Maxent modelling for distribution of plant species habitats of rangelands (Iran)

Quantifying the pattern of habitat distribution for range plant species can assist sustainable planning of rangeland use and management. However, data of plant species distribution are often scarce and modeling of habitat distribution using commonly used models is difficult. In this study, the Maximum Entropy Method (Max-Ent) was used to model the distribution of plant habitat to find the effective variables in plant species occurrence in the Poshtkouh rangelands on Yazd province, central Iran. Maps of the environmental variables were generated using GIS and Geostatistics facilities. Accuracy of model output was assessed using area under the curve (AUC) of the receiver operating characteristic and keeping 30 percent of the data. Evaluation of model accuracy by AUC indicated good and acceptable predictive accuracy for all plant species habitats, except Artemisia sieberi which had high frequency. The predictive maps of Artemisia aucheri, Scariola orientalis Astragalus albispinus, A. sieberi, and A. sieberi Zygophyllum eurypterum had fair agreement with their corresponding observed maps. In addition, the accuracy of S. orientalis - A. sieberi and Tamarix ramosissima predictive maps was low and the estimated conformity rate of prediction and observed maps was poor. In fact, due to differences in the optimal ecological range, level of agreement of predictive and observed maps at each site was different. MaxEnt was substantially excellent to predict distributions of plant species habitat with narrow ecological niches e.g. Rheum ribes - A. sieberi, Seidlitzia rosmarinus and Cornulaca monacantha. It can also perform well with fairly few samples due to employing regularization.