Assessment of production risk in grazing models

Cacho, Oscar J.; Bywater, Anthony C.; Dillon, John L.

doi:10.1016/s0308-521x(99)00020-7

Cited by 40 publications

(30 citation statements)

References 8 publications

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“…These enterprises are characterised by complex herd structures and dynamics that are subject to interactions between a highly variable climate and pasture resource, which drives considerable production risk (Cacho et al, 1999). Although a number of beef cattle simulation models have been produced to mimic different production systems around the world (e.g., Foran et al, 1990;Tess and Kolstad, 2000;Teague and Foy, 2002), none of the available models were particularly suited for simulating either extensive production systems in sub-tropical and tropical regions or the types of technology interventions that may be possible for application in the coming two decades.…”

Section: Introductionmentioning

confidence: 99%

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Ash

Hunt

McDonald

et al. 2015

Agricultural Systems

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The financial health of beef cattle enterprises in northern Australia has declined markedly over the last decade due to an escalation in production and marketing costs and a real decline in beef prices. Historically, gains in animal productivity have offset the effect of declining terms of trade on farm incomes. This raises the question of whether future productivity improvements can remain a key path for lifting enterprise profitability sufficient to ensure that the industry remains economically viable over the longer term. The key objective of this study was to assess the production and financial implications for north Australian beef enterprises of a range of technology interventions (development scenarios), including genetic gain in cattle, nutrient supplementation, and alteration of the feed base through introduced pastures and forage crops, across a variety of natural environments. To achieve this objective a beef systems model was developed that is capable of simulating livestock production at the enterprise level, including reproduction, growth and mortality, based on energy and protein supply from natural C 4 pastures that are subject to high inter-annual climate variability. Comparisons between simulation outputs and enterprise performance data in three case study regions suggested that the simulation model (the Northern Australia Beef Systems Analyser) can adequately represent the performance beef cattle enterprises in northern Australia. Testing of a range of development scenarios suggested that the application of individual technologies can substantially lift productivity and profitability, especially where the entire feedbase was altered through legume augmentation. The simultaneous implementation of multiple technologies that provide benefits to different aspects of animal productivity resulted in the greatest increases in cattle productivity and enterprise profitability, with projected weaning rates increasing by 25%, liveweight gain by 40% and net profit by 150% above current baseline levels, although gains of this magnitude might not necessarily be realised in practice. While there were slight increases in total methane output from these development scenarios, the methane emissions per kg of beef produced were reduced by 20% in scenarios with higher productivity gain. Combinations of technologies or innovative practices applied in a systematic and integrated fashion thus offer scope for providing the productivity and profitability gains necessary to maintain viable beef enterprises in northern Australia into the future.Crown

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Section: Introductionmentioning

confidence: 99%

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Ash

Hunt

McDonald

et al. 2015

Agricultural Systems

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“…The 10-year Monte Carlo simulations of the DPRD model were used to derive a risk-efficient frontier (Cacho et al 1999). The method consists of testing different combinations of technologies and management strategies and ranking them based on expected returns and risk to identify optimal sets of risk-efficient strategies.…”

Section: Methodsmentioning

confidence: 99%

“…Expected present values were then used to identify optimal sets of management strategies using a risk-efficient frontier (Cacho et al 1999) for each level of fertiliser input cost (Fig. 4).…”

Section: Optimal Management Strategiesmentioning

confidence: 99%

Simulating the impact of fertiliser strategies and prices on the economics of developing and managing the Cicerone Project farmlets under climatic uncertainty

et al. 2013

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Abstract. The application of fertilisers to pastures in the high rainfall regions of southern Australia has contributed to large increases in carrying capacity following the widespread adoption of the practice since the late 1940s. Recently, large shifts in the worldwide demand for fertiliser inputs have lead to large rises in the cost of fertiliser inputs. These increasing costs have significant potential ramifications on the future management of soil fertility and its interaction with the persistence and profitability of sown pastures, especially during periods of climatic uncertainty.A dynamic pasture resource development simulation model was used to investigate the implications of fertiliser rates and costs on the efficient management of soil fertility under climatic uncertainty. The framework also allowed the investigation of how the management of soil fertility interacts with the utilisation of pasture resources through different stocking rates. In the application of this method to the Cicerone Project farmlets case study, fertiliser input costs were found to influence the optimal combination of fertiliser inputs and stocking rate. Analyses of the dynamic interaction between fertiliser application and cost, stocking rate and the persistence of desirable species enabled the identification of the most risk-efficient strategies. The implications for grazing industries in the high rainfall regions of southern Australia are discussed.Additional keywords: climatic uncertainty, dynamic pasture resource model, fertiliser input costs, pasture persistence, risk-efficient frontier.

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“…That is, decision makers are looking for options that are robust in the face of uncertainty, not just optimal "on average". Furthermore, analysis of risk is valuable in highlighting the trade-offs between increasing profit and increasing risk (Cacho et al 1999;Simpson et al 2001;Romera et al 2005c;c.f. Pannell 1996).…”

Section: Uncertainty and Riskmentioning

confidence: 99%

Better simulation modelling to support farming systems innovation: Review and synthesis

Woodward

Romera

Beskow

et al. 2008

New Zealand Journal of Agricultural Research

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Simulation modelling is a methodology that appears highly suitable for use in farming systems innovation. However, if the aim is to improve farming systems by supporting farmer behaviour change, model-based approaches seem to have delivered surprisingly little observable benefit to date. This paper identifies the problems underlying this apparent lack of impact, and proposes better approaches to improve on-farm benefits from farming systems modelling. A key principle that has been neglected in farm simulation modelling is intimate involvement of clients (defined as "the individuals or groups whose approval is needed for change to be implemented") throughout the innovation process. We argue that client participation is essential in the problem definition, model design and testing and policy design and evaluation phases of model-based research projects. The role of a simulation model within the innovation process, then, is to be a jointlycreated "virtual world" wherein experiments may be conducted to facilitate learning about the relevant system. We argue that whole farm simulation models that use decision rules to specify alternative farm management strategies are the best available form of virtual world models of farming systems. Besides appropriate client input, high quality models require excellent software development practices and strenuous attention to building user confidence. The latter should include analysing the model to assess its stability and sensitivity properties, before using it to simulate experiments that compare several management alternatives under a range of environmental and local conditions. This approach allows estimation of the variations in farm system performance that are likely to result from interactions between initial farm state, farm management policy and future weather and markets. On the other hand, using simulation models to discover "optimal" farm systems would usually be inappropriate due to the complexity arising from multiple-stakeholder views, multiple-criteria, and the dynamic nature of farming systems problems. An improved systems modelling methodology is proposed that should be better able to provide benefits into farming practice.

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Assessment of production risk in grazing models

Cited by 40 publications

References 8 publications

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Simulating the impact of fertiliser strategies and prices on the economics of developing and managing the Cicerone Project farmlets under climatic uncertainty

Better simulation modelling to support farming systems innovation: Review and synthesis

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