Macro-scale influence of climate on crop production in the Fitzroy catchment of Central Queensland

When the dynamics of a system is too complex to be analytically modelled, i t has been found useful to assume that expected values of explanatory varia bles generate expected values of the response variable, and hence, deviatio ns from the expected value of the response variable can be modelled by a Li near Perturbation Model (LPM) of the explanatory variables. This method is used in this study to develop a technique to update crop forecasts where cl imate is a major factor in crop production. The study is important because modern cultivars, which are the result of genetic gains, are sensitive to c limatic variability, and recent studies with general circulation models sug gest that one of the consequences of an increase in greenhouse gases may be greater variability in the climate of a region. The usefulness of the LPM technique in the study of agriculture-climate rel ationships is tested through application to the Fitzroy catchment in Centra l Queensland. Since no reported climatic change is yet occurring in the reg ion, the expected values for climatic conditions are obtained through avera ging. By contrast, the expected values of crop yield are obtained from tren d analysis; such trends are mainly attributable to genetic gains in the rec ent past. Three crops (wheat, barley, and sunflower) have been studied. Dev iations (or perturbations) in crop yields are related, in the framework of LPM, to deviations in minimum, maximum, and average values of rainfall, tem perature, and humidity at planting, flowering, and harvesting time. The mos t significant climatic factors affecting deviations in crop yield are ident ified. Regression models are developed which are capable of filtering and u pdating crop forecasts due to any unexpected climatic conditions, assuming consistent genetic trends and management practices.