Abstract
Abstract. Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world's forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. We found that the two most descriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns.
Highlights
Tree size and growth rate are influenced by their local wind environment (Bonnesoeur et al, 2016; MacFarlane and Kane, 2017) which in turn has an impact on forest carbon storage and dynamics
We found that a number of catch22 features were important for classifying tree types and were highly correlated with tree size (S3–S4)
We compared trees and tested trends based on features extracted from the tree motion time series
Summary
Tree size and growth rate are influenced by their local wind environment (Bonnesoeur et al, 2016; MacFarlane and Kane, 2017) which in turn has an impact on forest carbon storage and dynamics. Trees have characteristic and recognizable swaying patterns This means that tree motion time series are distinct from each other and from the time series of local wind speeds. These tree motion characteristics are determined by tree size, shape, and, to a lesser extent, material properties (Dargahi et al, 2020; Jackson et al, 2019; Sellier and Fourcaud, 2009). Trees in dense forests generally have a slender form with a small crown near the top (MacFarlane and Kane, 2017), which leads to a slow, pendulum-like motion (Sellier and Fourcaud, 2009)
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