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Statistical models for animal movement and landscape connectivity

dc.contributor.authorHanks, Ephraim M., author
dc.contributor.authorHooten, Mevin B., advisor
dc.contributor.authorHoeting, Jennifer, committee member
dc.contributor.authorWang, Haonan, committee member
dc.contributor.authorAlldredge, Mat, committee member
dc.contributor.authorTheobald, David, committee member
dc.date.accessioned2007-01-03T05:53:41Z
dc.date.available2007-01-03T05:53:41Z
dc.date.issued2013
dc.description.abstractThis dissertation considers statistical approaches to the study of animal movement behavior and landscape connectivity, with particular attention paid to modeling how movement and connectivity are influenced by landscape characteristics. For animal movement data, a novel continuous-time, discrete-space model of animal movement is proposed. This model yields increased computational efficiency relative to existing discrete-space models for animal movement, and a more flexible modeling framework than existing continuous-space models. In landscape genetic approaches to landscape connectivity, spatially-referenced genetic allele data are used to study landscape effects on gene flow. An explicit link is described between a common circuit-theoretic approach to landscape genetics and variogram fitting for Gaussian Markov random fields. A hierarchical model for landscape genetic data is also proposed, with a multinomial data model and latent spatial random effects to model spatial correlation.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierHanks_colostate_0053A_11890.pdf
dc.identifier.urihttp://hdl.handle.net/10217/80147
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.titleStatistical models for animal movement and landscape connectivity
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineStatistics
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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