A new algorithm for reconstructing tree height growth with stem analysis data

Abstract

Abstract 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. 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. 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. Based on the findings, I recommend using this new stem analysis algorithm to reconstruct tree height growth with stem analysis data.

Keywords

• equivalence testing
• forest ecology
• growth rates
• height growth models
• mixed‐effects models