@article {775,
	title = {Choosing surrogates for biodiversity conservation in complex planning environments},
	journal = {Journal of Conservation Planning},
	volume = {1},
	year = {2005},
	month = {2005},
	pages = {44-63},
	abstract = {The coarse filter/fine filter hypothesis suggests that by conserving high-quality examples of all ecological systems along with imperiled species and communities, we could protect the majority of native biodiversity. Given the cost of data collection, conservation planners might wonder how large this set of elements must be. We conducted an analysis of the sensitivity of selecting a set of reserves to the choice of surrogates in Napa County, California, USA. The study evaluated the extent to which conservation goals for the coarse/fine-filter elements were met by surrogates and whether the same general locations were being selected. Napa County represents a data-rich setting, whereas the test surrogates portrayed a range of circumstances where less data are available. A worst (data-poor) case, based only on landscape condition with no biological data, was tested to identify the value of improved information. Our results suggest that in complex planning environments, there are no simple shortcuts in collecting data. None of the surrogate sets was particularly effective at meeting all the goals for the full set of baseline elements. There was also relatively low spatial congruence between the test solutions and the baseline. However, we did find that all combinations of surrogates provided some degree of protection in notional reserves, suggesting that in less complex planning problems, simpler surrogates can serve a useful function. Studies like this will help planners gauge how much effort it is prudent to spend in compiling spatial data relative to the risks and irreplaceability to native biodiversity.},
	keywords = {coarse-filter, conservation planning, fine-filter, Napa County, reserve selection, sensitivity analysis, Sites, surrogates},
	url = {http://www.journalconsplanning.org/2005/volume1/issue1/stoms/manuscript.pdf},
	author = {Stoms, D. M. and Comer, P. J. and Crist, P. J. and Grossman, D. H.}
}
@article {782,
	title = {Geographic analysis of California condor sighting data},
	journal = {Conservation Biology},
	volume = {7},
	year = {1993},
	month = {1993},
	pages = {148-159},
	abstract = {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 {\textquoteright}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.},
	keywords = {habitat suitability, sensitivity analysis},
	url = {<Go to ISI>://A1993KR98600021},
	author = {Stoms, D. M. and Davis, F. W. and Cogan, C. B. and Painho, M. O. and Duncan, B. W. and Scepan, J. and Scott, J. M.}
}
@article {763,
	title = {Effects of habitat map generalization in biodiversity assessment},
	journal = {Photogrammetric Engineering and Remote Sensing},
	volume = {58},
	year = {1992},
	month = {1992},
	pages = {1587-1591},
	abstract = {Species richness is being mapped as part of an inventory of biological diversity in California (i.e., gap analysis). Species distributions are modeled with a GIS on the basis of maps of each species{\textquoteright} preferred habitats. Species richness is then tallied in equal-area sampling units. A GIS sensitivity analysis examined the effects of the level of generalization of the habitat map on the predicted distribution of species richness in the southern Sierra Nevada. As the habitat map was generalized, the number of habitat types mapped within grid cells tended to decrease with a corresponding decline in numbers of species predicted. Further, the ranking of grid cells in order of predicted numbers of species changed dramatically between levels of generalization. Areas predicted to be of greatest conservation value on the basis of species richness may therefore be sensitive to GIS data resolution.},
	keywords = {habitat suitability, scale, sensitivity analysis, species richness},
	url = {<Go to ISI>://A1992JV67200007},
	author = {Stoms, D. M.}
}
@article {781,
	title = {Sensitivity of wildlife habitat models to uncertainties in GIS data},
	journal = {Photogrammetric Engineering and Remote Sensing},
	volume = {58},
	year = {1992},
	month = {1992},
	pages = {843-850},
	abstract = {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.},
	keywords = {habitat suitability, sensitivity analysis},
	url = {<Go to ISI>://A1992HX38700006},
	author = {Stoms, D. M. and Davis, F. W. and Cogan, C. B.}
}
