Faraham Ahmadzadeh; Negar Amiri; Elham Ebrahimi
Volume 10, Issue 2 , September 2018, , Pages 95-108
Abstract
Today, it is well-known that predicting the distribution potential of endangered species by usingspatial modeling methods is highly beneficial and using these methods can greatly contribute toecological conservation and management. Rana pesudodalmatina is one of the Iranian endemicamphibian species of ...
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Today, it is well-known that predicting the distribution potential of endangered species by usingspatial modeling methods is highly beneficial and using these methods can greatly contribute toecological conservation and management. Rana pesudodalmatina is one of the Iranian endemicamphibian species of Iran. In order to predict the potential geographic distribution of the species itsoccurrence points were collected through field work and 19 so-called bioclim climate variables asspatial environmental predictors were extracted from the Worldclim database. By applying Pearsoncorrelation test, the highly correlated variables with correlation coefficient of 0.75 were eliminated.Species distribution modeling was done using newly published R package which includes GLM,GAM, RF, MARS, CART, FDA, BRT and SVM models. All individual models were compound as anensemble to reduce the uncertainty which increase the accuracy and predictive power. The resultsrevealed that the long-legged wood frog has maximum distribution potential in Hyrcanian forest ofIran. Also, the results of the valuation of the models showed that the AUC and TSS had better statusand the SVM model was the most credible. In addition, the results of measuring the importance ofeach of the variables showed that BIO6 had the highest and BIO19 had the least importance for this.
