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dc.contributor.authorLonergan, Michael Edward
dc.contributor.authorThompson, David
dc.contributor.authorThomas, Leonard Joseph
dc.contributor.authorDuck, Callan David
dc.date.accessioned2014-05-01T16:01:01Z
dc.date.available2014-05-01T16:01:01Z
dc.date.issued2011
dc.identifier.citationLonergan , M E , Thompson , D , Thomas , L J & Duck , C D 2011 , ' An approximate Bayesian method applied to estimating the trajectories of four British grey seal (Halichoerus grypus) populations from pup counts. ' , Journal of Marine Biology . https://doi.org/10.1155/2011/597424en
dc.identifier.issn1687-9481
dc.identifier.otherPURE: 469603
dc.identifier.otherPURE UUID: f804d5cc-7032-4bfb-9882-c535e8442521
dc.identifier.otherstandrews_research_output: 32202
dc.identifier.otherORCID: /0000-0002-7436-067X/work/29591712
dc.identifier.otherORCID: /0000-0003-1546-2876/work/56862192
dc.identifier.urihttps://hdl.handle.net/10023/4688
dc.description.abstract1. For British grey seals, as with many pinniped species, population monitoring is implemented by aerial surveys of pups at breeding colonies. Scaling pup counts up to population estimates requires assumptions about population structure; this is straightforward when populations are growing exponentially, but not when growth slows, since it is unclear whether density dependence affects pup survival or fecundity. 2. We present an approximate Bayesian method for fitting pup trajectories, estimating adult population size and investigating alternative biological models. The method is equivalent to fitting a density dependent Leslie matrix model, within a Bayesian framework, but with the forms of the density dependent effects as outputs rather than assumptions. 3. This approach requires fewer assumptions than the state space models currently used, and produces similar estimates. The simplifications made the models easier to fit, reducing their computational intensity and allowing regional differences in demographic parameters to be considered. 4. The approach is not restricted to situations where only a single component of the population is observable, but, particularly in those cases, provides a practical method for extracting information from limited datasets. 5. We discuss the potential and limitations of the method and suggest that this approach provides a useful tool for at least the preliminary analysis of similar datasets.
dc.format.extent7
dc.language.isoeng
dc.relation.ispartofJournal of Marine Biologyen
dc.rightsCopyright © 2011 Mike Lonergan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.subjectQH301 Biologyen
dc.subjectQL Zoologyen
dc.subject.lccQH301en
dc.subject.lccQLen
dc.titleAn approximate Bayesian method applied to estimating the trajectories of four British grey seal (Halichoerus grypus) populations from pup counts.en
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.identifier.doihttps://doi.org/10.1155/2011/597424
dc.description.statusPeer revieweden
dc.identifier.urlhttp://www.hindawi.com/journals/jmb/2011/597424/en


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