Does deadwood moisture vary jointly with surface soil water content?. Issue 4 (14th May 2022)

• Record Type: Journal Article
• Authors: Green, Mark B.; Fraver, Shawn; Lutz, David A.; Woodall, Christopher W.; D'Amato, Anthony W.; Evans, Daniel M.
• Is Part Of: Soil Science Society of America Journal. Volume 86:Issue 4(2022)
• Page Start: 1113
• Page End: 1121
• Publication Date: 2022-05-14
• Subjects: Soils -- United States -- Periodicals; Soil science -- Periodicals; Periodicals; 631.4973
• DOI: 10.1002/saj2.20413
• Languages: English
• ISSNs: 0361-5995

Abstract

Abstract: Deadwood moisture plays a major role in regulating deadwood decomposition rates and may also affect forest microclimate. Despite this, the temporal variability of deadwood moisture at 15‐min time scales remains relatively unknown because techniques for using high‐frequency sensors for tracking moisture at appropriate spatial and temporal intensities have been lacking. We installed a high‐density sensor array in and around a downed log to gain a detailed assessment regarding the temporal variation of volumetric water content at multiple locations within one downed dead log, the source snag, and the surrounding soil. We also measured micrometeorological variables near the log in order to predict variability of the deadwood moisture. We found that the deadwood varied in similar fashion as the soil moisture, and that this similarity allowed us to make accurate predictions of deadwood moisture using micrometeorological data and soil moisture. The primary driver of deadwood moisture was rainfall; however, diurnal cycles of subcanopy humidity and temperature seemed to cause variation in the deadwood moisture between rain events. Our findings highlight the need for applying similar techniques to a variety of forest types, deadwood types, and different forest management strategies to gain a broader understanding of high‐frequency deadwood moisture dynamics and their feedbacks with ecosystem processes, like decomposition and forest fire hazards. Core Ideas: High‐frequency deadwood moisture variation can be monitored with TDR sensors. Deadwood wets and dries in a similar fashion as shallow soil moisture. Diurnal evaporation and condensation variation causes deadwood moisture variation. Temporal variation of deadwood moisture can be well predicted with machine learning models.