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林业科学 ›› 2023, Vol. 59 ›› Issue (12): 71-77.doi: 10.11707/j.1001-7488.LYKX20210495

• 研究论文 • 上一篇    下一篇

吉林蛟河针阔混交林生物与非生物因素对生产力的影响

张萌1(),范秀华1,*(),岳庆敏2,韩卓秀2,黄一鑫1   

  1. 1. 北京林业大学理学院 北京 100083
    2. 北京林业大学国家林业和草原局森林经营工程技术研究中心 北京 100083
  • 收稿日期:2021-07-03 接受日期:2023-12-01 出版日期:2023-12-25 发布日期:2024-01-08
  • 通讯作者: 范秀华 E-mail:zhangmeng0897@126.com;blfanxh@bjfu.edu.cn
  • 基金资助:
    国家重点研发计划重点专项项目(2022YFD2201003)。

Effects of Biotic and Abiotic Factors on Productivity of Coniferous and Broad-LeavedMixed Forest in Jiaohe, Jilin Province

Meng Zhang1(),Xiuhua Fan1,*(),Qingmin Yue2,Zhuoxiu Han2,Yixin Huang1   

  1. 1. College of Science, Beijing Forestry University Beijing 100083
    2. Research Center of Forest Management Engineering of National Forestry and Grassland Administration, Beijing Forestry University Beijing 100083
  • Received:2021-07-03 Accepted:2023-12-01 Online:2023-12-25 Published:2024-01-08
  • Contact: Xiuhua Fan E-mail:zhangmeng0897@126.com;blfanxh@bjfu.edu.cn

摘要:

目的: 探究生物与非生物因素对林分生产力的影响和维持作用,为东北针阔混交林可持续经营提供科学依据和理论指导。方法: 以吉林蛟河针阔混交林固定样地为研究对象,利用多元回归分析,量化解释变量(生物因素包括单位面积胸高断面积、林木分化程度、生物多样性,非生物因素即地形因子)对响应变量(保留木生产力、进阶木生产力、死亡量)的影响,采用变差分解法分析3种生物量变化对生物量净变化量的相对重要性。结果: 对保留木生产力,所有解释变量可解释其总方差的12.07%,单位面积胸高断面积有显著正效应,坡度有显著负效应。对进阶木生产力,所有解释变量可解释其总方差的22.62%,胸径变异系数和系统发育多样性指数有显著正效应,单位面积胸高断面积、海拔和坡度有显著负效应。对死亡量,所有解释变量可解释其总方差的3.51%,单位面积胸高断面积有显著正效应。进阶木生产力、保留木生产力和死亡量对生物量净变化量方差的单独解释量分别占0.01%、20.87%和74.54%,其中,死亡量相对贡献最大,但可预测性较低。结论: 单位面积胸高断面积对不同生物量动态过程的作用不同,其中较高的单位面积胸高断面积促进保留木生长,加速林木死亡,对进阶木生长有明显抑制作用。林木分化程度及系统发育多样性促进进阶木生长。在地形因子中,保留木生长受坡度限制,进阶木生长同时受海拔和坡度限制。生物量净变化量主要受死亡量和保留木生产力影响。

关键词: 单位面积胸高断面积, 林木分化程度, 生物多样性, 地形因子, 生产力, 死亡量

Abstract:

Objective: Taking the fixed sample plot of Jiaohe mixed coniferous and broad-leaved forest in Jilin as the object, this study explores the impact and maintenance role of biological and abiotic factors on forest productivity, providing scientific basis and theoretical guidance for the sustainable management of the mixed coniferous and broad-leaved forest in Northeast China. Method: Multiple regression analysis was used to quantify the impact of explanatory variables (biological factors including unit area basal area, forest differentiation degree, biodiversity, and abiotic factor, namely topographical factor) on the response variable(biomass increment of survivors, biomass increment of recruits, biomass mortality). Determine the relative importance of the above three biomass changes on the net biomass change through variance decomposition. Result: For biomass increment of survivors, all explanatory variables together explained 12.07% of its total variance, with a significant positive effect of basal area per unit stand area and a significant negative effect of slope. For biomass increment of recruits, all explanatory variables together explained 22.62% of its total variance. The coefficient of DBH variation and phylogenetic diversity had significant positive effects on the biomass increment of recruits. Basal area per unit stand area, elevation, and slope showed significant negative relationships with the biomass increment of recruits. For biomass mortality, all explanatory variables together explained 3.51% of its total variance, with a significant positive effect of basal area per unit stand area. The fraction of the total variance of net change in biomass that could be explained by biomass increment of recruits, biomass increment of survivors and biomass mortality was 0.01%, 20.87% and 74.54%, respectively. The relative contribution of biomass mortality to the net biomass change was the largest, but its predictability was low. Conclusion: Basal area per unit stand area had different effects on different processes of biomass dynamics . Basal area per unit stand area promoted biomass mortality as well as the growth of survivors but suppressed the growth of recruits. The tree differentiation degree and phylogenetic diversity enhanced the growth of recruits. Among the topographic factors, the growth of survivors was negatively related with the slope, the growth of recruits was negatively related with the elevation and the slope .The net biomass change was mainly influenced by biomass mortality and biomass increment of survivors.

Key words: basal area per unit stand area, tree differentiation degree, biodiversity, topographic factors, productivity, biomass mortality

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