MaxEnt Modeling for Predicting Impacts of Environmental Factors on the Potential Distribution of Artemisia aucheri and Bromus tomentellus-Festuca ovina in Iran

The main goal of this study was to estimate the geographic distribution of Artemisia aucheri and Bromus tomentellus-Festuca ovina habitat using the maximum entropy modeling technique (MaxEnt) in the Chaharbagh rangeland of Golestan Province in Iran. Vegetation sampling was done using the random-systematic method. A total of 120 plots were placed in the study area. Soil samples were taken 0-30 cm (sampling of the soil due to the mountainous terrain and deep rooted plants, depths were determined at the 0-30 cm layer). Measured soil properties included texture, organic carbon, lime, pH, EC, and N. Topographical data (obtained from a DEM map) was elevation, slope, and aspect. To prepare the data for being enterer into MaxEnt software, first the map of soil factors was obtained through the kriging method in GIS software. Then, for analysis, the elevation, and slope, geographic directions, and soil factors maps and the presence points of plant species were entered. Using the jackknife method and response curve we found the most important environmental predictor variables. Results showed that N, sand, and clay had the greatest impacts on the distribution of A. aucheri and N, sand, silt, clay, and lime in soil had the greatest impacts on the distribution of B. tomentellus-F. ovina in the study area. Correspondence of actual map with the predictive one was assessed at a satisfactory level (Kappa coefficient = 0.05 for A. aucheri but Kappa coefficient = 0.51 for B. tomentellus-F. ovina). So MaxEnt method is the more successful in predicting B. tomentellus-F. ovina habitat than A. aucheri habitat, because the distribution of A. aucheri habitat was vast and outspread in the study area.