1. Accuracy of the pneumatic method for estimating xylem vulnerability to embolism in temperate diffuse-porous tree species
- Author
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Paligi Ss, Roman M. Link, Luciano Pereira, Bernhard Schuldt, Emilie Isasa, Juliano Sarmento Cabral, Rafael S. Oliveira, Steven Jansen, and Paulo R. L. Bittencourt
- Subjects
0106 biological sciences ,0303 health sciences ,Xylem ,Soil science ,15. Life on land ,Xylem water potential ,01 natural sciences ,03 medical and health sciences ,Hydraulic conductivity ,13. Climate action ,Temperate climate ,Range (statistics) ,Environmental science ,Sensitivity (control systems) ,Porosity ,Tree species ,030304 developmental biology ,010606 plant biology & botany - Abstract
SummaryThe increasing frequency of global change-type droughts has created a need for fast, accurate and widely applicable techniques for estimating xylem embolism resistance to improve forecasts of future forest changes.We used data from 12 diffuse-porous temperate tree species covering a wide range of xylem safety to compare the pneumatic and flow-centrifuge method for constructing xylem vulnerability curves. We evaluated the agreement between parameters estimated with both methods and the sensitivity of pneumatic measurements to the measurement duration.The agreement between xylem water potentials at 50% air discharged (PAD) estimated with the Pneumatron and 50% loss of hydraulic conductivity (PLC) estimated with the flow-centrifuge method was high (mean signed deviation: 0.12 MPa, Pearson correlation: 0.96 after 15 sec of gas extraction). However, the relation between the estimated slopes was more variable, resulting in lower agreement in xylem water potential at 12% and 88% PAD/PLC. All parameters were sensitive to the duration of the pneumatic measurement, with highest overall agreement between methods after 16 sec.We conclude that, if applied correctly, the pneumatic method enables fast and inexpensive estimations of embolism resistance for a wide range of temperate, diffuse-porous species, which makes it attractive for predicting plant performance under climate change.
- Published
- 2021
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