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

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.