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\textbf{Fig 8: Classification of target regions based on the local regression coefficient of the given predictor}. The minimum temperature of coldest month (bio6), slope, topographical slope (topo\_slope),  and precipitation of the warmest quarter (bio18) were the most important factors in this model. Example of interpretation: the high habitat suitability values of Peloponnese (ID=10) can be explained by a positive coefficient of bio6 (habitat suitability increasing with higher winter temperatures), aslope  coefficient less for the topographical slope lower  than 0.029 (slope (topographical slope  values around its optimum), and a regression  coefficient for bio18 around or below 0 (optimum 0, indicating an optimum  precipitation of the warmest quarter). quarter.