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Item Análise de componentes principais aplicada à dendrocronologiaSilva, Daniela Oliveira da; Oliveira, Virgínia Klausner de; Prestes, Alan; Macedo, Humberto GimenesItem Climate Influence in Dendrochronological Series of Araucaria angustifolia from Campos do Jordão, Brazil(MDPI) Silva, Daniela Oliveira da; Prestes, Alan; Klausner, Virginia; Souza, Táyla Gabrielle Gonçalves deA dendrochronological series of Araucaria angustifolia was analyzed for a better under- standing of the climatic factors that operate in Campos do Jordão city, São Paulo state, Brazil. The dendroclimatic analysis was carried out using 45 samples from 16 Araucaria angustifolia trees to recon- struct the precipitation and the temperature over the 1803–2012 yearly interval. To this end, Pearson’s correlation was calculated between mean chronology and the climatic time series using a monthly temporal resolution to calibrate our models. We obtained correlations as high as r = 0.22 (α = 0.1) for precipitation (February), and r = 0.21 (α = 0.1) for temperature (March), both corresponding to the end of the summer season. Our results show evidence of temporal instabilities because the corre- lations for the halves of 1963–2012 were very different, as well as for the full period. To overcome this problem, the dendrochronological series and the climatic data were investigated using the wavelet techniques searching for time-dependent cause–effect relationships. From these analyses, we find a strong influence of the region’s precipitation and temperature on the growth of tree ring widths.Item Principal component analysis applied to dendrochronology(Universidade Federal do Rio Grande do Norte) Silva, Daniela Oliveira da; Klausner, Virginia; Prestes, Alan; Macedo, Humberto GimenesThis work uses samples of the species Ocotea porosa (Nees & Mart) Barroso (Imbuia), collected in the city of General Carneiro, Southeast region of the State of Paraná (26o24'01 25"S 51o24'03 91"W), Brazil, to generate average chronology (GC index) of this region. The objective of this article is to remove the natural growth trends of trees using a tool that is still little explored for this purpose, Principal Component Analysis (PCA). In each tree sample, the width of each growth ring was measured, obtaining a time series (1 ring per year). The samples were selected using Cluster Analysis, which classifies samples based on their similarities. Once the Principal Components (PCs) were obtained, the dendrochronological series were reconstructed without the first PC. This methodology is an estimate of the trend that best represents the natural growth of all trees on the site. The arithmetic mean of the series without the 1st PC is the GC index. It was found that PCA has three benefits: fast data processing, preservation of low-frequency signals and, when integrated with a powerful tool, the Alternated Least Squares (ALS) method, missing data estimation.Item Principal Components Analysis: An Alternative Way for Removing Natural Growth Trends(Springer Nature Link) Silva, Daniela Oliveira da; Klausner, Virginia; Prestes, Alan; Macedo, Humberto Gimenes; Aakala, Tuomas; Silva, Iuri Rojahn daIn this article, we establish a new approach for removing natural growth trends from tree-ring samples, also called detrending. We demonstrate this approach using Ocotea porosa (Nees & Mart) Barroso trees. Nondestructive samples were collected in General Carneiro city, located in the Brazilian southern region (Paraná state). To remove natural tree growth trends, principal components analysis (PCA) was applied on the tree-ring series as a new detrending method. From this, we obtained the tree-ring indices by reconstructing the tree-ring series without the first principal component (PC), which we expect to represent the natural growth trend. The performance of this PCA method was then compared to other detrending methods commonly used in dendrochronology, such as the cubic spline method, negative exponential or linear regression curve, and the regional curve standardization method. A comparison of these methods showed that the PCA detrending method can be used as an alternative to traditional methods since (1) it preserves the low-frequency variance in the 566-year chronology and (2) represents an automatic way to remove the natural growth trends of all individual measurement series at the same time. Moreover, when implemented using the alternating least squares (ALS) method, the PCA can deal with tree-ring series of different lengths.