Figure 2

AUC values of the models for Ixodes ricinus . Pseudo-absence records were either a set of 10,000 random records, or selected at different membership values of the background or randomly distributed over the target territory. Models were trained with remotely sensed variables from MODIS imagery, at either 0.05° or 0.1° of spatial resolution. Covariates are the 12 monthly layers of surface temperatures and 12 other layers of NDVI (“Monthly”), the reduction of these monthly values by a principal components analysis (“PCA”) involving six covariates, and the coefficients of a harmonic regression (“Harmonic”) involving eight covariates.