The use of correlation between tree-ring series as a proximity indicator in dendroprovenance analyses is often questioned. High correlations may occur between series at a great distance, but conversely, low correlations may occur between series that are close to each other. This discrepancy has prompted the exploration of alternative dendroprovenancing methods, but many of them have proven to be unreliable or impractical. In this study, approximately 12,000 geolocalised tree-ring series from the three main Alpine conifers—spruce, larch, and fir—were analysed to investigate the extent to which correlation analysis can be used as a dendroprovenance tool. The results clearly indicate a significant increase of correlation at low distance and validate the proposed correlation approach. The large dataset also made it possible to develop a simplified quantile regression model that could be used to estimate distance in kilometres based on correlation values between the tree-ring series. Spruce exhibited the most promising results, which is attributed in part to the extensive dataset available, while there were challenges with fir in accurately determining distances between sites. Finally, the study also evaluated the impact of altitude on distance estimation and showed how this environmental factor influences variations in dendroprovenance analyses.

Correlation between tree-ring series as a dendroprovenancing evaluation tool

Bernabei M.
;
2024

Abstract

The use of correlation between tree-ring series as a proximity indicator in dendroprovenance analyses is often questioned. High correlations may occur between series at a great distance, but conversely, low correlations may occur between series that are close to each other. This discrepancy has prompted the exploration of alternative dendroprovenancing methods, but many of them have proven to be unreliable or impractical. In this study, approximately 12,000 geolocalised tree-ring series from the three main Alpine conifers—spruce, larch, and fir—were analysed to investigate the extent to which correlation analysis can be used as a dendroprovenance tool. The results clearly indicate a significant increase of correlation at low distance and validate the proposed correlation approach. The large dataset also made it possible to develop a simplified quantile regression model that could be used to estimate distance in kilometres based on correlation values between the tree-ring series. Spruce exhibited the most promising results, which is attributed in part to the extensive dataset available, while there were challenges with fir in accurately determining distances between sites. Finally, the study also evaluated the impact of altitude on distance estimation and showed how this environmental factor influences variations in dendroprovenance analyses.
2024
Istituto per la BioEconomia - IBE - Sede Secondaria San Michele all'Adige (TN)
Abies alba
Alps
Conifers
Correlation tests
Dendroprovenancing
Elevation
Larix decidua
Picea abies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/535898
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