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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/130729
Ver los metadatos del registro completo
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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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.070432 |