International Journal of Research in Engineering, Science and Management Volume-1, Issue-10, October-2018 www.ijresm.com | ISSN (Online): 2581-5782 52 Abstract—Plants have been used medicinally since pre-historic times. The pharmacological activity of chemical compounds present in medicinal plants gives them their scientific basis to be used as modern drugs. Investigations of such compounds in plants have been done by the science of ethno botany. Ethno botany limits itself in mining traditional uses of medicinal plants in drug discovery effects. Field work for plant investigation is time consuming and difficult because it needs high cost and extensive labor. However overall geographic distribution of particular medicinal plant species is of growing interest. The maximum entropy distribution modelling or Maxent model can be used to study the probability distribution of medicinal plant species over a geographical range. Provided with detailed environmental data, endangered and threatened medicinal plant species can also be studied as well as protected with help of such models. The present study is based on use of Maxent model for prediction of species based on presence only data. Maxent model helps in determining spread and explore complex relationships of environment as well as species. Accurate modelling not only helps in study the distribution pattern but also provides a platform to study the ecological as well as conservation status. Index Terms—pharmacological, ethno botany, maxent, endangered, threatened I. INTRODUCTION Remote sensing and geographic information system (RS and GIS) is a powerful technology in species distribution models. They can be used to study habitat distribution of species as well as their suitability in a particular area. The present study is an introduction to species distribution model (SDM) also known as niche modelling, habitat modelling, climate envelope- modelling etc. A common application of SDM is to predict species ranges with other factors as predictors. Remotely sensed data cannot readily identify the plant species, it needs existing environmental and spatial data to identify the potential distribution sites. Many factors would be considered, although the exact choice depends on data availability (Walker & Cocks 1991). For plant investigations various Climatic (temperature, humidity, rainfall), Edaphic (fertility, drainage), Landform (slope, aspect) factors are important for more robust analysis. Further biotic information of land cover and distribution of predators and competitors can be used (Leathwick 2002).Such distribution models are based on: 1) Locations of occurrence of species. 2) Environmental data (climatic, edaphic) etc. 3) Environmental values used along with locations to fit the model. 4) Model is finally used to predict the distribution of species over an area of interest (for past as well future also). Earlier distribution models were based on relationships with environmental gradient (Murray1866, Schimper 1903, Grinnell 1904). Many models like DIVA, BIOMAPPER (Hirzel and Guisan 2002), GAM (Yee and Mitchell 1991), GARP (Stockwell, 1999) GLM (Lehmann et al., 2002), DOMAIN (Carpenter et al., 1993BIOCLIM (Busby 1991), Maxent (Phillips et al., 2004) have been used as SDM’s (Kriticos and Randall. 2001; Philips et al., 2004; Guisan and Thuiller., 2005; Elith et al., 2006; Sun and Liu., 2010). Several studies indicated that Maxent modeling performed well or better than the other models (Phillips et al., 2006; Elith et al., 2006; Hernandez et al., 2006). It is the least biased estimate possible on the given information (Jaynes., 1957) and also estimates the probability of presence of a plant or animal species based on occurrence records and randomly generated background points by finding the maximum entropy distribution (Phillips et al., 2006). II. MATERIALS AND METHODS The datasets for distribution studies include Satellite images and DEM (digital elevation model) obtained from USGS (United States Geological Survey) source. Maximum entropy model (Maxent) uses precise Geographic coordinates (Latitude and longitude) of species occurrence. The geographic locations of a particular medicinal plant are determined using GPS (Global positioning system). Precise geographic locations with 10 to 15 reference points are to be taken for an effective evaluation. The climatic data including minimum, maximum and mean temperatures, annual rainfall representing long term Modelling Potential of Maxent Model in Predicting Geographic Distributions of Medicinal Plants Mamita Kalita 1 , P. L. N. Raju 2 , Nilakshee Devi 3 1 JRF, Department of Space, North Eastern Space Applications Centre (NESAC), Umiam, India 2 Director, Department of Space, North Eastern Space Applications Centre (NESAC), Umiam, India 3 Professor, Department of Botany, Gauhati University, Guwahati, India