Ray, Rajasri and Gururaja, KV and Ramchandra, TV (2011) Predictive distribution modeling for rare Himalayan medicinal plant Berberis aristata DC. In: Journal of Environmental Biology (JEB), 32 (6). pp. 725-730.
Predictive.pdf - Published Version
Restricted to Registered users only
Download (308Kb) | Request a copy
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 Himalayan region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. GeneticAlgorithm for Rule-set Production (GARP), Bioclim and Maximum entroys(MaxEnt). Maximum entropy 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. atistata. 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.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Triveni Enterprises.|
|Keywords:||Berberis aristata;Bioclim and Maximum entropy;Distribution modeling;GARP;Indian Himalayan region|
|Department/Centre:||Division of Biological Sciences > Centre for Ecological Sciences
|Date Deposited:||17 Nov 2011 08:57|
|Last Modified:||17 Nov 2011 08:57|
Actions (login required)