[Cumulative effects of K-function in the research of point patterns]

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 K function has been commonly used for point pattern analysis. However, the cumulative effect of Ripley's K function may lead to specific spatial pattern charcteristics. To explore how the cumulative effect of Ripley's K function affects population pattern, the data of clumped distribution, random distribution and regular distribution of Stipa grandis were simulated by R software. All data generated by R software were analyzed by Ripley's K function and the non-cumulative pairwise correlation function g(r). The results showed that for clumped distribution (or regular distribution), the cumulative effect of Ripley's K function was manifested in two aspects. On the one hand, the scale of clumped distribution (or regular distribution) was increased due to Ripley's K function. On the other hand, Ripley's K 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 K function had no cumulative effect. In conclusion, the combination of Ripley's K function and pairwise correlation function by collecting replicate samples could better reveal the essential characteristics of the pattern in the study of population pattern.