Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis
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 individu...
| Main Authors: | , , , , , , , |
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
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Plos One
2019
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| Subjects: | |
| Online Access: | 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 |
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| author | Rossi, Jean Pierre Nardin, Maxime Godefroid, Martin Ruiz Diaz, Manuela Sergent, Anne Sophie Martinez Meier, Alejandro Paques, Luc Rozenberg, Philippe |
| author_browse | Godefroid, Martin Martinez Meier, Alejandro Nardin, Maxime Paques, Luc Rossi, Jean Pierre Rozenberg, Philippe Ruiz Diaz, Manuela Sergent, Anne Sophie |
| author_facet | Rossi, Jean Pierre Nardin, Maxime Godefroid, Martin Ruiz Diaz, Manuela Sergent, Anne Sophie Martinez Meier, Alejandro Paques, Luc Rozenberg, Philippe |
| author_sort | Rossi, Jean Pierre |
| collection | INTA Digital |
| 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. |
| format | info:ar-repo/semantics/artículo |
| id | INTA4928 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Plos One |
| publisherStr | Plos One |
| record_format | dspace |
| spelling | INTA49282019-04-17T12:48:02Z Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis Rossi, Jean Pierre Nardin, Maxime Godefroid, Martin Ruiz Diaz, Manuela Sergent, Anne Sophie Martinez Meier, Alejandro Paques, Luc Rozenberg, Philippe Arboles Forestales Anillo de Crecimiento Procesamiento de Datos Cambio Climático Análisis de Datos Forest Trees Growth Rings Data Processing Climate Change Data Analysis 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 2019-04-17T12:46:08Z 2019-04-17T12:46:08Z 2014-09 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 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 eng 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) application/pdf Plos One Plos One 9 (9) : e108332. (2014) |
| spellingShingle | Arboles Forestales Anillo de Crecimiento Procesamiento de Datos Cambio Climático Análisis de Datos Forest Trees Growth Rings Data Processing Climate Change Data Analysis Rossi, Jean Pierre Nardin, Maxime Godefroid, Martin Ruiz Diaz, Manuela Sergent, Anne Sophie Martinez Meier, Alejandro Paques, Luc Rozenberg, Philippe 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 |
| 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_short | 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 |
| topic | Arboles Forestales Anillo de Crecimiento Procesamiento de Datos Cambio Climático Análisis de Datos Forest Trees Growth Rings Data Processing Climate Change Data Analysis |
| 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 |
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