Ovine Observer

An economic analysis of sheep flock structures for mixed enterprise Australian farm businesses

Michael Young and Ross Kingwell, DPIRD and UWA Perth, WA; John Young, Farming Systems Analysis Service Denmark, WA; and Phil Vercoe UWA Perth, WA

Introduction

Farming systems can be complex, sometimes involving large areas with a range of soil types, and several crop, pasture, and livestock enterprise choices. The complexity of farming systems complicates decision-making, and even with access to data and information, decision-making remains a challenge. Industry tends to use simple decision-making tools such as whole-farm budgets, partial-farm budgets, and gross margins. These techniques offer a quick and affordable ways to evaluate farm strategies and plans, but they often fail to accurately capture important aspects, such as biological interactions between enterprises and technical details such as soil type. An alternative to the simple appraisal techniques used by many farm management advisers is to opt for detailed whole-farm optimisation modelling. Whole-farm modelling provides a detailed representation of the whole-farm system, including its various resources of finance, soils, labour, machinery, livestock, crops, and pastures. This allows farmers to identify what areas of the farm system are current and potential drivers of profit, and how they should be managed to maximise whole-farm profit. 

Aims

To help address the question of ‘what structure and size of sheep flock can best serve the profit interests of mixed enterprise farms in Australia?’, this study applies whole-farm bioeconomic modelling in a study region in the southwest of the Western Australian grain belt. We examine how different sheep flock structures and sizes of the sheep flock affect farm profitability, farm management and business strategy. Using whole-farm bioeconomic modelling and wide-ranging sensitivity analyses, we test the hypothesis that whole-farm profit is sensitive to flock structure.

Methods

Whole-farm bioeconomic modelling, combined with broad-ranging sensitivity analysis, is used to examine the profitability of different sheep flock structures and sizes.

The whole-farm model employed in this analysis is known as Model of an Integrated Dryland Agricultural System (MIDAS). MIDAS is a whole-farm linear programming model with a joint emphasis on biology and economics. It can evaluate the economic significance of alternative farm strategies, in a steady-state format, by revealing farm management decisions that maximise whole-farm profit under a given set of constraints, with a range of production possibilities and enterprise interactions that typify the strategy being examined. 

The Great Southern regional version suite of MIDAS was used, this version represents an average farm in the Great Southern region of Western Australia. In this study, the model was also tailored to represent a larger farm business in the South-west of Western Australia using the key characteristics listed in Table 1. Table 2 lists the sheep flock structures analysed in this study. These different systems range from wool-focused production to specialist meat production and a mix of both meat and wool production.

Note: *Yields presented above are the average across all the of rotations

Results & Discussion

Flock comparison and flock structure choice

Whole-farm profitability varied by $630 000 per year (or $99/ha) between the least and most profitable flock structures evaluated. The most profitable structure was the Specialist-MTS flock, generating $1 266 000 farm profit, almost double the least profitable flock. The least profitable flock was Trade Wether which generated $636 000. This finding provides evidence to support the hypothesis that whole-farm profit in mixed enterprise farms in Australia currently is highly sensitive to flock structure.   

Flocks based on Merino ewes and selling finished Merino or first-cross lambs were the most profitable (Specialist-MTS, SRF-MTS, MPL), being over 20% more profitable than flocks that retained wethers (Figure 1). A related main finding was that the longer the wethers were retained, the lower the farm profit. However, the Composite flock was less profitable because the composite genotype did not produce the quality and quantity of wool of the pure Merino genotype, and the Store flock was less profitable because its lambs were sold at a lighter weight, thereby generating less sales income. Within the Merino flocks that sold finished lambs, revenue was increased by including terminal sires. Mating all Merino ewes to a terminal sire (Specialist-MTS) increased profit by 9% compared to mating only surplus ewes (SRF-MTS), and increased profit by 15% compared to not mating any ewes to terminal sires (MPL).

Figure 1. Whole-farm profit for each flock structure in this analysis

Optimal farm management varied for the different flocks. Generally, the longer the wethers were retained, the lower the proportion of ewes in the flock. As the proportion of ewes in the flock decreased, the stocking rate and supplementary feed also decreased. Flocks selling first-cross lambs had the highest stocking rates and supplementary feed requirements (Table 3).

Weaning weight had a large impact on the profitability of Composite and MTS flocks (Figure 2). These flocks had a greater focus on meat production and the lambs were sold at 4–4.5 months of age, so they required extra grain feeding to reach finishing weights if they were weaned at a lower weight. A 5% reduction in weaning weight reduced the profit of the Specialist-MTS flock by as much as $104 000 (8%). However, profit reduced by <1% for flocks that retained wethers older than 17 months of age.

Figure 2. Whole-farm profit for each flock when lamb weaning weights were reduced

Changing the stocking rate by 10% from the optimum reduced the profit by as little as 2% for the first 10% change, but up to 10% as the stocking rate moved further from the optimum. This pattern and the magnitudes of reductions in profit were very similar for each flock structure (Figure 3). 

Figure 3. Farm profit when stocking rate of each flock was altered from the optimum

The stocking rates indicated to be feasible and optimal in this study are higher than commonly observed on farms. For example, in the study region, in the production year of 2018 when close to average annual rainfall was received, the average stocking rate was 7.4 DSE/ha and the top 25% of farms, ranked by operating surplus/ha/mm of growing season rainfall, recorded an average stocking rate of 8.5 DSE/ha (Planfarm 2019). This study’s results indicated that altering the stocking rate away from the optimum reduced farm profit. However, most importantly, the relative profitability between the different flock structures was not altered. Hence, if farmers selected to be, for example, 20% below the optimum identified in this study, there was no change in the optimal flock structure. These results provide farmers, at least those in the region investigated, with confidence regarding the optimal flock structure, even if these farmers are risk averse or reliant on imperfect information that leads to a reduction in their farm’s stocking rate. 

Crop management

The optimal cropping proportion for the farm was between 40% and 60%, depending on the particular flock structure selected. Cropping proportions as low as 20% and as high as 80% remained economically viable (Figure 4). The ranking of flock structures was the same at all cropping levels, with Merino flocks selling finished lambs being the most profitable. A key finding was that, within 30–70% cropping, farm profit was affected more by selecting the optimal flock than altering crop allocation. Interestingly, rotation choice was independent of flock structure, with the optimal rotation on each land management unit being the same for all flock structures.

Figure 4. Farm profit for each flock structure option over a range of cropping proportions

Selecting the correct rotation for each soil type was important. It was most profitable to have continuous pasture on the less productive soils and continuous crop with complementary smaller areas of continuous pasture on the more productive soils. Continuous cropping on the poor soil reduced farm profit by $80/ha, and a pasture crop rotation also reduced farm profit by $69/ha. Conversely, continuous pasture on the best soil reduced farm profits by $170/ha, and on the same soil, a pasture crop rotation reduced farm profit by $66/ha.

Although there are many interactions between cropping and livestock operations, rotation selection and crop allocation did not affect the choice of flock structure and vice versa. This means farmers can independently alter their flock structure and crop management, which provides confidence in the flexibility of the mixed farm system.

Price sensitivity and variation

Increasing the carcass weight price of lamb, as expected, increased the profit of flocks turning off finished lambs, whilst decreasing the carcass weight price of lamb had the opposite effect. In contrast, increasing the wool price increased the profit of the flocks retaining wethers, whilst decreasing the wool price had the opposite impact. However, a 20% increase or decrease in the carcass weight price of lamb or wool prices was not enough to alter the optimal flock structure.

A 20% increase in grain prices shifted the optimal cropping proportion towards 70% and increased farm profit by up to 18%. At crop levels below 20% however, the increase in profit was minimal because the cost of supplementary feed increased reducing the profit of the sheep enterprise, and the volume of grain sold at the higher prices was small. In addition, the increase in supplementary feed costs was not enough to change the optimal flock structure. Merino flocks turning off finished lambs were still the most profitable (Figure 5).

Figure 5. Farm profit for each flock structure at a range of cropping proportions when grain prices were (a) 20% less, (b) unchanged, (c) 20% more

Altering the price of labour affected whole-farm profit. Reducing the labour price by 20% increased farm profit by $170 000 per year, and the same percentage increase in the labour price had the opposite impact. Changing the labour price affected each flock structure similarly and therefore had no impact on a farmer’s choice of flock structure.

Flocks that produced a balanced mix of wool and sheep for sale were less exposed to separate changes in wool or sheep meat prices. Price variation had the greatest impact on the profitability of flocks based on either a composite genotype (meat emphasis) or a Merino flock dominated by wethers (wool emphasis). However, the choice of the optimal flock structure was robust to price changes as large as 20%. 

Flock structure also was robust to price changes in key inputs such as supplementary feed and labour. However, the profitability of flocks purchasing sheep, such as the Specialist-MTS and trade wether flocks, was affected differently if specific classes of sheep sufficiently changed in price. For example, an increase in the price of ewes reduced the profitability of the Specialist-MTS flock. However, ewe prices needed to increase by over 35% before switching to a self-replacing flock became more profitable. Similarly, the price of store lambs had to drop by over 35% before farmers would consider a trade wether flock, which is unlikely given that the price of store lambs is driven by the demand for lambs to feedlot; therefore, the lack of demand from store wether buyers is unlikely to drive down the price. 

Selection of a Merino flock that turned off finished lambs also helped mitigate risks associated with variation in grain prices. This flock structure depended on supplementary feed, so if grain prices dropped, then the loss of crop income could be offset by cheaper sheep feed. In general, farmers can be confident with their choice of flock structure in the face of market uncertainty.

Conclusion

This study assessed the role and profitability of different flock structures in a mixed enterprise farm business in the grainbelt region of Western Australia. We found that farm profit was greater when a Merino flock turning off finished lambs was selected. These flocks remained the most profitable among a range of flock options, even if key input prices and commodity prices were subject to moderate change. However, to achieve the maximum profit, these flocks required more attention to sheep management. 

Choice of flock structure had a larger impact on profit than moderate changes in land allocation to cropping. Selection of the most profitable flock structure generated double the farm profit from that of the least profitable flock structure. More conservatively, a farm plan based on cropping and a self-replacing Merino flock using surplus ewes for first-cross, meat lamb production earned 33% more profit than a farm plan based on a traditional self-replacing Merino flock that emphasised wool production. An additional feature of optimal farm plans was to commit to continuous pasture on all the poor soils whilst continuously cropping the more productive soils, with some complementary areas of permanent pasture. 

Key Messages

• The most profitable flock structure were flocks based on Merino ewes and selling finished Merino or first-cross lambs. These were over 20% more profitable than flocks that retained wethers.
• Choice of flock structure had a larger impact on profit than moderate changes in land allocation to cropping. Additionally, rotation selection and crop allocation did not affect the choice of flock structure and vice versa.
• Flocks that produced a balanced mix of wool and sheep for sale were less exposed to separate changes in wool or sheep meat prices.

References

Planfarm (2019). Planfarm Benchmarks 2018–2019. Osborne Park, WA.