Tracheidogram’s Classification as a New Potential Proxy in High-Resolution Dendroclimatic Reconstructions

Author:

Zharkov Mikhail S.ORCID,Huang Jian-GuoORCID,Yang BaoORCID,Babushkina Elena A.ORCID,Belokopytova Liliana V.ORCID,Vaganov Eugene A.,Zhirnova Dina F.,Ilyin Victor A.,Popkova Margarita I.ORCID,Shishov Vladimir V.ORCID

Abstract

Quantitative wood anatomy (QWA) is widely used to resolve a fundamental problem of tree responses to past, ongoing and forecasted climate changes. Potentially, QWA data can be considered as a new proxy source for long-term climate reconstruction with higher temporal resolution than traditional dendroclimatic data. In this paper, we considered a tracheidogram as a set of two interconnected variables describing the dynamics of seasonal variability in the radial cell size and cell wall thickness in conifer trees. We used 1386 cell profiles (tracheidograms) obtained for seven Scots pine (Pinus sylvestris) trees growing in the cold semiarid conditions of Southern Siberia over the years 1813–2018. We developed a “deviation tracheidogram” approach for adequately describing the traits of tree-ring formation in different climate conditions over a long-term time span. Based on the NbClust approach and K-means method, the deviation tracheidograms were reliably split into four clusters (classes) with clear bio-ecological interpretations (from the most favorable growth conditions to worse ones) over the years 1813–2018. It has been shown that the obtained classes of tracheidograms can be directly associated with different levels of water deficit, for both the current and previous growing seasons. The tracheidogram cluster reconstruction shows that the entire 19th century was characterized by considerable water deficit, which has not been revealed by the climate-sensitive tree-ring chronology of the study site. Therefore, the proposed research offers new perspectives for better understanding how tree radial growth responds to changing seasonal climate and a new independent proxy for developing long-term detailed climatic reconstructions through the detailed analysis of long-term archives of QWA data for different conifer species and various forest ecosystems in future research.

Funder

Russian Science Foundation

Publisher

MDPI AG

Subject

Forestry

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