Suitable habitat conditions for brown trout Salmo trutta, were modeled with MaxEnt software using sets of bioclimatic variables for current conditions and topographic variables for landscape and drainage conditions. Our model revealed that the most favorable conditions for brown trout were present in the Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Arunachal and Sikkim regions of the Himalayas. We analyzed 83 parameters using the MaxEnt model for Salmo trutta which showed that it was an outstanding prediction model as area under curve (AUC) was 0.947 and was very much close to 1. The major climatic factors for expansion of Salmo trutta distribution revealed that contribution of the corresponding altitudinal variable (GMTED_DEM) was 55.9%, Precipitation of Driest Quarter (Bio_17) was 22.5%, and Precipitation Seasonality (Bio_15) was 12.5% and they were the drivers of further distribution expansion of Salmo trutta in the Himalayan states. Future projections revealed significant changes in the probability distribution of the fish, where they can be of interest developing organized angling in the Himalayan regions and can contribute to the prioritization of angling and restoration sites.

Introduced alien brown trout Salmo trutta fario and rainbow trout Oncorhynchus mykiss are although abundantly available in western Himalaya, its distribution is now expanding in different Himalayan states. We present the first assessment of environmental drivers’ responsible for current distribution and potential expansion of S. trutta fario and O. mykiss in the Himalayan ecosystem. MaxEnt model was used in this study, which was overlaid with presence data into environmental layers with a total of 81 occurrence points to estimate contemporary suitable habitat. Results of this study indicated that the precipitation of driest quarter (Bio_17) contributed 71.4% for S. trutta fario and 61.1% for O. mykiss distribution respectively. The other environmental variables responsible were altitudinal variable (GMTED_DEM) 7.9% and precipitation seasonality (Bio_ 15) 10.9% for brown trout distribution. In case of O. mykiss, the contributed three layer of permutation importance were driest quarter (Bio_9) 10.8%; precipitation (Prec_03) 9.6% and length_slope 7%. Our findings facilitate understanding of bioclimatic factors responsible for expanding habitat distribution of trout and forecasting environmental variables and climate change trade-offs towards habitat regime shift in the Himalayan region of Asian continent suggesting need of their sustainable management.