Article ID Journal Published Year Pages File Type
86930 Forest Ecology and Management 2014 9 Pages PDF
Abstract

•We validate the bivariate distribution of structural parameters from the point of tree population.•The bivariate distribution of structural parameters reveals microstructure of tree population.•Different species constitute spatial structure diversity of forest.•Different sizes for a some population show different spatial attributes.•The bivariate distribution of structural parameters is helpful to biodiversity conservation and discovery.

Many indices can be used to describe the structural characteristics of tree populations at the forest stand scale. However, each of these indices can only express the whole or unilateral structure, i.e., none can simultaneously provide two or more aspects of the structural attributes of a tree population. The purpose of this study is to validate the bivariate distribution of structural parameters—a spatial structure analysis method based on the relationships between nearest-neighbor tree groups and to display its ability of analyzing tree population. Three common associated tree species, China ash (Fraxinus mandshurica Rupr.), Manchurian walnut (Juglans mandshurica Maxim.), and Amur lilac (Syringa amurensis Rupr.), in a mixed forest of China ash–Manchurian walnut were used as an example to validate the method. This type of mixed forest is one of the most common Korean pine broad-leaved forests in northeast China. Each population and resident individuals within different size classes were analyzed in detail. Our results demonstrate that the new method not only effectively reflects the similarities and differences among the three populations from two aspects, but also well represents the structural differentiation among trees within a species. The method provides much more structural information than most traditional methods, which may be helpful to further our understanding of population structure and to discover and protect biodiversity in the future.

Related Topics
Life Sciences Agricultural and Biological Sciences Ecology, Evolution, Behavior and Systematics
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