Quantifying temporal change in biodiversity: challenges and opportunities

Maria Dornelas*, Anne E. Magurran, Stephen T. Buckland, Anne Chao, Robin L. Chazdon, Robert K. Colwell, Tom Curtis, Kevin J. Gaston, Nicholas J. Gotelli, Matthew A. Kosnik, Brian McGill, Jenny L. McCune, Hélène Morlon, Peter J. Mumby, Lise Øvreås, Angelika Studeny, Mark Vellend

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    177 Citations (Scopus)


    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, unidimensionality, 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.

    Original languageEnglish
    Article number20121931
    Pages (from-to)1-10
    Number of pages10
    JournalProceedings of the Royal Society B: Biological Sciences
    Issue number1750
    Publication statusPublished - 2013


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