Abstract
Aim of the study: Neighborhood-based stand spatial structure parameters can quantify and characterize forest spatial structure effectively. How these neighborhood-based structure parameters are influenced by the selection of different numbers of nearest-neighbor trees is unclear, and there is some disagreement in the literature regarding the appropriate number of nearest-neighbor trees to sample around reference trees. Understanding how to efficiently characterize forest structure is critical for forest management.Area of study: Multi-species uneven-aged forests of Northern ChinaMaterial and methods: We simulated stands with different spatial structural characteristics and systematically compared their structure parameters when two to eight neighboring trees were selected.Main results: Results showed that values of uniform angle index calculated in the same stand were different with different sizes of structure unit. When tree species and sizes were completely randomly interspersed, different numbers of neighbors had little influence on mingling and dominance indices. Changes of mingling or dominance indices caused by different numbers of neighbors occurred when the tree species or size classes were not randomly interspersed and their changing characteristics can be detected according to the spatial arrangement patterns of tree species and sizes.Research highlights: The number of neighboring trees selected for analyzing stand spatial structure parameters should be fixed. We proposed that the four-tree structure unit is the best compromise between sampling accuracy and costs for practical forest management.
Highlights
Forest management emphasizes the importance of structure and function, and focuses on achieving a natural state (Petritan et al, 2012)
Many approaches have been used to characterize forest structure and structure parameters (Gadow et al, 2012), but those based on relationships between nearest-neighbor tree groups are the effective and less expensive, since these set of parameters can be acquired by point sampling method without knowing the mapped data of forest and they are easy to calculate and interpret (Aguirre et al, 2003)
The fixed number structure unit has been successfully applied in the structure attributes analysis, our results showed the neighborhood-based structure analyses can be influenced by the structure unit size
Summary
Forest management emphasizes the importance of structure and function, and focuses on achieving a natural state (Petritan et al, 2012). Recent studies have addressed various stand spatial structure parameters based on relationships between nearest-neighbor tree groups: uniform angle index, mingling, and dominance (Graz, 2008; Petritan et al, 2012; Li et al, 2012; Gao et al, 2013, Zhang et al, 2014; Szmyt, 2014; Bettinger & Tang, 2015) These have been implemented to assess tree spatial distribution patterns, quantify the degree of interspersion of tree species and reflect size dominance of trees, respectively. Among forest structure parameters, these are Hongxiang Wang, Gongqiao Zhang, Gangying Hui, Yuanfa Li, Yanbo Hu, Zhonghua Zhao efficient in characterizing spatial structure and are cost efficient because researchers are not required to measure tree positions or distances between trees (Hui & Gadow, 2003) Researchers can evaluate these three structure parameters by comparing a reference tree with its n neighbors, simplifying sampling and making it possible to investigate forest structure and diversity along with traditional forest surveys. This set of structural parameters can be described by a mean structural index at the forest stand level or by a probability density distribution, and has a unique advantage in guiding forest structure management and simulating spatial structure
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