A new method for measuring population distribution patterns of forest trees based on the mingling degree.

Analysis of spatial patterns of populations is an important approach to study the characteristics of populations, interaction among populations and relations between a population and its environment and has been a research focus in ecology for some time. The mingling degree is an index to describe spatial segregation among tree species, i.e., the probability that the nearest adjacent tree, a random occurrence in a mixed forest, belongs to another species. As yet, we are not aware of publications of any analysis of population distribution patterns by a direct use of this mingling degree, recognized not only as a clear and scientific index for describing tree species segregation, but is also a simple and effective way for data collection and measurements. We propose a new method, DM, of testing population distributions by analyzing the relationship between expected and observed values of this mingling degree. A statistical significance test method was introduced. The method was applied to measure the distribution pattern of tree species in a natural mixed forest in Xiaolong Mountain, Gansu Province, northwestern China. Compared with the classic aggregation index R, the test accuracy of DM is 100%, suggesting that the theoretical defect of the aggregation index R has been avoided. Application of this method will enhance research on the spatial structure of stands, based on the relationships between adjacent trees.