4.7 Article

Wood Anatomical Traits Respond to Climate but More Individualistically as Compared to Radial Growth: Analyze Trees, Not Means

期刊

FORESTS
卷 13, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/f13060956

关键词

dendroclimatology; Pinus lumholtzii; Pinus halepensis; Pinus sylvestris; quantitative wood anatomy; xylem

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资金

  1. Mexican CONACYT [CB-2013/222522-A1-S-21471]

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Wood encodes environmental information that can be recovered through the study of tree-ring width and wood anatomical variables. Wood anatomical variables show a more individualistic response to hydroclimate compared to tree-ring width, highlighting the importance of inter-individual variation in long-term studies on wood anatomical characteristics and understanding tree species' responses to climate change.
Wood encodes environmental information that can be recovered through the study of tree-ring width and wood anatomical variables such as lumen area or cell-wall thickness. Anatomical variables often provide a stronger hydroclimate signal than tree-ring width, but they show a low tree-to-tree coherence. We investigate the sources of variation in tree-ring width, lumen area, and cell-wall thickness in three pine species inhabiting sites with contrasting climate conditions: Pinus lumholtzii in wet-summer northern Mexico, and Pinus halepensis and Pinus sylvestris in dry-summer north-eastern Spain. We quantified the amount of variance of these three variables explained by spring and summer water balance and how it varied among trees. Wood anatomical variables accounted for a larger inter-individual variability than tree-ring width data. Anatomical traits responded to hydroclimate more individualistically than tree-ring width. This individualistic response represents an important issue in long-term studies on wood anatomical characteristics. We emphasized the degree of variation among individuals of the same population, which has far-reaching implications for understanding tree species' responses to climate change. Dendroclimatic and wood anatomical studies should focus on trees rather than on the mean population series.

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