A Tree-Ring-Based Assessment of Pinus armandii Adaptability to Climate Using Two Statistical Methods in Mt. Yao, Central China during 1961–2016
Assessing the characteristics and limiting factors of tree growth is of practical significance for environmental studies and climatic reconstruction, especially in climate transition zones. In this study, four sites of Pinus armandii Franeh are investigated to understand regional climate-tree growth...
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Published in | Forests Vol. 12; no. 6; p. 780 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
01.06.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Assessing the characteristics and limiting factors of tree growth is of practical significance for environmental studies and climatic reconstruction, especially in climate transition zones. In this study, four sites of Pinus armandii Franeh are investigated to understand regional climate-tree growth response in Mt. Yao, central China. Based on the high similarity of four residual chronologies and high correlations between chronologies and climatic factors, we analyzed the correlations of regional residual chronology with monthly climatic factors and the self-calibrating Palmer Drought Severity Index (scPDSI) from 1961–2016. The results indicate that the hydrothermal combination of prior August and current May and the scPDSI in May are main limiting factors of regional tree growth in Mt. Yao. The results of stepwise regression models also show that temperature and scPDSI in May are the main limiting factors of tree growth, but the limiting effect of scPDSI is more than temperature in this month. Through the analysis of the number of tree growth years corresponding to high temperature and high scPDSI, it was further confirmed that scPDSI in May is the main limiting factor on the growth of P. armandii in Mt. Yao. However, the influence of scPDSI in May has weakened, while temperature in May has increasingly significant influence on tree growth. The above findings will help improve our understanding of forest dynamics in central China under global climate change. |
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ISSN: | 1999-4907 1999-4907 |
DOI: | 10.3390/f12060780 |