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Dornelasetal2013ProcRSocB280QuantifyingTemporalChange.pdf567.29 kBAdobe PDFView/Open
Title: Quantifying temporal change in biodiversity : challenges and opportunities
Authors: Dornelas, Maria
Magurran, Anne
Buckland, Stephen Terrence
Chao, Anne
Chazdon, Robin L
Colwell, Robert K
Curtis, Tom
Gaston, Kevin J
Gotelli, Nicolas J
Kosnik, Matthew A
McGill, Brian
McCune, Jenny L
Morlon, Hélène
Mumby, Peter J
Øvreås, Lise
Studeny, Angelika
Vellend, Mark
Keywords: Biological diversity
Legacy data
Global change
QH301 Biology
Issue Date: 7-Jan-2013
Citation: Dornelas , 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 . , 10.1098/rspb.2012.1931
Abstract: Growing 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.
Version: Publisher PDF
Status: Peer reviewed
ISSN: 0962-8452
Type: Journal article
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.
Appears in Collections:Scottish Oceans Institute Research
St Andrews Sustainablity Institute Research
Institute of Behavioural and Neural Sciences Research
Centre for Research into Ecological & Environmental Modelling (CREEM) Research
Mathematics & Statistics Research
Biology Research
University of St Andrews Research

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