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Generalized mixed effects models for estimating demographic parameters with mark-resight data

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dc.contributor.authorMcClintock, Brett Thomas, author
dc.contributor.authorWhite, Gary C., advisor
dc.date.accessioned2024-03-13T20:12:25Z
dc.date.available2024-03-13T20:12:25Z
dc.date.issued2008
dc.description.abstractMark-resight methods constitute a slightly different type of data than found in traditional mark-recapture, but they are in the same spirit of accounting for imperfect detection towards reliably estimating demographic parameters. Compared to mark-recapture, mark-resight can often be a less expensive and less invasive alternative in long-term population monitoring programs. However, the mark-resight estimators developed to date do not provide a flexible framework allowing the efficient use of covariates in modeling the detection process, information-theoretic model selection and multimodel inference, and the joint estimation of abundance and related demographic parameters. Here I develop a series of mark-relight models for the sampling conditions most often encountered in these studies that address this need for a more generalized framework. In Chapter 1, I introduce the the logit-normal mixed effects model (LNE) for estimating abundance when sampling is without replacement and the number of marked individuals in the population is known exactly. I compare the model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley. Fiordland National Park. I also summarize its relative performance in simulation experiments. It can often be difficult to achieve sampling without replacement or to know the exact number of harked individuals in a population. In Chapter 2, I address these limitations of LNE by introducing the (zero-truncated) Poisson-log normal mixed effects abundance model, (Z)PNE. I demonstrate the use and advantages of (Z)PNE using black-tailed prairie dog (Cynomys ludovicianus) data recently collected in Colorado. I also investigate the expected relative performance of the model in simulation experiments. In Chapter 3, I extend (Z)PNE to a full-likelihood robust design model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. I illustrate the use of the model with additional New Zealand robin data collected in Fiordland National Park, New Zealand. I also report on a series of simulation experiments evaluating the performance of the model under a variety of sampling conditions.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierETDF_McClintock_2008_3321297.pdf
dc.identifier.urihttps://hdl.handle.net/10217/237866
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.rights.licensePer the terms of a contractual agreement, all use of this item is limited to the non-commercial use of Colorado State University and its authorized users.
dc.subjectBowden's estimator
dc.subjectCynomys ludovicianus
dc.subjectdemographic parameters
dc.subjectfiordland national park
dc.subjectindividual heterogeneity
dc.subjectmark-resight data
dc.subjectNew Zealand
dc.subjectpopulation size
dc.subjectprogram mark
dc.subjectprogram noremark
dc.subjectsighting probability
dc.subjectecology
dc.subjectstatistics
dc.subjectforestry
dc.titleGeneralized mixed effects models for estimating demographic parameters with mark-resight data
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.disciplineFish, Wildlife, and Conservation Biology
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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