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Abstract: The FARMSCAPE Information System emerged in a long-running research program aimed at making simulation models useful to Australian farmers in managing climatic variability. This paper is about how well it has worked. This is reported in relation to two standards: (1) the value to thinking and action expressed by farmers and their consultants, (2) correspondence with theory about learning and judgement in uncertain external environments. The former utilises recorded narrative interviews with participants over many years. The latter uses a cognitive framework drawn from theory of judgment and decision making featuring the relationship between intuition and analysis (). The cognitive theory framework makes sense of several evaluation surprises. The first was high enthusiasm by largely-intuitive farmers for an analytic approach to soil water in conjunction with a newly-appreciated “bucket” metaphor for water balance. The second surprise was the virtual absence of soil water measurement 10years later. This had been replaced by various intuitive estimates, calibrated to maintain a heuristic relationship with regard to the “bucket” as a resource. Farmers and their advisers were facilitated in using simulation for thought experiments and planning under climatic uncertainty. Benchmarking enabled problem solving in documented conditions. Scenario analysis using historical climate records supported thought experiments by providing probability distributions that were valued for shaping expectations as a “history of the future”. In retrospective evaluation interviews, researchers were surprised to find that yield forecasting and tactical decision making, anticipated to be analyses that were both site- and season-specific forecasts, had served farmers as “management gaming” simulations to aid formulating action rules for such conditions, thus reducing the need for an on-going decision-aiding service. Equipped with their soil monitoring techniques and with their heuristic rules, farmers still reserved a place for simulation “when you’ve got a planting situation out of the ordinary.” [Copyright &y& Elsevier]

Abstract: Policy makers in the agricultural sector are confronted with challenges which might drive land use change and ultimately agricultural profitability to a substantial degree. The challenges include questions around climate variability, demographic changes, use of land for bio-fuel production and ensuring an increase in food production. As profitability triggers many agri-business decisions, knowledge about the existing socio-economic landscape and the economic profile of a region as well as potential impacts on profits provides useful contextual information when agricultural policies are designed. Given the upcoming challenges and their associated uncertainties, it is important to ensure that a map of agricultural profit can be reproduced in a scenario and simulation setting which will allow exploring uncertainties around the impacts on agricultural profits as well. There is however currently no flexible system in operation which allows for a consistent update of a map of agricultural profits in Australia or elsewhere. This paper describes a process that has been developed to produce a map of agricultural profit for Australia for the year 2005/2006. The process involves a complex data architecture that accounts for heterogeneous information that is collected by a variety of institutions across different scales. All information can be comfortably queried and query results can be forwarded for immediate processing and subsequent visualisation in a geographic information system (GIS). To facilitate the production of profit maps in the future, the system provides flexibility regarding an update of new economic information but it can also be linked to maps that show an updated distribution of land use. A map of agricultural profit on a large scale and regular updates thereof will help understand profit trends in time and across space. It will help identifying regions that have a lower economic profile and will inform decisions regarding the design of regulatory policies. As these maps are developed using national scale data, we do not recommend using the results at the farm level but we suggest using separate catchment scale profit assessments to calibrate the national scale profit map. The proposed system is well suited to be used in various land use management and economic scenarios and will represent a step forward regarding a scenario impact assessment on agricultural profits. It will also help understand the economic benefit of land use on a large scale. [Copyright &y& Elsevier]

Mixed crop-livestock farming systems provide food for over half of the global population. However, some important food exporting countries, like Australia, are predicted to be vulnerable to climate change and may require transformative adaptations if they are to continue their role in food exportation. This paper assesses the potential impacts of projected climate change by 2030 (0.4–1.6° increase in mean temperature) on Australian mixed crop-livestock systems and examines the consequences of shifts in land allocations to cropping and grazing, in these systems, as an adaptation option. Farm bio-economic simulation models were developed for these mixed enterprise systems in several regions of Australia. These models were based on biophysically coupled crop, pasture, and livestock simulation models that in turn drew on site-based downscaled climate projection datasets. The farm models calculated farm profitability and risk measures. A range of land use changes was investigated. At drier locations facing adverse climate change, results showed a transition towards a greater emphasis on livestock production could be beneficial when assessed against multiple criteria of farm profit, downside financial risk, and environmental damage. We highlight some industry and government actions and policies that could facilitate these preferred adaptation strategies at such locations. • Temperature increase of 0.4–1.6° affect mixed crop-livestock systems in Australia. • Transition towards a greater emphasis on livestock production is often desirable. • Financially optimal land allocations vary between historical and future climate. • Increase in the land devoted to pasture is a strategy to manage future climate risk. [ABSTRACT FROM AUTHOR]