Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics

Autores
Aráoz, Ezequiel; Morales, Juan Manuel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The loss of evidence poses a major challenge to historical ecology. For example, dendroecological studies aiming at relating tree establishment with past climate should consider the possibility that many plants might not survive to be recorded at the date of the study. A standard approach to deal with this data loss consists in fitting an exponential decay curve to the observed age structure and using the residuals of this fit as a proxy of tree establishment. Here, we show that hierarchical Bayesian analysis (HBA), where tree establishment is modeled as a latent variable, can outperform the standard approach. We illustrate the use of HBA with a simulation study in which the goal is to infer population dynamics from dendrochronological age structures. Both methods are also used to analyze empirical data from expanding Alnus acuminata Kunth forests in northwestern Argentina. The simulation study showed that the standard approach underestimated the association between rainfall and tree establishment. The HBA was unbiased and had narrower uncertainty around estimates. In the empirical study, the HBA detected effects of rainfall on tree establishment, which were deemed not significant by the standard approach. Besides these advantages, the flexibility of the HBA should allow for the analysis of more complex (and realistic) models.
Fil: Aráoz, Ezequiel. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales E Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina
Fil: Morales, Juan Manuel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentina
Materia
Bayes
Coveraje
Dendrochronology
Hierarchical Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/11646

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spelling Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamicsAráoz, EzequielMorales, Juan ManuelBayesCoverajeDendrochronologyHierarchical Analysishttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The loss of evidence poses a major challenge to historical ecology. For example, dendroecological studies aiming at relating tree establishment with past climate should consider the possibility that many plants might not survive to be recorded at the date of the study. A standard approach to deal with this data loss consists in fitting an exponential decay curve to the observed age structure and using the residuals of this fit as a proxy of tree establishment. Here, we show that hierarchical Bayesian analysis (HBA), where tree establishment is modeled as a latent variable, can outperform the standard approach. We illustrate the use of HBA with a simulation study in which the goal is to infer population dynamics from dendrochronological age structures. Both methods are also used to analyze empirical data from expanding Alnus acuminata Kunth forests in northwestern Argentina. The simulation study showed that the standard approach underestimated the association between rainfall and tree establishment. The HBA was unbiased and had narrower uncertainty around estimates. In the empirical study, the HBA detected effects of rainfall on tree establishment, which were deemed not significant by the standard approach. Besides these advantages, the flexibility of the HBA should allow for the analysis of more complex (and realistic) models.Fil: Aráoz, Ezequiel. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales E Instituto Miguel Lillo. Instituto de Ecología Regional; ArgentinaFil: Morales, Juan Manuel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; ArgentinaNatl Research Council Canada-n R C Research Press2015-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/11646Aráoz, Ezequiel; Morales, Juan Manuel; Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics; Natl Research Council Canada-n R C Research Press; Canadian Journal Of Forest Research; 45; 12; 8-2015; 1720-17270045-5067enginfo:eu-repo/semantics/altIdentifier/url/http://www.nrcresearchpress.com/doi/abs/10.1139/cjfr-2015-0073#.WIEQWvnhCJAinfo:eu-repo/semantics/altIdentifier/doi/10.1139/cjfr-2015-0073info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:47:11Zoai:ri.conicet.gov.ar:11336/11646instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:47:11.462CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
title Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
spellingShingle Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
Aráoz, Ezequiel
Bayes
Coveraje
Dendrochronology
Hierarchical Analysis
title_short Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
title_full Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
title_fullStr Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
title_full_unstemmed Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
title_sort Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics
dc.creator.none.fl_str_mv Aráoz, Ezequiel
Morales, Juan Manuel
author Aráoz, Ezequiel
author_facet Aráoz, Ezequiel
Morales, Juan Manuel
author_role author
author2 Morales, Juan Manuel
author2_role author
dc.subject.none.fl_str_mv Bayes
Coveraje
Dendrochronology
Hierarchical Analysis
topic Bayes
Coveraje
Dendrochronology
Hierarchical Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The loss of evidence poses a major challenge to historical ecology. For example, dendroecological studies aiming at relating tree establishment with past climate should consider the possibility that many plants might not survive to be recorded at the date of the study. A standard approach to deal with this data loss consists in fitting an exponential decay curve to the observed age structure and using the residuals of this fit as a proxy of tree establishment. Here, we show that hierarchical Bayesian analysis (HBA), where tree establishment is modeled as a latent variable, can outperform the standard approach. We illustrate the use of HBA with a simulation study in which the goal is to infer population dynamics from dendrochronological age structures. Both methods are also used to analyze empirical data from expanding Alnus acuminata Kunth forests in northwestern Argentina. The simulation study showed that the standard approach underestimated the association between rainfall and tree establishment. The HBA was unbiased and had narrower uncertainty around estimates. In the empirical study, the HBA detected effects of rainfall on tree establishment, which were deemed not significant by the standard approach. Besides these advantages, the flexibility of the HBA should allow for the analysis of more complex (and realistic) models.
Fil: Aráoz, Ezequiel. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales E Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina
Fil: Morales, Juan Manuel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentina
description The loss of evidence poses a major challenge to historical ecology. For example, dendroecological studies aiming at relating tree establishment with past climate should consider the possibility that many plants might not survive to be recorded at the date of the study. A standard approach to deal with this data loss consists in fitting an exponential decay curve to the observed age structure and using the residuals of this fit as a proxy of tree establishment. Here, we show that hierarchical Bayesian analysis (HBA), where tree establishment is modeled as a latent variable, can outperform the standard approach. We illustrate the use of HBA with a simulation study in which the goal is to infer population dynamics from dendrochronological age structures. Both methods are also used to analyze empirical data from expanding Alnus acuminata Kunth forests in northwestern Argentina. The simulation study showed that the standard approach underestimated the association between rainfall and tree establishment. The HBA was unbiased and had narrower uncertainty around estimates. In the empirical study, the HBA detected effects of rainfall on tree establishment, which were deemed not significant by the standard approach. Besides these advantages, the flexibility of the HBA should allow for the analysis of more complex (and realistic) models.
publishDate 2015
dc.date.none.fl_str_mv 2015-08
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 http://hdl.handle.net/11336/11646
Aráoz, Ezequiel; Morales, Juan Manuel; Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics; Natl Research Council Canada-n R C Research Press; Canadian Journal Of Forest Research; 45; 12; 8-2015; 1720-1727
0045-5067
url http://hdl.handle.net/11336/11646
identifier_str_mv Aráoz, Ezequiel; Morales, Juan Manuel; Modeling unobserved variables in dendrochronological age structures improves inferences about population dynamics; Natl Research Council Canada-n R C Research Press; Canadian Journal Of Forest Research; 45; 12; 8-2015; 1720-1727
0045-5067
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.nrcresearchpress.com/doi/abs/10.1139/cjfr-2015-0073#.WIEQWvnhCJA
info:eu-repo/semantics/altIdentifier/doi/10.1139/cjfr-2015-0073
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Natl Research Council Canada-n R C Research Press
publisher.none.fl_str_mv Natl Research Council Canada-n R C Research Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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