文献类型：期刊文献

英文题名：Development of improved and comprehensive growth and yield models for genetically improved stands

作者：Deng, Cheng[1] Froese, Robert E.[2] Zhang, Shougong[3] Lu, Yuanchang[4] Xu, Xiaojun[1] Li, Qingfen[1]

第一作者：Deng, Cheng

通信作者：Li, QF[1]|[a000587a9d2fa34a2eefb]李青粉;

机构：[1]South China Agr Univ, Coll Forestry & Landscape Architecture, Guangzhou, Peoples R China;[2]Michigan Technol Univ, Sch Forest Resources & Environm Sci, Houghton, MI 49931 USA;[3]Chinese Acad Forestry, Res Inst Forestry, Beijing, Peoples R China;[4]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing, Peoples R China

年份：2020

卷号：77

期号：3

外文期刊名：ANNALS OF FOREST SCIENCE

收录：;Scopus(收录号：2-s2.0-85090342854);WOS:【SCI-EXPANDED(收录号:WOS:000570946000002)】；

基金：This research was funded by the Central Public-Interest Scientific Institution Basal Research Fund for Chinese Academy of Forestry (grant number IFRIT201501).

语种：英文

外文关键词：Genetically improved stands; Growth difference; Genetic gain; Growth simulation; Yield prediction

摘要：Key message This synthesis of the literature on incorporation of genetic gain into growth and yield models reveals a fundamental challenge associated with the rapid progress in genetics and breeding and limited empirical data on improved stands. Model improvements depend on a better understanding of both the biological basis for gain and of interactions between genetic and non-genetic factors on gain. Context Continued development of new genetic varieties of trees requires accurate stand growth and yield models to predict growth trajectories and genetic gain of the new varieties using early-age growth data. Aims To identify how the effects of genetic variety on growth and yield models could be analyzed and genetic information could be incorporated into these models for accurate growth simulation and improved yield prediction of genetically improved stands. Results Genetic variety may affect one or several of the asymptotic parameters, shape parameters, and rate parameters of growth and yield models, which can be assessed by testing the parameter differences of the models. After determination of the influence of genetic varieties on model parameters and considering the existing general stand growth equation, the genetic gain can be incorporated into growth and yield models by calculation of genetic gain multipliers, adjustment of the site index, and calibration of the new model parameters. Conclusion Accurate and effective growth and yield models for genetically improved stands require a better understanding of the effects of genetics, environment, and silviculture measures on tree and stand growth.