Yield potential determines Australian wheat growers’ capacity to close yield gaps while mitigating economic risk

Australia’s farmers are among the most efficient in the world, despite a relatively large gap between potential and achieved water-limited grain yield. With wheat yield gaps typically > 1.7 t/ha or 50% of the water-limited yield, it is important to investigate the degree to which this gap may be attributable to (rational) subprofit-maximising input levels in response to risk and risk aversion in many major grain-growing regions, particularly those with lower and more variable rainfall. Here, we use a set of 14 case study sites across the Australian wheatbelt to examine the risk-return profile of several agronomic management practices and show the extent to which the farmers’ risk attitude determines their decision-making. Using a novel profit-risk-utility framework that incorporates crop simulation, probability theory, finance techniques and risk-aversion analysis, we were able to better demonstrate how farmers might select practices that manage economic risk across sites ranging from low to high rainfall. Results varied with risk preference and yield potential. However, there are real opportunities to close the yield gap by adopting non-limiting or near non-limiting nitrogen fertiliser practices and controlling fallow weeds. We show for the first time that yields associated with current best practice can be surpassed for most levels of risk aversion by adopting an emergent practice of optimising the site-specific time of sowing and matching variety to time of sowing. For some sites and risk profiles, the emerging best practice package which includes additional N fertiliser is also profitable under risk. We also propose a modified integrated framework for yield gaps. Here, we distinguish allocative input constrains due to risk aversion from those due to access to resources, and we account for an innovation gap where the current agronomic frontier is shifted upwards by growers successfully, implementing new technologies that are not yet part of current best practice.