Regional differences in beef cattle trade and movements associated with the COVID-19 pandemic in Australia

Joshua Aboah; Peggy Schrobback; Stephen McFallan; Dianne Mayberry

doi:10.1071/AN23402

RESEARCH ARTICLE (Open Access)

Previous Contents Vol 64(14)

Regional differences in beef cattle trade and movements associated with the COVID-19 pandemic in Australia

Joshua Aboah

^A ^* , Peggy Schrobback ^A , Stephen McFallan ^B and Dianne Mayberry

^A

+ Author Affiliations

- Author Affiliations

^A Commonwealth Scientific and Industrial Research Organisation, Agriculture & Food, 306 Carmody Road, St Lucia, Qld 4067, Australia.

^B Commonwealth Scientific and Industrial Research Organisation, Environment, 41 Boggo Road, Dutton Park, Qld 4102, Australia.

^* Correspondence to: joshua.aboah@csiro.au

Handling Editor: Ed Charmley

Animal Production Science 64, AN23402 https://doi.org/10.1071/AN23402

Submitted: 7 December 2023 Accepted: 16 August 2024 Published: 9 September 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-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

The COVID-19 pandemic caused mandated restrictions on movements and distancing of people with implications for meat supply chains. Despite the COVID restrictions, agricultural activities were permitted to continue as essential services in Australia. However, there were reported shortages of meat on the shelves of supermarkets and a general increase in the price of meat in Australia during the COVID period. Hence, there is a need to establish whether the restrictions affected upstream activities in Australia’s beef supply chain.

Aim

This study aims to examine the impact of the COVID-19 pandemic and confounding factors including rainfall and export bans on beef cattle trade and movement in Australia.

Methods

Using annual data on beef cattle sold, purchased, transferred off-farm and transferred onto farms sourced from the database of the Australian Bureau of Agricultural and Resource Economics and Sciences, a t-test analysis was conducted to establish the significant changes in cattle movement and trade for the pre-COVID (2014–2019) and COVID (2020–2022) periods. Additionally, a flexible least squares model augmented with a flexible generalised least squares model was used to assess the impact of confounding factors on cattle trade and movement.

Key results

The results indicate no significant change in the proportion of beef cattle sold nationwide. Tasmania, New South Wales, and Western Australia (WA) recorded significant changes (1.4% increase, 3.6% increase, and 3.8% decrease, respectively) in the proportion of beef cattle purchased. For WA, these changes were localised to changes that occurred in WA Central and Southern Wheat Belt and WA Southwest Coastal regions. Moreover, rainfall did not significantly impact cattle trade but did affect cattle movements. The export ban only significantly impacted beef cattle sold in Queensland.

Conclusions

Overall, the findings suggest that most regions in Australia did not experience significant changes in farm-level decisions regarding beef cattle movement and trade during the COVID period. Instead, minor adjustments were made to address the demand changes.

Implications

The findings imply that adopted policies that facilitated the implementation of biosecurity bubbles and the movements of animal transport workers for breeding facilities and abattoirs during the COVID period were effective in normalising farm-level operations.

Keywords: abattoir, beef cattle, biosecurity, COVID-19, farm decisions, food chains, food security, meat works, trade.

References

ABARES (2023) Farm Data Portal Beta v1.21. Australian Bureau of Agricultural and Resource Economics and Sciences. Available at https://www.agriculture.gov.au/abares/data/farm-data-portal#data-definitions-concepts-and-methods [accessed 11 July 2023]

Baptista J, Blache D, Cox-Witton K, Craddock N, Dalziel T, De Graaff N, Fernandes J, Green R, Jenkins H, Kahn S, Kelly D, Lauber M, Maloney SK, Peachey B, Rodger I, Skuse J, Tilbrook AJ, Walker FR, Wall K, Zito S (2021) Impact of the COVID-19 pandemic on the welfare of animals in Australia. Frontiers in Veterinary Science 7, 621843.
| Crossref | Google Scholar | PubMed |

Bennett CJ, Christian M, Phan S, McCabe M, Cornish K, Kleve S (2022) Food insecurity during COVID-19: an Australian university experience. Health & Social Care in the Community 30(6), e5401-e5411.
| Crossref | Google Scholar |

BoM (2024) Climate data. Australian Bureau of Meteorology. Available at http://www.bom.gov.au/cgi-bin/climate/change/timeseries.cgi?graph=rranom&area=wa&season=0112&ave_yr=A

Bowen MK, Chudleigh F (2021) Achieving drought resilience in the grazing lands of northern Australia: preparing, responding and recovering. The Rangeland Journal 43(3), 67-76.
| Crossref | Google Scholar |

Bowen MK, Chudleigh F, Sallur NM, Sommerfield J (2022) Opportunities to build resilience of beef cattle properties in the mulga lands of south-western Queensland, Australia. The Rangeland Journal 44(2), 115-128.
| Crossref | Google Scholar |

Brennan ML, Christley RM (2012) Biosecurity on cattle farms: a study in north-west England. PLoS ONE 7(1), e28139.
| Crossref | Google Scholar | PubMed |

Bucci N (2020) Meatworks and coronavirus: the ‘domino effect’ from Victoria’s abattoirs pushing COVID-19 case numbers higher. ABC News 26 July. Available at https://www.abc.net.au/news/2020-07-26/coronavirus-covid-19-meatworks-abattoirs-victoria/12490178.
| Google Scholar |

Christianson MK, Barton MA (2021) Sensemaking in the time of COVID-19. Journal of Management Studies 58(2), 572-576.
| Crossref | Google Scholar |

Cobon DH, Stone G, Carter J, McKeon G, Zhang B, Heidemann H (2020) Native pastures and beef cattle show a spatially variable response to a changing climate in Queensland, Australia. European Journal of Agronomy 114, 126002.
| Crossref | Google Scholar |

Cowan T, Wheeler MC, Alves O, Narsey S, de Burgh-Day C, Griffiths M, Jarvis C, Cobon DH, Hawcroft MK (2019) Forecasting the extreme rainfall, low temperatures, and strong winds associated with the northern Queensland floods of February 2019. Weather and Climate Extremes 26, 100232.
| Crossref | Google Scholar |

Edwards-Jones G (2006) Modelling farmer decision-making: concepts, progress and challenges. Animal Science 82(6), 783-790.
| Crossref | Google Scholar |

Godde C, Dizyee K, Ash A, Thornton P, Sloat L, Roura E, Henderson B, Herrero M (2019) Climate change and variability impacts on grazing herds: insights from a system dynamics approach for semi-arid Australian rangelands. Global Change Biology 25(9), 3091-3109.
| Crossref | Google Scholar |

Godrich SL, Lo J, Kent K, Macau F, Devine A (2022) A mixed-methods study to determine the impact of COVID-19 on food security, food access and supply in regional Australia for consumers and food supply stakeholders. Nutrition Journal 21, 17.
| Crossref | Google Scholar |

Grieger JA, Habibi N, O’Reilly SL, Harrison CL, Moran LJ, Vo H, Sabir S, Enticott J, Teede H, Siew Lim MND (2022) Psychological distress and its association with intake of sugar-sweetened beverages, discretionary foods, and alcohol in women during the COVID-19 pandemic in Australia. Nutrition 103, 111794.
| Crossref | Google Scholar |

Halter A (2024) Australian beef industry looks towards resuming China trade after COVID-19 bans. Available at https://www.abc.net.au/news/rural/2024-05-06/australian-beef-industry-looks-to-resume-trade-china-covid-bans/103794206

Hayden MT, Mattimoe R, Jack L (2021) Sensemaking and the influencing factors on farmer decision-making. Journal of Rural Studies 84, 31-44.
| Crossref | Google Scholar |

Hidano A, Gates MC (2019) Why sold, not culled? Analysing farm and animal characteristics associated with livestock selling practices. Preventive Veterinary Medicine 166, 65-77.
| Crossref | Google Scholar | PubMed |

Hidano A, Gates MC, Enticott G (2019) Farmers’ decision making on livestock trading practices: cowshed culture and behavioural triggers amongst New Zealand dairy farmers. Frontiers in Veterinary Science 6, 320.
| Crossref | Google Scholar | PubMed |

Hughes N, Lu M, Soh WY, Lawson K (2022) Modelling the effects of climate change on the profitability of Australian farms. Climatic Change 172(1), 12.
| Crossref | Google Scholar |

Iglesias RM, East IJ (2015) Cattle movement patterns in Australia: an analysis of the NLIS database 2008–2012. Australian Veterinary Journal 93(11), 394-403.
| Crossref | Google Scholar | PubMed |

Kalaba R, Tesfatsion L (1989) Time-varying linear regression via flexible least squares. Computers & Mathematics with Applications 17(8–9), 1215-1245.
| Crossref | Google Scholar |

Kent K, Murray S, Penrose B, Auckland S, Godrich S, Lester E, Visentin D (2022) Food insecure households faced greater challenges putting healthy food on the table during the COVID-19 pandemic in Australia. Appetite 169, 105815.
| Crossref | Google Scholar | PubMed |

Kibona CA, Yuejie Z (2021) Factors that influence market participation among traditional beef cattle farmers in the Meatu District of Simiyu Region, Tanzania. PLoS ONE 16(4), e0248576.
| Crossref | Google Scholar | PubMed |

Kleve S, Bennett CJ, Davidson ZE, Kellow NJ, McCaffrey TA, O’Reilly S, Enticott J, Moran LJ, Harrison CL, Teede H, Lim S (2021) Food insecurity prevalence, severity and determinants in Australian households during the COVID-19 pandemic from the perspective of women. Nutrients 13(12), 4262.
| Crossref | Google Scholar |

Lee AJ, Patay D, Herron L-M, Tan RC, Nicoll E, Fredericks B, Lewis M (2021) Affordability of heathy, equitable and more sustainable diets in low-income households in Brisbane before and during the COVID-19 pandemic. Nutrients 13(12), 4386.
| Crossref | Google Scholar | PubMed |

Lewis M, Herron L-M, Chatfield MD, Tan RC, Dale A, Nash S, Lee AJ (2023) Healthy food prices increased more than the prices of Unhealthy Options during the COVID-19 Pandemic and Concurrent Challenges to the Food System. International Journal of Environmental Research and Public Health 20(4), 3146.
| Crossref | Google Scholar | PubMed |

Louie S, Shi Y, Allman-Farinelli M (2022) The effects of the COVID-19 pandemic on food security in Australia: a scoping review. Nutrition & Dietetics 79(1), 28-47.
| Crossref | Google Scholar | PubMed |

Martin-Clouaire R (2017) Modelling operational decision-making in agriculture. Agricultural Sciences 8(7), 527-544.
| Crossref | Google Scholar |

Maye D, Chan KWR (2020) On-farm biosecurity in livestock production: farmer behaviour, cultural identities and practices of care. Emerging Topics in Life Sciences 4(5), 521-530.
| Crossref | Google Scholar | PubMed |

McKay FH, Bastian A, Lindberg R (2021) Exploring the response of the Victorian emergency and community food sector to the COVID-19 pandemic. Journal of Hunger & Environmental Nutrition 16(4), 447-461.
| Crossref | Google Scholar |

McKeon G, Stone G, Ahrens D, Carter J, Cobon D, Irvine S, Syktus J (2021) Queensland’s multi-year Wet and Dry periods: implications for grazing enterprises and pasture resources. The Rangeland Journal 43(3), 121-142.
| Crossref | Google Scholar |

Meat and Livestock Australia (2020) COVID-19 crisis sees surge in domestic retail demand. Available at https://www.mla.com.au/prices-markets/market-news/2020/covid-19-crisis-sees-surge-in-domestic-demand/ [accessed 21 September 2020]

Mihrshahi S, Dharmayani PNA, Amin J, Bhatti A, Chau JY, Ronto R, Turnip D, Taylor M (2022) Higher prevalence of food insecurity and psychological distress among international university students during the COVID-19 pandemic: an australian perspective. International Journal of Environmental Research and Public Health 19(21), 14101.
| Crossref | Google Scholar | PubMed |

MLA (2023) Price and Market Database. Meat and Livestock Authority. Available at https://www.mla.com.au/prices-markets/slaughter/ [accessed 11 July 2023]

Montana G, Triantafyllopoulos K, Tsagaris T (2009) Flexible least squares for temporal data mining and statistical arbitrage. Expert Systems with Applications 36(2), 2819-2830.
| Crossref | Google Scholar |

Murato Y, Hayama Y, Kondo S, Sawai K, Yamaguchi E, Yamamoto T (2023) Region-wise analysis of beef cow movements in Japan. Frontiers in Veterinary Science 10, 1012978.
| Crossref | Google Scholar | PubMed |

Murphy M, Carey R, Alexandra L (2023) Building the resilience of agri-food systems to compounding shocks and stresses: a case study from Melbourne, Australia. Frontiers in Sustainable Food Systems 7, 1130978.
| Crossref | Google Scholar |

Ogier EM, Smith DC, Breen S, Gardner C, Gaughan DJ, Gorfine HK, Hobday AJ, Moltschaniwskyj N, Murphy R, Saunders T, Steer M, Woodhams J (2023) Initial impacts of the COVID-19 pandemic on Australian fisheries production, research organisations and assessment: shocks, responses and implications for decision support and resilience. Reviews in Fish Biology and Fisheries 33(2), 513-534.
| Crossref | Google Scholar | PubMed |

Rahmani E, Khatami M, Stephens E (2024) Using probabilistic machine learning methods to improve beef cattle price modelling and promote beef production efficiency and sustainability in Canada. Sustainability 16(5), 1789.
| Crossref | Google Scholar |

Snow V, Rodriguez D, Dynes R, Kaye-Blake W, Mallawaarachchi T, Zydenbos S, Cong L, Obadovic I, Agnew R, Amery N, Bell L, Benson C, Clinton P, Fernanda Dreccer M, Dunningham A, Gleeson M, Harrison M, Hayward A, Holzworth D, Johnstone P, Meinke H, Mitter N, Mugera A, Pannell D, Silva LFP, Roura E, Siddharth P, Siddique KHM, Stevens D (2021) Resilience achieved via multiple compensating subsystems: the immediate impacts of COVID-19 control measures on the agri-food systems of Australia and New Zealand. Agricultural Systems 187, 103025.
| Crossref | Google Scholar |

Steele SG, Toribio JALML, Mor SM (2021) Global health security must embrace a One Health approach: contributions and experiences of veterinarians during the COVID-19 response in Australia. One Health 13, 100314.
| Crossref | Google Scholar | PubMed |

Sutherland L-A, Burton RJF, Ingram J, Blackstock K, Slee B, Gotts N (2012) Triggering change: towards a conceptualisation of major change processes in farm decision-making. Journal of Environmental Management 104, 142-151.
| Crossref | Google Scholar | PubMed |

Tomkins NW, O’Reagain PJ, Swain D, Bishop-Hurley G, Charmley E (2009) Determining the effect of stocking rate on the spatial distribution of cattle for the subtropical savannas. The Rangeland Journal 31(3), 267-276.
| Crossref | Google Scholar |

Vo LH, Martinus K, Smith B (2023) A demand systems approach to understanding medium-term post-pandemic consumption trends. Economic Papers: A Journal of Applied Economics and Policy 42, 183-199.
| Crossref | Google Scholar |

Whelan J, Brown AD, Coller L, Strugnell C, Allender S, Alston L, Hayward J, Brimblecombe J, Bell C (2021) The impact of COVID-19 on rural food supply and demand in Australia: utilising group model building to identify retailer and customer perspectives. Nutrients 13(2), 417.
| Crossref | Google Scholar | PubMed |

Windsor PA (2021) Progress with livestock welfare in extensive production systems: lessons from Australia. Frontiers in Veterinary Science 8, 674482.
| Crossref | Google Scholar |