Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis

Autores
Rossi, Jean Pierre; Nardin, Maxime; Godefroid, Martin; Ruiz Diaz, Manuela; Sergent, Anne Sophie; Martinez Meier, Alejandro; Paques, Luc; Rozenberg, Philippe
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Tree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967–2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967–2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.
EEA Bariloche
Fil: Rossi, Jean Pierre. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; Francia
Fil: Nardin, Maxime. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
Fil: Godefroid, Martin. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; Francia
Fil: Ruiz Diaz Britez, Manuela. Universidad Nacional de Misiones. Parque Tecnológico Misiones; Argentina.
Fil: Sergent, Anne Sophie. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Paques, Luc. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
Fil: Rozenberg, Philippe. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
Fuente
Plos One 9 (9) : e108332. (2014)
Materia
Arboles Forestales
Anillo de Crecimiento
Procesamiento de Datos
Cambio Climático
Análisis de Datos
Forest Trees
Growth Rings
Data Processing
Climate Change
Data Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/4928
Acceder
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oai_identifier_str oai:localhost:20.500.12123/4928
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network_name_str INTA Digital (INTA)
spelling Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic AnalysisRossi, Jean PierreNardin, MaximeGodefroid, MartinRuiz Diaz, ManuelaSergent, Anne SophieMartinez Meier, AlejandroPaques, LucRozenberg, PhilippeArboles ForestalesAnillo de CrecimientoProcesamiento de DatosCambio ClimáticoAnálisis de DatosForest TreesGrowth RingsData ProcessingClimate ChangeData AnalysisTree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967–2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967–2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.EEA BarilocheFil: Rossi, Jean Pierre. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; FranciaFil: Nardin, Maxime. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; FranciaFil: Godefroid, Martin. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; FranciaFil: Ruiz Diaz Britez, Manuela. Universidad Nacional de Misiones. Parque Tecnológico Misiones; Argentina.Fil: Sergent, Anne Sophie. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Paques, Luc. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; FranciaFil: Rozenberg, Philippe. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; FranciaPlos One2019-04-17T12:46:08Z2019-04-17T12:46:08Z2014-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0108332http://hdl.handle.net/20.500.12123/49281932-6203https://doi.org/10.1371/journal.pone.0108332Plos One 9 (9) : e108332. (2014)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:29:30Zoai:localhost:20.500.12123/4928instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:29:30.689INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
title Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
spellingShingle Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
Rossi, Jean Pierre
Arboles Forestales
Anillo de Crecimiento
Procesamiento de Datos
Cambio Climático
Análisis de Datos
Forest Trees
Growth Rings
Data Processing
Climate Change
Data Analysis
title_short Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
title_full Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
title_fullStr Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
title_full_unstemmed Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
title_sort Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
dc.creator.none.fl_str_mv Rossi, Jean Pierre
Nardin, Maxime
Godefroid, Martin
Ruiz Diaz, Manuela
Sergent, Anne Sophie
Martinez Meier, Alejandro
Paques, Luc
Rozenberg, Philippe
author Rossi, Jean Pierre
author_facet Rossi, Jean Pierre
Nardin, Maxime
Godefroid, Martin
Ruiz Diaz, Manuela
Sergent, Anne Sophie
Martinez Meier, Alejandro
Paques, Luc
Rozenberg, Philippe
author_role author
author2 Nardin, Maxime
Godefroid, Martin
Ruiz Diaz, Manuela
Sergent, Anne Sophie
Martinez Meier, Alejandro
Paques, Luc
Rozenberg, Philippe
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Arboles Forestales
Anillo de Crecimiento
Procesamiento de Datos
Cambio Climático
Análisis de Datos
Forest Trees
Growth Rings
Data Processing
Climate Change
Data Analysis
topic Arboles Forestales
Anillo de Crecimiento
Procesamiento de Datos
Cambio Climático
Análisis de Datos
Forest Trees
Growth Rings
Data Processing
Climate Change
Data Analysis
dc.description.none.fl_txt_mv Tree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967–2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967–2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.
EEA Bariloche
Fil: Rossi, Jean Pierre. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; Francia
Fil: Nardin, Maxime. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
Fil: Godefroid, Martin. Institut National de la Recherche Agronomique. Centre de Biologie pour la Gestion des Populations; Francia
Fil: Ruiz Diaz Britez, Manuela. Universidad Nacional de Misiones. Parque Tecnológico Misiones; Argentina.
Fil: Sergent, Anne Sophie. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Paques, Luc. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
Fil: Rozenberg, Philippe. Institut National de la Recherche Agronomique. Amélioration Génétique et Physiologie Forestières; Francia
description Tree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967–2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967–2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
2019-04-17T12:46:08Z
2019-04-17T12:46:08Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0108332
http://hdl.handle.net/20.500.12123/4928
1932-6203
https://doi.org/10.1371/journal.pone.0108332
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0108332
http://hdl.handle.net/20.500.12123/4928
https://doi.org/10.1371/journal.pone.0108332
identifier_str_mv 1932-6203
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Plos One
publisher.none.fl_str_mv Plos One
dc.source.none.fl_str_mv Plos One 9 (9) : e108332. (2014)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.712165

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