关键词: 空间分布格局, 标记相关函数, 空间点格局, 生境异质性, 生境划分, 邻体效应

Abstract:

Objective: The CSR (complete spatial randomness) null model of the point pattern analysis requires that the habitat background is homogeneous, but the most factors in natural forest habitat are heterogeneous, which will inevitably influence the point pattern analysis. This paper attempts to divide the heterogeneous plots into several relatively homogeneous subareas by the method of habitat division, and discusses the interaction rules among individual trees in different habitat subareas through the analysis of mark point pattern, in order to provide theoretical support for the management and operation of forest management. Method: Based on the data of 21.12 hm² natural mixed broadleaved-conifer forest, the forest plot was divided into two relatively homogeneous habitats (A and B) according to the topographic variables. The interaction effects between adjacent individuals were tested by using mark correlation function combined with the complete spatial randomness simulation process. Result: The mark correlation analysis of individual tree species showed that the vast majority of tree species in areas A and B showed negative spatial correlation between individual DBHs. Moreover, at the scale of r < 6 m, the number of tree species with negative correlation in area A was significantly higher than that in area B. At the scale of r < 9 m, no positive correlation between the individual DBHs was detected. Without considering the heterogeneity of habitat conditions, mark correlation analysis was carried out in the whole sample plot. At the scale of 0-8 m, the individual DBHs of canopy layer showed a significant negative correlation, and there was no significant spatial correlation between those of subcanopy layer and understorey layer. When the spatial autocorrelation of the attributes of individual DBHs in each forest layer was tested in a relatively uniform habitat, there was no significant spatial correlation between the individual DBHs of the sub-canopy layer and the understory layer, while those of the canopy layer had significant negative correlation at small scale. The interaction scale of the canopy individuals in area A was 0-6.9 m, and that of area B was 0-5.6 m. Conclusion: Under different habitat conditions (i.e., subzone A and B), the spatial negative correlation scales of DBH of adjacent individuals in the forest canopy are different. Therefore, in the process of forest management, the influence of habitat differences should be fully considered when determining the final stocking density of retained trees.

Key words: spatial distribution patterns, mark correlation function, spatial point pattern, habitat heterogeneity, habitat division, neighborhood competition effect