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Increasing the Accuracy of Tree-Ring Data Processing to Improve Models for Reconstructing Climate

Abstract Number:

2678 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Bailey Reutinger (1), Nicholas Bussberg (1), David Vandermast (1)

Institutions:

(1) Elon University, Elon, NC

Co-Author(s):

Nicholas Bussberg  
Elon University
David Vandermast  
Elon University

First Author:

Bailey Reutinger  
Elon University

Presenting Author:

Bailey Reutinger  
N/A

Abstract Text:

Tree-ring data is used to reconstruct past climate and to predict future climate trends. In each year of a tree's lifespan a distinct ring is added to the tree's width, and widths of individual rings vary depending on the environment in which a tree lives. To process tree-ring data, two cores from each tree are extracted, and then all cores are combined before analysis. We aim to improve the modeling of future climate scenarios by assessing the accuracy of tree-ring data collection. Our investigation of data from the International Tree-Ring Data Bank found that correlated tree cores do not necessarily have the same ring widths, and trees with low correlation may have worse correlation with local climate data. These findings imply that only trees with moderate or better internal correlation should be used for climate modeling. To target differences among tree-ring data processing methods, we collected cores from trees in Elon University Forest. With this data, we combined and correlated widths of rings on each core with local climate. By combining these cores according to existing dendrochronological methods, we recommend best approaches that produce the best-fit with local climate.

Keywords:

Tree-rings| Climate| Environment| Dendrochronology| Climate Modeling|

Sponsors:

Section on Statistics and the Environment

Tracks:

Environmental and Ecological Monitoring

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