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Exploring stand and tree variability in mixed Nothofagus second-growth forests through multivariate analyses

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Moreno, Paulo C
Gezan, Salvador A
Palmas, Sebastian
Escobedo, Francisco J
Cropper, Wendell P

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2018

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Universidad Austral de Chile

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Abstract
Second-growth forests of Nothofagus obliqua (roble), N. alpina (raulí) and N. dombeyi (coihue), known locally as RO-RA-CO forest type, are among the most important natural mixed forest types of Chile. Several studies have identified a wide range of factors that could influence both stand and tree variability found in these forests. To better characterize potential tree- and stand-level factors that are associated with RO-RA-CO variability, and that are available in typical forest inventories, several unsupervised multivariate statistical methods were evaluated: 1) non-metric multidimensional scaling (NMDS); 2) principal coordinates analysis (PCoA); and 3) principal component analysis (PCA). The data used in this study originated from a sample of 158 plots consisting of two plot networks that covered the full geographic area of the RO-RA-CO forest type in Chile. We found that site productivity and growth zones did not explain the differences within the sampled population. However, stand development stages, tree-to-tree competition, and tree-size attributes were critical variables with a high percentage of variance explained using PCA, ranging from 61 % to 67 %. In addition, for the PCoA analysis, the variable stand density is important, with ~78 % variance explained. © 2018, Universidad Austral de Chile. All rights reserved.
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K-means cluster , NMDS , PCA , Pcoa , RO-RA-CO forest type
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