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Modeling the distribution patterns of species is a generally efficient tool for understanding their ecological characteristics. In this study, we used the ensemble predictions of the best performing models in order to project the probability of the Mesopotamian spiny-tailed lizard's presence in southwestern Iran. The models used in our study showed that two of the variables had the highest importance in describing the distribution of this species. These two were the annual mean temperature and the maximum temperature in the warmest month of the year. All of the models used in this study reached AUC values of above 0.9 (RF (AUC = 1), GBM (AUC = 0.99), MARS (AUC = 0.98), GLM (AUC = 0.97), and Maxent (AUC = 0.95)), indicating good overall prediction accuracy. The accuracy of random forest (RF) was the highest. The most suitable areas for the presence of this species in Iran were located in Bushehr, Khuzestan, southern Ilam, and western Kermanshah provinces. Furthermore, we modeled the extent of the suitable areas under a climate change scenario, where the results showed a potential increase in the area of suitable habitats for the species in the future. An overlay of the Iranian Conservation Network with the habitat suitability map showed poor representation (13% overlap) of the species in the network of nationally protected areas.

turkish journal of zoology :

Ensemble distribution modeling of the Mesopotamian spiny-tailed lizard, Saara loricata (Blanford, 1874), in Iran: an insight into the impact of climate change