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    邓雯文, 代莹, 赵秀海, 张春雨. 吉林蛟河针阔混交林不同尺度下生物量稳定性及影响因子[J]. 北京林业大学学报, 2024, 46(7): 55-66. DOI: 10.12171/j.1000-1522.20220315
    引用本文: 邓雯文, 代莹, 赵秀海, 张春雨. 吉林蛟河针阔混交林不同尺度下生物量稳定性及影响因子[J]. 北京林业大学学报, 2024, 46(7): 55-66. DOI: 10.12171/j.1000-1522.20220315
    Deng Wenwen, Dai Ying, Zhao Xiuhai, Zhang Chunyu. Biomass stability and influencing factors of mixed coniferous and broadleaved forests at different scales in Jiaohe, Jilin Province of northeastern China[J]. Journal of Beijing Forestry University, 2024, 46(7): 55-66. DOI: 10.12171/j.1000-1522.20220315
    Citation: Deng Wenwen, Dai Ying, Zhao Xiuhai, Zhang Chunyu. Biomass stability and influencing factors of mixed coniferous and broadleaved forests at different scales in Jiaohe, Jilin Province of northeastern China[J]. Journal of Beijing Forestry University, 2024, 46(7): 55-66. DOI: 10.12171/j.1000-1522.20220315

    吉林蛟河针阔混交林不同尺度下生物量稳定性及影响因子

    Biomass stability and influencing factors of mixed coniferous and broadleaved forests at different scales in Jiaohe, Jilin Province of northeastern China

    • 摘要:
      目的 探讨不同空间尺度下物种多样性、结构多样性、物种异步性、林分密度和环境因素对群落生物量稳定性的影响及相互之间的作用路径,旨在解析生物量的稳定性在不同空间尺度上的主要驱动因素,为森林的可持续经营及科学管理提供理论基础。
      方法 以吉林蛟河针阔混交林为研究对象,利用2010—2020年的样地群落调查数据,通过结构方程模型探讨20 m × 20 m和40 m × 40 m两个空间尺度上生物因素(物种多样性、结构多样性、物种异步性、林分密度)和非生物因素(地形因子、土壤理化性质)与群落生物量稳定性间的关系及作用机制。
      结果 在20 m × 20 m空间尺度上,生物量稳定性与物种异步性、结构多样性、林分密度均有显著正向关系,非生物因素中地形因子(坡度、凹凸度)与生物量稳定性呈正相关关系;而在40 m × 40 m空间尺度上,生物量稳定性与物种异步性呈现显著正相关,非生物因素中土壤理化性质(速效钾、全磷和速效氮)与生物量稳定性呈现负相关关系。结构方程模型分析表明,在20 m × 20 m空间尺度上,物种异步性对生物量稳定性的影响高于林分密度和结构多样性,路径系数为0.40。土壤理化性质(全钾、全氮和速效氮)通过显著影响物种多样性间接作用于生物量稳定性,路径系数为0.10。在40 m × 40 m空间尺度上,生物因素中只有物种异步性对生物量稳定性有显著正向影响,路径系数为0.64。地形因子(坡度、凹凸度)通过调整结构多样性间接作用于林分生物量稳定性,路径系数为0.35。
      结论 在不同的空间尺度上,虽然生物因素与非生物因素对生物量稳定性的作用路径和影响力不尽相同,但物种异步性均为生物量稳定性的主要驱动因子。在20 m × 20 m空间尺度上,物种异步性、林分密度、结构多样性等生物因素通过直接正向效应来影响生物量稳定性,非生物因素通过间接效应作用于生物量稳定性;在40 m × 40 m空间尺度上,林分生物量稳定性主要影响因子则是物种异步性和土壤理化性质。

       

      Abstract:
      Objective This paper aims to explore the effects of species diversity, structural diversity, species asynchronism, stand density and environmental factors on community biomass stability and their interaction paths at different spatial scales, and to analyze the main driving factors of biomass stability at different spatial scales, so as to provide a theoretical basis for sustainable forest management and scientific management.
      Method Based on the survey data of coniferous and broadleaved mixed forest in Jiaohe, Jilin Province of northeastern China from 2010 to 2020, the relationship between biotic factors (species diversity, structural diversity, species asynchronism, stand density) and abiotic factors (topographic factors, soil physical and chemical properties) and community biomass stability at 20 m × 20 m and 40 m × 40 m spatial scales and their mechanism were investigated by structural equation model.
      Result At the scale of 20 m × 20 m, biomass stability was significantly positively correlated with species asynchrony, structural diversity, and stand density. Among abiotic factors, topographic factors (slope and convexity) were positively correlated with biomass stability. At the scale of 40 m × 40 m, biomass stability was positively correlated with species asynchrony, while soil physicochemical properties (available potassium, total phosphorus and available nitrogen) were negatively correlated with biomass stability. The structural equation model analysis showed that the effect of species asynchrony on biomass stability was higher than that of stand density and structural diversity at the scale of 20 m × 20 m, and the path coefficient was 0.40. Soil physicochemical properties indirectly affected stand biomass stability by significantly affecting species diversity, and the path coefficient was 0.10. At the scale of 40 m × 40 m, only species asynchrony had a significant positive effect on biomass stability, with a path coefficient of 0.64. Topographic factors (slope and convexity) indirectly affected stand biomass stability by adjusting structural diversity, and the path coefficient was 0.35.
      Conclusion At different spatial scales, although biotic factors and abiotic factors have different paths and influences on biomass stability, species asynchrony is the main driving factor for biomass stability. At the scale of 20 m × 20 m, biological factors such as species asynchrony, stand density, and structural diversity affect biomass stability through direct positive effects, while environmental factors affect biomass stability through indirect effects. At the scale of 40 m × 40 m, species asynchrony and soil physicochemical properties (available potassium, total phosphorus and available nitrogen) are the main influencing factors for biomass stability.

       

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