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Item Exploring patterns in dendrochronological data through cluster analysis(Universidade Federal do Paraná) Muraja, Daniela Oliveira Silva; Leite, Cecília Lemes; Klausner, Virginia; Prestes, Alan; Silva, Iuri Rojahn daThis study employed the dendrogram methodology to analyze time series data obtained from measuring tree growth rings. A total of 64 samples were collected from 21 individual trees. Polynomials were applied to filter the natural growth pattern of the trees and enhance the impact of external factors, such as climate influences. Cluster analysis using Ward's minimum variance and Euclidean squared distance was utilized to group the data based on similarity. Three dendrograms were constructed, consisting of 10, 47, and 64 samples, respectively. The analysis revealed that the samples with the highest correlations, encompassing over 95% of the total samples, formed homogeneous groups. Pearson correlation was also employed to confirm the results obtained from the dendrograms. Consequently, it can be affirmed that the most suitable samples were utilized in constructing the average chronology from the available data.Item Exploring the centennial-scale climate history of Southern Brazil with Ocotea porosa (Nees & Mart.) Barroso Tree-Rings(MDPI) Muraja, Daniela Oliveira Silva; Klausner, Virginia; Prestes, Alan; Aakala, Tuomas; Macedo, Humberto Gimenes; Silva, Iuri Rojahn daThis article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as |rx,P| = 0.32 for precipitation and |rx,T| = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso.Item Ocean–atmosphere interaction identified in tree-ring time series from southern Brazil using cross-wavelet analysis(Springer Nature Link) Muraja, Daniela Oliveira Silva; Klausner, Virginia; Prestes, Alan; Silva, Iuri Rojahn daTropical dendrochronology has gained significant attention in recent years, particularly with the dendrochronological study of new species that produce annual growth rings and are responsive to environmental changes. Despite the progress, the extent to which ocean–atmosphere interactions influence regional climate and, consequently, tree growth, is not fully understood. Among the new species, Ocotea porosa (Nees & Mart.) Barroso (also known as Imbuia) has shown excellent potential for climate research. This study investigates the climatic and solar influences on a chronology of 41 Imbuia tree samples. Pearson’s correlation was used alongside Wavelet transform to evaluate periodicities between the tree-ring chronology and climatic parameters such as the southern-oscillation index (SOI), annual precipitation, El Niño 3.4 (PACE), and the South Atlantic Index (ATLS). Our analysis revealed evidence of the influence of the El Niño Southern Oscillation (SOI) on rainfall variability in the region, the Hale and Gleissberg solar cycles causing precipitation variation, likely due to the influence of the Atlantic Ocean, and the Brückner-Egeson-Lockyer climatic cycle, which is correlated with sunspot activity. Furthermore, our wavelet analysis identified possible connections to the Eastern Pacific-type El Niño events during five specific periods: 1911–1912, 1918–1919, 1976–1977, 1982–1983, and 1986–1987. The results indicate that southern Brazil is affected by several climatic and geophysical parameters from both the Atlantic and Pacific oceans, which directly affect the growth of Imbuia trees as their tree-ring series display sensitivity to these parameters.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.