Predicting age - age genetic correlations in tree - breeding programs : a case study

A meta-analysis of 520 parents and 5 1,439 individuals was used to develop two equations for predicting age-age genetic correlations in Pinus taeda L. Genetic and phenotypic family mean correlat ions and heritabilities were estimated for ages ranging from 2 to 25 years on 31 sites in the southern U.S. and Zimbabwe. Equations for predicting age-age correlations based on P. taeda populat ions from west and east of the Mississ ippi River proved statistically different. Both predictive equations proved conservative for validation datasets consisting of younger tests in the U.S. and Zimbabwe. Age-dependent log-linear predictive equations were favored over growth-dependent equations. All P. taedu predictive equations based on genetic correlations favored earlier selection when compared to a generalized conifer predict ive equation based on phenotypic correlat ions. The ageage correlat ions structure showed stabil i ty independent of planting density and across a wide range of family sizes. C o m m u n i c a t e d b y P . M . A . T i g e r s t e d t D.F? Gwaze Forest Research Center, P.O. Box HG595, Highlands, Harare, Zimbabwe F.E. Bridgwater (m) USDA-Forest Service, Forest Science Lab, Texas A&M University, College Station Texas 77843-2585, USA e-maii: [email protected] Fax: +409-862-2629 T.D. Byram F o r e s t S c i e n c e L a b , T e x a s A & M U n i v e r s i t y , College Station Texas 77843-2585, USA J.A. Woolliams Roslin Institute, Roslin Midlothian EH 25 9PS, Edinburgh, Scotland, UK C.G. Williams Forest Science Dept., Texas A&M University, College Station Texas 77843-2135, USA