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应用生态学报 ›› 2025, Vol. 36 ›› Issue (4): 1053-1061.doi: 10.13287/j.1001-9332.202504.004

• 研究论文 • 上一篇    下一篇

黑龙江省丰林县林下灌木与幼树生物量模型构建

李泽霖1,2, 贾炜玮1,2*, 赵阳1,2, 江珊1,2   

  1. 1东北林业大学林学院, 哈尔滨 150040;
    2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:2024-12-14 接受日期:2025-02-09 出版日期:2025-04-18 发布日期:2025-10-18
  • 通讯作者: *E-mail: jiaww2002@163.com
  • 作者简介:李泽霖, 男, 1999年生, 博士研究生。主要从事林分生长与收获模型研究。E-mail: 3296726873@qq.com
  • 基金资助:
    国家重点研发计划项目(2022YFD2201003-02)

Construction of biomass models for understory shrubs and tree saplings in Fenglin County, Heilongjiang Province, China.

LI Zelin1,2, JIA Weiwei1,2*, ZHAO Yang1,2, JIANG Shan1,2   

  1. 1College of Forestry, Northeast Forestry University, Harbin 150040, China;
    2Key Laboratory of Sustainable Management of Forest Ecosystem, Ministry of Education, Harbin 150040, China
  • Received:2024-12-14 Accepted:2025-02-09 Online:2025-04-18 Published:2025-10-18

摘要: 灌木和幼树是天然林林下植被的重要组成部分,具有丰富的种类和广泛的生态适应性,在土壤保水、水源涵养和防风防沙等方面发挥关键作用。然而,目前研究多集中于乔木层与林下植被层的相互作用,对林下植被的生长动态、生物量更新及其环境适应性关注较少。本研究基于黑龙江省丰林县林下18种灌木和6种幼树的植被数据及样地的气候信息,引入林分密度和龄级2种哑变量,构建了林下灌木与幼树的生物量模型。结果表明: 在基础模型中引入气候因子(年平均温度和年平均降水量)构建的气候敏感生物量模型显著提高了模型的拟合精度,决定系数(R2)由基础模型的0.732提高至0.741,提升了6.8%。在气候敏感生物量模型的基础上,分别引入龄级单一哑变量和林分密度与龄级双哑变量建模,双哑变量模型的拟合效果最佳,R2达到0.840,显著高于单哑变量模型(R2=0.787)和气候敏感生物量模型(R2=0.741)。本研究在气候敏感生物量模型的基础上结合林分密度与龄级双哑变量构建的模型能够有效反映不同龄级和林分密度下灌木与幼树生物量的变化,为森林生态管理和生物量的科学估算提供了依据,具有重要的应用价值。

关键词: 灌木, 幼树, 生物量, 气候因子, 单哑变量模型, 双哑变量模型

Abstract: Shrubs and tree saplings are important components of understory in natural forests, possessing rich species diversity and broad ecological adaptability. They play a key role in soil moisture retention, water conservation, and wind and sand prevention. However, current research has mostly focused on the interactions between the tree layer and understory, with less attention on the growth dynamics, biomass renewal, and environmental adaptability of understory. Based on data of 18 shrub species and sapling of six tree species from the understory of Fenglin County in Heilongjiang Province, along with climate data from the sampling sites, we introduced two dummy variables, stand density and age class, to construct a biomass model for understory shrubs and tree saplings. The results showed that incorporating climate factors (mean annual temperature and mean annual precipitation) into the base model to construct a climate-sensitive biomass model significantly improved the model's fitting accuracy. The coefficient of determination (R2) increased from 0.732 in the base model to 0.741, with an improvement of 6.8%. Based on the climate-sensitive biomass model, single dummy variables for age class and a dual dummy variable model combining stand density and age class were introduced. The dual dummy variable model showed the best fit, with an R2 of 0.840, being significantly higher than the single dummy variable model (R2=0.787) and the climate-sensitive biomass model (R2=0.741). The model constructed based on the climate-sensitive biomass model and incorporating dual dummy variables for stand density and age class, could effectively reflect the biomass variations of shrubs and tree saplings under different age classes and stand densities. It would provide a basis for forest ecological management and the scientific estimation of biomass, with significant practical value.

Key words: shrub, young tree, biomass, climate factor, single dummy variable model, double dummy variable model