Data from a multiyear farm systems study evaluating the effect of stocking rate (SR) on pasture production and utilization, milk production per cow and per hectare, reproduction, and cow health were used to determine the economic implications of altering SR. The effect of SR was also evaluated relative to cow size and total feed available (comparative stocking rate; CSR), to account for differences in cow size and feed supplement availability. Milk production, gross revenue, operating expenses, and operating profit per cow all declined with increasing SR and CSR. In comparison, milk production, gross revenue, and operating expenses per hectare increased with increasing SR and CSR. These effects were irrespective of milk price. The effect of SR on operating profit and return on assets, however, was dependent on milk payment system. When payment was based on the economic value of milk fat and protein, operating profit and return on assets were quadratically associated with both SR and CSR, declining at an SR greater or less than 3.3 cows/ha and a CSR greater or less than 77 kg of body weight/t of feed dry matter available. In comparison, when milk payment was based on a fluid milk pricing system, profit per hectare increased linearly with increasing SR and CSR, but return on assets was not affected by SR or CSR.

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The profitability of dairy farms in Australia and New Zealand is closely related to the amount of pasture dry matter consumed per hectare per year. There is variability in the pasture growth curve within years (seasonal variation) and between years (interannual variation) in all dairy regions in both countries. Therefore, the biological efficiency of production systems depends on the accuracy and timeliness of the many strategic and tactical decisions that influence the balance between feed supply and demand over an annual cycle. In the case of interannual variation, decisions are made with only limited quantitative information on the range of possible pasture growth outcomes. To address this limitation, we used the biophysical simulation model ‘DairyMod’ to estimate mean monthly herbage accumulation rates of annual or perennial ryegrass-based pastures in 100 years (1907–2006) for five Australian sites (Kyabram in northern Victoria, Terang in south-west Victoria, Ellinbank in Gippsland, Elliott in north-west Tasmania and Vasse in south-west Western Australia) and in 35 years (1972–2006) for three sites in New Zealand (Hamilton in the Waikato, Palmerston North in the Manawatu and Winchmore in Canterbury). The aim was to evaluate whether or not a probabilistic approach to the analysis of pasture growth could provide useful information to support decision making. For the one site where annual ryegrass was simulated, Vasse, the difference between the 25th and 75th percentile years was 20 kg DM/ha.day or less in all months when pasture growth occurred. Irrigation at Kyabram and Winchmore also resulted in a narrow range of growth rates in most months. For non-irrigated sites, the 25th–75th percentile range was narrow (10–15 kg DM/ha.day) from May or June through to September or October, because plant available soil water was adequate to support perennial ryegrass growth, and the main source of interannual variability was variation in temperature. Outside of these months, however, variability in growth was large. There was a positive relationship between total annual herbage accumulation rate and mean stocking for four southern Australian regions (northern Victoria, south-west Victoria, Gippsland and Tasmania), but there was evidence of a negative relationship between the co-efficient of variation in pasture growth and stocking rate. The latter suggests that farmers do account for risk in pasture supply in their stocking rate decisions. However, for the one New Zealand region included in this analysis, Waikato, stocking rate was much higher than would be expected based on the variability in pasture growth, indicating that farmers in this region have well defined decision rules for coping with feed deficits or surpluses. Model predictions such as those presented here are one source of information that can support farm management decision making, but should always be coupled with published data, direct experience, and other relevant information to analyse risk for individual farm businesses.

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The profitability of dairy businesses in southern Australia is closely related to the amount of feed consumed from perennial ryegrass-dominant pasture. Historically, the dairy industry has relied on improvements in pasture productivity and utilisation to support profitable increases in stocking rate and milk production per hectare. However, doubts surround the extent to which the industry can continue to rely on perennial ryegrass technology to provide the necessary productivity improvements required into the future. This paper describes the design and management of a dairy systems experiment at Terang in south-west Victoria (780-mm average annual rainfall) conducted over four lactations (June 2005–March 2009) to compare the production and profitability of two forage base options for non-irrigated dairy farms. These options were represented by two self-contained farmlets each milking 36 mixed-age, autumn-calving Holstein-Friesian cows at peak: (1) well managed perennial ryegrass pasture (‘Ryegrass Max’, or ‘RM’); and (2) perennial ryegrass plus complementary forages (‘CF’) including 15% of farmlet area under double cropping with annual species (winter cereal grown for silage followed by summer brassica for grazing on the same land) and an average of 25% of farmlet area in perennial pasture based on tall fescue for improved late spring–early summer feed supply. The design of these systems was informed by farming systems models (DairyMod, UDDER and Redsky), which were used to estimate the effects of introducing different forage options on farm profitability. The design of the CF system was selected based on modelled profitability increases assuming that all forage components could be managed to optimise forage production and be effectively integrated to optimise milk production per cow. Using the historical ‘average’ pasture growth curve for the Terang district and a mean milk price of $3.71 per kg milk solids, the models estimated that the return on assets of the RM and CF systems would be 9.4 and 15.0%, respectively. The objectives of the experiment described here were to test whether or not such differences in profitability could be achieved in practice, and to determine the risks associated with including complementary forages on a substantial proportion of the effective farm area. Key results of the experiment are presented in subsequent papers.