Тип публикации: статья из журнала

Год издания: 2022

Идентификатор DOI: 10.3390/f13070970

Ключевые слова: cell wall thickness, classification, climate reconstructions, deviation tracheidogram, radial cell sizes, water deficit

Аннотация: 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, weПоказать полностьюconsidered 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. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Журнал: Forests

Выпуск журнала: Vol. 13, Is. 7

Номера страниц: 970

ISSN журнала: 19994907

Издатель: MDPI

• Zharkov M.S. (Mathematical Methods and IT Department, Siberian Federal University, Krasnoyarsk, 660041, Russian Federation)
• Huang J.-G. (Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510070, China, Center of Plant Ecology, Core Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510070, China)
• Yang B. (Key Laboratory of Desert and Desertification, Northwest Institute of Eco‐Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China)
• Babushkina E.A. (Khakass Technical Institute, Siberian Federal University, Abakan, 655000, Russian Federation)
• Belokopytova L.V. (Khakass Technical Institute, Siberian Federal University, Abakan, 655000, Russian Federation)
• Vaganov E.A. (Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, 660036, Russian Federation, Institute of Ecology and Geography, Siberian Federal University, Krasnoyarsk, 660041, Russian Federation)
• Zhirnova D.F. (Khakass Technical Institute, Siberian Federal University, Abakan, 655000, Russian Federation)
• Ilyin V.A. (Mathematical Methods and IT Department, Siberian Federal University, Krasnoyarsk, 660041, Russian Federation)
• Popkova M.I. (Mathematical Methods and IT Department, Siberian Federal University, Krasnoyarsk, 660041, Russian Federation)
• Shishov V.V. (Mathematical Methods and IT Department, Siberian Federal University, Krasnoyarsk, 660041, Russian Federation, Center of Plant Ecology, Core Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510070, China)

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