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

Autor(es)

Da Silva, Daniela Oliveira ^[1] ; Klausner, Virginia ^[1] ; Prestes, Alan ^[1] ; Macedo, Humberto Gimenes ^[1] ; Aakala, Tuomas ^[2] ; Da Silva, Iuri Rojahn ^{[1, 2]}

Afiliação do(s) autor(es)

^[1] Vale Paraiba Univ UNIVAP, Res & Dev Inst IP&D, Sao Jose Dos Campos, SP - Brazil

^[2] Univ Eastern Finland UEF, Sch Forest Sci, Joensuu - Finland

• Tipo de documento: Artigo Científico
• Fonte: PURE AND APPLIED GEOPHYSICS; v. 178, n. 8, p. 3131-3149, AUG 2021.
• Citações Web of Science: 1

Resumo

In 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 (Parana 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. (AU)

• Processo FAPESP: 09/02907-8 - Estudo das inter-relações sol-terra-clima por meio de registros observacionais e naturais
• Beneficiário: Alan Prestes
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores