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Development of improved and comprehensive growth and yield models for genetically improved stands
Annals of Forest Science ( IF 2.5 ) Pub Date : 2020-09-01 , DOI: 10.1007/s13595-020-00995-5
Cheng Deng , Robert E. Froese , Shougong Zhang , Yuanchang Lu , Xiaojun Xu , Qingfen Li

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. 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. 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. 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. 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.

中文翻译:

为遗传改良林开发改良的综合生长和产量模型

将遗传增益纳入生长和产量模型的文献综合揭示了与遗传学和育种的快速进展以及改良林分有限经验数据相关的基本挑战。模型改进取决于对增益的生物学基础以及遗传和非遗传因素对增益的相互作用的更好理解。树木新遗传品种的持续开发需要准确的林分生长和产量模型,以使用早期生长数据预测新品种的生长轨迹和遗传增益。确定如何分析遗传品种对生长和产量模型的影响,并将遗传信息纳入这些模型,以进行准确的生长模拟和改进遗传改良林分的产量预测。遗传多样性可能会影响生长和产量模型的渐近参数、形状参数和速率参数中的一个或几个,可以通过测试模型的参数差异来评估。在确定遗传品种对模型参数的影响并考虑现有的一般林分生长方程后,通过计算遗传增益乘数、调整立地指数和校准新模型,将遗传增益纳入生长和产量模型参数。用于遗传改良林分的准确有效的生长和产量模型需要更好地了解遗传学、环境和造林措施对树木和林分生长的影响。这可以通过测试模型的参数差异来评估。在确定遗传品种对模型参数的影响并考虑现有的一般林分生长方程后,通过计算遗传增益乘数、调整立地指数和校准新模型,将遗传增益纳入生长和产量模型参数。用于遗传改良林分的准确有效的生长和产量模型需要更好地了解遗传学、环境和造林措施对树木和林分生长的影响。这可以通过测试模型的参数差异来评估。在确定遗传品种对模型参数的影响并考虑现有的一般林分生长方程后,通过计算遗传增益乘数、调整立地指数和校准新模型,将遗传增益纳入生长和产量模型参数。用于遗传改良林分的准确有效的生长和产量模型需要更好地了解遗传学、环境和造林措施对树木和林分生长的影响。通过计算遗传增益乘数、调整场地指数和校准新模型参数,可以将遗传增益纳入生长和产量模型。准确有效的遗传改良林分生长和产量模型需要更好地了解遗传学、环境和造林措施对树木和林分生长的影响。通过计算遗传增益乘数、调整场地指数和校准新模型参数,可以将遗传增益纳入生长和产量模型。用于遗传改良林分的准确有效的生长和产量模型需要更好地了解遗传学、环境和造林措施对树木和林分生长的影响。
更新日期:2020-09-01
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