Correction to: Principal Components Analysis: An Alternative Way for Removing Natural Growth Trends

Silva, Daniela Oliveira Da; Klausner, Virginia; Prestes, A.; Macedo, Humberto Gimenes; Aakala, Tuomas; Silva, Iuri Rojahn da

doi:10.1007/s00024-021-02807-x

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“…The measurement of the tree ring width was performed on a Velmex Table . The natural growth rate varies according to the biological characteristics of each species; in order to maximize climate signals, a detrending in each series must be performed. The detrending model depends on the study goal [26]. As this study aims to determine the climatological variabilities, the following steps were: (1) to obtain the tree ring widths for each (Figure 3); (2) to detrend the tree ring series using the 67% nspline (two-third spline) with 50% of frequency cutoff as the individual growth trend; (3) to subtract the trend from each tree series sample; (4) to calculate the mean chronology vising to minimize anomalies and/or damage or any other sporadic phenomenon that may occur in any tree (Figure 3); and (5) to improve the quality of the mean chronology, we used the statistical program COFECHA to find possible errors between samples and to check the synchronization between the tree ring series and the master series [27,28].…”

Section: The Chronologiesmentioning

confidence: 99%

Climate Influence in Dendrochronological Series of Araucaria angustifolia from Campos do Jordão, Brazil

et al. 2021

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A dendrochronological series of Araucaria angustifolia was analyzed for a better understanding 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 reconstruct 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 correlations 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.

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Section: The Chronologiesmentioning

confidence: 99%