Key message We propose a methodology to develop a preliminary version of a growth model when tree-level growth data are unavailable. This modelling approach predicts individual tree growth using only one-time observations from temporary plots. A virtual dataset was generated by linking the whole stand and diameter distribution models. The individual tree model was parameterized using Bayesian calibration and a likelihood of diameter distributions. Context A key component of tree-level growth and yield prediction is the diameter increment model that requires at least two different points in time with individual tree measurements. In some cases, however, sufficient inventory data from remeasured permanent or semitemporary plots are unavailable or difficult to access. Aims The purpose of this study was to propose a three-stage approach for modelling individual tree diameter growth based on temporary plots. Methods The first stage is to predict stand dynamics at 5-year intervals based on stand-level resource inventory data. The second stage is to simulate diameter distribution at 5-year intervals using a Weibull function based on tree-level research inventory data. The final stage is to improve the reliability of individual tree diameter estimates by updating parameters with Bayesian calibration based on a likelihood of diameter distributions. Results The virtual-data-based diameter increment model provided logical patterns and reliable performances in both tree- and stand-level predictions. Although it underestimated the growth of suppressed trees compared with tree cores and remeasurements, this bias was negligible when aggregating tree-level simulations into stand-level growth predictions. Conclusion Our virtual-data-based modelling approach only requires one-time observations from temporary plots, but provide reliable predictions of stand- and tree-level growth when validated with tree cores and whole-stand models. This preliminary model can be updated in a Bayesian framework when growth data from tree cores or remeasurements were obtained.

中文翻译：

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使用林分模拟、直径分布和贝叶斯校准预测单个树木的生长

关键信息 我们提出了一种在无法获得树级生长数据时开发生长模型初步版本的方法。这种建模方法仅使用来自临时地块的一次性观察来预测单个树木的生长。通过链接整个林分和直径分布模型生成虚拟数据集。使用贝叶斯校准和直径分布的可能性对单个树模型进行参数化。背景 树木水平生长和产量预测的一个关键组成部分是直径增量模型，该模型需要至少两个不同的时间点对单个树木进行测量。然而，在某些情况下，重新测量的永久或半临时地块的足够清单数据不可用或难以访问。目的 本研究的目的是提出一种基于临时样地模拟单个树木直径增长的三阶段方法。方法 第一阶段是基于林分资源清单数据以 5 年为间隔预测林分动态。第二阶段是使用基于树级研究清单数据的威布尔函数以 5 年为间隔模拟直径分布。最后阶段是通过基于直径分布的可能性使用贝叶斯校准更新参数来提高单个树木直径估计的可靠性。结果 基于虚拟数据的直径增量模型在树级和林分级预测中提供了逻辑模式和可靠的性能。尽管与树芯和重新测量相比，它低估了受抑制树木的生长，当将树级模拟汇总到林分级增长预测中时，这种偏差可以忽略不计。结论我们的基于虚拟数据的建模方法只需要从临时地块中进行一次观察，但在使用树核和整个林分模型进行验证时，可以提供对林分和树木水平生长的可靠预测。当获得来自树核或重新测量的生长数据时，可以在贝叶斯框架中更新该初步模型。