Abstract
To increase the adaptability and economic value of plantations, tree improvement professionals often manage multiple traits in their breeding programs. When these traits are unfavorably correlated, breeders must weigh the economic importance of each trait and select for a desirable aggregate phenotype. Stochastic simulation allows breeders to test the effects of different breeding and selection strategies without the costs associated with empirical tests. However, most available simulation programs have limited applicability because they only model the management of a single trait. To solve this problem, we are developing a parameter-based stochastic simulation program that can model a variety of multiple-trait tree improvement strategies.
Parent Publication
Citation
Myszewski, Jennifer; Byram, Thomas; Bridgwater, Floyd. 2006. Parameter-based stochastic simulation of selection and breeding for multiple traits. Gen. Tech. Rep. SRS-92. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 357