, Thompson AN, Curnow M, Oldham CM (2011) Whole-farm profit and the optimum maternal liveweight profile of Merino ewe flocks lambing in winter and spring are influenced by the effects of ewe nutrition on the progeny’s survival and lifetime wool production. Animal Production Science 51, 821-833.
| Crossref | Google Scholar |

Young M, Kingwell R, Young J, Vercoe P (2020) An economic analysis of sheep flock structures for mixed enterprise Australian farm businesses. Australian Journal of Agricultural and Resource Economics 64, 677-699.
| Crossref | Google Scholar |

Young M, Vercoe PE, Kingwell RS (2022) Optimal sheep stocking rates for broad-acre farm businesses in Western Australia: a review. Animal Production Science 62, 803-817.
| Crossref | Google Scholar |

Young M, Young J, Kingwell R, Vercoe P (2023a) Improved whole-farm planning for mixed-enterprise systems in Australia using a four-stage stochastic model with recourse. Australian Farm Business Management 20, 1.
| Google Scholar |

Young M, Young J, Kingwell RS, Vercoe PE (2023b) Representing weather-year variation in whole-farm optimisation models: four-stage single-sequence vs eight-stage multi-sequence. Australian Journal of Agricultural and Resource Economics 68, 44-59.
| Crossref | Google Scholar |