We aimed to assess different methods for evaluating performance accuracy in species distribution models based on the application of five types of bioclimatic models under three threshold selections to predict the distributions of eight different species in Australia, treated as an independent area. Five discriminatory correlative species distribution models (SDMs), were used to predict the species distributions of eight different plants. A global training data set, excluding the Australian locations, was used for model fitting. Four accuracy measurement methods were compared under three threshold selections of i) maximum sensitivity + specificity, ii) sensitivity = specificity and iii) predicted probability of 0.5 (default). Results showed that the choice of modeling methods had an impact on potential distribution predictions for an independent area. Examination of the four accuracy methods underexamined threshold selections demonstrated that TSS is a more realistic and practical method, in comparison with AUC, Sensitivity and Specificity. Accurate projection of the distribution of a species is extremely complex. As models provided slight variances in projections of the same group of species, it may be more expedient to use TSS as an intuitive method for measuring the performances of the SDMs, in comparison to AUC, Sensitivity, and Specificity.