Embedded risk management in dryland sheep systems I. Field results and development of a destocking algorithm
This paper presents part of a study evaluating alternative management strategies to address effects of climatic variability on productivity and profitability in dryland sheep farming in New Zealand. The study included a field trial and the development and use of quantitative models of sheep grazing systems. Field research carried out to investigate and demonstrate key aspects of high performance sheep systems in dryland environments is briefly described and a summary of results presented. These demonstrate that it is possible to maintain high pasture quality throughout the growing season with a relatively high stocking rate, leading to rapid lamb growth and sale. Flexibility to change feed demand quickly when conditions dry may reduce the variability of income between years (i.e. reduce risk) in comparison to the average farm in the region represented by a regional monitor farm model.To explore effects of different flexibility options and embedded climate risk responses over a number of years, a de-stocking and marketing algorithm has been developed. This combines information on current and projected feed supply and demand, and the probability of rain from long range weather forecasts into a 'severity index' which affects how aggressively a farmer might react to a change in climate conditions. Soil moisture level in the top 25cm of soil (SML₂₅) is suggested as a 'trigger' variable to prompt a response in terms of sale of trading stock (lambs and cattle) or capital stock (breeding ewes and cows). The algorithm may be used as a stand-alone decision aid, in which case the farmer needs to enter a sale or disposal priority list of stock classes (which may change during the season), the current stock on hand and current feed supply (expressed as the number of days grazing available). The algorithm is designed to be used iteratively to manage stock sales and utilisation of feed to the end of the season.The algorithm has also been included in a sheep farm simulation model. Implementation and testing within the Lincfarm model, set up for a hypothetical farm, shows that the algorithm generates appropriate sales profiles for scenarios involving different feed supply situations. This illustrates that it is possible to simulate the complex interactions between animals, pastures and management components in dryland grazing systems to investigate tactical adjustments in risk management strategies. Long term impacts of alternative policy:risk response combinations are described in a subsequent paper.... [Show full abstract]
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