Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.
Identifieur interne : 000092 ( Main/Corpus ); précédent : 000091; suivant : 000093Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.
Auteurs : Allan Buras ; Marieke Van Der Maaten-Theunissen ; Ernst Van Der Maaten ; Svenja Ahlgrimm ; Philipp Hermann ; Sonia Simard ; Ingo Heinrich ; Gerd Helle ; Martin Unterseher ; Martin Schnittler ; Pascal Eusemann ; Martin WilmkingSource :
- PloS one [ 1932-6203 ] ; 2016.
English descriptors
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Abstract
This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA.
DOI: 10.1371/journal.pone.0158346
PubMed: 27467508
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Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Van Der Maaten Theunissen, Marieke" sort="Van Der Maaten Theunissen, Marieke" uniqKey="Van Der Maaten Theunissen M" first="Marieke" last="Van Der Maaten-Theunissen">Marieke Van Der Maaten-Theunissen</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Van Der Maaten, Ernst" sort="Van Der Maaten, Ernst" uniqKey="Van Der Maaten E" first="Ernst" last="Van Der Maaten">Ernst Van Der Maaten</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Ahlgrimm, Svenja" sort="Ahlgrimm, Svenja" uniqKey="Ahlgrimm S" first="Svenja" last="Ahlgrimm">Svenja Ahlgrimm</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Hermann, Philipp" sort="Hermann, Philipp" uniqKey="Hermann P" first="Philipp" last="Hermann">Philipp Hermann</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Simard, Sonia" sort="Simard, Sonia" uniqKey="Simard S" first="Sonia" last="Simard">Sonia Simard</name><affiliation><nlm:affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Heinrich, Ingo" sort="Heinrich, Ingo" uniqKey="Heinrich I" first="Ingo" last="Heinrich">Ingo Heinrich</name><affiliation><nlm:affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Helle, Gerd" sort="Helle, Gerd" uniqKey="Helle G" first="Gerd" last="Helle">Gerd Helle</name><affiliation><nlm:affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Unterseher, Martin" sort="Unterseher, Martin" uniqKey="Unterseher M" first="Martin" last="Unterseher">Martin Unterseher</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Schnittler, Martin" sort="Schnittler, Martin" uniqKey="Schnittler M" first="Martin" last="Schnittler">Martin Schnittler</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Eusemann, Pascal" sort="Eusemann, Pascal" uniqKey="Eusemann P" first="Pascal" last="Eusemann">Pascal Eusemann</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Wilmking, Martin" sort="Wilmking, Martin" uniqKey="Wilmking M" first="Martin" last="Wilmking">Martin Wilmking</name><affiliation><nlm:affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</nlm:affiliation></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Ecology</term><term>Monte Carlo Method</term><term>Principal Component Analysis</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Ecology</term><term>Monte Carlo Method</term><term>Principal Component Analysis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">27467508</PMID><DateCompleted><Year>2017</Year><Month>07</Month><Day>26</Day></DateCompleted><DateRevised><Year>2019</Year><Month>12</Month><Day>10</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>7</Issue><PubDate><Year>2016</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.</ArticleTitle><Pagination><MedlinePgn>e0158346</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0158346</ELocationID><Abstract><AbstractText>This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Buras</LastName><ForeName>Allan</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>van der Maaten-Theunissen</LastName><ForeName>Marieke</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>van der Maaten</LastName><ForeName>Ernst</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ahlgrimm</LastName><ForeName>Svenja</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hermann</LastName><ForeName>Philipp</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Simard</LastName><ForeName>Sonia</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Heinrich</LastName><ForeName>Ingo</ForeName><Initials>I</Initials><AffiliationInfo><Affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Helle</LastName><ForeName>Gerd</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>GFZ German Research Centre for Geosciences, Section 5.2, Telegrafenberg, 14473 Potsdam, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Unterseher</LastName><ForeName>Martin</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schnittler</LastName><ForeName>Martin</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Eusemann</LastName><ForeName>Pascal</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wilmking</LastName><ForeName>Martin</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-Universität, Soldmannstraße 15, 17487 Greifswald, Germany.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D023361">Validation Study</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>07</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D004463" MajorTopicYN="Y">Ecology</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009010" MajorTopicYN="N">Monte Carlo Method</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D025341" MajorTopicYN="N">Principal Component Analysis</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year><Month>07</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2016</Year><Month>06</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>7</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>7</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2017</Year><Month>7</Month><Day>27</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">27467508</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0158346</ArticleId><ArticleId IdType="pii">PONE-D-15-33439</ArticleId><ArticleId IdType="pmc">PMC4965043</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>PLoS One. 2011;6(7):e22813</Citation><ArticleIdList><ArticleId IdType="pubmed">21829523</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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