基于贝叶斯法的针阔混交林树高与胸径混合效应模型

在多树种多层次针阔混交林中，基于贝叶斯混合效应模型法构建树高与胸径关系的混合效应模型，以提高预测模型参数稳定性，为研究混交林多树种生长规律、资源分配差异及森林质量精准提升提供科学依据。以河北省塞罕坝机械林场华北落叶松和白桦针阔混交林为研究对象，基于112块标准地（30 m×30 m）调查数据，选取6个包含不同林分因子的理论方程作为构建混交林不同树种树高与胸径关系的基础模型，选择出拟合精度较高的模型，分别采用两水平非线性混合效应模型法和贝叶斯混合效应模型法构建包含哑变量的多树种树高与胸径关系模型。基于贝叶斯混合效应模型法构建的非线性混合效应模型，充分考虑混交林多树种树高与胸径关系模型参数的不确定性，模型预测效果更具可靠性和稳定性。

In multi-species and multi-layered coniferous and broadleaved mixed forests, this study constructs a mixed-effects model for the relationship between tree height and diameter at breast height (DBH) using the Bayesian mixed-effects modeling method, aiming to improve the stability of predictive model parameters and provide a scientific basis for investigating the growth patterns of multiple tree species in mixed forests, disparities in resource allocation, and the targeted improvement of forest quality.
Taking the coniferous and broadleaved mixed forest of Larix principis-rupprechtii and Betula platyphylla in the Saihanba Mechanized Forest Farm, Hebei Province as the research subject, based on the survey data of 112 sample plots (30 m × 30 m), six theoretical equations incorporating different stand factors were selected as the basic models for establishing the tree height-DBH relationship of different tree species in mixed forests. After selecting the models with high fitting accuracy, the two-level nonlinear mixed-effects modeling method and the Bayesian mixed-effects modeling method were respectively adopted to construct multi-species tree height-DBH relationship models with dummy variables.
The nonlinear mixed-effects model developed via the Bayesian mixed-effects modeling method fully accounts for the uncertainty of the parameters in the multi-species tree height-DBH relationship model of mixed forests, endowing the model with more reliable and stable predictive performance.

搜集汇总

背景与挑战

背景概述

该数据集基于河北省塞罕坝机械林场的华北落叶松和白桦针阔混交林调查数据，采用贝叶斯混合效应模型法构建了树高与胸径关系的非线性混合效应模型。其目的是提高模型参数的稳定性和预测可靠性，为混交林生长规律研究和森林质量提升提供科学依据。