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dc.contributor.authorDornelas, Maria
dc.contributor.authorMagurran, Anne
dc.contributor.authorBuckland, Stephen Terrence
dc.contributor.authorChao, Anne
dc.contributor.authorChazdon, Robin L
dc.contributor.authorColwell, Robert K
dc.contributor.authorCurtis, Tom
dc.contributor.authorGaston, Kevin J
dc.contributor.authorGotelli, Nicolas J
dc.contributor.authorKosnik, Matthew A
dc.contributor.authorMcGill, Brian
dc.contributor.authorMcCune, Jenny L
dc.contributor.authorMorlon, Hélène
dc.contributor.authorMumby, Peter J
dc.contributor.authorØvreås, Lise
dc.contributor.authorStudeny, Angelika
dc.contributor.authorVellend, Mark
dc.identifier.citationDornelas , M , Magurran , A , Buckland , S T , Chao , A , Chazdon , R L , Colwell , R K , Curtis , T , Gaston , K J , Gotelli , N J , Kosnik , M A , McGill , B , McCune , J L , Morlon , H , Mumby , P J , Øvreås , L , Studeny , A & Vellend , M 2013 , ' Quantifying temporal change in biodiversity : challenges and opportunities ' , Proceedings of the Royal Society B: Biological Sciences , vol. 280 , no. 1750 , 20121931 .
dc.identifier.otherPURE: 40852888
dc.identifier.otherPURE UUID: 6d0bb115-817c-4b91-bd53-8a546bb898c6
dc.identifier.otherWOS: 000311943100007
dc.identifier.otherScopus: 84869843025
dc.identifier.otherORCID: /0000-0002-0036-2795/work/43550266
dc.identifier.otherORCID: /0000-0002-9939-709X/work/73701074
dc.description.abstractGrowing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series—lack of physical boundaries, uni-dimensionality, autocorrelation and directionality—that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.
dc.relation.ispartofProceedings of the Royal Society B: Biological Sciencesen
dc.rights© 2012 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.en
dc.subjectBiological diversityen
dc.subjectLegacy dataen
dc.subjectGlobal changeen
dc.subjectQH301 Biologyen
dc.titleQuantifying temporal change in biodiversity : challenges and opportunitiesen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.Fish Behaviour and Biodiversity Research Groupen
dc.contributor.institutionUniversity of St Andrews.Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews.St Andrews Sustainability Instituteen
dc.contributor.institutionUniversity of St Andrews.Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews.School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews.Centre for Biological Diversityen
dc.description.statusPeer revieweden

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