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Species distribution modeling has been an expedient tool. The optimization of species distribution models for Eastern Himalayan hill stream fishes remains a substantial challenge. This study has constructed a potentially informative species distribution model for an economically important and Near Threatened hill stream fish, Neolissochilus hexagonolepis. The wild habitats of this species along the Ganges-Brahmaputra basin of the Eastern Himalayas are under enormous threat. Initially, 21 predictor variables were selected based on their ecological relevance to stream fish distribution. The maximum entropy (MaxEnt) algorithm was employed to predict the habitat suitability in current and ensemble two future scenarios considering different global circulation models of climate change. Our results suggested that seasonality in annual temperature, precipitation, terrain wetness index, and eco-regional attributes had a higher contribution to the model. The fish species seems to be distributed in freshwater rivers, streams, and headwaters of lower (elevation < 500 m) to medium (elevation < 1000 m) elevation in north-eastern states of India along with other countries of Eastern Himalayas. A potential loss of current-suitable habitats is predicted in future scenarios along the lower altitudes (500 m < elevation < 1000 m). Country-wide shifts appear significant in the analysis of variance. The maximum habitat loss is projected in the sub-Himalayan belt of India and Bangladesh. The results also indicate that this species would tend to disperse towards higher altitudes and northward. Overall, this study emphasizes preserving dispersal connectivity and identifying crucial corridors for this commercially essential cold-water fish species. The stakes of becoming climate change winners for such fish species are low, considering successful colonization to upstream habitats tracking their habitat suitability.

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