Habitat suitability modelling for Gaur (<i>Bos gaurus</i>) using multiple logistic regression, remote sensing and GIS

Abstract

The aim of this study is to produce georeferenced ecological information about the suitable habitats available for gaur Bos gaurus in Chandoli tiger reserve, India (17° 04′ 00″ N to 17° 19′ 54″ N and 73° 40′ 43″ E to 73° 53′ 09″ E). Habitat suitability index (H.S.I.) was developed using multiple logistic regression (MLR) integrated with remote sensing (RS) and geographic information system (GIS). Satellite imageries of study area, acquired from Indian remote sensing satellite-P6, linear imaging self-scanning satellite-III of 2005, was digitally processed, whereas topographic maps were used for generating the collateral data in a GIS framework. Various layers of different variables such as forest density, Landuse land cover, measures of proximity to disturbances and water resources and a digital terrain model were created from satellite and topographic data. These layers along with global positioning system location of gaur presence/absence and MLR technique were integrated in a GIS environment for modelling the H.S.I. of gaur. The results indicate that approximately 91.80 km2 (31.14%) of the forest of tiger reserve is highly suitable for gaur, whereas, 115.18 km2 (39.07%) is suitable, 72.12 km2 (24.47%) moderately suitable and 15.67 km2 (5.32%) is least suitable. The accuracy level of this model is 70.7%. However, model is potent enough to advocate that forests of this area are most appropriate for declaring it as a reserve, for gaur conservation.