1. Stem analysis allows us to obtain an abundant amount of information on tree growth. A couple of algorithms exist to utilize section height and growth ring data for reconstructing height and age time-series information.
2. I evaluated two alternatives, a well-known and a newly proposed algorithm using stem analysis data of four species, including deciduous and evergreen broadleaves and a conifer. I reconstructed height–age pairs by both algorithms. I fit height growth equations in a mixed-effects model framework for each species, using the generated data with the respective algorithm. Comparisons considered confidence intervals of the estimated parameters, as well as regression-based equivalence tests.
3. Results showed that the fitted growth models obtained from both stem analysis algorithms were statistically equivalent. However, the proposed algorithm is simpler and thus provides a useful alternative to current methods.
4. Based on the findings, I recommend using this new stem analysis algorithm to reconstruct tree height growth with stem analysis data.

中文翻译：

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一种利用茎分析数据重建树高生长的新算法

1. 茎分析使我们能够获得大量有关树木生长的信息。存在几种算法来利用截面高度和年轮数据来重建高度和年龄时间序列信息。
2. 我评估了两个替代方案，一个众所周知的算法和一个新提出的算法，使用四种物种的茎分析数据，包括落叶和常绿阔叶树和针叶树。我通过两种算法重建了身高-年龄对。我使用生成的数据和相应的算法在每个物种的混合效应模型框架中拟合高度增长方程。比较考虑了估计参数的置信区间，以及基于回归的等价性检验。
3. 结果表明，从两种茎分析算法获得的拟合生长模型在统计上是等效的。然而，所提出的算法更简单，因此为当前方法提供了有用的替代方案。
4. 基于这些发现，我建议使用这种新的茎分析算法，用茎分析数据重建树高生长。