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Dissecting the space-time structure of tree-ring datasets using the partial triadic analysis.

Jean-Pierre Rossi1, Maxime Nardin2, Martin Godefroid1

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Partial triadic analysis (PTA) effectively analyzes complex tree-ring data, revealing spatial structures and temporal dynamics. This method highlights inter-individual variability and links tree growth patterns to climate change and defoliation events.

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Area of Science:

  • Dendrochronology
  • Ecology
  • Climatology
  • Wood Science
  • Multivariate Statistics

Background:

  • Tree-ring datasets offer insights into archaeology, climatology, forest ecology, and wood technology.
  • Traditional multivariate analyses often simplify tree-ring data (ring variables × trees × time) into two-way matrices.
  • Extracting comprehensive space-time information from these complex datacubes remains a challenge.

Purpose of the Study:

  • To explore the potential of partial triadic analysis (PTA) for analyzing three-way tree-ring datasets.
  • To investigate the space-time structure of tree-ring data, specifically focusing on temporal evolution of spatial structures and spatial structure of temporal dynamics.
  • To apply PTA to a dataset of European larch (Larix decidua Miller) tree-ring descriptors.

Main Methods:

  • Collected 11 tree-ring descriptors (e.g., ring width, early/latewood density) from 149 georeferenced European larch individuals (1967-2007).
  • Processed microdensity profiles to generate a three-way data table (descriptors × trees × time).
  • Applied partial triadic analysis (PTA) to analyze the temporal evolution of spatial structures and the spatial structure of temporal dynamics.

Main Results:

  • Identified a common spatial structure across years, indicating significant inter-individual variability in ring descriptors at the stand scale.
  • Revealed a common temporal trajectory for the trees, separable into high-frequency (inter-annual variations, possibly defoliation) and low-frequency (long-term trend, possibly climate change) signals.
  • Demonstrated the presence of distinct spatial and temporal patterns within the tree-ring data.

Conclusions:

  • Partial triadic analysis (PTA) is a powerful multivariate tool for unraveling complex variations in tree-ring datasets.
  • PTA effectively captures both spatial structures and temporal dynamics, providing a more holistic understanding of tree growth.
  • The study highlights PTA's utility in identifying environmental influences like climate change and defoliation events on tree growth patterns.