Development of tiger habitat suitability model using geospatial tools—a case study in Achankmar Wildlife Sanctuary (AMWLS), Chhattisgarh India
- 238 Downloads
Geospatial tools supported by ancillary geo-database and extensive fieldwork regarding the distribution of tiger and its prey in Anchankmar Wildlife Sanctuary (AMWLS) were used to build a tiger habitat suitability model. This consists of a quantitative geographical information system (GIS) based approach using field parameters and spatial thematic information. The estimates of tiger sightings, its prey sighting and predicted distribution with the assistance of contextual environmental data including terrain, road network, settlement and drainage surfaces were used to develop the model. Eight variables in the dataset viz., forest cover type, forest cover density, slope, aspect, altitude, and distance from road, settlement and drainage were seen as suitable proxies and were used as independent variables in the analysis. Principal component analysis and binomial multiple logistic regression were used for statistical treatments of collected habitat parameters from field and independent variables respectively. The assessment showed a strong expert agreement between the predicted and observed suitable areas. A combination of the generated information and published literature was also used while building a habitat suitability map for the tiger. The modeling approach has taken the habitat preference parameters of the tiger and potential distribution of prey species into account. For assessing the potential distribution of prey species, independent suitability models were developed and validated with the ground truth. It is envisaged that inclusion of the prey distribution probability strengthens the model when a key species is under question. The results of the analysis indicate that tiger occur throughout the sanctuary. The results have been found to be an important input as baseline information for population modeling and natural resource management in the wildlife sanctuary. The development and application of similar models can help in better management of the protected areas of national interest.
KeywordsGeospatial tools Habitat Model Prey Suitability Tiger
Unable to display preview. Download preview PDF.
- Burgman, M. A., & Lindenmayer, D. B. (1998). Conservation biology for the Australian environment. Sydney: Surrey Beatty and Sons.Google Scholar
- ESRI (1999). ArcView GIS vers. 3.2. Redlands, CA, USA: Environmental Systems Research Institute, Inc.Google Scholar
- Hirzel, A. H., Hausser, J., & Perrin, N. (2006). Biomapper 3.2. Lab. For conservation biology. University of Lausanne, Lausanne. http://www.unil.ch/biomapper.
- Marcot, B. G. (2006). Characterizing species at risk I: Modeling rare species under the Northwest Forest Plan. Ecology and Society, 11, 10.Google Scholar
- SPSS (1988). SPSS-X user’s guide (3rd ed). Chicago: SPSS Inc.Google Scholar
- Stoms, D. M., Davis, F. W., & Cogan, C. B. (1992). Sensitivity of wildlife habitat models to uncertainties in GIS data. Photogrammetric Engineering and Remote Sensing, 58, 843–850.Google Scholar
- USFWS (1980). Habitat evaluation procedures report ESM 102. Washington, DC, USA: United States Fish and Wildlife Service.Google Scholar
- USFWS (1996) Habitat evaluation procedures report 870 FW 1. Washington, DC, USA: United States Fish and Wildlife Service.Google Scholar
- Wightmann, R. (1995). GIS-based forest management planning in New Brunswick. Proceedings of ninth annual symposium on geographic information systems in natural resources management (Vol. 2, pp. 503–506) Vancouver, BC, Canada. GIS World.Google Scholar
- Yamada, K., Elith, J., McCarthy, M., & Zerger, A. (2003). Eliciting and integrating expert knowledge for wildlife habitat modeling. Environmental Modelling, 165, 251–264.Google Scholar