Abstract

Predictive distribution modelling of Berberis aristata DC a rare, threatened plant with high medicinal values has been done with an aim to understand its potential distribution zones in Indian Himalaya Region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. Genetic Algorithm for Rule-set Production (GARP), Bioclim and Maximum Entropy (MaxEnt). MaxEnt has predicted wider potential distribution (10.36%) compared to GARP (4.63%) and Bioclim (2.44%). Validation confirms that these outputs are comparable to the present distribution pattern of the B. aristata. This exercise highlights that this species favours western Himalaya. However GARP and MaxEnt’s prediction of eastern Himalayan states (i.e. Arunachal Pradesh, Nagaland and Manipur) are also identified as potential occurrence places require further exploration.

Keywords: Berberis aristata, Bioclim, Distribution modeling, GARP, Indian Himalayan Region, MaxEnt