Prediction of potential habitats of Astracantha gossypina (Fisch.) Using the maximum entropy model in regional scale

Astracantha gossypina (Fisch.) is one of the most important rangeland plants in the northeastern region of Iran and has a great role in soil conservation and the economy of ranchers. unreasonable uses and management of desire plant species usually led to species loss and the replacement of endemic and specialist species by invasive endemic or exotic species. This study was conducted to determine the potential habitat of As. gossypina species in the rangelands of Khorasan Razavi and North Khorasan provinces using MaxEnt model. In this purpose, 757 species presence points in 17 different areas recorded by GPSMap 60CSx in field sampling. Environmental variables including 19 bioclimatic layers, 3 layers of slope, direction and altitude, geology and soil data layers (texture, soil potential, hydrological groups) as predictor variables analyzed for correlation and corelated variables were removed. Analysis of prediction layers and presence points performed using Maxent 3.3 software. According to the results the area under the curve index (AUC = 0.98) showed, the maximum entropy model had good accuracy and efficiency in detecting the factors affecting the geographical distribution of the species. Based on the jackknife test results, environmental factors included DEM, SOILLAND, BIO1, geology, BIO17, BIO19 and BIO15 respectively had the most role in determining the habitat suitability of the species. Finally, the study area was divided into four suitability classes and more than 218 thousand hectares, equivalent to 1.52% had moderate to good potential for the growth and harvesting of the species.