欢迎访问《应用生态学报》官方网站,今天是 分享到:

应用生态学报 ›› 2025, Vol. 36 ›› Issue (8): 2270-2278.doi: 10.13287/j.1001-9332.202508.004

• 研究论文 • 上一篇    下一篇

长白落叶松人工林单木最大冠幅模型及应用

张薇, 陈冠谋, 董灵波*   

  1. 东北林业大学林学院, 森林生态系统可持续经营教育部重点实验室, 哈尔滨 150040
  • 收稿日期:2025-04-22 接受日期:2025-06-01 出版日期:2025-08-18 发布日期:2026-02-18
  • 通讯作者: *E-mail: farrell0503@126.com
  • 作者简介:张 薇, 女, 2001年生, 硕士研究生。主要从事森林培育与经营研究。E-mail: 840523638@qq.com
  • 基金资助:
    国家自然科学基金项目(32171778)

Maximum crown width model of Larix olgensis plantation and its application

ZHANG Wei, CHEN Guanmou, DONG Lingbo*   

  1. Ministry of Education Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China
  • Received:2025-04-22 Accepted:2025-06-01 Online:2025-08-18 Published:2026-02-18

摘要: 本研究以东北林业大学帽儿山实验林场55块长白落叶松人工林固定样地调查数据为基础,采用均值±标准差法将林分密度指数(SDI)划分为3个等级,即SDI Ⅰ∈(0,695]、SDI Ⅱ∈(695,1027]、SDI Ⅲ∈(1027, ∞] 株·hm-2;以Logistic方程为基础,耦合哑变量和分位数回归构建不同SDI等级下的3个分位点处(0.90、0.95和0.99)的单木最大冠幅预测模型,进而采用树冠投影面积法编制不同SDI等级下的林分经营密度数表,探讨林分密度对蓄积量和碳储量的影响。结果表明:不同SDI的单木最大冠幅模型具有显著差异,且均以0.90分位点能够更好地模拟单木最大冠幅;独立样本检验表明,与Logistic基础模型相比,单木哑变量分位数最大冠幅模型的Radj2可显著提高0.20,而均方根误差显著降低0.15 m。基于建立的单木哑变量分位数最大冠幅模型和树冠投影面积法,编制出了不同SDI等级下的林分经营密度数表;当培育目标直径为30 cm时,与SDIⅠ相比,不区分SDI等级时相应的林分蓄积量和碳储量分别被高估26.16 m3·hm-2和10.10 t C·hm-2;与SDIⅡ相比,其同样被高估15.99 m3·hm-2和6.12 t C·hm-2;但与SDI Ⅲ相比,其被显著低估85.13 m3·hm-2和33.04 t C·hm-2,表明忽略SDI等级差异会系统性高估低密度林分的碳汇能力,同时低估高密度林分的实际贡献。因此,按SDI等级开展林分密度调控,有利于实现该地区长白落叶松人工林质量的精准提升。

关键词: 长白落叶松, 分位数回归, 冠幅模型, 林分经营密度数表

Abstract: Based on the survey data of 55 permanent plots of Larix olgensis plantation in Maoershan Experimental Forest Farm of Northeast Forestry University, we divided the stand density index (SDI) of the plots into three grades by mean±standard deviation method, namely SDI Ⅰ∈(0, 695], SDI Ⅱ∈(695, 1027], and SDI Ⅲ∈(1027, ∞] trees·hm-2. Based on the Logistic equation, we constructed the maximum crown width prediction model of individual tree at three quantiles (0.90, 0.95, and 0.99) under different SDI grades by coupling dummy variables and quantile regression. We further used the crown projection area method to compile the stand management density number table under different SDI grades and quantified the influence of stand density on stand volume and carbon storage. The results showed that the maximum crown width models of individual tree with different SDI had significant differences, and that the maximum crown width of individual tree could be better simulated at 0.90 quantile. The independent sample test showed that compared with the Logistic basic model, the Radj2 of the single-tree dummy variable quantile maximum crown model could be significantly increased by 0.20, while the root mean square error was significantly reduced by 0.15 m. Based on the established single tree dummy variable quantile maximum crown width model and crown projection area method, we compiled the stand management density number table under different SDI grades. When the target diameter of cultivation was 30 cm, compared with SDI Ⅰ, stand volume and carbon storage were overestimated by 26.16 m3·hm-2 and 10.10 t C·hm-2, respectively, when SDI grades were not distinguished. Similarly, compared with SDIⅡ, these values were overestimated by 15.99 m3·hm-2 and 6.12 t C·hm-2. However, compared with SDIⅢ, they were significantly underestimated by 85.13 m3·hm-2 and 33.04 t C·hm-2. Our results indicated that ignoring the differences of SDI grades could overestimate the carbon sequestration capacity of low-density stands but underestimate the actual contribution of high-density stands. Therefore, implementing stand density regulation based on SDI grades is conducive to achieving precise quality improvement of L. olgensis plantations.

Key words: Larix olgensis, quantile regression, crown width model, stand management density number table