Habitat suitability modelling for Gaur (Bos gaurus) 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 (178 04? 00ƒ N to 178 19? 54ƒ N and 738 40? 43ƒ E to 738 53? 09ƒ 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.

Spatial Pattern of Species Richness among Terrestrial Mammals in China

“…In keeping with this relative lack of raw geographical data, most previous research concentrated on mathematical statistical models [31][32][33], rather than including empirical information on spatial structure. However, as geographical information system (GIS) technology continues to influence research on animal distributions [34,35], we have seen powerful spatial analyses applied to biological-resource management, animal-habitat evaluation [36,37], species-distribution predictions [38][39][40], and biodiversity conservation [41][42][43].…”

Field Evaluation of Attracticides in Managing Potato Tuber Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae) in Bhutan

“…Choudhury (2002) and Duckworth et al (2008) defined habitat loss due to increase in human population as the large scale decline of Gaur range indicating it as a major threat to Gaur conservation in Asia. Imam and Kushwaha (2013) also pointed the anthropogenic pressure negatively affecting the Gaur population in CTR. Paliwal and Mathur (2012) also reported about Gaur avoiding areas where there are human presences in Tadoba Andhari Tiger Reserve in central India.…”

Impact of Judicial Doctrine and Geo Spatial Technologies in Refinement of Environmental Impact Assessment Laws and Policies in India

“…[19] The use of HS models by the U.S Fish and Wildlife Service, 1983 for Coho Salmon, [20] Sub-Saharan Africa, IUCN red listed species, [21] and spatial distribution of gaur in Chandoli tiger reserve are pointer to this effect. [22] Thus the HS Studies in EIA will be fruitful to heritage sites, defence installations inland, national boundaries coastal, marine and underground waters.…”