Improving Genetic Analysis of Corymbia citriodora subsp. variegata with Single- and Multiple-Trait Spatial-Competition Models

Author:

Hernández Mariano Agustín1,López Juan Adolfo1,Cappa Eduardo Pablo23ORCID

Affiliation:

1. Instituto Nacional de Tecnología Agropecuaria, Corrientes, Argentina

2. Instituto Nacional de Tecnología Agropecuaria, Instituto de Recursos Biológicos, Centro de Investigación en Recursos Naturales, Hurlingham, Buenos Aires, Argentina

3. Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina

Abstract

Abstract Environmental heterogeneity and/or genetic and environmental competition were quantified on two growth traits, diameter at breast height and total height, and wood density in a progeny trial of Corymbia citriodora subsp. variegata. Three single-trait mixed models with random spatial and/or competition effects were compared to a standard analysis by analyzing fit, dispersion parameters, accuracy of breeding values, genetic gains, and ranking of trees. In addition, a multiple-trait spatial-competition model was fitted to estimate correlations among direct and indirect additive genetic effects, and to explore relations between traits. Single-trait analyses with spatial and/or competition effects outperformed the standard model. However, the performance of these models depended on the sensitivity of each trait to detect each effect. Direct–indirect genetic correlations from the multiple-trait spatial-competition model showed inverse and strong relations among growth traits and wood density, suggesting that growth traits can be affected by competition and environmental heterogeneity, but also wood density might be influenced by these effects. The approach proposed was useful to improve the genetic analysis of the species as well as to gain an understanding of the genetic relations between traits under the influence of environmental heterogeneity and competition.

Funder

Agencia Nacional de Ciencia y Tecnología

Publisher

Oxford University Press (OUP)

Subject

Ecological Modeling,Ecology,Forestry

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