Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model

Autores
Cappa, Eduardo Pablo; Cantet, Rodolfo Juan Carlos
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
An individual tree model with additive direct and competition effects is introduced to account for competitive effects in forest genetics evaluation. The mixed linear model includes fixed effects as well as direct and competition breeding values plus permanent environmental effects. Competition effects, either additive or environmental, are identified in the phenotype of a competitor tree by means of ‘intensity of competition’ elements (IC), which are non-zero elements of the incidence matrix of the additive competition effects. The ICs are inverse function of the distance and the number of competing individuals, either row-column wise or diagonally. The ICs allow standardization of the variance of competition effects in the phenotypic variance of any individual tree, so that the model accounts for unequal number of neighbors. Expressions are obtained for the bias in estimating additive variance using the covariance between half-sibs, when ignoring competition effects for row-plot designs and for single-tree plot designs. A data set of loblolly pines on growth at breast height is used to estimate the additive variances of direct and competition effects, the covariance between both effects, and the variance of permanent environmental effects using a Bayesian method via Gibbs sampling and Restricted Maximum Likelihood procedures (REML) via the Expectation-Maximization (EM) algorithm. No problem of convergence was detected with the model and ICs used when compared to what has been reported in the animal breeding literature for such models. Posterior means (standard error) of the estimated parameters were σˆ 2 Ad = 12.553 (1.447), σˆ 2 Ac = 1.259 (0.259), σˆ AdAc = –3.126 (0.492), σˆ 2 p = 1.186 (0.289), and σˆ 2 e = 5.819 (1.07). Leaving permanent environmental competition effects out of the model may bias the predictions of direct breeding values. Results suggest that selection for increasing direct growth while keeping a low level of competition is feasible.
Fil: Cappa, Eduardo Pablo. Ministerio de Ciencia, Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica. Fondo para la Investigación Científica y Tecnológica; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
COMPETITION EFFECTS
INDIVIDUAL TREE MIXED MODEL
ADDITIVE AND DIRECT COMPETITION EFFECTS
ESTIMATION OF ADDITIVE (CO)VARIANCES
GIBBS SAMPLING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/130729

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network_name_str CONICET Digital (CONICET)
spelling Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed ModelCappa, Eduardo PabloCantet, Rodolfo Juan CarlosCOMPETITION EFFECTSINDIVIDUAL TREE MIXED MODELADDITIVE AND DIRECT COMPETITION EFFECTSESTIMATION OF ADDITIVE (CO)VARIANCESGIBBS SAMPLINGhttps://purl.org/becyt/ford/4.5https://purl.org/becyt/ford/4An individual tree model with additive direct and competition effects is introduced to account for competitive effects in forest genetics evaluation. The mixed linear model includes fixed effects as well as direct and competition breeding values plus permanent environmental effects. Competition effects, either additive or environmental, are identified in the phenotype of a competitor tree by means of ‘intensity of competition’ elements (IC), which are non-zero elements of the incidence matrix of the additive competition effects. The ICs are inverse function of the distance and the number of competing individuals, either row-column wise or diagonally. The ICs allow standardization of the variance of competition effects in the phenotypic variance of any individual tree, so that the model accounts for unequal number of neighbors. Expressions are obtained for the bias in estimating additive variance using the covariance between half-sibs, when ignoring competition effects for row-plot designs and for single-tree plot designs. A data set of loblolly pines on growth at breast height is used to estimate the additive variances of direct and competition effects, the covariance between both effects, and the variance of permanent environmental effects using a Bayesian method via Gibbs sampling and Restricted Maximum Likelihood procedures (REML) via the Expectation-Maximization (EM) algorithm. No problem of convergence was detected with the model and ICs used when compared to what has been reported in the animal breeding literature for such models. Posterior means (standard error) of the estimated parameters were σˆ 2 Ad = 12.553 (1.447), σˆ 2 Ac = 1.259 (0.259), σˆ AdAc = –3.126 (0.492), σˆ 2 p = 1.186 (0.289), and σˆ 2 e = 5.819 (1.07). Leaving permanent environmental competition effects out of the model may bias the predictions of direct breeding values. Results suggest that selection for increasing direct growth while keeping a low level of competition is feasible.Fil: Cappa, Eduardo Pablo. Ministerio de Ciencia, Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica. Fondo para la Investigación Científica y Tecnológica; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaJ D Sauerlanders Verlag2008-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/130729Cappa, Eduardo Pablo; Cantet, Rodolfo Juan Carlos; Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model; J D Sauerlanders Verlag; Silvae Genetica; 57; 1-6; 12-2008; 45-562509-8934CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciendo.com/article/10.1515/sg-2008-0008info:eu-repo/semantics/altIdentifier/doi/10.1515/sg-2008-0008info:eu-repo/semantics/altIdentifier/url/https://www.agro.uba.ar/users/ecappa/Index_ingles.htmlinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:52:07Zoai:ri.conicet.gov.ar:11336/130729instacron: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 09:52:08.168CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
title Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
spellingShingle Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
Cappa, Eduardo Pablo
COMPETITION EFFECTS
INDIVIDUAL TREE MIXED MODEL
ADDITIVE AND DIRECT COMPETITION EFFECTS
ESTIMATION OF ADDITIVE (CO)VARIANCES
GIBBS SAMPLING
title_short Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
title_full Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
title_fullStr Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
title_full_unstemmed Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
title_sort Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model
dc.creator.none.fl_str_mv Cappa, Eduardo Pablo
Cantet, Rodolfo Juan Carlos
author Cappa, Eduardo Pablo
author_facet Cappa, Eduardo Pablo
Cantet, Rodolfo Juan Carlos
author_role author
author2 Cantet, Rodolfo Juan Carlos
author2_role author
dc.subject.none.fl_str_mv COMPETITION EFFECTS
INDIVIDUAL TREE MIXED MODEL
ADDITIVE AND DIRECT COMPETITION EFFECTS
ESTIMATION OF ADDITIVE (CO)VARIANCES
GIBBS SAMPLING
topic COMPETITION EFFECTS
INDIVIDUAL TREE MIXED MODEL
ADDITIVE AND DIRECT COMPETITION EFFECTS
ESTIMATION OF ADDITIVE (CO)VARIANCES
GIBBS SAMPLING
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.5
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv An individual tree model with additive direct and competition effects is introduced to account for competitive effects in forest genetics evaluation. The mixed linear model includes fixed effects as well as direct and competition breeding values plus permanent environmental effects. Competition effects, either additive or environmental, are identified in the phenotype of a competitor tree by means of ‘intensity of competition’ elements (IC), which are non-zero elements of the incidence matrix of the additive competition effects. The ICs are inverse function of the distance and the number of competing individuals, either row-column wise or diagonally. The ICs allow standardization of the variance of competition effects in the phenotypic variance of any individual tree, so that the model accounts for unequal number of neighbors. Expressions are obtained for the bias in estimating additive variance using the covariance between half-sibs, when ignoring competition effects for row-plot designs and for single-tree plot designs. A data set of loblolly pines on growth at breast height is used to estimate the additive variances of direct and competition effects, the covariance between both effects, and the variance of permanent environmental effects using a Bayesian method via Gibbs sampling and Restricted Maximum Likelihood procedures (REML) via the Expectation-Maximization (EM) algorithm. No problem of convergence was detected with the model and ICs used when compared to what has been reported in the animal breeding literature for such models. Posterior means (standard error) of the estimated parameters were σˆ 2 Ad = 12.553 (1.447), σˆ 2 Ac = 1.259 (0.259), σˆ AdAc = –3.126 (0.492), σˆ 2 p = 1.186 (0.289), and σˆ 2 e = 5.819 (1.07). Leaving permanent environmental competition effects out of the model may bias the predictions of direct breeding values. Results suggest that selection for increasing direct growth while keeping a low level of competition is feasible.
Fil: Cappa, Eduardo Pablo. Ministerio de Ciencia, Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica. Fondo para la Investigación Científica y Tecnológica; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description An individual tree model with additive direct and competition effects is introduced to account for competitive effects in forest genetics evaluation. The mixed linear model includes fixed effects as well as direct and competition breeding values plus permanent environmental effects. Competition effects, either additive or environmental, are identified in the phenotype of a competitor tree by means of ‘intensity of competition’ elements (IC), which are non-zero elements of the incidence matrix of the additive competition effects. The ICs are inverse function of the distance and the number of competing individuals, either row-column wise or diagonally. The ICs allow standardization of the variance of competition effects in the phenotypic variance of any individual tree, so that the model accounts for unequal number of neighbors. Expressions are obtained for the bias in estimating additive variance using the covariance between half-sibs, when ignoring competition effects for row-plot designs and for single-tree plot designs. A data set of loblolly pines on growth at breast height is used to estimate the additive variances of direct and competition effects, the covariance between both effects, and the variance of permanent environmental effects using a Bayesian method via Gibbs sampling and Restricted Maximum Likelihood procedures (REML) via the Expectation-Maximization (EM) algorithm. No problem of convergence was detected with the model and ICs used when compared to what has been reported in the animal breeding literature for such models. Posterior means (standard error) of the estimated parameters were σˆ 2 Ad = 12.553 (1.447), σˆ 2 Ac = 1.259 (0.259), σˆ AdAc = –3.126 (0.492), σˆ 2 p = 1.186 (0.289), and σˆ 2 e = 5.819 (1.07). Leaving permanent environmental competition effects out of the model may bias the predictions of direct breeding values. Results suggest that selection for increasing direct growth while keeping a low level of competition is feasible.
publishDate 2008
dc.date.none.fl_str_mv 2008-12
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/11336/130729
Cappa, Eduardo Pablo; Cantet, Rodolfo Juan Carlos; Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model; J D Sauerlanders Verlag; Silvae Genetica; 57; 1-6; 12-2008; 45-56
2509-8934
CONICET Digital
CONICET
url http://hdl.handle.net/11336/130729
identifier_str_mv Cappa, Eduardo Pablo; Cantet, Rodolfo Juan Carlos; Direct and Competition Additive Effects in Tree Breeding: Bayesian Estimation From an Individual Tree Mixed Model; J D Sauerlanders Verlag; Silvae Genetica; 57; 1-6; 12-2008; 45-56
2509-8934
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciendo.com/article/10.1515/sg-2008-0008
info:eu-repo/semantics/altIdentifier/doi/10.1515/sg-2008-0008
info:eu-repo/semantics/altIdentifier/url/https://www.agro.uba.ar/users/ecappa/Index_ingles.html
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv J D Sauerlanders Verlag
publisher.none.fl_str_mv J D Sauerlanders Verlag
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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