Modelling potential distribution of fluvial fish species for expanding conservation knowledge: Case study of the genus Barbus in Iran

Abstract

Species inhabiting fresh waters are severely influenced by anthropogenic factors. Effective management and conservation plans require high accurate and reliable species distribution forecasts. Here, we modelled potential distribution of the genus Barbus in Iran, based on environmental variables using Species Distribution Models (SDMs). Six environmental predictors (i.e. slope, bankfull width, elevation, mean air temperature, range of air temperature and annual precipitation) were applied for modelling. The models were selected among different technique (GLM, GAM, CTA, SRE, GBM, RF, MARS, and FDA) which their results were summarized through ensemble forecasting approaches. According to the TSS (True Skill Statistic), the accuracy of the implemented models was greater than 0.8. The results showed that the projected distributions not only were observed in the same recorded basins but also in the new basins. Presented results deepen the conservation knowledge in Iran and act as a guidance for management decisions aimed at legal identification of critical habitats for species as well as informing them for translocation of threatened or captive-bred populations.