Evaluating Tree Species Spatial Diversity Based on Neighborhood Relationships
This contribution presents a method for describing forest tree species diversity based on the analysis of tree neighborhoods. The proposed measure of tree species spatial diversity (TSS) is compared with four commonly used diversity indices using empirical and simulated data. The empirical dataset includes field observations with known tree coordinates from different forest types in China, Mongolia, Mexico, Germany, Myanmar, and South Africa. The simulated set uses 12 specifically designed patterns of spatial species mingling. The results show that the value of the TSS criterion increases with increasing tree species richness. In addition, TSS is sensitive to rare species and to variations in community structure, including species spatial isolation and spatial mingling. For these reasons, the TSS criterion is much more effective for measuring tree species diversity than the commonly used indices. It allows detailed interpretation of forest spatial diversity and of forest structural modifications after selective thinnings in multispecies forests. A particular advantage of the TSS index is the fact that its assessment, which is based on neighborhood relations, can be easily integrated in routine forest management surveys at practically no additional cost.
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Document Type: Research Article
Publication date: 2011-08-01
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Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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