Wang Xin-Ting, Wang Dian-Jie, Li Hai-Bing, Tai Yang, Jiang Chao, Liu Fang, Li Su-Ying, Miao Bai-Ling
School of Energy and Power Engineering, Inner Mongolia University of Technology/Key Laboratory of Environmental Pollution Control and Remediation at Universities of Inner Mongolia Autonomous Region, Hohhot 010051, China.
Inner Mongolia Research Academy of Ecological and Environmental Sciences, Hohhot 010011, China.
Ying Yong Sheng Tai Xue Bao. 2022 May;33(5):1275-1282. doi: 10.13287/j.1001-9332.202205.005.
The spatial pattern of plant population is one of primary issues in ecological research. Point pattern analy-sis is considered as an important method to study the spatial pattern of plant population. Ripley's function has been commonly used for point pattern analysis. However, the cumulative effect of Ripley's function may lead to specific spatial pattern charcteristics. To explore how the cumulative effect of Ripley's function affects population pattern, the data of clumped distribution, random distribution and regular distribution of were simulated by R software. All data generated by R software were analyzed by Ripley's function and the non-cumulative pairwise correlation function (). The results showed that for clumped distribution (or regular distribution), the cumulative effect of Ripley's function was manifested in two aspects. On the one hand, the scale of clumped distribution (or regular distribution) was increased due to Ripley's function. On the other hand, Ripley's function could detect the difference of the distribution of cluster (or negative interaction range) in the sampling space, exhibiting different pattern characteristics. For random distribution, Ripley's function had no cumulative effect. In conclusion, the combination of Ripley's function and pairwise correlation function by collecting replicate samples could better reveal the essential characteristics of the pattern in the study of population pattern.
植物种群的空间格局是生态学研究的主要问题之一。点格局分析被认为是研究植物种群空间格局的一种重要方法。Ripley's函数已被广泛用于点格局分析。然而，Ripley's函数的累积效应可能导致特定的空间格局特征。为了探究Ripley's函数的累积效应如何影响种群格局，利用R软件模拟了聚集分布、随机分布和规则分布的数据。对R软件生成的所有数据进行Ripley's函数和非累积成对相关函数分析。结果表明，对于聚集分布（或规则分布），Ripley's函数的累积效应体现在两个方面。一方面，Ripley's函数使聚集分布（或规则分布）的尺度增大。另一方面，Ripley's函数能够检测采样空间中聚集体分布（或负相互作用范围）的差异，呈现出不同的格局特征。对于随机分布，Ripley's函数没有累积效应。总之，在种群格局研究中，通过收集重复样本将Ripley's函数与成对相关函数相结合，能够更好地揭示格局的本质特征。
