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The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees
Published on: December 27, 2017
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Tree water balance drives temperate forest responses to drought
A B Berdanier1,2, J S Clark2,3
1University Program in Ecology, Duke University, Durham, North Carolina, 27708, USA.
Ecology
|August 26, 2018
Summary
Forest drought vulnerability can be predicted by tracking tree moisture reservoirs using a mass balance approach. This method links moisture depletion to tree performance and survival, improving drought impact assessments.
Area of Science:
- Ecology
- Forestry
- Environmental Science
Background:
- Intensifying drought is a major driver of global forest diebacks.
- Quantifying tree moisture access and depletion is challenging, limiting understanding of drought vulnerability.
- Forest moisture depletion primarily occurs through tree water use (transpiration).
Purpose of the Study:
- To develop a predictive model for drought impacts on tree fitness and demographic performance.
- To quantify how species and size differences influence tree moisture availability across landscapes.
- To link individual tree moisture deficit to biomass growth and reproductive output.
Main Methods:
- Developed a hierarchical state-space framework to estimate tree moisture reservoir as a mass balance.
- Applied the model to seasonal droughts using tree transpiration measurements.
- Tracked individual moisture reservoir depletion over drought periods.
Main Results:
- Drought impacts on tree fitness and demographic performance can be predicted by tracking the moisture reservoir.
- Species and size modulate moisture availability, influencing vulnerability across landscapes.
- Individual moisture deficit was successfully linked to biomass growth and reproductive output.
Conclusions:
- A mass balance approach effectively tracks tree moisture reservoirs and predicts drought vulnerability.
- This method provides insights into individual tree moisture deficit and demographic performance.
- The approach can forecast drought vulnerability in forest stands using sample tree data.
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