Modelling and mapping agricultural opportunity costs to guide landscape planning for natural resource management

On-farm actions to better manage natural resources often involve an opportunity cost associated with foregone agricultural production. Spatial information on agricultural opportunity costs is a key indicator that has been demonstrated to increase the cost-effectiveness of environmental investment through spatial targeting. In this paper we develop a method for calculating expected profit as a more robust spatial measure of economic rent accruing from agricultural land and indicator of opportunity cost for use in landscape and planning for natural resource management. We apply this method to the Lower Murray region in southern Australia. Agricultural profit is calculated for three farming system phases (cereals, legumes, and grazing) by census zones based on agricultural statistics and cost of production information within a GIS environment. Zonal profit layers are smoothed using pycnophylactic (mass preserving) interpolation. Farming system rotations are quantified as a set of continuous spatial probability layers for each phase using a moving window kernel density technique based on existing land use data and these probability layers are used in a weighted allocation of expected profit across the landscape. The expected profit layer provides a high spatial resolution description of opportunity costs associated with natural resource management over the Lower Murray region suitable for input into systematic landscape planning analyses. Validation of the opportunity cost layer by field survey identified both random and systematic error. Interpretation of systematic error highlighted the need to augment pycnophylactic interpolation techniques with consideration of covariates of profit such as rainfall for better estimation in areas with high profit gradients.