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Quantifying temporal change in biodiversity: challenges and opportunities
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 statist...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3574422/ https://www.ncbi.nlm.nih.gov/pubmed/23097514 http://dx.doi.org/10.1098/rspb.2012.1931 |
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author | Dornelas, Maria Magurran, Anne E. Buckland, Stephen T. Chao, Anne Chazdon, Robin L. Colwell, Robert K. Curtis, Tom Gaston, Kevin J. Gotelli, Nicholas J. Kosnik, Matthew A. McGill, Brian McCune, Jenny L. Morlon, Hélène Mumby, Peter J. Øvreås, Lise Studeny, Angelika Vellend, Mark |
author_facet | Dornelas, Maria Magurran, Anne E. Buckland, Stephen T. Chao, Anne Chazdon, Robin L. Colwell, Robert K. Curtis, Tom Gaston, Kevin J. Gotelli, Nicholas J. Kosnik, Matthew A. McGill, Brian McCune, Jenny L. Morlon, Hélène Mumby, Peter J. Øvreås, Lise Studeny, Angelika Vellend, Mark |
author_sort | Dornelas, Maria |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3574422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-35744222013-03-01 Quantifying temporal change in biodiversity: challenges and opportunities Dornelas, Maria Magurran, Anne E. Buckland, Stephen T. Chao, Anne Chazdon, Robin L. Colwell, Robert K. Curtis, Tom Gaston, Kevin J. Gotelli, Nicholas J. Kosnik, Matthew A. McGill, Brian McCune, Jenny L. Morlon, Hélène Mumby, Peter J. Øvreås, Lise Studeny, Angelika Vellend, Mark Proc Biol Sci Review Articles 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. The Royal Society 2013-01-07 /pmc/articles/PMC3574422/ /pubmed/23097514 http://dx.doi.org/10.1098/rspb.2012.1931 Text en http://creativecommons.org/licenses/by/3.0/ © 2012 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Review Articles Dornelas, Maria Magurran, Anne E. Buckland, Stephen T. Chao, Anne Chazdon, Robin L. Colwell, Robert K. Curtis, Tom Gaston, Kevin J. Gotelli, Nicholas J. Kosnik, Matthew A. McGill, Brian McCune, Jenny L. Morlon, Hélène Mumby, Peter J. Øvreås, Lise Studeny, Angelika Vellend, Mark Quantifying temporal change in biodiversity: challenges and opportunities |
title | Quantifying temporal change in biodiversity: challenges and opportunities |
title_full | Quantifying temporal change in biodiversity: challenges and opportunities |
title_fullStr | Quantifying temporal change in biodiversity: challenges and opportunities |
title_full_unstemmed | Quantifying temporal change in biodiversity: challenges and opportunities |
title_short | Quantifying temporal change in biodiversity: challenges and opportunities |
title_sort | quantifying temporal change in biodiversity: challenges and opportunities |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3574422/ https://www.ncbi.nlm.nih.gov/pubmed/23097514 http://dx.doi.org/10.1098/rspb.2012.1931 |
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