关键词: 高黎贡山, 点格局, 成对相关函数, 空间分布, 种间关联

Abstract: Aims The spatial distribution and associations of tree species can reflect interspecies relationships and their interaction with the surrounding environment, which are of great significance for revealing community construction and species coexistence. Methods Therefore, to explore the spatial distribution pattern of the tree species in the mid-mountain moist evergreen broadleaf forest in the southern of Gaoligong Mountains, the spatial distribution and interspecies associations of the top ten dominant species with important values were analyzed by using the point patter analysis method for all woody plant with DBH ≥ 1 cm in the 4 hm2 plot of Gaoligong Mountains. Important findings The results showed that: (1) The diameter class structure of the ten dominant species and the species of whole plot were distinctly J-shaped, which indicated that they were a growing population and conducive to population recruitment. (2) Under the complete spatial model randomness with univariate pairwise correlation functions, the small-scale distribution was aggregation. The degree of aggregation then decreased with increasing scale, the large scale was random distribution and uniform distribution. After removing environmental heterogeneity, the scale range of aggregation distribution was shortened, and the scale range of random distribution and uniform distribution were increased. (3) Under the bivariate pairwise correlation functions test simulation, complete spatial randomness model of the correlation among the ten species was dominated by significant positive association, while the prerequisite model was dominated by no association. To conclude, the distribution pattern and correlation of four dominant species in Gaoligong Mountains varied with the spatial scale, which further proved that the spatial distribution of species were strongly scale-dependent. Thereby, the forest was affected by several factors, such as diffusion restriction, negative density dependence and habitat heterogeneity and so on.

Key words: Gaoligong Mountains, point pattern, pairwise correlation function, spatial distribution, interspecies associations