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An Approach to Estimate Individual Tree Ages Based on Time Series Diameter Data—A Test Case for Three Subtropical Tree Species in China.

Authors :
Zhang, Yiru
Li, Haikui
Zhang, Xiaohong
Lei, Yuancai
Huang, Jinjin
Liu, Xiaotong
Source :
Forests (19994907); Apr2022, Vol. 13 Issue 4, p614-614, 18p
Publication Year :
2022

Abstract

Accurate knowledge of individual tree ages is critical for forestry and ecological research. However, previous methods suffer from flaws such as tree damage, low efficiency, or ignoring autocorrelation among residuals. In this paper, an approach for estimating the ages of individual trees is proposed based on the diameter series of Cinnamomum camphora (Cinnamomum camphora (L.) Presl), Schima superba (Schima superba Gardn. et Champ.), and Liquidambar formosana (Liquidambar formosana Hance). Diameter series were obtained by stem analysis. Panel data contains more information, more variability, and more efficiency than pure time series data or cross-sectional data, which is why diameter series at stump and breast heights were chosen to form the panel data. After choosing a base growth equation, a constraint was added to the equation to improve stability. The difference method was used to reduce autocorrelation and the parameter classification method was used to improve model suitability. Finally, the diameter increment equation of parameter a-classification was developed. The mean errors of estimated ages based on the panel data at breast height for C. camphora, S. superba, and L. formosana were 0.47, 2.46, and −0.56 years and the root mean square errors were 2.04, 3.15 and 2.47 years, respectively. For C. camphora and L. formosana, the estimated accuracy based on the panel data was higher at breast height than at stump height. This approach to estimating individual tree ages is highly accurate and reliable, and provides a feasible way to obtain tree ages by field measurement. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19994907
Volume :
13
Issue :
4
Database :
Complementary Index
Journal :
Forests (19994907)
Publication Type :
Academic Journal
Accession number :
156531385
Full Text :
https://doi.org/10.3390/f13040614