Analysis and simulation of dynamic response behavior of Scots pine trees to wind loading

Area of Science:

• Forestry science
• Biophysics
• Computational modeling

Background:

• Wind significantly impacts forest ecosystems, influencing tree stability and dynamics.
• Understanding wind-tree interactions is crucial for forest management and risk assessment.

Purpose of the Study:

• To develop an empirical method for analyzing and simulating wind-induced stem displacement in Scots pine trees.
• To characterize complex tree motion patterns using singular spectrum analysis (SSA).
• To correlate specific motion components with wind characteristics and simulate tree responses.

Main Methods:

• Singular Spectrum Analysis (SSA) for time series decomposition of stem displacement.
• Correlation and spectral analysis to discriminate SSA components.
• Neural network training using SSA-derived components and wind speed data.

Main Results:

• SSA successfully decomposed tree stem displacement into trend, sway, and noise components.
• Non-oscillatory trend components showed direct correlation with wind characteristics.
• Tree sway, while dominant, was largely decoupled from near-surface airflow.
• Trained neural networks reasonably simulated Scots pine tree response to wind excitation.

Conclusions:

• SSA provides a robust method for characterizing complex wind-induced tree motion.
• The study demonstrates the potential of data-driven models (neural networks) for simulating forest dynamics.
• Distinguishing motion components is key to understanding wind-tree interactions in forest canopies.