Distribution modelling of Tor putitora (Hamilton, 1822), an endangered cyprinid in the Himalayan river system using MaxEnt

Abstract

Freshwater fishes are threatened by habitat modification, overfishing, pollution, invasive species, and climate change. Hence, habitat assessment using geospatial technology is essential in predicting the distribution of threatened candidates. Tor putitora, an endangered game fish is declining due to indiscriminate fishing and habitat destruction. Meager attempts have been made so far to understand habitat predilection of the species. In this study, we used Maximum Entropy (MaxEnt) model with occurrence records and environmental variables. The occurrences and environmental variables were collected from survey and secondary sources and used after removing biases, multicollinearity test and contribution analysis. The model performed well with area under curve (AUC) 0.867, partial AUC 0.895 and true skill statistic (TSS) 0.756. The main contributing variables were upstream elevation (35.3%) and flow length (21.4%). The model predicted 10% suitable, 33% slight to moderate suitable and 57% unsuitable. So, modelling is useful in identifying river networks for conservation and eco-restoration of freshwater fishes.