An optimisation model for spatially allocating commodity production and forecasting its impact on regional productivity
2016-09-21T00:04:21Z (GMT) by
The prototype Spatial Optimizer 1.0 program for allocation of commodity production is demonstrated to show its potential as a decision support aid for policy making. The case study involves a set of agricultural commodities in south eastern Australia and the program uses estimates of each grid cell’s soil suitability for each of the eight crops, both in the year 2000 and in the year 2050, by which time soil characteristics are expected to have been affected by environmental change. We first predict how much total regional production will result from a judicious re-location of commodity types, both under conditions of complete flexibility and when constrained by more realistic, upper and lower limits on production, and we compare such predictions with current production levels. We also estimate potential total regional revenue, both in the short term when current prices are assumed to remain static and in the long term when prices are assumed to change according to how much of each commodity is produced compared to its current output level, and we compare these results with current agricultural revenue. Our long-term estimates are based on year 2000 soil-suitability values and then on year 2050 soil-suitability values in order to gauge the probable impacts of environmental change. Finally, we run the 2050 simulation twice more, with one of the recommended, dominant crops removed in each instance. This generates maps of some localised concentrations of other commodities that will become necessary in the future if maximum revenue is to be retained after one of the more lucrative crops is discontinued.