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Journal of Environmental Biology

pISSN: 0254-8704 ; eISSN: 2394-0379 ; CODEN: JEBIDP

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    Abstract - Issue Nov 2011, 32 (6)                                     Back


nstantaneous and historical temperature effects on a-pinene

Predictive distribution modeling for rare Himalayan

medicinal plant Berberis aristata DC

 

Author Details

 

Rajasri Ray

Energy and Wetland Research Group, Centre for Ecological Sciences, Indian Institute of Science,

Bangalore - 560 012, India

K.V. Gururaja

Energy and Wetland Research Group, Centre for Ecological Sciences, Indian Institute of Science,

Bangalore - 560 012, India

T.V. Ramchandra

(Corresponding author)

Energy and Wetland Research Group, Centre for Ecological Sciences, Indian Institute of Science,

Bangalore - 560 012, India

e-mail: cestvr@ces.iisc.ernet.in

 

 

Publication Data

Paper received:

15 May 2010

 

Revised received:

21 October 2010

 

Accepted:

20 November 2010

 

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 Himalayan 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). 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. 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.

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Key words

Berberis aristata, Bioclim and Maximum entropy, Distribution modeling, GARP, Indian Himalayan region

 

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