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dc.contributor.authorCaillat, Marjolaine
dc.contributor.authorCordes, Line
dc.contributor.authorThompson, Paul
dc.contributor.authorMatthiopoulos, Jason
dc.contributor.authorSmout, Sophie
dc.date.accessioned2020-09-05T23:35:11Z
dc.date.available2020-09-05T23:35:11Z
dc.date.issued2019-09-06
dc.identifier.citationCaillat , M , Cordes , L , Thompson , P , Matthiopoulos , J & Smout , S 2019 , ' Use of state-space modelling to identify ecological covariates associated with trends in pinniped demography ' , Aquatic Conservation: Marine and Freshwater Ecosystems , vol. 29 , no. S1 , pp. 101-118 . https://doi.org/10.1002/aqc.3130en
dc.identifier.issn1052-7613
dc.identifier.otherPURE: 261125995
dc.identifier.otherPURE UUID: ff19a4ae-66e4-4fb1-9f7b-8a0cdbe8f228
dc.identifier.otherRIS: urn:710B589BB0D7FCE87FA61FB2408BD897
dc.identifier.otherScopus: 85071891869
dc.identifier.otherWOS: 000484997200008
dc.identifier.urihttp://hdl.handle.net/10023/20566
dc.descriptionFunding information: Marine Scotland. Grant Number: MMSS/001/11en
dc.description.abstract1. Identifying and understanding ecological drivers that influence wildlife populations is challenging but critical for conservation. This typically requires integrating long-term data on both the population and potential drivers within statistical models that are suitable for analysing these complex relationships. State-space models offer one method for integrating such data. Once implemented within a Bayesian framework, these analyses can control for multifactorial influences on populations, allowing one to extract otherwise undetectable correlations between the environment and the underlying, inferred demography. 2. In the Moray Firth, Scotland, harbour seals have been counted annually for 30 years (1988?2018). A Bayesian state-space model was used to explore whether patterns in vital rates were correlated to changes in prey abundance, inter-specific competition (grey seal abundance), environmental variables [the North Atlantic Oscillation (NAO) and sea-surface temperature], or level of biotoxins (saxitoxin and domoic acid) in the Moray Firth waters. 3. The credible interval of the posterior distributions of three of these covariate coefficients (sandeel proxy, NAO and grey seal abundance) suggested that there was a relationship between those covariates and vital rates. Both the sandeel proxy and NAO showed a positive correlation with fecundity, whereas grey seal abundance had a negative impact on pup survival. 4. This work demonstrates how an integrated state-space modelling approach can bring together diverse data sets and point to important interactions with prey, and with other predators in the system. This suggests that the wider-scale management of UK harbour seal populations with their contrasting temporal trends needs to account for variation in the marine ecosystem at appropriate spatial scales, in line with current policy concerning spatial planning in the marine environment.
dc.format.extent18
dc.language.isoeng
dc.relation.ispartofAquatic Conservation: Marine and Freshwater Ecosystemsen
dc.rightsCopyright © 2019 John Wiley & Sons, Ltd. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1002/aqc.3130en
dc.subjectBayesianen
dc.subjectEnvironmental changeen
dc.subjectFecundityen
dc.subjectHarbour sealen
dc.subjectInter-specific competitionen
dc.subjectPopulation changeen
dc.subjectPrey availabilityen
dc.subjectSurvivalen
dc.subjectQH301 Biologyen
dc.subjectDASen
dc.subject.lccQH301en
dc.titleUse of state-space modelling to identify ecological covariates associated with trends in pinniped demographyen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1002/aqc.3130
dc.description.statusPeer revieweden
dc.date.embargoedUntil2020-09-06


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