Replication data for: Enhanced Structural Complexity Index: An Improved Index for Describing Forest Structural Complexity
World Agroforestry - Research Data Repository Dataverse OAI Archive
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Title |
Replication data for: Enhanced Structural Complexity Index: An Improved Index for Describing Forest Structural Complexity
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Identifier |
https://doi.org/10.34725/DVN/25315
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Creator |
Rhett D Harrison
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Publisher |
World Agroforestry - Research Data Repository
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Description |
The horizontal distribution of stems, stand density and the differentiation of tree dimensions are among the most important aspects of stand structure. An increasing complexity of stand structure is often linked to a higher number of species and to greater ecological stability. For quantification, the Structural Com- plexity Index (SCI) describes structural complexity by means of an area ratio of the surface that is gener- ated by connecting the tree tops of neighbouring trees to form triangles to the surface that is covered by all triangles if projected on a flat plane. Here, we propose two ecologically relevant modifications of the SCI: The degree of mingling of tree attributes, quantified by a vector ruggedness measure, and a stem density term. We investigate how these two modifications influence index values. Data come from forest inventory field plots sampled along a disturbance gradient from heavily disturbed shrub land, through secondary regrowth to mature montane rainforest stands in Mengsong, Xishuangbanna, Yunnan, China. An application is described linking structural complexity, as described by the SCI and its modified ver- sions, to changes in species composition of insect communities. The results of this study show that the Enhanced Structural Complexity Index (ESCI) can serve as a valuable tool for forest manag ers and ecolo- gists for describing the structural complexity of forest stands and is particularly valuable for natural for- ests with a high degree of structural complexity. |
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Subject |
Agricultural Sciences
tropical forest structure |
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Date |
2013
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Type |
tree dbh and position and biodiversity data
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