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A Technical Perspective in Modern Tree-ring Research - How to Overcome Dendroecological and Wood Anatomical Challenges
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Monitoring wood phenology using dendrometers: opportunities and pitfalls
Ignatius Kristia Adikurnia1, Cyrille B K Rathgeber2
1Department of Material and Environmental Technology, Tallinn University of Technology, Estonia.
Quantitative Plant Biology
|December 25, 2025
Summary
Dendrometers provide unreliable estimates of tree growth phenology, varying by species and environment. Concurrent monitoring of xylogenesis alongside dendrometers is recommended for accurate wood formation assessment.
Area of Science:
- Forest ecology
- Climate change impacts
- Tree physiology
Background:
- Climate change significantly affects tree growth and carbon sequestration.
- Dendrometers and microcores are common methods for studying wood formation and phenology.
- The accuracy of dendrometers for estimating growth phenology requires further evaluation.
Purpose of the Study:
- To assess the reliability of dendrometer-based phenology estimates compared to microcore-based xylogenesis.
- To investigate how species traits, climate, and site conditions influence dendrometer accuracy.
- To provide recommendations for accurate monitoring of tree wood phenology.
Main Methods:
- Comparative analysis of phenological data derived from dendrometers and microcores.
- Study included six tree species with diverse ring structures and bark types across varied sites.
- Phenology was assessed under contrasting climatic and site conditions.
Main Results:
- Dendrometer estimates of growth phenology showed poor accuracy.
- Accuracy varied significantly based on species life traits, climate, and site conditions.
- Microcore analysis revealed discrepancies with dendrometer-derived phenological timing.
Conclusions:
- Dendrometers have significant limitations for accurately assessing tree wood phenology.
- Accurate evaluation of wood phenology necessitates combining dendrometer data with xylogenesis monitoring.
- Understanding these limitations is crucial for climate change impact research on forests.
