Proximal sensing at VPDrought in Pfynwald

Under conditions of low soil moisture and high atmospheric water demand, a growing fraction of absorbed light cannot be used for photosynthesis and must instead be diverted to non-photosynthetic pathways to protect the photosynthetic apparatus from damage. These shifts in energy utilization alter the light reflected by the canopy, producing a distinct spectral signature that reveals the tree's physiological state. To better understand this spectral signature, we installed point spectroradiometers continuously measuring reflected and emitted radiation across multiple tree canopies within the VPDrought experiment.

Since 2024 Infrared Radiometer Sensors have been recording canopy temperature between 8 - 14 µm at eight experimental plots, each subjected to one of the following treatments: control, irrigation, irrigation + VPD, drought, and drought + VPD, with three replicates per treatment. In 2025 we have further added Spectral Reflectance Sensor measuring at 532 nm (green) and 570 nm (yellow), enabling calculation of the Photochemical Reflectance Index (PRI). These sensors are installed in two treatments - control and irrigation - with three replicates per treatment.

The following parameters are continuously monitored:

• Surface (or canopy) temperature in the 8-14 µm wavelength range (°C)
• Upwelling (canopy) narrowband spectral radiance (µmol m^-2 s^-1) at 531 nm and 570 nm
• Downwelling (sun) narrowband spectral radiance (µmol m^-2 s^-1) at 531 nm and 570 nm

We use SI-411-SS sensors from Apogee to measure canopy temperature and SRS sensors from Meter to measure spectral radiance. All sensors are mounted on poles fixed to the scaffold structures above the tree canopies.

Combined, these measurements provide high temporal resolution insights into the dynamics of energy use in tree canopies under varying environmental stress. They serve as a pre-visual indicator, offering early warning of stress before visible symptoms such as canopy discoloration or defoliation appear. Additionally, they constitute a valuable reference dataset for validating temporally discrete observations from remote sensing platforms, including drones, aircraft, and satellites.