In applied studies, the investigation of the relationship between a plant species and environmental variables is essential to manage ecological problems and rangeland ecosystems. This research was conducted in summer 2016. The aim of this study was to compare the predictive power of a number of Species Distribution Models (SDMs) and to evaluate the importance of a range of environmental variables as predictors in the context of rangeland vegetation. In this study, Aflah rangelands with 5721 ha were selected. In this research, predictor variables included climatic, topographic and edaphic parameters. The sampling method was equal random-classification for vegetation and soil. Topographic factors including slope, elevation and aspect were determined in Arc GIS software. In each sample unit, 10 plots were established (total 350 plots) and the lists of the species, their number, their presence or absence were recorded. The efficacy of five different modelling techniques to predict the distribution of five dominant rangeland plant species (Agropyron repens, Festuca ovina, Leucopoa sclerophylla, Stachys lavandulifolia and Tragopogon graminifolius) was evaluated. The models were generalized linear regression (GLM), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and random forest (RF). Data analysis was done using the R software, version 3.1.1. The results showed that GAM model demonstrated most consistently high predictive power over the species in the rangeland context investigated here. GAM model exhibited the most predictive power. The importance analysis of the environmental variables showed that N, pH and aspect were the most important variables in the GAM model. Overall, N, P and C/N soil (0.452, 0.437 and 0.389) were the most important environmental variables. Manuscript profile

Different indices of functional diversity as: functional richness (FRic), functional evenness (FEve) and functional divergence (FDiv), could help to understanding of the relationship between plant diversity and ecosystem function. Therefore, this study was aimed to evaluate changes in species diversity and functional diversity of vegetation under different grazing intensities in relation to soil physic-chemical properties in Changizchal rangelands, Mazandaran province, Iran. During the spring and summer of 2014. Three functional traits including Specific Leaf Area (SLA), Vegetation Height (VH), and Leaf Dry Matter Content (LDMC) were measured in three grazing intensities (low, moderate and high). Taxonomic diversity was quantified using several indices including Species richness (S), Shannon (H), Evenness (E) and Simpson (D). In addition, functional diversity was quantified using single trait-based (FDvar) and multi trait-based indices (functional richness (FRic), functional divergence (FDiv), and functional evenness (FEve). The result showed that functional richness and species richness increased at moderate grazing. Similarly, the higher values of FDvar of the SLA were observed in a moderate grazing. Whereas, the FDvar of VH values significantly increased in light grazing. The low grazing induced increase in the FDive and FEve coupled with decreasing soil organic carbon (P<0.05). The FDvar for SLA had a positive relationship with soil N and P in low grazing. Stable grazing on Changizchal rangelands tends to increase competition for soil N and P, resulting in an increase in the functional richness in grazed plant communities. The present study highlights the potential importance of low to moderate grazing intensities in mediating and reducing competition between plants for nutrient resources. Manuscript profile