Executive Summary
What the report is about
Some of the solutions to the market and environmental challenges facing Australian agriculture may lie in more diverse land use, in which enterprises and practices are better matched to soil and climate circumstances. Innovations that explicitly capitalise on variability across paddocks, farms and catchments, such as precision agriculture and mosaic farming hold promise through their potential to increase production efficiency while reducing on-site degradation of soil resources and off-site environmental problems.

Who is the report targeted at
This report is target to Australian farmers looking to explore the value of technologies to increase production efficiency.

Background
Australian agriculture is confronted by the dual challenge of a market environment in which farmers’ terms of trade and the real net value of agricultural production have both shown strong and persisting downward trends (National Land and Water Resources Audit 2002) and a need to develop sustainable systems more in tune with Australia’s unique soil and climate conditions (Williams and Gascoigne 2003). Diversity was a prominent feature of many natural Australian landscapes, but all too often this diversity has been eliminated in the agriculture established since European settlement.

Objectives
This project aimed to provide improved tools and processes to evaluate the economic and environmental benefits, and risks, associated with technologies that address spatial variability in Australian farming systems. The research was based on two case studies and revolved around the decisions faced by farmers seeking to manage spatial variability, as observed through yield maps, on their grain farms. Such an approach allowed farmers to explore the value of the technologies in a real-life situation.

Methods
The first case study explored the profitability of spatially-variable nitrogen fertiliser management for a grains-based farm, near Moree, in the north-east Australian wheat belt. The second case study farm, in a cropping area in the Upper Murray Catchment, in the south-east Murray-Darling Basin, was selected to explore mosaic farming opportunities involving the incorporation of perennial crops into annual cropping systems for economic / environmental benefit. Two study groups were formed to consider the analyses conducted for each case-study farm. Each group included the farmer responsible for managing the farm, other local farmers and advisers (both private consultants and agronomists in local state agriculture departments).

The research process commenced with farmers nominating their hypotheses of what was responsible for spatial variation on their farms. These hypotheses were then tested through the application of soil characterisation, crop monitoring and farming systems simulation. Farming systems simulation was conducted using a computer model called ASPIM, which can simulate the growth of a range of crops in response to a variety of management practices, crop mixtures, rotation sequences and, importantly, climatic conditions. The issue of interaction between spatial and temporal (climate-driven, seasonal) variability, and their respective interactions with a range of management options, was explored in the study groups, along with the implications of this for economic and environmental performance.

Results
For the case study on spatially-variable nitrogen management, both temporal (climate-driven) and spatial variability (in this case, attributed to variation in soil depth across the paddock) impacted on economically optimal nitrogen management practices. Optimal nitrogen rates were calculated for uniform and zone-based management under conditions of both full (perfect) and incomplete knowledge of the in-season climatic conditions. In some years, there was potential to make substantial economic returns and in others the benefits would unlikely outweigh the cost of the investment in the PA technology, even with perfect information.

The biophysical response function relating nitrogen input to yield underpins the economic responsiveness of varying the level of nitrogen applied to a crop. If, for example, the shape of the simulated economic response surfaces of grain crops to nitrogen fertiliser was flat around the optimum nitrogen rate, the management implication was often that applying a ‘roughly right’ rate of nitrogen did not result in a high economic penalty. We suggest that any proposed application of PA technology to spatially-variable input management start with a thorough investigation into the nature of the biophysical response surface.

This analysis also suggested that in an environment where the consequences of climate-driven temporal variability can exceed those of spatial variability, there is little value in applying spatially variable rates unless seasonal adjustments are also made.

Conclusions
Conclusions about the value of precision agriculture for varying inputs at the sub-paddock scale in the north eastern wheat belt should be further informed by sensitivity analysis considering variation in crop prices and input costs, the influence of nitrogen fertiliser and soil water carry over effects, and protein variation, in economic returns.

An important question for mosaic farming is how to match the spatial location of the various enterprises of the mosaic (e.g. deep-rooted perennials in an annual cropping system) with landscape position and soil attributes. For the case study farm selected to explore mosaic farming, the ability to recognise spatial variation in economic returns across the paddock was found to be a necessary but not sufficient information requirement for mosaic farming design. The collaborating landholder noted that the uncertainties involved with interpreting variability made the final step of managing spatial variability, based on the data captured, a very difficult task to undertake with confidence. Historical climate records and simulation models assisted in explaining spatial and temporal variability, particularly by aiding diagnosis of possible constraints to yield such as frost, waterlogging and the influence of catchment-scale hydrological processes on yield. Simulation of management alternatives demonstrated that the economic and environmental outcomes from a mosaic farming system could vary within a farming landscape depending on where various elements of the mosaic farming system are located.

Although this case study highlights opportunities for mosaic farming design, further research is needed to fully evaluate the implications of changing the mix and location of enterprises on this case study property. Scaling up implementation of mosaic farming to the farm scale requires that a greater range of factors be considered for further analysis. Examples provided during the discussions included the interactions between enterprises (e.g. crop and livestock activities) within the mosaic, risk factors, and costs and benefits that are incurred at whole-farm scale, such as redefining and / or re-fencing paddock boundaries to create feasible management zones. The impact that mosaic farming has on longer term sustainability factors must be also considered.

Collaborating farmers reported that they were comfortable to make their own assessment of management alternatives, provided that they had confidence in understanding the biophysical processes taking place. One measure of this project’s success has been the collaborators’ improved understanding of their own or their client’s spatial variability from the soil characterisation and monitoring activities which provided reliable measurements of soil water, nitrogen and other physical and chemical properties. The discussion sessions using APSIM with landholders and their advisers have indicated strong interest in the potential of APSIM to complement PA technologies that sense variability and help explore spatially-variable management alternatives. When used with historical climate records, simulation models such as APSIM and can play an important role in interpreting the causes of variability and placing the performance of individual seasons in a long-term context, as well as assessing the likely responses to changed management practice.

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