Calibration of a new transient thermal dissipation-based Internet of Things (IoT)-sensor for xylem sap flow density...

Measuring xylem sap flow is crucial for calculating water use in trees and forests, but remote measurements are challenging, especially regarding power supply. The transient thermal dissipation (TTD) system addresses these challenges by being power-efficient and robust. This study assesses the TreeTalker© system (version TT+), a newly developed battery-powered, Internet of Things (IoT)-based measurement system with new probes in terms of structure and material compared with previous versions. To calibrate the system, different flow indices (Ki) were derived for various heating/cooling cycles at several sap flow densities (SFD) using an artificial hydraulic column made of sawdust. To provide a calibration equation for different species, freshly cut stem segments with three distinct xylem structures of temperate trees were used under controlled conditions: Quercus robur L. (oak, ring-porous), Abies alba Mill. (fir, coniferous) and Fagus sylvatica L. (beech, diffuse-porous). A linear model best described the relationship between Ki and SFD for sawdust and oak, while a power function suited fir and beech. Compared with the literature, the regression steepness increased with the conduit size. Using the sawdust equation for oak resulted in a 55 ± 3% underestimation of SFD. For fir and beech, using the sawdust equation overestimated daily water use by 149 ± 116% and 71 ± 41%, respectively. A multi-media equation across all tested media reduced the underestimation in oak to 19 ± 3% but increase the overestimation for fir and beech compared with the sawdust equation to 352 ± 210% and 209 ± 75%, respectively. For more accurate estimation of absolute values, species-specific calibration equations are recommended assess SFD using the TTD method. However, there appears to be a dependency when comparing different linear calibration equations with the corresponding conduit sizes of the tree species.