Predicting the impacts of climate change on the potential distribution pattern of endangered Himalayan natives (Ulmus wallichiana and U. villosa) in Pakistan

Climate change negatively affects living biota and environment, particularly for those of restricted ecology and distribution range. Here, we applied the maximum entropy algorithm (MaxEnt) to predict the current and future potential distribution of Ulmus wallichiana and U. villosa in Himalayas of Pakistan to provide a basis for its protection and conservation. A total of 353 occurrence points were collected from both species across the study area during 2017–2019. In total, 19 bioclimatic and three topographic variables were used to model the potential distribution area under the current and future scenarios. Predicted suitable habitat layers for Ulmus wallichiana and U. villosa were generated through MaxEnt model. The overall performance of the modeling was positive. Area under the curve values recorded were 0.980 and 0.947 for training data of Ulmus wallichiana and U. villosa. Bio 4 was recorded as the strongest contributor for both the species. The jackknife test illustrated the same variable with highest gain. In the study area, the estimated area of occupancy in the observed localities was about 68 and 156 km2 for Ulmus wallichiana and U. villosa. Nonetheless, the cover area for Ulmus wallichiana and U. villosa as predicted by model will be 45 and 126 km2, respectively. The prediction model illustrated significant depletion in cover as well as in shifting of both the species. Our results highlight the impact of future climate change on two threatened and valuable species. The results can be further useful to initiate farming of these ecologically and economically important species based on climatically suitable zone and for designing a germplasm conservation strategy.