%0 Book Section %B Predicting Species Occurrences: Issues of Accuracy and Scale %D 2002 %T Biodiversity conflict analysis at multiple spatial scales %A Cogan, C. B. %E Scott, J. M. %E Heglund, P. J. %E Morrison, M. L. %E Haufler, J. %E Raphael, M. G. %E Wall, W. A. %E Samson, F. B. %B Predicting Species Occurrences: Issues of Accuracy and Scale %I Island Press %C Washington, DC %P 229-239 %G eng %0 Book Section %B Predicting Species Occurrences: Issues of Accuracy and Scale %D 2002 %T Biodiversity conflict analysis at multiple spatial scales %A Cogan, C. B. %E Scott, J. M. %E Heglund, P. J. %E Morrison, M. L. %E Haufler, J. %E Raphael, M. G. %E Wall, W. A. %E Samson, F. B. %B Predicting Species Occurrences: Issues of Accuracy and Scale %I Island Press %C Washington, DC %P 229-239 %8 2002 %G eng %U http://www.ets.uidaho.edu/coop/1999_symposium.htm %0 Generic %D 2001 %T Applications of Urban Growth Models and Wildlife Habitat Models to Assess Biodiversity Losses %A Cogan, C. B. %A Davis, F. W. %A Clarke, K. C. %X Habitat loss and subsequent fragmentation due to urban development is part of a larger suite of anthropogenic impacts on biodiversity, but it now ranks among the principle causes of species endangerment in the United States. Several types of urban growth simulation models have been developed which can supply useful information for biodiversity planning. In many cases however, the data required for biodiversity planning may not be compatible with the urban models, leading to analytical inaccuracies and misleading conclusions. Here, we examine several lines of logic likely to be employed in biodiversity assessment and show how assumptions built into the data influence model outcome. %I University of California, Santa Barbara %8 October, 2001 %G eng %9 Final report %0 Journal Article %J Conservation Biology %D 1993 %T Geographic analysis of California condor sighting data %A Stoms, D. M. %A Davis, F. W. %A Cogan, C. B. %A Painho, M. O. %A Duncan, B. W. %A Scepan, J. %A Scott, J. M. %K habitat suitability %K sensitivity analysis %X Observation and habitat data were compiled and analyzed in conjunction with recovery planning for the endangered California Condor (Gymnogyps californianus). A geographic information system (GIS) was used to provide a quantitative inventory of recent historical Condor habitats, to measure the association of Condor activity patterns and mapped habitat variables, and to examine spatio-temporal changes in the range of the species during its decline. Only five percent of the study area within the historic range is now used for urban or cultivated agricultural purposes. Observations of Condor feeding perching, and nesting were nonrandomly associated with mapped land cover, in agreement with life history information for the species. The precipitous decline in numbers of Condors in this century produced only a small reduction in the limits of the observed species 'range, as individual birds continued to forage over most of the range. Some critical risk factors such as shooting and lead poisoning are difficult to map and bave not been included in the database Besides the applications demonstrated in this case study, GIS can be a valuable tool for recovery planning, in the design of stratified sampling schemes, or for extrapolation of habitat models over unsurveyed regions. We conclude with recommendations from this case study regarding when to consider using GIS and the importance of pilot studies and sensitivity analysis. %B Conservation Biology %V 7 %P 148-159 %8 1993 %G eng %U ://A1993KR98600021 %0 Thesis %B Geography %D 1993 %T Quantitative Analysis of Habitat Use by the California Condor %A Cogan, C. B. %B Geography %I University of California %C Santa Barbara %P 141 %8 1993 %G eng %0 Journal Article %J Photogrammetric Engineering and Remote Sensing %D 1992 %T Sensitivity of wildlife habitat models to uncertainties in GIS data %A Stoms, D. M. %A Davis, F. W. %A Cogan, C. B. %K habitat suitability %K sensitivity analysis %X Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of "truth." Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a GIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications. %B Photogrammetric Engineering and Remote Sensing %V 58 %P 843-850 %8 1992 %G eng %U ://A1992HX38700006