Predicting distribution of major forest tree species to potential impacts of climate change in the central Himalayan region

Predicting climatic niche of species and projecting their potential range shifts in geographic distribution under future climate scenarios is essential for assessing impacts of climate change. Ecological niche-based models are widely used to map habitat suitability of current and future potential distribution of species, using precise coordinates of species occurrences, along with climatic and various environmental variables. Despite the importance of high dependence on forest resources in the Himalayan region, the direct impacts of climate change on major forest tree species is not well-documented. In the present study, we used MaxEnt (or maximum entropy) modelling to predict current distribution and changes in the future distributions of four ecologically and economically dominant forest tree species (Quercus leucotrichophora, Q. semecarpifolia, Q. floribunda, and Pinus roxburghii) in the central Himalayan region. Future predictions were based on representative concentration pathways (RCPs) for two time periods (2050s and 2070s). We demonstrated the use of MaxEnt by combining different climatic, geomorphologic, and pedologic variables as predictor variables to model the potential climatic niches. We evaluated the model performance with an average AUC value varying as 0.809 (±0.020), 0.982 (±0.008), 0.966 (±0.006), and 0.803 (±0.025) for Q. leucotrichophora, Q. semecarpifolia, Q. floribunda and P. roxburghii, respectively. Depending upon the RCPs, the results show both increase and decrease in suitable habitat range of these species across all future climate scenarios. The shifts in geographic distributions of climatic niches show unusual patterns, implying the need for urgent adaptive forest management strategies. Our approach can be used as a baseline database for broad-scale applicability in forest tree species restoration and conservation planning.