The effects of seasonal as well as spatial variability in yield maps for precision farming are poorly understood, and as a consequence may lead to low predictability of future crop yield. The potential to utilise terrain derivatives and proximally sensed datasets to improve this situation was explored. Yield data for four seasons between 1996 and 2005, proximal datasets including EM38, EM31, and γ-ray spectra for 2003–06, were collected from a site near Birchip. Elevation data were obtained from a Differential Global Positioning System and terrain derivatives were formulated. Yield zones developed from grain yield data and yield biomass estimations were included in this analysis. Statistical analysis methods, including spatial regression modelling, discriminant analysis via canonical variates analysis, and Bayesian spatial modelling, were undertaken to examine predictive capabilities of these datasets. Modelling of proximal data in association with crop yield found that EM38h, EM38v, and γ-ray total count were significantly correlated with yield for all seasons, while the terrain derivatives, relative elevation, slope, and elevation, were associated with yield for one season (1996, 1998, or 2005) only. Terrain derivatives, aspect, and profile and planimetric curvature were not associated with yield. Modest predictions of crop yield were established using these variables for the 1996 yield, while poor predictions were established in modelling yield zones.

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A survey was undertaken in the Great Sandy Desert, Western Australia, to document changes in total plant species richness and the richness of plants of significance to Aboriginal people, with time since fire. Species richness was highest in the early post-fire seral stages, then declined with time as ‘fire ephemerals’ completed their life cycle. Culturally significant plants, which comprised ~42% of all plants recorded, were found in all seral stages but were most abundant in the early stages post fire. A fine-scale mosaic of seral stages created by frequent patch burning provides a higher variety of plant resources per unit area, increasing harvesting efficiency of culturally important plants.

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