Modeling of potential habitat for Stipa barbata And Agropyron intermedium species using artificial neural network model in rangeland of Central Taleghan

The purpose of this study was to provide spatial distribution prediction map of Stipa barbata and Agropyron intermedium species using artificial neural network model. For modeling, vegetation data in addition to site condition information including topography, climate, geology and soil were prepared. Within each sampling unit, three parallel transects with 150 m length each containing 15 quadrats were established. Sampling method was randomized-systematic method. Quadrats size determined for each vegetation type using the minimal area and their number were determined according to vegetation variation. Soil samples were taken from 0-30 cm depth along of each transects. Measured soil properties included grovel, texture, pH, EC, organic matter, lime, soluble ions (N+, P+, K+). Geostatistical methods were used for data analysis and preparation of environmental variables maps, while an artificial neural network with back-propagation algorithm applied for maps prediction. The accuracy of the network for habitat of A. intermedium and S. barbata was 98.7% and 97.6%, respectively. This indicates that the soil and climatic parameters used in the final model of this study were able in predicting potential distribution of the species. According to the results of the models assessment using the Kappa coefficient, artificial neural network model has predicted habitat for of A. intermedium and S. barbata species at an excellent and good levels (kappa= 0.95% and 0.70%). It can be concluded that the neural network model have high accuracy in predict the spatial distribution of species in rangeland of central Taleghan.