Identifying the spatial and temporal variability of economic opportunity costs to promote the adoption of alternative land uses in grain growing agricultural areas: an Australian example

Grain growers face many future challenges requiring them to adapt their land uses to changing economic, social and environmental conditions. To understand where to make on ground changes without significant negative financial repercussions, high resolution information on income generation over time is required. We propose a methodology which utilises high resolution yield data collected with precision agriculture (PA) technology, gross margin financial analysis and a temporal standardisation technique to highlight the spatial and temporal consistency of farm income. On three neighbouring farms in Western Australia, we found non-linear relationships between income and area. Spatio-temporal analysis on one farm over varying seasons found that between 37 and 49% (1082-1433ha) of cropping area consistently produced above the selected income thresholds and 43-32% (936-1257ha) regularly produced below selected thresholds. Around 20% of area showed inconsistent temporal variation in income generation. Income estimated from these areas represents the income forgone if a land use change is undertaken (the economic opportunity cost) and the average costs varied spatially from $190±114/ha to $560±108/ha depending on what scenario was chosen. The interaction over space and time showed the clustering of areas with similar values at a resolution where growers make input decisions. This new evidence suggests that farm area could be managed with two strategies: (a) one that maximises grain output using PA management in temporally stable areas which generate moderate to high income returns and (b) one that proposes land use change in low and inconsistent income returning areas where the financial returns from an alternative land use may be comparable. The adoption of these strategies can help growers meet the demand for agricultural output and offer income diversity and adaptive capacity to deal with the future challenges to agricultural production.