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首页> 外文期刊>Journal of Forest Science >Multivariate analysis for assessment of the tree populations based on dendrometric data with an example of similarity among Norway spruce subpopulations
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Multivariate analysis for assessment of the tree populations based on dendrometric data with an example of similarity among Norway spruce subpopulations

机译:基于树状图数据的树木种群评估多变量分析,以挪威云杉亚种群之间的相似性为例

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摘要

The new method for evaluation of tree populations presented here is based on a correlation analysis within a set of dendrometric variables. The correlation analysis is carried out for each population separately. The method evaluates differences between resulting correlation matrices. These distances can be used by hierarchical cluster analysis (unweighted pair-group average) or by ordination analysis (non-metric multidimensional scaling – NMS). Test data were obtained in 10 research plots in the area of Medvědí Mt., ?umava National Park. Plots are located in Norway spruce [Picea abies (Linnaeus) H. Karsten] climax forests. The results enable ecological interpretation of both classification and NMS. The populations (subpopulations) differ in their origin (spontaneous succession or partial planting) and environmental conditions (extreme environment near the mountain summit versus water-logged soils). These differences were reflected in results of the classification and ordination of the spruce (sub)populations.
机译:本文介绍的评估树木种群的新方法基于一组树状变量中的相关性分析。对每个人群分别进行相关分析。该方法评估所得相关矩阵之间的差异。这些距离可以用于层次聚类分析(未加权对组平均值)或排序分析(非度量多维标度– NMS)。测试数据是在乌马瓦国家公园Medvědí山的10个研究地块中获得的。地块位于挪威云杉[Picea abies(Linnaeus)H. Karsten]高潮森林中。结果使分类和NMS的生态解释成为可能。种群(亚种群)的来源(自发演替或部分种植)和环境条件(山顶附近的极端环境与积水的土壤)不同。这些差异反映在云杉(亚)种群的分类和排序结果中。

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