Tracing Tree Water Storage and Transport in Trembling Aspen and Douglas Fir in Idaho, USA: An in Situ Study Using Deuterated Water and CRDS Spectroscopy
Abstract
Ecohydrological models frequently assume steady-state water flow through the soil-plant-atmosphere continuum, but this assumption overlooks complex spatial and temporal dynamics of water movement and within trees. We used isotopic tracer methods to investigate non-steady state dynamics of water storage and transport at weekly to monthly temporal scales to help address knowledge gaps in current ecophysiological and hydrological frameworks. We injected deuterated water (0.5 g 99.9% APE D2O per centimeter of tree circumference at breast height) at 0.3 meters above the base of the stem into the sap woods of two common tree species trampling Aspen (Populus tremuloides) and Douglas Fir (Pseudotsuga menziesii) located in a montane forest in southern Idaho, USA. We monitored Delta 2H pre- and post-injection in the sapwood and heartwood at 3 levels along the stems of mature trees, by measuring water vapor in boreholes using a Picarro L2130-i isotopic water analyzer. In Douglas Fir tracer was found to move quickly from the base of the tree to the upper stem, where it was distributed throughout the sapwood and heartwood for approximately 18 days before returning to the pre-injection 2H concentration level. Aspen showed a similar pattern but with a much weaker isotopic signature. The total length of time we found tracer in trees was significantly less than a similar study conducted the previous summer in a much wetter environment in the eastern USA. Results of this study suggest that water moves quickly within these particular tree species growing in a semiarid environment.
Furthermore, these findings indicate minimal long-term water storage (<7 days) along the tree stem. Climate models project changes in seasonal precipitation patterns and extreme heat in these regions, and trees with greater water storage capacity may be more resilient to the effects of drought stress. Thus, findings from this study may improve the predictive capabilities of hydrological models at the individual tree- and landscape level with shifting climate variables.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.B53D..02B