林分胸径和树高关系评价全国针叶树种立地质量的适用性

    Applicability of the relationship between stand DBH and height to evaluate the site quality of major coniferous stands in China

    • 摘要:
      目的 建立科学的立地质量评价体系,指导林业生产实践。
      方法 根据全国主要针叶林分样地数量情况,划分16个针叶树种组,采用Richards、Logistic和Korf模型拟合导线曲线,构建立地形指数模型,并进行落点检验,运用1999—2018年连续4期清查数据进行立地形等级动态变化分析。
      结果 Richards、Logistic和Korf模型拟合导向曲线决定系数均值均大于0.95,建立的立地形指数模型落点检验值均大于90.00%,落点检验均值达96.59%,适用于实际生产。20年间,针叶林分Ⅰ级和Ⅱ级均值合计增长了7.60个百分点,Ⅲ级均值合计减少了3.50个百分点,Ⅳ级和Ⅴ级均值合计减少了4.10个百分点,立地质量表现为较好的改善趋势。
      结论 基于胸径−树高关系建立全国统一的立地质量评价模型具有可行性和合理性,通过减少气候差异导致基于树龄的生长速率对立地质量评价的影响偏差,使不同地区间相同林分的评价结果具有可比性,在大尺度水平具有较好的适用性,但仍然需要警惕经营措施和小样本数据导致的评价结果不确定。

       

      Abstract:
      Objective  To establish a scientific site quality evaluation system, guide forestry production practice.
      Method Based on the number of major coniferous forest stand plots across the country, 16 coniferous tree groups were classified. The Richards, Logistic, and Korf models were applied to fit the guiding curves and establish a site form index model, which was then validated through a scatter plot test. Data from four consecutive forest inventory periods from 1999 to 2018 were used to analyze dynamic changes in site form levels.
      Result The mean coefficients of determination for guiding curves fitted with the Richards, Logistic, and Korf models were all above 0.95. The scatter plot validation of the established site form index model showed test values exceeding 90.00%, with an average value of 96.59%, indicating its feasibility for practical use. Over 20 years, site quality for coniferous stands improved, with a combined proportion increase of 7.60 percent in grades I and II, a 3.50 percent decrease in grade III, and a combined reduction of 4.10 percent in grades IV and V.
      Conclusion  Developing a national unified site quality assessment model based on DBH-height relationships is feasible and reasonable. This approach reduces the impact deviations of climate-induced and age-based growth rate on site quality assessment, allowing for comparable site quality evaluations across regions. The model demonstrates good applicability on a large scale, though it is essential to consider potential uncertainties due to management practices and limited sample data.

       

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