在Larix olgensis中模拟纵向结的生长和采样策略
Ze-Lin Li1,2, Wei-Wei Jia1,2, Guo-Qiang Zhao3
1Ministry of Education Key Laboratory of Sustainable Forest Ecosystem Management, Harbin 150040, China.
Ying yong sheng tai xue bao = The journal of applied ecology
|December 15, 2025
概括
了解木结的生长是木材质量的关键. 这项研究开发了一种混合效应模型,用于预测Larix olgensis中节点的大小,并建议采集上茎样本,以进行准确的森林管理.
科学领域:
- 林业科学 林业科学
- 木材科学 木材科学 木材科学
- 量化林业 量化林业是什么
背景情况:
- 木结对机械性能和视觉吸引力有很大的影响.
- 了解结的纵向生长对于木材质量评估和管理至关重要.
研究的目的:
- 为了研究Larix olgensis中节点的纵向生长模式.
- 开发节点宽度的预测模型,并优化森林管理的采样策略.
主要方法:
- 检查了27个Larix olgensis个体的1137个结样.
- 模拟了垂直结的生长动态,并比较了七种生长模型.
- 开发了一个重新参数化的混合效应模型,包含树和结变量.
主要成果:
- 混合效应模型显示出优异的性能 (R2=0.6051,RMSE=2.3865).
- 采样策略显著影响了预测准确性;对七个上茎节点的随机采样是最佳的.
- 节点宽度与分支插入高度和角度正相关,与高度-直径比负相关.
结论:
- 一个混合效应模型与上茎节点采样提供准确的节点宽度预测Larix olgensis.
- 建议修剪树干上方的树枝,以减少结的大小并提高森林管理中的木材质量.
相关概念视频
01:16Stratified Sampling Method
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
01:20Cluster Sampling Method
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...