Development of improved and comprehensive growth and yield models for genetically improved stands
- PDF / 518,759 Bytes
- 12 Pages / 595.276 x 790.866 pts Page_size
- 37 Downloads / 166 Views
REVIEW PAPER
Development of improved and comprehensive growth and yield models for genetically improved stands Cheng Deng 1 & Robert E. Froese 2 & Shougong Zhang 3 & Yuanchang Lu 4 & Xiaojun Xu 1 & Qingfen Li 1 Received: 5 February 2020 / Accepted: 27 August 2020 # INRAE and Springer-Verlag France SAS, part of Springer Nature 2020
Abstract & 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. Keywords Genetically improved stands . Growth difference . Genetic gain . Growth simulation . Yield prediction
1 Introduction Growth and yield models can simulate the natural growth processes of trees, stands, and forests and reflect the impact of management measures on development and condition,
making these effective tools to consider dynamic changes of spatial and temporal stand structure and to accurately predict response to management interventions (Cao and Strub 2008; Pretzsch 2009; Weiskittel et al. 2011; Orellana et al. 2016; Soukhovolsky and Ivanova 2018). Forestry research and
Handling Editor: John M Lhotka * Qingfen Li [email protected] Cheng Deng [email protected]
Xiaojun Xu [email protected] 1
College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
2
School of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI, USA
Shougong Zhang [email protected]
3
Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
Yuanchang Lu [email protected]
4
Data Loading...
