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Correlation between tree-ring series as a dendroprovenancing evaluation tool.

Mauro Bernabei1, Pietro Franceschi2

  • 1Institute of Bioeconomy, National Research Council, Via F. Biasi 75, 38098 San Michele all'Adige, TN, Italy.

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|September 26, 2024
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Summary
This summary is machine-generated.

This study validates using tree-ring correlation for dendroprovenance, showing increased correlation at closer distances. A new model estimates distance in kilometers, with spruce showing promising results.

Keywords:
Abies albaAlpsConifersCorrelation testsDendroprovenancingElevationLarix deciduaPicea abies

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Area of Science:

  • Dendrochronology
  • Geospatial Analysis
  • Environmental Science

Background:

  • Dendroprovenancing relies on tree-ring analysis, but correlation's efficacy as a proximity indicator is debated.
  • Existing methods face challenges with accuracy and practicality, necessitating new approaches.

Purpose of the Study:

  • To investigate the reliability of correlation analysis for dendroprovenance using a large dataset of Alpine conifers.
  • To develop and validate a quantitative model for estimating geographical distance based on tree-ring correlation.

Main Methods:

  • Analysis of approximately 12,000 geolocalised tree-ring series from spruce, larch, and fir.
  • Statistical correlation analysis and development of a quantile regression model for distance estimation.
  • Evaluation of altitude's influence on dendroprovenance accuracy.

Main Results:

  • A significant increase in correlation was observed at shorter distances, validating the correlation approach.
  • A simplified quantile regression model was developed to estimate distance in kilometers.
  • Spruce yielded the most promising results, while fir presented challenges; altitude impacts distance estimation.

Conclusions:

  • Correlation analysis is a viable tool for dendroprovenance, especially with large datasets.
  • The developed model offers a practical method for estimating distances between tree-ring sample sites.
  • Further research is needed to refine methods for species like fir and account for environmental factors like altitude.