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

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 coherenc...

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Bibliographic Details
Main Authors: Angelo Rita, Jesús Julio Camarero, Michele Colangelo, Ester González de Andrés, Marín Pompa-García
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/13/6/956
Description
Summary: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: <i>Pinus lumholtzii</i> in wet-summer northern Mexico, and <i>Pinus halepensis</i> and <i>Pinus sylvestris</i> 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.
ISSN:1999-4907