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