Geospatial Multiple Logistic Regression Approach for Habitat Characterization of scarce Plant Population: A case study of Pittosporum eriocarpum Royle (An Endemic Species of Uttarakhand, India)

Increasing concern for biodiversity conservation at species level resulted in the development of cost effective tools for getting information at larger scale. Modeling distribution of species using remote sensing and geographic information has already proved its potentials to get such information with less effort. Pittosporum eriocarpum Royle is an endemic and threatened tree species of Uttarakhand, yet till now its regional distribution is poorly known. This study using geospatial modelling tools indentified several localities of potential occurrence of this species in the Mussoorie hills and Doon valley, and also provides information on its habitat specificity. The main objective of the study is to predict the suitable habitats for endangered plant species in Himalayan region using logistic regression model where availability of sufficient data on species presence-absence is a major limitation for larger areas.