高级检索
    李冠男, 张春雨, 赵秀海. 吉林蛟河针阔混交林幼苗动态及环境驱动因子[J]. 北京林业大学学报, 2021, 43(8): 41-49. DOI: 10.12171/j.1000-1522.20200356
    引用本文: 李冠男, 张春雨, 赵秀海. 吉林蛟河针阔混交林幼苗动态及环境驱动因子[J]. 北京林业大学学报, 2021, 43(8): 41-49. DOI: 10.12171/j.1000-1522.20200356
    Li Guannan, Zhang Chunyu, Zhao Xiuhai. Seedling dynamics and environmental driving factors of coniferous and broadleaved mixed forest in Jiaohe, Jilin Province of northeastern China[J]. Journal of Beijing Forestry University, 2021, 43(8): 41-49. DOI: 10.12171/j.1000-1522.20200356
    Citation: Li Guannan, Zhang Chunyu, Zhao Xiuhai. Seedling dynamics and environmental driving factors of coniferous and broadleaved mixed forest in Jiaohe, Jilin Province of northeastern China[J]. Journal of Beijing Forestry University, 2021, 43(8): 41-49. DOI: 10.12171/j.1000-1522.20200356

    吉林蛟河针阔混交林幼苗动态及环境驱动因子

    Seedling dynamics and environmental driving factors of coniferous and broadleaved mixed forest in Jiaohe, Jilin Province of northeastern China

    • 摘要:
        目的  本文以吉林蛟河不同发育阶段针阔混交林为研究对象,对比分析幼苗密度的核密度估计曲线年际变化规律,探讨土壤因子的边际变化和土壤因子的分布变化对幼苗密度分布动态的相对影响。
        方法  在420 m × 520 m的中龄林样地和500 m × 840 m的成熟林样地中系统布设幼苗调查样方。利用分位数回归和反事实分解法检验环境因子在不同分位数水平上对幼苗密度的边际影响,进而明确幼苗密度在不同分位点上呈现不均衡变化的主导因素。
        结果  幼苗密度的核密度估计曲线呈峰值向左偏移、长尾向右侧延伸的正偏态分布。在θ = 0.90的高分位点,中龄林样地中幼苗密度变化值为−5.9,成熟林样地幼苗密度变化值为−2.6。中龄林样地在θ = 0.75时幼苗密度变化值为5.8,成熟林样地在θ = 0.50和θ = 0.75时幼苗密度变化值均为2。在高分位点上幼苗密度的更大变化反映了右单尾概率分布的不均衡性。在不同估计分位点上系数效应和协变量效应对幼苗密度分布变化的相对作用大小不同。中龄林样地中系数效应在全部估计分位点上都具有很高的解释量;成熟林样地中在θ = 0.50分位点上,协变量效应对幼苗密度变化具有89%的解释量,在其他的估计分位点上系数效应的解释量更高。因此,土壤因子分布变化对幼苗密度分布变化影响的相对作用更大,而土壤因子边际变化则是导致幼苗密度不均衡变化的主要因素。土壤中速效氮、速效磷、速效钾分布变化对每个估计分位点上幼苗密度变化的解释量大多不足30%,而土壤含水量和土壤pH值对幼苗密度变化具有相对更大的影响。
        结论  幼苗密度的年际变化在不同分位点上是不均衡的,在高分位点上的变化尤为明显。土壤因子的边际变化和土壤因子的分布变化共同决定了幼苗的存活动态。

       

      Abstract:
        Objective  In this paper, taking the coniferous and broadleaved mixed forest at different development stages in Jiaohe, Jilin Province of northeastern China as research object, the interannual variation of kernel density estimation curve of seedling density was compared and analyzed. The relative effects of marginal changes of soil factors and distribution changes of soil factors on the dynamics of seedling density distribution were discussed.
        Method  Seedling investigation sample plots were systematically arranged in 420 m × 520 m half-matured forest (HF) sample plots and 500 m × 840 m mature forest (MF) sample plots. Quantile regression and counterfactual decomposition were used to test the marginal effects of environmental factors on seedling density at different quantile levels, and then to identify the leading factors resulting in the unequal change of seedling density.
        Result  The kernel density estimation curve of seedling density showed a positive skewed distribution with peak value shifting to the left and long tail extending to the right. At the high quantile of θ = 0.90, the change value of seedling density was −5.9 in HF sample plots and −2.6 in MF sample plots. The change value of seedling density in HF sample plot was 5.8 when θ = 0.75, and that in MF sample plot was 2 when θ = 0.50 and θ = 0.75. The greater change of seedling density at high quantile reflects the inequality of probability distribution of the right single tail. The relative effects of coefficient effect and covariant effect on seedling density distribution were different in varied estimated quantiles. The coefficient effect in HF sample plots had a high explanation on all estimated quantiles; in MF sample plots, the covariant effect had 89% explanation for the change of seedling density at θ = 0.50 quantile. In other estimated quantiles, the explanation of coefficient effect was higher. Therefore, the relative effect of distribution of soil factors on the distribution of seedling density was greater, and the marginal change of soil factors was the main factor leading to unequal change of seedling density. Most of the changes in the distribution of available nitrogen, available phosphorus and available potassium in soil explained less than 30% of the changes in seedling density at each estimated quantile, while soil water content and soil pH had a relatively greater effect on the change of seedling density.
        Conclusion  The interannual variation of seedling density is unequal in different quantiles, especially in the high quantile. The marginal change of soil factors and the distribution of soil factors determine the survival dynamics of seedlings.

       

    /

    返回文章
    返回