Chin J Plant Ecol ›› 2017, Vol. 41 ›› Issue (5): 577-584.DOI: 10.17521/cjpe.2016.0383

• Method and Technology • Previous Articles     Next Articles

Point pattern analysis under conditions of replicated sampling

Xin-Ting WANG1,*, Wei-Hua ZHANG1, Chao JIANG2,*, Cun-Zhu LIANG3   

  1. 1School of Energy and Power Engineering, Inner Mongolia University of Technology, Huhhot 010051, China

    2Institute of Grassland Research, Chinese Academy of Agriculture Sciences, Key of Laboratory of Grassland Ecology and Restoration, Ministry of Agriculture, Huhhot 010010, China

    3College of Ecology and Environment, Inner Mongolia University, Huhhot 010021, China
  • Online:2017-05-10 Published:2017-06-22
  • Contact: Xin-Ting WANG,Chao JIANG
  • About author:KANG Jing-yao(1991-), E-mail:


Aims The analysis of point patterns, which deals with data sets consisting of mapped locations of organisms in a study region, is especially important to plant ecological studies because the locations of plants can often be approximated as points. However, few studies used point pattern analysis with data collected by replicated sampling a principle procedure of acquiring data in ecological research. Therefore, we explore the applicability of point pattern analysis under conditions of replicated sampling in this studyMethodsThree replicated 5 m × 5 m plots of homogenous communities were established on a site with eight years of restoration in Nei Mongol steppe. In each plot, the locations of individuals in Leymus chinensis and Stipa grandis populations were mapped. O-Ring function was used to describe the population patterns and species association between L. chinensis and S. grandis for each plot as well as the integrative data of the three replicates.Important findings Population patterns and species associations differed among the three replicated plots. This illustrates that if point pattern analysis was applied to describe the population patterns and species associations only by using data from a single plot sampling, the results could be misleading. Whereas it would be more reliable to integrate the data of replicated plots in the point pattern analysis because in this way the resulting O-Ring function is a weighted average, where the weight is the number of points in the replicate i divided by the total number of points in all replicated plots.

Key words: replicated sampling, point pattern analysis, O-Ring function