A simulation model of grazing sheep: I. Animal growth and intake

Finlayson, John D.; Cacho, Oscar J.; Bywater, Anthony C.

doi:10.1016/0308-521x(95)93643-r

Cited by 37 publications

(22 citation statements)

References 51 publications

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“…In order to be used as a stand-alone decision aid, the farmer would be required to provide a stock type prioritization list, an estimate of the feed available at the time, and his or her estimate of the prospects of rainfall, presumably based on official current forecasts (from NIWA in the case of New Zealand). The algorithm has been incorporated into the LincFarm grazing system model [4,6] model and an evaluation of the extended model carried out for all the new extensions before use in evaluating alternative risk management strategies. …”

Section: Discussionmentioning

confidence: 99%

“…Setting stocking rate (SR) is the principal managerial decision in these systems [2] but a variety of other short-or medium-term management options (tactical responses) are available [3]. The most commonly used strategy in managing the effects of climatic variability in dryland grazed systems is understocking [4]. This results in lost opportunity of increased profitability in better than average seasons (when feed supply exceeds demand).…”

Section: Background Informationmentioning

confidence: 99%

“…The extra income derived from including tactical responses can be viewed as the cost to the farmer of basing choice regarding a management strategy on analysis that neglects the tactical advantages afforded by such a strategy. This chapter describes a destocking and marketing algorithm integrated into a grazed system model (LincFarm; [4,6]) to implement tactical adjustments to climatic variability in a dryland grazed system in Canterbury Plains in New Zealand. The algorithm is implementable in any grazed system as an in an integral part of the model or a standalone subsystem.…”

Section: Background Informationmentioning

confidence: 99%

“…This strategy would be expected to reduce market risk but it may come with increased financial risk [52]. The study by Finlayson et al [4] identified destocking as the most used strategy in drought with farmers preferring to dispose of stock instead of incurring the cost of supplementing animals or grazing them off. Other options used in response to dry conditions have been summarized by MAFPolicy [54] as rotational grazing, maintenance of buffer stock, wintering dry ewes and reducing replacement numbers to match feed supply.…”

Section: Risk Sources and Management Strategies In Dryland Pastoral Smentioning

confidence: 99%

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Production and Marketing Risks Management System in Grazed Systems: Destocking and Marketing Algorithm

Gicheha¹,

Edwrads²,

B³

et al. 2017

Theory and Application on Cognitive Factors and Risk Management - New Trends and Procedures

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This study was carried out to explore potential approaches to managing production and market risks associated with climatic variability in dryland grazed systems. The methodology is novel in that it considers farmers' ability to make sequential adjustments to their production activities when information on uncertain events becomes available. Traditional approaches to evaluation of farmers' response to risk assume perfect knowledge of production resources and that risk emanates from uncertainty in yield returns. Strategic approaches are mostly considered in evaluating farmer's risk attitude implying that managing the variability (risk) assumes that different production activities resource requirements are known (non-embedded risk). In real farming systems, the producers make sequential decisions and adjust the timing and methods of their activities as a season progresses and more information on uncertainty becomes available (embedded risk). This chapter describes a platform adopted in making destocking and marketing decisions by simulating the impact of implementing alternative tactical adjustments. The algorithm was successfully tested in a research that investigated the physical and economic impact of incorporating tactical responses in risk management strategies in dryland sheep production systems in New Zealand. The algorithm can be integrated into existing grazing models and can also be used as a standalone system.

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Section: Discussionmentioning

confidence: 99%

Section: Background Informationmentioning

confidence: 99%

Section: Background Informationmentioning

confidence: 99%

Section: Risk Sources and Management Strategies In Dryland Pastoral Smentioning

confidence: 99%

See 2 more Smart Citations

Production and Marketing Risks Management System in Grazed Systems: Destocking and Marketing Algorithm

Gicheha¹,

Edwrads²,

B³

et al. 2017

Theory and Application on Cognitive Factors and Risk Management - New Trends and Procedures

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“…The Lincoln University Farm model (LINCFaRM) Finlayson et al 1995) was developed in the early 1990s at Lincoln University, New Zealand. LINCFaRM incorporates a simple pasture growth module, multiple paddocks, animal mobs, management and detailed animal growth, lactation, wool and intake representations.…”

Section: Lincoln University Farm Model -Lincfarmmentioning

confidence: 99%

Modelling pastoral farm agro‐ecosystems: A review

Bryant

Snow

2008

New Zealand Journal of Agricultural Research

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A pastoral farm is a complex agro-ecosystem that produces agricultural outputs such as milk, meat and wool. Detailed consideration of the complexities of agro-ecosystem components, and the interactions between these components, may be best approached with simulation modelling. We reviewed nine simulation models (APSIM, EcoMod, FASSET, GRAZPLAN, GPFARM, Hurley Pasture Model, IFSM, LINCFARM, and WFM) used primarily for research of grazing systems. GrassGro (one of the GRAZPLAN suite of decision support tools), LINC-FARM, and WFM had particular strength in their simulation of animal production and farm management. The strengths of APSIM, EcoMod and FAS-SET lie in their simulation of soil nutrient dynam ics, crop or pasture production and spatial variations in soil properties. The Hurley Pasture Model has particular capability to model nutrient cycling in the presence of climate change. The IFSM includes a comprehensive representation of machinery. GP-FARM can be used to predict forage production of different plant functional groups.We suggest that more emphasis could be placed on including the effects of pests and diseases on pasture production and animal performance, more detailed representation of management practices, inclusion of more mechanistic voluntary feed intake and rumen processes and including the effect of specific genes and gene-by-environment interactions on plant quality and yields, nutrient use and animal performance. The Common Modelling Protocol, used in APSIM and the GRAZPLAN suite, may enable the development of a powerful and flexible pastoral agro-ecosystem model which incorporates newly developed modules of the nature mentioned above.

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