Validation of a geographic information system predictive habitat model for burrowing owls (Athene cunicularia) at US Army, Dugway Proving Ground - White, Boyd Winston, author; Rittenhouse, Larry R., advisor; Bunnell, Kevin D., advisor; Woodmansee, Robert George, committee member; Peel, R. Kraig, committee member (Colorado State University. Libraries, 2009)
This study was designed to validate the use of Geological Information Systems (GIS) for creating a predictive habitat model that produces raster maps of acceptable habitats for Burrowing Owls, Athene cunicularia (ATCU). The model was designed to locate ATCU habitat for long-term monitoring purposes at U.S. Army Dugway Proving Ground. ArcGIS 9 was used to manipulate data from three data layers: Southwest Regional Gap Analysis vegetation layer, slope data, and proximity to edge. A weighted index was assigned to individual pixels. The weighted index was a product of the weighting factors (0.45, 0.35, and 0.25 for vegetation types, slope and proximity, respectively times the index (3, 2, 1, 0 for excellent, fair, poor and non-habitat, respectively). The display layer was the sum of the weighted layers. The display was Excellent, Fair, Poor and Non- Habitat. Visual and auditory field observations were conducted in each of the four habitat delineations to validate the models predictive capability. In conclusion, we could not discriminate Excellent, Fair, Poor, or Non-habitat, based on the two proportions test and the Z-statistic at the 80% Confidence Interval. Validation was hampered by the low incidence of ATCU sightings in the 2008 season.
Department Head: Michael J. Manfredo.