Climate niche modeling of Scorpio kruglovi(Scorpiones: Scorpionidae) in Iran

Species distribution models (SDMs) are one of the most effective tools that determinethefactorsresponsible for shaping the geneticstructure of different taxa. These algorithms integrate the presence points and environmental predictors to estimate the probability of species occurrence across geographical areas. In the present study, we predicted the climate niche of Scorpio kruglovi(Scorpiones: Scorpionidae) in Iranusing eight uncorrelated bioclimatic variables and occurrence localities. This species was long considered a subspecies of S. maurusbutlater in 2015, itwas recognized as a distinct species. The area under curve (AUC) valueof 0.975indicated the excellent discriminative performance of the MaxEnt algorithm. The precipitation seasonality, minimum temperature of the coldest month,and precipitation of the coldest quarter had the highest percentage of contribution (63.3%)in building the model.The response curvessuggestedthatS. krugloviprefers the parts of Iran having 64-79%precipitationseasonality, 110-130 mm precipitation of the coldest quarter, and -7 to -13 0Cminimum temperature of the coldest month. Thesouthern half of the country was predicted as unsuitable habitats for the speciesoccurrence. Our findings confirmedtwo geographically distinctsuitable habitat patches in the northeastand northwest of Iran. Combining the obtained climate niche map withfuture genetic data is an effective approach for determining the boundaries of spatial patterns of intraspecific genetic variation.