Improving Management Plans by Downscaling Hunting Yield Models: A Case Study with the Red‐Legged Partridge Alectoris rufa in Southern Spain

This is the authors' abstract. We don't add key points for this paper.

The aim of our work is to predict potentially optimal areas for red‐legged partridge Alectoris rufa hunting success in Andalusia (southern Spain) according to topographic, climatic and vegetation factors and their interaction. We analysed 32,134 annual hunting reports from the period 1993–2001 reported by 6,049 game estates to estimate the average hunting yields of red‐legged partridge in each Andalusian municipality (N= 771). We modelled the favourability for obtaining good hunting yields using generalised linear models (GLM) on a set of climatic, topographic, land use and vegetation variables. The variables that affected hunting yields of red‐legged partridge were dry herbaceous and wood crops, annual number of frost days, altitude and mean annual temperature. Vegetation was the most important factor of those considered in our study explaining the distribution of good hunting yields of the red‐legged partridge in Andalusia. The favourability equation was used to create a downscaled image representing the favourability of obtaining good hunting yields for the red‐legged partridge in 1 × 1‐km squares in Andalusia, using the Idrisi Image Calculator. Downscaling the model from municipalities to 1 × 1‐km squares provided a much higher spatial resolution when predicting the optimal areas for good hunting yields for the red‐legged partridge.