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林业科学 ›› 2022, Vol. 58 ›› Issue (11): 181-190.doi: 10.11707/j.1001-7488.20221117

• 研究简报 • 上一篇    

针阔混交林生物量稳定性驱动因子

于水今1,王娟1,*,何海燕2,张春雨1,赵秀海1   

  1. 1. 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
    2. 吉林省长白山保护开发区管理委员会机关事务管理中心 延边朝鲜族自治州 133613
  • 收稿日期:2021-05-23 出版日期:2022-11-25 发布日期:2023-03-08
  • 通讯作者: 王娟

Driving Factors of the Temporal Stability of Biomass of Mixed Broadleaf-Conifer Forest

Shuijin Yu1,Juan Wang1,*,Haiyan He2,Chunyu Zhang1,Xiuhai Zhao1   

  1. 1. Research Center of Forest Management Engineering of National Forestry and Grassland Administration, Beijing Forestry University Beijing 100083
    2. Office Management Center of Jilin Changbai Mountain Protection Development Management Committee Yanbian Korean Aubonomous Prefecture 133613
  • Received:2021-05-23 Online:2022-11-25 Published:2023-03-08
  • Contact: Juan Wang

摘要:

目的: 阐明生物多样性、胸径结构和地形因子对针阔混交林生物量稳定性的相对影响,明确不同空间尺度下生物量稳定性的主要驱动因素。方法: 在吉林蛟河两个大型固定样地的基础上,通过随机抽取20 m×20 m、40 m×40 m和60 m×60 m样方的方式,定量分析不同空间尺度的影响。利用广义可加模型构建了三类嵌套模型:稳定性~生物多样性+胸径结构(模型1)、稳定性~生物多样性+地形因子(模型2)、稳定性~生物多样性+胸径结构+地形因子(模型3),并与稳定性~生物多样性(模型0)进行比较,通过赤池信息量准则变化量(△AIC)、贝叶斯信息量准则变化量(△BIC)、调整后的决定系数变化量(△Radj2)和偏差解释率变化量(△DE)评价不同解释因子的相对贡献大小。结果: 广义可加模型分析显示,在20 m×20 m、40 m×40 m、60 m×60 m三个尺度上,生物多样性对生物量稳定性的相对贡献率分别为15.18%、12.66%和47.64%,胸径结构的相对贡献率分别为11.30%、72.38%和23.48%,地形因子的相对贡献率分别为73.52%、14.96%和28.88%;生物多样性和胸径结构两类变量仅在60 m×60 m尺度上与生物量稳定性显著相关(P<0.05),其中物种丰富度和Faith系统发育多样性指数与生物量稳定性间显著负相关,胸径最大值和林分密度与生物量稳定性间显著正相关,胸径变异系数与生物量稳定性间显著负相关;在地形因子指标中,坡向在20 m×20 m尺度上与生物量稳定性显著相关,海拔和坡度在60 m×60 m尺度上与生物量稳定性显著相关;上述解释变量对生物量稳定性的偏差解释百分比随尺度增大而增大;蓄积量稳定性与生物量稳定性的驱动因子基本一致。结论: 在不同空间尺度上地形因子、胸径结构、生物多样性对生物量稳定性的相对影响大小不同,具有显著的尺度效应;在20 m×20 m尺度上地形因子对生物量稳定性起主要影响作用,在40 m×40 m尺度上胸径结构对生物量稳定性起主要影响作用,在60 m×60 m尺度上生物多样性对生物量稳定性起主要影响作用;研究结果可为东北针阔混交林生态系统稳定性提升提供理论依据。

关键词: 生物量稳定性, 生物多样性, 胸径结构, 地形因子, 空间尺度

Abstract:

Objective: The objective was to investigate the effects of biodiversity, DBH structure and topography on the temporal stability of biomass and clarify the main driving factors for the temporal stability of biomass at different spatial scales. Method: Based on two large fixed sample plots in Jiaohe, Jilin, the influences of different spatial scales was quantitatively analyzed by randomly sampling 20 m×20 m, 40 m×40 m, and 60 m×60 m plots. Three types of nested models were constructed using generalized additive models: stability~biodiversity + DBH structure (model 1), stability-biodiversity + topographic factors (model 2), stability-biodiversity + DBH structure + topographic factors (model 3), and compared with stability~biodiversity (model 0). The relative contributions of different explanatory factors are evaluated by the variation of Akaike information criterion (△AIC), the variation of Bayesian information criterion (△BIC), the variation of adjusted determination coefficient (△Radj2) and the variation of deviance explained (△DE). Result: The analysis of the generalized additive model shows that at the three scales of 20 m×20 m, 40 m×40 m, and 60 m×60 m, the relative contribution rates of biodiversity are 15.18%, 12.66%, and 47.64%, respectively; the relative contribution rates of DBH structure are 11.30%, 72.38%, and 23.48%, respectively; the relative contribution rates of topography are 73.52%, 14.96%, and 28.88%, respectively. Biodiversity and DBH structure are only significantly correlated with the temporal stability of biomass on the 60 m×60 m scale (P < 0.05). Among them, species richness and Faith phylogenetic diversity index are significantly negatively correlated with the temporal stability of biomass. The maximum diameter at breast height and basal area per hectare are significantly positively correlated with the temporal stability of biomass, and the coefficient of variation of diameter at breast height is significantly negatively correlated with the temporal stability of biomass. Among the topographic factors, the aspect is significantly related to the temporal stability of biomass at the 20 m×20 m scale, and the elevation and slope are significantly related to the temporal stability of biomass at the 60 m×60 m scale. The explanation rate of the deviation of the above explanatory variables on the temporal stability of biomass increases with the spatial scale. The driving factor for the temporal stability of volume is basically the same as the temporal stability of biomass. Conclusion: The relative influences of topographic factors, DBH structure and biodiversity have significant scale effects on the temporal stability of biomass and shift along different spatial scales. Topographical factors play a major role in the temporal stability of biomass at the scale of 20 m×20 m. DBH structure plays a major role in the temporal stability of biomass at the scale of 40 m×40 m and biodiversity plays a major role in the temporal stability of biomass at the scale of 60 m×60 m. The results provide a theoretical basis for improving the stability of the northeast coniferous and broad-leaved mixed forest ecosystem.

Key words: temporal stability of biomass, biodiversity, DBH structure, topography, spatial scale

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