Predicting the impact of climate change on potential habitats of Stipa hohenackeriana Trin & Rupr in Central Zagros

Stipa hohenackeriana in terms of forage production and soil protection is especially important. In this study, was predicted the potential effects of climate change on the future geography distribution of this species in Chaharmahal va Bakhtiari province located in Central Zagros region. To do this, 122 species presence point of this species is collected by GPS, along with 9 environmental variables including bioclimatic, physiographic and land cover/land use variables were used. Ensemble methods were used to predict S. hohenackeriana distribution including the Generalized Linear Model (GLM), Artificial Neural Network (ANN), Generalized Boosting Method (GBM), Flexible Discriminant Analysis (FDA), Multivariate Adaptive Regression Splines (MARS), Maximum Entropy (MaxEnt) and Random Forest (RF). The future projections were made for both year 2050 and 2070 with four Representative Concentration Pathways (RCPs) scenario (2.6, 4.5, 6 and 8.5) and general circulation model MRI-CGCM3. Our findings show that estimated suitable habitats of the species covers about 22.37% of the study area for the S. hohenackeriana. The mean temperature of the wettest quarter, Precipitation Seasonality and Isothermality had the greatest effects on the species’ distribution in the study area. Due to climate change, the least and most decline of suitable habitats of 18.72% (RCP2.6) to 42.87% (RCP8.5) may occur by 2050 and 2070, respectively. Based on the assessments, Random Forest was determined to be the most reliable model among the seven models studied. The region mapped in the study as suitable habitats’ for the species could be effective for the re-establishment and re-introduction of S. hohenackeriana species.