Frontiers in Forests and Global Change (Jun 2023)

A method to quantify and account for the hygroscopic effect in stem diameter variations

  • Fabien Delapierre,
  • Patrick Fonti,
  • Heike Lischke,
  • Christine Moos

DOI
https://doi.org/10.3389/ffgc.2023.1167542
Journal volume & issue
Vol. 6

Abstract

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Dendrometers recording stem diameter variations (SDV) at high-resolution are useful to assess trees' water relation since water reserves are stored in the elastic tissue of the bark. These tissues typically shrink during the day as they release water when evaporative demand is high and swell during the night as they are replenished when evaporative demand is low, generating the typical SDV profile known as the diel SDV cycle. However, similar SDV cycles have been observed on dead trees due to the hygroscopic shrinking and swelling of the dead bark tissues. In order to remove this hygroscopic effect of the bark, dendrometers are applied as close as possible to the living bark tissues by removing the outer dead layer, however with questionable success. In this study, we used SDV time series from 40 point dendrometers applied on dead-bark-removed mature trees to assess and quantify the remaining hygroscopic effect on individual trees. To do so, we checked SDV behavior in the cold season and explored the relation between the diel SDV cycle and changes in relative humidity (RH). Our results showed that (a) the hygroscopic effect in SDV can be well-detected based on the amplitude of the diel SDV cycle (diel SDVampl) and the correlation between SDV and RH during both the cold and the warm season; (b) the level of the hygroscopic effect varies strongly among individuals; (c) diel SDVampl is proportional to both changes in RH and transpiration so that the hygroscopic effect on the diel SDV cycle can be quantified using a linear model where (diel SDVampl) is a function of RH changes and transpiration. These results allow the use of the model to correct the amplitude of the diel SDV cycles and suggest that this method can be applied to other ecological relevant water-related SDV variables such as tree water deficit.

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