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杉木生态林林分间伐空间结构优化模型

曹小玉*,李际平,胡园杰,杨静   

  1. (中南林业科技大学林学院, 长沙 410004)
  • 出版日期:2017-04-10 发布日期:2017-04-10

Spatial structure optimizing model of stand thinning of Cunninghamia lanceolata ecological forest.

CAO Xiao-yu, LI Jing-ping, HU Yuan-jie, YANG Jing   

  1. (School of Forestry, Central South University of Forestry & Technology, Changsha 410004, China).
  • Online:2017-04-10 Published:2017-04-10

摘要: 采用乘除法对全混交度、林层指数、W_V_Hegyi竞争指数、角尺度、开敞度5个林分空间结构参数进行多目标规划,确定林分空间结构优化目标函数,以林分空间结构和非空间结构为约束条件,在采用综合灰色关联度分析法确定林分空间结构约束条件优先次序的基础上,构建杉木生态林林分间伐空间结构优化模型,并将该模型用于确定样地中最该采伐的林木。结果表明:杉木生态林林分空间结构优化目标函数值与相关的空间结构指数的灰色综合关联度排序依次为全混交度(0.7016)>林层指数(0.7008)>角尺度(0.6578)>开敞度(0.5960)>W_V_Hegyi竞争指数(0.5785),因此在进行林木单株间伐前考虑林分空间结构约束条件时,首先要考虑林分的混交度,其次是林层指数;将构建的模型用于研究样地(20 m×30 m)确定的最优间伐木为14株,间伐强度为14.1%,间伐后描述林分非空间结构的径阶数和树种数均未减少,保持原有的径阶个数和树种个数;间伐后林分全混交度提高2.71%,林分树种空间隔离程度得到提高;林分林层指数提高10.91%,林分垂直分层结构有较大幅度的改善;林分W_V_Hegyi竞争指数降低8.64%,林分中林木所受的竞争压力减小;林分|角尺度-0.5︱降低8.25%,林分空间分布格局更加趋向于随机分布;开敞度增加了11.98%,林分的透光条件有一定程度的改善,林分空间结构优化模型目标函数Q(g)值提高了12.18%。林分空间结构整体上趋向优化。

Abstract: The methods of multiplication and division were adopted to carry out the multiobjective programming and to determine the objective function so as to optimize stand spatial structure for the total mingling, forest layer index, W_V_Hegyi competition index, uniform angle index, and open degree, taking spatial structure and nonspatial structure as constraints. The model of stand thinning spatial structure optimizing model of Cunninghamia lanceolata ecological forest was built based on the determination of stand spatial structure constraint conditions priority by using grey relation method. This model was then used to determine the optimal solution of stand thinning spatial structure optimization of C. lanceolata ecological forest. The results showed that the stand spatial structure optimization objective function values of C. lanceolata ecological forest followed the order of total mingling (0.7016) > forest layer index (0.7008) > uniform angle index (0.6578) > open degree (0.5960) > W_V_Hegyi competition index (0.5785). Therefore, when considering stand spatial structure constraint condition before stand thinning, we must consider mingling firstly, followed by the forest layer index. The model was used in plots (20 m×30 m), where 14 optimally cutting trees were chosen with a thinning intensity of 14.1%. After thinning, the numbers of diameter class and tree species that describe nonspatial structure remained unchanged; stand mingling was increased by 2.71%, and species spatial isolation level was enhanced; forest layer index was increased by 10.91%, stand vertical hierarchical structure was improved greatly; W_V_Hegyi competition index was reduced by 8.64%, which showed a decline in stand competition pressure; uniform angle index was reduced by 8.25%, which showed a tendency of random distribution in stand spatial structure; open degree increased by 11.98%, which showed an improvement of light transmission. The objective function Q(g) value of stand spatial structure optimization model was increased by 12.18%.