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dc.contributor.advisorZube, Ervin H.en_US
dc.contributor.authorPereira, Jose Miguel Oliveira Cardoso.
dc.creatorPereira, Jose Miguel Oliveira Cardoso.en_US
dc.date.accessioned2011-10-31T17:19:25Z
dc.date.available2011-10-31T17:19:25Z
dc.date.issued1989en_US
dc.identifier.urihttp://hdl.handle.net/10150/184821
dc.description.abstractMultivariate statistical techniques were applied to the development of habitat suitability models for the Mt. Graham red squirrel, an endangered species. A digital map data base and a geographic information system (GIS) were used to support the analysis and provide input for two logistic multiple regression models. Squirrel presence/absence is the dichotomous dependent variable whose probability the models pretend to predict. Independent variables are a set of environmental factors in the first model, and locational variables in the second case, where a logistic trend surface was developed. Bayesian statistics were then used to integrate the models into a combined model. Potential habitat losses resulting from the development of an astronomical observatory were assessed using the environmental model and are found to represent about 3% of currently available habitat.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectSquirrels -- Habitat -- Arizona -- Graham, Mount.en_US
dc.subjectHabitat (Ecology) -- Mathematical models.en_US
dc.titleA spatial approach to statistical habitat suitability modeling: The Mt. Graham red squirrel case study.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.identifier.oclc703274091en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberIttelson, William H.en_US
dc.contributor.committeememberItami, Robert M.en_US
dc.contributor.committeememberDanil, Terry C.en_US
dc.contributor.committeememberShaw, William W.en_US
dc.contributor.committeememberKvamme, Kenneth L.en_US
dc.identifier.proquest9004972en_US
thesis.degree.disciplineRenewable Natural Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-07-01T05:17:24Z
html.description.abstractMultivariate statistical techniques were applied to the development of habitat suitability models for the Mt. Graham red squirrel, an endangered species. A digital map data base and a geographic information system (GIS) were used to support the analysis and provide input for two logistic multiple regression models. Squirrel presence/absence is the dichotomous dependent variable whose probability the models pretend to predict. Independent variables are a set of environmental factors in the first model, and locational variables in the second case, where a logistic trend surface was developed. Bayesian statistics were then used to integrate the models into a combined model. Potential habitat losses resulting from the development of an astronomical observatory were assessed using the environmental model and are found to represent about 3% of currently available habitat.


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