The Effect of Soil and Topography Factors on Larix gmelinii var. Principis-rupprechtii Forest Mortality and Capability of Decision Tree Binning Method and Generalized Linear Models in Predicting Tree Mortality

Forests, Год журнала: 2024, Номер 15(12), С. 2060 - 2060

Опубликована: Ноя. 22, 2024

Understanding the factors influencing individual tree mortality is essential for sustainable forest management, particularly Prince Rupprech’s larch (Larix gmelinii var. Principis-rupprechtii) in North China’s natural forests. This study focused on 20 sample plots (20 × m each) established Shanxi Province, China. compared three models—Generalized Linear Model (GLM), Discriminant Analysis (LDA), and Bayesian Generalized (Bayesian GLM)—finding that both GLM achieved approximately 0.87 validation accuracy test dataset. Due to its simplicity, was selected as final model. Building model, six binning methods were applied categorize diameter at breast height (DBH): equal frequency binning, width cluster-based quantile Chi-square decision binning. Among these, method highest performance, with an of 90.12% F1 score 90.06%, indicating effectiveness capturing size-dependent patterns. approach provides valuable insights into affecting offers practical guidance managing Larix Principis-rupprechtii forests temperate regions.

Язык: Английский

Modeling the Dominant Height of Larix principis-rupprechtii in Northern China—A Study for Guandi Mountain, Shanxi Province

Forests, Год журнала: 2022, Номер 13(10), С. 1592 - 1592

Опубликована: Сен. 29, 2022

An accurate estimate of the site index is essential for informing decision-making in forestry. In this study, we developed (SI) models using stem analysis data to and dominant height growth Larix gmelinii var. principis-rupprechtii northern China. The included 5122 height–age pairs from 75 trees 29 temporary sample plots (TSPs). Nine commonly used functions were parameterized modeling method, which accounts heterogeneous variance autocorrelation time-series introduces plot-level random effects model. results show that Duplat Tran-Ha I model with described largest proportion variation. This accurately evaluated quality predicted tree natural forests Guandi Mountain region. As an important supplement improving methods evaluation, may serve as a fundamental tool scientific management larch forests. research can inform evaluation predict forest area well provide theoretical basis at similar sites.

Язык: Английский