Species distribution modeling is based on the relationship between the occurrence data of a given species and the environmental variables. Nowadays, in plant ecology, producing the species distributio maps is being greatly paid attention to due to the expansion of statistical methods and geographical information systems. In order to model the potential habitat of Rheum ribes in Isfahan Province, two modeling methods of Maximum Entropy and Genetic Algorithm were used. The location of species occurrence data (74 present sites) were recorded during the field surveys using GPS from 6 sub – provinces (Meymeh, Fereydounshahr, Fereydan, Khansar, Golpayegan and Chadegan). Climatic data (19 variables), remote sensing data (20 principal components resulted from the PCA on the NDVI) and topographic data (slope, aspect and altitude) were entered in the modeling process as environmental layers. Using these variables, seven approaches were chosen which led to the production of 16 scenarios using two modeling algorithms (MAXENT and GARP). After analyzing the results of the 16 scenarios and evaluating the performance of the models, two scenarios of PCA Topo Data (three topographic data and 20 principal components of PCA) and PCA Bio Data (19 climatic variables and 20 principal components of PCA analyses), were selected as the best scenarios for predicting the potential habitat of Rheum ribes. The results showed that in PCA Topo Data scenario, the most effective factors on Rheum ribes distribution were elevation and the second component of the PCA while in PCA Bio Data, the most important factors were temperature seasonality (Bio 4), mean temperature of warmest quarter (Bio 10) and the annual precipitation (Bio 12). A collection of independent data was used to evaluate model using area under curve of ROC plot. The performances of both models were Key words: Habitat Modeling, Rheum ribes L., Maximum Entropy (Maxent), Genetic Algorithm (GARP), Isfahan Province.
