Tuyển tập các báo cáo nghiên cứu về lâm nghiệp được đăng trên tạp chí lâm nghiệp quốc tế đề tài: Improving models of wood density by including genetic effects: A case study in Douglas-fir. | 385 Ann. For. Sci. 58 2001 385-394 INRA EDP Sciences 2001 Original article Improving models of wood density by including genetic effects A case study in Douglas-fir Philippe Rozenberg Alain Franc Catherine Bastien and Christine Cahalan INRA Centre de Recherches d Orléans Avenue de la Pomme de Pin BP 20169 Ardon 45166 Olivet Cedex France Received 6 March 2000 accepted 4 January 2001 Abstract - Many models have been published for relating wood characteristics such as wood density to growth traits. At a tree population level ring density is known to be significantly correlated with cambial age and ring width. However at the individual tree level the predictive value of models based on this relationship is usually poor as there is an important so-called tree effect in the residuals of such models. We hypothesise that this effect arises from within population genetic variability and have tested this hypothesis by adjusting linear models for Douglas-fir populations with different levels of genetic variability ranging from provenances to clones. The addition of a genetic effect significantly increased the predictive value of the model and decreased the residuals. At the clone level for example inclusion of the genetic effect increased the explained variance adjusted R2 value from 20 to 54 . It is suggested that most of the observed variability in the wood density growth relationship of Douglas-fir populations has a genetic origin. genetics model wood density ring width cambial age Douglas-fir Résumé - Amelioration de modèles de densité du bois par l introduction d effets génétiques une étude de cas chez le Douglas. De nombreux modèles ont été publiés mettant en relation chez de nombreuses espèces des propriétés du bois avec des caractères de croissance. A l échelle de la population d arbres on sait que la densité d un cerne dépend significativement de sa largeur et de son âge cambial. Toutefois la valeur predictive de ce type de relation est généralement faible à cause de
