Utilising bioeconomic modelling to examine the impact of lambing percentages and pre-weaning lamb growth rates on farm profitability : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Agricultural Science, School of Agriculture and Environment, Massey University, Manawatu, New Zealand
Since 1980, the production and sale of sheep for meat has overtaken wool as the primary profit driver of Class 4 sheep enterprises in the Western North Island of New Zealand. While the sale of cull ewes and rams contributes to sheep enterprise production it’s the production of lamb that contributes the greatest amount. Lambs born on farm can either be grown to heavier liveweights and sent direct to the works (termed prime for slaughter) or sold as store lambs for others to finish. Therefore, the production of lamb as a profit driver is dependent on the number of lambs along with the individual liveweight of each lamb. There is, however, no recent information that directly quantifies and compares the impacts of either increased lamb numbers, increased lamb liveweights, or a combination of both which maximises farmer profit. Bio-economic modelling is a relatively recently adapted tool used in agricultural production systems such as New Zealand sheep enterprises. A bio-economic systems dynamics model has recently been created to compare changes in various sheep enterprises in New Zealand, with the model output production values found to be close to realised values. This bio-economic systems-dynamic model was identified as the most suitable model to use to complete this research. The specific objectives of this research were to update the current STELLA bio-economic system-dynamic model with more recent industry statistics before running eight scenarios with differing lambing percentage and pre-weaning growth rates to examine the impact on operating profitability. The model has six key major modules within the sheep enterprise: the purebred flock, feed supply, feed demand, feed balance, wool production, and economics. These major modules all had submodules. Model inputs were driven by recently published industry standards, ensuring model outputs would replicate realised values as closely as possible. Scenario 1 uses New Zealand average values for lambing percentage (133.5%) and lamb weaning weight. Scenarios 2, 3 and 4 use average lamb weaning weights but had lambing percentages of 140%, 150% and 160% respectively. Scenarios 5, 6 & 7 used average lambing percentage (133.5%) but has 10%, 20% & 30% greater pre-weaning lamb growth rates respectively. Scenario 8 had a lambing percentage of 140% and 10% increased pre-weaning lamb growth rates. Increasing lambing percentage from 133.5% in scenario 1 to 160% in scenario 4 increased the proportion of lambs sold store due to a greater proportion of lambs being born as multiples. This scenario increased farm cash operating surplus from ‡2 91/ha to ‡3 68/ha. Gestational energy demand limited flock size, with the number of ewes decreasing from scenario 1 to 4. Increasing pre-weaning lamb growth rates to 30% (scenario 7) above average (scenario 1) while leaving lambing percentage as average also decreased flock size but increased the farm COS from ‡2 91/ha to ‡4 44/ha. Lactational demand to meet the increased lamb growth was the factor limiting flock size. In the scenario with 140% lambing and a 10% increase in pre-weaning lamb growth rates (scenario 8) farm COS increased to ‡3 65/ha, ‡7 4/ha above scenario 1. Overall, increasing pre-weaning lamb growth was more profitable than increasing lambing percentage. Therefore the results of this research indicates that if a farmer has a lambing percentage of 140% or above, it is recommended emphasis should be placed on improving pre-weaning lamb growth rates compared to lambing percentage. There are several further considerations such as feed supply and lamb numbers, which must be considered before using these results. With the model relying solely on pasture for feed, any circumstances that leads to reduced feed supply may reduce the viability of these results.