Abstract [Objective] Secondary forests generally have issues such as not optimal stand structure, poor stability, and low biodiversity. To provide a basis and ideas for achieving sustainable forest management and optimizing and adjusting stand structure, we utilized the multivariate distribution of stand spatial structure parameters to comprehensively and systematically describe and analyze the spatial structure characteristics of secondary forests of Pinus yunnanensis on the eastern slope of Cangshan Mountain in Dali. [Method] The 11 circular sample plots with a radius of 12–35 m on the eastern slope of Cangshan Mountain were established to per-tree checking and spatial localization, while the complete mingling (Mc), the uniform angle index (W), the neighborhood comparison (U), and the crowding degree (C) of each stand were calculated, and the relative frequencies of the multivariate distributions were counted and multivariate distribution maps were plotted. [Result] The set of mean values of Pinus yunnanensis secondary forest indicates a moderately dense growth status with a uniform overall distribution and relatively low mixing (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10525_2025_10124_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="21" /> </InlineMediaObject> <EquationSource Format="TEX">\(\bar {W}\)</EquationSource>  </InlineEquation> = 0.408, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10525_2025_10124_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="29" /> </InlineMediaObject> <EquationSource Format="TEX">\(\bar {M}c\)</EquationSource>  </InlineEquation> = 0.133, <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10525_2025_10124_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="17" /> </InlineMediaObject> <EquationSource Format="TEX">\(\bar {C}\)</EquationSource>  </InlineEquation> = 0.431, <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10525_2025_10124_Article_IEq4.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">\(\bar {U}\)</EquationSource>  </InlineEquation> = 0.494). The univariate distribution reveals a similar distribution of the neighborhood comparison within the forest stands, with 76.5% of trees exhibiting low mixing, 36.2% randomly distributed, and 82.3% tending towards denseness. The multivariate distributions from bivariate to quadrivariate demonstrate that regardless of the combination of structural parameters, the majority of trees in the forest stands exhibit a random distribution under different structural combinations. [Conclusion] The multivariate distribution of structural parameters comprehensively and systematically interprets the spatial characteristics of forest stands from various levels and perspectives. This analysis provides a scientific basis for employing selection cutting, tending cutting and so on, aiming to achieve sustainable management by guiding the succession of secondary forests towards a near-natural forest structure.

Spatial Structural Multivariate Distribution Characteristics of Secondary Forests of Pinus yunnanensis Franch

期刊论文
发表日期：

2025年2月1日

查看全文

Jian Zhao,
JianMing Wang,
JiTing Yin,
YaDong Guan

摘要

Abstract

[Objective] Secondary forests generally have issues such as not optimal stand structure, poor stability, and low biodiversity. To provide a basis and ideas for achieving sustainable forest management and optimizing and adjusting stand structure, we utilized the multivariate distribution of stand spatial structure parameters to comprehensively and systematically describe and analyze the spatial structure characteristics of secondary forests of Pinus yunnanensis on the eastern slope of Cangshan Mountain in Dali. [Method] The 11 circular sample plots with a radius of 12–35 m on the eastern slope of Cangshan Mountain were established to per-tree checking and spatial localization, while the complete mingling (Mc), the uniform angle index (W), the neighborhood comparison (U), and the crowding degree (C) of each stand were calculated, and the relative frequencies of the multivariate distributions were counted and multivariate distribution maps were plotted. [Result] The set of mean values of Pinus yunnanensis secondary forest indicates a moderately dense growth status with a uniform overall distribution and relatively low mixing ( \(\bar {W}\) = 0.408, \(\bar {M}c\) = 0.133, \(\bar {C}\) = 0.431, \(\bar {U}\) = 0.494). The univariate distribution reveals a similar distribution of the neighborhood comparison within the forest stands, with 76.5% of trees exhibiting low mixing, 36.2% randomly distributed, and 82.3% tending towards denseness. The multivariate distributions from bivariate to quadrivariate demonstrate that regardless of the combination of structural parameters, the majority of trees in the forest stands exhibit a random distribution under different structural combinations. [Conclusion] The multivariate distribution of structural parameters comprehensively and systematically interprets the spatial characteristics of forest stands from various levels and perspectives. This analysis provides a scientific basis for employing selection cutting, tending cutting and so on, aiming to achieve sustainable management by guiding the succession of secondary forests towards a near-natural forest structure.