In this work we used the information of the Annual Hunting Reports (AHRs) to obtain a high-resolution model of the
potential favourableness for wild rabbit harvesting in Andalusia (southern Spain), using environmental and land-use
variables as predictors. We analysed 32,134 AHRs from the period 1993/2001 reported by 6049 game estates to estimate
the average hunting yields of wild rabbit in each Andalusian municipality (n5771). We modelled the favourableness for
obtaining good hunting yields using stepwise logistic regression on a set of climatic, orographical, land use, and vegetation
variables. The favourability equation was used to create a downscaled image representing the favourableness of obtaining
good hunting yields for the wild rabbit in 161 km squares in Andalusia, using the Idrisi Image Calculator. The variables that
affected hunting yields of wild rabbit were altitude, dry wood crops (mainly olive groves, almond groves, and vineyards),
temperature, pasture, slope, and annual number of frost days. The 161 km squares with high favourableness values are
scattered throughout the territory, which seems to be caused mainly by the effect of vegetation. Finally, we obtained quality
categories for the territory by combining the probability values given by logistic regression with those of the environmental
favourability function
