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Abstract Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind‐induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearmanr = 0.72 to 0.80,p < 0.001). Greater canopy SWE was associated with storm temperatures between −7°C and 0°C and wind speeds less than 4 m s−1. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway.
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Monitoring Tree Sway as an Indicator of Water Stress
Abstract Understanding and predicting future consequences of increasingly frequent and intense droughts requires improved monitoring of forest response. Over the course of a day, tree mass and stiffness respond dynamically to changing atmospheric and hydraulic conditions. By conducting a 24‐hr experiment, we sought to disentangle the effects of changing mass and stiffness on tree sway period. We observed that tree mass and stiffness are influenced by changes in tree water content and that diurnal changes in tree sway period are chiefly driven by the loss and recovery of tree stiffness. Over a season‐long time series in twoQuercus rubra(red oak) trees, we observed more pronounced and substantially higher midday increases (+7%) in sway period during days with the driest soil moisture (<0.09) as compared to days when soils were wetter. These findings suggest that continuously monitoring tree sway period offers an innovative approach to detecting water stress in trees.
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- Award ID(s):
- 1700983
- PAR ID:
- 10448946
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 46
- Issue:
- 21
- ISSN:
- 0094-8276
- Format(s):
- Medium: X Size: p. 12021-12029
- Size(s):
- p. 12021-12029
- Sponsoring Org:
- National Science Foundation
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