*2.2. Environmental Data*

We used bioclimatic variables from the CliMond dataset (https://www.climond.org/ (accessed on 27 December 2020), following A1B climate change prediction scenario, of MIROC H global climate model. The above mentioned variables represent annual trends (e.g., mean annual temperature, annual precipitation) and extreme limiting environmental factors (e.g., temperature of the warmest month, precipitation in the wettest quarter), that are predicted for the whole planet (or its particular regions) and are known to influence species distributions [26]. Of 35 bioclimatic variables, highly correlated (r > 0.7) predictors were chosen using the 'virtualspecies' package in R, resulting in a selection of 18 variables predicted for 1975 (1970–2000) and 2090 (2081–2100) years. The following bioclimatic variables (CliMond) were chosen to be used in the analysis: bio01 Annual mean temperature (◦C), bio02 Mean diurnal temperature range (mean (period max-min)) (◦C), bio03 Isothermality (Bio02–Bio07), bio04 Temperature seasonality (C of V), bio14 Precipitation of driest week (mm), bio06 Min temperature of coldest week (◦C), bio07 Temperature annual range (Bio05–Bio06) (◦C), bio08 Mean temperature of wettest quarter (◦C), bio10 Mean temperature of warmest quarter (◦C), bio11 Mean temperature of coldest quarter (◦C), bio12 Annual precipitation (mm), bio14 Precipitation of driest week (mm), bio15 Precipitation seasonality (C of V), bio18 Precipitation of warmest quarter (mm), bio25 Radiation of driest quarter (W m<sup>−</sup>2), bio28 Annual mean moisture index, bio31 Moisture index seasonality (C of V), bio34 Mean moisture index of warmest quarter.
