Canopy wetting patterns and the determinants of dry season dewfall in an old growth Douglas-fir canopy

Year: 
2022
Publications Type: 
Journal Article
Publication Number: 
5232
Citation: 

Sibley, A., Schulze, M., Jones, J., Kennedy, A., Still, C. 2022. Canopy wetting patterns and the determinants of dry season dewfall in an old growth Douglas-fir canopy. Agricultural and Forest Meteorology. 323: 109069. doi:https://doi.org/10.1016/j.agrformet.2022.109069

Abstract: 

Canopy wetting and drying has a variety of effects on the function of plant foliage, ranging from increased risk of pathogenic infection to reduced diffusion of gases to enhanced leaf water status in plants capable of foliar water uptake (FWU). Projected shifts in rainfall regimes and increases in summertime vapor pressure deficit will likely change the timing and duration of canopy wetting, yet current patterns of wetting are poorly understood. In this study, we investigated patterns of wetting by source (rain, dew, or frost), at different canopy heights, and at annual, seasonal and diurnal time scales using leaf wetness sensor data collected over a 4-year period in an old growth Douglas-fir tree in a temperate wet forest. We found that canopy layers were wet for roughly half the year with strong seasonal variation, staying wet 83% of the cold winter season but only 1.9% of the dry season. Upper canopy layers experienced higher wetting frequency and shorter wetting duration in all seasons compared to lower canopy layers. Outside of the dry season, wetness was predominantly caused by rain, while in the dry season the predominant source was dewfall. Throughout the year and particularly in the dry season, dewfall was restricted to the upper canopy, occurring on 28.5% of dry season nights. Multiple models which use meteoro­logical variables to predict dewfall timing and length were developed and evaluated. Using in-tree observations, dry season dewfall was best predicted with a logistic model using dewpoint depression as a predictor. Using observations from a nearby weather station in a clearing, dry season dewfall was best predicted with the Penman equation, a biophysical model. The most important determinant of dry season dewfall in our study was sufficient nighttime cooling of the air, suggesting that increasing nighttime temperatures will lead to a decrease in dew formation frequency in the future.