Modelling Climate-Change Impact on the Spatial Distribution of Garra Rufa (Heckel, 1843) (Teleostei: Cyprinidae)

Climate change has been recognized as one of the biggest threats to biodiversity conservation. Therefore, predicting and quantifying the impacts of climate change on biodiversity can be useful for its conservation and management. In this regard, we forecasted climate-change effects on one of the common fish species in catches in south-western Iran, i.e. Garra rufa by using species distribution modelling tools. Seven environmental variables (i.e. basin, stream slope, bank-full width, elevation, mean air temperature, air temperature range, and annual precipitation) were used for modelling by BioMOD2 package in R software. Moreover, six modelling techniques (i.e. GLM, GAM, GBM, MARS, ANN, and RF) were applied and finally summarized by the ensemble model in order to reduce the uncertainty. According to true skill statistic, the average accuracy of the modelling was excellent (0.91). This species showed both expansion (gain) and reduction (loss) under different climate-change scenarios [optimistic and pessimistic scenarios (RCP 4.5 and RCP 8.5)] in 2050 and 2080. Consequently, in order to protect this species, it is necessary for managers to implement appropriate measures for conservation of future predicted potential suitable areas as well as areas where this species is likely disappeared.

Automated summary

The study used species distribution modeling tools to predict the impact of climate change on a common fish species in south-western Iran, Garra rufa. Seven environmental variables were used for modeling, with six modeling techniques applied and summarized by an ensemble model to reduce uncertainty. The modeling accuracy was excellent, showing both expansion and reduction of the species under different climate-change scenarios in 2050 and 2080.