韦彩丽, 孔令华, 何晓慧, 等. 黄牛木种群扩散动态研究[J]. 华南农业大学学报, 2019, 40(4): 69-76. DOI: 10.7671/j.issn.1001-411X.201806022
    引用本文: 韦彩丽, 孔令华, 何晓慧, 等. 黄牛木种群扩散动态研究[J]. 华南农业大学学报, 2019, 40(4): 69-76. DOI: 10.7671/j.issn.1001-411X.201806022
    WEI Caili, KONG Linghua, HE Xiaohui, et al. Dispersal dynamics of Cratoxylum cochinchinense population[J]. Journal of South China Agricultural University, 2019, 40(4): 69-76. DOI: 10.7671/j.issn.1001-411X.201806022
    Citation: WEI Caili, KONG Linghua, HE Xiaohui, et al. Dispersal dynamics of Cratoxylum cochinchinense population[J]. Journal of South China Agricultural University, 2019, 40(4): 69-76. DOI: 10.7671/j.issn.1001-411X.201806022

    黄牛木种群扩散动态研究

    Dispersal dynamics of Cratoxylum cochinchinense population

    • 摘要:
      目的  研究黄牛木Cratoxylum cochinchinens种群空间分布格局的形成机制和扩散规律,旨在促进黄牛木天然林的保护管理,推动其在珠三角地区生态脆弱地带绿化改造中的应用和推广。
      方法  采用样方调查法,选取广州市茶山和白云山以及台山市石花山的黄牛木典型样地,通过ArcGIS信息平台进行数字化处理,绘制种群空间分布点图和种群扩散动态分布图,分析黄牛木的种子传播方式和扩散动态,构建黄牛木种群的扩散速率(y)−胸径(x)的函数模型,预测种群扩散规律。
      结果  样地中的黄牛木总是在当地风向的下风向呈现聚集分布,并呈现扩散趋势;各样地种群冠层投影面积的增长量总是先增大后减小,不同样地的冠层扩散速率与平均胸径的函数模型均可为一元二次方程;单株黄牛木的冠幅增长量先增大后减小,其冠层扩散速率(y0)与胸径(x0)的函数模型为:y0=−0.013 5x02 + 0.310 6x0 +b 0.111 3 (R2=0.999,P=0.000)。
      结论  1)黄牛木种群靠风力扩散;2)种群冠层扩散速率先增大后减小,当种群扩散速率达到最大值时,冠层投影面积的增长量亦达到最大,当扩散速率为0时,冠层投影面积的增长量为0, 此时种群的生长受到限制;3)在人工经营下,当黄牛木的胸径为11.5 cm时,种群处于第6径阶,其冠幅扩散速率达到最大值1.90 m2/cm,此时应对种群进行适当间伐,以保证其最大效益;当黄牛木胸径达到23.4 cm时,种群处于第12径阶,种群的扩散受到阻碍,此时应进行疏伐以促进种群的更新生长。

       

      Abstract:
      Objective  The formation mechanism and diffusion pattern of the spatial distribution of Cratoxylum cochinchinense were studied to promote the protection and management of the natural forest and landscape construction and application in Pearl River Delta areas with poor ecological environment.
      Method  We used quadrat survey method and selected C. cochinchinense stands distributed in three different areas (Chashan area and Baiyun mountain in Guangzhou, and Shihua mountain in Taishan). The maps of population spatial distribution and diffusion dynamics were drawn using digital processing with ArcGIS platform. These maps were used for analyzing seed dispersal mode and dispersal dynamics. The function model of diffusion rate (y)-DBH (x) of the C. cochinchinense population was established for predicting population diffusion rate.
      Result  The C. cochinchinense trees always aggregated at the local downwind and showed a distribution trend in sampled areas. The growth in projection area of canopy always increased first and then decreased, and the functions of diffusion rate-DBH were univariate quadratic equations in different sampled areas. The growth of canopy of single C. cochinchinense tree first increased and then decreased, and the function model of diffusion rate(y0)-DBH(x0) for single C. cochinchinense tree was: y0=−0.013 5x02+0.310 6x0+0.111 3 (R2=0.999, P=0.000).
      Conclusion  1) C. cochinchinense population spread by wind. 2) The diffusion rate of canopy first increased and then decreased. The growth of canopy area increased to the peak when the diffusion rate reached the maximum, and the growth of canopy area was 0 when the diffusion rate was 0. At this time, diffusion of the population was limited. 3) Under artificial management, the diffusion rate of canopy reached the maximum of 1.90 m2/cm when tree DBH was 11.5 cm and the population belonged to the 6th diameter class. At this time thinning should be appropriately done to ensure the maximum benefits. The population diffusion was limited when tree DBH was 23.4 cm and the population belonged to the 12th diameter class. At this time thinning must be done to promote the growth and update of population.

       

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