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

Species distribution models (SDMs) are one of the most effective tools that determine the factors responsible for shaping the genetic structure 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 Iran using eight uncorrelated bioclimatic variables and occurrence localities. This species was long considered a subspecies of S. maurus but later in 2015, it was recognized as a distinct species. The area under curve (AUC) value of 0.975 indicated 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 curves suggested that S. kruglovi prefers the parts of Iran having 64-79% precipitation seasonality, 110-130 mm precipitation of the coldest quarter, and -7 to -13 0C minimum temperature of the coldest month. The southern half of the country was predicted as unsuitable habitats for the species occurrence. Our findings confirmed two geographically distinct suitable habitat patches in the northeast and northwest of Iran. Combining the obtained climate niche map with future genetic data is an effective approach for determining the boundaries of spatial patterns of intraspecific genetic variation.