AMAP, Université de Montpellier, CIRAD, CNRS, INRA, IRD, Montpellier, France.
Université de Lomé, Faculté des Sciences, Département de Botanique, Lomé, Togo.
Ann Bot. 2018 Jun 8;121(7):1397-1410. doi: 10.1093/aob/mcy040.
For a given genotype, the observed variability of tree forms results from the stochasticity of meristem functioning and from changing and heterogeneous environmental factors affecting biomass formation and allocation. In response to climate change, trees adapt their architecture by adjusting growth processes such as pre- and neoformation, as well as polycyclic growth. This is the case for the teak tree. The aim of this work was to adapt the plant model, GreenLab, in order to take into consideration both these processes using existing data on this tree species.
This work adopted GreenLab formalism based on source-sink relationships at organ level that drive biomass production and partitioning within the whole plant over time. The stochastic aspect of phytomer production can be modelled by a Bernoulli process. The teak model was designed, parameterized and analysed using the architectural data from 2- to 5-year-old teak trees in open field stands.
Growth and development parameters were identified, fitting the observed compound organic series with the theoretical series, using generalized least squares methods. Phytomer distributions of growth units and branching pattern varied depending on their axis category, i.e. their physiological age. These emerging properties were in accordance with the observed growth patterns and biomass allocation dynamics during a growing season marked by a short dry season.
Annual growth patterns observed on teak, including shoot pre- and neoformation and polycyclism, were reproduced by the new version of the GreenLab model. However, further updating is discussed in order to ensure better consideration of radial variation in basic specific gravity of wood. Such upgrading of the model will enable teak ideotypes to be defined for improving wood production in terms of both volume and quality.
对于给定的基因型,观察到的树木形态变异是由于分生组织功能的随机性以及影响生物量形成和分配的变化和异质环境因素造成的。为了应对气候变化,树木通过调整生长过程(如预形成和新形成以及多循环生长)来适应其结构。柚木就是这种情况。这项工作的目的是通过利用有关该树种的现有数据,调整植物模型 GreenLab 以考虑这两个过程。
这项工作采用了基于器官水平源库关系的 GreenLab 形式主义,该关系驱动整个植物随时间的生物质生产和分配。可以通过伯努利过程对植物分生组织的产生进行随机建模。使用来自大田林分的 2 至 5 年生柚木的建筑数据设计、参数化和分析了柚木模型。
使用广义最小二乘法确定了生长和发育参数,这些参数与观察到的复合有机系列拟合,理论系列,使用广义最小二乘法。生长单元和分枝模式的分生组织分布因它们的轴类别(即它们的生理年龄)而异。这些新兴特性与在以短旱季为特征的生长季节中观察到的生长模式和生物量分配动态一致。
GreenLab 模型的新版本再现了柚木的年度生长模式,包括新梢的预形成和新形成以及多循环性。然而,为了确保更好地考虑木材基本比重的径向变化,讨论了进一步的更新。这种模型的升级将使人们能够定义柚木理想型,以提高木材的产量和质量。