Introduction

The Indian Himalayan Region (IHR) harbours a wide spectrum of biodiversity which is reflected in diverse groups of flora, fauna and microorganisms. It supports about 8000 species of angiosperms of which 40% are endemics and the region is aptly considered as “hotspot” of Indian flora as well as part of the recently announced Himalaya “hotspot” (Nayar, 1996; Conservation International, 2007). The presence of rich biodiversity is mainly attributed to diverse habitat types influenced by wide altitudinal range (300 – 8000 m), varied rainfall and precipitation, temperature regime and complex topographical features (Samant et al., 1998).

The vast number of medicinal plants present in the region is an integral part of the livelihood of local communities. Apart from their medicinal usage, many plants are used as edible items, source for oil, fodder, fuel and timber which has been documented for a long time (Singh et al., 1984; Olsen and Larsen, 2003). However, the exponential increment of natural resource utilization, booming market demand and environmental changes nowadays put the medicinal plant resources under serious threat of existence (Ved et al., 2003).  The growing list of rare, threatened and endangered plants of the region is a direct outcome of these consequences.

The raising awareness towards the importance of Himalayan biodiversity and alarming rate at which they are being exploited from natural habitats leads to initiate various conservation actions to mitigate such uncontrolled resource exploitation and its management (Arunachalam et al., 2004; Rana and Samant, 2010). As a part of the conservation and management programme, species distribution and its ecological characteristic features must be taken into consideration for species protection / restoration activities (Hirzel et al., 2004; Sanchez-Cordero et al., 2005; Martinez-Meyer et al., 2006). Himalayan region requires special attention in this regard, as frequent environmental changes take place because of its mountainous nature. The enormous variation in the altitude, latitude and longitude of the Himalayas has added to the multiplicity of habitats and provides diverse microclimates and ecological niches for all the living beings (Karan, 1989; Carpenter, 2005; Anonymous, 2006). Although information on plant distribution and their environmental association in IHR are available to some extent, there is a gap in understanding species ecological amplitude and its application in systematic management of resources.

Berberis aristata, a well known medicinal plant in IHR and its occurrence is reported from middle altitude areas (1800-3000 m) of the state of Uttarakhand and Himachal Pradesh (Samant et al., 1998; Chauhan, 1999). It is a spinescent shrub, 3-6 m in height with obovate to elliptic, toothed leaves, yellow flowers in corymbose racemes and oblong-ovoid, bright red berries. The extract from root-barks, roots and lower stem-wood, (known as Rasanjana or Rasaut or Rasavanti) is used as stomachic, laxative, hepato-protective, antipyretic and in other ailments (Wang et al., 2004; Shahid et al., 2009; Semwal et al., 2010). It is useful in eye diseases particularly in conjunctivitis, indolent ulcers and in hemorrhoids (Rashmi et al., 2008). The plant is mostly collected from wild areas, and its agro-technique, cultivation is poorly known. Therefore, high demand for local usage as well as for pharmaceuticals creates a serious pressure on the natural resource which already categorized the plant as endangered (Srivastava et al., 2006; Ali et al., 2008). As a remedial measure, exploration of new resource, conservation of the existing resources and establishment of cultivation are of prime importance for what systematic planning and management is essential and where distribution modeling can play a key role.

Predictive distribution models aid in forecasting the spatial occurrence of species, especially, habitat suitability or realized niche based on the data from traditional field work in conjunction with climatic and topographic factors (such as slope, elevation, and precipitation) (Pearson, 2007). This habitat suitability or niche prediction is done through various algorithms or principles which usually integrate the species occurrence information and environmental data to find out the possible favourable places. A number of algorithms are available nowadays for performing the task and each unique to their data requirement, statistical methods and ease of use.

We selected Genetic Algorithm for Rule-set Production (GARP), Bioclim and Maximum Entropy (MaxEnt) methods for our study because of their predictive abilities and wide usage.

Precise prediction of the distribution of endemic and endangered species is useful for decision makers, especially for those whose conservation and management activities involve large areas but constrained by resources to carry out detail exploration / investigation. Potential distribution of species prioritises the favourable biogeographic areas to lead the conservation / management activity in a more focused way. The advantages of distribution modeling is manifold like, explaining basic ecological phenomenon behind species distribution, understanding biogeography and dispersal barriers, verification of the earlier presence records, explored the yet uncovered regions, assessment of impacts of environmental changes over species distribution, conservation planning and reserve system design (Peterson, 2006; Guisan and Thuiller, 2005; Johnson, 2005). Considering the extent of plant distribution and diversity in India, available data related to ecology and environmental preference still represents a small fraction of this vast field especially distribution modelling  (Ganeshaiah et al., 2003;  Irfan Ullah et al., 2007;  Giriraj et al., 2008).

In our study, we developed predictive distribution models of Berberis aristata using three different modeling techniques, GARP, Bioclim and MaxEnt to know its potential distribution in Indo-Himalayan region.